Repository: Gen-Verse/LatentMAS
Branch: main
Commit: b9b2095f4109
Files: 16
Total size: 21.3 MB
Directory structure:
gitextract_kqtlwho5/
├── LICENSE
├── README.md
├── __init__.py
├── data/
│ └── medqa.json
├── data.py
├── example_logs/
│ ├── qwen3_14b_humanevalplus_hierarchical.txt
│ └── qwen3_14b_mbppplus_sequential.txt
├── methods/
│ ├── __init__.py
│ ├── baseline.py
│ ├── latent_mas.py
│ └── text_mas.py
├── models.py
├── prompts.py
├── requirements.txt
├── run.py
└── utils.py
================================================
FILE CONTENTS
================================================
================================================
FILE: LICENSE
================================================
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================================================
FILE: README.md
================================================
Latent Collaboration in Multi-Agent Systems
---
## 💡 Introduction
**LatentMAS** is a multi-agent reasoning framework that **moves agent collaboration from token space into the model’s latent space**.
Instead of producing long textual reasoning traces, agents communicate by **passing latent thoughts** through their own **working memory**. LatentMAS has the following key features:
- **Efficient** multi-step reasoning with drastically fewer tokens
- **Training-free** latent-space alignment for stable generation
- **A general technique** compatible with **any HF model** and optionally **vLLM** backends.
Overall, LatentMAS achieves **superior performance**, **lower token usage**, and **major wall-clock speedups** of the multi-agent system.
## 🔔 News
- **[2026-02-26]** 🦞 Check out [**OpenClaw-RL**](https://github.com/Gen-Verse/OpenClaw-RL) from our Gen-Verse group! OpenClaw-RL is a fully asynchronous RL framework that trains personalized AI agents directly from natural conversation feedback — no manual labels, no API keys. It introduces two learning paradigms (Binary RL via GRPO and On-Policy Distillation) and runs the entire stack on your own infrastructure. A great complement to LatentMAS's efficient multi-agent reasoning!
- **[2025-12-20]** Check [**Science-LatentMAS**](https://github.com/Gen-Verse/LatentMAS/tree/Science-LatentMAS), an excellent extension of LatentMAS developed by Prof. Markus J. Buehler and the [LAMM Lab](https://github.com/lamm-mit) at MIT. Science-LatentMAS is specifically designed for the scientific discovery downstream applications! For more details and instructions, please check our README section "Science-LatentMAS" below and the new `Science-LatentMAS` branch.
- **[2025-12-15]** Check out these amazing community-driven extensions of LatentMAS!
- **[KNN-LatentMAS](https://github.com/Bookmaster9/kNN-latentMAS)** — Enables more efficient KV utilization for latent memory.
- **[Hybrid-LatentMAS](https://github.com/nhminle/LatentMAS-Hybrid)** — Extends LatentMAS to support hybrid, heterogeneous multi-agent systems.
- **[2025-11-25]** We have released our paper and code implementations for LatentMAS! Stay tuned for more model-backbone supports and advanced features!
- **[2025-11-25]** We are featured as 🤗 [**HuggingFace 1st Paper of the Day**](https://huggingface.co/papers/2511.20639)!
## 🌐 Awesome Works Built on Top of LatentMAS
Explore community-driven extensions that expand LatentMAS into new domains, architectures, and collaboration patterns:
### 🔬 1. **Science-LatentMAS**
**By Prof. Markus J. Buehler & MIT LAMM Group**
- **New Branch:** https://github.com/Gen-Verse/LatentMAS/tree/Science-LatentMAS
- **Original Code:** https://github.com/lamm-mit/LatentMAS/tree/flexible_agents
**New Features:** Extends LatentMAS for scientific modeling and material-system collaboration, enabling flexible agent types and specialized latent communication for science domains.
### 🧠 2. **KNN-LatentMAS**
**By Bookmaster9**
- **Blog (Overview):** https://bookmaster9.github.io/kNN-latentMAS/
- **Code:** https://github.com/Bookmaster9/kNN-latentMAS
- **New Features:** Introduce kNN-based latent retrieval to improve KV-cache usage, boosting memory efficiency and multi-step reasoning stability across agents.
### 🤖 3. **Hybrid-LatentMAS**
**By nhminle**
- **Code:** https://github.com/nhminle/LatentMAS-Hybrid
- **New Features:** Support heterogeneous/hybrid agent collaboration (LLM + non-LLM agents), enabling modular multi-agent pipelines that mix models, tools, and reasoning strategies.
### 🌍 4. **Awareness Network**
**By Everest-AN**
- **Website:** https://awareness.market/
- **Code:** https://github.com/everest-an/Awareness-Market
- **New Features:** A decentralized AI awareness market product built on LatentMAS research, enabling autonomous agent collaboration and memory sharing.
### 🧩 5. LatentMAS-SLoRA
**By Arifuzzaman Joy**
- **Demo:** https://www.youtube.com/watch?v=g7sxYjwgRRk
- **Code:** https://github.com/Arifuzzamanjoy/latent_mas_slora
- **New Features:** Augment LatentMAS with role-specialized, dynamically switchable LoRA adapters for better specialization and adaptability.
### 🛰️ 6. AVP (Agent Vector Protocol)
**By VectorArc**
- **Blog:** https://blog.avprotocol.ai/avp-binary-protocol-latent-agent-communication/
- **Code:** https://github.com/VectorArc/avp-python
- **New Features:** Enables agents to share KV-cache and hidden states instead of text, supporting zero-training latent handoff, cross-model transfer, and faster multi-agent collaboration.
**If your work extends LatentMAS, feel free to open a PR and we’ll feature it here! 🚀**
## 📊 Experiments Overview
### ⭐ Main Results
Three main tables from our paper spanning 9 tasks across math & science reasoning, commensonse reasoning, and code generation:
- **Table 1 — LatentMAS under the Sequantial MAS setting**
- **Table 2 — LatentMAS under the Hierarchical MAS setting**
- **Table 3 — Main Results on Reasoning Intensive Tasks**
### ⚡ Superior Efficiency on **Time and Tokens**
Overall, LatentMAS reduces:
- **~50–80% tokens**
- **~3×–7× wall-clock time**
compared to standard Text-MAS or chain-of-thought baselines.
## 🛠️ Getting Started
This repository provides all code for reproducing LatentMAS, TextMAS, and baseline single-agent experiments across GSM8K, AIME24/25, GPQA, ARC-Easy/Challenge, MBPP+, HumanEval+, and MedQA.
### ⚙️ Setup Environment Variables
We recommend setting your HF cache directory to avoid repeated downloads:
```bash
export HF_HOME=/path/to/huggingface
export TRANSFORMERS_CACHE=$HF_HOME
export HF_DATASETS_CACHE=$HF_HOME
````
Models and datasets will automatically be downloaded into `$HF_HOME`.
### 📦 Install Packages
```bash
conda create -n latentmas python=3.10 -y
conda activate latentmas
pip install -r requirements.txt
```
If you want **vLLM support**, also install:
```bash
pip install vllm
```
## 🚀 Quick Start
### 1. Clone the repo
```bash
git clone https://github.com/Gen-Verse/LatentMAS.git
cd LatentMAS
```
### 2. Repository Structure
```
LatentMAS/
│── run.py # Main entry for experiments
│── models.py # Wrapper for HF + vLLM + latent realignment
│── methods/
│ ├── baseline.py # Single-agent baseline
│ ├── text_mas.py # Token-space multi-agent method
│ └── latent_mas.py # Latent-space multi-agent (our method)
│── prompts.py # Prompt constructors
│── data.py # Dataset loaders
│── data/ # Provided data + figures (We give medqa.json as an example here)
│── utils.py # Answer parsing / timeout / helpers
│── example_logs/ # Example logs from LatentMAS
│── requirements.txt
```
## 🧪 Running Experiments (standard HF backend)
### 🔹 **Baseline (single model)**
```bash
python run.py --method baseline --model_name Qwen/Qwen3-14B --task gsm8k --max_samples -1 --max_new_tokens 2048
```
### 🔹 **TextMAS (text based multi-agent system)**
```bash
python run.py --method text_mas --model_name Qwen/Qwen3-14B --task gsm8k --prompt sequential --max_samples -1 --max_new_tokens 2048
```
### 🔹 **LatentMAS (our latent mas method)**
```bash
python run.py --method latent_mas --model_name Qwen/Qwen3-14B --task gsm8k --prompt sequential --max_samples -1 --max_new_tokens 2048
```
#### Notes:
* **`--latent_steps`** ∈ [0, 80]
Tune for best performance.
* **`--latent_space_realign`**
Enables latent→embedding alignment
We treat this as a **hyperparameter** — enable/disable depending on task/model:
```bash
python run.py --method latent_mas --model_name Qwen/Qwen3-14B --task gsm8k --prompt sequential --max_samples -1 --latent_space_realign --max_new_tokens 2048
```
## 📘 Example Logs
Two example LatentMAS logs are provided for reference purposes:
* `example_logs/qwen3_14b_mbppplus_sequential.txt`
* `example_logs/qwen3_14b_humanevalplus_hierarchical.txt`
Please refer to additional experiment logs [here](https://drive.google.com/drive/folders/1evGv5YAmLb4YM_D9Yu0ABa1nfqHC5N-l?usp=drive_link).
You can open them to view the full agent interaction traces and outputs.
## ⚡ vLLM Integration
LatentMAS supports vLLM for faster inference.
### 🔹 Baseline with vLLM
```bash
python run.py --method baseline --model_name Qwen/Qwen3-14B --task gsm8k --max_samples -1 --use_vllm --max_new_tokens 2048
```
### 🔹 TextMAS with vLLM
```bash
python run.py --method text_mas --model_name Qwen/Qwen3-14B --task gsm8k --prompt sequential --max_samples -1 --use_vllm --max_new_tokens 2048
```
### 🔹 LatentMAS with vLLM
LatentMAS supports a **hybrid HF + vLLM pipeline** for fast inference:
- vLLM handles **final text generation** (with prefix caching, tensor parallelism, etc.)
- A HuggingFace model handles **latent-space rollout** and hidden-state alignment
For this setup, we recommend using two GPUs:
- One GPU for vLLM (`--device`, e.g., `cuda:0`)
- One GPU for the auxiliary HF model (`--device2`, e.g., `cuda:1`)
```bash
CUDA_VISIBLE_DEVICES=0,1 python run.py --method latent_mas --model_name Qwen/Qwen3-14B --task gsm8k --prompt sequential --max_samples -1 --max_new_tokens 2048 \
--use_vllm \
--use_second_HF_model \
--enable_prefix_caching \
--device2 cuda:1
```
**📍Important Note:**
> vLLM does **not** officially support modifying KV-cache or prompting via latent embeddings.
> We modify the partial inner package inside vLLM backend for our method implementation.
> Note minor numeric differences may arise compared to offical HF backend due to different decoding (generation) strategies. Please Use the HF backend to reproduce the official published results.
## 📚 Citation
💫 If you find **LatentMAS** helpful, please kindly give us a star ⭐️ and cite below. Thanks!
```
@article{zou2025latentmas,
title={Latent Collaboration in Multi-Agent Systems},
author={Zou, Jiaru and Yang, Xiyuan and Qiu, Ruizhong and Li, Gaotang and Tieu, Katherine and Lu, Pan and Shen, Ke and Tong, Hanghang and Choi, Yejin and He, Jingrui and Zou, James and Wang, Mengdi and Yang, Ling},
journal={arXiv preprint arXiv:2511.20639},
year={2025}
}
```
## 🤝 Ackowledgement
This code is partially based on the amazing work of [vLLM](https://github.com/vllm-project/vllm).
================================================
FILE: __init__.py
================================================
__all__ = []
================================================
FILE: data/medqa.json
================================================
[
{
"idx": 0,
"question": "A 34-year-old man comes to the physician because of a 3-week history of colicky abdominal pain and diarrhea. He has bowel movements 10–12 times daily; the stool contains blood and mucus. He constantly has the urge to defecate. His vital signs are within normal limits. Examination of the abdomen shows diffuse tenderness to palpation. Serum concentration of C-reactive protein is 20 mg/L (N<10). Colonoscopy shows a bleeding, ulcerated rectal mucosa with several pseudopolyps. Which of the following is this patient at greatest risk of developing?\nA. Hemolytic uremic syndrome\nB. Oral ulcers\nC. Colorectal cancer\nD. Pancreatic cancer\n\nA. Hemolytic uremic syndrome\nB. Oral ulcers\nC. Colorectal cancer\nD. Pancreatic cancer",
"options": [
"A. Hemolytic uremic syndrome",
"B. Oral ulcers",
"C. Colorectal cancer",
"D. Pancreatic cancer"
],
"answer": "Colorectal cancer",
"gen_text_store": "",
"pid": "0",
"query": "A 34-year-old man comes to the physician because of a 3-week history of colicky abdominal pain and diarrhea. He has bowel movements 10–12 times daily; the stool contains blood and mucus. He constantly has the urge to defecate. His vital signs are within normal limits. Examination of the abdomen shows diffuse tenderness to palpation. Serum concentration of C-reactive protein is 20 mg/L (N<10). Colonoscopy shows a bleeding, ulcerated rectal mucosa with several pseudopolyps. Which of the following is this patient at greatest risk of developing?\nA. Hemolytic uremic syndrome\nB. Oral ulcers\nC. Colorectal cancer\nD. Pancreatic cancer\nChoose the correct option.",
"image": null
},
{
"idx": 1,
"question": "A 38-year-old woman presents to her primary care physician for her yearly exam. Her only complaint is difficulty losing weight. Her BMI is 34 kg/m^2. In addition to a standard physical exam, the physician orders a glucose tolerance test. The woman's fasting blood glucose level is 120 mg/dL and two-hour post 75g glucose load blood glucose level is 190 mg/dL. The physician informs the patient that she is \"pre-diabetic\" or at risk of developing diabetes and recommends lifestyle modification with follow-up in 6 months. Which of the following endogenous signaling molecules or receptors will increase insulin sensitivity in this patient?\nA. Catecholamines\nB. Glucagon\nC. Glucocorticoids\nD. Peroxisome proliferator-activated receptor gamma\n\nA. Catecholamines\nB. Glucagon\nC. Glucocorticoids\nD. Peroxisome proliferator-activated receptor gamma",
"options": [
"A. Catecholamines",
"B. Glucagon",
"C. Glucocorticoids",
"D. Peroxisome proliferator-activated receptor gamma"
],
"answer": "Peroxisome proliferator-activated receptor gamma",
"gen_text_store": "",
"pid": "1",
"query": "A 38-year-old woman presents to her primary care physician for her yearly exam. Her only complaint is difficulty losing weight. Her BMI is 34 kg/m^2. In addition to a standard physical exam, the physician orders a glucose tolerance test. The woman's fasting blood glucose level is 120 mg/dL and two-hour post 75g glucose load blood glucose level is 190 mg/dL. The physician informs the patient that she is \"pre-diabetic\" or at risk of developing diabetes and recommends lifestyle modification with follow-up in 6 months. Which of the following endogenous signaling molecules or receptors will increase insulin sensitivity in this patient?\nA. Catecholamines\nB. Glucagon\nC. Glucocorticoids\nD. Peroxisome proliferator-activated receptor gamma\nChoose the correct option.",
"image": null
},
{
"idx": 2,
"question": "A 33-year-old man presents to the emergency department after a motor vehicle collision. He was the front seat unrestrained driver in a head-on collision. The patient has a Glasgow Coma Scale of 5 and is subsequently intubated. Physical exam is notable for subcutaneous emphysema in the clavicular area. Needle decompression and chest tube placement are performed, and the patient is stabilized after receiving 2 units of blood and 2 liters of fluid. Chest radiography demonstrates proper tube location and resolution of the pneumothorax. The patient is transferred to the trauma intensive care unit. On the unit, a repeat chest radiograph is notable for a recurrent pneumothorax with the chest tube in place. Which of the following is the most likely diagnosis?\nA. Inappropriate chest tube placement\nB. Spontaneous pneumothorax\nC. Tension pneumothorax\nD. Tracheobronchial rupture\n\nA. Inappropriate chest tube placement\nB. Spontaneous pneumothorax\nC. Tension pneumothorax\nD. Tracheobronchial rupture",
"options": [
"A. Inappropriate chest tube placement",
"B. Spontaneous pneumothorax",
"C. Tension pneumothorax",
"D. Tracheobronchial rupture"
],
"answer": "Tracheobronchial rupture",
"gen_text_store": "",
"pid": "2",
"query": "A 33-year-old man presents to the emergency department after a motor vehicle collision. He was the front seat unrestrained driver in a head-on collision. The patient has a Glasgow Coma Scale of 5 and is subsequently intubated. Physical exam is notable for subcutaneous emphysema in the clavicular area. Needle decompression and chest tube placement are performed, and the patient is stabilized after receiving 2 units of blood and 2 liters of fluid. Chest radiography demonstrates proper tube location and resolution of the pneumothorax. The patient is transferred to the trauma intensive care unit. On the unit, a repeat chest radiograph is notable for a recurrent pneumothorax with the chest tube in place. Which of the following is the most likely diagnosis?\nA. Inappropriate chest tube placement\nB. Spontaneous pneumothorax\nC. Tension pneumothorax\nD. Tracheobronchial rupture\nChoose the correct option.",
"image": null
},
{
"idx": 3,
"question": "A 45-year-old mechanic presents to the emergency department complaining of acute-onset shortness of breath while repairing a plowing tractor for his neighbor. The patient denies having any history of asthma or respiratory symptoms, and does not smoke. His temperature is 99.8°F (37.7°C), pulse is 65/min, blood pressure is 126/86 mmHg, and respirations are 20/min. His oxygen saturation is 97%. On exam, he is pale and diaphoretic. His pupils are contracted. Diffuse wheezes are noted in all lung fields. What is the best treatment for his condition?\nA. Succinylcholine\nB. Inhaled ipratropium and oxygen\nC. Atropine and pralidoxime\nD. Inhaled albuterol and oxygen\n\nA. Succinylcholine\nB. Inhaled ipratropium and oxygen\nC. Atropine and pralidoxime\nD. Inhaled albuterol and oxygen",
"options": [
"A. Succinylcholine",
"B. Inhaled ipratropium and oxygen",
"C. Atropine and pralidoxime",
"D. Inhaled albuterol and oxygen"
],
"answer": "Atropine and pralidoxime",
"gen_text_store": "",
"pid": "3",
"query": "A 45-year-old mechanic presents to the emergency department complaining of acute-onset shortness of breath while repairing a plowing tractor for his neighbor. The patient denies having any history of asthma or respiratory symptoms, and does not smoke. His temperature is 99.8°F (37.7°C), pulse is 65/min, blood pressure is 126/86 mmHg, and respirations are 20/min. His oxygen saturation is 97%. On exam, he is pale and diaphoretic. His pupils are contracted. Diffuse wheezes are noted in all lung fields. What is the best treatment for his condition?\nA. Succinylcholine\nB. Inhaled ipratropium and oxygen\nC. Atropine and pralidoxime\nD. Inhaled albuterol and oxygen\nChoose the correct option.",
"image": null
},
{
"idx": 4,
"question": "A 64-year-old man comes to the physician with a 1-week history of sore mouth. He says that swallowing is not painful. He has had asthma for more than 20 years. His only medication is a high-dose combination salmeterol/fluticasone inhaler. His temperature is 37.1°C (98.8°F), pulse is 74/min, respirations are 14/min, and blood pressure is 125/65 mm Hg. A photograph of his oral mucosa is shown. Indirect mirror examination of the posterior oropharynx, larynx, and hypopharynx shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Fluconazole\nB. Isotretinoin\nC. Nystatin\nD. Penicillin V\n\nA. Fluconazole\nB. Isotretinoin\nC. Nystatin\nD. Penicillin V",
"options": [
"A. Fluconazole",
"B. Isotretinoin",
"C. Nystatin",
"D. Penicillin V"
],
"answer": "Nystatin",
"gen_text_store": "",
"pid": "4",
"query": "A 64-year-old man comes to the physician with a 1-week history of sore mouth. He says that swallowing is not painful. He has had asthma for more than 20 years. His only medication is a high-dose combination salmeterol/fluticasone inhaler. His temperature is 37.1°C (98.8°F), pulse is 74/min, respirations are 14/min, and blood pressure is 125/65 mm Hg. A photograph of his oral mucosa is shown. Indirect mirror examination of the posterior oropharynx, larynx, and hypopharynx shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Fluconazole\nB. Isotretinoin\nC. Nystatin\nD. Penicillin V\nChoose the correct option.",
"image": null
},
{
"idx": 5,
"question": "A 62-year-old man presents with episodes of palpitations for the past 3 weeks. He says that he has episodes where he feels his heart is ‘racing and pounding’, lasting 1–2 hours on average. Initially, he says the episodes would happen 1–2 times per week but now happen almost every day. This last episode has been constant for the past 2 days. He denies any seizure, loss of consciousness, dizziness, chest pain, or similar symptoms in the past. His past medical history is significant for an ischemic stroke of the right anterior cerebral artery 1 month ago, status post intravenous (IV) tissue plasminogen activator (tPA) with still some residual neurologic impairment, and long-standing gastroesophageal reflux secondary to a hiatal hernia, managed medically. The patient reports a 15-pack-year smoking history, but no alcohol or recreational drug use. The vital signs include: temperature 37.0°C (98.6°F), blood pressure 100/70 mm Hg, pulse 105/min, and respiratory rate 16/min. On physical examination, muscle strength in the lower extremities is 4/5 on the left and 5/5 on the right, along with sensory loss on the left, all of which is improved from his previous exam 3 weeks ago. There is a loss of the left half of the visual field bilaterally which is stable from the previous exam. Cardiac examination is significant for a new-onset irregular rate and rhythm. No rubs, thrills or murmurs. A noncontrast computed tomography (CT) scan shows evidence of an area of infarction in the vicinity of the right anterior cerebral artery showing normal interval change with no evidence of new hemorrhage or expansion of the area of infarction. An electrocardiogram (ECG) is performed, which is shown in the exhibit (see image below). Which of the following is the most appropriate intervention to best prevent future cerebrovascular accidents (CVAs) in this patient?\nA. Begin aspirin therapy\nB. Begin clopidogrel\nC. Carotid endarterectomy\nD. Begin warfarin and heparin\n\nA. Begin aspirin therapy\nB. Begin clopidogrel\nC. Carotid endarterectomy\nD. Begin warfarin and heparin",
"options": [
"A. Begin aspirin therapy",
"B. Begin clopidogrel",
"C. Carotid endarterectomy",
"D. Begin warfarin and heparin"
],
"answer": "Begin warfarin and heparin",
"gen_text_store": "",
"pid": "5",
"query": "A 62-year-old man presents with episodes of palpitations for the past 3 weeks. He says that he has episodes where he feels his heart is ‘racing and pounding’, lasting 1–2 hours on average. Initially, he says the episodes would happen 1–2 times per week but now happen almost every day. This last episode has been constant for the past 2 days. He denies any seizure, loss of consciousness, dizziness, chest pain, or similar symptoms in the past. His past medical history is significant for an ischemic stroke of the right anterior cerebral artery 1 month ago, status post intravenous (IV) tissue plasminogen activator (tPA) with still some residual neurologic impairment, and long-standing gastroesophageal reflux secondary to a hiatal hernia, managed medically. The patient reports a 15-pack-year smoking history, but no alcohol or recreational drug use. The vital signs include: temperature 37.0°C (98.6°F), blood pressure 100/70 mm Hg, pulse 105/min, and respiratory rate 16/min. On physical examination, muscle strength in the lower extremities is 4/5 on the left and 5/5 on the right, along with sensory loss on the left, all of which is improved from his previous exam 3 weeks ago. There is a loss of the left half of the visual field bilaterally which is stable from the previous exam. Cardiac examination is significant for a new-onset irregular rate and rhythm. No rubs, thrills or murmurs. A noncontrast computed tomography (CT) scan shows evidence of an area of infarction in the vicinity of the right anterior cerebral artery showing normal interval change with no evidence of new hemorrhage or expansion of the area of infarction. An electrocardiogram (ECG) is performed, which is shown in the exhibit (see image below). Which of the following is the most appropriate intervention to best prevent future cerebrovascular accidents (CVAs) in this patient?\nA. Begin aspirin therapy\nB. Begin clopidogrel\nC. Carotid endarterectomy\nD. Begin warfarin and heparin\nChoose the correct option.",
"image": null
},
{
"idx": 6,
"question": "An investigator is studying cellular regeneration of epithelial cells. She has obtained a tissue sample from a normal thyroid gland for histopathologic examination. It shows follicles lined by a single layer of cube-like cells with large central nuclei. Which of the following parts of the female reproductive tract is also lined by this type of epithelium?\nA. Ovaries\nB. Vagina\nC. Fallopian tubes\nD. Vulva\n\nA. Ovaries\nB. Vagina\nC. Fallopian tubes\nD. Vulva",
"options": [
"A. Ovaries",
"B. Vagina",
"C. Fallopian tubes",
"D. Vulva"
],
"answer": "Ovaries",
"gen_text_store": "",
"pid": "6",
"query": "An investigator is studying cellular regeneration of epithelial cells. She has obtained a tissue sample from a normal thyroid gland for histopathologic examination. It shows follicles lined by a single layer of cube-like cells with large central nuclei. Which of the following parts of the female reproductive tract is also lined by this type of epithelium?\nA. Ovaries\nB. Vagina\nC. Fallopian tubes\nD. Vulva\nChoose the correct option.",
"image": null
},
{
"idx": 7,
"question": "A 4-year-old girl is brought to the emergency department with a persistent cough, fever, and vomiting. The past year the child has been admitted to the hospital 3 times with pneumonia. For the past 1 week, the child has been experiencing thick purulent cough and says that her chest feels ‘heavy’. Her stools have been loose and foul-smelling over the past week. Her parents are also concerned that she has not gained much weight due to her frequent hospital visits. She was born at 39 weeks gestation via spontaneous vaginal delivery and is up to date on all vaccines and is meeting all developmental milestones. On physical exam, the temperature is 39.1°C (102.4°F). She appears lethargic and uncomfortable. Crackles are heard in the lower lung bases, with dullness to percussion. A small nasal polyp is also present on inspection. Which of the following is the most likely cause for the girl’s symptoms?\nA. Dysfunction in a transmembrane regulator\nB. Inefficient breakdown of leucine, isoleucine, and valine\nC. Dysfunction in the motility of respiratory cilia\nD. Deficiency in lymphocytic activity\n\nA. Dysfunction in a transmembrane regulator\nB. Inefficient breakdown of leucine, isoleucine, and valine\nC. Dysfunction in the motility of respiratory cilia\nD. Deficiency in lymphocytic activity",
"options": [
"A. Dysfunction in a transmembrane regulator",
"B. Inefficient breakdown of leucine, isoleucine, and valine",
"C. Dysfunction in the motility of respiratory cilia",
"D. Deficiency in lymphocytic activity"
],
"answer": "Dysfunction in a transmembrane regulator",
"gen_text_store": "",
"pid": "7",
"query": "A 4-year-old girl is brought to the emergency department with a persistent cough, fever, and vomiting. The past year the child has been admitted to the hospital 3 times with pneumonia. For the past 1 week, the child has been experiencing thick purulent cough and says that her chest feels ‘heavy’. Her stools have been loose and foul-smelling over the past week. Her parents are also concerned that she has not gained much weight due to her frequent hospital visits. She was born at 39 weeks gestation via spontaneous vaginal delivery and is up to date on all vaccines and is meeting all developmental milestones. On physical exam, the temperature is 39.1°C (102.4°F). She appears lethargic and uncomfortable. Crackles are heard in the lower lung bases, with dullness to percussion. A small nasal polyp is also present on inspection. Which of the following is the most likely cause for the girl’s symptoms?\nA. Dysfunction in a transmembrane regulator\nB. Inefficient breakdown of leucine, isoleucine, and valine\nC. Dysfunction in the motility of respiratory cilia\nD. Deficiency in lymphocytic activity\nChoose the correct option.",
"image": null
},
{
"idx": 8,
"question": "A 70-year-old woman is brought to the emergency department for the evaluation of abdominal pain, nausea, and vomiting for 1 day. Computed tomography shows a small bowel perforation. The patient is prepared for emergent exploratory laparotomy. She is sedated with midazolam, induced with propofol, intubated, and maintained on nitrous oxide and isoflurane for the duration of the surgery. A single perforation in the terminal ileum is diagnosed intraoperatively and successfully repaired. The patient is transferred to the intensive care unit. The ventilator is set at an FiO2 of 50%, tidal volume of 1000 mL, respiratory rate of 12/min, and positive end-expiratory pressure of 2.5 cm H2O. Her temperature is 37.3°C (99.1°F), pulse is 76/min, and blood pressure is 111/50 mm Hg. She is responsive to painful stimuli. Lung examination shows bilateral rales. Abdominal examination shows a distended abdomen and intact abdominal surgical incisions. The remainder of the physical examination shows no abnormalities. Arterial blood gas analysis shows:\npH 7.44\npO2 54 mm Hg\npCO2 31 mm Hg\nHCO3- 22 mm Hg\nWhich of the following is the best next step in the management of this patient?\"\nA. Increase the FiO2\nB. Increase the tidal volume\nC. Increase PEEP\nD. Increase the respiratory rate\n\nA. Increase the FiO2\nB. Increase the tidal volume\nC. Increase PEEP\nD. Increase the respiratory rate",
"options": [
"A. Increase the FiO2",
"B. Increase the tidal volume",
"C. Increase PEEP",
"D. Increase the respiratory rate"
],
"answer": "Increase PEEP",
"gen_text_store": "",
"pid": "8",
"query": "A 70-year-old woman is brought to the emergency department for the evaluation of abdominal pain, nausea, and vomiting for 1 day. Computed tomography shows a small bowel perforation. The patient is prepared for emergent exploratory laparotomy. She is sedated with midazolam, induced with propofol, intubated, and maintained on nitrous oxide and isoflurane for the duration of the surgery. A single perforation in the terminal ileum is diagnosed intraoperatively and successfully repaired. The patient is transferred to the intensive care unit. The ventilator is set at an FiO2 of 50%, tidal volume of 1000 mL, respiratory rate of 12/min, and positive end-expiratory pressure of 2.5 cm H2O. Her temperature is 37.3°C (99.1°F), pulse is 76/min, and blood pressure is 111/50 mm Hg. She is responsive to painful stimuli. Lung examination shows bilateral rales. Abdominal examination shows a distended abdomen and intact abdominal surgical incisions. The remainder of the physical examination shows no abnormalities. Arterial blood gas analysis shows:\npH 7.44\npO2 54 mm Hg\npCO2 31 mm Hg\nHCO3- 22 mm Hg\nWhich of the following is the best next step in the management of this patient?\"\nA. Increase the FiO2\nB. Increase the tidal volume\nC. Increase PEEP\nD. Increase the respiratory rate\nChoose the correct option.",
"image": null
},
{
"idx": 9,
"question": "A 47-year-old man with a history of HIV1 infection presents to his HIV clinic to discuss his antiretroviral medications. He is interested in including maraviroc in his maintenance regimen after seeing advertisements about the medication. On exam, his temperature is 98.8°F (37.1°C), blood pressure is 116/74 mmHg, pulse is 64/min, and respirations are 12/min. His viral load is undetectable on his current regimen, and his blood count, electrolytes, and liver function tests have all been within normal limits. In order to consider maraviroc for therapy, a tropism assay needs to be performed. Which of the following receptors is affected by the use of maraviroc?\nA. gp120\nB. gp160\nC. p24\nD. Reverse transcriptase\n\nA. gp120\nB. gp160\nC. p24\nD. Reverse transcriptase",
"options": [
"A. gp120",
"B. gp160",
"C. p24",
"D. Reverse transcriptase"
],
"answer": "gp120",
"gen_text_store": "",
"pid": "9",
"query": "A 47-year-old man with a history of HIV1 infection presents to his HIV clinic to discuss his antiretroviral medications. He is interested in including maraviroc in his maintenance regimen after seeing advertisements about the medication. On exam, his temperature is 98.8°F (37.1°C), blood pressure is 116/74 mmHg, pulse is 64/min, and respirations are 12/min. His viral load is undetectable on his current regimen, and his blood count, electrolytes, and liver function tests have all been within normal limits. In order to consider maraviroc for therapy, a tropism assay needs to be performed. Which of the following receptors is affected by the use of maraviroc?\nA. gp120\nB. gp160\nC. p24\nD. Reverse transcriptase\nChoose the correct option.",
"image": null
},
{
"idx": 10,
"question": "A 23-year-old woman comes to the physician because of a 2-month history of episodic headaches associated with dizziness, nausea, and vomiting. Over-the-counter pain medications have failed to reduce her symptoms. An MRI of the brain shows isolated dilation of the left lateral ventricle. This dilatation is most likely caused by blockade of which of the following structures?\nA. Arachnoid villi\nB. Interventricular foramen\nC. Median aperture\nD. Lateral apertures\n\nA. Arachnoid villi\nB. Interventricular foramen\nC. Median aperture\nD. Lateral apertures",
"options": [
"A. Arachnoid villi",
"B. Interventricular foramen",
"C. Median aperture",
"D. Lateral apertures"
],
"answer": "Interventricular foramen",
"gen_text_store": "",
"pid": "10",
"query": "A 23-year-old woman comes to the physician because of a 2-month history of episodic headaches associated with dizziness, nausea, and vomiting. Over-the-counter pain medications have failed to reduce her symptoms. An MRI of the brain shows isolated dilation of the left lateral ventricle. This dilatation is most likely caused by blockade of which of the following structures?\nA. Arachnoid villi\nB. Interventricular foramen\nC. Median aperture\nD. Lateral apertures\nChoose the correct option.",
"image": null
},
{
"idx": 11,
"question": "A 65-year-old man comes to the physician because of progressively worsening fatigue for 6 months. During this time, he has also had shortness of breath and palpitations on exertion. He has noticed blood in his stools on three separate occasions in the past 4 months. He has type 2 diabetes mellitus and end-stage renal disease. He drinks two to four beers daily. He does not smoke. His pulse is 95/min and blood pressure is 120/70 mm Hg. Examination shows pale conjunctivae. The abdomen is soft with no organomegaly. Rectal examination is unremarkable. His hemoglobin concentration is 7.2 g/dL, hematocrit is 32%, and mean corpuscular volume is 68 μm3. Which of the following is the most likely underlying cause of this patient's bleeding?\nA. Inflammation in an outpouching of the colonic wall\nB. Symptomatic enlargement of hemorrhoidal plexus\nC. Chronic mucosal and submucosal inflammation of the colon\nD. Arteriovenous malformation in the colonic wall\n\nA. Inflammation in an outpouching of the colonic wall\nB. Symptomatic enlargement of hemorrhoidal plexus\nC. Chronic mucosal and submucosal inflammation of the colon\nD. Arteriovenous malformation in the colonic wall",
"options": [
"A. Inflammation in an outpouching of the colonic wall",
"B. Symptomatic enlargement of hemorrhoidal plexus",
"C. Chronic mucosal and submucosal inflammation of the colon",
"D. Arteriovenous malformation in the colonic wall"
],
"answer": "Arteriovenous malformation in the colonic wall",
"gen_text_store": "",
"pid": "11",
"query": "A 65-year-old man comes to the physician because of progressively worsening fatigue for 6 months. During this time, he has also had shortness of breath and palpitations on exertion. He has noticed blood in his stools on three separate occasions in the past 4 months. He has type 2 diabetes mellitus and end-stage renal disease. He drinks two to four beers daily. He does not smoke. His pulse is 95/min and blood pressure is 120/70 mm Hg. Examination shows pale conjunctivae. The abdomen is soft with no organomegaly. Rectal examination is unremarkable. His hemoglobin concentration is 7.2 g/dL, hematocrit is 32%, and mean corpuscular volume is 68 μm3. Which of the following is the most likely underlying cause of this patient's bleeding?\nA. Inflammation in an outpouching of the colonic wall\nB. Symptomatic enlargement of hemorrhoidal plexus\nC. Chronic mucosal and submucosal inflammation of the colon\nD. Arteriovenous malformation in the colonic wall\nChoose the correct option.",
"image": null
},
{
"idx": 12,
"question": "An 11-month-old boy is brought to the physician for a well-child examination. He is growing along with the 75th percentile and meeting all milestones. Physical examination shows a poorly rugated scrotum. The palpation of the scrotum shows only 1 testicle. A 2nd testicle is palpated in the inguinal canal. The examination of the penis shows a normal urethral meatus. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Chorionic gonadotropin therapy\nB. Exploratory laparoscopy\nC. Orchiectomy\nD. Orchiopexy\n\nA. Chorionic gonadotropin therapy\nB. Exploratory laparoscopy\nC. Orchiectomy\nD. Orchiopexy",
"options": [
"A. Chorionic gonadotropin therapy",
"B. Exploratory laparoscopy",
"C. Orchiectomy",
"D. Orchiopexy"
],
"answer": "Orchiopexy",
"gen_text_store": "",
"pid": "12",
"query": "An 11-month-old boy is brought to the physician for a well-child examination. He is growing along with the 75th percentile and meeting all milestones. Physical examination shows a poorly rugated scrotum. The palpation of the scrotum shows only 1 testicle. A 2nd testicle is palpated in the inguinal canal. The examination of the penis shows a normal urethral meatus. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Chorionic gonadotropin therapy\nB. Exploratory laparoscopy\nC. Orchiectomy\nD. Orchiopexy\nChoose the correct option.",
"image": null
},
{
"idx": 13,
"question": "A 24-year-old woman presents to her primary care physician for a wellness visit. She says that she has been generally healthy but has noticed difficulty concentrating, becoming increasingly fatigued, and a 15-pound weight increase over the course of a few months. She also reports mild constipation and joint pain. Approximately 6-months ago, she experienced palpitations, increased stool frequency, and a hand tremor. Her past medical history is significant for asthma. Her father is not living and had Parkinson disease, and her mother has poorly controlled rheumatoid arthritis. She is currently sexually active in a monogamous relationship and uses contraception consistently. She denies cigarette smoking and occasionally drinks wine. She experimented once with lysergic acid diethylamide 6 years ago. Her temperature is 99°F (37.2°C), blood pressure is 127/98 mmHg, pulse is 55/min, and respirations are 13/min. On physical exam, the patient has slow speech and movement. She has tenderness to palpation of her wrist and ankle joints. She has delayed relaxation of deep tendon reflexes. Which of the following will most likely be found in this patient?\nA. Elevated TSH\nB. High Patient Health Questionnaire-9 (PHQ-9) score\nC. Positive anti-CCP antibodies\nD. Positive urine toxicology\n\nA. Elevated TSH\nB. High Patient Health Questionnaire-9 (PHQ-9) score\nC. Positive anti-CCP antibodies\nD. Positive urine toxicology",
"options": [
"A. Elevated TSH",
"B. High Patient Health Questionnaire-9 (PHQ-9) score",
"C. Positive anti-CCP antibodies",
"D. Positive urine toxicology"
],
"answer": "Elevated TSH",
"gen_text_store": "",
"pid": "13",
"query": "A 24-year-old woman presents to her primary care physician for a wellness visit. She says that she has been generally healthy but has noticed difficulty concentrating, becoming increasingly fatigued, and a 15-pound weight increase over the course of a few months. She also reports mild constipation and joint pain. Approximately 6-months ago, she experienced palpitations, increased stool frequency, and a hand tremor. Her past medical history is significant for asthma. Her father is not living and had Parkinson disease, and her mother has poorly controlled rheumatoid arthritis. She is currently sexually active in a monogamous relationship and uses contraception consistently. She denies cigarette smoking and occasionally drinks wine. She experimented once with lysergic acid diethylamide 6 years ago. Her temperature is 99°F (37.2°C), blood pressure is 127/98 mmHg, pulse is 55/min, and respirations are 13/min. On physical exam, the patient has slow speech and movement. She has tenderness to palpation of her wrist and ankle joints. She has delayed relaxation of deep tendon reflexes. Which of the following will most likely be found in this patient?\nA. Elevated TSH\nB. High Patient Health Questionnaire-9 (PHQ-9) score\nC. Positive anti-CCP antibodies\nD. Positive urine toxicology\nChoose the correct option.",
"image": null
},
{
"idx": 14,
"question": "A 16-year-old boy is rushed to the emergency room with acute vomiting and abdominal pain that began earlier today. His parents say that the boy was doing well until two days ago when he told them that he was feeling unwell. He has diabetes and takes insulin but stopped taking it when he began to feel poorly two days ago. His temperature is 37°C (98.6°F), respirations are shallow and rapid with a rate of 33/min, pulse is 107/min, and blood pressure is 101/68 mm Hg. He appears severely dehydrated, showing signs of fatigue, and poor skin turgor. His breath has a fruity smell to it. His blood glucose level is 691 mg/dL. Blood is drawn for labs and the results are given below:\nSerum: \n pH: 7.21\n pCO2: 32 mm HG\n HCO 3-: 15.2 mEq/L\nSodium: 122 mEq/L\nPotassium: 5.8 mEq/L\nUrinalysis is positive for ketone bodies. What is the most appropriate immediate step in the management of this patient?\nA. Administer IV fluids and insulin\nB. Administer IV antibiotics\nC. Administer IV fluids with oral antidiabetic medications\nD. Administer potassium and magnesium\n\nA. Administer IV fluids and insulin\nB. Administer IV antibiotics\nC. Administer IV fluids with oral antidiabetic medications\nD. Administer potassium and magnesium",
"options": [
"A. Administer IV fluids and insulin",
"B. Administer IV antibiotics",
"C. Administer IV fluids with oral antidiabetic medications",
"D. Administer potassium and magnesium"
],
"answer": "Administer IV fluids and insulin",
"gen_text_store": "",
"pid": "14",
"query": "A 16-year-old boy is rushed to the emergency room with acute vomiting and abdominal pain that began earlier today. His parents say that the boy was doing well until two days ago when he told them that he was feeling unwell. He has diabetes and takes insulin but stopped taking it when he began to feel poorly two days ago. His temperature is 37°C (98.6°F), respirations are shallow and rapid with a rate of 33/min, pulse is 107/min, and blood pressure is 101/68 mm Hg. He appears severely dehydrated, showing signs of fatigue, and poor skin turgor. His breath has a fruity smell to it. His blood glucose level is 691 mg/dL. Blood is drawn for labs and the results are given below:\nSerum: \n pH: 7.21\n pCO2: 32 mm HG\n HCO 3-: 15.2 mEq/L\nSodium: 122 mEq/L\nPotassium: 5.8 mEq/L\nUrinalysis is positive for ketone bodies. What is the most appropriate immediate step in the management of this patient?\nA. Administer IV fluids and insulin\nB. Administer IV antibiotics\nC. Administer IV fluids with oral antidiabetic medications\nD. Administer potassium and magnesium\nChoose the correct option.",
"image": null
},
{
"idx": 15,
"question": "A 22-year-old woman comes to the physician for the evaluation of irregular menstrual bleeding. Menses have occurred at 45- to 90-day intervals since menarche at the age of 15 years. Her last menstrual period was 5 weeks ago. The patient reports that she was too embarrassed to discuss this issue with anyone until now. Over the past two years, she was unable to become pregnant despite having unprotected sexual intercourse with her husband on a regular basis. There is no personal or family history of serious illness. She is 170 cm (5 ft 7 in) tall and weighs 85 kg (187 lb); BMI is 29.4 kg/m2. Her vital signs are within normal limits. Examination shows oily skin and severe facial acne. There is abnormal pigmented hair on the upper lip and around both nipples. The patient wishes to have children. In addition to recommending lifestyle modifications, which of the following is the most appropriate step in management?\nA. In vitro fertilization with patient's egg\nB. Progesterone therapy\nC. Clomiphene therapy\nD. Leuprolide therapy\n\nA. In vitro fertilization with patient's egg\nB. Progesterone therapy\nC. Clomiphene therapy\nD. Leuprolide therapy",
"options": [
"A. In vitro fertilization with patient's egg",
"B. Progesterone therapy",
"C. Clomiphene therapy",
"D. Leuprolide therapy"
],
"answer": "Clomiphene therapy",
"gen_text_store": "",
"pid": "15",
"query": "A 22-year-old woman comes to the physician for the evaluation of irregular menstrual bleeding. Menses have occurred at 45- to 90-day intervals since menarche at the age of 15 years. Her last menstrual period was 5 weeks ago. The patient reports that she was too embarrassed to discuss this issue with anyone until now. Over the past two years, she was unable to become pregnant despite having unprotected sexual intercourse with her husband on a regular basis. There is no personal or family history of serious illness. She is 170 cm (5 ft 7 in) tall and weighs 85 kg (187 lb); BMI is 29.4 kg/m2. Her vital signs are within normal limits. Examination shows oily skin and severe facial acne. There is abnormal pigmented hair on the upper lip and around both nipples. The patient wishes to have children. In addition to recommending lifestyle modifications, which of the following is the most appropriate step in management?\nA. In vitro fertilization with patient's egg\nB. Progesterone therapy\nC. Clomiphene therapy\nD. Leuprolide therapy\nChoose the correct option.",
"image": null
},
{
"idx": 16,
"question": "A 61-year-old man presents to the clinic with complaints of excessive thirst, frequent urination, and partial visual loss in both eyes for 1 day. His family history is significant for type 2 diabetes mellitus in his mother and cousin. His weight is 112 kg ( 246.9 lb), height 187 cm (6 ft 1 in), blood pressure: 150/90 mm Hg, heart rate: 89/min, respiratory rate: 14/min, and temperature: 36.7℃ (98.4℉). The physical examination is significant for dry skin, a pustular rash over the patient’s shoulders and back, an accentuated second heart sound (S2) best heard in the second intercostal space at the right sternal border, and distal loss of vibration sensitivity in both feet. A fundoscopic examination shows small red dots in the superficial retinal layers suggestive of microaneurysms. The HbA1c is 9% and the urinalysis shows the following:\nColor Pale yellow (light/pale-to-dark/deep amber)\nClarity Cloudy\npH 6.6\nSpecific gravity 1.010\nGlucose 199 mg/dl\nKetones None\nNitrites Negative\nLeukocyte esterase Negative\nBilirubin Negative\nUrinary bilirubin Traces\nRed blood cells 3 RBCs\nProtein 120 mg/d\nRBCs ≤ 2 RBCs/hpf\nWBCs 22 WBCs/hpf\nEpithelial cells 27 squamous epithelial cells/hpf\nCasts 5 hyaline casts/lpf\nCrystals Occasional\nBacteria None\nYeast Present\nWhich of the following statements best describes the cause of this patient’s glucosuria?\nA. There is a disruption of primary active transport of glucose in the proximal renal tubules\nB. Secondary active transporters fail to completely reabsorb glucose in the renal tubules\nC. There is a disruption of passive transport of the glucose in the proximal renal tubules\nD. Glucosuria results from increased glomerular filtration rate\n\nA. There is a disruption of primary active transport of glucose in the proximal renal tubules\nB. Secondary active transporters fail to completely reabsorb glucose in the renal tubules\nC. There is a disruption of passive transport of the glucose in the proximal renal tubules\nD. Glucosuria results from increased glomerular filtration rate",
"options": [
"A. There is a disruption of primary active transport of glucose in the proximal renal tubules",
"B. Secondary active transporters fail to completely reabsorb glucose in the renal tubules",
"C. There is a disruption of passive transport of the glucose in the proximal renal tubules",
"D. Glucosuria results from increased glomerular filtration rate"
],
"answer": "Secondary active transporters fail to completely reabsorb glucose in the renal tubules",
"gen_text_store": "",
"pid": "16",
"query": "A 61-year-old man presents to the clinic with complaints of excessive thirst, frequent urination, and partial visual loss in both eyes for 1 day. His family history is significant for type 2 diabetes mellitus in his mother and cousin. His weight is 112 kg ( 246.9 lb), height 187 cm (6 ft 1 in), blood pressure: 150/90 mm Hg, heart rate: 89/min, respiratory rate: 14/min, and temperature: 36.7℃ (98.4℉). The physical examination is significant for dry skin, a pustular rash over the patient’s shoulders and back, an accentuated second heart sound (S2) best heard in the second intercostal space at the right sternal border, and distal loss of vibration sensitivity in both feet. A fundoscopic examination shows small red dots in the superficial retinal layers suggestive of microaneurysms. The HbA1c is 9% and the urinalysis shows the following:\nColor Pale yellow (light/pale-to-dark/deep amber)\nClarity Cloudy\npH 6.6\nSpecific gravity 1.010\nGlucose 199 mg/dl\nKetones None\nNitrites Negative\nLeukocyte esterase Negative\nBilirubin Negative\nUrinary bilirubin Traces\nRed blood cells 3 RBCs\nProtein 120 mg/d\nRBCs ≤ 2 RBCs/hpf\nWBCs 22 WBCs/hpf\nEpithelial cells 27 squamous epithelial cells/hpf\nCasts 5 hyaline casts/lpf\nCrystals Occasional\nBacteria None\nYeast Present\nWhich of the following statements best describes the cause of this patient’s glucosuria?\nA. There is a disruption of primary active transport of glucose in the proximal renal tubules\nB. Secondary active transporters fail to completely reabsorb glucose in the renal tubules\nC. There is a disruption of passive transport of the glucose in the proximal renal tubules\nD. Glucosuria results from increased glomerular filtration rate\nChoose the correct option.",
"image": null
},
{
"idx": 17,
"question": "A 61-year-old woman presents to an outpatient clinic with fatigue and mild neck pain for a month. She adds that she is having difficulty swallowing. She denies trouble with her breathing but endorses 5–10 lb of unintentional weight loss over the past few months. On physical exam, the patient’s fingernails appear flat and mild conjunctival pallor is noted. An upper barium esophagram shows an upper esophageal web. A complete blood count reveals:\nHb% 10 gm/dL\nTotal count (WBC) 11,000 /mm3\nDifferential count:\nNeutrophile 70%\nLymphocytes 25%\nMonocytes 5%\nESR 10 mm/hr\nWhat is the most likely diagnosis?\nA. Plummer-Vinson syndrome\nB. Esophageal squamous cell carcinoma\nC. Zenker’s diverticulum\nD. Achalasia\n\nA. Plummer-Vinson syndrome\nB. Esophageal squamous cell carcinoma\nC. Zenker’s diverticulum\nD. Achalasia",
"options": [
"A. Plummer-Vinson syndrome",
"B. Esophageal squamous cell carcinoma",
"C. Zenker’s diverticulum",
"D. Achalasia"
],
"answer": "Plummer-Vinson syndrome",
"gen_text_store": "",
"pid": "17",
"query": "A 61-year-old woman presents to an outpatient clinic with fatigue and mild neck pain for a month. She adds that she is having difficulty swallowing. She denies trouble with her breathing but endorses 5–10 lb of unintentional weight loss over the past few months. On physical exam, the patient’s fingernails appear flat and mild conjunctival pallor is noted. An upper barium esophagram shows an upper esophageal web. A complete blood count reveals:\nHb% 10 gm/dL\nTotal count (WBC) 11,000 /mm3\nDifferential count:\nNeutrophile 70%\nLymphocytes 25%\nMonocytes 5%\nESR 10 mm/hr\nWhat is the most likely diagnosis?\nA. Plummer-Vinson syndrome\nB. Esophageal squamous cell carcinoma\nC. Zenker’s diverticulum\nD. Achalasia\nChoose the correct option.",
"image": null
},
{
"idx": 18,
"question": "A 28-year-old woman with no significant past medical history presents to her primary care physician with increased menstrual bleeding over the past three months. She also notes easy bruising and bleeding from her gums when brushing her teeth. She is sexually active with multiple partners and has no history of intravenous drug use. Physical exam is remarkable for petechiae and scattered ecchymoses on the patient's bilateral upper and lower extremities. Urine beta-HCG is negative. Laboratory results are as follows: Hgb 13.0 g/dL, WBCs 6,000/mL, platelets 95,000/mL, PT 13.2s, aPTT 30s. Peripheral blood smear shows normocytic, normochromic red blood cells and few platelets with no morphologic abnormalities. Which diagnostic study should be performed next?\nA. Serum factor VIII levels and von Willebrand factor activity\nB. Measurement of ADAMTS13 activity\nC. HIV and HCV testing\nD. Bone marrow aspiration\n\nA. Serum factor VIII levels and von Willebrand factor activity\nB. Measurement of ADAMTS13 activity\nC. HIV and HCV testing\nD. Bone marrow aspiration",
"options": [
"A. Serum factor VIII levels and von Willebrand factor activity",
"B. Measurement of ADAMTS13 activity",
"C. HIV and HCV testing",
"D. Bone marrow aspiration"
],
"answer": "HIV and HCV testing",
"gen_text_store": "",
"pid": "18",
"query": "A 28-year-old woman with no significant past medical history presents to her primary care physician with increased menstrual bleeding over the past three months. She also notes easy bruising and bleeding from her gums when brushing her teeth. She is sexually active with multiple partners and has no history of intravenous drug use. Physical exam is remarkable for petechiae and scattered ecchymoses on the patient's bilateral upper and lower extremities. Urine beta-HCG is negative. Laboratory results are as follows: Hgb 13.0 g/dL, WBCs 6,000/mL, platelets 95,000/mL, PT 13.2s, aPTT 30s. Peripheral blood smear shows normocytic, normochromic red blood cells and few platelets with no morphologic abnormalities. Which diagnostic study should be performed next?\nA. Serum factor VIII levels and von Willebrand factor activity\nB. Measurement of ADAMTS13 activity\nC. HIV and HCV testing\nD. Bone marrow aspiration\nChoose the correct option.",
"image": null
},
{
"idx": 19,
"question": "A 55-year-old man with a history of chronic glomerulonephritis due to IgA nephropathy presents to your office with bone pain. Which of the following laboratory findings would you most expect upon analysis of this patient's serum?\nA. Increased PTH, decreased calcium, increased phosphate, decreased calcitriol\nB. Decreased PTH, increased calcium, increased phosphate, increased calcitriol\nC. Decreased PTH, decreased calcium, increased phosphate, decreased calcitriol\nD. Normal PTH, normal calcium, normal phosphate, normal calcitriol\n\nA. Increased PTH, decreased calcium, increased phosphate, decreased calcitriol\nB. Decreased PTH, increased calcium, increased phosphate, increased calcitriol\nC. Decreased PTH, decreased calcium, increased phosphate, decreased calcitriol\nD. Normal PTH, normal calcium, normal phosphate, normal calcitriol",
"options": [
"A. Increased PTH, decreased calcium, increased phosphate, decreased calcitriol",
"B. Decreased PTH, increased calcium, increased phosphate, increased calcitriol",
"C. Decreased PTH, decreased calcium, increased phosphate, decreased calcitriol",
"D. Normal PTH, normal calcium, normal phosphate, normal calcitriol"
],
"answer": "Increased PTH, decreased calcium, increased phosphate, decreased calcitriol",
"gen_text_store": "",
"pid": "19",
"query": "A 55-year-old man with a history of chronic glomerulonephritis due to IgA nephropathy presents to your office with bone pain. Which of the following laboratory findings would you most expect upon analysis of this patient's serum?\nA. Increased PTH, decreased calcium, increased phosphate, decreased calcitriol\nB. Decreased PTH, increased calcium, increased phosphate, increased calcitriol\nC. Decreased PTH, decreased calcium, increased phosphate, decreased calcitriol\nD. Normal PTH, normal calcium, normal phosphate, normal calcitriol\nChoose the correct option.",
"image": null
},
{
"idx": 20,
"question": "A 50-year-old man presents to his primary care doctor following an inguinal hernia repair. The patient reports no pain in his lower abdomen or groin, no constipation, and states that he enjoys his usual diet. He denies any use of alcohol, tobacco, or illicit drugs. He has returned to work as a cruise ship attendant. Preoperative workup included chest radiography which demonstrated an opacification in his right middle lobe. The patient agrees to undergo computed tomography (CT) of his chest without contrast for further evaluation. The radiologist reports an 8 mm nodule in the patient's peripheral right middle lobe that has regular margins and appears calcified. One year later, the patient obtains another chest CT without contrast that reports the nodule size as 10 mm with similar characteristics. What is the most appropriate next step in management?\nA. CT chest without contrast in 24 months\nB. Positive emission tomography (PET) of chest now\nC. Right middle lobectomy now\nD. Bronchoscopy-guided biopsy now\n\nA. CT chest without contrast in 24 months\nB. Positive emission tomography (PET) of chest now\nC. Right middle lobectomy now\nD. Bronchoscopy-guided biopsy now",
"options": [
"A. CT chest without contrast in 24 months",
"B. Positive emission tomography (PET) of chest now",
"C. Right middle lobectomy now",
"D. Bronchoscopy-guided biopsy now"
],
"answer": "Positive emission tomography (PET) of chest now",
"gen_text_store": "",
"pid": "20",
"query": "A 50-year-old man presents to his primary care doctor following an inguinal hernia repair. The patient reports no pain in his lower abdomen or groin, no constipation, and states that he enjoys his usual diet. He denies any use of alcohol, tobacco, or illicit drugs. He has returned to work as a cruise ship attendant. Preoperative workup included chest radiography which demonstrated an opacification in his right middle lobe. The patient agrees to undergo computed tomography (CT) of his chest without contrast for further evaluation. The radiologist reports an 8 mm nodule in the patient's peripheral right middle lobe that has regular margins and appears calcified. One year later, the patient obtains another chest CT without contrast that reports the nodule size as 10 mm with similar characteristics. What is the most appropriate next step in management?\nA. CT chest without contrast in 24 months\nB. Positive emission tomography (PET) of chest now\nC. Right middle lobectomy now\nD. Bronchoscopy-guided biopsy now\nChoose the correct option.",
"image": null
},
{
"idx": 21,
"question": "An 8-year-old boy is brought to the physician by his parents for short stature. Neither his clothing nor his shoe size have changed over the past year. He also frequently bumps into obstacles such as furniture and has headaches at night. He is always thirsty for cold water and has been urinating more frequently. Three years ago, he had an asthma attack that was treated with albuterol and a one-week course of steroids. His mother has Hashimoto's thyroiditis and had precocious puberty. His mother's height is 147 cm (4 ft 10 in) and his father's height is 160 cm (5 ft 3 in). He is at the 5th percentile for height and 5th percentile for weight. His temperature is 37°C (98.6°F), pulse is 98/min, respirations are 16/min, and blood pressure is 100/64 mm Hg. Examination shows a soft and nontender abdomen. The genitals and pubic hair are both Tanner stage 1. Axillary hair is absent. Patellar reflexes are 1+ bilaterally. Laboratory studies show:\nNa+ 145 mEq/L\nK+ 4.1 mEq/L\nCl- 102 mEq/L\nHCO3- 25 mEq/L\nCa2+ 9.4 mg/dL\nGlucose 110 mg/dL\nThyroid-stimulating hormone 0.3 μU/mL\nThyroxine 3.9 μg/dL\nInsulin-like growth factor 1 24 ng/mL (N=61–356 ng/mL)\nInsulin-like growth factor binding protein 3 2.1 mcg/mL (N=1.6–6.5 μg/mL)\nWhich of the following is the most likely diagnosis?\"\nA. Rathke cleft cyst\nB. Craniopharyngioma\nC. Multiple endocrine neoplasia\nD. Pituitary adenoma\n\nA. Rathke cleft cyst\nB. Craniopharyngioma\nC. Multiple endocrine neoplasia\nD. Pituitary adenoma",
"options": [
"A. Rathke cleft cyst",
"B. Craniopharyngioma",
"C. Multiple endocrine neoplasia",
"D. Pituitary adenoma"
],
"answer": "Craniopharyngioma",
"gen_text_store": "",
"pid": "21",
"query": "An 8-year-old boy is brought to the physician by his parents for short stature. Neither his clothing nor his shoe size have changed over the past year. He also frequently bumps into obstacles such as furniture and has headaches at night. He is always thirsty for cold water and has been urinating more frequently. Three years ago, he had an asthma attack that was treated with albuterol and a one-week course of steroids. His mother has Hashimoto's thyroiditis and had precocious puberty. His mother's height is 147 cm (4 ft 10 in) and his father's height is 160 cm (5 ft 3 in). He is at the 5th percentile for height and 5th percentile for weight. His temperature is 37°C (98.6°F), pulse is 98/min, respirations are 16/min, and blood pressure is 100/64 mm Hg. Examination shows a soft and nontender abdomen. The genitals and pubic hair are both Tanner stage 1. Axillary hair is absent. Patellar reflexes are 1+ bilaterally. Laboratory studies show:\nNa+ 145 mEq/L\nK+ 4.1 mEq/L\nCl- 102 mEq/L\nHCO3- 25 mEq/L\nCa2+ 9.4 mg/dL\nGlucose 110 mg/dL\nThyroid-stimulating hormone 0.3 μU/mL\nThyroxine 3.9 μg/dL\nInsulin-like growth factor 1 24 ng/mL (N=61–356 ng/mL)\nInsulin-like growth factor binding protein 3 2.1 mcg/mL (N=1.6–6.5 μg/mL)\nWhich of the following is the most likely diagnosis?\"\nA. Rathke cleft cyst\nB. Craniopharyngioma\nC. Multiple endocrine neoplasia\nD. Pituitary adenoma\nChoose the correct option.",
"image": null
},
{
"idx": 22,
"question": "A 9-month-old boy is brought to his pediatrician by his mother for a routine health checkup. The boy was born at 39 weeks gestation via spontaneous vaginal delivery. He is up to date on all vaccines and is meeting all developmental milestones. He was breastfed for the first 3 months and then switched to cow’s milk and about two months ago she started giving him fruits and vegetables. Family history is noncontributory. Today, his heart rate is 120/min, respiratory rate is 40/min, blood pressure is 90/50 mm Hg, and temperature of 37.0°C (98.6°F). On examination, he has a heartbeat with a regular rate and rhythm and his lungs are clear to auscultation bilaterally. Generally, the boy looks pale. His weight and height fall within the expected range. A complete blood count (CBC) shows the following:\nHemoglobin (Hb): 9.1 g/dL\nMean corpuscular volume (MCV): 65 fL\nTotal iron binding capacity (TIBC): 550 μg/dL\nSerum iron: 45 µg/dL\nSerum lead: < 5 µg/dL\nWhat is the best treatment for this patient?\nA. Iron supplementation only\nB. Proper diet and iron supplementation\nC. Multivitamins\nD. Proper diet only\n\nA. Iron supplementation only\nB. Proper diet and iron supplementation\nC. Multivitamins\nD. Proper diet only",
"options": [
"A. Iron supplementation only",
"B. Proper diet and iron supplementation",
"C. Multivitamins",
"D. Proper diet only"
],
"answer": "Proper diet and iron supplementation",
"gen_text_store": "",
"pid": "22",
"query": "A 9-month-old boy is brought to his pediatrician by his mother for a routine health checkup. The boy was born at 39 weeks gestation via spontaneous vaginal delivery. He is up to date on all vaccines and is meeting all developmental milestones. He was breastfed for the first 3 months and then switched to cow’s milk and about two months ago she started giving him fruits and vegetables. Family history is noncontributory. Today, his heart rate is 120/min, respiratory rate is 40/min, blood pressure is 90/50 mm Hg, and temperature of 37.0°C (98.6°F). On examination, he has a heartbeat with a regular rate and rhythm and his lungs are clear to auscultation bilaterally. Generally, the boy looks pale. His weight and height fall within the expected range. A complete blood count (CBC) shows the following:\nHemoglobin (Hb): 9.1 g/dL\nMean corpuscular volume (MCV): 65 fL\nTotal iron binding capacity (TIBC): 550 μg/dL\nSerum iron: 45 µg/dL\nSerum lead: < 5 µg/dL\nWhat is the best treatment for this patient?\nA. Iron supplementation only\nB. Proper diet and iron supplementation\nC. Multivitamins\nD. Proper diet only\nChoose the correct option.",
"image": null
},
{
"idx": 23,
"question": "Three patients present to the pediatrician for routine well-child visits. The first child’s mother reports that he seems to be breastfeeding well and voids at least eight times per day. His stools are a yellow color, and he does not seem to be straining. In the office, he can lift his head and chest when in the prone position, and he can track an object with his eyes to the midline. His hands remain fisted 50% of the time.\n\nThe second child’s parents report that she is doing well at home and seems to enjoy playing with her older brother. In the office, she can roll from supine to prone and can transfer her rattle from hand to hand. She cannot yet say any words.\n\nThe third child’s father reports that he is starting to explore the world around him. He has begun taking independent steps at home. In the office, he seems to recognize the name of several objects, but he cannot follow the direction to “grab the ball.” All three children are assessed as developmentally normal.\n\nWhich of the following represents these patient's respective ages?\nA. Ages 1 month, 4 months, and 9 months\nB. Ages 2 months, 4 months, and 12 months\nC. Ages 2 months, 6 months, and 9 months\nD. Ages 2 months, 6 months, and 12 months\n\nA. Ages 1 month, 4 months, and 9 months\nB. Ages 2 months, 4 months, and 12 months\nC. Ages 2 months, 6 months, and 9 months\nD. Ages 2 months, 6 months, and 12 months",
"options": [
"A. Ages 1 month, 4 months, and 9 months",
"B. Ages 2 months, 4 months, and 12 months",
"C. Ages 2 months, 6 months, and 9 months",
"D. Ages 2 months, 6 months, and 12 months"
],
"answer": "Ages 2 months, 6 months, and 12 months",
"gen_text_store": "",
"pid": "23",
"query": "Three patients present to the pediatrician for routine well-child visits. The first child’s mother reports that he seems to be breastfeeding well and voids at least eight times per day. His stools are a yellow color, and he does not seem to be straining. In the office, he can lift his head and chest when in the prone position, and he can track an object with his eyes to the midline. His hands remain fisted 50% of the time.\n\nThe second child’s parents report that she is doing well at home and seems to enjoy playing with her older brother. In the office, she can roll from supine to prone and can transfer her rattle from hand to hand. She cannot yet say any words.\n\nThe third child’s father reports that he is starting to explore the world around him. He has begun taking independent steps at home. In the office, he seems to recognize the name of several objects, but he cannot follow the direction to “grab the ball.” All three children are assessed as developmentally normal.\n\nWhich of the following represents these patient's respective ages?\nA. Ages 1 month, 4 months, and 9 months\nB. Ages 2 months, 4 months, and 12 months\nC. Ages 2 months, 6 months, and 9 months\nD. Ages 2 months, 6 months, and 12 months\nChoose the correct option.",
"image": null
},
{
"idx": 24,
"question": "A 22-year-old primigravida presents for a regular prenatal visit at 16 weeks gestation. She is concerned about the results of a dipstick test she performed at home, which showed 1+ glucose. She does not know if her liquid consumption has increased, but she urinates more frequently than before. The course of her pregnancy has been unremarkable and she has no significant co-morbidities. The BMI is 25.6 kg/cm2 and she has gained 3 kg (6.72 lb) during the pregnancy. The blood pressure is 110/80 mm Hg, the heart rate is 82/min, the respiratory rate is 14/min, and the temperature is 36.6℃ (97.9℉). The lungs are clear to auscultation, the heart sounds are normal with no murmurs, and there is no abdominal or costovertebral angle tenderness. The laboratory tests show the following results:\nFasting glucose 97 mg/L\nALT 12 IU/L\nAST 14 IU/L\nTotal bilirubin 0.8 mg/dL(15 µmol/L)\nPlasma creatinine 0.7 mg/dL (61.9 µmol/L)\nWhich of the following tests are indicated to determine the cause of the abnormal dipstick test results?\nA. HbA1c measurement\nB. No tests required\nC. Urinalysis\nD. Oral glucose tolerance test\n\nA. HbA1c measurement\nB. No tests required\nC. Urinalysis\nD. Oral glucose tolerance test",
"options": [
"A. HbA1c measurement",
"B. No tests required",
"C. Urinalysis",
"D. Oral glucose tolerance test"
],
"answer": "No tests required",
"gen_text_store": "",
"pid": "24",
"query": "A 22-year-old primigravida presents for a regular prenatal visit at 16 weeks gestation. She is concerned about the results of a dipstick test she performed at home, which showed 1+ glucose. She does not know if her liquid consumption has increased, but she urinates more frequently than before. The course of her pregnancy has been unremarkable and she has no significant co-morbidities. The BMI is 25.6 kg/cm2 and she has gained 3 kg (6.72 lb) during the pregnancy. The blood pressure is 110/80 mm Hg, the heart rate is 82/min, the respiratory rate is 14/min, and the temperature is 36.6℃ (97.9℉). The lungs are clear to auscultation, the heart sounds are normal with no murmurs, and there is no abdominal or costovertebral angle tenderness. The laboratory tests show the following results:\nFasting glucose 97 mg/L\nALT 12 IU/L\nAST 14 IU/L\nTotal bilirubin 0.8 mg/dL(15 µmol/L)\nPlasma creatinine 0.7 mg/dL (61.9 µmol/L)\nWhich of the following tests are indicated to determine the cause of the abnormal dipstick test results?\nA. HbA1c measurement\nB. No tests required\nC. Urinalysis\nD. Oral glucose tolerance test\nChoose the correct option.",
"image": null
},
{
"idx": 25,
"question": "A four-day-old neonate is brought to the pediatrician with vaginal discharge for the last two days. Her mother is concerned about the blood-tinged discharge but states that her daughter has been feeding and voiding well. The neonate was delivered at 39 weeks gestation by an uncomplicated vaginal delivery, and she and her mother were discharged home after two days. The prenatal course was complicated by chlamydia in the mother during the first trimester, for which she and the partner were both treated with a negative test of cure. The neonate’s biological father is no longer involved the patient's care, but her mother’s boyfriend has been caring for the baby whenever the mother rests. At this visit, the neonate’s temperature is 98.5°F (36.9°C), pulse is 138/min, and respirations are 51/min. She appears comfortable, and cardiopulmonary and abdominal exams are unremarkable. There are no bruises or marks on her skin. Examination of the genitals reveals no vulvar irritation or skin changes, but there is scant pink mucoid discharge at the introitus. Which of the following is the best next step in management?\nA. Vaginal exam under anesthesia\nB. Vaginal culture\nC. Warm water irrigation of the vagina\nD. Reassurance\n\nA. Vaginal exam under anesthesia\nB. Vaginal culture\nC. Warm water irrigation of the vagina\nD. Reassurance",
"options": [
"A. Vaginal exam under anesthesia",
"B. Vaginal culture",
"C. Warm water irrigation of the vagina",
"D. Reassurance"
],
"answer": "Reassurance",
"gen_text_store": "",
"pid": "25",
"query": "A four-day-old neonate is brought to the pediatrician with vaginal discharge for the last two days. Her mother is concerned about the blood-tinged discharge but states that her daughter has been feeding and voiding well. The neonate was delivered at 39 weeks gestation by an uncomplicated vaginal delivery, and she and her mother were discharged home after two days. The prenatal course was complicated by chlamydia in the mother during the first trimester, for which she and the partner were both treated with a negative test of cure. The neonate’s biological father is no longer involved the patient's care, but her mother’s boyfriend has been caring for the baby whenever the mother rests. At this visit, the neonate’s temperature is 98.5°F (36.9°C), pulse is 138/min, and respirations are 51/min. She appears comfortable, and cardiopulmonary and abdominal exams are unremarkable. There are no bruises or marks on her skin. Examination of the genitals reveals no vulvar irritation or skin changes, but there is scant pink mucoid discharge at the introitus. Which of the following is the best next step in management?\nA. Vaginal exam under anesthesia\nB. Vaginal culture\nC. Warm water irrigation of the vagina\nD. Reassurance\nChoose the correct option.",
"image": null
},
{
"idx": 26,
"question": "A group of researchers decided to explore whether the estimates of incidence and prevalence rates of systemic lupus erythematosus (SLE) were influenced by the number of years it took to examine administrative data. These estimates were not only based on hospital discharges, but also on physician billing codes. For study purposes, the researchers labeled incident cases at the initial occurrence of SLE diagnosis in the hospital database, while prevalent cases were those that were coded as harboring SLE at any time, with patients maintaining their diagnosis until death. Which statement is true regarding the relationship between incidence and prevalence rates during the time period that might be chosen for this specific study?\nA. Incidence rates will be higher during shorter time periods than longer periods.\nB. The prevalence of SLE during consecutively shorter time windows will be overestimated.\nC. The inclusion of attack rates would increase incidence estimates in longer time periods.\nD. The inclusion of attack rates would decrease incidence estimates in shorter time periods.\n\nA. Incidence rates will be higher during shorter time periods than longer periods.\nB. The prevalence of SLE during consecutively shorter time windows will be overestimated.\nC. The inclusion of attack rates would increase incidence estimates in longer time periods.\nD. The inclusion of attack rates would decrease incidence estimates in shorter time periods.",
"options": [
"A. Incidence rates will be higher during shorter time periods than longer periods.",
"B. The prevalence of SLE during consecutively shorter time windows will be overestimated.",
"C. The inclusion of attack rates would increase incidence estimates in longer time periods.",
"D. The inclusion of attack rates would decrease incidence estimates in shorter time periods."
],
"answer": "Incidence rates will be higher during shorter time periods than longer periods.",
"gen_text_store": "",
"pid": "26",
"query": "A group of researchers decided to explore whether the estimates of incidence and prevalence rates of systemic lupus erythematosus (SLE) were influenced by the number of years it took to examine administrative data. These estimates were not only based on hospital discharges, but also on physician billing codes. For study purposes, the researchers labeled incident cases at the initial occurrence of SLE diagnosis in the hospital database, while prevalent cases were those that were coded as harboring SLE at any time, with patients maintaining their diagnosis until death. Which statement is true regarding the relationship between incidence and prevalence rates during the time period that might be chosen for this specific study?\nA. Incidence rates will be higher during shorter time periods than longer periods.\nB. The prevalence of SLE during consecutively shorter time windows will be overestimated.\nC. The inclusion of attack rates would increase incidence estimates in longer time periods.\nD. The inclusion of attack rates would decrease incidence estimates in shorter time periods.\nChoose the correct option.",
"image": null
},
{
"idx": 27,
"question": "A 76-year-old woman visits a physician for a general medical examination. She is asymptomatic. Six months prior, she had a cerebral stroke with left hemiparesis, from which she has almost completely recovered with physiotherapy. She has a history of hypertension and atrial fibrillation (AF). She has no significant ischemic, valvular, or structural heart disease. She takes metoprolol, amlodipine, warfarin, and atorvastatin. Blood pressure is 125/70 mm Hg, pulse is 75/min with an irregular rhythm. Respirations are 13/min. She has a minor limp and weakness in her left arm and leg. Heart exam shows no abnormalities other than irregular beats. To assess adherence and therapeutic efficacy in this patient, which of the following studies should be ordered?\nA. Echocardiogram\nB. International normalized ratio\nC. Partial thromboplastin time\nD. Serum drug levels\n\nA. Echocardiogram\nB. International normalized ratio\nC. Partial thromboplastin time\nD. Serum drug levels",
"options": [
"A. Echocardiogram",
"B. International normalized ratio",
"C. Partial thromboplastin time",
"D. Serum drug levels"
],
"answer": "International normalized ratio",
"gen_text_store": "",
"pid": "27",
"query": "A 76-year-old woman visits a physician for a general medical examination. She is asymptomatic. Six months prior, she had a cerebral stroke with left hemiparesis, from which she has almost completely recovered with physiotherapy. She has a history of hypertension and atrial fibrillation (AF). She has no significant ischemic, valvular, or structural heart disease. She takes metoprolol, amlodipine, warfarin, and atorvastatin. Blood pressure is 125/70 mm Hg, pulse is 75/min with an irregular rhythm. Respirations are 13/min. She has a minor limp and weakness in her left arm and leg. Heart exam shows no abnormalities other than irregular beats. To assess adherence and therapeutic efficacy in this patient, which of the following studies should be ordered?\nA. Echocardiogram\nB. International normalized ratio\nC. Partial thromboplastin time\nD. Serum drug levels\nChoose the correct option.",
"image": null
},
{
"idx": 28,
"question": "A 16-year-old boy with a seizure disorder and cognitive delay is brought to the physician because of progressively worsening right lower extremity weakness for the past 6 months. He does not make eye contact and sits very close to his mother. Physical examination shows a grade 3/6 holosystolic murmur at the cardiac apex. Neurological examination shows decreased strength in the right lower leg with normal strength in the other extremities. Fundoscopic examination shows several multinodular, calcified lesions in the retina bilaterally. A photograph of his skin findings is shown. This patient's condition is most likely due to a mutation in which of the following?\nA. NF1 gene on chromosome 17\nB. NF2 gene on chromosome 22\nC. TSC1 gene on chromosome 9\nD. VHL gene on chromosome 3\n\nA. NF1 gene on chromosome 17\nB. NF2 gene on chromosome 22\nC. TSC1 gene on chromosome 9\nD. VHL gene on chromosome 3",
"options": [
"A. NF1 gene on chromosome 17",
"B. NF2 gene on chromosome 22",
"C. TSC1 gene on chromosome 9",
"D. VHL gene on chromosome 3"
],
"answer": "TSC1 gene on chromosome 9",
"gen_text_store": "",
"pid": "28",
"query": "A 16-year-old boy with a seizure disorder and cognitive delay is brought to the physician because of progressively worsening right lower extremity weakness for the past 6 months. He does not make eye contact and sits very close to his mother. Physical examination shows a grade 3/6 holosystolic murmur at the cardiac apex. Neurological examination shows decreased strength in the right lower leg with normal strength in the other extremities. Fundoscopic examination shows several multinodular, calcified lesions in the retina bilaterally. A photograph of his skin findings is shown. This patient's condition is most likely due to a mutation in which of the following?\nA. NF1 gene on chromosome 17\nB. NF2 gene on chromosome 22\nC. TSC1 gene on chromosome 9\nD. VHL gene on chromosome 3\nChoose the correct option.",
"image": null
},
{
"idx": 29,
"question": "A 75-year-old woman presents to the emergency department with 30 minutes of slurred speech and arm weakness. On the drive over to the hospital, her symptoms have resolved completely. The patient has a past medical history of hypertension, atrial fibrillation, diabetes, morbid obesity, gout, and vascular claudication. Her temperature is 99.0°F (37.2°C), blood pressure is 184/111 mmHg, pulse is 88/min, respirations are 15/min, and oxygen saturation is 98% on room air. Physical exam reveals cranial nerves II-XII as grossly intact with normal strength and sensation in the patient's upper and lower extremities. The patient's memory is intact and her speech seems normal and fluent. Her gait is stable with no ataxia. An initial head CT demonstrates diffuse atrophy which is consistent with previous head CT scans. Which of the following is the best next step in management?\nA. CT angiogram\nB. Echocardiogram\nC. Heparin\nD. MRI\n\nA. CT angiogram\nB. Echocardiogram\nC. Heparin\nD. MRI",
"options": [
"A. CT angiogram",
"B. Echocardiogram",
"C. Heparin",
"D. MRI"
],
"answer": "CT angiogram",
"gen_text_store": "",
"pid": "29",
"query": "A 75-year-old woman presents to the emergency department with 30 minutes of slurred speech and arm weakness. On the drive over to the hospital, her symptoms have resolved completely. The patient has a past medical history of hypertension, atrial fibrillation, diabetes, morbid obesity, gout, and vascular claudication. Her temperature is 99.0°F (37.2°C), blood pressure is 184/111 mmHg, pulse is 88/min, respirations are 15/min, and oxygen saturation is 98% on room air. Physical exam reveals cranial nerves II-XII as grossly intact with normal strength and sensation in the patient's upper and lower extremities. The patient's memory is intact and her speech seems normal and fluent. Her gait is stable with no ataxia. An initial head CT demonstrates diffuse atrophy which is consistent with previous head CT scans. Which of the following is the best next step in management?\nA. CT angiogram\nB. Echocardiogram\nC. Heparin\nD. MRI\nChoose the correct option.",
"image": null
},
{
"idx": 30,
"question": "An investigator is studying the pattern of glutamate release from presynaptic nerve terminals in human volunteers with Alzheimer disease. The concentration of glutamate in the CA1 region of the hippocampus is measured using magnetic resonance spectroscopy after Schaffer collateral fibers are electrically stimulated. Which of the following events most likely occurs immediately prior to the release of neurotransmitters?\nA. Activation of G protein-coupled receptors\nB. Accumulation of cAMP\nC. Opening of ligand-gated ion channels\nD. Influx of calcium\n\nA. Activation of G protein-coupled receptors\nB. Accumulation of cAMP\nC. Opening of ligand-gated ion channels\nD. Influx of calcium",
"options": [
"A. Activation of G protein-coupled receptors",
"B. Accumulation of cAMP",
"C. Opening of ligand-gated ion channels",
"D. Influx of calcium"
],
"answer": "Influx of calcium",
"gen_text_store": "",
"pid": "30",
"query": "An investigator is studying the pattern of glutamate release from presynaptic nerve terminals in human volunteers with Alzheimer disease. The concentration of glutamate in the CA1 region of the hippocampus is measured using magnetic resonance spectroscopy after Schaffer collateral fibers are electrically stimulated. Which of the following events most likely occurs immediately prior to the release of neurotransmitters?\nA. Activation of G protein-coupled receptors\nB. Accumulation of cAMP\nC. Opening of ligand-gated ion channels\nD. Influx of calcium\nChoose the correct option.",
"image": null
},
{
"idx": 31,
"question": "A 35-year-old woman presents to her primary care provider concerned that she may be pregnant. She has a history of regular menstruation every 4 weeks that lasts about 4 days with mild to moderate bleeding, but she missed her last period 2 weeks ago. A home pregnancy test was positive. She has a 6-year history of hyperthyroidism that is well-controlled with daily methimazole. She is currently asymptomatic and has no complaints or concerns. A blood specimen is taken and confirms the diagnosis. Additionally, her thyroid-stimulating hormone (TSH) is 2.0 μU/mL. Which of the following is the next best step in the management of this patient?\nA. Continue methimazole\nB. Discontinue methimazole, start propylthiouracil\nC. Add glucocorticoids\nD. Refer for radioiodine therapy\n\nA. Continue methimazole\nB. Discontinue methimazole, start propylthiouracil\nC. Add glucocorticoids\nD. Refer for radioiodine therapy",
"options": [
"A. Continue methimazole",
"B. Discontinue methimazole, start propylthiouracil",
"C. Add glucocorticoids",
"D. Refer for radioiodine therapy"
],
"answer": "Discontinue methimazole, start propylthiouracil",
"gen_text_store": "",
"pid": "31",
"query": "A 35-year-old woman presents to her primary care provider concerned that she may be pregnant. She has a history of regular menstruation every 4 weeks that lasts about 4 days with mild to moderate bleeding, but she missed her last period 2 weeks ago. A home pregnancy test was positive. She has a 6-year history of hyperthyroidism that is well-controlled with daily methimazole. She is currently asymptomatic and has no complaints or concerns. A blood specimen is taken and confirms the diagnosis. Additionally, her thyroid-stimulating hormone (TSH) is 2.0 μU/mL. Which of the following is the next best step in the management of this patient?\nA. Continue methimazole\nB. Discontinue methimazole, start propylthiouracil\nC. Add glucocorticoids\nD. Refer for radioiodine therapy\nChoose the correct option.",
"image": null
},
{
"idx": 32,
"question": "A 63-year-old man is aiming to improve his health by eating a well balanced diet, walking daily, and quitting smoking following a 45-year smoking history. While on his daily walks he notices a strong cramping pain in his calves that consistently appears after a mile of walking. He sees his physician and a diagnosis of peripheral artery disease with intermittent claudication is made. To improve his symptoms, cilostazol is prescribed. What is the mechanism of action of this medication?\nA. Irreversible cyclooxygenase inhibitor\nB. Thromboxane synthase inhibitor\nC. Adenosine diphosphate receptor inhibitor\nD. Phosphodiesterase inhibitor\n\nA. Irreversible cyclooxygenase inhibitor\nB. Thromboxane synthase inhibitor\nC. Adenosine diphosphate receptor inhibitor\nD. Phosphodiesterase inhibitor",
"options": [
"A. Irreversible cyclooxygenase inhibitor",
"B. Thromboxane synthase inhibitor",
"C. Adenosine diphosphate receptor inhibitor",
"D. Phosphodiesterase inhibitor"
],
"answer": "Phosphodiesterase inhibitor",
"gen_text_store": "",
"pid": "32",
"query": "A 63-year-old man is aiming to improve his health by eating a well balanced diet, walking daily, and quitting smoking following a 45-year smoking history. While on his daily walks he notices a strong cramping pain in his calves that consistently appears after a mile of walking. He sees his physician and a diagnosis of peripheral artery disease with intermittent claudication is made. To improve his symptoms, cilostazol is prescribed. What is the mechanism of action of this medication?\nA. Irreversible cyclooxygenase inhibitor\nB. Thromboxane synthase inhibitor\nC. Adenosine diphosphate receptor inhibitor\nD. Phosphodiesterase inhibitor\nChoose the correct option.",
"image": null
},
{
"idx": 33,
"question": "A 25-year-old woman comes to the physician because of irregular menstrual bleeding. Menses have occurred at 30- to 90-day intervals since menarche at the age of 12 years. Her last menstrual period was 6 weeks ago. She is sexually active with her husband and they do not use condoms. There is no personal or family history of serious illness. She is 170 cm (5 ft 7 in) tall and weighs 73 kg (161 lb); BMI is 25.3 kg/m2. Her vital signs are within normal limits. Examination shows oily skin and severe acne on the face. There is dark hair on the upper lip and around both nipples. Laboratory studies show:\nDehydroepiandrosterone sulfate 6.2 μg/mL (N=0.5–5.4)\nFollicle-stimulating hormone 20 mIU/mL\nLuteinizing hormone 160 mIU/mL\nTestosterone 4.1 nmol/L (N < 3.5)\nA urine pregnancy test is negative. Which of the following tests is the most appropriate next step in screening for comorbidities in this patient?\"\nA. 17-hydroxyprogesterone and cortisol level measurements\nB. CA-125 level measurement\nC. Blood glucose and cholesterol level measurements\nD. TSH and T4 level measurements\n\nA. 17-hydroxyprogesterone and cortisol level measurements\nB. CA-125 level measurement\nC. Blood glucose and cholesterol level measurements\nD. TSH and T4 level measurements",
"options": [
"A. 17-hydroxyprogesterone and cortisol level measurements",
"B. CA-125 level measurement",
"C. Blood glucose and cholesterol level measurements",
"D. TSH and T4 level measurements"
],
"answer": "Blood glucose and cholesterol level measurements",
"gen_text_store": "",
"pid": "33",
"query": "A 25-year-old woman comes to the physician because of irregular menstrual bleeding. Menses have occurred at 30- to 90-day intervals since menarche at the age of 12 years. Her last menstrual period was 6 weeks ago. She is sexually active with her husband and they do not use condoms. There is no personal or family history of serious illness. She is 170 cm (5 ft 7 in) tall and weighs 73 kg (161 lb); BMI is 25.3 kg/m2. Her vital signs are within normal limits. Examination shows oily skin and severe acne on the face. There is dark hair on the upper lip and around both nipples. Laboratory studies show:\nDehydroepiandrosterone sulfate 6.2 μg/mL (N=0.5–5.4)\nFollicle-stimulating hormone 20 mIU/mL\nLuteinizing hormone 160 mIU/mL\nTestosterone 4.1 nmol/L (N < 3.5)\nA urine pregnancy test is negative. Which of the following tests is the most appropriate next step in screening for comorbidities in this patient?\"\nA. 17-hydroxyprogesterone and cortisol level measurements\nB. CA-125 level measurement\nC. Blood glucose and cholesterol level measurements\nD. TSH and T4 level measurements\nChoose the correct option.",
"image": null
},
{
"idx": 34,
"question": "During the normal catabolism of protein, urea and ammonia are produced as waste products. If these waste products are not cleared by the liver and kidneys, hyperammonemia can occur, leading to confusion and delirium. Fortunately, a healthy liver can clear these waste products via the urea cycle. Which of the following reactions is the rate limiting step in this cycle?\nA. NH3 + HCO3- + 2 ATP --> carbamoyl phosphate + 2 ADP + Pi\nB. Carbamoyl phosphate + ornithine --> citrulline+ Pi\nC. Citrulline + aspartate + ATP --> arginosuccinate + AMP + PPi\nD. Arginine + H20 --> ornithine + urea\n\nA. NH3 + HCO3- + 2 ATP --> carbamoyl phosphate + 2 ADP + Pi\nB. Carbamoyl phosphate + ornithine --> citrulline+ Pi\nC. Citrulline + aspartate + ATP --> arginosuccinate + AMP + PPi\nD. Arginine + H20 --> ornithine + urea",
"options": [
"A. NH3 + HCO3- + 2 ATP --> carbamoyl phosphate + 2 ADP + Pi",
"B. Carbamoyl phosphate + ornithine --> citrulline+ Pi",
"C. Citrulline + aspartate + ATP --> arginosuccinate + AMP + PPi",
"D. Arginine + H20 --> ornithine + urea"
],
"answer": "NH3 + HCO3- + 2 ATP --> carbamoyl phosphate + 2 ADP + Pi",
"gen_text_store": "",
"pid": "34",
"query": "During the normal catabolism of protein, urea and ammonia are produced as waste products. If these waste products are not cleared by the liver and kidneys, hyperammonemia can occur, leading to confusion and delirium. Fortunately, a healthy liver can clear these waste products via the urea cycle. Which of the following reactions is the rate limiting step in this cycle?\nA. NH3 + HCO3- + 2 ATP --> carbamoyl phosphate + 2 ADP + Pi\nB. Carbamoyl phosphate + ornithine --> citrulline+ Pi\nC. Citrulline + aspartate + ATP --> arginosuccinate + AMP + PPi\nD. Arginine + H20 --> ornithine + urea\nChoose the correct option.",
"image": null
},
{
"idx": 35,
"question": "A 65-year-old man with metastatic lung cancer has been experiencing severe, unremitting pain. He has required escalating doses of oral morphine, but is now having dose limiting side-effects. His pain management team recommends using a medication that can reduce his opioid need through interaction with the NMDA-receptor. Which of the following was the most likely recommended agent?\nA. Propofol\nB. Ketamine\nC. Fentanyl\nD. Midazolam\n\nA. Propofol\nB. Ketamine\nC. Fentanyl\nD. Midazolam",
"options": [
"A. Propofol",
"B. Ketamine",
"C. Fentanyl",
"D. Midazolam"
],
"answer": "Ketamine",
"gen_text_store": "",
"pid": "35",
"query": "A 65-year-old man with metastatic lung cancer has been experiencing severe, unremitting pain. He has required escalating doses of oral morphine, but is now having dose limiting side-effects. His pain management team recommends using a medication that can reduce his opioid need through interaction with the NMDA-receptor. Which of the following was the most likely recommended agent?\nA. Propofol\nB. Ketamine\nC. Fentanyl\nD. Midazolam\nChoose the correct option.",
"image": null
},
{
"idx": 36,
"question": "An 81-year-old man is brought to the clinic by his son to be evaluated for memory issues. The patient’s son says he has difficulty remembering recent events and names. He says the patient’s symptoms have progressively worsened over the last several years but became acutely worse just recently. Also, yesterday, the patient complained that he could not see out of his right eye, but today he can. When asked about these concerns, the patient seems to have no insight into the problem and reports feeling well. His medical history is significant for diabetes mellitus type 2 and hypertension. He had a left basal ganglia hemorrhage 12 years ago and a right middle cerebral artery infarction 4 years ago. Current medications are amlodipine, aspirin, clopidogrel, metformin, sitagliptin, and valsartan. He lives with his son and can feed himself and change his clothes. There is no history of urinary or fecal incontinence. His vitals include: blood pressure 137/82 mm Hg, pulse 78/min, respiratory rate 16/min, temperature 37.0°C (98.6°F). On physical examination, the patient is alert and oriented. He is unable to perform simple arithmetic calculations and the mini-mental status exam is inconclusive. He can write his name and comprehend written instructions. Muscle strength is 4/5 on the right side. The tone is also slightly reduced on the right side with exaggerated reflexes. His gait is hemiparetic. Which of the following is the most likely diagnosis in this patient?\nA. Alzheimer's disease\nB. Lewy body dementia\nC. Normal-pressure hydrocephalus\nD. Vascular dementia\n\nA. Alzheimer's disease\nB. Lewy body dementia\nC. Normal-pressure hydrocephalus\nD. Vascular dementia",
"options": [
"A. Alzheimer's disease",
"B. Lewy body dementia",
"C. Normal-pressure hydrocephalus",
"D. Vascular dementia"
],
"answer": "Vascular dementia",
"gen_text_store": "",
"pid": "36",
"query": "An 81-year-old man is brought to the clinic by his son to be evaluated for memory issues. The patient’s son says he has difficulty remembering recent events and names. He says the patient’s symptoms have progressively worsened over the last several years but became acutely worse just recently. Also, yesterday, the patient complained that he could not see out of his right eye, but today he can. When asked about these concerns, the patient seems to have no insight into the problem and reports feeling well. His medical history is significant for diabetes mellitus type 2 and hypertension. He had a left basal ganglia hemorrhage 12 years ago and a right middle cerebral artery infarction 4 years ago. Current medications are amlodipine, aspirin, clopidogrel, metformin, sitagliptin, and valsartan. He lives with his son and can feed himself and change his clothes. There is no history of urinary or fecal incontinence. His vitals include: blood pressure 137/82 mm Hg, pulse 78/min, respiratory rate 16/min, temperature 37.0°C (98.6°F). On physical examination, the patient is alert and oriented. He is unable to perform simple arithmetic calculations and the mini-mental status exam is inconclusive. He can write his name and comprehend written instructions. Muscle strength is 4/5 on the right side. The tone is also slightly reduced on the right side with exaggerated reflexes. His gait is hemiparetic. Which of the following is the most likely diagnosis in this patient?\nA. Alzheimer's disease\nB. Lewy body dementia\nC. Normal-pressure hydrocephalus\nD. Vascular dementia\nChoose the correct option.",
"image": null
},
{
"idx": 37,
"question": "A 28-year-old woman is brought to the emergency room after a motor vehicle accident. On arrival, she is stable and says that she hit a car at an intersection that \"came out of nowhere\". She states that she had similar close encounters with other cars these past few weeks but was able to avoid collisions with those. She has also had intermittent headaches over the last month and has noticed that her shirts have been getting wet unexpectedly. Blood tests reveal an abnormal elevation of a circulating substance. Which of following changes is also associated with the physiologic function of the most likely substance in this case?\nA. Decreased oxytocin\nB. Decreased progesterone\nC. Increased follicle stimulating hormone\nD. Increased progesterone\n\nA. Decreased oxytocin\nB. Decreased progesterone\nC. Increased follicle stimulating hormone\nD. Increased progesterone",
"options": [
"A. Decreased oxytocin",
"B. Decreased progesterone",
"C. Increased follicle stimulating hormone",
"D. Increased progesterone"
],
"answer": "Decreased progesterone",
"gen_text_store": "",
"pid": "37",
"query": "A 28-year-old woman is brought to the emergency room after a motor vehicle accident. On arrival, she is stable and says that she hit a car at an intersection that \"came out of nowhere\". She states that she had similar close encounters with other cars these past few weeks but was able to avoid collisions with those. She has also had intermittent headaches over the last month and has noticed that her shirts have been getting wet unexpectedly. Blood tests reveal an abnormal elevation of a circulating substance. Which of following changes is also associated with the physiologic function of the most likely substance in this case?\nA. Decreased oxytocin\nB. Decreased progesterone\nC. Increased follicle stimulating hormone\nD. Increased progesterone\nChoose the correct option.",
"image": null
},
{
"idx": 38,
"question": "A 25-year-old African American man presents to his primary care provider for routine blood work. He is a well-known case of sickle cell disease treated with hydroxyurea and tramadol as needed for pain. He does not smoke or drink alcohol. The patient asks if his disease can adversely affect his kidneys because his friend was recently diagnosed with end-stage renal failure. Which of the following is a renal complication of sickle cell disease?\nA. Membranous glomerulonephritis\nB. Proximal renal tubular acidosis\nC. Impaired urine diluting ability\nD. Impaired urine concentration ability\n\nA. Membranous glomerulonephritis\nB. Proximal renal tubular acidosis\nC. Impaired urine diluting ability\nD. Impaired urine concentration ability",
"options": [
"A. Membranous glomerulonephritis",
"B. Proximal renal tubular acidosis",
"C. Impaired urine diluting ability",
"D. Impaired urine concentration ability"
],
"answer": "Impaired urine concentration ability",
"gen_text_store": "",
"pid": "38",
"query": "A 25-year-old African American man presents to his primary care provider for routine blood work. He is a well-known case of sickle cell disease treated with hydroxyurea and tramadol as needed for pain. He does not smoke or drink alcohol. The patient asks if his disease can adversely affect his kidneys because his friend was recently diagnosed with end-stage renal failure. Which of the following is a renal complication of sickle cell disease?\nA. Membranous glomerulonephritis\nB. Proximal renal tubular acidosis\nC. Impaired urine diluting ability\nD. Impaired urine concentration ability\nChoose the correct option.",
"image": null
},
{
"idx": 39,
"question": "A 24-year-old woman is brought to the emergency room (ER) by her co-workers after they found her unconscious in her cubicle when they returned from lunch. They tell you that she has diabetes but do not know anything more about her condition. The woman’s vital signs include: pulse 110/min, respiratory rate 24/min, temperature 36.7°C (98.0°F), and blood pressure 90/60 mm Hg. On physical examination, the patient is breathing heavily and gives irrelevant responses to questions. The skin and mucous membranes appear dry. Examination of the abdomen reveals mild diffuse tenderness to palpation. Deep tendon reflexes in the extremities are 1+ bilaterally. Laboratory studies show:\nFinger stick glucose 630 mg/dL\nArterial blood gas analysis:\npH 7.1\nPO2 90 mm Hg\nPCO2 33 mm Hg\nHCO3 8 mEq/L\nSerum:\nSodium 135 mEq/L\nPotassium 3.1 mEq/L\nChloride 136 mEq/L\nBlood urea nitrogen 20 mg/dL\nSerum creatinine 1.2 mg/dL\nUrine examination shows:\nGlucose Positive\nKetones Positive\nLeukocytes Negative\nNitrite Negative\nRBCs Negative\nCasts Negative\nThe patient is immediately started on a bolus of intravenous (IV) 0.9% sodium chloride (NaCl). Which of the following is the next best step in the management of this patient?\nA. Infuse NaHCO3 slowly\nB. Switch fluids to 0.45% NaCl\nC. Start IV insulin infusion\nD. Replace potassium intravenously\n\nA. Infuse NaHCO3 slowly\nB. Switch fluids to 0.45% NaCl\nC. Start IV insulin infusion\nD. Replace potassium intravenously",
"options": [
"A. Infuse NaHCO3 slowly",
"B. Switch fluids to 0.45% NaCl",
"C. Start IV insulin infusion",
"D. Replace potassium intravenously"
],
"answer": "Replace potassium intravenously",
"gen_text_store": "",
"pid": "39",
"query": "A 24-year-old woman is brought to the emergency room (ER) by her co-workers after they found her unconscious in her cubicle when they returned from lunch. They tell you that she has diabetes but do not know anything more about her condition. The woman’s vital signs include: pulse 110/min, respiratory rate 24/min, temperature 36.7°C (98.0°F), and blood pressure 90/60 mm Hg. On physical examination, the patient is breathing heavily and gives irrelevant responses to questions. The skin and mucous membranes appear dry. Examination of the abdomen reveals mild diffuse tenderness to palpation. Deep tendon reflexes in the extremities are 1+ bilaterally. Laboratory studies show:\nFinger stick glucose 630 mg/dL\nArterial blood gas analysis:\npH 7.1\nPO2 90 mm Hg\nPCO2 33 mm Hg\nHCO3 8 mEq/L\nSerum:\nSodium 135 mEq/L\nPotassium 3.1 mEq/L\nChloride 136 mEq/L\nBlood urea nitrogen 20 mg/dL\nSerum creatinine 1.2 mg/dL\nUrine examination shows:\nGlucose Positive\nKetones Positive\nLeukocytes Negative\nNitrite Negative\nRBCs Negative\nCasts Negative\nThe patient is immediately started on a bolus of intravenous (IV) 0.9% sodium chloride (NaCl). Which of the following is the next best step in the management of this patient?\nA. Infuse NaHCO3 slowly\nB. Switch fluids to 0.45% NaCl\nC. Start IV insulin infusion\nD. Replace potassium intravenously\nChoose the correct option.",
"image": null
},
{
"idx": 40,
"question": "A 27-year-old man presents to the emergency department after a motor vehicle accident. The patient has a past medical history of asthma and cocaine use. His current medications include albuterol and ibuprofen. His temperature is 99.5°F (37.5°C), blood pressure is 70/35 mmHg, pulse is 150/min, respirations are 19/min, and oxygen saturation is 98% on room air. On initial trauma evaluation, his airway is intact and he is breathing spontaneously. The patient's dorsalis pedis and radial pulses are palpable bilaterally. His Glasgow Coma Scale is 9. Head to toe examination reveals instability of the pelvis when downwards force is applied. The patient is started on IV fluids and norepinephrine, and a pelvic binder is placed. The patient's vitals are measured again and his temperature is 99.5°F (37.5°C), blood pressure is 100/55 mmHg, pulse is 150/min, respirations are 17/min, and oxygen saturation is 98% on room air. A blood transfusion is started, and the patient is given hydromorphone. The patient suddenly becomes short of breath with notable bilateral wheezing with poor air movement. His blood pressure is 60/35 mmHg and pulse is 160/min. The patient is treated appropriately, intubated, stabilized, and transferred to the surgical intensive care unit. Which of the following is most likely to be found in this patient's history?\nA. Hemolytic anemia and ataxia\nB. Gum disease and poor wound healing\nC. Irregularly irregular heart rhythm\nD. Anti-A, B, or O antibodies in the serum\n\nA. Hemolytic anemia and ataxia\nB. Gum disease and poor wound healing\nC. Irregularly irregular heart rhythm\nD. Anti-A, B, or O antibodies in the serum",
"options": [
"A. Hemolytic anemia and ataxia",
"B. Gum disease and poor wound healing",
"C. Irregularly irregular heart rhythm",
"D. Anti-A, B, or O antibodies in the serum"
],
"answer": "Hemolytic anemia and ataxia",
"gen_text_store": "",
"pid": "40",
"query": "A 27-year-old man presents to the emergency department after a motor vehicle accident. The patient has a past medical history of asthma and cocaine use. His current medications include albuterol and ibuprofen. His temperature is 99.5°F (37.5°C), blood pressure is 70/35 mmHg, pulse is 150/min, respirations are 19/min, and oxygen saturation is 98% on room air. On initial trauma evaluation, his airway is intact and he is breathing spontaneously. The patient's dorsalis pedis and radial pulses are palpable bilaterally. His Glasgow Coma Scale is 9. Head to toe examination reveals instability of the pelvis when downwards force is applied. The patient is started on IV fluids and norepinephrine, and a pelvic binder is placed. The patient's vitals are measured again and his temperature is 99.5°F (37.5°C), blood pressure is 100/55 mmHg, pulse is 150/min, respirations are 17/min, and oxygen saturation is 98% on room air. A blood transfusion is started, and the patient is given hydromorphone. The patient suddenly becomes short of breath with notable bilateral wheezing with poor air movement. His blood pressure is 60/35 mmHg and pulse is 160/min. The patient is treated appropriately, intubated, stabilized, and transferred to the surgical intensive care unit. Which of the following is most likely to be found in this patient's history?\nA. Hemolytic anemia and ataxia\nB. Gum disease and poor wound healing\nC. Irregularly irregular heart rhythm\nD. Anti-A, B, or O antibodies in the serum\nChoose the correct option.",
"image": null
},
{
"idx": 41,
"question": "A 58-year-old man is brought to the emergency department because of sudden-onset right-sided body numbness for 1 hour. He reports that he has a 15-year history of hypertension treated with hydrochlorothiazide. He is alert and oriented to time, place, and person. Neurological examination shows decreased sensation to light pinprick and temperature on the right side of the face and body. Motor strength is 5/5 and deep tendon reflexes are 2+ bilaterally. Perfusion of which of the following structures of the brain is most likely impaired in this patient?\nA. Posterior limb of the internal capsule\nB. Lateral medulla\nC. Basal pons\nD. Ventral thalamus\n\nA. Posterior limb of the internal capsule\nB. Lateral medulla\nC. Basal pons\nD. Ventral thalamus",
"options": [
"A. Posterior limb of the internal capsule",
"B. Lateral medulla",
"C. Basal pons",
"D. Ventral thalamus"
],
"answer": "Ventral thalamus",
"gen_text_store": "",
"pid": "41",
"query": "A 58-year-old man is brought to the emergency department because of sudden-onset right-sided body numbness for 1 hour. He reports that he has a 15-year history of hypertension treated with hydrochlorothiazide. He is alert and oriented to time, place, and person. Neurological examination shows decreased sensation to light pinprick and temperature on the right side of the face and body. Motor strength is 5/5 and deep tendon reflexes are 2+ bilaterally. Perfusion of which of the following structures of the brain is most likely impaired in this patient?\nA. Posterior limb of the internal capsule\nB. Lateral medulla\nC. Basal pons\nD. Ventral thalamus\nChoose the correct option.",
"image": null
},
{
"idx": 42,
"question": "A 50-year-old man with congestive heart failure (CHF) was started on an experimental analog of atrial natriuretic peptide. Which of the following would he expect to experience?\nA. Increased water reabsorption by the renal collecting ducts\nB. Vasoconstriction, increased blood pressure, aldosterone release\nC. Increased glomerular filtration rate, restricted aldosterone release, vascular smooth muscle dilation\nD. Increased plasma calcium and decreased renal reabsorption of phosphate\n\nA. Increased water reabsorption by the renal collecting ducts\nB. Vasoconstriction, increased blood pressure, aldosterone release\nC. Increased glomerular filtration rate, restricted aldosterone release, vascular smooth muscle dilation\nD. Increased plasma calcium and decreased renal reabsorption of phosphate",
"options": [
"A. Increased water reabsorption by the renal collecting ducts",
"B. Vasoconstriction, increased blood pressure, aldosterone release",
"C. Increased glomerular filtration rate, restricted aldosterone release, vascular smooth muscle dilation",
"D. Increased plasma calcium and decreased renal reabsorption of phosphate"
],
"answer": "Increased glomerular filtration rate, restricted aldosterone release, vascular smooth muscle dilation",
"gen_text_store": "",
"pid": "42",
"query": "A 50-year-old man with congestive heart failure (CHF) was started on an experimental analog of atrial natriuretic peptide. Which of the following would he expect to experience?\nA. Increased water reabsorption by the renal collecting ducts\nB. Vasoconstriction, increased blood pressure, aldosterone release\nC. Increased glomerular filtration rate, restricted aldosterone release, vascular smooth muscle dilation\nD. Increased plasma calcium and decreased renal reabsorption of phosphate\nChoose the correct option.",
"image": null
},
{
"idx": 43,
"question": "A 7-year-old boy is rushed to the emergency room after losing consciousness 30 mins ago at home. The patient’s mother says that he has had a “running nose” for the past few days However, he did not receive any treatment for it, and his condition rapidly worsened today. He does not have any significant past medical history. His vaccination records are up to date. His temperature is 38.2°C (100.7°F), blood pressure is 90/50 mm Hg, heart rate is 120/min, and respiratory rate is 22/min. On physical examination, the patient is unresponsive. There is a petechial rash present on his chest, and he has some neck rigidity. Empiric intravenous antibiotics are started, and a lumbar puncture is performed. Which of the following is the most likely cause of this patient’s low blood pressure?\nA. Human immunodeficiency virus infection\nB. Hypertrophic cardiomyopathy\nC. Adrenocortical insufficiency\nD. Pheochromocytoma\n\nA. Human immunodeficiency virus infection\nB. Hypertrophic cardiomyopathy\nC. Adrenocortical insufficiency\nD. Pheochromocytoma",
"options": [
"A. Human immunodeficiency virus infection",
"B. Hypertrophic cardiomyopathy",
"C. Adrenocortical insufficiency",
"D. Pheochromocytoma"
],
"answer": "Adrenocortical insufficiency",
"gen_text_store": "",
"pid": "43",
"query": "A 7-year-old boy is rushed to the emergency room after losing consciousness 30 mins ago at home. The patient’s mother says that he has had a “running nose” for the past few days However, he did not receive any treatment for it, and his condition rapidly worsened today. He does not have any significant past medical history. His vaccination records are up to date. His temperature is 38.2°C (100.7°F), blood pressure is 90/50 mm Hg, heart rate is 120/min, and respiratory rate is 22/min. On physical examination, the patient is unresponsive. There is a petechial rash present on his chest, and he has some neck rigidity. Empiric intravenous antibiotics are started, and a lumbar puncture is performed. Which of the following is the most likely cause of this patient’s low blood pressure?\nA. Human immunodeficiency virus infection\nB. Hypertrophic cardiomyopathy\nC. Adrenocortical insufficiency\nD. Pheochromocytoma\nChoose the correct option.",
"image": null
},
{
"idx": 44,
"question": "A researcher is studying risk factors for open-angle glaucoma in a group of elderly patients at a primary care clinic. He is curious if patients with diabetes (defined as fasting serum glucose ≥126 mg/dL on two separate readings) are at increased risk of developing open-angle glaucoma over time. Which of the following is the best statement of the null hypothesis for this study?\nA. The future risk of open-angle glaucoma is the same in patients with and those without diabetes\nB. Having diabetes will not cause changes in risk of future open-angle glaucoma\nC. Diabetes is not associated with an increased prevalence of open-angle glaucoma\nD. Improved adherence to antidiabetics will not be effective in decreasing future open-angle glaucoma risk\n\nA. The future risk of open-angle glaucoma is the same in patients with and those without diabetes\nB. Having diabetes will not cause changes in risk of future open-angle glaucoma\nC. Diabetes is not associated with an increased prevalence of open-angle glaucoma\nD. Improved adherence to antidiabetics will not be effective in decreasing future open-angle glaucoma risk",
"options": [
"A. The future risk of open-angle glaucoma is the same in patients with and those without diabetes",
"B. Having diabetes will not cause changes in risk of future open-angle glaucoma",
"C. Diabetes is not associated with an increased prevalence of open-angle glaucoma",
"D. Improved adherence to antidiabetics will not be effective in decreasing future open-angle glaucoma risk"
],
"answer": "The future risk of open-angle glaucoma is the same in patients with and those without diabetes",
"gen_text_store": "",
"pid": "44",
"query": "A researcher is studying risk factors for open-angle glaucoma in a group of elderly patients at a primary care clinic. He is curious if patients with diabetes (defined as fasting serum glucose ≥126 mg/dL on two separate readings) are at increased risk of developing open-angle glaucoma over time. Which of the following is the best statement of the null hypothesis for this study?\nA. The future risk of open-angle glaucoma is the same in patients with and those without diabetes\nB. Having diabetes will not cause changes in risk of future open-angle glaucoma\nC. Diabetes is not associated with an increased prevalence of open-angle glaucoma\nD. Improved adherence to antidiabetics will not be effective in decreasing future open-angle glaucoma risk\nChoose the correct option.",
"image": null
},
{
"idx": 45,
"question": "A 67-year-old man comes to the clinic complaining of fatigue and dizziness for the past 2 months. He reports that he gets tired easily compared to his baseline and feels dizzy when he exerts himself (e.g., when he walks long distances). His past medical history is significant for hypertension that is controlled with lisinopril. A physical examination demonstrates moderate hepatomegaly and lymphadenopathy. His laboratory studies are shown below.\n\nLeukocyte count and differential:\nLeukocyte count: 11,500/mm^3\nSegmented neutrophils: 40%\nBands: 3%\nEosinophils: 1%\nBasophils: 0%\nLymphocytes: 50%\nMonocytes: 8%\n\nHemoglobin: 11.2 g/dL\nPlatelet count: 120,000/mm^3\nMean corpuscular hemoglobin concentration: 31%\nMean corpuscular volume: 80 µm^3\nReticulocyte count: 3%\nLactate dehydrogenase: 45 U/L\n\nA subsequent flow cytometry test demonstrates CD20+ cells. What is the most likely finding you would expect in this patient?\nA. Low levels of erythropoietin\nB. Low levels of leukocyte alkaline phosphatase (LAP)\nC. Presence of hairy cells\nD. Presence of smudge cells\n\nA. Low levels of erythropoietin\nB. Low levels of leukocyte alkaline phosphatase (LAP)\nC. Presence of hairy cells\nD. Presence of smudge cells",
"options": [
"A. Low levels of erythropoietin",
"B. Low levels of leukocyte alkaline phosphatase (LAP)",
"C. Presence of hairy cells",
"D. Presence of smudge cells"
],
"answer": "Presence of smudge cells",
"gen_text_store": "",
"pid": "45",
"query": "A 67-year-old man comes to the clinic complaining of fatigue and dizziness for the past 2 months. He reports that he gets tired easily compared to his baseline and feels dizzy when he exerts himself (e.g., when he walks long distances). His past medical history is significant for hypertension that is controlled with lisinopril. A physical examination demonstrates moderate hepatomegaly and lymphadenopathy. His laboratory studies are shown below.\n\nLeukocyte count and differential:\nLeukocyte count: 11,500/mm^3\nSegmented neutrophils: 40%\nBands: 3%\nEosinophils: 1%\nBasophils: 0%\nLymphocytes: 50%\nMonocytes: 8%\n\nHemoglobin: 11.2 g/dL\nPlatelet count: 120,000/mm^3\nMean corpuscular hemoglobin concentration: 31%\nMean corpuscular volume: 80 µm^3\nReticulocyte count: 3%\nLactate dehydrogenase: 45 U/L\n\nA subsequent flow cytometry test demonstrates CD20+ cells. What is the most likely finding you would expect in this patient?\nA. Low levels of erythropoietin\nB. Low levels of leukocyte alkaline phosphatase (LAP)\nC. Presence of hairy cells\nD. Presence of smudge cells\nChoose the correct option.",
"image": null
},
{
"idx": 46,
"question": "Thirty minutes after delivery, a 3600-g (7-lb 15-oz) newborn has noisy breathing, bluish discoloration of her lips, and intermittent respiratory distress. She was born at 38 weeks' gestation and required bag-mask resuscitation immediately after delivery. Pregnancy was uncomplicated. Her mother has noticed the bluish lip discoloration worsen when she fed and improve when she cried. The patient's pulse is 163/min, respirations are 62/min, and blood pressure is 60/30 mm Hg. The crying infant's lungs are clear to auscultation. Further evaluation of this patient is most likely to show which of the following?\nA. Diffuse reticulogranular densities on chest x-ray\nB. Boot-shaped heart on chest x-ray\nC. Passage of a gastric catheter through the mouth not possible\nD. Passage of a catheter through the nasal cavity not possible\n\nA. Diffuse reticulogranular densities on chest x-ray\nB. Boot-shaped heart on chest x-ray\nC. Passage of a gastric catheter through the mouth not possible\nD. Passage of a catheter through the nasal cavity not possible",
"options": [
"A. Diffuse reticulogranular densities on chest x-ray",
"B. Boot-shaped heart on chest x-ray",
"C. Passage of a gastric catheter through the mouth not possible",
"D. Passage of a catheter through the nasal cavity not possible"
],
"answer": "Passage of a catheter through the nasal cavity not possible",
"gen_text_store": "",
"pid": "46",
"query": "Thirty minutes after delivery, a 3600-g (7-lb 15-oz) newborn has noisy breathing, bluish discoloration of her lips, and intermittent respiratory distress. She was born at 38 weeks' gestation and required bag-mask resuscitation immediately after delivery. Pregnancy was uncomplicated. Her mother has noticed the bluish lip discoloration worsen when she fed and improve when she cried. The patient's pulse is 163/min, respirations are 62/min, and blood pressure is 60/30 mm Hg. The crying infant's lungs are clear to auscultation. Further evaluation of this patient is most likely to show which of the following?\nA. Diffuse reticulogranular densities on chest x-ray\nB. Boot-shaped heart on chest x-ray\nC. Passage of a gastric catheter through the mouth not possible\nD. Passage of a catheter through the nasal cavity not possible\nChoose the correct option.",
"image": null
},
{
"idx": 47,
"question": "A 15-year-old girl comes to the physician because of episodic pelvic pain radiating to her back and thighs for 4 months. The pain occurs a few hours before her menstrual period and lasts for 2 days. She has been taking ibuprofen, which has provided some relief. Menses have occurred at regular 28-day intervals since menarche at the age of 12 years and last for 5 to 6 days. She is sexually active with two male partners and uses condoms inconsistently. Vital signs are within normal limits. Physical examination shows no abnormalities. Which of the following is the most likely cause of this patient's symptoms?\nA. Endometrial sloughing and uterine contractions mediated by prostaglandin\nB. Ascending infection of the uterus, fallopian tubes, ovaries, or surrounding tissue\nC. Fluid-filled sac within the ovary\nD. Hormone-sensitive smooth muscle tumor of the myometrium\n\nA. Endometrial sloughing and uterine contractions mediated by prostaglandin\nB. Ascending infection of the uterus, fallopian tubes, ovaries, or surrounding tissue\nC. Fluid-filled sac within the ovary\nD. Hormone-sensitive smooth muscle tumor of the myometrium",
"options": [
"A. Endometrial sloughing and uterine contractions mediated by prostaglandin",
"B. Ascending infection of the uterus, fallopian tubes, ovaries, or surrounding tissue",
"C. Fluid-filled sac within the ovary",
"D. Hormone-sensitive smooth muscle tumor of the myometrium"
],
"answer": "Endometrial sloughing and uterine contractions mediated by prostaglandin",
"gen_text_store": "",
"pid": "47",
"query": "A 15-year-old girl comes to the physician because of episodic pelvic pain radiating to her back and thighs for 4 months. The pain occurs a few hours before her menstrual period and lasts for 2 days. She has been taking ibuprofen, which has provided some relief. Menses have occurred at regular 28-day intervals since menarche at the age of 12 years and last for 5 to 6 days. She is sexually active with two male partners and uses condoms inconsistently. Vital signs are within normal limits. Physical examination shows no abnormalities. Which of the following is the most likely cause of this patient's symptoms?\nA. Endometrial sloughing and uterine contractions mediated by prostaglandin\nB. Ascending infection of the uterus, fallopian tubes, ovaries, or surrounding tissue\nC. Fluid-filled sac within the ovary\nD. Hormone-sensitive smooth muscle tumor of the myometrium\nChoose the correct option.",
"image": null
},
{
"idx": 48,
"question": "A 35-year-old man comes to the physician because of episodes of difficulty swallowing for the past 3 months. He feels solid food getting stuck in his chest behind the sternum when he eats. Drinking does not cause any difficulty swallowing. He has no coughing or nasal regurgitation. He has no hoarseness or weight loss. He has had heartburn for 2 years with no response to high-dose omeprazole. His past medical history is also significant for asthma and eczema. He takes no medications except for omeprazole. His vital signs are within normal limits. Physical examination shows no abnormal findings. Which of the following best explains these findings?\nA. Achalasia\nB. Diffuse esophageal spasm\nC. Eosinophilic esophagitis\nD. Esophageal reflux disease\n\nA. Achalasia\nB. Diffuse esophageal spasm\nC. Eosinophilic esophagitis\nD. Esophageal reflux disease",
"options": [
"A. Achalasia",
"B. Diffuse esophageal spasm",
"C. Eosinophilic esophagitis",
"D. Esophageal reflux disease"
],
"answer": "Eosinophilic esophagitis",
"gen_text_store": "",
"pid": "48",
"query": "A 35-year-old man comes to the physician because of episodes of difficulty swallowing for the past 3 months. He feels solid food getting stuck in his chest behind the sternum when he eats. Drinking does not cause any difficulty swallowing. He has no coughing or nasal regurgitation. He has no hoarseness or weight loss. He has had heartburn for 2 years with no response to high-dose omeprazole. His past medical history is also significant for asthma and eczema. He takes no medications except for omeprazole. His vital signs are within normal limits. Physical examination shows no abnormal findings. Which of the following best explains these findings?\nA. Achalasia\nB. Diffuse esophageal spasm\nC. Eosinophilic esophagitis\nD. Esophageal reflux disease\nChoose the correct option.",
"image": null
},
{
"idx": 49,
"question": "A 68-year-old man presents to the emergency department because of fever, abdominal pain, and rapidly progressive distension of the abdomen. His appendix was removed for an abscess 3 days ago. The complete blood count showed leukocytosis. Anaerobic culture of the peritoneal fluid needle aspirate showed a gram-negative pathogen. Which of the following, in addition to polymicrobial infection, is the most likely cause of this patient’s condition?\nA. Bacteroides fragilis\nB. Campylobacter jejuni\nC. Clostridium perfringens\nD. Shigella sonnei\n\nA. Bacteroides fragilis\nB. Campylobacter jejuni\nC. Clostridium perfringens\nD. Shigella sonnei",
"options": [
"A. Bacteroides fragilis",
"B. Campylobacter jejuni",
"C. Clostridium perfringens",
"D. Shigella sonnei"
],
"answer": "Bacteroides fragilis",
"gen_text_store": "",
"pid": "49",
"query": "A 68-year-old man presents to the emergency department because of fever, abdominal pain, and rapidly progressive distension of the abdomen. His appendix was removed for an abscess 3 days ago. The complete blood count showed leukocytosis. Anaerobic culture of the peritoneal fluid needle aspirate showed a gram-negative pathogen. Which of the following, in addition to polymicrobial infection, is the most likely cause of this patient’s condition?\nA. Bacteroides fragilis\nB. Campylobacter jejuni\nC. Clostridium perfringens\nD. Shigella sonnei\nChoose the correct option.",
"image": null
},
{
"idx": 50,
"question": "A 51-year-old man presents the emergency room with chest pain. He mentions that the pain started several hours ago and radiates to his left neck and shoulder. He also mentions that he has some difficulty in breathing. He says that he has had similar chest pains before, but nothing seemed to be wrong at that time. He was diagnosed with high cholesterol during that episode and was prescribed medication. He also has a 3-year history of gastritis. The blood pressure is 130/80 mm Hg, respirations are 18/min, and the pulse is 110/min. He seems a little anxious. The physical examination reveals no significant abnormalities. An ECG shows slight changes in the leads. His physician talks to him about the benefits of taking low-dose aspirin daily. Which of the following would be a contraindication to the use of aspirin in this patient?\nA. ECG changes\nB. Hypercholesterolemia\nC. Gastritis\nD. Increased pulse rate\n\nA. ECG changes\nB. Hypercholesterolemia\nC. Gastritis\nD. Increased pulse rate",
"options": [
"A. ECG changes",
"B. Hypercholesterolemia",
"C. Gastritis",
"D. Increased pulse rate"
],
"answer": "Gastritis",
"gen_text_store": "",
"pid": "50",
"query": "A 51-year-old man presents the emergency room with chest pain. He mentions that the pain started several hours ago and radiates to his left neck and shoulder. He also mentions that he has some difficulty in breathing. He says that he has had similar chest pains before, but nothing seemed to be wrong at that time. He was diagnosed with high cholesterol during that episode and was prescribed medication. He also has a 3-year history of gastritis. The blood pressure is 130/80 mm Hg, respirations are 18/min, and the pulse is 110/min. He seems a little anxious. The physical examination reveals no significant abnormalities. An ECG shows slight changes in the leads. His physician talks to him about the benefits of taking low-dose aspirin daily. Which of the following would be a contraindication to the use of aspirin in this patient?\nA. ECG changes\nB. Hypercholesterolemia\nC. Gastritis\nD. Increased pulse rate\nChoose the correct option.",
"image": null
},
{
"idx": 51,
"question": "A 22-year-old woman presents to her primary care physician in April for seasonal allergies. She has suffered from seasonal allergies for the past 2 years and takes diphenhydramine as needed when her symptoms worsen. She has not yet seen a physician for her allergies. She reports that diphenhydramine has been helpful in controlling her symptoms, but she does not like feeling drowsy from the medication. Her past medical history is also notable for well-controlled asthma. She uses an albuterol inhaler on an as-needed basis. She smokes marijuana daily. Her temperature is 99.2°F (37.3°C), blood pressure is 120/70 mmHg, pulse is 76/min, and respirations are 16/min. She has a prominent nasal crease. Her nasal turbinates are boggy and bluish-gray. She has copious thin and watery nasal mucus. The physician suggests replacing diphenhydramine with fexofenadine to improve her drowsiness. What characteristic of fexodenadine allows it to be less sedating than diphenhydramine?\nA. Alpha-adrenergic antagonism\nB. Beta-adrenergic antagonism\nC. Relative lipophobicity\nD. Serotonergic antagonism\n\nA. Alpha-adrenergic antagonism\nB. Beta-adrenergic antagonism\nC. Relative lipophobicity\nD. Serotonergic antagonism",
"options": [
"A. Alpha-adrenergic antagonism",
"B. Beta-adrenergic antagonism",
"C. Relative lipophobicity",
"D. Serotonergic antagonism"
],
"answer": "Relative lipophobicity",
"gen_text_store": "",
"pid": "51",
"query": "A 22-year-old woman presents to her primary care physician in April for seasonal allergies. She has suffered from seasonal allergies for the past 2 years and takes diphenhydramine as needed when her symptoms worsen. She has not yet seen a physician for her allergies. She reports that diphenhydramine has been helpful in controlling her symptoms, but she does not like feeling drowsy from the medication. Her past medical history is also notable for well-controlled asthma. She uses an albuterol inhaler on an as-needed basis. She smokes marijuana daily. Her temperature is 99.2°F (37.3°C), blood pressure is 120/70 mmHg, pulse is 76/min, and respirations are 16/min. She has a prominent nasal crease. Her nasal turbinates are boggy and bluish-gray. She has copious thin and watery nasal mucus. The physician suggests replacing diphenhydramine with fexofenadine to improve her drowsiness. What characteristic of fexodenadine allows it to be less sedating than diphenhydramine?\nA. Alpha-adrenergic antagonism\nB. Beta-adrenergic antagonism\nC. Relative lipophobicity\nD. Serotonergic antagonism\nChoose the correct option.",
"image": null
},
{
"idx": 52,
"question": "A 40-year-old businessman who was previously well is brought into the emergency department by his assistant with a complaint of left-sided weakness after a chiropractic neck manipulation. He has never felt like this before. Past medical history is insignificant. His blood pressure is 125/75 mm Hg, pulse 86/min, respiratory rate 13/min, temperature 36.8°C (98.2°F). A T2-weighted MRI shows a left C5 hemicord lesion. The patient is treated with cervical immobilization, a course of steroids, and physical therapy. What other finding will most likely be seen in this patient?\nA. Spastic paralysis at the level of lesion\nB. Right-sided Horner's syndrome\nC. Contralateral corticospinal tract involvement\nD. Right-sided analgesia\n\nA. Spastic paralysis at the level of lesion\nB. Right-sided Horner's syndrome\nC. Contralateral corticospinal tract involvement\nD. Right-sided analgesia",
"options": [
"A. Spastic paralysis at the level of lesion",
"B. Right-sided Horner's syndrome",
"C. Contralateral corticospinal tract involvement",
"D. Right-sided analgesia"
],
"answer": "Right-sided analgesia",
"gen_text_store": "",
"pid": "52",
"query": "A 40-year-old businessman who was previously well is brought into the emergency department by his assistant with a complaint of left-sided weakness after a chiropractic neck manipulation. He has never felt like this before. Past medical history is insignificant. His blood pressure is 125/75 mm Hg, pulse 86/min, respiratory rate 13/min, temperature 36.8°C (98.2°F). A T2-weighted MRI shows a left C5 hemicord lesion. The patient is treated with cervical immobilization, a course of steroids, and physical therapy. What other finding will most likely be seen in this patient?\nA. Spastic paralysis at the level of lesion\nB. Right-sided Horner's syndrome\nC. Contralateral corticospinal tract involvement\nD. Right-sided analgesia\nChoose the correct option.",
"image": null
},
{
"idx": 53,
"question": "A 23-year-old man is admitted to the hospital with fever, chest discomfort, tachypnea, pain, needle-like sensations in the upper extremities, and profuse sweating. He also complains of a gradual decrease in vision over the past 3 months. He is a bodybuilding competitor and has a competition coming up in 1 week. The man reports that his symptoms appeared suddenly, 30 minutes after he took 2 foreign-manufactured fat-burning pills instead of the 1 he usually takes. His blood pressure is 140/90 mm Hg, heart rate is 137/min, respiratory rate is 26/min, and temperature is 39.9°C (103.8°F). Physical examination reveals a reddish maculopapular rash over the patient’s trunk, diminished lung and heart sounds, tenderness to palpation in his abdomen, and rotational bilateral nystagmus with an alternating gaze-dependent fast component. Ophthalmologic examination shows bilateral cataracts. The patient’s total blood count is as follows:\nErythrocytes 4.4 x 109/mm3\nHb 12 g/dL\nTotal leukocyte count 3750/mm3\nNeutrophils 57%\nLymphocyte 37%\nEosinophil 1%\nMonocyte 5%\nBasophil 0%\nPlatelet count 209,000/mm3\nWhich of the following statements best describes the pathogenesis of this patient’s condition?\nA. The patient’s symptoms are caused by an increased concentration of epinephrine released by the adrenal glands in response to the consumed substance.\nB. The drug caused uncoupling of the electron transport chain and oxidative phosphorylation.\nC. The patient has a pyretic reaction due to bacterial contamination of the pills.\nD. The drug has stimulated the hypothalamic temperature center to produce hyperthermia.\n\nA. The patient’s symptoms are caused by an increased concentration of epinephrine released by the adrenal glands in response to the consumed substance.\nB. The drug caused uncoupling of the electron transport chain and oxidative phosphorylation.\nC. The patient has a pyretic reaction due to bacterial contamination of the pills.\nD. The drug has stimulated the hypothalamic temperature center to produce hyperthermia.",
"options": [
"A. The patient’s symptoms are caused by an increased concentration of epinephrine released by the adrenal glands in response to the consumed substance.",
"B. The drug caused uncoupling of the electron transport chain and oxidative phosphorylation.",
"C. The patient has a pyretic reaction due to bacterial contamination of the pills.",
"D. The drug has stimulated the hypothalamic temperature center to produce hyperthermia."
],
"answer": "The drug caused uncoupling of the electron transport chain and oxidative phosphorylation.",
"gen_text_store": "",
"pid": "53",
"query": "A 23-year-old man is admitted to the hospital with fever, chest discomfort, tachypnea, pain, needle-like sensations in the upper extremities, and profuse sweating. He also complains of a gradual decrease in vision over the past 3 months. He is a bodybuilding competitor and has a competition coming up in 1 week. The man reports that his symptoms appeared suddenly, 30 minutes after he took 2 foreign-manufactured fat-burning pills instead of the 1 he usually takes. His blood pressure is 140/90 mm Hg, heart rate is 137/min, respiratory rate is 26/min, and temperature is 39.9°C (103.8°F). Physical examination reveals a reddish maculopapular rash over the patient’s trunk, diminished lung and heart sounds, tenderness to palpation in his abdomen, and rotational bilateral nystagmus with an alternating gaze-dependent fast component. Ophthalmologic examination shows bilateral cataracts. The patient’s total blood count is as follows:\nErythrocytes 4.4 x 109/mm3\nHb 12 g/dL\nTotal leukocyte count 3750/mm3\nNeutrophils 57%\nLymphocyte 37%\nEosinophil 1%\nMonocyte 5%\nBasophil 0%\nPlatelet count 209,000/mm3\nWhich of the following statements best describes the pathogenesis of this patient’s condition?\nA. The patient’s symptoms are caused by an increased concentration of epinephrine released by the adrenal glands in response to the consumed substance.\nB. The drug caused uncoupling of the electron transport chain and oxidative phosphorylation.\nC. The patient has a pyretic reaction due to bacterial contamination of the pills.\nD. The drug has stimulated the hypothalamic temperature center to produce hyperthermia.\nChoose the correct option.",
"image": null
},
{
"idx": 54,
"question": "A 6-month-old boy is brought to the physician by his parents for difficulty breathing and bluish discoloration of the lips for the past hour. During the past 3 months, the patient has had several upper respiratory tract infections and poor weight gain. Physical examination shows crackles over both lung fields and enlargement of the tonsils and cervical lymph nodes. His serum IgA, IgE, and IgG titers are decreased. An x-ray of the chest shows bilateral interstitial infiltrates. Methenamine silver staining of bronchial lavage fluid shows disc-shaped cysts. A defect in which of the following is the most likely underlying cause of this patient's condition?\nA. Actin filament assembly\nB. T-cell receptor signaling\nC. Microtubule polymerization\nD. B-cell maturation\n\nA. Actin filament assembly\nB. T-cell receptor signaling\nC. Microtubule polymerization\nD. B-cell maturation",
"options": [
"A. Actin filament assembly",
"B. T-cell receptor signaling",
"C. Microtubule polymerization",
"D. B-cell maturation"
],
"answer": "T-cell receptor signaling",
"gen_text_store": "",
"pid": "54",
"query": "A 6-month-old boy is brought to the physician by his parents for difficulty breathing and bluish discoloration of the lips for the past hour. During the past 3 months, the patient has had several upper respiratory tract infections and poor weight gain. Physical examination shows crackles over both lung fields and enlargement of the tonsils and cervical lymph nodes. His serum IgA, IgE, and IgG titers are decreased. An x-ray of the chest shows bilateral interstitial infiltrates. Methenamine silver staining of bronchial lavage fluid shows disc-shaped cysts. A defect in which of the following is the most likely underlying cause of this patient's condition?\nA. Actin filament assembly\nB. T-cell receptor signaling\nC. Microtubule polymerization\nD. B-cell maturation\nChoose the correct option.",
"image": null
},
{
"idx": 55,
"question": "A 25-year-old man presents to his primary care physician for pain in his back. The patient describes the pain as feeling worse in the morning. He says it is a general stiffness that improves when he goes to the gym and lifts weights. He also states that his symptoms seem to improve when he leans forward or when he is cycling. The patient is a current smoker and is sexually active. He admits to having unprotected sex with many different partners this past year. The patient has no significant past medical history and is not currently taking any medications. On physical exam, the patient demonstrates notable kyphosis of the thoracic spine and decreased mobility of the back in all 4 directions. The patient’s strength is 5/5 in his upper and lower extremities. The rest of his physical exam is within normal limits. Which of the following findings is associated with this patient’s presentation?\nA. Diminished pulses in the lower extremity\nB. Narrowing of the spinal canal when standing upright\nC. Pain with elevation of his leg while laying down\nD. Punctate bleeding spots when dermatologic scales are removed\n\nA. Diminished pulses in the lower extremity\nB. Narrowing of the spinal canal when standing upright\nC. Pain with elevation of his leg while laying down\nD. Punctate bleeding spots when dermatologic scales are removed",
"options": [
"A. Diminished pulses in the lower extremity",
"B. Narrowing of the spinal canal when standing upright",
"C. Pain with elevation of his leg while laying down",
"D. Punctate bleeding spots when dermatologic scales are removed"
],
"answer": "Punctate bleeding spots when dermatologic scales are removed",
"gen_text_store": "",
"pid": "55",
"query": "A 25-year-old man presents to his primary care physician for pain in his back. The patient describes the pain as feeling worse in the morning. He says it is a general stiffness that improves when he goes to the gym and lifts weights. He also states that his symptoms seem to improve when he leans forward or when he is cycling. The patient is a current smoker and is sexually active. He admits to having unprotected sex with many different partners this past year. The patient has no significant past medical history and is not currently taking any medications. On physical exam, the patient demonstrates notable kyphosis of the thoracic spine and decreased mobility of the back in all 4 directions. The patient’s strength is 5/5 in his upper and lower extremities. The rest of his physical exam is within normal limits. Which of the following findings is associated with this patient’s presentation?\nA. Diminished pulses in the lower extremity\nB. Narrowing of the spinal canal when standing upright\nC. Pain with elevation of his leg while laying down\nD. Punctate bleeding spots when dermatologic scales are removed\nChoose the correct option.",
"image": null
},
{
"idx": 56,
"question": "A 70-year-old man is brought to the emergency department by staff of the group home where he resides because of worsening confusion for the past week. He has a history of major depressive disorder and had an ischemic stroke 4 months ago. Current medications are aspirin and sertraline. He is lethargic and disoriented. His pulse is 78/min, and blood pressure is 135/88 mm Hg. Physical examination shows moist oral mucosa, normal skin turgor, and no peripheral edema. While in the waiting room, he has a generalized, tonic-clonic seizure. Laboratory studies show a serum sodium of 119 mEq/L and an elevated serum antidiuretic hormone concentration. Which of the following sets of additional laboratory findings is most likely in this patient?\n $$$ Serum osmolality %%% Urine sodium %%% Serum aldosterone $$$\nA. ↓ ↓ ↓\nB. ↑ ↓ normal\nC. ↓ ↑ ↑\nD. ↓ ↑ ↓\n\nA. ↓ ↓ ↓\nB. ↑ ↓ normal\nC. ↓ ↑ ↑\nD. ↓ ↑ ↓",
"options": [
"A. ↓ ↓ ↓",
"B. ↑ ↓ normal",
"C. ↓ ↑ ↑",
"D. ↓ ↑ ↓"
],
"answer": "↓ ↑ ↓",
"gen_text_store": "",
"pid": "56",
"query": "A 70-year-old man is brought to the emergency department by staff of the group home where he resides because of worsening confusion for the past week. He has a history of major depressive disorder and had an ischemic stroke 4 months ago. Current medications are aspirin and sertraline. He is lethargic and disoriented. His pulse is 78/min, and blood pressure is 135/88 mm Hg. Physical examination shows moist oral mucosa, normal skin turgor, and no peripheral edema. While in the waiting room, he has a generalized, tonic-clonic seizure. Laboratory studies show a serum sodium of 119 mEq/L and an elevated serum antidiuretic hormone concentration. Which of the following sets of additional laboratory findings is most likely in this patient?\n $$$ Serum osmolality %%% Urine sodium %%% Serum aldosterone $$$\nA. ↓ ↓ ↓\nB. ↑ ↓ normal\nC. ↓ ↑ ↑\nD. ↓ ↑ ↓\nChoose the correct option.",
"image": null
},
{
"idx": 57,
"question": "A 45-year-old woman with hypothyroidism comes to the physician because of progressive fatigue, lethargy, and epigastric pain after eating. Physical examination shows pale conjunctivae. Laboratory studies show decreased serum hemoglobin levels and increased serum gastrin levels. Esophagogastroduodenoscopy shows inflammation of the gastric body and fundus. A photomicrograph of a biopsy specimen taken from the gastric antrum is shown. Which of the following is the most likely cause of this patient's symptoms?\nA. Mucosal cell hyperplasia\nB. Enterochromaffin-like cell hyperplasia\nC. Parietal cell destruction\nD. Chief cell destruction\n\nA. Mucosal cell hyperplasia\nB. Enterochromaffin-like cell hyperplasia\nC. Parietal cell destruction\nD. Chief cell destruction",
"options": [
"A. Mucosal cell hyperplasia",
"B. Enterochromaffin-like cell hyperplasia",
"C. Parietal cell destruction",
"D. Chief cell destruction"
],
"answer": "Parietal cell destruction",
"gen_text_store": "",
"pid": "57",
"query": "A 45-year-old woman with hypothyroidism comes to the physician because of progressive fatigue, lethargy, and epigastric pain after eating. Physical examination shows pale conjunctivae. Laboratory studies show decreased serum hemoglobin levels and increased serum gastrin levels. Esophagogastroduodenoscopy shows inflammation of the gastric body and fundus. A photomicrograph of a biopsy specimen taken from the gastric antrum is shown. Which of the following is the most likely cause of this patient's symptoms?\nA. Mucosal cell hyperplasia\nB. Enterochromaffin-like cell hyperplasia\nC. Parietal cell destruction\nD. Chief cell destruction\nChoose the correct option.",
"image": null
},
{
"idx": 58,
"question": "A 66-year-old man is brought to the emergency room by his wife due to abdominal distension and persistent somnolence for the past 2 weeks. The patient’s wife says that he has been sleeping much more than usual for the past 5 days. His bowel and bladder habit have not changed. His past medical history is significant for alcoholic liver cirrhosis. His vital signs include: pulse 76/min, respiratory rate 15/min, temperature 38.0°C (100.4°F) and blood pressure 122/75 mm Hg. On physical examination, the patient is altered and not responsive to commands. Oriented x 0. The abdomen is significantly distended. Shifting dullness is present and a positive fluid wave can be elicited. Hyperreflexia and asterixis are noted. Laboratory findings are significant for the following:\nLaboratory test\nSodium 140 mEq/L\nPotassium 3.5 mEq/L\nChloride 97 mEq/L\nGlucose 90 mg/dL\nAmmonia 100 µg/dL (ref: 19-60 µg/dL)\nArterial blood gas\npH 7.4\npCO2 40 mm Hg\npO2 90 mm Hg\nHCO3 26 mEq/L\nAn abdominal ultrasound shows surface nodularity compatible with cirrhosis but no other changes aside from ascites. An upper GI endoscopy is performed which shows gastric varices with no signs of active bleeding. An MRI of the brain is insignificant. What is the most likely precipitating factor that led to this patient’s condition?\nA. Spontaneous bacterial peritonitis\nB. Metabolic alkalosis\nC. Portal vein thrombosis\nD. Hypoglycemia\n\nA. Spontaneous bacterial peritonitis\nB. Metabolic alkalosis\nC. Portal vein thrombosis\nD. Hypoglycemia",
"options": [
"A. Spontaneous bacterial peritonitis",
"B. Metabolic alkalosis",
"C. Portal vein thrombosis",
"D. Hypoglycemia"
],
"answer": "Spontaneous bacterial peritonitis",
"gen_text_store": "",
"pid": "58",
"query": "A 66-year-old man is brought to the emergency room by his wife due to abdominal distension and persistent somnolence for the past 2 weeks. The patient’s wife says that he has been sleeping much more than usual for the past 5 days. His bowel and bladder habit have not changed. His past medical history is significant for alcoholic liver cirrhosis. His vital signs include: pulse 76/min, respiratory rate 15/min, temperature 38.0°C (100.4°F) and blood pressure 122/75 mm Hg. On physical examination, the patient is altered and not responsive to commands. Oriented x 0. The abdomen is significantly distended. Shifting dullness is present and a positive fluid wave can be elicited. Hyperreflexia and asterixis are noted. Laboratory findings are significant for the following:\nLaboratory test\nSodium 140 mEq/L\nPotassium 3.5 mEq/L\nChloride 97 mEq/L\nGlucose 90 mg/dL\nAmmonia 100 µg/dL (ref: 19-60 µg/dL)\nArterial blood gas\npH 7.4\npCO2 40 mm Hg\npO2 90 mm Hg\nHCO3 26 mEq/L\nAn abdominal ultrasound shows surface nodularity compatible with cirrhosis but no other changes aside from ascites. An upper GI endoscopy is performed which shows gastric varices with no signs of active bleeding. An MRI of the brain is insignificant. What is the most likely precipitating factor that led to this patient’s condition?\nA. Spontaneous bacterial peritonitis\nB. Metabolic alkalosis\nC. Portal vein thrombosis\nD. Hypoglycemia\nChoose the correct option.",
"image": null
},
{
"idx": 59,
"question": "A 3-week-old newborn is brought to the physician by his parents because of poor feeding, irritability, and frequent vomiting over the past week. The vomitus is greenish in color and smells strange. His parents have tried to feed him every 4 hours, but the patient often spits up or refuses to eat. The patient was born at term and had his first bowel movement at 50 hours of life. He has since had one bowel movement daily. He is at the 50th percentile for length, 10th percentile for weight, and 40th percentile for head circumference. He does not appear to be in acute distress. His temperature is 36.9°C (98.4°F), pulse is 140/min, respirations are 40/min, and blood pressure is 90/60 mm Hg. Physical examination shows that the patient has small, low-set ears, a broad and flat nasal bridge, and a large space between the first and second toes bilaterally. The abdomen is distended. When the finger is removed following a rectal exam, there is an explosive release of stool from the patient's rectum. An x-ray of the abdomen shows a section of dilated colon followed by a segment of colon without stool or air. Which of the following is most likely to confirm the diagnosis?\nA. CT scan of the abdomen\nB. Transabdominal ultrasonography\nC. Anorectal manometry\nD. Rectal suction biopsy\n\nA. CT scan of the abdomen\nB. Transabdominal ultrasonography\nC. Anorectal manometry\nD. Rectal suction biopsy",
"options": [
"A. CT scan of the abdomen",
"B. Transabdominal ultrasonography",
"C. Anorectal manometry",
"D. Rectal suction biopsy"
],
"answer": "Rectal suction biopsy",
"gen_text_store": "",
"pid": "59",
"query": "A 3-week-old newborn is brought to the physician by his parents because of poor feeding, irritability, and frequent vomiting over the past week. The vomitus is greenish in color and smells strange. His parents have tried to feed him every 4 hours, but the patient often spits up or refuses to eat. The patient was born at term and had his first bowel movement at 50 hours of life. He has since had one bowel movement daily. He is at the 50th percentile for length, 10th percentile for weight, and 40th percentile for head circumference. He does not appear to be in acute distress. His temperature is 36.9°C (98.4°F), pulse is 140/min, respirations are 40/min, and blood pressure is 90/60 mm Hg. Physical examination shows that the patient has small, low-set ears, a broad and flat nasal bridge, and a large space between the first and second toes bilaterally. The abdomen is distended. When the finger is removed following a rectal exam, there is an explosive release of stool from the patient's rectum. An x-ray of the abdomen shows a section of dilated colon followed by a segment of colon without stool or air. Which of the following is most likely to confirm the diagnosis?\nA. CT scan of the abdomen\nB. Transabdominal ultrasonography\nC. Anorectal manometry\nD. Rectal suction biopsy\nChoose the correct option.",
"image": null
},
{
"idx": 60,
"question": "An 11-month-old boy is brought to the clinic by his mother for a rash on his trunk, which he has had for the past 2 days. She notes that he is eating less and is more cranky than usual. His birth history is insignificant, and his immunizations are up to date. Vital signs include: temperature is 37.8°C (100.0°F), pulse is 98/min, and respiratory rate is 16/min. The rash features thin-walled, fluid-filled blisters that rupture easily. Fluid samples from the lesions are sent for analysis to a microbiology lab. The results reveal an infection by the gram-positive bacterium Staphylococcus aureus. The patient is diagnosed with staphylococcal scalded skin syndrome. Which of the following is involved with the primary defense in response to the bacteria and toxins produced by this organism?\nA. Immunoglobulin- IgG\nB. Immunoglobulin- IgD\nC. Immunoglobulin- IgA\nD. Immunoglobulin- IgM\n\nA. Immunoglobulin- IgG\nB. Immunoglobulin- IgD\nC. Immunoglobulin- IgA\nD. Immunoglobulin- IgM",
"options": [
"A. Immunoglobulin- IgG",
"B. Immunoglobulin- IgD",
"C. Immunoglobulin- IgA",
"D. Immunoglobulin- IgM"
],
"answer": "Immunoglobulin- IgM",
"gen_text_store": "",
"pid": "60",
"query": "An 11-month-old boy is brought to the clinic by his mother for a rash on his trunk, which he has had for the past 2 days. She notes that he is eating less and is more cranky than usual. His birth history is insignificant, and his immunizations are up to date. Vital signs include: temperature is 37.8°C (100.0°F), pulse is 98/min, and respiratory rate is 16/min. The rash features thin-walled, fluid-filled blisters that rupture easily. Fluid samples from the lesions are sent for analysis to a microbiology lab. The results reveal an infection by the gram-positive bacterium Staphylococcus aureus. The patient is diagnosed with staphylococcal scalded skin syndrome. Which of the following is involved with the primary defense in response to the bacteria and toxins produced by this organism?\nA. Immunoglobulin- IgG\nB. Immunoglobulin- IgD\nC. Immunoglobulin- IgA\nD. Immunoglobulin- IgM\nChoose the correct option.",
"image": null
},
{
"idx": 61,
"question": "A 60-year-old man presents to his local walk-in clinic with 1 week of fever, chills, night sweats, anorexia, malaise, progressive shortness of breath, and sharp chest pain. He is found with a blood pressure of 100/80 mm Hg, a heart rate of 84/min, an elevated respiratory rate, and a holosystolic heart murmur III/VI. His palms and soles show non-tender erythematous lesions. His personal medical history is relevant for frequent visits to the ER for lower gastrointestinal bleeding in the last month with a recent colonoscopy that reported an ulcerative lesion suggestive of colorectal cancer. He has not been subjected to dental procedures recently, and he denies the use of psychoactive drugs. A chest plain film shows clear lungs and mild cardiomegaly, and echocardiography reports the presence of vegetations involving the mitral valve. Which of the following organisms is the most likely causative agent?\nA. Staphylococcus aureus\nB. Escherichia coli\nC. Haemophilus aphrophilus\nD. Streptococcus bovis\n\nA. Staphylococcus aureus\nB. Escherichia coli\nC. Haemophilus aphrophilus\nD. Streptococcus bovis",
"options": [
"A. Staphylococcus aureus",
"B. Escherichia coli",
"C. Haemophilus aphrophilus",
"D. Streptococcus bovis"
],
"answer": "Streptococcus bovis",
"gen_text_store": "",
"pid": "61",
"query": "A 60-year-old man presents to his local walk-in clinic with 1 week of fever, chills, night sweats, anorexia, malaise, progressive shortness of breath, and sharp chest pain. He is found with a blood pressure of 100/80 mm Hg, a heart rate of 84/min, an elevated respiratory rate, and a holosystolic heart murmur III/VI. His palms and soles show non-tender erythematous lesions. His personal medical history is relevant for frequent visits to the ER for lower gastrointestinal bleeding in the last month with a recent colonoscopy that reported an ulcerative lesion suggestive of colorectal cancer. He has not been subjected to dental procedures recently, and he denies the use of psychoactive drugs. A chest plain film shows clear lungs and mild cardiomegaly, and echocardiography reports the presence of vegetations involving the mitral valve. Which of the following organisms is the most likely causative agent?\nA. Staphylococcus aureus\nB. Escherichia coli\nC. Haemophilus aphrophilus\nD. Streptococcus bovis\nChoose the correct option.",
"image": null
},
{
"idx": 62,
"question": "A 53-year-old man comes to the physician because of a 2-month history of multiple episodes of small amounts of blood in his stools. Examination shows pale conjunctivae. His hemoglobin concentration is 8.3 g/dL and mean corpuscular volume is 72μm3. Colonoscopy shows a 2.3-cm polypoid mass in the ascending colon. A photomicrograph of a biopsy specimen of the lesion is shown. Which of the following processes is most likely to be involved in the pathogenesis of this patient's condition?\nA. Underexpression of COX-2\nB. Increased phosphorylation of serine and threonine\nC. Impaired degradation of β-catenin\nD. Abnormal transfer of phosphate to cellular proteins\n\nA. Underexpression of COX-2\nB. Increased phosphorylation of serine and threonine\nC. Impaired degradation of β-catenin\nD. Abnormal transfer of phosphate to cellular proteins",
"options": [
"A. Underexpression of COX-2",
"B. Increased phosphorylation of serine and threonine",
"C. Impaired degradation of β-catenin",
"D. Abnormal transfer of phosphate to cellular proteins"
],
"answer": "Impaired degradation of β-catenin",
"gen_text_store": "",
"pid": "62",
"query": "A 53-year-old man comes to the physician because of a 2-month history of multiple episodes of small amounts of blood in his stools. Examination shows pale conjunctivae. His hemoglobin concentration is 8.3 g/dL and mean corpuscular volume is 72μm3. Colonoscopy shows a 2.3-cm polypoid mass in the ascending colon. A photomicrograph of a biopsy specimen of the lesion is shown. Which of the following processes is most likely to be involved in the pathogenesis of this patient's condition?\nA. Underexpression of COX-2\nB. Increased phosphorylation of serine and threonine\nC. Impaired degradation of β-catenin\nD. Abnormal transfer of phosphate to cellular proteins\nChoose the correct option.",
"image": null
},
{
"idx": 63,
"question": "A 65-year-old male is treated for anal carcinoma with therapy including external beam radiation. How does radiation affect cancer cells?\nA. Induces the formation of thymidine dimers\nB. Induces the formation of disulfide bonds\nC. Induces deamination of cytosine\nD. Induces breaks in double-stranded DNA\n\nA. Induces the formation of thymidine dimers\nB. Induces the formation of disulfide bonds\nC. Induces deamination of cytosine\nD. Induces breaks in double-stranded DNA",
"options": [
"A. Induces the formation of thymidine dimers",
"B. Induces the formation of disulfide bonds",
"C. Induces deamination of cytosine",
"D. Induces breaks in double-stranded DNA"
],
"answer": "Induces breaks in double-stranded DNA",
"gen_text_store": "",
"pid": "63",
"query": "A 65-year-old male is treated for anal carcinoma with therapy including external beam radiation. How does radiation affect cancer cells?\nA. Induces the formation of thymidine dimers\nB. Induces the formation of disulfide bonds\nC. Induces deamination of cytosine\nD. Induces breaks in double-stranded DNA\nChoose the correct option.",
"image": null
},
{
"idx": 64,
"question": "A 17-year-old man presents to his family physician for an evaluation about the size of his penis. He feels increasingly anxious during physical education (PE) class as he has noticed that the size of his penis is significantly smaller when compared to his peers. Based on the physical examination, he is Tanner stage 1. The weight and height are 60 kg (132 lb) and 175 cm (5 ft 9 in), respectively. The cardiopulmonary examination is normal; however, the patient has difficulty identifying coffee grounds by smell. Which of the following explains the pathophysiology underlying this patient’s disorder?\nA. Expansion of a CTG trinucleotide repeat\nB. Isolated gonadotropin-releasing hormone (GnRH) deficiency\nC. Sex-specific epigenetic imprinting\nD. Non-disjunction of sex chromosomes\n\nA. Expansion of a CTG trinucleotide repeat\nB. Isolated gonadotropin-releasing hormone (GnRH) deficiency\nC. Sex-specific epigenetic imprinting\nD. Non-disjunction of sex chromosomes",
"options": [
"A. Expansion of a CTG trinucleotide repeat",
"B. Isolated gonadotropin-releasing hormone (GnRH) deficiency",
"C. Sex-specific epigenetic imprinting",
"D. Non-disjunction of sex chromosomes"
],
"answer": "Isolated gonadotropin-releasing hormone (GnRH) deficiency",
"gen_text_store": "",
"pid": "64",
"query": "A 17-year-old man presents to his family physician for an evaluation about the size of his penis. He feels increasingly anxious during physical education (PE) class as he has noticed that the size of his penis is significantly smaller when compared to his peers. Based on the physical examination, he is Tanner stage 1. The weight and height are 60 kg (132 lb) and 175 cm (5 ft 9 in), respectively. The cardiopulmonary examination is normal; however, the patient has difficulty identifying coffee grounds by smell. Which of the following explains the pathophysiology underlying this patient’s disorder?\nA. Expansion of a CTG trinucleotide repeat\nB. Isolated gonadotropin-releasing hormone (GnRH) deficiency\nC. Sex-specific epigenetic imprinting\nD. Non-disjunction of sex chromosomes\nChoose the correct option.",
"image": null
},
{
"idx": 65,
"question": "A 25-year-old man is brought to the emergency department by police. He was found at a local celebration acting very strangely and was reported by other patrons of the event. The patient is very anxious and initially is hesitant to answer questions. He denies any substance use and states that he was just trying to have a good time. The patient's responses are slightly delayed and he seems to have difficulty processing his thoughts. The patient tells you he feels very anxious and asks for some medication to calm him down. The patient has a past medical history of psoriasis which is treated with topical steroids. His temperature is 99.5°F (37.5°C), blood pressure is 120/75 mmHg, pulse is 110/min, respirations are 15/min, and oxygen saturation is 99% on room air. On physical exam, you note an anxious young man. HEENT exam reveals a dry mouth and conjunctival injection. Neurological exam reveals cranial nerves II-XII as grossly intact with normal strength and sensation in his upper and lower extremities. Cardiac exam reveals tachycardia, and pulmonary exam is within normal limits. Which of the following is the most likely intoxication in this patient?\nA. Alcohol\nB. Marijuana\nC. Cocaine\nD. Phencyclidine\n\nA. Alcohol\nB. Marijuana\nC. Cocaine\nD. Phencyclidine",
"options": [
"A. Alcohol",
"B. Marijuana",
"C. Cocaine",
"D. Phencyclidine"
],
"answer": "Marijuana",
"gen_text_store": "",
"pid": "65",
"query": "A 25-year-old man is brought to the emergency department by police. He was found at a local celebration acting very strangely and was reported by other patrons of the event. The patient is very anxious and initially is hesitant to answer questions. He denies any substance use and states that he was just trying to have a good time. The patient's responses are slightly delayed and he seems to have difficulty processing his thoughts. The patient tells you he feels very anxious and asks for some medication to calm him down. The patient has a past medical history of psoriasis which is treated with topical steroids. His temperature is 99.5°F (37.5°C), blood pressure is 120/75 mmHg, pulse is 110/min, respirations are 15/min, and oxygen saturation is 99% on room air. On physical exam, you note an anxious young man. HEENT exam reveals a dry mouth and conjunctival injection. Neurological exam reveals cranial nerves II-XII as grossly intact with normal strength and sensation in his upper and lower extremities. Cardiac exam reveals tachycardia, and pulmonary exam is within normal limits. Which of the following is the most likely intoxication in this patient?\nA. Alcohol\nB. Marijuana\nC. Cocaine\nD. Phencyclidine\nChoose the correct option.",
"image": null
},
{
"idx": 66,
"question": "A 40-year-old man presents to the clinic with complaints of increased bilateral pain in his knees. The pain developed over time and now limits his mobility. He states that the pain is worse at the end of the day, though he does have some early-morning stiffness lasting about 20 minutes. He used to have some success with over-the-counter NSAIDs; however, they no longer help. The patient also has been taking metformin for the past 2 years and is severely obese, with a BMI of 41 kg/m2. Additionally, he states that he has felt increasingly tired during the day, often dozes off during work, and no longer feels refreshed when he wakes up in the morning. Upon examination, there is no tenderness on palpation or erythema; however, some crepitus is felt. He has no other complaints but has a family history of rheumatoid arthritis (RA) on his mother’s side. Which of the following factors is the underlying cause of the patient’s pain, as well as the rest of his complaints?\nA. Medication side effect\nB. Excess weight\nC. Infection\nD. Occult malignancy\n\nA. Medication side effect\nB. Excess weight\nC. Infection\nD. Occult malignancy",
"options": [
"A. Medication side effect",
"B. Excess weight",
"C. Infection",
"D. Occult malignancy"
],
"answer": "Excess weight",
"gen_text_store": "",
"pid": "66",
"query": "A 40-year-old man presents to the clinic with complaints of increased bilateral pain in his knees. The pain developed over time and now limits his mobility. He states that the pain is worse at the end of the day, though he does have some early-morning stiffness lasting about 20 minutes. He used to have some success with over-the-counter NSAIDs; however, they no longer help. The patient also has been taking metformin for the past 2 years and is severely obese, with a BMI of 41 kg/m2. Additionally, he states that he has felt increasingly tired during the day, often dozes off during work, and no longer feels refreshed when he wakes up in the morning. Upon examination, there is no tenderness on palpation or erythema; however, some crepitus is felt. He has no other complaints but has a family history of rheumatoid arthritis (RA) on his mother’s side. Which of the following factors is the underlying cause of the patient’s pain, as well as the rest of his complaints?\nA. Medication side effect\nB. Excess weight\nC. Infection\nD. Occult malignancy\nChoose the correct option.",
"image": null
},
{
"idx": 67,
"question": "A 32-year-old Caucasian woman is referred to a gastroenterologist by her family physician for 8 months of abdominal pain, foul-smelling diarrhea with floating, bulky stools, weight loss, and macrocytic anemia. Her personal history is relevant for allergic rhinitis. Physical examination shows grouped, erythematous papulovesicular lesions on her arms, torso, and abdomen. Which of the following is the most appropriate approach for the management of this patient?\nA. Amitriptyline\nB. Octreotide\nC. Gluten-free diet\nD. Methysergide maleate\n\nA. Amitriptyline\nB. Octreotide\nC. Gluten-free diet\nD. Methysergide maleate",
"options": [
"A. Amitriptyline",
"B. Octreotide",
"C. Gluten-free diet",
"D. Methysergide maleate"
],
"answer": "Gluten-free diet",
"gen_text_store": "",
"pid": "67",
"query": "A 32-year-old Caucasian woman is referred to a gastroenterologist by her family physician for 8 months of abdominal pain, foul-smelling diarrhea with floating, bulky stools, weight loss, and macrocytic anemia. Her personal history is relevant for allergic rhinitis. Physical examination shows grouped, erythematous papulovesicular lesions on her arms, torso, and abdomen. Which of the following is the most appropriate approach for the management of this patient?\nA. Amitriptyline\nB. Octreotide\nC. Gluten-free diet\nD. Methysergide maleate\nChoose the correct option.",
"image": null
},
{
"idx": 68,
"question": "A 65-year-old man presents to his primary care physician with a neck mass. He first noticed a firm mass on the anterior aspect of his neck approximately 4 months ago. The mass is painless and has not increased in size since then. He has also noticed occasional fatigue and has gained 10 pounds in the past 4 months despite no change in his diet or exercise frequency. His past medical history is notable for gout for which he takes allopurinol. He denies any prior thyroid disorder. He runs 4 times per week and eats a balanced diet of mostly fruits and vegetables. He does not smoke and drinks a glass of wine with dinner. His family history is notable for medullary thyroid cancer in his maternal uncle. His temperature is 97.8°F (36.6°C), blood pressure is 127/72 mmHg, pulse is 87/min, and respirations are 19/min. On exam, he has a firm, symmetric, and stone-firm thyroid. A biopsy of this patient's lesion would most likely demonstrate which of the following findings?\nA. Diffuse infiltrate of lymphoid cells destroying thyroid follicles\nB. Dense fibroinflammatory infiltrate\nC. Pleomorphic undifferentiated infiltrative cells with necrosis\nD. Stromal amyloid deposition\n\nA. Diffuse infiltrate of lymphoid cells destroying thyroid follicles\nB. Dense fibroinflammatory infiltrate\nC. Pleomorphic undifferentiated infiltrative cells with necrosis\nD. Stromal amyloid deposition",
"options": [
"A. Diffuse infiltrate of lymphoid cells destroying thyroid follicles",
"B. Dense fibroinflammatory infiltrate",
"C. Pleomorphic undifferentiated infiltrative cells with necrosis",
"D. Stromal amyloid deposition"
],
"answer": "Dense fibroinflammatory infiltrate",
"gen_text_store": "",
"pid": "68",
"query": "A 65-year-old man presents to his primary care physician with a neck mass. He first noticed a firm mass on the anterior aspect of his neck approximately 4 months ago. The mass is painless and has not increased in size since then. He has also noticed occasional fatigue and has gained 10 pounds in the past 4 months despite no change in his diet or exercise frequency. His past medical history is notable for gout for which he takes allopurinol. He denies any prior thyroid disorder. He runs 4 times per week and eats a balanced diet of mostly fruits and vegetables. He does not smoke and drinks a glass of wine with dinner. His family history is notable for medullary thyroid cancer in his maternal uncle. His temperature is 97.8°F (36.6°C), blood pressure is 127/72 mmHg, pulse is 87/min, and respirations are 19/min. On exam, he has a firm, symmetric, and stone-firm thyroid. A biopsy of this patient's lesion would most likely demonstrate which of the following findings?\nA. Diffuse infiltrate of lymphoid cells destroying thyroid follicles\nB. Dense fibroinflammatory infiltrate\nC. Pleomorphic undifferentiated infiltrative cells with necrosis\nD. Stromal amyloid deposition\nChoose the correct option.",
"image": null
},
{
"idx": 69,
"question": "A 75-year-old man comes to the physician because of a 7-day history of nausea and vomiting. Over the past 2 days, he has also been feeling weak and tired. When standing up after sitting for a while, he feels dizzy. He says he has to go to the bathroom more often than usual, and that he is urinating “a normal amount” each time. He has not had diarrhea. He has hypertension, for which he has been taking hydrochlorothiazide for the past 6 months. He drinks 9 glasses of water per day and takes his medication regularly. He is 168 cm (5 ft 6 in) tall and weighs 90 kg (198 lb); BMI is 32 kg/m2. His temperature is 36.5°C (97.7°F), blood pressure is 106/54 mm Hg, and pulse is 92/min. Physical examination shows whitening of the tongue. Skin that is pinched on the back of the hand retracts after 5 seconds. On mental status examination, his speech is slowed; he is oriented to person, place, and time. Laboratory studies show:\nSerum\nNa+ 150 mEq/L\nCl− 97 mEq/L\nK+ 3.6 mEq/L\nHCO3− 30 mEq/L\nOsmolality 354 mOsm/kg\nHemoglobin A1C 10.5%\nUrine\nOsmolality 400 mOsm/kg\nWhich of the following is the most likely explanation for these findings?\"\nA. Diuretic overdose\nB. Osmotic diuresis\nC. Excess production of aldosterone\nD. Insufficient production of antidiuretic hormone\n\nA. Diuretic overdose\nB. Osmotic diuresis\nC. Excess production of aldosterone\nD. Insufficient production of antidiuretic hormone",
"options": [
"A. Diuretic overdose",
"B. Osmotic diuresis",
"C. Excess production of aldosterone",
"D. Insufficient production of antidiuretic hormone"
],
"answer": "Osmotic diuresis",
"gen_text_store": "",
"pid": "69",
"query": "A 75-year-old man comes to the physician because of a 7-day history of nausea and vomiting. Over the past 2 days, he has also been feeling weak and tired. When standing up after sitting for a while, he feels dizzy. He says he has to go to the bathroom more often than usual, and that he is urinating “a normal amount” each time. He has not had diarrhea. He has hypertension, for which he has been taking hydrochlorothiazide for the past 6 months. He drinks 9 glasses of water per day and takes his medication regularly. He is 168 cm (5 ft 6 in) tall and weighs 90 kg (198 lb); BMI is 32 kg/m2. His temperature is 36.5°C (97.7°F), blood pressure is 106/54 mm Hg, and pulse is 92/min. Physical examination shows whitening of the tongue. Skin that is pinched on the back of the hand retracts after 5 seconds. On mental status examination, his speech is slowed; he is oriented to person, place, and time. Laboratory studies show:\nSerum\nNa+ 150 mEq/L\nCl− 97 mEq/L\nK+ 3.6 mEq/L\nHCO3− 30 mEq/L\nOsmolality 354 mOsm/kg\nHemoglobin A1C 10.5%\nUrine\nOsmolality 400 mOsm/kg\nWhich of the following is the most likely explanation for these findings?\"\nA. Diuretic overdose\nB. Osmotic diuresis\nC. Excess production of aldosterone\nD. Insufficient production of antidiuretic hormone\nChoose the correct option.",
"image": null
},
{
"idx": 70,
"question": "An 18-year-old male is brought in by fire rescue. The patient was an unrestrained passenger in a motor vehicle crash and was ejected from the vehicle after collision. Upon arrival to the trauma bay, the patient has a Glasgow coma scale (GCS) of 6. He is rapidly intubated, and vitals are a temperature of 99.5°F (37.5°C), pulse of 130 bpm, and blood pressure of 83/64 mmHg. He is noted to have multiple ecchymoses over his body, as well as petechiae and purpura. He has a laceration over his clavicle that continues to bleed despite a pressure bandage. Radiographs of his lower extremity show multiple long bone fractures. Two large bore IV lines are placed, and the patient oozes from around the sites of venepuncture. Labs are notable for a WBC of 20,000/mm^3, Hb of 10.1g/dL, platelets of 48,000/mm^3, and prolongation of the PT and aPTT. This patient's presentation can best be explained by which of the following diagnoses?\nA. Air embolization\nB. Tension pneumothorax\nC. Disseminated intravascular coagulation\nD. Coagulopathy of trauma\n\nA. Air embolization\nB. Tension pneumothorax\nC. Disseminated intravascular coagulation\nD. Coagulopathy of trauma",
"options": [
"A. Air embolization",
"B. Tension pneumothorax",
"C. Disseminated intravascular coagulation",
"D. Coagulopathy of trauma"
],
"answer": "Disseminated intravascular coagulation",
"gen_text_store": "",
"pid": "70",
"query": "An 18-year-old male is brought in by fire rescue. The patient was an unrestrained passenger in a motor vehicle crash and was ejected from the vehicle after collision. Upon arrival to the trauma bay, the patient has a Glasgow coma scale (GCS) of 6. He is rapidly intubated, and vitals are a temperature of 99.5°F (37.5°C), pulse of 130 bpm, and blood pressure of 83/64 mmHg. He is noted to have multiple ecchymoses over his body, as well as petechiae and purpura. He has a laceration over his clavicle that continues to bleed despite a pressure bandage. Radiographs of his lower extremity show multiple long bone fractures. Two large bore IV lines are placed, and the patient oozes from around the sites of venepuncture. Labs are notable for a WBC of 20,000/mm^3, Hb of 10.1g/dL, platelets of 48,000/mm^3, and prolongation of the PT and aPTT. This patient's presentation can best be explained by which of the following diagnoses?\nA. Air embolization\nB. Tension pneumothorax\nC. Disseminated intravascular coagulation\nD. Coagulopathy of trauma\nChoose the correct option.",
"image": null
},
{
"idx": 71,
"question": "A 24-year-old woman gravida 2, para 1 at 24 weeks' gestation comes to the physician for a prenatal visit. She feels well. Her earlier pregnancy was uncomplicated. This is her 4th prenatal visit. She had an ultrasound scan 2 weeks ago that showed a live intrauterine pregnancy consistent with a 22-week gestation with no anomalies. She had a normal Pap smear 2 years ago. Vital signs are within normal limits. Pelvic examination shows a uterus consistent in size with a 24-week gestation. Her blood group and type is B positive. Which of the following is the most appropriate next step in management?\nA. Oral glucose challenge test\nB. Cardiotocography\nC. Swab for GBS culture\nD. Tdap vaccination\n\nA. Oral glucose challenge test\nB. Cardiotocography\nC. Swab for GBS culture\nD. Tdap vaccination",
"options": [
"A. Oral glucose challenge test",
"B. Cardiotocography",
"C. Swab for GBS culture",
"D. Tdap vaccination"
],
"answer": "Oral glucose challenge test",
"gen_text_store": "",
"pid": "71",
"query": "A 24-year-old woman gravida 2, para 1 at 24 weeks' gestation comes to the physician for a prenatal visit. She feels well. Her earlier pregnancy was uncomplicated. This is her 4th prenatal visit. She had an ultrasound scan 2 weeks ago that showed a live intrauterine pregnancy consistent with a 22-week gestation with no anomalies. She had a normal Pap smear 2 years ago. Vital signs are within normal limits. Pelvic examination shows a uterus consistent in size with a 24-week gestation. Her blood group and type is B positive. Which of the following is the most appropriate next step in management?\nA. Oral glucose challenge test\nB. Cardiotocography\nC. Swab for GBS culture\nD. Tdap vaccination\nChoose the correct option.",
"image": null
},
{
"idx": 72,
"question": "A 67-year-old man presents with feelings of nervousness and anxiety. He mentions that lately, he has been feeling increasingly restless and is unable to control feelings of nervousness pertaining to all his daily tasks. He noticed that these feelings were more prominent in the last 2 months but have been present on and off for the last year. On many occasions, his mind will be racing with thoughts that keep him up at night. During these moments, he finds his heart racing and feels light-headed and dizzy to the point of blacking out. He has also been experiencing back and neck pain with increased muscle tension in these areas. The patient reports no smoking or alcohol use but mentions that he had tried cocaine and heroin in his 20s and 30s. Which of the following would be the best course of treatment for this patient’s symptoms?\nA. Diazepam\nB. Ramelteon\nC. Buspirone\nD. Alprazolam\n\nA. Diazepam\nB. Ramelteon\nC. Buspirone\nD. Alprazolam",
"options": [
"A. Diazepam",
"B. Ramelteon",
"C. Buspirone",
"D. Alprazolam"
],
"answer": "Buspirone",
"gen_text_store": "",
"pid": "72",
"query": "A 67-year-old man presents with feelings of nervousness and anxiety. He mentions that lately, he has been feeling increasingly restless and is unable to control feelings of nervousness pertaining to all his daily tasks. He noticed that these feelings were more prominent in the last 2 months but have been present on and off for the last year. On many occasions, his mind will be racing with thoughts that keep him up at night. During these moments, he finds his heart racing and feels light-headed and dizzy to the point of blacking out. He has also been experiencing back and neck pain with increased muscle tension in these areas. The patient reports no smoking or alcohol use but mentions that he had tried cocaine and heroin in his 20s and 30s. Which of the following would be the best course of treatment for this patient’s symptoms?\nA. Diazepam\nB. Ramelteon\nC. Buspirone\nD. Alprazolam\nChoose the correct option.",
"image": null
},
{
"idx": 73,
"question": "A 45-year-old man arrives by ambulance to the emergency room after being involved in a very severe construction accident. The patient was found unconscious with a large metal spike protruding from his abdomen by a coworker who was unable to estimate the amount of time the patient went without medical aid. Upon arrival to the ER, the patient was unconscious and unresponsive. His vital signs are BP: 80/40, HR: 120 bpm, RR: 25 bpm, Temperature: 97.1 degrees, and SPO2: 99%.He is taken to the operating room to remove the foreign body and control the bleeding. Although both objectives were accomplished, the patient had an acute drop in his blood pressure during the surgery at which time ST elevations were noted in multiple leads. This resolved with adequate fluid resuscitation and numerous blood transfusions. The patient remained sedated after surgery and continued to have relatively stable vital signs until his third day in the intensive care unit, when he experiences an oxygen desaturation of 85% despite being on a respirator with 100% oxygen at 15 breaths/minute. On auscultation air entry is present bilaterally with the presence of crackles. A 2/6 systolic murmur is heard. Readings from a Swan-Ganz catheter display the following: central venous pressure (CVP): 4 mmHg, right ventricular pressure (RVP) 20/5 mmHg, pulmonary artery pressure (PAP): 20/5 mmHg. Pulmonary capillary wedge pressure (PCWP): 5 mm Hg. A chest x-ray is shown as Image A. The patient dies soon after this episode. What is the most likely direct cause of his death?\nA. Diffuse alveolar damage\nB. Ventricular septal defect\nC. Myocardial free wall rupture\nD. Myocardial reinfarction\n\nA. Diffuse alveolar damage\nB. Ventricular septal defect\nC. Myocardial free wall rupture\nD. Myocardial reinfarction",
"options": [
"A. Diffuse alveolar damage",
"B. Ventricular septal defect",
"C. Myocardial free wall rupture",
"D. Myocardial reinfarction"
],
"answer": "Diffuse alveolar damage",
"gen_text_store": "",
"pid": "73",
"query": "A 45-year-old man arrives by ambulance to the emergency room after being involved in a very severe construction accident. The patient was found unconscious with a large metal spike protruding from his abdomen by a coworker who was unable to estimate the amount of time the patient went without medical aid. Upon arrival to the ER, the patient was unconscious and unresponsive. His vital signs are BP: 80/40, HR: 120 bpm, RR: 25 bpm, Temperature: 97.1 degrees, and SPO2: 99%.He is taken to the operating room to remove the foreign body and control the bleeding. Although both objectives were accomplished, the patient had an acute drop in his blood pressure during the surgery at which time ST elevations were noted in multiple leads. This resolved with adequate fluid resuscitation and numerous blood transfusions. The patient remained sedated after surgery and continued to have relatively stable vital signs until his third day in the intensive care unit, when he experiences an oxygen desaturation of 85% despite being on a respirator with 100% oxygen at 15 breaths/minute. On auscultation air entry is present bilaterally with the presence of crackles. A 2/6 systolic murmur is heard. Readings from a Swan-Ganz catheter display the following: central venous pressure (CVP): 4 mmHg, right ventricular pressure (RVP) 20/5 mmHg, pulmonary artery pressure (PAP): 20/5 mmHg. Pulmonary capillary wedge pressure (PCWP): 5 mm Hg. A chest x-ray is shown as Image A. The patient dies soon after this episode. What is the most likely direct cause of his death?\nA. Diffuse alveolar damage\nB. Ventricular septal defect\nC. Myocardial free wall rupture\nD. Myocardial reinfarction\nChoose the correct option.",
"image": null
},
{
"idx": 74,
"question": "A 43-year-old man with a history of hepatitis C and current intravenous drug use presents with 5 days of fever, chills, headache, and severe back pain. On physical exam, temperature is 100.6 deg F (38.1 deg C), blood pressure is 109/56 mmHg, pulse is 94/min, and respirations are 18/min. He is thin and diaphoretic with pinpoint pupils, poor dentition, and track marks on his arms and legs. A high-pitched systolic murmur is heard, loudest in the left sternal border and with inspiration. He is admitted to the hospital and started on broad-spectrum antibiotics. One of the blood cultures drawn 12 hours ago returns positive for Staphylococcus aureus. Which of the following is the most appropriate next step to confirm the diagnosis?\nA. Repeat blood cultures now\nB. Repeat blood cultures 24 hours after initial cultures were drawn\nC. Repeat blood cultures 48 hours after initial cultures were drawn\nD. Do not repeat blood cultures\n\nA. Repeat blood cultures now\nB. Repeat blood cultures 24 hours after initial cultures were drawn\nC. Repeat blood cultures 48 hours after initial cultures were drawn\nD. Do not repeat blood cultures",
"options": [
"A. Repeat blood cultures now",
"B. Repeat blood cultures 24 hours after initial cultures were drawn",
"C. Repeat blood cultures 48 hours after initial cultures were drawn",
"D. Do not repeat blood cultures"
],
"answer": "Repeat blood cultures now",
"gen_text_store": "",
"pid": "74",
"query": "A 43-year-old man with a history of hepatitis C and current intravenous drug use presents with 5 days of fever, chills, headache, and severe back pain. On physical exam, temperature is 100.6 deg F (38.1 deg C), blood pressure is 109/56 mmHg, pulse is 94/min, and respirations are 18/min. He is thin and diaphoretic with pinpoint pupils, poor dentition, and track marks on his arms and legs. A high-pitched systolic murmur is heard, loudest in the left sternal border and with inspiration. He is admitted to the hospital and started on broad-spectrum antibiotics. One of the blood cultures drawn 12 hours ago returns positive for Staphylococcus aureus. Which of the following is the most appropriate next step to confirm the diagnosis?\nA. Repeat blood cultures now\nB. Repeat blood cultures 24 hours after initial cultures were drawn\nC. Repeat blood cultures 48 hours after initial cultures were drawn\nD. Do not repeat blood cultures\nChoose the correct option.",
"image": null
},
{
"idx": 75,
"question": "A 34-year-old man presents to the emergency department complaining of headache, fever, chills, cough, shortness of breath, and chest pain for the past 4 days. He smokes 2 packs per day and drinks 2–3 beers every day. He denies any previous medical problems except for seasonal allergies for which he takes diphenhydramine on occasions. At the hospital, the vital signs include: temperature 40.0°C (104.0°F), blood pressure 140/80 mm Hg, heart rate 98/min, and respiratory rate 28/min. On physical exam, he is thin and poorly kept. His clothes appear dirty. Small scars are visible in the decubitus region of both arms. The lung sounds are equal with bilateral crackles, and heart auscultation reveals a systolic murmur that radiates to the left axilla. Petechiae are seen on the hard palate and palms of his hands. A chest X-ray and blood cultures are ordered. What is the most likely organism causing his symptoms?\nA. Streptococci viridans\nB. Staphylococcus aureus\nC. Aspergillus fumigatus\nD. Staphylococcus epidermidis\n\nA. Streptococci viridans\nB. Staphylococcus aureus\nC. Aspergillus fumigatus\nD. Staphylococcus epidermidis",
"options": [
"A. Streptococci viridans",
"B. Staphylococcus aureus",
"C. Aspergillus fumigatus",
"D. Staphylococcus epidermidis"
],
"answer": "Staphylococcus aureus",
"gen_text_store": "",
"pid": "75",
"query": "A 34-year-old man presents to the emergency department complaining of headache, fever, chills, cough, shortness of breath, and chest pain for the past 4 days. He smokes 2 packs per day and drinks 2–3 beers every day. He denies any previous medical problems except for seasonal allergies for which he takes diphenhydramine on occasions. At the hospital, the vital signs include: temperature 40.0°C (104.0°F), blood pressure 140/80 mm Hg, heart rate 98/min, and respiratory rate 28/min. On physical exam, he is thin and poorly kept. His clothes appear dirty. Small scars are visible in the decubitus region of both arms. The lung sounds are equal with bilateral crackles, and heart auscultation reveals a systolic murmur that radiates to the left axilla. Petechiae are seen on the hard palate and palms of his hands. A chest X-ray and blood cultures are ordered. What is the most likely organism causing his symptoms?\nA. Streptococci viridans\nB. Staphylococcus aureus\nC. Aspergillus fumigatus\nD. Staphylococcus epidermidis\nChoose the correct option.",
"image": null
},
{
"idx": 76,
"question": "A 52-year-old man presents to the physician with a 6-month history of shortness of breath and nonproductive cough. He was recently diagnosed with stage 3 embryonal carcinoma testicular cancer. Following an orchiectomy, he was placed on chemotherapy. Cardiopulmonary examination shows fine inspiratory crackles bilaterally. There is clubbing present in the fingers bilaterally. Pulmonary function tests (PFTs) show FVC is 78% of expected and FEV1/FVC ratio is 92%. A CT scan of the chest is shown. Which of the following drugs is responsible for the patient’s condition?\nA. Bleomycin\nB. Carboplatin\nC. Cisplatin\nD. Ifosfamide\n\nA. Bleomycin\nB. Carboplatin\nC. Cisplatin\nD. Ifosfamide",
"options": [
"A. Bleomycin",
"B. Carboplatin",
"C. Cisplatin",
"D. Ifosfamide"
],
"answer": "Bleomycin",
"gen_text_store": "",
"pid": "76",
"query": "A 52-year-old man presents to the physician with a 6-month history of shortness of breath and nonproductive cough. He was recently diagnosed with stage 3 embryonal carcinoma testicular cancer. Following an orchiectomy, he was placed on chemotherapy. Cardiopulmonary examination shows fine inspiratory crackles bilaterally. There is clubbing present in the fingers bilaterally. Pulmonary function tests (PFTs) show FVC is 78% of expected and FEV1/FVC ratio is 92%. A CT scan of the chest is shown. Which of the following drugs is responsible for the patient’s condition?\nA. Bleomycin\nB. Carboplatin\nC. Cisplatin\nD. Ifosfamide\nChoose the correct option.",
"image": null
},
{
"idx": 77,
"question": "A 63-year-old man presents to the clinic for left calf pain when walking a distance of more than 200 m. He has had this pain for more than 8 months now, and he rates it as 7 out of 10. The pain subsides with rest. The patient has had a history of diabetes mellitus for the past 2 years which is well controlled. A percutaneous coronary intervention was performed in 2014. His current medications are insulin and aspirin. Family history is significant for coronary artery disease. He has an 80 pack-year history of smoking and currently smokes. He consumes 4 drinks per day of alcohol. On physical examination, his blood pressure is 144/89 mm Hg, the heart rate is 80/min and regular, the breathing rate is 25/min, and the pulse oximetry is 96%. Normal cardiac and lung sounds were heard on auscultation. Which of the following is the appropriate treatment to improve the patient’s symptoms?\nA. Cilostazol\nB. Femoral embolectomy\nC. Femoral-to-popliteal bypass graft\nD. Interventional endovascular treatment\n\nA. Cilostazol\nB. Femoral embolectomy\nC. Femoral-to-popliteal bypass graft\nD. Interventional endovascular treatment",
"options": [
"A. Cilostazol",
"B. Femoral embolectomy",
"C. Femoral-to-popliteal bypass graft",
"D. Interventional endovascular treatment"
],
"answer": "Cilostazol",
"gen_text_store": "",
"pid": "77",
"query": "A 63-year-old man presents to the clinic for left calf pain when walking a distance of more than 200 m. He has had this pain for more than 8 months now, and he rates it as 7 out of 10. The pain subsides with rest. The patient has had a history of diabetes mellitus for the past 2 years which is well controlled. A percutaneous coronary intervention was performed in 2014. His current medications are insulin and aspirin. Family history is significant for coronary artery disease. He has an 80 pack-year history of smoking and currently smokes. He consumes 4 drinks per day of alcohol. On physical examination, his blood pressure is 144/89 mm Hg, the heart rate is 80/min and regular, the breathing rate is 25/min, and the pulse oximetry is 96%. Normal cardiac and lung sounds were heard on auscultation. Which of the following is the appropriate treatment to improve the patient’s symptoms?\nA. Cilostazol\nB. Femoral embolectomy\nC. Femoral-to-popliteal bypass graft\nD. Interventional endovascular treatment\nChoose the correct option.",
"image": null
},
{
"idx": 78,
"question": "A 56-year-old man comes to the physician because of a 1-day history of sudden severe pain in his right great toe. Four months ago, he had an episode of severe joint pain involving his left knee that lasted several days and resolved with over-the-counter analgesics. He has a history of hypertension treated with hydrochlorothiazide and nephrolithiasis. Examination shows erythema, swelling, warmth, and tenderness of the right metatarsophalangeal joint; range of movement is limited by pain. His serum uric acid is 12 mg/dL. Arthrocentesis yields cloudy fluid with a leukocyte count of 18,500/mm3 (80% segmented neutrophils). Polarized light microscopy of the synovial fluid is shown. Which of the following is the mechanism of action of the most appropriate long-term pharmacotherapy for this patient's condition?\nA. Increased conversion of uric acid to allantoin\nB. Inhibition of phospholipase A\nC. Inhibition of xanthine oxidase\nD. Increased renal excretion of urate\n\nA. Increased conversion of uric acid to allantoin\nB. Inhibition of phospholipase A\nC. Inhibition of xanthine oxidase\nD. Increased renal excretion of urate",
"options": [
"A. Increased conversion of uric acid to allantoin",
"B. Inhibition of phospholipase A",
"C. Inhibition of xanthine oxidase",
"D. Increased renal excretion of urate"
],
"answer": "Inhibition of xanthine oxidase",
"gen_text_store": "",
"pid": "78",
"query": "A 56-year-old man comes to the physician because of a 1-day history of sudden severe pain in his right great toe. Four months ago, he had an episode of severe joint pain involving his left knee that lasted several days and resolved with over-the-counter analgesics. He has a history of hypertension treated with hydrochlorothiazide and nephrolithiasis. Examination shows erythema, swelling, warmth, and tenderness of the right metatarsophalangeal joint; range of movement is limited by pain. His serum uric acid is 12 mg/dL. Arthrocentesis yields cloudy fluid with a leukocyte count of 18,500/mm3 (80% segmented neutrophils). Polarized light microscopy of the synovial fluid is shown. Which of the following is the mechanism of action of the most appropriate long-term pharmacotherapy for this patient's condition?\nA. Increased conversion of uric acid to allantoin\nB. Inhibition of phospholipase A\nC. Inhibition of xanthine oxidase\nD. Increased renal excretion of urate\nChoose the correct option.",
"image": null
},
{
"idx": 79,
"question": "A 32-year-old male presents to the ED with acute-onset chest pain. His blood pressure is 157/90 mmHg and his his pulse is 116/min. He appears anxious and agitated and a careful exam reveals dilated pupils and a perforated nasal septum. An EKG reveals ST segment elevation so he is urgently taken for cardiac intervention. Upon review, this patient reveals that he has not had care from a physician since he graduated from college. In the interim he has been largely unemployed and admits that he has recently been homeless. When asked directly, the patient admits to alcohol and marijuana use but denies illicit drug use. Which of the following best describes the mechanism of action of the agent most likely responsible for this patient's presentation?\nA. Blocking reuptake of dopamine and norepinephrine\nB. Inhibiting breakdown of biogenic amines\nC. Antagonizing the NMDA receptor\nD. Inhibiting the GABA receptor\n\nA. Blocking reuptake of dopamine and norepinephrine\nB. Inhibiting breakdown of biogenic amines\nC. Antagonizing the NMDA receptor\nD. Inhibiting the GABA receptor",
"options": [
"A. Blocking reuptake of dopamine and norepinephrine",
"B. Inhibiting breakdown of biogenic amines",
"C. Antagonizing the NMDA receptor",
"D. Inhibiting the GABA receptor"
],
"answer": "Blocking reuptake of dopamine and norepinephrine",
"gen_text_store": "",
"pid": "79",
"query": "A 32-year-old male presents to the ED with acute-onset chest pain. His blood pressure is 157/90 mmHg and his his pulse is 116/min. He appears anxious and agitated and a careful exam reveals dilated pupils and a perforated nasal septum. An EKG reveals ST segment elevation so he is urgently taken for cardiac intervention. Upon review, this patient reveals that he has not had care from a physician since he graduated from college. In the interim he has been largely unemployed and admits that he has recently been homeless. When asked directly, the patient admits to alcohol and marijuana use but denies illicit drug use. Which of the following best describes the mechanism of action of the agent most likely responsible for this patient's presentation?\nA. Blocking reuptake of dopamine and norepinephrine\nB. Inhibiting breakdown of biogenic amines\nC. Antagonizing the NMDA receptor\nD. Inhibiting the GABA receptor\nChoose the correct option.",
"image": null
},
{
"idx": 80,
"question": "A 67-year-old man is brought to the emergency department with severe, crushing, retrosternal chest pain for the last 45 minutes. The pain radiates to his left shoulder and is associated with sweating. The past medical history is significant for hypercholesterolemia, for which he takes lovastatin. He smoked as a youth but quit at 40 years of age. On arrival at the emergency department, the vital signs were as follows: pulse 58/min, respiratory rate 22/min, and blood pressure 90/56 mm Hg. He is sweating profusely. The jugular venous pulse is visible 2.5 cm above the sternal angle. Auscultation reveals soft S1 and S2 heart sounds with an added S4 and bilateral inspiratory crackles at the lung bases. The electrocardiogram shows ST-elevations in leads V1 and V2. A diagnosis of an anteroseptal infarction is made. The patient was given aspirin on the way to the hospital. He is started on dopamine, morphine, nitroglycerin, and streptokinase. Which of the following would be the most concerning development over the next 24h this patient?\nA. Hemoptysis\nB. Easy fatigability\nC. Persistent ST-segment elevation\nD. Shortness of breath\n\nA. Hemoptysis\nB. Easy fatigability\nC. Persistent ST-segment elevation\nD. Shortness of breath",
"options": [
"A. Hemoptysis",
"B. Easy fatigability",
"C. Persistent ST-segment elevation",
"D. Shortness of breath"
],
"answer": "Hemoptysis",
"gen_text_store": "",
"pid": "80",
"query": "A 67-year-old man is brought to the emergency department with severe, crushing, retrosternal chest pain for the last 45 minutes. The pain radiates to his left shoulder and is associated with sweating. The past medical history is significant for hypercholesterolemia, for which he takes lovastatin. He smoked as a youth but quit at 40 years of age. On arrival at the emergency department, the vital signs were as follows: pulse 58/min, respiratory rate 22/min, and blood pressure 90/56 mm Hg. He is sweating profusely. The jugular venous pulse is visible 2.5 cm above the sternal angle. Auscultation reveals soft S1 and S2 heart sounds with an added S4 and bilateral inspiratory crackles at the lung bases. The electrocardiogram shows ST-elevations in leads V1 and V2. A diagnosis of an anteroseptal infarction is made. The patient was given aspirin on the way to the hospital. He is started on dopamine, morphine, nitroglycerin, and streptokinase. Which of the following would be the most concerning development over the next 24h this patient?\nA. Hemoptysis\nB. Easy fatigability\nC. Persistent ST-segment elevation\nD. Shortness of breath\nChoose the correct option.",
"image": null
},
{
"idx": 81,
"question": "A 52-year-old man presents to the physician because of ongoing shortness of breath, which is more prominent when he lies down. Occasionally, he experiences palpitations, especially during strenuous activities. In addition to this, he has been experiencing difficulty in digestion and often experiences regurgitation and dysphagia. He reports that he emigrated from Mexico 20 years ago and visits his hometown twice a year. The vital signs include: blood pressure 120/75 mm Hg, respiratory rate 19/min, and pulse 100/min. The physical examination shows jugular vein distention along with pitting edema in the ankles. Bilateral basilar crackles and an S3 gallop are heard on auscultation of the chest. A chest X-ray is taken. An electrocardiogram (ECG) shows no significant findings. What is the most likely explanation for this patient’s physical and diagnostic findings?\nA. Alcohol abuse\nB. Hypertensive changes\nC. Parasitic infection\nD. Bacterial infection\n\nA. Alcohol abuse\nB. Hypertensive changes\nC. Parasitic infection\nD. Bacterial infection",
"options": [
"A. Alcohol abuse",
"B. Hypertensive changes",
"C. Parasitic infection",
"D. Bacterial infection"
],
"answer": "Parasitic infection",
"gen_text_store": "",
"pid": "81",
"query": "A 52-year-old man presents to the physician because of ongoing shortness of breath, which is more prominent when he lies down. Occasionally, he experiences palpitations, especially during strenuous activities. In addition to this, he has been experiencing difficulty in digestion and often experiences regurgitation and dysphagia. He reports that he emigrated from Mexico 20 years ago and visits his hometown twice a year. The vital signs include: blood pressure 120/75 mm Hg, respiratory rate 19/min, and pulse 100/min. The physical examination shows jugular vein distention along with pitting edema in the ankles. Bilateral basilar crackles and an S3 gallop are heard on auscultation of the chest. A chest X-ray is taken. An electrocardiogram (ECG) shows no significant findings. What is the most likely explanation for this patient’s physical and diagnostic findings?\nA. Alcohol abuse\nB. Hypertensive changes\nC. Parasitic infection\nD. Bacterial infection\nChoose the correct option.",
"image": null
},
{
"idx": 82,
"question": "A 27-year-old HIV positive female gave birth to a 7lb 2oz (3.2 kg) baby girl. The obstetrician is worried that the child may have been infected due to the mother's haphazard use of her anti-retroviral medications. Which of the following assays would a hospital use detect the genetic material of HIV if the child had been infected?\nA. Enzyme-linked immunosorbent assay (ELISA)\nB. Rapid HIV antibody test\nC. Polymerase chain reaction\nD. Southern blot\n\nA. Enzyme-linked immunosorbent assay (ELISA)\nB. Rapid HIV antibody test\nC. Polymerase chain reaction\nD. Southern blot",
"options": [
"A. Enzyme-linked immunosorbent assay (ELISA)",
"B. Rapid HIV antibody test",
"C. Polymerase chain reaction",
"D. Southern blot"
],
"answer": "Polymerase chain reaction",
"gen_text_store": "",
"pid": "82",
"query": "A 27-year-old HIV positive female gave birth to a 7lb 2oz (3.2 kg) baby girl. The obstetrician is worried that the child may have been infected due to the mother's haphazard use of her anti-retroviral medications. Which of the following assays would a hospital use detect the genetic material of HIV if the child had been infected?\nA. Enzyme-linked immunosorbent assay (ELISA)\nB. Rapid HIV antibody test\nC. Polymerase chain reaction\nD. Southern blot\nChoose the correct option.",
"image": null
},
{
"idx": 83,
"question": "A 32-year-old man jumps off a 3 story building during a suicide attempt. Paramedics arrive quickly, and he is taken to the hospital where several stable lumbar fractures and a shattered right calcaneus are found. He undergoes surgery and his calcaneus is repaired with 11 screws. Which of the following statements best describes the long term post-surgery outcome in this patient?\nA. He will not be able to plantar flex his foot.\nB. He will not be able to point his toe.\nC. He will have pain with inversion and eversion of his foot.\nD. He will have pain while dorsiflexing his foot.\n\nA. He will not be able to plantar flex his foot.\nB. He will not be able to point his toe.\nC. He will have pain with inversion and eversion of his foot.\nD. He will have pain while dorsiflexing his foot.",
"options": [
"A. He will not be able to plantar flex his foot.",
"B. He will not be able to point his toe.",
"C. He will have pain with inversion and eversion of his foot.",
"D. He will have pain while dorsiflexing his foot."
],
"answer": "He will have pain with inversion and eversion of his foot.",
"gen_text_store": "",
"pid": "83",
"query": "A 32-year-old man jumps off a 3 story building during a suicide attempt. Paramedics arrive quickly, and he is taken to the hospital where several stable lumbar fractures and a shattered right calcaneus are found. He undergoes surgery and his calcaneus is repaired with 11 screws. Which of the following statements best describes the long term post-surgery outcome in this patient?\nA. He will not be able to plantar flex his foot.\nB. He will not be able to point his toe.\nC. He will have pain with inversion and eversion of his foot.\nD. He will have pain while dorsiflexing his foot.\nChoose the correct option.",
"image": null
},
{
"idx": 84,
"question": "A stillborn infant is delivered at 38 weeks' gestation to a 32-year-old woman. The mother had no prenatal care. Examination of the stillborn shows a small pelvis, shallow intergluteal cleft, and club feet. An x-ray shows the absence of the sacrum and lumbar vertebrae. Which of the following is the strongest predisposing factor for this patient's condition?\nA. Maternal oligohydramnios\nB. Intrauterine alcohol exposure\nC. Maternal diabetes\nD. Chromosome 18 trisomy\n\nA. Maternal oligohydramnios\nB. Intrauterine alcohol exposure\nC. Maternal diabetes\nD. Chromosome 18 trisomy",
"options": [
"A. Maternal oligohydramnios",
"B. Intrauterine alcohol exposure",
"C. Maternal diabetes",
"D. Chromosome 18 trisomy"
],
"answer": "Maternal diabetes",
"gen_text_store": "",
"pid": "84",
"query": "A stillborn infant is delivered at 38 weeks' gestation to a 32-year-old woman. The mother had no prenatal care. Examination of the stillborn shows a small pelvis, shallow intergluteal cleft, and club feet. An x-ray shows the absence of the sacrum and lumbar vertebrae. Which of the following is the strongest predisposing factor for this patient's condition?\nA. Maternal oligohydramnios\nB. Intrauterine alcohol exposure\nC. Maternal diabetes\nD. Chromosome 18 trisomy\nChoose the correct option.",
"image": null
},
{
"idx": 85,
"question": "A 33-year-old man presents to the infectious diseases clinic for follow-up. He was recently admitted to the hospital with fever, shortness of breath, and cough, and was found to have Pneumocystic jirovecii pneumonia and a new diagnosis of HIV. His CD4 count is 175, viral load is pending. As part of routine laboratory studies given his new diagnosis, an RPR was found to be positive with a titer of 1:64, and this is confirmed with a positive FTA-ABS. He is unsure when or how he acquired HIV or syphilis. His neurological examination is normal, and he has no symptoms. Which of the following is the most appropriate next step in management:\nA. Perform lumbar puncture, treat based on presence or absence of CNS disease\nB. Treat with three weekly injections of penicillin, obtain titers in 3 months\nC. Treat with three weekly injections of penicillin, obtain titers in 6 months\nD. Treat with a single injection of penicillin, obtain titers in 6 months\n\nA. Perform lumbar puncture, treat based on presence or absence of CNS disease\nB. Treat with three weekly injections of penicillin, obtain titers in 3 months\nC. Treat with three weekly injections of penicillin, obtain titers in 6 months\nD. Treat with a single injection of penicillin, obtain titers in 6 months",
"options": [
"A. Perform lumbar puncture, treat based on presence or absence of CNS disease",
"B. Treat with three weekly injections of penicillin, obtain titers in 3 months",
"C. Treat with three weekly injections of penicillin, obtain titers in 6 months",
"D. Treat with a single injection of penicillin, obtain titers in 6 months"
],
"answer": "Treat with three weekly injections of penicillin, obtain titers in 6 months",
"gen_text_store": "",
"pid": "85",
"query": "A 33-year-old man presents to the infectious diseases clinic for follow-up. He was recently admitted to the hospital with fever, shortness of breath, and cough, and was found to have Pneumocystic jirovecii pneumonia and a new diagnosis of HIV. His CD4 count is 175, viral load is pending. As part of routine laboratory studies given his new diagnosis, an RPR was found to be positive with a titer of 1:64, and this is confirmed with a positive FTA-ABS. He is unsure when or how he acquired HIV or syphilis. His neurological examination is normal, and he has no symptoms. Which of the following is the most appropriate next step in management:\nA. Perform lumbar puncture, treat based on presence or absence of CNS disease\nB. Treat with three weekly injections of penicillin, obtain titers in 3 months\nC. Treat with three weekly injections of penicillin, obtain titers in 6 months\nD. Treat with a single injection of penicillin, obtain titers in 6 months\nChoose the correct option.",
"image": null
},
{
"idx": 86,
"question": "A 57-year-old woman comes to the physician because of a 3-month history of fatigue. She also reports generalized itchiness that started approximately 2 months ago. Two weeks ago, she noticed yellowing of her eyes. She does not smoke or drink alcohol. She uses eyedrops for persistent dryness of the eyes. Her vital signs are within normal limits. Physical examination shows jaundice of the conjunctivae and skin. The mucous membranes of the mouth are dry. The abdomen is soft. The liver edge is palpable 3 cm below the right costal margin. There are generalized skin excoriations. Laboratory studies show:\nHemoglobin 15 g/dL\nLeukocyte count 7,700/mm3\nPlatelet count 332,000/mm3\nSerum\nGlucose 122 mg/dL\nTotal bilirubin 3.1 mg/dL\nDirect 2.5 mg/dL\nAlkaline phosphatase 452 U/L\nAST 155 U/L\nALT 168 U/L\nHepatitis B surface antigen negative\nHepatitis B core IgM antibody negative\nHepatitis B surface antibody positive\nHepatitis C antibody negative\nUltrasonography of the abdomen shows mildly increased echogenicity of the liver. Which of the following additional findings is most likely to be found in this patient?\"\nA. Inferior vena cava thrombosis\nB. Cutaneous xanthomas\nC. Increased CA 19-9 levels\nD. Kayser-Fleischer rings\n\"\n\nA. Inferior vena cava thrombosis\nB. Cutaneous xanthomas\nC. Increased CA 19-9 levels\nD. Kayser-Fleischer rings\n\"",
"options": [
"A. Inferior vena cava thrombosis",
"B. Cutaneous xanthomas",
"C. Increased CA 19-9 levels",
"D. Kayser-Fleischer rings\n\""
],
"answer": "Cutaneous xanthomas",
"gen_text_store": "",
"pid": "86",
"query": "A 57-year-old woman comes to the physician because of a 3-month history of fatigue. She also reports generalized itchiness that started approximately 2 months ago. Two weeks ago, she noticed yellowing of her eyes. She does not smoke or drink alcohol. She uses eyedrops for persistent dryness of the eyes. Her vital signs are within normal limits. Physical examination shows jaundice of the conjunctivae and skin. The mucous membranes of the mouth are dry. The abdomen is soft. The liver edge is palpable 3 cm below the right costal margin. There are generalized skin excoriations. Laboratory studies show:\nHemoglobin 15 g/dL\nLeukocyte count 7,700/mm3\nPlatelet count 332,000/mm3\nSerum\nGlucose 122 mg/dL\nTotal bilirubin 3.1 mg/dL\nDirect 2.5 mg/dL\nAlkaline phosphatase 452 U/L\nAST 155 U/L\nALT 168 U/L\nHepatitis B surface antigen negative\nHepatitis B core IgM antibody negative\nHepatitis B surface antibody positive\nHepatitis C antibody negative\nUltrasonography of the abdomen shows mildly increased echogenicity of the liver. Which of the following additional findings is most likely to be found in this patient?\"\nA. Inferior vena cava thrombosis\nB. Cutaneous xanthomas\nC. Increased CA 19-9 levels\nD. Kayser-Fleischer rings\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 87,
"question": "A 40-year-old man comes to the physician because of shortness of breath, double vision, and fatigue for the past 4 weeks. He has no history of serious medical illness and takes no medications. Physical examination shows drooping of the eyelids bilaterally. He is unable to hold his arms up for longer than 3 minutes. A CT scan of the chest shows an anterior mediastinal mass with smooth contours. A photomicrograph of a specimen from the mass is shown. Which of the following immunologic processes normally occurs in the region indicated by the arrow?\nA. B-cell maturation\nB. V(D)J recombination\nC. Thymocyte formation\nD. Negative selection\n\nA. B-cell maturation\nB. V(D)J recombination\nC. Thymocyte formation\nD. Negative selection",
"options": [
"A. B-cell maturation",
"B. V(D)J recombination",
"C. Thymocyte formation",
"D. Negative selection"
],
"answer": "Negative selection",
"gen_text_store": "",
"pid": "87",
"query": "A 40-year-old man comes to the physician because of shortness of breath, double vision, and fatigue for the past 4 weeks. He has no history of serious medical illness and takes no medications. Physical examination shows drooping of the eyelids bilaterally. He is unable to hold his arms up for longer than 3 minutes. A CT scan of the chest shows an anterior mediastinal mass with smooth contours. A photomicrograph of a specimen from the mass is shown. Which of the following immunologic processes normally occurs in the region indicated by the arrow?\nA. B-cell maturation\nB. V(D)J recombination\nC. Thymocyte formation\nD. Negative selection\nChoose the correct option.",
"image": null
},
{
"idx": 88,
"question": "A 69-year-old gentleman presents to his primary care physician for pain in his right shoulder. The patient was helping his son move this past weekend, and he noticed after the move that he had pain and weakness in his right shoulder. The patient thought that this pain was just him being in poor shape so he started going to the gym and lifting weights which made his symptoms significantly worse. The patient has a past medical history of diabetes, obesity, and asthma. His current medications include albuterol, lisinopril, metformin, and glipizide. On physical exam you note an obese gentleman who seems to be in pain. You note prominent weakness of external rotation of his right upper extremity. When you ask the patient to slowly lower his right arm to his side when he holds it overhead, you note that he suddenly drops his arm and appears to be in pain. The patient's strength is 1/5 for abduction of the right arm. Which of the following is most likely injured in this patient?\nA. Supraspinatus\nB. Infraspinatus\nC. Teres minor\nD. Deltoid\n\nA. Supraspinatus\nB. Infraspinatus\nC. Teres minor\nD. Deltoid",
"options": [
"A. Supraspinatus",
"B. Infraspinatus",
"C. Teres minor",
"D. Deltoid"
],
"answer": "Supraspinatus",
"gen_text_store": "",
"pid": "88",
"query": "A 69-year-old gentleman presents to his primary care physician for pain in his right shoulder. The patient was helping his son move this past weekend, and he noticed after the move that he had pain and weakness in his right shoulder. The patient thought that this pain was just him being in poor shape so he started going to the gym and lifting weights which made his symptoms significantly worse. The patient has a past medical history of diabetes, obesity, and asthma. His current medications include albuterol, lisinopril, metformin, and glipizide. On physical exam you note an obese gentleman who seems to be in pain. You note prominent weakness of external rotation of his right upper extremity. When you ask the patient to slowly lower his right arm to his side when he holds it overhead, you note that he suddenly drops his arm and appears to be in pain. The patient's strength is 1/5 for abduction of the right arm. Which of the following is most likely injured in this patient?\nA. Supraspinatus\nB. Infraspinatus\nC. Teres minor\nD. Deltoid\nChoose the correct option.",
"image": null
},
{
"idx": 89,
"question": "A 17-year-old female is brought to the emergency room by her father because she has been experiencing shortness of breath and chest pain. She says that the chest pain is worse when she breathes or coughs. Furthermore, on the way to the hospital she noticed that there were specks of blood on a tissue that she coughed into. She has no previous medical history and does not recall anything that could have provoked these symptoms. On presentation her temperature is 99°F (37.2°C), blood pressure is 107/65 mmHg, pulse is 102/min, respirations are 21/min, and O2 saturation is 91% on room air. Further testing shows a large filling defect in the pulmonary vessels, and the patient is started on an appropriate treatment intravenously. After drug administration, the effects of the drug are monitored using a standard blood test. Surprisingly, the test results come back within normal parameters. The most likely underlying cause of this patient's symptoms has which of the following modes of inheritance?\nA. Autosomal dominant\nB. Autosomal partial dominance\nC. X-linked dominant\nD. X-linked recessive\n\nA. Autosomal dominant\nB. Autosomal partial dominance\nC. X-linked dominant\nD. X-linked recessive",
"options": [
"A. Autosomal dominant",
"B. Autosomal partial dominance",
"C. X-linked dominant",
"D. X-linked recessive"
],
"answer": "Autosomal dominant",
"gen_text_store": "",
"pid": "89",
"query": "A 17-year-old female is brought to the emergency room by her father because she has been experiencing shortness of breath and chest pain. She says that the chest pain is worse when she breathes or coughs. Furthermore, on the way to the hospital she noticed that there were specks of blood on a tissue that she coughed into. She has no previous medical history and does not recall anything that could have provoked these symptoms. On presentation her temperature is 99°F (37.2°C), blood pressure is 107/65 mmHg, pulse is 102/min, respirations are 21/min, and O2 saturation is 91% on room air. Further testing shows a large filling defect in the pulmonary vessels, and the patient is started on an appropriate treatment intravenously. After drug administration, the effects of the drug are monitored using a standard blood test. Surprisingly, the test results come back within normal parameters. The most likely underlying cause of this patient's symptoms has which of the following modes of inheritance?\nA. Autosomal dominant\nB. Autosomal partial dominance\nC. X-linked dominant\nD. X-linked recessive\nChoose the correct option.",
"image": null
},
{
"idx": 90,
"question": "A 61-year-old nulliparous woman comes to the physician for a follow-up examination. Her last Pap smear 3 years ago showed atypical squamous cells of undetermined significance. HPV testing was negative at that time. On questioning, she has had fatigue and an increase in abdominal girth despite a 5-kg (11.0-lb) weight loss over the past 6 months. She has gastroesophageal reflux disease and Hashimoto's thyroiditis. Menarche was at the age of 10 years and her last menstrual period was 2 years ago. Current medications include omeprazole and levothyroxine. Abdominal examination shows shifting dullness. There is tenderness to palpation of the right lower quadrant but no guarding or rebound. Bimanual palpation shows a small uterus and a right adnexal mass. Further evaluation of this patient is most likely to show which of the following findings?\nA. Elevated serum CA-125 level\nB. Elevated serum beta-hCG level\nC. Prolonged prothrombin time\nD. Cervical dysplasia on Pap smear\n\nA. Elevated serum CA-125 level\nB. Elevated serum beta-hCG level\nC. Prolonged prothrombin time\nD. Cervical dysplasia on Pap smear",
"options": [
"A. Elevated serum CA-125 level",
"B. Elevated serum beta-hCG level",
"C. Prolonged prothrombin time",
"D. Cervical dysplasia on Pap smear"
],
"answer": "Elevated serum CA-125 level",
"gen_text_store": "",
"pid": "90",
"query": "A 61-year-old nulliparous woman comes to the physician for a follow-up examination. Her last Pap smear 3 years ago showed atypical squamous cells of undetermined significance. HPV testing was negative at that time. On questioning, she has had fatigue and an increase in abdominal girth despite a 5-kg (11.0-lb) weight loss over the past 6 months. She has gastroesophageal reflux disease and Hashimoto's thyroiditis. Menarche was at the age of 10 years and her last menstrual period was 2 years ago. Current medications include omeprazole and levothyroxine. Abdominal examination shows shifting dullness. There is tenderness to palpation of the right lower quadrant but no guarding or rebound. Bimanual palpation shows a small uterus and a right adnexal mass. Further evaluation of this patient is most likely to show which of the following findings?\nA. Elevated serum CA-125 level\nB. Elevated serum beta-hCG level\nC. Prolonged prothrombin time\nD. Cervical dysplasia on Pap smear\nChoose the correct option.",
"image": null
},
{
"idx": 91,
"question": "A group of researchers wants to evaluate how often the human immunodeficiency virus (HIV) is related to high-risk behaviors in female sex workers from their country. An additional aim is to evaluate the association between HIV acquisition and certain sociodemographic factors. The researchers collect data through interviewer-administered questionnaires (for behavioral and sociodemographic data) as well as through clinical and serological evaluation/screening methods for HIV and other sexually transmitted infections. Which of the following could be the main outcome measure of their study?\nA. Incidence\nB. Prevalence\nC. Hazard rate\nD. Attributable risk\n\nA. Incidence\nB. Prevalence\nC. Hazard rate\nD. Attributable risk",
"options": [
"A. Incidence",
"B. Prevalence",
"C. Hazard rate",
"D. Attributable risk"
],
"answer": "Prevalence",
"gen_text_store": "",
"pid": "91",
"query": "A group of researchers wants to evaluate how often the human immunodeficiency virus (HIV) is related to high-risk behaviors in female sex workers from their country. An additional aim is to evaluate the association between HIV acquisition and certain sociodemographic factors. The researchers collect data through interviewer-administered questionnaires (for behavioral and sociodemographic data) as well as through clinical and serological evaluation/screening methods for HIV and other sexually transmitted infections. Which of the following could be the main outcome measure of their study?\nA. Incidence\nB. Prevalence\nC. Hazard rate\nD. Attributable risk\nChoose the correct option.",
"image": null
},
{
"idx": 92,
"question": "A 25-year-old girl is brought to the emergency room after a suicide attempt. Her mother states that she found a large empty pill bottle next to her. The patient is conscious and tearful. She is currently complaining of severe abdominal pain but refuses to give any other history. She has a blood pressure of 135/86, respiratory rate of 18/min, and heart rate of 86/min. On examination, her abdomen is exquisitely tender with evidence of crepitus in the epigastric region. Abdominal CT reveals a gastric perforation. Which of the following is the most likely cause?\nA. Decreased production of PGE2\nB. Buildup of a toxic metabolite due to kidney disease\nC. Increased stimulation of the vagus nerve\nD. Hypovolemia\n\nA. Decreased production of PGE2\nB. Buildup of a toxic metabolite due to kidney disease\nC. Increased stimulation of the vagus nerve\nD. Hypovolemia",
"options": [
"A. Decreased production of PGE2",
"B. Buildup of a toxic metabolite due to kidney disease",
"C. Increased stimulation of the vagus nerve",
"D. Hypovolemia"
],
"answer": "Decreased production of PGE2",
"gen_text_store": "",
"pid": "92",
"query": "A 25-year-old girl is brought to the emergency room after a suicide attempt. Her mother states that she found a large empty pill bottle next to her. The patient is conscious and tearful. She is currently complaining of severe abdominal pain but refuses to give any other history. She has a blood pressure of 135/86, respiratory rate of 18/min, and heart rate of 86/min. On examination, her abdomen is exquisitely tender with evidence of crepitus in the epigastric region. Abdominal CT reveals a gastric perforation. Which of the following is the most likely cause?\nA. Decreased production of PGE2\nB. Buildup of a toxic metabolite due to kidney disease\nC. Increased stimulation of the vagus nerve\nD. Hypovolemia\nChoose the correct option.",
"image": null
},
{
"idx": 93,
"question": "Two hours following an elective cholecystectomy, a 43-year-old woman has fever and chills. The patient received cephalexin for antibiotic prophylaxis and one unit of packed red blood cells during the procedure. She underwent a hysterectomy 9 years ago for leiomyomata uteri. She has a 5-year history of hypertension treated with lisinopril. Her temperature is 39.5°C (102.3°F), pulse is 90/min, respirations are 18/min, and blood pressure is 125/90 mm Hg. Examination shows a mildly tender abdominal wound without erythema. The lungs are clear to auscultation. Cardiac examination shows no abnormalities. She had a Foley catheter and peripheral line access placed at the time of the procedure. Which of the following is the most likely cause of this patient's symptoms?\nA. Adverse effect of medication\nB. Malignant hyperthermia\nC. Urinary tract infection\nD. Transfusion reaction\n\nA. Adverse effect of medication\nB. Malignant hyperthermia\nC. Urinary tract infection\nD. Transfusion reaction",
"options": [
"A. Adverse effect of medication",
"B. Malignant hyperthermia",
"C. Urinary tract infection",
"D. Transfusion reaction"
],
"answer": "Transfusion reaction",
"gen_text_store": "",
"pid": "93",
"query": "Two hours following an elective cholecystectomy, a 43-year-old woman has fever and chills. The patient received cephalexin for antibiotic prophylaxis and one unit of packed red blood cells during the procedure. She underwent a hysterectomy 9 years ago for leiomyomata uteri. She has a 5-year history of hypertension treated with lisinopril. Her temperature is 39.5°C (102.3°F), pulse is 90/min, respirations are 18/min, and blood pressure is 125/90 mm Hg. Examination shows a mildly tender abdominal wound without erythema. The lungs are clear to auscultation. Cardiac examination shows no abnormalities. She had a Foley catheter and peripheral line access placed at the time of the procedure. Which of the following is the most likely cause of this patient's symptoms?\nA. Adverse effect of medication\nB. Malignant hyperthermia\nC. Urinary tract infection\nD. Transfusion reaction\nChoose the correct option.",
"image": null
},
{
"idx": 94,
"question": "A 6-year-old boy is brought to the emergency department by his mother for worsening wheezing and shortness of breath over the past day. He has not had a fever, cough, vomiting, or diarrhea. He has asthma and eczema. He uses a glucocorticoid inhaler and an albuterol inhaler but has missed his medications for the past week while on vacation. He appears uncomfortable. His temperature is 36°C (96.8°F), pulse is 120/min, respirations are 40/min, and blood pressure is 100/80. Expiratory and inspiratory wheezing is heard throughout both lung fields. There are moderate intercostal and subcostal retractions and a decreased inspiratory to expiratory ratio. Nebulized albuterol and ipratropium treatments and intravenous methylprednisolone are given in the emergency department for a presumed asthma exacerbation. One hour later, the child is limp and lethargic. Magnesium sulfate is administered. His temperature is 36°C (96.8°F), pulse is 150/min, respirations are 22/min, and blood pressure is 100/70. No wheezing is heard on repeat pulmonary examination. Which of the following is the most appropriate next step in management?\nA. Intubate with mechanical ventilation\nB. Perform needle thoracostomy at the 2nd intercostal space\nC. Perform bronchoscopy\nD. Provide additional dose of methylprednisolone\n\nA. Intubate with mechanical ventilation\nB. Perform needle thoracostomy at the 2nd intercostal space\nC. Perform bronchoscopy\nD. Provide additional dose of methylprednisolone",
"options": [
"A. Intubate with mechanical ventilation",
"B. Perform needle thoracostomy at the 2nd intercostal space",
"C. Perform bronchoscopy",
"D. Provide additional dose of methylprednisolone"
],
"answer": "Intubate with mechanical ventilation",
"gen_text_store": "",
"pid": "94",
"query": "A 6-year-old boy is brought to the emergency department by his mother for worsening wheezing and shortness of breath over the past day. He has not had a fever, cough, vomiting, or diarrhea. He has asthma and eczema. He uses a glucocorticoid inhaler and an albuterol inhaler but has missed his medications for the past week while on vacation. He appears uncomfortable. His temperature is 36°C (96.8°F), pulse is 120/min, respirations are 40/min, and blood pressure is 100/80. Expiratory and inspiratory wheezing is heard throughout both lung fields. There are moderate intercostal and subcostal retractions and a decreased inspiratory to expiratory ratio. Nebulized albuterol and ipratropium treatments and intravenous methylprednisolone are given in the emergency department for a presumed asthma exacerbation. One hour later, the child is limp and lethargic. Magnesium sulfate is administered. His temperature is 36°C (96.8°F), pulse is 150/min, respirations are 22/min, and blood pressure is 100/70. No wheezing is heard on repeat pulmonary examination. Which of the following is the most appropriate next step in management?\nA. Intubate with mechanical ventilation\nB. Perform needle thoracostomy at the 2nd intercostal space\nC. Perform bronchoscopy\nD. Provide additional dose of methylprednisolone\nChoose the correct option.",
"image": null
},
{
"idx": 95,
"question": "A 26-year-old female complains of frequent, large volume urination. This negatively affects her sleep, as she has to frequently wake up at night to urinate. She also complains of increased thirst. Her past medical history is significant for bipolar disorder that is treated with lithium for 3 years. Serum osmolality is 425 mOsm/kg, and urine osmolality is 176 mOsm/kg. Which of the following best explains this patient’s serum and urine osmolality?\nA. Hypothalamic over-production of antidiuretic hormone (ADH)\nB. Decreased production of ADH\nC. ADH resistance in the renal collecting ducts\nD. Increased sodium reabsorption and potassium excretion\n\nA. Hypothalamic over-production of antidiuretic hormone (ADH)\nB. Decreased production of ADH\nC. ADH resistance in the renal collecting ducts\nD. Increased sodium reabsorption and potassium excretion",
"options": [
"A. Hypothalamic over-production of antidiuretic hormone (ADH)",
"B. Decreased production of ADH",
"C. ADH resistance in the renal collecting ducts",
"D. Increased sodium reabsorption and potassium excretion"
],
"answer": "ADH resistance in the renal collecting ducts",
"gen_text_store": "",
"pid": "95",
"query": "A 26-year-old female complains of frequent, large volume urination. This negatively affects her sleep, as she has to frequently wake up at night to urinate. She also complains of increased thirst. Her past medical history is significant for bipolar disorder that is treated with lithium for 3 years. Serum osmolality is 425 mOsm/kg, and urine osmolality is 176 mOsm/kg. Which of the following best explains this patient’s serum and urine osmolality?\nA. Hypothalamic over-production of antidiuretic hormone (ADH)\nB. Decreased production of ADH\nC. ADH resistance in the renal collecting ducts\nD. Increased sodium reabsorption and potassium excretion\nChoose the correct option.",
"image": null
},
{
"idx": 96,
"question": "A 55-year-old man presents to the emergency department with a headache. He states that this is the worst headache he has ever had and that his symptoms have not been improving. The patient complains of pain in his jaw that is worse when he chews. He has a past medical history of insomnia and is currently taking alprazolam. His temperature is 98.2°F (36.8°C), blood pressure is 157/98 mmHg, pulse is 90/min, respirations are 15/min, and oxygen saturation is 98% on room air. Physical exam is notable for tenderness over the patient's scalp, jaw, and temporal area. Which of the following is the best next step in management?\nA. CT head\nB. Ibuprofen\nC. IV steroids\nD. Lumbar puncture\n\nA. CT head\nB. Ibuprofen\nC. IV steroids\nD. Lumbar puncture",
"options": [
"A. CT head",
"B. Ibuprofen",
"C. IV steroids",
"D. Lumbar puncture"
],
"answer": "IV steroids",
"gen_text_store": "",
"pid": "96",
"query": "A 55-year-old man presents to the emergency department with a headache. He states that this is the worst headache he has ever had and that his symptoms have not been improving. The patient complains of pain in his jaw that is worse when he chews. He has a past medical history of insomnia and is currently taking alprazolam. His temperature is 98.2°F (36.8°C), blood pressure is 157/98 mmHg, pulse is 90/min, respirations are 15/min, and oxygen saturation is 98% on room air. Physical exam is notable for tenderness over the patient's scalp, jaw, and temporal area. Which of the following is the best next step in management?\nA. CT head\nB. Ibuprofen\nC. IV steroids\nD. Lumbar puncture\nChoose the correct option.",
"image": null
},
{
"idx": 97,
"question": "A 60-year-old woman is brought to the clinic by her daughter for evaluation. The daughter reports that her mother has recently been having difficulty combing her hair in the mornings. The patient’s family history is significant for an ischemic stroke in her father. The patient’s past medical history is positive for diverticulosis. She takes no medication. Her blood pressure is 120/70 mm Hg, heart rate is 75/min, respiratory rate is 14/min, and temperature is 37.6°C (99.7°F). On physical examination, the patient’s neck is stiff and she also has bilateral shoulder tenderness; muscle strength is intact. Laboratory work is performed and presented below:\nHemoglobin 12.9 g/dL\nHematocrit 37.7% \nLeukocyte count 5,500/mm3\nNeutrophils 65%\nLymphocytes 30%\nMonocytes 5%\nMean corpuscular volume 82.2 μm3\nPlatelet count 190,000/mm3\nErythrocyte sedimentation rate 65 mm/h\nC-reactive protein 44 mg/dL\nFor which of the symptoms below should the patient be screened?\nA. Jaw claudication\nB. Heliotrope rash\nC. Gastroesophageal reflux\nD. Pink plaques with silvery scales\n\nA. Jaw claudication\nB. Heliotrope rash\nC. Gastroesophageal reflux\nD. Pink plaques with silvery scales",
"options": [
"A. Jaw claudication",
"B. Heliotrope rash",
"C. Gastroesophageal reflux",
"D. Pink plaques with silvery scales"
],
"answer": "Jaw claudication",
"gen_text_store": "",
"pid": "97",
"query": "A 60-year-old woman is brought to the clinic by her daughter for evaluation. The daughter reports that her mother has recently been having difficulty combing her hair in the mornings. The patient’s family history is significant for an ischemic stroke in her father. The patient’s past medical history is positive for diverticulosis. She takes no medication. Her blood pressure is 120/70 mm Hg, heart rate is 75/min, respiratory rate is 14/min, and temperature is 37.6°C (99.7°F). On physical examination, the patient’s neck is stiff and she also has bilateral shoulder tenderness; muscle strength is intact. Laboratory work is performed and presented below:\nHemoglobin 12.9 g/dL\nHematocrit 37.7% \nLeukocyte count 5,500/mm3\nNeutrophils 65%\nLymphocytes 30%\nMonocytes 5%\nMean corpuscular volume 82.2 μm3\nPlatelet count 190,000/mm3\nErythrocyte sedimentation rate 65 mm/h\nC-reactive protein 44 mg/dL\nFor which of the symptoms below should the patient be screened?\nA. Jaw claudication\nB. Heliotrope rash\nC. Gastroesophageal reflux\nD. Pink plaques with silvery scales\nChoose the correct option.",
"image": null
},
{
"idx": 98,
"question": "A 48-year-old woman comes to the physician because of a 7-day history of progressively worsening shortness of breath. She has a history of asthma and has frequent exacerbations despite receiving maximal medical therapy. Physical examination shows scattered expiratory wheezing. Laboratory studies show a leukocyte count of 9,800/mm3 (13% eosinophils) and elevated serum concentration of immunoglobulin E. An x-ray of the chest shows thickened bronchial walls and perihilar opacities. Sputum culture shows scattered septate hyphae that branch at 45 degrees. Which of the following is most likely to be increased in this patient?\nA. IL-28\nB. TGF-β\nC. IFN-α\nD. IL-4\n\nA. IL-28\nB. TGF-β\nC. IFN-α\nD. IL-4",
"options": [
"A. IL-28",
"B. TGF-β",
"C. IFN-α",
"D. IL-4"
],
"answer": "IL-4",
"gen_text_store": "",
"pid": "98",
"query": "A 48-year-old woman comes to the physician because of a 7-day history of progressively worsening shortness of breath. She has a history of asthma and has frequent exacerbations despite receiving maximal medical therapy. Physical examination shows scattered expiratory wheezing. Laboratory studies show a leukocyte count of 9,800/mm3 (13% eosinophils) and elevated serum concentration of immunoglobulin E. An x-ray of the chest shows thickened bronchial walls and perihilar opacities. Sputum culture shows scattered septate hyphae that branch at 45 degrees. Which of the following is most likely to be increased in this patient?\nA. IL-28\nB. TGF-β\nC. IFN-α\nD. IL-4\nChoose the correct option.",
"image": null
},
{
"idx": 99,
"question": "An 81-year-old man patient recently moved into an assisted living facility and presents today with itchy blisters in his axilla. He attributes these to a poor diet. He also complains that the nurse practitioner at the facility started him on 4 new medications, in addition to his existing prescriptions. On physical examination, tense axillary bullae are noted that do not rupture with light, gloved touch. On direct immunofluorescence, linear C3 and IgG deposits are seen along the basement membrane. Which of the following is the most likely diagnosis?\nA. Staphylococcal scalded skin syndrome\nB. Bullous pemphigoid\nC. Pemphigus vulgaris\nD. Cicatricial pemphigoid\n\nA. Staphylococcal scalded skin syndrome\nB. Bullous pemphigoid\nC. Pemphigus vulgaris\nD. Cicatricial pemphigoid",
"options": [
"A. Staphylococcal scalded skin syndrome",
"B. Bullous pemphigoid",
"C. Pemphigus vulgaris",
"D. Cicatricial pemphigoid"
],
"answer": "Bullous pemphigoid",
"gen_text_store": "",
"pid": "99",
"query": "An 81-year-old man patient recently moved into an assisted living facility and presents today with itchy blisters in his axilla. He attributes these to a poor diet. He also complains that the nurse practitioner at the facility started him on 4 new medications, in addition to his existing prescriptions. On physical examination, tense axillary bullae are noted that do not rupture with light, gloved touch. On direct immunofluorescence, linear C3 and IgG deposits are seen along the basement membrane. Which of the following is the most likely diagnosis?\nA. Staphylococcal scalded skin syndrome\nB. Bullous pemphigoid\nC. Pemphigus vulgaris\nD. Cicatricial pemphigoid\nChoose the correct option.",
"image": null
},
{
"idx": 0,
"question": "A 29-year-old man is referred by his marriage counselor to the outpatient psychiatry clinic. The patient’s wife is with him and states that her husband is always complaining and critical of others. He was recently fired from his job to which he claims that his boss was jealous of his hard work. He also does not trust his neighbors and thinks they are out to get all the nice things he has. His wife also says that he has begun to doubt her fidelity and believes that even the marriage counselor is on her side. Which of the following psychiatric disorders also belongs to the same cluster of symptoms?\nA. Schizotypal personality disorder\nB. Obsessive-compulsive personality disorder\nC. Antisocial personality disorder\nD. Personality disorder not otherwise specified\n\nA. Schizotypal personality disorder\nB. Obsessive-compulsive personality disorder\nC. Antisocial personality disorder\nD. Personality disorder not otherwise specified",
"options": [
"A. Schizotypal personality disorder",
"B. Obsessive-compulsive personality disorder",
"C. Antisocial personality disorder",
"D. Personality disorder not otherwise specified"
],
"answer": "Schizotypal personality disorder",
"gen_text_store": "",
"pid": "0",
"query": "A 29-year-old man is referred by his marriage counselor to the outpatient psychiatry clinic. The patient’s wife is with him and states that her husband is always complaining and critical of others. He was recently fired from his job to which he claims that his boss was jealous of his hard work. He also does not trust his neighbors and thinks they are out to get all the nice things he has. His wife also says that he has begun to doubt her fidelity and believes that even the marriage counselor is on her side. Which of the following psychiatric disorders also belongs to the same cluster of symptoms?\nA. Schizotypal personality disorder\nB. Obsessive-compulsive personality disorder\nC. Antisocial personality disorder\nD. Personality disorder not otherwise specified\nChoose the correct option.",
"image": null
},
{
"idx": 1,
"question": "A 72-year-old woman is brought to the physician by her daughter because of a 6-month history of worsening short-term memory deficits and social withdrawal. Treatment with galantamine is initiated. Two weeks later, the patient develops vomiting, mild crampy abdominal pain, and watery, nonbloody diarrhea. Which of the following is the most appropriate pharmacotherapy?\nA. Bethanechol\nB. Metoclopramide\nC. Atropine\nD. Oxybutynin\n\nA. Bethanechol\nB. Metoclopramide\nC. Atropine\nD. Oxybutynin",
"options": [
"A. Bethanechol",
"B. Metoclopramide",
"C. Atropine",
"D. Oxybutynin"
],
"answer": "Atropine",
"gen_text_store": "",
"pid": "1",
"query": "A 72-year-old woman is brought to the physician by her daughter because of a 6-month history of worsening short-term memory deficits and social withdrawal. Treatment with galantamine is initiated. Two weeks later, the patient develops vomiting, mild crampy abdominal pain, and watery, nonbloody diarrhea. Which of the following is the most appropriate pharmacotherapy?\nA. Bethanechol\nB. Metoclopramide\nC. Atropine\nD. Oxybutynin\nChoose the correct option.",
"image": null
},
{
"idx": 2,
"question": "A 40-year-old woman with Down syndrome comes to the physician for the evaluation of fatigue, progressive clumsiness when using her hands, and difficulty walking for 3 months. During this period, the patient has had several episodes of dizziness as well as double vision. She also reports that she has lost control of her bladder on several occasions lately. She has not had any trauma or weight changes. She lives with her sister and works as a cashier in a local retail store. She takes no medications. Her vital signs are within normal limits. On mental status examination, she is oriented to person and place only. There is moderate weakness of the upper and lower extremities. Sensory examination shows no abnormalities. Deep tendon reflexes are 3+ bilaterally. Babinski's sign is present bilaterally. Which of the following would most likely improve this patient's symptoms?\nA. Administration of botulism antitoxin\nB. Surgical fusion of C1/C2\nC. Administration of methylprednisolone\nD. Administration of pyridostigmine\n\"\n\nA. Administration of botulism antitoxin\nB. Surgical fusion of C1/C2\nC. Administration of methylprednisolone\nD. Administration of pyridostigmine\n\"",
"options": [
"A. Administration of botulism antitoxin",
"B. Surgical fusion of C1/C2",
"C. Administration of methylprednisolone",
"D. Administration of pyridostigmine\n\""
],
"answer": "Surgical fusion of C1/C2",
"gen_text_store": "",
"pid": "2",
"query": "A 40-year-old woman with Down syndrome comes to the physician for the evaluation of fatigue, progressive clumsiness when using her hands, and difficulty walking for 3 months. During this period, the patient has had several episodes of dizziness as well as double vision. She also reports that she has lost control of her bladder on several occasions lately. She has not had any trauma or weight changes. She lives with her sister and works as a cashier in a local retail store. She takes no medications. Her vital signs are within normal limits. On mental status examination, she is oriented to person and place only. There is moderate weakness of the upper and lower extremities. Sensory examination shows no abnormalities. Deep tendon reflexes are 3+ bilaterally. Babinski's sign is present bilaterally. Which of the following would most likely improve this patient's symptoms?\nA. Administration of botulism antitoxin\nB. Surgical fusion of C1/C2\nC. Administration of methylprednisolone\nD. Administration of pyridostigmine\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 3,
"question": "A 60-year-old woman presents to a physician for worsening shortness of breath and increasing abdominal distention over the last 3 months. She says that the shortness of breath is worse on exertion and improves with rest. While she could previously walk to the nearby store for her groceries, she now has to drive because she gets ''winded'' on the way. The patient was diagnosed with diabetes 5 years ago and is compliant with her medications. The medical history is otherwise unremarkable. The physical examination reveals gross ascites and visibly engorged periumbilical veins. Bilateral pitting edema is noted around the ankles. The finger-prick blood glucose level is 100 mg/dL. What is the mechanism of action of the anti-diabetic medication this patient is most likely taking?\nA. Binding to the alpha subunit of the insulin receptor\nB. Closure of ATP-sensitive K-channels in the pancreatic beta-cell\nC. Increased gene expression of GLUT-4\nD. Glucagon-like peptide-1 receptor agonist\n\nA. Binding to the alpha subunit of the insulin receptor\nB. Closure of ATP-sensitive K-channels in the pancreatic beta-cell\nC. Increased gene expression of GLUT-4\nD. Glucagon-like peptide-1 receptor agonist",
"options": [
"A. Binding to the alpha subunit of the insulin receptor",
"B. Closure of ATP-sensitive K-channels in the pancreatic beta-cell",
"C. Increased gene expression of GLUT-4",
"D. Glucagon-like peptide-1 receptor agonist"
],
"answer": "Increased gene expression of GLUT-4",
"gen_text_store": "",
"pid": "3",
"query": "A 60-year-old woman presents to a physician for worsening shortness of breath and increasing abdominal distention over the last 3 months. She says that the shortness of breath is worse on exertion and improves with rest. While she could previously walk to the nearby store for her groceries, she now has to drive because she gets ''winded'' on the way. The patient was diagnosed with diabetes 5 years ago and is compliant with her medications. The medical history is otherwise unremarkable. The physical examination reveals gross ascites and visibly engorged periumbilical veins. Bilateral pitting edema is noted around the ankles. The finger-prick blood glucose level is 100 mg/dL. What is the mechanism of action of the anti-diabetic medication this patient is most likely taking?\nA. Binding to the alpha subunit of the insulin receptor\nB. Closure of ATP-sensitive K-channels in the pancreatic beta-cell\nC. Increased gene expression of GLUT-4\nD. Glucagon-like peptide-1 receptor agonist\nChoose the correct option.",
"image": null
},
{
"idx": 4,
"question": "A 47-year-old man presents to the emergency department with fever, fatigue, and loss of appetite for 1 week, followed by right shoulder pain, generalized abdominal pain, and paroxysmal cough. He has had diabetes mellitus for 15 years, for which he takes metformin and gliclazide. His vital signs include a temperature of 38.3°C (101.0°F), pulse of 85/min, and blood pressure of 110/70 mm Hg. On examination, he is ill-appearing, and he has a tender liver edge that is palpable approx. 2 cm below the right costal margin. Percussion and movement worsens the pain. Abdominal ultrasonography is shown. Stool is negative for Entamoeba histolytica antigen. Which of the following is the best initial step in management of this patient condition?\nA. Metronidazole and paromomycin\nB. Cholecystectomy\nC. Antibiotics and drainage\nD. Endoscopic retrograde cholangiopancreatography (ERCP)\n\nA. Metronidazole and paromomycin\nB. Cholecystectomy\nC. Antibiotics and drainage\nD. Endoscopic retrograde cholangiopancreatography (ERCP)",
"options": [
"A. Metronidazole and paromomycin",
"B. Cholecystectomy",
"C. Antibiotics and drainage",
"D. Endoscopic retrograde cholangiopancreatography (ERCP)"
],
"answer": "Antibiotics and drainage",
"gen_text_store": "",
"pid": "4",
"query": "A 47-year-old man presents to the emergency department with fever, fatigue, and loss of appetite for 1 week, followed by right shoulder pain, generalized abdominal pain, and paroxysmal cough. He has had diabetes mellitus for 15 years, for which he takes metformin and gliclazide. His vital signs include a temperature of 38.3°C (101.0°F), pulse of 85/min, and blood pressure of 110/70 mm Hg. On examination, he is ill-appearing, and he has a tender liver edge that is palpable approx. 2 cm below the right costal margin. Percussion and movement worsens the pain. Abdominal ultrasonography is shown. Stool is negative for Entamoeba histolytica antigen. Which of the following is the best initial step in management of this patient condition?\nA. Metronidazole and paromomycin\nB. Cholecystectomy\nC. Antibiotics and drainage\nD. Endoscopic retrograde cholangiopancreatography (ERCP)\nChoose the correct option.",
"image": null
},
{
"idx": 5,
"question": "A 34-year-old man with acute lymphocytic leukemia presents for follow-up in the oncology clinic after his second cycle of chemotherapy. In addition to intermittent nausea, he has mild weakness, tingling, and numbness in his left hand. With his affected hand, he is able to grip, but occasionally drops small objects. His oncologist tells him that one of his chemotherapy agents likely caused his neuropathy given its strong association with neurotoxicity. He was recently treated with cyclophosphamide, vincristine, doxorubicin, dexamethasone, and dasatinib. The culprit medication works by which of the following mechanisms of action?\nA. Covalently X-links DNA\nB. Blocks microtubule formation\nC. Intercalates between DNA\nD. Modifies DNA transcription and protein synthesis\n\nA. Covalently X-links DNA\nB. Blocks microtubule formation\nC. Intercalates between DNA\nD. Modifies DNA transcription and protein synthesis",
"options": [
"A. Covalently X-links DNA",
"B. Blocks microtubule formation",
"C. Intercalates between DNA",
"D. Modifies DNA transcription and protein synthesis"
],
"answer": "Blocks microtubule formation",
"gen_text_store": "",
"pid": "5",
"query": "A 34-year-old man with acute lymphocytic leukemia presents for follow-up in the oncology clinic after his second cycle of chemotherapy. In addition to intermittent nausea, he has mild weakness, tingling, and numbness in his left hand. With his affected hand, he is able to grip, but occasionally drops small objects. His oncologist tells him that one of his chemotherapy agents likely caused his neuropathy given its strong association with neurotoxicity. He was recently treated with cyclophosphamide, vincristine, doxorubicin, dexamethasone, and dasatinib. The culprit medication works by which of the following mechanisms of action?\nA. Covalently X-links DNA\nB. Blocks microtubule formation\nC. Intercalates between DNA\nD. Modifies DNA transcription and protein synthesis\nChoose the correct option.",
"image": null
},
{
"idx": 6,
"question": "A 21-year-old woman presents with sudden onset of high blood pressure. She is concerned about her health especially after her colleagues noticed that her face gets red at times while at work. She has even started to use blankets to cover her feet, even on the warmest days in the summer, even though her hands feel warm to the touch. She is a student who exercises and eats a well-balanced diet every day. There is no family history of hypertension or other metabolic syndromes. On examination, her blood pressure is 145/92 mm Hg, respirations are 19/min, pulse is 64/min, and temperature is 36.7°C (98.0°F). An echocardiogram is ordered for investigation. This patient is likely affected by a condition which is associated with which of the following options?\nA. Fibromuscular dysplasia\nB. Marfan syndrome\nC. Turner syndrome\nD. Takayasu's arteritis\n\nA. Fibromuscular dysplasia\nB. Marfan syndrome\nC. Turner syndrome\nD. Takayasu's arteritis",
"options": [
"A. Fibromuscular dysplasia",
"B. Marfan syndrome",
"C. Turner syndrome",
"D. Takayasu's arteritis"
],
"answer": "Turner syndrome",
"gen_text_store": "",
"pid": "6",
"query": "A 21-year-old woman presents with sudden onset of high blood pressure. She is concerned about her health especially after her colleagues noticed that her face gets red at times while at work. She has even started to use blankets to cover her feet, even on the warmest days in the summer, even though her hands feel warm to the touch. She is a student who exercises and eats a well-balanced diet every day. There is no family history of hypertension or other metabolic syndromes. On examination, her blood pressure is 145/92 mm Hg, respirations are 19/min, pulse is 64/min, and temperature is 36.7°C (98.0°F). An echocardiogram is ordered for investigation. This patient is likely affected by a condition which is associated with which of the following options?\nA. Fibromuscular dysplasia\nB. Marfan syndrome\nC. Turner syndrome\nD. Takayasu's arteritis\nChoose the correct option.",
"image": null
},
{
"idx": 7,
"question": "A 27-year-old man presents to the emergency department due to a change in his skin color. The patient went on a long hike this morning, and his girlfriend noticed that his skin had changed color when they were driving home. The patient has a past medical history of marijuana use, IV drug use, alcohol use, and asthma. His current medications include albuterol, fluticasone, and ibuprofen. His temperature is 97.5°F (36.4°C), blood pressure is 120/75 mmHg, pulse is 60/min, respirations are 10/min, and oxygen saturation is 98% on room air. Laboratory studies are ordered and are seen below.\n\nHemoglobin: 10 g/dL\nHematocrit: 32%\nLeukocyte count: 5,500 cells/mm^3 with normal differential\nPlatelet count: 207,000/mm^3\n\nSerum:\nNa+: 139 mEq/L\nCl-: 99 mEq/L\nK+: 4.3 mEq/L\nHCO3-: 24 mEq/L\nBUN: 17 mg/dL\nGlucose: 89 mg/dL\nCreatinine: 1.0 mg/dL\nCa2+: 10.1 mg/dL\nBilirubin, total: 11.3 mg/dL\nBilirubin, direct: 7.8 mg/dL\n\nPhysical exam is notable for a patient with skin that appears yellow/orange. Cardiac, pulmonary, abdominal, and neurological exams are within normal limits. Which of the following is associated with this patient's underlying pathology?\nA. A pathology responsive to sofosbuvir\nB. Decreased UDP-glucuronyl transferase activity\nC. Hyperpigmentation of the liver\nD. Increased consumption of beta-carotene\n\nA. A pathology responsive to sofosbuvir\nB. Decreased UDP-glucuronyl transferase activity\nC. Hyperpigmentation of the liver\nD. Increased consumption of beta-carotene",
"options": [
"A. A pathology responsive to sofosbuvir",
"B. Decreased UDP-glucuronyl transferase activity",
"C. Hyperpigmentation of the liver",
"D. Increased consumption of beta-carotene"
],
"answer": "Hyperpigmentation of the liver",
"gen_text_store": "",
"pid": "7",
"query": "A 27-year-old man presents to the emergency department due to a change in his skin color. The patient went on a long hike this morning, and his girlfriend noticed that his skin had changed color when they were driving home. The patient has a past medical history of marijuana use, IV drug use, alcohol use, and asthma. His current medications include albuterol, fluticasone, and ibuprofen. His temperature is 97.5°F (36.4°C), blood pressure is 120/75 mmHg, pulse is 60/min, respirations are 10/min, and oxygen saturation is 98% on room air. Laboratory studies are ordered and are seen below.\n\nHemoglobin: 10 g/dL\nHematocrit: 32%\nLeukocyte count: 5,500 cells/mm^3 with normal differential\nPlatelet count: 207,000/mm^3\n\nSerum:\nNa+: 139 mEq/L\nCl-: 99 mEq/L\nK+: 4.3 mEq/L\nHCO3-: 24 mEq/L\nBUN: 17 mg/dL\nGlucose: 89 mg/dL\nCreatinine: 1.0 mg/dL\nCa2+: 10.1 mg/dL\nBilirubin, total: 11.3 mg/dL\nBilirubin, direct: 7.8 mg/dL\n\nPhysical exam is notable for a patient with skin that appears yellow/orange. Cardiac, pulmonary, abdominal, and neurological exams are within normal limits. Which of the following is associated with this patient's underlying pathology?\nA. A pathology responsive to sofosbuvir\nB. Decreased UDP-glucuronyl transferase activity\nC. Hyperpigmentation of the liver\nD. Increased consumption of beta-carotene\nChoose the correct option.",
"image": null
},
{
"idx": 8,
"question": "A 64-year-old man with multiple sclerosis comes to the physician because of a 4-month history of urinary incontinence. The urge to urinate occurs suddenly, and he often is unable to make it to the bathroom before leaking urine. He has no incontinence with coughing or laughing. Digital rectal examination shows no abnormalities. Ultrasonography shows a normal post-void residual volume. Which of the following is the most appropriate pharmacotherapy for this patient's incontinence?\nA. Midodrine\nB. Rivastigmine\nC. Mirtazapine\nD. Tolterodine\n\nA. Midodrine\nB. Rivastigmine\nC. Mirtazapine\nD. Tolterodine",
"options": [
"A. Midodrine",
"B. Rivastigmine",
"C. Mirtazapine",
"D. Tolterodine"
],
"answer": "Tolterodine",
"gen_text_store": "",
"pid": "8",
"query": "A 64-year-old man with multiple sclerosis comes to the physician because of a 4-month history of urinary incontinence. The urge to urinate occurs suddenly, and he often is unable to make it to the bathroom before leaking urine. He has no incontinence with coughing or laughing. Digital rectal examination shows no abnormalities. Ultrasonography shows a normal post-void residual volume. Which of the following is the most appropriate pharmacotherapy for this patient's incontinence?\nA. Midodrine\nB. Rivastigmine\nC. Mirtazapine\nD. Tolterodine\nChoose the correct option.",
"image": null
},
{
"idx": 9,
"question": "A 45-year-old woman comes to the physician with a lump on her throat that has steadily increased in size over the past 5 months. She does not have difficulties swallowing, dyspnea, or changes in voice. Examination shows a 3-cm, hard swelling on the left side of her neck that moves with swallowing. There is no cervical or axillary lymphadenopathy. The remainder of the examination shows no abnormalities. Thyroid functions tests are within the reference range. Ultrasound of the neck shows an irregular, hypoechogenic mass in the left lobe of the thyroid. A fine-needle aspiration biopsy is inconclusive. The surgeon and patient agree that the most appropriate next step is a diagnostic lobectomy and isthmectomy. Surgery shows a 3.5-cm gray tan thyroid tumor with invasion of surrounding blood vessels, including the veins. The specimen is sent for histopathological examination. Which of the following is most likely to be seen on microscopic examination of the mass?\nA. Undifferentiated giant cells\nB. Capsular invasion\nC. Infiltration of atypical lymphoid tissue\nD. Orphan Annie nuclei\n\"\n\nA. Undifferentiated giant cells\nB. Capsular invasion\nC. Infiltration of atypical lymphoid tissue\nD. Orphan Annie nuclei\n\"",
"options": [
"A. Undifferentiated giant cells",
"B. Capsular invasion",
"C. Infiltration of atypical lymphoid tissue",
"D. Orphan Annie nuclei\n\""
],
"answer": "Capsular invasion",
"gen_text_store": "",
"pid": "9",
"query": "A 45-year-old woman comes to the physician with a lump on her throat that has steadily increased in size over the past 5 months. She does not have difficulties swallowing, dyspnea, or changes in voice. Examination shows a 3-cm, hard swelling on the left side of her neck that moves with swallowing. There is no cervical or axillary lymphadenopathy. The remainder of the examination shows no abnormalities. Thyroid functions tests are within the reference range. Ultrasound of the neck shows an irregular, hypoechogenic mass in the left lobe of the thyroid. A fine-needle aspiration biopsy is inconclusive. The surgeon and patient agree that the most appropriate next step is a diagnostic lobectomy and isthmectomy. Surgery shows a 3.5-cm gray tan thyroid tumor with invasion of surrounding blood vessels, including the veins. The specimen is sent for histopathological examination. Which of the following is most likely to be seen on microscopic examination of the mass?\nA. Undifferentiated giant cells\nB. Capsular invasion\nC. Infiltration of atypical lymphoid tissue\nD. Orphan Annie nuclei\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 10,
"question": "A type of fatal adrenal cancer has an average survival rate of 3 years after the onset of clinically significant symptoms. It is determined that patients have a 4-year asymptomatic period prior to developing clinical symptoms from this adrenal cancer. A new screening test is developed, and the cancer can now be detected 2 years prior to developing clinical symptoms. A new observational case-control study of screened and unscreened patients measures the median 5-year survival of patients who decline medical and surgical treatment. The screened population has statistically better outcomes. Which step should be undertaken to prevent bias in these conclusions?\nA. Using survival rates in the analysis\nB. Using mortality rates in the analysis\nC. Increasing the number of screened individuals\nD. Decreasing the number of screened individuals\n\nA. Using survival rates in the analysis\nB. Using mortality rates in the analysis\nC. Increasing the number of screened individuals\nD. Decreasing the number of screened individuals",
"options": [
"A. Using survival rates in the analysis",
"B. Using mortality rates in the analysis",
"C. Increasing the number of screened individuals",
"D. Decreasing the number of screened individuals"
],
"answer": "Using mortality rates in the analysis",
"gen_text_store": "",
"pid": "10",
"query": "A type of fatal adrenal cancer has an average survival rate of 3 years after the onset of clinically significant symptoms. It is determined that patients have a 4-year asymptomatic period prior to developing clinical symptoms from this adrenal cancer. A new screening test is developed, and the cancer can now be detected 2 years prior to developing clinical symptoms. A new observational case-control study of screened and unscreened patients measures the median 5-year survival of patients who decline medical and surgical treatment. The screened population has statistically better outcomes. Which step should be undertaken to prevent bias in these conclusions?\nA. Using survival rates in the analysis\nB. Using mortality rates in the analysis\nC. Increasing the number of screened individuals\nD. Decreasing the number of screened individuals\nChoose the correct option.",
"image": null
},
{
"idx": 11,
"question": "A 21-year-old female presents to the office after a health screening in which she was found to have high blood pressure. At the office, the blood pressure is 168/114 mm Hg. You have seen the patient in the past for amenorrhea and infertility issues, but she denies taking any medication at this time. On examination, the patient is short and normal weight but has a webbed neck. Which of the following is the most likely cause of the elevated blood pressure?\nA. Central fusion of the inferior poles of the kidneys \nB. Genetic predisposition to essential hypertension\nC. Neuroendocrine tumor of the adrenal gland\nD. Oral contraceptive use\n\nA. Central fusion of the inferior poles of the kidneys \nB. Genetic predisposition to essential hypertension\nC. Neuroendocrine tumor of the adrenal gland\nD. Oral contraceptive use",
"options": [
"A. Central fusion of the inferior poles of the kidneys ",
"B. Genetic predisposition to essential hypertension",
"C. Neuroendocrine tumor of the adrenal gland",
"D. Oral contraceptive use"
],
"answer": "Central fusion of the inferior poles of the kidneys ",
"gen_text_store": "",
"pid": "11",
"query": "A 21-year-old female presents to the office after a health screening in which she was found to have high blood pressure. At the office, the blood pressure is 168/114 mm Hg. You have seen the patient in the past for amenorrhea and infertility issues, but she denies taking any medication at this time. On examination, the patient is short and normal weight but has a webbed neck. Which of the following is the most likely cause of the elevated blood pressure?\nA. Central fusion of the inferior poles of the kidneys \nB. Genetic predisposition to essential hypertension\nC. Neuroendocrine tumor of the adrenal gland\nD. Oral contraceptive use\nChoose the correct option.",
"image": null
},
{
"idx": 12,
"question": "A 14-year-old obese boy presents with severe right hip and knee pain. The patient says that he has been limping with mild pain for the past three weeks, but the pain acutely worsened today. He describes the pain as severe, non-radiating, sharp and aching in character, and localized to the right hip and knee joints. The patient denies recent illness, travel, trauma, or similar symptoms in the past. No significant past medical history and no current medications. The patient is not sexually active and denies any alcohol, smoking or drug use. The vital signs include: temperature 37.0°C (98.6°F), blood pressure 110/70 mm Hg, pulse 72/min, respiratory rate 15/min, and oxygen saturation 99% on room air. Body mass index (BMI) is 32 kg/m2. On physical examination, the patient is alert and cooperative. The right leg is externally rotated, and there is a limited range of motion in the right hip. Strength is 4 out of 5 at the right hip joint and 5 out of 5 elsewhere. There is no tenderness to palpation. No joint erythema, edema or effusion present. Sensation is intact. Deep tendon reflexes are 2+ bilaterally. Laboratory tests are unremarkable. Plain radiographs of the right hip joint are significant for displacement of the right femoral head inferoposterior off the femoral neck. Which of the following is the most appropriate course of treatment for this patient?\nA. Reassess in 3 months\nB. Intra-articular corticosteroid injection of the right hip joint\nC. Pavlik harness\nD. Surgical pinning of the right hip\n\nA. Reassess in 3 months\nB. Intra-articular corticosteroid injection of the right hip joint\nC. Pavlik harness\nD. Surgical pinning of the right hip",
"options": [
"A. Reassess in 3 months",
"B. Intra-articular corticosteroid injection of the right hip joint",
"C. Pavlik harness",
"D. Surgical pinning of the right hip"
],
"answer": "Surgical pinning of the right hip",
"gen_text_store": "",
"pid": "12",
"query": "A 14-year-old obese boy presents with severe right hip and knee pain. The patient says that he has been limping with mild pain for the past three weeks, but the pain acutely worsened today. He describes the pain as severe, non-radiating, sharp and aching in character, and localized to the right hip and knee joints. The patient denies recent illness, travel, trauma, or similar symptoms in the past. No significant past medical history and no current medications. The patient is not sexually active and denies any alcohol, smoking or drug use. The vital signs include: temperature 37.0°C (98.6°F), blood pressure 110/70 mm Hg, pulse 72/min, respiratory rate 15/min, and oxygen saturation 99% on room air. Body mass index (BMI) is 32 kg/m2. On physical examination, the patient is alert and cooperative. The right leg is externally rotated, and there is a limited range of motion in the right hip. Strength is 4 out of 5 at the right hip joint and 5 out of 5 elsewhere. There is no tenderness to palpation. No joint erythema, edema or effusion present. Sensation is intact. Deep tendon reflexes are 2+ bilaterally. Laboratory tests are unremarkable. Plain radiographs of the right hip joint are significant for displacement of the right femoral head inferoposterior off the femoral neck. Which of the following is the most appropriate course of treatment for this patient?\nA. Reassess in 3 months\nB. Intra-articular corticosteroid injection of the right hip joint\nC. Pavlik harness\nD. Surgical pinning of the right hip\nChoose the correct option.",
"image": null
},
{
"idx": 13,
"question": "A 31-year-old man with a history of schizophrenia is brought to the emergency department by police after being found agitated and attempting to steal from a grocery store. His past medical history is only notable for a recent office note from his primary care doctor for treatment of seasonal allergies. His temperature is 101°F (38.3°C), blood pressure is 173/97 mmHg, pulse is 105/min, respirations are 16/min, and oxygen saturation is 98% on room air. Physical exam is notable for a man who is very irritable and restless. He is not cooperative with exam or history and becomes combative requiring intramuscular medications and security restraining him. After this event, the rest of his exam is notable for 7 mm pupils which are equal and reactive to light, spontaneous movement of all limbs, normal sensation, and warm and sweaty skin. The patient is answering questions and states he wants to kill himself. Which of the following substances was most likely used by this patient?\nA. Alcohol\nB. Cocaine\nC. Diphenhydramine\nD. Haloperidol\n\nA. Alcohol\nB. Cocaine\nC. Diphenhydramine\nD. Haloperidol",
"options": [
"A. Alcohol",
"B. Cocaine",
"C. Diphenhydramine",
"D. Haloperidol"
],
"answer": "Cocaine",
"gen_text_store": "",
"pid": "13",
"query": "A 31-year-old man with a history of schizophrenia is brought to the emergency department by police after being found agitated and attempting to steal from a grocery store. His past medical history is only notable for a recent office note from his primary care doctor for treatment of seasonal allergies. His temperature is 101°F (38.3°C), blood pressure is 173/97 mmHg, pulse is 105/min, respirations are 16/min, and oxygen saturation is 98% on room air. Physical exam is notable for a man who is very irritable and restless. He is not cooperative with exam or history and becomes combative requiring intramuscular medications and security restraining him. After this event, the rest of his exam is notable for 7 mm pupils which are equal and reactive to light, spontaneous movement of all limbs, normal sensation, and warm and sweaty skin. The patient is answering questions and states he wants to kill himself. Which of the following substances was most likely used by this patient?\nA. Alcohol\nB. Cocaine\nC. Diphenhydramine\nD. Haloperidol\nChoose the correct option.",
"image": null
},
{
"idx": 14,
"question": "A 55-year-old woman presents to the office because she has been feeling weak. For the past 2 years, she has been urinating a considerable volume every time she goes to the bathroom. She has no past medical history. Her heart rate is 86/min, respiratory rate is 15/min, temperature is 37.4°C (99.3°F), and blood pressure is 111/79 mm Hg. Laboratory studies are significant for the following:\nCalcium 13.8 mg/dL\nPTH 230 pg/mL\nHer complete metabolic panel is otherwise within normal limits. Imaging studies show subperiosteal resorption and osteoporosis. Scintigraphy reveals the most common pathologic condition associated with the patient’s diagnosis. Which of the following is the most likely diagnosis in this patient?\nA. Adenoma\nB. Carcinoma\nC. Decreased calcitriol concentration\nD. Phosphate retention\n\nA. Adenoma\nB. Carcinoma\nC. Decreased calcitriol concentration\nD. Phosphate retention",
"options": [
"A. Adenoma",
"B. Carcinoma",
"C. Decreased calcitriol concentration",
"D. Phosphate retention"
],
"answer": "Adenoma",
"gen_text_store": "",
"pid": "14",
"query": "A 55-year-old woman presents to the office because she has been feeling weak. For the past 2 years, she has been urinating a considerable volume every time she goes to the bathroom. She has no past medical history. Her heart rate is 86/min, respiratory rate is 15/min, temperature is 37.4°C (99.3°F), and blood pressure is 111/79 mm Hg. Laboratory studies are significant for the following:\nCalcium 13.8 mg/dL\nPTH 230 pg/mL\nHer complete metabolic panel is otherwise within normal limits. Imaging studies show subperiosteal resorption and osteoporosis. Scintigraphy reveals the most common pathologic condition associated with the patient’s diagnosis. Which of the following is the most likely diagnosis in this patient?\nA. Adenoma\nB. Carcinoma\nC. Decreased calcitriol concentration\nD. Phosphate retention\nChoose the correct option.",
"image": null
},
{
"idx": 15,
"question": "A 61-year-old Caucasian male presents to your office with chest pain. He states that he is worried about his heart, as his father died at age 62 from a heart attack. He reports that his chest pain worsens with large meals and spicy foods and improves with calcium carbonate. He denies dyspnea on exertion and an ECG is normal. What is the most likely cause of this patient's pain?\nA. Partially occluded coronary artery\nB. Umbilical hernia\nC. Gastroesophageal junction incompetence\nD. Intestinal metaplasia at the gastroesophageal junction\n\nA. Partially occluded coronary artery\nB. Umbilical hernia\nC. Gastroesophageal junction incompetence\nD. Intestinal metaplasia at the gastroesophageal junction",
"options": [
"A. Partially occluded coronary artery",
"B. Umbilical hernia",
"C. Gastroesophageal junction incompetence",
"D. Intestinal metaplasia at the gastroesophageal junction"
],
"answer": "Gastroesophageal junction incompetence",
"gen_text_store": "",
"pid": "15",
"query": "A 61-year-old Caucasian male presents to your office with chest pain. He states that he is worried about his heart, as his father died at age 62 from a heart attack. He reports that his chest pain worsens with large meals and spicy foods and improves with calcium carbonate. He denies dyspnea on exertion and an ECG is normal. What is the most likely cause of this patient's pain?\nA. Partially occluded coronary artery\nB. Umbilical hernia\nC. Gastroesophageal junction incompetence\nD. Intestinal metaplasia at the gastroesophageal junction\nChoose the correct option.",
"image": null
},
{
"idx": 16,
"question": "An otherwise healthy 26-year-old man comes to the physician for medication counseling after recently being diagnosed with schizophrenia. Risperidone therapy is initiated. This patient is at increased risk for which of the following adverse effects?\nA. Agranulocytosis\nB. Shortened QT interval\nC. Gynecomastia\nD. Weight loss\n\nA. Agranulocytosis\nB. Shortened QT interval\nC. Gynecomastia\nD. Weight loss",
"options": [
"A. Agranulocytosis",
"B. Shortened QT interval",
"C. Gynecomastia",
"D. Weight loss"
],
"answer": "Gynecomastia",
"gen_text_store": "",
"pid": "16",
"query": "An otherwise healthy 26-year-old man comes to the physician for medication counseling after recently being diagnosed with schizophrenia. Risperidone therapy is initiated. This patient is at increased risk for which of the following adverse effects?\nA. Agranulocytosis\nB. Shortened QT interval\nC. Gynecomastia\nD. Weight loss\nChoose the correct option.",
"image": null
},
{
"idx": 17,
"question": "A 65-year-old man presents to his primary care physician for a change in his behavior over the past few months. Initially, the patient was noted to be behaving inappropriately including using foul language and grabbing people unexpectedly. This has progressed to a worsening of his memory and trouble caring for himself. His temperature is 98.1°F (36.7°C), blood pressure is 162/103 mmHg, pulse is 83/min, respirations are 13/min, and oxygen saturation is 98% on room air. Physical exam is notable for an elderly man who laughs inappropriately at times and who is a poor historian. When he is engaged in conversation, he exhibits word finding difficulty and is rather inattentive. Which of the following is the most likely diagnosis?\nA. Alzheimer dementia\nB. Frontotemporal dementia\nC. Kluver-Bucy syndrome\nD. Vascular dementia\n\nA. Alzheimer dementia\nB. Frontotemporal dementia\nC. Kluver-Bucy syndrome\nD. Vascular dementia",
"options": [
"A. Alzheimer dementia",
"B. Frontotemporal dementia",
"C. Kluver-Bucy syndrome",
"D. Vascular dementia"
],
"answer": "Frontotemporal dementia",
"gen_text_store": "",
"pid": "17",
"query": "A 65-year-old man presents to his primary care physician for a change in his behavior over the past few months. Initially, the patient was noted to be behaving inappropriately including using foul language and grabbing people unexpectedly. This has progressed to a worsening of his memory and trouble caring for himself. His temperature is 98.1°F (36.7°C), blood pressure is 162/103 mmHg, pulse is 83/min, respirations are 13/min, and oxygen saturation is 98% on room air. Physical exam is notable for an elderly man who laughs inappropriately at times and who is a poor historian. When he is engaged in conversation, he exhibits word finding difficulty and is rather inattentive. Which of the following is the most likely diagnosis?\nA. Alzheimer dementia\nB. Frontotemporal dementia\nC. Kluver-Bucy syndrome\nD. Vascular dementia\nChoose the correct option.",
"image": null
},
{
"idx": 18,
"question": "A 5-year-old boy is brought to his pediatrician due to sore throat and fever. He was in his usual state of health until 3 days ago when he began to complain of a sore throat as well as general malaise. The patient's past medical history reveals recurrent upper respiratory infections but no skin or soft tissue infections. The child had cardiac surgery as an infant but has otherwise been healthy. On presentation, his temperature is 100°F (37.8 °C), blood pressure is 115/72 mmHg, pulse is 65/min, and respirations are 22/min. Physical exam shows white plaques on the tongue and mouth. A scraping of this material reveals a characteristic morphology after being treated with KOH. Serum protein electrophoresis shows a normal distribution of bands from this patient. Which of the following findings would most likely be found in this patient?\nA. Delayed separation of the umbilical cord\nB. Hypoparathyroidism\nC. Partial albinism\nD. Thrombocytopenic purpura\n\nA. Delayed separation of the umbilical cord\nB. Hypoparathyroidism\nC. Partial albinism\nD. Thrombocytopenic purpura",
"options": [
"A. Delayed separation of the umbilical cord",
"B. Hypoparathyroidism",
"C. Partial albinism",
"D. Thrombocytopenic purpura"
],
"answer": "Hypoparathyroidism",
"gen_text_store": "",
"pid": "18",
"query": "A 5-year-old boy is brought to his pediatrician due to sore throat and fever. He was in his usual state of health until 3 days ago when he began to complain of a sore throat as well as general malaise. The patient's past medical history reveals recurrent upper respiratory infections but no skin or soft tissue infections. The child had cardiac surgery as an infant but has otherwise been healthy. On presentation, his temperature is 100°F (37.8 °C), blood pressure is 115/72 mmHg, pulse is 65/min, and respirations are 22/min. Physical exam shows white plaques on the tongue and mouth. A scraping of this material reveals a characteristic morphology after being treated with KOH. Serum protein electrophoresis shows a normal distribution of bands from this patient. Which of the following findings would most likely be found in this patient?\nA. Delayed separation of the umbilical cord\nB. Hypoparathyroidism\nC. Partial albinism\nD. Thrombocytopenic purpura\nChoose the correct option.",
"image": null
},
{
"idx": 19,
"question": "A 50-year-old man presents to the office with complaints of fever and chills for 4 weeks. He adds that he is fatigued all the time and has generalized weakness. He has drenching night sweats and has had 2 episodes of non-bilious vomiting over the past few days. He traveled to the Netherlands for 4 days a month ago. His symptoms started a few days after he returned home. Laboratory testing revealed the following:\nHemoglobin 11.2 g/dL\nHematocrit 29%\nLeukocyte count 2,950/mm3\nNeutrophils 59%\nBands 3%\nEosinophils 1%\nBasophils 0%\nLymphocytes 31%\nMonocytes 4%\nPlatelet count 60,000/mm3\nUnconjugated bilirubin 12 mg/dL\nAlanine aminotransferase 200 IU/L\nAspartate aminotransferase 355 IU/L\nThe peripheral blood smear showed basophilic ring- and pear-shaped structures inside many red cells and extracellular basophilic rings on Wright-Giemsa staining. Further evaluation revealed parasitemia and a few schistocytes, poikilocytes, and merozoites in tetrad formation. The findings are most consistent with which diagnosis?\nA. Malaria\nB. Babesiosis\nC. Tuberculosis\nD. Lyme disease\n\nA. Malaria\nB. Babesiosis\nC. Tuberculosis\nD. Lyme disease",
"options": [
"A. Malaria",
"B. Babesiosis",
"C. Tuberculosis",
"D. Lyme disease"
],
"answer": "Babesiosis",
"gen_text_store": "",
"pid": "19",
"query": "A 50-year-old man presents to the office with complaints of fever and chills for 4 weeks. He adds that he is fatigued all the time and has generalized weakness. He has drenching night sweats and has had 2 episodes of non-bilious vomiting over the past few days. He traveled to the Netherlands for 4 days a month ago. His symptoms started a few days after he returned home. Laboratory testing revealed the following:\nHemoglobin 11.2 g/dL\nHematocrit 29%\nLeukocyte count 2,950/mm3\nNeutrophils 59%\nBands 3%\nEosinophils 1%\nBasophils 0%\nLymphocytes 31%\nMonocytes 4%\nPlatelet count 60,000/mm3\nUnconjugated bilirubin 12 mg/dL\nAlanine aminotransferase 200 IU/L\nAspartate aminotransferase 355 IU/L\nThe peripheral blood smear showed basophilic ring- and pear-shaped structures inside many red cells and extracellular basophilic rings on Wright-Giemsa staining. Further evaluation revealed parasitemia and a few schistocytes, poikilocytes, and merozoites in tetrad formation. The findings are most consistent with which diagnosis?\nA. Malaria\nB. Babesiosis\nC. Tuberculosis\nD. Lyme disease\nChoose the correct option.",
"image": null
},
{
"idx": 20,
"question": "A 2-year-old boy is brought to the physician for evaluation of pallor and increasing lethargy for 2 days. One week ago, he experienced abdominal pain, vomiting, and bloody diarrhea that have since subsided. The patient's father states that they returned early from a 6-week roadtrip in Mexico because of these symptoms. His parents have been giving him oral rehydration solution. His immunizations are up-to-date. He appears pale. His temperature is 38.4°C (101.1°F), pulse is 130/min, respirations are 35/min, and blood pressure is 95/50 mm Hg. Examination shows scleral icterus. The abdomen is soft and nontender; there is no rebound or guarding. Bowel sounds are hyperactive. The remainder of the examination shows no abnormalities. Laboratory studies show:\nHemoglobin 8.5 g/dL\nMean corpuscular volume 94 μm3\nLeukocyte count 18,000/mm3\nPlatelet count 45,000/mm3\nProthrombin time 12 sec\nPartial thromboplastin time 34 sec\nSerum\nUrea nitrogen 28 mg/dL\nCreatinine 1.6 mg/dL\nBilirubin\nTotal 2.5 mg/dL\nDirect 0.1 mg/dL\nLactate dehydrogenase 1658 U/L\nA blood smear shows schistocytes. Which of the following is the most likely diagnosis?\"\nA. Henoch-Schönlein Purpura\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Immune thrombocytopenic purpura\n\nA. Henoch-Schönlein Purpura\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Immune thrombocytopenic purpura",
"options": [
"A. Henoch-Schönlein Purpura",
"B. Thrombotic thrombocytopenic purpura",
"C. Hemolytic uremic syndrome",
"D. Immune thrombocytopenic purpura"
],
"answer": "Hemolytic uremic syndrome",
"gen_text_store": "",
"pid": "20",
"query": "A 2-year-old boy is brought to the physician for evaluation of pallor and increasing lethargy for 2 days. One week ago, he experienced abdominal pain, vomiting, and bloody diarrhea that have since subsided. The patient's father states that they returned early from a 6-week roadtrip in Mexico because of these symptoms. His parents have been giving him oral rehydration solution. His immunizations are up-to-date. He appears pale. His temperature is 38.4°C (101.1°F), pulse is 130/min, respirations are 35/min, and blood pressure is 95/50 mm Hg. Examination shows scleral icterus. The abdomen is soft and nontender; there is no rebound or guarding. Bowel sounds are hyperactive. The remainder of the examination shows no abnormalities. Laboratory studies show:\nHemoglobin 8.5 g/dL\nMean corpuscular volume 94 μm3\nLeukocyte count 18,000/mm3\nPlatelet count 45,000/mm3\nProthrombin time 12 sec\nPartial thromboplastin time 34 sec\nSerum\nUrea nitrogen 28 mg/dL\nCreatinine 1.6 mg/dL\nBilirubin\nTotal 2.5 mg/dL\nDirect 0.1 mg/dL\nLactate dehydrogenase 1658 U/L\nA blood smear shows schistocytes. Which of the following is the most likely diagnosis?\"\nA. Henoch-Schönlein Purpura\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Immune thrombocytopenic purpura\nChoose the correct option.",
"image": null
},
{
"idx": 21,
"question": "A 22-year-old woman with a history of asthma visits her physician for worsening shortness of breath. She states that she feels as though her “lungs are falling apart,” noting that her lung function has been steadily deteriorating. She further states that she has visited a number of other physicians who prescribed several different types of inhalers, but she feels that they have not helped her control her asthma exacerbations. She has experienced 4 episodes of pneumonia in the last 3 years and often suffers from “random” bouts of excessive coughing and wheezing. When asked if her coughing episodes produce sputum, she states, “Yes, the stuff is greenish with specks of red in it.” She also states that her coughing and wheezing episodes are associated with fever, malaise, and occasional expectoration of brown mucous plugs. The vital signs include: blood pressure 122/70 mm Hg, pulse 66/min, respiratory rate 26/min, and temperature 37.0°C (98.6°F). On physical exam, the patient appears frail-looking and in moderate respiratory distress. Auscultation reveals inspiratory crackles in the right lung base and coarse breath sounds in the bilateral upper lung lobes. Chest radiograph, as shown below, reveals atelectasis in the right lung base. There are also branched radiodensities that the radiologist notes as being “glove-finger shadows” (noted by the arrow in the image). Serum immunoglobulin E (IgE) levels are elevated. Which of the following is the most appropriate therapy in this patient?\nA. Isoniazid\nB. Fluconazole\nC. Caspofungin\nD. Prednisone\n\nA. Isoniazid\nB. Fluconazole\nC. Caspofungin\nD. Prednisone",
"options": [
"A. Isoniazid",
"B. Fluconazole",
"C. Caspofungin",
"D. Prednisone"
],
"answer": "Prednisone",
"gen_text_store": "",
"pid": "21",
"query": "A 22-year-old woman with a history of asthma visits her physician for worsening shortness of breath. She states that she feels as though her “lungs are falling apart,” noting that her lung function has been steadily deteriorating. She further states that she has visited a number of other physicians who prescribed several different types of inhalers, but she feels that they have not helped her control her asthma exacerbations. She has experienced 4 episodes of pneumonia in the last 3 years and often suffers from “random” bouts of excessive coughing and wheezing. When asked if her coughing episodes produce sputum, she states, “Yes, the stuff is greenish with specks of red in it.” She also states that her coughing and wheezing episodes are associated with fever, malaise, and occasional expectoration of brown mucous plugs. The vital signs include: blood pressure 122/70 mm Hg, pulse 66/min, respiratory rate 26/min, and temperature 37.0°C (98.6°F). On physical exam, the patient appears frail-looking and in moderate respiratory distress. Auscultation reveals inspiratory crackles in the right lung base and coarse breath sounds in the bilateral upper lung lobes. Chest radiograph, as shown below, reveals atelectasis in the right lung base. There are also branched radiodensities that the radiologist notes as being “glove-finger shadows” (noted by the arrow in the image). Serum immunoglobulin E (IgE) levels are elevated. Which of the following is the most appropriate therapy in this patient?\nA. Isoniazid\nB. Fluconazole\nC. Caspofungin\nD. Prednisone\nChoose the correct option.",
"image": null
},
{
"idx": 22,
"question": "A 67-year-old woman presents to her primary care physician for urinary incontinence. She has been waking up every morning with her underwear soaked in urine. She notices that at work if she does not take regular bathroom breaks her underwear will have some urine in it. She urinates 5 to 11 times per day but she claims it is a small volume. Her current medications include lisinopril, metformin, insulin, aspirin, atorvastatin, sodium docusate, and loratadine. Her temperature is 98.2°F (36.8°C), blood pressure is 167/108 mmHg, pulse is 90/min, respirations are 15/min, and oxygen saturation is 99% on room air. Physical exam is notable for decreased pinprick sensation in the lower extremities and a systolic murmur along the right upper sternal border. Which of the following is the best treatment for this patient?\nA. Bethanechol and intermittent straight catheterization\nB. Bethanechol during the day and oxybutynin at night\nC. No recommendations needed\nD. Reduce fluid intake and discontinue diuretics\n\nA. Bethanechol and intermittent straight catheterization\nB. Bethanechol during the day and oxybutynin at night\nC. No recommendations needed\nD. Reduce fluid intake and discontinue diuretics",
"options": [
"A. Bethanechol and intermittent straight catheterization",
"B. Bethanechol during the day and oxybutynin at night",
"C. No recommendations needed",
"D. Reduce fluid intake and discontinue diuretics"
],
"answer": "Bethanechol and intermittent straight catheterization",
"gen_text_store": "",
"pid": "22",
"query": "A 67-year-old woman presents to her primary care physician for urinary incontinence. She has been waking up every morning with her underwear soaked in urine. She notices that at work if she does not take regular bathroom breaks her underwear will have some urine in it. She urinates 5 to 11 times per day but she claims it is a small volume. Her current medications include lisinopril, metformin, insulin, aspirin, atorvastatin, sodium docusate, and loratadine. Her temperature is 98.2°F (36.8°C), blood pressure is 167/108 mmHg, pulse is 90/min, respirations are 15/min, and oxygen saturation is 99% on room air. Physical exam is notable for decreased pinprick sensation in the lower extremities and a systolic murmur along the right upper sternal border. Which of the following is the best treatment for this patient?\nA. Bethanechol and intermittent straight catheterization\nB. Bethanechol during the day and oxybutynin at night\nC. No recommendations needed\nD. Reduce fluid intake and discontinue diuretics\nChoose the correct option.",
"image": null
},
{
"idx": 23,
"question": "A 62-year-old woman presents to the emergency department for vision changes. About 90 minutes ago she was on the couch watching television with her husband when she suddenly noticed that she couldn't see the screen normally. She also felt a little dizzy. She has never had anything like this happen before. Her general physical exam is unremarkable. Her neurologic exam is notable for loss of vision in the right visual field of both eyes with macular sparing, though extraocular movements are intact. A computed tomography (CT) scan of the head shows no acute intracranial process. Angiography of the brain will most likely show a lesion in which of the following vessels?\nA. Internal carotid artery\nB. Anterior cerebral artery\nC. Posterior cerebral artery\nD. Basilar artery\n\nA. Internal carotid artery\nB. Anterior cerebral artery\nC. Posterior cerebral artery\nD. Basilar artery",
"options": [
"A. Internal carotid artery",
"B. Anterior cerebral artery",
"C. Posterior cerebral artery",
"D. Basilar artery"
],
"answer": "Posterior cerebral artery",
"gen_text_store": "",
"pid": "23",
"query": "A 62-year-old woman presents to the emergency department for vision changes. About 90 minutes ago she was on the couch watching television with her husband when she suddenly noticed that she couldn't see the screen normally. She also felt a little dizzy. She has never had anything like this happen before. Her general physical exam is unremarkable. Her neurologic exam is notable for loss of vision in the right visual field of both eyes with macular sparing, though extraocular movements are intact. A computed tomography (CT) scan of the head shows no acute intracranial process. Angiography of the brain will most likely show a lesion in which of the following vessels?\nA. Internal carotid artery\nB. Anterior cerebral artery\nC. Posterior cerebral artery\nD. Basilar artery\nChoose the correct option.",
"image": null
},
{
"idx": 24,
"question": "A 32-year-old woman comes to the physician because of fatigue and joint pain for the past 4 months. Examination shows erythema with scaling on both cheeks that spares the nasolabial folds and two 1-cm ulcers in the oral cavity. Further evaluation of this patient is most likely to show which of the following findings?\nA. Decreased lymphocyte count\nB. Increased platelet count\nC. Increased prothrombin time\nD. Decreased gamma globulin\n\nA. Decreased lymphocyte count\nB. Increased platelet count\nC. Increased prothrombin time\nD. Decreased gamma globulin",
"options": [
"A. Decreased lymphocyte count",
"B. Increased platelet count",
"C. Increased prothrombin time",
"D. Decreased gamma globulin"
],
"answer": "Decreased lymphocyte count",
"gen_text_store": "",
"pid": "24",
"query": "A 32-year-old woman comes to the physician because of fatigue and joint pain for the past 4 months. Examination shows erythema with scaling on both cheeks that spares the nasolabial folds and two 1-cm ulcers in the oral cavity. Further evaluation of this patient is most likely to show which of the following findings?\nA. Decreased lymphocyte count\nB. Increased platelet count\nC. Increased prothrombin time\nD. Decreased gamma globulin\nChoose the correct option.",
"image": null
},
{
"idx": 25,
"question": "A previously healthy 46-year-old woman comes to the physician because of progressive shortness of breath, fatigue, and chest pain during exercise for the last 6 months. She does not smoke. Her maternal uncle had similar symptoms. Cardiac examination shows wide splitting of S2. The second component of S2 is loud and best heard at the 2nd left intercostal space. The lungs are clear to auscultation. Which of the following is the most likely cause of this patient's cardiac findings?\nA. Increased right ventricular preload\nB. Increased left ventricular preload\nC. Increased right ventricular afterload\nD. Increased left-to-right shunting\n\nA. Increased right ventricular preload\nB. Increased left ventricular preload\nC. Increased right ventricular afterload\nD. Increased left-to-right shunting",
"options": [
"A. Increased right ventricular preload",
"B. Increased left ventricular preload",
"C. Increased right ventricular afterload",
"D. Increased left-to-right shunting"
],
"answer": "Increased right ventricular afterload",
"gen_text_store": "",
"pid": "25",
"query": "A previously healthy 46-year-old woman comes to the physician because of progressive shortness of breath, fatigue, and chest pain during exercise for the last 6 months. She does not smoke. Her maternal uncle had similar symptoms. Cardiac examination shows wide splitting of S2. The second component of S2 is loud and best heard at the 2nd left intercostal space. The lungs are clear to auscultation. Which of the following is the most likely cause of this patient's cardiac findings?\nA. Increased right ventricular preload\nB. Increased left ventricular preload\nC. Increased right ventricular afterload\nD. Increased left-to-right shunting\nChoose the correct option.",
"image": null
},
{
"idx": 26,
"question": "Current recommendations state that a single hemoglobin A1c value of greater than 6.5% is diagnostic of diabetes mellitus. If this 6.5% cut-off is to be increased to 7.0%, which of the following would be true?\nA. Increase in false negative test results\nB. Increase in false positive test results\nC. Decrease in true negative test results\nD. Increase in true positive test results\n\nA. Increase in false negative test results\nB. Increase in false positive test results\nC. Decrease in true negative test results\nD. Increase in true positive test results",
"options": [
"A. Increase in false negative test results",
"B. Increase in false positive test results",
"C. Decrease in true negative test results",
"D. Increase in true positive test results"
],
"answer": "Increase in false negative test results",
"gen_text_store": "",
"pid": "26",
"query": "Current recommendations state that a single hemoglobin A1c value of greater than 6.5% is diagnostic of diabetes mellitus. If this 6.5% cut-off is to be increased to 7.0%, which of the following would be true?\nA. Increase in false negative test results\nB. Increase in false positive test results\nC. Decrease in true negative test results\nD. Increase in true positive test results\nChoose the correct option.",
"image": null
},
{
"idx": 27,
"question": "An otherwise healthy 25-year-old woman comes to the physician because of a 2-day history of pain and swelling of her right knee joint and left wrist. She went camping with her new boyfriend 3 weeks ago but does not recall any tick bites. Her temperature is 37.8°C (100.0°F). Examination of the right knee shows swelling, warmth, and tenderness on passive movement. There is a tender pustule on the sole of the left foot. Arthrocentesis of the right knee joint yields 8 mL of cloudy fluid with a leukocyte count of 45,000/mm3 (90% segmented neutrophils with intracellular organisms). Which of the following is the strongest risk factor for this patient's condition?\nA. Autoantibody production\nB. Intravenous drug use\nC. Sexually transmitted infection\nD. HLA-B 27 positivity\n\nA. Autoantibody production\nB. Intravenous drug use\nC. Sexually transmitted infection\nD. HLA-B 27 positivity",
"options": [
"A. Autoantibody production",
"B. Intravenous drug use",
"C. Sexually transmitted infection",
"D. HLA-B 27 positivity"
],
"answer": "Sexually transmitted infection",
"gen_text_store": "",
"pid": "27",
"query": "An otherwise healthy 25-year-old woman comes to the physician because of a 2-day history of pain and swelling of her right knee joint and left wrist. She went camping with her new boyfriend 3 weeks ago but does not recall any tick bites. Her temperature is 37.8°C (100.0°F). Examination of the right knee shows swelling, warmth, and tenderness on passive movement. There is a tender pustule on the sole of the left foot. Arthrocentesis of the right knee joint yields 8 mL of cloudy fluid with a leukocyte count of 45,000/mm3 (90% segmented neutrophils with intracellular organisms). Which of the following is the strongest risk factor for this patient's condition?\nA. Autoantibody production\nB. Intravenous drug use\nC. Sexually transmitted infection\nD. HLA-B 27 positivity\nChoose the correct option.",
"image": null
},
{
"idx": 28,
"question": "A 36-year-old woman comes to the physician for intermittent stabbing face pain. The pain typically occurs in waves of several individual episodes lasting about one second. It is bilateral, but rarely occurs on both sides simultaneously. Touching her face or brushing her teeth can trigger an attack. Four months ago, she had an episode of weakness in her right arm that lasted for about a week. Family history is notable for migrainous headaches in her mother and brother. Vital signs are within normal limits. There is decreased sensation in the V2 and V3 distribution of her face bilaterally. Muscle strength is 3/5 in the left upper extremity and 5/5 in the right upper extremity. There is spasticity of the lower extremities with sustained clonus. Further evaluation is most likely going to reveal which of the following findings?\nA. Multiple periventricular sclerotic plaques\nB. Erythematous papules in the V2/V3 nerve distribution\nC. Photophobia and phonophobia\nD. Rhinorrhea, lacrimination, and ptosis\n\nA. Multiple periventricular sclerotic plaques\nB. Erythematous papules in the V2/V3 nerve distribution\nC. Photophobia and phonophobia\nD. Rhinorrhea, lacrimination, and ptosis",
"options": [
"A. Multiple periventricular sclerotic plaques",
"B. Erythematous papules in the V2/V3 nerve distribution",
"C. Photophobia and phonophobia",
"D. Rhinorrhea, lacrimination, and ptosis"
],
"answer": "Multiple periventricular sclerotic plaques",
"gen_text_store": "",
"pid": "28",
"query": "A 36-year-old woman comes to the physician for intermittent stabbing face pain. The pain typically occurs in waves of several individual episodes lasting about one second. It is bilateral, but rarely occurs on both sides simultaneously. Touching her face or brushing her teeth can trigger an attack. Four months ago, she had an episode of weakness in her right arm that lasted for about a week. Family history is notable for migrainous headaches in her mother and brother. Vital signs are within normal limits. There is decreased sensation in the V2 and V3 distribution of her face bilaterally. Muscle strength is 3/5 in the left upper extremity and 5/5 in the right upper extremity. There is spasticity of the lower extremities with sustained clonus. Further evaluation is most likely going to reveal which of the following findings?\nA. Multiple periventricular sclerotic plaques\nB. Erythematous papules in the V2/V3 nerve distribution\nC. Photophobia and phonophobia\nD. Rhinorrhea, lacrimination, and ptosis\nChoose the correct option.",
"image": null
},
{
"idx": 29,
"question": "A 72-year-old woman is admitted to the hospital for treatment of unstable angina. Cardiac catheterization shows occlusion that has caused a 50% reduction in the diameter of the left circumflex artery. Resistance to blood flow in this vessel has increased by what factor relative to a vessel with no occlusion?\nA. 64\nB. 16\nC. 8\nD. 4\n\nA. 64\nB. 16\nC. 8\nD. 4",
"options": [
"A. 64",
"B. 16",
"C. 8",
"D. 4"
],
"answer": "16",
"gen_text_store": "",
"pid": "29",
"query": "A 72-year-old woman is admitted to the hospital for treatment of unstable angina. Cardiac catheterization shows occlusion that has caused a 50% reduction in the diameter of the left circumflex artery. Resistance to blood flow in this vessel has increased by what factor relative to a vessel with no occlusion?\nA. 64\nB. 16\nC. 8\nD. 4\nChoose the correct option.",
"image": null
},
{
"idx": 30,
"question": "An 18-year-old college student presents to the student health clinic complaining of excessive sleepiness. He first noticed the daytime sleepiness about a year ago but reports that it significantly worsened once he started college. He reports that he goes to bed around 9 p.m. and wakes up for class at 8 a.m.. He naps between classes for a total of 4 hours during the day. Despite this, he wakes up feeling exhausted. He easily falls asleep during class and while studying. This has started to affect both his academics and his social life. On weekends, he can sleep up to 20 hours a day. He reports 2 recent episodes of sudden generalized body weakness along with ptosis and difficulty speaking that occurred after he became angry. Each episode lasted about 10 seconds, but he says he felt back to normal within 15 minutes without any persistent deficits. His Epworth Sleepiness Scale score is 17. Which of the following is the best next step in therapy?\nA. Clomipramine\nB. Dextroamphetamine\nC. Modafinil\nD. Sleep deprivation\n\nA. Clomipramine\nB. Dextroamphetamine\nC. Modafinil\nD. Sleep deprivation",
"options": [
"A. Clomipramine",
"B. Dextroamphetamine",
"C. Modafinil",
"D. Sleep deprivation"
],
"answer": "Modafinil",
"gen_text_store": "",
"pid": "30",
"query": "An 18-year-old college student presents to the student health clinic complaining of excessive sleepiness. He first noticed the daytime sleepiness about a year ago but reports that it significantly worsened once he started college. He reports that he goes to bed around 9 p.m. and wakes up for class at 8 a.m.. He naps between classes for a total of 4 hours during the day. Despite this, he wakes up feeling exhausted. He easily falls asleep during class and while studying. This has started to affect both his academics and his social life. On weekends, he can sleep up to 20 hours a day. He reports 2 recent episodes of sudden generalized body weakness along with ptosis and difficulty speaking that occurred after he became angry. Each episode lasted about 10 seconds, but he says he felt back to normal within 15 minutes without any persistent deficits. His Epworth Sleepiness Scale score is 17. Which of the following is the best next step in therapy?\nA. Clomipramine\nB. Dextroamphetamine\nC. Modafinil\nD. Sleep deprivation\nChoose the correct option.",
"image": null
},
{
"idx": 31,
"question": "A 59-year-old man presents to his primary care provider with fatigue. He has been seen in the emergency room 5 times in the past 2 years for acute alcohol intoxication. His past medical history is notable for diabetes mellitus and gout. He takes metformin, glyburide, and allopurinol. His temperature is 98.6°F (37°C), blood pressure is 130/85 mmHg, pulse is 86/min, and respirations are 16/min. He is in no acute distress. A positive fluid wave is noted. The dorsal surface of the tongue is depapillated, and there are erythematous swollen patches at the oral commissures. A complete blood count and iron studies are reported below:\n\nHemoglobin: 12.1 g/dL\nHematocrit: 36%\nLeukocyte count: 6,000/mm^3 with normal differential\nPlatelet count: 170,000/mm^3\n\nMean corpuscular volume: 70 um^3\nIron: 250 ug/dL\nFerritin: 300 ng/mL\nTotal iron binding capacity: 200 mcg/dL^3\n\nWhich of the following findings is most likely to be seen in this patient?\nA. Erythroblasts with mitochondrial iron deposits\nB. Erythrocytes lacking central pallor\nC. Erythrocytes with a ring of relative pallor\nD. Inclusions of denatured hemoglobin\n\nA. Erythroblasts with mitochondrial iron deposits\nB. Erythrocytes lacking central pallor\nC. Erythrocytes with a ring of relative pallor\nD. Inclusions of denatured hemoglobin",
"options": [
"A. Erythroblasts with mitochondrial iron deposits",
"B. Erythrocytes lacking central pallor",
"C. Erythrocytes with a ring of relative pallor",
"D. Inclusions of denatured hemoglobin"
],
"answer": "Erythroblasts with mitochondrial iron deposits",
"gen_text_store": "",
"pid": "31",
"query": "A 59-year-old man presents to his primary care provider with fatigue. He has been seen in the emergency room 5 times in the past 2 years for acute alcohol intoxication. His past medical history is notable for diabetes mellitus and gout. He takes metformin, glyburide, and allopurinol. His temperature is 98.6°F (37°C), blood pressure is 130/85 mmHg, pulse is 86/min, and respirations are 16/min. He is in no acute distress. A positive fluid wave is noted. The dorsal surface of the tongue is depapillated, and there are erythematous swollen patches at the oral commissures. A complete blood count and iron studies are reported below:\n\nHemoglobin: 12.1 g/dL\nHematocrit: 36%\nLeukocyte count: 6,000/mm^3 with normal differential\nPlatelet count: 170,000/mm^3\n\nMean corpuscular volume: 70 um^3\nIron: 250 ug/dL\nFerritin: 300 ng/mL\nTotal iron binding capacity: 200 mcg/dL^3\n\nWhich of the following findings is most likely to be seen in this patient?\nA. Erythroblasts with mitochondrial iron deposits\nB. Erythrocytes lacking central pallor\nC. Erythrocytes with a ring of relative pallor\nD. Inclusions of denatured hemoglobin\nChoose the correct option.",
"image": null
},
{
"idx": 32,
"question": "A 41-year-old woman presents with shortness of breath that is worse when she lies on her left side. About 10 days ago, she had an episode of unexplained loss of consciousness. Past medical history is negative and family history is irrelevant. Clinical examination shows a diastolic murmur, which is prominent when she lies on her left side. Jugular venous distention is present, and chest examination reveals fine crackles that do not clear with coughing. Chest X-ray shows pulmonary congestion, and 2-dimensional echocardiogram shows a mass in the left atrium attached to the atrial septum. Which of the following is the most likely diagnosis?\nA. Rheumatic fever\nB. Innocent murmur\nC. Non-bacterial thrombotic endocarditis\nD. Atrial myxoma\n\nA. Rheumatic fever\nB. Innocent murmur\nC. Non-bacterial thrombotic endocarditis\nD. Atrial myxoma",
"options": [
"A. Rheumatic fever",
"B. Innocent murmur",
"C. Non-bacterial thrombotic endocarditis",
"D. Atrial myxoma"
],
"answer": "Atrial myxoma",
"gen_text_store": "",
"pid": "32",
"query": "A 41-year-old woman presents with shortness of breath that is worse when she lies on her left side. About 10 days ago, she had an episode of unexplained loss of consciousness. Past medical history is negative and family history is irrelevant. Clinical examination shows a diastolic murmur, which is prominent when she lies on her left side. Jugular venous distention is present, and chest examination reveals fine crackles that do not clear with coughing. Chest X-ray shows pulmonary congestion, and 2-dimensional echocardiogram shows a mass in the left atrium attached to the atrial septum. Which of the following is the most likely diagnosis?\nA. Rheumatic fever\nB. Innocent murmur\nC. Non-bacterial thrombotic endocarditis\nD. Atrial myxoma\nChoose the correct option.",
"image": null
},
{
"idx": 33,
"question": "A 27-year-old woman was referred to a dermatology clinic due to a changing discoloration of her fingers from white to red to blue. Although she has not had any recent changes in her daily routines, she also complains of increasing fatigue, muscle weakness, and weight loss. She has a blood pressure of 126/77 mm Hg, respiratory rate of 14/min, and heart rate of 88/min. Physical examination reveals regular heart and lung sounds. Anti-U1 RNP antibodies and increased creatinine kinase were found in her serum. What is the most likely diagnosis in this patient?\nA. Mixed connective tissue disease\nB. Polymyositis\nC. Systemic sclerosis\nD. Rheumatoid arthritis\n\nA. Mixed connective tissue disease\nB. Polymyositis\nC. Systemic sclerosis\nD. Rheumatoid arthritis",
"options": [
"A. Mixed connective tissue disease",
"B. Polymyositis",
"C. Systemic sclerosis",
"D. Rheumatoid arthritis"
],
"answer": "Mixed connective tissue disease",
"gen_text_store": "",
"pid": "33",
"query": "A 27-year-old woman was referred to a dermatology clinic due to a changing discoloration of her fingers from white to red to blue. Although she has not had any recent changes in her daily routines, she also complains of increasing fatigue, muscle weakness, and weight loss. She has a blood pressure of 126/77 mm Hg, respiratory rate of 14/min, and heart rate of 88/min. Physical examination reveals regular heart and lung sounds. Anti-U1 RNP antibodies and increased creatinine kinase were found in her serum. What is the most likely diagnosis in this patient?\nA. Mixed connective tissue disease\nB. Polymyositis\nC. Systemic sclerosis\nD. Rheumatoid arthritis\nChoose the correct option.",
"image": null
},
{
"idx": 34,
"question": "A 71-year-old man complains of urinary hesitancy and nocturia of increasing frequency over the past several months. Digital rectal exam was positive for a slightly enlarged prostate but did not detect any additional abnormalities of the prostate or rectum. The patient’s serum PSA was measured to be 6 ng/mL. Image A shows a transabdominal ultrasound of the patient. Which of the following medications should be included to optimally treat the patient's condition?\nA. Clonidine\nB. Finasteride\nC. Dihydrotestosterone\nD. Furosemide\n\nA. Clonidine\nB. Finasteride\nC. Dihydrotestosterone\nD. Furosemide",
"options": [
"A. Clonidine",
"B. Finasteride",
"C. Dihydrotestosterone",
"D. Furosemide"
],
"answer": "Finasteride",
"gen_text_store": "",
"pid": "34",
"query": "A 71-year-old man complains of urinary hesitancy and nocturia of increasing frequency over the past several months. Digital rectal exam was positive for a slightly enlarged prostate but did not detect any additional abnormalities of the prostate or rectum. The patient’s serum PSA was measured to be 6 ng/mL. Image A shows a transabdominal ultrasound of the patient. Which of the following medications should be included to optimally treat the patient's condition?\nA. Clonidine\nB. Finasteride\nC. Dihydrotestosterone\nD. Furosemide\nChoose the correct option.",
"image": null
},
{
"idx": 35,
"question": "An 18-year-old woman comes to the physician because of a pruritic rash on her back for the past 2 hours. This morning, she started a course of ceftriaxone for treatment of pyelonephritis. A photograph of the rash is shown. This patient's skin findings are most likely associated with which of the following?\nA. Direct tissue damage by irradiated antibiotic agent\nB. Cytotoxic T-cell destruction of antigen-tagged cells\nC. Hyperpermeability of superficial dermal microvasculature\nD. Mast cell activation in subcutaneous tissues\n\nA. Direct tissue damage by irradiated antibiotic agent\nB. Cytotoxic T-cell destruction of antigen-tagged cells\nC. Hyperpermeability of superficial dermal microvasculature\nD. Mast cell activation in subcutaneous tissues",
"options": [
"A. Direct tissue damage by irradiated antibiotic agent",
"B. Cytotoxic T-cell destruction of antigen-tagged cells",
"C. Hyperpermeability of superficial dermal microvasculature",
"D. Mast cell activation in subcutaneous tissues"
],
"answer": "Hyperpermeability of superficial dermal microvasculature",
"gen_text_store": "",
"pid": "35",
"query": "An 18-year-old woman comes to the physician because of a pruritic rash on her back for the past 2 hours. This morning, she started a course of ceftriaxone for treatment of pyelonephritis. A photograph of the rash is shown. This patient's skin findings are most likely associated with which of the following?\nA. Direct tissue damage by irradiated antibiotic agent\nB. Cytotoxic T-cell destruction of antigen-tagged cells\nC. Hyperpermeability of superficial dermal microvasculature\nD. Mast cell activation in subcutaneous tissues\nChoose the correct option.",
"image": null
},
{
"idx": 36,
"question": "A 60-year-old man with severe persistent asthma since the age of 14 presents with an acute exacerbation of shortness of breath, wheezing, and coughing over the last several days. His asthmatic symptoms are usually well controlled with regular high-dose inhaled triamcinolone, but over the last week or so he has developed a nocturnal cough and mild wheezing despite good compliance with controller medications. A review of several spirometry reports suggest of bronchial asthma with a partial irreversible airway obstruction. Which of the following is most likely to be associated with the recent loss of asthma control in this patient?\nA. Airway epithelial shedding\nB. Airway smooth muscle atrophy\nC. Airway remodeling\nD. Airway hyperresponsiveness\n\nA. Airway epithelial shedding\nB. Airway smooth muscle atrophy\nC. Airway remodeling\nD. Airway hyperresponsiveness",
"options": [
"A. Airway epithelial shedding",
"B. Airway smooth muscle atrophy",
"C. Airway remodeling",
"D. Airway hyperresponsiveness"
],
"answer": "Airway remodeling",
"gen_text_store": "",
"pid": "36",
"query": "A 60-year-old man with severe persistent asthma since the age of 14 presents with an acute exacerbation of shortness of breath, wheezing, and coughing over the last several days. His asthmatic symptoms are usually well controlled with regular high-dose inhaled triamcinolone, but over the last week or so he has developed a nocturnal cough and mild wheezing despite good compliance with controller medications. A review of several spirometry reports suggest of bronchial asthma with a partial irreversible airway obstruction. Which of the following is most likely to be associated with the recent loss of asthma control in this patient?\nA. Airway epithelial shedding\nB. Airway smooth muscle atrophy\nC. Airway remodeling\nD. Airway hyperresponsiveness\nChoose the correct option.",
"image": null
},
{
"idx": 37,
"question": "A 10-year-old Caucasian female with Turner's syndrome underwent an abdominal imaging study and was discovered that the poles of her kidneys were fused inferiorly. Normal ascension of kidney during embryological development would be prevented by which of the following anatomical structures?\nA. Superior mesenteric artery\nB. Inferior mesenteric artery\nC. Celiac artery\nD. Splenic artery\n\nA. Superior mesenteric artery\nB. Inferior mesenteric artery\nC. Celiac artery\nD. Splenic artery",
"options": [
"A. Superior mesenteric artery",
"B. Inferior mesenteric artery",
"C. Celiac artery",
"D. Splenic artery"
],
"answer": "Inferior mesenteric artery",
"gen_text_store": "",
"pid": "37",
"query": "A 10-year-old Caucasian female with Turner's syndrome underwent an abdominal imaging study and was discovered that the poles of her kidneys were fused inferiorly. Normal ascension of kidney during embryological development would be prevented by which of the following anatomical structures?\nA. Superior mesenteric artery\nB. Inferior mesenteric artery\nC. Celiac artery\nD. Splenic artery\nChoose the correct option.",
"image": null
},
{
"idx": 38,
"question": "A 42-year-old man is admitted to the intensive care unit with decreased consciousness and convulsions. His wife reports that 30 min following the onset of her husband’s condition, which started approximately 6 hours ago, he treated his garden bed with pesticides against mice. He developed nausea, vomiting, and abdominal cramps. The patient noted facial muscle twitching and developed a tonic-clonic seizure that lasted 3 minutes, 4 hours following the onset of his condition. His past medical history is insignificant for any seizure disorders, and he does not take any medications. His blood pressure is 95/60 mm Hg, heart rate is 104/min, respiratory rate is 10/min, and the temperature is 37.0°C (98.6°F). On physical examination, the patient’s consciousness is decreased with a Glasgow Coma Scale score of 13. He is pale and sweaty. His lung sounds are normal, cardiac sounds are decreased, and no murmurs are present. Abdominal palpation reveals epigastric tenderness. Neurological examination shows rapid downbeating nystagmus, facial muscle twitching, and symmetrically decreased sensation to all the sensory modalities on both the upper and lower extremities. Further discussion reveals that the patient was using sodium fluoroacetate as a pesticide, which is known to form fluorocitrate in the cells of aerobic organisms. Which of the following substances will accumulate in the patient’s cells?\nA. Fumarate\nB. Citrate\nC. Malate\nD. Succinate\n\nA. Fumarate\nB. Citrate\nC. Malate\nD. Succinate",
"options": [
"A. Fumarate",
"B. Citrate",
"C. Malate",
"D. Succinate"
],
"answer": "Citrate",
"gen_text_store": "",
"pid": "38",
"query": "A 42-year-old man is admitted to the intensive care unit with decreased consciousness and convulsions. His wife reports that 30 min following the onset of her husband’s condition, which started approximately 6 hours ago, he treated his garden bed with pesticides against mice. He developed nausea, vomiting, and abdominal cramps. The patient noted facial muscle twitching and developed a tonic-clonic seizure that lasted 3 minutes, 4 hours following the onset of his condition. His past medical history is insignificant for any seizure disorders, and he does not take any medications. His blood pressure is 95/60 mm Hg, heart rate is 104/min, respiratory rate is 10/min, and the temperature is 37.0°C (98.6°F). On physical examination, the patient’s consciousness is decreased with a Glasgow Coma Scale score of 13. He is pale and sweaty. His lung sounds are normal, cardiac sounds are decreased, and no murmurs are present. Abdominal palpation reveals epigastric tenderness. Neurological examination shows rapid downbeating nystagmus, facial muscle twitching, and symmetrically decreased sensation to all the sensory modalities on both the upper and lower extremities. Further discussion reveals that the patient was using sodium fluoroacetate as a pesticide, which is known to form fluorocitrate in the cells of aerobic organisms. Which of the following substances will accumulate in the patient’s cells?\nA. Fumarate\nB. Citrate\nC. Malate\nD. Succinate\nChoose the correct option.",
"image": null
},
{
"idx": 39,
"question": "A 65-year old man presents with gradually worsening rigidity of his arms and legs and slowness in performing tasks. He says he has also noticed hand tremors, which increase at rest and decrease with focused movements. On examination, the patient does not swing his arms while walking and has a shortened, shuffling gait. An antiviral drug is prescribed which alleviates the patient’s symptoms. Which of the following drugs was most likely prescribed to this patient?\nA. Amantadine\nB. Ribavirin\nC. Levodopa\nD. Zidovudine\n\nA. Amantadine\nB. Ribavirin\nC. Levodopa\nD. Zidovudine",
"options": [
"A. Amantadine",
"B. Ribavirin",
"C. Levodopa",
"D. Zidovudine"
],
"answer": "Amantadine",
"gen_text_store": "",
"pid": "39",
"query": "A 65-year old man presents with gradually worsening rigidity of his arms and legs and slowness in performing tasks. He says he has also noticed hand tremors, which increase at rest and decrease with focused movements. On examination, the patient does not swing his arms while walking and has a shortened, shuffling gait. An antiviral drug is prescribed which alleviates the patient’s symptoms. Which of the following drugs was most likely prescribed to this patient?\nA. Amantadine\nB. Ribavirin\nC. Levodopa\nD. Zidovudine\nChoose the correct option.",
"image": null
},
{
"idx": 40,
"question": "A 35-year-old woman comes to the physician for the evaluation of increasing weakness and numbness of the upper extremities for 5 days. During the past 2 days, she has had urinary incontinence not related to sneezing or laughing. Last summer, she had weakness and numbness of her right lower extremity that was worse when she was outside; she regained her strength 3 weeks later. She has no history of serious illness. She has had 10 male sexual partners in her lifetime and uses condoms inconsistently. Vital signs are within normal limits. Examination shows an impaired tandem gait. There is mild spasticity and muscle strength is decreased in both upper extremities. Deep tendon reflexes are 4+ bilaterally. The abdominal reflex is absent. Muscle strength in the right lower extremity is mildly decreased. Sensation to vibration and fine touch is decreased over the upper extremities. Which of the following is the most appropriate next step in diagnosis?\nA. Muscle biopsy\nB. Rapid plasma reagin test\nC. MRI of the brain and spine\nD. Lumbar puncture\n\nA. Muscle biopsy\nB. Rapid plasma reagin test\nC. MRI of the brain and spine\nD. Lumbar puncture",
"options": [
"A. Muscle biopsy",
"B. Rapid plasma reagin test",
"C. MRI of the brain and spine",
"D. Lumbar puncture"
],
"answer": "MRI of the brain and spine",
"gen_text_store": "",
"pid": "40",
"query": "A 35-year-old woman comes to the physician for the evaluation of increasing weakness and numbness of the upper extremities for 5 days. During the past 2 days, she has had urinary incontinence not related to sneezing or laughing. Last summer, she had weakness and numbness of her right lower extremity that was worse when she was outside; she regained her strength 3 weeks later. She has no history of serious illness. She has had 10 male sexual partners in her lifetime and uses condoms inconsistently. Vital signs are within normal limits. Examination shows an impaired tandem gait. There is mild spasticity and muscle strength is decreased in both upper extremities. Deep tendon reflexes are 4+ bilaterally. The abdominal reflex is absent. Muscle strength in the right lower extremity is mildly decreased. Sensation to vibration and fine touch is decreased over the upper extremities. Which of the following is the most appropriate next step in diagnosis?\nA. Muscle biopsy\nB. Rapid plasma reagin test\nC. MRI of the brain and spine\nD. Lumbar puncture\nChoose the correct option.",
"image": null
},
{
"idx": 41,
"question": "A 22-year-old woman is brought to the emergency department because of a 2-day history of fever, intermittent rigors, and night sweats. She also has a 1-month history of progressive fatigue. Five weeks ago, she was hospitalized and received intravenous antibiotics for treatment of bacterial meningitis while visiting relatives in Guatemala. Her temperature is 39.4°C (102.9°F), pulse is 130/min, and blood pressure is 105/70 mm Hg. Examination shows pallor and scattered petechiae and ecchymoses. Laboratory studies show a hemoglobin concentration of 9.0 g/dL, a leukocyte count of 1,100/mm3 with 30% segmented neutrophils, and a platelet count of 20,000/mm3 . Blood cultures grow coagulase-negative staphylococci. The patient was most likely treated with which of the following antibiotics?\nA. Doxycycline\nB. Trimethoprim/sulfamethoxazole\nC. Linezolid\nD. Chloramphenicol\n\nA. Doxycycline\nB. Trimethoprim/sulfamethoxazole\nC. Linezolid\nD. Chloramphenicol",
"options": [
"A. Doxycycline",
"B. Trimethoprim/sulfamethoxazole",
"C. Linezolid",
"D. Chloramphenicol"
],
"answer": "Chloramphenicol",
"gen_text_store": "",
"pid": "41",
"query": "A 22-year-old woman is brought to the emergency department because of a 2-day history of fever, intermittent rigors, and night sweats. She also has a 1-month history of progressive fatigue. Five weeks ago, she was hospitalized and received intravenous antibiotics for treatment of bacterial meningitis while visiting relatives in Guatemala. Her temperature is 39.4°C (102.9°F), pulse is 130/min, and blood pressure is 105/70 mm Hg. Examination shows pallor and scattered petechiae and ecchymoses. Laboratory studies show a hemoglobin concentration of 9.0 g/dL, a leukocyte count of 1,100/mm3 with 30% segmented neutrophils, and a platelet count of 20,000/mm3 . Blood cultures grow coagulase-negative staphylococci. The patient was most likely treated with which of the following antibiotics?\nA. Doxycycline\nB. Trimethoprim/sulfamethoxazole\nC. Linezolid\nD. Chloramphenicol\nChoose the correct option.",
"image": null
},
{
"idx": 42,
"question": "A 19-year-old man in a 3-month relationship with a woman experiences frequent sexual fantasies about male coworkers. He lives in a conservative community and does not know any openly gay men. Two days ago, he joined a local group considered by many organizations to be a hate group. Together with the other members, he attacked a gay couple on their way home from dinner. Which of the following psychological defense mechanisms is he demonstrating?\nA. Sublimation\nB. Reaction formation\nC. Intellectualization\nD. Projection\n\nA. Sublimation\nB. Reaction formation\nC. Intellectualization\nD. Projection",
"options": [
"A. Sublimation",
"B. Reaction formation",
"C. Intellectualization",
"D. Projection"
],
"answer": "Reaction formation",
"gen_text_store": "",
"pid": "42",
"query": "A 19-year-old man in a 3-month relationship with a woman experiences frequent sexual fantasies about male coworkers. He lives in a conservative community and does not know any openly gay men. Two days ago, he joined a local group considered by many organizations to be a hate group. Together with the other members, he attacked a gay couple on their way home from dinner. Which of the following psychological defense mechanisms is he demonstrating?\nA. Sublimation\nB. Reaction formation\nC. Intellectualization\nD. Projection\nChoose the correct option.",
"image": null
},
{
"idx": 43,
"question": "A pulmonologist is analyzing the vital signs of patients with chronic obstructive pulmonary disease (COPD) who presented to an emergency room with respiratory distress and subsequently required intubation. The respiratory rates of 7 patients with COPD during their initial visit to the emergency room are shown:\nPatient 1 22 breaths per minute\nPatient 2 32 breaths per minute\nPatient 3 23 breaths per minute\nPatient 4 30 breaths per minute\nPatient 5 32 breaths per minute\nPatient 6 32 breaths per minute\nPatient 7 23 breaths per minute\nWhich of the following is the mode of these respiratory rates?\"\nA. 30 breaths per minute\nB. 32 breaths per minute\nC. 10 breaths per minute\nD. 27.7 breaths per minute\n\nA. 30 breaths per minute\nB. 32 breaths per minute\nC. 10 breaths per minute\nD. 27.7 breaths per minute",
"options": [
"A. 30 breaths per minute",
"B. 32 breaths per minute",
"C. 10 breaths per minute",
"D. 27.7 breaths per minute"
],
"answer": "32 breaths per minute",
"gen_text_store": "",
"pid": "43",
"query": "A pulmonologist is analyzing the vital signs of patients with chronic obstructive pulmonary disease (COPD) who presented to an emergency room with respiratory distress and subsequently required intubation. The respiratory rates of 7 patients with COPD during their initial visit to the emergency room are shown:\nPatient 1 22 breaths per minute\nPatient 2 32 breaths per minute\nPatient 3 23 breaths per minute\nPatient 4 30 breaths per minute\nPatient 5 32 breaths per minute\nPatient 6 32 breaths per minute\nPatient 7 23 breaths per minute\nWhich of the following is the mode of these respiratory rates?\"\nA. 30 breaths per minute\nB. 32 breaths per minute\nC. 10 breaths per minute\nD. 27.7 breaths per minute\nChoose the correct option.",
"image": null
},
{
"idx": 44,
"question": "A 55-year-old man recovering from knee replacement surgery complains of breathlessness in the postoperative ward. He has been confined to bed for the past 5 days and is under observation. He felt a sudden difficulty in breathing and called for the ward nurse. He says that he is unable to take deep breaths and has a sharp pain on the right side of his chest with each inspiration. His temperature is 37.5°C (99.8°F), the pulse is 111/min, the respirations are 31/min, and the blood pressure is 85/55 mm Hg. He experiences pain in his right calf on dorsiflexion. There are no other prominent findings on physical examination. His chest X-ray does not show anything significant. The ECG reveals sinus tachycardia. Which of the following is the best course of management at this time?\nA. Subcutaneous fondaparinux\nB. Inferior vena cava filter\nC. Ventilation-perfusion scan\nD. Lower extremity doppler\n\nA. Subcutaneous fondaparinux\nB. Inferior vena cava filter\nC. Ventilation-perfusion scan\nD. Lower extremity doppler",
"options": [
"A. Subcutaneous fondaparinux",
"B. Inferior vena cava filter",
"C. Ventilation-perfusion scan",
"D. Lower extremity doppler"
],
"answer": "Subcutaneous fondaparinux",
"gen_text_store": "",
"pid": "44",
"query": "A 55-year-old man recovering from knee replacement surgery complains of breathlessness in the postoperative ward. He has been confined to bed for the past 5 days and is under observation. He felt a sudden difficulty in breathing and called for the ward nurse. He says that he is unable to take deep breaths and has a sharp pain on the right side of his chest with each inspiration. His temperature is 37.5°C (99.8°F), the pulse is 111/min, the respirations are 31/min, and the blood pressure is 85/55 mm Hg. He experiences pain in his right calf on dorsiflexion. There are no other prominent findings on physical examination. His chest X-ray does not show anything significant. The ECG reveals sinus tachycardia. Which of the following is the best course of management at this time?\nA. Subcutaneous fondaparinux\nB. Inferior vena cava filter\nC. Ventilation-perfusion scan\nD. Lower extremity doppler\nChoose the correct option.",
"image": null
},
{
"idx": 45,
"question": "An 83-year-old man is admitted to the hospital with fever, weakness, and decreased responsiveness. He is diagnosed with urosepsis based on urinalysis and culture and started on ceftriaxone and intravenous fluids. By hospital day 3, he is clinically improving. During the evening, the patient becomes irritable. He is talking to someone despite nobody being present in the room. He is easily agitated and attempts to strike a nurse with a remote control to his TV. Subsequently, the patient keeps getting out of bed and trying to walk away despite being a fall risk. Which of the following is the most appropriate next step in management?\nA. Diphenhydramine\nB. Lorazepam\nC. Olanzapine\nD. Physical restraints\n\nA. Diphenhydramine\nB. Lorazepam\nC. Olanzapine\nD. Physical restraints",
"options": [
"A. Diphenhydramine",
"B. Lorazepam",
"C. Olanzapine",
"D. Physical restraints"
],
"answer": "Olanzapine",
"gen_text_store": "",
"pid": "45",
"query": "An 83-year-old man is admitted to the hospital with fever, weakness, and decreased responsiveness. He is diagnosed with urosepsis based on urinalysis and culture and started on ceftriaxone and intravenous fluids. By hospital day 3, he is clinically improving. During the evening, the patient becomes irritable. He is talking to someone despite nobody being present in the room. He is easily agitated and attempts to strike a nurse with a remote control to his TV. Subsequently, the patient keeps getting out of bed and trying to walk away despite being a fall risk. Which of the following is the most appropriate next step in management?\nA. Diphenhydramine\nB. Lorazepam\nC. Olanzapine\nD. Physical restraints\nChoose the correct option.",
"image": null
},
{
"idx": 46,
"question": "A 52-year-old man is brought to the emergency department because of worsening shortness of breath for 6 hours. For the past 5 days, he has had intermittent stabbing pain in the middle of his chest that worsens with lying down or taking deep breaths. He has also had a runny nose and a dry cough for the past 2 weeks. He has hypercholesterolemia and hypertension. He has smoked a pack of cigarettes daily for 34 years. His current medications include atorvastatin, enalapril, and hydrochlorothiazide. He appears pale and sweaty. His temperature is 38.3°C (100.9°F), pulse is 105/min, and respirations are 25/min. Blood pressure is 107/72 mm Hg during expiration and 86/65 mm Hg during inspiration. Examination shows jugular venous distention and pitting edema below the knees. Which of the following is the most likely cause of this patient's findings?\nA. Dilation of the atria and ventricles\nB. Occlusion of a coronary artery\nC. Accumulation of fluid in the pericardial space\nD. Fibrous thickening of the pericardium\n\nA. Dilation of the atria and ventricles\nB. Occlusion of a coronary artery\nC. Accumulation of fluid in the pericardial space\nD. Fibrous thickening of the pericardium",
"options": [
"A. Dilation of the atria and ventricles",
"B. Occlusion of a coronary artery",
"C. Accumulation of fluid in the pericardial space",
"D. Fibrous thickening of the pericardium"
],
"answer": "Accumulation of fluid in the pericardial space",
"gen_text_store": "",
"pid": "46",
"query": "A 52-year-old man is brought to the emergency department because of worsening shortness of breath for 6 hours. For the past 5 days, he has had intermittent stabbing pain in the middle of his chest that worsens with lying down or taking deep breaths. He has also had a runny nose and a dry cough for the past 2 weeks. He has hypercholesterolemia and hypertension. He has smoked a pack of cigarettes daily for 34 years. His current medications include atorvastatin, enalapril, and hydrochlorothiazide. He appears pale and sweaty. His temperature is 38.3°C (100.9°F), pulse is 105/min, and respirations are 25/min. Blood pressure is 107/72 mm Hg during expiration and 86/65 mm Hg during inspiration. Examination shows jugular venous distention and pitting edema below the knees. Which of the following is the most likely cause of this patient's findings?\nA. Dilation of the atria and ventricles\nB. Occlusion of a coronary artery\nC. Accumulation of fluid in the pericardial space\nD. Fibrous thickening of the pericardium\nChoose the correct option.",
"image": null
},
{
"idx": 47,
"question": "A previously healthy 35-year-old primigravid woman at 12 weeks' gestation comes to the physician because of a fever, persistent headache, nausea, and abdominal discomfort for 1 week. During this time, she has also noticed that her gums bleed while brushing her teeth. A month ago, she returned from a camping trip to Sri Lanka. Her temperature is 39.3°C (102.8°F), pulse is 104/min, respirations are 24/min, and blood pressure is 135/88 mm Hg. Examination shows pallor and mild scleral icterus. There are a few scattered petechiae over the trunk and back. There is no lymphadenopathy. Physical and neurologic examinations show no other abnormalities. Test of the stool for occult blood is positive. Laboratory studies show:\nHemoglobin 8.2 g/dL\nLeukocyte count 10,000/mm3\nPlatelet count 18,000/mm3\nINR 1.0\nCoomb's test negative\nFibrin split products negative\nSerum\nUrea 20 mg/dL\nCreatinine 1.1 mg/dL\nBilirubin\nTotal 3.0 mg/dL\nDirect 0.8 mg/dL\nAlanine aminotransferase 20 U/L\nAspartate aminotransferase 16 U/L\nLactate dehydrogenase 900 U/L\nUrine\nProtein 1+\nWBCs occasional\nRBCs 50–60/hpf\nBacteria nil\nA photograph of the peripheral blood smear is shown. Blood and urine cultures are negative. Which of the following is the most likely diagnosis?\"\nA. HELLP syndrome\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Autoimmune hemolytic anemia\n\"\n\nA. HELLP syndrome\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Autoimmune hemolytic anemia\n\"",
"options": [
"A. HELLP syndrome",
"B. Thrombotic thrombocytopenic purpura",
"C. Hemolytic uremic syndrome",
"D. Autoimmune hemolytic anemia\n\""
],
"answer": "Thrombotic thrombocytopenic purpura",
"gen_text_store": "",
"pid": "47",
"query": "A previously healthy 35-year-old primigravid woman at 12 weeks' gestation comes to the physician because of a fever, persistent headache, nausea, and abdominal discomfort for 1 week. During this time, she has also noticed that her gums bleed while brushing her teeth. A month ago, she returned from a camping trip to Sri Lanka. Her temperature is 39.3°C (102.8°F), pulse is 104/min, respirations are 24/min, and blood pressure is 135/88 mm Hg. Examination shows pallor and mild scleral icterus. There are a few scattered petechiae over the trunk and back. There is no lymphadenopathy. Physical and neurologic examinations show no other abnormalities. Test of the stool for occult blood is positive. Laboratory studies show:\nHemoglobin 8.2 g/dL\nLeukocyte count 10,000/mm3\nPlatelet count 18,000/mm3\nINR 1.0\nCoomb's test negative\nFibrin split products negative\nSerum\nUrea 20 mg/dL\nCreatinine 1.1 mg/dL\nBilirubin\nTotal 3.0 mg/dL\nDirect 0.8 mg/dL\nAlanine aminotransferase 20 U/L\nAspartate aminotransferase 16 U/L\nLactate dehydrogenase 900 U/L\nUrine\nProtein 1+\nWBCs occasional\nRBCs 50–60/hpf\nBacteria nil\nA photograph of the peripheral blood smear is shown. Blood and urine cultures are negative. Which of the following is the most likely diagnosis?\"\nA. HELLP syndrome\nB. Thrombotic thrombocytopenic purpura\nC. Hemolytic uremic syndrome\nD. Autoimmune hemolytic anemia\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 48,
"question": "A 10-year-old boy is brought to his pediatrician after discovering a painless mass in the left testicle. Results from tumor markers and a biopsy are as follows:\nAFP 350 ng/mL (normal value < 10 ng/mL)\nhCG 0.4 IU/L (normal value < 0.5 IU/L)\nBiopsy: Presence of glomeruli-like structures with a central capillary within a mesodermal core, lined by flattened layers of germ cells.\nWhat is the most likely diagnosis in this patient?\nA. Classic seminoma\nB. Choriocarcinoma\nC. Teratoma\nD. Yolk sac tumor\n\nA. Classic seminoma\nB. Choriocarcinoma\nC. Teratoma\nD. Yolk sac tumor",
"options": [
"A. Classic seminoma",
"B. Choriocarcinoma",
"C. Teratoma",
"D. Yolk sac tumor"
],
"answer": "Yolk sac tumor",
"gen_text_store": "",
"pid": "48",
"query": "A 10-year-old boy is brought to his pediatrician after discovering a painless mass in the left testicle. Results from tumor markers and a biopsy are as follows:\nAFP 350 ng/mL (normal value < 10 ng/mL)\nhCG 0.4 IU/L (normal value < 0.5 IU/L)\nBiopsy: Presence of glomeruli-like structures with a central capillary within a mesodermal core, lined by flattened layers of germ cells.\nWhat is the most likely diagnosis in this patient?\nA. Classic seminoma\nB. Choriocarcinoma\nC. Teratoma\nD. Yolk sac tumor\nChoose the correct option.",
"image": null
},
{
"idx": 49,
"question": "A 24-year-old woman comes to the emergency department with her boyfriend 2 hours after an episode of loss of consciousness. She was seated and was being tattooed on her right upper flank when she became diaphoretic, pale, and passed out. According to her boyfriend, the patient slipped to the floor and her arms and legs moved in a jerky fashion for a few seconds. She regained consciousness within half a minute and was alert and fully oriented immediately. She has no history of serious illness. She works as an event manager and has had more stress than usual due to a recent concert tour. She appears well. Her temperature is 37°C (98.4°F), pulse is 68/min, respirations are 16/min, and blood pressure is 120/72 mm Hg. Her cardiopulmonary examination shows no abnormalities. Neurologic examination shows no focal findings. An ECG shows an incomplete right bundle branch block. Which of the following is the most likely diagnosis?\nA. Vasovagal syncope\nB. Orthostatic syncope\nC. Cardiac arrhythmia\nD. Cardiac structural abnormality\n\"\n\nA. Vasovagal syncope\nB. Orthostatic syncope\nC. Cardiac arrhythmia\nD. Cardiac structural abnormality\n\"",
"options": [
"A. Vasovagal syncope",
"B. Orthostatic syncope",
"C. Cardiac arrhythmia",
"D. Cardiac structural abnormality\n\""
],
"answer": "Vasovagal syncope",
"gen_text_store": "",
"pid": "49",
"query": "A 24-year-old woman comes to the emergency department with her boyfriend 2 hours after an episode of loss of consciousness. She was seated and was being tattooed on her right upper flank when she became diaphoretic, pale, and passed out. According to her boyfriend, the patient slipped to the floor and her arms and legs moved in a jerky fashion for a few seconds. She regained consciousness within half a minute and was alert and fully oriented immediately. She has no history of serious illness. She works as an event manager and has had more stress than usual due to a recent concert tour. She appears well. Her temperature is 37°C (98.4°F), pulse is 68/min, respirations are 16/min, and blood pressure is 120/72 mm Hg. Her cardiopulmonary examination shows no abnormalities. Neurologic examination shows no focal findings. An ECG shows an incomplete right bundle branch block. Which of the following is the most likely diagnosis?\nA. Vasovagal syncope\nB. Orthostatic syncope\nC. Cardiac arrhythmia\nD. Cardiac structural abnormality\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 50,
"question": "Six days after undergoing surgical repair of a hip fracture, a previously healthy 79-year-old woman is agitated and confused. She is unarousable during the day, but then is awake and impulsive during the night, requiring frequent reorientation. Her husband says that she usually drinks one to two glasses of wine weekly. Her only current medication is oxycodone for pain. Her vital signs are within normal limits. She is distressed and oriented to person but not to place or time. Neurologic examination shows inattentiveness but no focal deficits. Urine dipstick is normal. Which of the following is the most likely cause of her current condition?\nA. Dementia\nB. Opioid intoxication\nC. Delirium\nD. Urinary tract infection\n\nA. Dementia\nB. Opioid intoxication\nC. Delirium\nD. Urinary tract infection",
"options": [
"A. Dementia",
"B. Opioid intoxication",
"C. Delirium",
"D. Urinary tract infection"
],
"answer": "Delirium",
"gen_text_store": "",
"pid": "50",
"query": "Six days after undergoing surgical repair of a hip fracture, a previously healthy 79-year-old woman is agitated and confused. She is unarousable during the day, but then is awake and impulsive during the night, requiring frequent reorientation. Her husband says that she usually drinks one to two glasses of wine weekly. Her only current medication is oxycodone for pain. Her vital signs are within normal limits. She is distressed and oriented to person but not to place or time. Neurologic examination shows inattentiveness but no focal deficits. Urine dipstick is normal. Which of the following is the most likely cause of her current condition?\nA. Dementia\nB. Opioid intoxication\nC. Delirium\nD. Urinary tract infection\nChoose the correct option.",
"image": null
},
{
"idx": 51,
"question": "A 46-year-old man comes to the physician with a 1-week history of yellowish discoloration of his eyes, generalized fatigue, and pruritus. He was diagnosed with ulcerative colitis 7 years ago. At the time of diagnosis, a pANCA test was also positive. Physical examination shows scleral icterus and multiple scratch marks on the trunk and extremities. Abdominal examination is unremarkable. Serum studies show a total bilirubin concentration of 3.2 mg/dL, direct bilirubin concentration of 2.5 mg/dL, and alkaline phosphatase level of 450 U/L. Magnetic resonance cholangiopancreatography shows focal areas of intrahepatic bile duct strictures alternating with areas of dilation. Histologic examination of a liver biopsy specimen is most likely to show which of the following findings?\nA. Periductal concentric scarring and fibrosis\nB. Periportal lymphocytic infiltration and piecemeal necrosis\nC. Irregular ductal glands lined by atypical and pleomorphic cells\nD. Ductopenia and fibrotic degeneration of periportal hepatocytes\n\nA. Periductal concentric scarring and fibrosis\nB. Periportal lymphocytic infiltration and piecemeal necrosis\nC. Irregular ductal glands lined by atypical and pleomorphic cells\nD. Ductopenia and fibrotic degeneration of periportal hepatocytes",
"options": [
"A. Periductal concentric scarring and fibrosis",
"B. Periportal lymphocytic infiltration and piecemeal necrosis",
"C. Irregular ductal glands lined by atypical and pleomorphic cells",
"D. Ductopenia and fibrotic degeneration of periportal hepatocytes"
],
"answer": "Periductal concentric scarring and fibrosis",
"gen_text_store": "",
"pid": "51",
"query": "A 46-year-old man comes to the physician with a 1-week history of yellowish discoloration of his eyes, generalized fatigue, and pruritus. He was diagnosed with ulcerative colitis 7 years ago. At the time of diagnosis, a pANCA test was also positive. Physical examination shows scleral icterus and multiple scratch marks on the trunk and extremities. Abdominal examination is unremarkable. Serum studies show a total bilirubin concentration of 3.2 mg/dL, direct bilirubin concentration of 2.5 mg/dL, and alkaline phosphatase level of 450 U/L. Magnetic resonance cholangiopancreatography shows focal areas of intrahepatic bile duct strictures alternating with areas of dilation. Histologic examination of a liver biopsy specimen is most likely to show which of the following findings?\nA. Periductal concentric scarring and fibrosis\nB. Periportal lymphocytic infiltration and piecemeal necrosis\nC. Irregular ductal glands lined by atypical and pleomorphic cells\nD. Ductopenia and fibrotic degeneration of periportal hepatocytes\nChoose the correct option.",
"image": null
},
{
"idx": 52,
"question": "A 28-year-old female visits her physician for workup of a new onset diastolic murmur found on physical examination. Past medical history is insignificant. Her temperature is 37.0 degrees C, blood pressure is 115/75 mm Hg, pulse is 76/min, and respiratory rate is 16/min. The patient denies dyspnea, fatigue, and syncope. Transthoracic echocardiography reveals a large, pedunculated tumor in the left atrium. This patient is most at risk for:\nA. Abrupt hypotension\nB. Sudden cardiac death\nC. Acute arterial occlusion\nD. Septic embolism\n\nA. Abrupt hypotension\nB. Sudden cardiac death\nC. Acute arterial occlusion\nD. Septic embolism",
"options": [
"A. Abrupt hypotension",
"B. Sudden cardiac death",
"C. Acute arterial occlusion",
"D. Septic embolism"
],
"answer": "Acute arterial occlusion",
"gen_text_store": "",
"pid": "52",
"query": "A 28-year-old female visits her physician for workup of a new onset diastolic murmur found on physical examination. Past medical history is insignificant. Her temperature is 37.0 degrees C, blood pressure is 115/75 mm Hg, pulse is 76/min, and respiratory rate is 16/min. The patient denies dyspnea, fatigue, and syncope. Transthoracic echocardiography reveals a large, pedunculated tumor in the left atrium. This patient is most at risk for:\nA. Abrupt hypotension\nB. Sudden cardiac death\nC. Acute arterial occlusion\nD. Septic embolism\nChoose the correct option.",
"image": null
},
{
"idx": 53,
"question": "A research group has developed a low-cost diagnostic retinal imaging device for cytomegalovirus retinitis in a population of HIV-infected patients. In a pilot study of 50 patients, the imaging test detected the presence of CMV retinitis in 50% of the patients. An ophthalmologist slit lamp examination, which was performed for each patient to serve as the gold standard for diagnosis, confirmed a diagnosis of CMV retinitis in 20 patients that were found to be positive through imaging, as well as 1 patient who tested negative with the device. If the prevalence of CMV retinitis in the population decreases due to increased access to antiretroviral therapy, how will positive predictive value and negative predictive value of the diagnostic test be affected?\nA. PPV decreases, NPV decreases\nB. PPV decreases, NPV increases\nC. PPV increases, NPV decreases\nD. PPV unchanged, NPV unchanged\n\nA. PPV decreases, NPV decreases\nB. PPV decreases, NPV increases\nC. PPV increases, NPV decreases\nD. PPV unchanged, NPV unchanged",
"options": [
"A. PPV decreases, NPV decreases",
"B. PPV decreases, NPV increases",
"C. PPV increases, NPV decreases",
"D. PPV unchanged, NPV unchanged"
],
"answer": "PPV decreases, NPV increases",
"gen_text_store": "",
"pid": "53",
"query": "A research group has developed a low-cost diagnostic retinal imaging device for cytomegalovirus retinitis in a population of HIV-infected patients. In a pilot study of 50 patients, the imaging test detected the presence of CMV retinitis in 50% of the patients. An ophthalmologist slit lamp examination, which was performed for each patient to serve as the gold standard for diagnosis, confirmed a diagnosis of CMV retinitis in 20 patients that were found to be positive through imaging, as well as 1 patient who tested negative with the device. If the prevalence of CMV retinitis in the population decreases due to increased access to antiretroviral therapy, how will positive predictive value and negative predictive value of the diagnostic test be affected?\nA. PPV decreases, NPV decreases\nB. PPV decreases, NPV increases\nC. PPV increases, NPV decreases\nD. PPV unchanged, NPV unchanged\nChoose the correct option.",
"image": null
},
{
"idx": 54,
"question": "A 26-year-old nullipara presents to her physician for a routine check-up at 18 weeks gestation. She has no co-morbidities. Her only complaints are fatigability and a depressed mood for the past 2 weeks. Her vital signs are as follows: blood pressure, 125/80 mm Hg; heart rate, 87/min; respiratory rate, 14/min; and temperature, 36.7℃ (98℉). The physical examination is unremarkable and the gynecologic examination is consistent with 18 weeks gestation. A thyroid profile s ordered to check for a possible cause of the fatigability and decreased mood:\nThyroid stimulating hormone (TSH) 0.3 mU/L\nTotal T4 160 nmol/L\nFree T4 13 pmol/L\nCorresponding to the obtained results, how should the patient be managed?\nA. Prescribe levothyroxine 50 mcg daily\nB. No specific management required\nC. Recommend additional anti-TPO test\nD. Recommend additional T3 assessment\n\nA. Prescribe levothyroxine 50 mcg daily\nB. No specific management required\nC. Recommend additional anti-TPO test\nD. Recommend additional T3 assessment",
"options": [
"A. Prescribe levothyroxine 50 mcg daily",
"B. No specific management required",
"C. Recommend additional anti-TPO test",
"D. Recommend additional T3 assessment"
],
"answer": "No specific management required",
"gen_text_store": "",
"pid": "54",
"query": "A 26-year-old nullipara presents to her physician for a routine check-up at 18 weeks gestation. She has no co-morbidities. Her only complaints are fatigability and a depressed mood for the past 2 weeks. Her vital signs are as follows: blood pressure, 125/80 mm Hg; heart rate, 87/min; respiratory rate, 14/min; and temperature, 36.7℃ (98℉). The physical examination is unremarkable and the gynecologic examination is consistent with 18 weeks gestation. A thyroid profile s ordered to check for a possible cause of the fatigability and decreased mood:\nThyroid stimulating hormone (TSH) 0.3 mU/L\nTotal T4 160 nmol/L\nFree T4 13 pmol/L\nCorresponding to the obtained results, how should the patient be managed?\nA. Prescribe levothyroxine 50 mcg daily\nB. No specific management required\nC. Recommend additional anti-TPO test\nD. Recommend additional T3 assessment\nChoose the correct option.",
"image": null
},
{
"idx": 55,
"question": "A 52-year-old fisherman presents to the clinic for an evaluation of a pigmented lesion on his neck. He states that he first noticed the lesion last year, but he believes that it has been slowly growing in size. Dermatopathology determines that the lesion contains neoplastic cells of melanocytic origin. Which of the following characteristics of the lesion would likely be found on physical examination?\nA. Brown-black color in one area of the lesion to red-white in a different area\nB. Macule that is 5mm in diameter\nC. Well-circumscribed papule with smooth borders\nD. Itching and pain to palpation\n\nA. Brown-black color in one area of the lesion to red-white in a different area\nB. Macule that is 5mm in diameter\nC. Well-circumscribed papule with smooth borders\nD. Itching and pain to palpation",
"options": [
"A. Brown-black color in one area of the lesion to red-white in a different area",
"B. Macule that is 5mm in diameter",
"C. Well-circumscribed papule with smooth borders",
"D. Itching and pain to palpation"
],
"answer": "Brown-black color in one area of the lesion to red-white in a different area",
"gen_text_store": "",
"pid": "55",
"query": "A 52-year-old fisherman presents to the clinic for an evaluation of a pigmented lesion on his neck. He states that he first noticed the lesion last year, but he believes that it has been slowly growing in size. Dermatopathology determines that the lesion contains neoplastic cells of melanocytic origin. Which of the following characteristics of the lesion would likely be found on physical examination?\nA. Brown-black color in one area of the lesion to red-white in a different area\nB. Macule that is 5mm in diameter\nC. Well-circumscribed papule with smooth borders\nD. Itching and pain to palpation\nChoose the correct option.",
"image": null
},
{
"idx": 56,
"question": "A 60-year-old female patient with a history of hypertension presents to an outpatient office for regular check-up and is found to have hypertriglyceridemia. Her physician prescribes high-dose niacin and recommends taking the medication along with aspirin. The side effect the physician is trying to avoid is thought to be mediated by what mechanism?\nA. Bile deposition in the dermis\nB. Release of prostaglandins\nC. Mast cell degranulation\nD. T cell activation\n\nA. Bile deposition in the dermis\nB. Release of prostaglandins\nC. Mast cell degranulation\nD. T cell activation",
"options": [
"A. Bile deposition in the dermis",
"B. Release of prostaglandins",
"C. Mast cell degranulation",
"D. T cell activation"
],
"answer": "Release of prostaglandins",
"gen_text_store": "",
"pid": "56",
"query": "A 60-year-old female patient with a history of hypertension presents to an outpatient office for regular check-up and is found to have hypertriglyceridemia. Her physician prescribes high-dose niacin and recommends taking the medication along with aspirin. The side effect the physician is trying to avoid is thought to be mediated by what mechanism?\nA. Bile deposition in the dermis\nB. Release of prostaglandins\nC. Mast cell degranulation\nD. T cell activation\nChoose the correct option.",
"image": null
},
{
"idx": 57,
"question": "A 65-year-old man presents with painless swelling of the neck over the past week. He also says he has been having intermittent fevers and severe night sweats which require a change of bed sheets the next day. His past medical history is significant for human immunodeficiency virus (HIV) diagnosed 10 years ago with which he admits to not always being compliant with his antiretroviral medication. The patient reports a 20-pack-year smoking history but no alcohol or recreational drug use. A review of systems is significant for a 6 kg (13.2 lb) unintentional weight loss over the past 2 months. The vital signs include: temperature 37.8℃ (100.0℉) and blood pressure 120/75 mm Hg. On physical examination, there are multiple non-tender swollen lymph nodes averaging 2 cm in diameter that is palpable in the anterior and posterior triangles of the neck bilaterally. Axillary and inguinal lymphadenopathy is present on the right side. A cardiopulmonary exam is unremarkable. The spleen size is 16 cm on percussion. Laboratory studies show the following:\nHemoglobin 9 g/dL\nMean corpuscular volume 88 μm3\nLeukocyte count 18,000/mm3\nPlatelet count 130,000/mm3\n Serum creatinine 1.1 mg/dL\nSerum lactate dehydrogenase 1,000 U/L\nAn excisional biopsy of a superficial axillary lymph node on the right is performed and a histopathologic analysis confirms the most likely diagnosis. Which of the following is the next best diagnostic step in the workup of this patient?\nA. Antinuclear antibody\nB. Hepatitis C virus antibodies\nC. JAK-2 mutation\nD. Tartrate-resistant acid phosphatase (TRAP) test\n\nA. Antinuclear antibody\nB. Hepatitis C virus antibodies\nC. JAK-2 mutation\nD. Tartrate-resistant acid phosphatase (TRAP) test",
"options": [
"A. Antinuclear antibody",
"B. Hepatitis C virus antibodies",
"C. JAK-2 mutation",
"D. Tartrate-resistant acid phosphatase (TRAP) test"
],
"answer": "Hepatitis C virus antibodies",
"gen_text_store": "",
"pid": "57",
"query": "A 65-year-old man presents with painless swelling of the neck over the past week. He also says he has been having intermittent fevers and severe night sweats which require a change of bed sheets the next day. His past medical history is significant for human immunodeficiency virus (HIV) diagnosed 10 years ago with which he admits to not always being compliant with his antiretroviral medication. The patient reports a 20-pack-year smoking history but no alcohol or recreational drug use. A review of systems is significant for a 6 kg (13.2 lb) unintentional weight loss over the past 2 months. The vital signs include: temperature 37.8℃ (100.0℉) and blood pressure 120/75 mm Hg. On physical examination, there are multiple non-tender swollen lymph nodes averaging 2 cm in diameter that is palpable in the anterior and posterior triangles of the neck bilaterally. Axillary and inguinal lymphadenopathy is present on the right side. A cardiopulmonary exam is unremarkable. The spleen size is 16 cm on percussion. Laboratory studies show the following:\nHemoglobin 9 g/dL\nMean corpuscular volume 88 μm3\nLeukocyte count 18,000/mm3\nPlatelet count 130,000/mm3\n Serum creatinine 1.1 mg/dL\nSerum lactate dehydrogenase 1,000 U/L\nAn excisional biopsy of a superficial axillary lymph node on the right is performed and a histopathologic analysis confirms the most likely diagnosis. Which of the following is the next best diagnostic step in the workup of this patient?\nA. Antinuclear antibody\nB. Hepatitis C virus antibodies\nC. JAK-2 mutation\nD. Tartrate-resistant acid phosphatase (TRAP) test\nChoose the correct option.",
"image": null
},
{
"idx": 58,
"question": "Please refer to the summary above to answer this question\nA cardiologist at another institution is trying to replicate the table in the abstract with a very similar study that he is conducting. After collecting data on changes in plaque volume, LDL-C levels, FEV1/FVC ratio, and ACQ scores from baseline to 12-month follow-up, he is curious if the changes in the aforementioned measurements are statistically significant. Which of the following is the most appropriate statistical method to compare the groups?\"\n\"Impact of pulmharkimab on asthma control and cardiovascular disease progression in patients with coronary artery disease and comorbid asthma\nIntroduction:\nActive asthma has been found to be associated with a more than two-fold increase in the risk of myocardial infarction, even after adjusting for cardiovascular risk factors. It has been suggested that the inflammatory mediators and accelerated atherosclerosis characterizing systemic inflammation may increase the risk of both asthma and cardiovascular disease. This study evaluated the efficacy of the novel IL-1 inhibitor pulmharkimab in improving asthma and cardiovascular disease progression.\nMethods:\nIn this double-blind, randomized controlled trial, patients (N=1200) with a history of coronary artery disease, myocardial infarction in the past 2 years, and a diagnosis of comorbid adult-onset asthma were recruited from cardiology clinics at a large academic medical center in Philadelphia, PA. Patients who were immunocompromised or had a history of recurrent infections were excluded.\nPatients were subsequently randomly assigned a 12-month course of pulmharkimab 75 mg/day, pulmharkimab 150 mg/day, or a placebo, with each group containing 400 participants. All participants were included in analysis and analyzed in the groups to which they were randomized regardless of medication adherence. Variables measured included plaque volume, serum LDL-C levels, FEV1/FVC ratio, and Asthma Control Questionnaire (ACQ) scores, which quantified the severity of asthma symptoms. Plaque volume was determined by ultrasound.\nAnalyses were performed from baseline to month 12.\nResults:\nAt baseline, participants in the two groups did not differ by age, gender, race, plaque volume, serum LDL-C levels, FEV1/FVC ratio, and ACQ scores (p > 0.05 for all). A total of 215 participants (18%) were lost to follow-up. At 12-month follow-up, the groups contained the following numbers of participants:\nPulmharkimab 75 mg/d: 388 participants\nPulmharkimab 150 mg/d: 202 participants\nPlacebo: 395 participants\nTable 1: Association between pulmharkimab and both pulmonary and cardiovascular outcomes. Models were adjusted for sociodemographic variables and medical comorbidities. All outcome variables were approximately normally distributed.\nPulmharkimab 75 mg/d, (Mean +/- 2 SE) Pulmharkimab 150 mg/d, (Mean +/- 2 SE) Placebo, (Mean +/- 2 SE) P-value\nPlaque volume (mm3), change from baseline 6.6 ± 2.8 1.2 ± 4.7 15.8 ± 2.9 < 0.01\nLDL-C levels, change from baseline -9.4 ± 3.6 -11.2 ± 14.3 -8.4 ± 3.9 0.28\nFEV1/FVC ratio, change from baseline 0.29 ± 2.21 0.34 ± 5.54 -0.22 ± 3.21 0.27\nACQ scores, change from baseline 0.31 ± 1.22 0.46 ± 3.25 0.12 ± 1.33 0.43\nConclusion:\nPulmharkimab may be effective in reducing plaque volume but does not lead to improved asthma control in patients with a history of myocardial infarction and comorbid asthma.\nSource of funding: Southeast Institute for Advanced Lung and Cardiovascular Studies, American Center for Advancement of Cardiovascular Health\"\nA. Pearson correlation analysis\nB. Chi-square test\nC. Analysis of variance\nD. Kaplan-Meier analysis\n\nA. Pearson correlation analysis\nB. Chi-square test\nC. Analysis of variance\nD. Kaplan-Meier analysis",
"options": [
"A. Pearson correlation analysis",
"B. Chi-square test",
"C. Analysis of variance",
"D. Kaplan-Meier analysis"
],
"answer": "Analysis of variance",
"gen_text_store": "",
"pid": "58",
"query": "Please refer to the summary above to answer this question\nA cardiologist at another institution is trying to replicate the table in the abstract with a very similar study that he is conducting. After collecting data on changes in plaque volume, LDL-C levels, FEV1/FVC ratio, and ACQ scores from baseline to 12-month follow-up, he is curious if the changes in the aforementioned measurements are statistically significant. Which of the following is the most appropriate statistical method to compare the groups?\"\n\"Impact of pulmharkimab on asthma control and cardiovascular disease progression in patients with coronary artery disease and comorbid asthma\nIntroduction:\nActive asthma has been found to be associated with a more than two-fold increase in the risk of myocardial infarction, even after adjusting for cardiovascular risk factors. It has been suggested that the inflammatory mediators and accelerated atherosclerosis characterizing systemic inflammation may increase the risk of both asthma and cardiovascular disease. This study evaluated the efficacy of the novel IL-1 inhibitor pulmharkimab in improving asthma and cardiovascular disease progression.\nMethods:\nIn this double-blind, randomized controlled trial, patients (N=1200) with a history of coronary artery disease, myocardial infarction in the past 2 years, and a diagnosis of comorbid adult-onset asthma were recruited from cardiology clinics at a large academic medical center in Philadelphia, PA. Patients who were immunocompromised or had a history of recurrent infections were excluded.\nPatients were subsequently randomly assigned a 12-month course of pulmharkimab 75 mg/day, pulmharkimab 150 mg/day, or a placebo, with each group containing 400 participants. All participants were included in analysis and analyzed in the groups to which they were randomized regardless of medication adherence. Variables measured included plaque volume, serum LDL-C levels, FEV1/FVC ratio, and Asthma Control Questionnaire (ACQ) scores, which quantified the severity of asthma symptoms. Plaque volume was determined by ultrasound.\nAnalyses were performed from baseline to month 12.\nResults:\nAt baseline, participants in the two groups did not differ by age, gender, race, plaque volume, serum LDL-C levels, FEV1/FVC ratio, and ACQ scores (p > 0.05 for all). A total of 215 participants (18%) were lost to follow-up. At 12-month follow-up, the groups contained the following numbers of participants:\nPulmharkimab 75 mg/d: 388 participants\nPulmharkimab 150 mg/d: 202 participants\nPlacebo: 395 participants\nTable 1: Association between pulmharkimab and both pulmonary and cardiovascular outcomes. Models were adjusted for sociodemographic variables and medical comorbidities. All outcome variables were approximately normally distributed.\nPulmharkimab 75 mg/d, (Mean +/- 2 SE) Pulmharkimab 150 mg/d, (Mean +/- 2 SE) Placebo, (Mean +/- 2 SE) P-value\nPlaque volume (mm3), change from baseline 6.6 ± 2.8 1.2 ± 4.7 15.8 ± 2.9 < 0.01\nLDL-C levels, change from baseline -9.4 ± 3.6 -11.2 ± 14.3 -8.4 ± 3.9 0.28\nFEV1/FVC ratio, change from baseline 0.29 ± 2.21 0.34 ± 5.54 -0.22 ± 3.21 0.27\nACQ scores, change from baseline 0.31 ± 1.22 0.46 ± 3.25 0.12 ± 1.33 0.43\nConclusion:\nPulmharkimab may be effective in reducing plaque volume but does not lead to improved asthma control in patients with a history of myocardial infarction and comorbid asthma.\nSource of funding: Southeast Institute for Advanced Lung and Cardiovascular Studies, American Center for Advancement of Cardiovascular Health\"\nA. Pearson correlation analysis\nB. Chi-square test\nC. Analysis of variance\nD. Kaplan-Meier analysis\nChoose the correct option.",
"image": null
},
{
"idx": 59,
"question": "A 31-year-old man presents to his primary care physician with fevers, chills, and night sweats. After a physical exam and a series of laboratory tests, the patient undergoes a lymph node biopsy (Image A). Three days later, while awaiting treatment, he presents to his physician complaining of generalized swelling and is found to have 4+ protein in his urine. Which of the following pathological findings is most likely to be found on renal biopsy in this patient?\nA. Rapidly progresive glomerulonephritis\nB. Amyloidosis\nC. Focal segmental glomerulosclerosis\nD. Minimal change disease\n\nA. Rapidly progresive glomerulonephritis\nB. Amyloidosis\nC. Focal segmental glomerulosclerosis\nD. Minimal change disease",
"options": [
"A. Rapidly progresive glomerulonephritis",
"B. Amyloidosis",
"C. Focal segmental glomerulosclerosis",
"D. Minimal change disease"
],
"answer": "Minimal change disease",
"gen_text_store": "",
"pid": "59",
"query": "A 31-year-old man presents to his primary care physician with fevers, chills, and night sweats. After a physical exam and a series of laboratory tests, the patient undergoes a lymph node biopsy (Image A). Three days later, while awaiting treatment, he presents to his physician complaining of generalized swelling and is found to have 4+ protein in his urine. Which of the following pathological findings is most likely to be found on renal biopsy in this patient?\nA. Rapidly progresive glomerulonephritis\nB. Amyloidosis\nC. Focal segmental glomerulosclerosis\nD. Minimal change disease\nChoose the correct option.",
"image": null
},
{
"idx": 60,
"question": "A 72-year-old man with hypertension and type 2 diabetes mellitus is admitted to the hospital for the evaluation of breathlessness and fatigue. His pulse is 100/min, and blood pressure is 90/60 mm Hg. Further evaluation shows a systemic vascular resistance of 35 mm Hg × min/L with an end-systolic volume of 80 mL. Which of the following describes the ejection fraction in this patient?\nA. 30%\nB. 15%\nC. 25%\nD. 20%\n\nA. 30%\nB. 15%\nC. 25%\nD. 20%",
"options": [
"A. 30%",
"B. 15%",
"C. 25%",
"D. 20%"
],
"answer": "20%",
"gen_text_store": "",
"pid": "60",
"query": "A 72-year-old man with hypertension and type 2 diabetes mellitus is admitted to the hospital for the evaluation of breathlessness and fatigue. His pulse is 100/min, and blood pressure is 90/60 mm Hg. Further evaluation shows a systemic vascular resistance of 35 mm Hg × min/L with an end-systolic volume of 80 mL. Which of the following describes the ejection fraction in this patient?\nA. 30%\nB. 15%\nC. 25%\nD. 20%\nChoose the correct option.",
"image": null
},
{
"idx": 61,
"question": "A 65-year-old man presents to the emergency department with back pain. The patient states that he has gradually worsening back pain that seems to have worsened after moving furniture the other day. He also states that while he walks, he feels numbness and weakness in his legs. The only time the patient states his back pain is improved is when he is riding his bike or pushing a cart at the grocery store. The patient has a past medical history of osteoporosis, dyslipidemia, and diabetes. He drinks 3 alcoholic drinks every day and has a 44 pack-year smoking history. His temperature is 99.5°F (37.5°C), blood pressure is 157/108 mmHg, pulse is 90/min, respirations are 17/min, and oxygen saturation is 98% on room air. Physical exam is notable for a non-tender spine with normal mobility in all 4 directions. Radiography of the spine and basic labs are ordered. Which of the following is the most likely diagnosis?\nA. Compression fracture\nB. Herniated nucleus pulposus\nC. Musculoskeletal strain\nD. Spinal stenosis\n\nA. Compression fracture\nB. Herniated nucleus pulposus\nC. Musculoskeletal strain\nD. Spinal stenosis",
"options": [
"A. Compression fracture",
"B. Herniated nucleus pulposus",
"C. Musculoskeletal strain",
"D. Spinal stenosis"
],
"answer": "Spinal stenosis",
"gen_text_store": "",
"pid": "61",
"query": "A 65-year-old man presents to the emergency department with back pain. The patient states that he has gradually worsening back pain that seems to have worsened after moving furniture the other day. He also states that while he walks, he feels numbness and weakness in his legs. The only time the patient states his back pain is improved is when he is riding his bike or pushing a cart at the grocery store. The patient has a past medical history of osteoporosis, dyslipidemia, and diabetes. He drinks 3 alcoholic drinks every day and has a 44 pack-year smoking history. His temperature is 99.5°F (37.5°C), blood pressure is 157/108 mmHg, pulse is 90/min, respirations are 17/min, and oxygen saturation is 98% on room air. Physical exam is notable for a non-tender spine with normal mobility in all 4 directions. Radiography of the spine and basic labs are ordered. Which of the following is the most likely diagnosis?\nA. Compression fracture\nB. Herniated nucleus pulposus\nC. Musculoskeletal strain\nD. Spinal stenosis\nChoose the correct option.",
"image": null
},
{
"idx": 62,
"question": "A 24-year-old G2P1 woman at 39 weeks’ gestation presents to the emergency department complaining of painful contractions occurring every 10 minutes for the past 2 hours, consistent with latent labor. She says she has not experienced vaginal discharge, bleeding, or fluid leakage, and is currently taking no medications. On physical examination, her blood pressure is 110/70 mm Hg, heart rate is 86/min, and temperature is 37.6°C (99.7°F). She has had little prenatal care and uses condoms inconsistently. Her sexually transmitted infections status is unknown. As part of the patient’s workup, she undergoes a series of rapid screening tests that result in the administration of zidovudine during delivery. The infant is also given zidovudine to reduce the risk of transmission. A confirmatory test is then performed in the mother to confirm the diagnosis of HIV. Which of the following is most true about the confirmatory test?\nA. It is a Southwestern blot, identifying the presence of DNA-binding proteins\nB. It is a Northern blot, identifying the presence of RNA\nC. It is a Northern blot, identifying the presence of DNA\nD. It is an HIV-1/HIV2 antibody differentiation immunoassay\n\nA. It is a Southwestern blot, identifying the presence of DNA-binding proteins\nB. It is a Northern blot, identifying the presence of RNA\nC. It is a Northern blot, identifying the presence of DNA\nD. It is an HIV-1/HIV2 antibody differentiation immunoassay",
"options": [
"A. It is a Southwestern blot, identifying the presence of DNA-binding proteins",
"B. It is a Northern blot, identifying the presence of RNA",
"C. It is a Northern blot, identifying the presence of DNA",
"D. It is an HIV-1/HIV2 antibody differentiation immunoassay"
],
"answer": "It is an HIV-1/HIV2 antibody differentiation immunoassay",
"gen_text_store": "",
"pid": "62",
"query": "A 24-year-old G2P1 woman at 39 weeks’ gestation presents to the emergency department complaining of painful contractions occurring every 10 minutes for the past 2 hours, consistent with latent labor. She says she has not experienced vaginal discharge, bleeding, or fluid leakage, and is currently taking no medications. On physical examination, her blood pressure is 110/70 mm Hg, heart rate is 86/min, and temperature is 37.6°C (99.7°F). She has had little prenatal care and uses condoms inconsistently. Her sexually transmitted infections status is unknown. As part of the patient’s workup, she undergoes a series of rapid screening tests that result in the administration of zidovudine during delivery. The infant is also given zidovudine to reduce the risk of transmission. A confirmatory test is then performed in the mother to confirm the diagnosis of HIV. Which of the following is most true about the confirmatory test?\nA. It is a Southwestern blot, identifying the presence of DNA-binding proteins\nB. It is a Northern blot, identifying the presence of RNA\nC. It is a Northern blot, identifying the presence of DNA\nD. It is an HIV-1/HIV2 antibody differentiation immunoassay\nChoose the correct option.",
"image": null
},
{
"idx": 63,
"question": "A 14-year-old boy presents with right upper quadrant abdominal pain and is found on ultrasound to have a gallstone. Based on clinical suspicion, a CBC, a Coombs test, and a bilirubin panel are obtained to determine the etiology of the gallstone. These tests reveal a mild normocytic anemia with associated reticulocytosis as well as an increased RDW. In addition there is an indirect hyperbilirubinemia and the Coombs test results are negative. To confirm the diagnosis, an osmotic fragility test is performed which shows increased fragility in hypotonic solution. In this patient, what findings would most likely be anticipated if a blood smear were obtained?\nA. Hypersegmented neutrophils\nB. Sideroblasts\nC. Spherocytes\nD. Dacrocytes\n\nA. Hypersegmented neutrophils\nB. Sideroblasts\nC. Spherocytes\nD. Dacrocytes",
"options": [
"A. Hypersegmented neutrophils",
"B. Sideroblasts",
"C. Spherocytes",
"D. Dacrocytes"
],
"answer": "Spherocytes",
"gen_text_store": "",
"pid": "63",
"query": "A 14-year-old boy presents with right upper quadrant abdominal pain and is found on ultrasound to have a gallstone. Based on clinical suspicion, a CBC, a Coombs test, and a bilirubin panel are obtained to determine the etiology of the gallstone. These tests reveal a mild normocytic anemia with associated reticulocytosis as well as an increased RDW. In addition there is an indirect hyperbilirubinemia and the Coombs test results are negative. To confirm the diagnosis, an osmotic fragility test is performed which shows increased fragility in hypotonic solution. In this patient, what findings would most likely be anticipated if a blood smear were obtained?\nA. Hypersegmented neutrophils\nB. Sideroblasts\nC. Spherocytes\nD. Dacrocytes\nChoose the correct option.",
"image": null
},
{
"idx": 64,
"question": "An 8-week-old male presents with his mother to the pediatrician for a well visit. The patient has been breastfed since birth, and usually feeds for 30 minutes every 2-3 hours. The patient’s mother is concerned that her milk production is not keeping up with the patient’s nutritional requirements. She reports that about two weeks ago the patient began regurgitating breastmilk through his nose and mouth after some feeds. She reports that he seems mildly upset during the episodes of regurgitation but usually settles down quickly and is hungry again soon afterwards. The patient’s mother has already tried limiting the volume of each feed, which seems to have reduced the frequency of the regurgitation. She denies any diarrhea, hematochezia, or family history of food allergies. Her older son had a similar problem with vomiting that resolved around 12 months of age. Four weeks ago, the patient’s height and weight were in the 40th and 34th percentiles, respectively. His height and weight are now respectively in the 37th and 36th percentiles. On physical exam, the patient is cooing in his mother’s lap and smiles reciprocally with her. He lifts his head and shoulders off the examination table when placed in the supine position. His abdomen is soft, non-tender and non-distended. Bowel sounds are normoactive.\n\nWhich of the following is the best next step in management?\nA. Initiate proton pump inhibitor\nB. Obtain abdominal ultrasound\nC. Reassurance and counseling on positioning\nD. Recommend modification of mother’s diet\n\nA. Initiate proton pump inhibitor\nB. Obtain abdominal ultrasound\nC. Reassurance and counseling on positioning\nD. Recommend modification of mother’s diet",
"options": [
"A. Initiate proton pump inhibitor",
"B. Obtain abdominal ultrasound",
"C. Reassurance and counseling on positioning",
"D. Recommend modification of mother’s diet"
],
"answer": "Reassurance and counseling on positioning",
"gen_text_store": "",
"pid": "64",
"query": "An 8-week-old male presents with his mother to the pediatrician for a well visit. The patient has been breastfed since birth, and usually feeds for 30 minutes every 2-3 hours. The patient’s mother is concerned that her milk production is not keeping up with the patient’s nutritional requirements. She reports that about two weeks ago the patient began regurgitating breastmilk through his nose and mouth after some feeds. She reports that he seems mildly upset during the episodes of regurgitation but usually settles down quickly and is hungry again soon afterwards. The patient’s mother has already tried limiting the volume of each feed, which seems to have reduced the frequency of the regurgitation. She denies any diarrhea, hematochezia, or family history of food allergies. Her older son had a similar problem with vomiting that resolved around 12 months of age. Four weeks ago, the patient’s height and weight were in the 40th and 34th percentiles, respectively. His height and weight are now respectively in the 37th and 36th percentiles. On physical exam, the patient is cooing in his mother’s lap and smiles reciprocally with her. He lifts his head and shoulders off the examination table when placed in the supine position. His abdomen is soft, non-tender and non-distended. Bowel sounds are normoactive.\n\nWhich of the following is the best next step in management?\nA. Initiate proton pump inhibitor\nB. Obtain abdominal ultrasound\nC. Reassurance and counseling on positioning\nD. Recommend modification of mother’s diet\nChoose the correct option.",
"image": null
},
{
"idx": 65,
"question": "A 55-year-old man presents to a rheumatologist with bilateral wrist and knee pain that has been present for the last 10 years. The patient was a professional athlete who retired at age 50. He also notes morning stiffness in his joints that lasts approx. 50 minutes. He denies joint swelling, color changes in his digits, dryness of mucous membranes, and constitutional symptoms such as fever and chills. On physical exam, the physician notes several non-tender nodules on the left 1st, 3rd, and 4th distal interphalangeal joints. There is also tenderness with palpation at the base of both thumbs. The patient’s knees are enlarged, bilaterally, and he has pain and crepitus on passive range of motion. Which of the following is the most likely diagnosis?\nA. Ankylosing spondylitis\nB. Gout\nC. Osteoarthritis\nD. Fibromyalgia\n\nA. Ankylosing spondylitis\nB. Gout\nC. Osteoarthritis\nD. Fibromyalgia",
"options": [
"A. Ankylosing spondylitis",
"B. Gout",
"C. Osteoarthritis",
"D. Fibromyalgia"
],
"answer": "Osteoarthritis",
"gen_text_store": "",
"pid": "65",
"query": "A 55-year-old man presents to a rheumatologist with bilateral wrist and knee pain that has been present for the last 10 years. The patient was a professional athlete who retired at age 50. He also notes morning stiffness in his joints that lasts approx. 50 minutes. He denies joint swelling, color changes in his digits, dryness of mucous membranes, and constitutional symptoms such as fever and chills. On physical exam, the physician notes several non-tender nodules on the left 1st, 3rd, and 4th distal interphalangeal joints. There is also tenderness with palpation at the base of both thumbs. The patient’s knees are enlarged, bilaterally, and he has pain and crepitus on passive range of motion. Which of the following is the most likely diagnosis?\nA. Ankylosing spondylitis\nB. Gout\nC. Osteoarthritis\nD. Fibromyalgia\nChoose the correct option.",
"image": null
},
{
"idx": 66,
"question": "A 22-year-old female college student is treated with metronidazole after presenting to student health services with itching, discharge, and pain in her vagina. At a party shortly afterward she experiences facial flushing, nausea, tachycardia, dyspnea, headache, and abdominal cramps after consuming alcohol. Serum levels of which of the following are likely elevated in this patient following alcohol consumption:\nA. Acetaldehyde\nB. Uric acid\nC. Cytochrome P-450 enzymes\nD. Amylase\n\nA. Acetaldehyde\nB. Uric acid\nC. Cytochrome P-450 enzymes\nD. Amylase",
"options": [
"A. Acetaldehyde",
"B. Uric acid",
"C. Cytochrome P-450 enzymes",
"D. Amylase"
],
"answer": "Acetaldehyde",
"gen_text_store": "",
"pid": "66",
"query": "A 22-year-old female college student is treated with metronidazole after presenting to student health services with itching, discharge, and pain in her vagina. At a party shortly afterward she experiences facial flushing, nausea, tachycardia, dyspnea, headache, and abdominal cramps after consuming alcohol. Serum levels of which of the following are likely elevated in this patient following alcohol consumption:\nA. Acetaldehyde\nB. Uric acid\nC. Cytochrome P-450 enzymes\nD. Amylase\nChoose the correct option.",
"image": null
},
{
"idx": 67,
"question": "A 22-year-old woman presents to the emergency department for abdominal pain. The patient has been trying to get pregnant and was successful recently, but now she is experiencing abdominal pain, contractions, and a bloody vaginal discharge. According to her last appointment with her primary care provider, she is 10 weeks pregnant. The patient has a past medical history of constipation, anxiety, and substance abuse. She is not currently taking any medications. Her temperature is 99.5°F (37.5°C), blood pressure is 107/58 mmHg, pulse is 90/min, respirations are 17/min, and oxygen saturation is 98% on room air. Physical exam is notable for a bloody vaginal discharge and an open cervix. The patient is initially extremely grateful for the care she is receiving and thanks the doctor and the nursing staff for saving her baby. Upon hearing the news that she is having a spontaneous abortion, the patient becomes angry and aggressive and states that her physician and the medical staff are incompetent, evil, and she is going to sue all of them. The patient is left to grieve but upon entering the room again you notice that the patient has new lacerations over her wrists and that some of the medical equipment in the room is broken. Which of the following is the most likely diagnosis?\nA. Antisocial personality disorder\nB. Borderline personality disorder\nC. Normal grief response\nD. Post-traumatic stress disorder\n\nA. Antisocial personality disorder\nB. Borderline personality disorder\nC. Normal grief response\nD. Post-traumatic stress disorder",
"options": [
"A. Antisocial personality disorder",
"B. Borderline personality disorder",
"C. Normal grief response",
"D. Post-traumatic stress disorder"
],
"answer": "Borderline personality disorder",
"gen_text_store": "",
"pid": "67",
"query": "A 22-year-old woman presents to the emergency department for abdominal pain. The patient has been trying to get pregnant and was successful recently, but now she is experiencing abdominal pain, contractions, and a bloody vaginal discharge. According to her last appointment with her primary care provider, she is 10 weeks pregnant. The patient has a past medical history of constipation, anxiety, and substance abuse. She is not currently taking any medications. Her temperature is 99.5°F (37.5°C), blood pressure is 107/58 mmHg, pulse is 90/min, respirations are 17/min, and oxygen saturation is 98% on room air. Physical exam is notable for a bloody vaginal discharge and an open cervix. The patient is initially extremely grateful for the care she is receiving and thanks the doctor and the nursing staff for saving her baby. Upon hearing the news that she is having a spontaneous abortion, the patient becomes angry and aggressive and states that her physician and the medical staff are incompetent, evil, and she is going to sue all of them. The patient is left to grieve but upon entering the room again you notice that the patient has new lacerations over her wrists and that some of the medical equipment in the room is broken. Which of the following is the most likely diagnosis?\nA. Antisocial personality disorder\nB. Borderline personality disorder\nC. Normal grief response\nD. Post-traumatic stress disorder\nChoose the correct option.",
"image": null
},
{
"idx": 68,
"question": "A 6-week-old male infant is brought to the physician by his mother because of a 2-day history of recurrent nonbilious vomiting. Vomiting occurs almost immediately after most feeds. Each time, he becomes irritable while feeding and refuses to finish the bottle. He was born at 37 weeks' gestation and weighed 3300 g (7 lb 4 oz); he currently weighs 4000 g (8 lb 13 oz). He has Down syndrome. His vaccinations are up-to-date. He appears agitated and cries during the examination. His temperature is 37.2°C (99°F), pulse is 156/min, respirations are 32/min, and blood pressure is 100/49 mm Hg. Examination shows upward slanting of the eyelids, a broad and flat nasal bridge, and a single transverse palmar crease on both hands. The abdomen is soft and nontender. A 2.5-cm (1-inch) epigastric mass is palpated. Cardiac examination shows no abnormalities. Arterial blood gas analysis is within normal limits. Further diagnostic evaluation of the patient is most likely to show which of the following?\nA. Dilated colon segment on abdominal x-ray\nB. Detection of rotavirus antigen on enzyme immunoassay (EIA)\nC. Elongated and thickened pylorus on abdominal ultrasound\nD. Tripple bubble sign on abdominal x-ray\n\nA. Dilated colon segment on abdominal x-ray\nB. Detection of rotavirus antigen on enzyme immunoassay (EIA)\nC. Elongated and thickened pylorus on abdominal ultrasound\nD. Tripple bubble sign on abdominal x-ray",
"options": [
"A. Dilated colon segment on abdominal x-ray",
"B. Detection of rotavirus antigen on enzyme immunoassay (EIA)",
"C. Elongated and thickened pylorus on abdominal ultrasound",
"D. Tripple bubble sign on abdominal x-ray"
],
"answer": "Elongated and thickened pylorus on abdominal ultrasound",
"gen_text_store": "",
"pid": "68",
"query": "A 6-week-old male infant is brought to the physician by his mother because of a 2-day history of recurrent nonbilious vomiting. Vomiting occurs almost immediately after most feeds. Each time, he becomes irritable while feeding and refuses to finish the bottle. He was born at 37 weeks' gestation and weighed 3300 g (7 lb 4 oz); he currently weighs 4000 g (8 lb 13 oz). He has Down syndrome. His vaccinations are up-to-date. He appears agitated and cries during the examination. His temperature is 37.2°C (99°F), pulse is 156/min, respirations are 32/min, and blood pressure is 100/49 mm Hg. Examination shows upward slanting of the eyelids, a broad and flat nasal bridge, and a single transverse palmar crease on both hands. The abdomen is soft and nontender. A 2.5-cm (1-inch) epigastric mass is palpated. Cardiac examination shows no abnormalities. Arterial blood gas analysis is within normal limits. Further diagnostic evaluation of the patient is most likely to show which of the following?\nA. Dilated colon segment on abdominal x-ray\nB. Detection of rotavirus antigen on enzyme immunoassay (EIA)\nC. Elongated and thickened pylorus on abdominal ultrasound\nD. Tripple bubble sign on abdominal x-ray\nChoose the correct option.",
"image": null
},
{
"idx": 69,
"question": "A 23-year-old woman presents to the hospital for elective surgery. However, due to an unexpected bleeding event, the physician had to order a blood transfusion to replace the blood lost in the surgery. After this, the patient became irritable and had difficulty breathing, suggesting an allergic reaction, which was immediately treated with epinephrine. This patient is otherwise healthy, and her history does not indicate any health conditions or known allergies. The physician suspects an immunodeficiency disorder that was not previously diagnosed. If serum is taken from this patient to analyze her condition further, which of the following would be expected?\nA. High IgM, low IgA, and IgE\nB. Low IgA, normal IgG, and IgM\nC. High IgE, normal IgA, and IgG\nD. Normal serum immunoglobulin values\n\nA. High IgM, low IgA, and IgE\nB. Low IgA, normal IgG, and IgM\nC. High IgE, normal IgA, and IgG\nD. Normal serum immunoglobulin values",
"options": [
"A. High IgM, low IgA, and IgE",
"B. Low IgA, normal IgG, and IgM",
"C. High IgE, normal IgA, and IgG",
"D. Normal serum immunoglobulin values"
],
"answer": "Low IgA, normal IgG, and IgM",
"gen_text_store": "",
"pid": "69",
"query": "A 23-year-old woman presents to the hospital for elective surgery. However, due to an unexpected bleeding event, the physician had to order a blood transfusion to replace the blood lost in the surgery. After this, the patient became irritable and had difficulty breathing, suggesting an allergic reaction, which was immediately treated with epinephrine. This patient is otherwise healthy, and her history does not indicate any health conditions or known allergies. The physician suspects an immunodeficiency disorder that was not previously diagnosed. If serum is taken from this patient to analyze her condition further, which of the following would be expected?\nA. High IgM, low IgA, and IgE\nB. Low IgA, normal IgG, and IgM\nC. High IgE, normal IgA, and IgG\nD. Normal serum immunoglobulin values\nChoose the correct option.",
"image": null
},
{
"idx": 70,
"question": "A 22-year-old gravida 1 presents to her physician at 15 weeks gestation for a prenatal appointment. She complains of a rash involving her chest, face, and arms, a watery nasal discharge, and mild bilateral knee pain. She has had these symptoms for about 5 days. The symptoms do not seem to bother her too much, but she is concerned for the baby. She had contact with her younger sister, who also had a rash and was diagnosed with rubella infection about 10 days ago at a family gathering. She cannot confirm her vaccination history. Her vital signs are as follows: blood pressure, 110/70 mmHg; heart rate, 89/min; respiratory rate, 12/min; and temperature, 37.6℃ (99.7℉). Examination shows a moderately dense maculopapular lacy rash spread over the patient’s trunk, extremities, and face. No lymph node, liver, or spleen enlargement is noted. The knee joints appear normal.\nSerology performed 1 year ago Current serology\nRubella IgM - negative Rubella IgM - negative\nRubella IgG - 1:128 Rubella IgG - 1:64\nRubella IgG avidity - high Rubella IgG avidity - high\nWhat is the proper next step in the management of this woman?\nA. Reassure and recommend vaccination against rubella postpartum\nB. Recommend pregnancy termination\nC. Arrange a chorionic villus sampling\nD. Recommend additional serologic testing for parvovirus B19\n\nA. Reassure and recommend vaccination against rubella postpartum\nB. Recommend pregnancy termination\nC. Arrange a chorionic villus sampling\nD. Recommend additional serologic testing for parvovirus B19",
"options": [
"A. Reassure and recommend vaccination against rubella postpartum",
"B. Recommend pregnancy termination",
"C. Arrange a chorionic villus sampling",
"D. Recommend additional serologic testing for parvovirus B19"
],
"answer": "Recommend additional serologic testing for parvovirus B19",
"gen_text_store": "",
"pid": "70",
"query": "A 22-year-old gravida 1 presents to her physician at 15 weeks gestation for a prenatal appointment. She complains of a rash involving her chest, face, and arms, a watery nasal discharge, and mild bilateral knee pain. She has had these symptoms for about 5 days. The symptoms do not seem to bother her too much, but she is concerned for the baby. She had contact with her younger sister, who also had a rash and was diagnosed with rubella infection about 10 days ago at a family gathering. She cannot confirm her vaccination history. Her vital signs are as follows: blood pressure, 110/70 mmHg; heart rate, 89/min; respiratory rate, 12/min; and temperature, 37.6℃ (99.7℉). Examination shows a moderately dense maculopapular lacy rash spread over the patient’s trunk, extremities, and face. No lymph node, liver, or spleen enlargement is noted. The knee joints appear normal.\nSerology performed 1 year ago Current serology\nRubella IgM - negative Rubella IgM - negative\nRubella IgG - 1:128 Rubella IgG - 1:64\nRubella IgG avidity - high Rubella IgG avidity - high\nWhat is the proper next step in the management of this woman?\nA. Reassure and recommend vaccination against rubella postpartum\nB. Recommend pregnancy termination\nC. Arrange a chorionic villus sampling\nD. Recommend additional serologic testing for parvovirus B19\nChoose the correct option.",
"image": null
},
{
"idx": 71,
"question": "A 7-year-old woman presents shortly after her birthday with red scaly plaques over both ears. Her mother reports that the patient recently received a pair of fashionable silver earrings from her older sister as a birthday present. Physical examination is only significant for erythema and tenderness over the lobules of the ears bilaterally. Her vital signs show a blood pressure of 121/73 mm Hg, heart rate of 72/min, and a respiratory rate of 21/min. Her medical history is non-significant. Of the following options, which is the mechanism of this reaction?\nA. Type I–anaphylactic hypersensitivity reaction\nB. Type III–immune complex-mediated hypersensitivity reaction\nC. Type IV–cell-mediated (delayed) hypersensitivity reaction\nD. Type III and IV–mixed immune complex and cell-mediated hypersensitivity reactions\n\nA. Type I–anaphylactic hypersensitivity reaction\nB. Type III–immune complex-mediated hypersensitivity reaction\nC. Type IV–cell-mediated (delayed) hypersensitivity reaction\nD. Type III and IV–mixed immune complex and cell-mediated hypersensitivity reactions",
"options": [
"A. Type I–anaphylactic hypersensitivity reaction",
"B. Type III–immune complex-mediated hypersensitivity reaction",
"C. Type IV–cell-mediated (delayed) hypersensitivity reaction",
"D. Type III and IV–mixed immune complex and cell-mediated hypersensitivity reactions"
],
"answer": "Type IV–cell-mediated (delayed) hypersensitivity reaction",
"gen_text_store": "",
"pid": "71",
"query": "A 7-year-old woman presents shortly after her birthday with red scaly plaques over both ears. Her mother reports that the patient recently received a pair of fashionable silver earrings from her older sister as a birthday present. Physical examination is only significant for erythema and tenderness over the lobules of the ears bilaterally. Her vital signs show a blood pressure of 121/73 mm Hg, heart rate of 72/min, and a respiratory rate of 21/min. Her medical history is non-significant. Of the following options, which is the mechanism of this reaction?\nA. Type I–anaphylactic hypersensitivity reaction\nB. Type III–immune complex-mediated hypersensitivity reaction\nC. Type IV–cell-mediated (delayed) hypersensitivity reaction\nD. Type III and IV–mixed immune complex and cell-mediated hypersensitivity reactions\nChoose the correct option.",
"image": null
},
{
"idx": 72,
"question": "The parents of a 14-year-old patient are concerned and have questions about the use of insulin for their son’s recently diagnosed type 1 diabetes. The patient has developed an upper respiratory infection while at school. He is coughing and has a runny nose. His temperature is 37.8° C (100.2° F) and vital signs are within normal limits. Physical examination is unremarkable. Which of the following modifications to his insulin regimen would you recommend to this patient and his parents?\nA. Increase the frequency of blood glucose checks.\nB. Reduce the insulin dose.\nC. Continue same regimen.\nD. Hold insulin until the patient gets better.\n\nA. Increase the frequency of blood glucose checks.\nB. Reduce the insulin dose.\nC. Continue same regimen.\nD. Hold insulin until the patient gets better.",
"options": [
"A. Increase the frequency of blood glucose checks.",
"B. Reduce the insulin dose.",
"C. Continue same regimen.",
"D. Hold insulin until the patient gets better."
],
"answer": "Increase the frequency of blood glucose checks.",
"gen_text_store": "",
"pid": "72",
"query": "The parents of a 14-year-old patient are concerned and have questions about the use of insulin for their son’s recently diagnosed type 1 diabetes. The patient has developed an upper respiratory infection while at school. He is coughing and has a runny nose. His temperature is 37.8° C (100.2° F) and vital signs are within normal limits. Physical examination is unremarkable. Which of the following modifications to his insulin regimen would you recommend to this patient and his parents?\nA. Increase the frequency of blood glucose checks.\nB. Reduce the insulin dose.\nC. Continue same regimen.\nD. Hold insulin until the patient gets better.\nChoose the correct option.",
"image": null
},
{
"idx": 73,
"question": "A 64-year-old man presents to the clinic with easy fatigability and breathlessness when climbing stairs for the last 2 weeks. He also mentions that he occasionally has bouts of cough at night after about 2–3 hours of sleep which is relieved when he sits upright. He denies shortness of breath at rest, palpitations, and loss of consciousness. He has had hypertension for the last 20 years and is on antihypertensive medications. On physical examination, his temperature is 36.9°C (98.4°F), pulse is 104/min, blood pressure is 122/82 mm Hg, and respirations are 18/min. Chest auscultation reveals crackles over the lung bases bilaterally. Examination of his abdomen reveals mildly tender hepatomegaly. Laboratory investigation results include a hemoglobin of 14.8 g/dL (9.18 mmol/L) and an elevated serum B-type natriuretic peptide. His two-dimensional echocardiogram reveals an enlarged left atrium and an ejection fraction of 55%. Which of the following novel drugs is most likely to benefit the patient in addition to valsartan?\nA. Etanercept\nB. Moxonidine\nC. Sacubitril\nD. Aliskiren\n\nA. Etanercept\nB. Moxonidine\nC. Sacubitril\nD. Aliskiren",
"options": [
"A. Etanercept",
"B. Moxonidine",
"C. Sacubitril",
"D. Aliskiren"
],
"answer": "Sacubitril",
"gen_text_store": "",
"pid": "73",
"query": "A 64-year-old man presents to the clinic with easy fatigability and breathlessness when climbing stairs for the last 2 weeks. He also mentions that he occasionally has bouts of cough at night after about 2–3 hours of sleep which is relieved when he sits upright. He denies shortness of breath at rest, palpitations, and loss of consciousness. He has had hypertension for the last 20 years and is on antihypertensive medications. On physical examination, his temperature is 36.9°C (98.4°F), pulse is 104/min, blood pressure is 122/82 mm Hg, and respirations are 18/min. Chest auscultation reveals crackles over the lung bases bilaterally. Examination of his abdomen reveals mildly tender hepatomegaly. Laboratory investigation results include a hemoglobin of 14.8 g/dL (9.18 mmol/L) and an elevated serum B-type natriuretic peptide. His two-dimensional echocardiogram reveals an enlarged left atrium and an ejection fraction of 55%. Which of the following novel drugs is most likely to benefit the patient in addition to valsartan?\nA. Etanercept\nB. Moxonidine\nC. Sacubitril\nD. Aliskiren\nChoose the correct option.",
"image": null
},
{
"idx": 74,
"question": "A 75-year-old man presents to a medical clinic for evaluation of a large, tense, pruritic bulla on his inner thighs, abdomen, and lower abdomen. A skin biopsy is performed, which shows an epidermal basement membrane with immunoglobulin G (IgG) antibodies and linear immunofluorescence. Which of the following is the most likely cell junction to which the antibodies bind?\nA. Desmosomes\nB. Gap junctions\nC. Hemidesmosomes\nD. Tight junctions\n\nA. Desmosomes\nB. Gap junctions\nC. Hemidesmosomes\nD. Tight junctions",
"options": [
"A. Desmosomes",
"B. Gap junctions",
"C. Hemidesmosomes",
"D. Tight junctions"
],
"answer": "Hemidesmosomes",
"gen_text_store": "",
"pid": "74",
"query": "A 75-year-old man presents to a medical clinic for evaluation of a large, tense, pruritic bulla on his inner thighs, abdomen, and lower abdomen. A skin biopsy is performed, which shows an epidermal basement membrane with immunoglobulin G (IgG) antibodies and linear immunofluorescence. Which of the following is the most likely cell junction to which the antibodies bind?\nA. Desmosomes\nB. Gap junctions\nC. Hemidesmosomes\nD. Tight junctions\nChoose the correct option.",
"image": null
},
{
"idx": 75,
"question": "A 65-year-old woman comes to the physician for a routine bone mineral density screening. She does not have any children. Menopause was at age 55. Her mother died of breast cancer at the age of 48 years. She has hypertension for which she takes ramipril. Dual-energy x-ray absorptiometry at the femoral neck shows a T-score of -2.7 SD. The physician considers treatment with raloxifene. This medication would put her at increased risk of developing which of the following conditions?\nA. Pulmonary embolism\nB. Cellulitis\nC. Breast cancer\nD. Hypercholesterolemia\n\nA. Pulmonary embolism\nB. Cellulitis\nC. Breast cancer\nD. Hypercholesterolemia",
"options": [
"A. Pulmonary embolism",
"B. Cellulitis",
"C. Breast cancer",
"D. Hypercholesterolemia"
],
"answer": "Pulmonary embolism",
"gen_text_store": "",
"pid": "75",
"query": "A 65-year-old woman comes to the physician for a routine bone mineral density screening. She does not have any children. Menopause was at age 55. Her mother died of breast cancer at the age of 48 years. She has hypertension for which she takes ramipril. Dual-energy x-ray absorptiometry at the femoral neck shows a T-score of -2.7 SD. The physician considers treatment with raloxifene. This medication would put her at increased risk of developing which of the following conditions?\nA. Pulmonary embolism\nB. Cellulitis\nC. Breast cancer\nD. Hypercholesterolemia\nChoose the correct option.",
"image": null
},
{
"idx": 76,
"question": "A 44-year-old man comes to the clinic because of a 6-month history of progressive fatigue. He has a history of intravenous heroin use. Physical examination shows scleral icterus. A serum study is positive for hepatitis C RNA. Therapy with interferon-α is initiated in combination with a second drug. The expected beneficial effect of the additional drug is most likely due to inhibition of which of the following enzymes?\nA. Inosine monophosphate dehydrogenase\nB. DNA-dependent RNA polymerase\nC. DNA gyrase\nD. Dihydroorotate dehydrogenase\n\nA. Inosine monophosphate dehydrogenase\nB. DNA-dependent RNA polymerase\nC. DNA gyrase\nD. Dihydroorotate dehydrogenase",
"options": [
"A. Inosine monophosphate dehydrogenase",
"B. DNA-dependent RNA polymerase",
"C. DNA gyrase",
"D. Dihydroorotate dehydrogenase"
],
"answer": "Inosine monophosphate dehydrogenase",
"gen_text_store": "",
"pid": "76",
"query": "A 44-year-old man comes to the clinic because of a 6-month history of progressive fatigue. He has a history of intravenous heroin use. Physical examination shows scleral icterus. A serum study is positive for hepatitis C RNA. Therapy with interferon-α is initiated in combination with a second drug. The expected beneficial effect of the additional drug is most likely due to inhibition of which of the following enzymes?\nA. Inosine monophosphate dehydrogenase\nB. DNA-dependent RNA polymerase\nC. DNA gyrase\nD. Dihydroorotate dehydrogenase\nChoose the correct option.",
"image": null
},
{
"idx": 77,
"question": "A 51-year-old man is brought to the physician by his wife because of a 3-week history of abnormal behavior. His wife reports he has been preoccupied with gambling at the local casino. He becomes restless and irritable when his wife attempts to restrict his gambling. Four months ago, he was diagnosed with Parkinson disease and treatment was initiated. Which of the following best describes the mechanism of action of the drug that was most likely prescribed for this patient?\nA. Peripheral inhibition of DOPA decarboxylase\nB. Direct activation of dopamine receptors\nC. Selective inhibition of monoamine oxidase B\nD. Inhibition of catechol-O-methyl transferase\n\nA. Peripheral inhibition of DOPA decarboxylase\nB. Direct activation of dopamine receptors\nC. Selective inhibition of monoamine oxidase B\nD. Inhibition of catechol-O-methyl transferase",
"options": [
"A. Peripheral inhibition of DOPA decarboxylase",
"B. Direct activation of dopamine receptors",
"C. Selective inhibition of monoamine oxidase B",
"D. Inhibition of catechol-O-methyl transferase"
],
"answer": "Direct activation of dopamine receptors",
"gen_text_store": "",
"pid": "77",
"query": "A 51-year-old man is brought to the physician by his wife because of a 3-week history of abnormal behavior. His wife reports he has been preoccupied with gambling at the local casino. He becomes restless and irritable when his wife attempts to restrict his gambling. Four months ago, he was diagnosed with Parkinson disease and treatment was initiated. Which of the following best describes the mechanism of action of the drug that was most likely prescribed for this patient?\nA. Peripheral inhibition of DOPA decarboxylase\nB. Direct activation of dopamine receptors\nC. Selective inhibition of monoamine oxidase B\nD. Inhibition of catechol-O-methyl transferase\nChoose the correct option.",
"image": null
},
{
"idx": 78,
"question": "A 44-year-old woman with hypothyroidism comes to the physician because of a 1-month history of tingling in her feet and poor balance. Her only medication is levothyroxine. Physical examination shows conjunctival pallor and an ataxic gait. Proprioception and sense of vibration are decreased in her toes bilaterally. Laboratory studies show macrocytic anemia and normal thyroid hormone levels. Histological evaluation of tissue samples obtained by esophagogastroduodenoscopy reveals atrophic changes of the gastric body and fundus with normal antral mucosa. Which of the following structures is most likely being targeted by antibodies in this patient?\nA. Islet cell cytoplasm\nB. Deamidated gliadin peptide\nC. Parietal cells\nD. Smooth muscle\n\nA. Islet cell cytoplasm\nB. Deamidated gliadin peptide\nC. Parietal cells\nD. Smooth muscle",
"options": [
"A. Islet cell cytoplasm",
"B. Deamidated gliadin peptide",
"C. Parietal cells",
"D. Smooth muscle"
],
"answer": "Parietal cells",
"gen_text_store": "",
"pid": "78",
"query": "A 44-year-old woman with hypothyroidism comes to the physician because of a 1-month history of tingling in her feet and poor balance. Her only medication is levothyroxine. Physical examination shows conjunctival pallor and an ataxic gait. Proprioception and sense of vibration are decreased in her toes bilaterally. Laboratory studies show macrocytic anemia and normal thyroid hormone levels. Histological evaluation of tissue samples obtained by esophagogastroduodenoscopy reveals atrophic changes of the gastric body and fundus with normal antral mucosa. Which of the following structures is most likely being targeted by antibodies in this patient?\nA. Islet cell cytoplasm\nB. Deamidated gliadin peptide\nC. Parietal cells\nD. Smooth muscle\nChoose the correct option.",
"image": null
},
{
"idx": 79,
"question": "A 45-year-old man comes to his primary-care doctor with his wife for a 4-week history of constipation. The patient reports that his bowel habits have changed from every day to every 3 or 4 days. He also now has to strain to pass stool. On further questioning, his wife has also noticed that he has seemed fatigued, with little interest in going on their usual afternoon walks. Medical history is notable for hypertension and hyperlipidemia, both managed medically. He was last seen for follow-up of these conditions 1 month ago. Physical examination is unremarkable. Which of the following is the cellular target of the medicine that is most likely responsible for this patient's symptoms?\nA. Angiotensin-II receptors in the membranes of vascular smooth muscle cells\nB. Angiotensin-converting enzyme\nC. Na+/Cl- cotransporter in the membranes of epithelial cells in the distal convoluted tubule\nD. Na+/K+/2Cl- transporters in the membranes of epithelial cells in the ascending loop of Henle\n\nA. Angiotensin-II receptors in the membranes of vascular smooth muscle cells\nB. Angiotensin-converting enzyme\nC. Na+/Cl- cotransporter in the membranes of epithelial cells in the distal convoluted tubule\nD. Na+/K+/2Cl- transporters in the membranes of epithelial cells in the ascending loop of Henle",
"options": [
"A. Angiotensin-II receptors in the membranes of vascular smooth muscle cells",
"B. Angiotensin-converting enzyme",
"C. Na+/Cl- cotransporter in the membranes of epithelial cells in the distal convoluted tubule",
"D. Na+/K+/2Cl- transporters in the membranes of epithelial cells in the ascending loop of Henle"
],
"answer": "Na+/Cl- cotransporter in the membranes of epithelial cells in the distal convoluted tubule",
"gen_text_store": "",
"pid": "79",
"query": "A 45-year-old man comes to his primary-care doctor with his wife for a 4-week history of constipation. The patient reports that his bowel habits have changed from every day to every 3 or 4 days. He also now has to strain to pass stool. On further questioning, his wife has also noticed that he has seemed fatigued, with little interest in going on their usual afternoon walks. Medical history is notable for hypertension and hyperlipidemia, both managed medically. He was last seen for follow-up of these conditions 1 month ago. Physical examination is unremarkable. Which of the following is the cellular target of the medicine that is most likely responsible for this patient's symptoms?\nA. Angiotensin-II receptors in the membranes of vascular smooth muscle cells\nB. Angiotensin-converting enzyme\nC. Na+/Cl- cotransporter in the membranes of epithelial cells in the distal convoluted tubule\nD. Na+/K+/2Cl- transporters in the membranes of epithelial cells in the ascending loop of Henle\nChoose the correct option.",
"image": null
},
{
"idx": 80,
"question": "A medical student decides to join an immunology research center, which specifically works on capsular polysaccharide vaccine development against bacteria, such as Haemophilus influenzae type b (Hib), Neisseria meningitidis, and Streptococcus pneumoniae. As a member of a research team working on the Hib vaccine, he asks his senior colleague why capsular polysaccharides are conjugated to protein carriers like tetanus toxoid during vaccine development. Which of the following is the best response to this question?\nA. Conjugation with a protein carrier generates IgG2 dominant antibody responses\nB. Conjugation with a protein carrier generates IgM dominant antibody responses\nC. Conjugation with a protein carrier improves vaccine stability\nD. Conjugation with a protein carrier provides effective protection to infants\n\nA. Conjugation with a protein carrier generates IgG2 dominant antibody responses\nB. Conjugation with a protein carrier generates IgM dominant antibody responses\nC. Conjugation with a protein carrier improves vaccine stability\nD. Conjugation with a protein carrier provides effective protection to infants",
"options": [
"A. Conjugation with a protein carrier generates IgG2 dominant antibody responses",
"B. Conjugation with a protein carrier generates IgM dominant antibody responses",
"C. Conjugation with a protein carrier improves vaccine stability",
"D. Conjugation with a protein carrier provides effective protection to infants"
],
"answer": "Conjugation with a protein carrier provides effective protection to infants",
"gen_text_store": "",
"pid": "80",
"query": "A medical student decides to join an immunology research center, which specifically works on capsular polysaccharide vaccine development against bacteria, such as Haemophilus influenzae type b (Hib), Neisseria meningitidis, and Streptococcus pneumoniae. As a member of a research team working on the Hib vaccine, he asks his senior colleague why capsular polysaccharides are conjugated to protein carriers like tetanus toxoid during vaccine development. Which of the following is the best response to this question?\nA. Conjugation with a protein carrier generates IgG2 dominant antibody responses\nB. Conjugation with a protein carrier generates IgM dominant antibody responses\nC. Conjugation with a protein carrier improves vaccine stability\nD. Conjugation with a protein carrier provides effective protection to infants\nChoose the correct option.",
"image": null
},
{
"idx": 81,
"question": "A 58-year-old woman comes to the physician because of a 3-month history of left knee pain as well as stiffness upon waking for about 10–15 minutes. The pain is worse after standing a lot at work and when she climbs stairs. There is no history of trauma. She has hypercholesterolemia and hypertension. Her mother died of metastatic breast cancer 15 years ago, at the age of 65 years. She does not smoke or drink alcohol. Current medications include atorvastatin, labetalol, and aspirin. Over the past 2 months, she has been taking over-the-counter ibuprofen as needed for the joint pain. She is 163 cm (5 ft 4 in) tall and weighs 84 kg (185 lb); BMI is 31.8 kg/m2. Her temperature is 37°C (98.6°F), pulse is 88/min, and blood pressure is 114/68 mm Hg. Examination of the left knee shows tenderness on palpation of the anteromedial joint line; there is crepitus and pain with full flexion and extension. Serum uric acid concentration is 8.0 mg/dL and erythrocyte sedimentation rate is 15 mm/h. Which of the following is the most likely finding on imaging of the left knee?\nA. Osteophytes with joint-space narrowing on x-ray\nB. Diffuse lytic-sclerotic bone lesions on x-ray\nC. Joint effusion and pannus on ultrasound\nD. Fluid-filled pouch on ultrasound\n\nA. Osteophytes with joint-space narrowing on x-ray\nB. Diffuse lytic-sclerotic bone lesions on x-ray\nC. Joint effusion and pannus on ultrasound\nD. Fluid-filled pouch on ultrasound",
"options": [
"A. Osteophytes with joint-space narrowing on x-ray",
"B. Diffuse lytic-sclerotic bone lesions on x-ray",
"C. Joint effusion and pannus on ultrasound",
"D. Fluid-filled pouch on ultrasound"
],
"answer": "Osteophytes with joint-space narrowing on x-ray",
"gen_text_store": "",
"pid": "81",
"query": "A 58-year-old woman comes to the physician because of a 3-month history of left knee pain as well as stiffness upon waking for about 10–15 minutes. The pain is worse after standing a lot at work and when she climbs stairs. There is no history of trauma. She has hypercholesterolemia and hypertension. Her mother died of metastatic breast cancer 15 years ago, at the age of 65 years. She does not smoke or drink alcohol. Current medications include atorvastatin, labetalol, and aspirin. Over the past 2 months, she has been taking over-the-counter ibuprofen as needed for the joint pain. She is 163 cm (5 ft 4 in) tall and weighs 84 kg (185 lb); BMI is 31.8 kg/m2. Her temperature is 37°C (98.6°F), pulse is 88/min, and blood pressure is 114/68 mm Hg. Examination of the left knee shows tenderness on palpation of the anteromedial joint line; there is crepitus and pain with full flexion and extension. Serum uric acid concentration is 8.0 mg/dL and erythrocyte sedimentation rate is 15 mm/h. Which of the following is the most likely finding on imaging of the left knee?\nA. Osteophytes with joint-space narrowing on x-ray\nB. Diffuse lytic-sclerotic bone lesions on x-ray\nC. Joint effusion and pannus on ultrasound\nD. Fluid-filled pouch on ultrasound\nChoose the correct option.",
"image": null
},
{
"idx": 82,
"question": "An investigator is studying the growth pattern of a particular bacterial strain that caused a respiratory disease outbreak in children in rural Venezuela. The bacteria are found to be able to grow in a specialized culture that contains sheep blood, cystine, and potassium tellurite; the colonies are black and have a shining surface. The isolated bacteria are most likely which of the following?\nA. Legionella pneumophila\nB. Haemophilus influenzae\nC. Bordetella pertussis\nD. Corynebacterium diphtheriae\n\nA. Legionella pneumophila\nB. Haemophilus influenzae\nC. Bordetella pertussis\nD. Corynebacterium diphtheriae",
"options": [
"A. Legionella pneumophila",
"B. Haemophilus influenzae",
"C. Bordetella pertussis",
"D. Corynebacterium diphtheriae"
],
"answer": "Corynebacterium diphtheriae",
"gen_text_store": "",
"pid": "82",
"query": "An investigator is studying the growth pattern of a particular bacterial strain that caused a respiratory disease outbreak in children in rural Venezuela. The bacteria are found to be able to grow in a specialized culture that contains sheep blood, cystine, and potassium tellurite; the colonies are black and have a shining surface. The isolated bacteria are most likely which of the following?\nA. Legionella pneumophila\nB. Haemophilus influenzae\nC. Bordetella pertussis\nD. Corynebacterium diphtheriae\nChoose the correct option.",
"image": null
},
{
"idx": 83,
"question": "A 27-year-old graduate student is bitten by a coral snake while he was hiking alone through the woods and dies 2 hours later from respiratory failure. His body was discovered 7 hours later by a group of campers who promptly called the police. On arrival, the police found his body to be cold and stiff. Which of the following processes is responsible for the rigidity observed?\nA. Activation of muscle contraction by neurotoxins\nB. Effect of low temperature on muscle proteins\nC. Inhibition of cross-bridge cycling\nD. Depletion of intracellular calcium\n\nA. Activation of muscle contraction by neurotoxins\nB. Effect of low temperature on muscle proteins\nC. Inhibition of cross-bridge cycling\nD. Depletion of intracellular calcium",
"options": [
"A. Activation of muscle contraction by neurotoxins",
"B. Effect of low temperature on muscle proteins",
"C. Inhibition of cross-bridge cycling",
"D. Depletion of intracellular calcium"
],
"answer": "Inhibition of cross-bridge cycling",
"gen_text_store": "",
"pid": "83",
"query": "A 27-year-old graduate student is bitten by a coral snake while he was hiking alone through the woods and dies 2 hours later from respiratory failure. His body was discovered 7 hours later by a group of campers who promptly called the police. On arrival, the police found his body to be cold and stiff. Which of the following processes is responsible for the rigidity observed?\nA. Activation of muscle contraction by neurotoxins\nB. Effect of low temperature on muscle proteins\nC. Inhibition of cross-bridge cycling\nD. Depletion of intracellular calcium\nChoose the correct option.",
"image": null
},
{
"idx": 84,
"question": "A 31-year-old G1-P0 woman at 28-weeks gestation presents with shortness of breath and nonspecific right-sided chest pain that is worse with inspiration. She works as a graduate student at the local university, and she informs you that she recently returned to the west coast from a trip to New York for an Economics conference. Her medical history is positive only for frequent bouts of sinusitis. She currently denies any smoking, drinks a glass of red wine/day, and she denies any past illicit drug use. The vital signs include: temperature 36.7°C (98.0°F), blood pressure 126/74 mm Hg, heart rate 87/min, and respiratory rate 23/min. Her physical examination shows decreased air movement throughout the right lung but otherwise clear lungs on auscultation, grade 2/6 holosystolic murmur, and a gravid uterus without acute findings. On physical examination, she is afebrile, tachycardic to 121/min, normotensive, and demonstrates an O2 saturation of 92%. Which of the following is the best next step in the evaluation of the most likely diagnosis for this patient?\nA. ECG\nB. Chest radiography\nC. V/Q scan\nD. CT pulmonary angiogram\n\nA. ECG\nB. Chest radiography\nC. V/Q scan\nD. CT pulmonary angiogram",
"options": [
"A. ECG",
"B. Chest radiography",
"C. V/Q scan",
"D. CT pulmonary angiogram"
],
"answer": "V/Q scan",
"gen_text_store": "",
"pid": "84",
"query": "A 31-year-old G1-P0 woman at 28-weeks gestation presents with shortness of breath and nonspecific right-sided chest pain that is worse with inspiration. She works as a graduate student at the local university, and she informs you that she recently returned to the west coast from a trip to New York for an Economics conference. Her medical history is positive only for frequent bouts of sinusitis. She currently denies any smoking, drinks a glass of red wine/day, and she denies any past illicit drug use. The vital signs include: temperature 36.7°C (98.0°F), blood pressure 126/74 mm Hg, heart rate 87/min, and respiratory rate 23/min. Her physical examination shows decreased air movement throughout the right lung but otherwise clear lungs on auscultation, grade 2/6 holosystolic murmur, and a gravid uterus without acute findings. On physical examination, she is afebrile, tachycardic to 121/min, normotensive, and demonstrates an O2 saturation of 92%. Which of the following is the best next step in the evaluation of the most likely diagnosis for this patient?\nA. ECG\nB. Chest radiography\nC. V/Q scan\nD. CT pulmonary angiogram\nChoose the correct option.",
"image": null
},
{
"idx": 85,
"question": "A 25-year-old woman comes to the physician because of periodic painful double vision for 3 days. Her symptoms occur only when looking sideways. She has myopia and has been wearing corrective lenses for 10 years. Ten days ago, she lost her balance and fell off her bike, for which she went to a hospital. A CT scan of the head at that time showed no abnormalities and she was released without further treatment. Her only medication is an oral contraceptive. Her vital signs are within normal limits. The pupils are equal and reactive to light. Her best corrected visual acuity is 20/40 in each eye. She has an adduction deficit in the right eye and nystagmus in the left eye when looking left; she has an adduction deficit in the left eye and nystagmus in the right eye when looking right. Fundoscopy reveals bilateral disc hyperemia. Which of the following is the most likely cause of this patient's findings?\nA. Demyelination of the medial longitudinal fasciculus\nB. Compressive tumor of the pons\nC. Oxidative damage due to thiamine deficiency\nD. Infarction of the brainstem\n\nA. Demyelination of the medial longitudinal fasciculus\nB. Compressive tumor of the pons\nC. Oxidative damage due to thiamine deficiency\nD. Infarction of the brainstem",
"options": [
"A. Demyelination of the medial longitudinal fasciculus",
"B. Compressive tumor of the pons",
"C. Oxidative damage due to thiamine deficiency",
"D. Infarction of the brainstem"
],
"answer": "Demyelination of the medial longitudinal fasciculus",
"gen_text_store": "",
"pid": "85",
"query": "A 25-year-old woman comes to the physician because of periodic painful double vision for 3 days. Her symptoms occur only when looking sideways. She has myopia and has been wearing corrective lenses for 10 years. Ten days ago, she lost her balance and fell off her bike, for which she went to a hospital. A CT scan of the head at that time showed no abnormalities and she was released without further treatment. Her only medication is an oral contraceptive. Her vital signs are within normal limits. The pupils are equal and reactive to light. Her best corrected visual acuity is 20/40 in each eye. She has an adduction deficit in the right eye and nystagmus in the left eye when looking left; she has an adduction deficit in the left eye and nystagmus in the right eye when looking right. Fundoscopy reveals bilateral disc hyperemia. Which of the following is the most likely cause of this patient's findings?\nA. Demyelination of the medial longitudinal fasciculus\nB. Compressive tumor of the pons\nC. Oxidative damage due to thiamine deficiency\nD. Infarction of the brainstem\nChoose the correct option.",
"image": null
},
{
"idx": 86,
"question": "A 45-year-old man comes to the physician because of mild left-sided abdominal pain when lifting heavy objects that has developed over the past 6 months. He has had a weight loss of 41 kgs (90 lbs) in the past year. Physical examination shows a soft bulge inferior and lateral to the navel on the left. A CT scan of the abdomen of a patient with the same condition is shown. Which of the following muscles is located directly medial to the pathology seen on the CT scan?\nA. Psoas major\nB. External oblique\nC. Rectus abdominis\nD. Transverse abdominal\n\"\n\nA. Psoas major\nB. External oblique\nC. Rectus abdominis\nD. Transverse abdominal\n\"",
"options": [
"A. Psoas major",
"B. External oblique",
"C. Rectus abdominis",
"D. Transverse abdominal\n\""
],
"answer": "Rectus abdominis",
"gen_text_store": "",
"pid": "86",
"query": "A 45-year-old man comes to the physician because of mild left-sided abdominal pain when lifting heavy objects that has developed over the past 6 months. He has had a weight loss of 41 kgs (90 lbs) in the past year. Physical examination shows a soft bulge inferior and lateral to the navel on the left. A CT scan of the abdomen of a patient with the same condition is shown. Which of the following muscles is located directly medial to the pathology seen on the CT scan?\nA. Psoas major\nB. External oblique\nC. Rectus abdominis\nD. Transverse abdominal\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 87,
"question": "An 11-year-old boy presents to your office with pitting edema and proteinuria exceeding 3.5g in 24 hours. You suspect that this patient has experienced a loss of polyanions in his glomerular basement membranes. Which of the following findings would confirm your diagnosis?\nA. WBC casts in the urine\nB. Selective albuminuria\nC. Negatively birefringent crystals in the urine\nD. Bence-Jones proteinuria\n\nA. WBC casts in the urine\nB. Selective albuminuria\nC. Negatively birefringent crystals in the urine\nD. Bence-Jones proteinuria",
"options": [
"A. WBC casts in the urine",
"B. Selective albuminuria",
"C. Negatively birefringent crystals in the urine",
"D. Bence-Jones proteinuria"
],
"answer": "Selective albuminuria",
"gen_text_store": "",
"pid": "87",
"query": "An 11-year-old boy presents to your office with pitting edema and proteinuria exceeding 3.5g in 24 hours. You suspect that this patient has experienced a loss of polyanions in his glomerular basement membranes. Which of the following findings would confirm your diagnosis?\nA. WBC casts in the urine\nB. Selective albuminuria\nC. Negatively birefringent crystals in the urine\nD. Bence-Jones proteinuria\nChoose the correct option.",
"image": null
},
{
"idx": 88,
"question": "A 24-year-old woman comes to the physician because of 1-day history of nausea and weakness. She has no history of serious illness. She is sexually active with 2 male partners and uses an oral contraceptive; she uses condoms inconsistently. Her last menstrual period was 4 days ago. Her temperature is 37.8°C (100°F), pulse is 88/min, respirations are 18/min, and blood pressure is 115/70 mm Hg. Physical examination shows right costovertebral angle tenderness. The abdomen is soft and nontender. Cardiopulmonary examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14 g/dL\nLeukocyte count 13,000/mm3\nPlatelet count 250,000/mm3\nSerum\nUrea nitrogen 18 mg/dL\nCreatinine 0.8 mg/dL\nGlucose 95 mg/dL\nC-reactive protein 16.4 mg/L (N=0.08–3.1)\nWhich of the following is the most appropriate next step in management?\"\nA. Urinalysis\nB. Cervical swab\nC. Blood culture\nD. CT scan of the abdomen\n\"\n\nA. Urinalysis\nB. Cervical swab\nC. Blood culture\nD. CT scan of the abdomen\n\"",
"options": [
"A. Urinalysis",
"B. Cervical swab",
"C. Blood culture",
"D. CT scan of the abdomen\n\""
],
"answer": "Urinalysis",
"gen_text_store": "",
"pid": "88",
"query": "A 24-year-old woman comes to the physician because of 1-day history of nausea and weakness. She has no history of serious illness. She is sexually active with 2 male partners and uses an oral contraceptive; she uses condoms inconsistently. Her last menstrual period was 4 days ago. Her temperature is 37.8°C (100°F), pulse is 88/min, respirations are 18/min, and blood pressure is 115/70 mm Hg. Physical examination shows right costovertebral angle tenderness. The abdomen is soft and nontender. Cardiopulmonary examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14 g/dL\nLeukocyte count 13,000/mm3\nPlatelet count 250,000/mm3\nSerum\nUrea nitrogen 18 mg/dL\nCreatinine 0.8 mg/dL\nGlucose 95 mg/dL\nC-reactive protein 16.4 mg/L (N=0.08–3.1)\nWhich of the following is the most appropriate next step in management?\"\nA. Urinalysis\nB. Cervical swab\nC. Blood culture\nD. CT scan of the abdomen\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 89,
"question": "A 55-year-old nulligravid woman comes to the physician because of a 3-day history of heavy vaginal bleeding, requiring more than 5 pads per day. Menopause occurred 1 year ago. She attained menarche at 10 years of age. She has a history of hypothyroidism and type 2 diabetes mellitus. She has smoked 1 pack of cigarettes daily for 20 years but quit 5 years ago. Current medications include levothyroxine and metformin. She is 165 cm (5 ft 5 in) tall and weighs 86 kg (190 lb); BMI is 32 kg/m2. Physical examination shows mild vaginal atrophy and a normal cervix. The uterus and adnexa are nontender to palpation. Transvaginal ultrasonography shows an endometrial thickness of 6 mm. Endometrial biopsy shows non-invasive proliferation of endometrial glands with no nuclear or cytological atypia. Which of the following is the most appropriate next step in management?\nA. Total hysterectomy\nB. Estrogen vaginal cream\nC. Reassurance and follow-up\nD. Progestin therapy\n\nA. Total hysterectomy\nB. Estrogen vaginal cream\nC. Reassurance and follow-up\nD. Progestin therapy",
"options": [
"A. Total hysterectomy",
"B. Estrogen vaginal cream",
"C. Reassurance and follow-up",
"D. Progestin therapy"
],
"answer": "Progestin therapy",
"gen_text_store": "",
"pid": "89",
"query": "A 55-year-old nulligravid woman comes to the physician because of a 3-day history of heavy vaginal bleeding, requiring more than 5 pads per day. Menopause occurred 1 year ago. She attained menarche at 10 years of age. She has a history of hypothyroidism and type 2 diabetes mellitus. She has smoked 1 pack of cigarettes daily for 20 years but quit 5 years ago. Current medications include levothyroxine and metformin. She is 165 cm (5 ft 5 in) tall and weighs 86 kg (190 lb); BMI is 32 kg/m2. Physical examination shows mild vaginal atrophy and a normal cervix. The uterus and adnexa are nontender to palpation. Transvaginal ultrasonography shows an endometrial thickness of 6 mm. Endometrial biopsy shows non-invasive proliferation of endometrial glands with no nuclear or cytological atypia. Which of the following is the most appropriate next step in management?\nA. Total hysterectomy\nB. Estrogen vaginal cream\nC. Reassurance and follow-up\nD. Progestin therapy\nChoose the correct option.",
"image": null
},
{
"idx": 90,
"question": "A 62-year-old woman with a history of hypertension and type 2 diabetes mellitus comes to the physician for a routine health maintenance examination. She has smoked 1 pack of cigarettes daily for the last 15 years. Current medications include glyburide and amlodipine. The physician prescribes a medication that decreases the production of mevalonate. Which of the following changes to the serum is most likely to develop as an adverse effect of the prescribed drug?\nA. Increased creatine kinase concentration\nB. Decreased glucose concentration\nC. Increased triglyceride concentration\nD. Increased bradykinin concentration\n\nA. Increased creatine kinase concentration\nB. Decreased glucose concentration\nC. Increased triglyceride concentration\nD. Increased bradykinin concentration",
"options": [
"A. Increased creatine kinase concentration",
"B. Decreased glucose concentration",
"C. Increased triglyceride concentration",
"D. Increased bradykinin concentration"
],
"answer": "Increased creatine kinase concentration",
"gen_text_store": "",
"pid": "90",
"query": "A 62-year-old woman with a history of hypertension and type 2 diabetes mellitus comes to the physician for a routine health maintenance examination. She has smoked 1 pack of cigarettes daily for the last 15 years. Current medications include glyburide and amlodipine. The physician prescribes a medication that decreases the production of mevalonate. Which of the following changes to the serum is most likely to develop as an adverse effect of the prescribed drug?\nA. Increased creatine kinase concentration\nB. Decreased glucose concentration\nC. Increased triglyceride concentration\nD. Increased bradykinin concentration\nChoose the correct option.",
"image": null
},
{
"idx": 91,
"question": "A 28-year-old man is brought to the emergency department because of a 3-day history of fever, chills, and generalized weakness. He has no cough. He was treated for a neck abscess 6 months ago. He takes no medications. He has smoked one pack of cigarettes daily for 10 years and drinks two to three beers daily. He has been using intravenous cocaine and heroin for 6 years. He appears ill. His temperature is 38.6°C (101.5°F), pulse is 112/min, respirations are 20/min, and blood pressure is 110/70 mm Hg. Examination shows track marks on both cubital fossae. There are retinal hemorrhages with pale centers. The lungs are clear to auscultation. A grade 3/6 holosystolic murmur is heard best at the lower left sternal border. Laboratory studies show:\nHemoglobin 13.3 g/dL\nLeukocyte count 14,300/mm3\nPlatelet count 278,000/mm3\nSerum\nGlucose 96 mg/dL\nCreatinine 1.0 mg/dL\nTotal bilirubin 0.4 mg/dL\nAST 18 U/L\nALT 22 U/L\nTransthoracic echocardiography shows multiple vegetations on the tricuspid valve and moderate tricuspid regurgitation. Two sets of blood cultures are collected. Which of the following is the most appropriate next step in management?\"\nA. Transesophageal echocardiography\nB. Intravenous vancomycin therapy\nC. X-ray of the chest\nD. CT pulmonary angiogram\n\nA. Transesophageal echocardiography\nB. Intravenous vancomycin therapy\nC. X-ray of the chest\nD. CT pulmonary angiogram",
"options": [
"A. Transesophageal echocardiography",
"B. Intravenous vancomycin therapy",
"C. X-ray of the chest",
"D. CT pulmonary angiogram"
],
"answer": "Intravenous vancomycin therapy",
"gen_text_store": "",
"pid": "91",
"query": "A 28-year-old man is brought to the emergency department because of a 3-day history of fever, chills, and generalized weakness. He has no cough. He was treated for a neck abscess 6 months ago. He takes no medications. He has smoked one pack of cigarettes daily for 10 years and drinks two to three beers daily. He has been using intravenous cocaine and heroin for 6 years. He appears ill. His temperature is 38.6°C (101.5°F), pulse is 112/min, respirations are 20/min, and blood pressure is 110/70 mm Hg. Examination shows track marks on both cubital fossae. There are retinal hemorrhages with pale centers. The lungs are clear to auscultation. A grade 3/6 holosystolic murmur is heard best at the lower left sternal border. Laboratory studies show:\nHemoglobin 13.3 g/dL\nLeukocyte count 14,300/mm3\nPlatelet count 278,000/mm3\nSerum\nGlucose 96 mg/dL\nCreatinine 1.0 mg/dL\nTotal bilirubin 0.4 mg/dL\nAST 18 U/L\nALT 22 U/L\nTransthoracic echocardiography shows multiple vegetations on the tricuspid valve and moderate tricuspid regurgitation. Two sets of blood cultures are collected. Which of the following is the most appropriate next step in management?\"\nA. Transesophageal echocardiography\nB. Intravenous vancomycin therapy\nC. X-ray of the chest\nD. CT pulmonary angiogram\nChoose the correct option.",
"image": null
},
{
"idx": 92,
"question": "A 54-year-old man comes to the emergency department because of a 2-day history of increasingly severe abdominal pain, nausea, and bilious vomiting. His last bowel movement was yesterday and he has not passed flatus since then. He underwent appendectomy at the age of 39. He has psoriasis, hypertension, type 2 diabetes mellitus, and chronic back pain. He drinks two beers daily. He takes a topical corticosteroid, ramipril, metformin, and ibuprofen daily. He is 176 cm (5 ft 9 in) tall and weighs 108 kg (240 lb); BMI is 35.4 kg/m2. His temperature is 36.8°C (98.4°F), respirations are 15/min, pulse is 90/min, and blood pressure is 112/67 mm Hg. Examination shows thick, scaly, plaques over both elbows and knees. Abdominal examination shows three well-healed laparoscopic scars. The abdomen is distended and there are frequent, high-pitched bowel sounds on auscultation. Digital rectal examination shows an empty rectum. Laboratory studies show:\nHematocrit 44%\nLeukocyte count 9,000/mm3\nPlatelet count 225,000/mm3\nSerum\nNa+ 139 mEq/L\nK+ 4.1 mEq/L\nCl− 101 mEq/L\nHCO3− 26 mEq/L\nGlucose 95 mg/dL\nCreatinine 1.1 mg/dL\nAlkaline phosphatase 78 U/L\nAspartate aminotransferase (AST, GOT) 19 U/L\nAlanine aminotransferase (ALT, GPT) 14 U/L\nγ-Glutamyltransferase (GGT) 52 U/L (N=5–50 U/L)\nHemoglobin A1C 6.4%\nAbdominal ultrasound shows nonpropulsive peristalsis of the small bowel. Which of the following is the most likely cause of this patient's condition?\"\nA. Chronic inflammatory bowel disease\nB. Ibuprofen\nC. History of abdominal surgery\nD. Alcohol\n\nA. Chronic inflammatory bowel disease\nB. Ibuprofen\nC. History of abdominal surgery\nD. Alcohol",
"options": [
"A. Chronic inflammatory bowel disease",
"B. Ibuprofen",
"C. History of abdominal surgery",
"D. Alcohol"
],
"answer": "History of abdominal surgery",
"gen_text_store": "",
"pid": "92",
"query": "A 54-year-old man comes to the emergency department because of a 2-day history of increasingly severe abdominal pain, nausea, and bilious vomiting. His last bowel movement was yesterday and he has not passed flatus since then. He underwent appendectomy at the age of 39. He has psoriasis, hypertension, type 2 diabetes mellitus, and chronic back pain. He drinks two beers daily. He takes a topical corticosteroid, ramipril, metformin, and ibuprofen daily. He is 176 cm (5 ft 9 in) tall and weighs 108 kg (240 lb); BMI is 35.4 kg/m2. His temperature is 36.8°C (98.4°F), respirations are 15/min, pulse is 90/min, and blood pressure is 112/67 mm Hg. Examination shows thick, scaly, plaques over both elbows and knees. Abdominal examination shows three well-healed laparoscopic scars. The abdomen is distended and there are frequent, high-pitched bowel sounds on auscultation. Digital rectal examination shows an empty rectum. Laboratory studies show:\nHematocrit 44%\nLeukocyte count 9,000/mm3\nPlatelet count 225,000/mm3\nSerum\nNa+ 139 mEq/L\nK+ 4.1 mEq/L\nCl− 101 mEq/L\nHCO3− 26 mEq/L\nGlucose 95 mg/dL\nCreatinine 1.1 mg/dL\nAlkaline phosphatase 78 U/L\nAspartate aminotransferase (AST, GOT) 19 U/L\nAlanine aminotransferase (ALT, GPT) 14 U/L\nγ-Glutamyltransferase (GGT) 52 U/L (N=5–50 U/L)\nHemoglobin A1C 6.4%\nAbdominal ultrasound shows nonpropulsive peristalsis of the small bowel. Which of the following is the most likely cause of this patient's condition?\"\nA. Chronic inflammatory bowel disease\nB. Ibuprofen\nC. History of abdominal surgery\nD. Alcohol\nChoose the correct option.",
"image": null
},
{
"idx": 93,
"question": "A 36-year-old woman presents with increased tiredness and lethargy for the past 4 weeks. Investigations show her hemoglobin level to be 8.6 gm/dL and serum creatinine of 4.6 mg/dL. The serum is negative for antinuclear antibodies (ANA) and positive for C3 nephritic factor. Urinalysis shows a 3+ proteinuria. The renal biopsy demonstrates hypercellular glomerulus with electron dense deposits along the glomerular basement membrane. What is the most likely cause?\nA. Membrano proliferative glomerulonephritis (MPGN)\nB. Rapidly progressive glomerulonephritis (RPGN)\nC. Minimal change disease\nD. Membranous glomerulonephritis (MGN)\n\nA. Membrano proliferative glomerulonephritis (MPGN)\nB. Rapidly progressive glomerulonephritis (RPGN)\nC. Minimal change disease\nD. Membranous glomerulonephritis (MGN)",
"options": [
"A. Membrano proliferative glomerulonephritis (MPGN)",
"B. Rapidly progressive glomerulonephritis (RPGN)",
"C. Minimal change disease",
"D. Membranous glomerulonephritis (MGN)"
],
"answer": "Membrano proliferative glomerulonephritis (MPGN)",
"gen_text_store": "",
"pid": "93",
"query": "A 36-year-old woman presents with increased tiredness and lethargy for the past 4 weeks. Investigations show her hemoglobin level to be 8.6 gm/dL and serum creatinine of 4.6 mg/dL. The serum is negative for antinuclear antibodies (ANA) and positive for C3 nephritic factor. Urinalysis shows a 3+ proteinuria. The renal biopsy demonstrates hypercellular glomerulus with electron dense deposits along the glomerular basement membrane. What is the most likely cause?\nA. Membrano proliferative glomerulonephritis (MPGN)\nB. Rapidly progressive glomerulonephritis (RPGN)\nC. Minimal change disease\nD. Membranous glomerulonephritis (MGN)\nChoose the correct option.",
"image": null
},
{
"idx": 94,
"question": "A 50-year-old man visits his physician after 20 years of not seeking any medical care. He is concerned about his health after a colleague recently had a heart attack. The patient has no active complaints and says he feels healthy; however, he does not exercise regularly and lives a sedentary lifestyle. He is employed as an administrative position at a local college, and is seated at a desk most of the day. His father had a heart attack at age 54 and his mother is still alive with no health concerns. He does not smoke, only drinks socially, and does not use drugs. Today, his blood pressure is 130/90 mm Hg, pulse is 84/min, and respiratory rate is 14/min. Physical examination reveals an obese male with no significant findings. An ECG shows no abnormalities, and laboratory testing shows the following:\nLaboratory test\nSerum glucose (fasting) 105 mg/dL\nSerum electrolytes \nSodium 142 mEq/L\nPotassium 3.9 mEq/L\nChloride 101 mEq/L\nSerum creatinine 0.8 mg/dl\nBlood urea nitrogen 10 mg/dl\nCholesterol, total 250 mg/dL\nHDL-cholesterol 35 mg/dL\nLDL-cholesterol 186 mg/dL\nTriglycerides 170 mg/dL\nUrinalysis \nGlucose negative\nKetones negative\nLeucocytes negative\nNitrites negative \nRed blood cells (RBC) negative \nCasts negative \nWhich of the following lab abnormalities in this patient is an indication for treatment?\nA. Blood pressure reading\nB. Patient’s weight\nC. High LDL-cholesterol\nD. Serum glucose level\n\nA. Blood pressure reading\nB. Patient’s weight\nC. High LDL-cholesterol\nD. Serum glucose level",
"options": [
"A. Blood pressure reading",
"B. Patient’s weight",
"C. High LDL-cholesterol",
"D. Serum glucose level"
],
"answer": "High LDL-cholesterol",
"gen_text_store": "",
"pid": "94",
"query": "A 50-year-old man visits his physician after 20 years of not seeking any medical care. He is concerned about his health after a colleague recently had a heart attack. The patient has no active complaints and says he feels healthy; however, he does not exercise regularly and lives a sedentary lifestyle. He is employed as an administrative position at a local college, and is seated at a desk most of the day. His father had a heart attack at age 54 and his mother is still alive with no health concerns. He does not smoke, only drinks socially, and does not use drugs. Today, his blood pressure is 130/90 mm Hg, pulse is 84/min, and respiratory rate is 14/min. Physical examination reveals an obese male with no significant findings. An ECG shows no abnormalities, and laboratory testing shows the following:\nLaboratory test\nSerum glucose (fasting) 105 mg/dL\nSerum electrolytes \nSodium 142 mEq/L\nPotassium 3.9 mEq/L\nChloride 101 mEq/L\nSerum creatinine 0.8 mg/dl\nBlood urea nitrogen 10 mg/dl\nCholesterol, total 250 mg/dL\nHDL-cholesterol 35 mg/dL\nLDL-cholesterol 186 mg/dL\nTriglycerides 170 mg/dL\nUrinalysis \nGlucose negative\nKetones negative\nLeucocytes negative\nNitrites negative \nRed blood cells (RBC) negative \nCasts negative \nWhich of the following lab abnormalities in this patient is an indication for treatment?\nA. Blood pressure reading\nB. Patient’s weight\nC. High LDL-cholesterol\nD. Serum glucose level\nChoose the correct option.",
"image": null
},
{
"idx": 95,
"question": "An investigator is studying the effect of drug X on the retinoblastoma (Rb) gene on chromosome 13 in endometrial cells. Endometrial cells obtained from study participants are plated on growth media and the distribution of cell cycle phase is measured with flow cytometry. Drug X, which is known to activate cyclin-dependent kinase 4, is administered to all the cells, and the distribution of cell cycle phase is measured again 1 hour later. Which of the following is most likely to result from the action of drug X on the Rb gene?\nA. G1 phase arrest\nB. Prophase I arrest\nC. Initiation of S phase\nD. Completion of G2 phase\n\nA. G1 phase arrest\nB. Prophase I arrest\nC. Initiation of S phase\nD. Completion of G2 phase",
"options": [
"A. G1 phase arrest",
"B. Prophase I arrest",
"C. Initiation of S phase",
"D. Completion of G2 phase"
],
"answer": "Initiation of S phase",
"gen_text_store": "",
"pid": "95",
"query": "An investigator is studying the effect of drug X on the retinoblastoma (Rb) gene on chromosome 13 in endometrial cells. Endometrial cells obtained from study participants are plated on growth media and the distribution of cell cycle phase is measured with flow cytometry. Drug X, which is known to activate cyclin-dependent kinase 4, is administered to all the cells, and the distribution of cell cycle phase is measured again 1 hour later. Which of the following is most likely to result from the action of drug X on the Rb gene?\nA. G1 phase arrest\nB. Prophase I arrest\nC. Initiation of S phase\nD. Completion of G2 phase\nChoose the correct option.",
"image": null
},
{
"idx": 96,
"question": "A 1-month-old girl is brought to the pediatrician by her parents. They are concerned that she becomes lethargic and irritated between meals. They found that feeding her often with small servings helps. She was born at 39 weeks via spontaneous vaginal delivery and is meeting all developmental milestones. Her mother has one brother that occasionally requires blood transfusions. Today, her blood pressure is 55/33 mm Hg, his heart rate is 120/min, respiratory rate is 40/min, and temperature of 37.0°C (98.6°F). On physical exam, the infant is irritated. She is slightly jaundiced. Her heart has a regular rate and rhythm and her lungs are clear to auscultation bilaterally. Her blood work shows normocytic anemia with elevated reticulocyte count and decreased haptoglobin. Sickle cell anemia and other hemoglobinopathies are also ruled out. A Coombs test is negative. Red blood cell osmotic fragility gap is normal. The physician determined that these findings are related to an enzyme deficiency. Which of the following allosterically inhibits this enzyme?\nA. Alanine\nB. Adenosine monophosphate\nC. Fructose 1,6-bisphosphate\nD. Fructose 2,6-bisphosphate\n\nA. Alanine\nB. Adenosine monophosphate\nC. Fructose 1,6-bisphosphate\nD. Fructose 2,6-bisphosphate",
"options": [
"A. Alanine",
"B. Adenosine monophosphate",
"C. Fructose 1,6-bisphosphate",
"D. Fructose 2,6-bisphosphate"
],
"answer": "Alanine",
"gen_text_store": "",
"pid": "96",
"query": "A 1-month-old girl is brought to the pediatrician by her parents. They are concerned that she becomes lethargic and irritated between meals. They found that feeding her often with small servings helps. She was born at 39 weeks via spontaneous vaginal delivery and is meeting all developmental milestones. Her mother has one brother that occasionally requires blood transfusions. Today, her blood pressure is 55/33 mm Hg, his heart rate is 120/min, respiratory rate is 40/min, and temperature of 37.0°C (98.6°F). On physical exam, the infant is irritated. She is slightly jaundiced. Her heart has a regular rate and rhythm and her lungs are clear to auscultation bilaterally. Her blood work shows normocytic anemia with elevated reticulocyte count and decreased haptoglobin. Sickle cell anemia and other hemoglobinopathies are also ruled out. A Coombs test is negative. Red blood cell osmotic fragility gap is normal. The physician determined that these findings are related to an enzyme deficiency. Which of the following allosterically inhibits this enzyme?\nA. Alanine\nB. Adenosine monophosphate\nC. Fructose 1,6-bisphosphate\nD. Fructose 2,6-bisphosphate\nChoose the correct option.",
"image": null
},
{
"idx": 97,
"question": "A 26-year-old woman comes to the clinic for an annual wellness examination. She is healthy with no prior history of significant illness. She exercises 3-4 times a week and eats a plant-based diet with no carbonated drinks. When asked if anything is bothering her, she reports that she has been having recurring episodes of sneezing, congestion, and itchy eyes for the past year. She denies any fever, sick contacts, cough, headaches, chest pain, urinary symptoms, or constipation/diarrhea during these episodes. She is told to take a medication to alleviate her symptoms as needed. What is the likely mechanism of action of the medication in question?\nA. Alpha-adrenergic agonist\nB. Competitive blockage of muscarinic receptors\nC. Disruption of disulfide bonds\nD. Short acting beta-2 agonist\n\nA. Alpha-adrenergic agonist\nB. Competitive blockage of muscarinic receptors\nC. Disruption of disulfide bonds\nD. Short acting beta-2 agonist",
"options": [
"A. Alpha-adrenergic agonist",
"B. Competitive blockage of muscarinic receptors",
"C. Disruption of disulfide bonds",
"D. Short acting beta-2 agonist"
],
"answer": "Alpha-adrenergic agonist",
"gen_text_store": "",
"pid": "97",
"query": "A 26-year-old woman comes to the clinic for an annual wellness examination. She is healthy with no prior history of significant illness. She exercises 3-4 times a week and eats a plant-based diet with no carbonated drinks. When asked if anything is bothering her, she reports that she has been having recurring episodes of sneezing, congestion, and itchy eyes for the past year. She denies any fever, sick contacts, cough, headaches, chest pain, urinary symptoms, or constipation/diarrhea during these episodes. She is told to take a medication to alleviate her symptoms as needed. What is the likely mechanism of action of the medication in question?\nA. Alpha-adrenergic agonist\nB. Competitive blockage of muscarinic receptors\nC. Disruption of disulfide bonds\nD. Short acting beta-2 agonist\nChoose the correct option.",
"image": null
},
{
"idx": 98,
"question": "A 58-year-old man with hypertension and dyslipidemia comes to the physician for a routine health maintenance examination. He says he feels well. He is 180 cm (5 ft 11 in) tall and weighs 103 kg (227 lb); BMI is 32 kg/m2. His BMI last year was 27 kg/m2. When asked about his diet, he says, “Being overweight runs in my family. Rather than fight it, I just try to enjoy myself and eat what I want.” Which of the following defense mechanisms best describes the patient's response to the physician?\nA. Rationalization\nB. Fantasy\nC. Distortion\nD. Intellectualization\n\nA. Rationalization\nB. Fantasy\nC. Distortion\nD. Intellectualization",
"options": [
"A. Rationalization",
"B. Fantasy",
"C. Distortion",
"D. Intellectualization"
],
"answer": "Rationalization",
"gen_text_store": "",
"pid": "98",
"query": "A 58-year-old man with hypertension and dyslipidemia comes to the physician for a routine health maintenance examination. He says he feels well. He is 180 cm (5 ft 11 in) tall and weighs 103 kg (227 lb); BMI is 32 kg/m2. His BMI last year was 27 kg/m2. When asked about his diet, he says, “Being overweight runs in my family. Rather than fight it, I just try to enjoy myself and eat what I want.” Which of the following defense mechanisms best describes the patient's response to the physician?\nA. Rationalization\nB. Fantasy\nC. Distortion\nD. Intellectualization\nChoose the correct option.",
"image": null
},
{
"idx": 99,
"question": "A 65-year-old female patient comes to the physician’s office for her annual check-up. The patient’s only complaint is that she feels her vision has been getting more blurry over the past year. The patient has a past medical history of diabetes diagnosed 20 years ago and osteoarthritis. Her medications include metformin, glimepiride, and ibuprofen as needed for pain. Fundoscopic examination of this patient reveals narrowing of retinal arteries and microaneurysms. This patient’s symptoms are likely caused by tissue specific differences in expression of which of the following enzymes?\nA. Sorbitol dehydrogenase\nB. Galactocerebrosidase\nC. Arylsulfatase A\nD. Sphingomyelinase\n\nA. Sorbitol dehydrogenase\nB. Galactocerebrosidase\nC. Arylsulfatase A\nD. Sphingomyelinase",
"options": [
"A. Sorbitol dehydrogenase",
"B. Galactocerebrosidase",
"C. Arylsulfatase A",
"D. Sphingomyelinase"
],
"answer": "Sorbitol dehydrogenase",
"gen_text_store": "",
"pid": "99",
"query": "A 65-year-old female patient comes to the physician’s office for her annual check-up. The patient’s only complaint is that she feels her vision has been getting more blurry over the past year. The patient has a past medical history of diabetes diagnosed 20 years ago and osteoarthritis. Her medications include metformin, glimepiride, and ibuprofen as needed for pain. Fundoscopic examination of this patient reveals narrowing of retinal arteries and microaneurysms. This patient’s symptoms are likely caused by tissue specific differences in expression of which of the following enzymes?\nA. Sorbitol dehydrogenase\nB. Galactocerebrosidase\nC. Arylsulfatase A\nD. Sphingomyelinase\nChoose the correct option.",
"image": null
},
{
"idx": 100,
"question": "A 19-year-old female presents to the emergency room with 6 days of lower abdominal pain. She states that her symptoms have progressed and she now feels feverish as well. She also notes an episode of nonbloody diarrhea 2 days ago and has been increasingly nauseous. While being evaluated in the emergency room, she vomits three times. The patient has no significant past medical history but was recently treated with ciprofloxacin for an uncomplicated urinary tract infection. She also notes irregular periods, with a last menstrual period 6 weeks ago. She is a college student who has had 3 sexual partners in the last year with inconsistent use of barrier protection. Her temperature is 100.5°C (38.1°F), blood pressure is 102/68 mmHg, pulse is 97/min, and respirations are 14/min. On exam, the patient is noticeably uncomfortable. There is marked tenderness to palpation in the suprapubic region and right lower quadrant, with voluntary guarding but no rebound. Pelvic exam shows moderate purulent discharge in the vaginal vault, cervical motion tenderness, and a tender adnexal mass on the right side. Which of the following is the best next step in treating this patient’s condition?\nA. Intramuscular ceftriaxone and oral doxycycline with outpatient follow-up\nB. Intravenous cefotetan and doxycycline with inpatient admission\nC. Oral vancomycin with outpatient follow-up\nD. Methotrexate with outpatient follow-up\n\nA. Intramuscular ceftriaxone and oral doxycycline with outpatient follow-up\nB. Intravenous cefotetan and doxycycline with inpatient admission\nC. Oral vancomycin with outpatient follow-up\nD. Methotrexate with outpatient follow-up",
"options": [
"A. Intramuscular ceftriaxone and oral doxycycline with outpatient follow-up",
"B. Intravenous cefotetan and doxycycline with inpatient admission",
"C. Oral vancomycin with outpatient follow-up",
"D. Methotrexate with outpatient follow-up"
],
"answer": "Intravenous cefotetan and doxycycline with inpatient admission",
"gen_text_store": "",
"pid": "100",
"query": "A 19-year-old female presents to the emergency room with 6 days of lower abdominal pain. She states that her symptoms have progressed and she now feels feverish as well. She also notes an episode of nonbloody diarrhea 2 days ago and has been increasingly nauseous. While being evaluated in the emergency room, she vomits three times. The patient has no significant past medical history but was recently treated with ciprofloxacin for an uncomplicated urinary tract infection. She also notes irregular periods, with a last menstrual period 6 weeks ago. She is a college student who has had 3 sexual partners in the last year with inconsistent use of barrier protection. Her temperature is 100.5°C (38.1°F), blood pressure is 102/68 mmHg, pulse is 97/min, and respirations are 14/min. On exam, the patient is noticeably uncomfortable. There is marked tenderness to palpation in the suprapubic region and right lower quadrant, with voluntary guarding but no rebound. Pelvic exam shows moderate purulent discharge in the vaginal vault, cervical motion tenderness, and a tender adnexal mass on the right side. Which of the following is the best next step in treating this patient’s condition?\nA. Intramuscular ceftriaxone and oral doxycycline with outpatient follow-up\nB. Intravenous cefotetan and doxycycline with inpatient admission\nC. Oral vancomycin with outpatient follow-up\nD. Methotrexate with outpatient follow-up\nChoose the correct option.",
"image": null
},
{
"idx": 101,
"question": "A 25-year-old female is brought to the emergency department by her family. They found her somnolent next to her computer and scattered pill bottles over two hours ago. The family cannot recall the types of pill bottles that they found and did not bring them to the ED. The patient's past medical history is notable for anxiety, obesity, hypertension, and polycystic ovarian syndrome. She is currently not on any medications other than an exercise program with which she is non-compliant. A physical exam is performed and is within normal limits. The patient begins communicating with the physician and states that she did take acetaminophen but it was only a few pills. Her temperature is 99.5°F (37.5°C), pulse is 82/min, blood pressure is 125/85 mmHg, respirations are 11/min, and oxygen saturation is 97% on room air. Which of the following is the next best step in management?\nA. N-acetylcysteine\nB. Charcoal\nC. IV fluids\nD. Syrup of ipecac\n\nA. N-acetylcysteine\nB. Charcoal\nC. IV fluids\nD. Syrup of ipecac",
"options": [
"A. N-acetylcysteine",
"B. Charcoal",
"C. IV fluids",
"D. Syrup of ipecac"
],
"answer": "N-acetylcysteine",
"gen_text_store": "",
"pid": "101",
"query": "A 25-year-old female is brought to the emergency department by her family. They found her somnolent next to her computer and scattered pill bottles over two hours ago. The family cannot recall the types of pill bottles that they found and did not bring them to the ED. The patient's past medical history is notable for anxiety, obesity, hypertension, and polycystic ovarian syndrome. She is currently not on any medications other than an exercise program with which she is non-compliant. A physical exam is performed and is within normal limits. The patient begins communicating with the physician and states that she did take acetaminophen but it was only a few pills. Her temperature is 99.5°F (37.5°C), pulse is 82/min, blood pressure is 125/85 mmHg, respirations are 11/min, and oxygen saturation is 97% on room air. Which of the following is the next best step in management?\nA. N-acetylcysteine\nB. Charcoal\nC. IV fluids\nD. Syrup of ipecac\nChoose the correct option.",
"image": null
},
{
"idx": 102,
"question": "A 42-year-old chronic alcoholic man was admitted to the hospital for inappropriate behavior and disturbed memory. He presents with severe retrograde memory loss, confusion, and confabulation. Neurologic examination showed horizontal nystagmus. He also has bilateral pretibial pitting edema and perioral erythema. CT studies of the brain were normal. The duty physician suspects the patient may be vitamin deficient. Which of the following reactions does the deficient vitamin mediate?\nA. Alpha-Ketoglutarate + NAD+ + CoA <=> Succinyl-CoA + CO2 + NADH\nB. Succinate + FAD (enzyme bound) <=> Fumarate + FADH2\nC. Isocitrate + NAD+ <=> Alpha-Ketoglutarate + CO2 + NADH\nD. Succinyl-CoA + Pi + GDP <=> Succinate + GTP + CoA\n\nA. Alpha-Ketoglutarate + NAD+ + CoA <=> Succinyl-CoA + CO2 + NADH\nB. Succinate + FAD (enzyme bound) <=> Fumarate + FADH2\nC. Isocitrate + NAD+ <=> Alpha-Ketoglutarate + CO2 + NADH\nD. Succinyl-CoA + Pi + GDP <=> Succinate + GTP + CoA",
"options": [
"A. Alpha-Ketoglutarate + NAD+ + CoA <=> Succinyl-CoA + CO2 + NADH",
"B. Succinate + FAD (enzyme bound) <=> Fumarate + FADH2",
"C. Isocitrate + NAD+ <=> Alpha-Ketoglutarate + CO2 + NADH",
"D. Succinyl-CoA + Pi + GDP <=> Succinate + GTP + CoA"
],
"answer": "Alpha-Ketoglutarate + NAD+ + CoA <=> Succinyl-CoA + CO2 + NADH",
"gen_text_store": "",
"pid": "102",
"query": "A 42-year-old chronic alcoholic man was admitted to the hospital for inappropriate behavior and disturbed memory. He presents with severe retrograde memory loss, confusion, and confabulation. Neurologic examination showed horizontal nystagmus. He also has bilateral pretibial pitting edema and perioral erythema. CT studies of the brain were normal. The duty physician suspects the patient may be vitamin deficient. Which of the following reactions does the deficient vitamin mediate?\nA. Alpha-Ketoglutarate + NAD+ + CoA <=> Succinyl-CoA + CO2 + NADH\nB. Succinate + FAD (enzyme bound) <=> Fumarate + FADH2\nC. Isocitrate + NAD+ <=> Alpha-Ketoglutarate + CO2 + NADH\nD. Succinyl-CoA + Pi + GDP <=> Succinate + GTP + CoA\nChoose the correct option.",
"image": null
},
{
"idx": 103,
"question": "A study is conducted to determine the most effective ways to prevent transmission of various infective agents. One of the agents studied is a picornavirus that preferentially infects hepatocytes. The investigator determines that inactivating this virus can prevent its spread. Which of the following disinfectants is most likely to inactivate this virus?\nA. Chlorhexidine\nB. Sodium hypochlorite\nC. Sulfuric acid\nD. Ethyl alcohol\n\nA. Chlorhexidine\nB. Sodium hypochlorite\nC. Sulfuric acid\nD. Ethyl alcohol",
"options": [
"A. Chlorhexidine",
"B. Sodium hypochlorite",
"C. Sulfuric acid",
"D. Ethyl alcohol"
],
"answer": "Sodium hypochlorite",
"gen_text_store": "",
"pid": "103",
"query": "A study is conducted to determine the most effective ways to prevent transmission of various infective agents. One of the agents studied is a picornavirus that preferentially infects hepatocytes. The investigator determines that inactivating this virus can prevent its spread. Which of the following disinfectants is most likely to inactivate this virus?\nA. Chlorhexidine\nB. Sodium hypochlorite\nC. Sulfuric acid\nD. Ethyl alcohol\nChoose the correct option.",
"image": null
},
{
"idx": 104,
"question": "A 44-year-old man presents to the family medicine clinic for some small bumps on his left thigh. The lesions are non-pruritic and have been present for the last 3 weeks. He reports feeling fatigued and malaise for the past few months. The patient has no known medical problems and takes no medications. He smokes one pack of cigarettes per day and uses intravenous street drugs. His heart rate is 82/min, the respiratory rate is 14/min, the temperature is 36.7°C (98.1°F), and the blood pressure is 126/80 mm Hg. Auscultation of the heart is without murmurs. Lungs are clear to auscultation bilaterally. Three 2-3 mm, dome-shaped, hardened papules are noted on the left thigh. Central umbilication can be observed in each papule. There is a non-tender cervical lymphadenopathy present. Which of the following is the most likely diagnosis?\nA. Bed bug bite\nB. Molluscum contagiosum\nC. Atopic dermatitis\nD. Acute urticaria\n\nA. Bed bug bite\nB. Molluscum contagiosum\nC. Atopic dermatitis\nD. Acute urticaria",
"options": [
"A. Bed bug bite",
"B. Molluscum contagiosum",
"C. Atopic dermatitis",
"D. Acute urticaria"
],
"answer": "Molluscum contagiosum",
"gen_text_store": "",
"pid": "104",
"query": "A 44-year-old man presents to the family medicine clinic for some small bumps on his left thigh. The lesions are non-pruritic and have been present for the last 3 weeks. He reports feeling fatigued and malaise for the past few months. The patient has no known medical problems and takes no medications. He smokes one pack of cigarettes per day and uses intravenous street drugs. His heart rate is 82/min, the respiratory rate is 14/min, the temperature is 36.7°C (98.1°F), and the blood pressure is 126/80 mm Hg. Auscultation of the heart is without murmurs. Lungs are clear to auscultation bilaterally. Three 2-3 mm, dome-shaped, hardened papules are noted on the left thigh. Central umbilication can be observed in each papule. There is a non-tender cervical lymphadenopathy present. Which of the following is the most likely diagnosis?\nA. Bed bug bite\nB. Molluscum contagiosum\nC. Atopic dermatitis\nD. Acute urticaria\nChoose the correct option.",
"image": null
},
{
"idx": 105,
"question": "A 35-year-old woman presents with severe fear reactions to seeing dogs after moving into a new suburban neighborhood. She states that she has always had an irrational and excessive fear of dogs but has been able to avoid it for most of her life while living in the city. When she sees her neighbors walking their dogs outside, she is terrified and begins to feel short of breath. Recently, she has stopped picking up her children from the bus stop and no longer plays outside with her children in order to avoid seeing any dogs. Which of the following would be the best definitive treatment for this patient?\nA. Selective serotonin reuptake inhibitors (SSRIs)\nB. Short-acting benzodiazepines\nC. Systematic desensitization\nD. Cognitive behavioral therapy\n\nA. Selective serotonin reuptake inhibitors (SSRIs)\nB. Short-acting benzodiazepines\nC. Systematic desensitization\nD. Cognitive behavioral therapy",
"options": [
"A. Selective serotonin reuptake inhibitors (SSRIs)",
"B. Short-acting benzodiazepines",
"C. Systematic desensitization",
"D. Cognitive behavioral therapy"
],
"answer": "Systematic desensitization",
"gen_text_store": "",
"pid": "105",
"query": "A 35-year-old woman presents with severe fear reactions to seeing dogs after moving into a new suburban neighborhood. She states that she has always had an irrational and excessive fear of dogs but has been able to avoid it for most of her life while living in the city. When she sees her neighbors walking their dogs outside, she is terrified and begins to feel short of breath. Recently, she has stopped picking up her children from the bus stop and no longer plays outside with her children in order to avoid seeing any dogs. Which of the following would be the best definitive treatment for this patient?\nA. Selective serotonin reuptake inhibitors (SSRIs)\nB. Short-acting benzodiazepines\nC. Systematic desensitization\nD. Cognitive behavioral therapy\nChoose the correct option.",
"image": null
},
{
"idx": 106,
"question": "A 3-year-old boy is brought to the emergency room by his mother after she found him somnolent at home next to multiple open pill bottles. The boy had seemingly opened several different pill bottles that were in a cabinet in his parent’s bathroom. The mother has brought the empty bottles to the emergency room, and they include aspirin, metoprolol, acetaminophen, levothyroxine, and lorazepam. The boy has no past medical history and takes no medications. His temperature is 98.6°F (37°C), blood pressure is 110/65 mmHg, pulse is 85/min, and respirations are 28/min. On exam, the boy is lethargic but responsive. He appears to be grasping at his ears and swaying from side-to-side when attempting to ambulate. He vomited once in the emergency room. Which of the following arterial blood gas readings is most likely to be found in this patient?\nA. pH 7.29, PCO2 47 mmHg, and HCO3- 22 mEq/L\nB. pH 7.35, PCO2 29 mmHg, and HCO3- 15 mEq/L\nC. pH 7.36, PCO2 22 mmHg, and HCO3- 16 mEq/L\nD. pH 7.47, PCO2 41 mmHg, and HCO3- 29 mEq/L\n\nA. pH 7.29, PCO2 47 mmHg, and HCO3- 22 mEq/L\nB. pH 7.35, PCO2 29 mmHg, and HCO3- 15 mEq/L\nC. pH 7.36, PCO2 22 mmHg, and HCO3- 16 mEq/L\nD. pH 7.47, PCO2 41 mmHg, and HCO3- 29 mEq/L",
"options": [
"A. pH 7.29, PCO2 47 mmHg, and HCO3- 22 mEq/L",
"B. pH 7.35, PCO2 29 mmHg, and HCO3- 15 mEq/L",
"C. pH 7.36, PCO2 22 mmHg, and HCO3- 16 mEq/L",
"D. pH 7.47, PCO2 41 mmHg, and HCO3- 29 mEq/L"
],
"answer": "pH 7.36, PCO2 22 mmHg, and HCO3- 16 mEq/L",
"gen_text_store": "",
"pid": "106",
"query": "A 3-year-old boy is brought to the emergency room by his mother after she found him somnolent at home next to multiple open pill bottles. The boy had seemingly opened several different pill bottles that were in a cabinet in his parent’s bathroom. The mother has brought the empty bottles to the emergency room, and they include aspirin, metoprolol, acetaminophen, levothyroxine, and lorazepam. The boy has no past medical history and takes no medications. His temperature is 98.6°F (37°C), blood pressure is 110/65 mmHg, pulse is 85/min, and respirations are 28/min. On exam, the boy is lethargic but responsive. He appears to be grasping at his ears and swaying from side-to-side when attempting to ambulate. He vomited once in the emergency room. Which of the following arterial blood gas readings is most likely to be found in this patient?\nA. pH 7.29, PCO2 47 mmHg, and HCO3- 22 mEq/L\nB. pH 7.35, PCO2 29 mmHg, and HCO3- 15 mEq/L\nC. pH 7.36, PCO2 22 mmHg, and HCO3- 16 mEq/L\nD. pH 7.47, PCO2 41 mmHg, and HCO3- 29 mEq/L\nChoose the correct option.",
"image": null
},
{
"idx": 107,
"question": "A 36-year-old man is brought to the emergency department 25 minutes after being involved in a high speed motor-vehicle collision in which he was an unrestrained passenger. He has acute myeloid leukemia and is currently receiving chemotherapy. On arrival, his temperature is 37°C (98.6°F), pulse is 63/min, respirations are 10/min, and blood pressure is 100/70 mm Hg. The pupils are equal and sluggish. There are multiple bruises over the face, trunk, and right upper and lower extremities. There is a 4-cm (1.6-in) laceration over his right cheek. He does not respond to any commands, but does groan. Painful stimuli cause him to open his eyes and withdraw all extremities. There are decreased breath sounds over the right lung base. There is tenderness to palpation over the left chest wall. Cardiac examination shows no abnormalities. The abdomen is soft and shows diffuse tenderness to palpation with no guarding or rebound. There is swelling of the right elbow and wrist. The right lower extremity is shorter than the left lower extremity. There are 2 lacerations around 2 cm (0.8 in) each on the right leg. The right knee is swollen. Which of the following is the most appropriate next step in management?\nA. Insertion of intercostal chest tube\nB. CT scan of the head and neck\nC. X-rays of the extremities\nD. Intubation and mechanical ventilation\n\nA. Insertion of intercostal chest tube\nB. CT scan of the head and neck\nC. X-rays of the extremities\nD. Intubation and mechanical ventilation",
"options": [
"A. Insertion of intercostal chest tube",
"B. CT scan of the head and neck",
"C. X-rays of the extremities",
"D. Intubation and mechanical ventilation"
],
"answer": "Intubation and mechanical ventilation",
"gen_text_store": "",
"pid": "107",
"query": "A 36-year-old man is brought to the emergency department 25 minutes after being involved in a high speed motor-vehicle collision in which he was an unrestrained passenger. He has acute myeloid leukemia and is currently receiving chemotherapy. On arrival, his temperature is 37°C (98.6°F), pulse is 63/min, respirations are 10/min, and blood pressure is 100/70 mm Hg. The pupils are equal and sluggish. There are multiple bruises over the face, trunk, and right upper and lower extremities. There is a 4-cm (1.6-in) laceration over his right cheek. He does not respond to any commands, but does groan. Painful stimuli cause him to open his eyes and withdraw all extremities. There are decreased breath sounds over the right lung base. There is tenderness to palpation over the left chest wall. Cardiac examination shows no abnormalities. The abdomen is soft and shows diffuse tenderness to palpation with no guarding or rebound. There is swelling of the right elbow and wrist. The right lower extremity is shorter than the left lower extremity. There are 2 lacerations around 2 cm (0.8 in) each on the right leg. The right knee is swollen. Which of the following is the most appropriate next step in management?\nA. Insertion of intercostal chest tube\nB. CT scan of the head and neck\nC. X-rays of the extremities\nD. Intubation and mechanical ventilation\nChoose the correct option.",
"image": null
},
{
"idx": 108,
"question": "A 25-year-old male involved in a knife fight presents with a penetrating wound to the chest. The patient is unconscious and cannot provide any further history. Vitals show a temperature of 37-0°C (98.6°F), blood pressure of 85/55 mm Hg, pulse of 115/min, respirations of 19/min, and oxygen saturation of 92% on room air. On physical examination, the patient is diaphoretic and unresponsive. Extremities are pale and cool. There is a 3-inch long penetrating wound between the 3rd and 4th intercostal space on the left side of the chest, which is bleeding profusely. Transthoracic echocardiography reveals a full thickness penetrating injury to the right ventricular free wall. There are no apparent injuries to any coronary arteries or major branches. The patient is intubated and aggressive fluid resuscitation is initiated, including a blood transfusion. Which of the following is the best definitive surgical approach to take in this patient?\nA. Immediate cardiac transplant\nB. Watchful waiting while resuscitative fluids are initiated\nC. Interrupted 2-0 polypropylene suture with supporting pledgets\nD. Needle thoracostomy over the 2nd intercostal space\n\nA. Immediate cardiac transplant\nB. Watchful waiting while resuscitative fluids are initiated\nC. Interrupted 2-0 polypropylene suture with supporting pledgets\nD. Needle thoracostomy over the 2nd intercostal space",
"options": [
"A. Immediate cardiac transplant",
"B. Watchful waiting while resuscitative fluids are initiated",
"C. Interrupted 2-0 polypropylene suture with supporting pledgets",
"D. Needle thoracostomy over the 2nd intercostal space"
],
"answer": "Interrupted 2-0 polypropylene suture with supporting pledgets",
"gen_text_store": "",
"pid": "108",
"query": "A 25-year-old male involved in a knife fight presents with a penetrating wound to the chest. The patient is unconscious and cannot provide any further history. Vitals show a temperature of 37-0°C (98.6°F), blood pressure of 85/55 mm Hg, pulse of 115/min, respirations of 19/min, and oxygen saturation of 92% on room air. On physical examination, the patient is diaphoretic and unresponsive. Extremities are pale and cool. There is a 3-inch long penetrating wound between the 3rd and 4th intercostal space on the left side of the chest, which is bleeding profusely. Transthoracic echocardiography reveals a full thickness penetrating injury to the right ventricular free wall. There are no apparent injuries to any coronary arteries or major branches. The patient is intubated and aggressive fluid resuscitation is initiated, including a blood transfusion. Which of the following is the best definitive surgical approach to take in this patient?\nA. Immediate cardiac transplant\nB. Watchful waiting while resuscitative fluids are initiated\nC. Interrupted 2-0 polypropylene suture with supporting pledgets\nD. Needle thoracostomy over the 2nd intercostal space\nChoose the correct option.",
"image": null
},
{
"idx": 109,
"question": "A 28-year-old man reports to his physician that he is having second thoughts about his long-term compatibility with his wife ever since they relocated to a new city. He admits that he has noticed himself flirting with some of the female co-workers at his new workplace. When he goes on a dinner date with his wife after work one evening, he accuses her of giving their waiter flirtatious looks and asks her whether she has been cheating on him or trying to spend time with other men. The man’s actions are most consistent with which of the following psychological defense mechanisms?\nA. Displacement\nB. Dissociation\nC. Projection\nD. Repression\n\nA. Displacement\nB. Dissociation\nC. Projection\nD. Repression",
"options": [
"A. Displacement",
"B. Dissociation",
"C. Projection",
"D. Repression"
],
"answer": "Projection",
"gen_text_store": "",
"pid": "109",
"query": "A 28-year-old man reports to his physician that he is having second thoughts about his long-term compatibility with his wife ever since they relocated to a new city. He admits that he has noticed himself flirting with some of the female co-workers at his new workplace. When he goes on a dinner date with his wife after work one evening, he accuses her of giving their waiter flirtatious looks and asks her whether she has been cheating on him or trying to spend time with other men. The man’s actions are most consistent with which of the following psychological defense mechanisms?\nA. Displacement\nB. Dissociation\nC. Projection\nD. Repression\nChoose the correct option.",
"image": null
},
{
"idx": 110,
"question": "A 60-year-old man is referred to a dermatologist by his family physician for management of a rare case of dermatitis that has not responded to standard therapy with corticosteroids. The patient’s medical history is unremarkable, and he is currently working reduced hours at his job as an accountant. Physical examination reveals confluent scaly patches, plaques, and generalized erythroderma along the torso and lower extremities (see image). There is also a solid skin lesion with a diameter greater than 1 cm. The dermatologist suspects a malignancy and orders a biopsy. Which of the following is the most accurate description of this condition?\nA. Vascular tumor containing spindle cells\nB. Tumor arising from the folliculosebaceous–apocrine germ\nC. Tumor arising from cutaneous T cells\nD. Tumor arising from epidermal keratinocytes\n\nA. Vascular tumor containing spindle cells\nB. Tumor arising from the folliculosebaceous–apocrine germ\nC. Tumor arising from cutaneous T cells\nD. Tumor arising from epidermal keratinocytes",
"options": [
"A. Vascular tumor containing spindle cells",
"B. Tumor arising from the folliculosebaceous–apocrine germ",
"C. Tumor arising from cutaneous T cells",
"D. Tumor arising from epidermal keratinocytes"
],
"answer": "Tumor arising from cutaneous T cells",
"gen_text_store": "",
"pid": "110",
"query": "A 60-year-old man is referred to a dermatologist by his family physician for management of a rare case of dermatitis that has not responded to standard therapy with corticosteroids. The patient’s medical history is unremarkable, and he is currently working reduced hours at his job as an accountant. Physical examination reveals confluent scaly patches, plaques, and generalized erythroderma along the torso and lower extremities (see image). There is also a solid skin lesion with a diameter greater than 1 cm. The dermatologist suspects a malignancy and orders a biopsy. Which of the following is the most accurate description of this condition?\nA. Vascular tumor containing spindle cells\nB. Tumor arising from the folliculosebaceous–apocrine germ\nC. Tumor arising from cutaneous T cells\nD. Tumor arising from epidermal keratinocytes\nChoose the correct option.",
"image": null
},
{
"idx": 111,
"question": "A 52-year-old man comes to the physician for an annual physical examination. He reports that his vision has progressively improved over the past 6 months and he no longer needs the glasses he used while driving. He has hypertension and type 2 diabetes mellitus. Current medications include glyburide, hydrochlorothiazide, and enalapril. Examination shows 20/20 vision bilaterally. Fundoscopy shows a few microaneurysms of retinal vessels. Which of the following is the most likely explanation for this patient's improved vision?\nA. Denaturation of lens protein\nB. Liquefication of the vitreous body\nC. Increased ciliary muscle tone\nD. Increased lens elasticity\n\nA. Denaturation of lens protein\nB. Liquefication of the vitreous body\nC. Increased ciliary muscle tone\nD. Increased lens elasticity",
"options": [
"A. Denaturation of lens protein",
"B. Liquefication of the vitreous body",
"C. Increased ciliary muscle tone",
"D. Increased lens elasticity"
],
"answer": "Denaturation of lens protein",
"gen_text_store": "",
"pid": "111",
"query": "A 52-year-old man comes to the physician for an annual physical examination. He reports that his vision has progressively improved over the past 6 months and he no longer needs the glasses he used while driving. He has hypertension and type 2 diabetes mellitus. Current medications include glyburide, hydrochlorothiazide, and enalapril. Examination shows 20/20 vision bilaterally. Fundoscopy shows a few microaneurysms of retinal vessels. Which of the following is the most likely explanation for this patient's improved vision?\nA. Denaturation of lens protein\nB. Liquefication of the vitreous body\nC. Increased ciliary muscle tone\nD. Increased lens elasticity\nChoose the correct option.",
"image": null
},
{
"idx": 112,
"question": "A 72-year-old woman comes to the physician because of a 1-month history of frequent headaches, double vision, fatigue, and myalgias. Physical examination shows pallor, tenderness to palpation over the temples, and inward deviation of the left eye. Laboratory studies show an erythrocyte sedimentation rate of 65 mm/h. Temporal artery biopsy shows transmural granulomatous inflammation and fragmentation of the internal elastic lamina. Treatment with high-dose intravenous corticosteroids is begun. The patient's condition puts her at greatest risk of developing which of the following complications?\nA. Pulmonary hypertension\nB. Lower extremity gangrene\nC. Palpable purpura\nD. Thoracic aortic aneurysm\n\nA. Pulmonary hypertension\nB. Lower extremity gangrene\nC. Palpable purpura\nD. Thoracic aortic aneurysm",
"options": [
"A. Pulmonary hypertension",
"B. Lower extremity gangrene",
"C. Palpable purpura",
"D. Thoracic aortic aneurysm"
],
"answer": "Thoracic aortic aneurysm",
"gen_text_store": "",
"pid": "112",
"query": "A 72-year-old woman comes to the physician because of a 1-month history of frequent headaches, double vision, fatigue, and myalgias. Physical examination shows pallor, tenderness to palpation over the temples, and inward deviation of the left eye. Laboratory studies show an erythrocyte sedimentation rate of 65 mm/h. Temporal artery biopsy shows transmural granulomatous inflammation and fragmentation of the internal elastic lamina. Treatment with high-dose intravenous corticosteroids is begun. The patient's condition puts her at greatest risk of developing which of the following complications?\nA. Pulmonary hypertension\nB. Lower extremity gangrene\nC. Palpable purpura\nD. Thoracic aortic aneurysm\nChoose the correct option.",
"image": null
},
{
"idx": 113,
"question": "A 49-year-old man comes to the physician because he has had multiple falls and multiple episodes of dizziness over the past 6 weeks. There is no personal or family history of serious illness. He drinks one pint of rum daily. He works as a foreman in a factory that produces industrial solvents. He is alert and oriented to time, place, and person. His temperature is 36.7°C (98.1°F), pulse is 88/min, and blood pressure is 108/70 mm Hg. Examination shows a wide-based gait. The patient is unable to stand with his feet together without support. There is a coarse tremor of the hands when he is asked to grab a pen. Muscle strength and tone are normal in all extremities. Sensation to pain, vibration, and position is intact bilaterally. Rapid alternating movements of the hands is impaired. Mental status examination shows no abnormalities. Which of the following is the most likely cause of this patient's condition?\nA. Korsakoff syndrome\nB. Methanol poisoning\nC. Cerebellar degeneration\nD. Wernicke's encephalopathy\n\nA. Korsakoff syndrome\nB. Methanol poisoning\nC. Cerebellar degeneration\nD. Wernicke's encephalopathy",
"options": [
"A. Korsakoff syndrome",
"B. Methanol poisoning",
"C. Cerebellar degeneration",
"D. Wernicke's encephalopathy"
],
"answer": "Cerebellar degeneration",
"gen_text_store": "",
"pid": "113",
"query": "A 49-year-old man comes to the physician because he has had multiple falls and multiple episodes of dizziness over the past 6 weeks. There is no personal or family history of serious illness. He drinks one pint of rum daily. He works as a foreman in a factory that produces industrial solvents. He is alert and oriented to time, place, and person. His temperature is 36.7°C (98.1°F), pulse is 88/min, and blood pressure is 108/70 mm Hg. Examination shows a wide-based gait. The patient is unable to stand with his feet together without support. There is a coarse tremor of the hands when he is asked to grab a pen. Muscle strength and tone are normal in all extremities. Sensation to pain, vibration, and position is intact bilaterally. Rapid alternating movements of the hands is impaired. Mental status examination shows no abnormalities. Which of the following is the most likely cause of this patient's condition?\nA. Korsakoff syndrome\nB. Methanol poisoning\nC. Cerebellar degeneration\nD. Wernicke's encephalopathy\nChoose the correct option.",
"image": null
},
{
"idx": 114,
"question": "A 56-year-old man presents to the clinic complaining of subacute back pain for the past month. The pain is described as a dull, constant ache that is worse at night. He could not recall any precipitating event except for an amateur weight-lifting competition that he participated in 2 months ago. Past medical history is significant for non-small cell lung cancer that was diagnosed and successfully treated. A PET scan 1 year ago demonstrated no recurrence. Physical exam was unremarkable except for some point tenderness along the lumbosacral area. What is the most likely imaging finding in this patient?\nA. Bulging disc impinging on lumbar spinal nerve\nB. Lytic lesions of the lumbar spine\nC. Narrowing of the lumbar disc space\nD. Sacroilitis and fusion of the lumbar spine\n\nA. Bulging disc impinging on lumbar spinal nerve\nB. Lytic lesions of the lumbar spine\nC. Narrowing of the lumbar disc space\nD. Sacroilitis and fusion of the lumbar spine",
"options": [
"A. Bulging disc impinging on lumbar spinal nerve",
"B. Lytic lesions of the lumbar spine",
"C. Narrowing of the lumbar disc space",
"D. Sacroilitis and fusion of the lumbar spine"
],
"answer": "Lytic lesions of the lumbar spine",
"gen_text_store": "",
"pid": "114",
"query": "A 56-year-old man presents to the clinic complaining of subacute back pain for the past month. The pain is described as a dull, constant ache that is worse at night. He could not recall any precipitating event except for an amateur weight-lifting competition that he participated in 2 months ago. Past medical history is significant for non-small cell lung cancer that was diagnosed and successfully treated. A PET scan 1 year ago demonstrated no recurrence. Physical exam was unremarkable except for some point tenderness along the lumbosacral area. What is the most likely imaging finding in this patient?\nA. Bulging disc impinging on lumbar spinal nerve\nB. Lytic lesions of the lumbar spine\nC. Narrowing of the lumbar disc space\nD. Sacroilitis and fusion of the lumbar spine\nChoose the correct option.",
"image": null
},
{
"idx": 115,
"question": "A 52-year-old man is brought to the emergency department with dry cough, shortness of breath, and low-grade fever that began 6 days ago. He also reports that he has had 3 episodes of watery diarrhea per day for the last 2 days. He appears slightly pale. His temperature is 38.0°C (100.4°F), pulse is 65/min, respirations are 15/min, and blood pressure is 140/78 mm Hg. Diffuse crackles are heard over bibasilar lung fields. Laboratory studies show:\nHemoglobin 13.8 g/dL\nLeukocyte count 16,000/mm3\nPlatelet count 150,000/mm3\nSerum\nNa+ 131 mEq/L\nCl-\n102 mEq/L\nK+ 4.7 mEq/L\nHCO3- 26 mEq/L\nUrea nitrogen 18 mg/dL\nCreatinine 1.2 mg/dL\nAn x-ray of the chest shows patchy infiltrates in both lungs. Which of the following is the most appropriate pharmacotherapy?\"\nA. Levofloxacin\nB. Trimethoprim/sulfamethoxazole\nC. Amoxicillin\nD. Rifampin\n\nA. Levofloxacin\nB. Trimethoprim/sulfamethoxazole\nC. Amoxicillin\nD. Rifampin",
"options": [
"A. Levofloxacin",
"B. Trimethoprim/sulfamethoxazole",
"C. Amoxicillin",
"D. Rifampin"
],
"answer": "Levofloxacin",
"gen_text_store": "",
"pid": "115",
"query": "A 52-year-old man is brought to the emergency department with dry cough, shortness of breath, and low-grade fever that began 6 days ago. He also reports that he has had 3 episodes of watery diarrhea per day for the last 2 days. He appears slightly pale. His temperature is 38.0°C (100.4°F), pulse is 65/min, respirations are 15/min, and blood pressure is 140/78 mm Hg. Diffuse crackles are heard over bibasilar lung fields. Laboratory studies show:\nHemoglobin 13.8 g/dL\nLeukocyte count 16,000/mm3\nPlatelet count 150,000/mm3\nSerum\nNa+ 131 mEq/L\nCl-\n102 mEq/L\nK+ 4.7 mEq/L\nHCO3- 26 mEq/L\nUrea nitrogen 18 mg/dL\nCreatinine 1.2 mg/dL\nAn x-ray of the chest shows patchy infiltrates in both lungs. Which of the following is the most appropriate pharmacotherapy?\"\nA. Levofloxacin\nB. Trimethoprim/sulfamethoxazole\nC. Amoxicillin\nD. Rifampin\nChoose the correct option.",
"image": null
},
{
"idx": 116,
"question": "A 39-year-old woman comes to the physician because of fever, generalized fatigue, and chills for 1 week. She has been having dull right-side abdominal pain during this period. She has nausea. She has no history of travel outside the United States. She has type 1 diabetes mellitus. Current medications include insulin and an oral contraceptive. She appears ill. Her temperature is 40°C (104°F), pulse is 118/min, and blood pressure is 106/70 mm Hg. On examination, the liver is palpated 2–3 cm below the right costal margin and is tender. There are decreased breath sounds over the right lung base. The remainder of the examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14.1 g/dL\nLeukocyte count 17,100/mm3\nSegmented neutrophils 74%\nEosinophils 1%\nLymphocytes 20%\nMonocytes 5%\nSerum\nGlucose 79 mg/dL\nCreatinine 1.1 mg/dL\nTotal bilirubin 0.9 mg/dL\nAlkaline phosphatase 180 U/L\nAST 69 U/L\nALT 100 U/L\nA right upper quadrant ultrasound is shown. Which of the following is the most appropriate next step in management?\"\nA. Discontinue the oral contraceptive\nB. Obtain hepatoiminodiacetic acid scan\nC. Perform endoscopic retrograde cholangiopancreatography\nD. Perform percutaneous drainage\n\"\n\nA. Discontinue the oral contraceptive\nB. Obtain hepatoiminodiacetic acid scan\nC. Perform endoscopic retrograde cholangiopancreatography\nD. Perform percutaneous drainage\n\"",
"options": [
"A. Discontinue the oral contraceptive",
"B. Obtain hepatoiminodiacetic acid scan",
"C. Perform endoscopic retrograde cholangiopancreatography",
"D. Perform percutaneous drainage\n\""
],
"answer": "Perform percutaneous drainage\n\"",
"gen_text_store": "",
"pid": "116",
"query": "A 39-year-old woman comes to the physician because of fever, generalized fatigue, and chills for 1 week. She has been having dull right-side abdominal pain during this period. She has nausea. She has no history of travel outside the United States. She has type 1 diabetes mellitus. Current medications include insulin and an oral contraceptive. She appears ill. Her temperature is 40°C (104°F), pulse is 118/min, and blood pressure is 106/70 mm Hg. On examination, the liver is palpated 2–3 cm below the right costal margin and is tender. There are decreased breath sounds over the right lung base. The remainder of the examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14.1 g/dL\nLeukocyte count 17,100/mm3\nSegmented neutrophils 74%\nEosinophils 1%\nLymphocytes 20%\nMonocytes 5%\nSerum\nGlucose 79 mg/dL\nCreatinine 1.1 mg/dL\nTotal bilirubin 0.9 mg/dL\nAlkaline phosphatase 180 U/L\nAST 69 U/L\nALT 100 U/L\nA right upper quadrant ultrasound is shown. Which of the following is the most appropriate next step in management?\"\nA. Discontinue the oral contraceptive\nB. Obtain hepatoiminodiacetic acid scan\nC. Perform endoscopic retrograde cholangiopancreatography\nD. Perform percutaneous drainage\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 117,
"question": "A hospitalized 34-year-old man with severe diarrhea and bloating for 1 month is diagnosed with celiac disease based on serology and duodenal biopsy. He has no history of any serious illnesses and takes no medications. He has no history of recent travel. His vital signs are within normal limits. Physical examination is unremarkable. At discharge from the hospital, he is given complete instructions for a strict gluten-free diet. Which of the following is the most appropriate recommendation for the temporary control of the severe diarrhea and bloating?\nA. Avoiding all dairy products\nB. Diphenoxylate\nC. Prednisone\nD. Restriction of soy products\n\nA. Avoiding all dairy products\nB. Diphenoxylate\nC. Prednisone\nD. Restriction of soy products",
"options": [
"A. Avoiding all dairy products",
"B. Diphenoxylate",
"C. Prednisone",
"D. Restriction of soy products"
],
"answer": "Avoiding all dairy products",
"gen_text_store": "",
"pid": "117",
"query": "A hospitalized 34-year-old man with severe diarrhea and bloating for 1 month is diagnosed with celiac disease based on serology and duodenal biopsy. He has no history of any serious illnesses and takes no medications. He has no history of recent travel. His vital signs are within normal limits. Physical examination is unremarkable. At discharge from the hospital, he is given complete instructions for a strict gluten-free diet. Which of the following is the most appropriate recommendation for the temporary control of the severe diarrhea and bloating?\nA. Avoiding all dairy products\nB. Diphenoxylate\nC. Prednisone\nD. Restriction of soy products\nChoose the correct option.",
"image": null
},
{
"idx": 118,
"question": "A 63-year-old man comes to the physician for the evaluation of an unintentional 10-kg (22-lb) weight loss over the past 6 months. During this period, the patient has had recurrent episodes of high-grade fever, night sweats, and feelings of fatigue. Two months ago, he had herpes zoster that was treated with acyclovir. He appears pale. Temperature is 38.5°C (101.3°F), pulse is 90/min, and blood pressure 130/80 mm Hg. Physical examination shows generalized painless lymphadenopathy. The liver and the spleen are palpated 2–3 cm below the right and the left costal margin, respectively. Laboratory studies show:\nHematocrit 42%\nLeukocyte count 15,000/mm3\nSegmented neutrophils 46%\nEosinophils 1%\nLymphocytes 50%\nMonocytes 3%\nPlatelet count 120,000/mm3\nBlood smear shows mature lymphocytes that rupture easily and appear as artifacts on a blood smear. Flow cytometry shows lymphocytes expressing CD5, CD19, CD20, and CD23. Which of the following is the most appropriate treatment?\"\nA. All-trans retinoic acid\nB. Fludarabine, cyclophosphamide, rituximab\nC. Observation and disease progression monitoring\nD. Imatinib only\n\"\n\nA. All-trans retinoic acid\nB. Fludarabine, cyclophosphamide, rituximab\nC. Observation and disease progression monitoring\nD. Imatinib only\n\"",
"options": [
"A. All-trans retinoic acid",
"B. Fludarabine, cyclophosphamide, rituximab",
"C. Observation and disease progression monitoring",
"D. Imatinib only\n\""
],
"answer": "Fludarabine, cyclophosphamide, rituximab",
"gen_text_store": "",
"pid": "118",
"query": "A 63-year-old man comes to the physician for the evaluation of an unintentional 10-kg (22-lb) weight loss over the past 6 months. During this period, the patient has had recurrent episodes of high-grade fever, night sweats, and feelings of fatigue. Two months ago, he had herpes zoster that was treated with acyclovir. He appears pale. Temperature is 38.5°C (101.3°F), pulse is 90/min, and blood pressure 130/80 mm Hg. Physical examination shows generalized painless lymphadenopathy. The liver and the spleen are palpated 2–3 cm below the right and the left costal margin, respectively. Laboratory studies show:\nHematocrit 42%\nLeukocyte count 15,000/mm3\nSegmented neutrophils 46%\nEosinophils 1%\nLymphocytes 50%\nMonocytes 3%\nPlatelet count 120,000/mm3\nBlood smear shows mature lymphocytes that rupture easily and appear as artifacts on a blood smear. Flow cytometry shows lymphocytes expressing CD5, CD19, CD20, and CD23. Which of the following is the most appropriate treatment?\"\nA. All-trans retinoic acid\nB. Fludarabine, cyclophosphamide, rituximab\nC. Observation and disease progression monitoring\nD. Imatinib only\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 119,
"question": "A 35-year-old woman comes to the physician because she has been feeling very stressed over the past several months. During this period, she has found it difficult to relax. She states that her head is full of worries. She works at an accountant's office and reports difficulty in concentrating on her work. She has been working longer shifts because one of her coworkers is on vacation and reports feeling more tired than usual. She is married and frequently fights with her husband. The patient states that in order to deal with her stress, she goes shopping. While shopping, she steals small trivial items and feels immediately relieved thereafter. She discards the objects she steals and has feelings of shame and guilt about her actions. Her husband is concerned about her behavior, but she is unable to stop shoplifting. Her vital signs are within normal limits. On mental status examination, she is oriented to person, place, and time. She reports feeling anxious. Physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Administration of lithium\nB. Interpersonal therapy\nC. Psychodynamic psychotherapy\nD. Cognitive behavioral therapy\n\nA. Administration of lithium\nB. Interpersonal therapy\nC. Psychodynamic psychotherapy\nD. Cognitive behavioral therapy",
"options": [
"A. Administration of lithium",
"B. Interpersonal therapy",
"C. Psychodynamic psychotherapy",
"D. Cognitive behavioral therapy"
],
"answer": "Cognitive behavioral therapy",
"gen_text_store": "",
"pid": "119",
"query": "A 35-year-old woman comes to the physician because she has been feeling very stressed over the past several months. During this period, she has found it difficult to relax. She states that her head is full of worries. She works at an accountant's office and reports difficulty in concentrating on her work. She has been working longer shifts because one of her coworkers is on vacation and reports feeling more tired than usual. She is married and frequently fights with her husband. The patient states that in order to deal with her stress, she goes shopping. While shopping, she steals small trivial items and feels immediately relieved thereafter. She discards the objects she steals and has feelings of shame and guilt about her actions. Her husband is concerned about her behavior, but she is unable to stop shoplifting. Her vital signs are within normal limits. On mental status examination, she is oriented to person, place, and time. She reports feeling anxious. Physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Administration of lithium\nB. Interpersonal therapy\nC. Psychodynamic psychotherapy\nD. Cognitive behavioral therapy\nChoose the correct option.",
"image": null
},
{
"idx": 120,
"question": "A 27-year-old woman comes to the physician because of increasing shortness of breath and a non-productive cough for 2 months. She has been unable to perform her daily activities. She has had malaise and bilateral ankle pain during this period. She noticed her symptoms after returning from a vacation to Arizona. She is a research assistant at the university geology laboratory. She is originally from Nigeria and visits her family there twice a year; her last trip was 3 months ago. Her temperature is 37.8°C (100°F), pulse is 100/min, respirations are 24/min, and blood pressure is 112/72 mm Hg. Pulse oximetry on room air shows an oxygen saturation of 94%. There is no palpable cervical or axillary lymphadenopathy. The lungs are clear to auscultation. Her left eye is notable for ciliary injection and photophobia. The remainder of the examination shows no abnormalities. A complete blood count is within the reference range. An x-ray of the chest is shown. Which of the following is the most likely diagnosis?\nA. Sarcoidosis\nB. Pulmonary tuberculosis\nC. Hodgkin's lymphoma\nD. Histoplasmosis\n\nA. Sarcoidosis\nB. Pulmonary tuberculosis\nC. Hodgkin's lymphoma\nD. Histoplasmosis",
"options": [
"A. Sarcoidosis",
"B. Pulmonary tuberculosis",
"C. Hodgkin's lymphoma",
"D. Histoplasmosis"
],
"answer": "Sarcoidosis",
"gen_text_store": "",
"pid": "120",
"query": "A 27-year-old woman comes to the physician because of increasing shortness of breath and a non-productive cough for 2 months. She has been unable to perform her daily activities. She has had malaise and bilateral ankle pain during this period. She noticed her symptoms after returning from a vacation to Arizona. She is a research assistant at the university geology laboratory. She is originally from Nigeria and visits her family there twice a year; her last trip was 3 months ago. Her temperature is 37.8°C (100°F), pulse is 100/min, respirations are 24/min, and blood pressure is 112/72 mm Hg. Pulse oximetry on room air shows an oxygen saturation of 94%. There is no palpable cervical or axillary lymphadenopathy. The lungs are clear to auscultation. Her left eye is notable for ciliary injection and photophobia. The remainder of the examination shows no abnormalities. A complete blood count is within the reference range. An x-ray of the chest is shown. Which of the following is the most likely diagnosis?\nA. Sarcoidosis\nB. Pulmonary tuberculosis\nC. Hodgkin's lymphoma\nD. Histoplasmosis\nChoose the correct option.",
"image": null
},
{
"idx": 121,
"question": "A 27-year-old woman presents to her primary care physician for a general checkup. She has been doing well in school and has no complaints. The patient has a past medical history of asthma which is controlled with albuterol. She is currently sexually active but states that she uses birth control. She has many friends and states that her mood is typically positive. The patient's last pap smear was 1 year ago. Her father died of colon cancer at the age of 68, and her mother was diagnosed with breast cancer at the age of 65. Her temperature is 98.7°F (37.1°C), blood pressure is 147/108 mmHg, pulse is 80/min, respirations are 15/min, and oxygen saturation is 99% on room air. The patient's BMI is 19 kg/m^2. Physical exam demonstrates a normal S1 and S2, normal breath sounds, and an abdominal exam that is within normal limits. Which of the following is the best next step in management?\nA. Colonoscopy\nB. Discontinue birth control and place an intrauterine device\nC. Pap smear\nD. Recommend weight loss\n\nA. Colonoscopy\nB. Discontinue birth control and place an intrauterine device\nC. Pap smear\nD. Recommend weight loss",
"options": [
"A. Colonoscopy",
"B. Discontinue birth control and place an intrauterine device",
"C. Pap smear",
"D. Recommend weight loss"
],
"answer": "Discontinue birth control and place an intrauterine device",
"gen_text_store": "",
"pid": "121",
"query": "A 27-year-old woman presents to her primary care physician for a general checkup. She has been doing well in school and has no complaints. The patient has a past medical history of asthma which is controlled with albuterol. She is currently sexually active but states that she uses birth control. She has many friends and states that her mood is typically positive. The patient's last pap smear was 1 year ago. Her father died of colon cancer at the age of 68, and her mother was diagnosed with breast cancer at the age of 65. Her temperature is 98.7°F (37.1°C), blood pressure is 147/108 mmHg, pulse is 80/min, respirations are 15/min, and oxygen saturation is 99% on room air. The patient's BMI is 19 kg/m^2. Physical exam demonstrates a normal S1 and S2, normal breath sounds, and an abdominal exam that is within normal limits. Which of the following is the best next step in management?\nA. Colonoscopy\nB. Discontinue birth control and place an intrauterine device\nC. Pap smear\nD. Recommend weight loss\nChoose the correct option.",
"image": null
},
{
"idx": 122,
"question": "A 5-year-old male is brought to the pediatrician with complaints of a painful mouth/gums, and vesicular lesions on the lips and buccal mucosa for the past 4 days. The patient has not been able to eat or drink due to the pain and has been irritable. The patient also reports muscle aches. His vital signs are as follows: T 39.1, HR 110, BP 90/62, RR 18, SpO2 99%. Physical examination is significant for vesicular lesions noted on the tongue, gingiva, and lips, with some vesicles having ruptured and ulcerated, as well as palpable cervical and submandibular lymphadenopathy. Which of the following is the most likely causative organism in this patient's presentation?\nA. CMV\nB. HIV\nC. HSV-1\nD. HSV-2\n\nA. CMV\nB. HIV\nC. HSV-1\nD. HSV-2",
"options": [
"A. CMV",
"B. HIV",
"C. HSV-1",
"D. HSV-2"
],
"answer": "HSV-1",
"gen_text_store": "",
"pid": "122",
"query": "A 5-year-old male is brought to the pediatrician with complaints of a painful mouth/gums, and vesicular lesions on the lips and buccal mucosa for the past 4 days. The patient has not been able to eat or drink due to the pain and has been irritable. The patient also reports muscle aches. His vital signs are as follows: T 39.1, HR 110, BP 90/62, RR 18, SpO2 99%. Physical examination is significant for vesicular lesions noted on the tongue, gingiva, and lips, with some vesicles having ruptured and ulcerated, as well as palpable cervical and submandibular lymphadenopathy. Which of the following is the most likely causative organism in this patient's presentation?\nA. CMV\nB. HIV\nC. HSV-1\nD. HSV-2\nChoose the correct option.",
"image": null
},
{
"idx": 123,
"question": "An investigator is studying bacterial adaptations to the environment in an infectious isolate and a noninfectious isolate of Hemophilus influenzae type B. Animals exposed to the noninfectious isolate do not develop symptoms of infection. The investigator cultivates the noninfectious isolate in a culture with lysed bacteria from the infectious isolate. Some of the animals exposed to these bacteria develop symptoms of infection. Which of the following processes is most likely responsible for the described findings?\nA. Conjugation\nB. Reassortment\nC. Transformation\nD. Recombination\n\nA. Conjugation\nB. Reassortment\nC. Transformation\nD. Recombination",
"options": [
"A. Conjugation",
"B. Reassortment",
"C. Transformation",
"D. Recombination"
],
"answer": "Transformation",
"gen_text_store": "",
"pid": "123",
"query": "An investigator is studying bacterial adaptations to the environment in an infectious isolate and a noninfectious isolate of Hemophilus influenzae type B. Animals exposed to the noninfectious isolate do not develop symptoms of infection. The investigator cultivates the noninfectious isolate in a culture with lysed bacteria from the infectious isolate. Some of the animals exposed to these bacteria develop symptoms of infection. Which of the following processes is most likely responsible for the described findings?\nA. Conjugation\nB. Reassortment\nC. Transformation\nD. Recombination\nChoose the correct option.",
"image": null
},
{
"idx": 124,
"question": "A 56-year-old man is brought to the emergency room after a motor vehicle accident. The patient’s vitals are as follows: blood pressure 80/40 mm Hg, heart rate 111/min, respiratory rate 39/min, and temperature 37.1°C (98.8℉). On physical examination, the patient is unconscious with a GCS of 9/15 and is cyanotic. There are open fractures of the left femur and left tibia, a likely shoulder dislocation, multiple contusions on the limbs and thorax, and a puncture wound on the left side of his chest. There are no breath sounds on the left side and there is hyperresonance to percussion on the left. Preparations are made for an emergency needle thoracostomy to be performed to treat this patient’s likely tension pneumothorax. Which one of the following is the best choice to provide informed consent for this procedure?\nA. The patient’s closest relatives (spouse, child or parent), who must be brought to the hospital as fast as possible\nB. One of the witnesses at the scene of the car accident, who should be brought to the hospital as fast as possible\nC. The hospital ethics committee\nD. Informed consent is not needed in this case\n\nA. The patient’s closest relatives (spouse, child or parent), who must be brought to the hospital as fast as possible\nB. One of the witnesses at the scene of the car accident, who should be brought to the hospital as fast as possible\nC. The hospital ethics committee\nD. Informed consent is not needed in this case",
"options": [
"A. The patient’s closest relatives (spouse, child or parent), who must be brought to the hospital as fast as possible",
"B. One of the witnesses at the scene of the car accident, who should be brought to the hospital as fast as possible",
"C. The hospital ethics committee",
"D. Informed consent is not needed in this case"
],
"answer": "Informed consent is not needed in this case",
"gen_text_store": "",
"pid": "124",
"query": "A 56-year-old man is brought to the emergency room after a motor vehicle accident. The patient’s vitals are as follows: blood pressure 80/40 mm Hg, heart rate 111/min, respiratory rate 39/min, and temperature 37.1°C (98.8℉). On physical examination, the patient is unconscious with a GCS of 9/15 and is cyanotic. There are open fractures of the left femur and left tibia, a likely shoulder dislocation, multiple contusions on the limbs and thorax, and a puncture wound on the left side of his chest. There are no breath sounds on the left side and there is hyperresonance to percussion on the left. Preparations are made for an emergency needle thoracostomy to be performed to treat this patient’s likely tension pneumothorax. Which one of the following is the best choice to provide informed consent for this procedure?\nA. The patient’s closest relatives (spouse, child or parent), who must be brought to the hospital as fast as possible\nB. One of the witnesses at the scene of the car accident, who should be brought to the hospital as fast as possible\nC. The hospital ethics committee\nD. Informed consent is not needed in this case\nChoose the correct option.",
"image": null
},
{
"idx": 125,
"question": "A 30-year-old male presents to the emergency department with a complaint of abdominal pain. The patient states he was at a barbecue around noon. Lunch was arranged as a buffet without refrigeration. Within 2 to 3 hours, he had abdominal pain with 3 episodes of watery diarrhea. On exam, vital signs are T 99.1, HR 103, BP 110/55, RR 14. Abdominal exam is significant for pain to deep palpation without any rebounding or guarding. There is no blood on fecal occult testing (FOBT). What is the most likely cause of this patient's presentation?\nA. Salmonella enteritidis\nB. Listeria monocytogenes\nC. Staphylococcus aureus\nD. Vibrio cholerae\n\nA. Salmonella enteritidis\nB. Listeria monocytogenes\nC. Staphylococcus aureus\nD. Vibrio cholerae",
"options": [
"A. Salmonella enteritidis",
"B. Listeria monocytogenes",
"C. Staphylococcus aureus",
"D. Vibrio cholerae"
],
"answer": "Staphylococcus aureus",
"gen_text_store": "",
"pid": "125",
"query": "A 30-year-old male presents to the emergency department with a complaint of abdominal pain. The patient states he was at a barbecue around noon. Lunch was arranged as a buffet without refrigeration. Within 2 to 3 hours, he had abdominal pain with 3 episodes of watery diarrhea. On exam, vital signs are T 99.1, HR 103, BP 110/55, RR 14. Abdominal exam is significant for pain to deep palpation without any rebounding or guarding. There is no blood on fecal occult testing (FOBT). What is the most likely cause of this patient's presentation?\nA. Salmonella enteritidis\nB. Listeria monocytogenes\nC. Staphylococcus aureus\nD. Vibrio cholerae\nChoose the correct option.",
"image": null
},
{
"idx": 126,
"question": "A 3-year-old male was brought to the pediatrician with severe lip lacerations, with a portion of his tongue appearing to be bitten off, as well as missing portions of the fingers on his right hand. A family history is notable for two similar cases in male cousins on the mother's side. A urinalysis revealed a high level of uric acid. Which of the following is the mode of inheritance for this disorder?\nA. X-linked recessive\nB. X-linked dominant\nC. Autosomal dominant\nD. Maternally inherited mitochondrial defect\n\nA. X-linked recessive\nB. X-linked dominant\nC. Autosomal dominant\nD. Maternally inherited mitochondrial defect",
"options": [
"A. X-linked recessive",
"B. X-linked dominant",
"C. Autosomal dominant",
"D. Maternally inherited mitochondrial defect"
],
"answer": "X-linked recessive",
"gen_text_store": "",
"pid": "126",
"query": "A 3-year-old male was brought to the pediatrician with severe lip lacerations, with a portion of his tongue appearing to be bitten off, as well as missing portions of the fingers on his right hand. A family history is notable for two similar cases in male cousins on the mother's side. A urinalysis revealed a high level of uric acid. Which of the following is the mode of inheritance for this disorder?\nA. X-linked recessive\nB. X-linked dominant\nC. Autosomal dominant\nD. Maternally inherited mitochondrial defect\nChoose the correct option.",
"image": null
},
{
"idx": 127,
"question": "A 53-year-old man presents to his physician’s office with a persistent cough which he has had over the last few months. He was diagnosed with chronic obstructive pulmonary disease (COPD) the previous year and since then has been on a short-acting β-agonist to help alleviate his symptoms. Since his diagnosis, he has quit smoking, a habit which he had developed about 30 years ago. He used to smoke about 2 packs of cigarettes daily. Today, he has come in with an increase in his symptoms. He tells his physician that he has been having a fever for the past 3 days, ranging between 37.8°–39°C (100°F–102.2°F). Along with this, he has a persistent cough with copious amounts of greenish-yellow sputum. He has also been having difficulty breathing. On examination, his temperature is 38.6°C (101.5°F), the respirations are 22/min, the blood pressure is 110/80 mm Hg, and the pulse is 115/min. Slight crackles and respiratory wheezes are prominent in the lower lung fields. His FEV1 is 57% of his normal predicted value. He is started on oxygen and a dose of oral prednisone. At this time, which of the following should also be considered as a treatment option?\nA. Doxycycline\nB. Ciprofloxacin\nC. Erythromycin\nD. Antibiotics would not be appropriate at this time\n\nA. Doxycycline\nB. Ciprofloxacin\nC. Erythromycin\nD. Antibiotics would not be appropriate at this time",
"options": [
"A. Doxycycline",
"B. Ciprofloxacin",
"C. Erythromycin",
"D. Antibiotics would not be appropriate at this time"
],
"answer": "Doxycycline",
"gen_text_store": "",
"pid": "127",
"query": "A 53-year-old man presents to his physician’s office with a persistent cough which he has had over the last few months. He was diagnosed with chronic obstructive pulmonary disease (COPD) the previous year and since then has been on a short-acting β-agonist to help alleviate his symptoms. Since his diagnosis, he has quit smoking, a habit which he had developed about 30 years ago. He used to smoke about 2 packs of cigarettes daily. Today, he has come in with an increase in his symptoms. He tells his physician that he has been having a fever for the past 3 days, ranging between 37.8°–39°C (100°F–102.2°F). Along with this, he has a persistent cough with copious amounts of greenish-yellow sputum. He has also been having difficulty breathing. On examination, his temperature is 38.6°C (101.5°F), the respirations are 22/min, the blood pressure is 110/80 mm Hg, and the pulse is 115/min. Slight crackles and respiratory wheezes are prominent in the lower lung fields. His FEV1 is 57% of his normal predicted value. He is started on oxygen and a dose of oral prednisone. At this time, which of the following should also be considered as a treatment option?\nA. Doxycycline\nB. Ciprofloxacin\nC. Erythromycin\nD. Antibiotics would not be appropriate at this time\nChoose the correct option.",
"image": null
},
{
"idx": 128,
"question": "A 28-year-old woman presents to her primary care physician for evaluation of amenorrhea. Her last period occurred 4 months ago but she has not had sex in the last year and home pregnancy tests have come back negative. She first started having periods at age 13 and her periods have been unremarkable up until they stopped 4 months ago. Her past medical history is significant for radius and ulnar forearm fractures that she sustained in a car crash 3 months ago. She didn't see the car coming and has had increasing difficulty noticing objects in her peripheral vision. She also notes having recurrent headaches 5 months ago. Otherwise she has been healthy with no previous pregnancies. Physical exam reveals galactorrhea and temporal field visual defects. Which of the following mechanisms is most likely responsible for this patient's amenorrhea?\nA. Inhibition of gonadotropin-releasing hormone release\nB. Intrauterine scar tissue accumulation\nC. Nondisjunction of chromosomes\nD. Nutritional imbalance\n\nA. Inhibition of gonadotropin-releasing hormone release\nB. Intrauterine scar tissue accumulation\nC. Nondisjunction of chromosomes\nD. Nutritional imbalance",
"options": [
"A. Inhibition of gonadotropin-releasing hormone release",
"B. Intrauterine scar tissue accumulation",
"C. Nondisjunction of chromosomes",
"D. Nutritional imbalance"
],
"answer": "Inhibition of gonadotropin-releasing hormone release",
"gen_text_store": "",
"pid": "128",
"query": "A 28-year-old woman presents to her primary care physician for evaluation of amenorrhea. Her last period occurred 4 months ago but she has not had sex in the last year and home pregnancy tests have come back negative. She first started having periods at age 13 and her periods have been unremarkable up until they stopped 4 months ago. Her past medical history is significant for radius and ulnar forearm fractures that she sustained in a car crash 3 months ago. She didn't see the car coming and has had increasing difficulty noticing objects in her peripheral vision. She also notes having recurrent headaches 5 months ago. Otherwise she has been healthy with no previous pregnancies. Physical exam reveals galactorrhea and temporal field visual defects. Which of the following mechanisms is most likely responsible for this patient's amenorrhea?\nA. Inhibition of gonadotropin-releasing hormone release\nB. Intrauterine scar tissue accumulation\nC. Nondisjunction of chromosomes\nD. Nutritional imbalance\nChoose the correct option.",
"image": null
},
{
"idx": 129,
"question": "A 45-year-old G5P4105 presents to her gynecologist’s office with six months of increasingly heavy periods. She now soaks one super absorbent tampon every two hours for five days each cycle. Her cycles have also become irregular, with intermenstrual bleeding for the last two months. She now experiences significant dysmenorrhea, requiring 400 mg ibuprofen every four hours for the majority of each menses. In addition, she reports new onset mild dyspareunia with intercourse and a “heavy feeling” in her pelvis. She has also noticed increased urinary frequency but denies bowel changes. The patient has a past medical history of obesity and type II diabetes on metformin. Her last child was born four years ago, and she has had five spontaneous vaginal deliveries. At this office visit, temperature is 98.5°F (36.9°C), blood pressure is 137/84 mmHg, pulse is 87/min, and respirations are 14/min. Which of the following physical exam findings is most likely to be present in this patient?\nA. Globular 10-week sized uterus\nB. Adnexal mass\nC. Irregular 14-week sized uterus\nD. No remarkable physical exam finding\n\nA. Globular 10-week sized uterus\nB. Adnexal mass\nC. Irregular 14-week sized uterus\nD. No remarkable physical exam finding",
"options": [
"A. Globular 10-week sized uterus",
"B. Adnexal mass",
"C. Irregular 14-week sized uterus",
"D. No remarkable physical exam finding"
],
"answer": "Globular 10-week sized uterus",
"gen_text_store": "",
"pid": "129",
"query": "A 45-year-old G5P4105 presents to her gynecologist’s office with six months of increasingly heavy periods. She now soaks one super absorbent tampon every two hours for five days each cycle. Her cycles have also become irregular, with intermenstrual bleeding for the last two months. She now experiences significant dysmenorrhea, requiring 400 mg ibuprofen every four hours for the majority of each menses. In addition, she reports new onset mild dyspareunia with intercourse and a “heavy feeling” in her pelvis. She has also noticed increased urinary frequency but denies bowel changes. The patient has a past medical history of obesity and type II diabetes on metformin. Her last child was born four years ago, and she has had five spontaneous vaginal deliveries. At this office visit, temperature is 98.5°F (36.9°C), blood pressure is 137/84 mmHg, pulse is 87/min, and respirations are 14/min. Which of the following physical exam findings is most likely to be present in this patient?\nA. Globular 10-week sized uterus\nB. Adnexal mass\nC. Irregular 14-week sized uterus\nD. No remarkable physical exam finding\nChoose the correct option.",
"image": null
},
{
"idx": 130,
"question": "A gunshot victim is brought to the Emergency Department and appears to be in shock. You note a penetrating wound at the level of L3. Assuming the bullet remained at this level, which vascular structure might have been injured?\nA. Inferior vena cava\nB. Internal iliac vein\nC. Renal artery\nD. Portal vein\n\nA. Inferior vena cava\nB. Internal iliac vein\nC. Renal artery\nD. Portal vein",
"options": [
"A. Inferior vena cava",
"B. Internal iliac vein",
"C. Renal artery",
"D. Portal vein"
],
"answer": "Inferior vena cava",
"gen_text_store": "",
"pid": "130",
"query": "A gunshot victim is brought to the Emergency Department and appears to be in shock. You note a penetrating wound at the level of L3. Assuming the bullet remained at this level, which vascular structure might have been injured?\nA. Inferior vena cava\nB. Internal iliac vein\nC. Renal artery\nD. Portal vein\nChoose the correct option.",
"image": null
},
{
"idx": 131,
"question": "A 48-year-old man presents to the clinic with nausea, vomiting, fever, and pain in the right upper quadrant of his abdomen for the past 18 hours. He mentions that he has been experiencing intermittent episodes of pain at the same location over the last 3 months and that these episodes usually occur after a heavy meal and subside within 1 or 2 hours. On physical examination, his temperature is 38.5°C (101.3°F), pulse is 130/min, respirations are 24/min, and blood pressure is 130/84 mm Hg. On examination of the abdomen, tenderness is present over the right upper quadrant; palpation over the area produces an inspiratory pause. An urgent bedside ultrasonogram shows a dilated common bile duct stone, but no stone in the common bile duct or in the gallbladder. Laboratory results show the following:\nHemoglobin 15.4 g/dL (9.56 mmol/L)\nTotal leukocyte count 14,000/mm3 (17.4 x 10*9/L)\nSegmented neutrophils 70%\nLymphocytes 25%\nMonocytes 4%\nEosinophils 1%\nBasophils 0%\nPlatelet count 32,0000/mm3 (320 x 10*9/L)\nSerum bilirubin (total) 1.8 mg/dL (30.78 μmol/L)\nSerum bilirubin (direct) 1.1 mg/dL (18.81 μmol/L)\nSerum alanine aminotransferase 96 U/L\nSerum aspartate aminotransferase 88 U/L\nSerum alkaline phosphatase\n350 U/L (5.83 μkat/L)\nWhich of the following is the most appropriate next step in management?\nA. Urgent laparoscopic cholecystectomy\nB. Medical management followed by elective laparoscopic cholecystectomy\nC. Urgent endoscopic retrograde cholangiopancreatography (ECRP)\nD. Cholecystotomy\n\nA. Urgent laparoscopic cholecystectomy\nB. Medical management followed by elective laparoscopic cholecystectomy\nC. Urgent endoscopic retrograde cholangiopancreatography (ECRP)\nD. Cholecystotomy",
"options": [
"A. Urgent laparoscopic cholecystectomy",
"B. Medical management followed by elective laparoscopic cholecystectomy",
"C. Urgent endoscopic retrograde cholangiopancreatography (ECRP)",
"D. Cholecystotomy"
],
"answer": "Urgent endoscopic retrograde cholangiopancreatography (ECRP)",
"gen_text_store": "",
"pid": "131",
"query": "A 48-year-old man presents to the clinic with nausea, vomiting, fever, and pain in the right upper quadrant of his abdomen for the past 18 hours. He mentions that he has been experiencing intermittent episodes of pain at the same location over the last 3 months and that these episodes usually occur after a heavy meal and subside within 1 or 2 hours. On physical examination, his temperature is 38.5°C (101.3°F), pulse is 130/min, respirations are 24/min, and blood pressure is 130/84 mm Hg. On examination of the abdomen, tenderness is present over the right upper quadrant; palpation over the area produces an inspiratory pause. An urgent bedside ultrasonogram shows a dilated common bile duct stone, but no stone in the common bile duct or in the gallbladder. Laboratory results show the following:\nHemoglobin 15.4 g/dL (9.56 mmol/L)\nTotal leukocyte count 14,000/mm3 (17.4 x 10*9/L)\nSegmented neutrophils 70%\nLymphocytes 25%\nMonocytes 4%\nEosinophils 1%\nBasophils 0%\nPlatelet count 32,0000/mm3 (320 x 10*9/L)\nSerum bilirubin (total) 1.8 mg/dL (30.78 μmol/L)\nSerum bilirubin (direct) 1.1 mg/dL (18.81 μmol/L)\nSerum alanine aminotransferase 96 U/L\nSerum aspartate aminotransferase 88 U/L\nSerum alkaline phosphatase\n350 U/L (5.83 μkat/L)\nWhich of the following is the most appropriate next step in management?\nA. Urgent laparoscopic cholecystectomy\nB. Medical management followed by elective laparoscopic cholecystectomy\nC. Urgent endoscopic retrograde cholangiopancreatography (ECRP)\nD. Cholecystotomy\nChoose the correct option.",
"image": null
},
{
"idx": 132,
"question": "A 56-year-old woman comes to the physician because of a 2-week history of fatigue and painless bruising over her arms and trunk. She has also had several episodes of nosebleeds that resolved with compression after a few minutes. She recently completed treatment for a urinary tract infection. She has had no changes in her weight. She has type 2 diabetes mellitus and hypertension. Her last menstrual cycle was 5 years ago. She does not smoke or drink alcohol. Home medications include metformin, amlodipine, and enalapril. Her vital signs are within normal limits. Physical examination shows pale conjunctivae. There are ecchymoses and petechiae over the upper extremities, chest, and back. There is no lymphadenopathy. The remainder of the physical examination is unremarkable. Laboratory studies show:\nHemoglobin 8.7 mg/dL\nLeukocyte count 1100/mm3\nPlatelet count 54,000/mm3\nReticulocyte count 0.1%\nMean corpuscular volume 93 μm3\nSerum\nTotal bilirubin 1.1 mg/dL\nLDH 80 U/L\nWhich of the following is most likely to confirm the diagnosis?\"\nA. Serum transferrin level\nB. Bone marrow biopsy\nC. Peripheral blood smear\nD. Serum porphobilinogen level\n\nA. Serum transferrin level\nB. Bone marrow biopsy\nC. Peripheral blood smear\nD. Serum porphobilinogen level",
"options": [
"A. Serum transferrin level",
"B. Bone marrow biopsy",
"C. Peripheral blood smear",
"D. Serum porphobilinogen level"
],
"answer": "Bone marrow biopsy",
"gen_text_store": "",
"pid": "132",
"query": "A 56-year-old woman comes to the physician because of a 2-week history of fatigue and painless bruising over her arms and trunk. She has also had several episodes of nosebleeds that resolved with compression after a few minutes. She recently completed treatment for a urinary tract infection. She has had no changes in her weight. She has type 2 diabetes mellitus and hypertension. Her last menstrual cycle was 5 years ago. She does not smoke or drink alcohol. Home medications include metformin, amlodipine, and enalapril. Her vital signs are within normal limits. Physical examination shows pale conjunctivae. There are ecchymoses and petechiae over the upper extremities, chest, and back. There is no lymphadenopathy. The remainder of the physical examination is unremarkable. Laboratory studies show:\nHemoglobin 8.7 mg/dL\nLeukocyte count 1100/mm3\nPlatelet count 54,000/mm3\nReticulocyte count 0.1%\nMean corpuscular volume 93 μm3\nSerum\nTotal bilirubin 1.1 mg/dL\nLDH 80 U/L\nWhich of the following is most likely to confirm the diagnosis?\"\nA. Serum transferrin level\nB. Bone marrow biopsy\nC. Peripheral blood smear\nD. Serum porphobilinogen level\nChoose the correct option.",
"image": null
},
{
"idx": 133,
"question": "A 68-year-old man comes to the physician with a 1-week history of painless hematuria. A CT scan of the urinary tract shows areas of bladder wall thickening. Cystoscopy shows several sessile masses with central necrosis arising from the bladder wall. A biopsy specimen of the bladder masses shows moderately differentiated urothelial cells with abundant mitotic figures and nuclear atypia. The patient most likely has a history of exposure to which of the following?\nA. Ionizing radiation\nB. Aromatic amines\nC. Aflatoxins\nD. Radon\n\nA. Ionizing radiation\nB. Aromatic amines\nC. Aflatoxins\nD. Radon",
"options": [
"A. Ionizing radiation",
"B. Aromatic amines",
"C. Aflatoxins",
"D. Radon"
],
"answer": "Aromatic amines",
"gen_text_store": "",
"pid": "133",
"query": "A 68-year-old man comes to the physician with a 1-week history of painless hematuria. A CT scan of the urinary tract shows areas of bladder wall thickening. Cystoscopy shows several sessile masses with central necrosis arising from the bladder wall. A biopsy specimen of the bladder masses shows moderately differentiated urothelial cells with abundant mitotic figures and nuclear atypia. The patient most likely has a history of exposure to which of the following?\nA. Ionizing radiation\nB. Aromatic amines\nC. Aflatoxins\nD. Radon\nChoose the correct option.",
"image": null
},
{
"idx": 134,
"question": "A 55-year-old man is brought to the emergency department 12 hours after the sudden onset of shortness of breath and substernal chest pain at rest; the pain is increased by inspiration. He has also had a nonproductive cough, fever, and malaise for the past 5 days. He does not smoke or use illicit drugs. His temperature is 38°C (100.4°F), pulse is 125/min, respirations are 32/min, and blood pressure is 85/45 mm Hg. Physical examination shows distended neck veins. Auscultation of the chest discloses bilateral basilar rales and muffled heart sounds. An ECG shows sinus tachycardia, diffuse ST segment elevation, low voltage QRS complexes, and fluctuating R wave amplitude. Which of the following is the most likely diagnosis?\nA. Kawasaki disease\nB. Rheumatic fever\nC. Infective endocarditis\nD. Cardiac tamponade\n\nA. Kawasaki disease\nB. Rheumatic fever\nC. Infective endocarditis\nD. Cardiac tamponade",
"options": [
"A. Kawasaki disease",
"B. Rheumatic fever",
"C. Infective endocarditis",
"D. Cardiac tamponade"
],
"answer": "Cardiac tamponade",
"gen_text_store": "",
"pid": "134",
"query": "A 55-year-old man is brought to the emergency department 12 hours after the sudden onset of shortness of breath and substernal chest pain at rest; the pain is increased by inspiration. He has also had a nonproductive cough, fever, and malaise for the past 5 days. He does not smoke or use illicit drugs. His temperature is 38°C (100.4°F), pulse is 125/min, respirations are 32/min, and blood pressure is 85/45 mm Hg. Physical examination shows distended neck veins. Auscultation of the chest discloses bilateral basilar rales and muffled heart sounds. An ECG shows sinus tachycardia, diffuse ST segment elevation, low voltage QRS complexes, and fluctuating R wave amplitude. Which of the following is the most likely diagnosis?\nA. Kawasaki disease\nB. Rheumatic fever\nC. Infective endocarditis\nD. Cardiac tamponade\nChoose the correct option.",
"image": null
},
{
"idx": 135,
"question": "A 33-year-old man presents to the emergency department with a cough. He states that 2 weeks ago, he had a fever, chills, and a cough, which his primary doctor treated with acetaminophen, ibuprofen, and rest. Since then, the patient’s symptoms have resolved with the exception of a chronic cough and a small amount of clear sputum that is occasionally laced with blood. The patient denies chest pain, shortness of breath, fever, or chills. The patient is otherwise healthy and is currently taking metformin and albuterol. His temperature is 98.3°F (36.8°C), blood pressure is 129/75 mmHg, pulse is 84/min, respirations are 15/min, and oxygen saturation is 99% on room air. Physical exam is notable for bilateral clear breath sounds, absence of lymphadenopathy on HEENT exam, and a normal oropharynx. Which of the following is the best next step in management?\nA. Chest radiograph\nB. D-dimer\nC. Sputum culture\nD. Supportive care\n\nA. Chest radiograph\nB. D-dimer\nC. Sputum culture\nD. Supportive care",
"options": [
"A. Chest radiograph",
"B. D-dimer",
"C. Sputum culture",
"D. Supportive care"
],
"answer": "Supportive care",
"gen_text_store": "",
"pid": "135",
"query": "A 33-year-old man presents to the emergency department with a cough. He states that 2 weeks ago, he had a fever, chills, and a cough, which his primary doctor treated with acetaminophen, ibuprofen, and rest. Since then, the patient’s symptoms have resolved with the exception of a chronic cough and a small amount of clear sputum that is occasionally laced with blood. The patient denies chest pain, shortness of breath, fever, or chills. The patient is otherwise healthy and is currently taking metformin and albuterol. His temperature is 98.3°F (36.8°C), blood pressure is 129/75 mmHg, pulse is 84/min, respirations are 15/min, and oxygen saturation is 99% on room air. Physical exam is notable for bilateral clear breath sounds, absence of lymphadenopathy on HEENT exam, and a normal oropharynx. Which of the following is the best next step in management?\nA. Chest radiograph\nB. D-dimer\nC. Sputum culture\nD. Supportive care\nChoose the correct option.",
"image": null
},
{
"idx": 136,
"question": "A 2-day-old boy delivered at 34 weeks gestation is found to have a murmur on routine exam. He is lying supine and is not cyanotic. He has a pulse of 195/min, and respirations of 59/min. He is found to have a nonradiating continuous machine-like murmur at the left upper sternal border. S1 and S2 are normal. The peripheral pulses are bounding. Assuming this patient has no other cardiovascular defects, what is the most appropriate treatment?\nA. Indomethacin\nB. Thiazide diuretic\nC. Aspirin\nD. Penicillin\n\nA. Indomethacin\nB. Thiazide diuretic\nC. Aspirin\nD. Penicillin",
"options": [
"A. Indomethacin",
"B. Thiazide diuretic",
"C. Aspirin",
"D. Penicillin"
],
"answer": "Indomethacin",
"gen_text_store": "",
"pid": "136",
"query": "A 2-day-old boy delivered at 34 weeks gestation is found to have a murmur on routine exam. He is lying supine and is not cyanotic. He has a pulse of 195/min, and respirations of 59/min. He is found to have a nonradiating continuous machine-like murmur at the left upper sternal border. S1 and S2 are normal. The peripheral pulses are bounding. Assuming this patient has no other cardiovascular defects, what is the most appropriate treatment?\nA. Indomethacin\nB. Thiazide diuretic\nC. Aspirin\nD. Penicillin\nChoose the correct option.",
"image": null
},
{
"idx": 137,
"question": "A student studying pharmacology is a member of a team that is conducting research related to the elimination of multiple anticoagulant medications. His duty as a member of the team is to collect serum samples of the subjects every 4 hours and send them for analysis of serum drug levels. He is also supposed to collect, document and analyze the data. For one of the subjects, he notices that the subject is eliminating 0.5 mg of the drug every 4 hours. Which of the following anticoagulants did this patient most likely consume?\nA. Warfarin\nB. Enoxaparin\nC. Fondaparinux\nD. Apixaban\n\nA. Warfarin\nB. Enoxaparin\nC. Fondaparinux\nD. Apixaban",
"options": [
"A. Warfarin",
"B. Enoxaparin",
"C. Fondaparinux",
"D. Apixaban"
],
"answer": "Warfarin",
"gen_text_store": "",
"pid": "137",
"query": "A student studying pharmacology is a member of a team that is conducting research related to the elimination of multiple anticoagulant medications. His duty as a member of the team is to collect serum samples of the subjects every 4 hours and send them for analysis of serum drug levels. He is also supposed to collect, document and analyze the data. For one of the subjects, he notices that the subject is eliminating 0.5 mg of the drug every 4 hours. Which of the following anticoagulants did this patient most likely consume?\nA. Warfarin\nB. Enoxaparin\nC. Fondaparinux\nD. Apixaban\nChoose the correct option.",
"image": null
},
{
"idx": 138,
"question": "A 7-month-old boy is brought to the physician because of a 2-month history of fatigue, weakness, and difficulty feeding. He was delivered at term to a 32-year-old woman. He is not able to sit upright on his own. He is at the 75th percentile for height and 25th percentile for weight. His temperature is 37.7°C (99.8°F), blood pressure is 110/68 mm Hg, pulse is 150/min, and respirations are 50/min. His tongue protrudes beyond the teeth. Neck veins are distended. Crackles are heard at both lung bases. Cardiac examination shows an S3 gallop. The liver is palpated 2 cm below the right costal margin. Neurologic examination shows profound weakness in proximal and distal muscles of the upper and lower extremities. He has 2+ reflexes bilaterally. A chest x-ray shows cardiomegaly. Serum glucose is 105 mg/dL. Which of the following is the enzyme most likely to be defective in this patient?\nA. Muscle glycogen phosphorylase\nB. Very-long-chain acyl-CoA dehydrogenase\nC. Lysosomal acid maltase\nD. Glycogen debranching enzyme\n\nA. Muscle glycogen phosphorylase\nB. Very-long-chain acyl-CoA dehydrogenase\nC. Lysosomal acid maltase\nD. Glycogen debranching enzyme",
"options": [
"A. Muscle glycogen phosphorylase",
"B. Very-long-chain acyl-CoA dehydrogenase",
"C. Lysosomal acid maltase",
"D. Glycogen debranching enzyme"
],
"answer": "Lysosomal acid maltase",
"gen_text_store": "",
"pid": "138",
"query": "A 7-month-old boy is brought to the physician because of a 2-month history of fatigue, weakness, and difficulty feeding. He was delivered at term to a 32-year-old woman. He is not able to sit upright on his own. He is at the 75th percentile for height and 25th percentile for weight. His temperature is 37.7°C (99.8°F), blood pressure is 110/68 mm Hg, pulse is 150/min, and respirations are 50/min. His tongue protrudes beyond the teeth. Neck veins are distended. Crackles are heard at both lung bases. Cardiac examination shows an S3 gallop. The liver is palpated 2 cm below the right costal margin. Neurologic examination shows profound weakness in proximal and distal muscles of the upper and lower extremities. He has 2+ reflexes bilaterally. A chest x-ray shows cardiomegaly. Serum glucose is 105 mg/dL. Which of the following is the enzyme most likely to be defective in this patient?\nA. Muscle glycogen phosphorylase\nB. Very-long-chain acyl-CoA dehydrogenase\nC. Lysosomal acid maltase\nD. Glycogen debranching enzyme\nChoose the correct option.",
"image": null
},
{
"idx": 139,
"question": "A 17-year-old woman presents to your office concerned that she has not had her menstrual period in 4 months. She states that menses began at age of 13 and has been regular until two months ago. She denies sexual activity, and urine pregnancy test is negative. On exam, she appears well-nourished with a BMI of 21 kg/m^2, but you note that she has enlarged cheeks bilaterally and has calluses on the dorsum of her hands. She says that she has been very stressed with school and has recently been binge eating. What other finding do you expect to see in this patient?\nA. Malar rash\nB. Increased blood glucose level\nC. Erosion of tooth enamel\nD. Elevated estrogen levels\n\nA. Malar rash\nB. Increased blood glucose level\nC. Erosion of tooth enamel\nD. Elevated estrogen levels",
"options": [
"A. Malar rash",
"B. Increased blood glucose level",
"C. Erosion of tooth enamel",
"D. Elevated estrogen levels"
],
"answer": "Erosion of tooth enamel",
"gen_text_store": "",
"pid": "139",
"query": "A 17-year-old woman presents to your office concerned that she has not had her menstrual period in 4 months. She states that menses began at age of 13 and has been regular until two months ago. She denies sexual activity, and urine pregnancy test is negative. On exam, she appears well-nourished with a BMI of 21 kg/m^2, but you note that she has enlarged cheeks bilaterally and has calluses on the dorsum of her hands. She says that she has been very stressed with school and has recently been binge eating. What other finding do you expect to see in this patient?\nA. Malar rash\nB. Increased blood glucose level\nC. Erosion of tooth enamel\nD. Elevated estrogen levels\nChoose the correct option.",
"image": null
},
{
"idx": 140,
"question": "A 40-year-old woman presents with severe shortness of breath. The patient is unable to provide a history due to her breathing difficulties. The patient’s roommate says that she came home and found her in this state. She also says that they both occasionally take sleeping pills to help them fall asleep. Physical examination reveals an obese female, dyspneic with diminished chest wall movements. The patient’s A-a gradient is calculated to be 10 mm Hg. Which of the following most likely accounts for this patient’s symptoms?\nA. Alveolar hypoventilation\nB. Impaired gas diffusion\nC. Left-to-right blood shunt\nD. Right-to-left blood shunt\n\nA. Alveolar hypoventilation\nB. Impaired gas diffusion\nC. Left-to-right blood shunt\nD. Right-to-left blood shunt",
"options": [
"A. Alveolar hypoventilation",
"B. Impaired gas diffusion",
"C. Left-to-right blood shunt",
"D. Right-to-left blood shunt"
],
"answer": "Alveolar hypoventilation",
"gen_text_store": "",
"pid": "140",
"query": "A 40-year-old woman presents with severe shortness of breath. The patient is unable to provide a history due to her breathing difficulties. The patient’s roommate says that she came home and found her in this state. She also says that they both occasionally take sleeping pills to help them fall asleep. Physical examination reveals an obese female, dyspneic with diminished chest wall movements. The patient’s A-a gradient is calculated to be 10 mm Hg. Which of the following most likely accounts for this patient’s symptoms?\nA. Alveolar hypoventilation\nB. Impaired gas diffusion\nC. Left-to-right blood shunt\nD. Right-to-left blood shunt\nChoose the correct option.",
"image": null
},
{
"idx": 141,
"question": "A 28-year-old woman, gravida 2, para 1, at 40 weeks of gestation is admitted to the hospital in active labor. The patient has attended many prenatal appointments and followed her physician's advice about screening for diseases, laboratory testing, diet, and exercise. Her pregnancy has been uncomplicated. She has no history of a serious illness. Her first child was delivered via normal vaginal delivery. Her vital signs are within normal limits. Cervical examination shows 100% effacement and 10 cm dilation. A cardiotocograph is shown. Which of the following is the most appropriate initial step in management?\nA. Amnioinfusion\nB. Induced vaginal delivery\nC. Reassurance\nD. Repositioning\n\nA. Amnioinfusion\nB. Induced vaginal delivery\nC. Reassurance\nD. Repositioning",
"options": [
"A. Amnioinfusion",
"B. Induced vaginal delivery",
"C. Reassurance",
"D. Repositioning"
],
"answer": "Reassurance",
"gen_text_store": "",
"pid": "141",
"query": "A 28-year-old woman, gravida 2, para 1, at 40 weeks of gestation is admitted to the hospital in active labor. The patient has attended many prenatal appointments and followed her physician's advice about screening for diseases, laboratory testing, diet, and exercise. Her pregnancy has been uncomplicated. She has no history of a serious illness. Her first child was delivered via normal vaginal delivery. Her vital signs are within normal limits. Cervical examination shows 100% effacement and 10 cm dilation. A cardiotocograph is shown. Which of the following is the most appropriate initial step in management?\nA. Amnioinfusion\nB. Induced vaginal delivery\nC. Reassurance\nD. Repositioning\nChoose the correct option.",
"image": null
},
{
"idx": 142,
"question": "A 54-year-old man comes to the clinic for management of his gastroesophageal reflux disease (GERD). He is currently on cimetidine for his condition and reports that his GERD initially improved. However, following his recent move to Michigan, he is experiencing more frequent episodes of chest pain (4-5 times a week). The pain is described as burning in quality and is concentrated around his epigastric region following food ingestion. It does not radiate anywhere and is alleviated when he takes antacids. A physical examination demonstrates a healthy male with unremarkable findings. He is subsequently prescribed a new medication for control of his symptoms. What is the most likely mechanism of action of this new medication?\nA. Irreversible inactivation of cyclooxygenase enzyme\nB. Irreversible inhibition of H+/K+-ATPase at parietal cells\nC. Reversible inhibition of H+/K+-ATPase at parietal cells\nD. Reversible inhibition of histamine H2 receptors\n\nA. Irreversible inactivation of cyclooxygenase enzyme\nB. Irreversible inhibition of H+/K+-ATPase at parietal cells\nC. Reversible inhibition of H+/K+-ATPase at parietal cells\nD. Reversible inhibition of histamine H2 receptors",
"options": [
"A. Irreversible inactivation of cyclooxygenase enzyme",
"B. Irreversible inhibition of H+/K+-ATPase at parietal cells",
"C. Reversible inhibition of H+/K+-ATPase at parietal cells",
"D. Reversible inhibition of histamine H2 receptors"
],
"answer": "Irreversible inhibition of H+/K+-ATPase at parietal cells",
"gen_text_store": "",
"pid": "142",
"query": "A 54-year-old man comes to the clinic for management of his gastroesophageal reflux disease (GERD). He is currently on cimetidine for his condition and reports that his GERD initially improved. However, following his recent move to Michigan, he is experiencing more frequent episodes of chest pain (4-5 times a week). The pain is described as burning in quality and is concentrated around his epigastric region following food ingestion. It does not radiate anywhere and is alleviated when he takes antacids. A physical examination demonstrates a healthy male with unremarkable findings. He is subsequently prescribed a new medication for control of his symptoms. What is the most likely mechanism of action of this new medication?\nA. Irreversible inactivation of cyclooxygenase enzyme\nB. Irreversible inhibition of H+/K+-ATPase at parietal cells\nC. Reversible inhibition of H+/K+-ATPase at parietal cells\nD. Reversible inhibition of histamine H2 receptors\nChoose the correct option.",
"image": null
},
{
"idx": 143,
"question": "A 30-year-old male presents to his primary care physician complaining of infertility. He and his wife have been trying to get pregnant for the past two years. They have used fertility monitors and other aids without success. A hysterosalpingogram in his wife was normal. The patient has a history of cleft lip and recurrent upper respiratory infections as a child. He was briefly hospitalized for severe pneumonia when he was 9-years-old. His temperature is 98.6°F (37°C), blood pressure is 120/85 mmHg, pulse is 90/min, and respirations are 18/min. On examination, he is a healthy-appearing male in no acute distress with fully developed reproductive organs. Notably, cardiac auscultation is silent in the left 5th intercostal space at the midclavicular line. This patient most likely has a mutation in which of the following classes of proteins?\nA. Microtubule monomeric protein\nB. Transmembrane ion channel protein\nC. Retrograde cytoskeletal motor protein\nD. Anterograde cytoskeletal motor protein\n\nA. Microtubule monomeric protein\nB. Transmembrane ion channel protein\nC. Retrograde cytoskeletal motor protein\nD. Anterograde cytoskeletal motor protein",
"options": [
"A. Microtubule monomeric protein",
"B. Transmembrane ion channel protein",
"C. Retrograde cytoskeletal motor protein",
"D. Anterograde cytoskeletal motor protein"
],
"answer": "Retrograde cytoskeletal motor protein",
"gen_text_store": "",
"pid": "143",
"query": "A 30-year-old male presents to his primary care physician complaining of infertility. He and his wife have been trying to get pregnant for the past two years. They have used fertility monitors and other aids without success. A hysterosalpingogram in his wife was normal. The patient has a history of cleft lip and recurrent upper respiratory infections as a child. He was briefly hospitalized for severe pneumonia when he was 9-years-old. His temperature is 98.6°F (37°C), blood pressure is 120/85 mmHg, pulse is 90/min, and respirations are 18/min. On examination, he is a healthy-appearing male in no acute distress with fully developed reproductive organs. Notably, cardiac auscultation is silent in the left 5th intercostal space at the midclavicular line. This patient most likely has a mutation in which of the following classes of proteins?\nA. Microtubule monomeric protein\nB. Transmembrane ion channel protein\nC. Retrograde cytoskeletal motor protein\nD. Anterograde cytoskeletal motor protein\nChoose the correct option.",
"image": null
},
{
"idx": 144,
"question": "A 24-year-old married woman presents to the emergency department with severe abdominal pain since last night. She also complains of scant vaginal bleeding. She says she visited a physician last year who said she had a pelvic infection, but she was never treated because of insurance issues. She also says her period has been delayed this month. She is afebrile. The pulse is 124/min and the blood pressure is 100/70 mm Hg. On examination, her abdomen is distended and tender. A pregnancy test was positive. A complication of infection with which of the following organisms most likely led to this patient’s condition?\nA. Candida albicans\nB. Neisseria gonorrhoeae\nC. Chlamydia trachomatis\nD. Haemophilus influenzae\n\nA. Candida albicans\nB. Neisseria gonorrhoeae\nC. Chlamydia trachomatis\nD. Haemophilus influenzae",
"options": [
"A. Candida albicans",
"B. Neisseria gonorrhoeae",
"C. Chlamydia trachomatis",
"D. Haemophilus influenzae"
],
"answer": "Chlamydia trachomatis",
"gen_text_store": "",
"pid": "144",
"query": "A 24-year-old married woman presents to the emergency department with severe abdominal pain since last night. She also complains of scant vaginal bleeding. She says she visited a physician last year who said she had a pelvic infection, but she was never treated because of insurance issues. She also says her period has been delayed this month. She is afebrile. The pulse is 124/min and the blood pressure is 100/70 mm Hg. On examination, her abdomen is distended and tender. A pregnancy test was positive. A complication of infection with which of the following organisms most likely led to this patient’s condition?\nA. Candida albicans\nB. Neisseria gonorrhoeae\nC. Chlamydia trachomatis\nD. Haemophilus influenzae\nChoose the correct option.",
"image": null
},
{
"idx": 145,
"question": "A 54-year-old male makes an appointment with his primary care physician due to chronic fatigue that has left him unable to hike or do other physically demanding activities with his friends. He has well-controlled hypertension and diabetes but has otherwise been healthy. He does not smoke but drinks socially with his friends. Physical exam reveals enlarged nodules that are not tender to palpation. A biopsy is obtained showing a characteristic change in chromosome 18. The regulation of which of the following proteins will be most abnormal in this patient?\nA. Caspase-9\nB. CD15\nC. Cyclin-dependent kinase 4\nD. Ras pathway transcription factors\n\nA. Caspase-9\nB. CD15\nC. Cyclin-dependent kinase 4\nD. Ras pathway transcription factors",
"options": [
"A. Caspase-9",
"B. CD15",
"C. Cyclin-dependent kinase 4",
"D. Ras pathway transcription factors"
],
"answer": "Caspase-9",
"gen_text_store": "",
"pid": "145",
"query": "A 54-year-old male makes an appointment with his primary care physician due to chronic fatigue that has left him unable to hike or do other physically demanding activities with his friends. He has well-controlled hypertension and diabetes but has otherwise been healthy. He does not smoke but drinks socially with his friends. Physical exam reveals enlarged nodules that are not tender to palpation. A biopsy is obtained showing a characteristic change in chromosome 18. The regulation of which of the following proteins will be most abnormal in this patient?\nA. Caspase-9\nB. CD15\nC. Cyclin-dependent kinase 4\nD. Ras pathway transcription factors\nChoose the correct option.",
"image": null
},
{
"idx": 146,
"question": "A 36-year-old man undergoes open reduction and internal fixation of a left femur fracture sustained after a motor vehicle collision. Three days after the surgery, he develops fever and redness around the surgical site. His temperature is 39.5°C (103.1°F). Physical examination shows purulent discharge from the wound with erythema of the surrounding skin. Wound culture of the purulent discharge shows gram-positive cocci in clusters. Treatment with oral dicloxacillin is initiated. Four days later, the patient continues to have high-grade fever, pain, and purulent discharge. Which of the following characteristics of the infecting organism best explains the failure to improve with antibiotic therapy?\nA. Presence of an impenetrable outer membrane\nB. Ability to cleave β-lactam rings\nC. Development of efflux pumps\nD. Adaptation in binding proteins\n\nA. Presence of an impenetrable outer membrane\nB. Ability to cleave β-lactam rings\nC. Development of efflux pumps\nD. Adaptation in binding proteins",
"options": [
"A. Presence of an impenetrable outer membrane",
"B. Ability to cleave β-lactam rings",
"C. Development of efflux pumps",
"D. Adaptation in binding proteins"
],
"answer": "Adaptation in binding proteins",
"gen_text_store": "",
"pid": "146",
"query": "A 36-year-old man undergoes open reduction and internal fixation of a left femur fracture sustained after a motor vehicle collision. Three days after the surgery, he develops fever and redness around the surgical site. His temperature is 39.5°C (103.1°F). Physical examination shows purulent discharge from the wound with erythema of the surrounding skin. Wound culture of the purulent discharge shows gram-positive cocci in clusters. Treatment with oral dicloxacillin is initiated. Four days later, the patient continues to have high-grade fever, pain, and purulent discharge. Which of the following characteristics of the infecting organism best explains the failure to improve with antibiotic therapy?\nA. Presence of an impenetrable outer membrane\nB. Ability to cleave β-lactam rings\nC. Development of efflux pumps\nD. Adaptation in binding proteins\nChoose the correct option.",
"image": null
},
{
"idx": 147,
"question": "A 25-year-old female with Hodgkin's lymphoma presents with a several day history of edema. Lab studies show:\n\nSerum Na+: 140 mmol/L\nSerum K+: 3.5 mmol/L\nSerum albumin: 1.9 g/dL\nTotal serum bilirubin: 1.0 mg/dL\nSerum creatinine: 1.2 mg/dL\n\nUrinalysis shows 4+ proteinuria and fatty casts. What is the most likely diagnosis?\nA. Focal segmental glomerulosclerosis\nB. Membranous nephropathy\nC. Minimal change disease\nD. Amyloidosis\n\nA. Focal segmental glomerulosclerosis\nB. Membranous nephropathy\nC. Minimal change disease\nD. Amyloidosis",
"options": [
"A. Focal segmental glomerulosclerosis",
"B. Membranous nephropathy",
"C. Minimal change disease",
"D. Amyloidosis"
],
"answer": "Minimal change disease",
"gen_text_store": "",
"pid": "147",
"query": "A 25-year-old female with Hodgkin's lymphoma presents with a several day history of edema. Lab studies show:\n\nSerum Na+: 140 mmol/L\nSerum K+: 3.5 mmol/L\nSerum albumin: 1.9 g/dL\nTotal serum bilirubin: 1.0 mg/dL\nSerum creatinine: 1.2 mg/dL\n\nUrinalysis shows 4+ proteinuria and fatty casts. What is the most likely diagnosis?\nA. Focal segmental glomerulosclerosis\nB. Membranous nephropathy\nC. Minimal change disease\nD. Amyloidosis\nChoose the correct option.",
"image": null
},
{
"idx": 148,
"question": "A 10-year-old boy is brought to the emergency room by his grandparents. He is in a wheelchair with soft restraints because he has been violent and had been trying to hurt himself that day. The child’s parents died in a car accident 1 month ago. His grandparents also brought the medications he stopped taking after his parents’ death, including multivitamins, allopurinol, and diazepam. They say that their grandson has been using these medications for many years; however, they are unable to provide any medical history and claim that their grandson has been behaving strangely, exhibiting facial grimacing, irregular involuntary contractions, and writhing movements for the past few days. They also note that he has had no teeth since the time they first met him at the age of 2. An intramuscular medication is administered to calm the boy down prior to drawing blood from him for laboratory tests. Which of the following biochemical pathway abnormalities is the most likely cause of this patient’s condition?\nA. Hypoxanthine-guanine phosphoribosyl transferase of the pyrimidine metabolism pathway\nB. Aminolevulinic acid synthetase of the heme metabolism pathway\nC. Hypoxanthine-guanine phosphoribosyl transferase of the purine metabolism pathway\nD. Thymidylate synthetase of the pyrimidine metabolism pathway\n\nA. Hypoxanthine-guanine phosphoribosyl transferase of the pyrimidine metabolism pathway\nB. Aminolevulinic acid synthetase of the heme metabolism pathway\nC. Hypoxanthine-guanine phosphoribosyl transferase of the purine metabolism pathway\nD. Thymidylate synthetase of the pyrimidine metabolism pathway",
"options": [
"A. Hypoxanthine-guanine phosphoribosyl transferase of the pyrimidine metabolism pathway",
"B. Aminolevulinic acid synthetase of the heme metabolism pathway",
"C. Hypoxanthine-guanine phosphoribosyl transferase of the purine metabolism pathway",
"D. Thymidylate synthetase of the pyrimidine metabolism pathway"
],
"answer": "Hypoxanthine-guanine phosphoribosyl transferase of the purine metabolism pathway",
"gen_text_store": "",
"pid": "148",
"query": "A 10-year-old boy is brought to the emergency room by his grandparents. He is in a wheelchair with soft restraints because he has been violent and had been trying to hurt himself that day. The child’s parents died in a car accident 1 month ago. His grandparents also brought the medications he stopped taking after his parents’ death, including multivitamins, allopurinol, and diazepam. They say that their grandson has been using these medications for many years; however, they are unable to provide any medical history and claim that their grandson has been behaving strangely, exhibiting facial grimacing, irregular involuntary contractions, and writhing movements for the past few days. They also note that he has had no teeth since the time they first met him at the age of 2. An intramuscular medication is administered to calm the boy down prior to drawing blood from him for laboratory tests. Which of the following biochemical pathway abnormalities is the most likely cause of this patient’s condition?\nA. Hypoxanthine-guanine phosphoribosyl transferase of the pyrimidine metabolism pathway\nB. Aminolevulinic acid synthetase of the heme metabolism pathway\nC. Hypoxanthine-guanine phosphoribosyl transferase of the purine metabolism pathway\nD. Thymidylate synthetase of the pyrimidine metabolism pathway\nChoose the correct option.",
"image": null
},
{
"idx": 149,
"question": "A 39-year-old woman presents with headaches, constipation, increased thirst, and increased urinary frequency. Her blood pressure is 160/100 mm Hg and pulse is 67/min. Blood tests reveal high blood glucose and low potassium level. Abdominal CT scan shows a well-circumscribed homogeneous mass in the left adrenal gland. The hormone excess responsible for her symptoms uses which of the following pathways to exert its action?\nA. Intracellular receptors\nB. cAMP pathway\nC. cGMP pathway\nD. JAK/STAT pathway\n\nA. Intracellular receptors\nB. cAMP pathway\nC. cGMP pathway\nD. JAK/STAT pathway",
"options": [
"A. Intracellular receptors",
"B. cAMP pathway",
"C. cGMP pathway",
"D. JAK/STAT pathway"
],
"answer": "Intracellular receptors",
"gen_text_store": "",
"pid": "149",
"query": "A 39-year-old woman presents with headaches, constipation, increased thirst, and increased urinary frequency. Her blood pressure is 160/100 mm Hg and pulse is 67/min. Blood tests reveal high blood glucose and low potassium level. Abdominal CT scan shows a well-circumscribed homogeneous mass in the left adrenal gland. The hormone excess responsible for her symptoms uses which of the following pathways to exert its action?\nA. Intracellular receptors\nB. cAMP pathway\nC. cGMP pathway\nD. JAK/STAT pathway\nChoose the correct option.",
"image": null
},
{
"idx": 150,
"question": "An 8-year-old boy who recently immigrated to the United States presents with a rash. Past medical history is significant for a recent sore throat which caused him to miss several days at school. The patient’s vaccination status is unknown. On physical examination, the patient is pale and ill-looking. There are pink rings present on the torso and inner surfaces of the limbs. Cardiac exam is significant for a holosystolic murmur heard best over the apex of the heart. Which of the following histopathologic findings is most likely associated with this patient’s condition?\nA. Atypical lymphocytes on peripheral blood smear\nB. Starry sky appearance\nC. Needle-shaped, negatively birefringent crystal deposits\nD. Granulomas with giant cells\n\nA. Atypical lymphocytes on peripheral blood smear\nB. Starry sky appearance\nC. Needle-shaped, negatively birefringent crystal deposits\nD. Granulomas with giant cells",
"options": [
"A. Atypical lymphocytes on peripheral blood smear",
"B. Starry sky appearance",
"C. Needle-shaped, negatively birefringent crystal deposits",
"D. Granulomas with giant cells"
],
"answer": "Granulomas with giant cells",
"gen_text_store": "",
"pid": "150",
"query": "An 8-year-old boy who recently immigrated to the United States presents with a rash. Past medical history is significant for a recent sore throat which caused him to miss several days at school. The patient’s vaccination status is unknown. On physical examination, the patient is pale and ill-looking. There are pink rings present on the torso and inner surfaces of the limbs. Cardiac exam is significant for a holosystolic murmur heard best over the apex of the heart. Which of the following histopathologic findings is most likely associated with this patient’s condition?\nA. Atypical lymphocytes on peripheral blood smear\nB. Starry sky appearance\nC. Needle-shaped, negatively birefringent crystal deposits\nD. Granulomas with giant cells\nChoose the correct option.",
"image": null
},
{
"idx": 151,
"question": "A 35-year-old woman presents to a psychiatrist for an initial consultation. She reports that for the past 3 years, she has experienced several periods of depressed mood. The episodes do not coincide with any specific life events and seem to resolve after 4-6 weeks. During these episodes, she experiences a depressed mood, sleep disturbances, and a poor appetite, but she at times is able to enjoy spending time with her children and husband but other times she is distressed and cannot enjoy time with them. Upon further questioning, she also reports experiencing occasional episodes of elevated mood over the past ten years. During these episodes, she is very productive at her work as a lawyer and requires less sleep than usual. Her past medical history is notable for obesity, type I diabetes mellitus, and rheumatoid arthritis. She is on insulin and takes methotrexate. She smokes marijuana occasionally. Her temperature is 99.2°F (37.3°C), blood pressure is 124/80 mmHg, pulse is 78/min, and respirations are 17/min. On exam, she is quiet with a flattened affect, but is cooperative and answers questions thoroughly. Which of the following is the most likely diagnosis in this patient?\nA. Bipolar I disorder\nB. Cyclothymic disorder\nC. Persistent depressive disorder\nD. Schizoaffective disorder\n\nA. Bipolar I disorder\nB. Cyclothymic disorder\nC. Persistent depressive disorder\nD. Schizoaffective disorder",
"options": [
"A. Bipolar I disorder",
"B. Cyclothymic disorder",
"C. Persistent depressive disorder",
"D. Schizoaffective disorder"
],
"answer": "Cyclothymic disorder",
"gen_text_store": "",
"pid": "151",
"query": "A 35-year-old woman presents to a psychiatrist for an initial consultation. She reports that for the past 3 years, she has experienced several periods of depressed mood. The episodes do not coincide with any specific life events and seem to resolve after 4-6 weeks. During these episodes, she experiences a depressed mood, sleep disturbances, and a poor appetite, but she at times is able to enjoy spending time with her children and husband but other times she is distressed and cannot enjoy time with them. Upon further questioning, she also reports experiencing occasional episodes of elevated mood over the past ten years. During these episodes, she is very productive at her work as a lawyer and requires less sleep than usual. Her past medical history is notable for obesity, type I diabetes mellitus, and rheumatoid arthritis. She is on insulin and takes methotrexate. She smokes marijuana occasionally. Her temperature is 99.2°F (37.3°C), blood pressure is 124/80 mmHg, pulse is 78/min, and respirations are 17/min. On exam, she is quiet with a flattened affect, but is cooperative and answers questions thoroughly. Which of the following is the most likely diagnosis in this patient?\nA. Bipolar I disorder\nB. Cyclothymic disorder\nC. Persistent depressive disorder\nD. Schizoaffective disorder\nChoose the correct option.",
"image": null
},
{
"idx": 152,
"question": "A 78-year-old man comes to the physician because of progressively worsening fatigue and headache for 6 months and occasional abdominal pain. He has not had any changes in his weight. He has a history of hypertension, type 2 diabetes mellitus, and chronic shoulder pain. Current daily medications include hydrochlorothiazide, metformin, and ibuprofen. He does not drink alcohol and does not smoke. His diet has mostly consisted of potatoes and lean meats since his wife passed away 1 year ago. His pulse is 92/min and blood pressure is 135/80 mm Hg. Examination shows conjunctival and mucosal pallor. Abdominal and rectal examination shows no abnormalities. Neurological exam shows mild postural tremor. Peripheral blood smear shows red blood cells with increased zones of central pallor and anisocytosis. Which of the following is the most likely underlying cause of this patient’s symptoms?\nA. Folic acid deficiency\nB. Intravascular hemolysis\nC. Impaired erythropoietin production\nD. Iron deficiency\n\nA. Folic acid deficiency\nB. Intravascular hemolysis\nC. Impaired erythropoietin production\nD. Iron deficiency",
"options": [
"A. Folic acid deficiency",
"B. Intravascular hemolysis",
"C. Impaired erythropoietin production",
"D. Iron deficiency"
],
"answer": "Iron deficiency",
"gen_text_store": "",
"pid": "152",
"query": "A 78-year-old man comes to the physician because of progressively worsening fatigue and headache for 6 months and occasional abdominal pain. He has not had any changes in his weight. He has a history of hypertension, type 2 diabetes mellitus, and chronic shoulder pain. Current daily medications include hydrochlorothiazide, metformin, and ibuprofen. He does not drink alcohol and does not smoke. His diet has mostly consisted of potatoes and lean meats since his wife passed away 1 year ago. His pulse is 92/min and blood pressure is 135/80 mm Hg. Examination shows conjunctival and mucosal pallor. Abdominal and rectal examination shows no abnormalities. Neurological exam shows mild postural tremor. Peripheral blood smear shows red blood cells with increased zones of central pallor and anisocytosis. Which of the following is the most likely underlying cause of this patient’s symptoms?\nA. Folic acid deficiency\nB. Intravascular hemolysis\nC. Impaired erythropoietin production\nD. Iron deficiency\nChoose the correct option.",
"image": null
},
{
"idx": 153,
"question": "A 9-year-old boy is brought in by his mother because of bruising on his torso and limbs. The patient’s mother denies any other symptoms and says he is otherwise healthy. Physical examination shows multiple petechiae and bruising on the torso and extremities bilaterally. The remainder of the physical exam is unremarkable. A complete blood count is normal. His coagulation profile reveals:\nProthrombin time (PT) 12 sec\nActivated partial thromboplastin time (aPTT) 60 sec\nWhich of the following is the most likely diagnosis in this patient?\nA. Acute lymphoblastic leukemia\nB. Immune thrombocytopenic purpura\nC. Von Willebrand disease\nD. Hemophilia A\n\nA. Acute lymphoblastic leukemia\nB. Immune thrombocytopenic purpura\nC. Von Willebrand disease\nD. Hemophilia A",
"options": [
"A. Acute lymphoblastic leukemia",
"B. Immune thrombocytopenic purpura",
"C. Von Willebrand disease",
"D. Hemophilia A"
],
"answer": "Von Willebrand disease",
"gen_text_store": "",
"pid": "153",
"query": "A 9-year-old boy is brought in by his mother because of bruising on his torso and limbs. The patient’s mother denies any other symptoms and says he is otherwise healthy. Physical examination shows multiple petechiae and bruising on the torso and extremities bilaterally. The remainder of the physical exam is unremarkable. A complete blood count is normal. His coagulation profile reveals:\nProthrombin time (PT) 12 sec\nActivated partial thromboplastin time (aPTT) 60 sec\nWhich of the following is the most likely diagnosis in this patient?\nA. Acute lymphoblastic leukemia\nB. Immune thrombocytopenic purpura\nC. Von Willebrand disease\nD. Hemophilia A\nChoose the correct option.",
"image": null
},
{
"idx": 154,
"question": "A 26-year-old man with no significant past medical history presents to the ED following a motor vehicle accident. Vital signs on presentation are T 99.0 F, BP 100/60 mmHg, HR 125 bpm, RR 16/min, SpO2 98% on room air. He complains of extreme abdominal pain worse in the left upper quadrant which has worsened over the past 30 minutes. Exam demonstrates abdominal wall rigidity, involuntary guarding, and tenderness on light percussion. Bedside sonography shows evidence for hemoperitoneum. Despite administering more intravenous fluids, repeat vitals are T 98.9 F, BP 82/50 mm hg, HR 180 bpm, RR 20/min, SpO2 97% on room air. Which of the following is the best next step?\nA. Normal saline bolus and re-evaluation of hemodynamics after infusion\nB. CT abdomen and pelvis\nC. Morphine\nD. Exploratory laparotomy\n\nA. Normal saline bolus and re-evaluation of hemodynamics after infusion\nB. CT abdomen and pelvis\nC. Morphine\nD. Exploratory laparotomy",
"options": [
"A. Normal saline bolus and re-evaluation of hemodynamics after infusion",
"B. CT abdomen and pelvis",
"C. Morphine",
"D. Exploratory laparotomy"
],
"answer": "Exploratory laparotomy",
"gen_text_store": "",
"pid": "154",
"query": "A 26-year-old man with no significant past medical history presents to the ED following a motor vehicle accident. Vital signs on presentation are T 99.0 F, BP 100/60 mmHg, HR 125 bpm, RR 16/min, SpO2 98% on room air. He complains of extreme abdominal pain worse in the left upper quadrant which has worsened over the past 30 minutes. Exam demonstrates abdominal wall rigidity, involuntary guarding, and tenderness on light percussion. Bedside sonography shows evidence for hemoperitoneum. Despite administering more intravenous fluids, repeat vitals are T 98.9 F, BP 82/50 mm hg, HR 180 bpm, RR 20/min, SpO2 97% on room air. Which of the following is the best next step?\nA. Normal saline bolus and re-evaluation of hemodynamics after infusion\nB. CT abdomen and pelvis\nC. Morphine\nD. Exploratory laparotomy\nChoose the correct option.",
"image": null
},
{
"idx": 155,
"question": "A 40-year-old woman presents to the emergency department with severe left upper quadrant pain (duration 3 hours, stabbing quality, 10/10 on the pain scale). Past medical history is significant for sickle cell anemia. Physical examination is significant for severe tenderness to palpation in the left upper quadrant. Significant splenomegaly is also noted. The patient is admitted to the hospital for close observation and placed on deep vein thrombosis (DVT) prophylaxis as part of a routine protocol. Laboratory findings drawn sometime after admission demonstrate a normal prothrombin time (PT) and elevated partial thromboplastin time (PTT). Which of the following factors is most directly affected by the DVT prophylaxis?\nA. VII\nB. VIIa\nC. X\nD. XII\n\nA. VII\nB. VIIa\nC. X\nD. XII",
"options": [
"A. VII",
"B. VIIa",
"C. X",
"D. XII"
],
"answer": "X",
"gen_text_store": "",
"pid": "155",
"query": "A 40-year-old woman presents to the emergency department with severe left upper quadrant pain (duration 3 hours, stabbing quality, 10/10 on the pain scale). Past medical history is significant for sickle cell anemia. Physical examination is significant for severe tenderness to palpation in the left upper quadrant. Significant splenomegaly is also noted. The patient is admitted to the hospital for close observation and placed on deep vein thrombosis (DVT) prophylaxis as part of a routine protocol. Laboratory findings drawn sometime after admission demonstrate a normal prothrombin time (PT) and elevated partial thromboplastin time (PTT). Which of the following factors is most directly affected by the DVT prophylaxis?\nA. VII\nB. VIIa\nC. X\nD. XII\nChoose the correct option.",
"image": null
},
{
"idx": 156,
"question": "A 27-year-old woman presents to the office with concerns about her long struggle with her physical appearance since adolescence. She says she has always been \"large\" and was constantly targeted by her classmates and coworkers for being so. Her main concern at the moment is her acne and unwanted facial hair on her upper lip, for which she often visits a local spa. She has tried numerous diet plans, exercise regimens, and cosmetic products with little to no effect. Recently, she underwent a glucose tolerance test that showed a plasma glucose level of 160 mg/dL (8.9 mmol/L) after 2 hours of a 75 g dose of oral glucose. She has a family history of type 2 diabetes mellitus and a menstrual cycle that occurs every 45 days. Her pulse is 72/min and the blood pressure is 138/80 mm Hg. On physical examination, her height is 160 cm (5 ft 3 in) and her weight is 85 kg (187 lb), and she has severe inflammatory acne over the cheeks and forehead and dark coarse hairs on the back. What is the most likely diagnosis of this patient?\nA. Hypothyroidism\nB. Idiopathic hirsutism\nC. Polycystic ovarian syndrome (PCOS)\nD. Ovarian hyperthecosis\n\nA. Hypothyroidism\nB. Idiopathic hirsutism\nC. Polycystic ovarian syndrome (PCOS)\nD. Ovarian hyperthecosis",
"options": [
"A. Hypothyroidism",
"B. Idiopathic hirsutism",
"C. Polycystic ovarian syndrome (PCOS)",
"D. Ovarian hyperthecosis"
],
"answer": "Polycystic ovarian syndrome (PCOS)",
"gen_text_store": "",
"pid": "156",
"query": "A 27-year-old woman presents to the office with concerns about her long struggle with her physical appearance since adolescence. She says she has always been \"large\" and was constantly targeted by her classmates and coworkers for being so. Her main concern at the moment is her acne and unwanted facial hair on her upper lip, for which she often visits a local spa. She has tried numerous diet plans, exercise regimens, and cosmetic products with little to no effect. Recently, she underwent a glucose tolerance test that showed a plasma glucose level of 160 mg/dL (8.9 mmol/L) after 2 hours of a 75 g dose of oral glucose. She has a family history of type 2 diabetes mellitus and a menstrual cycle that occurs every 45 days. Her pulse is 72/min and the blood pressure is 138/80 mm Hg. On physical examination, her height is 160 cm (5 ft 3 in) and her weight is 85 kg (187 lb), and she has severe inflammatory acne over the cheeks and forehead and dark coarse hairs on the back. What is the most likely diagnosis of this patient?\nA. Hypothyroidism\nB. Idiopathic hirsutism\nC. Polycystic ovarian syndrome (PCOS)\nD. Ovarian hyperthecosis\nChoose the correct option.",
"image": null
},
{
"idx": 157,
"question": "A 72-year-old woman is admitted to the intensive care unit for shortness of breath and palpitations. A cardiac catheterization is performed and measurements of the left ventricular volume and pressure at different points in the cardiac cycle are obtained. The patient's pressure-volume loop (gray) is shown with a normal pressure-volume loop (black) for comparison. Which of the following is the most likely underlying cause of this patient's symptoms?\nA. Mitral valve regurgitation\nB. Increased systemic vascular resistance\nC. Increased ventricular wall stiffness\nD. Impaired left ventricular contractility\n\nA. Mitral valve regurgitation\nB. Increased systemic vascular resistance\nC. Increased ventricular wall stiffness\nD. Impaired left ventricular contractility",
"options": [
"A. Mitral valve regurgitation",
"B. Increased systemic vascular resistance",
"C. Increased ventricular wall stiffness",
"D. Impaired left ventricular contractility"
],
"answer": "Increased ventricular wall stiffness",
"gen_text_store": "",
"pid": "157",
"query": "A 72-year-old woman is admitted to the intensive care unit for shortness of breath and palpitations. A cardiac catheterization is performed and measurements of the left ventricular volume and pressure at different points in the cardiac cycle are obtained. The patient's pressure-volume loop (gray) is shown with a normal pressure-volume loop (black) for comparison. Which of the following is the most likely underlying cause of this patient's symptoms?\nA. Mitral valve regurgitation\nB. Increased systemic vascular resistance\nC. Increased ventricular wall stiffness\nD. Impaired left ventricular contractility\nChoose the correct option.",
"image": null
},
{
"idx": 158,
"question": "A 16-year-old girl is brought to the emergency department with constant abdominal pain over the past 8 hours. The pain is in her right lower quadrant (RLQ), which is also where it began. She has had no nausea or vomiting despite eating a snack 2 hours ago. She had a similar episode last month which resolved on its own. Her menstrual cycles are 28–30 days apart with 3–5 days of vaginal bleeding. Her last menses ended 9 days ago. Her blood pressure is 125/75 mm Hg, the pulse is 78/min, the respirations are 15/min, and the temperature is 37.2°C (99.0°F). Abdominal examination shows moderate pain on direct pressure over the RLQ which decreases with the release of pressure. The remainder of the physical examination shows no abnormalities. Laboratory studies show:\nHemoglobin 12.5 mg/dL\nLeukocyte count 6000/mm3\nSegmented neutrophils 55%\nLymphocytes 39%\nPlatelet count 260,000/mm3\nSerum \nC-reactive protein 5 mg/L (N < 8 mg/L)\nUrine \nRBC 1-2 phf\nWBC None\nWhich of the following is the most appropriate next step in management?\nA. Methotrexate\nB. Nitrofurantoin\nC. Reassurance\nD. Referral for surgery\n\nA. Methotrexate\nB. Nitrofurantoin\nC. Reassurance\nD. Referral for surgery",
"options": [
"A. Methotrexate",
"B. Nitrofurantoin",
"C. Reassurance",
"D. Referral for surgery"
],
"answer": "Reassurance",
"gen_text_store": "",
"pid": "158",
"query": "A 16-year-old girl is brought to the emergency department with constant abdominal pain over the past 8 hours. The pain is in her right lower quadrant (RLQ), which is also where it began. She has had no nausea or vomiting despite eating a snack 2 hours ago. She had a similar episode last month which resolved on its own. Her menstrual cycles are 28–30 days apart with 3–5 days of vaginal bleeding. Her last menses ended 9 days ago. Her blood pressure is 125/75 mm Hg, the pulse is 78/min, the respirations are 15/min, and the temperature is 37.2°C (99.0°F). Abdominal examination shows moderate pain on direct pressure over the RLQ which decreases with the release of pressure. The remainder of the physical examination shows no abnormalities. Laboratory studies show:\nHemoglobin 12.5 mg/dL\nLeukocyte count 6000/mm3\nSegmented neutrophils 55%\nLymphocytes 39%\nPlatelet count 260,000/mm3\nSerum \nC-reactive protein 5 mg/L (N < 8 mg/L)\nUrine \nRBC 1-2 phf\nWBC None\nWhich of the following is the most appropriate next step in management?\nA. Methotrexate\nB. Nitrofurantoin\nC. Reassurance\nD. Referral for surgery\nChoose the correct option.",
"image": null
},
{
"idx": 159,
"question": "A 51-year-old man presents to his primary care provider complaining of malaise. He returned from a research trip to Madagascar 2 weeks ago and has since developed a worsening fever with a maximum temperature of 102.2°F (39°C). He also reports some swelling around his neck and groin. He works as a zoologist and was in rural Madagascar studying a rare species of lemur. His past medical history is notable for hypertension and gout. He takes lisinopril and allopurinol. His temperature is 101.9°F (38.3°C), blood pressure is 145/85 mmHg, pulse is 110/min, and respirations are 22/min. On exam, he has painful erythematous cervical, axillary, and inguinal lymphadenopathy. Black hemorrhagic eschars are noted on his fingertips bilaterally. The pathogen responsible for this patient’s condition produces a virulence factor that has which of the following functions?\nA. Cleave immunoglobulin\nB. Inhibit phagocytosis\nC. Inhibit ribosomal function\nD. Trigger widespread inflammation\n\nA. Cleave immunoglobulin\nB. Inhibit phagocytosis\nC. Inhibit ribosomal function\nD. Trigger widespread inflammation",
"options": [
"A. Cleave immunoglobulin",
"B. Inhibit phagocytosis",
"C. Inhibit ribosomal function",
"D. Trigger widespread inflammation"
],
"answer": "Inhibit phagocytosis",
"gen_text_store": "",
"pid": "159",
"query": "A 51-year-old man presents to his primary care provider complaining of malaise. He returned from a research trip to Madagascar 2 weeks ago and has since developed a worsening fever with a maximum temperature of 102.2°F (39°C). He also reports some swelling around his neck and groin. He works as a zoologist and was in rural Madagascar studying a rare species of lemur. His past medical history is notable for hypertension and gout. He takes lisinopril and allopurinol. His temperature is 101.9°F (38.3°C), blood pressure is 145/85 mmHg, pulse is 110/min, and respirations are 22/min. On exam, he has painful erythematous cervical, axillary, and inguinal lymphadenopathy. Black hemorrhagic eschars are noted on his fingertips bilaterally. The pathogen responsible for this patient’s condition produces a virulence factor that has which of the following functions?\nA. Cleave immunoglobulin\nB. Inhibit phagocytosis\nC. Inhibit ribosomal function\nD. Trigger widespread inflammation\nChoose the correct option.",
"image": null
},
{
"idx": 160,
"question": "A 14-year-old girl comes to the physician with her father for evaluation of her short stature. She feels well overall, but is concerned because all of her friends are taller than her. Her birth weight was normal. Her father reports he had a short stature during his teenage years; he is currently 177 cm (5 ft 10 in) tall. She is at the 2ndpercentile for height and 35th percentile for weight. Breast development is Tanner stage 2. Pubic and axillary hair is absent. An x-ray of the left hand and wrist shows a bone age of 11 years. Which of the following is the most appropriate next best step in management?\nA. Pelvic ultrasound\nB. Measure serum dehydroepiandrosterone levels\nC. Reassurance and follow-up\nD. MRI of the brain\n\nA. Pelvic ultrasound\nB. Measure serum dehydroepiandrosterone levels\nC. Reassurance and follow-up\nD. MRI of the brain",
"options": [
"A. Pelvic ultrasound",
"B. Measure serum dehydroepiandrosterone levels",
"C. Reassurance and follow-up",
"D. MRI of the brain"
],
"answer": "Reassurance and follow-up",
"gen_text_store": "",
"pid": "160",
"query": "A 14-year-old girl comes to the physician with her father for evaluation of her short stature. She feels well overall, but is concerned because all of her friends are taller than her. Her birth weight was normal. Her father reports he had a short stature during his teenage years; he is currently 177 cm (5 ft 10 in) tall. She is at the 2ndpercentile for height and 35th percentile for weight. Breast development is Tanner stage 2. Pubic and axillary hair is absent. An x-ray of the left hand and wrist shows a bone age of 11 years. Which of the following is the most appropriate next best step in management?\nA. Pelvic ultrasound\nB. Measure serum dehydroepiandrosterone levels\nC. Reassurance and follow-up\nD. MRI of the brain\nChoose the correct option.",
"image": null
},
{
"idx": 161,
"question": "An investigator is studying the frequency of polycythemia in a population of a remote, mountainous region. A representative sample of 100 men shows a normal distribution of hemoglobin concentration with a mean concentration of 17 g/dL and a standard error of 0.1 g/dL. Which of the following best represents the probability that a subject will have a hemoglobin concentration greater than 18 g/dL?\nA. 30%\nB. 15%\nC. 95%\nD. 99%\n\nA. 30%\nB. 15%\nC. 95%\nD. 99%",
"options": [
"A. 30%",
"B. 15%",
"C. 95%",
"D. 99%"
],
"answer": "15%",
"gen_text_store": "",
"pid": "161",
"query": "An investigator is studying the frequency of polycythemia in a population of a remote, mountainous region. A representative sample of 100 men shows a normal distribution of hemoglobin concentration with a mean concentration of 17 g/dL and a standard error of 0.1 g/dL. Which of the following best represents the probability that a subject will have a hemoglobin concentration greater than 18 g/dL?\nA. 30%\nB. 15%\nC. 95%\nD. 99%\nChoose the correct option.",
"image": null
},
{
"idx": 162,
"question": "An otherwise healthy 15-year-old boy presents to the emergency department with extreme fatigue and shortness of breath. His temperature is 36.5°C (97.7°F), the blood pressure is 100/60 mm Hg and the pulse is 100/min. Past medical history is noncontributory and he takes no medication. His father and aunt both suffer from mild anemia. On examination, he is very pale and his spleen is enlarged. His hemoglobin is 5 g/dL and platelet count is slightly reduced. His peripheral blood smear is shown in the picture. Over the next 2 weeks, the patient recovers, and his hemoglobin is 11 g/dL. Which of the following best represents the pattern of inheritance of this patient underlying disorder?\nA. Autosomal dominant\nB. X-linked recessive\nC. X-linked dominant\nD. Multifactorial\n\nA. Autosomal dominant\nB. X-linked recessive\nC. X-linked dominant\nD. Multifactorial",
"options": [
"A. Autosomal dominant",
"B. X-linked recessive",
"C. X-linked dominant",
"D. Multifactorial"
],
"answer": "Autosomal dominant",
"gen_text_store": "",
"pid": "162",
"query": "An otherwise healthy 15-year-old boy presents to the emergency department with extreme fatigue and shortness of breath. His temperature is 36.5°C (97.7°F), the blood pressure is 100/60 mm Hg and the pulse is 100/min. Past medical history is noncontributory and he takes no medication. His father and aunt both suffer from mild anemia. On examination, he is very pale and his spleen is enlarged. His hemoglobin is 5 g/dL and platelet count is slightly reduced. His peripheral blood smear is shown in the picture. Over the next 2 weeks, the patient recovers, and his hemoglobin is 11 g/dL. Which of the following best represents the pattern of inheritance of this patient underlying disorder?\nA. Autosomal dominant\nB. X-linked recessive\nC. X-linked dominant\nD. Multifactorial\nChoose the correct option.",
"image": null
},
{
"idx": 163,
"question": "A 39-year-old woman is brought to the emergency department because of fevers, chills, and left lower quadrant pain. Her temperature is 39.1°C (102.3°F), pulse is 126/min, respirations are 28/min, and blood pressure is 80/50 mm Hg. There is blood oozing around the site of a peripheral intravenous line. Pelvic examination shows mucopurulent discharge from the cervical os and left adnexal tenderness. Laboratory studies show:\nPlatelet count 14,200/mm3\nFibrinogen 83 mg/mL (N = 200–430 mg/dL)\nD-dimer 965 ng/mL (N < 500 ng/mL)\nWhen phenol is applied to a sample of the patient's blood at 90°C, a phosphorylated N-acetylglucosamine dimer with 6 fatty acids attached to a polysaccharide side chain is identified. A blood culture is most likely to show which of the following?\"\nA. Coagulase-positive, gram-positive cocci forming mauve-colored colonies on methicillin-containing agar\nB. Encapsulated, gram-negative coccobacilli forming grey-colored colonies on charcoal blood agar\nC. Spore-forming, gram-positive bacilli forming yellow colonies on casein agar\nD. Lactose-fermenting, gram-negative rods forming pink colonies on MacConkey agar\n\nA. Coagulase-positive, gram-positive cocci forming mauve-colored colonies on methicillin-containing agar\nB. Encapsulated, gram-negative coccobacilli forming grey-colored colonies on charcoal blood agar\nC. Spore-forming, gram-positive bacilli forming yellow colonies on casein agar\nD. Lactose-fermenting, gram-negative rods forming pink colonies on MacConkey agar",
"options": [
"A. Coagulase-positive, gram-positive cocci forming mauve-colored colonies on methicillin-containing agar",
"B. Encapsulated, gram-negative coccobacilli forming grey-colored colonies on charcoal blood agar",
"C. Spore-forming, gram-positive bacilli forming yellow colonies on casein agar",
"D. Lactose-fermenting, gram-negative rods forming pink colonies on MacConkey agar"
],
"answer": "Lactose-fermenting, gram-negative rods forming pink colonies on MacConkey agar",
"gen_text_store": "",
"pid": "163",
"query": "A 39-year-old woman is brought to the emergency department because of fevers, chills, and left lower quadrant pain. Her temperature is 39.1°C (102.3°F), pulse is 126/min, respirations are 28/min, and blood pressure is 80/50 mm Hg. There is blood oozing around the site of a peripheral intravenous line. Pelvic examination shows mucopurulent discharge from the cervical os and left adnexal tenderness. Laboratory studies show:\nPlatelet count 14,200/mm3\nFibrinogen 83 mg/mL (N = 200–430 mg/dL)\nD-dimer 965 ng/mL (N < 500 ng/mL)\nWhen phenol is applied to a sample of the patient's blood at 90°C, a phosphorylated N-acetylglucosamine dimer with 6 fatty acids attached to a polysaccharide side chain is identified. A blood culture is most likely to show which of the following?\"\nA. Coagulase-positive, gram-positive cocci forming mauve-colored colonies on methicillin-containing agar\nB. Encapsulated, gram-negative coccobacilli forming grey-colored colonies on charcoal blood agar\nC. Spore-forming, gram-positive bacilli forming yellow colonies on casein agar\nD. Lactose-fermenting, gram-negative rods forming pink colonies on MacConkey agar\nChoose the correct option.",
"image": null
},
{
"idx": 164,
"question": "A three-day-old, full-term infant born by uncomplicated vaginal delivery is brought to a pediatrician by his mother, who notes that her son's skin appears yellow. She reports that the child cries several times per day, but sleeps 7-8 hours at night, uninterrupted. She has been breastfeeding the infant but feels the latch has been poor and is unsure how much milk he has been consuming but feels it is not enough. A lactation consult was called for the patient and it was noted that despite proper instruction the observed latch was still poor. When asked the mother stated that the baby is currently making stools 2 times per day. Which of the following is the most likely etiology of the patient's presentation?\nA. Breast milk jaundice\nB. Breastfeeding jaundice\nC. Sepsis\nD. Physiologic hyperbilirubinemia\n\nA. Breast milk jaundice\nB. Breastfeeding jaundice\nC. Sepsis\nD. Physiologic hyperbilirubinemia",
"options": [
"A. Breast milk jaundice",
"B. Breastfeeding jaundice",
"C. Sepsis",
"D. Physiologic hyperbilirubinemia"
],
"answer": "Breastfeeding jaundice",
"gen_text_store": "",
"pid": "164",
"query": "A three-day-old, full-term infant born by uncomplicated vaginal delivery is brought to a pediatrician by his mother, who notes that her son's skin appears yellow. She reports that the child cries several times per day, but sleeps 7-8 hours at night, uninterrupted. She has been breastfeeding the infant but feels the latch has been poor and is unsure how much milk he has been consuming but feels it is not enough. A lactation consult was called for the patient and it was noted that despite proper instruction the observed latch was still poor. When asked the mother stated that the baby is currently making stools 2 times per day. Which of the following is the most likely etiology of the patient's presentation?\nA. Breast milk jaundice\nB. Breastfeeding jaundice\nC. Sepsis\nD. Physiologic hyperbilirubinemia\nChoose the correct option.",
"image": null
},
{
"idx": 165,
"question": "A 59-year-old man with a history of sickle cell disease presents to the emergency department for evaluation of his fever and night sweats. He is extremely lethargic and is unable to provide an adequate history to his physician. His wife noted that roughly 3 days ago, her husband mentioned that something bit him, but she cannot remember what exactly. The vital signs include blood pressure 85/67 mm Hg, pulse rate 107/min, and respiratory rate 35/min. Upon examination, the man is currently afebrile but is lethargic and pale. His spleen is surgically absent. There are some swollen bite marks on his right hand with red streaks extending to his elbow. Which of the following bites would be most concerning in this patient?\nA. Human bite\nB. Spider bite\nC. Fish bite\nD. Dog bite\n\nA. Human bite\nB. Spider bite\nC. Fish bite\nD. Dog bite",
"options": [
"A. Human bite",
"B. Spider bite",
"C. Fish bite",
"D. Dog bite"
],
"answer": "Dog bite",
"gen_text_store": "",
"pid": "165",
"query": "A 59-year-old man with a history of sickle cell disease presents to the emergency department for evaluation of his fever and night sweats. He is extremely lethargic and is unable to provide an adequate history to his physician. His wife noted that roughly 3 days ago, her husband mentioned that something bit him, but she cannot remember what exactly. The vital signs include blood pressure 85/67 mm Hg, pulse rate 107/min, and respiratory rate 35/min. Upon examination, the man is currently afebrile but is lethargic and pale. His spleen is surgically absent. There are some swollen bite marks on his right hand with red streaks extending to his elbow. Which of the following bites would be most concerning in this patient?\nA. Human bite\nB. Spider bite\nC. Fish bite\nD. Dog bite\nChoose the correct option.",
"image": null
},
{
"idx": 166,
"question": "A 75-year-old man becomes pulseless in the cardiac intensive care unit 48 hours after admission for ST-elevation myocardial infarction. His blood pressure is 50/20 mm Hg. The ECG monitor shows a tachycardic irregular rhythm with erratic undulations, but no discernible P waves or QRS complexes. During immediate advanced cardiac life support, two attempts at defibrillation are made, after which the patient is given 1 mg of IV epinephrine. After another attempt at defibrillation, the patient remains pulseless and his blood pressure is 60/35 mm Hg. The ECG monitor shows no changes. Administration of which of the following is the most appropriate next step in management?\nA. Amiodarone\nB. Epinephrine\nC. Dopamine\nD. Atropine\n\nA. Amiodarone\nB. Epinephrine\nC. Dopamine\nD. Atropine",
"options": [
"A. Amiodarone",
"B. Epinephrine",
"C. Dopamine",
"D. Atropine"
],
"answer": "Amiodarone",
"gen_text_store": "",
"pid": "166",
"query": "A 75-year-old man becomes pulseless in the cardiac intensive care unit 48 hours after admission for ST-elevation myocardial infarction. His blood pressure is 50/20 mm Hg. The ECG monitor shows a tachycardic irregular rhythm with erratic undulations, but no discernible P waves or QRS complexes. During immediate advanced cardiac life support, two attempts at defibrillation are made, after which the patient is given 1 mg of IV epinephrine. After another attempt at defibrillation, the patient remains pulseless and his blood pressure is 60/35 mm Hg. The ECG monitor shows no changes. Administration of which of the following is the most appropriate next step in management?\nA. Amiodarone\nB. Epinephrine\nC. Dopamine\nD. Atropine\nChoose the correct option.",
"image": null
},
{
"idx": 167,
"question": "An investigator is studying traumatic knee joint injuries in college athletes. Images and tissue samples are collected from 4 athletes with cartilaginous injury and 4 athletes with bone fractures. After 8 weeks, the athletes with bone fractures show almost complete resolution, while the athletes with cartilaginous injuries show only minimal signs of healing. The investigator hypothesizes that this is due to the absence of progenitor cells for matrix regeneration. Transplant of which of the following tissues would most likely promote healing in the group with cartilaginous injury?\nA. Perichondrium\nB. Proteoglycans\nC. Osteoblasts\nD. Mature chondrocytes\n\nA. Perichondrium\nB. Proteoglycans\nC. Osteoblasts\nD. Mature chondrocytes",
"options": [
"A. Perichondrium",
"B. Proteoglycans",
"C. Osteoblasts",
"D. Mature chondrocytes"
],
"answer": "Perichondrium",
"gen_text_store": "",
"pid": "167",
"query": "An investigator is studying traumatic knee joint injuries in college athletes. Images and tissue samples are collected from 4 athletes with cartilaginous injury and 4 athletes with bone fractures. After 8 weeks, the athletes with bone fractures show almost complete resolution, while the athletes with cartilaginous injuries show only minimal signs of healing. The investigator hypothesizes that this is due to the absence of progenitor cells for matrix regeneration. Transplant of which of the following tissues would most likely promote healing in the group with cartilaginous injury?\nA. Perichondrium\nB. Proteoglycans\nC. Osteoblasts\nD. Mature chondrocytes\nChoose the correct option.",
"image": null
},
{
"idx": 168,
"question": "A 47-year-old woman presents to a physician for evaluation of vomiting and diarrhea for 2 days. Her symptoms began following a company picnic a few days ago. Initially, she was unable to tolerate any solids or liquids by mouth, but now has been able to drink sips of water. She had a mild headache, which was relieved with acetaminophen. The past medical history is unremarkable. She does not take any medications. The blood pressure is 120/60 mm Hg and the heart rate is 60/min. On examination, the mucous membranes are dry and the eyes are slightly sunken. Where is most of the sodium reabsorbed in this patient’s kidneys?\nA. Distal tubule\nB. Descending limb of loop of Henle\nC. Proximal tubule\nD. Ascending limb of loop of Henle\n\nA. Distal tubule\nB. Descending limb of loop of Henle\nC. Proximal tubule\nD. Ascending limb of loop of Henle",
"options": [
"A. Distal tubule",
"B. Descending limb of loop of Henle",
"C. Proximal tubule",
"D. Ascending limb of loop of Henle"
],
"answer": "Proximal tubule",
"gen_text_store": "",
"pid": "168",
"query": "A 47-year-old woman presents to a physician for evaluation of vomiting and diarrhea for 2 days. Her symptoms began following a company picnic a few days ago. Initially, she was unable to tolerate any solids or liquids by mouth, but now has been able to drink sips of water. She had a mild headache, which was relieved with acetaminophen. The past medical history is unremarkable. She does not take any medications. The blood pressure is 120/60 mm Hg and the heart rate is 60/min. On examination, the mucous membranes are dry and the eyes are slightly sunken. Where is most of the sodium reabsorbed in this patient’s kidneys?\nA. Distal tubule\nB. Descending limb of loop of Henle\nC. Proximal tubule\nD. Ascending limb of loop of Henle\nChoose the correct option.",
"image": null
},
{
"idx": 169,
"question": "A 12-year-old boy is brought to the emergency department for the evaluation of persistent bleeding from his nose over the past hour. The bleeding started spontaneously. He has no history of a similar episode. He takes no medications. There is no history of abnormal bleeding in the family. His vital signs are within normal limits. On examination, he is pressing a gauze against his left nostril while hyperextending his head. The gauze is stained with blood and upon withdrawal of the gauze blood slowly drips out of his left nostrils. There is no bleeding from the right nostril. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate initial therapy?\nA. Anterior packing and topical antibiotics\nB. Oxymetazoline nasal spray\nC. Placement of an epinephrine gauze in the left nostril\nD. Squeezing the nostrils manually for 10 minutes with the head elevated\n\nA. Anterior packing and topical antibiotics\nB. Oxymetazoline nasal spray\nC. Placement of an epinephrine gauze in the left nostril\nD. Squeezing the nostrils manually for 10 minutes with the head elevated",
"options": [
"A. Anterior packing and topical antibiotics",
"B. Oxymetazoline nasal spray",
"C. Placement of an epinephrine gauze in the left nostril",
"D. Squeezing the nostrils manually for 10 minutes with the head elevated"
],
"answer": "Squeezing the nostrils manually for 10 minutes with the head elevated",
"gen_text_store": "",
"pid": "169",
"query": "A 12-year-old boy is brought to the emergency department for the evaluation of persistent bleeding from his nose over the past hour. The bleeding started spontaneously. He has no history of a similar episode. He takes no medications. There is no history of abnormal bleeding in the family. His vital signs are within normal limits. On examination, he is pressing a gauze against his left nostril while hyperextending his head. The gauze is stained with blood and upon withdrawal of the gauze blood slowly drips out of his left nostrils. There is no bleeding from the right nostril. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate initial therapy?\nA. Anterior packing and topical antibiotics\nB. Oxymetazoline nasal spray\nC. Placement of an epinephrine gauze in the left nostril\nD. Squeezing the nostrils manually for 10 minutes with the head elevated\nChoose the correct option.",
"image": null
},
{
"idx": 170,
"question": "A 51-year-old Caucasian woman presents to the physician for a routine health maintenance examination. She had a Colles' fracture 2 years ago. The rest of her past medical history is unremarkable. She has a sedentary lifestyle. She has been smoking 1 pack of cigarettes daily for 30 years. She drinks alcohol moderately. Her mother had a fracture of the wrist when she was in her late 60s. The physical examination shows no abnormal findings. Dual-energy X-ray absorptiometry (DEXA scan) shows a T-score of -3.2 standard deviations (SDs) in the hip. The patient is educated regarding her risk of falls. Exercise regimen and smoking cessation assistance are provided. Appropriate diet is indicated, as well as supplements with calcium and vitamin D. Which of the following is the most appropriate next step in pharmacotherapy?\nA. Alendronate\nB. Calcitonin\nC. Estrogen\nD. Tamoxifen\n\nA. Alendronate\nB. Calcitonin\nC. Estrogen\nD. Tamoxifen",
"options": [
"A. Alendronate",
"B. Calcitonin",
"C. Estrogen",
"D. Tamoxifen"
],
"answer": "Alendronate",
"gen_text_store": "",
"pid": "170",
"query": "A 51-year-old Caucasian woman presents to the physician for a routine health maintenance examination. She had a Colles' fracture 2 years ago. The rest of her past medical history is unremarkable. She has a sedentary lifestyle. She has been smoking 1 pack of cigarettes daily for 30 years. She drinks alcohol moderately. Her mother had a fracture of the wrist when she was in her late 60s. The physical examination shows no abnormal findings. Dual-energy X-ray absorptiometry (DEXA scan) shows a T-score of -3.2 standard deviations (SDs) in the hip. The patient is educated regarding her risk of falls. Exercise regimen and smoking cessation assistance are provided. Appropriate diet is indicated, as well as supplements with calcium and vitamin D. Which of the following is the most appropriate next step in pharmacotherapy?\nA. Alendronate\nB. Calcitonin\nC. Estrogen\nD. Tamoxifen\nChoose the correct option.",
"image": null
},
{
"idx": 171,
"question": "A 56-year-old man recently diagnosed with cirrhosis secondary to alcohol use presents to the clinic for a follow up evaluation. He states that he has abstained from alcohol and attends a support group regularly. He has not taken any new medications or encountered any sick contacts. The patient's blood pressure is 110/70 mmHg, pulse is 65/min, and respirations are 15/min. His physical exam is grossly unremarkable. He has brought an gastroduodenoscopy report for review, which reveals that the patient has small esophageal varices with red spots. What is the next best step to prevent bleeding?\nA. Endoscopic sclerotherapy\nB. Metoprolol\nC. Nadolol\nD. Repeat endoscopy\n\nA. Endoscopic sclerotherapy\nB. Metoprolol\nC. Nadolol\nD. Repeat endoscopy",
"options": [
"A. Endoscopic sclerotherapy",
"B. Metoprolol",
"C. Nadolol",
"D. Repeat endoscopy"
],
"answer": "Nadolol",
"gen_text_store": "",
"pid": "171",
"query": "A 56-year-old man recently diagnosed with cirrhosis secondary to alcohol use presents to the clinic for a follow up evaluation. He states that he has abstained from alcohol and attends a support group regularly. He has not taken any new medications or encountered any sick contacts. The patient's blood pressure is 110/70 mmHg, pulse is 65/min, and respirations are 15/min. His physical exam is grossly unremarkable. He has brought an gastroduodenoscopy report for review, which reveals that the patient has small esophageal varices with red spots. What is the next best step to prevent bleeding?\nA. Endoscopic sclerotherapy\nB. Metoprolol\nC. Nadolol\nD. Repeat endoscopy\nChoose the correct option.",
"image": null
},
{
"idx": 172,
"question": "A 28-year-old woman presents following a suicide attempt 2 days ago. She says that her attempt was a result of a fight with her boyfriend and that she slit her wrists in an attempt to keep him from breaking up with her. In the past, she has had many turbulent relationships, both romantic and in her family life. Her family members describe her as being very impulsive and frequently acting to manipulate people’s feelings. Since she was admitted to the hospital, she has spit at several staff members and alternated between sobbing and anger. She has no significant past medical history. The patient denies any history of smoking, alcohol use, or recreational drug use. Which of the following is the most likely diagnosis in this patient?\nA. Histrionic personality disorder\nB. Borderline personality disorder\nC. Dependent personality disorder\nD. Narcissistic personality disorder\n\nA. Histrionic personality disorder\nB. Borderline personality disorder\nC. Dependent personality disorder\nD. Narcissistic personality disorder",
"options": [
"A. Histrionic personality disorder",
"B. Borderline personality disorder",
"C. Dependent personality disorder",
"D. Narcissistic personality disorder"
],
"answer": "Borderline personality disorder",
"gen_text_store": "",
"pid": "172",
"query": "A 28-year-old woman presents following a suicide attempt 2 days ago. She says that her attempt was a result of a fight with her boyfriend and that she slit her wrists in an attempt to keep him from breaking up with her. In the past, she has had many turbulent relationships, both romantic and in her family life. Her family members describe her as being very impulsive and frequently acting to manipulate people’s feelings. Since she was admitted to the hospital, she has spit at several staff members and alternated between sobbing and anger. She has no significant past medical history. The patient denies any history of smoking, alcohol use, or recreational drug use. Which of the following is the most likely diagnosis in this patient?\nA. Histrionic personality disorder\nB. Borderline personality disorder\nC. Dependent personality disorder\nD. Narcissistic personality disorder\nChoose the correct option.",
"image": null
},
{
"idx": 173,
"question": "A 23-year-old man presents to his primary care physician after bleeding from his gums while brushing his teeth for the past week. Although he has had gum bleeding in the past, it has never been this severe. He has no family history available as he was adopted. He does not have any significant past medical history. His physical exam is within normal limits. Screening lab work is ordered with the following values:\nPlatelet count 330,000/mm3\nBleeding time 6 mins\nProthrombin time 12 sec\nActivated partial thromboplastin time 42 sec\nFactor VIII activity decreased\nRistocetin cofactor assay decreased\nHe is subsequently referred to a hematologist for further work-up and treatment. Which of the following aspects of coagulation would most likely be affected?\nA. Gp Ib\nB. Factor XI\nC. Vitamin K\nD. Antithrombin III\n\nA. Gp Ib\nB. Factor XI\nC. Vitamin K\nD. Antithrombin III",
"options": [
"A. Gp Ib",
"B. Factor XI",
"C. Vitamin K",
"D. Antithrombin III"
],
"answer": "Gp Ib",
"gen_text_store": "",
"pid": "173",
"query": "A 23-year-old man presents to his primary care physician after bleeding from his gums while brushing his teeth for the past week. Although he has had gum bleeding in the past, it has never been this severe. He has no family history available as he was adopted. He does not have any significant past medical history. His physical exam is within normal limits. Screening lab work is ordered with the following values:\nPlatelet count 330,000/mm3\nBleeding time 6 mins\nProthrombin time 12 sec\nActivated partial thromboplastin time 42 sec\nFactor VIII activity decreased\nRistocetin cofactor assay decreased\nHe is subsequently referred to a hematologist for further work-up and treatment. Which of the following aspects of coagulation would most likely be affected?\nA. Gp Ib\nB. Factor XI\nC. Vitamin K\nD. Antithrombin III\nChoose the correct option.",
"image": null
},
{
"idx": 174,
"question": "A 26-year-old Caucasian woman is admitted to the emergency department after 4 days of fever, malaise, vomiting, and nausea for which she has been taking ibuprofen and diclofenac. She has also noticed a decrease in urination. Her family and past medical history are unremarkable. Her temperature is 38.2°C (100.7°F), blood pressure is 118/76 mm Hg, heart rate is 74/min, and respiratory rate is 15/min. Upon physical examination, her mucous membranes are moist and she has no abdominal tenderness. Four hours after admission, she has a urinary output < 0.3 mL/kg/h and laboratory tests significant for the following:\nDifferential blood count\nWhite blood cells 8.1 x 109/L\nNeutrophils 4.8 x 109/L\nLymphocytes 2.1 x 109/L\nEosinophils 0.9 x 109/L\nMonocytes 0.3 x 109/L\nBasophils 0.04 x 109/L\n Serum creatinine (SCr) 1.9 mg/dL\nBlood urea nitrogen (BUN) 25 mg/dL\nNa+ 135 mEq/L\nK+ 5.4 mEq/L\nCl- 106 mEq/L\nUrine dipstick\nUrine density 1.010\npH 6.2\nRed blood cells per field of high power 2\nWBC casts Present\nWhich of the following skin manifestations would you also expect to find in this patient?\nA. Janeway lesions\nB. Diffuse maculopapular rash\nC. Malar rash\nD. Erythema nodosum\n\nA. Janeway lesions\nB. Diffuse maculopapular rash\nC. Malar rash\nD. Erythema nodosum",
"options": [
"A. Janeway lesions",
"B. Diffuse maculopapular rash",
"C. Malar rash",
"D. Erythema nodosum"
],
"answer": "Diffuse maculopapular rash",
"gen_text_store": "",
"pid": "174",
"query": "A 26-year-old Caucasian woman is admitted to the emergency department after 4 days of fever, malaise, vomiting, and nausea for which she has been taking ibuprofen and diclofenac. She has also noticed a decrease in urination. Her family and past medical history are unremarkable. Her temperature is 38.2°C (100.7°F), blood pressure is 118/76 mm Hg, heart rate is 74/min, and respiratory rate is 15/min. Upon physical examination, her mucous membranes are moist and she has no abdominal tenderness. Four hours after admission, she has a urinary output < 0.3 mL/kg/h and laboratory tests significant for the following:\nDifferential blood count\nWhite blood cells 8.1 x 109/L\nNeutrophils 4.8 x 109/L\nLymphocytes 2.1 x 109/L\nEosinophils 0.9 x 109/L\nMonocytes 0.3 x 109/L\nBasophils 0.04 x 109/L\n Serum creatinine (SCr) 1.9 mg/dL\nBlood urea nitrogen (BUN) 25 mg/dL\nNa+ 135 mEq/L\nK+ 5.4 mEq/L\nCl- 106 mEq/L\nUrine dipstick\nUrine density 1.010\npH 6.2\nRed blood cells per field of high power 2\nWBC casts Present\nWhich of the following skin manifestations would you also expect to find in this patient?\nA. Janeway lesions\nB. Diffuse maculopapular rash\nC. Malar rash\nD. Erythema nodosum\nChoose the correct option.",
"image": null
},
{
"idx": 175,
"question": "A 5-year-old male presents to the pediatrician with a 10-day history of cough that is worse at night. The patient has a history of mild intermittent asthma and has been using his albuterol inhaler without relief. He has also been complaining of headache and sore throat, and his mother has noticed worsening rhinorrhea. The patient’s past medical history is otherwise unremarkable, and he has no known drug allergies. In the office, his temperature is 101.8°F (38.8°C), blood pressure is 88/65 mmHg, pulse is 132/min, and respirations are 16/min. The patient has purulent mucus draining from the nares, and his face is tender to palpation over the maxillary sinuses. His pharynx is erythematous with symmetric swelling of the tonsils. On lung exam, he has moderate bilateral expiratory wheezing.\n\nWhich of the following is the best next step in management?\nA. Amoxicillin\nB. Amoxicillin-clavulanic acid\nC. Clindamycin\nD. Levofloxacin\n\nA. Amoxicillin\nB. Amoxicillin-clavulanic acid\nC. Clindamycin\nD. Levofloxacin",
"options": [
"A. Amoxicillin",
"B. Amoxicillin-clavulanic acid",
"C. Clindamycin",
"D. Levofloxacin"
],
"answer": "Amoxicillin-clavulanic acid",
"gen_text_store": "",
"pid": "175",
"query": "A 5-year-old male presents to the pediatrician with a 10-day history of cough that is worse at night. The patient has a history of mild intermittent asthma and has been using his albuterol inhaler without relief. He has also been complaining of headache and sore throat, and his mother has noticed worsening rhinorrhea. The patient’s past medical history is otherwise unremarkable, and he has no known drug allergies. In the office, his temperature is 101.8°F (38.8°C), blood pressure is 88/65 mmHg, pulse is 132/min, and respirations are 16/min. The patient has purulent mucus draining from the nares, and his face is tender to palpation over the maxillary sinuses. His pharynx is erythematous with symmetric swelling of the tonsils. On lung exam, he has moderate bilateral expiratory wheezing.\n\nWhich of the following is the best next step in management?\nA. Amoxicillin\nB. Amoxicillin-clavulanic acid\nC. Clindamycin\nD. Levofloxacin\nChoose the correct option.",
"image": null
},
{
"idx": 176,
"question": "While on a teaching sabbatical in Uruguay, a pathologist examined the excised liver of an 18-year-old otherwise healthy female who passed away due to massive hepatic necrosis 5 days after she underwent general anesthesia to repair a fractured femur. Which of the following is a general anesthetic most likely responsible for her death?\nA. Lidocaine\nB. Midazolam\nC. Halothane\nD. Desflurane\n\nA. Lidocaine\nB. Midazolam\nC. Halothane\nD. Desflurane",
"options": [
"A. Lidocaine",
"B. Midazolam",
"C. Halothane",
"D. Desflurane"
],
"answer": "Halothane",
"gen_text_store": "",
"pid": "176",
"query": "While on a teaching sabbatical in Uruguay, a pathologist examined the excised liver of an 18-year-old otherwise healthy female who passed away due to massive hepatic necrosis 5 days after she underwent general anesthesia to repair a fractured femur. Which of the following is a general anesthetic most likely responsible for her death?\nA. Lidocaine\nB. Midazolam\nC. Halothane\nD. Desflurane\nChoose the correct option.",
"image": null
},
{
"idx": 177,
"question": "A 52-year-old woman presents with a complaint of headache for the past 10 days. Her headache is diffuse, dull in character, moderate in intensity, and is worse in the morning. It is not associated with fever and sensitivity to light or sound. She experiences occasional nausea but no vomiting. She did not have similar headaches in the past. Her blood pressure is 140/90 mm Hg; pulse, 60/min, and body mass index is 33.5 kg/m2. The neurological examination reveals normal extraocular movements. Mild bilateral papilledema is present. A magnetic resonance imaging of the brain reveals a solitary lesion in the left temporal region with predominant hemorrhage. Refer to the image below of the MRI of the brain. Which of the following types of cancer has the highest tendency to cause this brain lesion?\nA. Lung cancer\nB. Melanoma\nC. Multiple myeloma\nD. Thyroid cancer\n\nA. Lung cancer\nB. Melanoma\nC. Multiple myeloma\nD. Thyroid cancer",
"options": [
"A. Lung cancer",
"B. Melanoma",
"C. Multiple myeloma",
"D. Thyroid cancer"
],
"answer": "Melanoma",
"gen_text_store": "",
"pid": "177",
"query": "A 52-year-old woman presents with a complaint of headache for the past 10 days. Her headache is diffuse, dull in character, moderate in intensity, and is worse in the morning. It is not associated with fever and sensitivity to light or sound. She experiences occasional nausea but no vomiting. She did not have similar headaches in the past. Her blood pressure is 140/90 mm Hg; pulse, 60/min, and body mass index is 33.5 kg/m2. The neurological examination reveals normal extraocular movements. Mild bilateral papilledema is present. A magnetic resonance imaging of the brain reveals a solitary lesion in the left temporal region with predominant hemorrhage. Refer to the image below of the MRI of the brain. Which of the following types of cancer has the highest tendency to cause this brain lesion?\nA. Lung cancer\nB. Melanoma\nC. Multiple myeloma\nD. Thyroid cancer\nChoose the correct option.",
"image": null
},
{
"idx": 178,
"question": "A 47-year-old female undergoes a thyroidectomy for treatment of Graves' disease. Post-operatively, she reports a hoarse voice and difficulty speaking. You suspect that this is likely a complication of her recent surgery. What is the embryologic origin of the damaged nerve that is most likely causing this patient's hoarseness?\nA. 1st pharyngeal arch\nB. 2nd pharyngeal arch\nC. 3rd pharyngeal arch\nD. 6th pharyngeal arch\n\nA. 1st pharyngeal arch\nB. 2nd pharyngeal arch\nC. 3rd pharyngeal arch\nD. 6th pharyngeal arch",
"options": [
"A. 1st pharyngeal arch",
"B. 2nd pharyngeal arch",
"C. 3rd pharyngeal arch",
"D. 6th pharyngeal arch"
],
"answer": "6th pharyngeal arch",
"gen_text_store": "",
"pid": "178",
"query": "A 47-year-old female undergoes a thyroidectomy for treatment of Graves' disease. Post-operatively, she reports a hoarse voice and difficulty speaking. You suspect that this is likely a complication of her recent surgery. What is the embryologic origin of the damaged nerve that is most likely causing this patient's hoarseness?\nA. 1st pharyngeal arch\nB. 2nd pharyngeal arch\nC. 3rd pharyngeal arch\nD. 6th pharyngeal arch\nChoose the correct option.",
"image": null
},
{
"idx": 179,
"question": "A 12-year-old girl is brought to your psychiatry office by her parents, who are concerned that she has not made any friends since starting middle school last year. The girl tells you that she gets nervous around other children, as she cannot tell what they are feeling, when they are joking, or what she has in common with them. Her teachers describe her as “easily distracted” and “easily upset by change.” When asked about her hobbies and interests, she states that “marine biology” is her only interest and gives you a 15-minute unsolicited explanation of how to identify different penguin species. Mental status exam is notable for intense eye contact, flat affect, and concrete thought process. Which of the following is true regarding this child’s disorder?\nA. Boys are more commonly affected than girls\nB. Impaired attention is a key feature of the disorder\nC. Intellectual disability is a key feature of the disorder\nD. Typical age of onset is 3-5 years of age\n\nA. Boys are more commonly affected than girls\nB. Impaired attention is a key feature of the disorder\nC. Intellectual disability is a key feature of the disorder\nD. Typical age of onset is 3-5 years of age",
"options": [
"A. Boys are more commonly affected than girls",
"B. Impaired attention is a key feature of the disorder",
"C. Intellectual disability is a key feature of the disorder",
"D. Typical age of onset is 3-5 years of age"
],
"answer": "Boys are more commonly affected than girls",
"gen_text_store": "",
"pid": "179",
"query": "A 12-year-old girl is brought to your psychiatry office by her parents, who are concerned that she has not made any friends since starting middle school last year. The girl tells you that she gets nervous around other children, as she cannot tell what they are feeling, when they are joking, or what she has in common with them. Her teachers describe her as “easily distracted” and “easily upset by change.” When asked about her hobbies and interests, she states that “marine biology” is her only interest and gives you a 15-minute unsolicited explanation of how to identify different penguin species. Mental status exam is notable for intense eye contact, flat affect, and concrete thought process. Which of the following is true regarding this child’s disorder?\nA. Boys are more commonly affected than girls\nB. Impaired attention is a key feature of the disorder\nC. Intellectual disability is a key feature of the disorder\nD. Typical age of onset is 3-5 years of age\nChoose the correct option.",
"image": null
},
{
"idx": 180,
"question": "A 61-year-old man was started on rosuvastatin 40 mg 8 weeks ago and presents today for a follow-up. He complains of pain in his legs and general weakness. On physical exam, he has full range of motion of his extremities but complains of pain. His blood pressure is 126/84 mm Hg and heart rate is 74/min. The decision is made to stop the statin and return to the clinic in 2 weeks to assess any changes in symptoms. After stopping the statin, his muscular symptoms resolve. What is the next best course of action to take regarding his LDL control?\nA. Restart rosuvastatin at a lower dose\nB. Initiate fenofibrate\nC. Initiate a different statin\nD. Initiate fish oils\n\nA. Restart rosuvastatin at a lower dose\nB. Initiate fenofibrate\nC. Initiate a different statin\nD. Initiate fish oils",
"options": [
"A. Restart rosuvastatin at a lower dose",
"B. Initiate fenofibrate",
"C. Initiate a different statin",
"D. Initiate fish oils"
],
"answer": "Restart rosuvastatin at a lower dose",
"gen_text_store": "",
"pid": "180",
"query": "A 61-year-old man was started on rosuvastatin 40 mg 8 weeks ago and presents today for a follow-up. He complains of pain in his legs and general weakness. On physical exam, he has full range of motion of his extremities but complains of pain. His blood pressure is 126/84 mm Hg and heart rate is 74/min. The decision is made to stop the statin and return to the clinic in 2 weeks to assess any changes in symptoms. After stopping the statin, his muscular symptoms resolve. What is the next best course of action to take regarding his LDL control?\nA. Restart rosuvastatin at a lower dose\nB. Initiate fenofibrate\nC. Initiate a different statin\nD. Initiate fish oils\nChoose the correct option.",
"image": null
},
{
"idx": 181,
"question": "A 26-year-old woman developed rapidly progressive septic shock associated with nuchal rigidity, petechiae, and purpura. She tested positive for both Kernig and Brudzinski's signs and shows signs of confusion, dyspnea, and hypotension. The blood culture results confirmed the presence of Neisseria meningitidis, and a complete blood count (CBC) revealed leukocytosis. Which one of the cytokines below takes part in the pathogenesis of septic shock?\nA. Tumor necrosis factor-α\nB. Interleukin-5\nC. Interleukin-12\nD. Interleukin-4\n\nA. Tumor necrosis factor-α\nB. Interleukin-5\nC. Interleukin-12\nD. Interleukin-4",
"options": [
"A. Tumor necrosis factor-α",
"B. Interleukin-5",
"C. Interleukin-12",
"D. Interleukin-4"
],
"answer": "Tumor necrosis factor-α",
"gen_text_store": "",
"pid": "181",
"query": "A 26-year-old woman developed rapidly progressive septic shock associated with nuchal rigidity, petechiae, and purpura. She tested positive for both Kernig and Brudzinski's signs and shows signs of confusion, dyspnea, and hypotension. The blood culture results confirmed the presence of Neisseria meningitidis, and a complete blood count (CBC) revealed leukocytosis. Which one of the cytokines below takes part in the pathogenesis of septic shock?\nA. Tumor necrosis factor-α\nB. Interleukin-5\nC. Interleukin-12\nD. Interleukin-4\nChoose the correct option.",
"image": null
},
{
"idx": 182,
"question": "A 38-year-old man is brought to the emergency room by his father because of altered mental status. According to the father, the patient was unable to get out of bed that morning and has become increasingly confused over the past several hours. The father also noticed it was “pretty cold” in his son's apartment because all of the windows were left open overnight. He has a history of hypothyroidism, schizoaffective disorder, type 2 diabetes mellitus, dyslipidemia, and hypertension for which he takes medication. Ten days ago, he was started on a new drug. He appears lethargic. His rectal temperature is 32°C (89.6°F), pulse is 54/min, respirations are 8/min, and blood pressure is 122/80 mm Hg. Examination shows weakness in the lower extremities with absent deep tendon reflexes. Deep tendon reflexes are 1+ in the upper extremities. The pupils are dilated and poorly reactive to light. Throughout the examination, the patient attempts to remove his clothing. Which of the following drugs is the most likely cause of these findings?\nA. Lisinopril\nB. Fluphenazine\nC. Levothyroxine\nD. Atorvastatin\n\"\n\nA. Lisinopril\nB. Fluphenazine\nC. Levothyroxine\nD. Atorvastatin\n\"",
"options": [
"A. Lisinopril",
"B. Fluphenazine",
"C. Levothyroxine",
"D. Atorvastatin\n\""
],
"answer": "Fluphenazine",
"gen_text_store": "",
"pid": "182",
"query": "A 38-year-old man is brought to the emergency room by his father because of altered mental status. According to the father, the patient was unable to get out of bed that morning and has become increasingly confused over the past several hours. The father also noticed it was “pretty cold” in his son's apartment because all of the windows were left open overnight. He has a history of hypothyroidism, schizoaffective disorder, type 2 diabetes mellitus, dyslipidemia, and hypertension for which he takes medication. Ten days ago, he was started on a new drug. He appears lethargic. His rectal temperature is 32°C (89.6°F), pulse is 54/min, respirations are 8/min, and blood pressure is 122/80 mm Hg. Examination shows weakness in the lower extremities with absent deep tendon reflexes. Deep tendon reflexes are 1+ in the upper extremities. The pupils are dilated and poorly reactive to light. Throughout the examination, the patient attempts to remove his clothing. Which of the following drugs is the most likely cause of these findings?\nA. Lisinopril\nB. Fluphenazine\nC. Levothyroxine\nD. Atorvastatin\n\"\nChoose the correct option.",
"image": null
},
{
"idx": 183,
"question": "In 2005, a group of researchers believed that prophylactically removing the ovaries and fallopian tubes (bilateral salpingo-oophorectomy) in BRCA-mutation positive women would reduce the chance that they developed breast cancer. To test this hypothesis, they reviewed a database of women who were known to be BRCA-mutation positive and divided the group into those with breast cancer and those without breast cancer. They used data in the registry and surveys about peoples’ surgical history to compare the proportion of each population that had undergone a bilateral salpingo-oophorectomy. Based on this data, they reported that women undergoing the procedure had a lower chance of developing breast cancer later in life with an odds ratio of 0.46. This is an example of what type of study design?\nA. Meta-analysis\nB. Cross-sectional\nC. Case-control\nD. Genome-wide association study\n\nA. Meta-analysis\nB. Cross-sectional\nC. Case-control\nD. Genome-wide association study",
"options": [
"A. Meta-analysis",
"B. Cross-sectional",
"C. Case-control",
"D. Genome-wide association study"
],
"answer": "Case-control",
"gen_text_store": "",
"pid": "183",
"query": "In 2005, a group of researchers believed that prophylactically removing the ovaries and fallopian tubes (bilateral salpingo-oophorectomy) in BRCA-mutation positive women would reduce the chance that they developed breast cancer. To test this hypothesis, they reviewed a database of women who were known to be BRCA-mutation positive and divided the group into those with breast cancer and those without breast cancer. They used data in the registry and surveys about peoples’ surgical history to compare the proportion of each population that had undergone a bilateral salpingo-oophorectomy. Based on this data, they reported that women undergoing the procedure had a lower chance of developing breast cancer later in life with an odds ratio of 0.46. This is an example of what type of study design?\nA. Meta-analysis\nB. Cross-sectional\nC. Case-control\nD. Genome-wide association study\nChoose the correct option.",
"image": null
},
{
"idx": 184,
"question": "A 36-year-old G3P2 woman with no significant past medical history delivers a 3.7 kg (8 lb, 3 oz) baby boy following an uncomplicated pregnancy. On physical examination in the delivery room, the pediatrician notes that the baby has upslanting palpebral fissures, epicanthal folds, a flat facial profile, small ears, a single palmar crease, and hypotonia. When discussing the diagnosis with the parents, which of the following is this baby at an increased risk for having?\nA. Tetralogy of Fallot\nB. Omphalocele\nC. Congenital cataracts\nD. Cleft lip\n\nA. Tetralogy of Fallot\nB. Omphalocele\nC. Congenital cataracts\nD. Cleft lip",
"options": [
"A. Tetralogy of Fallot",
"B. Omphalocele",
"C. Congenital cataracts",
"D. Cleft lip"
],
"answer": "Omphalocele",
"gen_text_store": "",
"pid": "184",
"query": "A 36-year-old G3P2 woman with no significant past medical history delivers a 3.7 kg (8 lb, 3 oz) baby boy following an uncomplicated pregnancy. On physical examination in the delivery room, the pediatrician notes that the baby has upslanting palpebral fissures, epicanthal folds, a flat facial profile, small ears, a single palmar crease, and hypotonia. When discussing the diagnosis with the parents, which of the following is this baby at an increased risk for having?\nA. Tetralogy of Fallot\nB. Omphalocele\nC. Congenital cataracts\nD. Cleft lip\nChoose the correct option.",
"image": null
},
{
"idx": 185,
"question": "A 57-year-old female with a past medical history of alcoholism presents to the emergency room vomiting bright red blood. She is accompanied by her partner, who reports that she had been complaining of black and tarry stools for the past several days. Vital signs are temperature 37 degrees celsius, heart rate 141 beats per minute, blood pressure 90/60, respiratory rate 20, and oxygen saturation 99% on room air. On physical examination, she has splenomegaly and a positive fluid wave. The remainder of her examination is within normal limits. The patient is stabilized with intravenous fluids, and her blood pressure improves. Subsequent emergent upper endoscopy reveals bleeding from the submucosal veins in the lower 1/3 of the esophagus, but no gastric bleed. In the endoscopy suite she also receives IV octreotide. After intervention and resolution of her acute bleed, which of the following pharmacologic agents is indicated?\nA. Phentolamine\nB. Prazosin\nC. Nifedipine\nD. Nadalol\n\nA. Phentolamine\nB. Prazosin\nC. Nifedipine\nD. Nadalol",
"options": [
"A. Phentolamine",
"B. Prazosin",
"C. Nifedipine",
"D. Nadalol"
],
"answer": "Nadalol",
"gen_text_store": "",
"pid": "185",
"query": "A 57-year-old female with a past medical history of alcoholism presents to the emergency room vomiting bright red blood. She is accompanied by her partner, who reports that she had been complaining of black and tarry stools for the past several days. Vital signs are temperature 37 degrees celsius, heart rate 141 beats per minute, blood pressure 90/60, respiratory rate 20, and oxygen saturation 99% on room air. On physical examination, she has splenomegaly and a positive fluid wave. The remainder of her examination is within normal limits. The patient is stabilized with intravenous fluids, and her blood pressure improves. Subsequent emergent upper endoscopy reveals bleeding from the submucosal veins in the lower 1/3 of the esophagus, but no gastric bleed. In the endoscopy suite she also receives IV octreotide. After intervention and resolution of her acute bleed, which of the following pharmacologic agents is indicated?\nA. Phentolamine\nB. Prazosin\nC. Nifedipine\nD. Nadalol\nChoose the correct option.",
"image": null
},
{
"idx": 186,
"question": "A 65-year-old man with a history of hypertension, obesity, and alcoholic cirrhosis is seen in clinic for follow-up. He feels well and currently drinks 5 glasses of wine each night. Medications include atenolol and lisinopril. On physical exam, temperature is 98.1 deg F (36.7 deg C), blood pressure is 151/82 mmHg, pulse is 71/min, and respirations are 14/min. He has spider angiomata on his chest; no asterixis, jaundice, ascites, or peripheral edema is noted. Screening ultrasound reveals a new liver nodule, and follow up CT demonstrates a 2 cm right hepatic lobe lesion with enhancement in the arterial phase. No hypodense attenuation is seen on the venous or delayed phase. What is the next step in management?\nA. Proceed with liver biopsy\nB. Refer for surgical resection\nC. Refer for radiofrequency ablation\nD. Observe and get follow-up imaging in 3 months\n\nA. Proceed with liver biopsy\nB. Refer for surgical resection\nC. Refer for radiofrequency ablation\nD. Observe and get follow-up imaging in 3 months",
"options": [
"A. Proceed with liver biopsy",
"B. Refer for surgical resection",
"C. Refer for radiofrequency ablation",
"D. Observe and get follow-up imaging in 3 months"
],
"answer": "Proceed with liver biopsy",
"gen_text_store": "",
"pid": "186",
"query": "A 65-year-old man with a history of hypertension, obesity, and alcoholic cirrhosis is seen in clinic for follow-up. He feels well and currently drinks 5 glasses of wine each night. Medications include atenolol and lisinopril. On physical exam, temperature is 98.1 deg F (36.7 deg C), blood pressure is 151/82 mmHg, pulse is 71/min, and respirations are 14/min. He has spider angiomata on his chest; no asterixis, jaundice, ascites, or peripheral edema is noted. Screening ultrasound reveals a new liver nodule, and follow up CT demonstrates a 2 cm right hepatic lobe lesion with enhancement in the arterial phase. No hypodense attenuation is seen on the venous or delayed phase. What is the next step in management?\nA. Proceed with liver biopsy\nB. Refer for surgical resection\nC. Refer for radiofrequency ablation\nD. Observe and get follow-up imaging in 3 months\nChoose the correct option.",
"image": null
},
{
"idx": 187,
"question": "Five days after undergoing an emergency appendectomy under general inhalational anesthesia while on a trip to Haiti, a 43-year-old woman develops low-grade fever, vomiting, and abdominal pain. During the surgery, she received a transfusion of 1 unit of packed red blood cells. Three days after the surgery, she was stable enough to be transported back to the United States. She has no history of serious illness and takes no medications. Her temperature is 38.3°C (100.9°F), pulse is 80/min, and blood pressure is 138/76 mm Hg. Examination shows jaundice of the skin and conjunctivae. Abdominal examination shows moderate tenderness over the liver. The liver is palpated 2 to 3 cm below the right costal margin. Laboratory studies show:\nHemoglobin count 12.0 g/dL\nLeukocyte count 10,400 mm3\nSegmented neutrophils 55%\nBands 1%\nEosinophils 13%\nLymphocytes 28%\nMonocytes 3%\nPlatelet count 160,000 mm3\nSerum\nAlkaline phosphatase 102 U/L\nAspartate aminotransferase 760 U/L\nBilirubin\nTotal 3.8 mg/dL\nDirect 3.1 mg/dL\nAnti-HAV IgG positive\nAnti-HAV IgM negative\nAnti-HBs positive\nHBsAg negative\nAnti-HCV antibodies negative\nAbdominal ultrasonography shows an enlarged liver. A biopsy of the liver shows massive centrilobular necrosis. Which of the following is the most likely underlying cause of this patient's condition?\"\nA. Adverse effect of anesthetic\nB. Gram negative bacteria in the bloodstream\nC. Acalculous inflammation of the gallbladder\nD. Excessive lysis of red blood cells\n\nA. Adverse effect of anesthetic\nB. Gram negative bacteria in the bloodstream\nC. Acalculous inflammation of the gallbladder\nD. Excessive lysis of red blood cells",
"options": [
"A. Adverse effect of anesthetic",
"B. Gram negative bacteria in the bloodstream",
"C. Acalculous inflammation of the gallbladder",
"D. Excessive lysis of red blood cells"
],
"answer": "Adverse effect of anesthetic",
"gen_text_store": "",
"pid": "187",
"query": "Five days after undergoing an emergency appendectomy under general inhalational anesthesia while on a trip to Haiti, a 43-year-old woman develops low-grade fever, vomiting, and abdominal pain. During the surgery, she received a transfusion of 1 unit of packed red blood cells. Three days after the surgery, she was stable enough to be transported back to the United States. She has no history of serious illness and takes no medications. Her temperature is 38.3°C (100.9°F), pulse is 80/min, and blood pressure is 138/76 mm Hg. Examination shows jaundice of the skin and conjunctivae. Abdominal examination shows moderate tenderness over the liver. The liver is palpated 2 to 3 cm below the right costal margin. Laboratory studies show:\nHemoglobin count 12.0 g/dL\nLeukocyte count 10,400 mm3\nSegmented neutrophils 55%\nBands 1%\nEosinophils 13%\nLymphocytes 28%\nMonocytes 3%\nPlatelet count 160,000 mm3\nSerum\nAlkaline phosphatase 102 U/L\nAspartate aminotransferase 760 U/L\nBilirubin\nTotal 3.8 mg/dL\nDirect 3.1 mg/dL\nAnti-HAV IgG positive\nAnti-HAV IgM negative\nAnti-HBs positive\nHBsAg negative\nAnti-HCV antibodies negative\nAbdominal ultrasonography shows an enlarged liver. A biopsy of the liver shows massive centrilobular necrosis. Which of the following is the most likely underlying cause of this patient's condition?\"\nA. Adverse effect of anesthetic\nB. Gram negative bacteria in the bloodstream\nC. Acalculous inflammation of the gallbladder\nD. Excessive lysis of red blood cells\nChoose the correct option.",
"image": null
},
{
"idx": 188,
"question": "A 19-year-old Caucasian male presents to your office with hypopigmented skin. He undergoes a skin biopsy and is found to have an absence of melanocytes in the epidermis. Which of the following is the most likely diagnosis?\nA. Tinea versicolor\nB. Albinism\nC. Vitiligo\nD. Melanoma\n\nA. Tinea versicolor\nB. Albinism\nC. Vitiligo\nD. Melanoma",
"options": [
"A. Tinea versicolor",
"B. Albinism",
"C. Vitiligo",
"D. Melanoma"
],
"answer": "Vitiligo",
"gen_text_store": "",
"pid": "188",
"query": "A 19-year-old Caucasian male presents to your office with hypopigmented skin. He undergoes a skin biopsy and is found to have an absence of melanocytes in the epidermis. Which of the following is the most likely diagnosis?\nA. Tinea versicolor\nB. Albinism\nC. Vitiligo\nD. Melanoma\nChoose the correct option.",
"image": null
},
{
"idx": 189,
"question": "A 20-year-old man comes to the physician because of worsening gait unsteadiness and bilateral hearing loss for 1 month. He has had intermittent tingling sensations on both cheeks over this time period. He has no history of serious medical illness and takes no medications. Audiometry shows bilateral sensorineural hearing loss. Genetic evaluation shows a mutation of a tumor suppressor gene on chromosome 22 that encodes merlin. This patient is at increased risk for which of the following conditions?\nA. Renal cell carcinoma\nB. Meningioma\nC. Astrocytoma\nD. Vascular malformations\n\nA. Renal cell carcinoma\nB. Meningioma\nC. Astrocytoma\nD. Vascular malformations",
"options": [
"A. Renal cell carcinoma",
"B. Meningioma",
"C. Astrocytoma",
"D. Vascular malformations"
],
"answer": "Meningioma",
"gen_text_store": "",
"pid": "189",
"query": "A 20-year-old man comes to the physician because of worsening gait unsteadiness and bilateral hearing loss for 1 month. He has had intermittent tingling sensations on both cheeks over this time period. He has no history of serious medical illness and takes no medications. Audiometry shows bilateral sensorineural hearing loss. Genetic evaluation shows a mutation of a tumor suppressor gene on chromosome 22 that encodes merlin. This patient is at increased risk for which of the following conditions?\nA. Renal cell carcinoma\nB. Meningioma\nC. Astrocytoma\nD. Vascular malformations\nChoose the correct option.",
"image": null
},
{
"idx": 190,
"question": "A 38-year-old nursing home worker presents to the clinic with complaints of fever, loss of appetite, fatigue, and productive cough for the past couple of months. His fever is low-grade and sputum is often blood-tinged. He has lost 6.8 kg (15.0 lb) during this period and complains of profound night sweats. A plain radiograph of the patient’s chest shows consolidation in the apical part of the right lung. Baseline investigations show the following:\nComplete blood count\nHemoglobin 11 g/dL\nWhite blood cells \nTotal count 16,000/mm3\nDifferential count \nNeutrophils 35%\nLymphocytes 54%\nEosinophils 11%\nErythrocyte sedimentation rate 84 mm\nThe physician suspects that the patient is suffering from a chronic lung infection. Which of the following statements best describes the type of lung inflammation in this patient?\nA. There are small granulomas with few epithelioid cells along with fibrosis.\nB. It has a granuloma with Anitchov cells around a core of fibrinoid collagen necrosis.\nC. It consists of a largely circumscribed granuloma with epithelioid cells with Langhans cells.\nD. This type of granulomatous inflammation is also seen in histoplasmosis.\n\nA. There are small granulomas with few epithelioid cells along with fibrosis.\nB. It has a granuloma with Anitchov cells around a core of fibrinoid collagen necrosis.\nC. It consists of a largely circumscribed granuloma with epithelioid cells with Langhans cells.\nD. This type of granulomatous inflammation is also seen in histoplasmosis.",
"options": [
"A. There are small granulomas with few epithelioid cells along with fibrosis.",
"B. It has a granuloma with Anitchov cells around a core of fibrinoid collagen necrosis.",
"C. It consists of a largely circumscribed granuloma with epithelioid cells with Langhans cells.",
"D. This type of granulomatous inflammation is also seen in histoplasmosis."
],
"answer": "It consists of a largely circumscribed granuloma with epithelioid cells with Langhans cells.",
"gen_text_store": "",
"pid": "190",
"query": "A 38-year-old nursing home worker presents to the clinic with complaints of fever, loss of appetite, fatigue, and productive cough for the past couple of months. His fever is low-grade and sputum is often blood-tinged. He has lost 6.8 kg (15.0 lb) during this period and complains of profound night sweats. A plain radiograph of the patient’s chest shows consolidation in the apical part of the right lung. Baseline investigations show the following:\nComplete blood count\nHemoglobin 11 g/dL\nWhite blood cells \nTotal count 16,000/mm3\nDifferential count \nNeutrophils 35%\nLymphocytes 54%\nEosinophils 11%\nErythrocyte sedimentation rate 84 mm\nThe physician suspects that the patient is suffering from a chronic lung infection. Which of the following statements best describes the type of lung inflammation in this patient?\nA. There are small granulomas with few epithelioid cells along with fibrosis.\nB. It has a granuloma with Anitchov cells around a core of fibrinoid collagen necrosis.\nC. It consists of a largely circumscribed granuloma with epithelioid cells with Langhans cells.\nD. This type of granulomatous inflammation is also seen in histoplasmosis.\nChoose the correct option.",
"image": null
},
{
"idx": 191,
"question": "A 40-year-old patient is brought into the emergency department after suffering a motor vehicle crash where he was pinned underneath his motorcycle for about 30 minutes before a passerby called 911. While evaluating him per your institution's trauma guidelines, you discover pain upon palpation of his right lower extremity which is much larger than his left counterpart. The patient admits to decreased sensation over his right lower extremity and cannot move his leg. There are no palpable dorsalis pedis or posterior tibial pulses on this extremity, and it is colder and paler in comparison to his left side. Measured compartment pressure of his distal right leg is 35 mm Hg. What is the next best step in this patient's care?\nA. Emergent fasciotomy\nB. Venous doppler\nC. Arteriogram\nD. External fixation\n\nA. Emergent fasciotomy\nB. Venous doppler\nC. Arteriogram\nD. External fixation",
"options": [
"A. Emergent fasciotomy",
"B. Venous doppler",
"C. Arteriogram",
"D. External fixation"
],
"answer": "Emergent fasciotomy",
"gen_text_store": "",
"pid": "191",
"query": "A 40-year-old patient is brought into the emergency department after suffering a motor vehicle crash where he was pinned underneath his motorcycle for about 30 minutes before a passerby called 911. While evaluating him per your institution's trauma guidelines, you discover pain upon palpation of his right lower extremity which is much larger than his left counterpart. The patient admits to decreased sensation over his right lower extremity and cannot move his leg. There are no palpable dorsalis pedis or posterior tibial pulses on this extremity, and it is colder and paler in comparison to his left side. Measured compartment pressure of his distal right leg is 35 mm Hg. What is the next best step in this patient's care?\nA. Emergent fasciotomy\nB. Venous doppler\nC. Arteriogram\nD. External fixation\nChoose the correct option.",
"image": null
},
{
"idx": 192,
"question": "A 42-year-old man comes to the physician after elevated liver function tests were found after a routine screening. He has had occasional headaches over the past year, but otherwise feels well. The patient reports that he was involved in a severe car accident 30 years ago. He does not smoke or drink alcohol. He has never used illicit intravenous drugs. He takes no medications and has no known allergies. His father had a history of alcoholism and died of liver cancer. The patient appears thin. His temperature is 37.8°C (100°F), pulse is 100/min, and blood pressure is 110/70 mm Hg. Physical examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14 g/dL\nLeukocyte count 10,000/mm3\nPlatelet count 146,000/mm3\nSerum\nGlucose 150 mg/dL\nAlbumin 3.2 g/dL\nTotal bilirubin 1.5 mg/dL\nAlkaline phosphatase 75 U/L\nAST 95 U/L\nALT 73 U/L\nHIV negative\nHepatitis B surface antigen negative\nHepatitis C antibody positive\nHCV RNA positive\nHCV genotype 1\nA liver biopsy is performed and shows mononuclear infiltrates that are limited to portal tracts and periportal hepatocyte necrosis. Which of the following is the most appropriate next step in management?\"\nA. Sofosbuvir and ledipasvir therapy\nB. Tenofovir and velpatasvir therapy\nC. Interferon and ribavirin therapy\nD. Tenofovir and entecavir therapy\n\nA. Sofosbuvir and ledipasvir therapy\nB. Tenofovir and velpatasvir therapy\nC. Interferon and ribavirin therapy\nD. Tenofovir and entecavir therapy",
"options": [
"A. Sofosbuvir and ledipasvir therapy",
"B. Tenofovir and velpatasvir therapy",
"C. Interferon and ribavirin therapy",
"D. Tenofovir and entecavir therapy"
],
"answer": "Sofosbuvir and ledipasvir therapy",
"gen_text_store": "",
"pid": "192",
"query": "A 42-year-old man comes to the physician after elevated liver function tests were found after a routine screening. He has had occasional headaches over the past year, but otherwise feels well. The patient reports that he was involved in a severe car accident 30 years ago. He does not smoke or drink alcohol. He has never used illicit intravenous drugs. He takes no medications and has no known allergies. His father had a history of alcoholism and died of liver cancer. The patient appears thin. His temperature is 37.8°C (100°F), pulse is 100/min, and blood pressure is 110/70 mm Hg. Physical examination shows no abnormalities. Laboratory studies show:\nHemoglobin 14 g/dL\nLeukocyte count 10,000/mm3\nPlatelet count 146,000/mm3\nSerum\nGlucose 150 mg/dL\nAlbumin 3.2 g/dL\nTotal bilirubin 1.5 mg/dL\nAlkaline phosphatase 75 U/L\nAST 95 U/L\nALT 73 U/L\nHIV negative\nHepatitis B surface antigen negative\nHepatitis C antibody positive\nHCV RNA positive\nHCV genotype 1\nA liver biopsy is performed and shows mononuclear infiltrates that are limited to portal tracts and periportal hepatocyte necrosis. Which of the following is the most appropriate next step in management?\"\nA. Sofosbuvir and ledipasvir therapy\nB. Tenofovir and velpatasvir therapy\nC. Interferon and ribavirin therapy\nD. Tenofovir and entecavir therapy\nChoose the correct option.",
"image": null
},
{
"idx": 193,
"question": "A 31-year-old female patient presents with significant swelling and redness of her fingers that is causing her significant pain. Her right knee has also been stiff and slightly swollen for the past 6 weeks. She is overall fatigued and has difficulty moving around but has not sought medical attention until now. On physical examination, the distal interphalangeal joints are swollen, warm, and painful; her nails are pitted and cracked. There are also rough, erythematous skin patches seen over her elbows which have been present for the last few months. She reports that herer father has a similar condition. They both use hydrating creams and topical glucocorticoids with moderate benefit. Which of the following is the most likely diagnosis?\nA. Gout\nB. Reactive arthritis\nC. Psoriatic arthritis\nD. Dermatomyositis\n\nA. Gout\nB. Reactive arthritis\nC. Psoriatic arthritis\nD. Dermatomyositis",
"options": [
"A. Gout",
"B. Reactive arthritis",
"C. Psoriatic arthritis",
"D. Dermatomyositis"
],
"answer": "Psoriatic arthritis",
"gen_text_store": "",
"pid": "193",
"query": "A 31-year-old female patient presents with significant swelling and redness of her fingers that is causing her significant pain. Her right knee has also been stiff and slightly swollen for the past 6 weeks. She is overall fatigued and has difficulty moving around but has not sought medical attention until now. On physical examination, the distal interphalangeal joints are swollen, warm, and painful; her nails are pitted and cracked. There are also rough, erythematous skin patches seen over her elbows which have been present for the last few months. She reports that herer father has a similar condition. They both use hydrating creams and topical glucocorticoids with moderate benefit. Which of the following is the most likely diagnosis?\nA. Gout\nB. Reactive arthritis\nC. Psoriatic arthritis\nD. Dermatomyositis\nChoose the correct option.",
"image": null
},
{
"idx": 194,
"question": "A 54-year-old man is brought to the emergency department after he was found outside in the middle of a blizzard. On presentation, he is conscious but does not know where he is nor how he got there. His wife is contacted and says that he has been getting increasingly confused over the past 6 weeks. This progressed from misplacing objects to getting lost in places that he knew how to navigate previously. Most worryingly, he has recently started forgetting the names of their children. In addition to these memory changes, she says that he now has rapid jerky movements of his extremities as well as coordination and balance problems. Finally, he has become extremely paranoid about government surveillance and has had hallucinations about secret agents in their house. His previous medical history is significant for a previous car crash in which the patient required internal fixation of a femur fracture and a corneal transplant for corneal degeneration. Otherwise he had no neurologic deficits prior to 6 weeks ago. Physical exam reveals myoclonus and ataxia. Which of the following is true of the most likely cause of this patient's symptoms?\nA. Can be transmitted on medical equipment even after autoclaving instruments\nB. Contains genetic material but is unable to survive independent from a host\nC. Has a cell wall containing peptidoglycan\nD. Leads to intracellular aggregations of hyperphosphorylated tau protein\n\nA. Can be transmitted on medical equipment even after autoclaving instruments\nB. Contains genetic material but is unable to survive independent from a host\nC. Has a cell wall containing peptidoglycan\nD. Leads to intracellular aggregations of hyperphosphorylated tau protein",
"options": [
"A. Can be transmitted on medical equipment even after autoclaving instruments",
"B. Contains genetic material but is unable to survive independent from a host",
"C. Has a cell wall containing peptidoglycan",
"D. Leads to intracellular aggregations of hyperphosphorylated tau protein"
],
"answer": "Can be transmitted on medical equipment even after autoclaving instruments",
"gen_text_store": "",
"pid": "194",
"query": "A 54-year-old man is brought to the emergency department after he was found outside in the middle of a blizzard. On presentation, he is conscious but does not know where he is nor how he got there. His wife is contacted and says that he has been getting increasingly confused over the past 6 weeks. This progressed from misplacing objects to getting lost in places that he knew how to navigate previously. Most worryingly, he has recently started forgetting the names of their children. In addition to these memory changes, she says that he now has rapid jerky movements of his extremities as well as coordination and balance problems. Finally, he has become extremely paranoid about government surveillance and has had hallucinations about secret agents in their house. His previous medical history is significant for a previous car crash in which the patient required internal fixation of a femur fracture and a corneal transplant for corneal degeneration. Otherwise he had no neurologic deficits prior to 6 weeks ago. Physical exam reveals myoclonus and ataxia. Which of the following is true of the most likely cause of this patient's symptoms?\nA. Can be transmitted on medical equipment even after autoclaving instruments\nB. Contains genetic material but is unable to survive independent from a host\nC. Has a cell wall containing peptidoglycan\nD. Leads to intracellular aggregations of hyperphosphorylated tau protein\nChoose the correct option.",
"image": null
},
{
"idx": 195,
"question": "A 58-year-old man comes to the physician because he is unable to achieve erections during sexual intercourse. He first noticed the problem 8 months ago, when he became sexually active with a new girlfriend. He states that his relationship with his girlfriend is good, but his inability to engage in sexual intercourse has been frustrating. He has hyperlipidemia and was diagnosed with major depressive disorder 3 years ago. He works as a lawyer and enjoys his job, but he has had a great deal of stress lately. He had not been sexually active for the previous 3 years, since the death of his wife. He does not smoke. He drinks 4–6 beers on weekends. Current medications include simvastatin and citalopram. His temperature is 37.5°C (99.5°F), pulse is 80/min, and blood pressure is 135/82 mm Hg. BMI is 30 kg/m2. Pedal pulses are difficult to palpate. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Psychotherapy\nB. Penile prosthesis insertion\nC. Nocturnal penile tumescence testing\nD. Switch citalopram to bupropion\n\nA. Psychotherapy\nB. Penile prosthesis insertion\nC. Nocturnal penile tumescence testing\nD. Switch citalopram to bupropion",
"options": [
"A. Psychotherapy",
"B. Penile prosthesis insertion",
"C. Nocturnal penile tumescence testing",
"D. Switch citalopram to bupropion"
],
"answer": "Nocturnal penile tumescence testing",
"gen_text_store": "",
"pid": "195",
"query": "A 58-year-old man comes to the physician because he is unable to achieve erections during sexual intercourse. He first noticed the problem 8 months ago, when he became sexually active with a new girlfriend. He states that his relationship with his girlfriend is good, but his inability to engage in sexual intercourse has been frustrating. He has hyperlipidemia and was diagnosed with major depressive disorder 3 years ago. He works as a lawyer and enjoys his job, but he has had a great deal of stress lately. He had not been sexually active for the previous 3 years, since the death of his wife. He does not smoke. He drinks 4–6 beers on weekends. Current medications include simvastatin and citalopram. His temperature is 37.5°C (99.5°F), pulse is 80/min, and blood pressure is 135/82 mm Hg. BMI is 30 kg/m2. Pedal pulses are difficult to palpate. The remainder of the physical examination shows no abnormalities. Which of the following is the most appropriate next step in management?\nA. Psychotherapy\nB. Penile prosthesis insertion\nC. Nocturnal penile tumescence testing\nD. Switch citalopram to bupropion\nChoose the correct option.",
"image": null
},
{
"idx": 196,
"question": "An otherwise healthy 29-year-old man presents to his family physician with a slowly growing left neck mass for the past 5 weeks. He denies fever or recent upper respiratory tract infections. His temperature is 37.1°C (98.7°F), the blood pressure is 115/72 mm Hg, and the pulse are 82/min. On examination, a 4-cm (1.5 in), firm, non-tender mass is detected on the mid-left neck. Excisional biopsy of the mass reveals Hodgkin’s cells. The patient is referred to the oncology department and chemotherapy is started. After the first cycle of chemotherapy, the patient notices that his urine becomes red. The urine tests are positive for blood on further analysis. Which of the following is the most likely cause of this patient condition?\nA. Bleomycin\nB. Cyclophosphamide\nC. Doxorubicin\nD. Etoposide\n\nA. Bleomycin\nB. Cyclophosphamide\nC. Doxorubicin\nD. Etoposide",
"options": [
"A. Bleomycin",
"B. Cyclophosphamide",
"C. Doxorubicin",
"D. Etoposide"
],
"answer": "Cyclophosphamide",
"gen_text_store": "",
"pid": "196",
"query": "An otherwise healthy 29-year-old man presents to his family physician with a slowly growing left neck mass for the past 5 weeks. He denies fever or recent upper respiratory tract infections. His temperature is 37.1°C (98.7°F), the blood pressure is 115/72 mm Hg, and the pulse are 82/min. On examination, a 4-cm (1.5 in), firm, non-tender mass is detected on the mid-left neck. Excisional biopsy of the mass reveals Hodgkin’s cells. The patient is referred to the oncology department and chemotherapy is started. After the first cycle of chemotherapy, the patient notices that his urine becomes red. The urine tests are positive for blood on further analysis. Which of the following is the most likely cause of this patient condition?\nA. Bleomycin\nB. Cyclophosphamide\nC. Doxorubicin\nD. Etoposide\nChoose the correct option.",
"image": null
},
{
"idx": 197,
"question": "A 55-year-old woman is found to have an abnormal mass on routine mammography. The mass is biopsied and cytology results are diagnostic for invasive ductal adenocarcinoma that is estrogen receptor positive. The patient is started on chemotherapy and ultimately has the mass resected. She is taking tamoxifen and has regular outpatient follow up appointments to monitor for any recurrence of cancer. The patient has a past medical history of asthma, obesity, and a uterine leimyoma which was definitively treated last year. Her last menstrual period was at the age of 47. The patient's vital signs and exam are unremarkable. Which of the following is a potential complication that could occur in this patient?\nA. Deep venous thrombosis\nB. Eruption of seborrheic keratoses\nC. Increased bleeding\nD. Osteoporosis\n\nA. Deep venous thrombosis\nB. Eruption of seborrheic keratoses\nC. Increased bleeding\nD. Osteoporosis",
"options": [
"A. Deep venous thrombosis",
"B. Eruption of seborrheic keratoses",
"C. Increased bleeding",
"D. Osteoporosis"
],
"answer": "Deep venous thrombosis",
"gen_text_store": "",
"pid": "197",
"query": "A 55-year-old woman is found to have an abnormal mass on routine mammography. The mass is biopsied and cytology results are diagnostic for invasive ductal adenocarcinoma that is estrogen receptor positive. The patient is started on chemotherapy and ultimately has the mass resected. She is taking tamoxifen and has regular outpatient follow up appointments to monitor for any recurrence of cancer. The patient has a past medical history of asthma, obesity, and a uterine leimyoma which was definitively treated last year. Her last menstrual period was at the age of 47. The patient's vital signs and exam are unremarkable. Which of the following is a potential complication that could occur in this patient?\nA. Deep venous thrombosis\nB. Eruption of seborrheic keratoses\nC. Increased bleeding\nD. Osteoporosis\nChoose the correct option.",
"image": null
},
{
"idx": 198,
"question": "A previously healthy, 24-year-old man comes to the physician because of a 6-week history of loose, nonbloody stools. He also reports abdominal pain, intermittent nausea, and fever. He has not had vomiting, tenesmus, or rectal pain. His vital signs are within normal limits. Abdominal examination reveals tenderness of the right lower abdomen without rebound tenderness. Rectal exam is unremarkable. Laboratory studies show a leukocyte count of 14,800/mm3 and an erythrocyte sedimentation rate of 51 mm/h. Test of the stool for occult blood and stool studies for infection are negative. A CT scan of the abdomen shows mural thickening and surrounding fat stranding of discrete regions of the terminal ileum and transverse colon. A colonoscopy is performed and biopsy specimens of the affected areas of the colon are taken. Which of the following findings is most specific for this patient's condition?\nA. Neutrophilic inflammation of the crypts\nB. Neutrophil-rich pseudomembranes\nC. Formation of noncaseating granulomas\nD. Presence of pseudopolyps\n\nA. Neutrophilic inflammation of the crypts\nB. Neutrophil-rich pseudomembranes\nC. Formation of noncaseating granulomas\nD. Presence of pseudopolyps",
"options": [
"A. Neutrophilic inflammation of the crypts",
"B. Neutrophil-rich pseudomembranes",
"C. Formation of noncaseating granulomas",
"D. Presence of pseudopolyps"
],
"answer": "Formation of noncaseating granulomas",
"gen_text_store": "",
"pid": "198",
"query": "A previously healthy, 24-year-old man comes to the physician because of a 6-week history of loose, nonbloody stools. He also reports abdominal pain, intermittent nausea, and fever. He has not had vomiting, tenesmus, or rectal pain. His vital signs are within normal limits. Abdominal examination reveals tenderness of the right lower abdomen without rebound tenderness. Rectal exam is unremarkable. Laboratory studies show a leukocyte count of 14,800/mm3 and an erythrocyte sedimentation rate of 51 mm/h. Test of the stool for occult blood and stool studies for infection are negative. A CT scan of the abdomen shows mural thickening and surrounding fat stranding of discrete regions of the terminal ileum and transverse colon. A colonoscopy is performed and biopsy specimens of the affected areas of the colon are taken. Which of the following findings is most specific for this patient's condition?\nA. Neutrophilic inflammation of the crypts\nB. Neutrophil-rich pseudomembranes\nC. Formation of noncaseating granulomas\nD. Presence of pseudopolyps\nChoose the correct option.",
"image": null
},
{
"idx": 199,
"question": "A 63-year-old man with diverticular disease comes to the emergency department because of painless rectal bleeding, dizziness, and lightheadedness for 2 hours. His temperature is 37.6°C (99.6°F), pulse is 115/min, respirations are 24/min, and blood pressure is 86/60 mm Hg. He appears pale. Physical examination shows bright red rectal bleeding. Colonoscopy shows profuse diverticular bleeding; endoscopic hemostasis is performed. After initiating fluid resuscitation, the patient becomes hemodynamically stable. The following day, laboratory studies show:\nHemoglobin 8 g/dL\nLeukocyte count 15,500/mm3\nPlatelet count 170,000/mm3\nSerum\nUrea nitrogen 60 mg/dL\nCreatinine 2.1 mg/dL\nBilirubin\nTotal 1.2 mg/dL\nIndirect 0.3 mg/dL\nAlkaline phosphatase 96 U/L\nAlanine aminotransferase (ALT, GPT) 2,674 U/L\nAspartate aminotransferase (AST, GOT) 2,254 U/L\nWhich of the following cells in the patient's liver were most likely damaged first?\"\nA. Periportal hepatocytes\nB. Hepatic sinusoidal endothelial cells\nC. Hepatic Kupffer cells\nD. Centrilobular hepatocytes\n\nA. Periportal hepatocytes\nB. Hepatic sinusoidal endothelial cells\nC. Hepatic Kupffer cells\nD. Centrilobular hepatocytes",
"options": [
"A. Periportal hepatocytes",
"B. Hepatic sinusoidal endothelial cells",
"C. Hepatic Kupffer cells",
"D. Centrilobular hepatocytes"
],
"answer": "Centrilobular hepatocytes",
"gen_text_store": "",
"pid": "199",
"query": "A 63-year-old man with diverticular disease comes to the emergency department because of painless rectal bleeding, dizziness, and lightheadedness for 2 hours. His temperature is 37.6°C (99.6°F), pulse is 115/min, respirations are 24/min, and blood pressure is 86/60 mm Hg. He appears pale. Physical examination shows bright red rectal bleeding. Colonoscopy shows profuse diverticular bleeding; endoscopic hemostasis is performed. After initiating fluid resuscitation, the patient becomes hemodynamically stable. The following day, laboratory studies show:\nHemoglobin 8 g/dL\nLeukocyte count 15,500/mm3\nPlatelet count 170,000/mm3\nSerum\nUrea nitrogen 60 mg/dL\nCreatinine 2.1 mg/dL\nBilirubin\nTotal 1.2 mg/dL\nIndirect 0.3 mg/dL\nAlkaline phosphatase 96 U/L\nAlanine aminotransferase (ALT, GPT) 2,674 U/L\nAspartate aminotransferase (AST, GOT) 2,254 U/L\nWhich of the following cells in the patient's liver were most likely damaged first?\"\nA. Periportal hepatocytes\nB. Hepatic sinusoidal endothelial cells\nC. Hepatic Kupffer cells\nD. Centrilobular hepatocytes\nChoose the correct option.",
"image": null
}
]
================================================
FILE: data.py
================================================
from typing import Dict, Iterable, Optional
from datasets import load_dataset
from utils import extract_gold, normalize_answer
def load_gsm8k(split: str = "test", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("gsm8k", "main", split=split, cache_dir=cache_dir)
for item in ds:
question = item["question"].strip()
solution = item["answer"]
gold = normalize_answer(extract_gold(solution))
yield {
"question": question,
"solution": solution,
"gold": gold,
}
def load_aime2025(split: str = "train", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("yentinglin/aime_2025", split=split, cache_dir=cache_dir)
for item in ds:
problem = item["problem"].strip()
answer = str(item["answer"]).strip()
gold = normalize_answer(answer)
yield {
"question": problem,
"solution": answer,
"gold": gold,
}
def load_aime2024(split: str = "train", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("HuggingFaceH4/aime_2024", split=split, cache_dir=cache_dir)
for item in ds:
problem = item["problem"].strip()
answer = str(item["answer"]).strip()
gold = normalize_answer(answer)
yield {
"question": problem,
"solution": answer,
"gold": gold,
}
def load_gpqa_diamond(split: str = "test", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("fingertap/GPQA-Diamond", split=split, cache_dir=cache_dir)
for item in ds:
question = item["question"].strip()
answer = item["answer"].strip()
gold = normalize_answer(answer)
yield {
"question": question,
"solution": answer,
"gold": gold,
}
def load_arc_easy(split: str = "test", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("allenai/ai2_arc", "ARC-Easy", split=split, cache_dir=cache_dir)
for item in ds:
stem = item["question"].strip()
choices = item["choices"]
labels = choices["label"]
texts = choices["text"]
label_map = {"1": "a", "2": "b", "3": "c", "4": "d"}
def map_label(l: str) -> str:
s = str(l).strip()
if s in label_map:
return label_map[s]
return s.lower()
# Map choices
formatted_choices = {}
mapped_order = []
for label, text in zip(labels, texts):
mlabel = map_label(label)
formatted_choices[mlabel] = text.strip()
mapped_order.append(mlabel)
ordered_lines = [f"{lab}: {formatted_choices[lab]}" for lab in mapped_order]
question = stem + "\n" + "\n".join(ordered_lines)
# Map answers
raw_answer = item.get("answerKey", "").strip()
mapped_answer = map_label(raw_answer) if raw_answer else ""
gold = normalize_answer(mapped_answer)
yield {
"question": question,
"solution": mapped_answer,
"gold": gold,
}
def load_arc_challenge(split: str = "test", cache_dir: Optional[str] = None) -> Iterable[Dict]:
ds = load_dataset("allenai/ai2_arc", "ARC-Challenge", split=split, cache_dir=cache_dir)
for item in ds:
stem = item["question"].strip()
choices = item["choices"]
labels = choices["label"]
texts = choices["text"]
label_map = {"1": "a", "2": "b", "3": "c", "4": "d"}
def map_label(l: str) -> str:
s = str(l).strip()
if s in label_map:
return label_map[s]
return s.lower()
formatted_choices = {}
mapped_order = []
for label, text in zip(labels, texts):
mlabel = map_label(label)
formatted_choices[mlabel] = text.strip()
mapped_order.append(mlabel)
ordered_lines = [f"{lab}: {formatted_choices[lab]}" for lab in mapped_order]
question = stem + "\n" + "\n".join(ordered_lines)
raw_answer = item.get("answerKey", "").strip()
mapped_answer = map_label(raw_answer) if raw_answer else ""
gold = normalize_answer(mapped_answer)
yield {
"question": question,
"solution": mapped_answer,
"gold": gold,
}
def load_winogrande(
split: str = "validation",
subset: str = "winogrande_debiased",
cache_dir: Optional[str] = None,
) -> Iterable[Dict]:
ds = load_dataset("allenai/winogrande", subset, split=split, cache_dir=cache_dir)
for item in ds:
ask_str = 'Pickout proper choice that fits the _ in the following sentence:'
sentence = item["sentence"].strip()
option1 = str(item["option1"]).strip()
option2 = str(item["option2"]).strip()
question = f"{ask_str}\n{sentence}\n1: {option1}\n2: {option2}"
answer = str(item["answer"])
gold = normalize_answer(answer)
yield {
"question": question,
"solution": answer,
"gold": gold,
}
def load_mbppplus(
split: str = "test",
subset: str = None,
cache_dir: Optional[str] = None,
) -> Iterable[Dict]:
ds = load_dataset("evalplus/mbppplus", subset, split=split, cache_dir=cache_dir)
for item in ds:
question = f"""Please provide a self-contained Python script that solves the following problem in a markdown code block:\n```python\nYOUR_PYTHON_CODE\n```:
{item["prompt"]}
Your answer will be tested on test cases like:
{item["test_list"][0]}
{item["test_list"][1]}
{item["test_list"][2]}
"""
answer = str(item["test"])
gold = answer
yield {
"question": question,
"solution": answer,
"gold": gold,
}
def load_humanevalplus(
split: str = "test",
subset: str = None,
cache_dir: Optional[str] = None,
) -> Iterable[Dict]:
ds = load_dataset("evalplus/humanevalplus", subset, split=split, cache_dir=cache_dir)
for item in ds:
question = f"""Please provide a self-contained Python script that solves the following problem in a markdown code block:\n```python\nYOUR_PYTHON_CODE\n```:
{item["prompt"]}
"""
raw_answer = str(item["test"])
answer = raw_answer.replace('candidate', item['entry_point'])
answer += f'\n\ncheck({item["entry_point"]})'
gold = answer
yield {
"question": question,
"solution": answer,
"gold": gold,
}
# qa data from https://github.com/lupantech/AgentFlow/tree/main
from typing import Iterable, Dict, Optional
from datasets import load_dataset
def load_medqa(split=None, subset=None, cache_dir=None):
ds = load_dataset("json", data_files="./data/medqa.json", split='train')
for item in ds:
question = item["query"]
raw_answer = str(item["answer"])
choice_map = {"0":"A", "1":"B", "2":"C", "3":"D"}
for idx, op in enumerate(item['options']):
if raw_answer in op:
answer = choice_map[str(idx)].lower()
break
gold = normalize_answer(answer)
yield {
"question": question,
"solution": answer,
"gold": gold,
}
================================================
FILE: example_logs/qwen3_14b_humanevalplus_hierarchical.txt
================================================
[File too large to display: 12.2 MB]
================================================
FILE: example_logs/qwen3_14b_mbppplus_sequential.txt
================================================
method: latent_mas
model_name: Qwen/Qwen3-14B
device: cuda
seed: 42
max_samples: -1
split: test
task: mbppplus
max_new_tokens: 4096
temperature: 0.6
top_p: 0.95
generate_bs: 15
think: True
out: None
use_vllm: False
enable_prefix_caching: False
use_second_HF_model: False
device2: cuda:1
prompt: sequential
=========================================
Question 0
error_msg: None
=========================================
Question 1
error_msg: None
=========================================
Question 2
error_msg: None
=========================================
Question 3
error_msg: None
=========================================
Question 4
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 31, in
File "", line 25, in assertion
AssertionError: out: {'words', 'characters', 'least', 'string', 'This', 'with', 'very', 'that', 'long', 'long.'}, exp: {'words', 'characters', 'least', 'string', 'This', 'with', 'very', 'that', 'long'}
=========================================
Question 5
error_msg: None
=========================================
Question 6
error_msg: None
=========================================
Question 7
error_msg: None
=========================================
Question 8
error_msg: None
=========================================
Question 9
error_msg: None
=========================================
Question 10
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 31, in
File "", line 25, in assertion
AssertionError: out: False, exp: True
=========================================
Question 11
error_msg: None
=========================================
Question 12
error_msg: None
=========================================
Question 13
error_msg: None
=========================================
Question 14
error_msg: None
==================== Problem #1 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the shared elements from the given two lists.
Your answer will be tested on test cases like:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the shared elements from the given two lists.
Your answer will be tested on test cases like:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the shared elements from the given two lists.
Your answer will be tested on test cases like:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the shared elements from the given two lists.
Your answer will be tested on test cases like:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the shared elements from the given two lists.
Your answer will be tested on test cases like:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called similar_elements that takes two lists (or maybe tuples?) and returns their shared elements. The test case uses tuples, but the function is supposed to work with lists, I think. Wait, the problem says "given two lists", but the example uses tuples. Hmm, but in Python, tuples are iterable like lists. So maybe the function can handle any iterables.
The goal is to find the elements that are present in both. The test case checks that the set of the result is equal to {4,5}, so the order doesn't matter, and duplicates are not considered. So the function should return a list (or maybe a tuple?) of the common elements, but without duplicates? Or does it need to preserve duplicates if they exist in both?
Wait, the example uses tuples as input, but the output is a set. The problem says "shared elements", which usually refers to the intersection. So the function should return the elements that are present in both, but each element once, regardless of how many times they appear in each list. Or maybe the problem expects to return all occurrences? Wait, the test case uses (3,4,5,6) and (5,7,4,10). The shared elements are 4 and 5. The output is (4,5), but the order isn't specified. The test uses set(similar_elements(...)) to check, so the order doesn't matter. So the function should return a list (or tuple) of the common elements, but each element once, regardless of duplicates in the input.
So, the approach is to find the intersection of the two input lists. But how to do that in Python?
Well, one way is to convert both to sets and take the intersection. But the problem says that the function should return the shared elements. However, the test case expects the output to be (4,5), which is a tuple. But the problem says the function is supposed to return the shared elements as a list? Wait, the problem says "given two lists", but the example uses tuples. But the function's parameters are given as (3,4,5,6) and (5,7,4,10), which are tuples. But the problem says the function is supposed to take two lists. Wait, maybe the parameters are actually tuples, but the function can handle any iterables.
But the user's test case uses tuples, but the function is supposed to work with lists. Maybe the function can take any two iterables. So, the function similar_elements should take two arguments, which are lists (or tuples, etc.), and return a list (or tuple?) of the elements that are present in both.
But the test case uses set(similar_elements(...)) == set((4,5)). So the output of similar_elements is a tuple (since the example uses (4,5)), but the set conversion is done to check the elements. So the function should return a tuple of the common elements, but in any order. But how to get the elements in the order they appear in the first list? Or maybe the order doesn't matter, as the test case uses set().
But the problem says "shared elements", which is an unordered collection. So the function can return the elements in any order. So the approach is to find the intersection of the two inputs.
But how to implement this in Python. Let's think: for each element in the first list, check if it's present in the second list. But that's O(n*m) time. Alternatively, convert both to sets and take the intersection. But then, the order is lost. However, the test case uses a tuple as input, but the output is a tuple. But when converting to a set, the order is not preserved. However, the test case uses set() to check the output, so the order doesn't matter.
So the function can return a list or a tuple of the elements in the intersection. But the example returns (4,5), which is a tuple. But the problem says the function is supposed to return the shared elements. So perhaps the function should return a list. However, the test case uses tuples. Wait, the user's test case is:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
So the function similar_elements is called with two tuples, and returns a tuple (4,5), which is then converted to a set. So the function is expected to return a tuple. But the problem says the function is supposed to take two lists. Maybe the function can accept any iterables, but the parameters are given as tuples in the test case.
But for the purpose of the problem, the function should take two lists. However, in the test case, the parameters are tuples. So maybe the function is supposed to handle any iterables, like lists or tuples.
So, the function can be written as follows:
def similar_elements(list1, list2):
# find the intersection of the two lists
# return as a tuple?
But how to get the elements in the intersection. Let's think: converting both to sets and taking the intersection.
But then, the order is not preserved. However, the test case uses a tuple, but when converted to a set, the order doesn't matter. So the function can return a list or a tuple of the elements in the intersection.
But the test case expects the output to be (4,5), which is a tuple. However, the problem says that the function should return the shared elements. So perhaps the function is supposed to return a list. However, in the test case, the user uses tuples. But the problem says that the function is supposed to take two lists. So maybe the function should return a list.
But the test case is using tuples, but the problem says that the function is supposed to take two lists. Maybe the test case is using tuples as an example, but the function should work with lists.
But regardless, the function needs to return the elements that are present in both. So, the code can be written as:
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
But this would return a list of the elements in the intersection, but the order is arbitrary. However, the test case uses a tuple (4,5), and the set conversion is done to check. So the actual order of the elements in the output doesn't matter, as the test uses set().
But the problem says that the test case is:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
So if the function returns [4,5], then converting to a set would match. But if the function returns a tuple (4,5), then the same. However, the function's return type is not specified. So the problem says that the function should return the shared elements. The problem says that the test case uses set() to check, so the function can return any iterable that contains the elements.
But the problem says that the user's code will be tested with that assertion. So the function similar_elements must return a list or tuple that, when converted to a set, matches the expected set.
So, for example, if the function returns a list [4,5], then set([4,5]) is {4,5}, which matches. Similarly, if it returns a tuple (4,5), same result.
But how to implement this in Python. The simplest way is to convert both lists to sets, take the intersection, and return the result as a list or tuple.
But the problem says that the function is supposed to return the shared elements. So perhaps the function is supposed to return a list. However, the test case uses tuples. But the problem's example uses tuples as input. However, the function's parameters are given as lists in the problem description. But the test case uses tuples. Maybe the function can accept any iterables.
But the problem says that the user's code will be tested with that test case. So the function must return a tuple? Or perhaps the function can return a list, and the test case uses set() to check.
In the test case, the user uses set(similar_elements(...)) == set(...). So the function's output can be any iterable that contains the elements. So, for example, if the function returns a list, that's okay.
But the test case uses tuples. However, the problem says that the function is supposed to take two lists. So maybe the function is supposed to return a list.
But in the test case, the user passes tuples, but the function is supposed to handle lists. However, in Python, tuples are iterable, so the code can handle any iterables.
So, the code can be written as:
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
But wait, what if the input lists have duplicate elements? For example, list1 is [4,4,5], list2 is [5,4]. The intersection would be {4,5}, and the function would return [4,5], which is correct. But the problem says that the test case uses (3,4,5,6) and (5,7,4,10), which have unique elements. So the function returns the elements in the intersection, regardless of duplicates.
But the problem says "shared elements" which usually refers to the elements that are present in both, not considering duplicates. So the function is correct.
But the problem says that the function is supposed to return the shared elements. So the code is correct.
But the test case uses tuples. However, the function returns a list. So when the test case does set(similar_elements(...)), it would convert the list to a set, which is correct.
So the code would pass the test case.
But wait, the test case uses (4,5) as the expected value. So if the function returns [4,5], then set([4,5]) is {4,5}, which matches set((4,5)). So the test case would pass.
So the code is correct.
But the problem says that the function is supposed to return the shared elements. However, the test case uses tuples, but the function returns a list. But the problem's test case uses set() to check, so the return type is not important as long as the elements are correct.
Therefore, the function can be written as:
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
But wait, the parameters are given as (3,4,5,6) and (5,7,4,10) in the test case. But in Python, tuples are passed as arguments. However, the function's parameters are named list1 and list2. But in Python, the function can accept any iterable, not just lists. So the code is correct.
But the problem says that the function is supposed to take two lists. However, in the test case, tuples are used. But the function can handle tuples as well. So the code is correct.
Another approach is to return a tuple. For example, return tuple(set(list1) & set(list2)). But the test case uses (4,5) as the expected value. However, when converting to a set, the order is not important. So whether the function returns a list or a tuple, the test case would pass.
But the problem's example uses tuples as input, but the function's return type is not specified. However, the user's test case uses set(similar_elements(...)), so the return type can be either list or tuple.
But the problem says that the answer should be a self-contained Python script. So the function is supposed to be written as per the problem's instructions.
But the problem's test case is:
assert set(similar_elements((3, 4, 5, 6),(5, 7, 4, 10))) == set((4, 5))
So the function similar_elements is called with two tuples. But the function's parameters are named list1 and list2. However, in Python, the function can accept any iterables, so that's okay.
So the code is correct.
But wait, the problem says that the function is supposed to take two lists. But the test case passes tuples. However, in Python, tuples are also iterables. So the code is correct.
Therefore, the function can be written as:
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
But let me test this with the sample input. The sample input is (3,4,5,6) and (5,7,4,10). The set conversion would be {3,4,5,6} and {5,7,4,10}. The intersection is {4,5}, which is converted to a list [4,5]. The test case uses set((4,5)) which is {4,5}. So the assertion would be True.
Yes, this works.
Another test case: if list1 is [1,2,2,3], list2 is [2,3,3,4], then the intersection is {2,3}, and the function returns [2,3], which is correct.
But what if the input is not a list? Like a tuple. But the function can handle that, as set() can take any iterable.
So the code is correct.
But the problem says that the function should be written as a Python function. So the code is correct.
Thus, the final code is:
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
But wait, the problem says that the function is supposed to return the shared elements. However, this code returns a list of the elements in the intersection, which is correct.
But the test case uses tuples. However, the function returns a list. But the test case uses set() to compare, so it's okay.
Yes, this code should work.
```python
def similar_elements(list1, list2):
return list(set(list1) & set(list2))
```
----------------------------------------------
Result: Pred=def similar_elements(list1, list2):
return list(set(list1) & set(list2)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
out = set(out)
exp = set(exp)
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[(3, 4, 5, 6), (5, 7, 4, 10)], [(1, 2, 3, 4), (5, 4, 3, 7)], [(11, 12, 14, 13), (17, 15, 14, 13)], [(), ()], [(1, 2, 3), ()], [(), (4, 5, 6)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (11, 12, 13, 14, 15, 16, 17, 18, 19, 20)], [(1, 2, 2, 3, 3, 4, 4, 5, 5), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(100, 200, 300, 400, 500), (100, 200, 400, 500)], [(10, 20, 30, 40, 50), (50, 60, 70, 80)], [(1, 2, 3, 4, 4, 5, 5), (4, 5, 6)], [(), (True, False, False, False, False, True)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 15)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15)], [(1, 2, 3, 1), ()], [('kx', 'DHBNiditD'), (4, 5, 6)], [(1, 2, 2, 70, 3, 4, 4, 5, 5, 4, 3), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(False, False, False, False, True), (False, False, False, False, False)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10)], [(8.514020219858878, -25.802494572247724, 5.873698915603498, 38.044354120134614, 11.222647627029431, 26.914534243589074, 78.41454157921689, -80.88414039955265), ('ceRuVEV', 'aAXslGdbD', 'DHBNiditD', 'fHRtFowQVh', 'ITntCqEvPi', 'SmJpP', 'DHBNiditD', 'kx', 'x')], [(False, False, False, False, False), (False, False, False, False, False)], [(), (5, 6)], [(1, 2, 2, 70, 3, 4, 4, 5, 5, 4, 3, 2), (1, 2, 2, 70, 3, 4, 4, 5, 5, 4, 3, 2)], [(1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10), (1, 3, 4, 5, 6, 7, 8, 9, 0, 10)], [(1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10, 10), (1, 3, 4, 5, 6, 7, 8, 9, 0, 10)], [(), (True, False, False, False)], [(4, 5, 16, 5), (1, 6, 3, 4, 4, 5, 5)], [('DRwvS', 'FdzAtAvnsS', 'ITntCqEvPi', 'nlUsIhET', 'ITntCqEvPi', 'x'), (True, False, True, False, True, False, True)], [(1, 2, 20), ()], [(11, 12, 13, 14, 15, 16, 17, 19, 20, 15), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15)], [(1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10, 10), (300, 1, 3, 4, 5, 6, 7, 8, 9, 0, 9)], [(False, False, False, False, False), (False, False, False, False)], [(1, 400, 3, 4, 4, 5, 5), (1, 400, 3, 4, 4, 5, 5, 5)], [(), (6,)], [(1, 2, 2, 3, 3, 4, 4, 5, 5), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 7)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 2, 10), (1, 2, 3, 4, 5, 6, 7, 8, 60, 10, 1)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (1, 2, 3, 4, 4, 6, 7, 8, 9, 10)], [(1, 2, 2, 3, 3, 4, 4, 5, 5, 3), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(100, 200, 300, 400, 500, 400, 300), (100, 200, 400, 500)], [('DRwvS', 'ITntCqEvPi', 'tUqF', 'ITntCqEvPi'), (4, 6, 6)], [(5, 2, 3), (1, 2, 3)], [(), (500, -45, 96, 22)], [(1, 2, 2, 70, 3, 4, 4, 5, 69, 5, 4, 3, 2), (1, 2, 2, 70, 3, 4, 4, 5, 69, 5, 4, 3, 2)], [(5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 7), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(1, 2, 2, 2, 70, 3, 4, 4, 5, 5, 4, 3), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(1, 2, 2, 3, 3, 4, 4, 5, 5, 3), (1, 2, 2, 3, 3, 4, 4, 5, 5, 3)], [('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'ITntCqEvPi'), (4, 6, 6)], [(5, 5, 6, 6, 7, 8, 9, 9), (5, 5, 6, 6, 7, 7, 8, 9, 9)], [(1, 2, 20), (1, 2, 20)], [(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 10), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15)], [(12, 2, 20), (1, 2, 19)], [(11, 12, 13, 14, 15, 16, 17, 19, 20, 15), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15, 20)], [(12, 2, 21), (12, 2, 20)], [(1, 2, 3, 5, 6, 12, 7, 8, 9, 10, 10), (1, 2, 3, 4, 5, 6, 12, 7, 8, 12, 0, 10, 10)], [(12, 2, 20, 20), (12, 2, 20)], [(6,), (6,)], [('LsgdJOGUO', 'nsDO', 'ceRuVEV', 'BohovaWqz', 'vovSNBB', 'BohovaWqz'), (True, False, False)], [('DRwvS', 'ITntCqEvPi', 'SmJpP', 'DRwvS'), ('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'ITntCqEvPi')], [(300, 1, 3, 4, 5, 6, 8, 9, 0, 9), (300, 1, 3, 4, 5, 6, 7, 8, 9, 0, 9)], [(False, True, False, True, False, False, True, False, True), (False, True, False, True, False, False, True, False, True)], [(1, 2, 3, 4, 5, 6, 7, 8, 9), (11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 15)], [(1, 3, 2, 3), (1, 3, 2, 3)], [(False, False, False, False, False), (False, False, False, False, True, False)], [('kx', 'DHBNiditD', 'DHBNiditD'), (4, 5, 6)], [(1, 1, 2, 3, 1), ()], [(1, 2, 3, 5, 6, 6, 7, 8, 9, 10), (1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10)], [(1, 2, 3, 4, 5, 6, 7, -45, 8, 9, 2, 10), (1, 2, 3, 4, 5, 6, 7, 8, 9, 2, 10)], [(26, True, 26.914534243589074, -44), ()], [(11, 12, 13, 14, 15, 70, 17, 18, 19, 20, 15), (11, 12, 13, 14, 15, 70, 17, 18, 19, 20, 15)], [(300, 1, 3, 2, 4, 5, 6, 8, 9, 0, 9), (300, 1, 3, 4, 5, 6, 7, 8, 9, 0, 9)], [(100, 201, 300, 400, 500), (100, 200, 300, 400, 500)], [(1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10, 10), (7, 1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10, 10)], [(False, True, False, False), (False, False, False, False)], [(7, 1, 2, 3, 4, 4, 6, 12, 7, 8, 9, 0, 10, 10), (7, 1, 2, 3, 4, 5, 6, 12, 7, 8, 9, 0, 10, 10)], [(4, 16, 5), (4, 5, 16, 5)], [(1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 9), (1, 2, 3, 5, 6, 6, 7, 8, 9, 10)], [(11, 12, 13, 14, 15, 16, 17, 19, 20, 15), (11, 12, 13, 4, 15, 16, 17, 19, 20, 15, 20)], [(7, 7), (6,)], [(1, 2, 2, 3, 3, 4, 4, 5, 5, 3, 4), (5, 5, 6, 6, 7, 7, 8, 8, 9, 9)], [(100, 200, 300, 400, 500, 400, 300), (499, 200, 400, 500)], [(False, False, False, False, False, False), (False, False, False, False, False, False)], [(), (4, 6, 6)], [(4, 5, 6), (4, 4, 5, 6)], [(12, 2, 20, 20, 2), (12, 2, 20, 20)], [(11, 12, 13, 14, 15, 16, 17, 19, 20, 15, 11), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15)], [(16, 1, 2, 3), (1, 2, 3)], [(1, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10), (1, 2, 3, 5, 6, 6, 7, 8, 9, 10)], [(30.445411706111912, 18.10848826924409, 24.97646124690165, -55.873347006206544), (500, -45, 96, 22)], [(12, 2, 20), (12, 2, 20, 20)], [(2, 3), (1, 2, 3)], [(1, 3, 2, 3), (1, 3, 3)], [(12, 20), (12, 18, 20)], [(False, False, False, False, False), (False, True, False, False, False, False)], [(4, 6, 6, 4), (4, 6, 6)], [(1, 1, 2, 3, 4, 5, 6, 7, 8, 9), (11, 15, 12, 13, 14, 15, 16, 17, 18, 19, 20, 16)], [(5, 5, 19, 6, 6, 7, 7, 8, 9, 9), (5, 5, 6, 6, 7, 7, 8, 9, 9)], [(5, 19, 5, 16, 5), (1, 6, 3, 4, 4, 5, 5)], [(-95.16136488545524, 8.514020219858878, -25.802494572247724, 5.873698915603498, 38.044354120134614, 11.222647627029431, 26.914534243589074, 78.41454157921689, -80.88414039955265), ('ceRuVEV', 'aAXslGdbD', 'DHBNiditD', 'fHRtFowQVh', 'ITntCqEvPi', 'SmJpP', 'DHBNiditD', 'kx', 'x')], [(100, 200, 300, 400), (100, 200, 300, 400)], [(1, 2, 20, 2), (1, 2, 20)], [(False, False, False, False), (False, True, False, False)], [(1, 2, 3, 4, 4, 6, 7, 8, 9, 10), (1, 2, 3, 4, 4, 6, 7, 8, 9, 10)], [(False, False, False, False), (False, True, False, False, True)], [(1, 400, 3, 4, 4, 5, 5, 5, 3), (1, 400, 3, 4, 12, 4, 5, 5, 5, 3)], [('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'kx', 'tUqF'), ('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'kx', 'tUqF')], [(1, 2, 3, 5, 6, 12, 7, 8, 9, 0, 10), (1, 3, 4, 5, 6, 7, 8, 9, 0, 10)], [('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'kx', 'SmITntCqEvPiJpP', 'tUqF'), ('DRwvS', 'ITntCqEvPi', 'SmJpP', 'tUqF', 'kx', 'tUqF')], [(1, 2, 3, 4, 5, 6, 7, 8, 9), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10)], [(11, 12, 13, 14, 15, 26, 16, 17, 19, 20, 15), (11, 12, 13, 14, 15, 16, 17, 19, 20, 15)], [(5, 19, 5, 16, 5, 5), (5, 19, 5, 6, 5)], [(1, 2, 3, 6, 12, 7, 8, 9, 10, 10), (1, 2, 3, 5, 6, 12, 7, 8, 9, 10, 10)]]
results = [(4, 5), (3, 4), (13, 14), (), (), (), (), (5,), (200, 100, 500, 400), (50,), (4, 5), (), (), (), (), (), (5,), (False,), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (), (False,), (), (1, 2, 3, 4, 5, 70), (0, 1, 3, 4, 5, 6, 7, 8, 9, 10), (0, 1, 3, 4, 5, 6, 7, 8, 9, 10), (), (4, 5), (), (), (11, 12, 13, 14, 15, 16, 17, 19, 20), (0, 1, 3, 4, 5, 6, 7, 8, 9), (False,), (1, 3, 4, 5, 400), (), (5,), (1, 2, 3, 4, 5, 6, 7, 8, 10), (1, 2, 3, 4, 6, 7, 8, 9, 10), (5,), (200, 100, 500, 400), (), (2, 3), (), (1, 2, 3, 4, 5, 70, 69), (5, 6, 7, 8, 9), (5,), (1, 2, 3, 4, 5), (), (5, 6, 7, 8, 9), (1, 2, 20), (), (2,), (11, 12, 13, 14, 15, 16, 17, 19, 20), (2, 12), (1, 2, 3, 5, 6, 7, 8, 10, 12), (2, 12, 20), (6,), (), ('SmJpP', 'ITntCqEvPi', 'DRwvS'), (0, 1, 3, 4, 5, 6, 8, 9, 300), (False, True), (), (1, 2, 3), (False,), (), (), (1, 2, 3, 5, 6, 7, 8, 9, 10), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10), (), (70, 11, 12, 13, 14, 15, 17, 18, 19, 20), (0, 1, 3, 4, 5, 6, 8, 9, 300), (400, 100, 500, 300), (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12), (False,), (0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12), (16, 4, 5), (1, 2, 3, 5, 6, 7, 8, 9), (11, 12, 13, 15, 16, 17, 19, 20), (), (5,), (200, 500, 400), (False,), (), (4, 5, 6), (2, 12, 20), (11, 12, 13, 14, 15, 16, 17, 19, 20), (1, 2, 3), (1, 2, 3, 5, 6, 7, 8, 9, 10), (), (2, 12, 20), (2, 3), (1, 3), (12, 20), (False,), (4, 6), (), (5, 6, 7, 8, 9), (5,), (), (200, 100, 400, 300), (1, 2, 20), (False,), (1, 2, 3, 4, 6, 7, 8, 9, 10), (False,), (1, 3, 4, 5, 400), ('SmJpP', 'DRwvS', 'tUqF', 'ITntCqEvPi', 'kx'), (0, 1, 3, 5, 6, 7, 8, 9, 10), ('SmJpP', 'DRwvS', 'tUqF', 'ITntCqEvPi', 'kx'), (1, 2, 3, 4, 5, 6, 7, 8, 9), (11, 12, 13, 14, 15, 16, 17, 19, 20), (19, 5), (1, 2, 3, 6, 7, 8, 9, 10, 12)]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(similar_elements(*inp), exp, 0)
| OK=True
==================== Problem #2 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to identify non-prime numbers.
Your answer will be tested on test cases like:
assert is_not_prime(2) == False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to identify non-prime numbers.
Your answer will be tested on test cases like:
assert is_not_prime(2) == False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to identify non-prime numbers.
Your answer will be tested on test cases like:
assert is_not_prime(2) == False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to identify non-prime numbers.
Your answer will be tested on test cases like:
assert is_not_prime(2) == False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to identify non-prime numbers.
Your answer will be tested on test cases like:
assert is_not_prime(2) == False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called is_not_prime that returns True if a number is not prime, and False otherwise. Let's think about how to determine if a number is non-prime.
First, what's a prime number? A prime is a number greater than 1 that has no divisors other than 1 and itself. So non-prime numbers are either 1, or any number that can be divided by something other than 1 and itself.
Wait, the function is called is_not_prime. So for example, if the input is 2, which is prime, the function should return False. For 4, which is not prime, return True.
So the steps for the function:
Check if the number is less than 2. If so, return True because 0 and 1 are not primes.
If the number is 2, return False because it's prime.
If the number is even and greater than 2, return True because it's divisible by 2.
For odd numbers greater than 2, check divisors from 3 up to the square root of the number. If any of them divide the number evenly, it's not prime. Otherwise, it is prime.
Wait, but how to implement this efficiently?
Let me outline the steps for the function:
Function is_not_prime(n):
- If n <= 1: return True (since they are not primes)
- If n == 2: return False (prime)
- If n is even (n % 2 == 0): return True (since even numbers >2 are not prime)
- Then, check for divisors from 3 to sqrt(n), stepping by 2 (since even divisors are already handled)
- If any divisor divides n, return True (not prime)
- If no divisors found, return False (it is prime)
So the code would look something like this:
def is_not_prime(n):
if n <= 1:
return True
if n == 2:
return False
if n % 2 == 0:
return True
max_divisor = int(n**0.5) + 1
for i in range(3, max_divisor, 2):
if n % i == 0:
return True
return False
Wait, but for numbers like 9, which is 3*3. The loop would check up to sqrt(9) which is 3. So when i is 3, 9%3 is 0, returns True. Correct.
What about n=3? The loop would have max_divisor as sqrt(3) ~1.732, so int(1.732) +1 is 1+1=2. So range(3, 2, 2) is empty. So returns False. Which is correct since 3 is prime.
Another test case: n=15. sqrt(15) is ~3.87. So max_divisor is 3+1=4. So range(3,4,2) is [3]. 15%3 is 0, returns True. Correct.
What about n=25? sqrt(25) is 5. So max_divisor is 5+1=6. The loop runs from 3 to 6, step 2. So i=3, 5. 25%3 is 1, then i=5, 25%5=0. Returns True. Correct.
Edge case: n=1, returns True. n=2 returns False. n=3 returns False. n=4 returns True (since 4%2==0).
So the code seems correct.
Now, the test case given is assert is_not_prime(2) == False. Which would pass.
Another test case: assert is_not_prime(4) == True. Also passes.
What about n=9? Returns True. Correct.
What about n=7? The function would check up to sqrt(7) ~2.64. So max_divisor is 2+1=3. The loop is range(3,3,2) which is empty. So returns False. Correct.
So the code should work.
```python
def is_not_prime(n):
if n <= 1:
return True
if n == 2:
return False
if n % 2 == 0:
return True
max_divisor = int(n**0.5) + 1
for i in range(3, max_divisor, 2):
if n % i == 0:
return True
return False
```
----------------------------------------------
Result: Pred=def is_not_prime(n):
if n <= 1:
return True
if n == 2:
return False
if n % 2 == 0:
return True
max_divisor = int(n**0.5) + 1
for i in range(3, max_divisor, 2):
if n % i == 0:
return True
return False | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[1], [2], [10], [35], [37], [7919], [10007], [524287], [7920], [True], [10006], [524288], [7921], [10008], [10005], [7918], [524289], [10004], [524286], [524290], [7922], [7923], [10009], [7917], [524285], [7916], [10003], [524284], [7924], [10010], [7915], [524283], [7925], [10011], [10002], [7914], [7926], [524291], [10012], [10001], [524292], [10000], [7927], [7928], [9999], [7929], [524293], [7913], [10013], [10014], [524282], [7912], [63], [9998], [62], [524281], [23], [64], [58], [60], [16], [59], [9997], [57], [10015], [61], [20], [56], [21], [7930], [55], [7911], [54], [19], [53], [9996], [524280], [22], [9995], [96], [9994], [7931], [10016], [524279], [97], [9993], [15], [94], [65], [93], [29], [66], [30], [92], [41], [95], [91], [14], [6], [524294], [4], [524278], [524277], [90], [524275], [5], [524295], [3]]
results = [True, False, True, True, False, False, False, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, False, True, True, True, False, True, True, True, True, True, True, True, False, False, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, False, True, True, True, False, True, True, True, True, True, True, True, True, True, True, False, True, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_not_prime(*inp), exp, 0)
| OK=True
==================== Problem #3 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the n largest integers from a given list of numbers, returned in descending order.
Your answer will be tested on test cases like:
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the n largest integers from a given list of numbers, returned in descending order.
Your answer will be tested on test cases like:
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the n largest integers from a given list of numbers, returned in descending order.
Your answer will be tested on test cases like:
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the n largest integers from a given list of numbers, returned in descending order.
Your answer will be tested on test cases like:
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the n largest integers from a given list of numbers, returned in descending order.
Your answer will be tested on test cases like:
assert heap_queue_largest( [25, 35, 22, 85, 14, 65, 75, 22, 58],3)==[85, 75, 65]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called heap_queue_largest that takes a list of numbers and an integer n, and returns the n largest integers in descending order. Let's think about how to approach this.
Hmm, the problem says to use a heap queue. Oh right, Python's heapq module has functions for working with heaps. But wait, heapq in Python provides a min-heap by default. So if I want the largest elements, maybe I need to use a max-heap. But since Python doesn't have a built-in max-heap, I remember that one common approach is to invert the numbers by multiplying by -1, then use a min-heap, and then invert them back when popping.
Alternatively, there's a function called nlargest in the heapq module. Oh right! The heapq.nlargest(n, iterable) function returns the n largest elements from the iterable, in descending order. So maybe the solution is to use that function directly.
Wait, the test case given is when the input list is [25, 35, 22, 85, 14, 65, 75, 22, 58], and n is 3, the output should be [85,75,65]. Let me check what heapq.nlargest(3, ...) would return. Yes, that should give exactly that. So then the function can be as simple as using heapq.nlargest.
But wait, the problem says to return them in descending order. The nlargest function returns them in descending order already, so that's exactly what's needed.
So the function can be written as:
import heapq
def heap_queue_largest(numbers, n):
return heapq.nlargest(n, numbers)
Wait, but the test case expects a list. The heapq.nlargest returns a list, so that's correct. Let me test with the sample input. The sample input list is [25, 35, 22, 85, 14, 65, 75, 22, 58]. The three largest are 85, 75, 65. So heapq.nlargest(3, ...) would return [85,75,65], which matches the sample. So that's correct.
But why is the function named heap_queue_largest? Because it's using the heap queue approach. The heapq module's nlargest is implemented using a heap, so this should be the correct approach.
So the code would be:
Import heapq, then define the function, and return the result of heapq.nlargest(n, numbers). That's straightforward.
Wait, but what if n is larger than the length of the list? Well, the problem probably expects that the function handles that, but the test case given has n=3 and the list has 9 elements, so it's okay. The heapq.nlargest function will return as many elements as possible if n is larger than the list length, but perhaps the problem expects that n is valid. However, the problem's test case doesn't cover that, so maybe we don't need to handle that here.
So the code is simple. The function uses heapq.nlargest. So the Python code would be:
import heapq
def heap_queue_largest(numbers, n):
return heapq.nlargest(n, numbers)
But wait, the problem says "returned in descending order". The nlargest function returns them in descending order, so that's correct. So this should work.
Let me check the sample input. For the given list, heapq.nlargest(3, [25, 35, 22, 85, 14, 65, 75, 22, 58]) would indeed return [85,75,65], which matches the expected output. So the code should be correct.
Therefore, the Python script is as simple as that.
```python
import heapq
def heap_queue_largest(numbers, n):
return heapq.nlargest(n, numbers)
```
----------------------------------------------
Result: Pred=import heapq
def heap_queue_largest(numbers, n):
return heapq.nlargest(n, numbers) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[25, 35, 22, 85, 14, 65, 75, 22, 58], 3], [[25, 35, 22, 85, 14, 65, 75, 22, 58], 2], [[25, 35, 22, 85, 14, 65, 75, 22, 58], 5], [[9, 8, 7, 6, 5, 4, 3, 2, 1], 3], [[100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 5], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25], 7], [[10, 20, 30, 40, 50, 60, 70, 80, 90, 100], 3], [[1000, 900, 800, 700, 600, 500, 400, 300, 200, 100], 4], [[-10, 50, 0, -20, 30, -40, 60, -70, 80, -90, 100], 6], [[-10, 50, 0, -20, 30, -40, 60, -70, 80, -90, 100, -70], 3], [[9, 8, 7, 6, 5, 4, 3, 2, 1], 2], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 25], 7], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 100], 4], [[1000, 900, 800, 700, 600, 500, 400, 300, 200, 100], 9], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 100], 5], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25], 7], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25], 7], [[10, 20, 30, 40, 50, 70, 80, 100], 3], [[9, 8, 7, 6, 5, 4, 3, 2, 1, 6], 9], [[100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 4], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11], 7], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11, 11], 7], [[9, 8, 7, 6, 5, 4, 3, 2, 1, 7], 4], [[1000, 900, 800, 700, 600, 500, 400, 300, 200, 100, 800], 9], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25], 8], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25], 6], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11, 11], 8], [[1000, 900, 700, 600, 500, 400, 300, 200, 100, 800], 9], [[1, 3, 5, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25], 8], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25], 8], [[1, 3, 5, 6, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25], 6], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11, 24, 11], 7], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 1, 23, 25, 25, 11, 11], 8], [[1, 3, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11, 24, 11], 7], [[1000, 900, 800, 700, 600, 500, 400, 300, 4, 100], 5], [[70, 900, 800, 700, 600, 500, 400, 300, 200, 100], 4], [[1000, 900, 800, 700, 600, 21, 500, 400, 300, 200, 100], 9], [[8, 7, 6, 5, 4, 2, 1], 2], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25, 40], 8], [[100, 200, 300, 400, 500, 600, 4, 700, 800, 900, 1000], 5], [[1, 3, 5, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25, 40], 8], [[100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 1], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 701, 100], 4], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25], 6], [[900, 700, 600, 500, 500, 400, 300, 200, 100, 800, 400], 9], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25], 2], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 701, 100], 5], [[10, 20, 40, 30, 40, 50, 60, 70, 80, 90, 100], 3], [[1000, 900, 800, 700, 600, 21, 500, 400, 300, 199, 100], 9], [[900, 700, 600, 500, 500, 400, 300, 200, 100, 800, 400], 10], [[8, 7, 6, 5, 5, 4, 2, 1], 2], [[1000, 800, 700, 600, 500, 400, 300, 4, 100], 5], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 24], 6], [[-10, 900, 800, 700, 600, 500, 400, 300, 200, 100, 800], 9], [[9, 8, 7, 6, 4, 3, 2, 1], 4], [[9, 8, 7, 6, 5, 4, 3, 2, 1, 7], 2], [[1, 3, 5, 7, 9, 11, 13, 14, 15, 17, 19, 21, 23, 25], 8], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 701, 100, 100], 5], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 24, 25], 7], [[1, 3, 5, 7, 9, 11, 13, 17, 19, 21, 23, 25, 25], 7], [[1000, 900, 800, 700, 600, 21, 500, 400, 300, 200, 100], 4], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 701], 4], [[-10, 900, 800, 700, 600, 500, 400, 300, 200, 100, 800], 10], [[10, 21, 30, 40, 50, 70, 80, 100], 3], [[1, 3, 5, 14, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25, 40], 8], [[1000, 900, 800, 700, 600, 500, 400, 300, 199, 701, 701], 4], [[1, 3, 5, 25, 7, 9, 11, 13, 15, 16, 19, 21, 23, 25], 7], [[1, 3, 5, 14, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25, 40], 2], [[1000, 900, 90, 800, 700, 600, 500, 400, 300, 199, 701, 99], 4], [[9, 8, 7, 6, 5, 4, 3, 2, 1, 6], 8], [[101, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000], 5], [[100, 200, 400, 500, 600, 800, 900, 1000], 5], [[1000, 900, 800, 700, 600, 21, 500, 400, 300, 200, 100], 5], [[1000, 900, 800, 700, 600, 21, 500, 400, 300, 199, 800, 100], 9], [[8, 7, 6, 5, 5, 4, 2, 0], 2], [[100, 200, 300, 400, 500, 599, 700, 800, 900, 1000], 1], [[1, 3, 5, 7, 21, 11, 13, 15, 17, 19, 21, 23, 25, 21], 7], [[1000, 8, 7, 6, 5, 4, 3, 2, 1, 6, 5], 9], [[101, 100, 200, 300, 3, 400, 500, 600, 700, 800, 900, 1000], 5], [[1, 3, 5, 7, 9, 11, 15, 17, 19, 21, 23, 40, 24, 25], 7], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 25, 7], 7], [[1000, 900, 800, 700, 900, 600, 500, 400, 300, 199, 100], 4], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 1, 23, 25, 25, 11, 11], 7], [[1000, 8, 7, 6, 5, 4, 3, 2, 1, 6], 9], [[101, 100, 200, 300, 3, 400, 500, 600, 700, 800, 40, 1000], 5], [[1, 23, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 1, 23, 25, 25, 11, 11], 8], [[1000, 900, 800, 700, 600, 15, 500, 400, 300, 4, 100, 400], 5], [[1, 3, 5, 7, 9, 11, 15, 17, 19, 21, 23, 40, 24, 25], 8], [[1, 3, 5, 7, 9, 11, 13, 17, 19, 21, 23, 25, 25], 8], [[1, 3, 5, 7, 9, 11, 13, 15, 18, 19, 21, 23, 25, 25, 11, 24, 11, 21], 7], [[8, 7, 6, 5, 4, 2, 1, 8], 2], [[1000, 900, 800, 400, 700, 600, 500, 400, 300, 199, 701, 100, 100], 5], [[1000, 900, 800, 700, 600, 500, 400, 1001, 300, 200, 100], 9], [[1000, 8, 7, 6, 5, 4, 3, 99, 2, 1, 6], 9], [[3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25], 9], [[-10, 900, 800, 700, 600, 500, 400, 300, 200, 100, 800], 3], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25], 5], [[1, 3, 5, 9, 11, 13, 15, 17, 21, 23, 40, 25, 25], 8], [[1, 3, 5, 9, 900, 13, 15, 17, 19, 21, 19, 25, 25, 7], 7], [[1, 3, 5, 6, 14, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25, 40], 2], [[9, 8, 7, 6, 5, 4, 3, 2, 1, 4, 7], 4], [[3, 5, 7, 9, 11, 15, 17, 19, 21, 23, 40, 24, 25], 8], [[1, 3, 5, 7, 9, 11, 13, 15, 13, 21, 1, 23, 25, 25, 11, 11], 8], [[100, 200, 400, 500, 800, 900, 1000], 5], [[1, 3, 5, 7, 9, 11, 22, 13, 15, 17, 19, 21, 23, 40, 25, 25], 8], [[3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 40, 25, 25], 8], [[3, 5, 8, 9, 11, 17, 19, 21, 23, 40, 24, 25], 7], [[100, 200, 300, 400, 30, 600, 700, 800, 900, 1000], 4], [[900, 700, 600, 500, 500, 400, 300, 200, 100, 800, 400, 900], 10]]
results = [[85, 75, 65], [85, 75], [85, 75, 65, 58, 35], [9, 8, 7], [1000, 900, 800, 700, 600], [25, 23, 21, 19, 17, 15, 13], [100, 90, 80], [1000, 900, 800, 700], [100, 80, 60, 50, 30, 0], [100, 80, 60], [9, 8], [25, 25, 23, 21, 19, 17, 15], [1000, 900, 800, 700], [1000, 900, 800, 700, 600, 500, 400, 300, 200], [1000, 900, 800, 700, 600], [40, 25, 25, 23, 21, 19, 17], [25, 25, 23, 21, 19, 18, 15], [100, 80, 70], [9, 8, 7, 6, 6, 5, 4, 3, 2], [1000, 900, 800, 700], [25, 25, 23, 21, 19, 18, 15], [25, 25, 23, 21, 19, 18, 15], [9, 8, 7, 7], [1000, 900, 800, 800, 700, 600, 500, 400, 300], [40, 25, 25, 23, 21, 19, 17, 15], [25, 25, 23, 21, 19, 18], [25, 25, 23, 21, 19, 18, 15, 13], [1000, 900, 800, 700, 600, 500, 400, 300, 200], [40, 25, 25, 23, 21, 19, 17, 15], [25, 23, 21, 19, 17, 15, 13, 11], [25, 25, 23, 21, 19, 18], [25, 25, 24, 23, 21, 19, 18], [25, 25, 23, 21, 19, 18, 15, 13], [25, 25, 24, 23, 21, 19, 18], [1000, 900, 800, 700, 600], [900, 800, 700, 600], [1000, 900, 800, 700, 600, 500, 400, 300, 200], [8, 7], [40, 40, 25, 25, 23, 21, 19, 17], [1000, 900, 800, 700, 600], [40, 40, 25, 25, 23, 21, 19, 17], [1000], [1000, 900, 800, 701], [25, 23, 21, 19, 17, 15], [900, 800, 700, 600, 500, 500, 400, 400, 300], [25, 25], [1000, 900, 800, 701, 700], [100, 90, 80], [1000, 900, 800, 700, 600, 500, 400, 300, 199], [900, 800, 700, 600, 500, 500, 400, 400, 300, 200], [8, 7], [1000, 800, 700, 600, 500], [25, 24, 23, 21, 19, 18], [900, 800, 800, 700, 600, 500, 400, 300, 200], [9, 8, 7, 6], [9, 8], [25, 23, 21, 19, 17, 15, 14, 13], [1000, 900, 800, 701, 700], [40, 25, 24, 23, 21, 19, 17], [25, 25, 23, 21, 19, 17, 13], [1000, 900, 800, 700], [1000, 900, 800, 701], [900, 800, 800, 700, 600, 500, 400, 300, 200, 100], [100, 80, 70], [40, 40, 25, 25, 23, 21, 19, 17], [1000, 900, 800, 701], [25, 25, 23, 21, 19, 16, 15], [40, 40], [1000, 900, 800, 701], [9, 8, 7, 6, 6, 5, 4, 3], [1000, 900, 800, 700, 600], [1000, 900, 800, 600, 500], [1000, 900, 800, 700, 600], [1000, 900, 800, 800, 700, 600, 500, 400, 300], [8, 7], [1000], [25, 23, 21, 21, 21, 19, 17], [1000, 8, 7, 6, 6, 5, 5, 4, 3], [1000, 900, 800, 700, 600], [40, 25, 24, 23, 21, 19, 17], [25, 25, 23, 21, 19, 17, 15], [1000, 900, 900, 800], [25, 25, 23, 21, 19, 18, 15], [1000, 8, 7, 6, 6, 5, 4, 3, 2], [1000, 800, 700, 600, 500], [25, 25, 23, 23, 21, 19, 18, 15], [1000, 900, 800, 700, 600], [40, 25, 24, 23, 21, 19, 17, 15], [25, 25, 23, 21, 19, 17, 13, 11], [25, 25, 24, 23, 21, 21, 19], [8, 8], [1000, 900, 800, 701, 700], [1001, 1000, 900, 800, 700, 600, 500, 400, 300], [1000, 99, 8, 7, 6, 6, 5, 4, 3], [40, 25, 25, 23, 21, 19, 17, 15, 13], [900, 800, 800], [25, 23, 21, 19, 17], [40, 25, 25, 23, 21, 17, 15, 13], [900, 25, 25, 21, 19, 19, 17], [40, 40], [9, 8, 7, 7], [40, 25, 24, 23, 21, 19, 17, 15], [25, 25, 23, 21, 15, 13, 13, 11], [1000, 900, 800, 500, 400], [40, 25, 25, 23, 22, 21, 19, 17], [40, 25, 25, 23, 21, 19, 17, 15], [40, 25, 24, 23, 21, 19, 17], [1000, 900, 800, 700], [900, 900, 800, 700, 600, 500, 500, 400, 400, 300]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(heap_queue_largest(*inp), exp, 0)
| OK=True
==================== Problem #4 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the two numbers differ at one bit position only or not.
Your answer will be tested on test cases like:
assert differ_At_One_Bit_Pos(13,9) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the two numbers differ at one bit position only or not.
Your answer will be tested on test cases like:
assert differ_At_One_Bit_Pos(13,9) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the two numbers differ at one bit position only or not.
Your answer will be tested on test cases like:
assert differ_At_One_Bit_Pos(13,9) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the two numbers differ at one bit position only or not.
Your answer will be tested on test cases like:
assert differ_At_One_Bit_Pos(13,9) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the two numbers differ at one bit position only or not.
Your answer will be tested on test cases like:
assert differ_At_One_Bit_Pos(13,9) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function that checks if two numbers differ at exactly one bit position. Let's think about how to approach this.
First, the problem says that the two numbers should differ by exactly one bit. So, for example, if the binary representations of the two numbers have exactly one bit that's different, then return True. Otherwise, False.
Hmm, how do I compare their bits? Well, maybe I can XOR the two numbers. Because XOR gives a 1 in every position where the bits are different. So if the XOR result has exactly one bit set to 1, then they differ by exactly one bit.
Right. So the steps would be:
1. Compute the XOR of the two numbers. Let's call it xor_result.
2. Check if xor_result is a power of two. Because a number that is a power of two has exactly one bit set to 1. For example, 2 (10), 4 (100), 8 (1000), etc.
Wait, but wait. If the XOR result is 0, that means the numbers are the same. So in that case, they differ by zero bits. So that should return False. But if the XOR is a power of two, then exactly one bit is different.
So the function can be structured as follows:
def differ_At_One_Bit_Pos(a, b):
xor_result = a ^ b
# Check if xor_result is a power of two and not zero
return xor_result != 0 and (xor_result & (xor_result - 1)) == 0
Wait, how does that work? Because for a number that's a power of two, subtracting 1 will flip all the lower bits. For example, 8 (1000) minus 1 is 7 (0111). And 8 & 7 is 0. So if xor_result is a power of two, then (xor_result & (xor_result -1)) will be zero. Also, we need to make sure that xor_result is not zero, because if it's zero, then the numbers are the same, which means zero bits differ.
So the condition is that xor_result is not zero and (xor_result & (xor_result -1)) == 0.
Let me test this with the example given: 13 and 9.
13 in binary is 1101, 9 is 1001. XOR would be 0100 (4). Which is 4, which is a power of two. So the function returns True. Which matches the sample test case.
Another test case: if the numbers differ by two bits. Let's say 3 (11) and 1 (01). XOR is 10 (2), which is a power of two. Wait, that's one bit difference. Wait, 3 is 11, 1 is 01. So they differ at the second bit. So that's one bit. So the function returns True. But if numbers are 3 (11) and 0 (00), XOR is 11 (3). Which is not a power of two. So the function returns False, which is correct because two bits differ.
Another example: 5 (101) and 7 (111). XOR is 010 (2), which is power of two. So returns True. Correct, since they differ at one bit.
So the logic seems correct.
So the code would be:
def differ_At_One_Bit_Pos(a, b):
xor = a ^ b
return xor != 0 and (xor & (xor - 1)) == 0
But wait, what about when xor is 1? Like a=0 and b=1. Then xor is 1. 1 & 0 is 0. So returns True. Which is correct.
Yes. So this should handle all cases.
So the Python function is as above. Now, I need to make sure that the code is self-contained. The test case given is assert differ_At_One_Bit_Pos(13,9) == True. Let's check:
13 ^ 9 is 1101 ^ 1001 = 0100 (4). So xor is 4. 4 is not zero. 4 & 3 is 0. So returns True. Correct.
Another test case: a=5 (101), b=7 (111). xor is 010 (2). 2 & 1 is 0. So returns True.
Another case: a=5 (101), b=4 (100). xor is 001 (1). So returns True.
If a=5 and b=6 (101 vs 110), xor is 011 (3). 3 & 2 is 2, not zero. So returns False. Which is correct since two bits differ.
So the code should work.
```python
def differ_At_One_Bit_Pos(a, b):
xor = a ^ b
return xor != 0 and (xor & (xor - 1)) == 0
```
----------------------------------------------
Result: Pred=def differ_At_One_Bit_Pos(a, b):
xor = a ^ b
return xor != 0 and (xor & (xor - 1)) == 0 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[13, 9], [15, 8], [2, 4], [2, 3], [5, 1], [1, 5], [0, 0], [-10, 10], [100, 100], [-50, -100], [123456789, -987654321], [-123456789, -987654321], [1000000000, 1000000001], [0, 1], [-100, -100], [-123456789, 0], [-10, -987654321], [1000000000, 100], [10, 0], [-101, -100], [1000000000, 1000000000], [10, 10], [-1, 0], [-101, 100], [-2, -2], [-123456789, -10], [-50, -50], [-50, -101], [-101, 1000000001], [1, -987654320], [-101, -101], [-11, -987654321], [-50, -102], [-3, 1], [-987654321, -987654320], [-987654321, -100], [0, 1000000001], [-50, -987654321], [-102, -987654321], [-102, 1], [1000000000, 10], [123456789, 1], [-10, -10], [10, -987654320], [-1, 1], [-101, -102], [-11, 0], [-1, -100], [-3, -987654320], [1, -50], [-123456789, -50], [-2, -1], [123456789, -2], [-2, -4], [-101, 10], [-2, 123456789], [-2, -987654321], [-1, -1], [1000000001, 1000000001], [-1, -2], [-50, 1000000000], [-3, -987654321], [-51, -50], [1, -1], [-100, -2], [1000000000, 101], [1000000000, -51], [-49, -102], [-102, -100], [-123456789, -123456789], [-51, -51], [-9, 10], [-4, -101], [-102, -101], [2, 2], [-50, -99], [-1, 101], [-2, -11], [-3, -2], [-987654321, -10], [-100, -49], [False, True], [True, True], [-987654321, -987654321], [123456789, -4], [123456789, 100], [9, 10], [-987654321, 1], [-3, -1], [-102, -102], [101, -101], [11, 10], [-50, -49], [False, False], [123456789, -50], [-10, 1], [-3, -51], [1, -10], [-10, 11], [-102, 2], [8, 8], [123456787, 1], [-987654321, 101], [9, -123456788], [8, -50], [-101, -3], [-123456788, 1000000000], [-12, 0], [-50, -1], [-987654320, 2], [-4, -123456789], [-2, -10], [-12, -101], [-9, -1]]
results = [True, False, False, True, True, True, False, False, False, False, False, False, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, True, False, True, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, True, False, False, False, False, False, False, True, False, False, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(differ_At_One_Bit_Pos(*inp), exp, 0)
| OK=True
==================== Problem #5 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find all words which are at least 4 characters long in a string.
Your answer will be tested on test cases like:
assert set(find_char_long('Please move back to stream')) == set(['Please', 'move', 'back', 'stream'])
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find all words which are at least 4 characters long in a string.
Your answer will be tested on test cases like:
assert set(find_char_long('Please move back to stream')) == set(['Please', 'move', 'back', 'stream'])
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find all words which are at least 4 characters long in a string.
Your answer will be tested on test cases like:
assert set(find_char_long('Please move back to stream')) == set(['Please', 'move', 'back', 'stream'])
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find all words which are at least 4 characters long in a string.
Your answer will be tested on test cases like:
assert set(find_char_long('Please move back to stream')) == set(['Please', 'move', 'back', 'stream'])
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find all words which are at least 4 characters long in a string.
Your answer will be tested on test cases like:
assert set(find_char_long('Please move back to stream')) == set(['Please', 'move', 'back', 'stream'])
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called find_char_long that takes a string and returns all the words which are at least 4 characters long. Let me think about how to approach this.
First, the input is a string. The output should be a list of words from that string where each word has 4 or more characters. Wait, the test case uses a set comparison, so maybe the order doesn't matter, but the function can return a list, and when they check with set, it's to ignore order.
So the steps I need to take are: split the input string into words, then filter those words based on their length.
Splitting the string can be done using the split() method, which by default splits on whitespace. But what if there are other cases, like punctuation? The problem statement's test case uses a string like 'Please move back to stream', which is straightforward. The example words are all separated by spaces. So maybe the function can split on whitespace and then check each word's length.
So, the plan is:
1. Split the input string into words.
2. Iterate over each word.
3. Check if the length of the word is >=4.
4. Collect those words into a list.
5. Return that list.
Wait, the test case uses set(['Please', 'move', 'back', 'stream']). Let me check the original example. The input string is 'Please move back to stream'. Splitting into words gives ['Please', 'move', 'back', 'to', 'stream']. The words with length >=4 are 'Please' (6), 'move' (4), 'back' (4), 'stream' (6). The word 'to' is 2, so excluded. So the expected output is those four words. The test uses set, so the function's output must be a list of those words, but in any order? Or perhaps the function returns a list, and the test converts it to a set for comparison.
So the function should return a list of the words in the original order, but the test uses a set to check because the order may not be important. But the function's output is a list, and the test uses set() to compare, so the function's output can be in any order? Or maybe the original order is preserved. However, the problem says to return all words, so the order should be as they appear in the input string.
But the test case uses set, so maybe the order isn't important. But the function should return the words in the order they appear. However, the test case's expected result is a set, which is unordered. So perhaps the function is supposed to return a list, but when testing, they convert both to sets to compare.
But regardless, the function needs to return the words in the original order, but the test case uses a set for comparison. So the function can return a list, and the test case uses set() to check for equality, regardless of order.
So the function can return a list of words that meet the condition.
Now, how to split the string into words. The split() method without arguments splits on any whitespace, which is correct.
So code steps:
def find_char_long(s):
words = s.split()
result = [word for word in words if len(word) >=4]
return result
Wait, but the test case's example: 'Please move back to stream' would split into the words as mentioned. The code would collect Please, move, back, stream. So the list would be ['Please', 'move', 'back', 'stream'], which when converted to a set matches the test case's expected set.
But the test case's expected set is written as set(['Please', 'move', 'back', 'stream']). However, in Python, the order in the list doesn't matter for the set. So the function's output list, when converted to a set, should match.
But the function is supposed to return a list. However, the problem's test case uses set() to compare. So the function's code is correct as written.
Wait, but the problem says that the function should return all words which are at least 4 characters long. So the code seems correct.
Testing with the sample input: 'Please move back to stream' → the code returns the list of words with len >=4. That's correct.
What about edge cases?
Case 1: Empty string. Then returns empty list.
Case 2: Words with exactly 4 letters. Like 'test' → included.
Case 3: Words with 3 letters. Excluded.
What about punctuation? For example, if a word is "hello!" — the problem's test case doesn't mention this, but the original question says "words". So perhaps the function is supposed to split on whitespace, and each word is considered as is. So the code would include "hello!" if it's 4 characters or more. But the problem's test case doesn't have such examples, so perhaps the code is correct as written.
So the code is as simple as that. The function splits the input string into words, filters those with len >=4, returns them as a list.
So the Python code would be:
def find_char_long(s):
return [word for word in s.split() if len(word) >=4]
Wait, but the problem says to write a function. So that's the code.
Testing the sample input:
find_char_long('Please move back to stream') → returns ['Please', 'move', 'back', 'stream'], which as a set matches the test case.
So the code should work.
But wait, the test case uses set(['Please', 'move', 'back', 'stream']). However, in Python 3, the syntax for set literals is { ... }, but the test case uses set([...]), which is correct. So the code's output is a list, and when converted to a set, matches the expected set.
Thus, the code should be correct.
```python
def find_char_long(s):
return [word for word in s.split() if len(word) >= 4]
```
----------------------------------------------
Result: Pred=def find_char_long(s):
return [word for word in s.split() if len(word) >= 4] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
out = set(out)
exp = set(exp)
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['Please move back to stream'], ['Jing Eco and Tech'], ['Jhingai wulu road Zone 3'], [''], ['This is a very long string with no words that are at least 4 characters long.'], ['words'], ['with'], ['4'], ['ve'], ['This is a very long string with no arewords that are along.t least 4 charatacters long.is'], ['arewords'], ['This is a very long string with no words that are at llongeast 4 characters long.'], ['arrewords'], ['This is a very long strigng with no words that are at least 4 characters long.'], ['least'], ['arerwordsThis'], ['stralong.t'], ['stralonwith.t'], ['vate'], ['Thicharatactercss'], ['wosrds'], ['vwosrds'], ['llongeast'], ['along.t'], ['vcharacterse'], ['This is a very long string with no arords that are along.t least 4 charatacters long.is'], ['Thicharatactercsvcharacterse'], ['ThicharatacterThis is a very long strigng with no words that are at least 4 characters long.csvcharacterse'], ['ThicharatacterT4his is a very long strigng with no words that are at least 4 characters long.csvcharacterse'], ['arords'], ['This is a very long string with no arewords that are along.t least 4 charatacters lonThis vwosrdsis a very long string with no words that are at least 4 characters long.g.is'], ['long.with'], ['Thicharattactercss'], ['This is a very long string with no alrords that are along.t least 4 charatacters long.is'], ['Thicharataercss'], ['arewds'], ['This is a very long string with no arords that are along.t least 4 charatacters long.isarords'], ['thatvcharacterse'], ['is'], ['tat'], ['stralong..t'], ['s'], ['string'], ['long.g.is'], ['This is a very long gstrigng with no words that are at least 4 characters long.'], ['This is a very long string with no words that are at llongeast 4 charactThis is a very long string with no arewords that are along.t least 4 charatacters lonThis vwosrdsis a very long string with no words that are at least 4 characters long.g.iss long.'], ['vwords'], ['that'], ['characters'], ['woords'], ['vworrds'], ['ThicharatacterThis is a very long strigng least 4 characters long.csvcharacterse'], ['srtring'], ['This is a very long sarrewordstring with no words that are at llongeast 4 characters long.'], ['long.alrordsg.is'], ['wossrds'], ['This is a very long strigng with no words that are at least 4 characters longcharactThis.'], ['arerwordsThis is a voery long gstrigng with no words that are at least 4 characters long.This'], ['vwdorrdwossrdss'], ['This is a very long string with no words that are at llongeast Thicharatactercssters long.'], ['longlong.This.gwith'], ['vworrrds'], ['charactThis'], ['Tchicharatactercsvcharacterse'], ['stralon'], ['alrords'], ['tast'], ['44'], ['avworrds'], ['srtring44'], ['leaet'], ['ThicharatacterThis'], ['ThicharacterscharattractercssarerwordsThis'], ['vcherse'], ['alrordlonThiss'], ['This is a very long string with no words that are at llongeast Thcharactersicharatactercssters long.'], ['ttat'], ['witth'], ['along.longcharactThis.t'], ['a'], ['at'], ['alrordlonThisllongeasts'], ['tlong.This'], ['ThicharatacterT4his is a very long strigng with no words that arevery at least 4 charactiers long.csvcharacterse'], ['srtrinrg'], ['tlong.TgstrignThcharactersicharatactercsstersghis'], ['wwith'], ['stringtast'], ['wilong.alrordsg.is'], ['long.This'], ['osrds'], ['stringtaststralong.t'], ['srtnoring'], ['vee'], ['ThicharatacterThis is a very long strigng with no words that are at least t4 characters long.csvcharacterse'], ['averyrewords'], ['thavworrdsat'], ['This is a very long string with no words that are at lllongeastcharacters long.'], ['stralong..ts'], ['thatvcharaccharactiersterthavworrdsatse'], ['loleaetg'], ['wwitThish'], ['aa'], ['atare'], ['avaeryrewords']]
results = [['Please', 'move', 'back', 'stream'], ['Jing', 'Tech'], ['Jhingai', 'wulu', 'road', 'Zone'], [], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'least', 'characters', 'long'], ['words'], ['with'], [], [], ['This', 'very', 'long', 'string', 'with', 'arewords', 'that', 'along', 'least', 'charatacters', 'long'], ['arewords'], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'llongeast', 'characters', 'long'], ['arrewords'], ['This', 'very', 'long', 'strigng', 'with', 'words', 'that', 'least', 'characters', 'long'], ['least'], ['arerwordsThis'], ['stralong'], ['stralonwith'], ['vate'], ['Thicharatactercss'], ['wosrds'], ['vwosrds'], ['llongeast'], ['along'], ['vcharacterse'], ['This', 'very', 'long', 'string', 'with', 'arords', 'that', 'along', 'least', 'charatacters', 'long'], ['Thicharatactercsvcharacterse'], ['ThicharatacterThis', 'very', 'long', 'strigng', 'with', 'words', 'that', 'least', 'characters', 'long', 'csvcharacterse'], ['ThicharatacterT4his', 'very', 'long', 'strigng', 'with', 'words', 'that', 'least', 'characters', 'long', 'csvcharacterse'], ['arords'], ['This', 'very', 'long', 'string', 'with', 'arewords', 'that', 'along', 'least', 'charatacters', 'lonThis', 'vwosrdsis', 'very', 'long', 'string', 'with', 'words', 'that', 'least', 'characters', 'long'], ['long', 'with'], ['Thicharattactercss'], ['This', 'very', 'long', 'string', 'with', 'alrords', 'that', 'along', 'least', 'charatacters', 'long'], ['Thicharataercss'], ['arewds'], ['This', 'very', 'long', 'string', 'with', 'arords', 'that', 'along', 'least', 'charatacters', 'long', 'isarords'], ['thatvcharacterse'], [], [], ['stralong'], [], ['string'], ['long'], ['This', 'very', 'long', 'gstrigng', 'with', 'words', 'that', 'least', 'characters', 'long'], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'llongeast', 'charactThis', 'very', 'long', 'string', 'with', 'arewords', 'that', 'along', 'least', 'charatacters', 'lonThis', 'vwosrdsis', 'very', 'long', 'string', 'with', 'words', 'that', 'least', 'characters', 'long', 'long'], ['vwords'], ['that'], ['characters'], ['woords'], ['vworrds'], ['ThicharatacterThis', 'very', 'long', 'strigng', 'least', 'characters', 'long', 'csvcharacterse'], ['srtring'], ['This', 'very', 'long', 'sarrewordstring', 'with', 'words', 'that', 'llongeast', 'characters', 'long'], ['long', 'alrordsg'], ['wossrds'], ['This', 'very', 'long', 'strigng', 'with', 'words', 'that', 'least', 'characters', 'longcharactThis'], ['arerwordsThis', 'voery', 'long', 'gstrigng', 'with', 'words', 'that', 'least', 'characters', 'long', 'This'], ['vwdorrdwossrdss'], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'llongeast', 'Thicharatactercssters', 'long'], ['longlong', 'This', 'gwith'], ['vworrrds'], ['charactThis'], ['Tchicharatactercsvcharacterse'], ['stralon'], ['alrords'], ['tast'], [], ['avworrds'], ['srtring44'], ['leaet'], ['ThicharatacterThis'], ['ThicharacterscharattractercssarerwordsThis'], ['vcherse'], ['alrordlonThiss'], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'llongeast', 'Thcharactersicharatactercssters', 'long'], ['ttat'], ['witth'], ['along', 'longcharactThis'], [], [], ['alrordlonThisllongeasts'], ['tlong', 'This'], ['ThicharatacterT4his', 'very', 'long', 'strigng', 'with', 'words', 'that', 'arevery', 'least', 'charactiers', 'long', 'csvcharacterse'], ['srtrinrg'], ['tlong', 'TgstrignThcharactersicharatactercsstersghis'], ['wwith'], ['stringtast'], ['wilong', 'alrordsg'], ['long', 'This'], ['osrds'], ['stringtaststralong'], ['srtnoring'], [], ['ThicharatacterThis', 'very', 'long', 'strigng', 'with', 'words', 'that', 'least', 'characters', 'long', 'csvcharacterse'], ['averyrewords'], ['thavworrdsat'], ['This', 'very', 'long', 'string', 'with', 'words', 'that', 'lllongeastcharacters', 'long'], ['stralong'], ['thatvcharaccharactiersterthavworrdsatse'], ['loleaetg'], ['wwitThish'], [], ['atare'], ['avaeryrewords']]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_char_long(*inp), exp, 0)
| OK=False
==================== Problem #6 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find squares of individual elements in a list.
Your answer will be tested on test cases like:
assert square_nums([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])==[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find squares of individual elements in a list.
Your answer will be tested on test cases like:
assert square_nums([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])==[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find squares of individual elements in a list.
Your answer will be tested on test cases like:
assert square_nums([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])==[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find squares of individual elements in a list.
Your answer will be tested on test cases like:
assert square_nums([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])==[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find squares of individual elements in a list.
Your answer will be tested on test cases like:
assert square_nums([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])==[1, 4, 9, 16, 25, 36, 49, 64, 81, 100]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called square_nums that takes a list of numbers and returns a new list where each element is the square of the original elements. Let me think about how to approach this.
First, the function should accept a list as input. Then, for each element in the list, I need to calculate its square. How do I do that? Well, squaring a number can be done by multiplying it by itself, like x*x. Alternatively, I could use the exponent operator **, like x**2. Both should work.
So, I can loop through each element in the input list. For each element, compute the square and add it to a new list. Then return that new list.
Wait, but maybe there's a more concise way using list comprehensions. Oh right! A list comprehension can iterate over each element, square it, and create the new list in one line. That would make the code shorter and more efficient.
So the function can be written as:
def square_nums(lst):
return [x**2 for x in lst]
Wait, but what about the test case provided? Let me check. The test case is assert square_nums([1,2,3,...10]) == [1,4,9,...100]. Using this function, each element is squared. Yes, that should work.
But wait, what if the input list is empty? Well, the function would return an empty list, which is correct. What if the list has negative numbers? Squaring them would make them positive, which is correct.
So the function seems straightforward. Let me make sure there are no edge cases I'm missing. The problem statement says "individual elements in a list", so I assume the input is a list of numbers. The function doesn't need to handle non-numeric elements since the problem doesn't mention that.
Therefore, the code should be as simple as that. Let me write the function using list comprehension.
```python
def square_nums(lst):
return [x**2 for x in lst]
```
----------------------------------------------
Result: Pred=def square_nums(lst):
return [x**2 for x in lst] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]], [[10, 20, 30]], [[12, 15]], [[]], [[-3, -2, -1, 0, 1, 2, 3]], [[9, 17, 5, 23, 10, 13, 19, 7, 2, 4]], [[-2, 17, 5, 23, 10, 13, 19, 7, 2, 4]], [[17, -3, -2, -1, 0, 1, 2, 3]], [[-2, 17, 5, 24, 10, 13, 19, 7, 2, 4]], [[-3, -2, -1, 0, 1, 2]], [[17, -3, -2, 1, 0, 1, 2, 3]], [[-3, -2, -1, 0, 1, 7, 2, 3]], [[-3, 1, -1, 0, 1, 2, 3]], [[17, -2, 1, -92, -36, 69, 18]], [[17, -2, 1, -92, -36, 69, 18, -36]], [[-3, 1, -1, 0, 1, 2, 3, 1]], [[False, True, False, True, False, True, True, True, False, False, False]], [[17, -3, -2, -1, 0, 1, 69, 3]], [[17, 4, -2, -1, 0, 1, 10, 3]], [[9, 17, 23, 10, 13, 19, 7, 7, 2, 4]], [[9, 17, 23, 10, 13, 19, 7, 7, 2, 9]], [[15, 17, -2, 1, -92, -36, 69, 18]], [[17, 1, 1, -92, -36, 69, 18, 17]], [[17, -3, -2, -1, 0, 1, 69, 17, 3]], [[-3, -2, -1, 0, 2, 1]], [[17, -2, 1, 1, -36, 69, 18]], [[-3, -2, -1, 0, 1, 69, 17, 3, -2]], [[-2, 17, 5, 24, 13, 19, 7, 2, 4]], [[False, True, False, True, False, True, True, True, False, False]], [[17, -2, 1, 1, -36, 18]], [[9, 17, 5, 12, 23, 10, 13, 19, 7, 2, 4]], [[17, -2, 1, -92, 18, -36, 17, -2]], [[17, -3, -2, -1, 0, 1, 2, 2, 3]], [[17, -2, 1, -92, -36, 69, 18, 17]], [[-2, 17, 24, 13, 19, 7, 2, 4]], [[24, 9, 17, 5, 12, 23, 10, 13, 19, 7, 2, 4]], [[17, -3, -2, 5, -1, 1, 2, 2, 3]], [[17, -2, 1, -92, -36, 69, 18, 17, 17]], [[17, -2, 1, -91, -92, -36, 69, 18]], [[17, -2, 1, -92, 18, -36, 17, 24, -2, -2]], [[17, -3, -2, 5, -1, 1, 2, 3, 3]], [[17, -3, -2, -1, 0, 1, 69, 3, -2]], [[-3, -2, -1, 2, 18, 1, 18, 7, 2, 3]], [[-3, -2, 15, 0, 2]], [[17, 4, -2, -1, 0, 3, 1, 3, 3]], [[17, 1, -1, 1, -92, -36, 69, 18, 1, 1]], [[-3, -2, -1, 0, 1, 69, 17, 3, -2, 17]], [[9, 17, 5, 12, 23, 10, 13, 19, 7, 4]], [[-3, -1, -2, -1, 0, 1, 2, 3, -1]], [[-3, -2, -1, 0, 1, 69, 3, -2, 17]], [[3, 17, 24, 13, 19, 7, 2, 4]], [[17, -2, 1, 18, -36, 17, -2]], [[4, -2, -1, 0, 3, 1, 3, 3]], [[-2, 17, 5, 23, 10, 13, 19, 7, 2, 4, 13]], [[17, -2, 1, -92, -36, 69, 18, 17, 18]], [[17, -1, -3, -2, -1, 0, 1, 2, 3, -1]], [[17, -3, -2, 4, 1, 0, 1, 2, 3]], [[17, -2, 1, 1, -35, 69, 18]], [[-2, 17, 5, 0, 23, 10, 13, 19, 7, 2, 4]], [[17, -3, -2, -1, 1, 69, 17, 3]], [[-2, 17, 5, 24, 13, 19, 7, 2, 3]], [[24, 9, 17, 6, 12, 23, 10, 13, 19, 7, 2, 4]], [[17, -2, 1, 18, -36, 17]], [[17, -2, -1, 0, 1, 7, 2, 3]], [[17, -2, 1, -36, 17, -2]], [[-2, 1, 18, -36, 16, -2]], [[24, 9, 17, 6, 12, 10, 13, 19, 7, 2, 4]], [[24, 10, 9, 17, 6, 12, 10, 13, 19, 7, 2, 4]], [[24, 9, 19, 6, 12, 10, 6, 13, 19, 7, 2, 4, 2, 6]], [[17, -3, 4, 1, 7, 1, 2, 3]], [[-3, 1, -1, 1, 2, 3, 1]], [[68, 17, -2, 1, -92, -36, 69, 1, 18]], [[6, 9, 17, 5, 12, 23, 10, 13, 19, 7, 4]], [[17, -3, -1, 0, 1, 69, 3, -2]], [[24, 9, -1, 19, 6, 12, 10, 6, 13, 19, 7, 2, 4, 2, 6, 2, -1]], [[24, 9, 17, 12, 10, 13, 19, 7, 2, 4, 68, 9]], [[17, -2, -91, -92, 18, -36, 17, 24, 7, -2, -2]], [[9, 17, 23, 10, 13, 19, 7, 7, 2, 9, 9]], [[17, -2, 4, 1, 0, 1, 2, 3]], [[17, -3, 4, 1, 7, 2, 3]], [[-2, 17, 5, 0, 10, 13, 19, 7, 2, 4]], [[-2, 10, -3, 18, -36, 16, -2]], [[17, -2, 4, 1, 18, -3, -36, 17, -2]], [[17, 17, 1, -92, -36, 69, 18, -36]], [[17, -2, -91, -92, 18, -36, 17, 24, 7, -2, -2, 24]], [[17, -3, -1, 0, 1, 69, 3, -2, 17]], [[-2, -91, 5, 0, 10, 14, 19, 7, 2, 4, -2]], [[17, -3, -2, -1, 0, 1, 69, -2]], [[17, 16, 6, 17, 1, -92, -36, 69, 18, -36]], [[24, 9, -2, 19, 6, 12, 10, 6, 13, 19, 7, 2, 4, 2, 6, 2, -1]], [[-3, -3, -2, -1, 0, 2, 3]], [[9, 17, 23, 10, 9, 13, 19, 7, 7, 2, 9]], [[17, -2, -91, -92, 18, -36, 17, -1, 24, 7, -2, -2, 24]], [[9, -3, -2, 5, -1, 1, 2, 2, 3]], [[-3, 1, -1, 0, 1, 2, 3, 1, 1]], [[24, 9, 17, 12, 23, 13, 19, 7, 2, 4]], [[16, 6, 17, 1, -92, -3, -36, 69, 18, -36]], [[-2, 1, 18, -36, 15, -2]], [[16, 17, 1, -92, -3, -36, 69, 18, -36, 1]], [[-2, 17, 3, 13, 23, 10, 13, 19, 7, 2, 4]], [[19, -3, -2, -1, 2, 1, 18, 7, 2, 3]], [[17, -2, 1, 68, 1, -35, 69, 18]], [[-2, 17, -2, 1, -92, -36, 69, 18, 17, 17]], [[-2, 1, 18, -3, -36, 15, -2, 18, -36]], [[-2, 17, 15, 5, 24, -2, 13, 7, 2, 3]], [[-3, -2, -1, 2, 18, -92, 18, 7, 2, 3]]]
results = [[1, 4, 9, 16, 25, 36, 49, 64, 81, 100], [100, 400, 900], [144, 225], [], [9, 4, 1, 0, 1, 4, 9], [81, 289, 25, 529, 100, 169, 361, 49, 4, 16], [4, 289, 25, 529, 100, 169, 361, 49, 4, 16], [289, 9, 4, 1, 0, 1, 4, 9], [4, 289, 25, 576, 100, 169, 361, 49, 4, 16], [9, 4, 1, 0, 1, 4], [289, 9, 4, 1, 0, 1, 4, 9], [9, 4, 1, 0, 1, 49, 4, 9], [9, 1, 1, 0, 1, 4, 9], [289, 4, 1, 8464, 1296, 4761, 324], [289, 4, 1, 8464, 1296, 4761, 324, 1296], [9, 1, 1, 0, 1, 4, 9, 1], [0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0], [289, 9, 4, 1, 0, 1, 4761, 9], [289, 16, 4, 1, 0, 1, 100, 9], [81, 289, 529, 100, 169, 361, 49, 49, 4, 16], [81, 289, 529, 100, 169, 361, 49, 49, 4, 81], [225, 289, 4, 1, 8464, 1296, 4761, 324], [289, 1, 1, 8464, 1296, 4761, 324, 289], [289, 9, 4, 1, 0, 1, 4761, 289, 9], [9, 4, 1, 0, 4, 1], [289, 4, 1, 1, 1296, 4761, 324], [9, 4, 1, 0, 1, 4761, 289, 9, 4], [4, 289, 25, 576, 169, 361, 49, 4, 16], [0, 1, 0, 1, 0, 1, 1, 1, 0, 0], [289, 4, 1, 1, 1296, 324], [81, 289, 25, 144, 529, 100, 169, 361, 49, 4, 16], [289, 4, 1, 8464, 324, 1296, 289, 4], [289, 9, 4, 1, 0, 1, 4, 4, 9], [289, 4, 1, 8464, 1296, 4761, 324, 289], [4, 289, 576, 169, 361, 49, 4, 16], [576, 81, 289, 25, 144, 529, 100, 169, 361, 49, 4, 16], [289, 9, 4, 25, 1, 1, 4, 4, 9], [289, 4, 1, 8464, 1296, 4761, 324, 289, 289], [289, 4, 1, 8281, 8464, 1296, 4761, 324], [289, 4, 1, 8464, 324, 1296, 289, 576, 4, 4], [289, 9, 4, 25, 1, 1, 4, 9, 9], [289, 9, 4, 1, 0, 1, 4761, 9, 4], [9, 4, 1, 4, 324, 1, 324, 49, 4, 9], [9, 4, 225, 0, 4], [289, 16, 4, 1, 0, 9, 1, 9, 9], [289, 1, 1, 1, 8464, 1296, 4761, 324, 1, 1], [9, 4, 1, 0, 1, 4761, 289, 9, 4, 289], [81, 289, 25, 144, 529, 100, 169, 361, 49, 16], [9, 1, 4, 1, 0, 1, 4, 9, 1], [9, 4, 1, 0, 1, 4761, 9, 4, 289], [9, 289, 576, 169, 361, 49, 4, 16], [289, 4, 1, 324, 1296, 289, 4], [16, 4, 1, 0, 9, 1, 9, 9], [4, 289, 25, 529, 100, 169, 361, 49, 4, 16, 169], [289, 4, 1, 8464, 1296, 4761, 324, 289, 324], [289, 1, 9, 4, 1, 0, 1, 4, 9, 1], [289, 9, 4, 16, 1, 0, 1, 4, 9], [289, 4, 1, 1, 1225, 4761, 324], [4, 289, 25, 0, 529, 100, 169, 361, 49, 4, 16], [289, 9, 4, 1, 1, 4761, 289, 9], [4, 289, 25, 576, 169, 361, 49, 4, 9], [576, 81, 289, 36, 144, 529, 100, 169, 361, 49, 4, 16], [289, 4, 1, 324, 1296, 289], [289, 4, 1, 0, 1, 49, 4, 9], [289, 4, 1, 1296, 289, 4], [4, 1, 324, 1296, 256, 4], [576, 81, 289, 36, 144, 100, 169, 361, 49, 4, 16], [576, 100, 81, 289, 36, 144, 100, 169, 361, 49, 4, 16], [576, 81, 361, 36, 144, 100, 36, 169, 361, 49, 4, 16, 4, 36], [289, 9, 16, 1, 49, 1, 4, 9], [9, 1, 1, 1, 4, 9, 1], [4624, 289, 4, 1, 8464, 1296, 4761, 1, 324], [36, 81, 289, 25, 144, 529, 100, 169, 361, 49, 16], [289, 9, 1, 0, 1, 4761, 9, 4], [576, 81, 1, 361, 36, 144, 100, 36, 169, 361, 49, 4, 16, 4, 36, 4, 1], [576, 81, 289, 144, 100, 169, 361, 49, 4, 16, 4624, 81], [289, 4, 8281, 8464, 324, 1296, 289, 576, 49, 4, 4], [81, 289, 529, 100, 169, 361, 49, 49, 4, 81, 81], [289, 4, 16, 1, 0, 1, 4, 9], [289, 9, 16, 1, 49, 4, 9], [4, 289, 25, 0, 100, 169, 361, 49, 4, 16], [4, 100, 9, 324, 1296, 256, 4], [289, 4, 16, 1, 324, 9, 1296, 289, 4], [289, 289, 1, 8464, 1296, 4761, 324, 1296], [289, 4, 8281, 8464, 324, 1296, 289, 576, 49, 4, 4, 576], [289, 9, 1, 0, 1, 4761, 9, 4, 289], [4, 8281, 25, 0, 100, 196, 361, 49, 4, 16, 4], [289, 9, 4, 1, 0, 1, 4761, 4], [289, 256, 36, 289, 1, 8464, 1296, 4761, 324, 1296], [576, 81, 4, 361, 36, 144, 100, 36, 169, 361, 49, 4, 16, 4, 36, 4, 1], [9, 9, 4, 1, 0, 4, 9], [81, 289, 529, 100, 81, 169, 361, 49, 49, 4, 81], [289, 4, 8281, 8464, 324, 1296, 289, 1, 576, 49, 4, 4, 576], [81, 9, 4, 25, 1, 1, 4, 4, 9], [9, 1, 1, 0, 1, 4, 9, 1, 1], [576, 81, 289, 144, 529, 169, 361, 49, 4, 16], [256, 36, 289, 1, 8464, 9, 1296, 4761, 324, 1296], [4, 1, 324, 1296, 225, 4], [256, 289, 1, 8464, 9, 1296, 4761, 324, 1296, 1], [4, 289, 9, 169, 529, 100, 169, 361, 49, 4, 16], [361, 9, 4, 1, 4, 1, 324, 49, 4, 9], [289, 4, 1, 4624, 1, 1225, 4761, 324], [4, 289, 4, 1, 8464, 1296, 4761, 324, 289, 289], [4, 1, 324, 9, 1296, 225, 4, 324, 1296], [4, 289, 225, 25, 576, 4, 169, 49, 4, 9], [9, 4, 1, 4, 324, 8464, 324, 49, 4, 9]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(square_nums(*inp), exp, 0)
| OK=True
==================== Problem #7 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the minimum number of rotations (greater than 0) required to get the same string.
Your answer will be tested on test cases like:
assert find_Rotations("aaaa") == 1
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the minimum number of rotations (greater than 0) required to get the same string.
Your answer will be tested on test cases like:
assert find_Rotations("aaaa") == 1
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the minimum number of rotations (greater than 0) required to get the same string.
Your answer will be tested on test cases like:
assert find_Rotations("aaaa") == 1
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the minimum number of rotations (greater than 0) required to get the same string.
Your answer will be tested on test cases like:
assert find_Rotations("aaaa") == 1
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the minimum number of rotations (greater than 0) required to get the same string.
Your answer will be tested on test cases like:
assert find_Rotations("aaaa") == 1
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
For the problem of finding the minimum number of rotations required to get the same string, I need to think about how string rotations work. A rotation means shifting the characters of the string. For example, for a string like "abc", one rotation would be "bca", and another would be "cab". If the string is made up of all the same characters like "aaaa", then any rotation would result in the same string, so the minimum number of rotations is 1.
So, the task is to find the smallest number of rotations (greater than 0) that results in the original string. How can I approach this?
First, I need to generate all possible rotations of the string and check which one matches the original. However, this might not be the most efficient way, but for the scope of this problem, it might be manageable.
Let's think about the possible rotations. For a string of length n, there are n possible rotations (including the original string). For example, "abc" has rotations "abc", "bca", "cab". So, the minimum number of rotations greater than 0 that gives the same string would be the smallest k (1 ≤ k < n) such that rotating the string k times gives the original string.
But how to compute this efficiently?
Another approach: for a string to be the same after k rotations, the string must be made up of a repeated pattern. For example, "abcabc" can be rotated 2 times to get the same string. The minimum rotation would be the length of the string divided by the length of the repeated pattern.
So, the problem reduces to finding the smallest k such that the string is made of a repeated pattern of length n/k. For example, if the string is "aaaa", the pattern is "a", and the minimum k is 1.
But how to find this in code?
An alternative approach is to check for all possible k from 1 to n-1, and for each k, check if rotating the string k times gives the original string. The first such k is the answer.
But how to rotate the string k times? For example, rotating once would be taking the first character and moving it to the end. Rotating k times would be taking the first k characters and moving them to the end. So, for a string s, rotating k times would result in s[k:] + s[:k].
Wait, but that's for a single rotation. For example, rotating once would be s[1:] + s[0], rotating twice would be s[2:] + s[:2], etc. So, for any k, the rotated string is s[k:] + s[:k].
So, the idea is to iterate k from 1 to len(s)-1, and check if s[k:] + s[:k] equals the original string. The first such k is the answer.
But for the case of "aaaa", the first k is 1, which would give "aaaa" again. So the code would return 1, which is correct.
But what about a string like "ababab"? The minimum rotation would be 2, because rotating twice would give "ababab" again. Let's see: the original string is "ababab", rotating once would be "bababa", rotating twice would be "ababab" again. So the answer would be 2.
So, the code would check for each k from 1 to len(s)-1, and return the first k where s[k:] + s[:k] == s.
But for longer strings, this approach could be O(n^2), which may not be efficient, but for the problem's purposes, perhaps it's acceptable.
So, the function can be written as follows:
def find_Rotations(s):
n = len(s)
for k in range(1, n):
if s[k:] + s[:k] == s:
return k
return n # if no rotation found, return n (but the problem says k must be >0, but for a string of length 1, it's not possible. However, the problem says to return the minimum number of rotations greater than 0. So, for a string that cannot be rotated to get the same string, like "abc", then the answer would be n (but in that case, the code would return n, which is not allowed. Wait, but the problem says the function should return the minimum number of rotations greater than 0 required to get the same string. So, if no such rotation exists, then the answer is not possible, but the problem says that the test case is like "aaaa" which returns 1. However, the problem might not have test cases where no rotation exists. But the code should return the correct value.
Wait, but for a string that cannot be rotated to get the same string, like "abc", the code would return n, which is 3. But rotating 3 times would bring the string back to the original. For example, rotating "abc" once: "bca", twice: "cab", thrice: "abc". So, the code would return 3 for "abc", which is correct. However, the problem says "greater than 0", so the answer is 3 for "abc".
But the problem's test case is "aaaa" which returns 1, which is correct.
So the code is correct.
Now, let's test with the given test case:
assert find_Rotations("aaaa") == 1
For "aaaa", the code checks k=1: s[1:] + s[:1] is "aaa" + "a" = "aaaa" which equals the original. So returns 1, which is correct.
Another test case: "ababab" would return 2.
Another test case: "abc" would return 3.
Another test case: "ab" would return 2.
But what about a string like "aabbaa"? Let's see. The length is 6. Let's check for k=2: s[2:] + s[:2] is "baa" + "aa" = "baaaaa"? No, original is "aabbaa". Wait, maybe not. Let's think.
Original string is "aabbaa".
k=2: s[2:] is "baa", s[:2] is "aa". So the rotated string is "baaaa"? No, that's 3+2=5 characters. Wait, the original length is 6. So s[2:] is "baa" (length 4?), no. Wait, original length is 6. s = "aabbaa"
s[2:] is "bbaa", and s[:2] is "aa". So rotated string is "bbaaaa"? No, that's 4 + 2 = 6 characters. Wait, "bbaa" + "aa" = "bbaaaa"? No, "bbaa" is 4 characters, "aa" is 2, total 6. So the rotated string would be "bbaaaa"? Let me check:
Original: a a b b a a
k=2: take s[2:] which is "bbaa" and s[:2] is "aa", so rotated string is "bbaa" + "aa" = "bbaaaa"? Which is not the same as original. So, perhaps the code would check for other k values.
But for the string "aabbaa", perhaps the minimal rotation is 2? Or not. Let me think. Let's try rotating once: "abbaaa"? No. Rotating twice: "bbaaaa"? Not same as original. Rotating 3 times: s[3:] is "baa", s[:3] is "aab", so rotated string is "baaaab"? Not same. Rotating 4 times: s[4:] is "aa", s[:4] is "aabb", rotated string is "aa" + "aabb" = "aaaa bb"? Which is "aaaabb"? Not same as original. Rotating 5 times: s[5:] is "a", s[:5] is "aabba", rotated string is "a" + "aabba" = "aaabba"? Not same as original. So the code would return 6, which is the length of the string. So for this string, the minimal rotation is 6, which would mean that no rotation less than 6 gives the original string.
But this is correct.
So, the code seems to handle all cases.
Now, the code can be written as:
def find_Rotations(s):
n = len(s)
for k in range(1, n):
if s[k:] + s[:k] == s:
return k
return n
But wait, for the case where the string is empty? But the problem probably assumes that the input string is non-empty. Also, for the case where the string is length 1, then the code returns 1, which is correct since rotating once would give the same string (but the code returns 1, which is correct).
But the problem says "greater than 0", so for the string of length 1, the answer is 1.
So, this code should handle all cases.
Now, let's write the Python function as required.
```python
def find_Rotations(s):
n = len(s)
for k in range(1, n):
if s[k:] + s[:k] == s:
return k
return n
```
----------------------------------------------
Result: Pred=def find_Rotations(s):
n = len(s)
for k in range(1, n):
if s[k:] + s[:k] == s:
return k
return n | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['aaaa'], ['ab'], ['abc'], ['aaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaab'], ['aaaaaaaaaaaaaaaaababab'], ['aaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaab'], ['aaaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaabaab'], ['aaaaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaabaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabb'], ['aaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaababab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaababab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaabaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaabaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaababab'], ['aaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaabaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaabaaababaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaabaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaabaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['pmUjgIomJ'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaabaaaaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaababaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabababaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaaaaaaaabaaaaaaaaaaaaaaaaaaabaabaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaaabaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabababaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaabaaaaaaabbaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaabaaaaabaaab'], ['aaaaaaaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabbabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaabaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaabaaaaaaaabaab'], ['pmUaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaabaaabjgmIomJ'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabababaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabababaaaaaaaaaaabaaaaaaababaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabaaaaaaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabababaaaaaaaaaaabaaaaaaababaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaababaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaabaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaabababaaaaaaaaaaaaabaab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaabaaaaaaabb'], ['aaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaabaaaaaaabaabaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaabab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabab'], ['aaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaabaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaabaaaaaaaabaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaababaaaaaaaaaaaaabababaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaabaabaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaabaababaaaabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbabb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaabaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaabaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaab'], ['pmaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaabaaaaaaaaaaaaaaaaabUjgIomJ'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabaaaaaaaaa'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaababaaabaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaababaaaabaabaaaaaaaaaaaaaaaaabUjgIomJb'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaaababaaaabaaabaaaaaaaaaaaaaaaaab'], ['aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaabaaaaaaabbaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaabaaaaaaaaaaaaaaaaaaaaaabaaaaaaaaaaaaaabaaaaabaaab']]
results = [1, 2, 3, 17, 18, 36, 22, 19, 56, 84, 103, 51, 142, 103, 16, 35, 89, 142, 37, 1, 90, 1, 109, 87, 20, 38, 82, 50, 21, 40, 100, 185, 160, 81, 57, 275, 181, 27, 182, 119, 153, 183, 17, 157, 146, 153, 57, 89, 175, 191, 28, 334, 116, 105, 159, 9, 88, 53, 43, 184, 231, 283, 246, 8, 327, 125, 233, 161, 70, 328, 106, 90, 18, 192, 120, 302, 126, 58, 214, 182, 99, 232, 385, 253, 386, 202, 135, 247, 40, 191, 9, 259, 41, 510, 28, 328, 49, 100, 353, 191, 51, 247, 126, 127]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_Rotations(*inp), exp, 0)
| OK=True
==================== Problem #8 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to remove first and last occurrence of a given character from the string.
Your answer will be tested on test cases like:
assert remove_Occ("hello","l") == "heo"
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to remove first and last occurrence of a given character from the string.
Your answer will be tested on test cases like:
assert remove_Occ("hello","l") == "heo"
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to remove first and last occurrence of a given character from the string.
Your answer will be tested on test cases like:
assert remove_Occ("hello","l") == "heo"
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to remove first and last occurrence of a given character from the string.
Your answer will be tested on test cases like:
assert remove_Occ("hello","l") == "heo"
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to remove first and last occurrence of a given character from the string.
Your answer will be tested on test cases like:
assert remove_Occ("hello","l") == "heo"
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called remove_Occ that takes a string and a character, and removes the first and last occurrence of that character from the string. Let's see. The example given is remove_Occ("hello","l") should return "heo". Let me think about how to approach this.
First, I need to find the first occurrence of the character. Then find the last occurrence. Then, create a new string that excludes those two positions. But wait, what if the character appears only once? Then removing first and last would be the same as removing that one occurrence. Or if the character isn't present at all, then return the original string.
So steps:
1. Check if the character exists in the string. If not, return the original string.
But even if it exists once, removing first and last would just remove that one occurrence.
So, how to find the first and last indices.
For the first occurrence, we can use the string's find() method. For example, s.find(c) gives the first index. For the last occurrence, maybe using rfind().
Once I have the first and last indices, I need to create a new string that skips those positions.
But wait, if the first and last are the same (like when there's only one occurrence), then I need to remove that once.
So, let's outline:
def remove_Occ(s, c):
first = s.find(c)
last = s.rfind(c)
if first == -1: # character not present
return s
# Now, create a new string that excludes the first and last occurrence.
# But how to handle when first and last are the same (only one occurrence)
# So, if first == last, then we need to remove that one occurrence once.
# Otherwise, remove both.
# So, the new string would be s[:first] + s[first+1 : last] + s[last+1 :]
# Wait, let's test with the example "hello" and 'l'.
# Original string: h e l l o
# indexes 0 1 2 3 4
# first is 2, last is 3.
# So, s[:2] is 'he', then s[3:3] is empty (since first+1 is 3, and last is 3, so from 3 to 3 is nothing), then s[4:] is 'o'. So combined 'he' + '' + 'o' = 'heo' which is correct.
# Another example: if the string is 'apple', c is 'p'. first is 1, last is 2. So s[:1] is 'a', then s[2:2] is empty, then s[3:] is 'le'. So 'a' + '' + 'le' = 'ale'? Wait, original string is 'apple' (a p p l e). Removing first and last p's. So the result should be a p l e? Wait, no. Wait, the first occurrence is index 1, the last is index 2. So removing those two, the remaining is a (from 0 to 1, not including 1?), then from 1+1=2 to last (2) is from 2 to 2, which is empty, then after last (2+1=3) is from 3 onwards. So the new string is s[:1] + s[2:2] + s[3:] → 'a' + '' + 'le' → 'ale'? But original is 'apple' → after removing first and last p, the string would be 'a' + 'p' (the middle one?) Wait, no. Wait, the original string is 'a p p l e'. The first occurrence is index 1, last is index 2. So removing those two, the remaining characters are a (index 0), then the characters between first+1 (2) and last (2) is nothing, then from last+1 (3) onwards. So the new string is 'a' + s[2:2] (nothing) + s[3:] → 'a' + '' + 'le' → 'ale'. But the original string after removing first and last p's would be a p l e? Wait, no. Because the first p is at index 1, the last is index 2. So the string after removing those two would be the original string without index 1 and 2. So the original is indexes 0,1,2,3,4. Removing 1 and 2, the remaining are 0, 3,4. So the string is s[0] + s[3:] → 'a' + 'le' → 'ale'. Which is correct. So the code seems to work.
Another example: if the string is 'banana', c is 'a'. The first occurrence is index 1, last is index 5. So the new string is s[:1] (b) + s[2:5] (n a n) + s[6:] (nothing). So 'b' + 'nan' → 'bnan'? Wait, original string is 'banana' → indexes 0: b, 1:a, 2:n, 3:a, 4:n, 5:a. So removing first (1) and last (5). The resulting string would be b + n a n → 'bnan'? But the original string is 'banana' → after removing first and last a's, it's 'b' + 'n' + 'a' + 'n' → 'bnan'? Or wait, the code would take s[:1] (b), then from first+1=2 to last (5) → s[2:5] is 'nan', then s[6:] is empty. So combined 'b' + 'nan' → 'bnan', which is correct.
Another case: when the character occurs once. For example, 'hello' and 'h'. first is 0, last is 0. So the code would take s[:0] (empty) + s[1:0] (empty) + s[1:] → 'ello'? Wait, no. Let me see:
s[:first] is s[:0] → empty. Then s[first+1 : last] → s[1:0], which is empty. Then s[last+1:] → s[1:] → 'ello'. So the result is empty + empty + 'ello' → 'ello', which is correct. Because the original string was 'hello', removing the first and last occurrence of 'h' (which is the same as the first occurrence, since it's only once). So the result is 'ello'.
Another case: if the string is 'a', and c is 'a'. Then first and last are 0. So the code would return s[:0] + s[1:0] + s[1:] → empty + empty + empty → empty string. Which is correct.
So the code logic seems to work.
So the steps are:
- Find first and last indices.
- If first is -1, return the original string.
- Else, create the new string by taking everything before first, then from first+1 to last (exclusive?), then everything after last.
Wait, the code is:
s[:first] + s[first+1 : last] + s[last+1 :]
Yes. Because between first+1 and last, which is from the index after first to the index before last. So for example, when first is 2 and last is 3 (as in the example), s[first+1 : last] is s[3:3], which is empty. So that part is correct.
So the code would be:
def remove_Occ(s, c):
first = s.find(c)
last = s.rfind(c)
if first == -1:
return s
# Now construct the new string
return s[:first] + s[first+1:last] + s[last+1:]
Wait, but what if the first and last are the same? Like when there is only one occurrence. For example, first = last = 0. Then s[:0] is empty, s[1:0] is empty, and s[1:] is the rest. So the code would return the string without the first occurrence. Which is correct.
So that's the code.
Now, let's test the sample input: remove_Occ("hello","l") → "heo".
Original string is 'hello' → indexes 0:h, 1:e, 2:l, 3:l, 4:o.
first is 2, last is 3.
s[:2] is 'he', s[3:3] is empty, s[4:] is 'o'. So combined 'he' + '' + 'o' → 'heo', which matches the sample.
Another test case: remove_Occ('apple', 'p') → 'ale'? Let's see. Original is 'apple' → indexes 0:a, 1:p, 2:p, 3:l, 4:e. first is 1, last is 2. So s[:1] is 'a', s[2:2] is empty, s[3:] is 'le'. So 'a' + '' + 'le' → 'ale', which is correct.
Another test case: remove_Occ('banana', 'a') → 'bnan'? Let's see. Original is 'banana' → indexes 0:b, 1:a, 2:n, 3:a, 4:n, 5:a. first is 1, last is 5. So s[:1] is 'b', s[2:5] is 'nan', s[6:] is empty. So 'b' + 'nan' → 'bnan'.
Another test case: remove_Occ('hello', 'h') → 'ello'. Which is correct.
Another case: remove_Occ('a', 'a') → ''. Correct.
What if the string is empty? Well, the function would return the original string (empty), which is correct.
What if the character is not present? For example, remove_Occ('hello', 'x') → 'hello'.
So the code seems to handle all these cases.
Now, implement this in Python.
But wait, in Python, the string's find method returns the first occurrence, and rfind returns the last occurrence. So the code is correct.
So the function is as written above.
Now, the user wants the code in a markdown code block. So the code would be:
def remove_Occ(s, c):
first = s.find(c)
last = s.rfind(c)
if first == -1:
return s
return s[:first] + s[first+1:last] + s[last+1:]
Wait, but in Python, when you slice a string, if the start index is greater than the end index, it returns an empty string. So for example, s[3:2] would be empty. So in the case where first+1 is greater than last (like when first and last are the same, like in the case of a single occurrence), then s[first+1:last] would be empty. Which is correct.
Yes. So that's the code.
Now, the user's test case is assert remove_Occ("hello","l") == "heo". Which would pass with this code.
Another test case: assert remove_Occ('apple', 'p') == 'ale'.
Another test case: assert remove_Occ('banana', 'a') == 'bnan'.
Another test case: assert remove_Occ('hello', 'h') == 'ello'.
So the code should work.
```python
def remove_Occ(s, c):
first = s.find(c)
last = s.rfind(c)
if first == -1:
return s
return s[:first] + s[first+1:last] + s[last+1:]
```
----------------------------------------------
Result: Pred=def remove_Occ(s, c):
first = s.find(c)
last = s.rfind(c)
if first == -1:
return s
return s[:first] + s[first+1:last] + s[last+1:] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['hello', 'l'], ['abcda', 'a'], ['PHP', 'P'], ['a', 'a'], ['aaa', 'a'], ['hello world', 'x'], ['worlda', 'a'], ['x', 'x'], ['hello world', 'a'], ['world', 'x'], ['xx', 'x'], ['xworlaaada', 'x'], ['axworlaaada', 'x'], ['waaaorlda', 'a'], ['xhello world', 'a'], ['xxx', 'x'], ['worlda', 'x'], ['world', 'a'], ['hwllo world', 'a'], ['axx', 'a'], ['hwllo world', 'x'], ['hwllo', 'a'], ['hwl', 'a'], ['ahwllo world', 'a'], ['xxx', 'a'], ['hwll', 'a'], ['hhwl', 'a'], ['ahwllo', 'x'], ['whwlloorld', 'a'], ['wda', 'x'], ['hwl', 'x'], ['xrworlaaada', 'x'], ['aahwllo', 'a'], ['a', 'x'], ['xxwaaaorlda', 'x'], ['wda', 'a'], ['hxworlaaadawllo', 'a'], ['aaaa', 'a'], ['xrworworldalaaadax', 'x'], ['aaawda', 'x'], ['hello worldx', 'x'], ['xrworworldalaaadax', 'a'], ['xrworlaaadaworldx', 'x'], ['aahwllo', 'x'], ['xworlaaadaaaaa', 'a'], ['xxxx', 'a'], ['xhello worlda', 'a'], ['xrworworaldalaaadax', 'a'], ['xaaaa', 'x'], ['xxwaahello worldxaorlda', 'x'], ['axworlaaada', 'a'], ['worldxaorlda', 'x'], ['hellloa', 'a'], ['xaaa', 'x'], ['aa', 'a'], ['xhello', 'a'], ['xrworlaaaada', 'x'], ['axxxaawda', 'x'], ['hello worldxxhello worlda', 'a'], ['xhello', 'x'], ['hxworlaaadawlolo', 'a'], ['aa', 'x'], ['lo', 'x'], ['xaaaa', 'a'], ['waaaorllda', 'a'], ['ahwllao', 'x'], ['aaa', 'x'], ['xxhello', 'x'], ['wdaa', 'a'], ['xrworworaldalaaadaxa', 'a'], ['waaaorlxxwaaaorlda', 'a'], ['aahwllao', 'x'], ['hello worldx', 'a'], ['lo', 'a'], ['hellloa', 'x'], ['helwdalloa', 'x'], ['worldxxhellox', 'x'], ['hello', 'x'], ['l', 'x'], ['waaaorlldalo', 'x'], ['xrwax', 'x'], ['waaaorllda', 'x'], ['whwlloorld', 'x'], ['aahhwla', 'x'], ['waaaorlda', 'x'], ['llo', 'l'], ['axaahwllaoworlaaada', 'a'], ['hwllor world', 'a'], ['xworlaaadaaaaa', 'x'], ['waaaorlldal', 'a'], ['aahawllao', 'x'], ['lllo', 'l'], ['worlaaaadxaorlda', 'x'], ['hello worldxxhhelloworlda', 'a'], ['hwlll', 'a'], ['xrworwoxxxraldalaaadaxa', 'a'], ['ll', 'x'], ['aaahwllaoo', 'a'], ['worldx', 'a'], ['xrworworaldalaaadaxa', 'x'], ['hxworlaaadawlolo', 'x'], ['whello world', 'x'], ['ahwllo', 'a'], ['ahxworlaaadawlolo', 'a'], ['whello', 'x'], ['ax', 'a']]
results = ['heo', 'bcd', 'H', '', 'a', 'hello world', 'world', '', 'hello world', 'world', '', 'worlaaada', 'aworlaaada', 'waaorld', 'xhello world', 'x', 'worlda', 'world', 'hwllo world', 'xx', 'hwllo world', 'hwllo', 'hwl', 'hwllo world', 'xxx', 'hwll', 'hhwl', 'ahwllo', 'whwlloorld', 'wda', 'hwl', 'rworlaaada', 'hwllo', 'a', 'waaaorlda', 'wd', 'hxworlaadwllo', 'aa', 'rworworldalaaada', 'aaawda', 'hello world', 'xrworworldlaaadx', 'rworlaaadaworld', 'aahwllo', 'xworlaadaaaa', 'xxxx', 'xhello world', 'xrworworldalaaadx', 'aaaa', 'xwaahello worldaorlda', 'xworlaaad', 'worldaorlda', 'helllo', 'aaa', '', 'xhello', 'rworlaaaada', 'axaawda', 'hello worldxxhello world', 'hello', 'hxworlaadwlolo', 'aa', 'lo', 'xaa', 'waaorlld', 'ahwllao', 'aaa', 'hello', 'wd', 'xrworworldalaaadax', 'waaorlxxwaaaorld', 'aahwllao', 'hello worldx', 'lo', 'hellloa', 'helwdalloa', 'worldxhello', 'hello', 'l', 'waaaorlldalo', 'rwa', 'waaaorllda', 'whwlloorld', 'aahhwla', 'waaaorlda', 'o', 'xaahwllaoworlaaad', 'hwllor world', 'worlaaadaaaaa', 'waaorlldl', 'aahawllao', 'lo', 'worlaaaadaorlda', 'hello worldxxhhelloworld', 'hwlll', 'xrworwoxxxrldalaaadax', 'll', 'aahwlloo', 'worldx', 'rworworaldalaaadaa', 'hworlaaadawlolo', 'whello world', 'hwllo', 'hxworlaaadwlolo', 'whello', 'x']
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(remove_Occ(*inp), exp, 0)
| OK=True
==================== Problem #9 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a given matrix in ascending order according to the sum of its rows.
Your answer will be tested on test cases like:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a given matrix in ascending order according to the sum of its rows.
Your answer will be tested on test cases like:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a given matrix in ascending order according to the sum of its rows.
Your answer will be tested on test cases like:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a given matrix in ascending order according to the sum of its rows.
Your answer will be tested on test cases like:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a given matrix in ascending order according to the sum of its rows.
Your answer will be tested on test cases like:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called sort_matrix that sorts a given matrix based on the sum of its rows in ascending order. Let me think about how to approach this.
First, the problem says that each row's sum determines its order. So for each row in the matrix, I need to calculate the sum of its elements. Then, sort the rows based on these sums from smallest to largest.
Let me think about the steps. The input is a list of lists, each sublist is a row. For example, [[1,2,3], [2,4,5], [1,1,1]]. The sums here are 6, 11, and 3. So the sorted order should be the row with sum 3 first, then 6, then 11. Which matches the test case given.
So how to do this in Python. The key is to sort the matrix, but the sort needs to be based on the sum of each row. In Python, the sort function can take a key. So for each row in the matrix, the key would be the sum of that row.
So the function would be something like: sorted_matrix = sorted(matrix, key=lambda row: sum(row)).
Wait, but the original matrix is a list of lists. So the sorted function will sort the rows based on their sum. That seems right.
So the function sort_matrix would take the matrix as input and return the sorted version using that key.
Wait, but what about the original order if sums are equal? Well, the problem says 'ascending order according to the sum of its rows'. If two rows have the same sum, their order might not matter, but the problem's test case doesn't cover that. The default sorted function in Python is stable, but when the keys are equal, their original order is preserved. However, the problem might not require handling that case, but the code should handle it correctly regardless.
So the code for the function would be:
def sort_matrix(matrix):
return sorted(matrix, key=lambda x: sum(x))
Wait, but the test case given is:
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
Let me check. The sums are 6, 11, 3. So sorted by sum, the order is 3, 6, 11. Which gives the rows [1,1,1], [1,2,3], [2,4,5]. Which matches the expected output. So the code should work.
But wait, the original matrix is [[1,2,3], [2,4,5], [1,1,1]]. When we sort, the key for each row is sum. So the sorted function will arrange them in order of their sums. So yes, the code should work.
But what about if the matrix is empty or has only one row? Well, the code should handle that as sorted returns the same list if it's empty or has one element.
So the function is straightforward. The code is simple. Let me write that as the Python function.
But the problem says to write a function. So the code would be:
def sort_matrix(matrix):
return sorted(matrix, key=lambda row: sum(row))
Wait, but the problem says that the answer will be tested on the given test case. Let me test that.
In the test case, the input is [[1,2,3], [2,4,5], [1,1,1]]. The sorted function will sort the rows based on their sum. The sum of [1,2,3] is 6, [2,4,5] is 11, [1,1,1] is 3. So sorted order is [1,1,1], [1,2,3], [2,4,5], which matches the expected output. So the code should work.
So the Python function is as simple as that. I think that's the correct approach.
```python
def sort_matrix(matrix):
return sorted(matrix, key=lambda row: sum(row))
```
----------------------------------------------
Result: Pred=def sort_matrix(matrix):
return sorted(matrix, key=lambda row: sum(row)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[[1, 2, 3], [2, 4, 5], [1, 1, 1]]], [[[1, 2, 3], [-2, 4, -5], [1, -1, 1]]], [[[5, 8, 9], [6, 4, 3], [2, 1, 4]]], [[[-5, -8, -9], [-6, -4, -3], [-2, -1, -4]]], [[[1000000, 999999, 999998], [999997, 999996, 999995], [999994, 999993, 999992]]], [[[999999999, 999999998, 999999997], [999999996, 999999995, 999999994], [999999993, 999999992, 999999991]]], [[[9, 8, 7], [6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5]]], [[[5, -2, 4], [1, -3, 7], [-6, 8, -1], [0, 9, -5]]], [[[11, -5, 23, 0], [6, 9, -8, 15], [-2, 10, 7, -4], [20, -3, 1, 18]]], [[[999999999, 999999998, 999999997], [999999996, 999999995, 999999994], [999999993, 999999992, 999999991], [999999999, 999999998, 999999997]]], [[[1000000, 999999, 999998], [999997, 999996, 999995], [999994, 999993, 999992], [999997, 999996, 999995]]], [[[-2, 10, 7, -4], [20, -3, 1, 18]]], [[[1, -3, 7], [-6, 8, -1]]], [[[6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5]]], [[[-5, -8, -9], [-6, -4, -3], [-5, -8, -9]]], [[[-5, -8, -9]]], [[[1000000, 999999, 999998], [999994, 999993, 999999998], [999997, 999996, 999995], [999994, 999993, 999999998], [999997, 999996, 999995]]], [[[999999999, 999999998, 999999997], [999999996, 999999995, 999999994], [999999993, 999999992, 999999991], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]]], [[[999999999, 999999998, 999999997], [999999996, 999999995, 999999994], [999999993, 999999992, 999999991], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]]], [[[-5, -8, -9, -9]]], [[[-6, -4, -3], [-2, -1, -4]]], [[[-5, -8, -9, -9, -5]]], [[[-5, -8, -9, -9], [-5, -8, -9, -9]]], [[[20, -3, 1, 18]]], [[[6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5], [0, -1, -2]]], [[[1000000, 999999, 999998], [999997, 999996, 999995], [999994, 999993, 999992], [1000000, 999999, 999998]]], [[[3, 2, 1], [0, -1, -2], [-3, -4, -5], [0, -1, -2]]], [[[-6, -4, -3], [-2, -1, -4], [-2, -1, -4]]], [[[-5, -8, -9], [-2, -1, -4]]], [[[999995, -1, -2], [6, 5, 4], [3, 2, 1], [999995, -1, -2], [-3, -4, -5], [999995, -1, -2]]], [[[-5, -8, -9], [999999999, -1, -4]]], [[[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]]], [[[1000000, 999999, 999998], [999997, 999996, 999995]]], [[[-5, -8, -9, -9, -5], [-5, -8, -9, -9, -5]]], [[[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]]], [[[-5, -8, -9], [-6, -4, -3], [-5, -8, -9], [-5, -8, -9]]], [[[999994, 999993, 1], [1000000, 999999, 999998], [999994, 999993, 1], [999997, 999996, 999995], [999994, 999993, 1], [999997, 999996, 999995]]], [[[5, -2, 4], [-6, 8, -1], [0, 9, -5]]], [[[1000000, 999999, 999998], [999997, 999996, 999995], [999994, 999993, 999992], [999997, 999996, 999995], [1000000, 999999, 999998]]], [[[-5, -8, 999999991], [-6, -4, -3], [-5, -8, 999999991], [-5, -8, 999999991]]], [[[999994, 999993, 1], [1000000, 999999, 999998], [999994, 999993, 1], [999997, 999996, 999995], [999997, 999996, 999995], [999997, 999996, 999995]]], [[[-9, 20, -3, 1, 18]]], [[[5, -2, 4], [-6, 8, -1]]], [[[999994, 999993, 1], [1000000, 999999, 999998], [999994, 999993, 1], [999995, 999996, 999995], [999995, 999996, 999995], [999995, 999996, 999995]]], [[[999999996, 999999995, 999999994], [999999993, 999999992, 999999991], [999999999, 999999998, 999999997]]], [[[9, 8, 7], [6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5], [3, 2, 1]]], [[[0, 0, -6, 8, -1], [0, 0, -6, 8, -1], [0, 0, -6, 8, -1]]], [[[-1, 999999999, -1, -4], [-1, 999999999, -1, -4]]], [[[6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5], [3, 2, 1]]], [[[-5, -8, 2, -9], [-5, -8, 2, -9], [-5, -8, 2, -9]]], [[[9, 8, 7], [6, 5, 4], [0, -1, -2], [-3, -4, -5], [3, 2, 1], [3, 2, 1]]], [[[-5, -8, -9, -9], [-5, -8, -9, -9], [-5, -8, -9, -9]]], [[[9, 8, 7], [6, 5, 4], [3, 2, 1], [0, -1, -2], [-3, -4, -5], [0, -1, -2]]], [[[-7, -4, -3], [-7, -4, -3]]], [[[999999996, 999999994, 999999994], [999999993, 999999992, 999999991]]], [[[-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991]]], [[[0, 6, 0, -6, 8, -1], [0, 6, 0, -6, 8, -1], [0, 6, 0, -6, 8, -1]]], [[[9, 8, 7], [6, 5, 4], [0, -1, -2], [-3, -4, -5], [5, 2, 1], [5, 2, 1], [0, -1, -2]]], [[[-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5]]], [[[0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1]]], [[[-5, -8, -9, -5]]], [[[-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6]]], [[[6, 5, 4], [0, -1, -2], [-3, -4, -5], [0, -1, -2]]], [[[10, -1, -2], [3, 2, 1], [10, -1, -2], [10, -1, -2], [-3, -4, -5], [10, -1, -2], [10, -1, -2]]], [[[1000000, 999999, 999998], [999994, 999993, 999999998], [999997, 999996, 999995], [999994, 999993, 999999998], [999997, 999996, 999995], [999994, 999993, 999999998]]], [[[9, 8, 7], [6, 5, 4], [0, -1, -2], [3, 2, 1], [3, 2, 1]]], [[[999997, 999996, 999995]]], [[[20, -3, 18]]], [[[999999996, 999999995, 999999994], [-1, 999999992, 999999991], [-1, 999999992, 999999991], [999999999, 999999998, 999999997]]], [[[-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8]]], [[[-5, -9, -8, -9, -9, -5], [-5, -9, -8, -9, -9, -5]]], [[[5, -2, 4], [-6, 8, -1], [5, -2, 4]]], [[[999994, 999993, 1], [999994, 999993, 1], [999995, 999996, 999995], [999995, 999996, 999995], [999995, 999996, 999995]]], [[[-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8]]], [[[-5, -9, 2, -9], [-5, -9, 2, -9], [-5, -9, 2, -9]]], [[[20, -3, 1, 18], [20, -3, 1, 18]]], [[[-3, 1, 18], [-3, 1, 18], [-3, 1, 18], [-3, 1, 18]]], [[[999997, 999996, 999995], [999994, 10, 999992], [999997, 999996, 999995]]], [[[9, 8, 7], [6, 5, 4], [0, -1, -2], [-3, -4, -5]]], [[[0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1]]], [[[-5, -8, -9], [-5, -8, -9]]], [[[-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2]]], [[[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]]], [[[-5, -8, -9], [-6, -4, -3], [-2, -1, -4], [-2, -1, -4]]], [[[1000000, 999999, 999998], [999997, 999996, 999995], [1000000, 999999, 999998]]], [[[-6, 8, -1, -1]]], [[[9, 8, 7], [0, -1, -2], [-3, -4, -5]]], [[[0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8]]], [[[-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9]]], [[[999999999, 999999998, 999999997], [999999996, 999999995, 999999994], [999999993, 999999992, 999999991], [999999999, 999999998, 999999997], [999999996, 999999995, 999999994]]], [[[-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8]]], [[[6, 5, 4], [0, 0, -2], [3, 2, 1], [0, 0, -2], [-3, -4, -5], [0, 0, -2]]], [[[-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18]]], [[[11, -5, 23, 0], [-2, 10, 7, -4]]], [[[-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10]]], [[[8, 1, 7], [8, 1, 7], [8, 1, 7], [-6, 8, -1]]], [[[-1, 999999999, -1, -4], [-1, 999999999, -1, -4], [-1, 999999999, -1, -4]]], [[[-5, -8, -9], [-6, -4, -3], [-2, -1, -4], [-5, -8, -9]]], [[[-4, -3], [-4, -3], [-4, -3]]], [[[0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1]]], [[[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]]], [[[999994, 999993, 1], [1000000, 999999, 999998], [999997, 999996, 999995], [999994, 999993, 1], [999997, 999996, 999995]]], [[[-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2]]], [[[999999998, -8, -8, -9, 18, -8, -6], [999999998, -8, -8, -9, 18, -8, -6]]], [[[-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9]]], [[[-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9]]], [[[-9, 20, -3, 1, 1000000, 18]]], [[[-5, -8, 2], [-5, -8, 2], [-5, -8, 2]]], [[[-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9]]]]
results = [[[1, 1, 1], [1, 2, 3], [2, 4, 5]], [[-2, 4, -5], [1, -1, 1], [1, 2, 3]], [[2, 1, 4], [6, 4, 3], [5, 8, 9]], [[-5, -8, -9], [-6, -4, -3], [-2, -1, -4]], [[999994, 999993, 999992], [999997, 999996, 999995], [1000000, 999999, 999998]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997]], [[-3, -4, -5], [0, -1, -2], [3, 2, 1], [6, 5, 4], [9, 8, 7]], [[-6, 8, -1], [0, 9, -5], [1, -3, 7], [5, -2, 4]], [[-2, 10, 7, -4], [6, 9, -8, 15], [11, -5, 23, 0], [20, -3, 1, 18]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]], [[999994, 999993, 999992], [999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998]], [[-2, 10, 7, -4], [20, -3, 1, 18]], [[-6, 8, -1], [1, -3, 7]], [[-3, -4, -5], [0, -1, -2], [3, 2, 1], [6, 5, 4]], [[-5, -8, -9], [-5, -8, -9], [-6, -4, -3]], [[-5, -8, -9]], [[999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998], [999994, 999993, 999999998], [999994, 999993, 999999998]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]], [[-5, -8, -9, -9]], [[-6, -4, -3], [-2, -1, -4]], [[-5, -8, -9, -9, -5]], [[-5, -8, -9, -9], [-5, -8, -9, -9]], [[20, -3, 1, 18]], [[-3, -4, -5], [0, -1, -2], [0, -1, -2], [3, 2, 1], [6, 5, 4]], [[999994, 999993, 999992], [999997, 999996, 999995], [1000000, 999999, 999998], [1000000, 999999, 999998]], [[-3, -4, -5], [0, -1, -2], [0, -1, -2], [3, 2, 1]], [[-6, -4, -3], [-2, -1, -4], [-2, -1, -4]], [[-5, -8, -9], [-2, -1, -4]], [[-3, -4, -5], [3, 2, 1], [6, 5, 4], [999995, -1, -2], [999995, -1, -2], [999995, -1, -2]], [[-5, -8, -9], [999999999, -1, -4]], [[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]], [[999997, 999996, 999995], [1000000, 999999, 999998]], [[-5, -8, -9, -9, -5], [-5, -8, -9, -9, -5]], [[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]], [[-5, -8, -9], [-5, -8, -9], [-5, -8, -9], [-6, -4, -3]], [[999994, 999993, 1], [999994, 999993, 1], [999994, 999993, 1], [999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998]], [[-6, 8, -1], [0, 9, -5], [5, -2, 4]], [[999994, 999993, 999992], [999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998], [1000000, 999999, 999998]], [[-6, -4, -3], [-5, -8, 999999991], [-5, -8, 999999991], [-5, -8, 999999991]], [[999994, 999993, 1], [999994, 999993, 1], [999997, 999996, 999995], [999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998]], [[-9, 20, -3, 1, 18]], [[-6, 8, -1], [5, -2, 4]], [[999994, 999993, 1], [999994, 999993, 1], [999995, 999996, 999995], [999995, 999996, 999995], [999995, 999996, 999995], [1000000, 999999, 999998]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997]], [[-3, -4, -5], [0, -1, -2], [3, 2, 1], [3, 2, 1], [6, 5, 4], [9, 8, 7]], [[0, 0, -6, 8, -1], [0, 0, -6, 8, -1], [0, 0, -6, 8, -1]], [[-1, 999999999, -1, -4], [-1, 999999999, -1, -4]], [[-3, -4, -5], [0, -1, -2], [3, 2, 1], [3, 2, 1], [6, 5, 4]], [[-5, -8, 2, -9], [-5, -8, 2, -9], [-5, -8, 2, -9]], [[-3, -4, -5], [0, -1, -2], [3, 2, 1], [3, 2, 1], [6, 5, 4], [9, 8, 7]], [[-5, -8, -9, -9], [-5, -8, -9, -9], [-5, -8, -9, -9]], [[-3, -4, -5], [0, -1, -2], [0, -1, -2], [3, 2, 1], [6, 5, 4], [9, 8, 7]], [[-7, -4, -3], [-7, -4, -3]], [[999999993, 999999992, 999999991], [999999996, 999999994, 999999994]], [[-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991], [-5, 999999995, 10, 999999991]], [[0, 6, 0, -6, 8, -1], [0, 6, 0, -6, 8, -1], [0, 6, 0, -6, 8, -1]], [[-3, -4, -5], [0, -1, -2], [0, -1, -2], [5, 2, 1], [5, 2, 1], [6, 5, 4], [9, 8, 7]], [[-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5], [-5, 999999995, 10, 999999991, -5]], [[0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1]], [[-5, -8, -9, -5]], [[-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6], [-9, -5, -8, -8, -9, 18, -8, -6]], [[-3, -4, -5], [0, -1, -2], [0, -1, -2], [6, 5, 4]], [[-3, -4, -5], [3, 2, 1], [10, -1, -2], [10, -1, -2], [10, -1, -2], [10, -1, -2], [10, -1, -2]], [[999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998], [999994, 999993, 999999998], [999994, 999993, 999999998], [999994, 999993, 999999998]], [[0, -1, -2], [3, 2, 1], [3, 2, 1], [6, 5, 4], [9, 8, 7]], [[999997, 999996, 999995]], [[20, -3, 18]], [[-1, 999999992, 999999991], [-1, 999999992, 999999991], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997]], [[-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8]], [[-5, -9, -8, -9, -9, -5], [-5, -9, -8, -9, -9, -5]], [[-6, 8, -1], [5, -2, 4], [5, -2, 4]], [[999994, 999993, 1], [999994, 999993, 1], [999995, 999996, 999995], [999995, 999996, 999995], [999995, 999996, 999995]], [[-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8], [-5, -8, -8, -9, 18, -8, -6, -8]], [[-5, -9, 2, -9], [-5, -9, 2, -9], [-5, -9, 2, -9]], [[20, -3, 1, 18], [20, -3, 1, 18]], [[-3, 1, 18], [-3, 1, 18], [-3, 1, 18], [-3, 1, 18]], [[999994, 10, 999992], [999997, 999996, 999995], [999997, 999996, 999995]], [[-3, -4, -5], [0, -1, -2], [6, 5, 4], [9, 8, 7]], [[0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1], [0, 3, 3, -6, 8, -1]], [[-5, -8, -9], [-5, -8, -9]], [[-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2]], [[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]], [[-5, -8, -9], [-6, -4, -3], [-2, -1, -4], [-2, -1, -4]], [[999997, 999996, 999995], [1000000, 999999, 999998], [1000000, 999999, 999998]], [[-6, 8, -1, -1]], [[-3, -4, -5], [0, -1, -2], [9, 8, 7]], [[0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8], [0, 999999992, 0, -6, 8, -1, 8]], [[-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9]], [[999999993, 999999992, 999999991], [999999996, 999999995, 999999994], [999999996, 999999995, 999999994], [999999999, 999999998, 999999997], [999999999, 999999998, 999999997]], [[-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8], [-8, -8, -9, 18, -8, -6, -8]], [[-3, -4, -5], [0, 0, -2], [0, 0, -2], [0, 0, -2], [3, 2, 1], [6, 5, 4]], [[-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18], [-2, 2, -3, 1, 18]], [[-2, 10, 7, -4], [11, -5, 23, 0]], [[-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10], [-5, 999999995, 10, 999999991, 999999995, 10]], [[-6, 8, -1], [8, 1, 7], [8, 1, 7], [8, 1, 7]], [[-1, 999999999, -1, -4], [-1, 999999999, -1, -4], [-1, 999999999, -1, -4]], [[-5, -8, -9], [-5, -8, -9], [-6, -4, -3], [-2, -1, -4]], [[-4, -3], [-4, -3], [-4, -3]], [[0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1], [0, 3, -6, 8, -1]], [[-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6], [-5, -8, -8, -9, 18, -8, -6]], [[999994, 999993, 1], [999994, 999993, 1], [999997, 999996, 999995], [999997, 999996, 999995], [1000000, 999999, 999998]], [[-1, 999999999, -1, 2, -4, 2], [-1, 999999999, -1, 2, -4, 2]], [[999999998, -8, -8, -9, 18, -8, -6], [999999998, -8, -8, -9, 18, -8, -6]], [[-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9], [-5, -8, -8, -9, 18, -8, 20, -8, 11, -9]], [[-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9], [-5, -8, -7, -9, 18, -8, -6, -8, -9]], [[-9, 20, -3, 1, 1000000, 18]], [[-5, -8, 2], [-5, -8, 2], [-5, -8, 2]], [[-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9], [-5, -8, -8, -9, 18, -8, -6, -8, -9]]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(sort_matrix(*inp), exp, 0)
| OK=True
==================== Problem #10 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the volume of a triangular prism.
Your answer will be tested on test cases like:
assert find_Volume(10,8,6) == 240
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the volume of a triangular prism.
Your answer will be tested on test cases like:
assert find_Volume(10,8,6) == 240
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the volume of a triangular prism.
Your answer will be tested on test cases like:
assert find_Volume(10,8,6) == 240
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the volume of a triangular prism.
Your answer will be tested on test cases like:
assert find_Volume(10,8,6) == 240
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the volume of a triangular prism.
Your answer will be tested on test cases like:
assert find_Volume(10,8,6) == 240
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to find the volume of a triangular prism. Let me think about the formula for that. Oh right, the volume of a triangular prism is (base area) multiplied by the height of the prism. Wait, the base here is a triangle, so the area of the triangle is (base * height)/2. Then multiply by the length of the prism.
Wait, the parameters given in the test case are 10, 8, 6. The expected output is 240. Let me check: if those parameters are base, height, and length. Let's see: (10 * 8)/2 = 40, then multiplied by 6 gives 240. Yes, that matches the test case. So the function should take three parameters: base, height, and length. Or maybe the parameters are in a different order? Wait, the test case uses find_Volume(10,8,6). Let me think: the first two parameters are the base and height of the triangle, and the third is the length of the prism. So the formula is (base * height / 2) * length.
So the function should be called find_Volume, and take three arguments. Then compute that formula. So the code would be:
def find_Volume(base, height, length):
return (base * height / 2) * length
Wait, but maybe the parameters are in a different order? Let me check the test case again. The input is 10,8,6. So base=10, height=8, length=6. Then (10*8/2)*6 = 40*6 = 240. Which matches the expected output. So the parameters are base, height, length. So the function is correct.
So the Python function is straightforward. Just multiply the three parameters, then divide by 2. Wait, no: base * height / 2 * length. Which is the same as (base * height * length) / 2. So the code can be written as (base * height * length) // 2? Wait, but in Python, using / gives a float. However, the test case expects an integer. For example, 10*8*6 is 480, divided by 2 is 240. So using integer division with // would be okay here. But maybe the function should return a float if the inputs are not integers. But the test case uses integers and expects an integer. However, the problem says that the answer will be tested with cases like that. So perhaps using integer division is okay. But in Python, if you use /, it returns a float. For example, 10*8*6 is 480, divided by 2 is 240.0. But the test case expects 240. So maybe the function should return an integer. However, in Python, if you use //, then 480//2 is 240 as an integer. But if the inputs are such that the division is not exact, then using // would truncate. However, the problem may assume that the inputs are such that the volume is an integer. But the problem says that the test case is assert find_Volume(10,8,6) == 240. So in that case, using either / or // would work. However, in Python, if you use /, the result is a float. So 240.0. But the test case expects 240. So perhaps the function should return an integer. But how?
Wait, the problem says that the answer will be tested on test cases like that. So perhaps the function should return an integer. But in Python, if you use integer division, then for example, (10 * 8 * 6) // 2 is 240. So maybe the code should be written as (base * height * length) // 2. But what if the parameters are not integers? For example, if the base is 3, height is 4, length is 5, then (3*4*5)/2 = 30. So using integer division would be okay. But if the parameters are such that the product is even, then it's okay. However, if the product is odd, then using integer division would give a different result. But perhaps the problem expects that the inputs are such that the volume is an integer. So maybe the function can be written as (base * height * length) // 2. But perhaps the problem expects to use floating point division. But the test case uses integers and expects an integer. However, in Python, if you use /, then 10*8*6 is 480, divided by 2 is 240.0, which would not equal 240 in an assert statement. So the test case would fail. So to make sure that the function returns an integer, perhaps the code should use integer division. But how?
Wait, the problem says that the test case is assert find_Volume(10,8,6) == 240. So the function must return 240 as an integer. Therefore, using integer division would be necessary. But in Python, if the inputs are integers, then (base * height * length) // 2 would return an integer. But if the inputs are floats, then it would return a float. However, the problem may not specify that. But given the test case, the function must return an integer. So perhaps the code should be written as (base * height * length) // 2. However, in Python, if the product is even, then it's okay. But if the product is odd, then it would truncate. But perhaps the problem assumes that the product is even. However, the problem may not require handling that. So the code can be written as (base * height * length) // 2. But maybe the correct formula is (base * height / 2) * length. Which would be the same as (base * height * length) / 2. So in Python, perhaps the code can be written as (base * height * length) / 2. But then, for the test case, it would return 240.0, which would not match the expected 240. So that would cause the assert to fail. Therefore, the function must return an integer. Therefore, perhaps the code should use integer division. But how to handle that?
Alternatively, maybe the problem expects that the parameters are such that the volume is an integer, and the function can return a float, but the test case is written with == 240. But in Python, 240.0 == 240 is True. Wait, no. Wait, in Python, 240.0 is equal to 240. So the assert would pass. Let me check. For example, in Python, 240.0 == 240 returns True. So if the function returns 240.0, the assert would pass. Therefore, perhaps the code can be written as (base * height * length) / 2. So the code would be:
def find_Volume(base, height, length):
return (base * height * length) / 2
But then, for the test case, it returns 240.0, which is equal to 240. So the assert would pass. Therefore, that's acceptable.
So the code is straightforward. The parameters are base, height, and length. Multiply them all, divide by 2. So the function is as above.
So the Python code would be:
def find_Volume(base, height, length):
return (base * height * length) / 2
But wait, the parameters are in the order base, height, length? Let me check again. The test case is find_Volume(10,8,6) which is base=10, height=8, length=6. The calculation is (10*8*6)/2 = 480/2=240. Which is correct. So yes, the parameters are in the order base, height, length.
So the code is correct. Therefore, the function is written as such.
```python
def find_Volume(base, height, length):
return (base * height * length) / 2
```
----------------------------------------------
Result: Pred=def find_Volume(base, height, length):
return (base * height * length) / 2 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10, 8, 6], [3, 2, 2], [1, 2, 1], [100, 50, 10], [0.5, 0.2, 0.1], [123456789, 987654321, 12345], [15, 12, 18], [7.5, 3.5, 5.2], [50, 25, 35.5], [6.7, 4.9, 3.2], [2.3, 5.6, 4.1], [987654320, 12, 18], [12, 987654320, 987654320], [0.5, 0.4312792507522603, 0.5], [987654321, 14, 51], [0.8922229171130629, 0.2, 0.1], [10, 12, 12345], [12345, 12, 12346], [15, 12, 987654321], [12, 50, 987654320], [0.5307408226774875, 0.4312792507522603, 0.5], [0.5307408226774875, 0.6321031729360945, 0.5], [6.7, 1.2712163559940908, 0.37719260113270303], [50, 13, 15], [11, 12, 18], [987654320, 15, 987654320], [12, 15, 987654320], [1.2712163559940908, 3.5, 0.37719260113270303], [2.3, 7.5, 4.1], [0.1, 0.2, 0.2], [50, 10, 50], [25, 35.5, 35.5], [10, 12, 13], [0.8922229171130629, 0.24784643921729696, 0.1], [6.7, 7.093315941766064, 0.37719260113270303], [11, 12, 987654321], [12, 987654322, 15], [0.8922229171130629, 0.2, 0.2], [11, 12, 987654320], [25, 12346, 35.53719707762832], [0.5307408226774875, 4.9, 3.2], [5.8654364659053835, 4.9, 3.2], [12, 12346, 987654320], [12345, 25, 35.5], [6.7, 0.1, 4.9], [6.7, 7.114857913414879, 0.33367901527186616], [0.8922229171130629, 0.24784643921729696, 0.8922229171130629], [12, 18, 987654320], [987654322, 10, 987654322], [12345, 25, 12346], [50, 25, 50], [0.5, 0.5, 0.5], [1.8063834584596086, 1.2712163559940908, 0.1], [6.7, 6.958640279396424, 0.30093484569499246], [1.8063834584596086, 0.6356356838493147, 0.1], [7.5, 4.737243560970565, 5.2], [11, 15, 987654321], [35.5, 6.958640279396424, 6.958640279396424], [987654321, 15, 51], [0.5307408226774875, 0.2246713952032357, 0.4312792507522603], [6.7, 7.114857913414879, 0.6721959532506382], [7.5, 1.2712163559940908, 5.2], [2.3, 7.0513497877662985, 4.1], [50, 987654322, 10], [0.1, 4.9, 4.9], [987654321, 12346, 14], [123456789, 12345, 12345], [12345, 11, 12345], [2.3, 0.4312792507522603, 2.3], [10, 12, 12], [50, 100, 50], [2.3, 0.24784643921729696, 0.8922229171130629], [51, 100, 50], [12345, 25, 18], [26, 25, 12346], [25, 10, 35.5], [100, 26, 50], [12345, 25, 11], [0.4267076249145146, 0.4312792507522603, 7.093315941766064], [0.6721959532506382, 6.958640279396424, 6.958640279396424], [0.8922229171130629, 0.6356356838493147, 0.1], [123456789, 12345, 123456789], [50, 10, 12346], [35.5, 35.5, 35.5], [0.2, 35.5, 0.2], [26, 25, 12345], [0.6721959532506382, 0.6356356838493147, 0.1], [2.3, 0.1, 5.6], [0.2, 4.1, 4.1], [12345, 12345, 12345], [12, 12, 987654320], [0.5, 0.2, 0.30093484569499246], [50, 12345, 12345], [0.4267076249145146, 0.2804796558775843, 7.093315941766064], [987654321, 14, 987654321], [2.3, 0.16891917418428634, 0.8922229171130629], [51, 12, 50], [10, 12345, 11], [0.5, 0.2, 0.41099804295162595], [987654320, 14, 51], [1.2712163559940908, 7.5, 0.1], [0.41099804295162595, 0.33505200659362044, 0.6356356838493147], [10, 11, 11], [12346, 15, 51], [987654319, 987654320, 987654320], [2.3, 5.6, 0.5050561846753878], [4.748972607227519, 0.2, 0.1], [0.2, 0.1, 0.2], [7.058489893691628, 7.0513497877662985, 7.058489893691628], [7.058489893691628, 7.058489893691628, 2.3], [25, 12347, 987654320]]
results = [240.0, 6.0, 1.0, 25000.0, 0.005000000000000001, 7.526291655427412e+20, 1620.0, 68.25, 22187.5, 52.52800000000001, 26.403999999999996, 106666666560.0, 5.852766334887975e+18, 0.05390990634403254, 352592592597.0, 0.00892222917113063, 740700.0, 914468220.0, 88888888890.0, 296296296000.0, 0.05722437608699626, 0.08387073950528823, 1.6063029031314886, 4875.0, 1188.0, 7.315957918609968e+18, 88888888800.0, 0.8391134568597328, 35.3625, 0.0020000000000000005, 12500.0, 15753.125, 780.0, 0.011056713649727108, 8.963080073948216, 65185185186.0, 88888888980.0, 0.01784445834226126, 65185185120.0, 5484277.93900499, 4.161008049791502, 45.985021892698214, 73161481408320.0, 5478093.75, 1.6415000000000002, 7.953163920864196, 0.09865053306243339, 106666666560.0, 4.877305298826399e+18, 1905142125.0, 31250.0, 0.0625, 0.11481520987955135, 7.0152260847358585, 0.057410089245603174, 92.37624943892602, 81481481482.5, 859.5024730501806, 377777777782.5, 0.025713360830200257, 16.02163863612505, 24.78871894188477, 33.247114249318095, 246913580500.0, 1.2005000000000001, 85355061729462.0, 9407347136615362.0, 838194637.5, 1.1407336182397283, 720.0, 125000.0, 0.25430441394372344, 127500.0, 2777625.0, 4012450.0, 4437.5, 65000.0, 1697437.5, 0.6526919798079005, 16.274762935021045, 0.028356436203259606, 9.407864483555099e+19, 3086500.0, 22369.4375, 0.7100000000000001, 4012125.0, 0.02136358672126057, 0.6439999999999999, 1.6809999999999998, 940682981812.5, 71111111040.0, 0.015046742284749623, 3809975625.0, 0.4244739842486375, 6.828227404529797e+18, 0.17332059209908857, 15300.0, 678975.0, 0.0205499021475813, 352592592240.0, 0.476706133497784, 0.04376533443230769, 605.0, 4722345.0, 4.817091623958257e+26, 3.252561829309497, 0.047489726072275196, 0.0020000000000000005, 175.6571602689303, 57.29562151624887, 152432098613000.0]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_Volume(*inp), exp, 0)
| OK=True
==================== Problem #11 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to that returns true if the input string contains sequences of lowercase letters joined with an underscore and false otherwise.
Your answer will be tested on test cases like:
assert text_lowercase_underscore("aab_cbbbc")==(True)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to that returns true if the input string contains sequences of lowercase letters joined with an underscore and false otherwise.
Your answer will be tested on test cases like:
assert text_lowercase_underscore("aab_cbbbc")==(True)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to that returns true if the input string contains sequences of lowercase letters joined with an underscore and false otherwise.
Your answer will be tested on test cases like:
assert text_lowercase_underscore("aab_cbbbc")==(True)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to that returns true if the input string contains sequences of lowercase letters joined with an underscore and false otherwise.
Your answer will be tested on test cases like:
assert text_lowercase_underscore("aab_cbbbc")==(True)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to that returns true if the input string contains sequences of lowercase letters joined with an underscore and false otherwise.
Your answer will be tested on test cases like:
assert text_lowercase_underscore("aab_cbbbc")==(True)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, let's see. I need to write a Python function that checks if a string contains sequences of lowercase letters joined with an underscore. And it should return True or False. Hmm. The example given is "aab_cbbbc" which returns True. So the string is split into parts by underscores, and each part should be lowercase letters only.
Wait, the problem says "contains sequences of lowercase letters joined with an underscore". So the entire string should be made up of one or more sequences of lowercase letters separated by underscores. But what about the underscores? Like, the string should be something like "abc_def", where each part is lowercase letters, and the underscores are between them.
So the function needs to check that the entire string matches this pattern. How to approach this?
Maybe using regular expressions. Because regular expressions can check if the entire string matches a certain pattern.
So the pattern should be: the string starts with one or more lowercase letters, followed by an underscore, then again one or more lowercase letters, and so on. But how to represent that in regex.
Wait, but the string can have multiple underscores. For example, "a_b_c" would be valid. But the entire string must be composed of lowercase letters and underscores, but the underscores can't be at the start or end. Also, each part between underscores must be non-empty.
So the regex pattern should be that the entire string matches ^[a-z]+(_[a-z]+)*$. Let me think. Let's break it down:
- ^ : start of string
- [a-z]+ : one or more lowercase letters
- (_[a-z]+)* : zero or more occurrences of an underscore followed by one or more lowercase letters
- $ : end of string
Wait, but that would allow for a string like "a_b_c", which is correct. But what about a string that's just a single sequence, like "abc"? Because the * makes the (_[a-z]+) part optional. So the regex would match "abc" as well, which is correct. Because the problem says "sequences" joined with underscores. So if there's only one sequence, then there are no underscores. But the problem says "joined with an underscore"—but maybe that's implying that there's at least one underscore? Or maybe the problem allows for a single sequence. Let me check the example given.
The example input is "aab_cbbbc", which has an underscore. But what about a string like "abc"? The problem says "contains sequences of lowercase letters joined with an underscore". If there's only one sequence, then there's no underscore. So maybe the function should return True if the string is composed of lowercase letters and underscores, but the underscores are between sequences. So the entire string can be a single sequence (no underscores) or multiple sequences separated by underscores.
Wait, but the problem says "joined with an underscore"—so maybe the string must have at least two sequences, meaning at least one underscore. But the example given has one underscore, and returns True. However, the problem's wording is a bit ambiguous. Let me re-read the problem statement.
The problem says: returns true if the input string contains sequences of lowercase letters joined with an underscore. So perhaps the string must have at least one underscore. But maybe the problem allows for a single sequence. For example, if the string is "abc", is that considered as a single sequence, which is allowed? Or does the presence of underscores require that there are multiple sequences?
Looking at the example: the test case is "aab_cbbbc" which returns True. So that's two sequences. But if the input is "abc", would the function return True? Let me think about the problem's intention.
The problem says "sequences of lowercase letters joined with an underscore". So maybe the entire string should be composed of one or more sequences, separated by underscores. So the string can be a single sequence (no underscores) or multiple sequences. For example, "abc" would be valid, as well as "a_b_c".
But how to model that in regex. The regex pattern would be ^[a-z]+(_[a-z]+)*$. Let's see:
- For "abc": matches [a-z]+, and the rest is zero occurrences of the _ part. So yes.
- For "a_bc": matches [a-z]+ (a), then _[a-z]+ (bc). So yes.
- For "a_b_c": matches [a-z]+ (a), then _[a-z]+ (b), then _[a-z]+ (c). So yes.
But what about a string like "a__b"? That would have two underscores. The regex would not match, because between the underscores, there's nothing. Because the pattern is [a-z]+, which requires at least one character. So "a__b" would not match. Because the first part is a, then _ followed by [a-z]+ (which would be empty in the second part?), no. Wait, the regex is ^[a-z]+(_[a-z]+)*$. Let's see:
The first part is [a-z]+, then zero or more of (_[a-z]+). So for "a__b", the first part is a, then the next part would be _ followed by [a-z]+. But between the first _ and the next part, there's another _.
Wait, the regex would split the string into parts. Let me think. For example, the string "a__b" would be split as a, then _, then empty, then _b? No, the regex is looking for sequences of [a-z]+. So the entire string would be a, then _ followed by [a-z]+, but the [a-z]+ would have to be at least one character. So in "a__b", after the first a, the next part is _ followed by [a-z]+. But the [a-z]+ would be empty, because there's a _ followed by another _. So the regex would not match. So that's correct.
So the regex pattern ^[a-z]+(_[a-z]+)*$ would match strings that consist of one or more sequences of lowercase letters separated by underscores. So even a single sequence (no underscores) is allowed.
But wait, the problem says "joined with an underscore"—so perhaps the string must have at least two sequences, i.e., at least one underscore. For example, if the input is "abc", would the function return True? The problem's example has an underscore, but maybe the problem expects that the string must have at least one underscore.
But the original problem's test case is "aab_cbbbc" which returns True. So the function is supposed to return True when the string has sequences joined by underscores. So maybe the function should return True if the entire string is made up of lowercase letters and underscores, but the underscores are between sequences. However, the problem's wording is ambiguous. But perhaps the intended solution is that the entire string is composed of lowercase letters and underscores, but each underscore is between sequences of lowercase letters. So the string can be a single sequence (no underscores) or multiple sequences separated by underscores.
But how to check that. For example, the string "a_b" would be valid. The string "a" would be valid. The string "a_b_c" would be valid. But the string "a__b" would not be valid. The string "a_b_c_" would not be valid, because the last part is an underscore.
So the regex pattern would be ^[a-z]+(_[a-z]+)*$. Let me test that.
For "a_b_c", the regex would match. For "a", it matches. For "a_b", matches. For "a__b", no. For "a_b_c_", no. Because the last part is an underscore.
So the regex would correctly capture the required pattern.
So the function can be written using re.fullmatch() to check if the entire string matches this pattern.
So the Python code would be:
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)*$', s))
Wait, but what about the case where the string is empty? Well, the problem says "input string", but maybe the function should return False for empty string. Because the regex would not match, since [a-z]+ requires at least one character.
Testing the example given: "aab_cbbbc" would match. The regex would match that.
Another test case: "aab_cbbbc" → True. What about "aab_cbbbc_" → False. "aab_cbbbc__" → False. "aab_cbbbc_123" → False. "aab_cbbbc" → True. "abc" → True. "a_b" → True. "a_b_c" → True. "a__b" → False. So the regex seems to handle these cases.
So the code would be using re.fullmatch with that regex.
But wait, the problem says "contains sequences of lowercase letters joined with an underscore". So maybe the string can have other characters as long as there are sequences? No, the problem says that the entire string must be sequences joined with underscores. So the function should return True only if the entire string is made up of lowercase letters and underscores, with the underscores separating sequences of lowercase letters.
Therefore, the regex approach is correct.
So the code is:
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)*$', s))
Wait, but what about if the string is empty? Then it returns False. Which is correct.
Testing the sample input: assert text_lowercase_underscore("aab_cbbbc") == True → yes.
Another test case: assert text_lowercase_underscore("abc") → True. But according to the problem's wording, maybe that's allowed. But perhaps the problem expects that there is at least one underscore. However, the problem's example does not have that. The problem says "joined with an underscore"—but if there is only one sequence, then there's no underscore. But maybe the problem considers that as valid.
But the problem says "contains sequences of lowercase letters joined with an underscore". If there's only one sequence, then there are no underscores. But maybe the function is supposed to check that the string is made up of sequences of lowercase letters separated by underscores. So the function returns True if the string is composed of lowercase letters and underscores, with the underscores between sequences. So the function returns True for "abc" (one sequence) and for "a_b" (two sequences).
So the code as written would return True for "abc", which is correct.
Therefore, the code is correct.
Now, the code needs to be written as a self-contained Python function. Also, the user provided the test case, but the code should handle all cases.
So the final code is:
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)*$', s))
Wait, but the problem says "sequences of lowercase letters joined with an underscore". So perhaps the string must have at least two sequences. For example, "a_b" would be valid, but "a" would not. But the problem's example includes a string with one underscore. Let me check the problem statement again.
The problem says "returns true if the input string contains sequences of lowercase letters joined with an underscore". So maybe the string must have at least two sequences, i.e., at least one underscore. Because if there is only one sequence, then there are no underscores. But the wording is ambiguous.
But the example given is "aab_cbbbc" which has one underscore. So the function returns True. So the function must return True for strings with one or more underscores. But if the string is "abc", which has no underscores, does it return True?
The problem's wording says "contains sequences of lowercase letters joined with an underscore". If the string is "abc", it's a single sequence, not joined with an underscore. So perhaps the function should return False in that case. But how to know?
But the problem's example may not cover that. Let's think about the problem again. The user provided a test case where "aab_cbbbc" returns True. But what about the case where the string is "a"?
If the problem expects that the string must have at least one underscore, then the regex should be adjusted. For example, the regex would be ^[a-z]+(_[a-z]+)+$. Because the * allows zero or more, but + requires one or more. So the pattern would be ^[a-z]+(_[a-z]+)+$.
In that case, the string "a" would not match, but "a_b" would. Let's check.
If the regex is ^[a-z]+(_[a-z]+)+$, then the first part is [a-z]+, then one or more occurrences of (_[a-z]+). So the entire string must have at least one underscore. For example, "a_b" would match. But "a" would not. However, the problem's example "aab_cbbbc" would match.
But what does the problem require? The problem says "contains sequences of lowercase letters joined with an underscore". So the presence of underscores is required. So the string must have at least one underscore. Therefore, the regex should be ^[a-z]+(_[a-z]+)+$.
But then, the problem's example would be correct. But what about a string like "a_b_c"? It would match. But what about a string like "a"? It would not.
But the problem's wording is ambiguous. How to resolve this?
Looking back at the problem statement: the function returns true if the input string contains sequences of lowercase letters joined with an underscore. So the presence of underscores is required. Because if the string is "a", then there are no underscores. So the function should return False.
But how to confirm? Let's think about the example. The test case is "aab_cbbbc" which returns True. That string has one underscore. So the function returns True. But what about a string with no underscores? Like "abc"?
In that case, the function should return False. Because the string contains only one sequence, not joined with any underscores.
So the correct regex would be ^[a-z]+(_[a-z]+)+$.
So the regex must have at least one underscore. Therefore, the pattern is:
^ [a-z]+ ( _ [a-z]+ )+ $
So the first part is [a-z]+, then one or more occurrences of _ followed by [a-z]+.
So for "aab_cbbbc", it's [a-z]+ (aab) followed by one occurrence of _[a-z]+ (cbbbc). So yes.
But for "abc", it's [a-z]+, but no occurrences of the _ part. So the regex would not match. Hence, returns False.
But then the problem's example would be correct. But what about the case where the string is "a_b"?
Yes, it would match. So the function returns True.
But how to know what the problem expects. The problem says "joined with an underscore"—so the sequences must be joined with underscores. Which implies that there are at least two sequences. Hence, the regex should require at least one underscore.
But the problem's wording is ambiguous. However, given the example provided, the user may have intended that the string must contain at least one underscore. Because otherwise, the function would return True for "abc", but perhaps the problem expects that the string has underscores.
But the problem says "contains sequences of lowercase letters joined with an underscore". So the presence of underscores is required. For example, if there is only one sequence, then there are no underscores. Hence, the function returns False.
Therefore, the correct regex would be ^[a-z]+(_[a-z]+)+$.
So the code would be:
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)+$', s))
Testing the example: "aab_cbbbc" → matches. So returns True. For "abc" → no match, returns False. For "a_b" → matches, returns True. For "a" → no, returns False. For "a_b_c" → yes. For "a__b" → no, because the second part is [a-z]+, which requires at least one character. So "a__b" would be parsed as a, then _, then [a-z]+ would be empty? No. The regex would require that after the first [a-z]+, each _ is followed by [a-z]+. So in "a__b", the first part is a, then _ followed by [a-z]+, but the [a-z]+ would be empty (since the next character is _). So it would not match.
So this regex seems correct.
But then, what about the test case provided by the user? The user says that assert text_lowercase_underscore("aab_cbbbc") == (True). Which would be True with this regex.
So the code should be written with the regex ^[a-z]+(_[a-z]+)+$.
But then, what about the case where the string is "a_b_c"? It would match.
So the correct code is as above.
Therefore, the final Python code is:
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)+$', s))
But wait, the original problem says "contains sequences of lowercase letters joined with an underscore". So the string must have at least one underscore. Hence, the code is correct.
But I need to make sure that the code passes the given test case. Let's test the example.
The input is "aab_cbbbc". The regex would match this. The first part is [a-z]+ (aab), then one or more of (_[a-z]+). Here, there is one occurrence of _ followed by [a-z]+ (cbbbc). So it matches. Hence, returns True.
Yes.
Another test case: "a_b" → True. "a" → False. "ab" → False. "a_b_c" → True. "a__b" → False. "a_b_c_" → False. All correct.
So this code should be correct.
```python
import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)+$', s))
```
----------------------------------------------
Result: Pred=import re
def text_lowercase_underscore(s):
return bool(re.fullmatch(r'^[a-z]+(_[a-z]+)+$', s)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['aab_cbbbc'], ['aab_Abbbc'], ['Aaab_abbbc'], ['a_b_c_d_e_f_g_h_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z'], ['abc_def_ghi_jkl_mno_pqr_stu_vwx_yz'], ['_'], ['_abc'], ['abc_'], ['abc_def_ghi_'], ['A__B_ccC_dDd_eE_fFF_g_hhH_iJj'], ['a'], ['abc_DEF_ghi'], ['abc'], ['abc_def_'], ['_abc_def'], ['_abc_def_'], ['a_b_c_d_e_f_g_h_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z_'], ['_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yz'], ['ab_abc_def_c_'], ['_abc_deaf'], ['abc_def_ghi_jkl_mno_pqr_stu_vwxyz'], ['abdc_def_ghi_jkl_mno_pqr_stuu_vwx_yz'], ['A__B_cc_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yzC_dDd_eE_fFF_g_hhH_iJj'], ['abdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['_abcabc_d_ghi_jkl_mno_pqr_stu_vwx_yz'], ['abdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno__pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno__pqr_stu_vwx_yz_mno_pqrabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz_stuu_vwx_yzstuu_vwx_yz'], ['_abcabc_def_ghi_jkl_mno_pqr_stu_vwxq_yz'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pqr_stuu_vwx_yz'], ['wJz'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yztuu_vwx_yz'], ['abc_def_ghiabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abc_def_ghie_'], ['abc_def_ghi_jkl_mno_pqr_stu_vabc_def_ghie_wxyz'], ['aba_b_c_d_e_f_g_h_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z_abc_def_ghi_jkl_mno_pqr_stu_vwxyzc_def_'], ['_abcabc_def_ghi_jkl_mno_pqr_stu_vwxq_yabdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yztuu_vwx_yzz'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_afbc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yzabc_def_z'], ['PfGhQdq'], ['c'], ['ab_abc_A__B_ccC_dDd_eE_fFF_g_hhH_iJjdef_c_'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc_defi_jkl_abcabmno_pqr_stuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abdc_def_ghi_jkl_abcabc_def_ghi__jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc__def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pq_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno__pqr_stu_vwx_yz_mno_pqrabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz_stuu_vwx_yzstuu_vwx_yz_yyz_mno_pqr_stuu_vwx_yz'], ['A__B_cc_abcabc_def_ghi_jk_l_mno_pqr_stu_vwx_yzC_dDd_eE_fFF_g_hhH_iJj'], ['ac_'], ['abc_DEF_ghia'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno__pqr_stu_vwx_yz_mno_pqrabdc_def_xghi_jkl_abcabc_def_ghabc_def_ghi_jkl_mno_pqr_stu_vwxyztuu_vwx_yz_stuu_vwx_yzstuu_vwx_yz_yyz_mno_pqr_stuu_vwx_yz'], ['cc'], ['_abcabc_d_ghi_jkl_mno_pqr_stu_vmwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEaba_b_c_d_e_f_g_h_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z_abc_def_ghi_jkl_mno_pqr_stu_vwxyzc_def_F_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abc_d_abcabc_def_ghi_jkl_mno_pqr_stu_vwxq_yabdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yztuu_vwx_yzzef_ghi_'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_abc_defi_jkl_abcbabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yztuu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc_defi_jkl_abcaxbmno_pqr_stuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['_abcabc_def_ghi_jkl_mnao_pqr_stu_vwx_yz'], ['no_pqr_stuu_vwx_yzz'], ['abc_def_ghi_jkl_mnoc_pqr_stu_vabc_def_ghie_wxyz'], ['_ab_abc_defc_def_'], ['a_b_c_d_e_f_g_hf_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z'], ['abc_DEF_ghDia'], ['L'], ['abdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_afbc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yzabc_def_qz'], ['abc_def_ghi_jkl_mno_pqr_stmu_vwxyz'], ['_abcabc_def_ghi_jkl_mno_pqr_stmu_vwxyz_deaf'], ['A__B_cc_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yzC_dDd_eE_fFF_g_hhH_iJLj'], ['_abcabc_def_ghi_jkl_mno_pqr_stu_vwxq_yabdc_def_gh_abc_defi_jkl_abcabmino_pqr_sabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yztuu_vwx_yzz'], ['no__abc_deafpqr_stuu_vwx_LPfGhQdqyzz'], ['_aabc'], ['abc_defabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc_defi_jkl_abcabmno_pqr_stuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['A__B_cc_abcabc_def_ghi__jkl_mno_pqr_stu_vwx_yzC_dDd_eE_fFF_g_hhH_iJj'], ['PfGhQQdq'], ['abc_DEF_PfGhQdqghDia'], ['abc_def_ghiabdc_def_gh_abc_defi_ijkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abc_def__ghi_jkl_mnoc_pqr_stu_vabc_def_ghie_wxyz'], ['aabc'], ['ano_pqr_stuu_vwx_yzzbc_def_ghie_'], ['PfGhQQdq_abcabc_d_ghi_jkl_mno_pqr_stu_vmwx_yz'], ['abc_DEF_PfGhQdqghQDia'], ['abc_def_ghai_'], ['abdc_def_ghi_pqr_stuu_vwx_yz'], ['abc_defabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc_defi_jkl_abcabmno_pqr_stabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yzuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['abc_def_ghiabdc_def_gh_abc_defi_ijkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_spqr_stuu_vwx_yz'], ['abdc_def_ghi_jkl_abcabc_def_ghi__jkl_mno_pqr_ustu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['_abPfGhQQdqcabc_def_ghi_jkl_mno_pqr_stmu_vwxyz_deaf'], ['_ab_abc_defc_defabdc_def_ghi_jkl_abcabc_def_ghi_jkl_mno__pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abdbc_def_ghi_jkl_abcabc_def_ghi__jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['abc_def_ghi_jk_l_mno_spqr_stu_vwx_yz'], ['abc_defabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc__defi_jkl_abcabmno_pqr_stuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['A__B_cc_aghi_jk_l_mno_pqr_stu_vwx_yzC_da_b_tc_d_e_f_g_hf_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_zDd_eE_fFF_g_hhH_iJj'], ['vabc_def_ghi_jkl_mno_pqr_stu_vwx_yz'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mx_yz'], ['abc_def_abdc_def_gh_abc_defi_jkl_abcabmno_pqr_sabdc_def_gh_afbc_defi_jkl_abcabc_def_ghi_jkl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yzabc_def_qzghiabdc_def_gh_abc_defi_ijkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_spqr_stuu_vwx_yz'], ['abdc_def_ghi_jkl_mno_p_abc_def_qr_stuuPfGhQQdq_abcabc_d_ghi_jkl_mno_pqr_stu_vmwx_yz_vwx_yz'], ['_abcabc_d_ghi_jkl_mno_abc_def_ghai_pqr_stu_vwx_yz'], ['yz'], ['abdc_def_ghi_jkl_mno_p_abc_abc_defabdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEabcF_ghiqr_stabdc_def_gh_abc__defi_jkl_abcabmno_pqr_stuu_vwx_yzu_vwx_yyz_mno_pqr_stuu_vwx_yzdef_qr_stuuPfGhQQdq_abcabc_d_ghi_jkl_mno_pqr_stu_vmwx_yz_vwx_yz'], ['abdc_Edef_gh_abc_defi_jkl_abcabc__def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yyz_mno_pqr_stuu_vwx_yz'], ['bc_def_'], ['abc_def_dghi_'], ['abdcc_def_ghi_jkl_abcabc_def_ghi__jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz'], ['_acbc_def_'], ['abdc_Edef_gh_abc_defi_jkl_abcabc__def_ghi_jkl_yz'], ['habcghia'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_jkl_mno_pabc_DEF_ghiqr_stu_vwx_yeyz_mx_yz'], ['_abcabc_d_ghi_jkl_mno_pqr_stu_x_yz'], ['a_b_c_d_e_f_g_h_i_j_aba_b_c_d_e_f_g_h_i_j_k_l_m_n_o_p_q_r_s_t_u_v_w_x_y_z_abc_def_ghi_jkl_mno_pqr_stu_vwxyzc_def_m_n_o_p_q_r_s_t_u_v_w_x_y_z'], ['abdc_def_gh_abc_bdefi_jkl_abcabmno_pq_yz'], ['an_pqr_stuu_vwx_yzzbc_def_ghie_'], ['PfGhQdqL'], ['_abcabc_d_ghi_jkl_mno_pqr_stu_z'], ['abc_DEF_PhQdqghQDia'], ['abdc_def_gh_abc_defi_jkl_abcabc_def_ghi_abdbc_def_ghi_jkl_abcabc_def_ghi__jkl_mno_pqr_stu_vwx_yz_mno_pqr_stuu_vwx_yzl_mno_pa_abcbc_DEF_ghiqr_stu_vwx_yz_mno_pqr_stuu_vwx_yz']]
results = [True, False, False, True, True, False, False, False, False, False, True, False, True, False, False, False, False, False, False, False, True, True, False, True, False, False, False, False, False, False, False, True, False, False, False, False, True, False, False, False, False, True, False, False, False, False, True, False, False, False, False, False, True, False, False, False, False, False, False, True, True, False, True, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, True, False, False, False, False, False, False, True, False, False, True, False, False, False, False, True, False, False, False, False, False, False, False, True, False, False, True, True, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(text_lowercase_underscore(*inp), exp, 0)
| OK=False
==================== Problem #12 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function that returns the perimeter of a square given its side length as input.
Your answer will be tested on test cases like:
assert square_perimeter(10)==40
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function that returns the perimeter of a square given its side length as input.
Your answer will be tested on test cases like:
assert square_perimeter(10)==40
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function that returns the perimeter of a square given its side length as input.
Your answer will be tested on test cases like:
assert square_perimeter(10)==40
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function that returns the perimeter of a square given its side length as input.
Your answer will be tested on test cases like:
assert square_perimeter(10)==40
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function that returns the perimeter of a square given its side length as input.
Your answer will be tested on test cases like:
assert square_perimeter(10)==40
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called square_perimeter that takes the side length of a square and returns its perimeter. Let's think about how to approach this.
The perimeter of a square is calculated by adding up all four sides. Since all sides are equal, the formula should be 4 multiplied by the side length. So, if the side is 10, 4*10=40, which matches the test case given.
So the function is straightforward. The steps are: take the input parameter, multiply by 4, return the result.
Wait, what about input validation? The problem doesn't mention handling invalid inputs, so maybe I don't need to worry about that. Just assume the input is a positive number.
So the code would be:
def square_perimeter(side):
return 4 * side
Then, testing with assert square_perimeter(10) == 40 should pass. That's simple enough. I don't see any edge cases mentioned, so this should work.
```python
def square_perimeter(side):
return 4 * side
```
----------------------------------------------
Result: Pred=def square_perimeter(side):
return 4 * side | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10], [5], [4], [3.5], [3.867338210205425], [4.017438434643324], [4.487089891527536], [2.6642890317066636], [5.887984312046749], [6.072194086423373], [3.642116465724614], [3.695469856787123], [4.141400647038825], [6.035071486216641], [3.271150304405481], [True], [84], [22], [5.654807546008664], [4.820511953305605], [6.577316776519947], [5.002581120259965], [6.969535253031167], [3.718379579422467], [6.322289576625546], [5.632673587071418], [5.3345589524375985], [6.725440141493683], [6.516564500761447], [8.993452545033046], [5.319836337788916], [6.043399656495942], [6.185578656467972], [4.217038121909214], [87], [4.005528059933441], [6.208925187146142], [85], [2.5181655036830994], [82], [4.1150925428079805], [5.484648231650928], [6.701524882996955], [21], [5.568439992700058], [88], [6.843276090129513], [3.4382125488926367], [6.388475480286746], [7.660073820339544], [2.769573374810499], [6.898645835852767], [7.826927755593033], [2.4985782322950842], [5.8695983810477985], [4.773486580932547], [3.001034234443808], [5.395838439745376], [3.577918724597513], [5.170120644837316], [6.99185332198154], [3.449246178521576], [5.5411783354818605], [6.436883135688541], [3.49384577169542], [5.015277110821801], [3.4631036701381923], [3.38643188343381], [1.9894160159593337], [1.837789735808722], [5.245639801999035], [4.465805726769371], [5.309603748296835], [3.3070853809486187], [8.803439557651616], [5.447584681806455], [2.6402987239829994], [5.81268658921342], [2.203529850744147], [2.413369661283704], [2.8444882558095452], [2.9679176613024727], [5.635919297098677], [7.106142255754484], [3.673088666908028], [11.501115163046252], [3.3172795455753574], [3.2120053514572735], [6.650019959695511], [23], [2.413305987922484], [3.453597614102104], [6.8216792009730725], [1.2676205462665886], [6.866125113001431], [4.423165960786375], [1.9765423457339029], [4.395641502661771], [2.9248802236697493], [1.6520153932594805], [8.099418388939899], [5.066661526673157], [6.345597309471013], [2.66964983620433]]
results = [40, 20, 16, 14.0, 15.4693528408217, 16.069753738573297, 17.948359566110145, 10.657156126826655, 23.551937248186995, 24.288776345693492, 14.568465862898456, 14.781879427148493, 16.5656025881553, 24.140285944866562, 13.084601217621923, 4, 336, 88, 22.619230184034656, 19.28204781322242, 26.309267106079787, 20.01032448103986, 27.87814101212467, 14.873518317689868, 25.289158306502184, 22.53069434828567, 21.338235809750394, 26.901760565974733, 26.06625800304579, 35.97381018013218, 21.279345351155666, 24.173598625983768, 24.742314625871888, 16.868152487636856, 348, 16.022112239733765, 24.835700748584568, 340, 10.072662014732398, 328, 16.460370171231922, 21.93859292660371, 26.80609953198782, 84, 22.27375997080023, 352, 27.373104360518052, 13.752850195570547, 25.553901921146984, 30.640295281358178, 11.078293499241996, 27.594583343411067, 31.307711022372132, 9.994312929180337, 23.478393524191194, 19.093946323730187, 12.004136937775232, 21.583353758981502, 14.311674898390052, 20.680482579349263, 27.96741328792616, 13.796984714086303, 22.164713341927442, 25.747532542754165, 13.97538308678168, 20.061108443287203, 13.85241468055277, 13.54572753373524, 7.957664063837335, 7.351158943234888, 20.98255920799614, 17.863222907077486, 21.23841499318734, 13.228341523794475, 35.213758230606466, 21.79033872722582, 10.561194895931997, 23.25074635685368, 8.814119402976589, 9.653478645134816, 11.377953023238181, 11.87167064520989, 22.543677188394707, 28.424569023017938, 14.692354667632111, 46.00446065218501, 13.26911818230143, 12.848021405829094, 26.600079838782044, 92, 9.653223951689936, 13.814390456408416, 27.28671680389229, 5.070482185066354, 27.464500452005723, 17.6926638431455, 7.9061693829356114, 17.582566010647085, 11.699520894678997, 6.608061573037922, 32.397673555759596, 20.26664610669263, 25.382389237884052, 10.67859934481732]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(square_perimeter(*inp), exp, 0)
| OK=True
==================== Problem #13 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to remove characters from the first string which are present in the second string.
Your answer will be tested on test cases like:
assert remove_dirty_chars("probasscurve", "pros") == 'bacuve'
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to remove characters from the first string which are present in the second string.
Your answer will be tested on test cases like:
assert remove_dirty_chars("probasscurve", "pros") == 'bacuve'
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to remove characters from the first string which are present in the second string.
Your answer will be tested on test cases like:
assert remove_dirty_chars("probasscurve", "pros") == 'bacuve'
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to remove characters from the first string which are present in the second string.
Your answer will be tested on test cases like:
assert remove_dirty_chars("probasscurve", "pros") == 'bacuve'
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to remove characters from the first string which are present in the second string.
Your answer will be tested on test cases like:
assert remove_dirty_chars("probasscurve", "pros") == 'bacuve'
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called remove_dirty_chars that takes two strings. The goal is to remove all characters from the first string that are present in the second string. Let's see.
So, for example, if the first string is "probasscurve" and the second is "pros", then the result should be 'bacuve'. Let me check that. The original string has letters p, r, o, b, a, s, s, c, u, r, v, e. The second string is p, r, o, s. So we need to remove all occurrences of p, r, o, s from the first string. Let's see:
Original letters: p (remove), r (remove), o (remove), b (keep), a (keep), s (remove), s (remove), c (keep), u (keep), r (remove), v (keep), e (keep). So the remaining letters are b, a, c, u, v, e → "bacuve". Yep, that's correct.
So how to approach this? Well, for each character in the first string, check if it's not in the second string. Then collect those characters.
So, the steps could be:
1. Iterate over each character in the first string.
2. For each character, check if it is not present in the second string.
3. If it's not present, include it in the result.
4. Combine all such characters into a new string.
But how to implement this efficiently?
In Python, one way is to use a list comprehension. For example:
def remove_dirty_chars(s1, s2):
return ''.join([c for c in s1 if c not in s2])
Wait, but what about the case where the second string has duplicate characters? Like if s2 is "pros", then checking 'c in s2' would be False. So the code would work regardless of duplicates in s2. Because the 'in' operator checks presence, not count.
So that's straightforward. Let me test this with the sample input.
Sample input: s1 = "probasscurve", s2 = "pros".
The list comprehension would check each character in s1. For example, the first character is 'p', which is in s2 → excluded. Then 'r' → excluded. Then 'o' → excluded. Then 'b' → not in s2 → included. And so on. So the code would generate the correct output.
But wait, what about the order? The code preserves the order of the original string, which is correct.
So this seems like a simple solution. But perhaps the problem expects handling of case? Like, if the characters are case-sensitive. But the example given uses lowercase letters, and the problem statement doesn't mention case insensitivity. So I think the function should treat characters as case-sensitive. So the code as written would work.
Another test case: if s1 is "abc", s2 is "a", then the result is "bc".
Another test case: s1 is "aabbcc", s2 is "abc" → result is "".
Yes, that's correct.
So the code seems correct. Let me write the function accordingly.
But the problem says that the answer will be tested on the given test case. So the code should handle that.
So the function is straightforward. Now, the code should be written as a self-contained Python script. The user wants the code in a markdown code block.
So the code would be:
def remove_dirty_chars(s1, s2):
return ''.join(c for c in s1 if c not in s2)
Wait, but maybe using a set for s2 would be more efficient, especially if s2 is long. Because checking membership in a set is O(1) vs O(n) for a string. So for example, converting s2 into a set first.
Like:
def remove_dirty_chars(s1, s2):
s2_set = set(s2)
return ''.join(c for c in s1 if c not in s2_set)
This would be more efficient for longer s2. But for the problem's purposes, perhaps either approach works. But since the problem's example uses small strings, either way is acceptable.
But using a set is better practice for efficiency. So I should include that.
So the code would be as above.
Now, let me test the sample input. For "probasscurve" and "pros", the set s2_set is {'p','r','o','s'}. Then each character in s1 is checked against this set. So the code would produce the correct output.
Therefore, the function should work.
```python
def remove_dirty_chars(s1, s2):
s2_set = set(s2)
return ''.join(c for c in s1 if c not in s2_set)
```
----------------------------------------------
Result: Pred=def remove_dirty_chars(s1, s2):
s2_set = set(s2)
return ''.join(c for c in s1 if c not in s2_set) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['probasscurve', 'pros'], ['digitalindia', 'talent'], ['exoticmiles', 'toxic'], ['The quick brown fox jumps over the lazy dog', 'fox'], ['This is a sample string', 'i a'], ['1234567890', '01234'], ['abcd efgh', 'ab cd'], ['This is a sampile string', 'i a'], ['abcd efgh', 'This is a sampile string'], ['a', '01234'], ['This is a sample string', 'a'], ['abcabgh', 'ab'], ['i a', 'This is a sampile string'], ['dog', 'This is a sampile string'], ['01234', '01234'], ['abcabgh', 'a'], ['The quick brown fox jumps otver the lazy dog', 'fox'], ['do', 'This is a sampile string'], ['abcabggh', 'a'], ['This is a sample string', 'This'], ['ia', 'This is a sampile string'], ['ia', 'This is a sample stringsample'], ['This is a sasmple string', 'This is a sample strin1234567890g'], ['sis', 'dog'], ['abcd efgh', 'bab cd'], ['bab cd', 'bab cd'], ['bab cd', 'This is a sample stringsample'], ['This is a sampile string', 'This is a sampile string'], ['do', 'do'], ['This is a sample stringsample', 'Thish is a sampile string'], ['a', '1234567890'], ['dog', 'dog'], ['Thiss is a sampring', 'This is a sampring'], ['The quick brown fox jumps over the lazy dog', 'This is a sampile string'], ['brownabcd', 'iaquick'], ['This is a sasmple string', 'This is a sample strin1234567g'], ['This is a sample stringsamplae', 'This is a sample stringsample'], ['Thish is a sampile string', 'Thish is a sampile string'], ['1234567890', '1234567890'], ['a', '0123'], ['This is a sample stringsam', 'This is a sample stringsample'], ['This is a sample stringsample', 'stringsam'], ['bab cd', 'bdab cd'], ['This is a sampThis is a sample stringsamplele stringsample', 'Thish is a sampile string'], ['i a', 'i a'], ['aa', 'a'], ['1234567890', 'This is a sampThis is a sample stringsamplele stringsample'], ['a', 'dog'], ['i a', 'ia'], ['The quickfox jumps otver the lazy dog', 'fox'], ['bdab', 'The quick brown fox jumps over the lazy dog'], ['This is a sample stringsample', 'bab cd'], ['This is a sasmple string', 'Thiss is a sampring'], ['The quickfox jumpsg otver the latzy dog', 'The quickfox jumpsg otver the latzy dog'], ['This is a sample stringsam', 'stringsam'], ['The quick brown fox jumps otver the lazy dog', 'The quickfox jumpsg otver the latzy dog'], ['Tthis is a sampile sstring', 'This is a sampile string'], ['The quick brown fox jumps otver the lazy dog', 'sampile'], ['Thish is a sampile string', 'This is a sampile string'], ['0123', '01234'], ['012strin1234567g34', '01234'], ['aab', 'ab'], ['abdog', 'ab'], ['stringsamplea', 'a'], ['stringsamplea', 'stringsamplea'], ['1234567890', 'This is asampThis sampThis is a sample stringsamplele stringsample'], ['The quick brown fox jumps otver the lazy dog', 'foox'], ['Thiss is a sampring', 'The quickfox jumpsg otver the latzy dog'], ['dThis is a sampile stri', 'dThis is a sampile stri'], ['ab cd', 'ab cd'], ['jumpsg', 'jumpsg'], ['fstringsampleaox', 'fox'], ['the', '01234'], ['bdab cd', '1234567890'], ['This is a sample stringsample', 'This is a sample stringsample'], ['stri', 'stringsam'], ['brownabcd', 'brownabcd'], ['This issasmple a sampile string', 'This is a sampile string'], ['0123', '0123'], ['bdabb cd', '1234567890'], ['over', 'The quickfox jumpsg otver the latzy dog'], ['01234', '0134'], ['This is a sasmring', 'This is a sasmple string'], ['bdab cd', 'bdab cd'], ['ia', 'ia'], ['fstrix', 'The quickfox jumps otver the lazy dog'], ['aasampThisb', 'ab'], ['Thiss', 'bab cd'], ['stri', 'sampile'], ['This is a sample strimplae', 'This is a sample stringsample'], ['a', 'a'], ['bab cd', 'babstringsamplea cd'], ['abrownabcd', 'The quickfox jumps otver the lazy dog'], ['bdabcdab', 'This is a sample strin1234567g'], ['i aThis is a sasmple string', 'This is a sample strin1234567g'], ['Thish is a sampile string', 'stringsam'], ['bdabb cd', '0123'], ['This is a sampring', 'This is a sample strin1234567g'], ['The quick brown fox jumg', 'The quickfox jumpsg otver the latzy dog'], ['This is a sasmple string', 'This is a sample stringsample'], ['1234567890', 'fox'], ['foox', 'This is a sample strimplae'], ['This is a sasmple sstringstring', 'This is a sasmple sstringstring'], ['03134', '0134'], ['0123', 'llae'], ['bdabb cd', '01223'], ['aquickfox', 'dog']]
results = ['bacuve', 'digiidi', 'emles', 'The quick brwn jumps ver the lazy dg', 'Thsssmplestrng', '56789', 'efgh', 'Thsssmplestrng', 'bcdf', 'a', 'This is smple string', 'cgh', '', 'do', '', 'bcbgh', 'The quick brwn jumps tver the lazy dg', 'do', 'bcbggh', ' a ample trng', '', '', '', 'sis', 'efgh', '', 'bbcd', '', '', '', 'a', '', '', 'quckbowfoxjuovzydo', 'brownbd', '', '', '', '', 'a', '', 'Th ple ple', '', '', '', '', '1234567890', 'a', ' ', 'The quick jumps tver the lazy dg', '', 'Thisissmplestringsmple', 'let', '', 'Th ple ', 'bwn', '', 'Th quck brown fox ju otvr th zy dog', '', '', 'strin567g', '', 'dog', 'stringsmple', '', '1234567890', 'The quick brwn jumps tver the lazy dg', 'n', '', '', '', 'stringsamplea', 'the', 'bdab cd', '', '', '', '', '', 'bdabb cd', '', '2', '', '', '', '', 'smpThis', 'Thiss', 'tr', '', '', '', 'bwnb', 'bdbcdb', '', 'Thh ple ', 'bdabb cd', '', 'bwn', '', '1234567890', 'foox', '', '', '0123', 'bdabb cd', 'aquickfx']
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(remove_dirty_chars(*inp), exp, 0)
| OK=True
==================== Problem #14 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether a given array of integers contains any duplicate element.
Your answer will be tested on test cases like:
assert test_duplicate(([1,2,3,4,5]))==False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether a given array of integers contains any duplicate element.
Your answer will be tested on test cases like:
assert test_duplicate(([1,2,3,4,5]))==False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether a given array of integers contains any duplicate element.
Your answer will be tested on test cases like:
assert test_duplicate(([1,2,3,4,5]))==False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether a given array of integers contains any duplicate element.
Your answer will be tested on test cases like:
assert test_duplicate(([1,2,3,4,5]))==False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether a given array of integers contains any duplicate element.
Your answer will be tested on test cases like:
assert test_duplicate(([1,2,3,4,5]))==False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called test_duplicate that checks if an array of integers has any duplicate elements. Let's think about how to approach this.
First, the problem says that the function should return True if there are duplicates, and False otherwise. The example given is that test_duplicate([1,2,3,4,5]) should return False because all elements are unique.
So how do I check for duplicates? Well, one straightforward way is to compare the length of the original list with the length of a set made from the list. Because a set automatically removes duplicates. If the lengths are different, there must be duplicates.
Wait right. For example, if the list is [1,2,2,3], the set is {1,2,3} which has length 3, while the original list has length 4. So the difference in lengths indicates duplicates.
So the function can be written as: convert the list to a set and check if the length of the set is less than the original list's length. If yes, return True (there are duplicates), else False.
But wait, what about empty lists or single-element lists? Well, for empty list, the length is zero, and the set length is also zero. So no duplicates. For a single element, same thing. So the function would return False, which is correct.
So the code would be something like:
def test_duplicate(arr):
return len(arr) != len(set(arr))
Wait, but the problem says the input is an array of integers. So the function takes a list, right?
Yes. So this code should work. Let me test with the example given. The input is [1,2,3,4,5], length is 5. The set's length is also 5. So the function returns False, which matches the example.
Another test case: [1,2,3,4,1]. The set has 4 elements, original list has 5. So returns True. Which is correct.
But wait, what about if the list is [1,1,1,1]? The set is {1}, length 1. Original length is 4. So returns True, which is correct.
This approach seems solid. So the function is simple. But I need to make sure that the function is called test_duplicate and takes the array as an argument.
So the code would be:
def test_duplicate(arr):
return len(arr) != len(set(arr))
But wait, the problem says that the function should return whether the array contains any duplicate. So if the lengths are different, return True. Otherwise, False. That's exactly what this code does.
Yes. So that's the solution. Let me write that as the Python code.
```python
def test_duplicate(arr):
return len(arr) != len(set(arr))
```
----------------------------------------------
Result: Pred=def test_duplicate(arr):
return len(arr) != len(set(arr)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, 2, 3, 4, 5]], [[1, 2, 3, 4, 4]], [[1, 1, 2, 2, 3, 3, 4, 4, 5]], [[2, 5, 1, 4, 3, 6, 7, 8, 9, 10]], [[]], [[-81, True, False]], [[-81, False, True, False]], [[2, 5, 1, 4, 3, 3, 6, False, 7, 8, 9, 10, 7]], [[False, -81, True, False]], [[False, -81, True, True, False, True]], [[False, -81, True, True, False, True, True]], [[-82, True, False]], [[False, -81, True, False, True, True, True]], [[5, 1, 4, 3, 6, 7, 8, 9, 10]], [[False, True, True, False, True, True]], [[-81, False, False]], [[2, 5, 1, 6, 4, 3, 6, 7, 8, 9, 10]], [[True, True, -81, True, False, True, True, True]], [[False, -81, True, False, True, True, True, False]], [[True, False, -81, False, True, True, True]], [[True, False, False, True, True, True, True]], [[2, 5, 1, 4, 3, 3, 6, False, 3, 8, 9, 10, 7]], [[False, -81, False, True, True, True, True]], [[-81, True, True, False, False]], [[False, False, True, True, False, True, True]], [[False, False, False]], [[False, -81, True, False, True]], [[True, False, False, True, True, True, True, True, True]], [[True, False, True, True, True, True, True, True]], [[True, True, True, -81, True, False, True, True, True]], [[2, 5, 1, 4, 3, 6, 7, 9, 10, 10]], [[-81, False, False, False, -81]], [[True, True, True, -81, True, False, True, True, True, True]], [[False, -81, True, False, True, True, True, False, -81, False]], [[False, True, False]], [[False, 9, False, True, False, True, True, True, False]], [[2, 1, 4, 3, 3, 6, False, 7, 8, 9, 10, 7]], [[False, -81, True, False, True, True, False, True, False]], [[False, False, -81, True, False, True]], [[-56, 3, 7, 10, 3, 7]], [[-56, 3, -82, 10, 3, 7]], [[False, False]], [[True, False, False, True, True, True, True, True]], [[False, False, -81, True, True, False, True, True]], [[-56, 3, -82, 4, 10, 3, 7, 10]], [[False, -81, True, False, True, True, True, True]], [[2, 5, 1, 4, 3, 1, 7, 9, 10, 10]], [[2, 5, 1, 6, 4, 3, 6, 7, 5, 9, 10, 7]], [[2, 5, 1, 4, 3, 6, 7, 8, 9, 10, 3]], [[-81, False, False, False]], [[False, -81, False, True, True, True, True, True]], [[-56, 3, 10, -56, 3, 7]], [[False, -81, True, True, False, True, True, True, True]], [[2, 5, 1, 6, 3, 4, 3, 6, 7, 9, 10, 8]], [[False, False, -81, False, False, False, False, True, False]], [[True, False, True, False]], [[-82, True, False, False, False]], [[2, -82, 1, 10, 3, 3, 6, False, 7, 8, 9, 10, 7, 10]], [[2, 5, 1, 9, 4, 3, 3, 6, False, 2, 8, 9, 10, 7, 3]], [[2, 5, 3, 4, 3, 3, 6, False, 3, 8, 9, 10, 7]], [[False, -81, True, False, True, True, False, True, False, False, False]], [[2, 5, 1, 9, 4, 3, 3, 6, False, 2, 8, 9, 10, 3]], [[2, -82, 1, 10, 4, 3, 6, False, 7, 8, 9, 10, 7, 10]], [[False, False, True, False, False, True, True]], [[2, 5, 1, False, 3, 4, 3, 6, 7, 9, 10, 8]], [[2, 5, 1, 6, 5, 3, 6, 7, 9, 10, 8, 9]], [[2, 5, 1, False, 3, 4, 3, 6, 7, 9, 10, 8, 3]], [[False, True, False, -81, True, True, False, True, True]], [[5, 1, 4, 3, 6, 7, 8, 9, 11]], [[False, -81, False]], [[False, -81, True, False, True, True, True, False, False, -81]], [[False, -81, True, False, True, -81]], [[2, 5, 1, 9, 4, 3, 6, False, 2, 8, 9, 10, 7, 3]], [[True, -81, True, True, False, True, True, True, True]], [[True, False, -81, False, True, True]], [[2, 5, 1, 4, 3, 6, 7, 8, 9, 10, 3, 9]], [[False, -81, True, False, True, False, True, False]], [[False, False, True, False, True]], [[2, 1, 3, 3, 6, False, 7, 8, 9, 10, 7]], [[False, True, False, True, False, True, False]], [[2, 5, 1, 9, 6, 4, 3, 6, 7, 4, 9, 10, 7]], [[False, -81, True, False, True, False]], [[2, 1, 3, 3, 6, 8, False, 7, 8, 9, 10, 7]], [[5, 9, 6, 4, 3, 6, 7, 4, 9, 10, 7]], [[-80, False, True, False, True]], [[False, False, True, False, True, False]], [[5, 1, 4, 3, 6, 7, 8, 9, 11, 3]], [[False, -81, True, False, True, True, False, False]], [[5, 1, 4, 3, 6, 7, 8, 9, 10, 3, 9, 6]], [[5, 1, 4, 3, 6, 7, 5, 9, 10, 7, 8]], [[-81, True, False, True, True, False, -81, False]], [[-82, True, False, False]], [[5, 9, 6, 4, 3, 6, 7, 4, 9, 8, 7]], [[True, -81, True, True, False, True, True, True, True, True]], [[False, -81, False, True, True, True, True, True, True]], [[-56, 3, 7, 10, 11, 3, 7, 3]], [[True, False, -81, False, False, False, False, False, True, False]], [[2, 1, 3, 3, 6, False, 8, False, 7, 8, 9, 10, 7]], [[-82, 7, True, False, False, False]], [[10, 2, 5, 1, 4, 3, 3, 6, False, 7, 8, 5, 9, 10, 7]], [[False, True, False, True]], [[-81, True, False, False, False, -81]], [[-81, True, False, True, True, False, True, False, False, False]], [[10, 2, 5, 1, False, 3, 3, 6, False, 7, 8, 5, 9, 10, 7]], [[False, True, False, False]]]
results = [False, True, True, False, False, False, True, True, True, True, True, False, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(test_duplicate(*inp), exp, 0)
| OK=True
==================== Problem #15 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if the given number is woodball or not.
Your answer will be tested on test cases like:
assert is_woodall(383) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if the given number is woodball or not.
Your answer will be tested on test cases like:
assert is_woodall(383) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if the given number is woodball or not.
Your answer will be tested on test cases like:
assert is_woodall(383) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if the given number is woodball or not.
Your answer will be tested on test cases like:
assert is_woodall(383) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if the given number is woodball or not.
Your answer will be tested on test cases like:
assert is_woodall(383) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
A
To determine whether a number is a **woodall number**, we must understand the definition of a woodall number.
### Definition:
A **woodall number** is a number of the form:
$$
W_n = n \times 2^n - 1
$$
where $ n $ is a positive integer.
### Goal:
We are to write a function `is_woodall(num)` that returns `True` if the input number is a woodall number, and `False` otherwise.
---
### Steps to solve the problem:
1. **Iterate over possible values of `n`**:
For each positive integer `n`, compute $ W_n = n \times 2^n - 1 $ and compare it to the input number.
2. **Check for equality**:
If at any point $ W_n $ equals the input number, return `True`.
3. **Set a reasonable upper bound**:
Since $ 2^n $ grows exponentially, the number of iterations needed is small even for large inputs.
4. **Return `False`** if no match is found after checking all reasonable values of `n`.
---
### Final Python Code:
```python
def is_woodall(num):
if num < 1:
return False
n = 1
while True:
w = n * (2 ** n) - 1
if w == num:
return True
elif w > num:
return False
n += 1
```
----------------------------------------------
Result: Pred=def is_woodall(num):
if num < 1:
return False
n = 1
while True:
w = n * (2 ** n) - 1
if w == num:
return True
elif w > num:
return False
n += 1 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[383], [254], [200], [123456789], [123456788], [123456790], [-71], [-43.858003490436445], [-29.61114685387961], [123456791], [True], [-26.959954047393943], [-36.19806730921029], [False], [123456792], [123456793], [-29.871125367901588], [-29.522652685174876], [-28.83173048562741], [-36.46340914477242], [-21.3952610510801], [-54.31098212859848], [-29.97825041127243], [-69.13149487461008], [-69.25331473635698], [-30.672425597981977], [-70], [-31.492472971818966], [-23.37512371019188], [-26.87584184061303], [-68.8018442158572], [-72], [-68.9582596167829], [-38.639304621786174], [-36.762574512172826], [-29.71114112102485], [-29.147181618179903], [-45.96312293984687], [-62.29011681998471], [-102.18510964864885], [-37.926042220673814], [-21.669838537346024], [-58.62219921432578], [-49.3200214561046], [-20.415110882873073], [-70.16424320159742], [-40.25945493003661], [-70.28083008878951], [-29.42426596564329], [-36.42835541123631], [-68.24706572951847], [-69.41855382525948], [-14.166058474029754], [-62.72457764448362], [-67.51407654646718], [-43.87699809663642], [-20.51986489168823], [-15.085356836638901], [-67.0567942382996], [-19.580182972529585], [-39.15390942077779], [-35.784031914737916], [-60.94797432645206], [-30.593131467080347], [-28.30344245006401], [-29.774227963592523], [88.42189273276318], [123456794], [-31.744787544004495], [-68.40811941759871], [-56.99871844685891], [92.98004923674453], [-29.38824771469962], [-28.112821077251972], [-59.66653455441657], [-28.408958976827417], [-34.246016042728264], [-37.459933039490544], [-69.08278583390873], [-31.39943780262713], [-27.08300242071865], [-32.23443641065063], [-16.35377974137643], [-34.49166282951802], [-80.04075575777426], [-15.990708397802807], [-37.17075988866512], [-12.266024087946377], [-42.995821326318705], [-36.571652101601906], [-36.40347054615233], [-70.43269469508628], [-28.726570985744708], [-14.941982364755784], [-26.521563448513206], [-52.0451679843239], [-41.16822642698813], [-27.427877745731756], [93.65722410276985], [-61.5774096007493], [-32.14674769877757], [-21.464380924877055], [-67.55449156821463], [91.99125730826226]]
results = [True, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_woodall(*inp), exp, 0)
| OK=True
=========================================
Question 0
error_msg: None
=========================================
Question 1
error_msg: None
=========================================
Question 2
error_msg: None
=========================================
Question 3
error_msg: None
=========================================
Question 4
error_msg: python error: No python code block found
=========================================
Question 5
error_msg: None
=========================================
Question 6
error_msg: None
=========================================
Question 7
error_msg: None
=========================================
Question 8
error_msg: None
=========================================
Question 9
error_msg: None
=========================================
Question 10
error_msg: python error: No python code block found
=========================================
Question 11
error_msg: None
=========================================
Question 12
error_msg: None
=========================================
Question 13
error_msg: None
=========================================
Question 14
error_msg: python error: No python code block found
==================== Problem #16 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check if a given number is one less than twice its reverse.
Your answer will be tested on test cases like:
assert check(70) == False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check if a given number is one less than twice its reverse.
Your answer will be tested on test cases like:
assert check(70) == False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check if a given number is one less than twice its reverse.
Your answer will be tested on test cases like:
assert check(70) == False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check if a given number is one less than twice its reverse.
Your answer will be tested on test cases like:
assert check(70) == False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check if a given number is one less than twice its reverse.
Your answer will be tested on test cases like:
assert check(70) == False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called check that takes a number and returns True if it's one less than twice its reverse. Let's think about how to approach this.
First, the problem says the number should be one less than twice its reverse. So, for a given number n, the condition is n = 2 * reverse(n) - 1. Wait, no, wait. Wait, the problem says "one less than twice its reverse". So twice the reverse minus one. So the equation is n == 2 * reversed_n - 1. So, for example, if the reverse of n is r, then check if n equals 2r -1.
So the steps are: take the input number, reverse its digits, compute twice that reversed number minus one, and check if it equals the original number.
But how to reverse the digits? Let's think. For example, if the number is 70, its reverse is 07, but that's 7. Wait, but numbers can't have leading zeros. So when reversing, numbers like 70 would become 7. So, for example, the reverse of 70 is 7. Then 2*7 -1 is 13. 70 is not equal to 13, so the assertion given (assert check(70) == False) would be correct.
So the first step is to reverse the digits of the input number. How to do that in Python?
One way is to convert the number to a string, reverse the string, then convert back to integer. For example, n = 70. str_n = "70", reversed_str = "07", then reversed_num = int(reversed_str) which is 7. That seems correct.
So the function steps would be:
1. Take the input number, say n.
2. Reverse its digits to get reversed_n.
3. Calculate 2 * reversed_n - 1.
4. Check if this equals n. If yes, return True; else, False.
So the function would look something like:
def check(n):
reversed_n = int(str(n)[::-1])
return n == 2 * reversed_n - 1
Wait, but what about numbers with leading zeros after reversing? Well, when you reverse a number like 70, the reversed string is "07", but converting to int automatically removes leading zeros. So that's handled correctly.
Let me test this with the sample input. For n=70:
reversed_n is 7. 2*7-1=13. 70 is not equal to 13, so returns False. Which matches the assertion.
Another test case: Let's think of a number that satisfies the condition. Let's say n=1. Reverse is 1. 2*1-1=1. So 1 equals 1. So check(1) should return True.
Another example: n=3. Reverse is 3. 2*3-1=5. 3 !=5. So returns False.
What about n= 2*reverse(n) -1. Let's think of a number. Suppose reverse(n) is 5. Then n should be 2*5-1=9. So reverse of 9 is 9. 2*9-1=17. So 9 is not equal to 17. So that's not a solution. Hmm. Let's think of another example. Let's say reverse(n) is 3. Then n would be 5. Reverse of 5 is 5. 2*5-1=9. Not equal to 5. So no. Maybe there's no such numbers except for 1?
Wait let's check for n=1. Reverse is 1. 2*1-1=1. So yes. So check(1) returns True.
Another example: Let's think of n= 2*reverse(n) -1. Let's suppose n is 5. Reverse is 5. 2*5-1=9. So 5 is not equal to 9. Not a solution.
What about n= 9? Reverse is 9. 2*9-1=17. Not equal.
What about n= 17? Reverse is 71. 2*71 -1 = 141. 17 != 141.
Hmm. Maybe there are very few numbers that satisfy this condition. But the function needs to check for any given number.
So the code seems straightforward. The function would reverse the number, compute 2*reverse -1, compare with original.
So the code would be:
def check(n):
reversed_n = int(str(n)[::-1])
return n == 2 * reversed_n - 1
But wait, what about numbers with leading zeros when reversed? Well, when you reverse a number like 100, the reversed string is '001', which becomes 1 as an integer. So that's handled correctly.
So the code should work. Let's test with the sample input. For 70, reversed is 7. 2*7-1=13. 70 !=13 → returns False. Correct.
Another test case: check(1) → returns True. check(0)? Let's see. Reverse of 0 is 0. 2*0-1 = -1. 0 is not equal to -1 → returns False.
Another case: n= 2*reverse(n) -1. Suppose n= 3. Reverse is 3. 2*3-1=5. So 3 !=5. No. What about n=5? Reverse is 5. 2*5-1=9. No. So no.
Another example: Let's take n= 2*reverse(n) -1. Let's suppose reverse(n) is 2. Then n would be 3. Reverse of 3 is 3. 2*3-1=5. Not 3. So no.
So the only number that satisfies this condition is 1? Or maybe others?
Let me think of n= 1. Yes. What about n= 2*reverse(n) -1. Let's suppose n= 2*reverse(n) -1. Let's suppose n is 2*reverse(n) -1. Let's suppose n is 2*r -1. And r is the reverse of n.
So for example, let's take n= 2*r -1. And r is reverse(n). Let's try to find such numbers.
Let me try n= 1. r=1. 2*1-1=1 → yes.
Another example: Let's say n= 2*reverse(n) -1. Let's take n= 2*reverse(n) -1. Let's suppose n is 21. Reverse is 12. 2*12-1=23. 21 !=23. No.
What about n= 23? Reverse is 32. 2*32-1=63. 23 !=63.
What about n= 63? Reverse is 36. 2*36-1=71. 63 !=71.
n= 71 → reverse is 17 → 2*17-1=33. Not equal.
n= 33 → reverse is 33 → 2*33-1=65. Not equal.
n= 65 → reverse is 56 → 2*56-1=111. Not equal.
n= 111 → reverse is 111 → 2*111-1=221. Not equal.
Hmm. Maybe there are no other numbers except 1 that satisfy this condition. But regardless, the function needs to check for any given n.
So the code seems correct. So the Python function is as written.
```python
def check(n):
reversed_n = int(str(n)[::-1])
return n == 2 * reversed_n - 1
```
----------------------------------------------
Result: Pred=def check(n):
reversed_n = int(str(n)[::-1])
return n == 2 * reversed_n - 1 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[70], [23], [73], [0], [1], [9], [10], [20], [100], [1000], [11], [22], [33], [44], [55], [66], [77], [88], [99], [12], [21], [34], [43], [56], [65], [78], [87], [90], [8], [999], [45], [102], [42], [103], [79], [64], [41], [54], [72], [71], [13], [76], [98], [2], [86], [40], [57], [39], [7], [89], [63], [46], [53], [67], [38], [101], [80], [74], [15], [91], [37], [35], [24], [32], [75], [19], [14], [104], [3], [82], [6], [25], [1001], [85], [81], [5], [92], [18], [4], [83], [52], [105], [31], [30], [93], [36], [1002], [97], [1003], [95], [26], [1004], [27], [84], [68], [51], [96], [998], [47], [62], [50], [58], [49], [1005], [69], [29], [997], [17], [94], [28], [59], [48], [16], [60], [61], [107], [1006], [106], [996], [108], [1007], [995], [1008], [109], [110]]
results = [False, False, True, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(check(*inp), exp, 0)
| OK=True
==================== Problem #17 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the largest number that can be formed with the given list of digits.
Your answer will be tested on test cases like:
assert find_Max_Num([1,2,3]) == 321
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the largest number that can be formed with the given list of digits.
Your answer will be tested on test cases like:
assert find_Max_Num([1,2,3]) == 321
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the largest number that can be formed with the given list of digits.
Your answer will be tested on test cases like:
assert find_Max_Num([1,2,3]) == 321
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the largest number that can be formed with the given list of digits.
Your answer will be tested on test cases like:
assert find_Max_Num([1,2,3]) == 321
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the largest number that can be formed with the given list of digits.
Your answer will be tested on test cases like:
assert find_Max_Num([1,2,3]) == 321
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called find_Max_Num that takes a list of digits and returns the largest possible number formed by arranging those digits. Let's think about how to approach this.
Hmm, the problem seems straightforward. The largest number would be the digits sorted in descending order. Like, for [1,2,3], sorting descending gives [3,2,1], which combines to 321. So the approach is probably to sort the list in reverse order and then combine the digits into a number.
Wait, but what about leading zeros? Oh, but the problem says the input is a list of digits. If the input includes zeros, like [0,0,1], then the largest number would be 100. So when we sort in descending order, the 1 comes first, then the zeros. So that's handled correctly.
So the steps are: sort the list in descending order, then convert each digit to a string, join them, and convert to an integer. But wait, if the list is empty? Well, the problem probably expects that the input is a non-empty list. The test case given is [1,2,3], which works.
So the function would be something like:
def find_Max_Num(digits):
# sort the digits in descending order
digits_sorted = sorted(digits, reverse=True)
# convert each digit to string, join, then convert to integer
max_num = int(''.join(map(str, digits_sorted)))
return max_num
Wait, but what if the input is [0], then it returns 0, which is correct. Or [0,0], returns 0. So that's handled.
Let me test the sample case. [1,2,3] sorted descending is [3,2,1], joined as '321' → 321. Which matches the test case. So that should work.
So the code should be as above. Let me make sure there are no edge cases I'm missing. Like if the list has a single element, or all zeros. The code should handle those.
So the Python function is as written. Now, I need to present this in a markdown code block as per the instructions.
```python
def find_Max_Num(digits):
digits_sorted = sorted(digits, reverse=True)
max_num = int(''.join(map(str, digits_sorted)))
return max_num
```
----------------------------------------------
Result: Pred=def find_Max_Num(digits):
digits_sorted = sorted(digits, reverse=True)
max_num = int(''.join(map(str, digits_sorted)))
return max_num | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, 2, 3]], [[4, 5, 6, 1]], [[1, 2, 3, 9]], [[9, 3, 2, 1]], [[9, 8, 7, 6, 5, 4, 3, 2, 1]], [[9, 9, 3, 2, 2, 1]], [[9, 9, 3, 2, 2, 1, 1]], [[9, 8, 7, 6, 5, 4, 3, 3, 2, 1]], [[9, 8, 8, 7, 7, 6, 6, 5, 3, 3, 2]], [[9, 3, 3, 2, 1]], [[9, 3, 3, 3, 2, 1]], [[9, 3, 3, 3, 2, 2, 1]], [[9, 8, 7, 6, 5, 4, 3, 2, 2, 1]], [[9, 3, 2, 2, 1]], [[9, 9, 9, 3, 2, 2, 1]], [[9, 4, 3, 2, 1]], [[9, 5, 3, 2, 1]], [[9, 3, 2, 2, 2, 1]], [[9, 9, 9, 3, 2, 2, 1, 1]], [[9, 5, 2, 1]], [[9, 3, 2, 2, 2, 2, 1]], [[9, 9, 3, 3, 3, 2, 2, 1]], [[9, 8, 7, 6, 5, 4, 4, 3, 2, 1]], [[9, 4, 3, 2, 2, 2, 1]], [[9, 9, 9, 3, 2, 2, 1, 1, 1, 1]], [[9, 8, 7, 6, 5, 4, 4, 4, 3, 2, 1]], [[9, 9, 3, 2, 1]], [[9, 9, 3, 2, 2, 2]], [[9, 9, 9, 3, 2, 2, 2]], [[9, 8, 7, 6, 5, 5, 4, 2, 1]], [[9, 5, 5, 2, 1]], [[9, 9, 3, 3, 3, 3, 2, 2, 1]], [[9, 4, 3, 2, 2, 1, 1]], [[9, 4, 3, 3, 2]], [[9, 9, 3, 2, 2, 1, 1, 1]], [[9, 9, 3, 2, 2]], [[9, 8, 7, 6, 5, 4, 3, 3, 1]], [[9, 9, 9, 3, 2, 2]], [[9, 9, 7, 2, 1]], [[9, 4, 4, 3, 2, 1]], [[9, 9, 7, 3, 2, 2]], [[9, 6, 3, 2, 1, 1]], [[9, 3, 3, 3, 2, 1, 1]], [[9, 4, 3, 2, 1, 1]], [[9, 6, 3, 2, 2, 1, 1]], [[8, 7, 7, 6, 5, 4, 3, 2, 2, 1]], [[6, 5, 3, 2, 1, 1]], [[9, 6, 3, 2, 2, 2, 1, 1]], [[9, 9, 3, 3, 3, 3, 2, 2, 1, 1]], [[9, 9, 9, 3, 2, 2, 2, 2]], [[9, 9, 3, 3, 2]], [[9, 5, 3, 2, 2, 1]], [[9, 9, 5, 2, 1]], [[9, 9, 3, 3, 2, 1]], [[9, 5, 2, 2]], [[9, 9, 4, 4, 2, 2, 1]], [[9, 9, 1]], [[9, 3, 3, 2, 2, 2, 1]], [[9, 4, 3, 3, 2, 0]], [[9, 8, 7, 6, 6, 5, 3, 3, 2]], [[9, 5, 5, 2, 1, 1, 1, 1]], [[9, 9, 2, 0]], [[9, 8, 6, 5, 4, 3, 2, 1]], [[6, 5, 3, 2, 2, 1, 1]], [[9, 9, 7, 7, 2, 1]], [[6, 5, 3, 3, 2, 2, 2, 1]], [[9, 3, 3, 2, 2, 1]], [[9, 3, 3, 2, 2, 2, 2, 1]], [[9, 3, 3, 2, 2, 2]], [[9, 9, 9, 3, 2, 2, 1, 1, 1]], [[9, 6, 5, 4, 3, 2, 1]], [[9, 6, 3, 2, 1, 1, 0]], [[9, 8, 7, 6, 5, 4, 4, 3, 3, 2, 1]], [[9, 9, 3, 3, 2, 2, 1, 1, 1]], [[9, 6, 3, 2, 2, 1, 1, 1]], [[9, 8, 7, 6, 5, 4, 4, 3, 2, 1, 1]], [[9, 4, 3, 3, 1, 1]], [[6, 4, 3, 2, 2, 1, 1, 1]], [[9, 5, 4, 3, 2, 2, 1, 1]], [[9, 8, 7, 5, 5, 4, 2, 1]], [[8, 7, 7, 6, 5, 4, 2, 2, 1]], [[9, 9, 3, 3, 2, 2, 1]], [[9, 9, 7, 3, 2, 2, 1, 1]], [[9, 9, 3, 3, 3, 3, 3, 2, 2, 1, 1]], [[9, 6, 3, 1, 1, 0]], [[9, 8, 7, 7, 6, 5, 4, 3, 2, 2, 1]], [[9, 9, 9, 3, 3, 2, 2]], [[9, 5, 5, 2]], [[9, 9, 9, 9, 3, 3, 2, 2, 1, 1, 1]], [[9, 9, 9, 3, 2, 2, 2, 1, 1, 1]], [[9, 8, 7, 6, 5, 4, 3, 3, 3, 2, 1]], [[9, 9, 3, 3, 3, 3, 2, 1, 1]], [[8, 7, 7, 6, 5, 5, 4, 2, 2, 1]], [[9, 9, 3, 3, 2, 2, 1, 1, 1, 1]], [[9, 6, 5, 2, 1]]]
results = [321, 6541, 9321, 9321, 987654321, 993221, 9932211, 9876543321, 98877665332, 93321, 933321, 9333221, 9876543221, 93221, 9993221, 94321, 95321, 932221, 99932211, 9521, 9322221, 99333221, 9876544321, 9432221, 9993221111, 98765444321, 99321, 993222, 9993222, 987655421, 95521, 993333221, 9432211, 94332, 99322111, 99322, 987654331, 999322, 99721, 944321, 997322, 963211, 9333211, 943211, 9632211, 8776543221, 653211, 96322211, 9933332211, 99932222, 99332, 953221, 99521, 993321, 9522, 9944221, 991, 9332221, 943320, 987665332, 95521111, 9920, 98654321, 6532211, 997721, 65332221, 933221, 93322221, 933222, 999322111, 9654321, 9632110, 98765443321, 993322111, 96322111, 98765443211, 943311, 64322111, 95432211, 98755421, 877654221, 9933221, 99732211, 99333332211, 963110, 98776543221, 9993322, 9552, 99993322111, 9993222111, 98765433321, 993333211, 8776554221, 9933221111, 96521]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_Max_Num(*inp), exp, 0)
| OK=True
==================== Problem #18 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given two integers have opposite sign or not.
Your answer will be tested on test cases like:
assert opposite_Signs(1,-2) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given two integers have opposite sign or not.
Your answer will be tested on test cases like:
assert opposite_Signs(1,-2) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given two integers have opposite sign or not.
Your answer will be tested on test cases like:
assert opposite_Signs(1,-2) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given two integers have opposite sign or not.
Your answer will be tested on test cases like:
assert opposite_Signs(1,-2) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given two integers have opposite sign or not.
Your answer will be tested on test cases like:
assert opposite_Signs(1,-2) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called opposite_Signs that checks if two integers have opposite signs. Let's think about how to do this.
Hmm, so if one number is positive and the other is negative, their product should be negative. Because multiplying a positive and a negative gives a negative result. So maybe I can multiply the two numbers and check if the result is negative. But wait, what about zero? Oh, but the problem says integers. Wait, but if either of them is zero, then their product is zero, which is not negative. So in that case, they don't have opposite signs. So the function should return True only when one is positive and the other is negative. So the product being negative would indicate that. Because if a is positive and b is negative, a*b is negative. Similarly if a is negative and b is positive. So the product being less than zero would mean they have opposite signs.
So the approach would be: multiply the two numbers. If the product is less than zero, return True. Else, return False.
Wait, but what if one of them is zero? Like, if a is 0 and b is positive. Then product is zero, which is not less than zero. So the function returns False, which is correct because zero isn't considered as having a sign. So the function would correctly return False in such cases.
So the code can be written as:
def opposite_Signs(a, b):
return (a * b) < 0
Wait, but what about when a or b is zero? Let's test some cases.
Test case 1: opposite_Signs(1, -2) → 1*-2 = -2 <0 → True. Correct.
Test case 2: opposite_Signs(-3, 4) → -12 <0 → True. Correct.
Test case 3: opposite_Signs(0, 5) → 0*5=0 → not less than zero → returns False. Correct.
Test case 4: opposite_Signs(-5, 0) → same as above. Correct.
Test case 5: opposite_Signs(0, 0) → 0 → returns False. Correct.
Another case: opposite_Signs(-3, -4) → product is positive → returns False. Correct.
Yes, this seems to handle all cases.
So the function can be written simply as returning whether the product is negative.
So the code would be straightforward. Now, the user wants the function to be written, and the test case given is assert opposite_Signs(1,-2) == True. Which would pass with this code.
So the Python function is simple. Let me write that.
```python
def opposite_Signs(a, b):
return (a * b) < 0
```
----------------------------------------------
Result: Pred=def opposite_Signs(a, b):
return (a * b) < 0 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[1, -2], [3, 2], [-10, -10], [-2, 2], [1000000000000, -1000000000000], [999999999999, -999999999999], [1000000000, -1000000000], [999999999, -999999999], [987654321, -987654321], [1000000000000, -1000000000], [-1000000000, 999999999], [-987654321, -987654321], [1000000000000, 987654321], [1000000000000, 987654322], [999999999, -1000000000000], [999999999, 999999999], [999999999999, 1000000000000], [-1000000000000, -987654321], [-1000000000000, -1000000000000], [-999999999999, -1000000000000], [987654321, 987654321], [1000000000, 999999999999], [1000000000, -1000000000000], [987654321, 987654322], [-987654319, -987654320], [-999999998, -999999999], [987654321, 1000000000000], [-1000000000, -1000000000], [1000000000000, 1000000000000], [1000000000001, -1000000000000], [1000000000000, -1000000000001], [999999999999, -987654319], [-1000000000, 987654321], [999999999999, 999999999999], [987654322, 987654322], [-987654321, -999999998], [-987654322, -987654321], [999999999, -987654321], [-1000000000000, -987654320], [-987654320, -987654320], [-999999999, -999999999], [-1000000000001, -1000000000000], [-1000000000000, 999999999], [-987654322, -1000000000000], [987654320, -1000000000000], [-987654322, -987654322], [-999999998, -1000000000000], [999999999999, -1000000000], [-987654320, -987654319], [987654321, -1000000000001], [987654321, 987654323], [1000000000000, -987654322], [-987654322, 1000000000000], [1000000000000, -1000000000002], [-1000000000000, 1000000000000], [-999999999999, -999999999999], [-1000000000002, -1000000000000], [1000000000001, -987654321], [-999999999999, -999999999998], [-999999998, -1000000000002], [-987654321, -987654322], [-987654319, -1000000000000], [1000000000000, 999999999999], [-999999998, -1000000000], [999999999999, 987654322], [-1000000000002, -1000000000002], [-1000000000000, 987654323], [1000000000000, 1000000000], [-1000000000000, -987654319], [987654321, -999999999999], [1000000000001, 987654321], [-1000000000000, 987654322], [-987654319, -1000000000002], [-987654319, -1000000000001], [999999999, -999999998], [-999999999, 987654321], [987654321, -987654322], [987654321, 1000000000], [-1000000000001, -1000000000001], [-999999999, -1000000000002], [-1000000000000, 999999998], [1000000000002, -987654319], [1000000000, 987654321], [999999998, -999999998], [-1000000001, 987654321], [999999999999, 1000000000002], [-1000000000003, -987654321], [-987654319, -987654319], [-999999998, -987654321], [-1000000001, -999999999999], [-1000000000004, -1000000000002], [1000000000002, -1000000000001], [-1000000000002, 987654322], [-987654319, -1000000000003], [-1000000000, 987654323], [-1000000000003, 1000000000000], [-1000000000, 999999999999], [-1000000001, -1000000000], [1000000000000, 1000000000001], [-1000000000003, -1000000000000], [1000000000000, -987654319], [987654320, 987654321], [-1000000000001, -1000000000002], [987654322, 987654323], [-999999997, -1000000000], [-987654319, 999999999999], [-999999997, 1000000000000], [-1000000000000, -987654322], [1000000000001, 1000000000002]]
results = [True, False, False, True, True, True, True, True, True, True, True, False, False, False, True, False, False, False, False, False, False, False, True, False, False, False, False, False, False, True, True, True, True, False, False, False, False, True, False, False, False, False, True, False, True, False, False, True, False, True, False, True, True, True, True, False, False, True, False, False, False, False, False, False, False, False, True, False, False, True, False, True, False, False, True, True, True, False, False, False, True, True, False, True, True, False, False, False, False, False, False, True, True, False, True, True, True, False, False, False, True, False, False, False, False, True, True, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(opposite_Signs(*inp), exp, 0)
| OK=True
==================== Problem #19 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth octagonal number.
Your answer will be tested on test cases like:
assert is_octagonal(5) == 65
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth octagonal number.
Your answer will be tested on test cases like:
assert is_octagonal(5) == 65
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth octagonal number.
Your answer will be tested on test cases like:
assert is_octagonal(5) == 65
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth octagonal number.
Your answer will be tested on test cases like:
assert is_octagonal(5) == 65
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth octagonal number.
Your answer will be tested on test cases like:
assert is_octagonal(5) == 65
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to find the nth octagonal number. Let me think about what an octagonal number is. From what I remember, polygonal numbers are a type of figurate numbers. For example, triangular numbers, square numbers, pentagonal, etc. Each of these has a formula based on the number of sides of the polygon.
The formula for the nth octagonal number. Let me recall. The general formula for the k-th polygonal number with m sides is given by something like (m-2)*k*(k-1)/2 + k. Or maybe it's another form. Wait, for example, the square numbers are when m=4. Let me check for m=4, the formula would be (4-2)*k(k-1)/2 +k = 2*k(k-1)/2 +k = k(k-1) +k = k². Which is correct. So that formula seems right.
So for octagonal numbers, m=8. So substituting m=8 into that formula: (8-2)*k*(k-1)/2 +k = 6*k(k-1)/2 +k = 3k(k-1) +k. Let's simplify that: 3k² -3k +k = 3k² -2k. So the formula for the nth octagonal number is 3n² - 2n.
Wait, let me check with an example. Let's see, the first few octagonal numbers. For n=1, 3(1)^2 -2(1) = 3-2=1. That's correct. The first octagonal number is 1. For n=2, 3*4 -4= 12-4=8. Let me check if that's correct. The second octagonal number is 8. Let me see, maybe I can check online. Wait, I can't, but maybe I can think of the pattern. The octagonal numbers are 1, 8, 21, 40, etc. Let me check for n=3: 3*(9) -2*3 = 27-6=21. Yes, that's correct. And for n=4: 3*16 -8=48-8=40. So yes, the formula seems correct.
So the function to compute the nth octagonal number is simply returning 3n² - 2n.
Wait, but the test case given is assert is_octagonal(5) == 65. Let me compute that. For n=5: 3*25 - 10 = 75-10=65. Yes, that matches. So the formula is correct.
So the function is_octagonal(n) should compute 3*n^2 - 2*n.
So the Python function would be straightforward. Let me code that.
Wait, but the problem says to write a function to find the nth octagonal number. So the function name is is_octagonal? Wait, the test case uses is_octagonal(5) == 65. But that's probably a mistake. Wait, the problem says that the function is to find the nth octagonal number. But the test case uses is_octagonal(5) == 65. But the function name is is_octagonal? That seems odd. Wait, perhaps the function is called is_octagonal, but that's a bit confusing. Because the function is supposed to return the nth octagonal number. But the name is_octagonal might be a mistake. Wait, maybe the user made a typo. For example, perhaps the function is called get_octagonal or something else. But according to the test case given, the function is called is_octagonal, but that's probably a mistake. Wait, maybe the problem is that the user wants a function to check if a number is octagonal, but the problem says "find the nth octagonal number". So the test case is perhaps written incorrectly. But according to the problem statement, the user says that the answer will be tested on test cases like assert is_octagonal(5) == 65. So the function is_octagonal is supposed to return the nth octagonal number. So the function name is is_octagonal, but perhaps that's a mistake. But regardless, according to the problem, the function is called is_octagonal. So I need to write a function named is_octagonal that takes n and returns the nth octagonal number.
So the code would be:
def is_octagonal(n):
return 3 * n * n - 2 * n
But wait, maybe the user made a mistake in the function name. However, according to the problem statement, the test case uses is_octagonal(5) == 65, which is correct. So the function name is is_octagonal, but perhaps the name is a mistake. However, the user's problem says to write a function to find the nth octagonal number. So the function name is up to the user. But according to the test case, the function is called is_octagonal. So perhaps the user intended that function name. So I'll proceed with that.
So the Python code would be:
def is_octagonal(n):
return 3 * n**2 - 2 * n
But perhaps the user wants to handle n as an integer. But the function is straightforward. Let me test the sample input. For n=5, 3*25 - 10 = 65. Which matches the test case. So that's correct.
So the code is simple. Now, I need to write this as a self-contained Python function in a markdown code block. The code should be enclosed in ```python ... ```. Also, the user might have other test cases, but according to the problem, the code needs to pass the given test case.
So the final code is:
def is_octagonal(n):
return 3 * n * n - 2 * n
But wait, in Python, n**2 is the same as n*n. So either way is fine. But perhaps using n*n is more efficient, but for code clarity, perhaps n**2 is better. But both are acceptable.
So the code is as above. That's the solution.
```python
def is_octagonal(n):
return 3 * n * n - 2 * n
```
----------------------------------------------
Result: Pred=def is_octagonal(n):
return 3 * n * n - 2 * n | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[5], [10], [15], [100], [99], [98], [96], [101], [97], [102], [22], [True], [23], [103], [104], [21], [95], [105], [20], [7], [9], [8], [6], [4], [106], [24], [19], [11], [94], [25], [3], [26], [93], [12], [108], [92], [42], [41], [43], [107], [2], [1], [13], [14], [38], [39], [53], [37], [52], [18], [54], [91], [55], [51], [50], [40], [90], [89], [56], [17], [76], [109], [110], [111], [27], [16], [44], [57], [88], [77], [58], [75], [28], [113], [112], [87], [59], [78], [70], [71], [69], [86], [72], [45], [47], [46], [49], [29], [60], [36], [30], [85], [48], [73], [84], [114], [31], [35], [34], [79], [83]]
results = [65, 280, 645, 29800, 29205, 28616, 27456, 30401, 28033, 31008, 1408, 1, 1541, 31621, 32240, 1281, 26885, 32865, 1160, 133, 225, 176, 96, 40, 33496, 1680, 1045, 341, 26320, 1825, 21, 1976, 25761, 408, 34776, 25208, 5208, 4961, 5461, 34133, 8, 1, 481, 560, 4256, 4485, 8321, 4033, 8008, 936, 8640, 24661, 8965, 7701, 7400, 4720, 24120, 23585, 9296, 833, 17176, 35425, 36080, 36741, 2133, 736, 5720, 9633, 23056, 17633, 9976, 16725, 2296, 38081, 37408, 22533, 10325, 18096, 14560, 14981, 14145, 22016, 15408, 5985, 6533, 6256, 7105, 2465, 10680, 3816, 2640, 21505, 6816, 15841, 21000, 38760, 2821, 3605, 3400, 18565, 20501]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_octagonal(*inp), exp, 0)
| OK=True
==================== Problem #20 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of substrings with the sum of digits equal to their length.
Your answer will be tested on test cases like:
assert count_Substrings('112112') == 6
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of substrings with the sum of digits equal to their length.
Your answer will be tested on test cases like:
assert count_Substrings('112112') == 6
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of substrings with the sum of digits equal to their length.
Your answer will be tested on test cases like:
assert count_Substrings('112112') == 6
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of substrings with the sum of digits equal to their length.
Your answer will be tested on test cases like:
assert count_Substrings('112112') == 6
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of substrings with the sum of digits equal to their length.
Your answer will be tested on test cases like:
assert count_Substrings('112112') == 6
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called count_Substrings that takes a string of digits and returns the number of substrings where the sum of the digits equals the length of the substring. Let's think about how to approach this.
First, let's understand the problem. For a substring, say, of length n, the sum of its digits must be exactly n. For example, if the substring is "12", the sum is 1+2=3, and the length is 2. So that's not equal. But if the substring is "11", sum is 2, length is 2. That counts.
So the plan is to check all possible substrings of the input string and count those that satisfy the condition.
But how to efficiently check all substrings? The brute-force approach would be to generate all possible substrings, calculate their sum and length, and check if they match. However, for a string of length N, there are O(N^2) substrings. For each substring, calculating the sum could take O(N) time, leading to O(N^3) time complexity. That's probably okay for small strings, but maybe there's a smarter way.
Wait, but for the given example, '112112' returns 6. Let's see what substrings those are. Let me think:
The string is '1','1','2','1','1','2'.
Looking for substrings where sum equals length.
Let's consider each possible substring:
For length 1: the sum must be 1. So each '1' in the string counts. How many '1's are there? Let's see the string: positions 0,1,3,4 are 1s. So 4 substrings here.
Then for length 2: sum should be 2. Let's check each substring of length 2:
Positions 0-1: sum 1+1=2 → yes. Count 1.
Positions 1-2: 1+2=3 → no.
Positions 2-3: 2+1=3 → no.
Positions 3-4: 1+1=2 → yes. Count 2.
Positions 4-5: 1+2=3 → no. So two here.
So total so far is 4+2=6? Wait, but the example says the answer is 6. But maybe there are more substrings of longer lengths.
Wait, maybe there are substrings longer than 2. Let's check for length 3. Sum should be 3.
Check substrings of length 3:
0-2: 1+1+2=4 → no.
1-3: 1+2+1=4 → no.
2-4: 2+1+1=4 → no.
3-5: 1+1+2=4 → no. So none here.
Length 4: sum must be 4.
Check substrings:
0-3: sum 1+1+2+1=5 → no.
1-4: 1+2+1+1=5 → no.
2-5: 2+1+1+2=6 → no. So none.
Length 5: sum must be 5. Let's check:
0-4: sum 1+1+2+1+1=6 → no.
1-5: 1+2+1+1+2=7 → no.
Length 6: sum must be 6. The entire string sum is 1+1+2+1+1+2=8 → no.
So total is 4 (from length 1) + 2 (from length 2) = 6. Which matches the example. So that's correct.
So the brute-force approach would work here. But how to implement it efficiently?
The steps for the function:
Loop through all possible starting indices i from 0 to len(s)-1.
For each i, loop through all possible ending indices j from i to len(s)-1.
For each substring s[i..j], calculate the sum of its digits and check if it equals (j - i + 1) (the length of the substring).
If yes, increment the count.
But calculating the sum each time could be O(n) for each substring, leading to O(n^3) time. However, for small strings, this is acceptable. Let's see, for a string of length 6, the total number of substrings is 6*7/2 = 21. For each substring, summing digits takes up to 6 steps. So 21 * 6 = 126 steps. For longer strings, say 1000 characters, this would be 10^6 * 1000 = 10^9 steps, which is way too slow. But maybe the problem expects the brute-force approach, given the example.
But perhaps there's a way to optimize. Let's think about precomputing prefix sums.
Yes, we can precompute a prefix sum array. Let's say prefix_sum[i] is the sum of the first i digits (with prefix_sum[0] = 0, prefix_sum[1] = s[0], etc.). Then, the sum of digits from index i to j (inclusive) is prefix_sum[j+1] - prefix_sum[i].
So for each substring starting at i and ending at j (0-based), the length is (j - i + 1). The sum is (prefix_sum[j+1] - prefix_sum[i]).
So the condition is:
prefix_sum[j+1] - prefix_sum[i] == (j - i + 1)
Rearranging:
prefix_sum[j+1] - (j+1) == prefix_sum[i] - i
Because:
prefix_sum[j+1] - prefix_sum[i] = (j - i + 1)
=> prefix_sum[j+1] - (j+1) = prefix_sum[i] - i
So for each j, we can compute the value of (prefix_sum[j+1] - (j+1)), and check how many times this value has appeared in the prefix_sum[i] - i for i <= j.
Wait, this seems like a clever approach. Let me think again.
Let me rephrase the equation:
sum of digits from i to j is equal to the length of the substring (which is j - i + 1).
sum_digits = prefix_sum[j+1] - prefix_sum[i]
sum_digits = (j - i + 1)
=> prefix_sum[j+1] - prefix_sum[i] = (j - i + 1)
Rearranged:
prefix_sum[j+1] - (j+1) = prefix_sum[i] - i
Yes. So for each j, we can compute the value of (prefix_sum[j+1] - (j+1)), and check how many times this value has occurred in the prefix_sum[i] - i for i from 0 to j.
So if we can track these values as we iterate through the string, we can compute the count efficiently.
This approach would be O(n) time and space, which is much better than O(n^3).
So the steps would be:
1. Precompute the prefix_sum array. For example, for the string '112112', the digits are [1,1,2,1,1,2]. The prefix_sum array would be [0, 1, 2, 4, 5, 6, 8].
2. For each index j (from 0 to len(s)-1), compute the current value (prefix_sum[j+1] - (j+1)), and check how many times this value has appeared in the prefix_sum[i] - i for i from 0 to j. Each occurrence corresponds to a substring starting at i and ending at j that satisfies the condition.
But how to track the occurrences of (prefix_sum[i] - i) as we go?
We can use a dictionary (hash map) to keep track of the counts of (prefix_sum[i] - i) values as we process each index.
Let's think of the steps:
Initialize a dictionary, say, count_map, which keeps track of how many times each (prefix_sum[i] - i) has occurred. Initially, for i=0, the value is prefix_sum[0] - 0 = 0 - 0 = 0. So count_map starts with {0: 1}.
Then, for each j from 0 to len(s)-1:
- Compute the current prefix_sum[j+1] - (j+1). Let's call this current_val.
- The number of times current_val has appeared in the count_map is the number of substrings ending at j that satisfy the condition. So we add count_map.get(current_val, 0) to the total count.
- Then, we compute the value of (prefix_sum[j+1] - (j+1))? No, wait. Wait, for the next steps, we need to track the (prefix_sum[i] - i) for i up to j. Wait, for each j, after processing, we need to add the (prefix_sum[j+1] - (j+1))? Or wait, the i is from 0 to j, and for each i, the value is prefix_sum[i] - i. So when j is processed, the next step is to add the value for i = j+1? Or wait, perhaps I'm getting confused here.
Wait, the prefix_sum array is of length n+1, where n is the length of the string. For each index in the prefix_sum array, say, k (from 0 to n), the value prefix_sum[k] is the sum of the first k digits. Then, for each k, the value (prefix_sum[k] - k) is the value that we need to track.
So for the current j (the end index of the substring), which is from 0 to n-1, the j+1 is k (from 1 to n). So for each k (from 1 to n), we compute the current_val = prefix_sum[k] - k. Then, we check how many times this current_val has appeared in the previous entries (for k' < k). Because for each previous k' (which corresponds to i in the original problem), if the value of (prefix_sum[k'] - k') equals current_val, then there's a substring from i to k-1 (since k' is the prefix up to i, and k is the prefix up to j+1, so the substring is from i to j).
So the process is:
Initialize count_map with {0: 1} (since for k=0, prefix_sum[0] - 0 = 0).
Initialize total_count = 0.
Then, for each k in 1 to n (where n is the length of the string):
current_val = prefix_sum[k] - k.
Add to total_count the count_map.get(current_val, 0).
Then, we need to add the current (prefix_sum[k] - k) to the count_map? No, wait. Because for the next steps, when we process k+1, the previous entries are for k' up to k. Wait, no. Because for each k, when we process it, we are looking for previous k' (which are 0 to k-1) where prefix_sum[k'] -k' equals current_val. Then, after processing, we need to add the current k's value (prefix_sum[k] -k) to the count_map, so that future k's can refer to it.
Wait, no. Because for the next k, say, k_next, when we compute current_val_next = prefix_sum[k_next] -k_next, we need to check how many times this value has appeared in the prefix_sum[k'] -k' for k' from 0 to k_next-1. So during the iteration for k, after checking, we need to add the current (prefix_sum[k] -k) to the count_map for future steps.
Wait, but the initial count_map has the value for k=0. Then, for k=1, we check how many times current_val (prefix_sum[1] -1) has appeared in the count_map (which includes k=0). Then, we add the value for k=1 to the count_map. Then, for k=2, the count_map includes k=0 and k=1, etc.
Yes. So the steps are:
Initialize count_map with {0:1}.
total_count = 0
prefix_sum[0] = 0.
Then for k from 1 to len(s):
prefix_sum[k] = prefix_sum[k-1] + int(s[k-1])
current_val = prefix_sum[k] - k
total_count += count_map.get(current_val, 0)
then, we add current_val to the count_map (incrementing its count by 1).
Wait, but why? Because for the next steps, when processing k_next, the current_val for k is part of the previous entries.
Yes. So for example, when k is processed, the current_val is the value for prefix_sum[k] -k, which corresponds to i =k (since for the next steps, when we process k_next, the current_val would be for prefix_sum[k_next] -k_next, and the previous entries include k=0,1,...,k.
Wait, no. Because when we process k, the current_val is for the prefix_sum[k] -k. This value is added to the count_map so that when processing future k_next (k_next >k), this value is considered as part of the previous entries.
Yes. So the process is correct.
Let me test this with the example.
Example: '112112' → the digits are [1,1,2,1,1,2]. n=6.
prefix_sum array:
prefix_sum[0] = 0
prefix_sum[1] = 1
prefix_sum[2] = 1+1=2
prefix_sum[3] = 2+2=4
prefix_sum[4] = 4+1=5
prefix_sum[5] = 5+1=6
prefix_sum[6] = 6+2=8.
Now, for each k from 1 to 6:
Initialize count_map = {0:1}, total_count=0.
k=1:
prefix_sum[1] =1. current_val =1 -1=0. count_map has 0:1 → add 1 to total_count (now total is 1). Then add current_val 0 to count_map. Now count_map has 0:2.
Wait, but that's not correct. Because the current_val for k=1 is 0. So when we add it to the count_map, the count_map now has 0:2. But for the next steps, when we process k=2, we check for current_val and see how many times it's in the count_map (which includes previous entries, including k=0 and k=1).
But let's proceed.
k=1: total_count +=1 → total is 1.
k=2:
prefix_sum[2] =2. current_val =2 -2=0. count_map has 0:2 → add 2 to total_count (total becomes 1+2=3). Then add 0 to count_map, now count_map[0] is 3.
k=3:
prefix_sum[3] is 4. current_val =4 -3 =1. Check count_map for 1 → 0. So total remains 3. Then add 1 to count_map → {0:3, 1:1}.
k=4:
prefix_sum[4] =5. current_val =5 -4 =1. count_map has 1:1 → add 1 → total becomes 3+1=4. Then add 1 to count_map → {0:3, 1:2}.
k=5:
prefix_sum[5] =6. current_val =6 -5 =1. count_map has 1:2 → add 2 → total becomes 4+2=6. Then add 1 → count_map[1] becomes 3.
k=6:
prefix_sum[6] =8. current_val =8-6=2. Check count_map for 2 → 0. So total remains 6. Then add 2 to count_map.
So the total is 6, which matches the example. So this approach works.
So the algorithm is correct.
So the steps to implement this are:
1. Precompute the prefix_sum array.
But actually, we can compute the prefix_sum on the fly, without storing the entire array. Because for each k, we can compute prefix_sum[k] as prefix_sum_prev + current digit.
So, for the code:
Initialize prefix_sum = 0 (which is prefix_sum[0]).
Initialize count_map with {0:1}.
total_count = 0.
Then, for each index in the string (from 0 to len(s)-1):
current_digit = int(s[i])
prefix_sum += current_digit
current_val = prefix_sum - (i+1) # since k is i+1 (since for the first iteration, i=0, k=1)
then, check how many times current_val has been in count_map, add to total_count.
then, add current_val to count_map (increment its count by 1).
Wait, let's think:
For each i (from 0 to len(s)-1), the k is i+1. Because for the prefix_sum up to k = i+1, which is the sum of the first i+1 digits (digits 0 to i).
So during iteration, for each i (starting from 0), we compute the prefix_sum (which is prefix_sum_prev + s[i]).
Then, current_val = prefix_sum - (i+1).
So the code can be:
Initialize prefix_sum = 0
count_map = {0:1}
total = 0
for i in range(len(s)):
prefix_sum += int(s[i])
current_val = prefix_sum - (i+1)
total += count_map.get(current_val, 0)
# Now, add the current_val to the count_map for future steps
count_map[current_val] = count_map.get(current_val, 0) + 1
Wait, but why? Because the current_val is for k = i+1. So for the next steps, when processing i+1, the current_val for k = i+1 (which is the current_val here) is added to the count_map, so that when processing future steps, it's considered as part of the previous entries.
Yes. So this approach works.
Let me test with the example.
Example: '112112'
Processing each i from 0 to 5:
Initially, prefix_sum is 0, count_map {0:1}, total=0.
i=0:
prefix_sum +=1 → 1.
current_val =1 - (0+1) = 0.
total += count_map[0] → 1 → total=1
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['112112'], ['111'], ['1101112'], ['12233445566778899'], ['12345678987654321'], ['122338445566778899'], ['1252338445566778899'], ['122338412233344556677889945566778899'], ['12523384345566778899'], ['1252899122338445566778899'], ['1223384455667718899'], ['122334475566778899'], ['1258233843778899'], ['12781899'], ['122338412233334455667788994123456789876543215566778899'], ['122833445566778899'], ['1223318445566779'], ['1228334475566778899'], ['1223384122333344554667788994123456789876543215566778899'], ['122334455667788919'], ['12523383445566778899'], ['12528991223638445566778899'], ['12283344512233844556677188399566778899'], ['412233445566778899'], ['12233125823384377889984455667718899'], ['1122338445566778899252338445566778899'], ['12345678987'], ['1252899122363848899'], ['1223311223344556677889925823384377889984455667718899'], ['12523384345122338445566778899566778899'], ['122331122334455667788992582338437788998445566771881234567898799'], ['1223384122333344556677889941234567898765432155668778899'], ['1223381223344556677889941223333445566778899412345678987654321556677889122833445122338445566771883995667788999'], ['122122338412233334455667788994123456789876543215566778899338445566778899'], ['1252899122363848899122334475566778899'], ['122338412233344556677889945566778899122334475566778899'], ['1229833445566778841223344556677889999'], ['1223384122333445566677889945566778899'], ['122331122334455667798799'], ['412523384345122338445566778899566778899'], ['12233445566778'], ['125233843445122338445566778899566778899'], ['122233445566778899'], ['12233841223334245566677889945566778899'], ['12233112212523384455667788993344556677889925823384377889984455667718812233812233445566778899412233334455667788994123456789876543215566778891228334451223384455667718839956677889991234567898799'], ['12528991223318445566778899'], ['12233445566771272338412233334455667788994123456789876543215566778899'], ['41252338412233812233445566778899412233334455667788994123456789876543215566778891228334451223384455667718839956677889995122338445566778899566778899'], ['12233841223333445546677889941231456789876543215566778899'], ['812582338437788989'], ['12233841223333445546677889941231456788987654321556123456789876778899'], ['122335184455667125289912236384889912233447556677889979'], ['1228334455664778899'], ['812582312233445566778891938437788989'], ['122983341228334451223384455667718839956677889989999'], ['122983341212233841223334455667788994556677889928334451223384455667718839956677889989999'], ['125233843455667758899'], ['12233841223334122338122334455667788994122333344556677889941234567898765432155667788912283344512233844556677188399566778899966778899'], ['1221223384112233112233445566778899258233843778899844556677188992233334455667788994123456789876543215566778899338445566778899'], ['122338412233334455667788994123456789876543215566877899'], ['125233843455566778899'], ['81258233843177888989'], ['156748912233447556677889987'], ['1229833412122338412233314455667788994556677889928334451223384455667718839956677889989999'], ['12125289912233844556677889'], ['1223311223344556677889925823384377889984455667718821234567898799'], ['1223366778899'], ['122334455667712723384122333344556677889122122338411223311223344556677889925823384377889984455667718899223333445566778899412345678987654321556677889933844556677889994123456789876543215566778899'], ['122331256823384377889984455667718899'], ['122338412233344556677889945566778899125233843455667758899122334475566778899'], ['1212528991223455667788'], ['122334455667878899'], ['12523384344512781899122338445566778899566778899'], ['12582338431223384112233841223333445566778899412345678987654321556687788992233334455667788994123456789876543215566877899778899'], ['1125289912236384889925233843445127818919122338445566778899566778899'], ['1252338344556671252338434512233844556677889956677889978899'], ['12125289912677889'], ['12233841223334455666778899455667781223366778899899'], ['122334455667788299'], ['12298334455667784841223344556677889999'], ['122982334455667784841223344556677889999'], ['1567489122334125289912233844556677889947556677889987'], ['1223344556673788919'], ['41252338434512212345678987338445566778899566778899'], ['412523384345122123456789873384455667799'], ['4125233843451221234567898733844512528991223318445566778899566778899566778899'], ['125233893445566778899'], ['1125289912236384455667788992781899'], ['4125237384345122123456789873384455667799'], ['122338412233344556677889945566712233841223333445566778899412345678987654321556677889999'], ['125289912236384455667788899'], ['12283344512233844556612233445566787889966778899'], ['122667878899'], ['1122338445566778899252338'], ['124455667788919'], ['122983312233841223334122338122334455667788994122333344556677889941234567898765432155667788912283344512233844556677188399566778899966778899445566778841223344556677889999'], ['12528991223638445566778889'], ['125233812212233841122331122334455667788992582338437788998445566771889922333344556677889941234567898765432155667788993384455667788994344512233812781899445566778899566778899'], ['1223344556679788919'], ['1252338125233843455667788998899'], ['12233445556673788919'], ['122983341212233841223334455667788994556677889928334451223384455667718839912233844556677188997889989999'], ['12528991223638445566778125233893445566778899899'], ['12223312233112212523384455667788993344556677889925823384377889984455667718812233812233445566778899412233334455667788994123456789876543215566778891228334451223384455667718839956677889991234567898799445566778899'], ['41252399566778899']]
results = [6, 6, 12, 1, 2, 1, 1, 2, 1, 2, 2, 1, 1, 2, 4, 1, 2, 1, 4, 2, 1, 2, 3, 1, 3, 3, 1, 2, 5, 2, 6, 4, 8, 5, 3, 3, 2, 2, 4, 2, 1, 2, 1, 2, 15, 3, 5, 10, 5, 1, 6, 5, 1, 3, 4, 6, 1, 10, 11, 4, 1, 2, 2, 7, 3, 6, 1, 16, 3, 4, 3, 1, 4, 10, 8, 3, 3, 3, 1, 2, 2, 4, 2, 3, 3, 6, 1, 5, 3, 6, 2, 3, 1, 3, 2, 12, 2, 15, 2, 2, 2, 8, 3, 16, 1]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(count_Substrings(*inp), exp, 0)
| OK=False
==================== Problem #21 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find smallest number in a list.
Your answer will be tested on test cases like:
assert smallest_num([10, 20, 1, 45, 99]) == 1
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find smallest number in a list.
Your answer will be tested on test cases like:
assert smallest_num([10, 20, 1, 45, 99]) == 1
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find smallest number in a list.
Your answer will be tested on test cases like:
assert smallest_num([10, 20, 1, 45, 99]) == 1
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find smallest number in a list.
Your answer will be tested on test cases like:
assert smallest_num([10, 20, 1, 45, 99]) == 1
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find smallest number in a list.
Your answer will be tested on test cases like:
assert smallest_num([10, 20, 1, 45, 99]) == 1
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called smallest_num that finds the smallest number in a list. Let's think about how to approach this.
First, the function should take a list of numbers as input. The problem says that the list is provided, so I need to make sure that the function can handle that. The test case given is [10, 20, 1, 45, 99], and the expected output is 1. So the function should return the minimum value in the list.
Wait, the simplest way is to use the built-in min() function in Python. Like, return min(lst). But maybe the problem expects me to implement it manually without using built-in functions? Wait, the problem says "write a python function to find the smallest number in a list." It doesn't specify whether to use built-in functions or not. But the test case is straightforward. Let me check the example.
If I use min(), then for the test case, min([10, 20, 1, 45, 99]) is indeed 1. So the function can be as simple as returning min of the list. But maybe the user wants me to implement the logic manually?
But the problem says "write a function to find the smallest number", which could be done with the built-in function. However, perhaps the user expects a manual approach. Let me think. If the list is empty, but the problem's test case doesn't include that. But the problem's test case has a list with elements.
But the problem says "smallest number in a list"—so assuming that the list is non-empty. So the function can be written as:
def smallest_num(lst):
return min(lst)
But maybe the user wants to see a manual implementation. For example, initializing the smallest as the first element, then iterating through the list and comparing each element.
But the question says "write a python function"—so using the built-in function is acceptable. However, perhaps the test cases are designed to check for that. Let me think. If the user's test case is using assert smallest_num(...) == 1, then using min() would work.
But maybe the user wants to see the manual approach. Let me think. For example, if the list is [5, 3, 1], the function should return 1. So, the steps would be:
Initialize the smallest as the first element. Then loop through each element in the list. For each element, if it's smaller than the current smallest, update the smallest.
So code would be:
def smallest_num(lst):
smallest = lst[0]
for num in lst[1:]:
if num < smallest:
smallest = num
return smallest
But what if the list is empty? Well, the problem's test case doesn't include that. But perhaps the function should handle that? However, the problem's test case doesn't have that, and the user didn't mention handling empty lists. So assuming that the input list is non-empty.
So which approach is better? The problem says "self-contained Python script that solves the problem". Using the built-in function is straightforward and concise. However, maybe the user wants to see the manual implementation. But the problem says "write a function to find the smallest number", which can be done with min().
But perhaps the user is testing if the assistant knows how to implement it without using built-in functions. But the question does not specify that. So, perhaps the answer is to use min().
But maybe the problem expects the manual approach. Let me think. For example, in some coding interviews, they might ask to not use built-in functions. But since the problem says nothing about that, it's safer to use the built-in function.
But let's check the test case. For example, the test case is assert smallest_num([10, 20, 1, 45, 99]) == 1. If the function returns min(lst), then it passes. So the code would be:
def smallest_num(lst):
return min(lst)
But maybe the user wants to see the manual implementation. But the problem says "self-contained Python script", which can include using built-in functions.
But perhaps the user wants the manual approach. Let me think again. The problem says "write a python function to find smallest number in a list." So the answer could be either approach. However, using min() is the most straightforward and efficient way.
But perhaps the user is expecting the manual approach. Let me check the possible scenarios. If the list is [5, 3, 1], then min() returns 1, which is correct. So the function would work.
So, the answer could be either. However, since the problem says "write a function", perhaps the user is expecting the manual approach. But the problem may not specify, so I need to choose.
But the problem says that the answer will be tested on test cases like the given one. So, the code using min() would work. However, maybe the user wants the manual approach. Let me think about possible edge cases. For example, if the list has one element, then the function returns that element. Both approaches would handle that.
So, perhaps the answer is to use min(). So the code is simple. But maybe the user wants to see the manual approach. But since the problem doesn't specify, I can choose either.
But since the problem says "self-contained Python script", and using min() is part of Python's built-in functions, that's acceptable. Therefore, the function can be written as:
def smallest_num(lst):
return min(lst)
But let me think again. The problem might be expecting the manual approach. Let me think about the possible answer. For example, if the user is testing if the assistant can implement the logic without using built-in functions.
But since the problem does not specify that, I think using min() is acceptable. However, perhaps the user wants the manual approach. Let me think about the example.
In the test case, the list is [10, 20, 1, 45, 99], and the function returns 1. Using min() would work.
But perhaps the user is expecting the manual approach. Let me think about writing the code for that.
So, the code would be:
def smallest_num(lst):
smallest = lst[0]
for num in lst[1:]:
if num < smallest:
smallest = num
return smallest
But what if the list is empty? Well, the problem's test case doesn't include that. So assuming the list is non-empty.
So which approach is better? The problem says "smallest number in a list"—so the function is supposed to return that. Both approaches work.
But the problem says "write a function"—so perhaps the answer is to use the built-in function. However, perhaps the user wants to see the manual approach.
But since the problem says "self-contained Python script", and the code is supposed to be in a markdown code block, I think either approach is acceptable. But perhaps the user expects the manual approach. Let me think again.
If the user is testing for the ability to write the function without using built-in functions, then the manual approach is needed. Otherwise, the built-in is better.
But since the problem says "write a function to find the smallest number in a list", and the built-in function does that, then using min() is correct.
But maybe the user wants the manual approach. However, since the problem didn't specify, I think using min() is acceptable.
But to be safe, perhaps the user wants the manual approach. Let me think about the possible answer.
In many programming problems, using the built-in function is acceptable. However, if the problem is to implement the logic, then the manual approach is needed. Since the problem says "write a function to find the smallest number in a list", it's possible that the answer is to use the built-in function. But I'm not sure.
But given that the test case is straightforward, and the code is simple, perhaps the answer is to use min().
So the Python function would be:
def smallest_num(lst):
return min(lst)
But to make sure, perhaps I should write the manual approach. Let me think about the code again.
For example, if the list is [5, 3, 1], the code would start with smallest = 5, then compare 3 < 5 → update to 3. Then compare 1 < 3 → update to 1. Return 1. Correct.
So, the code would work. But which one is better?
The problem says "self-contained Python script", and the code is supposed to be in a markdown code block. The user may not care about the approach, as long as it passes the test case.
So, using min() is the simplest way. So the code would be:
def smallest_num(lst):
return min(lst)
But let's check if the user's test case would work. For the given example, yes.
But maybe the user wants the manual approach. However, since the problem does not specify, I think using min() is correct.
Therefore, the final answer is to write the function using the built-in min function.
```python
def smallest_num(lst):
return min(lst)
```
----------------------------------------------
Result: Pred=def smallest_num(lst):
return min(lst) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[10, 20, 1, 45, 99]], [[1, 2, 3]], [[45, 46, 50, 60]], [[10]], [[10, 10, 10]], [[10, 9, 10]], [[10, 9, 10, 9]], [[10, 10, 10, 10]], [[10, 9, 10, 10]], [[10, 10]], [[10, 10, 10, 9]], [[10, 10, 10, 9, 10]], [[10, 9, 10, 10, 10]], [[9, 10]], [[10, 9, 9, 10]], [[10, 10, 10, 10, 9]], [[10, 10, 10, 9, 10, 10]], [[9, 10, 10, 10, 10]], [[10, 9, 9]], [[10, 10, 9, 10, 9]], [[9, 10, 10]], [[11, 10, 9, 10, 9, 10]], [[10, 9, 10, 9, 9]], [[11, 10, 10]], [[9, 9, 10, 10]], [[10, 11, 10, 9]], [[10, 9, 9, 10, 9]], [[11, 10, 9, 10, 10, 10, 10, 10]], [[9, 10, 10, 9, 10]], [[9, 10, 10, 10, 9, 10, 10]], [[10, 9, 9, 9]], [[9, 10, 10, 10]], [[11, 10, 10, 9]], [[10, 10, 9, 10]], [[9, 9, 10]], [[9, 10, 9, 9, 10]], [[11, 11, 10, 10, 9]], [[10, 10, 8, 10, 9, 10]], [[8, 9, 10, 10, 9]], [[8, 10, 10]], [[10, 9, 8, 9, 10, 9]], [[8, 10]], [[10, 9, 9, 10, 9, 10]], [[11, 10, 10, 8, 9]], [[11, 11, 10, 10, 10, 9]], [[11, 11, 10, 10, 9, 10]], [[10, 10, 10, 11, 10, 10]], [[11]], [[12, 8, 11, 10]], [[10, 9, 10, 8, 10]], [[10, 10, 8, 10, 9, 10, 10]], [[9, 10, 9, 9, 10, 9, 9]], [[10, 9, 8, 9, 10]], [[11, 11, 10, 10, 10, 10]], [[9, 10, 10, 9, 8, 10]], [[8, 10, 9]], [[7, 8, 10]], [[8]], [[10, 10, 10, 8, 10, 9, 10, 10]], [[11, 10, 10, 10, 8, 10, 9, 10, 10]], [[11, 10, 10, 8]], [[11, 11, 10, 10, 11, 10, 9]], [[11, 11, 10, 10, 11, 10, 8]], [[10, 9, 8, 10]], [[10, 7, 9, 10]], [[11, 10, 10, 11, 9]], [[10, 10, 10, 11, 9, 10]], [[9, 10, 9, 9, 9, 10, 8, 9]], [[9, 10, 9, 9]], [[9, 10, 10, 9]], [[11, 8, 10, 10]], [[9, 10, 9, 8, 9, 10, 9]], [[11, 9, 10, 9, 10, 10, 9, 10]], [[11, 10, 10, 10, 8, 10, 11, 9, 10, 10]], [[11, 9, 9]], [[9, 9, 9, 10, 10, 9]], [[11, 9, 10, 10, 10, 9]], [[11, 10, 10, 11, 9, 10]], [[10, 10, 11, 10, 10]], [[9, 12, 10]], [[10, 9, 10, 10, 9]], [[11, 8, 10, 11, 10]], [[11, 10, 8, 9, 10]], [[12, 12, 8, 11, 10]], [[11, 10, 10, 10, 8, 10, 11, 8, 9, 10, 10, 10]], [[10, 9, 10, 9, 10]], [[11, 10, 7, 8]], [[7, 9, 10, 9, 10, 9, 10]], [[9, 10, 10, 10, 9, 10]], [[10, 10, 10, 9, 10, 10, 10, 10]], [[9, 10, 9, 9, 10, 9, 9, 10]], [[11, 11, 10, 10, 9, 9]], [[11, 9, 10]], [[9, 11, 9, 9, 10, 9, 9]], [[11, 11, 10, 10, 11, 10, 10]], [[10, 9, 9, 8, 9]], [[10, 9, 10, 10, 10, 10, 10]], [[11, 10, 9]], [[12, 12, 8, 11, 10, 12]], [[10, 9, 8, 9, 11, 10]], [[10, 7, 9]], [[10, 12, 9, 10, 9]], [[-115.40386094393058, 13.801990543244983, -90.4732800288427, -75.81228356592653]], [[7, 7, 8, 10]]]
results = [1, 1, 45, 10, 10, 9, 9, 10, 9, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 8, 8, 8, 8, 8, 9, 8, 9, 9, 10, 11, 8, 8, 8, 9, 8, 10, 8, 8, 7, 8, 8, 8, 8, 9, 8, 8, 7, 9, 9, 8, 9, 9, 8, 8, 9, 8, 9, 9, 9, 9, 10, 9, 9, 8, 8, 8, 8, 9, 7, 7, 9, 9, 9, 9, 9, 9, 10, 8, 9, 9, 8, 8, 7, 9, -115.40386094393058, 7]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(smallest_num(*inp), exp, 0)
| OK=True
==================== Problem #22 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between available pairs in the given tuple list.
Your answer will be tested on test cases like:
assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between available pairs in the given tuple list.
Your answer will be tested on test cases like:
assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between available pairs in the given tuple list.
Your answer will be tested on test cases like:
assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between available pairs in the given tuple list.
Your answer will be tested on test cases like:
assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between available pairs in the given tuple list.
Your answer will be tested on test cases like:
assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Problem Analysis:
Okay, I need to write a Python function called max_difference that takes a list of tuples and returns the maximum difference between available pairs. Let me think about the example given. The test case is assert max_difference([(3, 5), (1, 7), (10, 3), (1, 2)]) == 7. Let's see why that's the case.
Looking at the tuples, each has two elements. The problem says "available pairs"—so I guess for each tuple, we can take the difference between the two elements. Then find the maximum of all those differences.
Wait, for each pair (a, b) in the list, compute the absolute difference? Or just the difference? Let's check the example.
In the sample input:
(3,5): 5-3=2
(1,7): 7-1=6
(10,3): 10-3=7
(1,2): 2-1=1
The maximum is 7, which matches the test case. So the function is supposed to calculate the difference between the two elements of each tuple (probably subtracting the first from the second?), then find the maximum among those differences.
Wait, but what if the tuples are in a different order? Like if a tuple is (5,3), then 5-3 is 2. But if the tuple is (3,5), then 5-3 is 2 as well. So maybe the order doesn't matter. But the problem says "available pairs"—maybe the pairs are ordered, and the difference is second minus first. Because in the example, (10,3) gives 7, which is 10-3. So the difference is computed as second element minus first element. But if the tuple was (3,10), then it would be 7 as well. So regardless of the order, the absolute difference would be the same. But the problem says "maximum difference between available pairs"—maybe the problem is to compute the maximum of (second - first) for each tuple. But in that case, if a tuple has (5,3), then the difference would be -2, which would not contribute to the maximum. But the sample input's tuples all have the second element larger than the first. So perhaps the function is supposed to compute the maximum of (second - first) across all tuples.
But then, in that case, the sample input's maximum is 7, which comes from (10,3) where 10-3 is 7. So that's the maximum. So the function is to compute for each tuple the difference (second element minus first), and then take the maximum of those values.
But wait, what if a tuple has the first element larger than the second? For example, (5,3) would give 3-5 = -2. But if that's the case, then the maximum difference would be the maximum of all such differences. But if the problem is to find the maximum possible difference between any two elements in the list of tuples, perhaps considering all possible pairs across tuples, then the approach would be different. However, the sample test case seems to indicate that each tuple is considered as a pair, and the difference is calculated per tuple.
The problem statement says: "find the maximum difference between available pairs in the given tuple list." So the available pairs are the tuples in the list. So each tuple is a pair, and for each pair, compute the difference between the two elements. Then find the maximum among these differences.
So for each tuple (a, b), compute b - a, then take the maximum of all those values.
So the approach is:
- Iterate over each tuple in the list.
- For each tuple, compute the difference between the second element and the first.
- Collect all these differences.
- Return the maximum value among them.
But let me check the sample input again. The tuples are (3,5) → 5-3=2; (1,7) → 6; (10,3) →7; (1,2) →1. The maximum is 7. Which matches the sample output. So that's correct.
So the function can be implemented as follows:
def max_difference(tuples_list):
max_diff = float('-inf')
for a, b in tuples_list:
diff = b - a
if diff > max_diff:
max_diff = diff
return max_diff
But wait, what if the list is empty? Well, the problem says that the input is a list of tuples, and the test case has a non-empty list. So perhaps we can assume that the input is non-empty. But in Python, if the list is empty, this code would return -inf, which is not a valid integer. However, the problem's test cases may not include such cases. So perhaps the code is acceptable.
But the problem says that the function is to be tested on test cases like the one given. So the code should handle that.
So the code would be:
def max_difference(tuples_list):
return max(b - a for a, b in tuples_list)
Wait, that's even simpler. For example, the sample input would generate the list [2,6,7,1], and the max is 7. So that's correct.
But what if the tuples have more than two elements? Well, the problem says that the input is a list of tuples, and each tuple is a pair. So the code assumes that each tuple has exactly two elements. So the code will work as long as each tuple is of length 2.
So the function can be written as a one-liner using a generator expression.
But perhaps the problem expects that. So the code would be:
def max_difference(tuples_list):
return max(b - a for a, b in tuples_list)
But let me test the sample input. The sample input is [(3,5), (1,7), (10,3), (1,2)]. The generator expression would compute 5-3=2, 7-1=6, 3-10=-7, 2-1=1. Wait, wait! Wait, the third tuple is (10,3), so a is 10, b is 3. So b - a is 3 - 10 = -7. But in the sample test case, the expected output is 7. Oh, that's a problem. Wait, this suggests that the code as written would return 6 as the maximum, but the sample expects 7. So there's a mistake here.
Wait, this is a critical error. What's happening here?
In the sample input, the third tuple is (10,3). So according to the code, the difference is 3 - 10 = -7. But the sample expects that this tuple contributes a difference of 7. So this indicates that the code is wrong.
So why is the sample expecting 7? Because the difference between 10 and 3 is 7. But according to the code, it's computing b - a, which would be 3 - 10 = -7. So the code would return the maximum of 2,6,-7,1 → which is 6. But the sample expects 7. So there's a contradiction here.
This suggests that my initial understanding of the problem is wrong. So what's the correct way to interpret the problem?
The problem says: find the maximum difference between available pairs in the given tuple list.
Wait, perhaps the problem is not to compute the difference between the two elements of each tuple, but to find the maximum difference between any two elements in the entire list of tuples. For example, considering all elements in all tuples, find the maximum difference between any two elements. But that would be different.
But the sample input is [(3,5), (1,7), (10,3), (1,2)]. All elements are 3,5,1,7,10,3,1,2. The maximum element is 10, the minimum is 1. So the maximum difference would be 10 - 1 = 9. But the sample expects 7. So that's not matching.
Alternatively, perhaps the problem is to find the maximum difference between pairs of elements from different tuples. But that's unclear.
Alternatively, perhaps the problem is to find the maximum difference between the first elements of the tuples and the second elements of the tuples. For example, for each tuple, take the first element and the second element, and find the maximum difference between any two elements in the list. But again, not sure.
Wait, the sample expects the output to be 7. Let's think: in the sample input, the tuple (10,3) has elements 10 and 3. The difference between them is 7. But according to the code that computes b - a, that's 3 - 10 = -7. But the sample expects that this tuple contributes a difference of 7. So perhaps the problem is to compute the absolute difference between the two elements of each tuple, and then take the maximum of those absolute differences.
In that case, for the tuple (10,3), the absolute difference is 7. For (3,5) it's 2, etc. Then the maximum is 7. Which matches the sample.
So the problem is to compute the maximum absolute difference between the two elements of each tuple.
So the correct approach is, for each tuple, compute the absolute value of (a - b), then take the maximum of those values.
So in the sample input, the absolute differences are 2,6,7,1 → maximum is 7. Which matches the sample.
So the code should be:
def max_difference(tuples_list):
return max(abs(a - b) for a, b in tuples_list)
But then, for the tuple (10,3), a is 10, b is 3. So a - b is 7, absolute value is 7.
Yes. So the code would return 7 for the sample input.
So the original mistake was assuming that the difference was (b - a), but the correct approach is to take the absolute difference between the two elements of each tuple.
So the code needs to compute the absolute difference between the two elements of each tuple, then find the maximum of those.
Thus, the correct function is as above.
So the code would be:
def max_difference(tuples_list):
return max(abs(a - b) for a, b in tuples_list)
But let me test this with the sample input. The tuples are:
(3,5): 5-3=2 → abs is 2.
(1,7): 6 → abs 6.
(10,3): 7 → abs 7.
(1,2): 1 → abs 1.
Maximum is 7. Correct.
So this code would work.
But why did the problem's sample test case have (10,3) as a tuple? Because the absolute difference is 7, which is the maximum.
So the correct code is to compute the absolute difference between the two elements of each tuple, and return the maximum of those.
So the code is as written.
But then, what if the tuples have more than two elements? Well, the problem says that the input is a list of tuples. Assuming that each tuple has exactly two elements, which is the case in the sample.
So the code is correct.
So the final code would be:
def max_difference(tuples_list):
return max(abs(a - b) for a, b in tuples_list)
But wait, the problem's test case uses the tuple (10,3), which would have a difference of 7. So the code returns that, which is correct.
Thus, this is the correct solution.
```python
def max_difference(tuples_list):
return max(abs(a - b) for a, b in tuples_list)
```
----------------------------------------------
Result: Pred=def max_difference(tuples_list):
return max(abs(a - b) for a, b in tuples_list) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[(3, 5), (1, 7), (10, 3), (1, 2)]], [[(4, 6), (2, 17), (9, 13), (11, 12)]], [[(12, 35), (21, 27), (13, 23), (41, 22)]], [[(1000000, 999999), (10000000, 9999999), (100000000, 99999999), (1000000000, 999999999)]], [[(1, 2), (4, 5), (7, 8), (10, 11)]], [[(100, -100), (0, 200), (-50, 50), (300, 100)]], [[(0, 1), (2, 4), (3, 6), (5, 7)]], [[(-10, -5), (-3, 0), (2, 6), (9, 15)]], [[(1, 1000), (500, 700), (300, 900), (200, 800)]], [[(-3, -2), (-8, -7), (-5, -1), (-10, -9)]], [[(50000000, 100000000), (60000000, 110000000), (70000000, 120000000), (80000000, 130000000)]], [[(-10, 10), (-100, 100), (0, 1000), (-1000, 500)]], [[(100, -50), (-200, 200), (300, -300), (-400, 400)]], [[(1000000, -1000000), (999999, -999999), (-100000000, 100000000), (-5000000, 5000000)]], [[(1, -1), (100, -100), (1000, -1000), (10000, -10000)]], [[(0, -100), (100, -200), (1000, -300), (10000, -400)]], [[(1, 1), (2, 2), (3, 3), (4, 4)]], [[(5, 10), (15, 20), (25, 30), (35, 40)]], [[(100, 100), (200, 200), (300, 300), (400, 400)]], [[(500, 600), (700, 800), (900, 1000), (1100, 1200)]], [[(1000, 900), (800, 700), (600, 500), (400, 300)]], [[(10, 20), (30, 40), (50, 60), (70, 80)]], [[(101, 105), (200, 210), (300, 320), (400, 420)]], [[(1000, 1001), (2000, 2004), (3000, 3010), (4000, 4005)]], [[(500, 600), (700, 800), (1100, 1200)]], [[(999999, -999999), (70, 100000000), (-5000000, 5000000)]], [[(-10, -5), (-3, 0), (9, 15)]], [[(1, -1), (100, -100), (10000, -10000)]], [[(-10, -5), (-3, 70), (-3, 0), (-3, 0)]], [[(100, -100), (7, 200), (-50, 50), (300, 100)]], [[(100, -100), (0, 200), (-50, 50), (300, 100), (100, -100)]], [[(1, -1), (100, -100), (1000, -1000), (30, -1), (10000, -10000)]], [[(1000, 15), (-10, -5), (-3, 0), (2, 6), (9, 15)]], [[(0, -100), (100, -200), (1000, -300), (10000, -400), (10000, -400)]], [[(-200, 200), (100, -50), (-200, 200), (300, -300), (-400, 400), (100, -50)]], [[(-10, -5), (9, 15)]], [[(-10, -5), (2, 6), (9, 15)]], [[(-10, 5000000), (-3, 0), (2, 6), (9, 15)]], [[(999999, -999999), (999999, -999999), (70, 100000000), (-5000000, 5000000)]], [[(5, 10), (15, 20), (25, 30), (35, 40), (5, 10)]], [[(500, 600), (500, 80), (700, 800), (1100, 1200)]], [[(1, 2), (4, 5), (7, 8), (10, 11), (10, 11)]], [[(100, -50), (-200, 200), (300, -100000000), (-400, 400)]], [[(-300, -1), (100, -100), (10000, -10000)]], [[(-10, -5), (-3, 70), (-3, 0), (-3, 0), (-3, 0)]], [[(101, 105), (300, 320), (400, 420)]], [[(10, 20), (30, 40), (50, 60), (70, 80), (30, 40)]], [[(100, 100), (200, 200), (300, 300), (300, 300), (400, 400)]], [[(100, -100), (7, 200), (-50, 50), (300, 100), (100, -100)]], [[(100, -50), (-200, 200), (300, -100000000), (-400, 400), (300, -100000000)]], [[(1, 2), (4, 5), (7, 9), (10, 11)]], [[(-10, -5), (2, 6), (3010, 15), (9, 15)]], [[(300, 320), (400, 420)]], [[(-3, -2), (-8, -7), (-5, -1), (-8, -7), (-5, -1)]], [[(1, -1), (10000, 4), (100, -100), (30, -1), (10000, -10000)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400)]], [[(2000, 2004), (2004, 2004), (3000, 3010), (4000, 4005)]], [[(100, 100), (200, 200), (400, 400)]], [[(50000000, 100000000), (70000000, 120000000), (80000000, 130000000)]], [[(1, 2), (4, 5), (10, 11), (4, 5)]], [[(1000, 900), (400, 100000000), (800, 700), (600, 500), (400, 300)]], [[(0, 1), (2, 4), (3, 6), (5, 7), (5, 7)]], [[(-10, 5000000), (-3, 0), (2, 6)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400), (200, 200)]], [[(4005, 100000000), (999999, -999999), (70, 100000000), (-5000000, 5000000)]], [[(1000, 15), (-10, -5), (2, 6), (9, 15)]], [[(999999, -999999), (69, 100000000), (-5000000, 5000000)]], [[(100, -100), (7, 200), (-50, 50), (300, 100), (100, -100), (100, -100)]], [[(4, 9), (1, 1), (2, 2), (3, 3), (4, 4)]], [[(999999, 1000), (70, 100000000), (-5000000, 5000000)]], [[(50000000, 100000000), (60000000, 110000000), (70000000, 120000000), (80000000, 130000000), (50000000, 100000000)]], [[(10, 20), (30, 40), (50, 60), (1, 80)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400), (-3, 100), (200, 200)]], [[(100, 100), (300, 300), (400, 400)]], [[(500, 600), (700, 800), (900, 1000), (1100, 1200), (500, 600)]], [[(0, -100), (100, -200), (1000, -300), (10000, -400), (0, -100)]], [[(4, 5), (7, 8), (10, 11)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400), (100, 100)]], [[(100, -100), (7, 200), (-50, 50), (300, 100), (7, 200)]], [[(2000, 2004), (2004, 2004), (3000, 3010), (4000, 4005), (2004, 2004)]], [[(15, 20), (35, 40)]], [[(-10, 5000000), (-3, 0), (2, 6), (2, 6), (2, 6)]], [[(1000, 1001), (2000, 2004), (3000, 3010), (4000, 4005), (4000, 4005)]], [[(4, 9), (1, 1), (2, 2), (3, 3), (4, 4), (4, 4), (3, 3)]], [[(1, 1000), (500, 700), (300, 900), (200, 800), (300, 900)]], [[(500, 600), (500, 80), (700, 800), (1100, -8)]], [[(-8, -7), (-8, -7), (-5, -1)]], [[(1, -1), (10000, 4), (100, -100), (30, -1), (10000, -10000), (10000, -10000)]], [[(4, 9), (1, 1), (2, 2), (3, 3), (4, 4), (4, 4), (3, 3), (1, 1)]], [[(200, 200), (300, 300), (400, 400), (400, 400), (400, 400), (400, 400)]], [[(1000000, -1000000), (999999, -999999), (-100000000, 100000000)]], [[(1, 1), (3, 3), (4, 4), (3, 3)]], [[(500, 600), (700, 800), (900, 1000), (1100, 1200), (700, 800), (500, 600)]], [[(-10, 10), (-100, 100), (0, 1000), (-1000, 500), (-100, 100)]], [[(100, 15), (100, -100), (-50, 50), (300, 100), (100, -100), (-50, 50)]], [[(4, 9), (1, 1), (2, 2), (3, 3), (4, 4), (4, 4), (3, 3), (1, 1), (1, 1), (4, 4)]], [[(7, 8), (10, 11)]], [[(10, 20), (30, 40), (50, 60), (70, 80), (50, 60)]], [[(1000, 900), (400, 100000000), (800, 700), (400, 300)]], [[(1000, 15), (-10, -5), (-3, 0), (9, 15)]], [[(500, 600), (700, 800), (900, 1000), (1100, 1200), (700, 800), (500, 600), (900, 1000)]], [[(1, 2), (4, 5), (7, 9), (10, 11), (10, 11)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400), (-3, 100), (200, 200), (200, 200)]], [[(-201, 200), (100, -50), (-200, 200), (300, -300), (-400, 400), (100, -50), (100, -50)]], [[(3, 6), (1000, 15), (-10, -5), (2, 6), (9, 15)]], [[(-10, -5), (2, 6), (3010, 15), (9, 15), (-10, -5)]], [[(50000000, 100000000), (60000000, 110000000), (70000000, 120000000), (80000000, 130000000), (50000000, 100000000), (50000000, 100000000)]], [[(4, 9), (1, 1), (2, 2), (4, 4), (4, 4), (3, 3), (4, 4), (1, 1)]], [[(50000000, 100000000), (60000000, 110000000), (80000000, 130000000)]], [[(1, 1), (3, 3), (4, 4), (3, 3), (4, 4)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (100, 100), (300, 300), (400, 400)]], [[(4, 5), (7, 8), (10, 11), (4, 5)]], [[(1000000, -1000000), (999999, -999999), (-100000000, 100000000), (-300, 5000000)]], [[(1000000, -1000000), (999999, -999999), (-100000000, 100000000), (-5000000, 5000000), (-100000000, 100000000)]], [[(4, 9), (1, 1), (2, 2), (3, 3), (4, 4), (1, 1)]], [[(1000, -7), (-3, -2), (-8, -7), (-5, -1), (-8, -7), (-5, -1)]], [[(200, 200), (300, 300), (400, 400), (100, 100), (300, 300), (400, 400)]], [[(1000000, 999999), (10000000, 9999999), (100000000, 99999999)]], [[(1, -1), (10000, 4), (10000, 3), (100, -100), (30, -1), (10000, -10000), (10000, -10000)]], [[(1000000, -1000000), (999999, -999999), (-100000000, 100000000), (999999, -999999)]], [[(99, -50), (-200, 200), (300, -100000000), (-400, 400)]], [[(1, -1), (10000, 4), (100, -100), (10000, -10000), (10000, -10000)]], [[(100, -100), (300, 100)]], [[(100, 100), (200, 200), (300, 300), (400, 400), (400, 400), (100, 100), (300, 300)]]]
results = [7, 15, 23, 1, 1, 200, 3, 6, 999, 4, 50000000, 1500, 800, 200000000, 20000, 10400, 0, 5, 0, 100, 100, 10, 20, 10, 100, 99999930, 6, 20000, 73, 200, 200, 20000, 985, 10400, 800, 6, 6, 5000010, 99999930, 5, 420, 1, 100000300, 20000, 73, 20, 10, 0, 200, 100000300, 2, 2995, 20, 4, 20000, 0, 10, 0, 50000000, 1, 99999600, 3, 5000010, 0, 99999930, 985, 99999931, 200, 5, 99999930, 50000000, 79, 103, 0, 100, 10400, 1, 0, 200, 10, 5, 5000010, 10, 5, 999, 1108, 4, 20000, 5, 0, 200000000, 0, 100, 1500, 200, 5, 1, 10, 99999600, 985, 100, 2, 103, 800, 985, 2995, 50000000, 5, 50000000, 0, 0, 1, 200000000, 200000000, 5, 1007, 0, 1, 20000, 200000000, 100000300, 20000, 200, 0]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(max_difference(*inp), exp, 0)
| OK=True
==================== Problem #23 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of tuples using the second value of each tuple.
Your answer will be tested on test cases like:
assert subject_marks([('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)])==[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of tuples using the second value of each tuple.
Your answer will be tested on test cases like:
assert subject_marks([('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)])==[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of tuples using the second value of each tuple.
Your answer will be tested on test cases like:
assert subject_marks([('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)])==[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of tuples using the second value of each tuple.
Your answer will be tested on test cases like:
assert subject_marks([('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)])==[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of tuples using the second value of each tuple.
Your answer will be tested on test cases like:
assert subject_marks([('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)])==[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called subject_marks that sorts a list of tuples based on the second value of each tuple. Let me think about how to approach this.
So, the input is a list of tuples like [('English', 88), ...], and the output should be sorted by the second element, which is the mark. The example given shows that the sorted list starts with the lowest mark. Wait, in the test case, the output is [('Social sciences', 82), ...], which is sorted in ascending order. So the function needs to sort the list in ascending order based on the second element of the tuples.
How to sort tuples in Python? Oh right, the sorted() function can take a key parameter. For each tuple, the key would be the second element. So the key function would be something like lambda x: x[1].
Wait, but the default sort is ascending. So using sorted with the key as the second element should work. Let me test this logic with the example.
Original list: [('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)]
When sorted by the second element, the order should be 82, 88, 90, 97. So the sorted list would be [('Social sciences',82), ('English',88), ('Science',90), ('Maths',97)], which matches the test case.
So the function subject_marks should take the list and return the sorted list using the second element as the key.
So the code would be:
def subject_marks(lst):
return sorted(lst, key=lambda x: x[1])
Wait, but what if there are tuples with the same second value? Well, the problem doesn't mention handling that, so the default behavior of sorted (stable sort) should be okay.
Let me check the test case. The sample input when passed to this function would be sorted correctly. So the code seems right.
But wait, the problem says that the function should be called subject_marks and return the sorted list. So the code should be written as a function.
So putting it all together, the Python code would be:
def subject_marks(lst):
return sorted(lst, key=lambda x: x[1])
But wait, the test case uses == to compare the output. So the function must return a list sorted in ascending order based on the second element. Yes, this code should work.
Let me test with the sample input. The input list is [('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)]. When sorted by the second element, the order is 82, 88, 90, 97. So the output is as expected.
I think that's all. The code is straightforward.
```python
def subject_marks(lst):
return sorted(lst, key=lambda x: x[1])
```
----------------------------------------------
Result: Pred=def subject_marks(lst):
return sorted(lst, key=lambda x: x[1]) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[('English', 88), ('Science', 90), ('Maths', 97), ('Social sciences', 82)]], [[('Telugu', 49), ('Hindhi', 54), ('Social', 33)]], [[('Physics', 96), ('Chemistry', 97), ('Biology', 45)]], [[]], [[('English', 88)]], [[('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91)]], [[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 90)]], [[('Maths', 82), ('Social sciences', 82), ('English', 88), ('Science', 90), ('Computer Science', 90)]], [[('Biology', 45), ('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)]], [[('Physics', 90), ('Chemistry', 90), ('Biology', 90)]], [[('Physics', -76), ('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('Chemistry', 92)]], [[('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)]], [[('Chemistry', 68), ('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Maths', 84), ('Social sciences', 86), ('Computer Science', 88)]], [[('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)]], [[('Chemistry', -9), ('Physics', -3), ('Geography', 65), ('History', 73), ('Biology', 77), ('English', 81), ('Science', 82), ('Computer Science', 88), ('Maths', 94)]], [[('Computer Science', 75), ('English', 77), ('Physics', 78), ('Economics', 79), ('Chemistry', 80), ('Maths', 80), ('Science', 84), ('Geography', 85), ('Biology', 88), ('History', 92)]], [[('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96), ('Maths', 98)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Chemistry', 92)]], [[('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Social sciences', 86), ('Computer Science', 88)]], [[('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Maths', 96)]], [[('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('Chemistry', 92)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91), ('English', 95)]], [[('Geography', 70), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85, 85), ('Science', 88), ('Computer Science', 91)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Maths', 96)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Maths', 96), ('Physics', 96)]], [[('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Chemistry', 94), ('English', 95), ('Physics', 98)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Physics', 93)]], [[('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97), ('Maths', 97)]], [[('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)]], [[('Social sciences', 82), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Physics', 98)]], [[('Social sciences', 82), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90), ('Science', 92)]], [[('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)]], [[('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)]], [[('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85, 85), ('Computer Science', 91)]], [[('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Maths', 97), ('Maths', 97)]], [[('Maths', 82), ('Social sciences', 82), ('Science', 90), ('Computer Science', 90)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('ChemistrMathasy', 92), ('Chemistry', 92)]], [[('Social sciences', 82), ('English', 88), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Physics', -76), ('Computer Science', 82), ('Maths', 85), ('Chemistry', 92)]], [[('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Physics', 93), ('Maths', 96)]], [[('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Chemistry', 92), ('Chemistry', 92)]], [[('Chemistry', -9), ('Physics', -3), ('Geography', 65), ('History', 73), ('Biology', 77), ('Biology', 77), ('English', 81), ('Computer Science', 88), ('Maths', 94)]], [[('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91), ('English', 95)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Maths', 92), ('Physics', 93), ('Maths', 96)]], [[('Geography', 78), ('Biology', 81, 'Biology'), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Maths', 92), ('Physics', 93), ('Maths', 96)]], [[('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)]], [[('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)]], [[('English', 87), ('English', 87, 'English'), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Geography', 78), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 96)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Social sciences', 82), ('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 90)]], [[('Social sciences', 82), ('Mathas', 90), ('Science', 90), ('Maths', 90)]], [[('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)]], [[('Geography', 78), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Physics', 93), ('Maths', 96)]], [[('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Biology', 95)]], [[('Geography', 78), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)]], [[('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('ChemistrMathasy', 92), ('Chemistry', 92), ('Chemistry', 92)]], [[('Biology', 45), ('Maths', 85), ('Physics', 96), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Biology', 45), ('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Computer Science', 90), ('Physics', 93), ('Physics', 93), ('Physics', 93)]], [[('Science', 45), ('Science', 45), ('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)]], [[('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Maths', 97)]], [[('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 89), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)]], [[('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('English', 88), ('Science', 90), ('Maths', 97)]], [[('Art', 70), ('History', 75), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)]], [[('English', 87), ('English', 87, 'English'), ('Physics', 90), ('Geography', 91), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98)]], [[('Economics', 89), ('Physics', 90), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('History', 96)]], [[('Geography', 70), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Biology', 72), ('Biology', 72, 'Biology'), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Social sciences', 86), ('Computer Science', 88)]], [[('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('Maths', 85), ('Chemistry', 92)]], [[('English', 87), ('English', 87, 'ChemistrMathasy'), ('Physics', 90), ('Geography', 91), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)]], [[('Geography', 70), ('English', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Chemistry', 94), ('English', 95), ('Physics', 98)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Maths', 96), ('Physics', 96)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91)]], [[('Maths', 82), ('Social sciences', 82), ('English', 88), ('English', 88), ('Science', 90), ('Computer Science', 90)]], [[('Physics', 90), ('Biology', 90)]], [[('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('Social sciences', 82), ('English', 88), ('Maths', 97)]], [[('Physics', -76, 'Physics'), ('Computer Science', 82), ('Maths', 85)]], [[('Geography', 78), ('Biology', 81), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90), ('Physics', 93, 93), ('Physics', 93), ('Maths', 96)]], [[('Economics', 89), ('Physics', 90), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)]], [[('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98), ('Physics', 98)]], [[('Maths', 82), ('Social sciences', 82), ('Science', 90)]], [[('Computer Science', 65), ('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('nEnglish', 82), ('English', 82), ('Social sciences', 86)]], [[('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('English', 92, 92), ('Physics', 93), ('Physics', 93), ('Maths', 96), ('Physics', 96)]], [[('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Physics', 93), ('Maths', 96)]], [[('Art', 70), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90, 90), ('Geography', 92), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Biology', 95)]], [[('Economics', 89, 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)]], [[('Social sciences', 72), ('Computer Science', 82), ('English', 88), ('Maths', 97)]], [[('Maths', 82), ('Social sciences', 82), ('English', 88), ('English', 88), ('English', 88), ('Science', 90), ('Computer Science', 90)]], [[('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93), ('Computer Science', 94), ('History', 96)]], [[('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)]], [[('Geography', 78), ('Science', 87), ('History', 88), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)]], [[('Physics', 76), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93, 'Science'), ('Computer Science', 94), ('Physics', 95), ('Chemistry', 95), ('History', 96)]], [[('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98)]], [[('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91)]], [[('Geography', 78), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)]], [[('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 84, 'Biology'), ('Maths', 88), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98), ('Physics', 98)]], [[('Social sciences', 82), ('Social sciences', 82, 82), ('Computer Science', 82), ('English', 88), ('Maths', 97), ('Maths', 97)]], [[('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('BiolComputoer Scienceogy', 95), ('Biology', 95)]], [[('Maths', 82), ('Social sciences', 82), ('Maths', 82), ('Science', 90)]]]
results = [[('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 97)], [('Social', 33), ('Telugu', 49), ('Hindhi', 54)], [('Biology', 45), ('Physics', 96), ('Chemistry', 97)], [], [('English', 88)], [('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91)], [('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 90)], [('Maths', 82), ('Social sciences', 82), ('English', 88), ('Science', 90), ('Computer Science', 90)], [('Biology', 45), ('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)], [('Physics', 90), ('Chemistry', 90), ('Biology', 90)], [('Physics', -76), ('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('Chemistry', 92)], [('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)], [('Chemistry', 68), ('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Maths', 84), ('Social sciences', 86), ('Computer Science', 88)], [('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)], [('Chemistry', -9), ('Physics', -3), ('Geography', 65), ('History', 73), ('Biology', 77), ('English', 81), ('Science', 82), ('Computer Science', 88), ('Maths', 94)], [('Computer Science', 75), ('English', 77), ('Physics', 78), ('Economics', 79), ('Chemistry', 80), ('Maths', 80), ('Science', 84), ('Geography', 85), ('Biology', 88), ('History', 92)], [('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96), ('Maths', 98)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Chemistry', 92)], [('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Social sciences', 86), ('Computer Science', 88)], [('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Maths', 96)], [('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('Chemistry', 92)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91), ('English', 95)], [('Geography', 70), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85, 85), ('Science', 88), ('Computer Science', 91)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Maths', 96)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Maths', 96), ('Physics', 96)], [('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Chemistry', 94), ('English', 95), ('Physics', 98)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('Computer Science', 90), ('Physics', 93), ('Physics', 93)], [('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97), ('Maths', 97)], [('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)], [('Social sciences', 82), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Physics', 98)], [('Social sciences', 82), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90), ('Science', 92)], [('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)], [('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)], [('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82), ('Maths', 85, 85), ('Computer Science', 91)], [('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Maths', 97), ('Maths', 97)], [('Maths', 82), ('Social sciences', 82), ('Science', 90), ('Computer Science', 90)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('ChemistrMathasy', 92), ('Chemistry', 92)], [('Social sciences', 82), ('English', 88), ('English', 88), ('Mathas', 90), ('Science', 90), ('Maths', 90)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Physics', -76), ('Computer Science', 82), ('Maths', 85), ('Chemistry', 92)], [('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Physics', 93), ('Maths', 96)], [('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Chemistry', 92), ('Chemistry', 92)], [('Chemistry', -9), ('Physics', -3), ('Geography', 65), ('History', 73), ('Biology', 77), ('Biology', 77), ('English', 81), ('Computer Science', 88), ('Maths', 94)], [('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91), ('English', 95)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Maths', 92), ('Physics', 93), ('Maths', 96)], [('Geography', 78), ('Biology', 81, 'Biology'), ('Biology', 81), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Maths', 92), ('Physics', 93), ('Maths', 96)], [('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)], [('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)], [('English', 87), ('English', 87, 'English'), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Geography', 78), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 96)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Social sciences', 82), ('Social sciences', 82), ('English', 88), ('Science', 90), ('Maths', 90)], [('Social sciences', 82), ('Mathas', 90), ('Science', 90), ('Maths', 90)], [('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)], [('Geography', 78), ('Chemistry', 85), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90, 90), ('Physics', 93), ('Maths', 96)], [('Art', 70), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Biology', 95)], [('Geography', 78), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)], [('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('ChemistrMathasy', 92), ('Chemistry', 92), ('Chemistry', 92)], [('Biology', 45), ('Maths', 85), ('Physics', 96), ('Physics', 96), ('Physics', 96), ('Chemistry', 97)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Biology', 45), ('Maths', 85), ('Science', 88), ('Physics', 96), ('Physics', 96)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Computer Science', 90), ('Physics', 93), ('Physics', 93), ('Physics', 93)], [('Science', 45), ('Science', 45), ('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('English', 88), ('Science', 90), ('Maths', 97)], [('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('Maths', 97)], [('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 89), ('Geography', 92), ('Computer Science', 94), ('Biology', 95)], [('Social sciences', 82), ('Computer Science', 82), ('English', 88), ('English', 88), ('Science', 90), ('Maths', 97)], [('Art', 70), ('History', 75), ('History', 78), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94, 'Computer Science'), ('Biology', 95)], [('English', 87), ('English', 87, 'English'), ('Physics', 90), ('Geography', 91), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98)], [('Economics', 89), ('Physics', 90), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('History', 96)], [('Geography', 70), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Biology', 72), ('Biology', 72, 'Biology'), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('English', 82), ('Social sciences', 86), ('Computer Science', 88)], [('Biology', -45), ('Computer Science', 82), ('Maths', 85), ('MaMusicths', 85), ('Maths', 85), ('Maths', 85), ('Chemistry', 92)], [('English', 87), ('English', 87, 'ChemistrMathasy'), ('Physics', 90), ('Geography', 91), ('Geography', 91), ('Biology', 92), ('Biology', 92, 'Biology'), ('Science', 93), ('Computer Science', 94), ('Chemistry', 95), ('History', 96)], [('Geography', 70), ('English', 70), ('History', 77), ('Biology', 85), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Chemistry', 94), ('English', 95), ('Physics', 98)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Maths', 96), ('Physics', 96)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Maths', 85), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91)], [('Maths', 82), ('Social sciences', 82), ('English', 88), ('English', 88), ('Science', 90), ('Computer Science', 90)], [('Physics', 90), ('Biology', 90)], [('Social sciences', 82), ('Computer Science', 82), ('Computer Science', 82), ('Social sciences', 82), ('English', 88), ('Maths', 97)], [('Physics', -76, 'Physics'), ('Computer Science', 82), ('Maths', 85)], [('Geography', 78), ('Biology', 81), ('History', 88), ('History', 88), ('History', 88), ('Computer Science', 90), ('Physics', 93, 93), ('Physics', 93), ('Maths', 96)], [('Economics', 89), ('Physics', 90), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95)], [('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98), ('Physics', 98)], [('Maths', 82), ('Social sciences', 82), ('Science', 90)], [('Computer Science', 65), ('Biology', 72), ('History', 75), ('Physics', 78), ('Science', 79), ('Geography', 80), ('nEnglish', 82), ('English', 82), ('Social sciences', 86)], [('Geography', 78), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('English', 92, 92), ('Physics', 93), ('Physics', 93), ('Maths', 96), ('Physics', 96)], [('Geography', 78), ('Geography', 78, 'Geography'), ('Biology', 81), ('Chemistry', 85), ('Science', 87), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Physics', 93), ('Maths', 96)], [('Art', 70), ('Chemistry', 80), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90, 90), ('Geography', 92), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Computer Science', 94, 'Computoer Science', 'Computer Science'), ('Biology', 95)], [('Economics', 89, 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Computer Science', 94, 'Computer Science'), ('Chemistry', 95), ('History', 96)], [('Social sciences', 72), ('Computer Science', 82), ('English', 88), ('Maths', 97)], [('Maths', 82), ('Social sciences', 82), ('English', 88), ('English', 88), ('English', 88), ('Science', 90), ('Computer Science', 90)], [('Physics', 76), ('English', 87), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93), ('Computer Science', 94), ('History', 96)], [('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Biology', 85, 'Biology'), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('English', 95), ('Physics', 98)], [('Geography', 78), ('Science', 87), ('History', 88), ('English', 92), ('Physics', 93), ('Maths', 96), ('Physics', 96)], [('Physics', 76), ('Economics', 89), ('Physics', 90), ('Geography', 91), ('Biology', 92), ('Science', 93), ('Science', 93, 'Science'), ('Computer Science', 94), ('Physics', 95), ('Chemistry', 95), ('History', 96)], [('Geography', 70), ('Geography', 70), ('Geography', 70, 70), ('History', 77), ('Maths', 88), ('Chemistry', 90), ('Computer Science', 92), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98)], [('English', 72), ('Physics', 76), ('History', 78), ('Geography', 80), ('Chemistry', 82, 'Chemistry'), ('Chemistry', 82), ('Science', 88), ('Computer Science', 91, 91), ('Computer Science', 91)], [('Geography', 78), ('Chemistry', 85), ('Science', 87), ('History', 88), ('Computer Science', 90), ('English', 92), ('Physics', 93), ('Maths', 96)], [('Geography', 70), ('Geography', 70), ('History', 77), ('Biology', 84, 'Biology'), ('Maths', 88), ('Computer Science', 92), ('English', 95, 'English'), ('Physics', 98), ('Physics', 98)], [('Social sciences', 82), ('Social sciences', 82, 82), ('Computer Science', 82), ('English', 88), ('Maths', 97), ('Maths', 97)], [('Art', 70), ('History', 78), ('Chemistry', 81), ('Music', 82), ('Maths', 85), ('English', 87), ('Physics', 90), ('Geography', 92), ('Computer Science', 94), ('BiolComputoer Scienceogy', 95), ('Biology', 95)], [('Maths', 82), ('Social sciences', 82), ('Maths', 82), ('Science', 90)]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(subject_marks(*inp), exp, 0)
| OK=True
==================== Problem #24 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to flatten a list and sum all of its elements.
Your answer will be tested on test cases like:
assert recursive_list_sum(([1, 2, [3,4],[5,6]]))==21
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to flatten a list and sum all of its elements.
Your answer will be tested on test cases like:
assert recursive_list_sum(([1, 2, [3,4],[5,6]]))==21
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to flatten a list and sum all of its elements.
Your answer will be tested on test cases like:
assert recursive_list_sum(([1, 2, [3,4],[5,6]]))==21
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to flatten a list and sum all of its elements.
Your answer will be tested on test cases like:
assert recursive_list_sum(([1, 2, [3,4],[5,6]]))==21
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to flatten a list and sum all of its elements.
Your answer will be tested on test cases like:
assert recursive_list_sum(([1, 2, [3,4],[5,6]]))==21
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called recursive_list_sum that takes a list and returns the sum of all its elements, even if they are nested. Let's think about how to approach this.
So the problem is to flatten the list and then sum all elements. But how to handle the nested lists? Oh right, recursion might be useful here. Because each element could be a list itself, so I need to check if an element is a list. If it is, then I need to process that sublist recursively.
Wait, but in Python, how do I check if something is a list? Well, I can use isinstance(element, list). But wait, what about other iterables? Like tuples or other types? The problem examples use lists, so maybe we can assume that all nested elements are lists.
So the plan is: iterate through each element in the input list. For each element, if it's a list, then recursively call the function on that element. If it's not a list, add it to the sum. But wait, what about if the element is a different type, like an integer? Well, the problem says that the input is a list of integers and sublists, so maybe we can assume that all elements are either integers or lists.
So the function will loop through each element in the input. For each element, check if it's a list. If yes, then add the result of recursive_list_sum on that element. If not, add the element's value.
Wait, but the initial input is a list. So the function will take a list as input. For example, the test case is [1,2,[3,4],[5,6]]. The function should process each element. The first two elements are integers, so add them. The third and fourth are lists, so recursively sum them.
So the base case is when the element is not a list. Then add it. Otherwise, process the sublist.
Let me try to write this as a function.
The function recursive_list_sum would take a single argument, which is the list. Then, initialize a total sum as 0. Then for each element in the list:
if isinstance(element, list):
total += recursive_list_sum(element)
else:
total += element
Then return the total.
Yes, that seems right. Let's test this logic with the sample input.
Sample input: [1, 2, [3,4], [5,6]]
Processing each element:
1: add 1
2: add 2
[3,4]: call recursive_list_sum on [3,4], which returns 3+4=7
[5,6]: call recursive_list_sum on [5,6], returns 5+6=11
Total is 1+2+7+11 = 21. Which matches the sample output.
Another test case: if the input is [1, [2, [3, [4]]]], the sum should be 1+2+3+4=10. Let's see:
First element is 1, added. Then the sublist [2, [3, [4]]]. For that, 2 is added, then the sublist [3, [4]]. 3 is added, then [4], which adds 4. So total 1+2+3+4=10. Correct.
What about empty lists? Like if the input is [[]], then the sum is 0. Because the sublist is empty. So the function would process the empty list, which returns 0. So the total is 0.
But wait, what if the input is not a list? Well, according to the problem statement, the function is supposed to take a list. The test case shows that the input is a list. So maybe the function can assume that the input is a list. So the function can process the input as a list.
So the code would be:
def recursive_list_sum(lst):
total = 0
for element in lst:
if isinstance(element, list):
total += recursive_list_sum(element)
else:
total += element
return total
But wait, what if the input is not a list? Like if someone calls it with a non-list, but according to the problem, the function is supposed to handle the input as a list. So perhaps the function is designed to take a list as input, and the code can assume that.
So the code should work for the test case given. Let me check the sample assertion:
assert recursive_list_sum(([1, 2, [3,4],[5,6]])) == 21
Yes, that should work.
But wait, in Python, the function is called with the argument as a list. So the code should be correct.
So the function is written as above. Now, I need to write this in a Python script as a self-contained function. The code should be in a markdown code block. Also, the function is named recursive_list_sum and takes a single argument, which is the list.
So the code would be:
def recursive_list_sum(lst):
total = 0
for element in lst:
if isinstance(element, list):
total += recursive_list_sum(element)
else:
total += element
return total
But wait, what about if the elements are not integers? Like strings or other types. But the problem says that the elements are numbers, so we can assume that they are addable. The problem's test case uses integers, so the code should work.
Yes, that's the solution.
```python
def recursive_list_sum(lst):
total = 0
for element in lst:
if isinstance(element, list):
total += recursive_list_sum(element)
else:
total += element
return total
```
----------------------------------------------
Result: Pred=def recursive_list_sum(lst):
total = 0
for element in lst:
if isinstance(element, list):
total += recursive_list_sum(element)
else:
total += element
return total | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, 2, [3, 4], [5, 6]]], [[7, 10, [15, 14], [19, 41]]], [[10, 20, [30, 40], [50, 60]]], [[1, [2, [3, [4, [5, [6, [7, [8, 9]]]]]]]]], [[]], [[[], []]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[[[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]]]]]], [[[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]]], [[[[[[1], [2]], [3]], [[4], [5]]], [[[[6], [7]], [8]], [[9], [10]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[[[[10, 11], [12, 13]], [[14, 15], [16, 17]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]]]], [[[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[22, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[1, [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[1, [1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1]], [[17, 17]], [[1, [2, [3, [4, [5, [6, [7, [8, 9]]]]]]], 1]], [[2, [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]]], [21, [22, [23]]]]], [[[-63.05154180027262, -88.35789773161446, -67.78402311731799, -68.79245553684203, -70.3295437860673, -92.8058245239063, -93.56332101454589, -79.03594591232238, 26.92003787542201], [], []]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21], [21], [21]]], [[0, [1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[5, 1, [1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[[[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]], [[10, 11], [12, 13]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]]]], [[[21, [22, [23]], 21], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21]]], [[1]], [[[[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]], [[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]]]], [[[[[10, 11], [12, 13]], [[16, 17]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]], [[[10, 11], [12, 13]], [[16, 17]]]]], [[[[[22, 23], [24, 25]]], [[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[22, 23], [24, 25]]]]], [[[22, 2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1, [22, 2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]]]], [[[[[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11], [11]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11], [11]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]], [[10, 11], [12, 13]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]], [[10, 11], [12, 13]]]]], [[[], [], [], []]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 20, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 20, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[], [], [-63.05154180027262, -88.35789773161446, -67.78402311731799, -68.79245553684203, -70.3295437860673, -92.8058245239063, -93.56332101454589, -79.03594591232238, 26.92003787542201, -67.78402311731799]]], [[[[[10, 11], [12, 13]], [[16, 17]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]], [[[10, 11], [12, 13]], [[16, 17]]], [[[10, 11], [12, 13]], [[16, 17]]], [[[18, 19], [20, 21]], [[22, 23], [24, 25]]]]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]]]]], [[[[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]]]], [[1, [1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]], 1]], [[0, 1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[1, 0, 2, [2, [3, [4, [5, [6, [7, [8, 9]]]]]]]]], [[0, 1, 28, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[[21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[[4], [5], [5]], [[[1], [2]], [25, 3], [25, 3]], [[4], [5], [5]]], [[[4], [5], [5]], [[[1], [2]], [25, 3], [25, 3]], [[4], [5], [5]]], [[[[6], [7]], [8]], [[9], [10]]]]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[18, 19], [20, 21]], [[24, 22, 23], [24, 22, 23], [24, 25]], [[24, 22, 23], [24, 22, 23], [24, 25]]], [[[18, 19], [20, 21]], [[24, 22, 23], [24, 22, 23], [24, 25]], [[24, 22, 23], [24, 22, 23], [24, 25]]]]], [[[[[[[5, 6, 5], [[1, 2], [3, 4]], [5, 6, 5]], [7, [8, 9]]], [[[5, 6, 5], [[1, 2], [3, 4]], [5, 6, 5]], [7, [8, 9]]]]]]], [[12, 20, 16, 97, 4, 28, -13]], [[18, [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [[3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[12, 20, 16, 97, 4, 28, -13, -13]], [[[[[10, 11], [12, 13]], [[14, 15], [16, 17]], [[10, 11], [12, 13]]], [[[18, 18], [18, 18], [20, 21]], [[18, 18], [18, 18], [20, 21]], [[22, 23], [24, 25]]], [[[18, 18], [18, 18], [20, 21]], [[18, 18], [18, 18], [20, 21]], [[22, 23], [24, 25]]]]], [[[[[[1], [2]], [3]], [[4], [5]]], [[[[6], [7]], [8]], [[9], [10]]], [[[[6], [7]], [8]], [[9], [10]]]]], [[[[[[1], [2]], [3]], [[-13], [-13], [5]]], [[[[1], [2]], [3]], [[-13], [-13], [5]]], [[[[6], [7]], [8]], [[9], [10]]]]], [[[[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21]]], [[[[[10, 11], [12, 13]], [[14, 15], [16, 17]]]]], [[[[[[6], [7]], [8]], [[9], [10]]], [[[[6], [7]], [8]], [[9], [10]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 2, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 2, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 2, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[[[[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]], [[[[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[1, 2, 3], [4, 5, 6], [1, 2, 3]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]]]], [[[1, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]], 2, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[[[[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]], [12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]]], [[[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]], [12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]]], [[[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]], [12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[2, 27, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], 1, [2, 27, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[[1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]], 1, [1, 2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]], [[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 20, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[[1, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]], 2, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]], [1, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]], 2, [11, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20, [21]]]]]]]]]]]]]]]]]]]]]], [[[[[5, 6]], [[5, 6]], [7, [8, 9]]], [[[5, 6]], [[5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]], [[10, 11], [12, 13]]], [[[18, 19], [20, 21, 20]], [[18, 19], [20, 21, 20]], [[22, 23], [24, 25]]]]], [[[[[[1], [2]], [3]], [[-13], [5]]], [[[[1], [2]], [3]], [[-13], [5]]], [[[[1], [2]], [3]], [[-13], [5]]], [[[9], [10]]]]], [[1, 1]], [[12, 20, 16, 97, 4, 28, -13, 12]], [[[21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9, 8], [7, 8, 9, 8], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9, 8], [7, 8, 9, 8], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]]]]], [[[2, 27, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], 1, [2, 27, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [2, 27, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [22, 21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [22, 21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [12, 13]], [[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [12, 13]], [[12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [12, 13]], [[1, 2], [[3, 4], [[5, 6], [[7, 8], [[9, 10], 11]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[[22, 21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [22, 21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1], [11], [11]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1], [11], [11]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1], [11], [11]], [21, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[22, 2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1, [22, 2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], [22, 2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [[12, 20, 16, 97, 3, 28, -13, -13]], [[[[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]], [[[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[19, 20, 21], [22, 23, 24]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [[[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], 21, [[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], 21, [[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], 21, [[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]], 21, [[23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]]]], [[[[1, 2]], [[1, 2]], [[12, 20, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, 9]]]]]]], 1, 1]], [[[2, 26, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], 0, [2, 26, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [2, 26, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [2, 26, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[22]], [[12, 20, 16, 97, 4, 28, -13, 12, 12]], [[0, [2, [3, [4, [5, [6, [7, [8, 9]]]]]]], 1, 1]], [[12, 20, 18, 16, 97, 4, 28, -13, 12]], [[[[[[1, 2], [3, 4]], [5, 6]], [7, [8, 9]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]]], [[[10, 11], [12, 13]], [[14, 15], [16, 17]]]]], [[[2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]], 1]], [[[[[[13, 14, 15], [16, 17, 18]], [[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[13, 14, 15], [16, 17, 18]]]], [[[[13, 14, 15], [16, 17, 18]], [[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]], [[13, 14, 15], [16, 17, 18]]]]]], [[1, 11, 1]], [[[[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21], [21, [22, [23]], 21]]], [[[22, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [22, [22, [23, [24, [25, [26, [27, [28, [29, [30]]]]]]]]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]], [[22, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[1, 23, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]], [[[[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]], [[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]], [[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]]], [21, [22, [23]]], [[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]], [[[[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]], [[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]], [[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]], [[9, 12, 13], [[14, 15], [[16, 17], [[18, 19], [20, 21]]]], [9, 12, 13]]]], [[[[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]], [1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [21, [22, [23]], 21], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]], [1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]], [21, [22, [23]], 21], [[1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]], [1, 0, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]]]]], [[[[1, [2, [3, [4, [5, [6, [7, [8, [9, [10]]]]]]]]]], [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]], [21, [22, [23]], 21], [21, [22, [23]], 21]]], [[[[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]], [[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]], [[[[13, 14, 15], [16, 17, 18]]], [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]], [[[13, 14, 15], [16, 17, 18]]]]]], [[22, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]], 23, [2, [3, [4, [5, [6, [7, [8, [9, [10, [11, [12, [13, [14, [15, [16, [17, [18, [19, [20]]]]]]]]]]]]]]]]]]]]]]
results = [21, 106, 210, 45, 0, 0, 55, 45, 300, 55, 231, 465, 325, 210, 231, 280, 900, 396, 231, 622, 232, 56, 34, 46, 830, 342, -596.800515547467, 720, 273, 231, 237, 264, 975, 371, 681, 1, 528, 330, 233, 153, 312, 228, 1174, 525, 0, 436, -664.584538664785, 581, 153, 171, 233, 55, 47, 83, 510, 214, 949, 132, 164, 846, 151, 794, 95, 10, 594, 108, 80, 567, 816, 742, 475, 1581, 473, 463, 1047, 251, 950, 536, 13, 2, 176, 1467, 680, 709, 764, 1122, 109, 764, 999, 229, 150, 756, 1990, 191, 47, 940, 22, 188, 46, 194, 261, 55, 900, 13, 594, 722, 440, 233, 624, 552, 832, 969, 384, 792, 463]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(recursive_list_sum(*inp), exp, 0)
| OK=True
==================== Problem #25 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of positive numbers in a list.
Your answer will be tested on test cases like:
assert pos_count([1,-2,3,-4]) == 2
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of positive numbers in a list.
Your answer will be tested on test cases like:
assert pos_count([1,-2,3,-4]) == 2
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of positive numbers in a list.
Your answer will be tested on test cases like:
assert pos_count([1,-2,3,-4]) == 2
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of positive numbers in a list.
Your answer will be tested on test cases like:
assert pos_count([1,-2,3,-4]) == 2
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count the number of positive numbers in a list.
Your answer will be tested on test cases like:
assert pos_count([1,-2,3,-4]) == 2
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called pos_count that counts the number of positive numbers in a list. Let me think about how to approach this.
First, the problem says positive numbers. So, any number greater than zero. Wait, but what about zero itself? The question says positive, so zero isn't considered positive. So, the function should count elements in the list that are greater than zero.
The input is a list of numbers. The output is the count of those numbers that are positive.
So, the steps are: iterate through each element in the list, check if it's greater than zero, and increment a counter each time that's true.
How to implement this in Python. Let's see.
The function can be defined as def pos_count(lst):, where lst is the input list.
Initialize a counter variable to zero. Then loop through each element in the list. For each element, if it's > 0, add one to the counter.
Alternatively, I can use a list comprehension to create a list of True/False values where each is True if the element is positive, then sum them. Because in Python, True is 1 and False is 0 when summed. So sum(1 for x in lst if x > 0) would give the count.
Wait, but how about for numbers like 0.5? Well, the problem says "positive numbers", which includes any number greater than zero, not just integers. So that approach would work.
So the function can be written concisely as:
def pos_count(lst):
return sum(1 for x in lst if x > 0)
Wait, but what if the list is empty? Well, the sum would be zero, which is correct.
Testing the sample case: [1, -2, 3, -4]. The positive numbers are 1 and 3, so count is 2. The code would generate 1 for 1, 0 for -2, 1 for 3, 0 for -4. Sum is 2. Correct.
Another test case: [0, 0, 0], the count is zero. Because none are positive. Another case: [5], returns 1. And so on.
So this code should work. Let me make sure that the function is correctly named and that the parameters are correct. The function is called pos_count and takes a list as input.
Yes. So the code should be:
def pos_count(lst):
return sum(1 for x in lst if x > 0)
But wait, maybe using a generator expression here is efficient. Alternatively, using a loop.
Another approach:
def pos_count(lst):
count = 0
for num in lst:
if num > 0:
count +=1
return count
Either approach works. Which is better? Both are correct. The generator expression is more concise.
But for the purpose of the problem, either is acceptable. Let me check if there are any edge cases. For example, if the list contains non-integer numbers, like floats. But the problem says "numbers in a list", which can be integers or floats. The code handles that correctly.
So the function should work for all cases. Therefore, the code can be written as the sum of the generator expression.
So the final code is as written.
```python
def pos_count(lst):
return sum(1 for x in lst if x > 0)
```
----------------------------------------------
Result: Pred=def pos_count(lst):
return sum(1 for x in lst if x > 0) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, -2, 3, -4]], [[3, 4, 5, -1]], [[1, 2, 3, 4]], [[0, -1, 2, -3, 4, -5, 6, -7, 8, -9, 10]], [[]], [[1]], [[-1, -2, -3, 0, 1, 2, 3, 3, 2, 1, 0, -1]], [[-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]], [[1, 2, 3, 4, 5]], [[10, 20, 30, 40]], [[0, 1]], [[-5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]], [[-1, -2, -3, 0, 1, 2, 1, 3, 2, 1, 0, -1]], [[10, 20, 10, 30, 40]], [[-5, -4, -3, -2, -1, -1, 1, 2, 4, 5]], [[-2, -3, 0, 1, 2, 1, 3, 2, 1, 0, -1]], [[0, -1, 2, -3, 4, -5, 6, 8, -9, 10]], [[10, 20, -9, 40]], [[-5, -4, 3, -2, -1, 0, 1, 2, 3, 4, 5]], [[-1, -2, -3, 0, 1, 2, 1, 3, -1, 2, 1, 0, -1]], [[0, 1, 1]], [[0, -1, 2, -3, 4, -5, 6, 6, -7, 8, -9, 10]], [[2, 3, 4, 5]], [[-5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 4, 5]], [[-5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 0]], [[-2, -3, 0, 1, 2, 1, 3, 2, 1, -4, 0, -1]], [[10, -9, 40]], [[-5, -4, -3, -2, -1, 1, 2, 4, 5, 5]], [[10, 19, 30]], [[-1, -2, -3, 0, 1, 2, 1, 3, 1, 0, -1]], [[10, 30, 40, 10]], [[0, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4]], [[0, -1, 2, -2, -3, 4, -5, 6, 8, -9, 10, 4]], [[0, -1, 2, 4, -5, 6, 8, -9, 10, 4]], [[10, -2, -9, 40]], [[0, -1, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4, 4]], [[2, 3, 4, 2, 4]], [[3, 2, 3, 4, 2, 4, 2]], [[0, -1, 2, -3, 4, -5, 6, -7, 8, 10]], [[0, -1, 2, -3, 4, -5, 6, 8, -10, -9, 10, 4]], [[3, 2, 3, 4, 2, 5, 2]], [[-4, -2, -1, 1, 2, 4, 5, 5]], [[-1, -2, -3, 0, 1, 2, 10, 3, 3, 2, 1, 0, -1, 2]], [[-5, 3, -4, 3, -2, -1, 0, 1, 2, 3, -9, 4, 5]], [[-2, -2, 0, 1, 2, 1, 3, 1, -4, 0, -1, -1]], [[10, 20, -9]], [[0, -1, 2, -3, 4, -5, 6, 8, 2, 10]], [[30, 3, 4, 5, 3]], [[0, -1, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4, 4, 6]], [[-9, -4, -2, -1, -1, 1, 2, 4, 5]], [[-1, -2, -3, 0, 1, 2, 1, 3, 2, 1, 0, -1, 2]], [[-5, 3, -4, 3, -2, -1, 0, 1, 3, -9, 4, 5]], [[0, -1, -1, 1, -3, 4, -5, 6, 8, -9, 10, 4, 4]], [[-97.00921686941055, -62.31826514441987, -47.8901822007769, 27.86472361019527, 59.008009822655055]], [[9, 10, 10, 30]], [[10, 21, 20, -9]], [[10, 20, -9, 39]], [[0, -1, 2, -3, 4, -5, 6, -7, 8, 10, -7]], [[-1, -2, -3, 0, 1, 2, 10, 3, 3, 2, 1, 0, -1, 2, 2]], [[10, -9, 40, 40]], [[0, -1, 2, 4, -5, 6, -7, 8, 10]], [[-5, 3, -4, 3, -2, -1, -3, 0, 1, 2, 3, -9, 4, 5, 0]], [[3, 3, 2, 4, 2, 4, 2]], [[-5, -4, -3, -2, -1, -1, 1, 2, 3, 4, 5]], [[0, -1, 2, 4, 1, -5, 6, -7, 8, 10]], [[-5, -4, 3, -2, -1, 0, 1, 2, 3, 4, 5, 5]], [[-1, -2, -3, 3, 0, 1, 2, 3, 3, 2, 1, 0, -1, -3]], [[0, -1, 2, 4, -5, 6, 8, -9, 10, 4, -1]], [[-5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -4]], [[0, -1, -1, 2, 4, -3, 4, -5, 8, -9, 10, 4, 4]], [[0, -1, 2, 4, -5, 6, -7, 8, 10, 2]], [[9, 10, 11, 30]], [[9, 30, 5, 40, 10]], [[0, -1, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4, 4, 2]], [[0, -1, 2, 4, 6, 8, -9, 10, 4]], [[-1, -2, -3, 0, 1, 2, 1, 3, -2, 2, 1, 0, -1, 3]], [[-2, -5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -4]], [[-1, -2, -3, 0, 1, 10, 3, 3, 2, 1, 3, 0, -1, 2]], [[-5, -4, -3, -2, -1, -1, 1, 2, 39, 4, 5, 5]], [[-5, -3, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, -4, -1]], [[-1, -2, -3, 0, 1, 3, 3, 2, 1, 3, 0, -1, 2]], [[10, 20, 10, 9, 30, 5]], [[0, -1, -2, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4, 4, 2]], [[-2, -3, 0, 1, 2, 1, 3, 1, -4, -1, -1]], [[10, 20, 11, 39]], [[0, -1, 2, 4, 1, -5, 6, -7, 8, 10, 10]], [[10, 19, -9, 40, 40, 40]], [[-5, -3, -4, -3, -2, -1, 0, -2, 1, 2, 3, 4, 5, -4]], [[10, 20, -9, 39, 20]], [[0, -1, 20, -3, 4, -5, 6, 6, -7, 8, -9, 10]], [[-5, -3, -4, -3, -2, -1, 1, 2, 3, 4, 5]], [[0, -1, -1, 2, -3, 4, -5, 6, 8, -9, 10, 4, 4, -9]], [[-2, -3, 0, 1, 2, 1, 3, 2, 1, -4, 0, -1, 0]], [[10, -9, 40, 40, 40]], [[10, 0, -2, -9, 40, -2]], [[-5, -4, -3, -2, -1, -1, 3, 1, 2, 4, 5, 1]], [[-1, -3, -3, 0, 1, 2, 3, 11, 3, 2, 1, 0, -1, 3]], [[-9, -4, -2, -1, 1, 2, 4, 5]], [[0, -1, 2, 3, -3, 4, -5, 6, 8, -10, -9, 10, 4]], [[0, -1, 2, -3, -1, 4, -5, 6, 8, -10, -9, 10, 4]], [[10, 21, 20, -4, -9]], [[10, 20, -9, 40, -9]], [[-5, -3, -3, -3, -2, -1, 0, 1, 3, 4, 5, 0]], [[-11.074239280905289, 59.008009822655055, -62.31826514441987, 27.86472361019527, 59.008009822655055, -97.00921686941055]], [[10, 20, 19, -9, 40, -9]], [[-5, -3, -3, -2, -1, 0, 1, 2, 3, 4, 5, -4, -1]], [[0, -1, 2, -2, -3, 4, -5, 6, 8, -9, 10, 4, -3]], [[-9, -4, -2, -1, 1, 5, 2, 2, 4, 5, -1]], [[0, -1, 2, 4, -5, 6, -7, 8, 10, 2, 6]], [[10, 20, 10, 30, 5]]]
results = [2, 3, 4, 5, 0, 1, 6, 5, 5, 4, 1, 5, 6, 5, 4, 6, 5, 3, 6, 6, 2, 6, 4, 6, 5, 6, 2, 5, 3, 5, 4, 6, 6, 6, 2, 7, 5, 7, 5, 6, 7, 5, 8, 7, 5, 2, 6, 5, 8, 4, 7, 6, 7, 2, 4, 3, 3, 5, 9, 3, 5, 7, 7, 5, 6, 7, 7, 6, 5, 7, 6, 4, 5, 8, 6, 7, 5, 8, 6, 5, 7, 6, 8, 5, 4, 7, 5, 5, 4, 6, 5, 7, 6, 4, 2, 6, 8, 4, 7, 6, 3, 3, 4, 3, 4, 5, 6, 6, 7, 5]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(pos_count(*inp), exp, 0)
| OK=True
==================== Problem #26 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the number of ways to partition a set of Bell numbers.
Your answer will be tested on test cases like:
assert bell_number(2)==2
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the number of ways to partition a set of Bell numbers.
Your answer will be tested on test cases like:
assert bell_number(2)==2
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the number of ways to partition a set of Bell numbers.
Your answer will be tested on test cases like:
assert bell_number(2)==2
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the number of ways to partition a set of Bell numbers.
Your answer will be tested on test cases like:
assert bell_number(2)==2
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the number of ways to partition a set of Bell numbers.
Your answer will be tested on test cases like:
assert bell_number(2)==2
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to compute the Bell number for a given n. The Bell number represents the number of ways to partition a set of size n. The example given is bell_number(2) == 2, which makes sense because a set with two elements can be partitioned in two ways: either each element is in its own subset, or both are in the same subset.
So, how do I calculate Bell numbers? I remember that Bell numbers can be computed using the Bell triangle. The Bell triangle is constructed in a way similar to Pascal's triangle. Let me think about the method.
The Bell triangle method starts with B(0) = 1. Then, each subsequent row starts with the last element of the previous row. Each element in the row is the sum of the previous element in the same row and the element from the previous row's same position. Wait, maybe I should look up the exact method.
Alternatively, there's a formula using Stirling numbers of the second kind. The Bell number B(n) is the sum of Stirling numbers S(n, k) for k from 1 to n. But calculating Stirling numbers might be more complex.
Another approach is using dynamic programming with the Bell triangle. Let me recall the steps for building the Bell triangle. For example:
The first row (row 0) has one element: B(0) = 1.
Row 1 starts with the last element of row 0, which is 1. Then, each next element in the row is the sum of the previous element in the same row and the element from the previous row's same position. Wait, maybe I should think of the Bell triangle as follows:
The Bell triangle is constructed such that the first element of each row is the last element of the previous row. Then, each subsequent element in the row is the sum of the previous element in the same row and the element from the previous row's same position. For example:
Row 0: 1
Row 1: 1 (from row 0's last element), then 1+0? Wait, maybe I should look up the exact construction.
Alternatively, the Bell number B(n) is the sum of the elements in the (n-1)th row of the Bell triangle. Wait, perhaps I need to build the triangle up to row n-1 and then sum the elements of that row to get B(n).
Let me think of an example. For n=2, the Bell number is 2. Let's see:
Row 0: [1] → sum is 1 (which is B(0) = 1)
Row 1: starts with the last element of row 0, which is 1. Then, the next element is 1 (from row 0's element?) Wait, maybe the Bell triangle is built as follows:
The Bell triangle is constructed with the following rules:
- The first row (row 0) starts with B(0) = 1.
- For each subsequent row i, the first element is the last element of row i-1.
- Each subsequent element in the row is the sum of the previous element in the same row and the element from the previous row's same position.
Wait, perhaps I should look up the Bell triangle construction. For example, according to some references, the Bell triangle is built as follows:
The first row starts with B(0) = 1.
Row 1 starts with the last element of row 0 (which is 1), then each next element is the sum of the previous element in the same row and the element from the previous row's same position. Wait, maybe the Bell triangle is built like this:
Row 0: [1]
Row 1: [1, 1]
Row 2: [1, 2, 3]
Wait, but then the Bell number B(n) is the first element of row n. Or is it the sum of the elements in the row?
Alternatively, the Bell number B(n) is the sum of the elements in the (n-1)th row. Let me check for n=2. The Bell number B(2) is 2. If row 1 is [1, 1], then sum is 2, which matches. Then B(2) is sum of row 1.
So the approach is to build the Bell triangle up to row n-1, then sum the elements of that row to get B(n).
So for example, for n=2, the row is row 1 (since n-1=1), which is [1, 1], sum is 2.
Another example: B(3) is 5. Let's see:
Row 0: [1]
Row 1: [1 (from row 0's last element), then 1 (row 0's first element + row 1's previous element? Maybe I need to think about the exact steps.
Wait, here's a way to build the Bell triangle:
The Bell triangle is constructed as follows:
- The first row (row 0) has one element: B(0) = 1.
- For row i (i ≥ 1), the first element is the last element of row i-1.
- Then, each subsequent element in row i is the sum of the previous element in row i and the element from row i-1 at the same position.
Wait, maybe not. Let me look for an example.
For example, the Bell triangle for the first few rows is:
Row 0: 1
Row 1: 1, 2
Row 2: 2, 3, 5
Row 3: 5, 7, 10, 15
Wait, but then the Bell numbers are the first element of each row. For example, B(0)=1, B(1)=1, B(2)=2, B(3)=5, B(4)=15, etc. But that doesn't align with the example given where B(2)=2. So maybe the Bell number B(n) is the first element of row n.
Wait, according to Wikipedia, the Bell number B(n) can be found as the sum of the elements in the (n-1)th row of the Bell triangle. Or perhaps the Bell triangle is constructed differently.
Alternatively, the Bell triangle can be constructed using the recurrence relation:
B(n+1) = sum_{k=0}^n C(n, k) * B(k)
But that might not be helpful for dynamic programming.
Alternatively, the Bell number can be computed using the Bell triangle method. Let me find the correct way to build the triangle.
Upon checking, the Bell triangle is constructed as follows:
- The first row starts with B(0) = 1.
- Each subsequent row starts with the last element of the previous row.
- Then, each next element in the row is the sum of the previous element in the same row and the element from the previous row's same position.
For example, building the triangle step by step:
Row 0: [1]
Row 1 starts with the last element of row 0, which is 1. Then, the next element is 1 (previous element in row 1, which is 1) + the element from row 0's same position (which is 1?), but that would be 2? Wait, perhaps I'm misunderstanding the construction.
Let me look up the Bell triangle construction. According to Wikipedia's Bell number article, the Bell triangle is constructed as follows:
The Bell triangle is a triangular array of numbers, where the first row starts with B(0) = 1. Each subsequent row starts with the last number of the previous row. Then, each number after the first in a row is the sum of the previous number in the same row and the number from the previous row's same position.
So, for example:
Row 0: 1
Row 1: 1 (from previous row's last element), then 1 + 0? No, perhaps the first row is row 0, and the next row is row 1. Let's see:
Row 0: [1]
Row 1: first element is last element of row 0 (1). Then, the next element is the sum of the previous element in the row (1) and the element from the previous row's same position (row 0's first element, which is 1). So 1 + 1 = 2. So row 1 is [1, 2].
Row 2: first element is last element of row 1, which is 2. Then, next element is previous element in row 2 (2) + element from row 1's same position (row 1's first element, which is 1). So 2 + 1 = 3. Then, next element is previous element in row 2 (3) + element from row 1's second element (2). So 3 + 2 = 5. So row 2 is [2, 3, 5].
Row 3: first element is 5 (last of row 2). Then next elements:
5 (previous) + row 2's first element (2) → 5+2=7?
Then 7 (previous) + row 2's second element (3) → 7+3=10.
Then 10 + row 2's third element (5) → 15. So row 3 is [5, 7, 10, 15].
Now, the Bell number B(n) is the first element of row n. So B(0) is 1 (row 0), B(1) is 1 (row 1's first element), B(2) is 2 (row 2's first element), B(3) is 5 (row 3's first element), etc. But according to the example given, bell_number(2) should be 2. Which matches. So for n=2, B(2) is 2. So the function needs to return the first element of row n.
But how do we compute this?
So the approach is to generate the Bell triangle up to row n, and then take the first element of that row.
So, to compute B(n), we can generate the Bell triangle up to row n, and then take the first element of row n.
So for example, for n=2, the row is row 2, which is [2, 3, 5], first element is 2.
So the steps to compute B(n) would be:
Initialize a 2D list (triangle) where each row is built based on the rules.
But for efficiency, perhaps we can use a dynamic programming approach, storing each row as we build it.
Let me think about how to code this.
Let's say we need to compute B(n). Let's create a list of lists, where each sublist represents a row. Start with row 0 as [1]. Then for each row i from 1 to n:
- The first element of row i is the last element of row i-1.
- Then, for each subsequent element j in row i (starting from index 1), the value is row[i][j-1] + row[i-1][j-1].
Wait, for example, row 1:
row 0 is [1]. So row 1 starts with 1. Then, for j=1 (second element in row 1), it's row[1][0] (which is 1) + row[0][0] (which is 1) → 2. So row 1 is [1, 2].
Row 2 starts with row 1's last element, which is 2. Then for j=1: row[2][0] (2) + row[1][0] (1) → 3. Then j=2: row[2][1] (3) + row[1][1] (2) → 5. So row 2 is [2,3,5].
So the code can be structured as follows:
Initialize triangle as [[1]].
For i from 1 to n:
new_row = [triangle[i-1][-1]] # first element is last of previous row
for j in range(1, i+1): # since row i has i+1 elements? Wait, row 0 has 1 element, row 1 has 2 elements, row 2 has 3 elements, etc. So row i has i+1 elements. Wait, no. Wait row 0 is index 0, which has 1 element. Row 1 has 2 elements. So for row i, the number of elements is i+1. So for i from 0 to n, the row has i+1 elements.
But when building row i, we need to generate i+1 elements. But for the Bell triangle, each row i has i+1 elements. So for the code:
for i in range(1, n+1):
new_row = [triangle[i-1][-1]]
for j in range(1, i+1):
new_element = new_row[j-1] + triangle[i-1][j-1]
new_row.append(new_element)
triangle.append(new_row)
Wait, but for j in range(1, i+1), but for each j, we need to compute new_row[j-1] + triangle[i-1][j-1]. Wait, for j=1, new_row[j-1] is new_row[0], which is the first element of new_row, which is the last element of the previous row. And triangle[i-1][j-1] is triangle[i-1][0], which is the first element of the previous row.
But for example, when building row 1 (i=1), j runs from 1 to 1+1=2? Wait, no. Wait, for i=1, the row has i+1 elements? Wait, for i=1, row is 1, which has 2 elements. So j runs from 1 to i (since the first element is already added, and we need to add i elements more? Or maybe the loop should run for j from 1 to i, since the new_row starts with one element, and then we need to add i elements. Because for row i, there are i+1 elements. So for i=1, the new_row starts with 1 element, and then we need to add 1 more element (total 2 elements).
So the loop for j in range(1, i+1) would be for j from 1 to i (since in Python, range is exclusive on the upper bound). Wait, range(1, i+1) would be 1, 2, ..., i. So for i=1, j runs 1 to 1+1=2, but range(1, 2) is [1]. So for j in 1 to i, but how many times?
Wait, the initial new_row has 1 element. Then, for each j in 1 to i (so i elements), we add another element. So the total elements in new_row is 1 + i = i+1. Which is correct. So for i=1, j runs once. For i=2, j runs twice, etc.
So the code for building the triangle would be:
def bell_number(n):
if n == 0:
return 1
triangle = [[1]] # row 0
for i in range(1, n+1):
new_row = [triangle[i-1][-1]] # first element
for j in range(1, i+1):
new_element = new_row[j-1] + triangle[i-1][j-1]
new_row.append(new_element)
triangle.append(new_row)
return triangle[n][0]
Wait, let's test this for n=2.
For n=2, the loop runs i=1 and i=2.
i=1:
new_row starts as [triangle[0][-1] = 1]
then j runs from 1 to 1+1=2 → range(1, 2) is j=1.
new_element = new_row[0] (1) + triangle[0][0] (1) → 2. new_row becomes [1, 2]. triangle now is [[1], [1,2]]
i=2:
new_row starts with triangle[1][-1] = 2.
then j runs from 1 to 2+1=3 → range(1,3) → j=1 and j=2.
for j=1:
new_element = new_row[0] (2) + triangle[1][0] (1) → 3. new_row is [2,3]
for j=2:
new_element = new_row[1] (3) + triangle[1][1] (2) → 5. new_row is [2,3,5]
so triangle is [[1], [1,2], [2,3,5]]
return triangle[2][0] → 2. Which is correct.
Another test: n=3. The Bell number is 5. According to the code, triangle[3][0] is 5. Let's see:
i=3:
new_row starts with triangle[2][-1] =5.
then j runs 1 to 3+1=4 → range(1,4) is 1,2,3.
for j=1:
new_row[0] (5) + triangle[2][0] (2) → 5+2=7 → new_row is [5,7]
j=2: new_row[1] (7) + triangle[2][1] (3) → 7+3=10 → new_row [5,7,10]
j=3: new_row[2] (10) + triangle[2][2] (5) → 15 → new_row [5,7,10,15]
so triangle[3] is [5,7,10,15], and the first element is 5, which is B(3)=5. Correct.
So the code seems to work. Now, what about n=0? The function returns 1, which is correct.
Another test case: bell_number(1) should be 1. Let's see:
n=1, the loop runs for i=1. triangle starts as [[1]].
i=1:
new_row is [1], then j runs from 1 to 2 (range(1, 2) → j=1).
new_element is new_row[0] (1) + triangle[0][0] (1) → 2. new_row becomes [1, 2]. triangle is [[1], [1,2]].
return triangle[1][0] → 1. Correct.
So the code seems to handle the cases.
Now, the problem says that the function should return the Bell number for a given input. So the function bell_number(n) would be implemented as above.
But what about the case when n is 0? The code
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[2], [10], [56], [0], [100], [99], [True], [False], [98], [1], [3], [97], [96], [11], [12], [92], [95], [94], [14], [13], [55], [17], [15], [93], [16], [9], [91], [54], [25], [18], [4], [5], [6], [8], [90], [53], [7], [19], [64], [20], [21], [63], [52], [24], [57], [22], [62], [89], [51], [50], [88], [58], [49], [45], [65], [23], [87], [46], [59], [26], [44], [61], [48], [47], [60], [30], [27], [86], [28], [31], [29], [66], [67], [85], [70], [71], [43], [69], [82], [83], [72], [68], [81], [73], [32], [33], [42], [74], [84], [41], [80], [79], [75], [40], [76], [34], [35], [78], [77], [39], [38], [36]]
results = [2, 115975, 6775685320645824322581483068371419745979053216268760300, 1, 47585391276764833658790768841387207826363669686825611466616334637559114497892442622672724044217756306953557882560751, 1618706027446068305855680628161135741330684513088812399898409470089128730792407044351108134019449028191480663320741, 1, 1, 55494677927746340698788238667452126040563242441827634980157203368430358083090722409217101274455481270374885095618, 1, 5, 1917593350464112616752757157565032460248311804906650215954187246738986739924580790084847891233423398173059771233, 66790853422797408533421892496106177820862555650400879850993569405575404871887998514898872210341414631481213729, 678570, 4213597, 106611797892739782364113678801520610524431974731789913132104301942153476208366519192812848588253648356364, 2345129936856330144543337656630809098301482271000632150222900693128839447045930834163493232282141300734566042, 83012043550967281787120476720274991081436431402381752242504514629481800064636673934392827445150961387102019, 190899322, 27644437, 359334085968622831041960188598043661065388726959079837, 82864869804, 1382958545, 2962614388531218251190227244935749736828675583113926711461226180042633884248639975904464409686755210349399, 10480142147, 21147, 3868731362280702160655673912482765098905555785458740412264329844745080937342264610781770223818259614025, 19317287589145618265728950069285503257349832850302011, 4638590332229999353, 682076806159, 15, 52, 203, 4140, 141580318123392930464192819123202606981284563291786545804370223525364095085412667328027643050802912567, 1052928518014714166107781298021583534928402714242132, 877, 5832742205057, 172134143357358850934369963665272571125557575184049758045339873395, 51724158235372, 474869816156751, 8250771700405624889912456724304738028450190134337110943817172961, 58205338024195872785464627063218599149503972126463, 445958869294805289, 129482661947506964462616580633806000917491602609372517195, 4506715738447323, 400237304821454786230522819234667544935526963060240082269259738, 5225728505358477773256348249698509144957920836936865715700797250722975706153317517427783066539250012, 3263983870004111524856951830191582524419255819477, 185724268771078270438257767181908917499221852770, 194553897403965647871786295024290690576513032341195649821051001205884166153194143340809062985041067, 2507136358984296114560786627437574942253015623445622326263, 10726137154573358400342215518590002633917247281, 139258505266263669602347053993654079693415, 3633778785457899322415257682767737441410036994560435982365219287372, 44152005855084346, 7306720755827530589639480511232846731775215754200303890190355852772713202556415109429779445622537, 2265418219334494002928484444705392276158355, 49176743336309621659000944152624896853591018248919168867818, 49631246523618756274, 8701963427387055089023600531855797148876, 19652364471547941482114228389322789963345673460673370562378245, 628919796303118415420210454071849537746015761, 37450059502461511196505342096431510120174682, 976939307467007552986994066961675455550246347757474482558637, 846749014511809332450147, 545717047936059989389, 276844443054160876160126038812506987515878490163433019207947986484590126191194780416973565092618, 6160539404599934652455, 10293358946226376485095653, 71339801938860275191172, 77605907238843669482155930857960017792778059887519278038000759795263, 1676501284301523453367212880854005182365748317589888660477021013719409, 10583321873228234424552137744344434100391955309436425797852108559510434249855735357360593574749, 18075003898340511237556784424498369141305841234468097908227993035088029195, 408130093410464274259945600962134706689859323636922532443365594726056131962, 552950118797165484321714693280737767385, 809212768387947836336846277707066239391942323998649273771736744420003007, 624387454429479848302014120414448006907125370284776661891529899343806658375826740689137423, 15892292813296951899433594303207669496517041849871581501737510069308817348770226226653966474, 9314528182092653288251451483527341806516792394674496725578935706029134658745, 36628224206696135478834640618028539032699174847931909480671725803995436, 24761288718465863816962119279306788401954401906692653427329808967315171931611751006838915, 214834623568478894452765605511928333367140719361291003997161390043701285425833, 128064670049908713818925644, 1629595892846007606764728147, 35742549198872617291353508656626642567, 5006908024247925379707076470957722220463116781409659160159536981161298714301202, 408248141291805738980141314733701533991578374164094348787738475995651988600158415299211778933, 2351152507740617628200694077243788988, 991267988808424794443839434655920239360814764000951599022939879419136287216681744888844, 40064166844084356404509204005730815621427040237270563024820379702392240194729249115029, 117896026920858300966730642538212084059025603061199813571998059942386637656568797, 157450588391204931289324344702531067, 2804379077740744643020190973126488180455295657360401565474468309847623573788115607, 21195039388640360462388656799, 281600203019560266563340426570, 1635000770532737216633829256032779450518375544542935181844299348876855151241590189395, 67379449595254843852699636792665969652321946648374400833740986348378276368807261348, 10738823330774692832768857986425209, 746289892095625330523099540639146, 3819714729894818339975525681317]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(bell_number(*inp), exp, 0)
| OK=False
==================== Problem #27 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given array is monotonic or not.
Your answer will be tested on test cases like:
assert is_Monotonic([6, 5, 4, 4]) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given array is monotonic or not.
Your answer will be tested on test cases like:
assert is_Monotonic([6, 5, 4, 4]) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given array is monotonic or not.
Your answer will be tested on test cases like:
assert is_Monotonic([6, 5, 4, 4]) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given array is monotonic or not.
Your answer will be tested on test cases like:
assert is_Monotonic([6, 5, 4, 4]) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given array is monotonic or not.
Your answer will be tested on test cases like:
assert is_Monotonic([6, 5, 4, 4]) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to check if a given array is monotonic. Hmm, what's a monotonic array? Oh right, it's an array that is either entirely non-increasing or non-decreasing. So I need to determine if the array is either one or the other.
Let me think about how to approach this. Maybe I can check two separate conditions: one for non-decreasing and another for non-increasing. If either of them is true, then the array is monotonic.
Wait, how do I check for non-decreasing? For each element, the next element should be greater than or equal to the current. Similarly for non-increasing, each next element should be less than or equal to the current.
So the steps could be:
1. Iterate through the array, comparing each element with the next.
2. Check if all elements are non-decreasing (increasing or same) or all non-increasing.
Wait, but how do I do that efficiently? Maybe I can track two flags: one for increasing and another for decreasing. Initially, assume both are True. Then, as I compare elements, if I find a case where next element is less than current, then the increasing flag becomes False. Similarly, if next is greater than current, the decreasing flag becomes False. At the end, if either flag is still True, return True.
Yes, that makes sense. Because if during the iteration, any of the flags become False, but the other remains True, then the array is monotonic.
For example, if the array is [6,5,4,4], then the decreasing flag would stay True. The increasing flag would become False when 6>5. So the function returns True.
Another example: [1,2,2,3] would have the increasing flag True, and the decreasing flag would be False once 1<2.
So the algorithm would be:
Initialize increasing = True, decreasing = True.
Loop from i=0 to len(arr)-2:
if arr[i] < arr[i+1]:
decreasing = False
elif arr[i] > arr[i+1]:
increasing = False
After processing all elements, return increasing or decreasing.
Wait, but what if the array is empty or has one element? Well, according to the problem, the array is considered monotonic in those cases. So for empty array or single element, return True.
So the function can handle that.
Now, let's code this.
The function is_Monotonic takes an array as input. Let's implement this logic.
Wait, but what about the case where the array has elements that are both increasing and decreasing? Like [1, 2, 1]. Then, during the loop, when i=0, arr[0] < arr[1], so decreasing becomes False. Then i=1, arr[1] > arr[2], so increasing becomes False. So in the end, both flags are False, so return False. Which is correct.
Another example: [5,5,5]. All elements are equal. So for each step, neither of the conditions (arr[i] < or >) are met. So both flags remain True. So the function returns True, which is correct.
So the code would be:
def is_Monotonic(arr):
increasing = True
decreasing = True
for i in range(len(arr)-1):
if arr[i] < arr[i+1]:
decreasing = False
elif arr[i] > arr[i+1]:
increasing = False
return increasing or decreasing
Wait, but what if the array is empty? Let's see, if len(arr) is 0 or 1, then the loop doesn't run, and returns True. Which is correct.
Testing the sample input: [6,5,4,4]. Let's see:
i=0: 6>5 → increasing becomes False. decreasing is True.
i=1: 5>4 → increasing remains False. decreasing remains True.
i=2: 4 ==4 → no change. So after loop, increasing is False, decreasing is True. So return True.
Which matches the sample test case.
Another test case: [1,2,3,4] → increasing is True, decreasing becomes False. So returns True.
Another case: [4,3,2,1] → decreasing is True, increasing becomes False. Returns True.
Another case: [1,3,2,4] → during iteration, first 1<3 → decreasing becomes False. Then 3>2 → increasing becomes False. Then 2<4 → decreasing remains False. So both flags are False. Return False.
So this logic seems correct.
So the Python function should be written as such.
Now, the user wants the code in a markdown code block. So I need to put it inside triple backticks.
But the function is called is_Monotonic. Wait, the problem says the function is called is_Monotonic? Let me check the problem statement again.
Yes, the test case is assert is_Monotonic([6,5,4,4]) == True. So the function name is is_Monotonic.
So the code would be:
def is_Monotonic(arr):
increasing = True
decreasing = True
for i in range(len(arr)-1):
if arr[i] < arr[i+1]:
decreasing = False
elif arr[i] > arr[i+1]:
increasing = False
return increasing or decreasing
But wait, what about empty array? Let's see, if arr is empty, len(arr)-1 is -1, so the loop doesn't run. So returns True. Which is correct.
Yes, that should handle all cases.
So that's the code.
```python
def is_Monotonic(arr):
increasing = True
decreasing = True
for i in range(len(arr)-1):
if arr[i] < arr[i+1]:
decreasing = False
elif arr[i] > arr[i+1]:
increasing = False
return increasing or decreasing
```
----------------------------------------------
Result: Pred=def is_Monotonic(arr):
increasing = True
decreasing = True
for i in range(len(arr)-1):
if arr[i] < arr[i+1]:
decreasing = False
elif arr[i] > arr[i+1]:
increasing = False
return increasing or decreasing | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[6, 5, 4, 4]], [[1, 2, 2, 3]], [[1, 3, 2]], [[]], [[9, 3, 7, 2, 5, 1, 6]], [[9, 7, 7, 2, 5, 5, 1, 6]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -64.57664800604005]], [[43.01465662466188, -69.38224302373561, -10.481407073259263]], [[43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263]], [[43.01465662466188, -69.38224302373561, -9.527847657655224, -10.481407073259263, -34.902913681824856, -9.527847657655224]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263, -64.57664800604005]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -9.527847657655224, -10.481407073259263, -64.57664800604005]], [[43.01465662466188, -69.73647736308538, -10.481407073259263]], [[43.01465662466188, -69.38224302373561, -10.481407073259263, -69.73647736308538, 43.01465662466188]], [[43.01465662466188, -34.902913681824856, 42.59716035619264, -69.38224302373561, -9.527847657655224, -10.481407073259263, -64.57664800604005, 43.01465662466188]], [[-10.481407073259263, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005]], [[42.59716035619264, 43.01465662466188, -69.38224302373561, -10.481407073259263]], [[43.01465662466188, -10.481407073259263]], [[9, 5, 3, 7, 2, 5, 1, 1, 2, 6]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263]], [[43.01465662466188, -98.52620778096008, -69.73647736308538, -10.481407073259263]], [[9, 7, 7, 2, 5, 5, 3, 6]], [[-47.55433018390211, -10.481407073259263, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005, -34.902913681824856]], [[-34.902913681824856, -69.38224302373561, -10.481407073259263, -64.57664800604005]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -47.55433018390211, -64.57664800604005]], [[43.01465662466188, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005]], [[41.82235199511542, -68.76772490153975, 43.01465662466188, -69.38224302373561, -10.481407073259263, -69.38224302373561]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -64.57664800604005, -69.38224302373561]], [[43.01465662466188, -69.38224302373561, -69.88165026016243, -10.481407073259263, -69.73647736308538, 43.01465662466188, -69.88165026016243]], [[42.59716035619264, 43.01465662466188, -69.38224302373561, -10.481407073259263, -69.38224302373561]], [[-10.481407073259263, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005, -10.481407073259263]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005]], [[-34.902913681824856, -10.481407073259263, -69.38224302373561, -10.481407073259263]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265, -64.57664800604005]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265]], [[False, False, False]], [[-34.902913681824856, -69.38224302373561, -10.481407073259263, -94.97100584944054]], [[-34.902913681824856, -10.481407073259263, -94.97100584944054]], [[43.01465662466188, -69.38224302373561, -10.481407073259263, 43.01465662466188]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -69.38224302373561]], [[-94.97100584944054, -10.481407073259263, -10.481407073259263]], [[43.01465662466188, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, 27.4121976200018, -64.57664800604005]], [[-34.902913681824856, -10.481407073259263, -69.88165026016243, -94.97100584944054]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, 43.01465662466188]], [[42.59716035619264, -68.76772490153975, 43.01465662466188, 41.82235199511542, -10.481407073259263, -69.38224302373561]], [[-34.902913681824856, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005]], [[-34.902913681824856, -9.527847657655224, -10.481407073259263, -94.97100584944054, -34.902913681824856]], [[7, 3, 7, 2, 5, 5, 3, 6]], [[42.59716035619264, -68.76772490153975, 43.01465662466188, 41.82235199511542, -10.481407073259263, -69.38224302373561, 43.01465662466188]], [[False, False, False, False]], [[9, 5, 7, 2, 5, 1, 1, 2, 6]], [[27.4121976200018, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265]], [[9, 7, 7, 2, 5, 5, 3, 6, 5]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -94.97100584944054, -64.57664800604005]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263, -34.902913681824856]], [[42.59716035619264, 43.01465662466188, -69.38224302373561, -11.141086666406599, -10.481407073259263, -69.38224302373561]], [[-9.527847657655224, -34.902913681824856, 43.01465662466188, -69.38224302373561, -10.493584737965575, -64.57664800604005]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -9.527847657655224, -10.481407073259263, 27.4121976200018, -64.57664800604005]], [[-34.902913681824856, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005, -10.768528666126521]], [[9, 3, 5, 1, 1]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -64.57664800604005, 43.01465662466188]], [[-34.902913681824856, 42.81869869284685, -69.38224302373561, -10.481407073259263, -64.57664800604005, 43.01465662466188]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -69.88165026016243, -64.57664800604005, -34.902913681824856]], [[-34.902913681824856, 43.01465662466188, -64.57664800604005, -10.481407073259263, -64.57664800604005]], [[-34.902913681824856, 42.81869869284685, -69.38224302373561, -10.481407073259263, 43.01465662466188]], [[-96.47330712486206, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265]], [[7, 3, 5, -11, -4, 2, 54]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, 43.411858408450954, -10.768528666126521, -35.65861283942265]], [[-96.47330712486206, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265, -10.768528666126521]], [[-12.580228512164316, 42.59716035619264, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263, -10.481407073259263]], [[9, 4, 3, 7, 2, 5, 1, 1, 2, 6]], [[-34.902913681824856, -69.38224302373561, -10.481407073259263, -94.97100584944054, -34.902913681824856, -10.481407073259263, -94.97100584944054]], [[42.59716035619264, 43.01465662466188, -69.14764750208506, -69.38224302373561, -10.481407073259263, -69.38224302373561]], [[43.01465662466188, -34.902913681824856, -49.529210259810306, 42.59716035619264, -69.38224302373561, -9.527847657655224, -10.481407073259263, -64.57664800604005, 43.01465662466188]], [[42.59716035619264, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263]], [[43.01465662466188, -69.38224302373561, 42.81869869284685, -69.88165026016243, -10.481407073259263, -69.73647736308538, 43.01465662466188, -69.88165026016243]], [[43.01465662466188, -34.902913681824856, -35.42913486984109, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005]], [[True, False, False, False, False]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -64.57664800604005, 43.01465662466188, 43.01465662466188]], [[-96.47330712486206, 43.01465662466188, -96.47330712486206, -10.768528666126521, -35.65861283942265, -10.768528666126521]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, 43.411858408450954, -10.768528666126521, -35.65861283942265, 43.411858408450954]], [[42.87694882226923, -12.580228512164316, 42.59716035619264, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263, -10.481407073259263]], [[-34.967048506901335, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005]], [[43.01465662466188, -69.38224302373561, -69.88165026016243, -10.481407073259263, -69.73647736308538, -69.88165026016243]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005, -47.55433018390211]], [[-34.902913681824856, -9.527847657655224, -10.481407073259263, -94.97100584944054]], [[-10.902910189585176, -34.902913681824856, 43.01465662466188, -69.38224302373561, -10.481407073259263, -10.481407073259263, -34.902913681824856]], [[43.01465662466188, -10.481407073259263, 43.01465662466188]], [[42.59716035619264, 43.01465662466188, 41.82235199511542, -10.481407073259263, -69.38224302373561]], [[-34.902913681824856, 43.01465662466188, -69.38224302373561, -64.57664800604005, -69.38224302373561]], [[9, 3, 3, 7, 2, 5, 1, 1, 2, 6]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265, -69.14764750208506]], [[42.59716035619264, 43.01465662466188, 41.82235199511542, -10.481407073259263, -69.38224302373561, -10.481407073259263]], [[-34.902913681824856, 43.01465662466188, -34.902913681824856, 43.411858408450954, -10.768528666126521, -35.65861283942265, 43.411858408450954, -34.902913681824856]], [[-34.902913681824856, -34.902913681824856, -10.768528666126521, -35.65861283942265, -47.55433018390211, -64.57664800604005, -10.768528666126521, -10.768528666126521]], [[-34.902913681824856, -35.42913486984109, -34.967048506901335, 43.01465662466188, -34.902913681824856, -10.481407073259263, -64.57664800604005, -34.902913681824856]], [[9, 5, 4, 7, 2, 5, 1, 1, 2, 6]], [[42.81869869284685, 43.01465662466188, -96.47330712486206, -10.768528666126521, -35.65861283942265, -10.323022141346687]], [[-34.902913681824856, 43.01465662466188, -69.6514466229769, -10.481407073259263, 43.01465662466188]], [[-96.47330712486206, -34.902913681824856, 43.01465662466188, -34.902913681824856]], [[-9.527847657655224, -34.902913681824856, 43.01465662466188, -10.902910189585176, -10.493584737965575, -64.57664800604005]], [[43.01465662466188, -98.52620778096008, -69.73647736308538, -10.481407073259263, -10.481407073259263, 43.01465662466188]], [[-96.47330712486206, 42.87694882226923, 43.01465662466188, -34.902913681824856, -10.768528666126521, -35.65861283942265]], [[43.01465662466188, -34.902913681824856, 43.01465662466188, -34.902913681824856, -10.481407073259263, -9.527847657655224, -64.57664800604005, 43.01465662466188]], [[-10.768528666126521, -9.527847657655224, -10.481407073259263, -94.97100584944054, -34.902913681824856, -34.902913681824856]]]
results = [True, True, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, True, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_Monotonic(*inp), exp, 0)
| OK=True
==================== Problem #28 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether a list contains the given sublist or not.
Your answer will be tested on test cases like:
assert is_sublist([2,4,3,5,7],[3,7])==False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether a list contains the given sublist or not.
Your answer will be tested on test cases like:
assert is_sublist([2,4,3,5,7],[3,7])==False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether a list contains the given sublist or not.
Your answer will be tested on test cases like:
assert is_sublist([2,4,3,5,7],[3,7])==False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether a list contains the given sublist or not.
Your answer will be tested on test cases like:
assert is_sublist([2,4,3,5,7],[3,7])==False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether a list contains the given sublist or not.
Your answer will be tested on test cases like:
assert is_sublist([2,4,3,5,7],[3,7])==False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called is_sublist that checks if a list contains a given sublist. Let's think about how to approach this.
So the problem is, given a main list and a sublist, determine if the sublist appears in the main list in the same order. For example, if the main list is [1,2,3,4] and the sublist is [2,3], then it should return True. But if the sublist is [3,2], then False.
First, I need to consider how to check for the presence of the sublist. One straightforward way is to iterate through the main list and check at each position if the next elements match the sublist.
Let me think about the steps. Let's say the main list is called main and the sublist is sub. The length of the sublist is len_sub. For the sublist to be present, the main list must have at least len_sub elements. So first, check if len(main) < len(sub). If yes, return False.
Then, for each index i in main from 0 to len(main) - len_sub, check if the elements from i to i + len_sub -1 are equal to the sublist. If any of these slices matches, return True. If none do, return False.
Wait, how do I handle the slicing? Like, for each i in range(len(main) - len_sub + 1), right? Because if the main list is length 5 and the sublist is 2, then i can be 0,1,2,3. So len(main) - len_sub + 1 is the number of possible starting positions.
So the steps are:
1. Check if the sublist is empty? Well, maybe the problem assumes that the sublist is non-empty. But the test case given has a sublist of [3,7], which is length 2. But maybe the function should handle empty sublists? Well, the problem says "given sublist", but maybe the function should return True if the sublist is empty? Or maybe not. But the test case given doesn't have that. Let me think. For example, if the sublist is empty, then technically it's a sublist of any list. But perhaps the problem expects that the sublist is non-empty. However, the problem statement doesn't specify, so maybe the function should handle that. But since the test case given doesn't include that, maybe the problem expects that the sublist is non-empty. However, the function should handle all cases.
But for now, let's proceed with the general approach.
So, the code would be:
def is_sublist(main, sub):
len_main = len(main)
len_sub = len(sub)
if len_sub == 0:
return True # or maybe False? Depending on definition.
if len_main < len_sub:
return False
for i in range(len_main - len_sub + 1):
if main[i:i+len_sub] == sub:
return True
return False
Wait, but in Python, list slicing is up to but not including the end index. So main[i:i+len_sub] would get elements from index i to i + len_sub -1, which is correct.
So for example, if the sublist is [3,7], then in the main list [2,4,3,5,7], the code would check for each i:
i=0: [2,4] vs [3,7] no
i=1: [4,3] no
i=2: [3,5] no
i=3: [5,7] no. So returns False. Which matches the test case given: assert is_sublist([2,4,3,5,7],[3,7]) == False.
Another example: if main is [1,2,3,4], sub is [2,3], then i=1: [2,3] matches, returns True.
What about if the sublist is longer than the main list? Like main is [1,2], sub is [1,2,3]. Then len_main is 2, len_sub is 3. So len_main < len_sub, returns False.
What about if the sublist is empty? Well, the code as written would return True. But perhaps the problem expects that. However, the problem's test case doesn't cover that. But since the problem says "given sublist", maybe the function should handle empty sublists. However, perhaps the problem expects that the sublist is non-empty. But since the problem doesn't specify, perhaps the code should handle that.
But according to the problem's test case, the function is supposed to return False when the sublist is [3,7] in that example. So the code seems to handle that.
So the code seems correct. Now, let's write the function accordingly.
Now, the problem says that the function is called is_sublist, and the test case is assert is_sublist([2,4,3,5,7],[3,7])==False.
So the code should return False in that case. Let me test that scenario.
In the example, main list is [2,4,3,5,7], sub is [3,7]. The code checks for each i from 0 to 5-2=3 (i ranges from 0 to 3 inclusive). So i=0: [2,4] no. i=1: [4,3] no. i=2: [3,5] no. i=3: [5,7] no. So returns False. Correct.
Another test case: is_sublist([1,2,3,4], [2,3]) returns True. Another case: is_sublist([1,2,3,4], [3,4]) returns True. And if the sublist is [1,2,3], then main list [1,2,3] returns True.
So the code should work.
Now, the code needs to be written as a self-contained function. Also, the code needs to be in a markdown code block.
So the Python code would be:
def is_sublist(main, sub):
len_main = len(main)
len_sub = len(sub)
if len_sub == 0:
return True
if len_main < len_sub:
return False
for i in range(len_main - len_sub + 1):
if main[i:i+len_sub] == sub:
return True
return False
Wait, but what if the sublist is empty? For example, if sub is empty list, then according to the code, returns True. But maybe the problem expects that. However, the problem's test cases don't include this. But since the problem says "given sublist", perhaps the function should handle that. However, the problem's test case may not cover this. But the code is correct in that case.
But maybe the problem expects that the sublist is non-empty. However, the code is correct according to the problem's test case.
So this should be the correct code.
```python
def is_sublist(main, sub):
len_main = len(main)
len_sub = len(sub)
if len_sub == 0:
return True
if len_main < len_sub:
return False
for i in range(len_main - len_sub + 1):
if main[i:i+len_sub] == sub:
return True
return False
```
----------------------------------------------
Result: Pred=def is_sublist(main, sub):
len_main = len(main)
len_sub = len(sub)
if len_sub == 0:
return True
if len_main < len_sub:
return False
for i in range(len_main - len_sub + 1):
if main[i:i+len_sub] == sub:
return True
return False | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[2, 4, 3, 5, 7], [3, 7]], [[2, 4, 3, 5, 7], [4, 3]], [[2, 4, 3, 5, 7], [1, 6]], [[], []], [[], [1]], [['r'], []], [['sfIngs', 'GYVu', 'r'], []], [['r', 'sfIngs', 'GYVu'], [False, 'klXTmRZyQ']], [[False, 99.97028427774339, 82, 'GYVu', False, 'Ok', None, [1, -71.80691717114227]], []], [['r', 'sfIngs', 'GYVu', 'GYVu'], ['r', 'sfIngs', 'GYVu', 'GYVu']], [['r', 'sgfIngs', 'GYVu', 'GYVu'], ['r', 'sgfIngs', 'GYVu', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYVu'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu']], [['r', 'sfIngs', 'GYVu'], ['r', 'sfIngs', 'GYVu']], [['sfIngs', 'GYVu'], ['sfIngs', 'GYVu']], [['sgfIngs', 'sfIngs', 'GYVu', 'r', 'r', 'sfIngs'], ['sgfIngs', 'sfIngs', 'GYVu', 'r', 'r', 'sfIngs']], [['r', 'GYVu', 'r'], []], [['r', 'GYVu', 'r'], ['r', 'GYVu', 'r']], [['sgfIngs', 'sfIngs', 'GYVu', 'sfIngsr', 'GYV', 'r', 'sfIngs'], ['sgfIngs', 'sfIngs', 'GYVu', 'sfIngsr', 'GYV', 'r', 'sfIngs']], [[1], [1]], [[None, False, {'sfIngsr': 42.34905566158099, 'FHvMaMnTCg': -74.03921201241215, 'hKRFjm': -74.21853866002988, 'rKQ': 40.63712034844792}, {'24.822944608944297': 'pfIhkuLtSg', '-22.735241874996206': 's', '-13.009939375362165': 'sfIngsr', '-71.80691717114227': 'VtqKcYvzg', '99.97028427774339': 'DBzU', '68.8678541991217': 'GYVu', '-83.5332401941628': 'PctAoxwD'}, [66, 1, -51, 1, -59, 1, False, -71], True, 'sfIngs', 1], []], [['GYVu', 'pfIhkuLtSg', 'O', 'Odpagl', 'Casb'], []], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'GYV'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'GYV']], [[-42, 8, -83.5332401941628, -82, 38.16772877208774, {'VtqKcYvzg': 47.40072133316414, 'sLmQQSONWn': -13.009939375362165, 'O': 36, 'rKQ': [48, -59]}, -40], []], [[8, None, False, {'sfIngsr': 42.34905566158099, 'FHvMaMnTCg': -74.03921201241215, 'hKRFjm': -74.21853866002988, 'rKQ': 40.63712034844792}, {'24.822944608944297': 'pfIhkuLtSg', '-22.735241874996206': 's', '-13.009939375362165': 'sfIngsr', '-71.80691717114227': 'VtqKcYvzg', '99.97028427774339': 'DBzU', '68.8678541991217': 'GYVu', '-83.5332401941628': 'PctAoxwD'}, [66, 1, -51, 1, -59, 1, False, -71], True, 'sfIngs', 1], []], [['r', 'sfIngs', 's'], [False, 'klXTmRZyQ']], [['r', 'sgfIngs', 'GYVu', 'pfIhkuLtSgr', 'GYVu'], ['r', 'sgfIngs', 'GYVu', 'pfIhkuLtSgr', 'GYVu']], [[[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 90.16807182684596, 'qyujtuO', 82, 75.22089802044161, 82], [[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 90.16807182684596, 'qyujtuO', 82, 75.22089802044161, 82]], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'r']], [['GYVur', 'sgfIngs', 'GYVu', 'GYVu'], ['GYVur', 'sgfIngs', 'GYVu', 'GYVu']], [['sfIngsGYVu', 'sfIngs', 'GYVu'], ['sfIngsGYVu', 'sfIngs', 'GYVu']], [['r', 'GYVu', 'r', 'r'], ['r', 'GYVu', 'r', 'r']], [['sfIngSFVGYVVgWCfDjsGYVu', 'sfIngSFVVgWCfDjsGYVu', 'sfIngs', 'GYVu'], ['sfIngSFVGYVVgWCfDjsGYVu', 'sfIngSFVVgWCfDjsGYVu', 'sfIngs', 'GYVu']], [['r', 'GYVu', 'r'], [True, True, True, False, True, False, False, True]], [['r'], ['r']], [['r', 'GSFVVgWCfDju', 'GYVu', 'r'], ['r', 'GSFVVgWCfDju', 'GYVu', 'r']], [['sgfIngs', 'sfIngs', 'GYVu', 'sfIngsr', 'GYV', 'r', 'GYV'], ['sgfIngs', 'sfIngs', 'GYVu', 'sfIngsr', 'GYV', 'r', 'GYV']], [[], [True, False, True]], [['r', 'GYVu', 'r'], [-49.293443668830214, 11.89338685730192, 38.68012886425632, 64.91527494125927, -74.03921201241215, 0.3374408817541621]], [['r', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu'], ['r', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu']], [[90.16807182684596, 'qyujtuO', 82, 75.22089802044161, 82], [90.16807182684596, 'qyujtuO', 82, 75.22089802044161, 82]], [['r', 'sfIngs', 'GYVu', 'r', 'r'], ['r', 'sfIngs', 'GYVu', 'r', 'r']], [[90.16807182684596, 'qyujtuO', 75.22089802044161, 'sfIngSFVGYVVgWCfDjsGYVu', 82], [90.16807182684596, 'qyujtuO', 75.22089802044161, 'sfIngSFVGYVVgWCfDjsGYVu', 82]], [['r', 'GYVu', 'r'], [-49.293443668830214, 11.89338685730192, 38.68012886425632, 64.91527494125927, -74.03921201241215, 0.3374408817541621, -74.03921201241215]], [['GYVur', 'sgfIngs', 'GYVu', 'GYVu', 'GYVu'], ['GYVur', 'sgfIngs', 'GYVu', 'GYVu', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYYVu', 'GYV', 'GYVu', 'GYV'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYYVu', 'GYV', 'GYVu', 'GYV']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVu', 'r']], [[-42, 9, -83.5332401941628, -82, 38.16772877208774, {'VtqKcYvzg': 47.40072133316414, 'sLmQQSONWn': -13.009939375362165, 'O': 36, 'rKQ': [48, -59]}, -40], [-42, 9, -83.5332401941628, -82, 38.16772877208774, {'VtqKcYvzg': 47.40072133316414, 'sLmQQSONWn': -13.009939375362165, 'O': 36, 'rKQ': [48, -59]}, -40]], [['r', 'sfIngs', 'GYVu'], [False]], [['GSFVVgWCfDju', 'r', 'sfIngs', 'GYVu', 'r', 'r', 'GSFVVgWCfDju', 'r'], ['GSFVVgWCfDju', 'r', 'sfIngs', 'GYVu', 'r', 'r', 'GSFVVgWCfDju', 'r']], [['sfIngs', 'PctAoxwD', 'GYVu'], ['sfIngs', 'PctAoxwD', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r']], [['sfIngs', 'PctAoxwD', 'GVYVu', 'GYVu', 'PctAoxwD'], ['sfIngs', 'PctAoxwD', 'GVYVu', 'GYVu', 'PctAoxwD']], [['r', 'sfIngs', 'u', 'GYV', 'GYVu'], ['r', 'sfIngs', 'u', 'GYV', 'GYVu']], [['r', 'VtqKcYvzg', 'r'], []], [['GYVur', 'GYYVur', 'sgfIngs', 'GYVu', 'GYVu'], ['GYVur', 'GYYVur', 'sgfIngs', 'GYVu', 'GYVu']], [[True, True, True, False, True, False, False, True, True], [True, True, True, False, True, False, False, True, True]], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'rGSFVVgWCfDju', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'rGSFVVgWCfDju', 'GYVu', 'r']], [['r', 'sfIngs', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'r']], [[-74.03921201241215, 75.22089802044161, -38.48806518576453], []], [[False], [True, False, True]], [['sfIngs', 'GYVu', 'r'], ['sfIngs', 'GYVu', 'r']], [['r', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu'], ['r', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu', 'GYVu']], [['sfIngsGYVu', 'sfIngs', 'GYVu', 'sfIngs', 'sfIngsGYVu'], ['sfIngsGYVu', 'sfIngs', 'GYVu', 'sfIngs', 'sfIngsGYVu']], [['r', 'GYVu', 'r'], [True, True, True, True, False, False, True]], [['r', 'sfInVtqKcYvzggs', 'GYVu'], ['r', 'sfInVtqKcYvzggs', 'GYVu']], [['r', 'GYVu', 'r', 'r'], [True, True, True, False, True, False, False, True]], [[[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 65.5370586539689, 'qyujtuO', 82, 75.22089802044161, 82, 82], [[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 65.5370586539689, 'qyujtuO', 82, 75.22089802044161, 82, 82]], [['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r'], ['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r']], [['r', 'sfIngs', 's'], ['klXTmRZyQ']], [['r', 'GYYVu', 'GYVu'], ['r', 'GYYVu', 'GYVu']], [[[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 90.16807182684596, 'qyujtuO', 82, 82], [[95.17158052544048, 'SFVVgWCfDj', -0.3414328935261324], 90.16807182684596, 'qyujtuO', 82, 82]], [[[95.17158052544048, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 65.5370586539689, [95.17158052544048, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 'qyujtuO', 82, 75.22089802044161, 82], [[95.17158052544048, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 65.5370586539689, [95.17158052544048, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 'qyujtuO', 82, 75.22089802044161, 82]], [['r', 'sfIngs', 'GYVu', 'GYVusfIngSFVGYVVgWCfDjsGYVu', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVusfIngSFVGYVVgWCfDjsGYVu', 'GYVu', 'r']], [['r', 'sfIngs', 's'], ['klXTmRZyQ', 'klXTmRZyQ']], [['sfIngsGYVu', 'sfIngs', 'GYVu', 'ssfIngs', 'sfIngsGYVu'], ['sfIngsGYVu', 'sfIngs', 'GYVu', 'ssfIngs', 'sfIngsGYVu']], [[-49.293443668830214, -0.4410790823334596, 11.89338685730192, 38.68012886425632, 64.91527494125927, 47.40072133316414, -74.03921201241215, 0.3374408817541621], [-49.293443668830214, -0.4410790823334596, 11.89338685730192, 38.68012886425632, 64.91527494125927, 47.40072133316414, -74.03921201241215, 0.3374408817541621]], [['r', 'GYVu', 'FHvMaMnTCg', 'rr'], ['r', 'GYVu', 'FHvMaMnTCg', 'rr']], [['klXTmRZyQr', 'sfIngs', 'GYVu', 'GYVu', 'sfIsngs', 'GYVu'], ['klXTmRZyQr', 'sfIngs', 'GYVu', 'GYVu', 'sfIsngs', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r', 'r']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'GYV', 'GYVu'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'GYV', 'GYVu']], [['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r', 'GYVu'], ['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYYVu', 'GYV', 'GYVVu', 'GYV'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYYVu', 'GYV', 'GYVVu', 'GYV']], [['r', 'GYVu', 'r', 'r'], [True, True, True, True, False, False, True]], [[90.16807182684596, 'qyujtuO', 75.22089802044161, 'sfIngSFVGYVVgWCfDjsGYVu', 'GYYVur', 82], [90.16807182684596, 'qyujtuO', 75.22089802044161, 'sfIngSFVGYVVgWCfDjsGYVu', 'GYYVur', 82]], [['r', 'snfInVtqKcYvzggs', 'sfInVtqKcYvzggs', 'GYVu'], ['r', 'snfInVtqKcYvzggs', 'sfInVtqKcYvzggs', 'GYVu']], [['rGYV', 'GYVu'], ['rGYV', 'GYVu']], [['r', 'rGYV', 'GYVu'], ['r', 'rGYV', 'GYVu']], [[False], [False]], [['sfIngsGYVu', 'GSFVVgWCfDjusfIngs', 'sfIngs', 'GYVu', 'sfIngsGYVu'], ['sfIngsGYVu', 'GSFVVgWCfDjusfIngs', 'sfIngs', 'GYVu', 'sfIngsGYVu']], [['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVVu', 'GYVu', 'r', 'r', 'GYVu', 'r']], [['r', 'GYVu'], ['r', 'GYVu']], [['r', 'sgfIngs', 's', 'GYVu', 'pfIhkuLtSgr', 'GYVu'], ['r', 'sgfIngs', 's', 'GYVu', 'pfIhkuLtSgr', 'GYVu']], [['GYVGu', 'r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r'], ['GYVGu', 'r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'GYVGu', 'r']], [['r', 'sfIngs', 'GYVu', 'GYVusfIngSFVGYVVgWCfDjsGYVu', 's', 'Casb', 'GYVu', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVusfIngSFVGYVVgWCfDjsGYVu', 's', 'Casb', 'GYVu', 'r']], [['sfIngs', 'GYVu', 'sfIngrrs', 'GYVu', 'GOkV', 'GYVGu', 'rr'], ['sfIngs', 'GYVu', 'sfIngrrs', 'GYVu', 'GOkV', 'GYVGu', 'rr']], [['YrGYV', 'GYVu', 'GOku'], ['YrGYV', 'GYVu', 'GOku']], [['GYVu', 'pfIhkuLtSg', 'O', 'Odpagl', 'Casb', 'GYVu'], [[87.8259025409381, 'GYVusfIngSFVGYVVgWCfDjsGYVu', [True, True], {'-51': -74.03921201241215, '60': 40.71791810053759, 'false': 5.735570485483905, '-10': 24.822944608944297, '8': 0.3374408817541621, '41': 64.91527494125927, '-82': -25.52239838327162, '-36': -41.74691632795968, '61': -74.21853866002988, '-83': 99.97028427774339}, False, [66, 68, -71, -71, -82, -65, -51], {'GSFVVgWCfDjusfIngs': 'ssfIngs', 'GYYVu': 'GOkV', 'uTw': 'GYVGu', 's': 'SFVVgWCfDj', 'klXTmRZyQr': 'FHvMaMnTCg', 'sfIngrrs': 'mXw', 'HGEtjdFe': 'sfIsngs', 'DBzU': 'EV', 'sfIngSFVGYVVgWCfDjsGYVu': 'WpVzXU', 'Xf': 'sfIngrrs'}], [], -10, -29, None]], [[True, True, True, False, True, False, False, True, True, False], [True, True, True, False, True, False, False, True, True, False]], [['r', 'sfIngs', 'r', 'GYVVu', 'GYVu', 'r', 'r'], ['r', 'sfIngs', 'r', 'GYVVu', 'GYVu', 'r', 'r']], [['r', 'sfInsfIngSFVGYVVgWCfDjsGYVugs', 'u', 'GYV', 'GYVu'], ['r', 'sfInsfIngSFVGYVVgWCfDjsGYVugs', 'u', 'GYV', 'GYVu']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'ssfIngs', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GYV', 'GYVu', 'ssfIngs', 'r']], [['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'WpVzXU', 'r', 'r'], ['r', 'sfIngs', 'GYVu', 'GYVu', 'GOkV', 'WpVzXU', 'r', 'r']], [[[94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 65.5370586539689, [94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 'qyujtuO', 82, [94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 75.22089802044161, 82], [[94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 65.5370586539689, [94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 'qyujtuO', 82, [94.17409950967779, 'SFVVgWCfDj', 'SFVVgWCfsgfIngsDj', -0.3414328935261324], 75.22089802044161, 82]], [['sgfIngs', 's', 'GYVu', 'pfIhkuLtSgr'], ['sgfIngs', 's', 'GYVu', 'pfIhkuLtSgr']]]
results = [False, True, False, True, False, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True, False, True, True, True, False, False, True, True, True, True, False, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, False, True, False, True, True, False, True, True, True, True, False, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, False, True, True, True, True, True, True, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_sublist(*inp), exp, 0)
| OK=True
==================== Problem #29 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether all the given tuples have equal length or not.
Your answer will be tested on test cases like:
assert get_equal([(11, 22, 33), (44, 55, 66)]) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether all the given tuples have equal length or not.
Your answer will be tested on test cases like:
assert get_equal([(11, 22, 33), (44, 55, 66)]) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether all the given tuples have equal length or not.
Your answer will be tested on test cases like:
assert get_equal([(11, 22, 33), (44, 55, 66)]) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether all the given tuples have equal length or not.
Your answer will be tested on test cases like:
assert get_equal([(11, 22, 33), (44, 55, 66)]) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find whether all the given tuples have equal length or not.
Your answer will be tested on test cases like:
assert get_equal([(11, 22, 33), (44, 55, 66)]) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called get_equal that checks if all the tuples in a given list have the same length. Let's see. The input is a list of tuples, right? So the function should return True if every tuple has the same number of elements, and False otherwise.
First, I need to figure out how to get the length of each tuple. Oh right, in Python, you can use the len() function. So for each tuple in the list, I can check its length.
But how do I check if all of them are the same? Well, maybe I can take the length of the first tuple and then compare all others to that. But wait, what if the list is empty? Oh, the problem probably assumes there's at least one tuple, but maybe I should handle that case just in case.
Wait, the test case given is [(11, 22, 33), (44, 55, 66)], which are two tuples each of length 3. The function returns True. So the approach would be: check all tuples' lengths equal to the first one's.
So here's the plan: Get the length of the first tuple. Then loop through all the other tuples and check if each has the same length. If any of them doesn't, return False. Otherwise, return True.
But what if the input list is empty? Like, if there are no tuples? Well, the problem says "given tuples", but maybe the function should handle that. However, the test case provided has two tuples, so maybe the function is expected to handle non-empty lists. But to be safe, perhaps the function should return True if the list is empty? Or maybe the problem expects that the input is a non-empty list. Hmm, but the problem says "given tuples", so maybe the input list is not empty. But I should handle cases where the list has only one tuple, which would trivially have all equal lengths.
So, the steps:
1. Check if the list is empty. Well, if it's empty, maybe return True? Or maybe the problem expects that the input is a list of tuples. But the function's parameters would be a list. Let's think: if the list is empty, then there are no tuples, so technically all (zero) tuples have equal length. But that's a corner case. However, the problem's test case has two tuples, so maybe the function is supposed to handle that. But perhaps the problem expects that the input list is non-empty. However, the code should handle all possible cases.
But let's proceed. Let's assume that the input is a list of tuples, possibly empty.
So, for the code:
def get_equal(tuples_list):
# check if all tuples in tuples_list have the same length
# get the first length
if not tuples_list:
return True # or maybe raise an error? But the problem's test case doesn't have this.
first_len = len(tuples_list[0])
for t in tuples_list[1:]:
if len(t) != first_len:
return False
return True
Wait, but what if the list is empty? Like, if tuples_list is empty, then the code returns True. But maybe that's correct. For example, if there are zero tuples, then all of them (none) have equal length. But that's a bit of a logical edge case. However, the problem's test case has two tuples, so perhaps the function is intended to work for non-empty lists. However, the code should handle all cases.
But the problem says "given tuples", which may imply that the input list is non-empty. However, the code should handle all possibilities.
So, the code as written would handle that.
Testing the sample case: [(11,22,33), (44,55,66)] → first_len is 3. The next tuple is also 3 → returns True.
Another test case: [(1,2), (3,4,5)] → returns False.
Another case: [(1,), (2,)] → returns True.
What about if the list is empty? The code returns True. But maybe the problem expects that? Well, the problem's test case doesn't cover that, but the code is correct in that case.
So, the function should be written as such.
Now, the code needs to be written as a self-contained Python function. The user says that the answer will be tested on test cases like the given assert. So the function should be called get_equal and take a list of tuples as input.
So the code would be:
def get_equal(tuples_list):
if not tuples_list:
return True
first_len = len(tuples_list[0])
for t in tuples_list[1:]:
if len(t) != first_len:
return False
return True
But wait, what if the list has only one tuple? Then, the loop doesn't run, and returns True, which is correct.
Yes, that's correct.
So that's the code. Let me check for possible errors. For example, if the input is not a list of tuples? Well, the problem says that the input is given tuples, so perhaps the function is supposed to assume that the input is a list of tuples. So no need to handle that.
Thus, the code should be correct.
```python
def get_equal(tuples_list):
if not tuples_list:
return True
first_len = len(tuples_list[0])
for t in tuples_list[1:]:
if len(t) != first_len:
return False
return True
```
----------------------------------------------
Result: Pred=def get_equal(tuples_list):
if not tuples_list:
return True
first_len = len(tuples_list[0])
for t in tuples_list[1:]:
if len(t) != first_len:
return False
return True | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[(11, 22, 33), (44, 55, 66)]], [[(1, 2, 3), (4, 5, 6, 7)]], [[(1, 2), (3, 4)]], [[(1, 2, 3), (), (4, 5)]], [[(1, 2, 3), (), (4, 5), (6, 7, 8)]], [[(1,), (2, 3), (4, 5, 6), (7, 8, 9, 10), (11, 12, 13, 14, 15)]], [[(1,), (2, 3), (4, 5, 6), (7,)]], [[(1, 2, 3, 4), (5, 6), (7, 8, 9)]], [[(), (1,), (2, 3), (4, 5, 6), (7, 8, 9, 10)]], [[(1, 2, 3), (4, 5), (), (6, 7, 8), (9, 10)]], [[(1, 2, 3), (4,), (5, 6, 7), (8, 9, 10), (11, 12, 13)]], [[(1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12)]], [[(1, 2, 3), (4, 5), (6, 7), (8, 9), (10,)]], [[(1,), (2, 3), (), (4, 5, 6, 7), (8, 9, 10)]], [[(1, 2, 3, 4, 5), (6, 7, 8), (9, 10, 11, 12)]], [[(1, 2), (3, 4), (5, 6), (7, 8)]], [[(1, 2, 3), (4, 5, 6), (7, 8, 9), (10, 11, 12)]], [[(1, 2, 3), (4, 5), (6, 7, 8), (9, 10, 11)]], [[(1, 2), (3, 4), (5, 6, 7), (8,)]], [[(1, 2), (3, 4), (5, 6, 7)]], [[(1,), (2, 3), (4, 5), (6, 7, 8)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4)]], [[(1, 1), (2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (2, 3)]], [[(1, 2), (1, 2, 3), (), (4, 5), (6, 7, 8)]], [[(1, 2, 3), (4,), (5, 6, 7), (8, 9, 10), (8, 10), (11, 12, 13)]], [[(1, 2, 3, 4, 5), (6, 7, 8), (9, 10, 11, 12), (9, 10, 11, 12, 12)]], [[(1,), (2, 3, 2), (), (4, 5, 6, 7), (8, 9, 10)]], [[(1, 2, 3), (4, 5), (6, 7, 8), (9, 10, 11), (4, 5)]], [[(), (), (2, 3), (4, 5, 6), (7, 8, 9, 10), ()]], [[(1, 2, 3), (), (4, 4, 5)]], [[(2, 3, 2, 3), (1,), (2, 3, 2), (), (4, 5, 6, 7), (8, 11, 10), (8, 9, 10)]], [[(1,), (8, 3), (4, 5), (6, 7, 8)]], [[(1, 2, 3), (3, 4), (5, 6, 7), (8, 9, 10), (11, 12, 13)]], [[(1, 2, 3), (4,), (5, 7), (8, 9, 10), (8, 10), (11, 12, 13), (1, 2, 3)]], [[(1,), (2, 3, 2), (4, 5, 6, 7), (8, 9, 10)]], [[(1, 2), (3, 4), (5, 6, 7), (8,), (8,)]], [[(1, 2), (3, 4, 4), (3, 4), (5, 6, 7), (11, 4), (3, 4)]], [[(1, 2, 3), (), (4,), (6, 7, 8)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4), (1, 2)]], [[(1, 2, 3), (4, 5), (6, 7), (8, 9), (), (10,)]], [[(1, 2), (3, 4, 3), (5, 6, 7), (8,)]], [[(1,), (4, 5), (6, 7, 8)]], [[(1, 2, 3), (4, 5), (6, 7, 8), (9, 10, 5, 11)]], [[(1, 2, 3, 3), (), (9, 10)]], [[(1, 2), (1, 2, 3), (4, 5), (6, 7, 8), (9, 10, 5, 11), (1, 2)]], [[(1, 2), (3,), (5, 6, 5, 7), (8,), (8,)]], [[(2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (14, 2, 3)]], [[(1, 2, 3, 4), (5, 6), (8, 9)]], [[(1, 2, 3), (), ()]], [[(1, 2, 3), (4, 5, 6), (4, 5, 5, 6), (7, 8, 9), (10, 11, 12)]], [[(1, 2), (3, 4), (5, 6, 7), (1, 2)]], [[(1, 2, 3), (4,), (5, 7), (8, 10), (11, 12, 13), (1, 2, 3)]], [[(3, 1, 2), (1, 2), (3, 4), (5, 6, 7), (8,)]], [[(1, 2, 3), (4,), (7, 6, 7), (8, 9), (10,)]], [[(4, 5)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4), (5, 6, 7)]], [[(1, 2, 3), (4, 5), (5,), (6, 7, 8), (9, 10, 11), (4, 5)]], [[(1, 2, 3), (4, 5, 6), (4, 5, 5, 6), (7, 8, 9), (10, 11, 12), (7, 8, 9)]], [[(1, 2), (3, 4, 4), (3, 4), (5, 6, 7), (11, 4), (3, 4), (11, 11, 4)]], [[(1, 2, 3), (), (4, 5), (7, 8), (7, 8)]], [[(1, 2, 3), (4,), (5, 6, 7), (8, 9, 10), (8, 10), (11, 12, 13), (8, 10)]], [[(1, 2, 3), (7, 2, 3), (4, 5), (6, 7, 8), (9, 10, 11), (4, 5)]], [[(1,), (4, 5, 6), (2, 3, 2), (), (4, 5, 6, 7), (8, 9, 10)]], [[(1, 2), (3, 4), (5, 6, 7), (5, 6, 7)]], [[(2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (14, 2, 3), (11, 12, 13, 14, 15)]], [[(1,), (4, 5, 6), (), (4, 5, 6, 7), (8, 9, 10)]], [[(2,), (3, 4), (5, 6, 7), (3, 4, 4), (3, 4, 4), (3, 4)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4), (5, 6, 7), (5, 6, 7)]], [[(), (3,), (1,), (2, 3), (4, 5, 6), (7, 8, 9, 10), (2, 3), (1,)]], [[(), (3,), (1,), (2, 3), (4, 5, 6), (7, 8, 9, 10), (1,)]], [[(1,), (2, 2), (3,), (), (4, 5, 6, 7), (8, 9, 9, 10)]], [[(1, 1), (2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (2, 3), (1, 1)]], [[(1, 2), (3, 4, 4), (3, 4), (3, 4, 4), (5, 6, 7), (11, 4), (3, 4), (11, 11, 4)]], [[(1,), (2, 2), (2,), (3,), (4, 5, 6, 7), (8, 9, 9, 10)]], [[(1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12), (1, 2), (1, 2), (3, 4, 5)]], [[(1,), (8, 3), (4, 5), (4, 1, 5), (6, 7, 8)]], [[(2,), (3, 4), (5, 6, 7), (2, 2), (3, 4, 4), (3, 4, 4), (3, 4)]], [[(1, 1), (2, 3), (4, 5, 6), (11, 12, 13, 14, 15)]], [[(2, 2), (1, 2), (3,)]], [[(1,), (4, 5, 6), (4, 5, 6, 7), (8, 9, 10)]], [[(9, 10, 11, 10), (1, 2, 3), (4, 5), (6,), (5,), (6, 7, 8), (9, 10, 11), (4, 5)]], [[(1,), (4, 5, 6), (2, 3, 2), (), (4, 5, 6, 7), (8, 9, 10), (4, 5, 6, 7)]], [[(), ('D', 'DgNw'), (), (2, 3), (4, 5, 6), (), ()]], [[(1,), (4, 5), (6, 7, 8), (1,)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4), (8,), (8,)]], [[(4, 5, 5), (1, 2, 3), (), (6, 7, 8), (4, 5)]], [[(4, 5, 5), (1, 2, 3), (), (1, 14, 3), (6, 7, 8), (4, 5)]], [[(1,), (4, 5, 6), (2, 3, 2), (), (8, 9, 10)]], [[(4,), (4, 5)]], [[(1, 2), (3, 4), (5, 6, 7), (7,), (3, 4), (8,), (8,), (8,)]], [[(1, 2, 3), (4, 5), (6, 7, 8), (6, 7, 8, 6), (9, 10, 11)]], [[(1, 2, 3, 4), (5, 6), (6, 8, 9)]], [[(1, 1), (2, 3), (2, 3, 3), (4, 5, 6), (11, 12, 13, 14, 15), (2, 3), (1, 1)]], [[(1, 2, 3), (3, 4), (5, 6, 7), (8, 9, 10), (11, 12, 13), (1, 2, 3), (11, 12, 13), (3, 4)]], [[(2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (14, 2, 3), (11, 12, 13, 14, 15), (11, 12, 13, 14, 15)]], [[(1,), (4, 5, 6), (4, 5, 6, 7), (1,)]], [[(9, 10, 11, 10), (1, 2, 3), (4, 5), (5,), (6, 7, 8), (9, 10, 11), (4, 5, 5), (5,)]], [[(1, 1), (2,), (4, 5, 6, 4), (11, 12, 13, 14, 15), (2, 3)]], [[(1, 2, 3), (7, 8, 9), (10, 11, 12)]], [[(3, 3), (1, 1), (2, 3), (4, 5, 6), (5, 12, 13, 14, 15, 12), (2, 3)]], [[(1,), (4, 6, 6), (4, 5, 6, 7), (4, 5, 6, 7, 7), (1,)]], [[(1, 2, 2), (3, 4), (1, 2)]], [[(), ('D', 'DgNw'), (True, True, True, False, True, True), (2, 3), (4, 5, 6), (), (), ()]], [[(1, 2), (3, 4, 5), (6, 7, 8, 9), (10, 11, 12), (1, 2)]], [[(1, 2, 3), (4, 5, 5), (4, 5), (6, 7, 8), (6, 7, 8, 6), (9, 10, 11)]], [[(4, 5), (1, 2, 3), (), (4, 5), (7, 8), (7, 8)]], [[(9, 10, 11, 10), (1, 2, 3), (4, 5), (6, 7, 8), (9, 10, 11), (4, 5, 5), (4, 14), (5,)]], [[(1, 2, 3), (3, 4), (5, 6, 7), (8, 9, 10)]], [[(2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (14, 2, 13, 3), (11, 12, 13, 12, 14, 15)]], [[(2, 3, 2, 3), (1,), (2, 3, 2), ({'-50': -92, '-31': 10, '24': 8, '12': 5}, 'DgNw', True, -66, -77.47956663455827, None, None, False, 'DgNw'), (4, 5, 6, 7), (8, 11, 10), (8, 9, 10)]], [[(6, 7), (6, 7), (1, 2), (3, 4), (5, 6, 7), (1, 2)]], [[(2, 3), (4, 5, 6), (11, 12, 13, 14, 15), (2, 3), (1, 1)]], [[(1, 2, 3, 4), (5, 6), (5, 6, 6), (5, 6)]], [[(1, 2, 3), (1, 7, 2, 3), (3, 4), (5, 6, 7), (8, 9, 10), (11, 12, 13), (1, 2, 3), (11, 12, 13), (3, 4), (1, 2, 3), (8, 9, 10)]], [[(1,), (4, 5), (6, 7, 8), (4, 5)]], [[(1,), (6, 7, 8), (1,)]], [[(2,), (3, 4), (5, 6, 7), (2, 2), (3, 4, 4), (3, 4, 4), (2, 3, 2), (3, 4)]], [[(), (1,), (4, 5, 6), (4, 5, 6, 7, 5), (1,)]], [[(1, 2), (3, 4), (5, 6, 7), (3, 4), (3, 4)]], [[(1, 2, 3), ()]], [[(9, 10, 11, 11), (1, 2, 3), (4, 5), (6, 8), (6, 7, 8, 6), (9, 10, 11)]]]
results = [True, False, True, False, False, False, False, False, False, False, False, False, False, False, False, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(get_equal(*inp), exp, 0)
| OK=True
==================== Problem #30 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of elements.
Your answer will be tested on test cases like:
assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of elements.
Your answer will be tested on test cases like:
assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of elements.
Your answer will be tested on test cases like:
assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of elements.
Your answer will be tested on test cases like:
assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort a list of elements.
Your answer will be tested on test cases like:
assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called comb_sort that sorts a list of elements. The test case given is assert comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]. So the function should return a sorted list in ascending order.
Wait, the problem says to sort a list of elements. The example uses integers, but the function should probably work for any comparable elements. But the question doesn't specify if it's for integers only or any data type. Well, the standard sort in Python is stable and works for any elements that can be compared.
But how to implement comb_sort? Oh right, comb sort is a variant of bubble sort. Let me recall how comb sort works. The idea is to compare elements with a certain gap, which decreases over time. The gap starts at the length of the list divided by some factor (like 1.3), and then reduces by that factor each time until it reaches 1. Then it does a final bubble pass to ensure the list is sorted.
So the steps for comb_sort would be:
1. Initialize the gap as the length of the list. Then, while the gap is greater than 1, keep reducing it by dividing by 1.3 each time (taking the floor of the result). But wait, the initial gap is usually set to the length of the list, but maybe in some implementations it's set to the length minus 1. Hmm. Need to check the exact steps.
Wait, according to the comb sort algorithm, the initial gap is the length of the list. Then, in each iteration, the gap is divided by 1.3 (using floor division). The process continues until the gap is 1. Then, a final pass with gap 1 is done, which is essentially a bubble sort pass.
So the steps for the algorithm would be:
- Get the length of the list, n.
- Initialize gap to n.
- While gap > 1:
- Set gap = floor(gap / 1.3)
- Then, perform a series of comparisons and swaps with elements that are 'gap' apart.
- For i from 0 to n - gap - 1:
- If list[i] > list[i + gap], swap them.
- After the gap reaches 1, do a final pass to ensure the list is sorted.
Wait, but during the process, after each gap reduction, we need to perform a pass through the list with that gap. So the loop is: while gap > 1, do the pass, then reduce the gap.
Wait, the standard algorithm steps are:
gap = n
while gap > 1:
gap = gap / 1.3 (rounded down)
swapped = False
for i in range(0, n - gap):
if a[i] > a[i + gap]:
swap a[i] and a[i + gap]
swapped = True
if not swapped:
break
Wait, but in some implementations, after the gap is reduced, you have to check if any swaps occurred. If no swaps occurred during a pass, the list is already sorted, and you can break early.
But in the original problem, the function is supposed to return the sorted list. So the comb_sort function will need to modify the list in place or return a new sorted list. But since the test case uses a list and expects a new sorted list, perhaps the function should return a new list, not modify the original. However, in Python, lists are mutable, so if the function modifies the original list, the test case would pass if the original list is modified. But the test case is using comb_sort([5,15,...]) and expects the sorted list. So the function should return a new sorted list, not modify the original.
Wait, but the test case is written as comb_sort([5, 15, 37, 25, 79]) == [5, 15, 25, 37, 79]. So the function is supposed to return the sorted list, not modify the original. So the function should create a copy of the input list and sort that.
So first, the function should take the list as input, create a copy, then perform comb sort on the copy, and return it.
So, the steps for the function:
def comb_sort(lst):
# create a copy of the list to avoid modifying the original
arr = lst.copy()
n = len(arr)
gap = n
while gap > 1:
# calculate the new gap
gap = int(gap / 1.3)
# if gap is 0, set to 1?
# wait, when gap is 1, the loop will exit. So during the loop, gap is greater than 1.
# So during the loop, after calculating gap, if it becomes 0, we need to set to 1?
# For example, if n is 1, then gap is 1, loop doesn't run. But for n=2, initial gap is 2, then divided by 1.3 gives 1.538, which becomes 1. So the loop ends.
# perform a pass with current gap
swapped = False
for i in range(0, n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
# if no swaps, break early
if not swapped:
break
# after the loop, do a final pass with gap 1 (like bubble sort)
# but wait, the loop stops when gap is 1. So after the loop, gap is 1. But the loop condition is while gap > 1. So when gap becomes 1, the loop ends. Then, we need to perform a bubble pass with gap 1.
# So after the loop, we need to do another pass with gap = 1, but perhaps the code already does that?
# Wait, let's think. For example, if the initial gap is 5, then after division by 1.3, it becomes 3 (5/1.3 is ~3.846), then next gap is 2 (3/1.3 is ~2.3), then next gap is 1 (2/1.3 is ~1.538). So when gap is 1, the loop stops. So the code would not have done a pass with gap 1. So after the loop, we need to do a final pass with gap 1.
# So the code should have:
# after the loop, perform a bubble pass (gap=1)
# but how?
# So the code should be:
# after the loop, gap is 1. So we need to perform a pass with gap=1.
# So after the loop, we need to do:
gap = 1
swapped = True
while swapped:
swapped = False
for i in range(0, n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
gap = int(gap / 1.3)
# but wait, after gap is 1, the code would do another pass?
# Hmm, maybe not. Because in the original comb sort algorithm, after the gap reaches 1, the algorithm performs a final pass with gap 1, but the code may not have done that. So perhaps the code as written would miss that.
# So in the original code, the loop runs while gap > 1. So when the gap is 1, the loop stops. But the algorithm requires that after that, you perform a bubble sort pass (gap=1). So in the code, after the loop, we need to perform a pass with gap=1.
# Alternatively, perhaps the code as written does not do that. So the code may not be correct. So to make sure that the list is sorted, even after the loop ends, we need to perform a pass with gap=1.
# Let me think of an example. Suppose the list is [3, 2, 1]. The initial gap is 3. Then, gap becomes 2 (3/1.3 is ~2.3, floor to 2). Then during the pass with gap=2, compare 3 and 1, swap them. The list becomes [1, 2, 3]. Then, next gap is 2/1.3 = 1.538, floor to 1. So the loop ends. But the list is already sorted. So no problem.
# Another example: [2, 1, 3]. Initial gap is 3. Then gap becomes 2. So during pass with gap=2: compare 2 and 3 (i=0, i+gap=2). 2 < 3, no swap. Then gap is 2/1.3 = 1.538 → 1. So loop ends. The list is [2,1,3]. Which is not sorted. So the final pass with gap=1 is needed.
# So in this case, the code as written would not do that. Therefore, the code would not sort the list correctly. Therefore, the code needs to perform a final pass with gap=1.
# Therefore, after the loop, the code should perform a pass with gap=1, and then check if any swaps are needed. But how to implement that?
# So perhaps the code should be modified to:
# After the loop, perform a bubble sort pass (gap=1) until no swaps are done.
# So, after the loop, we can do:
# Perform a final pass with gap=1, but in the same way as before.
# So the code would be:
# After the initial loop, do:
gap = 1
swapped = True
while swapped:
swapped = False
for i in range(0, n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
gap = int(gap / 1.3)
# Wait, but after gap is 1, dividing by 1.3 gives 0. So gap becomes 0, and the loop would exit.
# But this seems like it's not the correct approach. Alternatively, perhaps the code should perform a single pass with gap=1.
# Let me check the original comb sort algorithm.
According to Wikipedia: The algorithm works by comparing elements with a certain gap between them. The gap starts at the length of the list and is reduced by a factor of 1.3 each time. The process is repeated until the gap is 1, and then a final pass is made with gap 1 (like a bubble sort pass) to ensure the list is sorted.
So, the code should have a pass with gap=1 after the loop.
So, in the code, after the loop (which stops when gap is 1), we need to perform a pass with gap=1. But how?
Let me think. The loop is:
gap = n
while gap > 1:
gap = int(gap / 1.3)
... perform pass with current gap
So after this loop, gap is 1. Then, perform a pass with gap=1.
So, in code:
# After the loop
gap = 1
swapped = True
while swapped:
swapped = False
for i in range(0, n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
# After this pass, check if any swaps occurred. If yes, repeat with gap=1 again?
# Wait, but according to the algorithm, after the gap reaches 1, we perform a single pass. But in the case where during that pass, swaps are made, then we need to perform another pass with gap=1 again?
Hmm, perhaps the original algorithm does not have that. The original comb sort algorithm says that after the gap is 1, perform a single pass. However, this may not be sufficient. Therefore, the code may need to perform a bubble sort pass (i.e., continue until no swaps are made).
Alternatively, perhaps the code can be modified to handle this.
So, perhaps the code should be:
def comb_sort(lst):
arr = lst.copy()
n = len(arr)
gap = n
while gap > 1:
gap = int(gap / 1.3)
swapped = False
for i in range(n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
if not swapped:
break
# Now perform a final bubble pass
gap = 1
while True:
swapped = False
for i in range(n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
if not swapped:
break
gap = int(gap / 1.3)
return arr
Wait, but this may not be correct. Let me think again.
Alternatively, perhaps the code can be written as:
def comb_sort(lst):
arr = lst.copy()
n = len(arr)
gap = n
while gap > 1:
gap = int(gap / 1.3)
swapped = False
for i in range(n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
if not swapped:
break
# Now, after the loop, perform a bubble sort pass (gap=1)
# But the code may not have done that yet. So, perform a pass with gap=1.
# However, the loop ends when gap is 1, but the code hasn't done a pass with gap=1 yet.
# So after the loop, we need to do a pass with gap=1.
# So, here, we can add:
# Now do a pass with gap=1
gap = 1
swapped = True
while swapped:
swapped = False
for i in range(n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
gap = int(gap / 1.3)
# But this would reduce gap to 0, so the loop would terminate.
# Wait, but this may not be the right way. Because after the initial loop, the gap is 1. So after the initial loop, we need to perform a pass with gap=1. However, the code as written may not do that.
So perhaps, after the initial loop, we need to perform a pass with gap=1, and then check if any swaps are made. If swaps are made, then perform another pass with gap=1 again.
But that's essentially bubble sort. So, perhaps the code after the initial loop should perform a bubble sort pass.
So, in code:
# After the initial loop, we need to perform a bubble sort pass.
# So, the code would be:
# Now perform a bubble sort pass (gap=1)
# So:
swapped = True
while swapped:
swapped = False
for i in range(n - 1):
if arr[i] > arr[i + 1]:
arr[i], arr[i + 1] = arr[i + 1], arr[i]
swapped = True
# This is the standard bubble sort pass.
# But why not integrate this into the previous loop? Because the initial loop may have stopped before the gap reaches 1, but in the code above, the initial loop stops when gap is 1, and then the code performs a bubble sort pass.
So, putting it all together:
def comb_sort(lst):
arr = lst.copy()
n = len(arr)
gap = n
while gap > 1:
gap = int(gap / 1.3)
swapped = False
for i in range(n - gap):
if arr[i] > arr[i + gap]:
arr[i], arr[i + gap] = arr[i + gap], arr[i]
swapped = True
if not swapped:
break
# Now perform a bubble sort pass
swapped = True
while swapped:
swapped = False
for i in range(n - 1):
if arr[i] > arr[i + 1]:
arr[i], arr[i + 1] = arr[i + 1], arr[i]
swapped = True
return arr
Let me test this code with the example given.
Example input: [5, 15, 37, 25, 79]
Initial copy: [5,15,37,25,79]
n = 5
Initial gap = 5.
Loop: gap >1 → yes.
gap = 5 / 1.3 = 3.846 → int is 3.
Now, for i in range(5-3) → range(2) → i=0,1.
i=0: compare arr[0] (5) and arr[3] (25). 5 < 25 → no swap.
i=1: compare arr[1] (15) and arr[4] (79). 15 < 79 → no swap.
swapped remains False. So break the loop.
Then, perform the bubble pass.
swapped = True.
First iteration:
swapped = False.
for i in 0 to 3:
i=0: compare 5 and 15 → no swap.
i=1: compare 15 and 37 → no swap.
i=2: compare 37 and 25 → 37 >25 → swap. Now arr is [5,15,25,37,79]. swapped is True.
i=3: compare 37 and 79 → no swap.
swapped is True → loop again.
Next iteration:
swapped = False.
i=0: 5 and 15 → no swap.
i=1: 15 and 25 → no swap.
i=2: 25 and 37 → no swap.
i=3
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[5, 15, 37, 25, 79]], [[41, 32, 15, 19, 22]], [[99, 15, 13, 47]], [[500, 1000, 1500, 2000, 3000]], [[444444444, 555555555, 777777777, 888888888, 999999999]], [[1000000000, 2000000000, 5000000000, 10000000000]], [[1, 2, 2, 3, 4, 7, 8, 8]], [[1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]], [[11, 22, 33, 44, 55, 66, 77, 88, 99]], [[99, 444444444, 777777777, 888888888, 999999999]], [[11, 22, 31, 32, 33, 55, 66, 77, 88]], [[500, 999, 1500, 3000]], [[11, 22, 33, 55, 66, 77, 88, 99, 10000000000]], [[11, 22, 31, 32, 33, 55, 66, 66, 77, 77]], [[1, 2, 3, 4, 4, 5, 7, 8, 9, 10]], [[11, 22, 33, 44, 44, 55, 66, 77, 88, 99]], [[11, 22, 33, 33, 55, 66, 77, 88, 99, 9999999999]], [[11, 22, 32, 33, 33, 55, 66, 66, 77, 77]], [[11, 22, 22, 31, 32, 32, 33, 55, 66, 77, 88]], [[1, 2, 3, 4, 5, 6, 6, 7, 9, 9, 10]], [[11, 11, 22, 33, 44, 55, 66, 66, 88, 99]], [[11, 11, 22, 44, 55, 66, 66, 89, 99]], [[2, 3, 4, 5, 6, 6, 7, 9, 9, 10, 6999]], [[11, 11, 44, 55, 66, 66, 89, 99]], [[11, 11, 22, 22, 22, 33, 55, 66, 77, 99, 10000000000]], [[1000000000, 2000000000, 2000000000, 10000000000]], [[1, 2, 3, 4, 4, 7, 8, 8]], [[1, 2, 3, 4, 7, 8, 8, 77]], [[500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 9000, 10000]], [[11, 22, 33, 44, 55, 66, 66, 77, 88, 99]], [[1, 2, 3, 4, 4, 5, 7, 8, 9, 9, 10]], [[1, 2, 2, 3, 4, 7, 8, 8, 1000000000]], [[1999999999, 2000000000, 5000000000, 10000000000]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10]], [[11, 33, 44, 44, 55, 66, 77, 88, 88, 99]], [[11, 22, 31, 32, 33, 55, 66, 67, 77, 77]], [[11, 22, 33, 33, 44, 55, 66, 66, 77, 88, 99]], [[8, 11, 22, 33, 44, 66, 77, 88, 99]], [[500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 8000, 9000, 10000]], [[1, 2, 3, 4, 4, 5, 7, 8, 9, 9, 10, 99]], [[11, 33, 44, 44, 55, 66, 77, 88, 88, 99, 99]], [[99, 6999, 444444444, 777777777, 888888888, 888888889, 999999999]], [[1999999999, 2000000000, 9999999999, 10000000000]], [[1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10]], [[1, 2, 3, 4, 5, 6, 6, 8, 9, 9, 10]], [[11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99]], [[1, 2, 3, 5, 6, 7, 9, 9, 10, 888888888, 888888888]], [[11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99, 4000]], [[11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99, 4000, 444444444]], [[1999999999, 2000000000, 5000000000, 5000000000, 10000000000]], [[11, 22, 31, 32, 33, 55, 66, 66, 66, 77, 77]], [[22, 33, 1999999999, 2000000000, 10000000000]], [[11, 22, 33, 33, 44, 55, 65, 66, 77, 99]], [[500, 500, 1000, 3000, 3001, 4000, 5000, 6000, 7000, 7001, 8000, 8000, 9000, 10000]], [[1, 23, 33, 1999999999, 2000000000, 9999999999, 10000000000]], [[11, 33, 43, 44, 54, 55, 66, 77, 77, 88, 88, 99, 99]], [[10, 22, 33, 33, 44, 55, 65, 65, 66, 77, 99]], [[55, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000]], [[1, 2, 3, 4, 4, 4, 7, 7, 8]], [[11, 22, 33, 44, 44, 55, 66, 66, 77, 88, 99]], [[11, 22, 32, 33, 34, 66, 66, 77, 77]], [[1, 2, 3, 4, 4, 7, 7, 8, 8]], [[1, 2, 3, 4, 4, 5, 7, 8, 9, 10, 100]], [[99, 6999, 444444444, 777777777, 888888888, 888888888, 888888889, 999999999]], [[11, 11, 44, 55, 66, 89, 99]], [[1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9, 10]], [[11, 22, 33, 33, 65, 66, 77, 88, 99, 4000, 444444444]], [[11, 22, 23, 31, 32, 32, 33, 55, 66, 77, 88]], [[99, 6999, 444444444, 888888888, 888888889, 999999999, 9999999999]], [[11, 11, 44, 44, 55, 66, 66, 89, 89, 99]], [[1, 2, 3, 4, 4, 5, 6, 8, 9, 10, 888888889]], [[11, 22, 32, 33, 33, 55, 66, 77, 88, 9999999999]], [[11, 22, 32, 33, 33, 66, 66, 88, 9999999999]], [[4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000]], [[11, 22, 33, 44, 55, 66, 77, 88, 99, 10000000000]], [[11, 22, 32, 33, 33, 33, 55, 66, 77, 77]], [[11, 22, 33, 33, 44, 55, 65, 77, 99]], [[11, 22, 33, 33, 65, 66, 77, 88, 99, 500, 501, 4000, 444444444]], [[55, 777777777, 888888888, 999999999]], [[11, 33, 33, 44, 55, 65, 66, 77, 77, 99, 4000, 444444444]], [[1, 2, 3, 4, 4, 4, 5, 7, 8, 9, 9, 9, 10, 99]], [[11, 23, 33, 44, 55, 66, 77, 88, 99, 10000000000]], [[44, 500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 9000, 10000]], [[11, 22, 31, 32, 33, 33, 55, 66, 66, 77, 77]], [[1, 2, 3, 4, 5, 5, 6, 6, 8, 9, 9, 10]], [[11, 22, 31, 32, 32, 33, 55, 66, 77, 88]], [[1999999999, 2000000000, 2000000000, 9999999999, 10000000000]], [[444444444, 777777777, 888888888, 999999999, 1000000000]], [[65, 4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000]], [[33, 33, 44, 55, 65, 66, 77, 99, 4000, 444444444]], [[500, 500, 1000, 3000, 3001, 4000, 5000, 6000, 7000, 7001, 8000, 9000, 10000]], [[500, 999, 1500, 1500, 3000]], [[5, 11, 33, 33, 44, 55, 66, 77, 77, 99, 4000, 444444444]], [[44, 100, 500, 500, 1000, 3001, 5000, 6000, 7000, 8000, 9000, 10000]], [[1, 2, 3, 4, 4, 4, 4, 5, 7, 8, 8, 9, 9, 9, 10, 99]], [[3, 11, 22, 31, 32, 33, 55, 66, 66, 77, 77]], [[11, 11, 22, 33, 44, 66, 66, 88, 99]], [[1, 2, 3, 3, 4, 5, 6, 7, 8, 8, 9, 9, 10]], [[100, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 8000, 9000, 10000]], [[8, 11, 22, 31, 32, 33, 33, 55, 66, 66, 77, 77, 77]], [[1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 9, 10]], [[4, 99, 6999, 444444444, 777777777, 888888888, 888888888, 888888889, 999999999]], [[11, 22, 30, 32, 32, 33, 55, 66, 77, 88, 5000000000]], [[1, 2, 5, 6, 7, 8, 9, 9, 10, 888888888, 888888888]], [[11, 33, 44, 44, 55, 66, 77, 88, 88, 99, 100]], [[11, 32, 33, 33, 44, 55, 65, 66, 77, 77, 99, 4000, 444444444]], [[64, 65, 4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000]]]
results = [[5, 15, 25, 37, 79], [15, 19, 22, 32, 41], [13, 15, 47, 99], [500, 1000, 1500, 2000, 3000], [444444444, 555555555, 777777777, 888888888, 999999999], [1000000000, 2000000000, 5000000000, 10000000000], [1, 2, 2, 3, 4, 7, 8, 8], [1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 22, 33, 44, 55, 66, 77, 88, 99], [99, 444444444, 777777777, 888888888, 999999999], [11, 22, 31, 32, 33, 55, 66, 77, 88], [500, 999, 1500, 3000], [11, 22, 33, 55, 66, 77, 88, 99, 10000000000], [11, 22, 31, 32, 33, 55, 66, 66, 77, 77], [1, 2, 3, 4, 4, 5, 7, 8, 9, 10], [11, 22, 33, 44, 44, 55, 66, 77, 88, 99], [11, 22, 33, 33, 55, 66, 77, 88, 99, 9999999999], [11, 22, 32, 33, 33, 55, 66, 66, 77, 77], [11, 22, 22, 31, 32, 32, 33, 55, 66, 77, 88], [1, 2, 3, 4, 5, 6, 6, 7, 9, 9, 10], [11, 11, 22, 33, 44, 55, 66, 66, 88, 99], [11, 11, 22, 44, 55, 66, 66, 89, 99], [2, 3, 4, 5, 6, 6, 7, 9, 9, 10, 6999], [11, 11, 44, 55, 66, 66, 89, 99], [11, 11, 22, 22, 22, 33, 55, 66, 77, 99, 10000000000], [1000000000, 2000000000, 2000000000, 10000000000], [1, 2, 3, 4, 4, 7, 8, 8], [1, 2, 3, 4, 7, 8, 8, 77], [500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 9000, 10000], [11, 22, 33, 44, 55, 66, 66, 77, 88, 99], [1, 2, 3, 4, 4, 5, 7, 8, 9, 9, 10], [1, 2, 2, 3, 4, 7, 8, 8, 1000000000], [1999999999, 2000000000, 5000000000, 10000000000], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 10], [11, 33, 44, 44, 55, 66, 77, 88, 88, 99], [11, 22, 31, 32, 33, 55, 66, 67, 77, 77], [11, 22, 33, 33, 44, 55, 66, 66, 77, 88, 99], [8, 11, 22, 33, 44, 66, 77, 88, 99], [500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 8000, 9000, 10000], [1, 2, 3, 4, 4, 5, 7, 8, 9, 9, 10, 99], [11, 33, 44, 44, 55, 66, 77, 88, 88, 99, 99], [99, 6999, 444444444, 777777777, 888888888, 888888889, 999999999], [1999999999, 2000000000, 9999999999, 10000000000], [1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 10], [1, 2, 3, 4, 5, 6, 6, 8, 9, 9, 10], [11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99], [1, 2, 3, 5, 6, 7, 9, 9, 10, 888888888, 888888888], [11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99, 4000], [11, 22, 33, 33, 44, 55, 65, 66, 77, 88, 99, 4000, 444444444], [1999999999, 2000000000, 5000000000, 5000000000, 10000000000], [11, 22, 31, 32, 33, 55, 66, 66, 66, 77, 77], [22, 33, 1999999999, 2000000000, 10000000000], [11, 22, 33, 33, 44, 55, 65, 66, 77, 99], [500, 500, 1000, 3000, 3001, 4000, 5000, 6000, 7000, 7001, 8000, 8000, 9000, 10000], [1, 23, 33, 1999999999, 2000000000, 9999999999, 10000000000], [11, 33, 43, 44, 54, 55, 66, 77, 77, 88, 88, 99, 99], [10, 22, 33, 33, 44, 55, 65, 65, 66, 77, 99], [55, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000], [1, 2, 3, 4, 4, 4, 7, 7, 8], [11, 22, 33, 44, 44, 55, 66, 66, 77, 88, 99], [11, 22, 32, 33, 34, 66, 66, 77, 77], [1, 2, 3, 4, 4, 7, 7, 8, 8], [1, 2, 3, 4, 4, 5, 7, 8, 9, 10, 100], [99, 6999, 444444444, 777777777, 888888888, 888888888, 888888889, 999999999], [11, 11, 44, 55, 66, 89, 99], [1, 2, 3, 4, 4, 5, 6, 7, 8, 9, 9, 10], [11, 22, 33, 33, 65, 66, 77, 88, 99, 4000, 444444444], [11, 22, 23, 31, 32, 32, 33, 55, 66, 77, 88], [99, 6999, 444444444, 888888888, 888888889, 999999999, 9999999999], [11, 11, 44, 44, 55, 66, 66, 89, 89, 99], [1, 2, 3, 4, 4, 5, 6, 8, 9, 10, 888888889], [11, 22, 32, 33, 33, 55, 66, 77, 88, 9999999999], [11, 22, 32, 33, 33, 66, 66, 88, 9999999999], [4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000], [11, 22, 33, 44, 55, 66, 77, 88, 99, 10000000000], [11, 22, 32, 33, 33, 33, 55, 66, 77, 77], [11, 22, 33, 33, 44, 55, 65, 77, 99], [11, 22, 33, 33, 65, 66, 77, 88, 99, 500, 501, 4000, 444444444], [55, 777777777, 888888888, 999999999], [11, 33, 33, 44, 55, 65, 66, 77, 77, 99, 4000, 444444444], [1, 2, 3, 4, 4, 4, 5, 7, 8, 9, 9, 9, 10, 99], [11, 23, 33, 44, 55, 66, 77, 88, 99, 10000000000], [44, 500, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 9000, 10000], [11, 22, 31, 32, 33, 33, 55, 66, 66, 77, 77], [1, 2, 3, 4, 5, 5, 6, 6, 8, 9, 9, 10], [11, 22, 31, 32, 32, 33, 55, 66, 77, 88], [1999999999, 2000000000, 2000000000, 9999999999, 10000000000], [444444444, 777777777, 888888888, 999999999, 1000000000], [65, 4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000], [33, 33, 44, 55, 65, 66, 77, 99, 4000, 444444444], [500, 500, 1000, 3000, 3001, 4000, 5000, 6000, 7000, 7001, 8000, 9000, 10000], [500, 999, 1500, 1500, 3000], [5, 11, 33, 33, 44, 55, 66, 77, 77, 99, 4000, 444444444], [44, 100, 500, 500, 1000, 3001, 5000, 6000, 7000, 8000, 9000, 10000], [1, 2, 3, 4, 4, 4, 4, 5, 7, 8, 8, 9, 9, 9, 10, 99], [3, 11, 22, 31, 32, 33, 55, 66, 66, 77, 77], [11, 11, 22, 33, 44, 66, 66, 88, 99], [1, 2, 3, 3, 4, 5, 6, 7, 8, 8, 9, 9, 10], [100, 500, 1000, 3001, 4000, 5000, 6000, 7000, 8000, 8000, 9000, 10000], [8, 11, 22, 31, 32, 33, 33, 55, 66, 66, 77, 77, 77], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 9, 10], [4, 99, 6999, 444444444, 777777777, 888888888, 888888888, 888888889, 999999999], [11, 22, 30, 32, 32, 33, 55, 66, 77, 88, 5000000000], [1, 2, 5, 6, 7, 8, 9, 9, 10, 888888888, 888888888], [11, 33, 44, 44, 55, 66, 77, 88, 88, 99, 100], [11, 32, 33, 33, 44, 55, 65, 66, 77, 77, 99, 4000, 444444444], [64, 65, 4000, 444444444, 1000000000, 2000000000, 2000000000, 5000000000, 10000000000]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(comb_sort(*inp), exp, 0)
| OK=False
=========================================
Question 0
error_msg: None
=========================================
Question 1
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 39, in
File "", line 33, in assertion
AssertionError: out: False, exp: True
=========================================
Question 2
error_msg: None
=========================================
Question 3
error_msg: None
=========================================
Question 4
error_msg: None
=========================================
Question 5
error_msg: None
=========================================
Question 6
error_msg: None
=========================================
Question 7
error_msg: None
=========================================
Question 8
error_msg: None
=========================================
Question 9
error_msg: None
=========================================
Question 10
error_msg: None
=========================================
Question 11
error_msg: None
=========================================
Question 12
error_msg: None
=========================================
Question 13
error_msg: None
=========================================
Question 14
error_msg: None
==================== Problem #31 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given number can be represented as the difference of two squares or not.
Your answer will be tested on test cases like:
assert dif_Square(5) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given number can be represented as the difference of two squares or not.
Your answer will be tested on test cases like:
assert dif_Square(5) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given number can be represented as the difference of two squares or not.
Your answer will be tested on test cases like:
assert dif_Square(5) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given number can be represented as the difference of two squares or not.
Your answer will be tested on test cases like:
assert dif_Square(5) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the given number can be represented as the difference of two squares or not.
Your answer will be tested on test cases like:
assert dif_Square(5) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, let's see. I need to write a Python function called dif_Square that checks if a given number can be represented as the difference of two squares. Hmm, how do I approach this?
Wait, the difference of two squares. Oh right, the formula is a² - b² = (a - b)(a + b). So the number N can be written as (a - b)(a + b). So for N to be expressible as such, there must be two integers x and y (where x = a - b and y = a + b) such that x * y = N. Also, since a and b are integers, x and y must have the same parity because a - b and a + b add up to 2a, which is even. So x + y must be even. That implies that x and y are both even or both odd. Therefore, their product N must be either odd (if both x and y are odd) or divisible by 4 (if both are even). Wait, because if x and y are both even, then their product is divisible by 4. If they are both odd, their product is odd. So if N is even but not divisible by 4, then it can't be expressed as a difference of squares.
So the key here is to check if N is either odd or divisible by 4. Wait, but what about numbers that are even but not divisible by 4? Like 2, 6, etc. For example, 2: can it be written as a² - b²? Let's see. Let's try possible a and b. Suppose a=2, b=1: 4-1=3. a=3, b=2: 9-4=5. a=1, b=0: 1-0=1. Hmm, maybe 2 can't be written as difference of squares. So according to the earlier logic, if N is even but not divisible by 4, then it's not possible. So for the function, the condition would be: if N is odd or divisible by 4, then True, else False. But wait, what about N=1? 1 can be written as 1² - 0². So 1 is odd, which fits. What about N=3? 2² -1²=4-1=3. So yes. For N=4, 2² -0²=4. So yes. N=5: 3² - 2²=9-4=5. So yes. So the test case given is 5, which returns True.
But wait, what about N=7? Let's see. 4² - 3² is 16-9=7. Yes. So that's odd. So the logic seems to hold. What about N=8? 3² -1²=9-1=8. So yes. 8 is divisible by 4. So that works. What about N=6? Let's see. Let me try possible a and b. Let's think: a² - b² =6. Let's see possible factors. So x*y=6. Possible pairs (x,y) are (1,6), (2,3). Check if x and y have same parity. For (1,6): 1 is odd, 6 even. Different parity. So no. For (2,3): 2 even, 3 odd. Different. So no. So no possible pairs. Hence 6 can't be written as difference of squares. Which fits with the rule that 6 is even but not divisible by 4.
So the conclusion is that a number can be expressed as difference of two squares if and only if it is not congruent to 2 mod 4. So the function can check if N is odd (N%2 ==1) or divisible by 4 (N%4 ==0). But wait, what about N=0? Well, the problem says "given number"—probably assuming positive integers. But the problem's test case uses 5, which is positive. So perhaps the function is intended for positive integers.
But the problem says "given number"—so maybe we need to handle all integers. However, the test case uses 5. Let's think about N=0. 0 can be written as 0² -0². So it's possible. But perhaps the problem is considering positive integers. But the question says "the given number"—so maybe the function should handle any integer. But for the purpose of the problem, perhaps the function is supposed to handle positive integers.
So the function can be written as follows: For a given number N, check if it is odd or divisible by 4. But wait, what about N=1? 1 is odd. So yes. N=2? 2 is even but not divisible by 4. So returns False.
So the code would be:
def dif_Square(n):
if n % 2 == 1 or n %4 ==0:
return True
else:
return False
But wait, what about N=0? Let's see. 0 mod 2 is 0, and 0 mod4 is 0. So returns True. Which is correct. But maybe the problem expects N to be a positive integer. However, the problem's test case is for 5, which is positive.
But the problem says "given number"—so perhaps the function should handle all integers, including zero and negatives. Wait, but difference of squares can be negative. For example, if N is negative, say -5, then it can be written as (b² -a²) where a and b are positive. So for example, -5 = 1² - 2². So the function should return True for N=-5. But according to the current code, if n is -5, then n%2 is -1 mod 2, which is 1. So the code returns True. Which is correct.
But let's check. For N= -5, it's odd. So the code returns True. Which is correct.
So the code seems to handle all cases. But let's test for N=0. The code returns True, which is correct.
But what about N=4? 4 is divisible by 4. So returns True. Which is correct.
So the code seems to handle all cases.
But wait, what about N=1? The code returns True. Which is correct.
So the function can be written as follows.
But wait, what about N=2? The code returns False. Which is correct.
So the code is correct.
So the Python function would be:
def dif_Square(n):
return n % 2 == 1 or n %4 ==0
Wait, but what about N=0? Let's see. 0%2 is 0, 0%4 is 0. So returns True. Which is correct.
But the problem's test case is assert dif_Square(5) == True. Which would be True because 5 is odd.
So this code should work.
But let me test some examples.
Test case 1: 5 is odd. Returns True. Correct.
Test case 2: 6. 6%2 is 0, 6%4 is 2. So returns False. Correct.
Test case 3: 4. 4%4 is 0. Returns True. Correct.
Test case 4: 2. Returns False. Correct.
Test case 5: 7 (odd). True. Correct.
Test case 6: 8 (div by 4). True. Correct.
Test case 7: 0. True. Correct.
Test case 8: -5. -5%2 is 1 (since -5 = (-3)*2 +1). So returns True. Correct.
So the code works for all these cases.
Therefore, the function is as simple as checking whether the number is odd or divisible by 4.
So the Python code is:
def dif_Square(n):
return n % 2 == 1 or n % 4 == 0
But wait, what about numbers that are even but not divisible by 4? Like 6, 2, etc. They return False, which is correct.
So this should be the solution.
```python
def dif_Square(n):
return n % 2 == 1 or n % 4 == 0
```
----------------------------------------------
Result: Pred=def dif_Square(n):
return n % 2 == 1 or n % 4 == 0 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[5], [10], [15], [991], [567], [13], [24], [568], [992], [569], [990], [566], [True], [989], [25], [14], [565], [23], [988], [12], [11], [16], [17], [993], [564], [563], [22], [994], [9], [21], [995], [996], [20], [18], [997], [8], [987], [45], [562], [570], [26], [561], [998], [19], [77], [7], [76], [560], [986], [27], [44], [571], [28], [75], [46], [78], [74], [985], [29], [572], [984], [73], [983], [79], [573], [47], [50], [982], [981], [71], [49], [80], [51], [999], [30], [81], [6], [1000], [980], [1001], [1002], [82], [1003], [52], [574], [53], [1004], [70], [575], [69], [576], [979], [83], [72], [68], [43], [89], [42], [977], [33], [4], [36], [978], [3]]
results = [True, False, True, True, True, True, True, True, True, True, False, False, True, True, True, False, True, True, True, True, True, True, True, True, True, True, False, False, True, True, True, True, True, False, True, True, True, True, False, False, False, True, False, True, True, True, True, True, False, True, True, True, True, True, False, False, False, True, True, True, True, True, True, True, True, True, False, False, True, True, True, True, True, True, False, True, False, True, True, True, False, False, True, True, False, True, True, False, True, True, True, True, True, True, True, True, True, False, True, True, True, True, False, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(dif_Square(*inp), exp, 0)
| OK=True
==================== Problem #32 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether it follows the sequence given in the patterns array.
Your answer will be tested on test cases like:
assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether it follows the sequence given in the patterns array.
Your answer will be tested on test cases like:
assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether it follows the sequence given in the patterns array.
Your answer will be tested on test cases like:
assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether it follows the sequence given in the patterns array.
Your answer will be tested on test cases like:
assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether it follows the sequence given in the patterns array.
Your answer will be tested on test cases like:
assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called is_samepatterns that checks if two lists follow the same sequence as per the patterns array. Let me think about how to approach this.
The example given is ["red","green","green"] and ["a", "b", "b"], which returns True. So the idea is that the pattern of elements in the first list should match the pattern of elements in the second list.
How do I determine the pattern? Well, for each list, I can create a mapping of elements to their positions. For example, in the first list, "red" is first, then "green" appears twice. The pattern here would be 0, 1, 1. Similarly for the second list, "a" is 0, then "b" is 1, so the pattern is 0,1,1. So if both lists have the same pattern of indices, then they match.
So the plan is: for each list, create a list that represents the order of first occurrences. For example, replace each element with the index of its first occurrence in the list. Then compare these two lists.
Wait, how to generate that? Let's take the first list: ["red", "green", "green"]. Let's process each element:
- "red" is first, so assign 0.
- "green" is next, assign 1.
- Next "green" is already seen, so assign 1 again.
So the pattern list would be [0,1,1]. For the second list ["a", "b", "b"], the pattern is [0,1,1]. So comparing these two pattern lists would result in True.
So the steps are:
1. For each of the two input lists, generate their pattern list based on the first occurrence indices.
2. Compare the two pattern lists. If they are the same, return True; else, False.
Now, how to implement this in Python?
Let's think about writing a helper function to generate the pattern list for a single list. For example, for a list like ["red","green","green"], the helper function would return [0,1,1].
How to do that? Let's think:
Initialize a dictionary to keep track of the elements we've seen so far. For each element in the input list, if it's not in the dictionary, assign it the next available index (like the length of the dictionary), and add it to the dictionary. Then, append that index to the pattern list.
Wait, for example:
For the first element, "red", the dictionary is empty. So we add "red" with value 0. The pattern list starts with 0.
Next element is "green". Not in the dict, so add with value 1. Pattern list is [0,1].
Third element is "green" again. It's already in the dict, so append 1. Pattern list becomes [0,1,1].
Yes, that works. So the helper function can be written as:
def get_pattern(lst):
mapping = {}
pattern = []
for element in lst:
if element not in mapping:
mapping[element] = len(mapping)
pattern.append(mapping[element])
return pattern
Then, the main function is_samepatterns would take two lists, generate their patterns, and compare them.
But wait, what if the two lists are of different lengths? For example, if one is longer than the other, then the patterns can't be the same. So first, check if the lengths are equal. If not, return False immediately.
So the steps for the main function:
Check if the lengths of the two input lists are the same. If not, return False.
Else, generate the pattern for both lists, compare them, return True if equal, else False.
So putting it all together:
def is_samepatterns(list1, list2):
if len(list1) != len(list2):
return False
# generate patterns for both lists
def get_pattern(lst):
mapping = {}
pattern = []
for element in lst:
if element not in mapping:
mapping[element] = len(mapping)
pattern.append(mapping[element])
return pattern
return get_pattern(list1) == get_pattern(list2)
Wait, but what about cases where the elements are different but the pattern is same? Like list1 is ["a", "b", "a"], list2 is ["x", "y", "x"], their patterns would be [0,1,0] and [0,1,0], so returns True. Which is correct.
Testing the sample input:
list1 = ["red","green","green"], list2 = ["a", "b", "b"]
get_pattern(list1) is [0,1,1], get_pattern(list2) is [0,1,1], so returns True. Which matches the sample.
Another test case: if list1 is ["a", "b", "c"], list2 is ["x", "y", "z"], then the patterns are [0,1,2] and [0,1,2], so returns True.
Another case: list1 is ["a", "a", "b"], list2 is ["x", "x", "y"], patterns are [0,0,1] and [0,0,1], returns True.
What if list1 is ["a", "b", "a"], list2 is ["a", "a", "a"]? The pattern for list1 is [0,1,0], list2's pattern is [0,0,0], so returns False.
Yes, that seems correct.
Now, the code. But the problem says that the function is called is_samepatterns, and the parameters are the two lists. So the code should be as written.
Now, the user provided the test case: assert is_samepatterns(["red","green","green"], ["a", "b", "b"])==True. Which should pass.
Another test case: if the lists are different lengths, returns False. For example, assert is_samepatterns(["a", "b"], ["a", "b", "c"]) == False.
What about empty lists? If both are empty, returns True. If one is empty and the other isn't, returns False.
So the code should handle all these cases.
Now, the code needs to be written as a self-contained Python function. The code should be in a markdown code block. So the final code would be:
def is_samepatterns(list1, list2):
if len(list1) != len(list2):
return False
def get_pattern(lst):
mapping = {}
pattern = []
for element in lst:
if element not in mapping:
mapping[element] = len(mapping)
pattern.append(mapping[element])
return pattern
return get_pattern(list1) == get_pattern(list2)
Wait, but in Python, the helper function can be inside the main function. That's acceptable.
Yes. So that's the code. Let me check if there are any edge cases.
Another test case: list1 is ["a"], list2 is ["b"], then the pattern for both is [0], so returns True.
Another case: list1 is ["a", "a"], list2 is ["b", "b"], patterns are [0,0] and [0,0], returns True.
Another case: list1 is ["a", "b"], list2 is ["a", "a"], patterns [0,1] vs [0,0], returns False.
Yes. So the code should work.
```python
def is_samepatterns(list1, list2):
if len(list1) != len(list2):
return False
def get_pattern(lst):
mapping = {}
pattern = []
for element in lst:
if element not in mapping:
mapping[element] = len(mapping)
pattern.append(mapping[element])
return pattern
return get_pattern(list1) == get_pattern(list2)
```
----------------------------------------------
Result: Pred=def is_samepatterns(list1, list2):
if len(list1) != len(list2):
return False
def get_pattern(lst):
mapping = {}
pattern = []
for element in lst:
if element not in mapping:
mapping[element] = len(mapping)
pattern.append(mapping[element])
return pattern
return get_pattern(list1) == get_pattern(list2) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[['red', 'green', 'green'], ['a', 'b', 'b']], [['red', 'green', 'greenn'], ['a', 'b', 'b']], [['red', 'green', 'greenn'], ['a', 'b']], [['red', 'green', 'blue'], ['a', 'b', 'c']], [['red', 'red', 'red'], ['a', 'a', 'a']], [['red', 'blue', 'green'], ['a', 'b', 'c']], [['red', 'green', 'blue', 'red'], ['a', 'b', 'c', 'a']], [['red', 'red', 'blue', 'blue'], ['a', 'a', 'b', 'b']], [['red', 'green', 'green', 'blue'], ['a', 'b', 'b', 'c']], [['red', 'red', 'red', 'red'], ['a', 'a', 'a', 'a']], [['red', 'red', 'green', 'blue'], ['a', 'a', 'b', 'c']], [['red', 'green', 'green', 'green'], ['a', 'b', 'b', 'b']], [[], ['a', 'b', 'c']], [[], []], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'b', 'c']], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'c', 'a']], [['red', 'red', 'red', 'red', 'red', 'red'], ['a', 'b', 'c', 'a', 'b', 'c']], [['red', 'green', 'blue', 'red', 'green', 'blue'], ['a', 'b', 'c', 'a', 'b', 'c']], [['red', 'green', 'blue', 'red', 'red', 'red'], ['a', 'b', 'c', 'a', 'b', 'c']], [['red', 'green', 'blue', 'red', 'blue', 'green'], ['a', 'b', 'c', 'a', 'b', 'c']], [['a', 'b', 'cc', 'c', 'a'], ['a', 'b', 'cc', 'c', 'a']], [['red', 'green', 'yellow'], ['a', 'b', 'c', 'a']], [['b', 'c', 'a', 'b', 'c'], ['red', 'red', 'red', 'red', 'bluered', 'red']], [['blue', 'red', 'red', 'red', 'red'], ['a', 'a', 'a', 'a']], [['a', 'a', 'b', 'b', 'b'], ['a', 'a', 'b', 'b', 'b']], [['blue', 'red', 'red', 'red', 'red'], ['ared', 'a']], [['red', 'red', 'red', 'red', 'red', 'red'], ['a', 'b', 'ared', 'c', 'a', 'b', 'c']], [['red', 'green', 'blue', 'red', 'red', 'red', 'red'], ['a', 'b', 'ccc', 'a', 'b']], [['red', 'green', 'bluue', 'red', 'red', 'red'], ['red', 'green', 'bluue', 'red', 'red', 'red']], [['red', 'red', 'red'], ['red', 'red', 'red']], [[False, True, False], [False, True, False]], [['red', 'green', 'blue', 'yellow'], ['red', 'green', 'blue', 'yellow']], [['a', 'b', '', 'c'], ['a', 'b', '', 'c']], [['ared', 'a'], ['blue', 'red', 'red', 'red', 'red']], [['blue', 'red', 'red', 'red', 'red'], ['blue', 'red', 'red', 'red', 'red']], [['bluered', 'red', 'yellow', 'red', 'reyellow', 'cc', 'red'], ['bluered', 'red', 'yellow', 'red', 'reyellow', 'cc', 'red']], [['ared', 'rred', 'green'], ['ared', 'rred', 'green']], [[False], [False]], [['red', 'green', 'green', 'green'], ['ccc', 'b', 'b', 'b']], [['blueccc', 'blue', 'red', 'red', 'red', 'cc'], ['bluue', 'a', 'a', 'a', 'a']], [['red', 'green', 'bluue', 'red', 'red'], ['red', 'green', 'bluue', 'red', 'red']], [['red', 'green', 'blue', 'eblue', 'yellow', 'blue'], ['red', 'green', 'blue', 'eblue', 'yellow', 'blue']], [['blueccc', 'blue', 'red', 'red', 'red', 'cc'], ['bluue', 'a', 'a', 'a']], [['a', 'a', 'b', 'bblueccc', 'b', 'b'], ['a', 'a', 'b', 'bblueccc', 'b', 'b']], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'c', 'a', 'a']], [['blue', 'red', 'red', 'red', 'red'], ['a', 'a', 'cc', 'a']], [['blueccc', 'ared', 'a'], ['blue', 'red', 'red', 'red', 'red']], [[False, True, False, False], [False, True, False, False]], [['belue', 'red', 'red', 'green', 'blue', 'red'], ['belue', 'red', 'red', 'green', 'blue', 'red']], [['red', 'greeen', 'blue', 'red', 'red', 'red', 'red', 'red'], ['red', 'greeen', 'blue', 'red', 'red', 'red', 'red', 'red']], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'c', 'a', 'a', 'aa']], [['red', 'blue', 'green'], ['a', 'byellow', 'c']], [['red', 'green', 'green'], ['ccc', 'b', 'b', 'b']], [['red', 'green', 'blue', 'red', 'blue', 'green'], ['b', 'c', 'a', 'b', 'c']], [['blueccc', 'blue', 'red', 'red', 'blcccueccc', 'red', 'cc'], ['blueccc', 'blue', 'red', 'red', 'blcccueccc', 'red', 'cc']], [['red', 'rred', 'green', 'blue', 'yellw', 'eblue', 'yellow', 'blue'], ['red', 'rred', 'green', 'blue', 'yellw', 'eblue', 'yellow', 'blue']], [['gbluered', 'yellow', 'red', 'blue', 'green'], ['gbluered', 'yellow', 'red', 'blue', 'green']], [[True, False], [True, False]], [['red', 'green', 'red'], ['a', 'b', 'c', 'a']], [['belue', 'a'], ['belue', 'a']], [['green', 'rred', 'yellw', 'green'], ['green', 'rred', 'yellw', 'green']], [['bluaredue', 'red', 'green', 'bluue', 'red', 'red', 'red'], ['bluaredue', 'red', 'green', 'bluue', 'red', 'red', 'red']], [['bluue', 'a', 'a', 'a'], ['bluue', 'a', 'a', 'a']], [['a', 'bb', 'c', 'a'], ['a', 'bb', 'c', 'a']], [['a', 'b', 'c', 'a', 'b', 'c'], ['a', 'b', 'c', 'a', 'b', 'c']], [['red', 'greeen', 'blue', 'red', 'red', 'red', 'red', 'red', 'greeen'], ['red', 'greeen', 'blue', 'red', 'red', 'red', 'red', 'red', 'greeen']], [['blueccc', 'blue', 'red', 'red', 'blueccc', 'red', 'cc', 'red', 'red', 'blueccc'], ['blueccc', 'blue', 'red', 'red', 'blueccc', 'red', 'cc', 'red', 'red', 'blueccc']], [['a', 'red', 'b', 'rred', 'c'], ['a', 'red', 'b', 'rred', 'c']], [['a', 'b', 'c', 'a', 'a', 'aa'], ['red', 'green', 'blue', 'yellow']], [['red', 'green', 'red'], ['a', 'b', 'c', 'a', 'a']], [['ared', 'rred', 'green', 'green'], ['ared', 'rred', 'green', 'green']], [['red', 'blue', 'yellow', 'red'], ['red', 'blue', 'yellow', 'red']], [['red', 'green', 'blue', 'bluue', 'red', 'red', 'red'], ['red', 'green', 'blue', 'bluue', 'red', 'red', 'red']], [['red', 'red', 'gbegen', 'gbeen', 'blue'], ['a', 'a', 'b', 'c']], [['red', 'green', 'blue', 'red', 'red', 'red', 'green', 'green'], ['red', 'green', 'blue', 'red', 'red', 'red', 'green', 'green']], [['green', 'c', 'yellw', 'green', 'green'], ['green', 'c', 'yellw', 'green', 'green']], [['red', 'green', 'blue', 'bluue', 'red', 'red'], ['red', 'green', 'blue', 'bluue', 'red', 'red']], [['a', 'b', 'aa', 'c', 'a'], ['a', 'b', 'aa', 'c', 'a']], [['red', 'greeen', 'red', 'red', 'red', 'red', 'red'], ['red', 'greeen', 'red', 'red', 'red', 'red', 'red']], [['red', 'red', 'red', 'red', 'red', 'yellow', 'red'], ['red', 'red', 'red', 'red', 'red', 'yellow', 'red']], [['green', 'rred', 'yellw'], ['green', 'rred', 'yellw']], [['gbluered', 'yellow', 'belue', 'blue', 'green'], ['gbluered', 'yellow', 'belue', 'blue', 'green']], [['gbluered', 'yellow', 'red', 'blue', 'green', 'red'], ['gbluered', 'yellow', 'red', 'blue', 'green', 'red']], [['red', 'green', 'blue', 'red', 'red', 'dred', 'red'], ['red', 'green', 'blue', 'red', 'red', 'dred', 'red']], [['gbluered', 'yellow', 'byellow', 'breyellowyellow', 'blue', 'green', 'red'], ['gbluered', 'yellow', 'byellow', 'breyellowyellow', 'blue', 'green', 'red']], [['red', 'green', 'blue', 'red', 'red', 'red'], ['red', 'green', 'blue', 'red', 'red', 'red']], [['red', 'green', 'yellow'], ['red', 'green', 'yellow']], [['gbegen', 'a', 'b', '', 'c'], ['gbegen', 'a', 'b', '', 'c']], [['blue', 'red', 'red', 'blueccc', 'cc', 'red', 'red', 'blueccc'], ['blue', 'red', 'red', 'blueccc', 'cc', 'red', 'red', 'blueccc']], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'b', 'c', 'b', 'a']], [['red', 'green', 'blue', 'red', 'blue', 'green'], ['b', 'c', 'bb', 'a', 'b', 'c']], [['green', 'blue', 'yellow', 'green'], ['a', 'b', 'c', 'a', 'a']], [['green', 'blue', 'bluue', 'red', 'red', 'red'], ['green', 'blue', 'bluue', 'red', 'red', 'red']], [['red', 'red', 'red', 'gbegen'], ['a', 'a', 'a', 'a']], [['red', 'red', 'rebd', 'red', 'bluered', 'red', 'red'], ['red', 'red', 'rebd', 'red', 'bluered', 'red', 'red']], [['red', 'green', 'blue', 'eblue', 'yellw', 'yellow', 'blue', 'blue'], ['red', 'green', 'blue', 'eblue', 'yellw', 'yellow', 'blue', 'blue']], [['aa', 'bluue', 'a', 'a', 'a'], ['aa', 'bluue', 'a', 'a', 'a']], [['red', 'rred', 'green', 'blue', 'yellw', 'eblue', 'yelolow', 'blue'], ['red', 'rred', 'green', 'blue', 'yellw', 'eblue', 'yelolow', 'blue']], [['a', 'b', '', 'c', 'a', 'a', 'aa'], ['red', 'green', 'blue', 'yellow']], [['red', 'green', 'red', 'green', 'blue'], ['red', 'green', 'red', 'green', 'blue']], [['red', 'green', 'blue', 'yellow'], ['a', 'b', 'c', 'green', 'a', 'a']], [['red', 'yellow', 'red'], ['red', 'yellow', 'red']], [['red', 'green', 'green', 'green', 'green'], ['red', 'green', 'green', 'green', 'green']], [['green', 'rred', 'yellw', 'breyellowyellow', 'green'], ['green', 'rred', 'yellw', 'breyellowyellow', 'green']], [['green', 'blue', 'yellow', 'green'], ['a', 'b', 'c', 'a']], [['reed', 'blue', 'red', 'red', 'red'], ['reed', 'blue', 'red', 'red', 'red']], [['blueccc', 'blue', 'red', 'red', 'blueccc', 'red', 'cc', 'red', 'blueccc', 'red'], ['blueccc', 'blue', 'red', 'red', 'blueccc', 'red', 'cc', 'red', 'blueccc', 'red']], [['red', 'green', 'green', 'green', 'bb'], ['ccc', 'b', 'b', 'b', 'ccc']], [['b', 'green', 'rred', 'yellw', 'breyellowyellow', 'breyellowyellow', 'green'], ['b', 'green', 'rred', 'yellw', 'breyellowyellow', 'breyellowyellow', 'green']], [['gbluered', 'yellow', 'bb', 'belue', 'rebd', 'blue', 'green', 'yellow'], ['gbluered', 'yellow', 'bb', 'belue', 'rebd', 'blue', 'green', 'yellow']], [['red', 'greeen', 'blue', 'red', 'red', 'reyellowd', 'red'], ['red', 'greeen', 'blue', 'red', 'red', 'reyellowd', 'red']], [['red', 'blue', 'yellow', 'yellow'], ['red', 'blue', 'yellow', 'yellow']], [['red', 'green', 'eblue', 'blue'], ['a', 'b', 'b', 'c']], [['red', 'green', 'gbluered', 'blue', 'bluue', 'gbluered', 'red', 'red'], ['red', 'green', 'gbluered', 'blue', 'bluue', 'gbluered', 'red', 'red']], [['ared'], ['blue', 'red', 'red', 'red', 'red']], [['red', 'red', 'red', 'red', 'red', 'red', 'red', 'red'], ['a', 'b', 'ared', 'c', 'a', 'b', 'c', 'a']], [['red', 'red', 'red', 'red', 'red', 'red', 'red', 'rrebded'], ['a', 'b', 'ared', 'c', 'a', 'b', 'c', 'a']], [['a', 'b', 'abluered', 'aa', 'c', 'aa', 'aa'], ['a', 'b', 'abluered', 'aa', 'c', 'aa', 'aa']], [['a', '', 'a', 'b', 'b'], ['a', '', 'a', 'b', 'b']], [['gbegen', 'a', 'b', 'c', 'c'], ['gbegen', 'a', 'b', 'c', 'c']]]
results = [True, False, False, True, True, True, True, True, True, True, True, True, False, True, False, False, True, True, False, False, True, False, False, False, True, False, False, False, True, True, True, True, True, False, True, True, True, True, True, False, True, True, False, True, False, False, False, True, True, True, False, True, False, False, True, True, True, True, False, True, True, True, True, True, True, True, True, True, False, False, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, False, False, False, True, False, True, True, True, True, False, True, False, True, True, True, True, True, True, False, True, True, True, True, False, True, False, True, False, True, True, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_samepatterns(*inp), exp, 0)
| OK=False
==================== Problem #33 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find tuples which have all elements divisible by k from the given list of tuples.
Your answer will be tested on test cases like:
assert find_tuples([(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6) == [(6, 24, 12)]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find tuples which have all elements divisible by k from the given list of tuples.
Your answer will be tested on test cases like:
assert find_tuples([(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6) == [(6, 24, 12)]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find tuples which have all elements divisible by k from the given list of tuples.
Your answer will be tested on test cases like:
assert find_tuples([(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6) == [(6, 24, 12)]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find tuples which have all elements divisible by k from the given list of tuples.
Your answer will be tested on test cases like:
assert find_tuples([(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6) == [(6, 24, 12)]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find tuples which have all elements divisible by k from the given list of tuples.
Your answer will be tested on test cases like:
assert find_tuples([(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6) == [(6, 24, 12)]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called find_tuples that takes a list of tuples and an integer k. The goal is to find all tuples in the list where every element is divisible by k. Let me think about how to approach this.
First, the function needs to iterate through each tuple in the input list. For each tuple, I have to check all its elements. If every element is divisible by k, then include that tuple in the result.
So, for each tuple in the list, I'll loop through each element. How to check divisibility? Well, using the modulo operator. If element % k == 0, then it's divisible. But I need all elements in the tuple to satisfy this condition.
Wait, how to handle the checking for all elements. Maybe using a helper function or a generator expression. Like, for a given tuple t, check if all elements in t are divisible by k. So, for each element in t, check if element % k == 0. If all are true, then include the tuple.
So, in Python, the all() function can be useful here. For example, all(x % k == 0 for x in t). That would return True if all elements in the tuple t are divisible by k.
So putting this together: the function will filter the list of tuples, keeping only those where all elements are divisible by k.
Let me outline the steps:
1. Define the function find_tuples with parameters list_of_tuples and k.
2. Initialize an empty list to store the result.
3. Iterate over each tuple in list_of_tuples.
4. For each tuple, check if all elements are divisible by k using the all() function.
5. If yes, add the tuple to the result list.
6. Return the result list.
Wait, but what about the case when k is 0? Oh, but the problem probably assumes that k is a non-zero integer. Since division by zero is not allowed. However, the test case given uses k=6, so maybe the function is supposed to handle k as a positive integer. But the problem statement might not mention handling k=0. So perhaps we can assume that k is a valid integer (non-zero). But in code, maybe need to handle that? But the problem's test cases probably don't include k=0. So perhaps proceed under the assumption that k is not zero.
Now, let's think about the sample input. For example, the input list is [(6,24,12), (7,9,6), (12,18,21)] and k=6. The first tuple's elements are 6,24,12. All divided by 6 give 1,4,2. So yes. The second tuple: 7%6 is 1, so no. Third tuple: 12%6 is 0, 18%6 is 0, 21%6 is 3. So third tuple is not included. So the output is [(6,24,12)], which matches the sample.
So the code would be something like:
def find_tuples(list_of_tuples, k):
result = []
for t in list_of_tuples:
if all(x % k == 0 for x in t):
result.append(t)
return result
Wait, but what if the tuple is empty? Well, the problem says 'given list of tuples' but probably each tuple has elements. But the code would handle empty tuples as well. For example, if a tuple is empty, then all() returns True (since there are no elements that are not divisible by k). But perhaps the problem doesn't consider that. However, the problem's test case uses tuples with elements, so maybe that's not an issue here.
So, the code seems straightforward. Let me test the sample case.
Sample input: list is [(6,24,12), (7,9,6), (12,18,21)], k=6.
Check first tuple: 6%6=0, 24%6=0, 12%6=0. All true. So included.
Second tuple: 7%6 is 1, so condition fails. Third tuple: 12%6=0, 18%6=0, 21%6=3. So condition fails. So output is [(6,24,12)], which matches the sample.
So the code should work.
Now, the function needs to be written as a self-contained Python script. The user wants the code in a markdown code block. So the code would be:
def find_tuples(list_of_tuples, k):
return [t for t in list_of_tuples if all(x % k == 0 for x in t)]
Alternatively, using a list comprehension. That's more concise.
But perhaps the code can be written as a function. So the code would be:
def find_tuples(list_of_tuples, k):
result = []
for t in list_of_tuples:
if all(x % k == 0 for x in t):
result.append(t)
return result
Either approach works. The list comprehension is more concise. Let me check if the code would handle the sample correctly.
Yes. So the code is correct.
Now, the user wants the code in a markdown code block. So the answer is:
```python
def find_tuples(list_of_tuples, k):
return [t for t in list_of_tuples if all(x % k == 0 for x in t)]
```
But wait, what if k is zero? Well, in that case, division by zero would occur. But the problem's test cases probably don't include that. The problem's sample uses k=6, so the code works for that. The problem may assume that k is a non-zero integer.
Thus, the code is correct as per the problem's requirements.
```python
def find_tuples(list_of_tuples, k):
return [t for t in list_of_tuples if all(x % k == 0 for x in t)]
```
----------------------------------------------
Result: Pred=def find_tuples(list_of_tuples, k):
return [t for t in list_of_tuples if all(x % k == 0 for x in t)] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[(6, 24, 12), (7, 9, 6), (12, 18, 21)], 6], [[(5, 25, 30), (4, 2, 3), (7, 8, 9)], 5], [[(7, 9, 16), (8, 16, 4), (19, 17, 18)], 4], [[(12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 3], [[], 4], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 11], [[(11, 22, 33, 44, 55), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 11], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 3], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 4], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 65], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 33], [[], 5], [[(12, 24, 36, 48, 60), (15, 30, 13, 60, 75), (22, 33, 44, 55, 66), (15, 30, 45, 60, 75, 75), (8, 16, 24, 32, 40)], 4], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (4, 8, 12, 16, 20)], 55], [[(12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 16], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 8], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 3], [[], 6], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 65], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (9, 18, 27, 36, 45)], 3], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 45], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 45], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (15, 30, 45, 60, 75)], 65], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 20], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 27], [[(22, 33, 65, 44, 55, 66), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (15, 30, 45, 60, 75)], 65], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (65, 32, 48, 64), (6, 12, 18)], 27], [[(13, 39, 66, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 11], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 10, 32, 40), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 44], [[(12, 24, 36, 59, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 4], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 32], [[(13, 26, 39, 52, 65), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 33], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 12], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 65], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18), (11, 12, 24, 36)], 20], [[(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 3], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 40], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66, 66), (8, 16, 24, 32, 40)], 40], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 18)], 27], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75, 15), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 65], [[(22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 65], [[(12, 24, 36), (5, 15, 20), (18, 9, 27, 27), (32, 48, 64), (6, 12, 18)], 16], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (48, 64), (6, 18, 6)], 13], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (48, 64), (18, 9, 27), (6, 18, 6)], 13], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (22, 33, 44, 55, 66)], 40], [[(15, 30, 45, 60, 75), (8, 16, 24, 32, 40, 16), (22, 33, 44, 55, 66), (8, 16, 10, 32, 40), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 44], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45), (6, 12, 18, 24, 30)], 32], [[(11, 22, 33, 44, 55), (17, 34, 51, 68, 85, 85), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 11], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 25, 32, 40), (22, 33, 44, 55, 66)], 40], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (27, 26, 39, 52, 65), (9, 18, 27, 36, 45)], 48], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75, 15), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 65], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 8], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55, 44), (11, 22, 33, 44, 55)], 3], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (4, 8, 12, 16, 20), (9, 18, 27, 36, 45)], 55], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 9], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45), (6, 44, 18, 24, 30), (6, 12, 18, 24, 30)], 32], [[(5, 15, 20, 20), (11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (48, 64), (6, 18, 6)], 8], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 85], [[(12, 24, 36, 48, 60, 48), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40), (15, 30, 45, 60, 75)], 4], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 27), (48, 64), (18, 9, 27), (6, 18, 6)], 13], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 24], [[], 3], [[(5, 15, 20, 20), (11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (11, 12, 24, 33), (18, 9, 27), (48, 64), (6, 18, 6)], 8], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45), (6, 44, 18, 24, 30), (6, 12, 18, 24, 30)], 55], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 66], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (9, 18, 27, 36, 45)], 85], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 34], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 48], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 41], [[(11, 22, 33, 44, 55), (17, 34, 51, 68, 6, 85, 85), (17, 34, 51, 68, 85, 85), (11, 54, 22, 33, 44, 55), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 52], [[(11, 12, 24, 36), (12, 24, 36), (18, 9, 27), (48, 64), (18, 9, 27), (6, 18, 6)], 40], [[(13, 26, 39, 53, 52, 65), (11, 22, 33, 44, 55), (17, 34, 51, 68, 85, 85), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 11], [[(13, 26, 39, 53, 52, 65), (11, 22, 33, 44, 55), (17, 34, 51, 68, 85, 85), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 9], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 10, 32, 40), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 45], [[(6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (27, 26, 39, 52, 65), (9, 18, 27, 36, 45)], 48], [[], 51], [[(13, 26, 39, 51, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 32], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45), (9, 18, 27, 36, 45)], 11], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 16, 24, 32, 40)], 8], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 28], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (65, 32, 48, 64), (6, 12, 18)], 3], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (6, 12, 18, 24, 30)], 8], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (8, 18, 24, 32, 40), (8, 16, 24, 32, 40)], 65], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (48, 64), (6, 18, 6)], 12], [[], 34], [[(12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 20], [[(15, 30, 45, 60, 75), (22, 33, 22, 44, 55, 66), (8, 16, 24, 32, 40), (15, 30, 45, 60, 75)], 65], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55), (9, 18, 27, 36, 45)], 64], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 48], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45), (9, 18, 27, 36, 45), (9, 18, 27, 36, 45)], 24], [[(13, 26, 39, 52, 65), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (22, 33, 44, 55, 66), (9, 18, 27, 36, 45)], 41], [[(5, 15, 20, 20), (11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (11, 12, 24, 33), (18, 9, 27), (48, 64), (6, 18, 6)], 64], [[(11, 12, 24, 36), (12, 24, 36), (20, 5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 28], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36), (11, 22, 33, 44, 55)], 18], [[(12, 24, 36), (6, 12, 18), (5, 15, 20), (18, 9, 27, 27), (32, 48, 64), (6, 12, 18)], 10], [[(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55)], 3], [[(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30), (9, 18, 15, 27, 36, 45), (11, 22, 33, 44, 55)], 3], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (32, 48, 64), (6, 12, 18)], 9], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75, 15), (45, 33, 44, 55, 66), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 65], [[(15, 30, 45, 60, 75), (22, 33, 44, 55, 66), (44, 8, 16, 10, 32, 40), (8, 16, 10, 32, 40), (8, 16, 24, 32, 40), (8, 16, 24, 32, 40)], 45], [[(5, 15, 20, 20), (11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (48,), (18, 9, 27), (48, 64), (6, 18, 6)], 8], [[(12, 24, 36, 48, 60), (15, 30, 45, 60, 75, 15), (22, 33, 44, 55, 66), (8, 16, 24, 32), (8, 16, 24, 32, 40), (15, 30, 45, 60, 75, 15), (22, 33, 44, 55, 66)], 65], [[(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30), (9, 18, 15, 27, 36, 45), (11, 22, 33, 44, 55)], 2], [[(11, 12, 24, 36), (12, 24, 36), (64,), (5, 15, 20), (18, 9, 27), (48, 64), (6, 18, 6)], 13], [[(11, 12, 24, 36), (12, 24, 36), (5, 15, 20), (18, 9, 27), (65, 32, 48, 64, 64), (6, 12, 18)], 3], [[(11, 22, 33, 44, 55), (17, 34, 51, 68, 85, 85), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 68], [[(4, 8, 12, 16, 20), (6, 12, 18, 24, 30), (9, 18, 27, 36, 45), (11, 22, 33, 44, 55, 44), (11, 22, 33, 44, 55)], 2], [[(17, 34, 51, 68, 85, 85), (13, 26, 39, 52, 65), (17, 34, 51, 68, 85), (5, 10, 15, 20, 25)], 16], [[(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30), (9, 18, 15, 27, 36, 45)], 2]]
results = [[(6, 24, 12)], [(5, 25, 30)], [(8, 16, 4)], [(12, 24, 36), (18, 9, 27), (6, 12, 18)], [], [(22, 33, 44, 55, 66)], [(11, 22, 33, 44, 55)], [(6, 12, 18, 24, 30), (9, 18, 27, 36, 45)], [(12, 24, 36, 48, 60), (8, 16, 24, 32, 40)], [], [], [], [(12, 24, 36, 48, 60), (8, 16, 24, 32, 40)], [], [(32, 48, 64)], [], [(6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45)], [], [], [(6, 12, 18, 24, 30), (9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45), (9, 18, 27, 36, 45)], [], [], [], [], [], [], [], [(22, 33, 44, 55, 66)], [], [(8, 16, 24, 32, 40)], [], [], [(12, 24, 36)], [], [], [(6, 12, 18, 24, 30), (9, 18, 27, 36, 45)], [], [], [], [], [], [(32, 48, 64)], [], [], [], [], [], [(11, 22, 33, 44, 55)], [], [], [], [], [(6, 12, 18, 24, 30), (9, 18, 27, 36, 45)], [], [(9, 18, 27, 36, 45, 45), (9, 18, 27, 36, 45)], [], [(48, 64)], [], [(12, 24, 36, 48, 60, 48), (8, 16, 24, 32, 40)], [], [], [], [(48, 64)], [], [], [], [], [], [], [], [], [(11, 22, 33, 44, 55)], [], [], [], [], [], [(22, 33, 44, 55, 66)], [(8, 16, 24, 32, 40)], [], [(12, 24, 36), (18, 9, 27), (6, 12, 18)], [], [], [(12, 24, 36)], [], [], [], [], [], [], [], [], [], [], [], [(9, 18, 27, 36, 45)], [(6, 12, 18, 24, 30), (9, 18, 15, 27, 36, 45)], [(18, 9, 27)], [], [], [(48,), (48, 64)], [], [(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30)], [], [(12, 24, 36), (18, 9, 27), (6, 12, 18)], [], [(4, 8, 12, 16, 20), (6, 12, 18, 24, 30)], [], [(4, 8, 12, 16, 20), (4, 8, 12, 16, 20, 16), (6, 12, 18, 24, 30)]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_tuples(*inp), exp, 0)
| OK=True
==================== Problem #34 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find whether a number is divisible by 11.
Your answer will be tested on test cases like:
assert is_Diff (12345) == False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find whether a number is divisible by 11.
Your answer will be tested on test cases like:
assert is_Diff (12345) == False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find whether a number is divisible by 11.
Your answer will be tested on test cases like:
assert is_Diff (12345) == False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find whether a number is divisible by 11.
Your answer will be tested on test cases like:
assert is_Diff (12345) == False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find whether a number is divisible by 11.
Your answer will be tested on test cases like:
assert is_Diff (12345) == False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to check if a number is divisible by 11. Let me think about the different ways to do this.
Hmm, the standard method for checking divisibility by 11 is the alternating sum of the digits. Like, for a number, you subtract and add digits alternately and see if the result is divisible by 11. For example, take 121: (1 - 2 + 1) = 0, which is divisible by 11, so 121 is divisible by 11.
Wait, but maybe there's another way. Like, just using the modulus operator. Because if a number mod 11 is zero, then it's divisible. But maybe the problem expects using the digit method, but the user didn't specify any constraints. However, using the modulus operator is straightforward. Let me check the test case given: assert is_Diff(12345) == False. Wait, the function name in the test is is_Diff, but the question says to write a function to check divisibility by 11. Maybe that's a typo. But the user's test case uses is_Diff, but perhaps the actual function should be named is_divisible_by_11 or something similar. Wait, the problem says the function is called is_Diff? Or maybe that's a mistake in the test case. Wait, the user wrote: "Your answer will be tested on test cases like: assert is_Diff (12345) == False". So the function is expected to be called is_Diff. But that's probably a typo. Maybe the original problem intended is_Divisible or something else. But according to the test case, the function name is is_Diff. So I need to write a function named is_Diff that returns True if the number is divisible by 11, else False.
But wait, the function name in the test case is is_Diff. Maybe that's a typo for is_Divisible. But regardless, the user's test case uses is_Diff, so the function must be named is_Diff.
So the function is_Diff(n) returns True if n is divisible by 11, else False.
Now, how to implement this. The simplest way is to check if n % 11 == 0. But maybe the user wants the alternative method. However, the problem says to write a function to find whether a number is divisible by 11. So using the modulus operator is the straightforward approach.
But let me think about possible edge cases. For example, negative numbers. But modulus in Python handles negatives. For example, -11 % 11 is 0. So that's okay.
So the function can be written as:
def is_Diff(n):
return n % 11 == 0
But wait, what about the test case given? Let's check 12345. Let's compute 12345 divided by 11. Let me calculate 11 * 1122 = 12342. 12345 - 12342 = 3. So remainder is 3, so 12345 mod 11 is 3. So the function returns False, which matches the test case. So that's correct.
But maybe the problem expects using the digit method. Let me think. For example, the alternating sum method. Let's see. For the number 12345, the digits are 1, 2, 3, 4, 5. The alternating sum would be 1 - 2 + 3 -4 +5 = (1-2) is -1, +3 is 2, -4 is -2, +5 is 3. So 3. Which is not divisible by 11, so returns False. Which matches the test case. So either method works.
But which method is better? Well, the modulus method is straightforward and efficient. However, if the problem is expecting the digit method, perhaps that's the way to go. But the problem says to write a function to find whether a number is divisible by 11. So either approach is correct.
But perhaps the user wants the modulus approach. So the code is simple. However, maybe the user has some constraints, like not using modulus. But the problem doesn't mention that. So the simplest solution is to use the modulus operator.
Therefore, the function is_Diff(n) can be implemented as return n % 11 == 0.
But wait, the function name is is_Diff. Maybe that's a typo, but the user's test case uses that name. So the code should have that function name.
So the code would be:
def is_Diff(n):
return n % 11 == 0
But let me check for some other cases. For example, 121: 121 % 11 is 0. So returns True. Which is correct. For 11, returns True. For 10, returns False. So this seems correct.
So the code is straightforward. So the final answer is the function is_Diff that checks if the number mod 11 is zero.
```python
def is_Diff(n):
return n % 11 == 0
```
----------------------------------------------
Result: Pred=def is_Diff(n):
return n % 11 == 0 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[12345], [1212112], [1212], [12345678901234567890], [98765432109876543210], [-1212], [-12345], [-12345678901234567890], [987654321098765432109876543210], [-123456789012345678901234567890], [123456789012345678901234567890], [-987654321098765432109876543210], [9876543210987654321098765432110], [9876543210987654321098765432101], [-9876543210987654321098765432110], [-9876543210987654321098765432101], [-1000], [1001], [0], [-65], [1002], [-12345678901234567889], [True], [-56], [98765432109876543209], [9876543210987654321098765432102], [-64], [-9876543210987654321098765432100], [-12344], [-63], [987654321098765432109876543211], [False], [-999], [98765432109876543211], [-57], [-66], [-55], [-123456789012345678901234567891], [-987654321098765432109876543211], [123456789012345678901234567891], [-67], [-39], [61], [987654321098765432109876543209], [-12343], [987654321098765432109876543208], [-54], [-58], [987654321098765432109876543212], [9876543210987654321098765432103], [-12345678901234567891], [-62], [-9876543210987654321098765432111], [-12345678901234567888], [12345678901234567891], [12345678901234567892], [1], [987654321098765432109876543214], [98765432109876543212], [-9876543210987654321098765432102], [-9876543210987654321098765432099], [81], [987654321098765432109876543213], [9876543210987654321098765432105], [-9876543210987654321098765432112], [123456789012345678901234567889], [9876543210987654321098765432104], [-59], [-61], [-9876543210987654321098765432098], [-1213], [96], [1000], [98765432109876543208], [12345678901234567889], [-123456789012345678901234567892], [-38], [-987654321098765432109876543208], [-123456789012345678901234567893], [-987654321098765432109876543212], [12345678901234567893], [999], [-60], [987654321098765432109876543215], [-40], [-53], [100], [82], [-12346], [80], [-52], [-78], [-123456789012345678901234567889], [-12342], [60], [-68], [9876543210987654321098765432100], [-9876543210987654321098765432113], [-123456789012345678901234567888], [1003], [47], [79], [59], [9876543210987654321098765432108], [36], [37], [9876543210987654321098765432107], [2], [12345678901234567894], [98765432109876543213], [-12347], [-1211], [-88], [1004], [98765432109876543214], [-51], [-998], [-50], [-9876543210987654321098765432109]]
results = [False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, True, False, False, True, False, False, True, False, False, False, False, False, False, True, False, False, False, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, True, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_Diff(*inp), exp, 0)
| OK=True
==================== Problem #35 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the length of the word is odd or not.
Your answer will be tested on test cases like:
assert word_len("Hadoop") == False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the length of the word is odd or not.
Your answer will be tested on test cases like:
assert word_len("Hadoop") == False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the length of the word is odd or not.
Your answer will be tested on test cases like:
assert word_len("Hadoop") == False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the length of the word is odd or not.
Your answer will be tested on test cases like:
assert word_len("Hadoop") == False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to check whether the length of the word is odd or not.
Your answer will be tested on test cases like:
assert word_len("Hadoop") == False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called word_len that checks if the length of a word is odd. Let's see. The problem says to return False if the length is even, like in the example where "Hadoop" has 6 letters, which is even, so the result is False. Wait, wait. Wait the example says assert word_len("Hadoop") == False. Wait, "Hadoop" is spelled H-A-D-O-O-P. That's 6 letters. So 6 is even, so the function returns False. So the function should return True if the length is odd, False otherwise.
So the steps are: take the input word, calculate its length, check if that length is odd. How to do that in Python.
So the function would be something like:
def word_len(word):
length = len(word)
return length % 2 != 0
Wait, because if the length modulo 2 is 1, then it's odd. So returning whether the length is not divisible by two. Alternatively, return length % 2 == 1. Either way.
But wait, the example given is "Hadoop" which has length 6. 6 mod 2 is 0, so the function returns False, which matches the example. So that's correct.
So the code is straightforward. The function takes a string, computes its length, checks if it's odd, returns True or False.
Now, I need to make sure that the code is self-contained. The user says to put all Python code in a markdown code block. So the code should be a function definition. Let me write that.
So the code would be:
def word_len(word):
return len(word) % 2 != 0
Wait, but maybe the problem expects the function to be named word_len. Let me check the target question again. Yes, the function is called word_len. So that's correct.
Testing with the example: "Hadoop" has len 6. 6%2 is 0, so 0 !=0 is False. So returns False. Which matches the test case. So that's correct.
I think that's all. The code is simple. No edge cases? Well, what if the word is empty? Well, len is 0, which is even, returns False. Which is correct.
So the code should work.
```python
def word_len(word):
return len(word) % 2 != 0
```
----------------------------------------------
Result: Pred=def word_len(word):
return len(word) % 2 != 0 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['Hadoop'], ['great'], ['structure'], ['a'], ['longstringwithmixture'], ['lonlongstringwithmixturegstringwithmixture'], ['lonlongstringwithmixturegstringwithmixturlongstringwithmixturee'], ['lonlongstringwithmixturegstringwithmxture'], ['longstringwithmiixtiure'], ['lnongstringwithmixture'], ['alongstringwithmiixtiure'], ['lonlongstringwitlongstringwithmiixtiurehmixturegstringwithmxture'], ['lonlongstringwithmixturegstringwithlongstringwithmixturemixture'], ['lonlongstringwitringwithmixture'], ['lnongstringwithmixturea'], ['mlongstringwithmiixtiure'], ['lonlongstrringwithmixturegstringwithlongstringwitnhmixturemixture'], ['longstringwithmiixlonlongstringwithmixturegstringwithmxturetiure'], ['lonlongstringwitringwhithmixture'], ['lonlongstringwithmixturegstringwithmixturlongstringwithmixturelongstringwithmiixlonlongstringwithmixturegstringwithmxturetiuree'], ['lonlongstringwithmixlonlongstringwithmixturegstringwithmixtureturegstringwithmixture'], ['lonlongstringwitringwithmixtongtstringwitringwhithmixture'], ['lnongstringwithmixlonlongstringwithmixturegstringwithmxtureturea'], ['lnmlongstringwithmiixtiureongstringwithmixturea'], ['longstringwithmiixlonlongstringwithmixturegstlringwithmxturetiure'], ['TtYAzEr'], ['lonlongstrlonlongstrringwithmixturegstringwithlongstringwitnhmixturemixtureingwithmixturegstringwithmxture'], ['lnmlongstringwithmiixtiureongstringwithmixturelonlongstringwitringwhithmixturea'], ['longstlongstringwithmiixlonlongstringwithmixturegstringwithmxturetiureringwithmiixtiure'], ['lonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnhmixturemixtureingwithmixturegstrinhmtxture'], ['aa'], ['longastringwithmiixtiure'], ['longastringxwithmiixtiure'], ['liongastringwithmixtiure'], ['lonlongstringwithmixlonlongstrilongstringwithmixturengwithmixturegstringwithmixtureturegstringwithmixture'], ['lnongstriengwithmixturea'], ['longstringwithmiixlonlongstringwithmialongstringwithmiixtiurexturegstringwithmxturetiure'], ['longstringwithmiixlonnlongstringwithmixturegstringwithmxturetiure'], ['alongslongastringwithmiixtiuretringwithmiixtiure'], ['lonlongstringwithmixturegstrinurlongstringwithmixturee'], ['longstringwithmiixlonlongstrinlonlongstringwithmixturelongstringwithmiixlonlongstringwithmixturegstringwithmxturetiuregstringwithlongstringwithmixturemixturethmxturetiure'], ['lonlongstringwitringwithmixtongtstringwitringwhitthmixture'], ['longstringwithmiixlonlongstringwithmialongstrilnmlongstringwithmiixtiureongstringwithmixtureangwithmiixtiurexturegstringwithmxturetiure'], ['lonlongstrinlonlongstringwithmixturegstringwithmxturegwitringwhithmixture'], ['lonlongstringwitringwithmixlonlongstringwithmixturegstringwithmxtureture'], ['mlongstringwithmiiwxtiure'], ['lionglongastringxwithmiixtiureastringwithmixtiure'], ['lonlongstringwitringwiithmixture'], ['longstlongstringwithmiixlonlongstringwithmixturegstringwithmxturetiurerinigwithmiixtiure'], ['mlongstringwwithmiixtiure'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiureonlongstrlonlongstrringwithmixturegstringwithlongstringwitnhmixturemixtureingwithmixturegstringwithmxtureingwitnhmixturemixture'], ['lnongstringwithmirea'], ['lonlongstringwithmixturegstringwithmixturlongstlonlongstrlonlongstrringwithmixturegstringwitlonlongstringwitringwithmixlonlongstringwithmixturegstringwithmxtureturegwithmixturee'], ['mxlongstringwithmiixtiure'], ['lonlongstringwithmixturegstringwithmxturlongstringwithmixturee'], ['lnmlongstringwithmiixtiureongstringwithmixtulongstlongstringwithmiixlonlongstringwithmixturegstringwithmxturetiurerinigwithmiixtiure'], ['mlongstrintgwwithmiixtiure'], ['lonlongstringwitringwithmixtongtstringwitringwhtithmixture'], ['lonlongstringwithmixturegstringwithmixturlongstlonlongstringwithmixturegstringwithmixturlongstringwithmixturelongstringwithmiixlonlongstringwithmixturegstringwithmxturetiureeringwithmixturelongstringwithmiixlonllonlongstringwitringwiithmixturegstringwithmxturetiuree'], ['lonlongstrhingwithmixlonlongstrilongstringwithmixturengwithmixturegstrhgingwithmixtureturegstringwithmixture'], ['ltiongastringwithmixtiure'], ['liongastringwithmtixtiure'], ['lnongstringwgithlnongstringwithmixtureturegstringwithmxtureturea'], ['lgstringwithmixturee'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiureonlongstrlonlongstrringwithmixturegstringwithlongstringwiwithmxtureingwitnhmixturemixture'], ['alonlongstringwithmixturegstringwithmixturlongstlonlongstrlonlongstrringwithmixturegstringwitlonlongstringwitringwithmixlonlongstringwithmixturegstringwithmxtureturegwithmixtureea'], ['lonlongstrhingwithmixlonlongstrilongstringwithmixturengwithmixturegstrhgingwithmixturture'], ['lonlongstrinlonlongstringwithmixturegstringwithmxturegwitringwhithmlongstringwithmiixlonlongstringwithmixturegstlringwithmxturetiureixture'], ['lnmlongstringwithmiixtiurreonwgstringwithmixturelonlongstringwitringwhithmixturea'], ['lonlongstrlongstringwithmiixlonlongstrinlonlongstringwithmixturelongstringwithmiixlonlongstringwithmixturegstringwithmxturetiuregstringwithlongstringwithmixturemixturethmxturetiureingwitringwithmixture'], ['lonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnlongastringxwithmiixtiurehmixturemixtureingwithmixturegstrinhmtxture'], ['lonlongstringwitringwlonlongstrringwithmgwitnhmixturemixturehithmixture'], ['lonlongstringwitritngwithmixture'], ['lnongs'], ['alongslonlongstrlonlongstrrinlonlongstringwithmixturegstringwithmixturlongstringwithmixtureegwithmixturegstringwithlongstringwitnhmixturemixtureingwithmixturegstringwithmxturelongastringwithmiixtiuretringwithmiixtiure'], ['lnongstrilonlongstrringwithmixturegstringwithlongstringwitnhmixturemixturengwithmixlonlongstringwithmixturelonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnlongastringxwithmiixtiurehmixturemixtureingwithmixturegstrinhmtxturegstringwithmxtureturea'], ['longastringxwithmiixtiurliongastringwithmtixtiuree'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiulreonlongstrlonlongstrringwithmixturegstringwithlongstringwiwithmxtureingwitnhmixturemixture'], ['longstringwithmiixlonlongstringwitlongstringwithmiixtiuremixturegstlringwithmxturetiure'], ['lonlongstringwithmixturegstrinurlongstringwithhmixturee'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiureonlongstrlonlongstrringwithmixturegstringwithlongstringwiwithmxtureingwitnhmixturemixre'], ['ltiongastringwithmixtinure'], ['lonlongstringwithmixturegstringwithmixturlongstlonlongstrlonlthmixturegstringwithmxtureturegwithmixturee'], ['lonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnhmixtulonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiureonlongstrlonlongstrringwithmixturegstringwithlongstringwiwithmxtureingwitnhmixturemixreremixtureingwithmixturegstrinhmtxture'], ['lonlongstringwitrinthmixtongtstrinigwitringwhtithmixture'], ['longstringwitlongstringwithmiixlonlongstringwithmilonlongstringwitringwithmxturexturegstlringwithmxturetiurehmiixtiure'], ['mxllonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnhmixturemixtustrinhmtxtureongstringwithmiixtiure'], ['lonlongstrlongstringwithmiixlonlongstrinlonlongstringwithmixturelongstringwithmiixlonlongstringwithmixturegstringwithmxturetiuoregstringwithlongstringwithmixturemixturethmxturetiureingwitringwithmixture'], ['lnmlongstringwithmiixtiureongstringwithmixturealonlongstringwithmixturegstringwithmixturlongstringwithmixturee'], ['longstlongstrsingwithmiixlonlongstringwithmixturegstringwithmxturetiuaare'], ['lgstringwithmlonlongstringwithmixturegstringwithmxtureixturee'], ['alongslonlongstrlonlongstrrinlonlongstringwithmixturegstringwithmixturlongstringwithmixtureegwithmixturegstringwithlongstringwitnhmtixturemixtureingwithmixturegstringwithmxturelongastringwithmiixtiuretringwithmiixtiure'], ['lithmiixtgwithmxturetiure'], ['lnmlongstringwithmiixtiurreonwgstringwithmixturelonlongstringwitlongstlongstringwithmiixlonlongstringwithmixturegstringwithmxturetiurerinigwithmiixtiureringwhithmixturlongstringwitlongstlonlongstringwitringwiithmixtureringwithmiixlonlongstringwithmilonlongstringwitringwithmxturexturegstlringwithmxturetiurehmiixtiureea'], ['mxllonlongstrlonlongstrringwithmixturegstringwithlongstringwitwnhmixturemixtustrinhmtxlonlongstringwithmixturegstringwithmixturlongstlonlongstrlonlthmixturegstringwithmxtureturegwithmixtureetureongstringwithmiixtiure'], ['lonlongstrlonlongstrringhwithmixturegstringwithlongstringwitnhmixturemixtureingwithmixturegstringwithure'], ['longstlongstrsingwithmiixlonlongsxtringwithmiithmxturetiuaare'], ['lgstringwithmixtlnongstringwithmireareelnmlongstringwithmiixtiureongstringwithmixturelonlongstringwitringwhithmixturea'], ['lolongastringxwithmiixtiurliongastringwithmtixtiureengstringwithmiixlonlongstrinlonlongstringwithmixturelongstringwithmiixlonlongstringwithmixturelongstringwithmiixlonnlongstringwithmixturegstringwithmxturetiuregstringwithmxturetiuregstringwithlongstringwithmixturemixturethmxturetiure'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiulreonlongstrlonlongstrringwithmixturegstringwlonlongstringwitringwithmixturethmxtureingwitnhmixturemixture'], ['lnmlongstringwithmiimxtiureongstringwithmixturea'], ['lonlongstrringwithmixturegstringwithlongstrllongstringwithmiixtiulreliongastringwithmtixtiureonlongstrlonlongstrringwithmixturegstringwithlongstringwiwithmxtureingwitnhmixturemixture'], ['longstrinithmixture'], ['lgstringwithmixtlnongstringwithmireareelnmlongstringwithmiixtiurheongstringwithmixturelonlongstringwitringwhithmixturea'], ['longasntringxwithmiixtiure']]
results = [False, True, True, True, True, False, True, True, True, False, False, False, True, True, True, False, True, False, False, True, False, True, False, True, True, True, False, True, True, False, False, False, True, False, True, False, False, True, False, False, False, False, True, True, False, True, True, False, False, True, False, False, True, True, False, False, False, False, False, False, True, True, False, False, False, True, True, False, True, True, True, True, False, False, True, False, False, True, True, True, False, False, False, False, False, False, False, False, False, True, True, False, True, True, False, False, True, False, True, True, False, False, True, True, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(word_len(*inp), exp, 0)
| OK=True
==================== Problem #36 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth tetrahedral number.
Your answer will be tested on test cases like:
assert tetrahedral_number(5) == 35
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth tetrahedral number.
Your answer will be tested on test cases like:
assert tetrahedral_number(5) == 35
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth tetrahedral number.
Your answer will be tested on test cases like:
assert tetrahedral_number(5) == 35
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth tetrahedral number.
Your answer will be tested on test cases like:
assert tetrahedral_number(5) == 35
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth tetrahedral number.
Your answer will be tested on test cases like:
assert tetrahedral_number(5) == 35
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called tetrahedral_number that takes an integer n and returns the nth tetrahedral number. Let me think about what a tetrahedral number is.
Hmm, I remember that tetrahedral numbers are a type of figurate number. They represent the number of objects in a tetrahedron with n layers. Oh right, the formula for the nth tetrahedral number is the sum of the first n triangular numbers. Or maybe there's a direct formula?
Wait, the formula for the nth tetrahedral number is n(n+1)(n+2)/6. Let me check that. For example, when n=1, it's 1*2*3/6=6/6=1. That's correct. For n=2, 2*3*4/6=24/6=4. Let me verify with the sum of triangular numbers. The first triangular number is 1, the second is 3. Sum is 1+3=4. Yep, matches. So the formula seems right.
So the function can be written by taking n, computing n*(n+1)*(n+2) divided by 6. But wait, since we're dealing with integers, we need to make sure that the division is exact. But since tetrahedral numbers are integers, the formula should always result in an integer.
So the steps for the function are straightforward. Take n as input, compute the product of n, n+1, n+2, then divide by 6. Return that as an integer.
Wait, but in Python, if I do integer division with //, maybe that's better. Let me see. For example, 5*(5+1)*(5+2) is 5*6*7 = 210. Divided by 6 is 35. Which matches the test case given: assert tetrahedral_number(5) == 35. So yes.
So the code would be:
def tetrahedral_number(n):
return n * (n + 1) * (n + 2) // 6
Wait, but what about for larger n? Let me test another case. Let's take n=3. The formula gives 3*4*5=60, divided by 6 is 10. Let me check the sum of triangular numbers. Triangular numbers are 1, 3, 6. Sum is 1+3+6=10. Correct. So the formula works.
So the function is simple. Just calculate that formula. So the code should be straightforward. Now, the user wants the function in a self-contained Python script. So the code would be:
def tetrahedral_number(n):
return n * (n + 1) * (n + 2) // 6
But wait, maybe I should handle n=0? Well, the problem says "nth tetrahedral number", but the test case starts with n=5. Let me check the definition. The first tetrahedral number is for n=1. So the function is intended for n ≥ 1. But the code would work for n=0 as well, returning 0*1*2//6=0, but maybe that's not required. However, the problem's test case uses n=5, so the code should handle that.
So the code is correct. The function is as simple as that. So the Python script would be as written.
```python
def tetrahedral_number(n):
return n * (n + 1) * (n + 2) // 6
```
----------------------------------------------
Result: Pred=def tetrahedral_number(n):
return n * (n + 1) * (n + 2) // 6 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[5], [6], [7], [10], [11], [True], [False], [12], [13], [9], [14], [8], [15], [16], [73], [17], [74], [75], [76], [29], [78], [18], [77], [19], [72], [28], [30], [55], [56], [3], [2], [57], [79], [4], [20], [31], [1], [71], [84], [54], [95], [85], [53], [39], [58], [80], [70], [59], [52], [32], [40], [38], [83], [82], [26], [60], [61], [62], [37], [33], [86], [81], [66], [41], [36], [96], [27], [35], [87], [69], [88], [97], [68], [65], [21], [34], [64], [94], [89], [67], [42], [98], [100], [22], [99], [90], [91], [43], [101], [0], [92], [63], [25], [23], [44], [51], [93], [24], [102], [50], [45]]
results = [35.0, 56.0, 84.0, 220.0, 286.0, 1.0, 0.0, 364.0, 455.0, 165.0, 560.0, 120.0, 680.0, 816.0, 67525.0, 969.0, 70300.0, 73150.0, 76076.0, 4495.0, 82160.0, 1140.0, 79079.0, 1330.0, 64824.0, 4060.0, 4960.0, 29260.0, 30856.0, 10.0, 4.0, 32509.0, 85320.0, 20.0, 1540.0, 5456.0, 1.0, 62196.0, 102340.0, 27720.0, 147440.0, 105995.0, 26235.0, 10660.0, 34220.0, 88560.0, 59640.0, 35990.0, 24804.0, 5984.0, 11480.0, 9880.0, 98770.0, 95284.0, 3276.0, 37820.0, 39711.0, 41664.0, 9139.0, 6545.0, 109736.0, 91881.0, 50116.0, 12341.0, 8436.0, 152096.0, 3654.0, 7770.0, 113564.0, 57155.0, 117480.0, 156849.0, 54740.0, 47905.0, 1771.0, 7140.0, 45760.0, 142880.0, 121485.0, 52394.0, 13244.0, 161700.0, 171700.0, 2024.0, 166650.0, 125580.0, 129766.0, 14190.0, 176851.0, 0.0, 134044.0, 43680.0, 2925.0, 2300.0, 15180.0, 23426.0, 138415.0, 2600.0, 182104.0, 22100.0, 16215.0]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(tetrahedral_number(*inp), exp, 0)
| OK=True
==================== Problem #37 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the volume of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(volume_sphere(10), 4188.790204786391, rel_tol=0.001)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the volume of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(volume_sphere(10), 4188.790204786391, rel_tol=0.001)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the volume of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(volume_sphere(10), 4188.790204786391, rel_tol=0.001)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the volume of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(volume_sphere(10), 4188.790204786391, rel_tol=0.001)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the volume of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(volume_sphere(10), 4188.790204786391, rel_tol=0.001)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called volume_sphere that calculates the volume of a sphere. Let me think about the formula for the volume of a sphere. Oh right, the formula is (4/3) * π * r³, where r is the radius.
So the function will take the radius as input. I need to make sure to import the math module to use math.pi for π. Then, compute the cube of the radius, multiply by 4/3 and π.
Wait, but in Python, the exponentiation is done with **. So r cubed would be r ** 3. Let me structure the function:
def volume_sphere(radius):
return (4/3) * math.pi * (radius ** 3)
But wait, the user provided a test case where they use math.isclose with rel_tol=0.001. So the function needs to return a float. Also, the example uses 10 as the radius, and the expected result is approximately 4188.79... Let me check that.
Calculating (4/3)*π*10³: 4/3 is about 1.333333. 10³ is 1000. Multiply by π (approx 3.14159) gives 1.3333 * 3.14159 * 1000. Let me compute that. 1.3333 * 3.14159 is roughly 4.18879, multiplied by 1000 gives 4188.79, which matches the test case. So the formula is correct.
So the function is straightforward. I need to import math, then implement that formula. Also, the function should handle the radius as a numeric type. The problem says to write a self-contained script, so the code should include the necessary imports and the function.
So putting it all together:
Import math, define the function, return the calculation. Then, the test case would be using math.isclose to check the result. But the user's test case is given as an example, but the code doesn't need to include the test, just the function.
So the code should be:
import math
def volume_sphere(radius):
return (4.0 / 3.0) * math.pi * (radius ** 3)
Wait, using 4.0 and 3.0 to ensure floating point division. But in Python 3, 4/3 would be 1.333... as a float. So maybe it's better to write 4/3 as 4.0/3.0 or just 4/3. Either way, the result is a float.
So the code is correct. Let me make sure there are no typos. The function is called volume_sphere, and the parameter is radius. Yes. So that's the code.
```python
import math
def volume_sphere(radius):
return (4.0 / 3.0) * math.pi * (radius ** 3)
```
----------------------------------------------
Result: Pred=import math
def volume_sphere(radius):
return (4.0 / 3.0) * math.pi * (radius ** 3) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10], [25], [20], [3.5], [1000000.0], [3.141], [10000000000.0], [3.14159265], [4.623802984914555], [3.3559788784471767], [66], [4.869200998343475], [3.8682074878773713], [918660.8851175675], [67], [2.882805679516125], [5.334665111091932], [3.3742973741685773], [1370408.3632012897], [2.1679948447223243], [6.1937397356958686], [68], [2.5343594560319853], [2.3432251842864593], [4.61675941883145], [4.371968506027651], [5.592539737328484], [745764.3921613692], [2.9898806623772485], [1300062.0481719284], [2.5896160698519415], [3.315962725294531], [8.526243131220685], [7.966847190064601], [3.4948208700163326], [3.092435587548573], [980845.2335352049], [2.161534559679202], [6.337453960004688], [918661.1231404628], [1.708581242035472], [6.268623349038191], [4.445885418463103], [69], [1206585.2634025752], [70], [5.253217457458149], [2.574352689612276], [8.876033871274153], [2.217295171366912], [5.148340229570737], [5.7430353597257335], [6.798195121344899], [918660.6321974591], [2.714392744717933], [1206585.7451337874], [4.454238599875553], [4.532844704583202], [2.9221428096017963], [5.9095950914668425], [1354585.0574878817], [1.3593066232553286], [870299.1979522441], [4.589385338378119], [2.111585416266776], [0.9463990934397435], [True], [82.06805292937108], [5.3222759634147385], [3.9025520292716678], [2.1319562379470947], [1206584.7863918154], [4.051515228306216], [2.760921157223623], [745765.2991203185], [980845.1688878584], [2.803507749709366], [1.862378605627123], [1.3300722837430694], [96.33023854016932], [2.9049275477536], [1000000.8406259468], [53], [2.9211190247221785], [8.442873354975713], [6.9904770599923065], [5.394810798758247], [6.555694849044899], [2.591536041748832], [2.121870489897608], [1054792.4194213152], [4.146640167841869], [1.7582778285009857], [3.716476256173695], [4.990472347611788], [9.380605161871557], [7.081577583743362], [3.2232571533460854], [1370408.265351601], [4.789548148841643], [5.40747011739556], [2.2367969243507684], [2.6601406350111847], [4.772435918308454], [1.5596351962154023], [3.150384912225208], [10.09894030966326], [7.0674793300609355]]
results = [4188.790204786391, 65449.84694978735, 33510.32163829113, 179.59438003021648, 4.1887902047863905e+18, 129.8052979860732, 4.188790204786391e+30, 129.8787876001121, 414.08220978930444, 158.32382216888948, 1204260.4287152681, 483.5726349709714, 242.4476021059143, 3.247538326860353e+18, 1259833.1083621692, 100.35400662135389, 635.9311421948506, 160.93061509637513, 1.0780492712041234e+19, 42.68382638675828, 995.2850155956486, 1317089.6816713943, 68.18569099949832, 53.892792610648506, 412.19274258212056, 350.04161887331406, 732.6825448095367, 1.7373748858280986e+18, 111.95672149275033, 9.204089870159217e+18, 72.74359389413357, 152.72760074601416, 2596.341094297716, 2118.1078549065246, 178.7982940837717, 123.8769764473433, 3.952665536814398e+18, 42.30338893623519, 1066.1862103964213, 3.247540851149853e+18, 20.892745378807877, 1031.8228406242654, 368.0979563398477, 1376055.2813841724, 7.358048728477464e+18, 1436755.040241732, 607.2461161644434, 71.46489269230332, 2929.175964425913, 45.66244298937992, 571.5975100450872, 793.4381530237991, 1316.0412010177686, 3.2475356445837937e+18, 83.77350123445713, 7.358057541621275e+18, 370.1766669381675, 390.1226183889083, 104.51844013626022, 864.4936053725879, 1.0411359697937727e+19, 10.520609679849587, 2.7611777121368146e+18, 404.90410609421207, 39.43797169014476, 3.550680181774695, 4.1887902047863905, 2315319.8702423535, 631.5107925092389, 248.9629462460541, 40.59041267476145, 7.358040001700004e+18, 278.57429246310744, 88.15574575552081, 1.7373812245443226e+18, 3.952664755255862e+18, 92.2983404073494, 27.057803045584475, 9.856309678586227, 3744350.682699433, 102.68204855624029, 4.1888007684124657e+18, 623614.5193179834, 104.40862321022539, 2520.9221472495924, 1430.8992429352018, 657.6839806372201, 1180.170621868424, 72.90551275879267, 40.01706455473447, 4.915747976785832e+18, 298.66041225981974, 22.76937494077028, 215.0219008825413, 520.6112753349555, 3457.6511864566255, 1487.5742834730097, 140.27280281573675, 1.0780490402800114e+19, 460.2271549341555, 662.3247644417065, 46.87791422091938, 78.8501277367148, 455.31182142822155, 15.891236508702901, 130.9723035400998, 4314.356467062602, 1478.7074138156142]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(volume_sphere(*inp), exp, 0.0001)
| OK=True
==================== Problem #38 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth number in the newman conway sequence.
Your answer will be tested on test cases like:
assert sequence(10) == 6
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth number in the newman conway sequence.
Your answer will be tested on test cases like:
assert sequence(10) == 6
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth number in the newman conway sequence.
Your answer will be tested on test cases like:
assert sequence(10) == 6
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth number in the newman conway sequence.
Your answer will be tested on test cases like:
assert sequence(10) == 6
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the nth number in the newman conway sequence.
Your answer will be tested on test cases like:
assert sequence(10) == 6
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to find the nth number in the Newman-Conway sequence. Let me think about how this sequence works.
From what I remember, the Newman-Conway sequence is a recursive sequence. Let me check the definition. Oh right, the sequence is defined such that each term is the sum of the previous term and the term at the position indicated by the previous term. Wait, maybe I should get the exact recurrence relation.
Wait, the Newman-Conway sequence is defined by the recurrence relation: P(n) = P(P(n-1)) + P(n - P(n-1)), with the base cases P(1) = 1 and P(2) = 1. So for example, P(3) would be P(P(2)) + P(3 - P(2)) = P(1) + P(2) = 1 + 1 = 2.
So the problem is to compute the nth term of this sequence. The challenge is to compute this efficiently, especially for larger n. Let's think about how to approach this.
First, for small n, like 1, 2, 3, etc., we can compute directly. But for larger n, recursion with memoization might be necessary. However, recursion could lead to repeated calculations and stack overflows. So perhaps a dynamic programming approach where we build up the sequence up to n would be better.
Let me think about the steps. Let's say we need to compute sequence(n). We can create a list (or array) where we store each term as we compute it. Starting with the base cases. For n=1 and 2, return 1. For n >=3, compute each term step by step.
For example, let's compute P(3) to P(10) manually to check:
P(1) = 1
P(2) = 1
P(3) = P(P(2)) + P(3 - P(2)) = P(1) + P(2) = 1 + 1 = 2
P(4) = P(P(3)) + P(4 - P(3)) = P(2) + P(4-2) = P(2) + P(2) = 1 + 1 = 2
P(5) = P(P(4)) + P(5 - P(4)) = P(2) + P(5-2) = P(2)+P(3) = 1+2=3
P(6) = P(P(5)) + P(6 - P(5)) = P(3) + P(6-3) = 2 + P(3) = 2 + 2 =4
P(7) = P(P(6)) + P(7-P(6)) = P(4) + P(7-4) = 2 + P(3) = 2 + 2 =4
P(8) = P(P(7)) + P(8 - P(7)) = P(4) + P(8-4) = 2 + P(4) = 2 + 2 =4
P(9) = P(P(8)) + P(9 - P(8)) = P(4) + P(9-4) = 2 + P(5) = 2 +3=5
P(10) = P(P(9)) + P(10 - P(9)) = P(5) + P(10-5) = 3 + P(5) = 3 +3=6. Which matches the test case given (sequence(10) ==6). So that's correct.
So the approach is to precompute the sequence up to n using dynamic programming. Let's think about how to implement this.
We can initialize a list dp where dp[i] represents P(i). The base cases are dp[1] = 1, dp[2] = 1. Then for each i from 3 to n, compute dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]].
Yes, that's the recurrence. So the steps for the function:
- Check if n is 1 or 2, return 1.
- Else, create a list dp of size n+1 (since we'll index from 1 to n).
- Initialize dp[1] = 1, dp[2] =1.
- For i from 3 to n:
dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]]
- Return dp[n]
But wait, what about when i-1 is larger than the current index? No, because for i starting from 3, we compute each step in order. So for i=3, we need dp[2] (which is already computed), and for i - dp[i-1], which for i=3 is 3 - dp[2] = 3-1=2, which is already computed. So the approach is correct.
Let me test this logic with the example for n=10.
Let's simulate:
dp = [0, 1, 1, ... ] for indexes 0,1,2...
i=3:
dp[3] = dp[dp[2]] + dp[3 - dp[2]] = dp[1] + dp[2] = 1 +1=2. Correct.
i=4:
dp[4] = dp[dp[3]] + dp[4 - dp[3]] → dp[2] + dp[4-2] → 1 + dp[2] → 1+1=2.
i=5: dp[4] is 2. So dp[5] = dp[2] + dp[5-2=3] → 1 + 2=3.
Yes, that's correct.
So the code seems correct. Now, implement this in Python.
Now, the function is called sequence(n). So the code would be:
def sequence(n):
if n == 1 or n ==2:
return 1
dp = [0]*(n+1)
dp[1] = 1
dp[2] = 1
for i in range(3, n+1):
dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]]
return dp[n]
Wait, but what if n is 0? Well, the problem says that the test case is for n=10, so probably n is >=1. So the function can assume n is at least 1.
But the problem says that the function is to find the nth number. So the code should handle n=1, 2, etc.
Testing with the sample input:
sequence(10) should return 6. Let's see:
Let me compute the dp array up to 10.
dp[1] = 1
dp[2] = 1
dp[3] = dp[1] + dp[2] = 1+1=2
dp[4] = dp[2] + dp[2] = 1+1=2
dp[5] = dp[2] + dp[3] → 1+2=3
dp[6] = dp[3] + dp[6-3=3] → 2 + 2 =4
dp[7] = dp[4] + dp[7-4=3] → 2 + 2 =4
dp[8] = dp[4] + dp[8-4=4] → 2 + 2 =4
dp[9] = dp[5] (which is 3) + dp[9-3=6] (which is 4) → 3+4=7? Wait, wait no. Wait for i=9:
dp[9] = dp[dp[8]] + dp[9 - dp[8]]
dp[8] is 4. So dp[dp[8]] is dp[4] = 2. 9 - dp[8] is 9-4=5. dp[5] is 3. So 2 +3=5. So dp[9] is 5. Then for dp[10], which is i=10:
dp[10] = dp[dp[9]] + dp[10 - dp[9]] → dp[5] + dp[10-5=5]. dp[5] is 3, so 3 +3=6. Which is correct. So yes, the code would return 6 for n=10.
So the code seems correct.
But wait, in the code, when n is 1 or 2, return 1. For n=3, the code returns 2, which is correct.
So the code should work.
Now, the code needs to be written as a self-contained Python function. The user's test case is assert sequence(10) ==6. So the code should handle that.
But what about when n is 0? Well, the problem says that the test cases are like sequence(10), so maybe n is always >=1. So the code is okay.
Now, write the code in Python.
So the function is:
def sequence(n):
if n == 1 or n == 2:
return 1
dp = [0] * (n + 1)
dp[1] = 1
dp[2] = 1
for i in range(3, n + 1):
dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]]
return dp[n]
But wait, for n=3, the code would create a list of size 4 (indices 0-3). But when i=3, the code is okay. So yes.
Testing this code with n=10 would return 6, as required.
So the code should be correct.
```python
def sequence(n):
if n == 1 or n == 2:
return 1
dp = [0] * (n + 1)
dp[1] = 1
dp[2] = 1
for i in range(3, n + 1):
dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]]
return dp[n]
```
----------------------------------------------
Result: Pred=def sequence(n):
if n == 1 or n == 2:
return 1
dp = [0] * (n + 1)
dp[1] = 1
dp[2] = 1
for i in range(3, n + 1):
dp[i] = dp[dp[i-1]] + dp[i - dp[i-1]]
return dp[n] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10], [2], [3], [100], [1000], [10000], [1000000], [49284], [76589], [92346], [109872], [92345], [76590], [1001], [10001], [109871], [True], [101], [99], [109873], [76588], [109870], [999999], [999998], [28], [9999], [109874], [49283], [102], [76591], [98], [92344], [29], [999], [109869], [109868], [97], [109867], [49285], [9998], [109866], [88], [49282], [30], [109876], [87], [31], [49280], [92343], [32], [92342], [49281], [103], [76592], [999997], [85], [95], [76587], [25], [86], [89], [104], [96], [27], [109875], [84], [1000001], [9997], [997], [49286], [1002], [105], [11], [9996], [1000002], [92341], [9], [8], [1000003], [76586], [109865], [12], [76585], [26], [996], [33], [49287], [92340], [76593], [92347], [76584], [7], [92348], [34], [92339], [106], [6], [76594], [109864], [92338], [998], [49288], [76595], [92337], [76583], [13], [83], [1004], [23], [82]]
results = [6, 1, 2, 57, 510, 5373, 510403, 26387, 40520, 49477, 58093, 49476, 40521, 510, 5374, 58093, 1, 57, 56, 58094, 40520, 58093, 510402, 510402, 16, 5372, 58094, 26386, 57, 40522, 56, 49476, 16, 509, 58093, 58093, 55, 58093, 26387, 5372, 58092, 50, 26385, 16, 58094, 49, 16, 26383, 49476, 16, 49475, 26384, 58, 40522, 510402, 48, 54, 40520, 15, 48, 51, 58, 54, 15, 58094, 48, 510403, 5371, 509, 26388, 510, 58, 7, 5370, 510403, 49475, 5, 4, 510403, 40519, 58092, 7, 40519, 15, 509, 17, 26389, 49474, 40523, 49477, 40518, 4, 49477, 18, 49473, 58, 4, 40523, 58092, 49473, 509, 26390, 40523, 49473, 40517, 8, 47, 510, 14, 47]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(sequence(*inp), exp, 0)
| OK=True
==================== Problem #39 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the surface area of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(surfacearea_sphere(10), 1256.6370614359173, rel_tol=0.001)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the surface area of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(surfacearea_sphere(10), 1256.6370614359173, rel_tol=0.001)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the surface area of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(surfacearea_sphere(10), 1256.6370614359173, rel_tol=0.001)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the surface area of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(surfacearea_sphere(10), 1256.6370614359173, rel_tol=0.001)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the surface area of a sphere.
Your answer will be tested on test cases like:
assert math.isclose(surfacearea_sphere(10), 1256.6370614359173, rel_tol=0.001)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to calculate the surface area of a sphere. Let me think about the formula. Oh right, the surface area of a sphere is 4 times π times the radius squared. So the formula is 4 * π * r².
Wait, the problem says the function should be called surfacearea_sphere, right? So I'll need to define a function with that name that takes a radius as input.
I should import math because I need π from math.pi. Then, the function will compute 4 * math.pi * (radius ** 2).
Let me check the test case given. The example uses math.isclose with a radius of 10. Let me calculate that. 4 * π * 10² is 4 * π * 100 = 400π. Let me compute that value. 400 * 3.14159... is approximately 1256.637, which matches the test case's expected value. So the formula seems right.
So the steps are: import math, define the function, compute the formula, return the result.
Wait, the function should be called surfacearea_sphere. Oh, and the parameter is probably 'radius'. So the code would be:
import math
def surfacearea_sphere(radius):
return 4 * math.pi * (radius ** 2)
That's straightforward. Let me make sure there are no typos. The test case uses math.isclose with rel_tol=0.001, which should handle floating point precision. The function returns a float, which should be correct.
I think that's all. The code is self-contained, uses the correct formula, and should pass the test case.
```python
import math
def surfacearea_sphere(radius):
return 4 * math.pi * (radius ** 2)
```
----------------------------------------------
Result: Pred=import math
def surfacearea_sphere(radius):
return 4 * math.pi * (radius ** 2) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10], [15], [20], [0.5], [1000], [1.25], [1e-10], [10000000000.0], [True], [0.8797935814628997], [0.5598154120615232], [1.099652034619149], [1.4666806892181193e-10], [0.30075595752911943], [0.14131211326255033], [1.5957056333538597], [2.8446633646372703], [1.0135226864402946], [999], [0.4652485633326504], [1.6160933440485161], [1.2395141071553297], [1001], [1.371623122065585], [6.016010239335242e-11], [0.3416547044021554], [1.4012158763654516], [0.2151302194789502], [0.9610743975015349], [1.2824168057024987], [1.2350343793427891], [1.741473062111801], [0.8328344786121058], [1.183605703278993], [0.3611170633175245], [0.7555326580733448], [97.62730112830147], [0.2732793706097826], [0.7951715096838966], [1.5501230356650713], [0.6842351453078037], [1.0317072568457641], [1.8059908182330324], [0.5075339315400214], [0.7681946087260797], [2.0852972065009174], [1.2988601893200238], [0.603044867219653], [1.4026942852103004], [0.523212033970379], [1.4597394961162697], [0.35775373645335146], [2.0479628632355526e-10], [35], [78], [0.6507313974062889], [4.365800974062854], [1.8456085367711623], [5.158707823383085], [79], [98.55913813353447], [1.4247236940537644], [1.9675371646406168], [0.9005697011096585], [1.8552473563367964], [2.012892104151268], [0.3631985979165624], [1.4033799197683636], [0.9268500963761888], [0.316208014117482], [1.2705215198025646e-10], [1002], [2.2262142172391357], [1.0831631055569682], [0.345186802549617], [0.4137398550418435], [0.5767615986315501], [2.07943497754721], [0.48838279998965645], [0.3271784231301367], [0.623788870153854], [0.5543692007776275], [9.149067620466951], [2.3096767309847452], [1.5560367329991556], [0.3202451092926611], [1.8404062689910736], [0.5726009377678422], [0.8357084454950721], [0.4686710492184495], [1.1902208721405216], [0.9609380264864483], [9857375230.431854], [1.6292570499973758], [0.776765114340302], [0.2810143961710297], [0.6386231930163654], [0.7825150182275014], [0.8887021798812079], [0.2705076454130074], [0.7063890179953193], [0.9919682715828331], [0.18724175315316485], [0.47251742847046363], [0.34091721710471784], [0.48848524318350334], [60.94952675176301], [0.34974511524935736]]
results = [1256.6370614359173, 2827.4333882308138, 5026.548245743669, 3.141592653589793, 12566370.614359172, 19.634954084936208, 1.2566370614359174e-19, 1.2566370614359173e+21, 12.566370614359172, 9.726832619158936, 3.9382163003339596, 15.195690108648744, 2.703217634758943e-19, 1.13668032210636, 0.25093927925565945, 31.997453787496053, 101.68844901583847, 12.908530718220105, 12541250.439501068, 2.720069153719145, 32.82031517135976, 19.30691176773525, 12591515.921958504, 23.641741216905338, 4.54806850439941e-20, 1.4668465178957841, 24.672886610187646, 0.5815843408186051, 11.607104116139439, 20.66656343307691, 19.167609733339184, 38.11038937458536, 8.71620139833934, 17.60451084482715, 1.6387242631072723, 7.173256278767029, 119771.208363825, 0.9384768446401073, 7.9456876114476875, 30.195498537699617, 5.8832949197696935, 13.37589449815103, 40.98651002826577, 3.2369800982648633, 7.415703784142983, 54.644415749371305, 21.19994212716799, 4.569925442654854, 24.724978307781246, 3.4400544170765532, 26.776917576370142, 1.6083413239943734, 5.2705267052500885e-19, 15393.804002589986, 76453.7988177612, 5.321246620984215, 239.517765202214, 42.80446217791458, 334.4196025588479, 78426.7190042156, 122068.51412734778, 25.507691623830816, 48.64696526587708, 10.191650611674147, 43.25272827005203, 50.91559890307731, 1.6576704306619072, 24.749155269049893, 10.795154513756298, 1.2564800847484752, 2.0284948753987144e-19, 12616686.362299066, 62.27930650166572, 14.7433977286196, 1.4973324276284565, 2.151119711703918, 4.180252717176976, 54.33761266654568, 2.997302561793732, 1.3451761972622496, 4.8897325708966495, 3.8619624976822404, 1051.8735604152196, 67.03664363817091, 30.426328801420468, 1.2887683917759631, 42.56349402840665, 4.120158979206829, 8.776461381642818, 2.7602353795407524, 17.801843875637474, 11.60381038513522, 1.2210471700828942e+21, 33.357161058245836, 7.582096177907874, 0.9923548627675614, 5.125063346891251, 7.694762623841729, 9.924813507923393, 0.919536456805351, 6.270436029828864, 12.365321902177747, 0.4405703453850948, 2.8057277502141176, 1.4605207561956501, 2.9985601222611042, 46682.116673171004, 1.5371391332804323]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(surfacearea_sphere(*inp), exp, 0.0001)
| OK=True
==================== Problem #40 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find nth centered hexagonal number.
Your answer will be tested on test cases like:
assert centered_hexagonal_number(10) == 271
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find nth centered hexagonal number.
Your answer will be tested on test cases like:
assert centered_hexagonal_number(10) == 271
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find nth centered hexagonal number.
Your answer will be tested on test cases like:
assert centered_hexagonal_number(10) == 271
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find nth centered hexagonal number.
Your answer will be tested on test cases like:
assert centered_hexagonal_number(10) == 271
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find nth centered hexagonal number.
Your answer will be tested on test cases like:
assert centered_hexagonal_number(10) == 271
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to find the nth centered hexagonal number. Let me think about what a centered hexagonal number is. From what I remember, centered polygonal numbers are a type of figurate number. For hexagonal numbers, each layer forms a hexagon around a central point.
Let me recall the formula. Oh right, the formula for the nth centered hexagonal number is 3n(n-1) + 1. Wait, or maybe it's something else. Let me check. For example, when n=1, it should be 1. Plugging into 3*1*(1-1)+1 gives 1, which is correct. For n=2, 3*2*1 +1 = 6+1=7. Let me see if that's right. The second centered hexagonal number should be 7. Let me think: the first layer around the center would have 6 numbers, so 1 + 6 =7. Yes, that makes sense. Then for n=3, 3*3*2 +1 = 18 +1=19. Let me check: the third layer would add 12 numbers (since each layer adds 6 more than the previous?), so 7 + 12 =19. Yep, that seems right.
So the formula is 3n(n-1) +1. So the function can be written as taking n, computing that formula.
Wait, but maybe there's another way. Let me see. Another way to think about it: the centered hexagonal numbers are also known as the hex pyramidal numbers. But the formula I have seems correct.
So the function is straightforward. Let me test with the sample input. The test case says that centered_hexagonal_number(10) should be 271. Let me compute 3*10*9 +1 = 270 +1 = 271. Yes, that's correct.
So the function can be written as:
def centered_hexagonal_number(n):
return 3 * n * (n - 1) + 1
Wait, but what if n is zero? Well, the problem probably assumes n is a positive integer, since the first term is n=1. So the function should handle n as a positive integer.
So the code is simple. Now, I need to write this as a self-contained Python function. The user will test it with the given assert statement. So the code should be as follows.
```python
def centered_hexagonal_number(n):
return 3 * n * (n - 1) + 1
```
----------------------------------------------
Result: Pred=def centered_hexagonal_number(n):
return 3 * n * (n - 1) + 1 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10], [2], [9], [1000000], [True], [1000001], [1000002], [999999], [79], [999998], [999997], [80], [1000003], [81], [78], [82], [999996], [77], [84], [83], [999995], [85], [999994], [76], [999993], [86], [75], [1000004], [74], [88], [93], [94], [92], [999992], [87], [999991], [91], [999989], [89], [999987], [90], [97], [52], [96], [53], [95], [999990], [1000005], [999986], [98], [999985], [51], [999984], [54], [50], [999982], [999988], [73], [999981], [49], [99], [38], [48], [37], [20], [21], [36], [72], [35], [55], [999983], [100], [70], [71], [1000006], [33], [19], [31], [32], [22], [30], [23], [101], [18], [24], [34], [56], [47], [102], [17], [29], [57], [69], [39], [103], [40], [58], [999980], [15], [104], [16], [28], [105], [27]]
results = [271, 7, 217, 2999997000001, 1, 3000003000001, 3000009000007, 2999991000007, 18487, 2999985000019, 2999979000037, 18961, 3000015000019, 19441, 18019, 19927, 2999973000061, 17557, 20917, 20419, 2999967000091, 21421, 2999961000127, 17101, 2999955000169, 21931, 16651, 3000021000037, 16207, 22969, 25669, 26227, 25117, 2999949000217, 22447, 2999943000271, 24571, 2999931000397, 23497, 2999919000547, 24031, 27937, 7957, 27361, 8269, 26791, 2999937000331, 3000027000061, 2999913000631, 28519, 2999907000721, 7651, 2999901000817, 8587, 7351, 2999889001027, 2999925000469, 15769, 2999883001141, 7057, 29107, 4219, 6769, 3997, 1141, 1261, 3781, 15337, 3571, 8911, 2999895000919, 29701, 14491, 14911, 3000033000091, 3169, 1027, 2791, 2977, 1387, 2611, 1519, 30301, 919, 1657, 3367, 9241, 6487, 30907, 817, 2437, 9577, 14077, 4447, 31519, 4681, 9919, 2999877001261, 631, 32137, 721, 2269, 32761, 2107]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(centered_hexagonal_number(*inp), exp, 0)
| OK=True
==================== Problem #41 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three dictionaries into a single dictionary.
Your answer will be tested on test cases like:
assert merge_dictionaries_three({ "R": "Red", "B": "Black", "P": "Pink" }, { "G": "Green", "W": "White" },{ "O": "Orange", "W": "White", "B": "Black" })=={'B': 'Black', 'R': 'Red', 'P': 'Pink', 'G': 'Green', 'W': 'White', 'O': 'Orange'}
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three dictionaries into a single dictionary.
Your answer will be tested on test cases like:
assert merge_dictionaries_three({ "R": "Red", "B": "Black", "P": "Pink" }, { "G": "Green", "W": "White" },{ "O": "Orange", "W": "White", "B": "Black" })=={'B': 'Black', 'R': 'Red', 'P': 'Pink', 'G': 'Green', 'W': 'White', 'O': 'Orange'}
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three dictionaries into a single dictionary.
Your answer will be tested on test cases like:
assert merge_dictionaries_three({ "R": "Red", "B": "Black", "P": "Pink" }, { "G": "Green", "W": "White" },{ "O": "Orange", "W": "White", "B": "Black" })=={'B': 'Black', 'R': 'Red', 'P': 'Pink', 'G': 'Green', 'W': 'White', 'O': 'Orange'}
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three dictionaries into a single dictionary.
Your answer will be tested on test cases like:
assert merge_dictionaries_three({ "R": "Red", "B": "Black", "P": "Pink" }, { "G": "Green", "W": "White" },{ "O": "Orange", "W": "White", "B": "Black" })=={'B': 'Black', 'R': 'Red', 'P': 'Pink', 'G': 'Green', 'W': 'White', 'O': 'Orange'}
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three dictionaries into a single dictionary.
Your answer will be tested on test cases like:
assert merge_dictionaries_three({ "R": "Red", "B": "Black", "P": "Pink" }, { "G": "Green", "W": "White" },{ "O": "Orange", "W": "White", "B": "Black" })=={'B': 'Black', 'R': 'Red', 'P': 'Pink', 'G': 'Green', 'W': 'White', 'O': 'Orange'}
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called merge_dictionaries_three that takes three dictionaries and merges them into one. The test case shows that when there are overlapping keys, the values from the later dictionaries should overwrite the earlier ones. Wait, looking at the example: the first dict has "B": "Black", the third one also has "B": "Black" and "W": "White". But in the result, "B" is Black and "W" is White. Wait, the first dict has "B" and "P", the second has "G" and "W", the third has "O", "W", "B". So when merging, the third dict's entries should overwrite the previous ones. So the order is first, second, third. So the third dict's keys take precedence over the second, which in turn takes precedence over the first.
So the approach is to create a new dictionary. Start by adding all items from the first dictionary. Then add items from the second, which might overwrite some keys from the first. Then add items from the third, which might overwrite keys from the first and second.
So how to do that in Python. The simplest way is to create a new dict, then update it with each of the three dictionaries in order. Because when you update a dictionary with another, the latter's keys overwrite the former's.
Wait, the merge order is first, then second, then third. So the correct way is to start with the first dict, then update with the second, then update with the third. Because the third's keys will overwrite the previous ones.
So the function would take dict1, dict2, dict3 as parameters. Then create a new dictionary, say merged = dict1.copy(), then merged.update(dict2), then merged.update(dict3). Then return merged.
Wait, but in Python, the update method adds the key-value pairs from the argument dictionary. If there are overlapping keys, the values from the argument dictionary will overwrite the existing ones. So yes, this approach would work.
So the function would be:
def merge_dictionaries_three(d1, d2, d3):
merged = d1.copy()
merged.update(d2)
merged.update(d3)
return merged
Wait, but what about if the dictionaries are modified? Well, since we're making a copy of d1, and then updating with d2 and d3, that should be okay.
Let me test the example given. The first dict is { "R": "Red", "B": "Black", "P": "Pink" }, second is { "G": "Green", "W": "White" }, third is { "O": "Orange", "W": "White", "B": "Black" }.
So merged starts as the first dict. Then update with second: adds G and W. Then update with third: adds O, and W (but W is already present, so it's overwritten with same value, but B is overwritten with same value. So the final merged dict would have all keys from all three, with third's values taking precedence. Which matches the test case.
So the code should be correct. Now, the function needs to be written, and the code must be self-contained. The test case uses assert, but the function itself is straightforward.
So the Python code would be:
def merge_dictionaries_three(d1, d2, d3):
merged = d1.copy()
merged.update(d2)
merged.update(d3)
return merged
But wait, what if the dictionaries are not hashable or something? Well, the problem says that the input is dictionaries, so we can assume they are valid.
So that's the code. Now, I need to present it in a markdown code block as specified.
```python
def merge_dictionaries_three(d1, d2, d3):
merged = d1.copy()
merged.update(d2)
merged.update(d3)
return merged
```
----------------------------------------------
Result: Pred=def merge_dictionaries_three(d1, d2, d3):
merged = d1.copy()
merged.update(d2)
merged.update(d3)
return merged | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[{'R': 'Red', 'P': 'Pink'}, {'G': 'Green'}, {'O': 'Orange', 'W': 'White', 'B': 'Black'}], [{'R': 'Red', 'P': 'Pink'}, {'G': 'Green', 'W': 'White'}, {'L': 'lavender', 'B': 'Blue'}], [{'R': 'Red', 'P': 'Pink'}, {'L': 'lavender', 'B': 'Blue'}, {'G': 'Green', 'W': 'White'}], [{}, {}, {}], [{}, {'A': 'Apple'}, {}], [{'A': 'Apple'}, {}, {}], [{}, {}, {'A': 'Apple'}], [{'A': {'B': {'C': {'D': 'Apple'}}}}, {}, {}], [{'R': {'B': {'P': {'M': 'Red'}}}}, {'L': {'B': 'Blue'}}, {'G': {'W': 'Green'}}], [{}, {'A': {'X': {'Y': {'Z': 'Apple'}}}}, {}], [{'R': {'B': {'P': {'M': 'Red'}}}}, {'G': {'W': 'White'}}, {'L': {'B': 'Blue'}}], [{'-20.518312632449252': -16, '-0.31776260008138024': 65}, {}, {}], [{'A': {'B': {'C': {'D': 'Apple'}}}}, {'B': 'yS', 'bXTSGefP': 'zqKImWxAN'}, {}], [{}, {'-59': -20.518312632449252, '65': -16}, {}], [{}, {'A': 'C', 'W': 'Appple'}, {}], [{}, {'-59': -20.518312632449252, '65': -16}, {'-73.06068215185819': 37, '-20.518312632449252': -49, '-50.80098800326578': -49}], [{'-24.325512454128287': 'ngwPYYUsW', '-0.31776260008138024': 'R', '64.10081127712078': ''}, {}, {}], [{'-24.325512454128287': 'ngwPYYUsW', '-0.31776260008138024': 'R', '64.10081127712078': ''}, {}, {'-34': True, '-86': -73.06068215185819, '74': {'37': False, '-95': False, '58': True, '65': True, '-85': True, '98': False, '51': True}, '-61': None, '-49': 'CjqqZMMy', '-47': -16, '65': 'D', '-59': True}], [{}, {'W': 'bXTSGefP'}, {}], [{}, {'A': {}, 'MA': {}, 'AMA': {'HzgYlcGpOG': 'White', 'ZfhiHxlH': 'Y', 'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}, 'MAA': {'HzgYlcGpOG': 'White', 'ZfhiHxlH': 'Y', 'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}}, {}], [{}, {'-59': -20.518312632449252}, {}], [{'R': {'B': {'P': {'M': 'Red', 'DM': 'R'}}, '': {'P': {'M': 'Red', 'DM': 'R'}}}}, {}, {'G': {'W': 'White', 'WW': 'WHzgYlcGpOGhite'}, 'GG': {'W': 'White', 'WW': 'WHzgYlcGpOGhite'}}], [{}, {}, {'-17': False, '98': True, '-49': False, '35': True}], [{'A': {'B': {'C': {'D': 'Appe'}}, 'Red': {'C': {'D': 'Appe'}}}}, {'B': 'yS', 'bXTSGefP': 'zqKImWxAN'}, {}], [{}, {'false': 'IANrUc', '-55': '', '-16': 'BdGTYTf', '-47': 'b', '87': 'HTv', '81': 'Green', '-59': 'yS', '65': 'AYC'}, {'A': {'B': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'Red': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'BlueB': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}}, 'P': {'B': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'Red': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'BlueB': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}}}], [{}, {}, {'-73.06068215185819': 37, '-20.518312632449252': -49, '-50.80098800326578': -49}], [{'-24.325512454128287': 'ngwPYYUsW', '-0.31776260008138024': 'R', '64.10081127712078': '', '-20.518312632449252': 'ngwPYYPUsW'}, {}, {'-34': True, '-86': -73.06068215185819, '74': {'37': False, '-95': False, '58': True, '65': True, '-85': True, '98': False, '51': True}, '-61': None, '-49': 'CjqqZMMy', '-47': -16, '65': 'D', '-59': True, '58': -16}], [{}, {}, {'-20.518312632449252': -16, '-0.31776260008138024': 65}], [{}, {'-59': -50.80098800326578}, {'-56': -95, '27': True}], [{}, {'R': {}, 'RR': {}}, {'G': {'W': 'White'}}], [{'ayuEVhTX': 'C', 'apglGpJ': 'klLihKVK', 'P': 'Awnq', 'OvdlVN': 'P', 'ngwPYYUsW': 'Y', 'W': 'Luto'}, {}, {'-17': False, '98': False, '-49': False, '35': False}], [{}, {}, {'-17': False, '-49': True, '35': False}], [{}, {'-50.80098800326578': -37.99257891277086, '-24.325512454128287': 70.78935461953051, '-0.31776260008138024': -50.80098800326578, '-50.392470117934096': -20.518312632449252}, {}], [{'35': -59}, {'R': {'B': {'P': {'M': 'Red', 'lCjSZS': 'RRed'}}}, 'Red': {'B': {'P': {'M': 'Red', 'lCjSZS': 'RRed'}}}}, {}], [{'D': 97, 'MAA': 56, 'HTv': 65}, {'42.54365262109431': 12, '-73.06068215185819': 99, '64.10081127712078': False, '-71.19218925050797': -27.722667031889188, '-70.6746308928394': 83.83304478046807}, {'IWhN': 'V'}], [{'37': False}, {}, {'NH': True, 'CjqqZMMy': True, 'ngwPYYUsW': False, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': False, 'Z': True, 'Red': False, 'Y': False, 'White': False}], [{'A': 'Apple'}, {'btabmgZJMp': 'bkk'}, {}], [{'D': 97, 'MAA': 56, 'HTv': 65}, {'42.54365262109431': 37, '-73.06068215185819': 99, '64.10081127712078': False, '-71.19218925050797': -27.722667031889188, '-70.6746308928394': 83.83304478046807}, {'IWhN': 'V'}], [{}, {'-59': -20.518312632449252}, {'BlueB': 'B', 'GyqTxRqw': 'IWhN', 'apglGpJ': 'TkzQdZezp'}], [{'R': {'B': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, '': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, 'WW': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}}, '': {'B': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, '': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, 'WW': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}}}, {}, {'G': {'W': 'White', 'WW': 'WHzgYlcGpOGhite'}, 'GG': {'W': 'White', 'WW': 'WHzgYlcGpOGhite'}}], [{}, {}, {'-50.80098800326578': -37.99257891277086, '-24.325512454128287': 70.78935461953051, '-0.31776260008138024': -50.80098800326578, '-50.392470117934096': -20.518312632449252, '-73.06068215185819': 42.54365262109431, '-24.096762660953626': 71.37539857958085, '-23.830002499577663': -19.83610846406233}], [{'R': {'B': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, '': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, 'WW': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}}, '': {'B': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, '': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}, 'WW': {'P': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}, 'White': {'M': 'Red', 'DM': 'R', 'MDM': 'RR'}}}}, {}, {'G': {'W': 'White', 'WW': 'WHzgYlcGpOGhite'}}], [{'37': False}, {'17.73931516433271': 'oxcd', '42.54365262109431': 23.795747795363283}, {'NH': True, 'CjqqZMMy': True, 'ngwPYYUsW': False, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': False, 'Z': True, 'Red': False, 'Y': False, 'White': False}], [{'-59': -20.518312632449252}, {'-3.700287742454634': False, '-38.26014318376585': None, '17.73931516433271': False, '62.77802727777075': ['apglGpJ', 'bz', 'DM', 'bN', 'BlueB', 'lwkww', 'IITWMS', 'DVeAQTRIZV'], '-67.57915780584574': 37.65070836123044, '-50.80098800326578': 'Awnq', '-71.19218925050797': -1.1152135632978002, '-70.6746308928394': -54.08169240148757}, {}], [{}, {}, {'A': {}, 'MA': {'-61.83059892834244': -21.3703814092123, '-74.60156534154282': 64.10081127712078, '17.73931516433271': -67.57915780584574}, 'AMA': {'ZfhiHxlH': 'Y', 'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}, 'MORPBKquPA': {'-67.57915780584574': -68, '70.78935461953051': 15, '89.92770337658328': 2, '-40.8169187894486': 20, '-53.026275322982166': -16, '64.10081127712078': 98, '-50.392470117934096': -4, '-89.55492254635429': 35}, 'OvdlVN': {'ZfhiHxlH': 'Y', 'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}}], [{'37': False}, {'17.73931516433271': 'oxcd', '42.54365262109431': 23.795747795363283}, {'NH': True, 'CjqqZMMy': True, 'ngwPYYUsW': False, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': False, 'Z': True, 'Red': False, 'Y': False, 'White': True}], [{}, {'W': 'bXTSGefP', 'OvdlVN': 'bXTSefP'}, {}], [{'-81.67842976641': 'Red', '-61.83059892834244': 'oxcd', '-21.3703814092123': 'V', '92.50540451758502': 'GG', '-27.722667031889188': 'NubHsqVl', '-53.026275322982166': 'Y', '89.92770337658328': 'ayuEVhTX', '-24.096762660953626': 'Awnq', '-53.805001572422206': 'VyMQgZV'}, {}, {'-17': False, '-49': False, '35': True}], [{}, {}, {'-17': False, '35': False}], [{'-59': -20.518312632449252, '65': -16}, {}, {}], [{}, {'-59': -50.80098800326578}, {}], [{}, {}, {'ayuEVhTX': 'C', 'apglGpJ': 'klLihngwPYYUsWKVK', 'P': 'Awnq', 'OvdlVN': 'P', 'ngwPYYUsW': 'Y', 'W': 'Luto'}], [{'-81.67842976641': 'Red', '-61.83059892834244': 'oxcd', '-21.3703814092123': 'V', '92.50540451758502': 'GG', '-27.722667031889188': 'NubHsqVl', '-53.026275322982166': 'Y', '89.92770337658328': 'ayuEVhTX', '-24.096762660953626': 'Awnq'}, {}, {'-17': False, '-49': False, '35': True}], [{}, {}, {'-34': True, '-86': -73.06068215185819, '74': {'37': False, '-95': False, '58': True, '65': True, '-85': True, '98': False, '51': True}, '-61': None, '-49': 'CjqqZMMy', '-47': -16, '65': 'D', '-59': True, '58': -16, '35': -73.71456655267669}], [{}, {'17.73931516433271': 'oxcd', '42.54365262109431': 23.795747795363283, '-53.805001572422206': 23.72761067835703}, {'37': False}], [{}, {'-81.67842976641': 'Red', '-61.83059892834244': 'oxcd', '-21.3703814092123': 'V', '92.50540451758502': 'GG', '-27.722667031889188': 'NubHsqVl', '-53.026275322982166': 'Y', 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'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}, 'MORPBKquPA': {'-67.57915780584574': -68, '70.78935461953051': 15, '89.92770337658328': 2, '-40.8169187894486': 20, '-53.026275322982166': -16, '64.10081127712078': 98, '-50.392470117934096': -4, '-89.55492254635429': 35}, 'OvdlVN': {'ZfhiHxlH': 'Y', 'lCjSZS': 'C', 'x': 'ngwPYYUsW', 'Green': '', 'A': 'ngwPYYPUsW'}}, {'ayuEVhTX': 'C', 'apglGpJ': 'klLihngwPYYUsWKVK', 'OvdlVN': 'P', 'ngwPYYUsW': 'Y', 'W': 'Luto', 'ngPYYUsW': 'AYC', 'ngPYYUW': 'CjqqZMMyY'}, {'35': True, '-50': False, '-81.67842976641': 'Red', '-61.83059892834244': 'oxcd', '-21.3703814092123': 'V', '92.50540451758502': 'GG', '-27.722667031889188': 'NubHsqVl', '-53.026275322982166': 'Y', '89.92770337658328': 'ayuEVhTX', '-24.096762660953626': 'Awnq'}, {'G': {'W': 'Green'}, 'R': {'B': {'P': {'M': 'Red'}}}}, {'-59': -20.518312632449252, '-58': -21.336793526122136}, {'-3.700287742454634': False, '-38.26014318376585': None, '17.73931516433271': False, '62.77802727777075': ['apglGpJ', 'bz', 'DM', 'bN', 'BlueB', 'lwkww', 'IITWMS', 'DVeAQTRIZV'], '-67.57915780584574': 37.65070836123044, '-50.80098800326578': 'Awnq', '-71.19218925050797': -1.1152135632978002, '-70.6746308928394': -54.08169240148757, '-59': -23.830002499577663, '-68': -0.31776260008138024}, {'L': {'B': 'Blue'}, 'G': {'W': 'White'}, 'R': {'B': {'P': {'M': 'klLihngwPYYUsWKVK'}, 'MAAP': {'M': 'klLihngwPYYUsWKVK'}}}, 'BlueB': {'B': {'P': {'M': 'klLihngwPYYUsWKVK'}, 'MAAP': {'M': 'klLihngwPYYUsWKVK'}}}}, {'NH': True, 'CjqqZMMy': True, 'ngwPYYUsW': False, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': True, 'Z': True, 'Red': False, 'Y': False, 'White': False, '-24.325512454128287': -63.86477732020253, '-20.518312632449252': 37.726530699576074, '-48.80497257880159': -0.31776260008138024, '86.95668320734566': -24.325512454128287, '18.83911988396234': 23.795747795363283, '37': False}, {'-17': True, '-49': False, '35': True, '36': False, '-16': False}, {'NH': True, 'CjqqZMMy': True, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': False, 'Z': True, 'Red': False, 'Y': False, 'White': True, '17.73931516433271': 'oxcd', '42.54365262109431': 23.795747795363283, '37': False}, {'-3.700287742454634': False, '-38.26014318376585': None, '17.73931516433271': False, '62.77802727777075': ['apglGpJ', 'bz', 'DM', 'bN', 'BlueB', 'lwkww', 'IITWMS', 'DVeAQTRIZV'], '-67.57915780584574': 37.65070836123044, '-50.80098800326578': 'Awnq', '-71.19218925050797': -1.1152135632978002, '-70.6746308928394': -54.08169240148757}, {'HKpALgf': 'HVI', 'DVeAQTRIZV': 'sjrFOEki', 'bKIhM': -67, 'bKI': 99}, {'-17': False, '98': True, '-49': False, '35': True, 'jqhlQTZUP': False, 'cPCszApk': False, 'YSRdUU': False, 'DVeAQTRIZV': True, 'ngPYYUW': False, 'x': False, 'zqKImWxAN': False, 'HTv': False}, {'ayuEVhTX': 'C', 'apglGpJ': 'klLihngwPYYUsWKVK', 'OvdlVN': 'P', 'ngwPYYUsW': 'Y', 'W': 'Luto', 'ngPYYUsW': 'AYC', 'ngPYYUW': 'CjqqZMMyY', 'RRed': 'klLibtabmgZJMphngwPYYUsWKVK'}, {'17.73931516433271': 'jqhlQTZUPoxcd', '42.54365262109431': 23.795747795363283, '-54.08169240148757': -91.20082277315413}, {'P': {'B': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'Red': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}, 'BlueB': {'C': {'D': 'Appe', 'Appe': 'lCjSZS'}}}, 'false': 'IANrUc', '-55': '', '-16': 'BdGTYTf', '-47': 'b', '87': 'HTv', '81': 'Green', '-59': 'yS', '65': 'AYC'}, {'MAAP': 'wSiRX', 'pasZZ': 'HVI', 'MAA': 'IANrUc', 'White': 'FP', 'klLihKVK': 'sbejlq'}, {'bKIhM': -67, 'bKI': 99}, {'R': {'B': {'P': {'M': 'ngPYYUsW'}}}}, {'35': -59, 'D': -79, 'fhesfV': 12, 'x': 39, 'MAA': 98, 'mSkrz': -2, 'hbbqUT': 43, 'bKI': 99}, {'D': -79, 'fhesfV': 12, 'x': 39, 'MAA': 98, 'mSkrz': -2, 'bKI': 99, '35': -59}, {'-24.325512454128287': -63.86477732020253, '-20.518312632449252': 37.726530699576074, '-48.80497257880159': -0.31776260008138024, '86.95668320734566': -24.325512454128287, '18.83911988396234': 23.795747795363283, 'NH': True, 'CjqqZMMy': True, 'ngwPYYUsW': False, 'ORPBKquP': False, 'XryExq': True, 'DVeAQTRIZV': True, 'Z': True, 'Red': False, 'Y': False, 'White': False}, {'A': {'B': {'C': {'D': 'Apple'}}}, '61.34541925801071': 80, '-53.19664788882594': -47, '-57.0298375483274': 51, '-40.8169187894486': -80}, {'IWhN': 'V', '42.54365262109431': 37, '-73.06068215185819': 99, '64.10081127712078': False, '-71.19218925050797': -27.722667031889188, '-70.6746308928394': 83.83304478046807, '-72.6127463653807': False}, {'-36': 54.45723754406529, '20': -80.33591878282283, '35': -26.51617320630959, '50': -61.05878653629404, '96': 92.7915796198375, '-68': -16.90079965432814, '74': -25.688963057095627, '-3.700287742454634': False, '-38.26014318376585': None, '17.73931516433271': False, '62.77802727777075': ['apglGpJ', 'bz', 'DM', 'bN', 'BlueB', 'lwkww', 'IITWMS', 'DVeAQTRIZV'], '-67.57915780584574': 37.65070836123044, '-50.80098800326578': 'Awnq', '-71.19218925050797': -1.1152135632978002, '-70.6746308928394': -54.08169240148757}, {'ayuEVhTX': 'C', 'apglGpJ': 'klLihngwPYYUsWKVK', 'OvdlVN': 'P', 'ngwPYYUsW': 'Y', 'W': 'Luto', 'ngPYYUsW': 'AYC', 'ngPYYUW': 'CjqqZMMyY', 'Appple': 'ORPBKquP'}, {'-20.518312632449252': -17, '-0.31776260008138024': 65, '-20.71434154199882': -67}, {'IWhN': 'V', '42.54365262109431': False, '-73.06068215185819': 99, '64.10081127712078': False, '-71.19218925050797': -27.722667031889188, '-70.6746308928394': 83.83304478046807, '-72.6127463653807': False, 'D': 97, 'MAA': 56, 'HTv': 65}, {'-36': 54.45723754406529, '20': -80.33591878282283, '35': -26.51617320630959, '50': -61.05878653629404, '96': 92.7915796198375, '-68': -16.90079965432814, '74': -25.688963057095627, '39': -42.95773384196735, '-3.700287742454634': False, '-38.26014318376585': None, '17.73931516433271': False, '62.77802727777075': ['apglGpJ', 'bz', 'DM', 'bN', 'BlueB', 'lwkww', 'IITWMS', 'DVeAQTRIZV'], '-67.57915780584574': 37.65070836123044, '-71.19218925050797': -1.1152135632978002, '-70.6746308928394': -54.08169240148757}, {'BlueB': 'B', 'GyqTxRqw': 'IWhN', '-59': -20.518312632449252}, {'G': {}}]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(merge_dictionaries_three(*inp), exp, 0)
| OK=True
==================== Problem #42 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the frequency of all the elements in a list, returned as a dictionary.
Your answer will be tested on test cases like:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30])==({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the frequency of all the elements in a list, returned as a dictionary.
Your answer will be tested on test cases like:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30])==({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the frequency of all the elements in a list, returned as a dictionary.
Your answer will be tested on test cases like:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30])==({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the frequency of all the elements in a list, returned as a dictionary.
Your answer will be tested on test cases like:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30])==({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the frequency of all the elements in a list, returned as a dictionary.
Your answer will be tested on test cases like:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30])==({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called freq_count that takes a list and returns a dictionary with the frequency of each element. Let's see. The example given is when the input is [10,10,10,10,20,20,20,20,40,40,50,50,30], the output is {10:4, 20:4, 40:2, 50:2, 30:1}. So each element's count is correct.
Hmm, how to approach this. Well, one way is to create a dictionary and iterate through the list. For each element, increment its count in the dictionary. Alternatively, maybe use a collections.Counter, which is a convenient way to count elements.
Wait, the problem says to return a dictionary. So using Counter might be a good approach. Because Counter is a subclass of dict, so converting it to a regular dictionary might be needed? Or maybe the test case expects a regular dict. Let me think. The example shows a regular dictionary, but the Counter would have the same structure. However, when you convert a Counter to a dict, it's the same as the Counter's contents. So maybe using Counter is acceptable here.
So the steps would be: import Counter from collections, then create a Counter object from the list, then convert it to a dictionary. But wait, the test case's expected output is a regular dict. So perhaps the function can return the Counter as a dict. Let me check.
Wait, the test case uses == to compare the result. So if the function returns a Counter instance, would that compare equal to a regular dict? Well, in Python, Counter is a subclass of dict, so when you compare a Counter to a dict, it should work as long as the keys and values match. But maybe the test case expects a regular dictionary. So perhaps converting it to a dict is better.
Alternatively, maybe the test case is written with a regular dict, so the function should return a regular dict. So using collections.Counter and then converting it to a dict.
Wait, let's think about the code. For example, if I have:
from collections import Counter
def freq_count(lst):
return dict(Counter(lst))
But then, in the example, the order of the keys in the dictionary may vary. However, in Python versions before 3.7, dictionaries do not preserve insertion order, but the test case's example shows a specific order. However, the test case uses assert with ==, which checks the contents, not the order. So the order of the keys in the dictionary doesn't matter. Because when you compare two dicts, the order of the key-value pairs is not considered. So even if the returned dict has the keys in a different order, the test case would still pass.
So the approach using Counter is valid. However, perhaps the problem expects a solution without using external libraries. But the problem says that the answer will be tested on the given test case. So if the test case uses a regular dict, then using Counter and converting to a dict would work.
Alternatively, I can implement the frequency count manually. Let's think about that. Initialize an empty dictionary. Then loop through each element in the list. For each element, if it's already in the dictionary, increment the count. Otherwise, add it with a count of 1.
So code steps:
def freq_count(lst):
freq = {}
for item in lst:
if item in freq:
freq[item] += 1
else:
freq[item] = 1
return freq
This approach doesn't require any imports. But which approach is better? Well, the problem says that the user is to write a function. Both approaches would work. However, the test case may have elements that are not hashable? Well, the problem says that the input is a list of elements. Assuming that all elements are hashable, which is required for using them as keys in a dictionary.
So the manual approach would be better in case the user wants to avoid using collections. But for code brevity, using Counter is better. However, the problem says that the code must be self-contained. So if the code uses collections, then the code must import it. But the problem says that the code should be self-contained. So the code must include any necessary imports.
So the code using the manual approach would not require any imports. So perhaps that's better for the problem. Let me think. The test case uses integers, but the function should work for any hashable elements.
So the function can be written with the manual approach. Let me test with the sample input.
Sample input: [10,10,10,10,20,20,20,20,40,40,50,50,30]
Processing each element:
10: first occurrence, set to 1. Then increments to 4.
Same for others. The resulting dictionary would be {10:4, 20:4, 40:2, 50:2, 30:1} which matches the test case.
So the manual approach would work.
So the code would be:
def freq_count(lst):
freq = {}
for item in lst:
if item in freq:
freq[item] += 1
else:
freq[item] = 1
return freq
But wait, in Python, another way is to use the get method. Like:
freq[item] = freq.get(item, 0) + 1
Which could be more concise. So the code can be written as:
def freq_count(lst):
freq = {}
for item in lst:
freq[item] = freq.get(item, 0) + 1
return freq
This is more concise and avoids the if-else.
Yes, that's a better way. So this code would handle all elements.
So that's the function. Now, the test case given is:
assert freq_count([10,10,10,10,20,20,20,20,40,40,50,50,30]) == ({10: 4, 20: 4, 40: 2, 50: 2, 30: 1})
But in Python, when you compare dictionaries, the order of the keys doesn't matter. So the test case's expected dictionary may have the keys in any order, but the code's output would have the same key-value pairs. So the test case would pass.
Therefore, this function should work.
Now, the code must be written as a self-contained Python script. So the function is written as per the code above. The code does not require any imports. So the code is correct.
Another test case: if the list is empty, returns empty dict. If the list has one element, returns {element: 1}.
Yes.
So the code is correct.
```python
def freq_count(lst):
freq = {}
for item in lst:
freq[item] = freq.get(item, 0) + 1
return freq
```
----------------------------------------------
Result: Pred=def freq_count(lst):
freq = {}
for item in lst:
freq[item] = freq.get(item, 0) + 1
return freq | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
import collections
def ref_func(list1):
freq_count= collections.Counter(list1)
return freq_count
inputs = [[[10, 10, 10, 10, 20, 20, 20, 20, 40, 40, 50, 50, 30]], [[1, 2, 3, 4, 3, 2, 4, 1, 3, 1, 4]], [[5, 6, 7, 4, 9, 10, 4, 5, 6, 7, 9, 5]], [[]], [[1, 1, 1, 1, 1]], [[1, 'a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b']], [[1, 'a', 2, 'b', 1, 'aa', 'a', 3, 2, 'b', 1, 3, 'a', 'b', 1]], [[2, 60, 1, 1, -18]], [[1, 1, 1, 1]], [[1, 1, 1, -18, 1]], [[2, 60, 60, 1, 1, -18]], [[1, 'a', 2, 'baa', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b']], [[1, 1, 1, -18, 1, 1]], [[1, 1, 2, 1, 1, 1]], [[1, 'a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b', 'a']], [[60, 1, 1, 1, -18, 1, 1]], [[1, 2, 1, 1, 1, 1]], [[2, 60, 1, 1, -18, 1]], [[60, 1, 1, 60, 1, -18, 1, 1]], [[1, 2, 1, 1, 1]], [[1, 'a', 2, 'b', 1, 3, 2, 'b', 3, 'a', 'b', 'a']], [[1, 'a', 2, 'baa', 1, 'a', 3, 2, 'b', 1, 3, 'a']], [[1, 1, 1, 1, 1, 1]], [[1, 'a', 2, 'b', 1, 3, 2, 'b', 3, 'a', 'b', 'a', 1, 3]], [[2, 60, 60, 1, -18]], [[1, 'a', 2, 'b', 2, 1, 3, 2, 'b', 3, 'a', 'b', 'a']], [[1, 'a', 2, 'b', 1, 3, 2, 'b', 3, 'aa', 'b', 'a', 1, 3]], [[2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', '']], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 2, 'b', 1, 3, 'a']], [['a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b', 'a']], [[1, 0, 2, 1, 1, 1]], [[60, 1, 1, 0, -18, 1, 1]], [[1, 'a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b', 'a', 1]], [[1, 'a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b', 2, 'a', 1, 2]], [[3, 'b', 1, 'a', 3, 2, 1, 3, 'a', '']], [[1, 1, 1, 1, 2]], [[60, 1, 1, 1, -18, 1, 1, 1]], [[60, 2, 60, 1, 1, -18, 2]], [[1, 'a', 2, 'baa', 1, 'a', 3, 2, 1, 3, 'a']], [[1, 'a', 2, 'b', 2, 1, 3, 2, 3, 'a', 'b', 'a']], [[1, 'a', 2, 'b', 2, 1, 2, 'b', 3, 'a', 'b', 'a']], [[1, 'a', 'a', 2, 'baa', 1, 'a', 60, 3, 2, 'b', 1, 3, 'a', 'a']], [[60, 1, 1, 1, -18, 1]], [[60, 1, 1, 60, 1, -18, 1, 60, 1]], [[1, 2, 1, -18, 1, 1, 1]], [[1, 2, 1, 0, 1]], [[3, 'bb', 1, 'a', 3, 2, 1, 1, 3, 'a', '']], [[1, 1, 1, -18, 1, 1, 1]], [[1, 2, 1, 1, 60, 2]], [[2, 60, 60, 1, -18, 60]], [[60, 0, 1, 60, 1, -18, 1, 1, 1]], [[1, 1, -1, 2, 1, 0, 1, 1]], [[60, 0, 1, 60, 1, -18, 1, 1, 1, 1, 1, 60]], [[1, 'a', 'a', 2, 'baa', 1, 'a', 60, 3, 2, 'b', 1, 'a', 3, 'a', 'a']], [[1, 1, 1]], [[1, 'a', 2, 'b', 60, 1, 2, 'b', 3, 'a', 'b', 'a']], [[60, 1, 1, 1, 0, -18, 1, 1]], [[1, 'a', 2, 'b', 1, 'aa', 3, 2, 'b', 1, 3, 'a', 'b', 1]], [[60, 1, 1, 60, 1, -18, -18, 61, 60, 1]], [[1, 'a', 2, 'b', 2, 1, 2, 'b', 3, 'a', '', 'a']], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 2, 1, 3, 'a', 1]], [['a', 2, 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', 'b', 'a']], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 2, 1, 3, 'aa', 'a', 1, 3]], [[60, 1, 1, 60, 1, -18, 61, 60, 1]], [[1, 'a', 2, 'b', 1, 3, 2, 'b', 'aa', 'b', 'a', 1, 3]], [[1, 'a', 2, 1, 'a', 60, 3, 2, 1, 3, 'aa', 'a', 1, 3, 1]], [[1, 2, 1, -18, 1, 0, 3]], [[1, 2, 1, 2]], [[60, 1, 1, 1, -18, 1, 1, 1, 1]], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 2, 1, 'aa', 'a', 1, 3, 3, 'aa']], [[60, 0, 1, 60, 1, -18, 1, 1, 1, 1, 1, 60, -18]], [[1, 1, 1, 1, 0, 0, -1]], [[1, 'a', 2, 'b', 1, 3, 2, 'b', 'aa', 'b', 'a', 1, 1, 3, 'a', 'a']], [[1, 60, 1, 1, 1, 1]], [[1, 'a', 2, 'b', 1, 'baa', 'a', 3, 2, 'b', 1, 3, 'a', 'b', 1]], [[1, 'a', 'a', 2, 'baa', 1, 'a', 60, 3, 2, 'b', 1, 'a', 'a', 'a']], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 2, 'aa', 'a', 1, 3, 3, 'aa']], [[1, 1, 1, 0, 1]], [[2, 1, 'a', 3, 2, 'b', 1, 3, 'a']], [[1, 1, -18, 1, -18, 1, 1, 1]], [['a', 2, 'b', 1, 'a', 3, 2, 'b', 1, 3, 'a', '', 2, 'a', 2]], [[1, 1, 60, 1, -18, 0, 1, 1]], [[1, 1]], [[1, 'baa', 2, 'b', 2, 1, 3, 2, 3, 'a', 'b', 'a']], [[2, 60, 1, -18]], [[1, 'a', 2, 'b', 60, 2, 2, 'b', 3, 'a', 'b', 'a']], [[1, 2, 'baa', 1, 'a', 3, 2, 'b', 1, 3, 'a']], [[-1, 1, 0, 1, 1]], [[1, 'a', 2, 'b', 1, 'aa', 'a', 3, 2, 'b', 1, 'a', 'b', 1]], [[1, 'a', 2, 'baa', 1, 'a', 60, 3, 60, 2, -18, 1, 3, 'aa', 'a', 3]], [[0, 2, 1, 1, 1]], [[60, 1, 1, 1, -18, 1, 1, 60, 60]], [[60, 1, 1, 60, 60, -18, 61, 1]], [[1, 'a', 2, 'baa', 1, 'a', 'bba', 60, 3, 2, 'b', 1, 3, 'a', 'a']], [[1, 'a', 2, 'b', 0, 3, 2, 'b', 'aa', 'b', 'a', 1, 3]], [[1, 2, 1, 1, 1, 1, 1]], [['a', 2, 3, 'baa', 1, 'a', 60, 3, 2, 1, 3, 'aa', 'a', 1, 3]], [[60, 1, 1, 1, -18, 1, 1, 1, 60]], [[0, 2, 1, -18, 1, 0, 3, 3, 3]], [[1, -18, 1, 1, 1, 1, 1, -18]], [[1, 60, 1, -18, 1, 1, 1]], [[60, 1, 60, 1, 1, 1, 1]], [[1, 'a', 2, 'b', 2, 1, 4, 2, 3, 'a', 'b', 'a']], [['a', 2, 3, 'baa', 1, 'a', 60, 3, 'aabaa', 1, 3, 'aa', 'a', 1, 3]], [[60, 1, 1, -18, 1, 1]], [[1, -18, -18, 1, 1, 1, 1, 1, -18]]]
for i, inp in enumerate(inputs):
assertion(freq_count(*inp), ref_func(*inp), 0)
| OK=True
==================== Problem #43 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the closest smaller number than n.
Your answer will be tested on test cases like:
assert closest_num(11) == 10
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the closest smaller number than n.
Your answer will be tested on test cases like:
assert closest_num(11) == 10
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the closest smaller number than n.
Your answer will be tested on test cases like:
assert closest_num(11) == 10
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the closest smaller number than n.
Your answer will be tested on test cases like:
assert closest_num(11) == 10
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the closest smaller number than n.
Your answer will be tested on test cases like:
assert closest_num(11) == 10
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called closest_num that takes an integer n and returns the closest smaller number than n. Wait, the example given is closest_num(11) == 10. So for 11, the closest smaller is 10. But what if n is a number that's not an integer? Wait, the problem says "number", but the example uses an integer. Hmm, maybe the function is supposed to handle integers, but maybe the input could be a float? Or maybe the function is intended for integers. Let me think.
Wait, the problem says "closest smaller number than n". So for example, if n is 11, the closest smaller is 10. But if n is 10.5, then the closest smaller would be 10. But how about if n is 10.0? Then the closest smaller would be 9. But maybe the function is intended for integers. Wait, the example given uses 11, which is an integer. But the problem says "number", so perhaps n can be a float.
But how to find the closest smaller number? For example, if n is 5.7, the closest smaller is 5. If n is 5.3, the closest smaller is 5. But if n is 5.0, then the closest smaller is 4. Wait, but maybe the problem is expecting the floor of n minus 1? Or maybe the floor of n minus 1? Wait, no. Let me think again.
Wait, the closest smaller number than n. So for any n, the closest smaller number would be the largest integer less than n. Wait, but that's the floor function. Wait, for example, if n is 11, floor is 11, but the closest smaller is 10. Wait, that's not matching. Wait, maybe I'm misunderstanding the problem. Let me check the example again. The example says closest_num(11) should return 10. So for n=11, the closest smaller is 10. So that's n-1. But if n is 10.5, then the closest smaller is 10. If n is 10.0, the closest smaller is 9? Or 10.0 is not allowed, but the problem says "smaller than n". So 10.0 is not smaller than itself. So for n=10.0, the closest smaller is 9.999...? But that's not possible. Wait, but the problem might be expecting that n is an integer. Let me check the example again. The test case is assert closest_num(11) == 10. So maybe the function is intended to take an integer n and return n-1. But that's too simple. But why would the problem be presented as such?
Alternatively, perhaps the problem is to find the closest number that is smaller than n, but in some context where numbers are in a list. But the problem statement doesn't mention a list. Wait, the problem says "find the closest smaller number than n". So maybe the function is supposed to take a number n and return the closest number that is smaller than n. But what's the context? Like, are there other numbers to compare against? Wait, the problem is not clear. But given the example, perhaps the function is intended to return the largest integer less than n. But for n=11, that would be 10. For n=10.5, it would be 10. For n=10.0, it would be 9.999... but that's not possible. But maybe the function is intended to take an integer and return n-1. But then why the name "closest smaller number"? Because for integers, the closest smaller is n-1. But if n is a float, like 5.7, then the closest smaller is 5.7 - 0.1 = 5.6? Or is it the floor(n) - 1? Or maybe the problem is expecting to return the floor(n) - 1? But that would not make sense for 11. For example, floor(11) is 11, subtract 1 gives 10, which matches the example. For 10.5, floor is 10, subtract 1 gives 9, but the closest smaller number would be 10.5-0.5=10.0. So that's conflicting.
Wait, perhaps the problem is to find the largest integer that is smaller than n. So for any n, the function returns floor(n) - 1 if n is an integer? No. Wait, for example, if n is 11, then the largest integer smaller than n is 10, which is correct. If n is 10.5, the largest integer smaller than n is 10. If n is 10.0, the largest integer smaller than n is 9. But how do you get that? The floor(n) would be 10 for 10.0, but the largest integer smaller than 10.0 is 9. So that's not correct. Wait, floor(n) gives the largest integer less than or equal to n. So to get the largest integer strictly less than n, we can do floor(n - 1e-9) or something. But maybe the problem is intended for integers. Let's look back at the test case. The test case is for 11, which is an integer. So maybe the function is supposed to return n-1 when n is an integer. But how to handle non-integer inputs?
Alternatively, perhaps the problem is to find the closest number that is smaller than n in the set of integers. So for any n, the closest smaller integer is floor(n) - 1 if n is an integer? No, for example, if n is 11, floor(n) is 11, subtract 1 gives 10, which is correct. If n is 10.5, floor(n) is 10, subtract 1 gives 9, but the closest smaller integer is 10, which is not smaller than n. Wait, that's not right. Wait, the closest smaller number than n would be the largest integer less than n. So for n=10.5, the largest integer less than n is 10. So the function should return 10. But according to the example, when n is 11, the function returns 10, which is the largest integer less than 11. So maybe the function is supposed to return floor(n) - 1 if n is an integer, but for non-integers, return floor(n). But that seems inconsistent.
Wait, perhaps the problem is that the function is supposed to return the largest integer less than n. So for any n, the function returns floor(n - 1e-9), which would handle the case where n is an integer. For example, if n is 11, then floor(11 - 1e-9) is 10. If n is 10.5, then floor(10.5 - 1e-9) is 10. If n is 10.0, then floor(10.0 - 1e-9) is 9. But that seems to be the case. However, perhaps the problem is intended for integers only, and the function is supposed to return n-1. But how to know?
The problem says "number", but the test case uses an integer. The problem statement is a bit ambiguous. However, given the example, the function closest_num(11) returns 10, which is 11-1. So perhaps the intended solution is to return n-1. But that would be too simple. But why is the problem called "closest smaller number"? Because for integers, the closest smaller is n-1. But for non-integers, like 5.7, the closest smaller would be 5.7-0.1=5.6, but that's not the case. However, perhaps the problem is intended to work with integers only.
But the problem says "number", not "integer". So perhaps the function is supposed to return the floor(n) if n is not an integer, but for integers, return n-1. But how to implement that?
Alternatively, maybe the problem is to return the floor(n) - 1. But that would not make sense for n=11, as floor(11) is 11, subtract 1 gives 10, which matches the example. For n=10.5, floor(10.5) is 10, subtract 1 gives 9. But the closest smaller number than 10.5 is 10. So that's conflicting. So that approach would not be correct.
Alternatively, maybe the problem is to return the largest integer less than n. Which for n=11 is 10, for n=10.5 is 10, for n=10.0 is 9. So how to compute that? Well, math.floor(n) if n is not integer, but for integer n, math.floor(n) is n. So to get the largest integer less than n, we can do math.floor(n - 1e-9). For example, for n=11, 11 - 1e-9 is 10.999999999..., which when floored is 10. For n=10.5, 10.5 - 1e-9 is 10.499999999..., which floors to 10. For n=10.0, 10.0 - 1e-9 is 9.999999999..., which floors to 9. So that seems to work.
So the function would be:
import math
def closest_num(n):
return math.floor(n - 1e-9)
But let's test this with the example. closest_num(11) would be math.floor(11 - 1e-9) = 10. Correct. For n=10.5, returns 10. For n=10.0, returns 9. But what if n is 9.999? Then the function returns floor(9.999 - 1e-9) = floor(9.9989999999) = 9. Which is correct. But what if n is 5.0? Then the function returns 4. But maybe that's what the problem wants.
But the problem's test case is for 11, which returns 10. So this approach would work for that.
But how to handle cases where n is not a float? Well, in Python, integers are handled as floats when you subtract 1e-9. For example, if n is 11 (integer), then n - 1e-9 is 10.999999999..., which floor to 10. So the function would return 10.
So this seems to handle all cases. However, the problem may not require handling floats. But the problem says "number", which could be a float. So this approach would be correct.
But how to implement this in Python? Let's write the code.
So, the code would be:
import math
def closest_num(n):
return math.floor(n - 1e-9)
But wait, what about when n is a very small number, like 0.0? For example, closest_num(0.0) would return math.floor(-1e-9) which is -1. But the closest smaller number than 0.0 is -1.0? That's correct. But if the problem expects that for n=0.0, the function returns -1, then this is correct.
But what about if n is 1.0? Then the function returns 0.0. Which is the closest smaller number. So that seems correct.
But the problem's test case is assert closest_num(11) == 10. Which would be correct with this function.
But what if n is a float that's not an integer, like 5.7? Then the function returns 5.0. Which is the largest integer less than 5.7. So that's correct.
Therefore, this function should work.
But wait, the problem says "number", but the example uses an integer. However, the function handles all numbers.
So the code would be:
import math
def closest_num(n):
return math.floor(n - 1e-9)
But wait, in Python, math.floor returns a float if the input is a float. For example, math.floor(10.9) is 10.0. But the test case expects 10 as an integer. However, in Python, when you do 10.0 == 10, it's True. So the assert statement would pass.
But the function returns a float, but the test case expects an integer. However, in Python, 10.0 == 10 is True, so the assert would pass. For example, assert closest_num(11) == 10 would be True because closest_num(11) returns 10.0, and 10.0 == 10 is True.
But maybe the problem expects an integer. However, the problem's test case uses == 10, which would work with a float. But perhaps the function should return an integer. So maybe we need to cast it to an integer.
Wait, for example, math.floor(10.9) is 10.0. So if the function returns that, but the test case expects 10 as an integer. But in Python, 10.0 == 10 is True, so the assert would pass. So the code as written would work.
But maybe the problem expects the function to return an integer. So, perhaps converting to int.
But then, for example, if n is 10.5, the function returns 10.0. Converting to int would be 10. So that's correct.
So perhaps the function should return int(math.floor(n - 1e-9)).
But then, for n=11, math.floor(n - 1e-9) is 10.0, converting to int gives 10. Which is correct.
So perhaps the code should be:
import math
def closest_num(n):
return int(math.floor(n - 1e-9))
But wait, what if n is a float like 10.0? Then math.floor(10.0 - 1e-9) is 9.0, converting to int is 9. Which is correct.
But for n=5.7, the function returns 5.0, converted to int is 5.
But the problem's test case is for n=11, which would return 10 as an integer. So this code would work.
But why not just return n - 1 if n is an integer? But how to check if n is an integer. For example, if n is 11.0, then n is an integer. But if n is 11.5, then it's not. But how to handle that.
But the problem's example is for 11, which is an integer. However, the function as written with math.floor(n - 1e-9) would work for both integers and floats.
So the code would be:
import math
def closest_num(n):
return int(math.floor(n - 1e-9))
But let me test this with some examples:
Test case 1: closest_num(11) → 10.0 → int is 10 → correct.
Test case 2: closest_num(10.5) → 10.0 → int is 10 → correct.
Test case 3: closest_num(10.0) → 9.0 → int is 9 → correct.
Test case 4: closest_num(5.7) → 5.0 → 5 → correct.
But what about if n is 0.0? Then it returns -1.0 → int is -1 → correct.
But what if n is a very large integer, like 1e100? The code should handle it.
So the code seems to handle all cases. Therefore, this should be the solution.
So the Python code would be:
import math
def closest_num(n):
return int(math.floor(n - 1e-9))
But wait, what if n is a string? Well, the problem says the function is tested on test cases like closest_num(11), so the input is a number. So the function is supposed to take a number, which can be int or float.
But in Python, if you pass an integer to math.floor, it will be converted to float. For example, math.floor(11) is 11.0. So the code would work.
But then, the function returns an integer. So the code should be correct.
But let me check for n=10.0:
n - 1e-9 is 10.0 - 0.000000001 = 9.999999999. math.floor of that is 9.0. int(9.0) is 9. Which is correct.
So this seems to work.
Therefore, the code should be as written.
```python
import math
def closest_num(n):
return int(math.floor(n - 1e-9))
```
----------------------------------------------
Result: Pred=import math
def closest_num(n):
return int(math.floor(n - 1e-9)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[11], [7], [12], [-5], [0], [True], [False], [-4], [-3], [-1], [-39], [-37], [-36], [-35], [-38], [47], [-20], [46], [-34], [45], [-40], [-33], [-21], [88], [89], [-2], [1], [2], [-59], [-41], [-32], [-58], [-31], [-6], [-42], [-60], [-7], [3], [-53], [4], [72], [-19], [-43], [5], [-52], [44], [52], [-51], [-54], [43], [-55], [55], [42], [-28], [-95], [-22], [-96], [-50], [73], [-97], [90], [-94], [53], [-49], [-23], [-98], [54], [6], [-29], [-30], [41], [91], [56], [63], [-56], [60], [-8], [-68], [48], [87], [86], [-27], [92], [51], [-24], [61], [-44], [-69], [84], [-70], [40], [-61], [-18], [-9], [39], [-93], [62], [64], [-62], [59], [-26], [-99], [-45], [-92], [-10]]
results = [10, 6, 11, -6, -1, 0, -1, -5, -4, -2, -40, -38, -37, -36, -39, 46, -21, 45, -35, 44, -41, -34, -22, 87, 88, -3, 0, 1, -60, -42, -33, -59, -32, -7, -43, -61, -8, 2, -54, 3, 71, -20, -44, 4, -53, 43, 51, -52, -55, 42, -56, 54, 41, -29, -96, -23, -97, -51, 72, -98, 89, -95, 52, -50, -24, -99, 53, 5, -30, -31, 40, 90, 55, 62, -57, 59, -9, -69, 47, 86, 85, -28, 91, 50, -25, 60, -45, -70, 83, -71, 39, -62, -19, -10, 38, -94, 61, 63, -63, 58, -27, -100, -46, -93, -11]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(closest_num(*inp), exp, 0)
| OK=True
==================== Problem #44 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the longest word.
Your answer will be tested on test cases like:
assert len_log(["python","PHP","bigdata"]) == 7
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the longest word.
Your answer will be tested on test cases like:
assert len_log(["python","PHP","bigdata"]) == 7
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the longest word.
Your answer will be tested on test cases like:
assert len_log(["python","PHP","bigdata"]) == 7
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the longest word.
Your answer will be tested on test cases like:
assert len_log(["python","PHP","bigdata"]) == 7
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the longest word.
Your answer will be tested on test cases like:
assert len_log(["python","PHP","bigdata"]) == 7
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called len_log that takes a list of words and returns the length of the longest word. Let's see. The example given is assert len_log(["python","PHP","bigdata"]) == 7. So in that case, "bigdata" has 7 letters. Right.
So the steps I need to take are: first, process each word in the list, find their lengths, then determine the maximum length.
Hmm, how to approach this. Well, maybe I can loop through each word in the input list. For each word, calculate its length using len(). Then keep track of the maximum value found so far.
Wait, but what if the list is empty? Oh, the problem probably assumes that the input is a non-empty list of strings. But maybe I should handle that case just in case. But the test case provided has elements, so maybe the function is expected to work with non-empty lists.
So the steps:
Initialize a variable to hold the maximum length, maybe start with 0. Then iterate over each word in the list. For each word, compute len(word). If this length is larger than the current max, update the max.
Alternatively, I can use a generator expression to compute all the lengths and then take the max. Like max(len(word) for word in words). That would be concise.
So the function can be written as:
def len_log(words):
return max(len(word) for word in words)
Wait, but what if the input is an empty list? Then this would return 0, which might not be desired. However, according to the problem statement, the test case provided has elements, and perhaps the function is expected to handle normal cases. The problem says that the answer will be tested on such test cases, so maybe the input is always a non-empty list. Therefore, this code should work.
Let me test the example. The input list is ["python","PHP","bigdata"]. The lengths are 6, 3, 7. The max is 7. Which matches the test case. So that should work.
So the code would be:
def len_log(words):
return max(len(word) for word in words)
But wait, the problem says to write a Python function. So that's all. The code is simple. Let me make sure that it's self-contained. The function is named len_log, takes a list of strings, returns the maximum length. Yes.
So the Python script would be:
def len_log(words):
return max(len(word) for word in words)
But maybe the user expects to have the code in a markdown code block. So the answer should be in the specified format.
```python
def len_log(words):
return max(len(word) for word in words)
```
----------------------------------------------
Result: Pred=def len_log(words):
return max(len(word) for word in words) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[['python', 'PHP', 'bigdata']], [['a', 'ab', 'abc']], [['small', 'big', 'tall']], [['Longest', 'word', 'length']], [['This', 'is', 'a', 'complex', 'example', 'to', 'test', 'the', 'function']], [['elephant', 'fox', 'monkey', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['fox', 'monkey', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['elephant', 'fox', 'monkey', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['fox', 'Longest', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['fox', 'monkey', 'zebra', 'lion', 'This', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'monkey']], [['elephant', 'fox', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['elephant', 'fox', 'monkey', 'zebra', 'tiger', 'giraffe', 'p', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['i', 'This', 'is', 'a', 'complex', 'example', 'to', 'test', 'the', 'ttoo', 'function']], [['elephant', 'fox', 'monkey', 'zebra', 'lion', 'tiger', 'gireaffe', 'kangaroo', 'panda', 'hippopotamus']], [['elephant', 'fox', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger', 'tiger']], [['elephant', 'fox', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangamonkeyroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['fox', 'monkey', 'zebra', 'tiger', 'giraffe', 'p', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['This', 'is', 'a', 'complex', 'example', 'to', 'test', 'the', 'function', 'a']], [['Longest', 'length']], [['fox', 'Longest', 'zebra', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['fox', 'monkey', 'zebra', 'tiger', 'giraffe', '', 'p', 'kangaroo', 'foelephantx', 'bear', 'panda', 'hippopotamus']], [['fox', 'Longest', 'zebra', 'pandaa', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['Longest', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['Longest', 'length', 'Longest']], [['fox', 'monkey', 'zebra', 'tiger', 'giraffe', '', 'p', 'kangaroo', 'foelephantx', 'bear', 'panda', 'hippopotamus', 'giraffe']], [['elephant', 'fox', 'monkey', 'function', 'zebra', 'lion', 'tiger', 'gireaffe', 'kangaroo', 'panda', 'hippopotamus']], [['length', 'LongestThis', 'Longest']], [['elephant', 'fox', 'monkey', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['This', 'is', '', 'a', 'complex', 'example', 'to', 'test', 'the', 'function', 'the']], [['This', 'is', 'a', 'complex', 'example', 'to', 'the', 'aa', 'function', 'a']], [['This', 'is', 'a', 'complex', 'example', 'to', 'test', 'the', 'function', 'a', 'a']], [['elephant', 'fox', 'teiger', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['elephant', 'fox', 'monkey', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['elephant', 'fx', 'monkey', 'zebra', 'lion', 'tiger', 'giraffe', 'giraff', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['elephant', 'fox', 'zebra', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['This', 'is', 'a', 'complex', 'example', 'is', 'test', 'the', 'function', 'a', 'a']], [['This', 'is', '', 'a', 'complex', 'example', 'to', 'test', 'the']], [['fox', 'monkey', 'zebra', 'lion', 'tigttooer', 'giraffe', 'kangaroo', 'bear', 'hippopotamus']], [['Longest', 'word', 'length', 'Longest']], [['This', 'a', 'complex', 'example', 'to', 'test', 'thte', 'function', 'a', 'a']], [['monkey', 'zebra', 'tiger', 'giraffe', '', 'p', 'kangaroo', 'foelephantx', 'bear', 'panda', 'hippopotamus']], [['Longest', 'Lonngest', 'length', 'Longest']], [['leth', 'LongestThis', 'Longest']], [['fnunction', 'This', 'is', 'a', 'complex', 'example', 'to', 'the', 'aa', 'function', 'a']], [['elephant', 'fox', 'monkey', 'LongestThis', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger', 'tiger']], [['This', 'is', 'elephant', 'complex', 'example', 'is', 'test', 'the', 'function', 'a', 'a']], [['fox', 'monkey', 'zebra', 'lion', 'This', 'giraffe', 'kangaroo', 'bear', 'panda', 'giraffbeare', 'hippopotamus', 'monkey']], [['elephant', 'fox', 'monkey', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'hippopotamus', 'tiger']], [['This', 'a', 'complex', 'giraffbeare', 'to', 'test', 'thte', 'function', 'a', 'a']], [['Longest', 'word', 'Lonpgest', 'length', 'Longest', 'Longest']], [['Longest', 'word', 'length', 'word']], [['This', 'is', 'a', 'complex', 'example', 'to', 'test', 'function', 'a', 'a']], [['This', 'is', 'a', 'complex', 'example', 'to', 'test', 'oto', 'function', 'a', 'a', 'is']], [['Longest']], [['fox', 'monkey', 'zebra', 'lion', 'giraffe', 'kangaroo', 'bear', 'hippopotamus']], [['leth', 'LongestThis', 'leelephantth', 'Longest']], [['Lot', 'word', 'length', 'word']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'kangaroo', 'bear', 'hippopotamus']], [['elephant', 'fx', 'monkey', 'zebra', 'foelephantx', 'lion', 'tiger', 'giraffe', 'giraff', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['This', 'a', 'example', 'to', 'test', 'thte', 'function', 'a', 'a']], [['This', 'a', 'complex', 'the', 'to', 'test', 'thte', 'function', 'a', 'a']], [['is', 'a', 'complex', 'example', 'to', 'test', 'the', 'function', 'a', 'a']], [['This', 'a', 'complex', 'the', 'to', 'apandaa', 'test', 'thte', 'function', 'a', 'a']], [['Longest', 'word', 'length', 'Longest', 'Longest']], [['Lonpgest', 'monkey', '', 'length', 'length']], [['lgth', 'Longest', 'length', 'Longest', 'length']], [['elephant', 'fox', 'monkey', 'zebra', 'zebralengthn', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger', 'tiger', 'elephant']], [['is', 'a', 'complex', 'word', 'to', 'test', 'the', 'function', 'a', 'a']], [['This', 'TThis', 'is', 'a', 't', 'complex', 'example', 'to', 'test', 'the', 'function', 'the']], [['LLot', 'word', 'length', 'word', 'word']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'bear', 'hippopotamus']], [['is', 'a', 'complex', '', 'example', 'to', 'test', 'the', 'function', 'a', 'a']], [['This', 'a', 'complex', 'the', 'to', 'apandaa', 'test', 'thtte', 'function', '', 'a']], [['Longest', 'lion', 'tigerLongest', 'giraffe', 'bbr', 'kangaroo', 'bbear', 'bear', 'hippopotamus']], [['Longest', 'word', 'length', 'Longest', 'Longest', 'word', 'Longest']], [['Lot', 'fox', 'monkey', 'zebra', 'zera', 'giraffe', 'hiippopotamus', 'kangaroo', 'bear', 'hippopotamus']], [['This', 'is', 'elephant', 'example', 'is', 'test', 'the', 'function', 'a', 'a']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'bearr', 'hippopotamus', 'fnunction']], [['LLot', 'word', 'length', 'word', 'panda']], [['fox', 'LongestThis', 'Longsest', 'example']], [['elephant', 'giraff', 'monkey', 'lion', 'tiger', 'mlengthonkey', 'giraffe', 'kangaroo', 'bear', 'panda', 'pada', 'hippopotamus']], [['elephant', 'fox', 'zebra', 'zebra', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger']], [['This', 'a', 'complex', 'the', 'to', 'apandaa', 'length', 'test', 'thtte', 'function', '', 'a']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'kangaroo', 'bear', 'hippopotamus', 'fnunction']], [['Longetst', 'zebra', 'lion', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['a', 'complex', 'giraffbeare', 'to', 'test', 'thte', 'function', 'a', 'a']], [['zera', 'Lot', 'word', 'length', 'word', 'zera']], [['oto', 'This', 'is', 'a', 'complex', 'example', 'to', 'the', 'aa', 'function', 'a']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'fnuncction', 'bear', 'hippopotamus']], [['oto', 'This', 'a', 'complex', 'example', 'aa', 'to', 'aa', 'function', 'a']], [['This', 'is', 'elephant', 'example', 'is', 'test', 'the', 'function', 'elephant', 'a']], [['lgth', 'Longest', 'length', 'Longest', 'length', 'Longest']], [['elephant', 'fox', 'monkey', 'LongestThis', 'zebran', 'tiger', 'giraffe', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger', 'kangamonkeyroo']], [['oto', 'This', 'is', 'a', 'complex', 'exampl', 'to', 'the', 'aa', 'function', 'hthe', 'a']], [['fox', 'p', 'zebra', 'tiger', 'giraffe', 'p', 'kangaroo', 'foelephantx', 'bear', 'panda', 'hippopotamus', 'giraffe']], [['elephant', 'fox', 'monkey', 'LongestThis', 'zebran', 'tiger', 'kangaroo', 'bear', 'panda', 'hippopotamus', 'tiger', 'kangamonkeyroo', 'monkey']], [['fox', 'Longest', 'zebra', 'lion', 'tiger', 'girafffoelephantx', 'kangaroo', 'bear', 'panda', 'hippopotamus']], [['elephant', 'fox', 'monkey', 'function', 'zebra', 'lion', 'tiger', 'gireaffe', 'to', 'kangaroo', 'panda', 'hippopotamus']], [['This', 'a', 'complex', 'the', 'to', 'apandaa', 'test', 'thte', 'function', 'a', 'a', 'apandaa']], [['fnunction', 'This', 'is', 'a', 'complex', 'example', 'to', 'the', 'aa', 'function', 'a', 'to', 'to']], [['is', 'a', 'complex', '', 'to', 'test', 'the', 'function', 'a', 'a']], [['This', 'a', 'complex', 'the', 'to', 'apandaa', 'test', 'thtte', 'function', '', 'a', 'complex']], [['This', 'is', '', 'a', 'complex', 'example', 'to', 'test', 'the', 'function', 'the', 'th', 'a']], [['elephant', 'fox', 'monkey', 'function', 'zebra', 'lion', 'tiger', 'gireaffe', 'kangaroo', 'panda', 'girafffoelephantx', 'hippopotamus']], [['Longest', 'fnunction', 'lion', 'tigerLongest', 'giraffe', 'bearr', 'fnunction']], [['Longest', 'lion', 'tigerLongest', 'giraffe', 'bearr', 'fnunction']]]
results = [7, 3, 5, 7, 8, 12, 12, 12, 12, 12, 12, 12, 8, 12, 12, 14, 12, 8, 7, 12, 12, 12, 12, 7, 12, 12, 11, 12, 8, 8, 8, 12, 12, 12, 12, 8, 7, 12, 7, 8, 12, 8, 11, 9, 12, 8, 12, 12, 11, 8, 7, 8, 8, 7, 12, 12, 6, 12, 12, 8, 8, 8, 8, 7, 8, 7, 12, 8, 8, 6, 12, 8, 8, 12, 7, 13, 8, 12, 6, 11, 12, 12, 8, 12, 12, 11, 6, 8, 12, 8, 8, 7, 14, 8, 12, 14, 17, 12, 8, 9, 8, 8, 8, 17, 12, 12]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(len_log(*inp), exp, 0)
| OK=True
==================== Problem #45 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string is present as a substring in a given list of string values.
Your answer will be tested on test cases like:
assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string is present as a substring in a given list of string values.
Your answer will be tested on test cases like:
assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string is present as a substring in a given list of string values.
Your answer will be tested on test cases like:
assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string is present as a substring in a given list of string values.
Your answer will be tested on test cases like:
assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string is present as a substring in a given list of string values.
Your answer will be tested on test cases like:
assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called find_substring that checks if a given string is present as a substring in any of the strings from a list. Let me think about how to approach this.
So the function takes two arguments: a list of strings and a target substring. The task is to check if the target exists as a substring in any of the list elements. For example, in the test case provided, the list is ["red", "black", "white", "green", "orange"], and the substring is "ack". The function should return True because "ack" is in "black".
How do I check for a substring in Python? Well, using the 'in' keyword. Like, if the substring is in any of the list items, then return True.
So the plan is: loop through each string in the list, check if the target substring is present in that string. If any of them contains it, return True. If none do, return False.
Wait, but how about case sensitivity? The problem examples don't mention it, so I assume it's case-sensitive. Like, if the substring is "Ack", then "ack" in the list wouldn't match. But the test case uses "ack" and the list has "black", which has "ack" in lowercase. So the function should be case-sensitive as per the example.
So the steps for the function:
1. Iterate over each string in the input list.
2. For each string, check if the target substring is present using 'in'.
3. If found in any string, return True immediately.
4. If after checking all strings none contain the substring, return False.
Now, coding this. The function definition would be:
def find_substring(string_list, substring):
for s in string_list:
if substring in s:
return True
return False
Wait, but what if the list is empty? Well, the problem says it's a list of string values, so maybe the function is supposed to handle that. If the list is empty, then it returns False, which is correct.
Testing the sample case: ["red", "black", "white", "green", "orange"], "ack". The loop checks each string. "black" contains "ack", so returns True. Which matches the test case.
Another test case: if the substring is not present, like "red" in the same list. Wait, the first element is "red", so if the substring is "re", then it would return True. But if the substring is "red", then "red" is in the list, so returns True. Wait, but the function checks for substring in each string. So if the substring is exactly equal to a string in the list, then it's a match. Because, for example, if the substring is "red" and the list has "red", then "red" is in "red" as a substring. So the function would return True. Which is correct.
So this function should handle all cases. Let me code that.
Now, the user wants the code in a markdown code block, self-contained. So the code would be:
def find_substring(string_list, substring):
for s in string_list:
if substring in s:
return True
return False
But wait, the problem says the function is to check if the string is present as a substring in the list. So the parameters are the list and the substring. The code seems correct.
Testing the given example: assert find_substring(["red", "black", "white", "green", "orange"],"ack")==True. The code would check each element. "black" has "ack", so returns True. The assertion passes.
Another test case: assert find_substring(["apple", "banana", "cherry"], "app") == True. Because "app" is in "apple". And if the substring is "banana", then it's in the list. So the code works.
What about if the substring is longer than some elements? Like, list is ["hi", "hello"], substring is "hello". The code checks "hi" (no), then "hello" (yes). So returns True. Correct.
So the code should work.
```python
def find_substring(string_list, substring):
for s in string_list:
if substring in s:
return True
return False
```
----------------------------------------------
Result: Pred=def find_substring(string_list, substring):
for s in string_list:
if substring in s:
return True
return False | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[['red', 'black', 'white', 'green', 'orange'], 'ack'], [['red', 'black', 'white', 'green', 'orange'], 'abc'], [['red', 'black', 'white', 'green', 'orange'], 'ange'], [[], 'abc'], [[], ''], [[], 'abac'], [[], 'aabac'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aabac'], [[], 'acbc'], [[], 'aabaac'], [[], 'acbacbcc'], [['aabac', '', 'aabac'], 'aabac'], [['acbc', 'acbacbcc'], 'acbacbcc'], [['acbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['acabcbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['mHUIYqZU', 'acabcbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aacbac'], [['acbacbccacbacbcc', 'acbacbcc'], 'acbacbccaacbacbcc'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aabaac'], [['acabcbc', 'acbabcbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaacbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbcc'], [['amHUIYqZUcbc', 'acbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['acabcbc', 'acbacbcc', 'acbacbcc'], 'acbacbccacbacbcc'], [[], 'abcbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'mHUIYqZU'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'amHUIYqZUcbc', 'abc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbcc'], [['acbacbccacbcacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbcc'], [['acbacbccacbcacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaaccacbacbccaaccbacbccbacbcc'], [[], 'aacbacacbacbccacbacbcc'], [['acbacbccacbacbcc', 'acbacbcc'], 'acbacbccaacbaccc'], [[], 'accbc'], [[], 'acbacbccacbcacbcc'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aacb'], [['', 'aabac', 'mHUIYqZU'], 'aabaac'], [['aabac', 'abc', 'aabac', 'mHUIYqZU'], 'aabaac'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'mHUIYqZU'], [['acbaccbcc'], 'acbacbccaacbacbcc'], [['acbacbccacbacbcc', 'mHUIYqZU'], 'abcaacb'], [['acabcbc', 'acbacbccaacbacbcc', 'acbacbcc'], 'acbacbccacbacbcc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac'], 'acbaccbccaacb'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'acbaccbccaacb'], [['acabcbc', 'acbacbcc', 'acbacbcc'], 'acbacbccaaccacbacbccaaccbacbccbacbcc'], [['acacbc', 'acbacbcc'], 'acbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'mHUIZU'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'aacbb'], [['acabcbc', 'acbabcbc', 'acbacbcc'], 'acbacbccacbacacbacbccaacbacbccbcc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'mHUIYamHUIYqZUcbcqZU'], [['acbacbccacbacbcc', 'amHUIYqZUcbc', 'acbc', 'acbacbcc'], 'acbacbccacbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbaacbacacbacbccacbacbcccc'], [[], 'acbcbacbcc'], [['acbacbccaaccacbacbccaaccbacbccbacbcc', 'acabcbc', 'acbabcbc', 'acbacbcc'], 'acbacbccacbacacbacbccaacbacbccbcc'], [['aabac', '', 'mHUIYqZU'], 'aacbac'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], ''], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc'], 'mHUIYmHUIYqZUqZU'], [['acbacbccacbcacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc', 'acbacbcc'], 'acbacbccaaccacbacbccaaccbacbccbacbcc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'mHaacbacacbacbccacbacbccUIYamHUIYqZUcbcqZU', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'mHUIYamHUIYqZUcbcqZU'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'acbaccbccaacb'], [['acabcbc', 'acbabcbc', 'acbacbcc', 'acbabcbc'], 'acbacbccacbacacbacbccaacbacbccbcc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'aacbac'], [['aacbabcbcabac', 'aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'mHUIYqZU'], [['aabac', '', 'mHUIYqZU'], 'aabaacbbaac'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbc', 'aacbacacbacbccacbacbcc', 'acbacbcc'], 'mHUIYqZU'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'amHUIYqZUcbc', 'acbcbacbcc', 'abc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbcc'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'acbc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbcabcaacbcacbacbcc'], 'acbacbccaaccbacbaacbacacbacbccacbacbcccc'], [['acabcbc', 'acbabcbc', 'acbacbcc'], 'acbaccbccaacb'], [['acbacbccacbacbcc', 'acbacbcc'], 'acbacbccaacba'], [['acabcbc', 'acbabcbc', 'acbacbcc', 'acabcbc'], 'acbaccbccaacb'], [['acbacbccacbacbcc', 'mHUIYqZU'], 'amHUIZUbcaacb'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'abcaacb', 'mHUIYamHUIYqZUcbcqZU'], 'mHUIYamHUIYqZUcbcqZU'], [['acbacbccaaccacbacbccaaccbacbccbacbcc', 'acabcbc', 'acbabcbc', 'acbacbcc'], 'acbacbccacbacacbacbacbccaaccacbacbccaaccbacbccbacbccacbccaacbacbccbcc'], [['aabac', '', 'mHUIZU', 'aabac', 'mHUIYqZU'], 'aabaac'], [['acbacbccacbacbcc', 'amHUIYqZUcbc', 'acbc', 'acbacbcc'], 'acbacbcccacbacbcc'], [['acbacbccacbcacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc', 'acbacbccacbcacbcc'], 'acbacbccaaccbacbcc'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aaabaac'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'aacbacacbacbccacbacbcc'], 'abc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'amHUIYqZUcbc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'acbaccbabcbacbccccaacb'], [['aabac', 'aaac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'aacbac'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU', 'aabac'], 'acbaccbabcbacbccccaacb'], [['acabcbc', 'acbacbcc', 'acbacbcc', 'acbacbcc'], 'amHUIYqZUcbc'], [['aabaacbacbccacbcacbccc', 'mHUaacbacacbacbccacbacbcIYqZU', '', 'mHUIZU', 'aabac', 'mHUIYqZU'], 'acbacbccaacbaccc'], [['aabac', '', 'mHUIaacbabcbcabacYqZU'], 'aacbac'], [['acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbacbccacbacbcc'], 'acbacbccaaccbacbaacbacacbacbccacbacbcccc'], [['acbacbccaaccacbacbccaaccbacbccbacbcc', 'acabcbc', 'acbabcbc', 'acbacbcc'], 'acbacbccacbacacbacbacbccaaccacbacbccaaccbacbcccbacbccacbccaacbacbccbcc'], [['aabac', 'acbacbcc'], 'acbacbcc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'aacbacacbacbccacbacbcc'], 'aabc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbccacc', 'acbacbcc', 'acbacbccacbacbcc'], 'mHUIYqZU'], [['aabac', '', 'aabac', 'mHUIYqZU'], 'aacbacabcbcac'], [['acbacbccacbacacbacbccaacbacbccbcc', 'acbacbccaaccbacbcc'], 'aabaacbbaac'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'aacbacacbacbccacbacbcc'], 'abbc'], [['acbacbccacbcacbcc', 'acbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'aacbacacbacbccacbacbcc'], 'a'], [['accbc', 'aabac', '', 'aabac', 'mHUIYqZU'], 'aacb'], [['acbacbccaaccacbacbccaaccbacbccbacbcc', 'acabcbc', 'acbabcbc'], 'acbacbccacbacacbacbacbccaaccacbacbccaaccbacbcccbacbccacbccaacbacbccbcc'], [['aabac', '', 'mHUIZU', 'aabac', 'mHUIYqZU'], 'acbacbcccacbacbcc'], [['acbacbccacbcacbcc', 'aacbbacbacbccacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc', 'acbaccbcc', 'acbacbccacbacbcc'], 'amHUIYqZUcbc'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'abcaacb', 'mHUIYamHUIYqZUcbcqZU'], 'mHUIYamHUIYqZmUcbcqZU'], [[], 'aacbbacbacbccacbacbcc'], [['acbacbccacbcacbcc', 'acbacbcacbaccbccaacbcacbacbcc', 'aacbacacbacbccacbacbcc', 'acbacbcc'], 'mHUIYmHUIYqZUqZU'], [['aabac', '', 'mHUIYqZU'], 'aabaacbaac'], [['acabcbc', 'acbabccbc', 'acbacbcc'], 'acbacbccacbacacbacbccaacbacbccbcc'], [[], 'acaabaacbbaacbc'], [['acbacbccacbacbcc', 'mHUIYqZU', 'mHUIYqZU'], 'amHUIZUbcaacb'], [['aabac', 'aabac', 'mHUIYqZU', 'mHUIYamHUIYqZUcbcqZU', 'aabac', 'aabac', 'mHUIYamHUIYqZUcbcqZU'], 'acbacbcabcaacbcacbacbcc']]
results = [True, False, True, False, False, False, False, True, False, False, False, True, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, True, True, False, False, False, False, True, False, False, True, False, False, False, True, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_substring(*inp), exp, 0)
| OK=True
=========================================
Question 0
error_msg: None
=========================================
Question 1
error_msg: None
=========================================
Question 2
error_msg: None
=========================================
Question 3
error_msg: None
=========================================
Question 4
error_msg: None
=========================================
Question 5
error_msg: None
=========================================
Question 6
error_msg: None
=========================================
Question 7
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 29, in
File "", line 23, in assertion
AssertionError: out: b101, exp: -101
=========================================
Question 8
error_msg: None
=========================================
Question 9
error_msg: None
=========================================
Question 10
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 29, in
File "", line 23, in assertion
AssertionError: out: PythonProgram, exp: ___PythonProgram
=========================================
Question 11
error_msg: None
=========================================
Question 12
error_msg: None
=========================================
Question 13
error_msg: None
=========================================
Question 14
error_msg: None
==================== Problem #46 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether the given number is undulating or not.
Your answer will be tested on test cases like:
assert is_undulating(1212121) == True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether the given number is undulating or not.
Your answer will be tested on test cases like:
assert is_undulating(1212121) == True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether the given number is undulating or not.
Your answer will be tested on test cases like:
assert is_undulating(1212121) == True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether the given number is undulating or not.
Your answer will be tested on test cases like:
assert is_undulating(1212121) == True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check whether the given number is undulating or not.
Your answer will be tested on test cases like:
assert is_undulating(1212121) == True
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called is_undulating that checks if a given number is undulating. Let me think about what an undulating number is. From what I remember, an undulating number is a number that has the form ababab... where a and b are digits. For example, 121212 is undulating because it alternates between 1 and 2. But wait, the first test case given is 1212121, which is True. So the number must have at least two digits, right? Wait, but maybe the definition varies. Let me check.
Wait, the problem says that the function should return True for 1212121. Let's see: 1,2,1,2,1,2,1. So the pattern alternates between 1 and 2. So the number must have a pattern where every pair of adjacent digits alternates between two different digits. But how to check that?
So the steps for the function:
First, convert the number to a string to check the digits. Then, check if the digits alternate between two different digits. But there's a catch: the number must have at least two digits. Wait, for example, 12 is undulating. But a single-digit number can't be undulating. Wait, but the problem's test case is 1212121, which is 7 digits. So the function must return True for numbers with two or more digits that follow the ababab... pattern.
So, the steps for checking:
1. Convert the number to a string. Let's call it s.
2. Check if the length of s is less than 2. If so, return False.
3. Then, check if all even-indexed digits (0-based) are the same, and all odd-indexed digits are the same. Wait, no. Because for example, 1212: the first digit is 1, second is 2, third is 1, fourth is 2. So even indices (0,2) are 1, and odd indices (1,3) are 2. So the pattern is that every even position is the same, and every odd position is the same. So for the string s, the first digit is s[0], the second s[1], then s[2] must equal s[0], s[3] equals s[1], and so on.
So the function can check that all even positions (0, 2, 4...) have the same digit, and all odd positions (1, 3, 5...) have the same digit. But also, the first two digits must be different. Because if the first two digits are the same, then the pattern would be like 1111, which is not undulating. Wait, for example, 1111 would have all even positions as 1 and all odd positions as 1. But then, the first two digits are same. So in this case, the function would return False, because the pattern is not ababab... but aaaa... which is not considered undulating.
So the steps are:
- Check if the length is less than 2: return False.
- Check if all even positions (starting from 0) are the same as the first digit.
- Check if all odd positions are the same as the second digit.
- Also, check that the first and second digits are different.
Wait, but what if the number is of length 2? Like 12. Then, the first digit is 1, second is 2. So even positions (0) is 1, odd positions (1) is 2. So that's valid. So for length 2, the check is that the two digits are different. So the function would return True for 12, but False for 11.
So putting this together:
First, convert the number to a string. Let's say s = str(n). Then:
if len(s) < 2: return False
if len(s) == 2: return s[0] != s[1]
Else:
Check that all even-indexed digits are equal to s[0], and all odd-indexed digits are equal to s[1]. Also, s[0] must not equal s[1].
So for example, 1212121: s[0] is '1', s[1] is '2'. Then, check for each even index i (0,2,4,6) that s[i] is '1', and for each odd index i (1,3,5) that s[i] is '2'. Also, check that '1' != '2'.
So how to implement this in Python.
The code steps:
def is_undulating(n):
s = str(n)
if len(s) < 2:
return False
if len(s) == 2:
return s[0] != s[1]
# For longer strings:
first = s[0]
second = s[1]
if first == second:
return False
for i in range(2, len(s)):
if i % 2 == 0:
if s[i] != first:
return False
else:
if s[i] != second:
return False
return True
Wait, but let's test this with the example 1212121. The string is '1212121'.
Indices 0:1, 1:2, 2:1 (even index, should be first), 3:2 (odd, should be second), etc. So the loop starts at i=2. For i=2, even, check if s[2] is first (1). Yes. Then i=3, odd, check if s[3] is second (2). Yes. Then i=4, even, check s[4] is 1. Yes. And so on. So returns True.
Another example: 1212. The code would check for i=2 (even, s[2] is 1, which is first. Then i=3 (odd, s[3] is 2. So returns True.
Another test case: 1221. The first two digits are 1 and 2. Then i=2 is even, s[2] is 2. Which is not equal to first (1). So returns False.
What about 11? len is 2, returns False. Correct.
What about 121? len is 3. first is 1, second is 2. Then i=2 (even index, 2). Check if s[2] is 1. Yes. So returns True. So 121 is considered undulating. But according to the problem's example, 1212121 is True. So that seems correct.
Wait, but what about a number like 12121? Let's see. The code checks:
i=2: even, 1. Correct. i=3: odd, 2. Correct. i=4: even, 1. Correct. So returns True.
Another case: 121212. The code would check all positions. So yes.
But what about a number like 12122? Let's see. The string is '12122'. The first two digits are 1 and 2. Then i=2 is 1 (correct), i=3 is 2 (correct), i=4 is 2. Since i=4 is even, it should be equal to first (1). But 2 != 1, so returns False. Correct.
So this logic seems to work.
But what about numbers where the first and second digits are same? For example, 1122. The code would check len(s) is 4. first is '1', second is '1'. So the code returns False. Which is correct.
Another case: 1212. The code returns True.
So the code seems to handle all these cases.
Now, what about numbers with leading zeros? Well, the input is a number. So for example, if the input is 0, then str(0) is '0', which has len 1. So returns False. But if the input is 00, but in Python, numbers can't have leading zeros. So the function will not receive such inputs. So the code doesn't need to handle that.
Now, what about numbers like 1? The code returns False, which is correct.
So the code seems correct.
Now, let's test the given test case: assert is_undulating(1212121) == True. The code would return True. Correct.
Another test case: is_undulating(1212) returns True. is_undulating(1221) returns False. is_undulating(12) returns True. is_undulating(11) returns False. is_undulating(121) returns True. is_undulating(121212) returns True. is_undulating(12121212) returns True. All correct.
So the code should be correct. Now, write the Python function accordingly.
```python
def is_undulating(n):
s = str(n)
if len(s) < 2:
return False
if len(s) == 2:
return s[0] != s[1]
first = s[0]
second = s[1]
if first == second:
return False
for i in range(2, len(s)):
if i % 2 == 0:
if s[i] != first:
return False
else:
if s[i] != second:
return False
return True
```
----------------------------------------------
Result: Pred=def is_undulating(n):
s = str(n)
if len(s) < 2:
return False
if len(s) == 2:
return s[0] != s[1]
first = s[0]
second = s[1]
if first == second:
return False
for i in range(2, len(s)):
if i % 2 == 0:
if s[i] != first:
return False
else:
if s[i] != second:
return False
return True | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[1212121], [1991], [121], [2121212121212121], [2121212121212122], [2121212121212119], [2121212121212123], [2121212121212124], [2121212121212125], [2121212121212120], [2121212121212118], [2121212121212126], [2121212121212117], [2121212121212127], [82], [40], [83], [39], [81], [2121212121212116], [2121212121212128], [2121212121212115], [41], [80], [19], [20], [42], [84], [18], [2121212121212129], [43], [21], [62], [17], [85], [2121212121212130], [79], [12], [2121212121212131], [86], [44], [52], [16], [11], [53], [63], [10], [78], [51], [61], [87], [50], [77], [54], [92], [55], [49], [22], [96], [38], [97], [56], [23], [91], [2121212121212114], [15], [93], [24], [48], [89], [60], [64], [65], [37], [76], [59], [35], [88], [2121212121212132], [58], [14], [94], [9], [47], [95], [66], [57], [36], [8], [13], [25], [45], [90], [2121212121212113], [67], [46], [7], [68], [75], [34], [2121212121212133], [2121212121212134], [26], [74]]
results = [True, False, True, True, False, False, False, False, False, False, False, False, False, False, True, True, True, True, True, False, False, False, True, True, True, True, True, True, True, False, True, True, True, True, True, False, True, True, False, True, False, True, True, False, True, True, True, True, True, True, True, True, False, True, True, False, True, False, True, True, True, True, True, True, False, True, True, True, True, True, True, True, True, True, True, True, True, False, False, True, True, True, False, True, True, False, True, True, False, True, True, True, True, False, True, True, False, True, True, True, False, False, True, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(is_undulating(*inp), exp, 0)
| OK=True
==================== Problem #47 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate the value of 'a' to the power 'b'.
Your answer will be tested on test cases like:
assert power(3,4) == 81
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate the value of 'a' to the power 'b'.
Your answer will be tested on test cases like:
assert power(3,4) == 81
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate the value of 'a' to the power 'b'.
Your answer will be tested on test cases like:
assert power(3,4) == 81
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate the value of 'a' to the power 'b'.
Your answer will be tested on test cases like:
assert power(3,4) == 81
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate the value of 'a' to the power 'b'.
Your answer will be tested on test cases like:
assert power(3,4) == 81
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called power that takes two arguments, a and b, and returns a raised to the power of b. Let me think about how to do this.
Wait, Python has an exponent operator, right? Like a ** b. So maybe the function is straightforward. But maybe I should handle some edge cases. For example, what if b is zero? Any number to the power of zero is 1. But the problem says to calculate a^b, so the built-in operator should handle that.
Wait, but the test case given is power(3,4) which is 81. Let me check 3**4 in Python. Yes, that's 81. So the function can be as simple as returning a ** b.
But wait, what about negative exponents? Like if b is negative, then a^b is 1/(a^abs(b)). But the problem says to calculate a to the power b, so the built-in operator should handle that as well. So the function can just return a ** b.
So the code would be:
def power(a, b):
return a ** b
But wait, maybe the problem expects using a loop to multiply a by itself b times. But the question says to calculate the value, and in Python, the exponent operator is the most straightforward way. The test case given uses positive integers, but the function should work for other cases too.
So the correct approach is to use the ** operator. Therefore, the code is simple. Let me test the sample case. power(3,4) returns 3**4 = 81, which matches the assertion. So the function should work.
I think that's all. So the Python function is just using the exponent operator.
```python
def power(a, b):
return a ** b
```
----------------------------------------------
Result: Pred=def power(a, b):
return a ** b | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[3, 4], [2, 3], [5, 5], [4, -2], [-2, 3], [0, 5], [-3, -4], [0, 10], [10, -1], [0, 0], [2, -3], [1, 100], [-1, 100], [5, 10], [5, 0], [-3, 2], [0, 9], [-1, 10], [0, 4], [5, -2], [4, 9], [-2, -2], [1, 99], [100, 5], [99, 2], [100, 100], [-4, -2], [100, 3], [0, 3], [5, 11], [4, 1], [-2, 0], [4, 4], [100, 6], [100, 4], [11, 5], [-4, -4], [5, 9], [11, 99], [100, -1], [6, 6], [-1, -1], [3, 0], [2, 2], [9, -1], [-4, 2], [-2, 5], [6, 0], [5, 4], [-1, 0], [99, 4], [-1, 9], [5, 2], [99, 1], [11, -1], [-4, 7], [7, 0], [98, 3], [100, -2], [99, -1], [3, 7], [-3, -3], [1, 6], [3, 1], [3, 8], [99, 99], [100, 9], [-1, 98], [7, -1], [9, 99], [5, 8], [11, 3], [3, -3], [2, 5], [99, -4], [5, 101], [9, 9], [8, 3], [99, -3], [1, 10], [7, 1], [101, 100], [8, 0], [100, 101], [4, 8], [2, 4], [3, 3], [8, 4], [101, -2], [98, 102], [8, 8], [2, -4], [-2, 101], [-1, -2], [100, 7], [-3, -2], [1, 2], [9, 3], [7, 7], [4, 3], [2, -2], [11, 10], [1, 0], [5, -3], [99, 3], [98, 2], [8, 7], [3, 6], [1, -1], [-1, 8], [101, 6]]
results = [81, 8, 3125, 0.0625, -8, 0, 0.012345679012345678, 0, 0.1, 1, 0.125, 1, 1, 9765625, 1, 9, 0, 1, 0, 0.04, 262144, 0.25, 1, 10000000000, 9801, 100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000, 0.0625, 1000000, 0, 48828125, 4, 1, 256, 1000000000000, 100000000, 161051, 0.00390625, 1953125, 12527829399838427440107579247354215251149392000034969484678615956504532008683916069945559954314411495091, 0.01, 46656, -1.0, 1, 4, 0.1111111111111111, 16, -32, 1, 625, 1, 96059601, -1, 25, 99, 0.09090909090909091, -16384, 1, 941192, 0.0001, 0.010101010101010102, 2187, -0.037037037037037035, 1, 3, 6561, 369729637649726772657187905628805440595668764281741102430259972423552570455277523421410650010128232727940978889548326540119429996769494359451621570193644014418071060667659301384999779999159200499899, 1000000000000000000, 1, 0.14285714285714285, 29512665430652752148753480226197736314359272517043832886063884637676943433478020332709411004889, 390625, 1331, 0.037037037037037035, 32, 1.0410203556852167e-08, 39443045261050590270586428264139311483660321755451150238513946533203125, 387420489, 512, 1.0306101521283646e-06, 1, 7, 270481382942152609326719471080753083367793838278100277689020104911710151430673927943945601434674459097335651375483564268312519281766832427980496322329650055217977882315938008175933291885667484249510001, 1, 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000, 65536, 16, 27, 4096, 9.802960494069208e-05, 127367821481320961306779453124811493852927587601071435268660949497933336539304230215165634203675222190265666055792155413670466901678107154499490273199816067233222775795686789175668564014387134300740911104, 16777216, 0.0625, -2535301200456458802993406410752, 1.0, 100000000000000, 0.1111111111111111, 1, 729, 823543, 64, 0.25, 25937424601, 1, 0.008, 970299, 9604, 2097152, 729, 1.0, 1, 1061520150601]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(power(*inp), exp, 0)
| OK=True
==================== Problem #48 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Given a list of tuples, write a function that returns the first value of the tuple with the smallest second value.
Your answer will be tested on test cases like:
assert index_minimum([('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]) == 'Varsha'
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Given a list of tuples, write a function that returns the first value of the tuple with the smallest second value.
Your answer will be tested on test cases like:
assert index_minimum([('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]) == 'Varsha'
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Given a list of tuples, write a function that returns the first value of the tuple with the smallest second value.
Your answer will be tested on test cases like:
assert index_minimum([('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]) == 'Varsha'
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Given a list of tuples, write a function that returns the first value of the tuple with the smallest second value.
Your answer will be tested on test cases like:
assert index_minimum([('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]) == 'Varsha'
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Given a list of tuples, write a function that returns the first value of the tuple with the smallest second value.
Your answer will be tested on test cases like:
assert index_minimum([('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]) == 'Varsha'
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, let's see. I need to write a Python function called index_minimum that takes a list of tuples and returns the first value of the tuple with the smallest second value. Hmm. So, for example, in the test case given, the list is [('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]. The second values are 143, 200, 100. The smallest is 100, which is in the third tuple. So the first value of that tuple is 'Varsha', which is the correct output.
So the steps I need to take are: first, find the tuple with the smallest second element. Then, return its first element.
How do I find the tuple with the smallest second value? Well, I can loop through each tuple in the list, compare their second elements, keep track of the minimum. Alternatively, maybe use a built-in function like min() with a key.
Right, the min function can take a key function. So if I use min on the list of tuples, and the key is the second element of each tuple. Then, once I find that tuple, I can return its first element.
Wait, the key for min would be lambda x: x[1], since each tuple's second value is x[1]. So the tuple with the smallest x[1] will be selected. Then, the first element is x[0].
So the function can be written as: take the list, find the tuple with min second value, then return its first element.
So putting that into code. The function index_minimum would take the list as input. Then, use min with key=lambda x: x[1], then return that tuple's first element.
Wait, but what if there are multiple tuples with the same smallest second value? Like if two tuples have the same second value. Then, the min function would return the first occurrence, right? But the problem says to return the first value of the tuple with the smallest second. So if there's a tie, which one to pick? The problem says "the first value of the tuple with the smallest second value". So if there are multiple tuples with the same minimum second value, which one's first value do we return? The first occurrence in the list?
For example, if the list is [('a', 5), ('b', 5)], then the first tuple's first value is 'a', so the function should return 'a'.
But the problem's test case example seems to indicate that the first occurrence is considered. But the problem statement says "the first value of the tuple with the smallest second value". So if there are multiple tuples with the same minimum second value, the first one in the list is the one to pick.
But when using the min function, if there are multiple elements with the same key, it returns the first one encountered. So that's correct.
So the code can be written as:
def index_minimum(lst):
return min(lst, key=lambda x: x[1])[0]
Wait, but the function is called index_minimum, but the problem says that the function returns the first value of the tuple with the smallest second value. So that code should work.
Let me test with the example. The input list is [('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]. The min with key x[1] would be ('Varsha', 100), so [0] is 'Varsha', which matches the test case.
Another test case: if the list is [('a', 5), ('b', 3), ('c', 3)], then the min would be ('b', 3) since it's the first occurrence of the minimum. So the function returns 'b'.
Yes, that's correct.
So the code is straightforward. The function uses the min function with the key, then returns the first element of that tuple.
So the Python code would be:
def index_minimum(lst):
return min(lst, key=lambda x: x[1])[0]
But wait, what if the list is empty? But the problem probably assumes that the input list is non-empty, as per the test cases given. So no need to handle empty lists.
So that's the code. Let me write that in the markdown code block.
```python
def index_minimum(lst):
return min(lst, key=lambda x: x[1])[0]
```
----------------------------------------------
Result: Pred=def index_minimum(lst):
return min(lst, key=lambda x: x[1])[0] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[('Rash', 143), ('Manjeet', 200), ('Varsha', 100)]], [[('Yash', 185), ('Dawood', 125), ('Sanya', 175)]], [[('Sai', 345), ('Salman', 145), ('Ayesha', 96)]], [[('John', 100)]], [[('Alice', 100), ('Bob', 100), ('Charlie', 100)]], [[('Alice', 100), ('Bob', 200), ('Charlie', 300), ('John', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False)]], [[('Adam', 150), ('Benjamin', 100), ('Charlie', 100), ('David', 125)]], [[('John', 100), ('Jane', 150), ('Jim', 200), ('Jill', 175)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False)]], [[('John', 100, 100), ('John', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True, 'Chicago'), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False)]], [[('John', 100), ('Jane', 150), ('Jim', 200)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', True, False, 100), ('David', 125, 'Miami', False)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True, 'Charlie'), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False)]], [[('Adam', 150), ('Benjamin', 100), ('Charlie', 100), ('Adam', 150, 150)]], [[('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True, 'Charlie'), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Adam', 150), ('Benjamin', 100), ('Charlie', 100), ('Benjamin', 100, 'Benjamin'), ('David', 125)]], [[('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False)]], [[('Adam', 150, 'NYC', 'NYBenjamin', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', True, False, 100), ('David', 125, 'Miami', False)]], [[('John', 100), ('Jane', 150), ('Jim', 200), ('Jill', 175), ('John', 100), ('Jim', 200)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Charlie', 200, 'Chicago', True)]], [[('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bob', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True, 'Chicago'), ('David', 125, 'Miami', False)]], [[('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Benjamin', True, 100), ('Charlie', 300), ('Benjamin', 100), ('John', 100)]], [[('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100), ('John', 100)]], [[('Alice', 100), ('Charlie', 101), ('Alice', 100), ('John', 100), ('Charlie', 100)]], [[('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100), ('John', 100), ('John', 100)]], [[('Alice', 100), ('Alice', 101), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Benjamin', 100)]], [[('Alice', 100), ('Charlie', 100), ('Alice', 100)]], [[('John', 100), ('Jim', 200), ('Jill', 175)]], [[('John', 100), ('John', 100)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bobb', 100), ('Alice', 100)]], [[('Alice', 101, 100), ('John', 300), ('Alice', True, 100), ('Bob', 200), ('John', 100), ('John', 100), ('Bob', 200)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False, False)]], [[('Adam', 150, 'NYC', 'NYBenjamin', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', True, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False, False)]], [[('Bob', 100), ('Charlie', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Adam', 150, 'NYC', True)]], [[('Adam', 150, 'NYC', 'NYBenjamin', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', True, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Bob', 100), ('Charlie', 100), ('Bob', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Adam', False, 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True), ('Charlie', 200, 'Chicago', True, 'Charlie'), ('David', 125, 'Miami', False)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Alice', 175), ('Benjamin', 100)]], [[('Alice', 100), ('Bob', 200), ('Charlie', 300), ('John', 100), ('Bob', 200)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Benjamin', 100)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('John', 100)]], [[('Charlie', 100), ('Adam', 150, 150)]], [[('Adam', 150), ('Benjamin', 100), ('David', 125)]], [[('AlNYCice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Alice', 100)]], [[('Charlie', 100), ('Bob', 100)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Benjamin', True, 100), ('Charlie', 300), ('Benjamin', 100), ('Bob', 200, 'Bob')]], [[('Alice', 100), ('Alice', 175), ('Benjamin', 100)]], [[('Adam', 150, 'NYC', 'NYBenjamin', True), ('Benjamin', 100, 'LA', False, False), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', True, False, 100), ('Benjamin', 100, 'LA', False, False)]], [[('Alice', 100), ('Bob', 100)]], [[('Alice', 100), ('Bob', 200, 'oBob', 'Bob'), ('Charlie', 300), ('Alice', 175), ('Benjamin', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True, 'Chicago'), ('Charlie', 200, 'Chicago', True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA', False)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Benjamin', True, 100, True), ('Charlie', 300), ('Benjamin', 100), ('Bob', 200, 'Bob')]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True), ('Charlie', 200, 'Chicago', True, 'Charlie'), ('David', 125, 'Miami', False)]], [[('Alice', 100), ('Charlie', 300)]], [[('John', 100), ('Jane', 150), ('Jim', 200), (300, 175)]], [[('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Benjamin', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True), ('Charlie', 200, 'Chicago', True, 'Charlie'), ('David', 125, 'Miami', True)]], [[('AlNYCice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Alice', 100), ('Bob', 200, 'Bob')]], [[('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100), ('John', 100), ('John', 100), ('John', 100), ('Alice', 100)]], [[('Alice', 100), ('Alice', 101), ('Bob', 200, 'Bob'), ('Charlie', 300), ('John', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True, 'Chicago', 'Charlie'), ('David', 125, 'Miami', False)]], [[('Alice', 100), ('BoAlNYCiceb', 100), ('Bob', 100), ('Bob', 100)]], [[('Alice', 101, 100, 'Alice'), ('John', 300), ('Alice', True, 100), ('Bob', 200), ('John', 100), ('John', 100), ('Bob', 200)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100, 100), ('Charlie', 100), ('Bobb', 100), ('Alice', 100), ('Bob', 100, 100)]], [[('Adam', 150, 'NYC', True, 'Adam'), ('AdaJanem', 150, 'NYC', True, 150), ('AdaJanem', 150, 'NYC', True), ('Adam', 150, 'NYC', True)]], [[('Alice', 100), ('Bob', 200), ('Charlie', 300), ('John', 100), ('Bob', 200), ('Charlie', 300), ('Charlie', 300)]], [[('Charlie', 100), ('Adam', 150, 149)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100, 100), ('Charlie', 100), ('Bobb', 100), ('Alice', 100), ('Bob', 100, 100), ('Charlie', 101), ('Charlie', 100), ('Bob', 100, 100)]], [[('Charlie', 300), ('John', 100), ('Bob', 200)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False), ('David', 125, 'Miami', False)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, False), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Bob', 300, 300), ('Charlie', 300, 300), ('Benjamin', 100)]], [[('Adam', 150, 'NYC', True), ('Charlie', 200, 'Chicago', True), ('Adam', 150, 'NYC', True)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, False), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Alice', 100), ('John', 100), ('John', 100), ('John', 100)]], [[('John', True), ('Alice', 100), ('Bob', 200), ('John', 100), ('John', 100), ('John', 100)]], [[('Adam', 150), ('Benjamin', 100), ('Charlie', 100), ('David', 124, 125)]], [[('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False)]], [[('Jane', 150), ('Jim', 200)]], [[('AlNYCice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Alice', 100), ('Bob', 200, 'Bob'), ('AlNYCice', 100)]], [[('Charlie', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, False), ('Adam', 150, 'NYC', True, True), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bobb', 100), ('Alice', 100), ('Bobb', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('BenLAjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('John', 100), ('Jane', 150), ('Jill', 175)]], [[('Adam', 150, 'NYC', True, 'Adam'), ('Benjamin', 100, 'LA', False), ('Charlie', 200, 'Chicago', True), ('Charlie', 200, 'Chicago', True, 'Charlie')]], [[('John', 100, 100), ('John', 100), ('John', 100, 100)]], [[('John', 100), ('Jill', 175)]], [[('Jane', 150), ('Jill', 175), ('Jane', 150)]], [[('AlNYCice', 100), ('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bob', 100)]], [[('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False), ('LA', 150, 'NYC', True), ('Charlie', 200, 'Chicago', True, 'Chicago'), ('David', 125, 'Miami', False)]], [[('Bob', 100), ('Charlie', 100), ('Bob', 100), ('Bob', 100), ('Bob', 100), ('Bob', 100)]], [[('Charlie', 101), ('Alice', 100), ('Bob', 100), ('Charlie', 100), ('Bobb', 100), ('Alice', 100), ('Bobb', 100), ('Bobb', 100)]], [[('Alice', 100), ('Charlie', 300), ('Benjamin', 100)]], [[('Alice', 100), ('Bob', 200, 'Bob'), ('Charlie', 300), ('Bob', 300, 300), ('Benjamin', 100)]], [[('Bob', 200, 'Bob'), ('Charlie', 300), ('Charlie', 300, 300), ('Benjamin', 100), ('Benjamin', 100, 'Benjamin')]], [[('Benjamin', 100, 'LA', False, False, 100), ('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, False), ('BenLAjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('NYBenjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]], [[('Benjamin', 100, 'LA', False, False, 100), ('Adam', 150, 'NYC', True), ('Benjamin', 100, 'LA', False, 100), ('Benjamin', 100, 'LA', False, False), ('BenLAjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False, 100), ('David', 125, 'Miami', False), ('NYBenjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA'), ('Benjamin', 100, 'LA', False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False), ('Benjamin', 100, 'LA', False, False)]]]
results = ['Varsha', 'Dawood', 'Ayesha', 'John', 'Alice', 'Alice', 'Benjamin', 'Benjamin', 'John', 'Benjamin', 'John', 'Benjamin', 'John', 'Benjamin', 'Benjamin', 'Benjamin', 'Alice', 'Benjamin', 'Benjamin', 'Alice', 'Benjamin', 'Benjamin', 'John', 'Alice', 'Adam', 'Alice', 'Benjamin', 'Alice', 'Benjamin', 'Alice', 'Alice', 'Alice', 'Alice', 'Benjamin', 'Alice', 'Alice', 'John', 'John', 'Alice', 'Alice', 'Benjamin', 'Benjamin', 'Bob', 'Adam', 'Benjamin', 'Bob', 'Adam', 'Alice', 'Alice', 'Alice', 'Alice', 'Charlie', 'Benjamin', 'AlNYCice', 'Charlie', 'Benjamin', 'Alice', 'Benjamin', 'Alice', 'Alice', 'Benjamin', 'Benjamin', 'Benjamin', 'Benjamin', 'Alice', 'John', 'Benjamin', 'Benjamin', 'AlNYCice', 'Alice', 'Alice', 'Benjamin', 'Alice', 'Alice', 'Alice', 'Adam', 'Alice', 'Charlie', 'Alice', 'John', 'Benjamin', 'Benjamin', 'Alice', 'Adam', 'Benjamin', 'Alice', 'John', 'Benjamin', 'Benjamin', 'Jane', 'AlNYCice', 'Charlie', 'Benjamin', 'Alice', 'Benjamin', 'John', 'Benjamin', 'John', 'John', 'Jane', 'AlNYCice', 'Benjamin', 'Bob', 'Alice', 'Alice', 'Alice', 'Benjamin', 'Benjamin', 'Benjamin']
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(index_minimum(*inp), exp, 0)
| OK=True
==================== Problem #49 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the smallest list in a list of lists.
Your answer will be tested on test cases like:
assert Find_Min_Length([[1],[1,2]]) == 1
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the smallest list in a list of lists.
Your answer will be tested on test cases like:
assert Find_Min_Length([[1],[1,2]]) == 1
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the smallest list in a list of lists.
Your answer will be tested on test cases like:
assert Find_Min_Length([[1],[1,2]]) == 1
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the smallest list in a list of lists.
Your answer will be tested on test cases like:
assert Find_Min_Length([[1],[1,2]]) == 1
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the length of the smallest list in a list of lists.
Your answer will be tested on test cases like:
assert Find_Min_Length([[1],[1,2]]) == 1
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called Find_Min_Length that takes a list of lists and returns the length of the smallest list. Let's see.
First, the function needs to process each sublist in the input list. For each sublist, I should calculate its length. Then find the minimum among those lengths.
Wait, how do I get the lengths? Like, for each list in the list_of_lists, take len(list). Then find the smallest of those numbers.
So, maybe I can use a generator expression to compute the lengths. Like, min(len(sublist) for sublist in list_of_lists).
But wait, what if the input is empty? Oh, the problem probably assumes that the input is a non-empty list of lists. Because if it's empty, the function would crash. But the test case given is [[1], [1,2]], which is valid.
So the function can be written as:
def Find_Min_Length(list_of_lists):
return min(len(sublist) for sublist in list_of_lists)
Wait, but what if there's an empty sublist? Like if the input is [[], [1,2]], then the min length is 0. That's correct according to the problem statement.
So this function should work. Let me test the sample case. The input is [[1], [1,2]]. The lengths are 1 and 2. The min is 1. Which matches the test case.
Another test case: if there's a sublist with zero elements, it should return 0. Like [[], [1], [2,3]] → min is 0.
So the code seems correct. Now, I need to write this as a self-contained function. The code should be in a markdown code block. Let me make sure there are no typos. Oh, the function name is Find_Min_Length, and it's case-sensitive. So the code should be:
def Find_Min_Length(list_of_lists):
return min(len(sublist) for sublist in list_of_lists)
Yes. That's the code. Let me put that into the markdown code block.
```python
def Find_Min_Length(list_of_lists):
return min(len(sublist) for sublist in list_of_lists)
```
----------------------------------------------
Result: Pred=def Find_Min_Length(list_of_lists):
return min(len(sublist) for sublist in list_of_lists) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[[1], [1, 2]]], [[[1, 2], [1, 2, 3], [1, 2, 3, 4]]], [[[3, 3, 3], [4, 4, 4, 4]]], [[[], [], [], [], [], []]], [[[1, 2, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13]]], [[[], [], [], [], []]], [[[], [], []]], [[[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[4, 1, 2, 3], [4, 5], [4, 1, 2, 3], [6, 7, 8, 9, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13]]], [[[], [], [9, 2, -89, 83, 13], [], [], [], []]], [[[]]], [[[], [], [], [True, False, 84.98850542252845, True], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [11, 12, 13]]], [[[False], [False]]], [[[84.98850542252845, -78.5618531155085]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [6, 7, 8, 5, 9]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [11, 12, 13], [1, 2, 3]]], [[[4, 1, 2, 3], [4, 8], [4, 1, 2, 3], [6, 11, 7, 8, 9, 10], [11, 12, 13]]], [[[85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [True, True, True, True, False, True, True]]], [[[], [], [], [True, False, 84.98850542252845, True], [], [], [], [], [], [], [False, False, False, True, True], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [1, 2, 3]]], [[[1, 2, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13], [1, 2, 3]]], [[[85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [True, True, True, True, False, True, True], [85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085]]], [[[1, 2, 3], [6, 7, 8, 9, 10], [11, 12, 13], [6, 7, 8, 9, 10]]], [[[1, 3, 6, 7, 3], [1, 3, 6, 7, 3], [1, 3, 6, 7, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 8, 5, 9], [6, 8, 5, 9], [4, 5], [6, 8, 5, 9], [11, 12, 13], [11, 12, 13]]], [[[1, 2, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13], [6, 7, 8, 9, 10]]], [[[85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [True, True, True, True, False, True, True, True], [85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085]]], [[[1, 2, 3], [6, 7, 8, 9, 10], [6, 7, 8, 9, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 5, 13], [4, 5], [6, 7, 8, 5, 13], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 5, 9], [6, 7, 5, 9]]], [[[4, 1, 2, 3], [4, 8], [4, 1, 2, 3], [11, 12, 13]]], [[[], [], [], [], [], [], [], ['nmUTpTB', 'LqgBbFug', 'A', 'YmVhY'], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[1, 2, 3], [6, 7, 8, 5, 8, 9], [4, 5], [6, 7, 8, 5, 8, 9], [11, 12, 13], [11, 12, 13]]], [[[], [], [], [-89, 12, 11], [False], [], []]], [[[4, 1, 3, 3], [4, 8], [4, 1, 3, 3], [4, 1, 3, 3], [11, 12, 13]]], [[[6, 7, 8, 9], [4, 5], [6, 7, 8, 9]]], [[[1, 2, 3], [6, 7, 8, 5, 8, 9], [4, 5, 5], [6, 7, 8, 5, 8, 9], [11, 12, 13], [11, 12, 13]]], [[[84.98850542252845, -78.5618531155085, -78.5618531155085], [84.98850542252845, -78.5618531155085, -78.5618531155085]]], [[[], [False, True, False, False, False, True, False, True], [], [], [], [], [], []]], [[[1, 2, 3], [6, 8, 5, 9], [6, 8, 5, 9], [6, 8, 5, 9], [11, 12, 13], [11, 12, 13], [1, 2, 3]]], [[[6, 7, 5, 9], [6, 7, 5, 9]]], [[[1, 2, 3], [6, 7, 8, 5, 8, 9], [4, 5], [6, 7, 8, 5, 8, 9], [11, 12, 13], [11, 12, 13], [11, 12, 13]]], [[[6, 7, 5, 9], [6, 7, 5, 9], [6, 7, 5, 9]]], [[[1, 2, 3], [4, 5], [6, 7, 8, 8, 10, 9], [6, 7, 8, 8, 10, 9], [11, 12, 13], [1, 2, 3]]], [[[], [33, 9, -70, False, -84, -42, False, -64, 7, -66], [], [], []]], [[[4, 2, 3], [6, 11, 7, 8, 9, 10], [4, 8], [4, 2, 3], [6, 11, 7, 8, 9, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 9, 10], [6, 7, 8, 9, 10], [11, 12, 13], [6, 7, 8, 9, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 8, 5, 9, 8], [6, 8, 5, 9, 8], [6, 8, 5, 9, 8], [6, 8, 5, 9, 8], [11, 12, 13], [11, 12, 13], [1, 2, 3], [6, 8, 5, 9, 8]]], [[[84.98850542252845, -78.5618531155085, -78.5618531155085]]], [[[6, 7, 8, 9], [4, 5], [6, 7, 8, 9], [6, 7, 8, 9]]], [[[4, 1, 2, 3], [4, 5], [4, 1, 2, 3], [6, 7, 8, 9, 10], [11, 12, 13], [4, 1, 2, 3], [6, 7, 8, 9, 10]]], [[[85.61630620077268, -90.47064487499253, 84.98850542252845, 84.52239660663136, -78.5618531155085], [True, True, True, True, False, True, True]]], [[[False]]], [[[], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84], [], [], [], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84]]], [[[1, 2, 2, 3], [4, 5], [11, 12, 13], [1, 2, 2, 3], [6, 7, 8, 9, 10]]], [[[33, 9, -70, False, -84, -42, False, -64, 7, -66], [], [], [90, 33, 2, 13, 69, 3, 83, 2]]], [[[2, -84, 3], [5], [5], [6, 7, 8, 9, 10], [2, -84, 3], [11, 12, 13]]], [[[3, 2, 3], [3, 2, 3], [6, 7, 8, 5, 9], [3, 2, 3], [4, 4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [11, 12, 13], [3, 2, 3]]], [[[], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84], [], [], [], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84], [33, 9, -70, False, -84, -42, False, -64, 7, -66, -84], []]], [[[6, 7, 8], [4, 5], [6, 7, 8]]], [[[1, 2, 3], [6, 7, 8, 9], [6, 7, 8, 9], [6, 7, 8, 9], [11, 12, 13], [6, 7, 8, 9], [11, 12, 13], [1, 2, 3]]], [[[], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[1, 3, 6, 7, 3], [1, 3, 6, 7, 3], [1, 3, 6, 7, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13], [6, 7, 8, 9, 10]]], [[[], [33, 9, False, -70, False, -84, -42, False, -64, 7, -66], [], [], []]], [[[4, 1, 2, 3], [4, 5], [4, 1, 2, 3], [6, 7, 8, 9, 10], [11, 12, 13], [11, 12, 13]]], [[[False, True, True, True, True, False, False, False], [], []]], [[[2, 9, 63, 9, 4, 2, -83, -84, -78], [33, 9, -70, False, -84, -42, False, -64, 7, -66], [], [], []]], [[[4, 1, 2, 2, 3], [4, 5], [4, 1, 2, 2, 3], [4, 1, 2, 2, 3], [6, 7, 8, 9, 10], [11, 12], [4, 1, 2, 2, 3]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13, 12], [11, 12, 13, 12]]], [[[], [33, 9, -70, False, -84, -42, False, -64, 7, -66], [], [], [], []]], [[[3, 2, 3, 3], [3, 2, 3, 3], [6, 7, 8, 5, 9], [3, 2, 3, 3], [4, 4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [11, 12, 13], [3, 2, 3, 3]]], [[[6, 7, -84, 8, 9], [6, 7, -84, 8, 9], [4, 5], [6, 7, -84, 8, 9]]], [[[4, 1, 2, 2, 3], [4, 5], [4, 1, 2, 2, 3], [4, 1, 2, 2, 3], [11, 12], [4, 1, 2, 2, 3]]], [[[4, 1, 2, 3, 4], [4, 1, 2, 3, 4], [4, 8], [11, 12, 13, 13], [4, 1, 2, 3, 4], [11, 12, 13, 13]]], [[[-58.13858535192631, 85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [-58.13858535192631, 85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [True, True, True, True, False, True, True, True], [True, True, True, True, False, True, True, True]]], [[[6, 11, 7, 8, 6, 10], [4, 2, 3], [6, 11, 7, 8, 6, 10], [4, 8], [4, 2, 3], [6, 11, 7, 8, 6, 10], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 9, 10, 7], [6, 7, 8, 9, 10, 7], [6, 7, 8, 9, 10, 7], [11, 12, 13], [6, 7, 8, 9, 10, 7], [11, 12, 13]]], [[[4, 5, 4], [6, 7, 8, 5, 13], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 13, 13, 12], [11, 13, 13, 12]]], [[[], [], [], [], [], [], [], ['nmUTpTB', 'LqgBbFug', 'A', 'YmVhY'], ['LqgBbFug', 'ADAvRmZZL', 'A', ''], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]], [[[2, -84, 3], [5], [5], [6, 7, 8, 9, 10], [2, -84, 3], [11, 12, 13], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 5, 8, 9], [4, 5, 5], [6, 7, 8, 5, 8, 9], [11, 12, 13]]], [[[1, 2, 3], [5, 7, 8, 5], [5, 7, 8, 5], [5, 7, 8, 5], [5, 7, 8, 5]]], [[[1, 2, 3], [4, 5], [6, 7, 8, 9, 10], [11, 12, 13], [6, 7, 8, 9, 10], [1, 2, 3]]], [[[], [33, 9, False, -84, -42, False, -64, 7, -66, -84], [], [], [], []]], [[[1, 2, 3], [6, 7, 8, 5, 9], [4, 5], [6, 7, 8, 5, 9], [11, 12, 13], [1, 2, 3], [6, 7, 8, 5, 9]]], [[[6, 11, 7, 8, 6, 10], [4, 2, 3], [6, 11, 7, 8, 6, 10], [4, 8], [6, 11, 7, 8, 6, 10], [11, 12, 13], [4, 8]]], [[[1, 2, 3], [6, 7, 5, 9], [4, 5], [6, 7, 5, 9], [12, 13, 12], [12, 13, 12]]], [[[1, 2, 3], [6, 9, 8, 9, 10], [6, 9, 8, 9, 10], [11, 12, 13], [6, 9, 8, 9, 10], [11, 12, 13]]], [[[], [False, True, False, False, False, True, False, True], [], [], [], [], [], [], []]], [[[False], [False], [False]]], [[[4, 1, 2, 2, 3], [4], [4, 1, 2, 2, 3], [4, 1, 2, 2, 3], [11, 12], [4, 1, 2, 2, 3]]], [[[1, 2, 3], [6, 8, 5, 9], [6, 8, 5, 9], [4, 5], [6, 8, 5, 9], [11, 12, 13, 11], [11, 12, 13, 11], [11, 12, 13, 11], [6, 8, 5, 9]]], [[[3, 2, 3, 3], [3, 2, 3, 3], [6, 7, 8, 5, 9, 8], [6, 7, 8, 5, 9, 8], [3, 2, 3, 3], [4, 4, 5], [6, 7, 8, 5, 9, 8], [11, 12, 13], [11, 12, 13], [3, 2, 3, 3], [11, 12, 13]]], [[[1, 2, 3], [6, 7, 8, 5, 9], [5], [11, 12, 13], [11, 12, 13], [6, 7, 8, 5, 9], [11, 12, 13]]], [[[], [], [], [True, False, 84.98850542252845, True], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [69, 8, -42, 6], [], [], [], [], [], []]], [[[85.61630620077268, -90.47064487499253, 87.92412950816434, 84.98850542252845, -78.5618531155085], [85.61630620077268, -90.47064487499253, 87.92412950816434, 84.98850542252845, -78.5618531155085]]], [[[False, True, False, False, False, True, False, True], [], [], [], [], [], []]], [[[85.61630620077268, 84.98850542252845, 84.98850542252845, -78.5618531155085], [True, True, True, True, False, True, True, True], [85.61630620077268, 84.98850542252845, 84.98850542252845, -78.5618531155085], [85.61630620077268, 84.98850542252845, 84.98850542252845, -78.5618531155085]]], [[[1, 2, 2, 3, 1], [4, 5], [11, 12, 13], [1, 2, 2, 3, 1], [1, 2, 2, 3, 1], [6, 7, 8, 9, 10], [1, 2, 2, 3, 1]]], [[[6, 11, 7, 8, 6, 10], [4, 2, 3], [6, 11, 7, 8, 6, 10], [8], [6, 11, 7, 8, 6, 10], [11, 12, 13], [8]]], [[[4, 1, 2, 3, 4], [4, 8], [7, 11, 12, 13, 13], [4, 1, 2, 3, 4], [7, 11, 12, 13, 13]]], [[[4, 5, 4], [6, 7, 8, 5, 13], [11, 12, 13], [4, 5, 4]]], [[[85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085], [85.61630620077268, -90.47064487499253, 84.98850542252845, 84.98850542252845, -78.5618531155085]]], [[[62.65634626917724, -78.5618531155085], [62.65634626917724, -78.5618531155085], [62.65634626917724, -78.5618531155085]]], [[[], [], [True, 'ERSEFXmEb', [-90.47064487499253, -61.40371790488326, 84.52239660663136], False, {'-80': None, '-78': -1.574803399508525, '47': 6, '-81': 4.848176964479563, '82': False, '6': 5}, -58.13858535192631, True, None, 'ERSEFXmEb'], [], [], [], []]]]
results = [1, 2, 3, 0, 2, 0, 0, 0, 2, 2, 0, 0, 0, 2, 1, 2, 3, 2, 2, 5, 0, 2, 2, 5, 3, 2, 2, 2, 5, 3, 2, 3, 2, 0, 2, 0, 2, 2, 3, 3, 0, 3, 4, 2, 4, 2, 0, 2, 3, 3, 3, 2, 2, 5, 1, 0, 2, 0, 1, 3, 0, 2, 3, 0, 2, 0, 2, 0, 0, 2, 2, 0, 3, 2, 2, 2, 6, 2, 3, 3, 2, 0, 1, 3, 3, 2, 0, 2, 2, 2, 3, 0, 1, 1, 2, 3, 1, 0, 5, 0, 4, 2, 1, 2, 3, 5, 2, 0]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(Find_Min_Length(*inp), exp, 0)
| OK=True
==================== Problem #50 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of divisors of a given integer.
Your answer will be tested on test cases like:
assert divisor(15) == 4
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of divisors of a given integer.
Your answer will be tested on test cases like:
assert divisor(15) == 4
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of divisors of a given integer.
Your answer will be tested on test cases like:
assert divisor(15) == 4
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of divisors of a given integer.
Your answer will be tested on test cases like:
assert divisor(15) == 4
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of divisors of a given integer.
Your answer will be tested on test cases like:
assert divisor(15) == 4
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called divisor that takes an integer and returns the number of its divisors. Let's think about how to approach this.
First, I remember that the number of divisors of a number can be found by checking all integers up to the square root of the number. For each divisor found, there's a corresponding pair. But I need to be careful with perfect squares to avoid counting the square root twice.
Wait, the steps would be something like: Initialize a count to zero. Loop from 1 to sqrt(n). For each i, if i divides n, check if i and n/i are the same. If they are, increment count by 1. Otherwise, increment count by 2. But wait, that's for all divisors, including 1 and n itself.
Wait, but the problem says "number of divisors", which includes all positive integers that divide the number. So for example, 15 has divisors 1, 3, 5, 15. So four divisors. The sample test case is divisor(15) ==4, which matches.
So how to compute this efficiently?
Let me think of the algorithm:
Initialize count to 0.
Loop i from 1 to sqrt(n) inclusive. For each i, check if i divides n.
If i divides n:
if i * i == n: then count +=1 (since it's a perfect square, only one divisor here)
else: count +=2 (since i and n/i are both divisors)
But wait, for example, for n=15, sqrt(15) is approx 3.87. So the loop would go up to 3. Let's see:
i=1: divides 15. 1*1 !=15, so count +=2 (1 and 15). Now count is 2.
i=2: 15%2 is 1, so no.
i=3: 15%3 is 0. 3*3 is 9 !=15. So count +=2 (3 and 5). Now count is 4. Which is correct.
So that seems to work.
But how to handle the loop? The loop should iterate up to the integer part of sqrt(n). So for i in range(1, int(math.sqrt(n)) +1). Because if n is a perfect square, then the sqrt is integer, and we need to include it.
But wait, for example, n=16: sqrt is 4. So loop up to 4.
i=1: 1 divides 16. 1*1 !=16. count +=2 (1 and 16). count is 2.
i=2: 2 divides 16. 2*2=4 !=16. count +=2 (2 and 8). count is 4.
i=3: 16%3 is 1. No.
i=4: 4 divides 16. 4*4=16. So count +=1. Now total is 5. Which is correct (divisors are 1,2,4,8,16). Wait, no. Wait 16 has divisors 1, 2, 4, 8, 16. That's 5 divisors. So the code would return 5. Which is correct.
So the algorithm seems correct.
Now, the code steps:
First, import math.
But wait, the function needs to handle n=0? Wait, the problem says "given integer". But for n=0, the number of divisors is infinite, but perhaps the function is intended for positive integers. The sample test case uses 15, which is positive. So perhaps the function is intended for positive integers. So we can assume n is a positive integer.
So the function can be written as follows:
def divisor(n):
if n == 0:
return 0 # but maybe the problem doesn't consider this case.
But the problem says "given integer", but maybe the test cases are for positive integers. So perhaps the function can assume that n is a positive integer.
So proceed.
So code:
import math
def divisor(n):
count = 0
for i in range(1, int(math.sqrt(n)) + 1):
if n % i == 0:
if i * i == n:
count +=1
else:
count +=2
return count
Wait, but what about when n is 1? Let's test.
n=1: sqrt(1) is 1. So loop runs i=1.
n%1 is 0. i*i is 1, which equals n. So count +=1. So returns 1. Which is correct (divisors are 1).
Another test case: n=2. sqrt(2) is ~1.414. So int is 1. Loop runs i=1.
n%1 is 0. i*i is 1 !=2. So count +=2. So returns 2. Which is correct (1 and 2).
Another test case: n=4. sqrt(4) is 2. So i ranges 1,2.
i=1: 4%1=0. 1*1 !=4. count +=2 (1 and 4). count is 2.
i=2: 4%2=0. 2*2=4. count +=1. total 3. Which is correct (1,2,4).
So the code seems to work.
But wait, the code for n=15 would loop i from 1 to 3 (since sqrt(15) is ~3.87, int is 3). So i=1, 2,3.
i=1: 15%1=0. 1*1 !=15. count +=2 (count=2).
i=2: 15%2=1. No change.
i=3: 15%3=0. 3*3=9 !=15. count +=2 (count=4). Which is correct.
Yes, so the code works.
But what about n=0? Well, the problem may not test that. But the code would have a problem because sqrt(0) is 0, and the loop would run from 1 to 0, which is not executed. So count remains 0. But for n=0, the number of divisors is infinite, but perhaps the function is not required to handle it. Since the test case is for 15, which is positive, perhaps the function is intended for positive integers.
Thus, the code should work.
So the Python code would be:
import math
def divisor(n):
count = 0
for i in range(1, int(math.sqrt(n)) + 1):
if n % i == 0:
if i * i == n:
count += 1
else:
count += 2
return count
But wait, what if n is 0? Well, the code would return 0, but that's not correct. However, the problem says that the test case is for 15, so maybe the function is intended for positive integers. So the code is correct for the given test case.
So the code should be written as such.
```python
import math
def divisor(n):
count = 0
for i in range(1, int(math.sqrt(n)) + 1):
if n % i == 0:
if i * i == n:
count += 1
else:
count += 2
return count
```
----------------------------------------------
Result: Pred=import math
def divisor(n):
count = 0
for i in range(1, int(math.sqrt(n)) + 1):
if n % i == 0:
if i * i == n:
count += 1
else:
count += 2
return count | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[15], [12], [9], [79337], [79336], [86], [87], [88], [85], [79335], [79334], [79333], [79332], [True], [89], [79331], [95], [90], [79338], [91], [92], [93], [84], [94], [83], [79330], [82], [46], [47], [44], [48], [49], [81], [43], [42], [96], [41], [45], [97], [79], [78], [79329], [80], [50], [40], [79328], [51], [17], [98], [39], [16], [18], [99], [38], [79327], [19], [20], [79325], [77], [79339], [37], [36], [79324], [79340], [79341], [35], [34], [79323], [73], [79322], [21], [22], [79320], [52], [23], [74], [65], [79326], [79321], [33], [79319], [76], [32], [14], [75], [57], [100], [62], [67], [72], [58], [59], [60], [66], [56], [53], [101], [54], [68], [63], [55], [61], [64]]
results = [4, 6, 3, 2, 16, 4, 4, 8, 4, 24, 4, 2, 24, 1, 2, 6, 4, 12, 16, 4, 6, 4, 12, 4, 2, 8, 4, 4, 2, 6, 10, 3, 5, 2, 8, 12, 2, 6, 2, 2, 8, 8, 10, 6, 8, 24, 4, 2, 6, 4, 5, 6, 6, 4, 4, 2, 6, 12, 4, 8, 2, 9, 12, 12, 8, 4, 4, 8, 2, 8, 4, 4, 32, 6, 2, 4, 4, 32, 4, 4, 2, 6, 6, 4, 6, 4, 9, 4, 2, 12, 4, 2, 12, 8, 8, 2, 2, 8, 6, 6, 4, 2, 7]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(divisor(*inp), exp, 0)
| OK=True
==================== Problem #51 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find frequency of each element in a flattened list of lists, returned in a dictionary.
Your answer will be tested on test cases like:
assert frequency_lists([[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]])=={1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find frequency of each element in a flattened list of lists, returned in a dictionary.
Your answer will be tested on test cases like:
assert frequency_lists([[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]])=={1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find frequency of each element in a flattened list of lists, returned in a dictionary.
Your answer will be tested on test cases like:
assert frequency_lists([[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]])=={1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find frequency of each element in a flattened list of lists, returned in a dictionary.
Your answer will be tested on test cases like:
assert frequency_lists([[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]])=={1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find frequency of each element in a flattened list of lists, returned in a dictionary.
Your answer will be tested on test cases like:
assert frequency_lists([[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]])=={1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, let's see. I need to write a Python function that takes a list of lists and returns the frequency of each element in the flattened version. The example given is when the input is [[1,2,3,2], [4,5,6,2], [7,8,9,5]], the output is {1:1, 2:3, etc.}.
First, I need to flatten the list. How do I do that? Well, maybe loop through each sublist and then each element in the sublist. Or maybe use a list comprehension. Like, for each sublist in the input list, extend a new list with its elements. So for example, [[1,2], [3]] becomes [1,2,3].
Once the list is flattened, I need to count the frequency of each element. How to do that? Well, I can use a dictionary. Initialize an empty dict. Then iterate over each element in the flattened list. For each element, if it's already a key in the dict, increment the count. Otherwise, add it with a count of 1.
Alternatively, maybe use the collections.Counter class. Because that's designed for counting hashable objects. So flattening the list and then passing it to Counter would give the frequencies. Then convert that Counter to a dictionary.
So the steps are:
1. Flatten the input list of lists into a single list.
2. Count the occurrences of each element in this flattened list.
3. Return the counts as a dictionary.
Let me think about how to flatten. Suppose the input is called lists. Then flattened = [element for sublist in lists for element in sublist]. That's a list comprehension that flattens one level.
Yes. So for example, [[1,2], [3]] becomes [1,2,3].
Once I have the flattened list, using Counter is straightforward. So from collections import Counter.
But the function needs to return a dictionary. So, the code would be something like:
from collections import Counter
def frequency_lists(lists):
flattened = [element for sublist in lists for element in sublist]
counts = Counter(flattened)
return dict(counts)
Wait, but the test case expects the keys to be in a certain order? Wait, no. The example given has the keys in the order 1,2,3,4,5,6,7,8,9. But dictionaries in Python (before 3.7) don't maintain order. However, the test case uses == to compare, which would require the same keys in the same order. But in Python 3.7+, regular dicts are insertion ordered. However, when using Counter, the order is based on the first occurrence. But in the test case, the order of the keys in the output dictionary may not matter as long as the counts are correct. Wait, the test case shows the dictionary as {1:1, 2:3, ...}, but when you convert a Counter to a dict, the order might not be the same as the test case. However, in Python, when you create a dictionary, the order of keys is not guaranteed unless you use OrderedDict or Python 3.7+ where insertion order is preserved. But the test case may not check for order, but for the correct counts. Because in the example, the assert statement uses ==, which for dictionaries checks that the key-value pairs are the same, regardless of order. Wait, no. In Python, when you compare two dictionaries with ==, the order of the keys does not matter. So {1:1, 2:2} == {2:2, 1:1} is True. So the test case's example may have the keys in a certain order, but the actual dictionary returned by the code may have the same key-value pairs but in a different order, but the assert would still pass. So the code is okay.
But let me check the example. The input is [[1,2,3,2], [4,5,6,2], [7,8,9,5]]. Flattened list is [1,2,3,2,4,5,6,2,7,8,9,5]. The counts are:
1:1, 2:3, 3:1, 4:1, 5:2, 6:1, 7:1, 8:1, 9:1. So the Counter would have these counts. When converted to a dict, the order of the keys depends on the insertion order. But in the test case, the expected dictionary is ordered in the way that the first occurrence of each element in the flattened list. For example, 1 comes first, then 2, then 3, etc. However, when using Counter, the elements are ordered by their first occurrence. So when converting to a dict, in Python 3.7+, the insertion order is preserved. But the test case may not require the order, but just the correct counts.
But the assert statement in the test case is expecting a specific dictionary. However, in Python, when you create a dictionary, the order of keys is not guaranteed unless using OrderedDict. However, in the test case, the sample output is given as {1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}. But when the code returns a dict, the order of keys may differ. However, the test case may not check for order. Because in Python, when two dictionaries have the same key-value pairs, they are considered equal regardless of order. So the assert statement would pass as long as the counts are correct.
So the code should work.
But wait, in the example, the test case uses ==. So if the code returns a dictionary with the same key-value pairs, regardless of order, the assert would pass. Therefore, the code is correct.
So the function can be written as:
Import Counter from collections.
But the problem says that the function must be self-contained. So the code must include all necessary imports.
But the user's test case may not have the import. However, the code must be self-contained. So the code should include the necessary import.
But the problem says that the answer should be a self-contained Python script. So the code must include the function and any necessary imports.
So the code would be:
from collections import Counter
def frequency_lists(lists):
flattened = [item for sublist in lists for item in sublist]
counts = Counter(flattened)
return dict(counts)
But let me test this with the sample input.
Sample input: [[1,2,3,2], [4,5,6,2], [7,8,9,5]]
Flattened list is [1,2,3,2,4,5,6,2,7,8,9,5]. The Counter would count:
1:1, 2:3, 3:1, 4:1, 5:2, 6:1, 7:1, 8:1, 9:1. So the dict would have these values. The test case expects exactly that. So the code should work.
But what about if the input is empty? Well, the function would return an empty dict. Which is correct.
Another test case: [[], [1,1], [2]] → flattened is [1,1,2]. The counts are 1:2, 2:1. So the function returns {1:2, 2:1}.
But in Python, when you convert a Counter to a dict, the order is based on insertion. However, the test case's expected output may not care about the order. So the code should be correct.
Therefore, the code should work.
```python
from collections import Counter
def frequency_lists(lists):
flattened = [item for sublist in lists for item in sublist]
counts = Counter(flattened)
return dict(counts)
```
----------------------------------------------
Result: Pred=from collections import Counter
def frequency_lists(lists):
flattened = [item for sublist in lists for item in sublist]
counts = Counter(flattened)
return dict(counts) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[[1, 2, 3, 2], [4, 5, 6, 2], [7, 8, 9, 5]]], [[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]], [[[20, 30, 40, 17], [18, 16, 14, 13], [10, 20, 30, 40]]], [[[1, 1, 1, 1], [2, 2, 2, 2], [3, 3, 3, 3]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 8], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 8], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 8]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 4, 5, 5, 5]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 8, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 3]]], [[[1, 2, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [1, 1, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 6, 7, 8, 9, 9], [1, 2, 3, 4, 6, 7, 8, 9, 9]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5], [1, 1, 1, 2, 2, 2, 3, 3, 3]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6]]], [[[2, 2, 2, 3, 4, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 3, 4, 5, 6, 7, 8, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9, 9, 3]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 8, 5, 5], [3, 3, 3, 4, 4, 4, 8, 5, 5]]], [[[1, 1, 1, 1], [2, 2, 6, 2, 2]]], [[[2, 3, 4, 5, 6, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [2, 3, 4, 5, 6, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 8], [2, 3, 1, 4, 5, 6, 7, 8, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 8], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[2, 3, 1, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5], [1, 1, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 8, 5, 5]]], [[[7, 1, 2, 3, 4, 5, 6, 7, 8, 2, 9, 9, 3], [7, 1, 2, 3, 4, 5, 6, 7, 8, 2, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 8], [7, 1, 2, 3, 4, 5, 6, 7, 8, 2, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 8], [1, 2, 3, 4, 5, 6, 7, 8, 8], [7, 1, 2, 3, 4, 5, 6, 7, 8, 2, 9, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 8]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [2, 3, 9, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 9, 4, 5, 6, 7, 8, 9], [2, 3, 9, 4, 5, 6, 7, 8, 9], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7], [1, 2, 4, 7, 6, 2, 7, 8, 9, 7]]], [[[2, 2, 2, 2], [3, 3, 3, 3]]], [[[1, 2, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5], [1, 1, 1, 2, 2, 2, 3, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[1, 3, 1, 1, 1, 2, 2, 3, 3, 3], [1, 3, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [8, 3, 3, 3, 4, 4, 4, 5, 5, 7], [2, 2, 2, 3, 3, 3, 4, 4, 4], [8, 3, 3, 3, 4, 4, 4, 5, 5, 7]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3, 1], [1, 1, 1, 2, 2, 2, 3, 3, 3, 1], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [3, 4, 5, 6, 7, 8, 9], [3, 4, 5, 6, 7, 8, 9], [3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [3, 4, 5, 6, 7, 8, 9]]], [[[1, 7, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 5, 5, 5], [1, 7, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 5, 5, 5]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5], [2, 2, 2, 3, 3, 3, 4, 4, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 5], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 5], [2, 2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 5], [2, 2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[1, 2, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 4, 5, 6, 7, 8, 9]]], [[[2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6], [2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 3, 1, 1, 1, 2, 2, 3, 3, 3], [1, 3, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [1, 3, 1, 1, 1, 2, 2, 3, 3, 3]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 8, 8, 8], [2, 3, 1, 4, 5, 6, 7, 8, 8, 8, 8], [2, 3, 1, 4, 5, 6, 7, 8, 8, 8, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 1, 4, 5, 6, 7, 8, 8, 8, 8], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9]]], [[[1, 2, 3, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 4], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[0, 1, 1, 1, 1], [0, 1, 1, 1, 1], [2, 2, 6, 2, 2]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6]]], [[[1, 3, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [1, 3, 1, 1, 1, 2, 2, 3, 3, 3]]], [[[2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6], [2, 3, 4, 5, 6, 7, 8, 9]]], [[[1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 4, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 1, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4, 4, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 2, 3, 4, 5, 6, 2, 7, 8, 9], [1, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 3, 2, 2, 3, 3, 2], [1, 1, 1, 3, 2, 2, 3, 3, 2], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 3, 1, 1, 1, 2, 2, 5, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [2, 2, 2, 3, 3, 3, 4, 9, 4, 4], [1, 3, 1, 1, 1, 2, 2, 5, 3, 3, 3], [1, 3, 1, 1, 1, 2, 2, 5, 3, 3, 3]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 6, 6, 7, 8, 9], [1, 2, 3, 4, 6, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3], [1, 2, 3, 4, 6, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 5, 9, 3]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5], [2, 2, 2, 3, 3, 3, 4, 4, 4]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 4, 4, 5, 6, 7, 8, 9], [1, 2, 4, 4, 5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 3, 2, 2, 3, 3, 2], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9]]], [[[1, 2, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9], [1, 2, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9]]], [[[1, 3, 2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 3, 2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 8, 5, 5]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [8, 3, 3, 3, 4, 4, 4, 5, 5, 7], [2, 2, 2, 3, 3, 3, 4, 4, 4], [8, 3, 3, 3, 4, 4, 4, 5, 5, 7]]], [[[1, 7, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 5, 5, 5], [1, 7, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 5, 5, 5], [3, 3, 3, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 7, 8, 9, 1]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 7, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 5, 5, 5]]], [[[2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6], [2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6], [1, 2, 3, 4, 6, 5, 6, 7, 8, 9, 6]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 1, 1, 2, 2, 2, 3, 3, 3], [2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 3, 4, 4, 4, 5, 5, 5], [1, 1, 1, 2, 2, 2, 3, 3, 3], [1, 1, 1, 2, 2, 2, 3, 3, 3]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [3, 3, 4, 4, 4, 5, 5, 5], [1, 1, 1, 8, 2, 2, 3, 3, 3, 1], [1, 1, 1, 8, 2, 2, 3, 3, 3, 1], [3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 7, 8, 6], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]], [[[2, 2, 2, 3, 3, 3, 4, 4, 4], [1, 1, 1, 2, 2, 2, 3, 3, 3], [1, 1, 1, 2, 2, 2, 3, 3, 3], [3, 3, 3, 4, 4, 4, 5, 5, 5], [3, 3, 3, 4, 4, 4, 5, 5, 5]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 7, 8], [1, 2, 3, 4, 5, 6, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9, 1], [1, 2, 3, 4, 5, 6, 7, 8, 9, 9]]], [[[1, 2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9], [1, 2, 4, 5, 6, 2, 7, 8, 9]]]]
results = [{1: 1, 2: 3, 3: 1, 4: 1, 5: 2, 6: 1, 7: 1, 8: 1, 9: 1}, {1: 1, 2: 1, 3: 1, 4: 1, 5: 1, 6: 1, 7: 1, 8: 1, 9: 1, 10: 1, 11: 1, 12: 1}, {20: 2, 30: 2, 40: 2, 17: 1, 18: 1, 16: 1, 14: 1, 13: 1, 10: 1}, {1: 4, 2: 4, 3: 4}, {1: 3, 2: 3, 3: 3, 4: 3, 5: 3, 6: 3, 7: 3, 8: 3, 9: 3}, {1: 3, 2: 6, 3: 9, 4: 6, 5: 3}, {1: 3, 2: 3, 3: 3, 4: 3, 5: 3, 6: 3, 7: 4, 8: 3, 9: 3}, {2: 9, 3: 12, 4: 9, 1: 3, 5: 3}, {1: 5, 2: 5, 3: 5, 4: 5, 5: 5, 6: 5, 7: 9, 8: 5, 9: 5}, {2: 6, 3: 9, 4: 6, 1: 3, 5: 3}, {1: 4, 2: 4, 3: 4, 4: 4, 5: 4, 6: 4, 7: 7, 8: 4, 9: 4}, {1: 5, 2: 5, 3: 5, 4: 5, 5: 5, 6: 5, 7: 9, 8: 8, 9: 5}, {1: 6, 2: 6, 3: 6, 4: 6, 5: 6, 6: 6, 7: 7, 8: 6, 9: 9}, {1: 4, 2: 6, 3: 4, 4: 4, 5: 4, 6: 4, 7: 4, 8: 4, 9: 4}, {1: 5, 2: 5, 3: 5, 4: 5, 5: 5, 6: 5, 7: 5, 8: 5, 9: 5}, {1: 3, 2: 3, 3: 3, 4: 3, 5: 3, 6: 3, 7: 6, 8: 3, 9: 3}, {1: 2, 2: 2, 3: 2, 4: 2, 5: 2, 6: 2, 7: 2, 8: 2, 9: 2}, {2: 9, 3: 12, 4: 10, 1: 3, 5: 3}, {1: 8, 2: 7, 3: 12, 4: 6, 5: 3}, {2: 3, 3: 6, 4: 6, 8: 1, 5: 2}, {1: 3, 2: 7, 3: 5, 4: 5, 5: 5, 6: 5, 7: 5, 8: 5, 9: 5}, {1: 7, 2: 7, 3: 11, 4: 7, 5: 7, 6: 7, 7: 8, 8: 7, 9: 11}, {1: 5, 2: 11, 4: 7, 5: 7, 6: 7, 7: 7, 8: 7, 9: 7, 3: 3}, {1: 8, 2: 10, 3: 18, 4: 14, 5: 6}, {2: 9, 3: 12, 4: 6, 1: 6, 5: 3}, {1: 6, 2: 5, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}, {1: 3, 2: 6, 3: 15, 4: 15, 5: 9}, {2: 5, 3: 5, 4: 5, 5: 5, 6: 7, 7: 5, 8: 5, 9: 5, 1: 3}, {3: 3, 4: 3, 5: 3}, {1: 6, 2: 8, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}, {1: 2, 2: 3, 3: 3, 4: 3, 5: 3, 6: 3, 7: 3, 8: 3, 9: 3}, {1: 4, 2: 4, 3: 4, 4: 4, 5: 4, 6: 4, 7: 5, 8: 4, 9: 4}, {2: 6, 3: 9, 4: 9, 5: 3}, {1: 7, 2: 7, 3: 7, 4: 7, 6: 7, 7: 8, 8: 7, 9: 11, 5: 3}, {2: 6, 3: 6, 4: 6, 5: 6, 6: 9, 7: 6, 8: 6, 9: 6, 1: 4}, {1: 7, 2: 15, 4: 9, 7: 21, 6: 9, 8: 9, 9: 9, 3: 3, 5: 3}, {1: 6, 2: 9, 3: 12, 4: 6, 5: 3}, {2: 4, 3: 4, 4: 4, 5: 4, 6: 6, 7: 4, 8: 4, 9: 4, 1: 3}, {1: 4, 2: 4, 3: 4, 4: 5, 5: 4, 6: 4, 7: 7, 8: 4, 9: 4}, {1: 8, 2: 7, 3: 12, 4: 7, 5: 3, 9: 1}, {2: 6, 3: 6, 4: 6, 5: 6, 6: 9, 7: 6, 8: 6, 9: 6, 1: 4}, {2: 6, 3: 8, 4: 7, 1: 3, 5: 3}, {1: 8, 3: 13, 4: 8, 5: 8, 6: 8, 7: 9, 8: 8, 9: 13, 2: 3}, {1: 2, 2: 2, 3: 2, 4: 2, 5: 2, 6: 2, 7: 3, 8: 2, 9: 2}, {2: 3, 3: 9, 4: 9, 8: 2, 5: 4}, {1: 4, 2: 4, 6: 1}, {2: 6, 3: 6, 4: 6, 5: 6, 6: 9, 8: 6, 9: 6, 1: 4, 7: 4}, {1: 6, 2: 8, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 9, 9: 3}, {1: 6, 2: 7, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}, {2: 6, 3: 5, 1: 5, 4: 5, 5: 5, 6: 5, 7: 5, 8: 5, 9: 5}, {1: 6, 2: 9, 3: 15, 4: 9, 5: 6}, {1: 4, 2: 4, 3: 4, 4: 4, 5: 4, 6: 4, 7: 7, 8: 4, 9: 4}, {1: 4, 2: 4, 3: 4, 4: 4, 5: 4, 6: 4, 7: 4, 8: 4, 9: 4}, {1: 4, 2: 9, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}, {1: 1, 2: 3, 3: 6, 4: 6, 8: 1, 5: 2}, {7: 14, 1: 9, 2: 13, 3: 13, 4: 9, 5: 9, 6: 9, 8: 13, 9: 9}, {1: 5, 2: 5, 3: 8, 4: 5, 5: 8, 6: 5, 7: 5, 8: 5, 9: 8}, {1: 7, 2: 16, 4: 10, 7: 22, 6: 10, 8: 10, 9: 13, 3: 4, 5: 4}, {2: 4, 3: 4}, {1: 4, 2: 4, 4: 4, 5: 4, 6: 4, 7: 8, 8: 4, 9: 4, 3: 2}, {1: 6, 2: 9, 3: 17, 4: 9, 5: 6}, {2: 12, 3: 12, 4: 9, 1: 3}, {1: 8, 3: 20, 2: 13, 4: 13, 5: 3, 9: 3}, {2: 9, 3: 15, 4: 12, 1: 3, 8: 2, 5: 4, 7: 2}, {1: 8, 2: 9, 3: 12, 4: 6, 5: 3}, {1: 3, 2: 5, 3: 7, 4: 7, 5: 7, 6: 7, 7: 7, 8: 7, 9: 7}, {1: 4, 7: 2, 2: 9, 3: 15, 4: 7, 5: 6}, {2: 5, 3: 9, 4: 6, 1: 4, 5: 3}, {1: 5, 2: 6, 3: 5, 4: 5, 5: 5, 6: 5, 7: 5, 8: 5, 9: 5}, {1: 6, 2: 6, 3: 6, 4: 8, 5: 6, 6: 6, 7: 7, 8: 6, 9: 9}, {2: 11, 3: 15, 4: 12, 1: 4, 5: 3}, {1: 8, 2: 12, 3: 21, 4: 18, 5: 12}, {1: 3, 2: 3, 4: 3, 5: 3, 6: 3, 7: 4, 8: 3, 9: 3, 3: 1}, {2: 6, 3: 6, 4: 6, 5: 6, 6: 12, 7: 6, 8: 6, 9: 8, 1: 4}, {1: 12, 3: 24, 2: 15, 4: 13, 5: 3, 9: 3}, {1: 7, 2: 9, 3: 7, 4: 7, 5: 7, 6: 7, 7: 7, 8: 19, 9: 3}, {1: 3, 2: 4, 3: 7, 4: 4, 5: 4, 6: 4, 7: 4, 8: 4, 9: 4}, {1: 8, 2: 10, 3: 18, 4: 16, 5: 6}, {0: 2, 1: 8, 2: 4, 6: 1}, {2: 5, 3: 5, 4: 5, 5: 5, 6: 8, 7: 5, 8: 5, 9: 5, 1: 4}, {1: 8, 3: 17, 2: 10, 4: 10, 5: 3, 9: 2}, {2: 7, 3: 7, 4: 7, 5: 7, 6: 10, 7: 7, 8: 7, 9: 7, 1: 4}, {1: 8, 2: 10, 3: 20, 4: 16, 5: 6}, {1: 6, 2: 6, 3: 6, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}, {2: 9, 3: 12, 4: 6, 1: 6, 5: 3}, {1: 12, 3: 21, 2: 12, 5: 6, 4: 10, 9: 2}, {1: 7, 2: 7, 3: 11, 4: 7, 5: 8, 6: 10, 7: 7, 8: 7, 9: 11}, {1: 3, 2: 9, 3: 12, 4: 9, 5: 3}, {1: 3, 2: 3, 3: 1, 4: 5, 5: 3, 6: 3, 7: 4, 8: 3, 9: 3}, {1: 5, 2: 5, 3: 5, 4: 5, 5: 5, 6: 5, 7: 9, 8: 5, 9: 5}, {2: 6, 3: 9, 4: 6, 1: 3, 5: 3}, {1: 10, 2: 7, 3: 7, 4: 7, 5: 7, 6: 7, 7: 8, 8: 7, 9: 9}, {1: 4, 2: 4, 4: 4, 5: 4, 6: 4, 7: 6, 8: 4, 9: 4, 3: 2}, {1: 2, 3: 11, 2: 6, 4: 9, 8: 1, 5: 2}, {2: 6, 3: 12, 4: 12, 8: 2, 5: 4, 7: 2}, {1: 4, 7: 2, 2: 9, 3: 18, 4: 9, 5: 9}, {1: 11, 2: 6, 3: 6, 4: 6, 5: 6, 6: 6, 7: 11, 8: 6, 9: 6}, {2: 6, 3: 9, 4: 5, 1: 2, 7: 1, 5: 3}, {2: 5, 3: 5, 4: 5, 5: 5, 6: 11, 7: 5, 8: 5, 9: 7, 1: 3}, {2: 3, 3: 6, 4: 6, 5: 3}, {1: 9, 2: 12, 3: 15, 4: 6, 5: 3}, {2: 7, 3: 13, 4: 9, 5: 6, 1: 8, 8: 2}, {1: 3, 2: 3, 3: 3, 4: 3, 5: 3, 6: 4, 7: 4, 8: 3, 9: 2}, {2: 9, 3: 15, 4: 9, 1: 6, 5: 6}, {1: 8, 2: 6, 3: 6, 4: 6, 5: 6, 6: 6, 7: 7, 8: 6, 9: 8}, {1: 4, 2: 9, 3: 3, 4: 6, 5: 6, 6: 6, 7: 6, 8: 6, 9: 6}]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(frequency_lists(*inp), exp, 0)
| OK=True
==================== Problem #52 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply all the numbers in a list and divide with the length of the list.
Your answer will be tested on test cases like:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply all the numbers in a list and divide with the length of the list.
Your answer will be tested on test cases like:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply all the numbers in a list and divide with the length of the list.
Your answer will be tested on test cases like:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply all the numbers in a list and divide with the length of the list.
Your answer will be tested on test cases like:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply all the numbers in a list and divide with the length of the list.
Your answer will be tested on test cases like:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called multiply_num that takes a list (or maybe a tuple?) of numbers, multiplies all of them together, then divides by the length of the list. Let me think about how to approach this.
First, the function's parameters. The example given uses a tuple (8, 2, 3, -1, 7), but the problem says "a list". Wait, maybe the input can be a list or a tuple? Or perhaps the function is supposed to accept any iterable. But the problem says "a list", but the test case uses a tuple. Hmm. Well, maybe the function should accept any sequence, but for the purpose of the problem, maybe it's better to convert it to a list or just process the elements regardless of the type. But in Python, multiplying all elements can be done with a loop.
So, the steps are:
1. Multiply all numbers in the input. Let's say the input is a tuple or list. So, for example, for (8,2,3,-1,7), the product is 8*2*3*(-1)*7. Let me calculate that: 8*2 is 16, 16*3 is 48, 48 * -1 is -48, multiplied by 7 gives -336. Then divide by the length of the list, which is 5. So -336 /5 is -67.2, which matches the test case.
So the function needs to compute the product of all elements, then divide by the length.
Now, how to compute the product. For an empty list? Well, the problem probably assumes that the input is non-empty, but maybe I should handle that? But the test case provided has elements, so perhaps the function can assume that the input is a non-empty sequence.
So, the steps for the function:
- Take the input sequence (maybe a list or tuple)
- Compute the product of all elements
- Divide by the length of the sequence
- Return the result.
Now, how to implement this in Python.
First, the product. For a list of numbers, I can initialize a variable as 1, then multiply each element.
For example:
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
Wait, but what if the input is a tuple? Well, in Python, tuples are iterable, so the loop will work. So the function can accept any iterable, like a list or tuple.
But the function's parameter is given as (8, 2, 3, -1, 7) in the test case. So the function's parameter is a tuple? Or perhaps the function is supposed to take a list. But the problem says "a list", but the test case uses a tuple. Maybe the function is supposed to accept a list, but the test case uses a tuple. Wait, maybe the problem has a typo, but the user's code should handle the input as a list or tuple. But in Python, the function can take any iterable. So the code should work regardless.
So, the function would be written as:
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
But wait, the test case uses math.isclose with rel_tol=0.001. So the function returns a float? Because when you divide integers, in Python 3, it returns a float. For example, 5/2 is 2.5. So the code should return a float, which is handled automatically.
Testing the example: multiply_num((8,2,3,-1,7)) would compute product as 8*2*3*-1*7 = -336. Divided by 5 gives -67.2, which matches the test case.
But the function is supposed to be called multiply_num, and the parameter is a list? Wait, the problem says "a list", but the test case passes a tuple. However, in Python, tuples are iterable, so the code would work regardless. So the function can accept any iterable, like a list or tuple.
So the code should be correct. However, what if the input is empty? Well, the problem probably expects that the input is non-empty. But since the test case uses a non-empty input, perhaps the function can assume that.
So the code would be as written.
But the problem says to write a function. So the code would be:
import math
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
Wait, but the test case uses math.isclose. For example, the test case is:
assert math.isclose(multiply_num((8, 2, 3, -1, 7)), -67.2, rel_tol=0.001)
So the function returns -67.2, which is exactly the value. But when using floating points, there might be precision issues. However, the code returns product divided by len(numbers), which for the example is -336 /5 = -67.2 exactly. So the code should work.
But what if the product is zero? Well, the code would handle it. For example, if the list contains a zero, the product is zero, divided by length, which is zero. But that's correct.
So the code seems correct. Now, the problem says to provide a self-contained Python script. So the code should include the function and any necessary imports. However, the test case uses math.isclose, but the function itself doesn't need to import math. However, the user's code may need to import math if they use it. But the function multiply_num doesn't use math, but the test case does. However, the problem says to write the function, not the test cases. So the code for the function would not need to import math, but the test case would.
But the problem says that the answer will be tested on test cases like that. So the function must return the correct value, which the code does.
So the code is as written. Therefore, the Python code is:
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
But wait, what if the input is not a list or tuple? Like a string? Well, the problem says that the input is a list of numbers, so the function is supposed to take a list. However, the test case uses a tuple. But the function would work for any iterable, as long as the elements are numbers.
But the problem says "a list", but the test case uses a tuple. However, the code will work for tuples as well. So the function is correct.
So the code should be written as such. Now, the problem says to put the code in a markdown code block. So the final answer is:
```python
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
```
Wait, but the problem says "self-contained Python script". Does that mean that the code should include the necessary imports? Well, the function doesn't need any imports. The test case uses math.isclose, but the function itself doesn't need it. So the code is self-contained as written.
Yes, that's correct. So the code is as above.
```python
def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers)
```
----------------------------------------------
Result: Pred=def multiply_num(numbers):
product = 1
for num in numbers:
product *= num
return product / len(numbers) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[8, 2, 3, -1, 7]], [[-10, -20, -30]], [[19, 15, 18]], [[100000, 2, 3]], [[2.5, 1.5, 0, -3, 4.2]], [[0.5, 0.75, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7]], [[1, 10, 100, 1000, 10000, 100000]], [[-1, -2, -3, -4, -5, -6, -7, -8, -9, -10]], [[0, 0]], [[2, 3, 4, -2, 0]], [[1000000, 2000000, 3000000, -1000000]], [[5, 5, 5, 5]], [[1, -2, 3, -4, 5]], [[1, -2, 3, -4, 5, -2]], [[2, -2, 3, -6, -2, 0]], [[0, 0, 0]], [[2, 3, 4, -2, 0, 2]], [[2, 2, 3, 4, -2, 0]], [[2, 3, 4, -2, 0, -2]], [[3, 100000, 2, 3]], [[1, 10, 100, 1000, 10000, 100000, 100000]], [[1, 10, 100, 1000, 10000, 100000, 10]], [[2, 3, 0, -2, 0, 2]], [[2, 1, -2, 0, 2]], [[1000000, 2000000, 3000000, -1000000, -1000000]], [[-1, -2, -3, -5, -6, -7, -8, -9, -10]], [[1000000, 2000000, -1000000]], [[100000, 2]], [[0]], [[1000000, 2000000, -9, -1000000, 1000000]], [[-9, -1, -2, -3, -4, -5, -7, -8, -9, -10]], [[2, -2, 3, -7, -6, -2, 0]], [[0.5, 0.75, 0.1, 0.2, 0.2734396265136305, 0.3, 0.4, 0.5, 0.6, 0.7]], [[-1, -2, -1, -3, -4, -5, -6, -7, -8, -9, -10, -1]], [[2, 3, -2, 0]], [[2, 3, -1, -6, -2, 0]], [[1000000, -1000000]], [[5, 5, 5]], [[5, 5]], [[-1, -2, -3, 0, -5, -6, -7, -8, -9, -10, -1]], [[100000, 2, 100001, 3]], [[0.5, 0.75, 0.1, 0.2, 0.3, 0.4, 0.5, 0.1027137544003226, 0.6, 0.7, 0.3]], [[2, 3, -4, 4, -2, 0]], [[100001, 2, -2, 0]], [[0.5, 0.75, 0.7, 0.1, 0.2, 0.3, 0.4, 0.5, 1.5, 0.6, 0.7]], [[-5, -2, 2, 5]], [[-1]], [[2, 3, -3, 4, -2, 0, -2]], [[1, 9, 10, 100, 1000, 10000, 100000, 10000, 1000]], [[2.5, 1.5, 0]], [[100000, 3]], [[0.5, 0.75, 0.1, 0.2, 0.3, 0.4, 0.5, 0.1027137544003226, 0.6, 0.7, 0.3, 0.7]], [[2, 3, -3, 4, -2, 0, -3]], [[-2, 2, -1, 5]], [[0.5, 0.75, 1.5, 0.2, 0.2734396265136305, 0.3, 0.4, 0.5, 0.6, 0.7]], [[1, 10, 100, 1000, 10000, -9]], [[1.6805641411244991, 2.5, 1.5, 0]], [[3000000, 2, 3, 4, 0, 1]], [[0, 6, 5, 5]], [[1, 10, 100, 1000, 10000, 100000, 100000, 1]], [[2.5, 0, 2.5]], [[-6, 0]], [[1000000, 2000000, 3000000, -1000000, -1000000, 3000000]], [[2, 3, -2, 0, 3]], [[0.5, 0.75, 0.1, 0.2, 0.3, 0.4, 0.2734396265136305, 0.5, 0.1027137544003226, 1.0039341653341238, 0.3, 0.7]], [[2, 3, -6, -2, 0]], [[1]], [[-9, 1000000, 2000000, 3000000, -1000000]], [[-5, -1, 2, 5]], [[5, 5, 1, 5]], [[100000, 2, 4]], [[1, 10, 101, 100, 1000, 10000, -9]], [[2, 3, 0, 2]], [[2, 3, -2, 0, 3, 3]], [[-1, -2, -1, -3, -4, -5, -6, -8, -8, -9, -10, -1]], [[1000000, 2000000, -9, -1000000, 1000000, 2000000]], [[0.5, 0.75, 0.1, 0.2, 0.3, 0.3408682932336746, 0.4, 0.2734396265136305, 0.5, 0.1027137544003226, 1.0039341653341238, 0.3, 0.7]], [[2, 3, 0, 100000, 2]], [[1000000, -1000000, 1000000]], [[-1, -2, -1, -3, -4, -5, -6, -8, -8, -9, -10, 9, -1]], [[2.5, 1.5, 0, 1.5]], [[2, 3, 4, -2, -10, 0, 2]], [[0, 0, 1000000, 0, 0]], [[1, 1]], [[2, 3, 4, 1, -2, 0]], [[100000, -2, 3, 100000]], [[2, 3, 0, -10, -2, 0, 2]], [[1.6805641411244991, 1.5, 0]], [[3]], [[2.5, 1.5]], [[1, 11, 101, 100, 1000, 10000, -9, 1]], [[1.6805641411244991, 1.6805641411244991]], [[-1, -2, -1, -3, -4, -5, -7, -8, -9, -10, -1]], [[1000000, 5]], [[1, 10, 100, 1000, -9, 9999, -9]], [[-6, -6]], [[2, -2, 3, -6, -2]], [[0.5, 0.75, 0.1, 0.2, 0.75, 0.4, 0.5, 0.6, 0.7]], [[2, 3, 4, -1, 1]], [[2000000, -9, -1000000, 1000000]], [[1, 10, 100, 1000, 100000]], [[-1000000, 1, 10, 100, 1000, -9, -9]], [[1, 3, 4, -2, -10, 0, 2]], [[2, 3, 4, -2, -10, 0, 2, -3, 2]], [[1, 10, 100, 10000, 100000, 100000, 1]], [[2.5, 0.1027137544003226, 1.5, 0]], [[2, 3, 0, -10, -2, 0, 3, 2]], [[1000001, 2000000, -9, -1000000, 1000000]], [[2, 2, 3, 0, -2, 0, 2]], [[1, 10, 100, 10000, 100000, 1]], [[2, 1, -2, 0, -2]], [[2.5, 1.5, 0, 1]], [[-5, -1, 1, 5]]]
results = [-67.2, -2000.0, 1710.0, 200000.0, -0.0, 2.1000000000000006e-05, 166666666666666.66, 362880.0, 0.0, 0.0, -1.5e+24, 156.25, 24.0, -40.0, 0.0, 0.0, 0.0, 0.0, 0.0, 450000.0, 1.4285714285714287e+19, 1428571428571428.5, 0.0, 0.0, 1.2e+30, -100800.0, -6.666666666666666e+17, 100000.0, 0.0, 3.6e+24, 544320.0, 0.0, 5.168008941107618e-06, 302400.0, 0.0, 0.0, -500000000000.0, 41.666666666666664, 12.5, 0.0, 15000150000.0, 5.294427158634811e-07, 0.0, 0.0, 1.8040909090909085e-05, 25.0, -1.0, 0.0, 1e+22, 0.0, 150000.0, 3.39725742679067e-07, 0.0, 5.0, 7.752013411661425e-05, -15000000000.0, 0.0, 0.0, 0.0, 1.25e+19, 0.0, 0.0, 3e+36, 0.0, 2.2204748199748898e-07, 0.0, 1.0, 1.08e+25, 12.5, 31.25, 266666.6666666667, -1298571428571.4285, 0.0, 0.0, 345600.0, 6e+30, 6.986671957414076e-08, 0.0, -3.333333333333333e+17, 2871138.4615384615, 0.0, 0.0, 0.0, 0.5, 0.0, -15000000000.0, 0.0, 0.0, 3.0, 1.875, -1249875000000.0, 1.4121479162167627, -54981.818181818184, 2500000.0, 115702714285.71428, 18.0, -28.8, 5.25e-05, -4.8, 4.5e+18, 20000000000.0, -11571428571428.572, 0.0, 0.0, 1.4285714285714286e+16, 0.0, 0.0, 3.6000036e+24, 0.0, 166666666666.66666, 0.0, 0.0, 6.25]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(multiply_num(*inp), exp, 0.0001)
| OK=True
==================== Problem #53 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert the given decimal number to its binary equivalent, represented as a string with no leading zeros.
Your answer will be tested on test cases like:
assert decimal_to_binary(8) == '1000'
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert the given decimal number to its binary equivalent, represented as a string with no leading zeros.
Your answer will be tested on test cases like:
assert decimal_to_binary(8) == '1000'
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert the given decimal number to its binary equivalent, represented as a string with no leading zeros.
Your answer will be tested on test cases like:
assert decimal_to_binary(8) == '1000'
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert the given decimal number to its binary equivalent, represented as a string with no leading zeros.
Your answer will be tested on test cases like:
assert decimal_to_binary(8) == '1000'
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert the given decimal number to its binary equivalent, represented as a string with no leading zeros.
Your answer will be tested on test cases like:
assert decimal_to_binary(8) == '1000'
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called decimal_to_binary that converts a given decimal number into its binary equivalent as a string, without leading zeros. Let's think about how to approach this.
First, I remember that Python has built-in functions for converting numbers to binary. Like, bin(8) gives '0b1000'. But the problem says the output should be a string without leading zeros. So, the function needs to return the binary digits as a string, starting with '1' unless the input is zero, which should return '0'.
Wait, but the test case given is decimal_to_binary(8) == '1000'. So for 8, which is 2^3, the binary is 1000. So the function needs to strip off the '0b' prefix and also ensure there are no leading zeros.
But how to handle the case when the input is zero? Because if the input is 0, the binary should be '0', not an empty string or something else.
So the steps I need to take are:
1. Check if the input number is 0. If so, return '0'.
2. Otherwise, convert the number to binary using bin(), remove the '0b' prefix, and then return the string.
Wait, but bin(0) returns '0b0', so stripping the prefix would leave '0', which is correct. So maybe the code can be as simple as:
def decimal_to_binary(n):
return bin(n)[2:]
Wait, let's test this. For n=8, bin(8) is '0b1000', so [2:] gives '1000' which matches the test case. For n=0, bin(0) is '0b0', so [2:] is '0', which is correct. What about numbers like 1? bin(1) is '0b1' → '1', which is correct. What about 2? bin(2) is '0b10' → '10', which is correct. So this seems to handle all cases.
But wait, what if the input is a negative number? The problem says "decimal number", but the examples use positive numbers. The problem statement might assume that the input is a non-negative integer. So the function is supposed to handle decimal numbers, but perhaps the input is a non-negative integer. So the code can assume that the input is a non-negative integer.
So the function can be written as:
def decimal_to_binary(n):
return bin(n)[2:]
But wait, the problem says "decimal number" which could be a float. But the example uses 8, which is an integer. The problem might be expecting to handle integers only. Because converting a float to binary is more complicated. However, the problem says "given decimal number" but the sample input is an integer. Let me check the problem statement again.
The target question says: "Write a function to convert the given decimal number to its binary equivalent..." but the test case is for 8, which is an integer. So perhaps the function is supposed to take an integer as input. So the code can assume that the input is a non-negative integer.
Therefore, the code is straightforward. But let me check for n=0. The code returns '0', which is correct.
So the function can be written as:
def decimal_to_binary(n):
return bin(n)[2:]
But wait, what if the input is a float? For example, 8.0. But the problem's test case uses 8 as an integer. The problem says "decimal number", but in Python, decimal numbers can be integers or floats. However, the function's parameter is probably expected to be an integer. For example, if someone passes 8.0, bin(8.0) would throw an error. But the problem's test case uses 8, which is an integer. So perhaps the function is intended to take an integer. Therefore, the code is correct.
So the code is as simple as that. Therefore, the Python function is as follows.
```python
def decimal_to_binary(n):
return bin(n)[2:]
```
----------------------------------------------
Result: Pred=def decimal_to_binary(n):
return bin(n)[2:] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[8], [18], [7], [0], [-5], [999999999999999999999999999999999999999999], [-1000000000000000000000000000000000000000000], [-33], [False], [-1], [-1000000000000000000000000000000000000000001], [999999999999999999999999999999999999999998], [-999999999999999999999999999999999999999999], [True], [-6], [-68], [-34], [-1000000000000000000000000000000000000000002], [1000000000000000000000000000000000000000000], [2], [26], [1], [-69], [80], [-87], [-2], [-3], [79], [-7], [-1000000000000000000000000000000000000000003], [-999999999999999999999999999999999999999998], [3], [-999999999999999999999999999999999999999997], [-999999999999999999999999999999999999999996], [4], [1000000000000000000000000000000000000000001], [1000000000000000000000000000000000000000002], [25], [-97], [-35], [27], [999999999999999999999999999999999999999997], [28], [81], [-70], [-32], [55], [78], [77], [-999999999999999999999999999999999999999993], [-24], [-96], [-71], [-86], [-23], [-25], [24], [29], [-72], [86], [82], [46], [-98], [-26], [-95], [30], [23], [56], [999999999999999999999999999999999999999996], [-999999999999999999999999999999999999999995], [-4], [85], [-36], [57], [87], [58], [83], [-1000000000000000000000000000000000000000004], [999999999999999999999999999999999999999995], [84], [54], [20], [31], [-999999999999999999999999999999999999999994], [-73], [-37], [-22], [45], [13], [-74], [75], [88], [71], [-31], [-99], [-100], [22], [76], [14], [59], [-88], [74], [-1000000000000000000000000000000000000000005], [-94], [-49], [1000000000000000000000000000000000000000003], [-93]]
results = ['1000', '10010', '111', '0', '-101', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111111', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000000', '-100001', '0', '-1', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000001', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111110', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111111', '1', '-110', '-1000100', '-100010', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000010', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000000', '10', '11010', '1', '-1000101', '1010000', '-1010111', '-10', '-11', '1001111', '-111', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000011', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111110', '11', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111101', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111100', '100', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000001', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000010', '11001', '-1100001', '-100011', '11011', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111101', '11100', '1010001', '-1000110', '-100000', '110111', '1001110', '1001101', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111001', '-11000', '-1100000', '-1000111', '-1010110', '-10111', '-11001', '11000', '11101', '-1001000', '1010110', '1010010', '101110', '-1100010', '-11010', '-1011111', '11110', '10111', '111000', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111100', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111011', '-100', '1010101', '-100100', '111001', '1010111', '111010', '1010011', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000100', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111011', '1010100', '110110', '10100', '11111', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111000111111111111111111111111111111111111111010', '-1001001', '-100101', '-10110', '101101', '1101', '-1001010', '1001011', '1011000', '1000111', '-11111', '-1100011', '-1100100', '10110', '1001100', '1110', '111011', '-1011000', '1001010', '-10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000101', '-1011110', '-110001', '10110111101010111100011000100111000001010000001100000101101011011111000101001010001111011001111001000000000000000000000000000000000000000011', '-1011101']
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(decimal_to_binary(*inp), exp, 0)
| OK=False
==================== Problem #54 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the next smallest palindrome of a specified integer, returned as an integer.
Your answer will be tested on test cases like:
assert next_smallest_palindrome(99)==101
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the next smallest palindrome of a specified integer, returned as an integer.
Your answer will be tested on test cases like:
assert next_smallest_palindrome(99)==101
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the next smallest palindrome of a specified integer, returned as an integer.
Your answer will be tested on test cases like:
assert next_smallest_palindrome(99)==101
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the next smallest palindrome of a specified integer, returned as an integer.
Your answer will be tested on test cases like:
assert next_smallest_palindrome(99)==101
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the next smallest palindrome of a specified integer, returned as an integer.
Your answer will be tested on test cases like:
assert next_smallest_palindrome(99)==101
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called next_smallest_palindrome that takes an integer and returns the next smallest palindrome. Let's think about how to approach this.
First, what's a palindrome? A number that reads the same forwards and backwards. For example, 121 is a palindrome. The next smallest palindrome after 99 is 101, as given in the test case.
So the problem is to find the smallest palindrome larger than the given number. How do I generate that?
Hmm, one straightforward approach is to start checking each number greater than the input until I find a palindrome. But for large numbers, this might be inefficient. However, given that the constraints aren't specified, maybe this approach is acceptable for simplicity.
Wait, but for numbers like 999, the next palindrome is 1001. So incrementing until we find a palindrome could work, but maybe there's a smarter way.
Alternatively, I can generate the next palindrome by considering the left half of the number and mirroring it. For example, for even length numbers, take the left half and mirror it. For odd lengths, take the left half (including the middle digit) and mirror the left part. But handling all cases might be complex.
But perhaps for the sake of simplicity, given that the input isn't too big, the brute-force approach is easier to code correctly. Let's think about that.
The steps would be:
1. Check if the current number is a palindrome. If not, increment by 1 and check again.
2. Repeat until a palindrome is found.
But how to check if a number is a palindrome? Well, convert the number to a string and check if it's equal to its reverse.
Yes. So the helper function is_palindrome(n) can be written as:
def is_palindrome(n):
s = str(n)
return s == s[::-1]
Then, the main function would be:
def next_smallest_palindrome(n):
candidate = n + 1
while True:
if is_palindrome(candidate):
return candidate
candidate += 1
But wait, what about the test case 99? Let's see: 99 + 1 is 100. Check if 100 is a palindrome. 100 reversed is 001, which is '100' reversed is '001' but as a string, it's '100' vs '001' which are not equal. So the code would check 100, 101. 101 is a palindrome, so returns 101. Which is correct.
Another test case: input 123. Next palindrome is 131? Or 121? Wait, 123 is not a palindrome. The next one would be 131? Let's see. Let's think: 123, check 124, 125... up to 131. So the code would find 131.
But what about numbers like 11? The next would be 22. But if the input is 11, the code would check 12, 13... up to 22. Which is correct.
But for large numbers, this approach could be slow. For example, if the input is 999999, the next palindrome is 1000001. The code would have to check 999999+1=1000000, which is not a palindrome, then 1000001 which is. So it would take two steps. So for numbers with a lot of 9s, this approach is okay.
But for numbers like 1999999999999, the next palindrome is 2000000000002. The code would have to check each number until that, which could take a while. However, given that Python can handle large integers, and for the problem's purposes, perhaps this is acceptable.
But maybe there's a more efficient way. However, given the time constraints and the need to code it quickly, perhaps the brute-force approach is easier to implement correctly.
So, the code would be:
Implement the helper function, then loop.
Wait, but the function is supposed to return the next smallest palindrome. So the code would be:
def next_smallest_palindrome(n):
def is_palindrome(x):
s = str(x)
return s == s[::-1]
candidate = n + 1
while True:
if is_palindrome(candidate):
return candidate
candidate += 1
But let's test this with the sample input. For 99, returns 101. Which is correct.
Another test case: 121. Next is 131. Let's see. 121+1=122, check if it's a palindrome. 122 reversed is 221, no. Then 123, 124... up to 131. So yes.
Another test case: 11. Next is 22. Correct.
What about 0? Well, the problem says specified integer. Assuming input is a positive integer. But perhaps the function needs to handle 0? Well, the problem says "specified integer", but the sample test case uses 99. Let's assume input is a positive integer. But if the input is 0, the next palindrome is 1. But the code would handle that.
But perhaps the function needs to handle numbers like 1, which would return 2? Wait, 1 is a palindrome. The next smallest palindrome would be 2? Or is the function supposed to return the next larger palindrome? The problem says "next smallest palindrome of a specified integer". So if the input is a palindrome, the next one would be the next higher palindrome.
For example, if input is 121, the next is 131. So the code would work as intended.
But what if the input is 999? The code would check 1000, which is not a palindrome, then 1001, which is. So returns 1001. Correct.
So this approach seems to handle all cases. However, for very large numbers, this could be slow. But given that the problem's test cases may not be too big, this approach is acceptable.
So the code would be as written. Now, code it as a self-contained function. The code needs to be in a markdown code block.
But the problem says that the function must be written as a Python script. So the code would be:
def next_smallest_palindrome(n):
def is_palindrome(x):
s = str(x)
return s == s[::-1]
candidate = n + 1
while True:
if is_palindrome(candidate):
return candidate
candidate += 1
But wait, what about numbers like 9999999999999999999 (many 9s)? The code would have to check each number until it finds the next palindrome, which could take a while. However, given that the problem's test cases may not include such cases, and the code is correct, perhaps this is acceptable.
So the code should work for the given test case and others. Let's test the sample input.
Sample input: 99. The code returns 101. Correct.
Another test case: 101. The next would be 111. Let's see. 101+1=102, check each until 111. So yes.
Another test case: 111. Next is 121. Correct.
So the code seems to work. Therefore, the code is as written.
```python
def next_smallest_palindrome(n):
def is_palindrome(x):
s = str(x)
return s == s[::-1]
candidate = n + 1
while True:
if is_palindrome(candidate):
return candidate
candidate += 1
```
----------------------------------------------
Result: Pred=def next_smallest_palindrome(n):
def is_palindrome(x):
s = str(x)
return s == s[::-1]
candidate = n + 1
while True:
if is_palindrome(candidate):
return candidate
candidate += 1 | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[99], [1221], [120], [0], [45678], [1], [45679], [2], [3], [45681], [4], [5], [45683], [45682], [45677], [6], [45676], [45675], [45680], [34], [45674], [33], [45673], [7], [32], [8], [58], [45672], [57], [55], [9], [31], [36], [56], [45684], [30], [29], [87], [45671], [40], [45685], [54], [35], [10], [45670], [96], [45669], [28], [11], [97], [59], [98], [27], [37], [45686], [41], [60], [53], [13], [26], [14], [52], [51], [25], [12], [50], [24], [85], [23], [45687], [39], [86], [88], [61], [38], [45668], [95], [84], [45667], [22], [45688], [42], [45666], [89], [15], [83], [45665], [90], [91], [49], [100], [45689], [94], [45664], [82], [62], [81], [16], [93], [101], [80], [102], [20], [48]]
results = [101, 1331, 121, 1, 45754, 2, 45754, 3, 4, 45754, 5, 6, 45754, 45754, 45754, 7, 45754, 45754, 45754, 44, 45754, 44, 45754, 8, 33, 9, 66, 45754, 66, 66, 11, 33, 44, 66, 45754, 33, 33, 88, 45754, 44, 45754, 55, 44, 11, 45754, 99, 45754, 33, 22, 99, 66, 99, 33, 44, 45754, 44, 66, 55, 22, 33, 22, 55, 55, 33, 22, 55, 33, 88, 33, 45754, 44, 88, 99, 66, 44, 45754, 99, 88, 45754, 33, 45754, 44, 45754, 99, 22, 88, 45754, 99, 99, 55, 101, 45754, 99, 45754, 88, 66, 88, 22, 99, 111, 88, 111, 22, 55]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(next_smallest_palindrome(*inp), exp, 0)
| OK=True
==================== Problem #55 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the kth element in the given array using 1-based indexing.
Your answer will be tested on test cases like:
assert kth_element([12,3,5,7,19], 2) == 3
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the kth element in the given array using 1-based indexing.
Your answer will be tested on test cases like:
assert kth_element([12,3,5,7,19], 2) == 3
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the kth element in the given array using 1-based indexing.
Your answer will be tested on test cases like:
assert kth_element([12,3,5,7,19], 2) == 3
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the kth element in the given array using 1-based indexing.
Your answer will be tested on test cases like:
assert kth_element([12,3,5,7,19], 2) == 3
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the kth element in the given array using 1-based indexing.
Your answer will be tested on test cases like:
assert kth_element([12,3,5,7,19], 2) == 3
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called kth_element that takes an array and a number k, and returns the kth element using 1-based indexing. Let me think about how arrays work in Python.
Wait, in Python, lists are 0-indexed. So if the problem uses 1-based indexing, then for example, if k is 1, we should return the first element, which is index 0 in Python. So the function needs to adjust k by subtracting 1 to get the correct index.
So the steps are: take the array, check that k is within the valid range. But the problem might not require handling invalid k values since the test case given has k=2 and the array has enough elements. However, maybe the function should handle cases where k is out of bounds? But the problem statement doesn't mention that, so perhaps we can assume that k is valid.
So the function would be straightforward. For example, given the array [12,3,5,7,19], the second element (k=2) is 3. So the code would be something like:
def kth_element(arr, k):
return arr[k-1]
Wait, but what if the array is empty or k is larger than the array length? But according to the problem's test case, it's expected that the function works for valid inputs. So the function is simple as that.
Let me test with the sample input. The array is [12,3,5,7,19], k=2. The 2nd element is 3. The code returns arr[1], which is 3. Correct.
So the code is just returning the element at index k-1. So the function is simple. Now, I need to write this in Python, making sure that the code is self-contained. The user provided an example of a code block with import math and a function. But in this case, no imports are needed. So the code would be:
def kth_element(arr, k):
return arr[k-1]
But wait, maybe the problem expects some error checking? However, the problem's test case doesn't include any such checks, and the problem statement says to write the function to find the kth element. So assuming that k is valid, this code should work.
So the final answer is the function that returns arr[k-1].
```python
def kth_element(arr, k):
return arr[k-1]
```
----------------------------------------------
Result: Pred=def kth_element(arr, k):
return arr[k-1] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[12, 3, 5, 7, 19], 2], [[17, 24, 8, 23], 3], [[16, 21, 25, 36, 4], 4], [[100, 99, 98, 97, 96], 5], [[50, 40, 30, 20, 10], 1], [[1000, 999, 998, 997, 996], 3], [[1000000, 500000, 100000, 50000, 10000], 4], [[50, 40, 30, 20, 10, 40], 1], [[100, 99, 98, 20, 97, 96], 5], [[100, 99, 98, 20, 97, 96], 6], [[100, 99, 98, 97, 96, 98], 5], [[51, 40, 99, 41, 30, 41, 20, 10], 1], [[500000, 100000, 50000, 10000], 4], [[1000, 999, 998, 997, 996, 999], 3], [[100, 99, 98, 97, 96], 4], [[100, 100, 98, 20, 97, 96, 100], 7], [[500000, 500000, 100000, 50000, 10000], 4], [[50, 40, 10, 20, 10, 40], 4], [[100, 99, 98, 98, 97, 96], 5], [[100, 99, 98, 20, 97], 5], [[100, 99, 96, 20, 97, 96], 6], [[100, 99, 96, 20, 97, 96], 5], [[100, 99, 99, 98, 97, 96], 4], [[51, 40, 99, 41, 30, 41, 20, 10], 7], [[100, 96, 20, 97, 96], 4], [[1000, 3, 999, 998, 997, 996, 999], 3], [[999, 100, 99, 98, 97, 96], 5], [[100, 99, 99, 98, 97], 4], [[1000, 3, 999, 998, 997, 996, 999], 4], [[100, 99, 99, 98, 96], 4], [[100, 99, 98, 99, 20, 97], 5], [[100, 99, 98, 20, 97, 100], 5], [[1000, 999, 998, 997, 996, 999], 4], [[51, 40, 99, 20, 41, 30, 41, 20, 10], 1], [[100, 99, 98, 97, 96, 98], 6], [[1000, 3, 999, 998, 997, 996, 998], 4], [[7, 100, 100, 98, 20, 97, 96, 100], 7], [[100, 99, 98, 97, 1000000, 96], 4], [[100, 19, 96, 20, 97, 96], 4], [[7, 100, 100, 98, 97, 19, 96, 100], 7], [[100, 99, 98, 20, 7, 97, 100], 4], [[100, 99, 98, 20, 96, 96], 5], [[500000, 100000, 50000, 10000], 3], [[7, 100, 100, 98, 97, 19, 96, 100], 8], [[7, 100, 100, 98, 97, 19, 96, 100], 3], [[51, 40, 99, 41, 30, 20, 10], 1], [[50, 997, 40, 30, 20, 10], 1], [[100, 99, 98, 97, 1000000, 96], 2], [[100, 95, 1, 98, 97, 1000000, 96], 4], [[51, 40, 99, 41, 30, 20, 10], 2], [[100, 100, 98, 20, 97, 96, 10000], 1], [[100, 99, 99, 98, 97], 5], [[100, 99, 98, 98, 97, 96], 6], [[100, 100, 98, 20, 97], 5], [[100, 99, 96, 19, 97, 96], 4], [[50, 40, 30, 20, 11], 1], [[100, 96, 99, 97, 20, 97, 96], 7], [[100, 99, 96, 10000, 20, 96], 3], [[50, 40, 30, 20, 7], 1], [[1000, 3, 999, 998, 997, 996, 999, 999], 3], [[100, 99, 98, 98, 97, 96, 100], 5], [[50, 40, 6, 20, 10, 40], 2], [[7, 100, 100, 98, 20, 97, 96, 100, 97], 7], [[100, 99, 96, 19, 97, 96, 99], 4], [[100, 99, 98, 4, 96, 96], 5], [[100, 99, 98, 20, 95, 96], 5], [[100, 19, 96, 20, 97, 96, 96], 4], [[41, 100, 100, 98, 20, 97, 96, 10000], 1], [[7, 100, 100, 6, 98, 97, 19, 96, 100], 8], [[7, 100, 100, 98, 20, 97, 96, 100, 100], 7], [[50, 997, 97, 40, 30, 20, 10], 1], [[100, 96, 20, 96, 96], 5], [[1000, 998, 997, 996, 999], 3], [[7, 51, 100, 98, 20, 97, 96, 100], 7], [[100, 19, 30, 20, 97, 96], 4], [[1000, 3, 999, 998, 997, 5, 996, 999], 3], [[7, 100, 100, 98, 11, 97, 96, 100, 100], 7], [[100, 99, 96, 20, 97, 95], 6], [[7, 100, 100, 98, 20, 97, 96, 100, 100], 6], [[100, 98, 98, 97, 96], 5], [[100, 99, 98, 98, 97, 96, 100, 99], 5], [[50, 40, 20, 10, 40], 1], [[51, 40, 99, 41, 30, 41, 20, 10], 6], [[51, 40, 99, 20, 41, 30, 41, 20, 10], 7], [[7, 100, 100, 98, 20, 30, 96, 100], 7], [[7, 51, 100, 98, 20, 30, 97, 96, 100], 7], [[101, 99, 98, 97, 96], 4], [[100, 99, 99, 98, 96], 3], [[50, 40, 20, 10, 40, 20], 1], [[50, 40, 20, 7], 1], [[100, 99, 98, 20, 95, 96], 4], [[7, 100, 100, 98, 20, 97, 10000, 96, 100], 7], [[97, 100, 99, 98, 97, 96, 98], 6], [[100, 96, 20, 97, 998, 96], 4], [[51, 3, 999, 998, 997, 996, 999], 3], [[101, 99, 98, 97, 96], 1], [[7, 100, 41, 98, 20, 30, 96, 100], 7], [[7, 100, 100, 96, 97, 19, 96, 100], 8], [[7, 51, 100, 20, 20, 97, 96, 100], 7], [[6, 7, 100, 100, 98, 97, 19, 96, 100], 7], [[100, 99, 98, 4, 96], 5], [[51, 3, 999, 998, 997, 996, 999], 4], [[7, 100, 98, 97, 19, 96, 100, 100], 7], [[100, 99, 98, 20, 7, 97, 100], 5], [[1000000, 100, 96, 20, 97, 96], 4], [[100, 99, 98, 20, 95], 5], [[1000, 998, 997, 996], 3]]
results = [3, 8, 36, 96, 50, 998, 50000, 50, 97, 96, 96, 51, 10000, 998, 97, 100, 50000, 20, 97, 97, 96, 97, 98, 20, 97, 999, 97, 98, 998, 98, 20, 97, 997, 51, 98, 998, 96, 97, 20, 96, 20, 96, 50000, 100, 100, 51, 50, 99, 98, 40, 100, 97, 96, 97, 19, 50, 96, 96, 50, 999, 97, 40, 96, 19, 96, 95, 20, 41, 96, 96, 50, 96, 997, 96, 20, 999, 96, 95, 97, 96, 97, 50, 41, 41, 96, 97, 97, 99, 50, 50, 20, 10000, 96, 97, 999, 101, 96, 100, 96, 19, 96, 998, 100, 7, 20, 95, 997]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(kth_element(*inp), exp, 0)
| OK=True
==================== Problem #56 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a snake case string to camel case string.
Your answer will be tested on test cases like:
assert snake_to_camel('python_program')=='PythonProgram'
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a snake case string to camel case string.
Your answer will be tested on test cases like:
assert snake_to_camel('python_program')=='PythonProgram'
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a snake case string to camel case string.
Your answer will be tested on test cases like:
assert snake_to_camel('python_program')=='PythonProgram'
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a snake case string to camel case string.
Your answer will be tested on test cases like:
assert snake_to_camel('python_program')=='PythonProgram'
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a snake case string to camel case string.
Your answer will be tested on test cases like:
assert snake_to_camel('python_program')=='PythonProgram'
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called snake_to_camel that converts a snake case string to camel case. Let's think about how snake case and camel case work.
Snake case uses underscores to separate words, like 'python_program'. Camel case doesn't use underscores; instead, each word after the first starts with a capital letter. So the example given is 'python_program' becoming 'PythonProgram'.
So the steps I need to take are: split the snake case string into individual words based on the underscores. Then, capitalize the first letter of each word except the first one. Wait, no—wait, in camel case, the first word is lowercase, and subsequent words are capitalized. Wait, the example shows that 'python_program' becomes 'PythonProgram'. Wait, the first word is 'python' which becomes 'Python' (capital P), and the second word 'program' becomes 'Program' (capital P). Wait, but in camel case, the first letter of the entire string is lowercase? Or uppercase?
Wait, the example given is that 'python_program' becomes 'PythonProgram'. So the first letter of the first word is uppercase, and the first letter of the second word is uppercase. Wait, but that's actually PascalCase, not camelCase. Wait, camelCase typically has the first word lowercase, and subsequent words capitalized. Like 'pythonProgram'. But the example here expects 'PythonProgram' which is PascalCase. Hmm, maybe the problem is using camel case to mean PascalCase here. Because the test case shows that the first letter is capitalized.
Wait, the problem says that the test case is assert snake_to_camel('python_program') == 'PythonProgram'. So the first letter of the first word is capitalized. So maybe the function is supposed to convert snake case to PascalCase, where each word is capitalized. But the problem says camel case. Maybe there's a confusion here. But according to the test case, the first letter is uppercase. So the function needs to capitalize the first letter of each word, including the first one.
So, the approach would be: split the string into parts using the underscore as a delimiter. Then, for each part, capitalize the first letter and make the rest lowercase? Or maybe just capitalize the first letter and leave the rest as is? Well, in snake case, the words are lowercase. So for example, 'python_program' is split into ['python', 'program']. Then, each part is capitalized. So 'Python' and 'Program', then concatenated to 'PythonProgram'.
So the steps are: split the string into parts, then capitalize each part's first letter, then join them all together.
But how to split the string? Using the split('_') method. Then, for each part in the split list, capitalize the first letter and lowercase the rest? Or just capitalize the first letter, assuming that the original snake case is all lowercase. For example, if the input is 'hello_world', splitting gives ['hello', 'world'], then each part is capitalized to 'Hello' and 'World', joined to 'HelloWorld'.
But the test case expects 'PythonProgram' for 'python_program', which matches this approach.
So the code would be:
def snake_to_camel(s):
parts = s.split('_')
# capitalize each part and join
return ''.join(part.capitalize() for part in parts)
Wait, but what if there are multiple underscores? Like 'hello__world'? Splitting with split('_') would result in ['hello', '', 'world'], and then capitalizing each part would give 'Hello', '', 'World' which would join to 'HelloWorld'. But maybe that's acceptable. However, the problem says that the input is a snake case string. So perhaps the input is properly formatted, with no consecutive underscores. But the function should handle such cases anyway.
But according to the problem's test case, the function is supposed to work for 'python_program' which splits into two parts. So the code above should work.
Testing the example: 'python_program' split into ['python', 'program'], each part is capitalized to 'Python' and 'Program', joined to 'PythonProgram', which matches the test case. So that's correct.
So the code would be:
def snake_to_camel(s):
return ''.join(word.capitalize() for word in s.split('_'))
Wait, but what if the input is empty? Well, the problem probably assumes that the input is a valid snake case string. So the function should handle that.
So the code is straightforward. Let me write the function as per that.
So the Python code would be:
def snake_to_camel(s):
return ''.join(word.capitalize() for word in s.split('_'))
But let me test with the example. For 'python_program', split into ['python', 'program'], capitalize each to 'Python' and 'Program', joined to 'PythonProgram' which matches the test case. So that's correct.
Another example: 'hello_world' becomes 'HelloWorld'. Another example: 'my_variable_name' becomes 'MyVariableName'.
Yes, that seems right. So the code should work.
```python
def snake_to_camel(s):
return ''.join(word.capitalize() for word in s.split('_'))
```
----------------------------------------------
Result: Pred=def snake_to_camel(s):
return ''.join(word.capitalize() for word in s.split('_')) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['python_program'], ['python_language'], ['programming_language'], ['___python_program'], ['__12_python__language___'], ['your_programming__langu__age___'], ['another__ex44ample___'], ['_'], ['word'], ['no_underscores'], ['_leading'], ['trailing_'], ['__multiple_consecutive__underscores__'], ['__12_python__languag_'], ['___p_ythonram'], ['your_nprogramming__langu__age___'], ['your_nprogramming_another__ex44ample____langu__age___'], ['__12_pythonno_underscores__languag_'], ['_lwordeading'], ['your_nprogramming_another__ex4no_underscores4ample____langu__age___'], ['your_programming__langu____12_python__languag_age___'], ['__12_pyth_'], ['__1__12_python__languag_2_pythonno_underscores__languag_'], ['___pgram'], ['_lwordeadin__12_python__language___g'], ['your_prtrailing___'], ['__12_pythonno_underscores__langu_ag_'], ['aiN'], ['worod'], ['_lwordeadin__12_python__languaage___g'], ['qaiNnJa'], ['aiN_lwordeading'], ['_lwordeadin__1_2_python__language___g'], ['your_nprogrammi__12_pyth_ng_another__ex4no_underscores4ample____langu__age___your_nprogramming__langu__age___'], ['your_pryour_nprogramming_another__ex4no_underscores4ample____langu__age___iling___'], ['__1____12_pythonno_underscores__langu_ag_12_python__languag_2_pythonno_underscores__languag_'], ['CVh'], ['_leadin_lwordeadin__12_python__languaage___gg'], ['_th_'], ['_lwordeadin__1_2_py__language___g'], ['trailing__12_python__languag__'], ['your_pr_th_ogramming__langu____12_python__languag_age___'], ['your_pryour_nprogramming_another__aiNex4no_underscores4ample____langu__age___iling___'], ['__12_python__language_g__'], ['aiN_lwordeadin__12_python__layour_nprogramming_another__ex4no_underscores4ample____langu__age___wordeading'], ['_lwordeadin__1_2_py__lawordnguaage___g'], ['__12_pythonno_underscores__lanuag_'], ['_____12_pyth_ram'], ['__1____12_pythonno_underscores__langu_a_lwordeadingg_12_python__languag_2_pythonno_underscores__languag_'], ['__'], ['_leadilng'], ['___python_progr__1____12_pythonno_underscores__langu_ag_12_python__l__languag_m'], ['__12_pythonno_underscores__langua_g_'], ['your_nprogramming_another__ex44ample_____12_pythonno_underscores__languag__langu__age___'], ['__12_python__l__'], ['__multiprlne_consecutive__underscores__'], ['___12_pyth_'], ['__1____12_pythonno_undngu_a_lwordeadingg_12_python__languag_2_pythonno_underscores__languag_'], ['your_nprogramming_another__ex44ample_____12_py___12_pyth_thonno_underscores__languag__langu__age___'], ['_____multiple_consecutive__underscores__python_program'], ['yo_ur_nprogr_amming_another__ex44ample____langu__age___'], ['_leadin_lwnordeadin__12_python__languaage___gg'], ['jzAx'], ['_leadin____12_pyth_lwordeadin__12_python__languaage___gg'], ['yo_ur_nprogr_amming_another__ex44am__multiprlne_consecutive__underscores__ple___1__12_python__languag_2_pythonno_underscores__languag___langu__age___'], ['__1____12_pythonno_underscores__langu_ag_12_python__languag_2_pythonno_underscores__languag_word'], ['_lwordeadin__12_python__lanuguage___g'], ['trailing___python_progr__1____12_pythonno_underscores__langu_ag_12_python__l__languag_m__12_python__languag__'], ['trailianguag_2_pythonno_underscores__languag__'], ['__1_2_p'], ['_leadil__multiple_consecutive__underscores__ng'], ['__1_2_qaiNnJap'], ['a__1_2_piN_lwordeading'], ['__NnJap'], ['__12_peythonno_underscores__lanuag_'], ['trailinig_'], ['trailiyour_yo_ur_nprogr_amming_another__ex44ample____langu__age___pryour_nprogramming_another__aiNex4no_underscores4ample____langu__ayour_nprogrammi__12_pyth_ng_another__ex4no_underscores4ample____langu__age___your_nprogramming__langu__age___ge___iling___'], ['X'], ['_leadin____12_pyth_lwordeadin__12_python__languaage___g1g'], ['_lwordeadin__1_2_py__lawordnguaage___g__1_2_p'], ['your_programming__langu____1y2_python__languag_age___'], ['your_pr_th_ogramming__langu____12__lwordeadingpython__languag_age___'], ['your_pr_th_ogramming__langu____12_your_programming__langu____1y2_python__languag_age____lwordeadingpython__languag_age___'], ['aiN_lwordeadiwordn__12_python__layour_nprogramming_another__ex4no_underscores4ample____langu__age___wordeading'], ['your_nprogr_lwordeadingammi__12_pyth_ng_another__ex4no_underscores4ample____langu__age___your_nprogramming__langu__age___'], ['___p_ythqaiNnJaonram'], ['12_python__l__'], ['_lwordeadin__12_python__lan_lwordeadin__12_python__languaage___gguaage___g'], ['__12_pythonaiN_lwordeading__l__'], ['trailing__12_python__layo_ur_nprogr_amming_another__ex44ample____langu__age___nguag__'], ['your__12_pythonno_underascores__langu_ag__nprogramming_another__ex4no_underscores4ample____langu__age'], ['your_pryour_nprotrailing__12_python__layo_ur_nprogr_amming_another__ex44ample____langu__age___nguag__gramming_another__ex4no_underscores4ample____langu__age___iling___'], ['__12n_pythonno_un_'], ['_____12_pyth__python_program'], ['_lwon__1__12_python__l__2_python__lanuguage___g'], ['your_programming__langu____12_python__languag_ag___pgram___'], ['____12n_pythonno_un_1_2_p'], ['_lwordeadin__12_python__lanugu_lwordeadingage___g'], ['aiyour_pryour_nprogramming_another__aiNex4no_undersco_lwordeadingres4ample____langu__age___iling___N'], ['__1_d___12_pythonno_underscores__langu_ag_12_python__languag_2_pythonno_underscores__languag_'], ['your_pr_th_ogramming__langu____12_your_programming__langu____1y2_python__languingpython__languag_age___'], ['your_nprogrammi__12__pyth_ng_another__ex4no_underscores4ample____langu__age___your_nprogramming__langu__age___'], ['your_pr_th_ogramming__langu____12_your_programming__langu____1y2_pythotn__languag_age____lwordeadingpython__languag_age___'], ['qaiNnJ_lwordeadin__1_2_py__language________12_pyth_ram'], ['your_pr_th_ogrammingyo_ur_nprogr_amming_another__ex44ample____langu__age_____langu____12_your_programming__langu____h1y2_python__languingpython__languag_age___'], ['____12n_pythonaiNno_un_1_2_p'], ['_lwordeadin__12_python__lanuguage_____pgram_g'], ['AOqPHkjh'], ['_lwon__1__12_python__l__2_python__lanuguage_no_underscores'], ['_____12_pyth_h_python_program_leadin_lwnordeadin__12_python__languaage___g'], ['your_pr_th_ogrammingyo_ur_nprogr_amming_another__ex44ample____langu__age_____ur_programming__langu____h1y2_python__languingpython__languag_age___'], ['your_pryour_nprotrailing__12_python__layo_ur_nprogr_amming_eanother__ex44ample____langu__age___nguag__gramming_another__ex4no_underscores4ample____langu__age___iling___'], ['your_pr_th_ogrammingyo_ur_nprogr_amming_another__ex44ample____langu__age_____ur_programming__langu____h1y2_python__lang__1_d___12_pythonno_underscores__langu_ag_12_python__languag_2_pythonno_underscores__languag_uingpython__languag_age___']]
results = ['PythonProgram', 'PythonLanguage', 'ProgrammingLanguage', '___PythonProgram', '__12Python_Language___', 'YourProgramming_Langu_Age___', 'Another_Ex44ample___', '__', 'Word', 'NoUnderscores', '_Leading', 'Trailing_', '__MultipleConsecutive_Underscores__', '__12Python_Languag_', '___PYthonram', 'YourNprogramming_Langu_Age___', 'YourNprogrammingAnother_Ex44ample___Langu_Age___', '__12PythonnoUnderscores_Languag_', '_Lwordeading', 'YourNprogrammingAnother_Ex4noUnderscores4ample___Langu_Age___', 'YourProgramming_Langu___12Python_LanguagAge___', '__12Pyth_', '__1_12Python_Languag2PythonnoUnderscores_Languag_', '___Pgram', '_Lwordeadin_12Python_Language__G', 'YourPrtrailing___', '__12PythonnoUnderscores_LanguAg_', 'Ain', 'Worod', '_Lwordeadin_12Python_Languaage__G', 'Qainnja', 'AinLwordeading', '_Lwordeadin_12Python_Language__G', 'YourNprogrammi_12PythNgAnother_Ex4noUnderscores4ample___Langu_Age__YourNprogramming_Langu_Age___', 'YourPryourNprogrammingAnother_Ex4noUnderscores4ample___Langu_Age__Iling___', '__1___12PythonnoUnderscores_LanguAg12Python_Languag2PythonnoUnderscores_Languag_', 'Cvh', '_LeadinLwordeadin_12Python_Languaage__Gg', '_Th_', '_Lwordeadin_12Py_Language__G', 'Trailing_12Python_Languag__', 'YourPrThOgramming_Langu___12Python_LanguagAge___', 'YourPryourNprogrammingAnother_Ainex4noUnderscores4ample___Langu_Age__Iling___', '__12Python_LanguageG__', 'AinLwordeadin_12Python_LayourNprogrammingAnother_Ex4noUnderscores4ample___Langu_Age__Wordeading', '_Lwordeadin_12Py_Lawordnguaage__G', '__12PythonnoUnderscores_Lanuag_', '_____12PythRam', '__1___12PythonnoUnderscores_LanguALwordeadingg12Python_Languag2PythonnoUnderscores_Languag_', '___', '_Leadilng', '___PythonProgr_1___12PythonnoUnderscores_LanguAg12Python_L_LanguagM', '__12PythonnoUnderscores_LanguaG_', 'YourNprogrammingAnother_Ex44ample____12PythonnoUnderscores_Languag_Langu_Age___', '__12Python_L__', '__MultiprlneConsecutive_Underscores__', '___12Pyth_', '__1___12PythonnoUndnguALwordeadingg12Python_Languag2PythonnoUnderscores_Languag_', 'YourNprogrammingAnother_Ex44ample____12Py__12PythThonnoUnderscores_Languag_Langu_Age___', '_____MultipleConsecutive_Underscores_PythonProgram', 'YoUrNprogrAmmingAnother_Ex44ample___Langu_Age___', '_LeadinLwnordeadin_12Python_Languaage__Gg', 'Jzax', '_Leadin___12PythLwordeadin_12Python_Languaage__Gg', 'YoUrNprogrAmmingAnother_Ex44am_MultiprlneConsecutive_Underscores_Ple__1_12Python_Languag2PythonnoUnderscores_Languag__Langu_Age___', '__1___12PythonnoUnderscores_LanguAg12Python_Languag2PythonnoUnderscores_LanguagWord', '_Lwordeadin_12Python_Lanuguage__G', 'Trailing__PythonProgr_1___12PythonnoUnderscores_LanguAg12Python_L_LanguagM_12Python_Languag__', 'Trailianguag2PythonnoUnderscores_Languag__', '__12P', '_Leadil_MultipleConsecutive_Underscores_Ng', '__12Qainnjap', 'A_12PinLwordeading', '__Nnjap', '__12PeythonnoUnderscores_Lanuag_', 'Trailinig_', 'TrailiyourYoUrNprogrAmmingAnother_Ex44ample___Langu_Age__PryourNprogrammingAnother_Ainex4noUnderscores4ample___Langu_AyourNprogrammi_12PythNgAnother_Ex4noUnderscores4ample___Langu_Age__YourNprogramming_Langu_Age__Ge__Iling___', 'X', '_Leadin___12PythLwordeadin_12Python_Languaage__G1g', '_Lwordeadin_12Py_Lawordnguaage__G_12P', 'YourProgramming_Langu___1y2Python_LanguagAge___', 'YourPrThOgramming_Langu___12_Lwordeadingpython_LanguagAge___', 'YourPrThOgramming_Langu___12YourProgramming_Langu___1y2Python_LanguagAge___Lwordeadingpython_LanguagAge___', 'AinLwordeadiwordn_12Python_LayourNprogrammingAnother_Ex4noUnderscores4ample___Langu_Age__Wordeading', 'YourNprogrLwordeadingammi_12PythNgAnother_Ex4noUnderscores4ample___Langu_Age__YourNprogramming_Langu_Age___', '___PYthqainnjaonram', '12Python_L__', '_Lwordeadin_12Python_LanLwordeadin_12Python_Languaage__Gguaage__G', '__12PythonainLwordeading_L__', 'Trailing_12Python_LayoUrNprogrAmmingAnother_Ex44ample___Langu_Age__Nguag__', 'Your_12PythonnoUnderascores_LanguAg_NprogrammingAnother_Ex4noUnderscores4ample___Langu_Age', 'YourPryourNprotrailing_12Python_LayoUrNprogrAmmingAnother_Ex44ample___Langu_Age__Nguag_GrammingAnother_Ex4noUnderscores4ample___Langu_Age__Iling___', '__12nPythonnoUn_', '_____12Pyth_PythonProgram', '_Lwon_1_12Python_L_2Python_Lanuguage__G', 'YourProgramming_Langu___12Python_LanguagAg__Pgram___', '____12nPythonnoUn12P', '_Lwordeadin_12Python_LanuguLwordeadingage__G', 'AiyourPryourNprogrammingAnother_Ainex4noUnderscoLwordeadingres4ample___Langu_Age__Iling__N', '__1D__12PythonnoUnderscores_LanguAg12Python_Languag2PythonnoUnderscores_Languag_', 'YourPrThOgramming_Langu___12YourProgramming_Langu___1y2Python_Languingpython_LanguagAge___', 'YourNprogrammi_12_PythNgAnother_Ex4noUnderscores4ample___Langu_Age__YourNprogramming_Langu_Age___', 'YourPrThOgramming_Langu___12YourProgramming_Langu___1y2Pythotn_LanguagAge___Lwordeadingpython_LanguagAge___', 'QainnjLwordeadin_12Py_Language_______12PythRam', 'YourPrThOgrammingyoUrNprogrAmmingAnother_Ex44ample___Langu_Age____Langu___12YourProgramming_Langu___H1y2Python_Languingpython_LanguagAge___', '____12nPythonainnoUn12P', '_Lwordeadin_12Python_Lanuguage____PgramG', 'Aoqphkjh', '_Lwon_1_12Python_L_2Python_LanuguageNoUnderscores', '_____12PythHPythonProgramLeadinLwnordeadin_12Python_Languaage__G', 'YourPrThOgrammingyoUrNprogrAmmingAnother_Ex44ample___Langu_Age____UrProgramming_Langu___H1y2Python_Languingpython_LanguagAge___', 'YourPryourNprotrailing_12Python_LayoUrNprogrAmmingEanother_Ex44ample___Langu_Age__Nguag_GrammingAnother_Ex4noUnderscores4ample___Langu_Age__Iling___', 'YourPrThOgrammingyoUrNprogrAmmingAnother_Ex44ample___Langu_Age____UrProgramming_Langu___H1y2Python_Lang_1D__12PythonnoUnderscores_LanguAg12Python_Languag2PythonnoUnderscores_LanguagUingpython_LanguagAge___']
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(snake_to_camel(*inp), exp, 0)
| OK=False
==================== Problem #57 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the Eulerian number a(n, m).
Your answer will be tested on test cases like:
assert eulerian_num(3, 1) == 4
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the Eulerian number a(n, m).
Your answer will be tested on test cases like:
assert eulerian_num(3, 1) == 4
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the Eulerian number a(n, m).
Your answer will be tested on test cases like:
assert eulerian_num(3, 1) == 4
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the Eulerian number a(n, m).
Your answer will be tested on test cases like:
assert eulerian_num(3, 1) == 4
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the Eulerian number a(n, m).
Your answer will be tested on test cases like:
assert eulerian_num(3, 1) == 4
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function to compute the Eulerian number a(n, m). Let me think about what Eulerian numbers are. From what I remember, Eulerian numbers count the number of permutations of a set of numbers where exactly m elements are smaller than their successor. Or maybe it's the number of permutations with a certain number of descents. Wait, right, Eulerian numbers are related to permutations with a specific number of descents. A descent is a position where the next element is smaller. So, the Eulerian number is the number of permutations of 1 to n with exactly m descents.
But how do I compute that? Let me think about the formula. There's a recurrence relation for Eulerian numbers. The recurrence is something like a(n, m) = (n - m) * a(n-1, m-1) + (m + 1) * a(n-1, m). Or maybe I have the coefficients mixed up. Alternatively, there's another formula involving sums with binomial coefficients and powers. Oh right, there's an explicit formula: a(n, m) = sum_{k=0}^m (-1)^k * C(n+1, k) * (m + 1 - k)^n. Wait, but I'm not sure. Let me check.
Alternatively, I remember that the Eulerian numbers can be computed using dynamic programming. The base cases would be a(0, 0) = 1, and for n >= 1, a(n, m) can be calculated using the recurrence. Wait, but for n=1, the only permutation is [1], which has 0 descents, so a(1, 0) = 1, and a(1, m) for m>0 is 0.
Let me think about the recurrence again. The correct recurrence is a(n, m) = (n - m) * a(n-1, m-1) + (m + 1) * a(n-1, m). But I need to confirm this. Let me check with the sample input given. The test case is eulerian_num(3, 1) == 4. Let's see:
For n=3, m=1. Let's compute using the recurrence. Let's assume that the base cases are handled correctly. For example, a(1, 0) = 1, a(1, m) for m>0 is 0. For n=2, a(2, 0) = 1 (permutation [1,2] has 0 descents), a(2, 1) = 1 (permutation [2,1] has 1 descent). Then for n=3, m=1:
a(3, 1) = (3-1)*a(2, 0) + (1+1)*a(2, 1) = 2*1 + 2*1 = 4. Which matches the sample. So the recurrence seems correct.
So the approach could be to use dynamic programming, building up a table of a(n, m) values up to the given n and m. However, for larger values of n and m, this could be computationally intensive, but for the purposes of the problem, perhaps it's manageable.
But how do I implement this in Python? Let's think about the function. The function eulerian_num(n, m) should return the correct value. Let's handle the base cases first. For example, if m is less than 0 or greater than n-1, return 0. Because for a permutation of n elements, the number of descents can be between 0 and n-1. So if m is outside this range, the answer is 0.
So for the base cases:
- If n == 0 and m == 0: return 1? Or is n >= 1? Wait, the problem says that the test case is eulerian_num(3, 1) == 4. So the function is for n ≥ 1? Or maybe n can be zero. Let me check the definition. The Eulerian numbers are defined for n ≥ 1 and m ≥ 0, but for n=0, perhaps a(0, 0) is 1. However, the problem's test case uses n=3, m=1. So in the function, we need to handle cases where m is in the valid range.
So the base case for the recurrence would be when n=1. For n=1, m can be 0 (a(1, 0) = 1) or any other m (return 0). So the function can use memoization or dynamic programming to compute the values.
But how to implement this? Let's think about using memoization. For example, using a memoization dictionary to store computed values. However, for Python, a recursive approach with memoization may not be efficient for large n, but for the problem's test cases, it's acceptable.
Alternatively, we can use dynamic programming with a 2D array. Let's think about the steps.
Another approach is to use the explicit formula. For example, the formula:
a(n, m) = sum_{k=0}^m (-1)^k * C(n+1, k) * (m + 1 - k)^n
Wait, I'm not sure about this formula. Let me check. For example, for n=3, m=1:
sum from k=0 to 1:
k=0: (-1)^0 * C(4, 0) * (1+1 - 0)^3 = 1 * 1 * 2^3 = 8
k=1: (-1)^1 * C(4, 1) * (2 - 1)^3 = -1 *4 *1 = -4
Total sum is 8-4=4. Which matches the sample. So this formula works. So that's a way to compute the Eulerian numbers.
So the formula is a(n, m) = sum_{k=0}^m (-1)^k * C(n+1, k) * (m + 1 -k)^n.
But wait, the formula might be for the Eulerian numbers. So this seems like a viable approach.
So the steps for the function would be:
- Check if m is out of the valid range (0 ≤ m ≤ n-1). If not, return 0.
- Compute the sum over k from 0 to m of (-1)^k * combination(n+1, k) * (m+1 -k)^n.
But how to compute combination(n+1, k)? For that, we can use the math.comb function in Python 3.10 and above. However, if the code is to be compatible with older versions, perhaps we need to implement it ourselves. But assuming that the environment uses Python 3.10+, math.comb is available.
So, the code can be written as follows:
import math
def eulerian_num(n, m):
if m < 0 or m >= n:
return 0
total = 0
for k in range(0, m+1):
sign = (-1)**k
comb = math.comb(n+1, k)
term = (m + 1 - k)**n
total += sign * comb * term
return total
Wait, but let's test this with the sample input. For n=3, m=1:
sum for k=0 to 1.
k=0: sign is 1, comb(4,0)=1, term (1+1 - 0)^3 = 2^3=8 → 1*1*8=8.
k=1: sign is -1, comb(4,1)=4, term (2-1)^3 =1 → -1 *4 *1 = -4. Total is 8-4=4. Correct.
Another test case: Let's see for n=2, m=1. The correct value is 1. Let's compute:
sum k=0 to 1:
k=0: 1 * C(3,0) * (2 - 0)^2 → 1*1*2²=4.
k=1: -1 * C(3,1) * (2-1)^2 → -3 * 1 = -3. Total is 4-3=1. Correct.
Another test case: n=2, m=0. The correct value is 1. Let's compute:
sum k=0 to 0:
k=0: 1 * C(3,0) * (0+1 -0)^2 = 1 *1 *1^2 = 1. So returns 1. Correct.
Another case: n=4, m=1. What is the value? Let me think. The Eulerian numbers for n=4, m=1 is 11. Let me check with the formula.
sum for k=0 to 1:
k=0: 1 * C(5,0) * (2)^4 = 1*1*16 = 16.
k=1: -1 * C(5,1) * (2-1)^4 = -5 * 1 = -5. Total is 11. Which is correct. So yes, this formula works.
So this approach seems correct. Therefore, the code can be written using this formula.
But what about when m is 0? For example, n=3, m=0. The Eulerian number a(3, 0) is 1. Let's compute with the formula:
sum for k=0 to 0:
term is 1 * C(4, 0) * (0+1 -0)^3 → 1*1*1^3=1. So returns 1. Which is correct.
Another case: n=4, m=2. The Eulerian number is 11? Wait, no. Let me check. For n=4, the Eulerian numbers are a(4, 0)=1, a(4,1)=11, a(4,2)=11, a(4,3)=1. So for m=2, it's 11. Let's compute using the formula:
sum for k=0 to 2:
k=0: 1 * C(5,0) * (3)^4 = 1 * 1 * 81 = 81.
k=1: -1 * C(5,1) * (3-1)^4 → -5 * 2^4 = -5*16 = -80.
k=2: 1 * C(5,2) * (3-2)^4 → 10 * 1 = 10. Total is 81-80+10=11. Correct.
So the formula works. Therefore, the code can be written as such.
Now, the code needs to handle cases where m is out of the valid range (0 ≤ m < n). For example, if m is equal to n, then return 0. Because for a permutation of n elements, the maximum number of descents is n-1. So for m >=n, return 0.
So the code first checks if m is less than 0 or m >=n, returns 0. Else, compute the sum.
Now, the code can be written as follows. Also, note that for n=0, but according to the problem's test case, n is at least 1. However, the code should handle n=0. For example, if n=0, then m must be 0. But according to the problem's test case, perhaps n is positive. However, the code should handle all n ≥0.
But according to the problem's test case, the function is called with n=3, m=1. So the code should handle n=0? Let's think. For n=0, the only possible m is 0, but according to the formula, the sum would be for k=0 to 0. But n=0, m=0. The formula would compute sum for k=0 to 0: (-1)^0 * C(0+1, 0) * (0+1 -0)^0 → 1 * 1 * 1^0 = 1. So returns 1. Which is correct, as a(0, 0) is 1. However, the problem's test case may not require handling n=0, but the code can handle it.
So the code is:
import math
def eulerian_num(n, m):
if m < 0 or m >= n:
return 0
total = 0
for k in range(0, m + 1):
sign = (-1) ** k
comb = math.comb(n + 1, k)
term = (m + 1 - k) ** n
total += sign * comb * term
return total
But wait, when n=0 and m=0, the code returns 1. But according to the condition, m >=n is 0 >=0 → which is false. So the code proceeds. For n=0, m=0, the code computes sum for k=0 to 0. Which is correct.
But let's check for n=0, m=0. The code returns 1, which is correct.
But what about for n=1, m=0? The code returns 1. Which is correct. For n=1, m=1, returns 0.
So this code should handle all cases.
But let's check another test case. For example, eulerian_num(4, 1) should be 11. Let's see:
n=4, m=1. The code computes:
sum k=0 to 1.
k=0: 1 * C(5,0) * (2)^4 = 1 *1 *16=16.
k=1: -1 * C(5,1) * (2-1)^4 → -5 *1= -5. Total is 11. Correct.
Yes.
So the code should work. Therefore, this is the correct approach.
```python
import math
def eulerian_num(n, m):
if m < 0 or m >= n:
return 0
total = 0
for k in range(0, m + 1):
sign = (-1) ** k
comb = math.comb(n + 1, k)
term = (m + 1 - k) ** n
total += sign * comb * term
return total
```
----------------------------------------------
Result: Pred=import math
def eulerian_num(n, m):
if m < 0 or m >= n:
return 0
total = 0
for k in range(0, m + 1):
sign = (-1) ** k
comb = math.comb(n + 1, k)
term = (m + 1 - k) ** n
total += sign * comb * term
return total | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[3, 1], [4, 1], [5, 3], [0, 0], [1, 1], [1, 2], [1, 0], [0, 2], [0, 1], [2, 1], [2, 0], [2, 2], [2, 3], [3, 2], [1, 3], [0, 3], [2, 4], [1, 4], [4, 2], [4, 4], [4, 0], [3, 0], [0, 4], [3, 4], [5, 4], [3, 3], [5, 2], [4, 5], [5, 0], [1, 5], [False, True], [5, 5], [5, 1], [True, True], [6, 6], [2, 6], [0, 5], [6, 2], [4, 3], [6, 1], [3, 5], [7, 3], [4, 6], [7, 4], [5, 6], [5, 7], [6, 3], [6, 7], [0, 6], [False, False], [3, 6], [6, 4], [7, 6], [0, 7], [7, 2], [8, 7], [8, 2], [6, 5], [True, False], [7, 0], [2, 7], [8, 5], [6, 0], [0, 8], [4, 8], [7, 1], [8, 1], [7, 7], [4, 7], [2, 5], [8, 4], [10, 9], [9, 9], [10, 3], [10, 10], [3, 9], [10, 2], [2, 8], [8, 3], [5, 8], [9, 10], [8, 8], [2, 9], [4, 9], [9, 6], [7, 8], [8, 9], [1, 8], [1, 10], [11, 10], [5, 9], [11, 9], [5, 11], [9, 2], [7, 5], [8, 0], [6, 8], [1, 9], [8, 6], [9, 8], [9, 4]]
results = [4, 11, 26, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 11, 0, 1, 1, 0, 0, 1, 0, 66, 0, 1, 0, 0, 0, 26, 0, 0, 0, 0, 302, 1, 57, 0, 2416, 0, 1191, 0, 0, 302, 0, 0, 0, 0, 57, 1, 0, 1191, 1, 4293, 1, 1, 1, 0, 4293, 1, 0, 0, 120, 247, 0, 0, 0, 15619, 1, 0, 455192, 0, 0, 47840, 0, 15619, 0, 0, 0, 0, 0, 14608, 0, 0, 0, 0, 1, 0, 2036, 0, 14608, 120, 1, 0, 0, 247, 1, 156190]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(eulerian_num(*inp), exp, 0)
| OK=True
==================== Problem #58 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort each sublist of strings in a given list of lists.
Your answer will be tested on test cases like:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"]))==[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort each sublist of strings in a given list of lists.
Your answer will be tested on test cases like:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"]))==[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort each sublist of strings in a given list of lists.
Your answer will be tested on test cases like:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"]))==[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort each sublist of strings in a given list of lists.
Your answer will be tested on test cases like:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"]))==[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sort each sublist of strings in a given list of lists.
Your answer will be tested on test cases like:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"]))==[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function that sorts each sublist of strings in a given list of lists. Let's see the example given. The input is something like (["green", "orange"], ["black", "white"], ["white", "black", "orange"]) and the output is each sublist sorted. So for the first sublist, "green" comes before "orange" alphabetically, which is correct. The second sublist becomes ['black', 'white'], which is already sorted. The third one becomes ['black', 'orange', 'white'].
So the task is to take each sublist in the input list and sort them in place. Wait, but the function is supposed to return the sorted list of lists. Wait, the example shows that the input is a tuple of lists? Wait, the test case uses a tuple as the input. Wait, the assert statement has the input as (["green", "orange"], ...), but the function is supposed to take a list of lists. Wait, but in Python, tuples are also iterable. But the function's parameter might be a list of lists, but the test case is passing a tuple of lists. Wait, the function's parameter might need to accept any iterable of lists. But the problem says "given list of lists", but the test case uses a tuple. Hmm, maybe the function is supposed to take a list of lists, but the test case uses a tuple. Wait, perhaps the function is supposed to take a list of lists, but in the test case, the input is a tuple of lists. Wait, but in Python, tuples are not lists. So maybe the function is supposed to accept any sequence of lists, but the problem says "given list of lists".
Wait, the problem says "given list of lists", so perhaps the input is a list of lists. But the test case shows the input as a tuple. Wait, the test case is written as:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"])) == ...
But the function is supposed to take a list of lists. Wait, perhaps the function is supposed to take a list of lists, but in the test case, they are using a tuple. That might be a mistake? Or maybe the function can accept any iterable of lists, like a tuple, list, etc. But the function's parameter is probably supposed to be a list of lists. However, in the test case, the input is a tuple of lists. So perhaps the function should accept any sequence of lists, but the problem says "given list of lists".
But regardless, the function needs to process each sublist. So the approach is: for each element in the input (assuming it's a list of lists), sort the sublist in alphabetical order.
So the steps to solve this:
First, the function will take a parameter, say, lists. Then, for each sublist in lists, we need to sort it. Then return the new list of sorted sublists.
Wait, but in the test case, the input is a tuple of lists. So perhaps the function should accept any iterable of lists. But the function's parameter is probably supposed to be a list of lists. However, the test case uses a tuple, but in Python, tuples are not lists. So maybe the test case is written with a mistake, but perhaps the function should accept a list of lists, and the test case's input is a tuple, but the function is supposed to process that. Wait, but the function can't take a tuple as input if the parameter is expecting a list. So maybe the function is supposed to take a list of lists, and the test case's input is a tuple, but perhaps the test case is written with a mistake. Alternatively, perhaps the function is supposed to take any sequence of lists, like a tuple, list, etc.
But regardless, the code can process each element in the input. So for example, if the input is a tuple of lists, then the function can iterate through each element of the tuple, sort each list, and return a list of the sorted lists. Wait, but the test case's expected output is a list of lists. So the function's return value is a list of lists, regardless of the input type.
So the function's code would be:
def sort_sublists(lists):
# for each sublist in lists, sort it
# return a new list of sorted sublists
return [sorted(sublist) for sublist in lists]
Wait, but the test case's input is a tuple of lists. Let's see. Let's take the test case:
Input is (["green", "orange"], ["black", "white"], ["white", "black", "orange"]). So when we iterate over this tuple, each element is a list. Then, sorted(sublist) would sort each list. Then, the return value is a list of those sorted lists. So the function returns a list of lists. Which matches the expected output.
But in the test case, the input is a tuple, but the function's parameter is called 'lists', which is a tuple. So the function can accept any iterable of lists. So the code would work regardless of whether the input is a list or a tuple.
So the function can be written as:
def sort_sublists(lists):
return [sorted(sublist) for sublist in lists]
But wait, the test case uses the input as a tuple. Let me check the test case:
The assert statement is:
assert sort_sublists((["green", "orange"], ["black", "white"], ["white", "black", "orange"])) == [['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']]
So when the function is called with a tuple, the code would process each element of the tuple. The code returns a list of sorted sublists. Which matches the expected output.
So this function should work. Let me test it with the sample input.
Sample input: (["green", "orange"], ["black", "white"], ["white", "black", "orange"])
Processing each sublist:
First sublist: ["green", "orange"] is already sorted. sorted returns same.
Second sublist: ["black", "white"] is already sorted.
Third sublist: ["white", "black", "orange"] → sorted would be ['black', 'orange', 'white'].
So the output is [[...], [...], [...]], which matches the expected result.
Therefore, this function should work.
But wait, the problem says that the input is a list of lists. But the test case uses a tuple. However, the function code is written to accept any iterable of lists. So the code is correct.
So the Python code is as simple as that. The function is written as a list comprehension, where each sublist is sorted.
So the code is:
def sort_sublists(lists):
return [sorted(sublist) for sublist in lists]
But wait, the problem says that the input is a list of lists. But in the test case, the input is a tuple. However, in Python, tuples are iterable, so the code will work regardless. So the function is correct.
But let me check if the test case is expecting the input to be a list. For example, if the input is a tuple, but the function is supposed to take a list. However, the test case's code is written as:
sort_sublists((...)) which is passing a tuple. So the function must accept that. Therefore, the code is correct.
So the final answer is the function as written.
```python
def sort_sublists(lists):
return [sorted(sublist) for sublist in lists]
```
----------------------------------------------
Result: Pred=def sort_sublists(lists):
return [sorted(sublist) for sublist in lists] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[['green', 'orange'], ['black', 'white'], ['white', 'black', 'orange']]], [[[' red ', 'green'], ['blue ', ' black'], [' orange', 'brown']]], [[['zilver', 'gold'], ['magnesium', 'aluminium'], ['steel', 'bronze']]], [[]], [[['apple', 'banana', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'banana']]], [[['orange', 'green', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'orange', 'green']]], [[['apple', 'banana', 'cherry'], [], ['cherry', 'apple', 'banana']]], [[['apple', 'banana', 'banana'], ['pear', 'pear'], ['orange', 'orange', 'orange']]], [[['apple', 'banana', 'cherry'], [], ['orange', 'plum', 'peach']]], [[['cat', 'dog', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger'], ['monkey']]], [[['pear', 'banana', 'banana'], ['apple', 'orange'], ['kiwi'], ['grape', 'mango', 'apple']]], [[['red', 'green', 'blue'], ['yellow', 'orange'], ['purple', 'pink', 'teal', 'brown']]], [[['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x'], ['y', 'z']]], [[[], [], []]], [[['apple', 'banana', 'cherry'], ['orange', 'plum', 'peach']]], [[['cherry', 'apple', 'banana'], ['orange', 'peach', 'plum'], ['banana', 'cherry', 'apple']]], [[['blue', 'red', 'green'], ['brown', 'purple', 'pink', 'teal'], ['orange', 'yellow']]], [[['orange', 'green'], ['white', 'black'], ['black', 'white', 'orange']]], [[['apple', 'zebra', 'cat'], ['dog', 'elephant'], ['giraffe', 'lion', 'banana']]], [[['red', 'green', 'blue'], [], ['orange', 'purple', 'brown']]], [[['cat', 'dog', 'elephant'], ['giraffe', 'tiger', 'zebra'], ['monkey', 'lion', 'tiger'], ['banana']]], [[['cherry', 'banana', 'apple'], ['peach', 'orange', 'plum'], ['cherry', 'banana', 'apple']]], [[['elephant', 'ant', 'bee'], ['dog', 'camel', 'cat'], ['zebra', 'giraffe', 'lion']]], [[['red', 'green', 'blue'], [], ['orange', 'purple', 'brown'], ['yellow', 'pink', 'teal']]], [[['red', 'green', 'bpinklue', 'blue'], ['yellow', 'orange']]], [[['blue', 'red', 'green'], ['brown', 'purple', 'pink', 'teal'], ['brown', 'purple', 'pink', 'teal']]], [[['pear', 'banana', 'banana'], ['apple', 'orange'], ['kiwi'], ['grape', 'mango', 'apple'], ['grape', 'mango', 'apple']]], [[['apple', 'banana', 'cherry'], ['cherry', 'appl', 'banana'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']]], [[['apple', 'orange'], ['kiwi'], ['grape', 'mango', 'apple']]], [[['apple', 'orange'], ['kiwi'], ['grape', 'mango', 'apple'], ['grape', 'mango', 'apple']]], [[['cat', 'dog', 'elephant'], [], ['zebra', 'lion', 'tiger'], ['monkey']]], [[['orange', 'green', 'green'], ['white', 'orange', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'green']]], [[['red', 'green', 'blue'], ['yellow', 'pink'], [], ['orange', 'purple', 'brown'], ['yellow', 'pink'], ['red', 'green', 'blue']]], [[[], ['cat', 'dog', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger'], []]], [[['banaa', 'cherry', 'banana', 'apple'], ['peach', 'orange', 'plum'], ['cherry', 'banana', 'apple']]], [[['cherry', 'apple', 'bsanana', 'banana'], ['apple', 'banana', 'cherry', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'bsanana', 'banana']]], [[['orange', 'green', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'bsanana', 'orange', 'green'], ['black', 'white', 'black', 'white']]], [[['elephant', 'ant', 'bee'], ['zebra', 'giraffe', 'lion']]], [[['white', 'black'], ['black', 'white', 'orange']]], [[['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['peach', 'orange', 'plum'], ['cherry', 'banana', 'apple']]], [[['banana', 'cherry'], ['cherry', 'apple'], ['cherry', 'apple', 'banana']]], [[['elephant', 'ant', 'bee']]], [[['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a'], ['cat', 'dog', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger']]], [[['red', 'green', 'blue'], ['yellow', 'orange']]], [[['apple', 'banana', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'banana'], ['banana', 'cherry', 'apple']]], [[['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['peach', 'orange', 'plum'], ['cherry', 'banana', 'apple', 'apple'], ['cherry', 'banana', 'apple', 'apple']]], [[['elephant', 'ant', 'bee'], ['elephant', 'ant', 'bee']]], [[['cherry', 'apple', 'banana', 'apple'], ['banana', 'cherry'], ['cherry', 'apple'], ['cherry', 'apple', 'banana', 'apple']]], [[[]]], [[['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['cherry', 'banana', 'p'], ['cherry', 'banana', 'apple', 'apple'], ['cherry', 'banana', 'apple', 'apple']]], [[['cherry', 'apple', 'bsanana', 'banana'], ['apple', 'banana', 'cherry', 'cherry']]], [[['dog', 'elephant', 'elephant'], ['dog', 'elephant', 'elephant'], ['giraffe', 'lion', 'banana']]], [[['cherry', 'apple', 'banana'], ['orange', 'peach', 'plum'], ['banana', 'cherry', 'apple'], ['banana', 'cherry', 'apple'], ['banana', 'cherry', 'apple'], ['orange', 'peach', 'plum']]], [[['cherry', 'apple', 'banana', 'apple'], ['cherry', 'apple'], ['cherry', 'apple', 'banana', 'apple']]], [[['apple', 'banana', 'cherry'], ['cherry', 'appl', 'banana', 'banana'], ['apple', 'banana', 'cherry'], ['cherry', 'appl', 'banana', 'banana'], ['apple', 'banana', 'cherry']]], [[['cherry', 'banana', 'apple'], ['peach', 'orange', 'plum'], ['cherry', 'banana', 'apple'], ['peach', 'orange', 'plum']]], [[[], ['cat', 'dog', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger'], [], [], [], []]], [[['orange', 'green', 'green'], ['white', 'orange', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'green'], ['black', 'white', 'black', 'white']]], [[['red', 'green'], ['red', 'green'], ['yellow', 'orange']]], [[['red', 'green', 'blue', 'green'], ['yellow'], ['red', 'green', 'blue', 'green'], ['yellow']]], [[['apple', 'banana', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'banana'], ['cherry', 'apple', 'banana']]], [[['black', 'orange', 'green'], ['white', 'black'], ['black', 'orange', 'green'], ['black', 'white', 'orange']]], [[['cbpinklueherry', 'cherry', 'apple', 'bsanana', 'banana'], ['banana', 'cherry', 'apple'], ['cbpinklueherry', 'cherry', 'apple', 'bsanana', 'banana']]], [[['orange', 'green']]], [[['cherry', 'apple', 'bsanana', 'banana'], ['orange', 'peach', 'plum'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'bsanana', 'banana'], ['banana', 'cherry', 'apple'], ['banana', 'cherry', 'apple'], ['orange', 'peach', 'plum']]], [[['apple', 'orange'], ['grape', 'mango', 'apple', 'grape'], ['grape', 'mango', 'apple', 'grape'], ['grape', 'mango', 'apple', 'grape']]], [[['zebra', 'lion', 'tiger', 'zebra'], ['cat', 'dog', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger', 'zebra'], ['monkey']]], [[['cherry', 'banana', 'apple'], ['peach', 'orage', 'plum'], ['peach', 'orage', 'plum'], ['cherry', 'banana', 'apple']]], [[['red', 'green'], ['red', 'green'], ['yellow', 'orange'], ['red', 'green']]], [[['red', 'green', 'blue', 'green'], ['yellow', 'yellow'], ['red', 'green', 'blue', 'green'], ['yellow', 'yellow'], ['yellow', 'yellow']]], [[['ngeant', 'nge']]], [[['red', 'green', 'blue'], ['yellow', 'orange'], ['purple', 'pink', 'teal', 'brown'], ['red', 'green', 'blue']]], [[['apple', 'banana', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple'], ['cherry', 'apple'], ['cherry', 'apple']]], [[['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a'], ['cat', 'dog', 'helephant', 'elephant'], ['cat', 'dog', 'helephant', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger']]], [[['red', 'green', 'blue', 'red'], ['yellow', 'orange']]], [[['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a', 'e'], ['cat', 'dog', 'elephant'], ['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a', 'e'], [], [], ['zebra', 'lion', 'tiger']]], [[[], ['cat', 'dog', 'elephant'], ['zebra', 'lion'], ['giraffe'], ['zebra', 'lion'], []]], [[['banana', 'cherry', 'apple'], ['cherry', 'apple', 'banana'], ['cherry', 'apple', 'banana']]], [[['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'orange', 'green'], ['white', 'orange', 'orange', 'green']]], [[['cat', 'dog', 'elephant'], [], ['zebra', 'lion', 'tiger'], ['monkey'], []]], [[['apple', 'banana', 'banana'], ['ant', 'pear', 'pear', 'pear'], ['ant', 'pear', 'pear', 'pear'], ['orange', 'orange', 'orange', 'orange'], ['orange', 'orange', 'orange', 'orange']]], [[['cherry', 'apple', 'banana', 'apple'], ['banana', 'cherry', 'banana'], ['banana', 'cherry', 'banana'], ['cherry', 'apple'], ['cherry', 'apple', 'banana', 'apple']]], [[['cat', 'dog', 'elephant'], ['giraffe', 'tiger', 'zebra'], ['monkey', 'lion', 'tiger']]], [[['cherry', 'apple', 'apple'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple']]], [[[], ['orange', 'purple', 'brown'], ['yellow', 'teai', 'pink', 'teal']]], [[['appletiger', 'banana', 'cherry', 'cherry'], ['cherry', 'apple', 'bsanana', 'banana'], ['appletiger', 'banana', 'cherry', 'cherry'], ['banana', 'cherry', 'apple'], ['cherry', 'apple', 'bsanana', 'banana']]], [[['apple', 'banana', 'mango'], ['apple', 'banana', 'mango'], ['cherry', 'appl', 'banana'], ['apple', 'banana', 'mango'], ['apple', 'banana', 'mango']]], [[['orange', 'orabluenge', 'e'], ['apple', 'banana', 'banana'], ['orange', 'orabluenge', 'e'], ['pear', 'pear'], ['orange', 'orabluenge', 'e'], ['apple', 'banana', 'banana']]], [[['apple', 'banana', 'banana'], ['pear', 'pear'], ['orange', 'orange']]], [[['red', 'green', 'orange', 'blue'], [], ['orange', 'purple', 'brown'], ['yellow', 'pink', 'teal']]], [[['banana', 'cherry', 'apple'], ['cdherry', 'apple', 'banana'], ['cdherry', 'apple', 'banana']]], [[['black', 'orange', 'green'], ['white', 'black'], ['black', 'orange', 'green'], ['black', 'white', 'orange'], ['black', 'white', 'orange']]], [[['orange', 'green', 'green', 'orange'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'bsanana', 'orange', 'green'], ['black', 'white', 'black', 'white']]], [[['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'orange', 'green'], ['white', 'orange', 'orange', 'green'], ['apple', 'green'], ['apple', 'green']]], [[['blue', 'red', 'green'], ['orange', 'yellow', 'orange'], ['brown', 'purple', 'pink', 'teal'], ['orange', 'yellow', 'orange']]], [[['elephant', 'ant', 'bee'], ['dog', 'camel', 'cat'], ['zebra', 'giraffe', 'lion'], ['dog', 'camel', 'cat']]], [[['cherry', 'apple', 'bsanana', 'banana'], ['orange', 'kiwi', 'plum', 'plum'], ['banana', 'cherry', 'apple', 'cherry'], ['cherry', 'apple', 'bsanana', 'banana'], ['orange', 'kiwi', 'plum', 'plum'], ['banana', 'cherry', 'apple', 'cherry'], ['banana', 'cherry', 'apple', 'cherry'], ['orange', 'kiwi', 'plum', 'plum']]], [[['banana', 'cherry'], ['cherry', 'apple'], ['cherry', 'apple', 'banana'], ['banana', 'cherry']]], [[['red'], ['red'], ['red'], ['yellow', 'orange'], ['red']]], [[['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x'], ['y', 'z']]], [[['red', 'green', 'blue', 'green', 'green'], ['red', 'green', 'blue', 'green', 'green'], ['red', 'green', 'blue', 'green', 'green'], ['yellow', 'yellow'], ['yellow', 'yellow'], ['red', 'green', 'blue', 'green', 'green']]], [[['pear', 'bakna', 'banana'], ['apple', 'orange'], ['kiwi'], ['grape', 'mango', 'apple'], ['grape', 'mango', 'apple']]], [[['pear', 'banana', 'banana'], ['apple', 'orange'], ['kiwi'], ['grape', 'pgrape', 'mango', 'apple']]], [[['a', 'orabluenge', 'e'], ['pear', 'pear', 'pear'], ['apple', 'banana', 'banana'], ['a', 'orabluenge', 'e'], ['pear', 'pear', 'pear'], ['a', 'orabluenge', 'e'], ['a', 'orabluenge', 'e'], ['apple', 'banana', 'banana']]], [[['cherry', 'apple', 'apple'], ['banana', 'chlrry', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple']]], [[['cat', 'banana', 'apple'], ['cherry', 'banana', 'apple'], ['peach', 'orange', 'plum'], ['cat', 'banana', 'apple']]], [[['orange', 'yellow', 'orange', 'orange'], ['blue', 'red', 'green'], ['orange', 'yellow', 'orange', 'orange'], ['brown', 'purple', 'pink', 'teal'], ['orange', 'yellow', 'orange', 'orange']]], [[['banana', 'cherry'], ['cherry', 'apple']]], [[['red', 'green', 'p', 'green'], ['yellow'], ['red', 'green', 'p', 'green'], ['yellow'], ['red', 'green', 'p', 'green']]], [[['cherry', 'apple', 'banana', 'apple'], ['banana', 'cherry', 'banana'], ['banana', 'cherry', 'banana'], ['cherry', 'apple', 'banana', 'apple']]], [[['pear', 'banana', 'banana'], ['apple', 'orange'], ['kiwi'], ['grape', 'apple'], ['grape', 'apple'], ['grape', 'apple']]], [[['red', 'green', 'orange', 'blue'], [], ['orange', 'purple'], ['orange', 'purple'], ['yellow', 'pink', 'teal']]], [[['cat', 'dog', 'elephant'], ['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a', 'e'], [], [], ['zebra', 'lion', 'tiger'], ['zebra', 'lion', 'tiger'], ['zebra', 'lion', 'tiger']]], [[['cherry', 'apple', 'apple'], ['banana', 'chlrry', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple'], ['cherry', 'apple', 'apple']]], [[['cherry', 'apple', 'banana'], ['orange', 'peach', 'plum'], ['banana', 'cherry', 'apple'], ['banana', 'cherry', 'apple'], ['orange', 'peach', 'plum']]], [[['apple', 'banana'], ['orange', 'orabluenge', 'e'], ['apple', 'banana'], ['orange', 'orabluenge', 'e'], ['pear', 'pear'], ['orange', 'orabluenge', 'e'], ['apple', 'banana']]], [[['cherry', 'apple', 'bsanana', 'banana'], ['orange', 'kiwi', 'plum', 'plum'], ['banana', 'cherry', 'apple', 'abanana', 'cherry'], ['cherry', 'apple', 'bsanana', 'banana'], ['orange', 'kiwi', 'plum', 'plum'], ['banana', 'cherry', 'apple', 'abanana', 'cherry'], ['orange', 'kiwi', 'plum', 'plum']]], [[['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x']]], [[['red', 'green', 'blue', 'green', 'green'], ['red', 'green', 'blue', 'green', 'green'], ['red', 'green', 'blue', 'green', 'green'], ['yellow', 'yellow'], ['yellow', 'yellow'], ['red', 'green', 'blue', 'green', 'green'], ['yellow', 'yellow']]], [[['cat', 'banana', 'apple'], ['cherry', 'banana', 'apple'], ['peach', 'orange', 'plum', 'plum'], ['peach', 'orange', 'plum', 'plum']]], [[['IODiWvh', 'e', 'f', 'dog', 'r', 'cat', 'a'], ['cat', 'dog', 'helephant', 'elephant'], ['cat', 'dog', 'helephant', 'elephant'], ['giraffe'], ['zebra', 'lion', 'tiger'], ['cat', 'dog', 'helephant', 'elephant']]], [[['apple', 'orange'], ['grape', 'mango', 'n', 'grape'], ['grape', 'mango', 'n', 'grape'], ['grape', 'mango', 'n', 'grape']]], [[['dog', 'camel', 'cat'], ['zebra', 'giraffe', 'lion']]], [[['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'white', 'black', 'white'], ['white', 'orange', 'green'], ['white', 'orange', 'green']]]]
results = [[['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']], [[' red ', 'green'], [' black', 'blue '], [' orange', 'brown']], [['gold', 'zilver'], ['aluminium', 'magnesium'], ['bronze', 'steel']], [], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['green', 'green', 'orange'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'orange', 'white']], [['apple', 'banana', 'cherry'], [], ['apple', 'banana', 'cherry']], [['apple', 'banana', 'banana'], ['pear', 'pear'], ['orange', 'orange', 'orange']], [['apple', 'banana', 'cherry'], [], ['orange', 'peach', 'plum']], [['cat', 'dog', 'elephant'], ['giraffe'], ['lion', 'tiger', 'zebra'], ['monkey']], [['banana', 'banana', 'pear'], ['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango']], [['blue', 'green', 'red'], ['orange', 'yellow'], ['brown', 'pink', 'purple', 'teal']], [['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x'], ['y', 'z']], [[], [], []], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum']], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry']], [['blue', 'green', 'red'], ['brown', 'pink', 'purple', 'teal'], ['orange', 'yellow']], [['green', 'orange'], ['black', 'white'], ['black', 'orange', 'white']], [['apple', 'cat', 'zebra'], ['dog', 'elephant'], ['banana', 'giraffe', 'lion']], [['blue', 'green', 'red'], [], ['brown', 'orange', 'purple']], [['cat', 'dog', 'elephant'], ['giraffe', 'tiger', 'zebra'], ['lion', 'monkey', 'tiger'], ['banana']], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry']], [['ant', 'bee', 'elephant'], ['camel', 'cat', 'dog'], ['giraffe', 'lion', 'zebra']], [['blue', 'green', 'red'], [], ['brown', 'orange', 'purple'], ['pink', 'teal', 'yellow']], [['blue', 'bpinklue', 'green', 'red'], ['orange', 'yellow']], [['blue', 'green', 'red'], ['brown', 'pink', 'purple', 'teal'], ['brown', 'pink', 'purple', 'teal']], [['banana', 'banana', 'pear'], ['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango'], ['apple', 'grape', 'mango']], [['apple', 'banana', 'cherry'], ['appl', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango']], [['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango'], ['apple', 'grape', 'mango']], [['cat', 'dog', 'elephant'], [], ['lion', 'tiger', 'zebra'], ['monkey']], [['green', 'green', 'orange'], ['green', 'orange', 'white'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'white']], [['blue', 'green', 'red'], ['pink', 'yellow'], [], ['brown', 'orange', 'purple'], ['pink', 'yellow'], ['blue', 'green', 'red']], [[], ['cat', 'dog', 'elephant'], ['giraffe'], ['lion', 'tiger', 'zebra'], []], [['apple', 'banaa', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry']], [['apple', 'banana', 'bsanana', 'cherry'], ['apple', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry']], [['green', 'green', 'orange'], ['black', 'black', 'white', 'white'], ['bsanana', 'green', 'orange', 'orange', 'white'], ['black', 'black', 'white', 'white']], [['ant', 'bee', 'elephant'], ['giraffe', 'lion', 'zebra']], [['black', 'white'], ['black', 'orange', 'white']], [['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry']], [['banana', 'cherry'], ['apple', 'cherry'], ['apple', 'banana', 'cherry']], [['ant', 'bee', 'elephant']], [['IODiWvh', 'a', 'cat', 'dog', 'e', 'f', 'r'], ['cat', 'dog', 'elephant'], ['giraffe'], ['lion', 'tiger', 'zebra']], [['blue', 'green', 'red'], ['orange', 'yellow']], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['orange', 'peach', 'plum'], ['apple', 'apple', 'banana', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [['ant', 'bee', 'elephant'], ['ant', 'bee', 'elephant']], [['apple', 'apple', 'banana', 'cherry'], ['banana', 'cherry'], ['apple', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [[]], [['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['banana', 'cherry', 'p'], ['apple', 'apple', 'banana', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [['apple', 'banana', 'bsanana', 'cherry'], ['apple', 'banana', 'cherry', 'cherry']], [['dog', 'elephant', 'elephant'], ['dog', 'elephant', 'elephant'], ['banana', 'giraffe', 'lion']], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum']], [['apple', 'apple', 'banana', 'cherry'], ['apple', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [['apple', 'banana', 'cherry'], ['appl', 'banana', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['appl', 'banana', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum']], [[], ['cat', 'dog', 'elephant'], ['giraffe'], ['lion', 'tiger', 'zebra'], [], [], [], []], [['green', 'green', 'orange'], ['green', 'orange', 'white'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'white'], ['black', 'black', 'white', 'white']], [['green', 'red'], ['green', 'red'], ['orange', 'yellow']], [['blue', 'green', 'green', 'red'], ['yellow'], ['blue', 'green', 'green', 'red'], ['yellow']], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['black', 'green', 'orange'], ['black', 'white'], ['black', 'green', 'orange'], ['black', 'orange', 'white']], [['apple', 'banana', 'bsanana', 'cbpinklueherry', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'bsanana', 'cbpinklueherry', 'cherry']], [['green', 'orange']], [['apple', 'banana', 'bsanana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum']], [['apple', 'orange'], ['apple', 'grape', 'grape', 'mango'], ['apple', 'grape', 'grape', 'mango'], ['apple', 'grape', 'grape', 'mango']], [['lion', 'tiger', 'zebra', 'zebra'], ['cat', 'dog', 'elephant'], ['giraffe'], ['lion', 'tiger', 'zebra', 'zebra'], ['monkey']], [['apple', 'banana', 'cherry'], ['orage', 'peach', 'plum'], ['orage', 'peach', 'plum'], ['apple', 'banana', 'cherry']], [['green', 'red'], ['green', 'red'], ['orange', 'yellow'], ['green', 'red']], [['blue', 'green', 'green', 'red'], ['yellow', 'yellow'], ['blue', 'green', 'green', 'red'], ['yellow', 'yellow'], ['yellow', 'yellow']], [['nge', 'ngeant']], [['blue', 'green', 'red'], ['orange', 'yellow'], ['brown', 'pink', 'purple', 'teal'], ['blue', 'green', 'red']], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'cherry'], ['apple', 'cherry'], ['apple', 'cherry']], [['IODiWvh', 'a', 'cat', 'dog', 'e', 'f', 'r'], ['cat', 'dog', 'elephant', 'helephant'], ['cat', 'dog', 'elephant', 'helephant'], ['giraffe'], ['lion', 'tiger', 'zebra']], [['blue', 'green', 'red', 'red'], ['orange', 'yellow']], [['IODiWvh', 'a', 'cat', 'dog', 'e', 'e', 'f', 'r'], ['cat', 'dog', 'elephant'], ['IODiWvh', 'a', 'cat', 'dog', 'e', 'e', 'f', 'r'], [], [], ['lion', 'tiger', 'zebra']], [[], ['cat', 'dog', 'elephant'], ['lion', 'zebra'], ['giraffe'], ['lion', 'zebra'], []], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry']], [['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'orange', 'white'], ['green', 'orange', 'orange', 'white']], [['cat', 'dog', 'elephant'], [], ['lion', 'tiger', 'zebra'], ['monkey'], []], [['apple', 'banana', 'banana'], ['ant', 'pear', 'pear', 'pear'], ['ant', 'pear', 'pear', 'pear'], ['orange', 'orange', 'orange', 'orange'], ['orange', 'orange', 'orange', 'orange']], [['apple', 'apple', 'banana', 'cherry'], ['banana', 'banana', 'cherry'], ['banana', 'banana', 'cherry'], ['apple', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [['cat', 'dog', 'elephant'], ['giraffe', 'tiger', 'zebra'], ['lion', 'monkey', 'tiger']], [['apple', 'apple', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry']], [[], ['brown', 'orange', 'purple'], ['pink', 'teai', 'teal', 'yellow']], [['appletiger', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry'], ['appletiger', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry']], [['apple', 'banana', 'mango'], ['apple', 'banana', 'mango'], ['appl', 'banana', 'cherry'], ['apple', 'banana', 'mango'], ['apple', 'banana', 'mango']], [['e', 'orabluenge', 'orange'], ['apple', 'banana', 'banana'], ['e', 'orabluenge', 'orange'], ['pear', 'pear'], ['e', 'orabluenge', 'orange'], ['apple', 'banana', 'banana']], [['apple', 'banana', 'banana'], ['pear', 'pear'], ['orange', 'orange']], [['blue', 'green', 'orange', 'red'], [], ['brown', 'orange', 'purple'], ['pink', 'teal', 'yellow']], [['apple', 'banana', 'cherry'], ['apple', 'banana', 'cdherry'], ['apple', 'banana', 'cdherry']], [['black', 'green', 'orange'], ['black', 'white'], ['black', 'green', 'orange'], ['black', 'orange', 'white'], ['black', 'orange', 'white']], [['green', 'green', 'orange', 'orange'], ['black', 'black', 'white', 'white'], ['bsanana', 'green', 'orange', 'orange', 'white'], ['black', 'black', 'white', 'white']], [['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'orange', 'white'], ['green', 'orange', 'orange', 'white'], ['apple', 'green'], ['apple', 'green']], [['blue', 'green', 'red'], ['orange', 'orange', 'yellow'], ['brown', 'pink', 'purple', 'teal'], ['orange', 'orange', 'yellow']], [['ant', 'bee', 'elephant'], ['camel', 'cat', 'dog'], ['giraffe', 'lion', 'zebra'], ['camel', 'cat', 'dog']], [['apple', 'banana', 'bsanana', 'cherry'], ['kiwi', 'orange', 'plum', 'plum'], ['apple', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry'], ['kiwi', 'orange', 'plum', 'plum'], ['apple', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'cherry', 'cherry'], ['kiwi', 'orange', 'plum', 'plum']], [['banana', 'cherry'], ['apple', 'cherry'], ['apple', 'banana', 'cherry'], ['banana', 'cherry']], [['red'], ['red'], ['red'], ['orange', 'yellow'], ['red']], [['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x'], ['y', 'z']], [['blue', 'green', 'green', 'green', 'red'], ['blue', 'green', 'green', 'green', 'red'], ['blue', 'green', 'green', 'green', 'red'], ['yellow', 'yellow'], ['yellow', 'yellow'], ['blue', 'green', 'green', 'green', 'red']], [['bakna', 'banana', 'pear'], ['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango'], ['apple', 'grape', 'mango']], [['banana', 'banana', 'pear'], ['apple', 'orange'], ['kiwi'], ['apple', 'grape', 'mango', 'pgrape']], [['a', 'e', 'orabluenge'], ['pear', 'pear', 'pear'], ['apple', 'banana', 'banana'], ['a', 'e', 'orabluenge'], ['pear', 'pear', 'pear'], ['a', 'e', 'orabluenge'], ['a', 'e', 'orabluenge'], ['apple', 'banana', 'banana']], [['apple', 'apple', 'cherry'], ['apple', 'banana', 'chlrry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry']], [['apple', 'banana', 'cat'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cat']], [['orange', 'orange', 'orange', 'yellow'], ['blue', 'green', 'red'], ['orange', 'orange', 'orange', 'yellow'], ['brown', 'pink', 'purple', 'teal'], ['orange', 'orange', 'orange', 'yellow']], [['banana', 'cherry'], ['apple', 'cherry']], [['green', 'green', 'p', 'red'], ['yellow'], ['green', 'green', 'p', 'red'], ['yellow'], ['green', 'green', 'p', 'red']], [['apple', 'apple', 'banana', 'cherry'], ['banana', 'banana', 'cherry'], ['banana', 'banana', 'cherry'], ['apple', 'apple', 'banana', 'cherry']], [['banana', 'banana', 'pear'], ['apple', 'orange'], ['kiwi'], ['apple', 'grape'], ['apple', 'grape'], ['apple', 'grape']], [['blue', 'green', 'orange', 'red'], [], ['orange', 'purple'], ['orange', 'purple'], ['pink', 'teal', 'yellow']], [['cat', 'dog', 'elephant'], ['IODiWvh', 'a', 'cat', 'dog', 'e', 'e', 'f', 'r'], [], [], ['lion', 'tiger', 'zebra'], ['lion', 'tiger', 'zebra'], ['lion', 'tiger', 'zebra']], [['apple', 'apple', 'cherry'], ['apple', 'banana', 'chlrry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry'], ['apple', 'apple', 'cherry']], [['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum'], ['apple', 'banana', 'cherry'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum']], [['apple', 'banana'], ['e', 'orabluenge', 'orange'], ['apple', 'banana'], ['e', 'orabluenge', 'orange'], ['pear', 'pear'], ['e', 'orabluenge', 'orange'], ['apple', 'banana']], [['apple', 'banana', 'bsanana', 'cherry'], ['kiwi', 'orange', 'plum', 'plum'], ['abanana', 'apple', 'banana', 'cherry', 'cherry'], ['apple', 'banana', 'bsanana', 'cherry'], ['kiwi', 'orange', 'plum', 'plum'], ['abanana', 'apple', 'banana', 'cherry', 'cherry'], ['kiwi', 'orange', 'plum', 'plum']], [['a', 'b'], ['c', 'd'], ['e', 'f'], ['g', 'h'], ['i', 'j', 'j'], ['k', 'l'], ['m', 'n'], ['o', 'p'], ['q', 'r'], ['s', 't'], ['u', 'v'], ['w', 'x']], [['blue', 'green', 'green', 'green', 'red'], ['blue', 'green', 'green', 'green', 'red'], ['blue', 'green', 'green', 'green', 'red'], ['yellow', 'yellow'], ['yellow', 'yellow'], ['blue', 'green', 'green', 'green', 'red'], ['yellow', 'yellow']], [['apple', 'banana', 'cat'], ['apple', 'banana', 'cherry'], ['orange', 'peach', 'plum', 'plum'], ['orange', 'peach', 'plum', 'plum']], [['IODiWvh', 'a', 'cat', 'dog', 'e', 'f', 'r'], ['cat', 'dog', 'elephant', 'helephant'], ['cat', 'dog', 'elephant', 'helephant'], ['giraffe'], ['lion', 'tiger', 'zebra'], ['cat', 'dog', 'elephant', 'helephant']], [['apple', 'orange'], ['grape', 'grape', 'mango', 'n'], ['grape', 'grape', 'mango', 'n'], ['grape', 'grape', 'mango', 'n']], [['camel', 'cat', 'dog'], ['giraffe', 'lion', 'zebra']], [['apple', 'green'], ['apple', 'green'], ['apple', 'green'], ['black', 'black', 'white', 'white'], ['green', 'orange', 'white'], ['green', 'orange', 'white']]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(sort_sublists(*inp), exp, 0)
| OK=True
==================== Problem #59 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count true booleans in the given list.
Your answer will be tested on test cases like:
assert count([True,False,True]) == 2
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count true booleans in the given list.
Your answer will be tested on test cases like:
assert count([True,False,True]) == 2
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count true booleans in the given list.
Your answer will be tested on test cases like:
assert count([True,False,True]) == 2
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count true booleans in the given list.
Your answer will be tested on test cases like:
assert count([True,False,True]) == 2
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to count true booleans in the given list.
Your answer will be tested on test cases like:
assert count([True,False,True]) == 2
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called count that takes a list and returns the number of True booleans in it. Let's see. The example given is count([True, False, True]) which should return 2. So the function needs to iterate through each element in the list, check if it's True, and count how many times that happens.
Hmm, how to approach this. Well, in Python, you can loop through the list. For each element, if it's True, increment a counter. Alternatively, maybe there's a more concise way using list comprehensions or built-in functions.
Wait, the sum function can be useful here. Because in Python, True is equivalent to 1 and False to 0 when summed. So if I sum all the elements in the list, that would give the count of Trues. But wait, what if the list contains other elements that are not booleans? Oh, but the problem says the given list contains booleans, so we don't have to worry about that. So the function can be as simple as summing the list.
Wait, let me test that. For example, [True, False, True] would sum to 1 + 0 + 1 = 2. Which matches the example. So that's correct.
So the function can be written as:
def count(lst):
return sum(lst)
But wait, the problem says the function is supposed to count the True booleans. So this approach works because True is 1 and False is 0. So summing them gives the count. That's a neat and efficient way.
But what if the list is empty? Well, sum of an empty list is 0, which is correct. So this should handle all cases.
So the code would be straightforward. The function takes a list, returns the sum of its elements. But wait, the problem says the list is given. So the function is supposed to take the list as input. So the code would be:
def count(lst):
return sum(lst)
But let me check the test case. The example given is assert count([True, False, True]) == 2. Summing that list gives 2, so that works. Another test case: count([False, False]) would return 0. And count([True]) returns 1. All correct.
So the function is simply summing the list. That's the most efficient way. No need for loops or counters. So the code is very simple. But I need to make sure that the function is named count and takes the list as an argument.
Yes. So the Python code would be:
def count(lst):
return sum(lst)
But wait, maybe the problem expects the function to handle cases where the list contains non-boolean elements? But according to the problem statement, the test cases are given with booleans, so the function can assume that the input list contains booleans. So the code is correct.
Therefore, the answer is to write the function as sum of the list.
```python
def count(lst):
return sum(lst)
```
----------------------------------------------
Result: Pred=def count(lst):
return sum(lst) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[True, False, True]], [[False, False]], [[True, True, True]], [[]], [[False, False, False, False]], [[False, True, False, True, True, False, True, False]], [[False, True, True, True, True, False, True, False]], [[False, False, False, False, False]], [[False, True, False, False, False, False]], [[False, False, False, False, False, False]], [[False, True, False, False, False, False, False]], [[False, True, False, False, False, True, True]], [[False, True, False, False, False, False, False, False]], [[False, True, False, True, False, False, False]], [[False, False, False, False, False, False, False]], [[True, False, False, False, False, False, False]], [[True, False, False, False, False]], [[False, True, False, True, False, True, False, False]], [[False, True, True, False, True, True, False, True, False]], [[False, False, False, False, False, False, False, False]], [[True, False, False, False, False, False, False, False]], [[True, False, True, False, True, False, False, False]], [[True, False, True, True, True, False, True, False]], [[False, False, False, True, False, False]], [[False, True, True, False, False, True, True]], [[False, False, False, False, False, False, True, False]], [[True, False, False, False, False, False, False, False, False]], [[False, False, False]], [[False, True, False, True, True, True, True, False]], [[True, False, True, True, False, False, True, True, False, True, True]], [[False, False, False, False, True, False, True, False]], [[False, True, False, False]], [[False, False, False, False, False, False, False, False, False]], [[True, False, True, True, True, False, False, False, True]], [[False, True, False, False, True, False, False, True]], [[False, True, False, False, False, False, False, False, False]], [[False, True, False, False, True, False, False]], [[True, False, True, True, True, True, False, False, False, False, True]], [[True, False, False, False, False, False]], [[False, False, False, False, False, False, True, False, False]], [[True, False, False, True, True, False, True, False]], [[False, False, True, False, True, False, False]], [[False, False, False, False, False, False, False, False, False, False, False]], [[True, False, True, False, False, False, False]], [[True, False, True, False, False]], [[False, True, True, True, True, False, False]], [[False, False, False, False, False, False, False, False, False, False]], [[False, False, True, False, True, False, False, False, False]], [[False, True, False, False, True, True, True]], [[False, True, False, True, False, False, False, True, True]], [[False, False, True, False, True, False, False, False]], [[False, False, False, True, False, False, False, False, False, False, False, False]], [[False, True, False, True, True, False, True, True, False, False]], [[False, True, False, True, True, False, False, False]], [[False, True, True, False, False, False]], [[False, True, False, True, True, False, True, False, False, False]], [[False, True, False, False, True, False, False, False]], [[False, True, False, True, False, False, False, False]], [[False, True, True, True, True, False, True, False, False]], [[False, False, False, False, False, False, False, False, False, False, False, False]], [[False, False, True, True, True, True, False, True, True, False]], [[False, True, False, True, False, False, False, False, True, True]], [[False, True, False, True, False, False, False, False, False]], [[False, False, False, False, True, False, False, False, False]], [[False, True, False, False, True, False, False, False, True, True]], [[False, True, False, False, False, True, True, False, False, True]], [[False, True, False, True, True, False, True, False, False]], [[True, False, True, False, False, False, False, False]], [[True, False, True, False, False, False]], [[False, False, False, True, True, False]], [[False, True, True, True, False, False, True, True]], [[True, False, True, False, True, False, False]], [[False, True, False, False, True, True, True, False, True]], [[False, False, False, True, False, False, False, False, False, True, False, False]], [[False, True, False, False, False]], [[False, False, False, False, False, True, False]], [[False, False, False, True, True, True, True, False, True, False]], [[False, False, False, False, False, True]], [[True, False, False, True, True, False, True, False, False]], [[False, True, False, True, False, True, False, False, False]], [[True, False, True, False, True, True, False, False, False]], [[False, True, True, False, False, True, True, True]], [[True, False, True, True, False, True, False]], [[True, False, False, True, True, True, True, False, False, False, False, True]], [[False, True, True, False, False, True, True, True, True]], [[False, True, False, True, True, False, False]], [[True, False, False, True, False, True, False, False, True, False]], [[False, True, False, True, False, False, True]], [[False, True, True, True, True, False, False, False, True]], [[True, False, True, True, False, False, True, True, False, True, True, False]], [[False, True, True, True, True, False, True, True, False]], [[False, True, True, False, True, False, True, False]], [[True, False, True, True, True, False, False, False, True, True]], [[True, False, True, True, True, False, False, False, False, True]], [[True, False, True, True, True, True, False, True, False]], [[False, True, False, True, False, False, False, False, True, True, False, True]], [[True, False, True, False, True, True, False, True, False, False]], [[False, True, True, False, False, True, False, False, False]], [[True, False, True, True, False, False, True, True, False, False, True, True]], [[False, False, True, False, True, False, False, True, True]], [[False, False, True, False, True, False, False, False, False, False]], [[False, True, False, False, False, False, True]], [[True, False, True, False, False, True]], [[False, False, False, False, True, False, False, False, False, False]], [[True, False, True, True, True, True, False, False, True]], [[True, False, True, True, False, True, True, True, False]]]
results = [2, 0, 3, 0, 0, 4, 5, 0, 1, 0, 1, 3, 1, 2, 0, 1, 1, 3, 5, 0, 1, 3, 5, 1, 4, 1, 1, 0, 5, 7, 2, 1, 0, 5, 3, 1, 2, 6, 1, 1, 4, 2, 0, 2, 2, 4, 0, 2, 4, 4, 2, 1, 5, 3, 2, 4, 2, 2, 5, 0, 6, 4, 2, 1, 4, 4, 4, 2, 2, 2, 5, 3, 5, 2, 1, 1, 5, 1, 4, 3, 4, 5, 4, 6, 6, 3, 4, 3, 5, 7, 6, 4, 6, 5, 6, 5, 5, 3, 7, 4, 2, 2, 3, 1, 6, 6]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(count(*inp), exp, 0)
| OK=True
==================== Problem #60 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to append the given list to the given tuples.
Your answer will be tested on test cases like:
assert add_lists([5, 6, 7], (9, 10)) == (9, 10, 5, 6, 7)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to append the given list to the given tuples.
Your answer will be tested on test cases like:
assert add_lists([5, 6, 7], (9, 10)) == (9, 10, 5, 6, 7)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to append the given list to the given tuples.
Your answer will be tested on test cases like:
assert add_lists([5, 6, 7], (9, 10)) == (9, 10, 5, 6, 7)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to append the given list to the given tuples.
Your answer will be tested on test cases like:
assert add_lists([5, 6, 7], (9, 10)) == (9, 10, 5, 6, 7)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to append the given list to the given tuples.
Your answer will be tested on test cases like:
assert add_lists([5, 6, 7], (9, 10)) == (9, 10, 5, 6, 7)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called add_lists that takes a list and a tuple, and appends the list to the tuple. Wait, but tuples are immutable in Python, right? So I can't just add the list elements to the tuple directly. Oh right, so the approach would be to convert the tuple into a list, then extend it with the given list, and then convert it back to a tuple.
Let me think about the steps. The function add_lists takes two arguments: the first is the list to append, and the second is the tuple to which we append. Wait, wait, the problem says "append the given list to the given tuples". Wait, the function parameters: the first argument is the list, the second is the tuple. Like in the example, add_lists([5,6,7], (9,10)) returns (9,10,5,6,7). So the list is added after the tuple's elements.
So the process is: take the input tuple, convert it to a list, then add all elements of the given list to this list, then convert back to a tuple.
So, for example, the tuple (9,10) becomes [9,10], then extend with [5,6,7] to make [9,10,5,6,7], then convert to tuple (9,10,5,6,7).
So the code would be something like:
def add_lists(lst, tpl):
new_list = list(tpl)
new_list.extend(lst)
return tuple(new_list)
Wait, but the parameters are ordered. The first parameter is the list, the second is the tuple. So in the example, the list is [5,6,7], and the tuple is (9,10). So converting the tuple to a list, then extending with the list. Then return as tuple.
Yes. So the code should be as above.
Testing the example: list((9,10)) is [9,10], extend with [5,6,7] gives [9,10,5,6,7], converted to tuple. Which matches the expected output.
What about edge cases? Like empty list or empty tuple? Well, the code should handle that. For example, if the list is empty, then the tuple remains as is. If the tuple is empty, then the list is added. But according to the problem statement, the function is supposed to append the list to the tuple. So the code should work in all cases.
So the function is straightforward. Now, the user wants the code in a markdown code block, as a self-contained Python script. So the code should include the function definition and any necessary imports. But in this case, no imports are needed. So the code would be:
def add_lists(lst, tpl):
new_list = list(tpl)
new_list.extend(lst)
return tuple(new_list)
But wait, the function name is add_lists, and the parameters are lst and tpl. The test case uses add_lists([5,6,7], (9,10)) which would be correct.
Yes. So that's the code. Let me check again. The example assertion would be:
assert add_lists([5,6,7], (9,10)) == (9,10,5,6,7)
Which would be true with this code. So this should work.
```python
def add_lists(lst, tpl):
new_list = list(tpl)
new_list.extend(lst)
return tuple(new_list)
```
----------------------------------------------
Result: Pred=def add_lists(lst, tpl):
new_list = list(tpl)
new_list.extend(lst)
return tuple(new_list) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[5, 6, 7], (9, 10)], [[6, 7, 8], (10, 11)], [[7, 8, 9], (11, 12)], [[], (1, 2, 3)], [[1, [2, 3], {'a': 4}], (5, [6, 7], {'b': 8})], [[], ()], [[1, 2, 3], ()], [[0.5, [1, 2], {'x': 3}], (4.5, [5, 6], {'y': 7})], [[[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 13]],)], [[[], [1, 2], {'a': [3, 4]}], (5, [6, 7], {'b': [8, [9]]})], [[{'x': [1, 2]}, {'y': [{'z': [3]}, 4]}], ([5, 6, [7]], [{'a': 8}])], [[[[1], 2], {'3': [4]}, [5, 6, 7]], (8, [9, [10]], {'a': 11})], [[[], [], []], ([], [], [])], [[[], [[]], [[], []]], ([[], []], [[]], [[], []])], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, [8, [9]], {'a': 10, 'b': 11})], [[[[1, 2], [3, 4]], [[5, 6], [7, 8]]], ([[9, 10], [11, 12]], [[13, 14], [15, 16]])], [[[1, 2], [3, 4]], ([5, 6], {'a': [7, [8, 9]]})], [[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], ([7, 8, {'c': {'d': [9, [10, 11]]}}],)], [[[[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7]], (8, [9, [10]])], [[[1, 2], [4]], ([5, 6], {'a': [7, [8, 9]]})], [[[], [[]], [[], []]], ([[], [], []], [[]], [[], []])], [[[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[5, 6], [7, 8]]], ([[9, 10], [11, 12]], [[13, 14], [15, 16]])], [[1, 2], ([7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[True, True, True, True, True, True, False], (4.5, 44.32264550231051, 0.5, 0.5, -1.6326583229058826, 4.5, 55.52796338743434)], [[[], [1, 2], {'a': [3, 4]}], ([6, 7], {'b': [8, [9]]})], [[2], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[[3, 4]], ([5, 6], {'a': [7, [8, 9]]})], [[[[1], 2], {'3': [4]}, [5, 6, 7]], (9, [9, [10]], {'a': 11})], [[[1, 2], [4]], ([5, 6], {'a': [7, [8, 9]]}, [5, 6])], [[[[1], 2], {'3': [4]}], (9, [9, [10]], {'a': 11})], [[[1, 2], [3, 4, 4], [3, 4, 4]], ([5, 6], {'a': [7, [8, 9]]})], [[15], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, 7, 7, [8, [9]], {'a': 10, 'b': 11})], [[[], [[]], [[], []]], ([[], [], []], [[]], [[], []], [[]])], [[[3, 4]], ([5, 6], {'a': [7, [8, 9]]}, [5, 6])], [[], ({'a': [7, 14, [8, 9]], 'hello': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]], 'hello': [7, 14, [8, 9]]})], [[{'3': [4]}, [5, 6, 7]], (9, [9, [10]], {'a': 11})], [[[], [1, 2], {'a': [3, 4]}], (6, [6, 7], {'b': [8, [9]]})], [[], (1, 2)], [[], ([4, 5, 6, 6], [4, 5, 6, 6], {'a': [7, [8, 9]]})], [[[1, 2], [3, 4], [3, 4]], ([5, 6], {'a': [7, [8, 9]]})], [[[], [], []], ([], [True, True, False, False, True])], [[True, True, True, True, True, True, False], (4.5, 44.32264550231051, 0.5, 0.4020733226756738, -1.6326583229058826, 4.5, 55.52796338743434, 0.5)], [[1, 2, [3, 4, {'a': {'b': [5, 6]}}], 1], ([7, 8, {'c': {'d': [9, [10, 11]]}}],)], [[1, 2, 3], (False, True)], [[1, 2, 3], (False, False, True, True)], [[[1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]], ([5, 6], {'a': [7, [8, 9]]})], [[], (False, True, False, False)], [[-96.96084131931524, -94.69555233395306, -95.59861164068568, -1.6326583229058826, 92.24778790461318], (1, 2)], [[69, -68, -26, 99, 9, -10, -55, 65, 13, 64], (1, 2)], [[True, False, False], (False, True, False, False)], [[1, 2], ([7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[[], [], [], []], ([], [], [])], [[['c', 'Tbzkr'], [], [], []], ([], [], [])], [[0, 2, 3], ()], [[[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 1, 13], [12, 1, 13]],)], [[15], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, [8, [9]], {'a': 10, 'b': 11}, 7)], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, 7, 7, [8, [9]], {'a': 10, 'b': 11}, {'a': 10, 'b': 11})], [[[], [[], []], [[], []], [[], []]], ([[], []], [[]], [[], []])], [[[], [[]], [[], []]], ([], [[], [], []], [], [[], []])], [[[1, 2, [3, 4, {'a': {'b': [5, 6]}}]]], ([[12, 13]],)], [[[7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 13], [12, 13]],)], [[[7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 1, 13], [12, 1, 13]],)], [[], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[{'3': [4]}, [5, 6, 7], [5, 6, 7]], (8, [9, [10]], {'a': 11})], [[[[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7], [[1], 4, [1]]], (8, [9, [10], 9], [9, [10], 9])], [[[], [[], []], [[], []], []], ([[], []], [], [[], []])], [[[[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7], {'3': [4]}], (8, [9, [10]])], [[[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {}, {}]], ([[12, 13]], [[12, 13]])], [[[], [], [[], []]], ([[], [], []], [[]], [[], []])], [[[7, 9, {}, {}]], ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]])], [['hello', 'z', 'ZJgH'], ({'a': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]]})], [[1, 2, 7, 3], (False, False, True, True, True)], [[[], [], [], []], ([], [], [36.685637329178746], [36.685637329178746])], [[1, 2, 2], ([9, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[[], 12, 'pOEmwo', 0.5, ['z', 'T'], 'Iuy', 7], (1, 2, 2)], [[{'x': [1, 2]}, {'y': [{'z': [3]}, 4]}, {'x': [1, 2]}], ([5, 6, [7]], [{'a': 8}])], [[{'3': []}, [5, 6, 7], [5, 6, 7]], (8, {'a': 11})], [[], (False, True, False, False, False)], [[0.5, [1, 2], {'x': 3, 'ZJgHx': 4}], (4.5, [5, 6], {'y': 7})], [[[2, 3], {'a': 4}], (5, [6, 7], {'b': 8})], [[[], [1, 2], {'a': [3, 4]}], (6, [6, 7], {})], [[15], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}])], [[], (-94.69555233395306, -96.96084131931524, -1.6326583229058826, 79.36778956924633, -42.0626870759427, 4.5, 94.66425529755756, -96.96084131931524)], [[[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 1, 13], [12, 1, 13], [12, 1, 13]], [[12, 1, 13], [12, 1, 13], [12, 1, 13]])], [[1, -55], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[[], [[], []], [[], []], [[], []]], ([[], []], [[]], [[]], [[]])], [[1, 1, 2, 3], (False, True)], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, 7, 7, {'a': 10, 'b': 11}, {'a': 10, 'b': 11})], [[[7, 9, {}, {}]], ([[12, 13], [12, 13]], [[12, 13], [12, 13]])], [[-55], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[[-5, 13, 99], [], []], ([], [True, True, False, False, True])], [[[1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]], ([5, 6],)], [[[1, 2], [3, 4, 4], [3, 4, 4]], ({'a': [7, [8, 9]]},)], [[[7, 9, {}, {}]], ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]])], [[[[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7]], ([9, [10]],)], [[], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}])], [[True, False, False], (True, True, False, False)], [[[1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]], ([5, 6], {})], [[[7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]], ([[12, 13], [12, 13]], [[12, 13], [12, 13]])], [[1, 2, [3, 4, {'a': {'b': [5, 6]}}]], ([7, 8, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}], [7, 8, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}])], [[False, False, False, False, True, True, True], (-94.69555233395306, -96.96084131931524, -1.6326583229058826, 79.36778956924633, -42.0626870759427, 4.5, 94.66425529755756, -96.96084131931524)], [[[1, 2], [], [1, 2]], ([5, 6], {'a': [7, [8, 9]]}, [5, 6])], [[[], [], [], [], []], ([], [True, True, False, False, True])], [[], ({'a': [7, [8, 9]], 'hello': [7, [8, 9]]}, {'a': [7, [8, 9]], 'hello': [7, [8, 9]]})], [[[], [], [], []], ([], [True, True, False, False, True])], [[1, 2, [3, 4, {'a': {'b': [5, 6]}}, 3], 1], ([7, 8, {'c': {'d': [9, [10, 11]]}}],)], [[[7, 9, {}, {}]], ([[12], [12], [12]], [[12], [12], [12]], [[12], [12], [12]], [[12], [12], [12]])], [[[3, 4]], ([5], {'a': [7, [8, 9]]}, [5], [5], [5])], [[[], [1, 2], {'a': [3, 4]}, [1, 2]], (5, [6, 7], {'b': [8, [9]]})], [['hello', 'z', 'ZJgH', 'z', 'hello'], ({'a': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]]})], [[[], [1, 2], {'a': [3, 4]}], (6, [6, 7], {'b': [8, [9]]}, 6)], [['hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}], (7, 7, 7, {'a': 9, 'b': 11}, {'a': 9, 'b': 11})], [[[1, 2], [4]], ({'a': [7, [8, 9]]}, [5, 6])], [[[3, 3, 4]], ([5], {'a': [7, [8, 9]]}, [5], [5], [5])], [[], ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}])], [[True, True, True, True, True, False, False], (4.5, 44.32264550231051, 0.5, 0.4020733226756738, -1.6326583229058826, 4.5, 55.52796338743434, 0.5)]]
results = [(9, 10, 5, 6, 7), (10, 11, 6, 7, 8), (11, 12, 7, 8, 9), (1, 2, 3), (5, [6, 7], {'b': 8}, 1, [2, 3], {'a': 4}), (), (1, 2, 3), (4.5, [5, 6], {'y': 7}, 0.5, [1, 2], {'x': 3}), ([[12, 13]], [1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]), (5, [6, 7], {'b': [8, [9]]}, [], [1, 2], {'a': [3, 4]}), ([5, 6, [7]], [{'a': 8}], {'x': [1, 2]}, {'y': [{'z': [3]}, 4]}), (8, [9, [10]], {'a': 11}, [[1], 2], {'3': [4]}, [5, 6, 7]), ([], [], [], [], [], []), ([[], []], [[]], [[], []], [], [[]], [[], []]), (7, [8, [9]], {'a': 10, 'b': 11}, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), ([[9, 10], [11, 12]], [[13, 14], [15, 16]], [[1, 2], [3, 4]], [[5, 6], [7, 8]]), ([5, 6], {'a': [7, [8, 9]]}, [1, 2], [3, 4]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2, [3, 4, {'a': {'b': [5, 6]}}]), (8, [9, [10]], [[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7]), ([5, 6], {'a': [7, [8, 9]]}, [1, 2], [4]), ([[], [], []], [[]], [[], []], [], [[]], [[], []]), ([[9, 10], [11, 12]], [[13, 14], [15, 16]], [[1, 2], [3, 4]], [[5, 6], [7, 8]], [[5, 6], [7, 8]]), ([7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2), (4.5, 44.32264550231051, 0.5, 0.5, -1.6326583229058826, 4.5, 55.52796338743434, True, True, True, True, True, True, False), ([6, 7], {'b': [8, [9]]}, [], [1, 2], {'a': [3, 4]}), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 2), ([5, 6], {'a': [7, [8, 9]]}, [3, 4]), (9, [9, [10]], {'a': 11}, [[1], 2], {'3': [4]}, [5, 6, 7]), ([5, 6], {'a': [7, [8, 9]]}, [5, 6], [1, 2], [4]), (9, [9, [10]], {'a': 11}, [[1], 2], {'3': [4]}), ([5, 6], {'a': [7, [8, 9]]}, [1, 2], [3, 4, 4], [3, 4, 4]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 15), (7, 7, 7, [8, [9]], {'a': 10, 'b': 11}, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), ([[], [], []], [[]], [[], []], [[]], [], [[]], [[], []]), ([5, 6], {'a': [7, [8, 9]]}, [5, 6], [3, 4]), ({'a': [7, 14, [8, 9]], 'hello': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]], 'hello': [7, 14, [8, 9]]}), (9, [9, [10]], {'a': 11}, {'3': [4]}, [5, 6, 7]), (6, [6, 7], {'b': [8, [9]]}, [], [1, 2], {'a': [3, 4]}), (1, 2), ([4, 5, 6, 6], [4, 5, 6, 6], {'a': [7, [8, 9]]}), ([5, 6], {'a': [7, [8, 9]]}, [1, 2], [3, 4], [3, 4]), ([], [True, True, False, False, True], [], [], []), (4.5, 44.32264550231051, 0.5, 0.4020733226756738, -1.6326583229058826, 4.5, 55.52796338743434, 0.5, True, True, True, True, True, True, False), ([7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2, [3, 4, {'a': {'b': [5, 6]}}], 1), (False, True, 1, 2, 3), (False, False, True, True, 1, 2, 3), ([5, 6], {'a': [7, [8, 9]]}, [1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]), (False, True, False, False), (1, 2, -96.96084131931524, -94.69555233395306, -95.59861164068568, -1.6326583229058826, 92.24778790461318), (1, 2, 69, -68, -26, 99, 9, -10, -55, 65, 13, 64), (False, True, False, False, True, False, False), ([7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 7, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2), ([], [], [], [], [], [], []), ([], [], [], ['c', 'Tbzkr'], [], [], []), (0, 2, 3), ([[12, 1, 13], [12, 1, 13]], [1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 15), (7, [8, [9]], {'a': 10, 'b': 11}, 7, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), (7, 7, 7, [8, [9]], {'a': 10, 'b': 11}, {'a': 10, 'b': 11}, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), ([[], []], [[]], [[], []], [], [[], []], [[], []], [[], []]), ([], [[], [], []], [], [[], []], [], [[]], [[], []]), ([[12, 13]], [1, 2, [3, 4, {'a': {'b': [5, 6]}}]]), ([[12, 13], [12, 13]], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]), ([[12, 1, 13], [12, 1, 13]], [7, 8, {'c': {'d': [9, [10, 11]]}}]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]), (8, [9, [10]], {'a': 11}, {'3': [4]}, [5, 6, 7], [5, 6, 7]), (8, [9, [10], 9], [9, [10], 9], [[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7], [[1], 4, [1]]), ([[], []], [], [[], []], [], [[], []], [[], []], []), (8, [9, [10]], [[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7], {'3': [4]}), ([[12, 13]], [[12, 13]], [1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {}, {}]), ([[], [], []], [[]], [[], []], [], [], [[], []]), ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]], [7, 9, {}, {}]), ({'a': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]]}, 'hello', 'z', 'ZJgH'), (False, False, True, True, True, 1, 2, 7, 3), ([], [], [36.685637329178746], [36.685637329178746], [], [], [], []), ([9, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2, 2), (1, 2, 2, [], 12, 'pOEmwo', 0.5, ['z', 'T'], 'Iuy', 7), ([5, 6, [7]], [{'a': 8}], {'x': [1, 2]}, {'y': [{'z': [3]}, 4]}, {'x': [1, 2]}), (8, {'a': 11}, {'3': []}, [5, 6, 7], [5, 6, 7]), (False, True, False, False, False), (4.5, [5, 6], {'y': 7}, 0.5, [1, 2], {'x': 3, 'ZJgHx': 4}), (5, [6, 7], {'b': 8}, [2, 3], {'a': 4}), (6, [6, 7], {}, [], [1, 2], {'a': [3, 4]}), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], 15), (-94.69555233395306, -96.96084131931524, -1.6326583229058826, 79.36778956924633, -42.0626870759427, 4.5, 94.66425529755756, -96.96084131931524), ([[12, 1, 13], [12, 1, 13], [12, 1, 13]], [[12, 1, 13], [12, 1, 13], [12, 1, 13]], [1, 2, [3, 4, {'a': {'b': [5, 6]}}]], [7, 8, {'c': {'d': [9, [10, 11]]}}]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], 1, -55), ([[], []], [[]], [[]], [[]], [], [[], []], [[], []], [[], []]), (False, True, 1, 1, 2, 3), (7, 7, 7, {'a': 10, 'b': 11}, {'a': 10, 'b': 11}, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [7, 9, {}, {}]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], -55), ([], [True, True, False, False, True], [-5, 13, 99], [], []), ([5, 6], [1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]), ({'a': [7, [8, 9]]}, [1, 2], [3, 4, 4], [3, 4, 4]), ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]], [[12, 13], [12, 13]], [7, 9, {}, {}]), ([9, [10]], [[1], 4, [1]], {'3': [4]}, [5, 6, 7], [[1], 4, [1]], [5, 6, 7]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}]), (True, True, False, False, True, False, False), ([5, 6], {}, [1, 2], [3, 4, 4], [3, 4, 4], [3, 4, 4]), ([[12, 13], [12, 13]], [[12, 13], [12, 13]], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]), ([7, 8, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}], [7, 8, {'c': {'d': [9], 'ZJgHx': [9]}, 'ZJgH': {'d': [9], 'ZJgHx': [9]}}], 1, 2, [3, 4, {'a': {'b': [5, 6]}}]), (-94.69555233395306, -96.96084131931524, -1.6326583229058826, 79.36778956924633, -42.0626870759427, 4.5, 94.66425529755756, -96.96084131931524, False, False, False, False, True, True, True), ([5, 6], {'a': [7, [8, 9]]}, [5, 6], [1, 2], [], [1, 2]), ([], [True, True, False, False, True], [], [], [], [], []), ({'a': [7, [8, 9]], 'hello': [7, [8, 9]]}, {'a': [7, [8, 9]], 'hello': [7, [8, 9]]}), ([], [True, True, False, False, True], [], [], [], []), ([7, 8, {'c': {'d': [9, [10, 11]]}}], 1, 2, [3, 4, {'a': {'b': [5, 6]}}, 3], 1), ([[12], [12], [12]], [[12], [12], [12]], [[12], [12], [12]], [[12], [12], [12]], [7, 9, {}, {}]), ([5], {'a': [7, [8, 9]]}, [5], [5], [5], [3, 4]), (5, [6, 7], {'b': [8, [9]]}, [], [1, 2], {'a': [3, 4]}, [1, 2]), ({'a': [7, 14, [8, 9]]}, {'a': [7, 14, [8, 9]]}, 'hello', 'z', 'ZJgH', 'z', 'hello'), (6, [6, 7], {'b': [8, [9]]}, 6, [], [1, 2], {'a': [3, 4]}), (7, 7, 7, {'a': 9, 'b': 11}, {'a': 9, 'b': 11}, 'hello', [1, [2, 3]], {'x': [4, 5, {'y': {'z': 6}}]}), ({'a': [7, [8, 9]]}, [5, 6], [1, 2], [4]), ([5], {'a': [7, [8, 9]]}, [5], [5], [5], [3, 3, 4]), ([7, 8, {'c': {'d': [9, [10, 11]]}}], [8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}], [7, 8, {'c': {'d': [9, [10, 11]]}}]), (4.5, 44.32264550231051, 0.5, 0.4020733226756738, -1.6326583229058826, 4.5, 55.52796338743434, 0.5, True, True, True, True, True, False, False)]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(add_lists(*inp), exp, 0)
| OK=True
=========================================
Question 0
error_msg: None
=========================================
Question 1
error_msg: python error: No python code block found
=========================================
Question 2
error_msg: None
=========================================
Question 3
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 31, in
File "", line 25, in assertion
AssertionError: out: False, exp: None
=========================================
Question 4
error_msg: None
=========================================
Question 5
error_msg: None
=========================================
Question 6
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 32, in
File "", line 5, in search
IndexError: list index out of range
=========================================
Question 7
error_msg: None
=========================================
Question 8
error_msg: python error: No python code block found
=========================================
Question 9
error_msg: python error: No python code block found
=========================================
Question 10
error_msg: Traceback (most recent call last):
File "/data_storage/zyf/zjr/MUSCLE/utils.py", line 76, in worker
exec(code, local_ns)
File "", line 34, in
File "", line 3, in find_length
IndexError: list index out of range
=========================================
Question 11
error_msg: None
=========================================
Question 12
error_msg: None
=========================================
Question 13
error_msg: None
=========================================
Question 14
error_msg: None
==================== Problem #61 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three lists into a single sorted list.
Your answer will be tested on test cases like:
assert merge_sorted_list([25, 24, 15, 4, 5, 29, 110],[19, 20, 11, 56, 25, 233, 154],[24, 26, 54, 48])==[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three lists into a single sorted list.
Your answer will be tested on test cases like:
assert merge_sorted_list([25, 24, 15, 4, 5, 29, 110],[19, 20, 11, 56, 25, 233, 154],[24, 26, 54, 48])==[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three lists into a single sorted list.
Your answer will be tested on test cases like:
assert merge_sorted_list([25, 24, 15, 4, 5, 29, 110],[19, 20, 11, 56, 25, 233, 154],[24, 26, 54, 48])==[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three lists into a single sorted list.
Your answer will be tested on test cases like:
assert merge_sorted_list([25, 24, 15, 4, 5, 29, 110],[19, 20, 11, 56, 25, 233, 154],[24, 26, 54, 48])==[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to merge three lists into a single sorted list.
Your answer will be tested on test cases like:
assert merge_sorted_list([25, 24, 15, 4, 5, 29, 110],[19, 20, 11, 56, 25, 233, 154],[24, 26, 54, 48])==[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called merge_sorted_list that takes three lists and returns a single sorted list. Let me think about how to approach this.
First, the problem says the input lists are sorted? Wait, the example given has the input lists as [25, 24, 15, 4, 5, 29, 110], which isn't sorted. Wait, but the output is sorted. Oh, right, the function's job is to merge them into a single sorted list. So the input lists themselves might not be sorted. Wait, but the example given has the first list as [25,24,15,4,5,29,110], which isn't sorted. So the function needs to take three arbitrary lists, combine them, and return a sorted list.
So the straightforward approach is to combine all elements from the three lists into one list, then sort it. But maybe there's a more efficient way if the input lists are already sorted. However, the example given doesn't have sorted input lists. Let me check the test case.
The test case given is:
merge_sorted_list([25, 24, 15, 4, 5, 29, 110], [19, 20, 11, 56, 25, 233, 154], [24, 26, 54, 48]) == [4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233]
Looking at the input lists, they are not sorted. For example, the first list starts with 25, then 24, which is smaller. So the function is supposed to merge them into a single sorted list regardless of their original order.
So the simplest way is to concatenate all three lists into one, then sort them. But maybe the problem expects a more efficient approach, like a merge of three sorted lists. However, the problem statement doesn't specify that the input lists are sorted. Therefore, the correct approach is to combine all elements and sort them.
Wait, but the function's name is merge_sorted_list. Maybe the original intention is that the input lists are already sorted, and the function needs to merge them efficiently. But the example given doesn't have sorted lists. For example, the first list is [25,24,15,4,5,29,110], which is not sorted. So perhaps the function's name is misleading, but the actual problem is to merge three lists (regardless of their order) into a single sorted list.
In that case, the solution is straightforward: combine all elements into a single list and sort them.
So the steps are:
1. Take the three input lists.
2. Combine them into one list (e.g., using list.extend or + operator).
3. Sort the combined list in ascending order.
4. Return the sorted list.
Let me test this approach with the given test case.
First list: [25, 24, 15, 4, 5, 29, 110]
Second list: [19, 20, 11, 56, 25, 233, 154]
Third list: [24, 26, 54, 48]
Combined list would have all elements. Then sorted.
Let me see the expected output: [4,5,11,15,19,20,24,24,25,25,26,29,48,54,56,110,154,233]
Yes, if we combine all elements and sort them, that's the result.
So the code can be written as:
def merge_sorted_list(list1, list2, list3):
merged = list1 + list2 + list3
merged.sort()
return merged
But wait, the function is supposed to return a list. The test case uses assert, so the function must return the sorted list.
But perhaps the problem expects the function to be called merge_sorted_list, but the code is straightforward.
Wait, but the problem says "merge three lists into a single sorted list". So the function is supposed to merge them, which could imply that the input lists are already sorted. But the example given shows that they are not. So perhaps the problem is not about merging sorted lists but just combining and sorting.
In any case, the test case passes with the approach of combining and sorting.
So the code would be as simple as that.
But let me check the test case. Let's take the three lists, combine them, and sort.
Combined list elements:
List1: 25,24,15,4,5,29,110
List2: 19,20,11,56,25,233,154
List3: 24,26,54,48
Combined list would have all these numbers. When sorted, they should be in order. Let me check the expected output.
Yes, the expected output is the sorted list of all elements. So the code would work.
Therefore, the Python function can be written as follows.
But the problem says to write a function. So the code would be:
def merge_sorted_list(list1, list2, list3):
combined = list1 + list2 + list3
combined.sort()
return combined
But wait, the test case uses the function with three lists and expects the sorted list. Let me check with the sample input.
Sample input lists:
list1 = [25, 24, 15, 4, 5, 29, 110]
list2 = [19, 20, 11, 56, 25, 233, 154]
list3 = [24, 26, 54, 48]
Combined list would be all elements. When sorted, the output is as given.
Yes, so this code should work.
But perhaps the problem expects a more efficient approach, but given that the problem's example doesn't have sorted lists, the correct approach is to combine and sort.
So the code is straightforward. Now, write the function as per the problem's instructions.
Now, the user wants the code in a markdown code block. So the final answer is:
```python
def merge_sorted_list(list1, list2, list3):
combined = list1 + list2 + list3
combined.sort()
return combined
```
But wait, the function is supposed to return a list. The code does that. The test case uses assert, so the function must return the correct list.
Yes, this should work. Let me check for possible errors.
What if the input lists are empty? Well, the code handles that. For example, if all lists are empty, returns empty list.
Another test case: if list1 is [3,2,1], list2 is [], list3 is [5], the merged list would be [1,2,3,5], which is correct.
Yes, this code should work.
```python
def merge_sorted_list(list1, list2, list3):
combined = list1 + list2 + list3
combined.sort()
return combined
```
----------------------------------------------
Result: Pred=def merge_sorted_list(list1, list2, list3):
combined = list1 + list2 + list3
combined.sort()
return combined | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[25, 24, 15, 4, 5, 29, 110], [19, 20, 11, 56, 25, 233, 154], [24, 26, 54, 48]], [[1, 3, 5, 6, 8, 9], [2, 5, 7, 11], [1, 4, 7, 8, 12]], [[18, 14, 10, 9, 8, 7, 9, 3, 2, 4, 1], [25, 35, 22, 85, 14, 65, 75, 25, 58], [12, 74, 9, 50, 61, 41]], [[1000, 999, 998, 997, 996], [1001, 1002, 1003, 1004], [1000, 999, 998, 997, 996]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], [], [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]], [[100, 200, 300, 400, 500, 600], [25, 50, 75, 200, 225, 250, 275], [350, 400, 450, 500, 550, 600, 650, 700]], [[5, 10, 15, 20, 25, 30, 35], [1, 2, 3, 4, 5, 6, 7], [50, 45, 40, 35, 30, 25, 20, 15, 10]], [[], [], []], [[-10, -9, -8, -7, -6, -5], [1000, 2000, 3000], [-100, -200, -300, -400, -500]], [[1.5, 2.5, 3.5, 4.5, 5.5], [0.5, 1.5, 2.5, 3.5, 4.5], [-5.5, -4.5, -3.5, -2.5, -1.5]], [[10, 20, 30, 40, 50], [5, 15, 25, 35, 45], [1, 2, 3, 4, 5]], [[100, 200, 300, 400, 500], [-100, -200, -300, -400, -500], [0.1, 0.2, 0.3, 0.4, 0.5]], [[1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2], [3, 3, 3, 3, 3, 3, 3]], [[1, 2, 3, 4, 5], [5, 4, 3, 2, 1], [1, 3, 5, 2, 4]], [[10, 20, 30, 40, 50, 60, 70], [5, 15, 25, 35, 45, 55, 65, 75], [1, 2, 3, 4, 5, 6, 7, 8, 9]], [[10, 15, 20, 25, 30], [5, 10, 15, 20, 25], [1, 2, 3, 4, 5]], [[100, 200], [50, 150, 250], [80, 160, 240]], [[10, 20, 30, 40, 50], [15, 25, 35, 45, 55], [10, 20, 30, 40, 50]], [[1, 3, 5, 7, 9], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9]], [[100, 200, 300, 400, 500], [250, 350, 450, 550, 650], [100, 200, 300, 400, 500]], [[1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50], [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50], [3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49]], [[12, 80, 160, 240], [650, 200], [12, 80, 160, 240]], [[650, 38], [650, 38], [12, 80, 160, 240]], [[10, 20, 30, 50, 60, 70], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]], [[1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2], [3, 3, 3, 3, 3, 2, 3]], [[1, 2, 3, 4, 5], [1, 3, 5, 3, 2, 4], [1, 3, 5, 3, 2, 4]], [[999, 998, 997, 996], [1001, 1002, 1003, 1004], [1000, 999, 998, 997, 996]], [[10, 20, 30, 40, 50], [15, 25, 35, 45, 55, 25], [15, 25, 35, 45, 55, 25]], [[11, 239, 80, 41, 240], [650, 38, 650], [11, 239, 80, 41, 240]], [[1, 2, 3, 60, 4, 5], [5, 4, 3, 2, 24], [1, 2, 3, 60, 4, 5]], [[650, 37], [650, 37], [12, 80, 160, 240]], [[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]], [[100, 300, 400, 500, 600], [25, 50, 75, 200, 225, 250, 275], [350, 400, 450, 500, 550, 600, 650, 700]], [[], [], [50, 150, 250]], [[12, 80, 160, 240], [200], [12, 80, 160, 240]], [[1, 3, 5, 7, 9], [2, 6, 8, 10], [1, 3, 5, 7, 9]], [[1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50], [2, 4, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50], [3, 5, 7, 9, 11, 13, 15, 17, 19, 15, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49]], [[10, 15, 20, 25, 30], [5, 10, 15, 20], [1, 1, 3, 4, 5]], [[2, 3, 3, 3, 3, 2, 2, 4, 3], [1, 1, 1, 1, 1, 1, 1], [2, 3, 3, 3, 3, 2, 2, 4, 3]], [[12, 81, 160, 240], [12, 81, 160, 240], [201, 200]], [[12, 81, 160, 240], [201], [201]], [[1, 2, 3, 60, 4, 5], [5, 4, 3, 3, 2, 24], [1, 2, 3, 60, 4, 5]], [[1, 3, 5, 7, 9], [1, 3, 5, 9], [1, 3, 5, 9]], [[650, 37], [12, 80, 160, 240], [650, 37]], [[-10, -9, -8, -7, -6, -5], [-100, -200, -300, -400, -500], [-100, -200, -300, -400, -500]], [[1, 2, 3, 4, 5, 6, 7, 9, 10, 3, 11, 12], [], [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]], [[11, 239, 81, 41, 240], [650, 38, 650], [650, 38, 650]], [[23, 650], [23, 650], [12, 80, 160, 39]], [[5, 10, 15, 20, 25, 30, 35], [1, 2, 3, 4, 1, 6, 7], [50, 45, 40, 35, 30, 25, 20, 15, 10]], [[650, 36], [650, 36], [12, 80, 160, 240]], [[12, 3, 160, 240], [12, 3, 160, 240], [12, 3, 160, 240]], [[10, 20, 30, 40, 50, 60, 70], [10, 20, 30, 40, 50, 60, 70], [10, 20, 30, 40, 50, 60, 70]], [[100, 200], [50, 250], [50, 250]], [[1000, 999, 998, 997, 996], [1000, 999, 998, 997, 996], [1001, 1002, 1003, 1004]], [[1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1], [3, 3, 3, 3, 3, 2, 3]], [[81, 160, 240], [81, 160, 240], [81, 160, 240]], [[1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2], [3, 3, 3, 4, 2, 3]], [[200, 200], [200, 200], [50, 250, 50]], [[1, 1, -6, 1, 1, 1, 1, 1], [1, 1, -6, 1, 1, 1, 1, 1], [3, 3, 3, 3, 3, 2, 3]], [[1, 3, 5, 7, 27, 9], [1, 3, 5, 7, 27, 9], [3, 5, 9]], [[650, 38, 38], [650, 38, 38], [650, 38, 38]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 7], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 7], [1, 2, 3, 4, 5, 6, 7, 8, 9, 6, 7]], [[12, 160, 240], [12, 160, 240], [201, 200]], [[11, 239, 80, 41, 240], [650, 38, 649, 650], [650, 38, 649, 650]], [[1, 18, 3, 5, 9], [1, 18, 3, 5, 9], [1, 18, 3, 5, 9]], [[50, 150], [50, 150], [80, 160, 240]], [[651, 23, 650, 23], [651, 23, 650, 23], [12, 80, 160, 39]], [[1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 3, 2, 2, 2], [3, 3, 3, 3, 3, 3, 3]], [[10, 20, 30, 50, 60, 70], [1, 2, 3, 4, 5, 6, 8, 9], [1, 2, 3, 4, 5, 6, 8, 9]], [[650, 38, 37], [650, 38, 37], [650, 38, 37]], [[200], [12, 80, 240], [12, 80, 240]], [[650, 38, 650, 649, 650, 650], [650, 38, 650, 649, 650, 650], [650, 38, 650, 649, 650, 650]], [[0.5, 1.5, 2.5, 3.5, 4.5], [-5.5, -4.5, -3.5, -1.5], [0.5, 1.5, 2.5, 3.5, 4.5]], [[200], [12, 80, 160, 240], [12, 80, 160, 240]], [[1, 2, 3, 4, 5, 6, 8, 9, 6, 7, 6], [1, 2, 3, 4, 5, 6, 8, 9, 6, 7, 6], [1, 2, 3, 4, 5, 6, 8, 9, 6, 7, 6]], [[1, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50], [2, 4, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50], [3, 5, 7, 9, 11, 13, 15, 19, 15, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49]], [[650, 37], [650, 37], [650, 37]], [[50, 13, 150, 13], [50, 13, 150, 13], [50, 13, 150, 13]], [[12, 81, 160, 240, 81], [], [12, 81, 160, 240, 81]], [[1, 1, -6, 1, 1, 1, 1, 1], [4, 3, 3, 3, 3, 2, 3], [4, 3, 3, 3, 3, 2, 3]], [[160, 240], [160, 240], [-100, 200]], [[1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 3, 2, 2, 2], [3, 3, 3, 3, 3, 3, 3]], [[10, 20, 30, 400, 40, 50], [5, 15, 25, 35, 45], [1, 2, 3, 4, 5]], [[1, 2, 100, 3, 4, 5, 6, 7, 9, 10, 3, 11, 12], [], [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]], [[650, 38, 650, 650, 650], [650, 38, 650, 650, 650], [650, 38, 650, 650, 650]], [[1, 2, 3, 4, 1, 6, 29], [50, 45, 40, 35, 30, 25, 20, 15, 10], [1, 2, 3, 4, 1, 6, 29]], [[12, 160, 240, 81], [], [12, 160, 240, 81]], [[651, 23], [651, 23], [651, 23]], [[650, 38, 650], [650, 38, 650], [11, 239, 81, 41, 240]], [[10, 20, 30, 40, 50, 10], [15, 25, 35, 45, 55, 25, 15, 25], [15, 25, 35, 45, 55, 25, 15, 25]], [[1, 3, 4, 5], [10, 20, 30, 40], [1, 3, 4, 5]], [[1, 2, 3, 5, 6, 8, 9, 6, 7, 6], [1, 2, 3, 5, 6, 8, 9, 6, 7, 6], [1, 2, 3, 5, 6, 8, 9, 6, 7, 6]], [[2, 2, 2, 2, 2, 2, 2], [1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2]], [[1, 1, -6, 1, 1, 1, 1, 1], [4, 3, 3, 3, 2, 3], [4, 3, 3, 3, 2, 3]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 2], [1, 2, 3, 4, 5, 6, 7, 8, 9, 2], [1, 2, 3, 4, 5, 6, 7, 8, 9, 2]], [[1, 3, 5, 9], [1, 3, 5, 9], [1, 3, 5, 9]], [[1, 2, 3, 4, 5, 6, 7, 9, 3, 11, 12], [], [13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 13]], [[1, 3, 5, 7, 9], [2, 6, 8, 10], [1, 60, 5, 7, 9]], [[10, 20, 30, 400, 40, 50, 10], [10, 20, 30, 400, 40, 50, 10], [1, 2, 3, 4, 5]], [[1, 2, 3, 4, 1, 6, -9], [1, 2, 3, 4, 1, 6, -9], [50, 45, 40, 35, 30, 25, 20, 15, 10]], [[-100, -200, -300, -400, -500], [-100, -200, -300, -400, -500], [-100, -200, -300, -400, -500]], [[10, 20, 30, 40, 50], [10, 20, 30, 40], [10, 20, 30, 40]], [[0.5, 1.5, 2.5, 3.5, 4.5], [-4.5, -3.5, -1.5], [0.5, 1.5, 2.5, 3.5, 4.5]], [[12, 27, 240, 15, 81], [12, 27, 240, 15, 81], [12, 27, 240, 15, 81]], [[40, 27, 240, 15, 81], [40, 27, 240, 15, 81], [40, 27, 240, 15, 81]], [[10, 20, 30, 50], [10, 20, 30, 40], [10, 20, 30, 40]], [[1, 1, 1, 1, 38, 1, 1, 1], [1, 1, 1, 1, 38, 1, 1, 1], [3, 3, 3, 3, 3, 2, 3]], [[11, 239, 80, 41, 240], [650, 651, -5, 38, 649, 650], [650, 651, -5, 38, 649, 650]], [[81, 240], [81, 240], [81, 240]], [[200], [12, 80, 160, 12, 240], [12, 80, 160, 12, 240]], [[-7, 12, 160, 37, 81], [-7, 12, 160, 37, 81], [-7, 12, 160, 37, 81]], [[1, 2, 3, 4, 1, 6, 29], [50, 45, 40, 35, 30, 25, 20, 15, 10, 10], [1, 2, 3, 4, 1, 6, 29]], [[1, 3, 3, 60, 4, 5], [5, 4, 3, 3, 2, 24], [1, 3, 3, 60, 4, 5]], [[200, 100, 200, 300, 400, 500], [-100, -200, -300, -400, -500], [0.1, 0.2, 0.3, 0.4, 0.5, 0.3]], [[81, 160, 159, 240], [81, 160, 159, 240], [81, 160, 159, 240]], [[-6, 81, 160, 240], [-6, 81, 160, 240], [-6, 81, 160, 240]], [[38, 650, 649, 650, 650], [38, 650, 649, 650, 650], [38, 650, 649, 650, 650]], [[10, 20, 40, -500, 50], [10, 20, 40, -500, 50], [10, 20, 40, -500, 50]], [[651, -7, 652, 23], [651, -7, 652, 23], [651, -7, 652, 23]], [[1, 1, 1, 1, 38, 1, 1, 1], [4, 3, 3, 3, 3, 3, 2, 3], [4, 3, 3, 3, 3, 3, 2, 3]], [[-100, -100, -200, -300, -400, -500], [-100, -100, -200, -300, -400, -500], [-100, -100, -200, -300, -400, -500]]]
results = [[4, 5, 11, 15, 19, 20, 24, 24, 25, 25, 26, 29, 48, 54, 56, 110, 154, 233], [1, 1, 2, 3, 4, 5, 5, 6, 7, 7, 8, 8, 9, 11, 12], [1, 2, 3, 4, 7, 8, 9, 9, 9, 10, 12, 14, 14, 18, 22, 25, 25, 35, 41, 50, 58, 61, 65, 74, 75, 85], [996, 996, 997, 997, 998, 998, 999, 999, 1000, 1000, 1001, 1002, 1003, 1004], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], [25, 50, 75, 100, 200, 200, 225, 250, 275, 300, 350, 400, 400, 450, 500, 500, 550, 600, 600, 650, 700], [1, 2, 3, 4, 5, 5, 6, 7, 10, 10, 15, 15, 20, 20, 25, 25, 30, 30, 35, 35, 40, 45, 50], [], [-500, -400, -300, -200, -100, -10, -9, -8, -7, -6, -5, 1000, 2000, 3000], [-5.5, -4.5, -3.5, -2.5, -1.5, 0.5, 1.5, 1.5, 2.5, 2.5, 3.5, 3.5, 4.5, 4.5, 5.5], [1, 2, 3, 4, 5, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50], [-500, -400, -300, -200, -100, 0.1, 0.2, 0.3, 0.4, 0.5, 100, 200, 300, 400, 500], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3], [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5], [1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75], [1, 2, 3, 4, 5, 5, 10, 10, 15, 15, 20, 20, 25, 25, 30], [50, 80, 100, 150, 160, 200, 240, 250], [10, 10, 15, 20, 20, 25, 30, 30, 35, 40, 40, 45, 50, 50, 55], [1, 1, 2, 3, 3, 4, 5, 5, 6, 7, 7, 8, 9, 9, 10], [100, 100, 200, 200, 250, 300, 300, 350, 400, 400, 450, 500, 500, 550, 650], [1, 2, 3, 4, 5, 5, 6, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 15, 16, 17, 18, 19, 20, 20, 21, 22, 23, 24, 25, 25, 26, 27, 28, 29, 30, 30, 31, 32, 33, 34, 35, 35, 36, 37, 38, 39, 40, 40, 41, 42, 43, 44, 45, 45, 46, 47, 48, 49, 50, 50], [12, 12, 80, 80, 160, 160, 200, 240, 240, 650], [12, 38, 38, 80, 160, 240, 650, 650], [1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 20, 30, 50, 60, 70], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3], [1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5], [996, 996, 997, 997, 998, 998, 999, 999, 1000, 1001, 1002, 1003, 1004], [10, 15, 15, 20, 25, 25, 25, 25, 30, 35, 35, 40, 45, 45, 50, 55, 55], [11, 11, 38, 41, 41, 80, 80, 239, 239, 240, 240, 650, 650], [1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 24, 60, 60], [12, 37, 37, 80, 160, 240, 650, 650], [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9], [25, 50, 75, 100, 200, 225, 250, 275, 300, 350, 400, 400, 450, 500, 500, 550, 600, 600, 650, 700], [50, 150, 250], [12, 12, 80, 80, 160, 160, 200, 240, 240], [1, 1, 2, 3, 3, 5, 5, 6, 7, 7, 8, 9, 9, 10], [1, 2, 3, 4, 5, 5, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 15, 15, 16, 17, 18, 19, 20, 20, 21, 22, 23, 24, 25, 25, 26, 27, 28, 29, 30, 30, 31, 32, 33, 34, 35, 35, 36, 37, 38, 39, 40, 40, 41, 42, 43, 44, 45, 45, 46, 47, 48, 49, 50, 50], [1, 1, 3, 4, 5, 5, 10, 10, 15, 15, 20, 20, 25, 30], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4], [12, 12, 81, 81, 160, 160, 200, 201, 240, 240], [12, 81, 160, 201, 201, 240], [1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5, 24, 60, 60], [1, 1, 1, 3, 3, 3, 5, 5, 5, 7, 9, 9, 9], [12, 37, 37, 80, 160, 240, 650, 650], [-500, -500, -400, -400, -300, -300, -200, -200, -100, -100, -10, -9, -8, -7, -6, -5], [1, 2, 3, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], [11, 38, 38, 41, 81, 239, 240, 650, 650, 650, 650], [12, 23, 23, 39, 80, 160, 650, 650], [1, 1, 2, 3, 4, 5, 6, 7, 10, 10, 15, 15, 20, 20, 25, 25, 30, 30, 35, 35, 40, 45, 50], [12, 36, 36, 80, 160, 240, 650, 650], [3, 3, 3, 12, 12, 12, 160, 160, 160, 240, 240, 240], [10, 10, 10, 20, 20, 20, 30, 30, 30, 40, 40, 40, 50, 50, 50, 60, 60, 60, 70, 70, 70], [50, 50, 100, 200, 250, 250], [996, 996, 997, 997, 998, 998, 999, 999, 1000, 1000, 1001, 1002, 1003, 1004], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 3, 3], [81, 81, 81, 160, 160, 160, 240, 240, 240], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4], [50, 50, 200, 200, 200, 200, 250], [-6, -6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 3, 3], [1, 1, 3, 3, 3, 5, 5, 5, 7, 7, 9, 9, 9, 27, 27], [38, 38, 38, 38, 38, 38, 650, 650, 650], [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 8, 8, 8, 9, 9, 9], [12, 12, 160, 160, 200, 201, 240, 240], [11, 38, 38, 41, 80, 239, 240, 649, 649, 650, 650, 650, 650], [1, 1, 1, 3, 3, 3, 5, 5, 5, 9, 9, 9, 18, 18, 18], [50, 50, 80, 150, 150, 160, 240], [12, 23, 23, 23, 23, 39, 80, 160, 650, 650, 651, 651], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3], [1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 8, 8, 9, 9, 10, 20, 30, 50, 60, 70], [37, 37, 37, 38, 38, 38, 650, 650, 650], [12, 12, 80, 80, 200, 240, 240], [38, 38, 38, 649, 649, 649, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650], [-5.5, -4.5, -3.5, -1.5, 0.5, 0.5, 1.5, 1.5, 2.5, 2.5, 3.5, 3.5, 4.5, 4.5], [12, 12, 80, 80, 160, 160, 200, 240, 240], [1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9], [1, 2, 3, 4, 5, 5, 7, 8, 9, 10, 10, 11, 12, 13, 14, 15, 15, 15, 16, 18, 19, 20, 20, 21, 22, 23, 24, 25, 25, 26, 27, 28, 29, 30, 30, 31, 32, 33, 34, 35, 35, 36, 37, 38, 39, 40, 40, 41, 42, 43, 44, 45, 45, 46, 47, 48, 49, 50, 50], [37, 37, 37, 650, 650, 650], [13, 13, 13, 13, 13, 13, 50, 50, 50, 150, 150, 150], [12, 12, 81, 81, 81, 81, 160, 160, 240, 240], [-6, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4], [-100, 160, 160, 200, 240, 240], [1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3], [1, 2, 3, 4, 5, 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 400], [1, 2, 3, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 100], [38, 38, 38, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650, 650], [1, 1, 1, 1, 2, 2, 3, 3, 4, 4, 6, 6, 10, 15, 20, 25, 29, 29, 30, 35, 40, 45, 50], [12, 12, 81, 81, 160, 160, 240, 240], [23, 23, 23, 651, 651, 651], [11, 38, 38, 41, 81, 239, 240, 650, 650, 650, 650], [10, 10, 15, 15, 15, 15, 20, 25, 25, 25, 25, 25, 25, 30, 35, 35, 40, 45, 45, 50, 55, 55], [1, 1, 3, 3, 4, 4, 5, 5, 10, 20, 30, 40], [1, 1, 1, 2, 2, 2, 3, 3, 3, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9], [1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2], [-6, 1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4], [1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6, 6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9], [1, 1, 1, 3, 3, 3, 5, 5, 5, 9, 9, 9], [1, 2, 3, 3, 4, 5, 6, 7, 9, 11, 12, 13, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], [1, 1, 2, 3, 5, 5, 6, 7, 7, 8, 9, 9, 10, 60], [1, 2, 3, 4, 5, 10, 10, 10, 10, 20, 20, 30, 30, 40, 40, 50, 50, 400, 400], [-9, -9, 1, 1, 1, 1, 2, 2, 3, 3, 4, 4, 6, 6, 10, 15, 20, 25, 30, 35, 40, 45, 50], [-500, -500, -500, -400, -400, -400, -300, -300, -300, -200, -200, -200, -100, -100, -100], [10, 10, 10, 20, 20, 20, 30, 30, 30, 40, 40, 40, 50], [-4.5, -3.5, -1.5, 0.5, 0.5, 1.5, 1.5, 2.5, 2.5, 3.5, 3.5, 4.5, 4.5], [12, 12, 12, 15, 15, 15, 27, 27, 27, 81, 81, 81, 240, 240, 240], [15, 15, 15, 27, 27, 27, 40, 40, 40, 81, 81, 81, 240, 240, 240], [10, 10, 10, 20, 20, 20, 30, 30, 30, 40, 40, 50], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 3, 3, 3, 3, 3, 38, 38], [-5, -5, 11, 38, 38, 41, 80, 239, 240, 649, 649, 650, 650, 650, 650, 651, 651], [81, 81, 81, 240, 240, 240], [12, 12, 12, 12, 80, 80, 160, 160, 200, 240, 240], [-7, -7, -7, 12, 12, 12, 37, 37, 37, 81, 81, 81, 160, 160, 160], [1, 1, 1, 1, 2, 2, 3, 3, 4, 4, 6, 6, 10, 10, 15, 20, 25, 29, 29, 30, 35, 40, 45, 50], [1, 1, 2, 3, 3, 3, 3, 3, 3, 4, 4, 4, 5, 5, 5, 24, 60, 60], [-500, -400, -300, -200, -100, 0.1, 0.2, 0.3, 0.3, 0.4, 0.5, 100, 200, 200, 300, 400, 500], [81, 81, 81, 159, 159, 159, 160, 160, 160, 240, 240, 240], [-6, -6, -6, 81, 81, 81, 160, 160, 160, 240, 240, 240], [38, 38, 38, 649, 649, 649, 650, 650, 650, 650, 650, 650, 650, 650, 650], [-500, -500, -500, 10, 10, 10, 20, 20, 20, 40, 40, 40, 50, 50, 50], [-7, -7, -7, 23, 23, 23, 651, 651, 651, 652, 652, 652], [1, 1, 1, 1, 1, 1, 1, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 38], [-500, -500, -500, -400, -400, -400, -300, -300, -300, -200, -200, -200, -100, -100, -100, -100, -100, -100]]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(merge_sorted_list(*inp), exp, 0)
| OK=True
==================== Problem #62 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of numbers with an odd value when rotating a binary string the given number of times.
Your answer will be tested on test cases like:
assert odd_Equivalent("011001",6) == 3
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of numbers with an odd value when rotating a binary string the given number of times.
Your answer will be tested on test cases like:
assert odd_Equivalent("011001",6) == 3
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of numbers with an odd value when rotating a binary string the given number of times.
Your answer will be tested on test cases like:
assert odd_Equivalent("011001",6) == 3
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of numbers with an odd value when rotating a binary string the given number of times.
Your answer will be tested on test cases like:
assert odd_Equivalent("011001",6) == 3
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the number of numbers with an odd value when rotating a binary string the given number of times.
Your answer will be tested on test cases like:
assert odd_Equivalent("011001",6) == 3
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
The assistant's thought process:
Okay, let's see. The problem is to find the number of numbers with an odd value when rotating a binary string a given number of times. Hmm. Wait, the function is called odd_Equivalent, and the example is assert odd_Equivalent("011001",6) == 3. So I need to figure out what exactly this function does.
First, let's understand what rotating a binary string means. Rotating a string by one time would mean shifting all characters by one position. For example, rotating "011001" once to the left would make it "110010". But wait, how many rotations are considered here? The problem says the given number of times. So for each rotation count from 1 to the given number, maybe? Or maybe for each possible rotation up to that number?
Wait, the example given is for 6 rotations. Let's think about the example. The input is "011001" and 6 rotations. The output is 3. So what's happening here?
Let me think: For each rotation count from 1 to 6, we need to check if the resulting binary number is odd. Then count how many times that happens.
Wait, but rotating a binary string multiple times. For example, rotating once, twice, etc. But for a string of length n, rotating n times brings it back to the original. So for a string of length 6, rotating 6 times would be same as original. So for each rotation count from 1 to 6, we need to check if the rotated binary number is odd.
But the example says that for 6 rotations, the answer is 3. Let me check that.
Let's take the example. The original string is "011001". Let's see each rotation:
But first, note that a binary number is odd if and only if its last digit is 1. So regardless of how you rotate the string, the value of the binary number's parity depends only on the last digit. Because any binary number ending with 0 is even, ending with 1 is odd.
Wait, that's a key insight! So for any rotation of the binary string, the parity (odd or even) of the number depends solely on the last digit of the rotated string. Therefore, for each rotation, if the rotated string ends with a '1', it's odd. So the problem reduces to counting how many times, after rotating the original string by k positions (for k from 1 to the given number of rotations), the rotated string ends with a '1'.
But wait, the given number of rotations is 6. But how many unique rotations are there? For a string of length n, rotating by k positions is equivalent to rotating by k mod n positions. So for example, if the string is length 6, rotating by 6 positions is same as rotating by 0 positions (original string). But the problem says "the given number of times"—so perhaps the function is considering rotations from 1 to the given number of times, but considering each rotation as a separate step. However, for the example, when the input is 6, the answer is 3. Let's think.
Original string: "011001" (length 6). Let's look at each rotation from 1 to 6:
Rotation 1: shift left once. The original string is 0 1 1 0 0 1. Rotating left once would make it 1 1 0 0 1 0. The last digit is 0 → even. So not counted.
Rotation 2: shift left twice. Original string rotated twice: 1 0 0 1 0 1. Last digit is 1 → odd. Counted.
Rotation 3: shift left three times. The string becomes 0 0 1 0 1 1. Last digit is 1 → counted.
Rotation 4: shift left four times. The string becomes 0 1 0 1 1 0. Last digit is 0 → no.
Rotation 5: shift left five times. The string becomes 1 0 1 1 0 0. Last digit is 0 → no.
Rotation 6: shift left six times. That's back to original. The original string ends with 1. So yes. So that's counted.
So for rotations 1-6, the counts are 2,3,6 → three times. Which matches the example. So the answer is 3.
So the problem reduces to: for each rotation count from 1 to the given number of rotations (let's call it R), check if the rotated string ends with a '1'. Then count how many such cases.
But how to compute that efficiently?
But the key is that rotating the string by k positions. The rotated string's last digit is the original string's (n - k)th position? Wait, let's think about rotation.
Assuming that rotating left once moves the first character to the end. For example, "abcd" rotated left once becomes "bcda". So for a rotation of k times, the rotated string is the original string shifted left by k positions. The last character of the rotated string is the original string's (k-th position from the start?), no. Wait, let's think for the original string s of length n.
After rotating left once, the last character is the original first character. Wait, no. For example, original is "abcd" (length 4). Rotating left once gives "bcda". The last character is 'a', which was the original first character. So for rotation k, the last character of the rotated string is the original character at position (k) mod n? Wait, for rotation k steps left, the rotated string is s[k:] + s[:k]. So the last character of the rotated string is s[k-1], because the rotated string is s[k], s[k+1], ..., s[n-1], s[0], s[1], ..., s[k-1]. So the last character is s[k-1], which is the original string's (k-1)th index. Wait, but when you rotate left once, the rotated string is s[1:] + s[0], so the last character is s[0]. So for k=1, the last character is s[0]. For k=2, the rotated string is s[2:] + s[:2], so the last character is s[1]. So in general, for rotation k, the last character of the rotated string is s[(k-1) mod n], where n is the length of the string.
Wait, but for k steps, the rotated string's last character is the original string's (k-1)th character. Because for each rotation step, the first character moves to the end. So after k rotations, the original first k characters are moved to the end. So the last character of the rotated string is the original (k-th) character? Wait, no. Let me take an example. Original string is "011001" (indices 0-5). Let's take k=2. Rotating left twice: the first two characters are moved to the end. Original string is 0,1,1,0,0,1. After rotating left once: 1,1,0,0,1,0. Rotating left again: 1,0,0,1,0,1. The last character is 1. Which is the original index 2 (original string's third character, since indexes start at 0). Wait, original index 2 is '1'. So for k=2, the last character is original index 1? Or 2? Let me see: original indexes are 0,1,2,3,4,5. After rotating left twice, the rotated string is s[2:] + s[:2]. So s[2:] is 1,0,0,1. s[:2] is 0,1. So the rotated string is 1,0,0,1,0,1. The last character is 1, which is the original s[1] (since s[:2] is 0,1, so the last element of s[:2] is s[1]). So for k=2, the last character is s[1]. Which is (k-1)th index. Because k=2, (k-1) is 1. So yes, the last character of the rotated string is s[k-1].
So for any rotation count k, the last character is s[k-1]. But since the string is of length n, when k exceeds n, it wraps around. For example, if k is n, then the rotated string is the original string. So the last character is s[n-1], which is the original last character. So for k steps, the last character is s[(k-1) mod n].
But since the problem is to consider rotations from 1 to R (the given number of times), for each k in 1..R, we need to check if s[(k-1) mod n] is '1'.
Wait, but for example, in the example given, R=6, n=6. For k=6, (k-1) mod 6 is 5. So s[5] is '1', which is correct. So for each rotation count k (from 1 to R), we check if the original string's (k-1) mod n position is '1'.
So the problem reduces to: count the number of times that s[(k-1) mod n] is '1', for k in 1..R.
But since (k-1) mod n is equivalent to (k-1) when k-1 < n, and wraps around otherwise. So for example, if R is larger than n, then for k from 1 to R, we have (k-1) mod n. But since the string is length n, the positions are 0..n-1.
So the problem can be rephrased as: for each k in 1 to R, check if the (k-1)th position (mod n) in the original string is '1'. Count how many such cases.
But how to compute that efficiently?
Let me think. For example, for the original string s, let's precompute the positions where the character is '1'. Then, for each k from 1 to R, we check if the (k-1) mod n is in the positions of '1's.
But how to compute the count? Let's think of the positions as a list. For example, for s = "011001", the positions with '1's are 1,2,5 (indices 0-based). So for each k in 1..R, (k-1) mod n is the index. So for R=6, the indices are 0,1,2,3,4,5. For each of these indices, check if they are in the '1's positions. For the example, the indices 0 (k=1) is 0 → not in the list. 1 (k=2) is in the list. 2 (k=3) is in the list. 3 (k=4) is not. 4 (k=5) is not. 5 (k=6) is in the list. So total of 3, which matches the example.
So the problem reduces to counting how many numbers in the range 1..R, when you take (k-1) mod n, gives an index where the original string has a '1'.
But how to compute this efficiently?
Let me think about the number of times each position is hit in the range of k from 1 to R.
Each position i (from 0 to n-1) will be hit once for each occurrence of (k-1) mod n = i, where k is in 1..R. So for each i, how many times does it occur in the range 1..R?
Let me think. For a given i, the values of k that satisfy (k-1) mod n = i are k = i + 1 + m * n, for m ≥ 0. So for k in 1..R, how many such values?
Let me find for each i, the number of times that (k-1) mod n = i, which is equivalent to k ≡ i+1 mod n. But k ranges from 1 to R. So the number of times is equal to the number of integers in [1, R] congruent to (i+1) mod n.
But perhaps a better way: For a given i, the k values that would hit this position are k = i+1, i+1 + n, i+1 + 2n, etc. So the number of such k's up to R is floor( (R - (i+1)) / n ) + 1 if (i+1) ≤ R. Otherwise 0.
But perhaps there's a simpler way. For each position i, the number of times it is hit in the range 1..R is equal to the number of times that (k-1) mod n = i, which is the same as the number of times that k-1 is congruent to i mod n. Which is the same as the number of times k is congruent to (i+1) mod n. So for k in 1..R, the count is floor( (R - (i+1)) / n ) + 1 if i+1 <= R. Else 0. But maybe there's a simpler formula.
Alternatively, the total number of times a position i is hit is equal to the number of integers in the range [1, R] that are congruent to (i+1) mod n. Which can be calculated as:
count = (R - (i+1) + n) // n if (i+1) <= R else 0. Or perhaps:
count = (R - (i+1)) // n + 1 if (i+1) <= R else 0.
But perhaps another approach: the number of times is equal to the number of full cycles plus the remainder. For example, the total number of times is equal to the floor( (R) / n ), and then plus 1 if the remainder is >= (i+1).
Wait, maybe it's easier to think of the total number of times that position i is hit is equal to the number of times that (k-1) is equal to i mod n, for k from 1 to R. So (k-1) ranges from 0 to R-1. So the number of times that (k-1) mod n = i is equal to the number of integers in 0..R-1 that are congruent to i mod n. Which is:
Let total = R
number = (total - i - 1) // n + 1 if i < total else 0.
Wait, no. For example, for the numbers from 0 to R-1, how many are congruent to i mod n?
Let me think of it as the count of x in [0, R-1] where x ≡ i mod n. Let me compute that.
Let m = R-1. The count is floor( (m - i)/n ) + 1 if i <= m. Else 0.
But since i is between 0 and n-1, and m is R-1.
So for each i, the count is:
if i <= m: floor( (m - i)/n ) + 1
else 0.
But m = R-1.
So for example, if R is 6 and n is 6, m=5. For i=5, (5-5)/6 = 0, +1 → 1. Which is correct, since in 0..5, there is exactly one occurrence of 5 mod 6.
So for each position i in the original string, if the character is '1', then the number of times it contributes to the count is the number of times it is hit in the k's from 1 to R. So the total answer is the sum over all i where s[i] == '1' of the count for that i.
So the approach would be:
1. Precompute the positions i where s[i] is '1'.
2. For each such i, compute how many times it is hit in the k's from 1 to R.
3. Sum all those counts.
But how to compute that count for each i?
Let me code that. For example, given R and n, for each i, compute the count.
But let's think of it as follows: the number of times that (k-1) mod n = i, for k from 1 to R is equal to the number of times that (k-1) is in the set {i, i + n, i + 2n, ...} and k-1 <= R-1 (since k ranges up to R).
Which is equivalent to the number of integers t >= 0 such that i + t * n <= R-1.
So solving for t: t <= (R-1 - i)/n.
The number of such t is floor( (R-1 -i)/n ) + 1 if i <= R-1. Else 0.
So for each i, the count is:
if i <= R-1:
count = (R-1 -i) // n + 1
else:
0
But since R can be larger than n, but i is between 0 and n-1, R-1 can be larger than i. So for example, if R is 6 and n is 6, then R-1 is 5, and i ranges up to 5. So for all i, i <= R-1. So the count is (5 -i) //6 +1. For example, i=5: (5-5)/6 = 0 → 0 +1=1. Which is correct.
Another example: R=7, n=6. Then R-1=6. For i=5, (6-5)/6 = 0.2 → floor is 0 → 0+1=1. So the count is 1. But for k=1 to 7, (k-1) ranges from 0 to 6. For i=5, the values are 5 and 5+6=11 (which is beyond 6). So only 5 is in the range. So count is 1. Correct.
Another example: R=7, n=6, i=0. (6-0)/6 = 1.0 → floor is 1 → 1+1=2. Which is correct: 0 and 0+6=6. Both are in 0..6. So count is 2.
So this formula works.
So the steps for the code:
Given the binary string s and R, the
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['011001', 6], ['11011', 5], ['1010', 4], ['1100110011', 5], ['0000', 3], ['10000100110011', 5], ['10000100110011', 3], ['11001100111100110011', 5], ['00011001100110', 4], ['1000110011100110', 4], ['11001100111100110011', 3], ['000110011000', 4], ['110011001111001100110001100111001101', 5], ['000110011000', 5], ['1000110011100110', 3], ['110011001111001100111100110011', 5], ['11001100111110011001111001100110001100111001101100110011', 5], ['00011001100110', 3], ['10001110011100110', 4], ['1000011001100111001100111100111001111001100110001100111001101', 5], ['10001100111001110001100111001100', 3], ['10001100111001110001100111001100', 5], ['110011001111001100111100110011', 4], ['11001100111110011001111001100110001100111001101100110011', 4], ['110011001111001100111100110011', 6], ['11001100111100110011', 6], ['1100110011110011001110100110011', 4], ['110011001111100110011110011001100001100110011', 4], ['1000000110011000110011100110', 4], ['110011001111100110011110011001100011001110101101100110011', 4], ['11001100111100110011', 7], ['110011001111001100110001100111001101', 7], ['1100110011110011001100110011110011001111', 7], ['1000111001111001100111100110011100110', 3], ['1000000110011000110011100110', 3], ['110011001111100110011110011001100011001110101101100110011', 7], ['1000011001100111001100111100111001111001100110001100111001101', 7], ['11001100111100110011110011001', 4], ['00011001100110', 5], ['1000011001100111001100111100111001111001100110001100111001101', 6], ['0001100110010', 5], ['1110011001111001100111100110011001100111110011001111001100110001100111001101100110011', 5], ['1100110011110011001100110011110011001111100110011110011001100011001110011011', 7], ['1100110011110011001111', 4], ['00110011001111001100111010011001100', 3], ['0001100110010', 7], ['11001100111100111100110011110011001100110011110011001111100110011110011001100011001110011011001111', 4], ['1000111001111001100111100110011100110', 4], ['1100110011110011001100110011110011001111', 4], ['11001100111100111000010011001100111100110011', 5], ['00110011001111001100111010011001100', 5], ['10001100111001110001100111001100', 2], ['1100110011110011100001001100110011110011001100110011001111001100111010011001100', 5], ['1000110011100110', 5], ['11001100111100110011110011001', 7], ['001100110011110011001110100110110011001111001100110011001111001100111110011001111001100110001100111001101101100', 5], ['00011110011001111100110011110011001100011001110011011001100110011000', 4], ['1100110011110011001111', 6], ['10001110011110011001111001100011100110', 4], ['11001100111110011001111001100110001100111001101100110011', 3], ['1000000110011000110011100110', 2], ['1100110011110011001100110011110011001111', 2], ['10000100110011', 7], ['1100110001111100110011110011001100011001110101101100110011', 7], ['110011001111001100110001100111001101', 6], ['110011001111001', 4], ['1110011001111001100111100110011001100111110011001111001100110001100111001101100110011', 7], ['11001100011111001100111100110001100011001110101101100110011', 7], ['11001100111100111000010011001100111100110011', 4], ['11001100111100110011101001010011', 3], ['1000110011100110', 6], ['000110011000110011001000110', 4], ['1000110011100111000110011100110011001111001100111100110011100', 7], ['11001100111100110011101001010011', 2], ['110011001111001100011101001010011', 2], ['000110011000110011001000110', 2], ['11001100111100110011101001010011', 1], ['110011001111001110000100110011001111100110011', 5], ['110011001111001100101000110011000111110011001111001100011000110011101011011001100111100111001101', 5], ['1100110011001100111100110011110011001001100101000110011000111001111001100011000110011101011011001100111100111001101', 5], ['111001100111100110011110010110011', 5], ['110011001111001100110011001111001110000100110011001111100110011011101001010011', 5], ['1000011001100111001100111100111001111001100110001100111001101', 4], ['110011001111001100110001100111001101', 8], ['110011001111001100110011001111001110000100110011001111100110011011101001010011', 1], ['1000110011100110', 7], ['110011001111100110011110011001100001100110011', 7], ['11001110011001111001100110001100111001101100111100111000010011001100111100110011', 6], ['1100110011110011000111001001010011', 5], ['110011001111001100111001001010011', 2], ['0001100011000110011001000110', 8], ['1100110011110011100001001100110011111100110011110011001110100110011100110011', 5], ['1000000110011000110011100110', 7], ['001100110011110011001110100110110011001111001100110011001111001100111110011001111001100110001100111001101101100', 4], ['11001100111100110011110011001', 8], ['000110011000110011001000110', 5], ['110011001111001100011101001100110011110011001110100110110011001111001100110011001111001100111110011001111001100110001100111001101101100001010011', 2], ['11001100111100111100110011110011001100110011110011001111100110011110011001100011001110011011001111', 7], ['1100110100110011', 6], ['111001100111100110011110010110011', 7], ['110011001111001100111001001010011', 6], ['11001100111100110011110011001', 5], ['11100110011110011001111001100110011001111100110011110011001100011001110011100110011110011001111001100110011001111100110011110011001100011001110011011001100111', 7], ['11001100111110011001111001100110001100111001101100110011', 6], ['0001110000001100110001100111001101001000110', 4]]
results = [3, 4, 2, 3, 0, 1, 1, 3, 1, 1, 2, 1, 3, 2, 1, 3, 3, 0, 1, 1, 1, 2, 2, 2, 4, 4, 2, 2, 1, 2, 4, 4, 4, 1, 1, 4, 3, 2, 2, 2, 2, 3, 4, 2, 1, 2, 2, 1, 2, 3, 2, 1, 3, 2, 4, 2, 1, 4, 1, 2, 1, 2, 2, 4, 4, 2, 5, 4, 2, 2, 3, 1, 3, 2, 2, 0, 1, 3, 3, 3, 3, 3, 1, 4, 1, 3, 4, 4, 3, 2, 2, 3, 1, 2, 4, 2, 2, 4, 4, 5, 4, 3, 5, 4, 1]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(odd_Equivalent(*inp), exp, 0)
| OK=False
==================== Problem #63 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the common elements in given nested lists.
Your answer will be tested on test cases like:
assert set(common_in_nested_lists([[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]))==set([18, 12])
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the common elements in given nested lists.
Your answer will be tested on test cases like:
assert set(common_in_nested_lists([[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]))==set([18, 12])
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the common elements in given nested lists.
Your answer will be tested on test cases like:
assert set(common_in_nested_lists([[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]))==set([18, 12])
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the common elements in given nested lists.
Your answer will be tested on test cases like:
assert set(common_in_nested_lists([[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]))==set([18, 12])
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the common elements in given nested lists.
Your answer will be tested on test cases like:
assert set(common_in_nested_lists([[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]))==set([18, 12])
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called common_in_nested_lists that finds the common elements in given nested lists. The test case provided expects the function to return a set containing 12 and 18 when given three lists. Let me think about how to approach this.
First, the problem is to find elements that are present in all of the nested lists. So, for each element in the first list, I need to check if it exists in all the other lists. But how do I handle multiple lists?
Wait, maybe I can use Python's set operations. The intersection of all the lists would give the common elements. But since the input is a list of lists, I need to convert each sublist into a set and then find the intersection of all those sets.
Right. So the steps could be:
1. Convert each of the nested lists into a set.
2. Find the intersection of all these sets.
But how to do that in Python? The set.intersection method can take multiple sets. Alternatively, I can use the reduce function from functools to compute the intersection across all sets.
Let me think. For example, if the input is [[12, 18, ...], [7, 12, 18...], ...], converting each to a set gives {12, 18, ...}, then the intersection of all these sets would be {12, 18}.
So the plan is:
- Take the list of lists as input.
- Convert each sublist to a set.
- Compute the intersection of all these sets.
But how to handle the initial step? Let's see. For the first list, convert to a set. Then for each subsequent list, take the intersection with the current result.
So, for example, start with the first set. Then for each next set, do current_set = current_set.intersection(next_set).
So, using reduce with the intersection operation.
Yes. So, in code:
from functools import reduce
def common_in_nested_lists(nested_lists):
# Convert each sublist to a set
sets = [set(lst) for lst in nested_lists]
# Compute the intersection of all sets
common = reduce(lambda s1, s2: s1.intersection(s2), sets)
return list(common)
Wait, but what if there are zero lists? Well, the problem probably assumes that the input is non-empty. But given the test case, the function is expected to handle at least three lists.
Testing the sample input:
nested_lists = [[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]
sets would be {12, 18, 23, 25, 45}, {7, 12, 18, 24, 28}, {1,5,8,12,15,16,18}
The intersection of all three would be {12, 18}, which matches the test case.
But the function returns a list. The test case uses set(common_in_nested_lists(...)) == set([18, 12]). So the order doesn't matter. So returning a list is okay, as converting it to a set would match.
But perhaps the function should return a set? However, the test case expects the function to return a list, because when you convert the result to a set, it matches. But the problem says "find the common elements" and the sample returns a list. However, the test case uses set() on the result. So maybe the function can return a list, but the order is not important.
But the problem says that the answer will be tested with the assert statement. So the function must return a list, but the order of elements in the list doesn't matter because the test uses set().
So the code as written would work.
But wait, what if there are no common elements? Then the function would return an empty list, which is correct.
Another edge case: if there's only one list, then all elements are common. So the function would return that list as a list.
But the problem says "given nested lists" which probably implies that there are multiple lists. But the code would handle that.
Now, the code needs to be self-contained. So the function must be written, and the code must import reduce from functools.
Wait, in Python 3, reduce is in functools, so the code needs to import that.
So putting it all together:
The code would be:
from functools import reduce
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
common = reduce(lambda s1, s2: s1.intersection(s2), sets)
return list(common)
Wait, but what if the nested_lists is empty? Well, the problem's test case has three lists. So perhaps the function is supposed to handle that.
But in the case of empty input, the code would throw an error. However, the problem's test cases probably don't include that.
Testing the sample input:
The code would return [12, 18], but the order may vary. However, when converted to a set, it's correct.
So the code should work.
But the problem says that the function should return the common elements. So the code seems correct.
Another way is to use set.intersection(*sets), but that requires that the sets are passed as arguments. For example:
common = set.intersection(*sets)
But in Python, the * operator can unpack the list of sets. However, if the list is empty, this would cause an error. But assuming that the input is non-empty, this would work.
So perhaps the code can be written as:
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
Wait, but set.intersection(*sets) would take all the sets as arguments. For example, if sets is [s1, s2, s3], then set.intersection(*sets) is equivalent to s1.intersection(s2, s3). Which would be the same as the reduce approach.
But how does that work? Let me check. The set.intersection method can take multiple arguments. So if you have multiple sets, you can pass them all as arguments to intersection.
So for example, set1.intersection(set2, set3) returns the intersection of all three.
So in code, if sets is a list of sets, then set.intersection(*sets) would compute the intersection of all of them. But the first set is the first element of the list. Wait, no. Because set.intersection(*sets) is equivalent to set1.intersection(set2, set3, ...). So the first set is the one that's being called, and the rest are the arguments. But in this case, the *sets would unpack all the sets as arguments. So the first set is the first element of the list, and the rest are the others. So the code would work.
But what if the list is empty? Well, the code would throw an error. But given the test case, it's probably safe.
So the code can be simplified to:
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
But wait, in Python, the set.intersection method returns a new set containing elements that are in all the sets. So passing *sets would unpack all the sets as arguments. So this should work.
Testing this with the sample input:
sets = [ {12, 18, 23, 25, 45}, {7, 12, 18, 24, 28}, {1,5,8,12,15,16,18} ]
set.intersection(*sets) would be the same as the first set intersected with the second and third. Which gives {12, 18}.
Yes.
So this approach is more concise.
But what if the nested_lists is empty? Well, the problem's test cases probably don't include that. So the code would work.
So the code can be written as:
import functools
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
Wait, but in Python, the set.intersection method can take multiple arguments. So when you do set.intersection(*sets), it's equivalent to passing all the sets as arguments. So this code would work.
But what if there are zero lists? Well, the code would have sets being an empty list. Then set.intersection(*sets) would be set.intersection() which returns a new set. But that's not correct. However, the problem's test cases probably have at least one list. But if the input is empty, this code would return a list of the elements of the empty set, which is empty. But in reality, if there are no lists, the common elements would be undefined. But the problem's test cases probably don't have that scenario.
But given the test case provided, this code should work.
So the code can be written as such. Now, the code needs to be self-contained. So the function must be written, and the code must import the necessary modules. However, in this case, the code doesn't need to import functools because the reduce approach is not needed. The set.intersection(*sets) approach is more concise.
But wait, in Python, the * operator in the function call would unpack the list of sets. So for example, if sets is [s1, s2, s3], then set.intersection(*sets) is equivalent to s1.intersection(s2, s3). But the first argument is the set that is called. So, in this case, the code is using the first set as the one to call intersection on, and then passing the rest as arguments. However, the set.intersection method can take multiple arguments. So this should work.
But what if the list of sets is empty? Well, then *sets would be nothing, and set.intersection() would return a new set. But that's not correct. However, the problem's test case probably doesn't have that scenario.
So, the code is correct for the given test case.
So the final code would be:
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
Wait, but how is the first set passed? Because set.intersection(*sets) would take the first set as the first argument. Wait, no. The set.intersection method is called on a set instance. For example, set1.intersection(set2, set3). So, in the code, when you do set.intersection(*sets), the first element of sets is passed as the first argument, and the rest are the other arguments. But the code is using set.intersection, which is a method of the set class. Wait, no. The code is written as set.intersection(*sets). But set is the class, not an instance. So this would be equivalent to calling the intersection method of the set class, which is not correct.
Wait, no. Wait, the set.intersection method is a method of the set class. So, for example, if you have a set s, then s.intersection(*others) returns the intersection. However, if you call set.intersection(*sets), that's equivalent to calling the method on the set class, which would require the first argument to be the set. Wait, no. The syntax is:
set.intersection(*others) is the same as the method of the set instance. But when you call set.intersection(*sets), you're actually calling the method on the set class, which requires that the first argument is the set. Wait, no. Let me think. For example:
s = {1, 2, 3}
s.intersection(t) is the same as set.intersection(s, t). But if you call set.intersection(s, t), that's the same as s.intersection(t). So, when you do set.intersection(*sets), you are passing the first set as the first argument, and the rest as the others. But in this case, the code is written as set.intersection(*sets), which would be equivalent to passing all the sets as arguments to the intersection method. However, the first argument is the set that is being used as the initial set. So, for example, if sets is [s1, s2, s3], then set.intersection(*sets) is equivalent to s1.intersection(s2, s3). But how does that work? Because the first argument is the set on which the method is called. Wait, no. The set.intersection method is called on an instance. So, if you have:
sets = [s1, s2, s3]
then set.intersection(*sets) would be the same as set.intersection(s1, s2, s3). But that's not correct. Because the first argument is the set that the method is called on. Wait, no. The syntax is that when you call set.intersection(*others), it's equivalent to the method being called on the first argument, and the rest are the others. But how?
Actually, in Python, when you call a method as a class method, like set.intersection(*args), it's equivalent to the method being called on the first argument. For example, set.intersection(s1, s2, s3) is equivalent to s1.intersection(s2, s3). So, in this case, if the sets list is [s1, s2, s3], then set.intersection(*sets) is equivalent to s1.intersection(s2, s3). Which is correct. So the code would work.
But what if the sets list is empty? Then set.intersection() would be called with no arguments. But that's not correct. However, the problem's test cases probably don't include that.
So the code would work for the given test case.
But wait, in the code, the line is set.intersection(*sets). But sets is a list of sets. So, for example, in the test case, sets is [s1, s2, s3], and set.intersection(*sets) is equivalent to s1.intersection(s2, s3). Which is correct.
So the code would return the correct elements.
So the code can be written as such.
But then, what if the nested_lists is empty? Well, the code would have sets being an empty list. Then, set.intersection(*sets) would be set.intersection(), which returns a new empty set. But that's not correct. However, the problem's test case probably doesn't have that scenario.
So the code seems correct.
So the final Python code would be:
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
But wait, in Python, the set.intersection(*others) method returns a new set containing elements that are in all the sets. So, when we pass *sets, which is all the sets in the list, the code should work.
But let's test this with the sample input.
Sample input: [[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]
sets = [ {12, 18, 23, 25, 45}, {7, 12, 18, 24, 28}, {1,5,8,12,15,16,18} ]
set.intersection(*sets) would be the intersection of all three sets, which is {12, 18}.
Yes.
So the code should work.
But in Python, when you call set.intersection(*sets), the first set is the first argument, and the rest are the others. So the code is correct.
But what if the nested_lists has only one list? Then, sets is [s1], and set.intersection(*sets) is set.intersection(s1), which returns s1. Which is correct, because all elements in the single list are common.
So this code should handle that.
Therefore, the code is correct.
Now, the problem requires that the function returns a list. The code returns a list of the elements in the intersection. The test case uses set(common_in_nested_lists(...)) == set([18, 12]), which would be true because the order doesn't matter.
Thus, the code should pass the test case.
Now, the code must be written as a self-contained Python function. The code does not need to import anything except for the standard libraries. However, the code uses set.intersection(*sets), which is part of the standard Python set methods.
So the final code is:
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
But wait, in Python, the set.intersection method can take multiple arguments. However, when you do set.intersection(*sets), the first element of the sets list is passed as the first argument, and the rest are passed as additional arguments. So, for example, if sets is [s1, s2, s3], then set.intersection(*sets) is equivalent to s1.intersection(s2, s3), which is correct.
Yes.
Thus, this code should work.
```python
def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets))
```
----------------------------------------------
Result: Pred=def common_in_nested_lists(nested_lists):
sets = [set(lst) for lst in nested_lists]
return list(set.intersection(*sets)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
out = set(out)
exp = set(exp)
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[[12, 18, 23, 25, 45], [7, 12, 18, 24, 28], [1, 5, 8, 12, 15, 16, 18]]], [[[12, 5, 23, 25, 45], [7, 11, 5, 23, 28], [1, 5, 8, 18, 23, 16]]], [[[2, 3, 4, 1], [4, 5], [6, 4, 8], [4, 5], [6, 8, 4]]], [[[], [], []]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [5, 6, 7, 8, 9]]], [[[1, 3, 5, 7, 9], [2, 4, 6, 8, 10], [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]]], [[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12], [13, 14, 15]]], [[[1, 2, 3, 4], [2, 3, 4, 5], [3, 4, 5, 6], [4, 5, 6, 7]]], [[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]], [[[], [], [], []]], [[[1, 2, 3, 4], [2, 3, 4, 5], [3, 4, 5, 6, 3], [3, 4, 5, 6, 3]]], [[[1, 2, 3, 4], [2, 3, 4, 5], [2, 4, 5, 6, 3], [2, 4, 5, 6, 3], [2, 4, 5, 6, 3]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [6, 7, 8, 9]]], [[[], []]], [[[1, 2, 3, 4, 5], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 4], [2, 15, 4, 5], [2, 15, 4, 5], [3, 4, 5, 6], [4, 5, 6, 7], [2, 15, 4, 5]]], [[[1, 2, 3, 2], [4, 5, 6], [7, 8, 9], [1, 2, 3, 2], [10, 11, 12], [13, 14, 15]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [5, 6, 7, 8, 9]]], [[[1, 2, 3, 4], [2, 3, 4, 5], [2, 4, 5, 6, 3], [2, 4, 5, 6, 3], [2, 4, 5, 6, 3], [1, 2, 3, 4]]], [[[1, 2, 3, 4, 5], [2, 6, 8, 10], [1, 3, 5, 7, 9]]], [[[], ['pesDUr', 'hHJC', 'tENrXrt', 'dFybnG', 'z', 'UymdT', 'G', 'UbwECYme'], [], []]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7, 6], [3, 4, 5, 6, 7, 6], [4, 5, 6, 7, 8]]], [[[1, 2, 3, 4], [2, 3, 4, 5], [3, 4, 5, 6, 3], [3, 4, 5, 6, 3], [3, 4, 5, 6, 3]]], [[[1, 2, 3, 2], [4, 5, 6], [7, 8, 9], [1, 2, 3, 2], [10, 11, 12], [13, 14, 15], [13, 14, 15]]], [[[1, 2, 2], [4, 5, 6], [6, 7, 8, 9], [1, 2, 2], [10, 11, 12], [13, 14, 15]]], [[[1, 2, 3, 4, 5], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10]]], [[[9, 8, 7, 6, 5], [13, 6, 7, 8, 9], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [13, 6, 7, 8, 9]]], [[[9, 8, 7, 6, 5], [13, 6, 7, 8, 9], [5, 5, 13, 6, 7, 8, 9], [5, 5, 13, 6, 7, 8, 9], [9, 8, 7, 6, 5], [13, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 4, 8, 10], [1, 3, 5, 7, 9], [1, 3, 5, 7, 9]]], [[[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12], [7, 8, 9]]], [[[1, 2, 3, 4], [2, 15, 4, 5, 4], [2, 15, 4, 5, 4], [3, 4, 5, 6], [4, 5, 6, 7], [2, 15, 4, 5, 4], [2, 15, 4, 5, 4]]], [[[2, 4, 6, 8, 10]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 4], [2, 15, 4, 5, 4, 4], [2, 15, 4, 5, 4, 4], [2, 15, 4, 5, 4, 4], [3, 4, 5, 6], [4, 5, 6, 7], [2, 15, 4, 5, 4, 4], [2, 15, 4, 5, 4, 4], [4, 5, 6, 7]]], [[[1, 2, 3, 3], [4, 5, 6], [7, 8, 9, 9], [10, 11, 12], [7, 8, 9, 9], [13, 14, 15]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5, 9], [5, 6, 7, 8, 9], [5, 6, 7, 8, 9]]], [[[1, 2, 3, 4], [2, 15, 4, 5], [2, 15, 4, 5], [3, 4, 5, 6], [5, 5, 6, 7], [2, 15, 4, 5]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9, 9], [5, 6, 7, 8, 9, 9], [9, 8, 7, 6, 5], [9, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 15, 6, 7, 6], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5]]], [[[1, 2, 3, 4, 5, 3], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1]]], [[[9, 2, 3], [4, 5, 6], [8, 9, 9], [10, 11, 12], [8, 9, 9], [8, 9, 9]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [1, 2, 3, 4, 5]]], [[[9, 8, 7, 6, 5], [13, 6, 7, 8, 9], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [13, 6, 7, 8, 9], [5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [1, 2, 3, 4, 5]]], [[[1, 2, 3, 4, 5, 3], [2, 4, 14, 8, 10], [2, 4, 14, 8, 10], [2, 4, 6, 8, 10], [2, 4, 14, 8, 10]]], [[[4, 5, 6, 7, 8, 8], [1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8, 8]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5]]], [[[1, 2, 3, 4, 5], [4, 5, 6, 7], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7, 6], [4, 5, 6, 7]]], [[[1, 2, 3], [4, 5, 6], [10, 11, 12], [7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 15, 6, 7, 6], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5], [2, 3, 4, 5, 6]]], [[[13, 15, 14, 15], [1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12], [13, 15, 14, 15]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 6, 8, 7, 6], [3, 4, 5, 6, 8, 7, 6], [3, 4, 5, 6, 8, 7, 6], [4, 5, 6, 7, 8]]], [[[1, 2, 3, 4, 5, 3], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 4, 5], [4, 3, 4, 5, 6], [4, 3, 4, 5, 6], [3, 4, 5, 6, 7], [4, 5, 6, 7, 8]]], [[[1, 2, 3, 4, 5], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10]]], [[[4, 4, 6], [1, 2, 3], [4, 4, 6], [7, 8, 9], [10, 11, 12]]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5]]], [[[1, 2, 3, 3], [4, 5, 6], [10, 11, 12], [7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10], [1, 2, 3, 4, 5], [2, 4, 6, 8, 10]]], [[[1, 2, 3], [7, 8, 9], [10, 11, 12]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1]]], [[[5, 6, 7, 8, 9], [9, 8, 7, 6, 5]]], [[[7, 7, 9, 9], [1, 2, 3, 3], [4, 5, 6], [7, 7, 9, 9], [10, 11, 12], [7, 7, 9, 9], [13, 14, 15]]], [[[1, 2, 3, 2], [4, 5, 6], [7, 8, 9], [1, 2, 3, 2], [10, 1, 11, 12], [13, 14, 15], [1, 2, 3, 2]]], [[[12, 1, 2, 3, 3], [4, 5, 6], [10, 11, 12], [7, 8, 9]]], [[[1, 2, 3, 3], [4, 5, 6], [7, 8, 9, 9], [11, 10, 11, 12], [11, 10, 11, 12], [7, 8, 9, 9], [13, 14, 15]]], [[[2, 15, 4, 5], [2, 15, 4, 5], [3, 4, 5, 6], [4, 5, 6, 7], [2, 15, 4, 5]]], [[[1, 2, 3, 4, 5], [3, 4, 5, 6], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8], [3, 4, 5, 6], [1, 2, 3, 4, 5]]], [[[12, 1, 2, 3, 3], [4, 5, 6], [10, 11, 11, 12], [7, 2, 8, 9]]], [[[1, 2, 3, 4, 5, 1], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]], [[[10, 8, 11, 12], [12, 1, 2, 3, 3, 3], [4, 5, 6], [10, 8, 11, 12], [7, 8, 9], [10, 8, 11, 12]]], [[[2, 3, 4, 5], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10]]], [[[1, 2, 3, 3], [4, 5, 6], [10, 11, 12], [7, 8, 9], [7, 8, 9]]], [[[10, 8, 7, 6, 5], [9, 8, 7, 6, 4], [5, 6, 7, 8, 9], [10, 8, 7, 6, 5]]], [[[87.07763738802882], [], [], []]], [[[1, 2, 3, 4, 5], [2, 3, 4, 5, 6], [3, 4, 5, 15, 6, 7, 6], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8]]], [[[3, 4, 5, 6, 3], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7, 8], [1, 2, 3, 4, 5]]], [[[1, 2, 3, 4, 5], [2, 4, 8, 10], [1, 3, 5, 7, 9], [1, 3, 5, 7, 9], [2, 4, 8, 10]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9, 1]]], [[[1, 2, 3, 4, 5], [2, 4, 8, 10], [1, 3, 5, 7, 9], [1, 3, 5, 7, 9], [1, 3, 5, 7, 9]]], [[[5, 6, 7, 8, 9], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [9, 8, 7, 6, 5]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10]]], [[[7, 8, 13], [1, 2, 3], [4, 5, 6], [7, 8, 13]]], [[[1, 2, 3], [7, 8, 9], [10, 11, 12], [10, 11, 12]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5]]], [[[1, 2, 3, 4, 5], [2, 2, 4, 8, 10], [1, 3, 5, 7, 9], [1, 3, 5, 7, 9], [2, 2, 4, 8, 10]]], [[[9, 8, 4, 7, 6, 5], [5, 6, 7, 8, 9], [5, 6, 7, 8, 9]]], [[[1, 2, 3, 4, 5], [2, 4, 8, 10], [1, 3, 5, 7, 9], [2, 4, 8, 10], [2, 4, 8, 10]]], [[[9, 8, 7, 6, 5, 8], [9, 8, 7, 6, 5, 8], [5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [9, 8, 7, 6, 5, 8]]], [[[5, 6, 7, 8, 9], [9, 8, 7, 6, 5], [5, 6, 7, 8, 9]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9, 8], [9, 8, 7, 6, 5], [6, 7, 8, 9]]], [[[4, 5, 6], [6, 7, 8, 9], [1, 2, 2], [10, 11, 12], [13, 14, 15], [1, 2, 2]]], [[[1, 2, 3, 4, 5], [2, 4, 8, 10], [1, 4, 5, 7, 9], [1, 4, 5, 7, 9], [2, 4, 8, 10]]], [[[1, 2, 3, 3], [4, 5, 6], [7, 7, 9, 9], [7, 7, 9, 9], [13, 14, 15]]], [[[1, 2, 3, 3], [4, 5, 6], [7, 8, 9]]], [[[9, 8, 7, 6, 5], [5, 6, 7, 8, 9, 6], [5, 6, 7, 8, 9, 6]]], [[[4, 5, 6], [10, 11, 12], [7, 8, 9]]], [[[13, 15, 14, 15], [1, 2, 3], [4, 5, 6], [7, 13, 8, 9], [7, 13, 8, 9], [10, 11, 12], [13, 15, 14, 15]]], [[[1, 2, 3, 4, 5], [2, 4, 6, 8, 10], [2, 4, 6, 8]]], [[[1, 2, 3, 4, 5, 3], [2, 4, 6, 8, 10], [1, 3, 5, 7, 9], [2, 4, 6, 8, 10]]], [[[5, 6, 7, 8, 9, 6], [9, 8, 7, 6, 5]]], [[[10, 8, 11, 2, 12], [12, 1, 4, 3, 3, 3], [4, 5], [12, 1, 4, 3, 3, 3], [10, 8, 11, 2, 12], [7, 8, 9], [10, 8, 11, 2, 12]]], [[[1, 2, 3, 4, 5], [1, 3, 5, 4, 9, 1], [2, 4, 6, 8, 10], [2, 4, 6, 8, 10], [1, 3, 5, 4, 9, 1]]], [[[1, 2, 3, 4, 5], [3, 4, 5, 6, 7, 6, 7], [2, 3, 4, 5, 6], [3, 4, 5, 6, 7, 6, 7], [3, 4, 5, 6, 7, 6, 7], [4, 5, 6, 7, 8], [3, 4, 5, 6, 7, 6, 7]]], [[[5, 2, 3, 4, 5], [3, 4, 5, 6], [4, 5, 6, 7], [5, 2, 3, 4, 5], [3, 4, 5, 15, 6, 7, 6], [4, 5, 6, 7], [3, 4, 5, 6], [5, 2, 3, 4, 5], [3, 4, 5, 6]]], [[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]]
results = [[18, 12], [5, 23], [4], [], [4, 5], [5, 6, 7, 8, 9], [], [], [4], [], [], [], [], [3, 4], [2, 3, 4], [8, 9, 6, 7], [], [], [], [4], [], [5, 6, 7, 8, 9], [2, 3, 4], [], [], [4, 5], [3, 4], [], [], [], [8, 9, 6, 7], [8, 9, 6, 7], [], [], [4], [2, 4, 6, 8, 10], [], [4], [], [5, 6, 7, 8, 9], [], [4, 5], [8, 9, 6, 7], [4, 5], [2, 4], [], [], [4, 5], [8, 9, 6, 7], [3, 4, 5], [2, 4], [4, 5], [5, 6, 7, 8, 9], [4, 5], [], [4, 5], [], [4, 5], [2, 4], [4, 5], [], [], [4, 5], [], [], [], [], [5, 6, 7, 8, 9], [], [], [], [], [4, 5], [4, 5], [], [], [], [], [], [8, 6, 7], [], [4, 5], [4, 5], [], [5, 6, 7, 8, 9], [], [], [5, 6, 7, 8, 9], [2, 4], [], [], [5, 6, 7, 8, 9], [], [5, 6, 7, 8, 9], [], [5, 6, 7, 8, 9], [5, 6, 7, 8, 9], [8, 9, 6, 7], [], [4], [], [], [5, 6, 7, 8, 9], [], [], [2, 4], [], [5, 6, 7, 8, 9], [], [4], [4, 5], [4, 5], []]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(common_in_nested_lists(*inp), exp, 0)
| OK=True
==================== Problem #64 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string represents an integer or not.
Your answer will be tested on test cases like:
assert check_integer("python")==False
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string represents an integer or not.
Your answer will be tested on test cases like:
assert check_integer("python")==False
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string represents an integer or not.
Your answer will be tested on test cases like:
assert check_integer("python")==False
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string represents an integer or not.
Your answer will be tested on test cases like:
assert check_integer("python")==False
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to check if a string represents an integer or not.
Your answer will be tested on test cases like:
assert check_integer("python")==False
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called check_integer that determines if a given string represents an integer. Let's think about how to approach this.
First, what defines a string being an integer? Well, integers can be positive, negative, or zero. They don't have decimal points. So the string should consist of optional leading '+' or '-' followed by one or more digits. But wait, there's a catch. If the string is empty, or has other characters, it's not valid.
So maybe using a regular expression would be the way to go. Regular expressions can accurately check the pattern of the string.
Let me think about the regex pattern. The string can start with an optional '+' or '-', then one or more digits. So the pattern would be something like ^[+-]?\d+$. But wait, the ^ and $ ensure that the entire string matches this pattern. Let me test some examples.
For example, "123" should match. "-456" should match. "+789" should match. "0" is okay. But "12.3" would have a decimal point, which is not allowed. Also, strings like "abc" or "12a" should not match.
But wait, what about leading zeros? Like "0005"? Well, the problem says it's supposed to check if the string represents an integer. In Python, integers can have leading zeros in strings, but when converted, they are treated as valid. For example, int("0005") is 5. So the function should return True for such cases. So the regex doesn't need to check for leading zeros; the presence of digits is enough.
So the regex pattern would be ^[+-]?\d+$. But wait, the string can't be empty. So the \d+ ensures there's at least one digit.
So the function can use re.fullmatch to check if the entire string matches this pattern.
So the steps are:
1. Import the re module.
2. Define the function check_integer(s).
3. Use re.fullmatch with the pattern ^[+-]?\d+$ to check the string.
4. Return True if there's a match, else False.
Wait, but what about cases where the string is something like "+123a"? The regex would not match because of the 'a' at the end. So that's handled.
Let me test some examples:
Test case 1: "python" → should return False. The regex doesn't match, so correct.
Test case 2: "123" → returns True.
Test case 3: "-456" → True.
Test case 4: "+789" → True.
Test case 5: "0" → True.
Test case 6: "000" → True.
Test case 7: "12.3" → False.
Test case 8: "12a" → False.
Test case 9: "" → empty string, returns False.
Another edge case: "+" → no digits, so returns False. Similarly for "-".
So the regex should handle these cases.
So the code would be:
import re
def check_integer(s):
return bool(re.fullmatch(r'[+-]?\d+', s))
Wait, but re.fullmatch requires the entire string to match. So the pattern is correct.
But wait, in Python, the re module's fullmatch function returns a match object if the entire string matches the pattern. So converting it to bool would return True if there's a match, else False.
Yes.
But what about leading '+' or '-' with no digits? Like "+" or "-". The \d+ requires at least one digit, so those cases would return False. Which is correct.
So this function should handle all the cases.
Let me test the sample test case given: assert check_integer("python") == False. That would be True, since "python" doesn't match the regex.
Another test case: check_integer("123") → True.
Another test case: check_integer("-123") → True.
What about check_integer("+123") → True.
Yes.
So this should work.
So the code is as follows.
```python
import re
def check_integer(s):
return bool(re.fullmatch(r'[+-]?\d+', s))
```
----------------------------------------------
Result: Pred=import re
def check_integer(s):
return bool(re.fullmatch(r'[+-]?\d+', s)) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['python'], ['1'], ['12345'], [''], ['-5'], ['10'], ['-100'], ['100000'], [' 15'], ['25 '], [' -200 '], ['123a'], ['-b456'], ['!7890@'], ['12ab34'], ['5@678'], ['123.45'], ['1,000'], ['1,0'], ['+123'], ['-987'], [' 1 2 3 '], [' 1 2 '], [' '], ['-b45b6'], [' '], ['-9+1237'], ['6-b456'], ['5 1 2 @678'], [' 1 2 '], ['123.4 -200 '], ['12ab324'], ['5 1 2 @678'], ['125,000'], ['123.4.5'], ['12ab341'], ['5'], ['--5'], ['1235'], ['6-b 1 2 456'], ['456'], ['12ab1235341'], ['-97'], ['6-b 1 2 1235 456'], [' 1 2 3 '], ['123.4 -200 4 '], ['1423.45'], ['4'], ['1423.5'], ['123.4 -212ab34100 '], ['12ab1235123.4 -200 4 341'], ['-212ab34100'], ['12ab13235123.4 -200 4 341'], ['-2132ab341012ab3240'], ['@@678'], [' 12ab324 1 1 2 '], ['@678'], ['44'], ['-9+14422371,000'], ['12ab21235341'], ['6-b 1 -2002 12355 456'], ['-2005'], ['12ab1235123.4'], ['-2-9+123712ab34100'], [' -2000 '], ['VuNmzvmS'], ['3'], ['12ab123512312ab1235123.4.4'], ['1,0456'], [' '], ['12ab3-b45641'], ['142443.45'], ['9-97'], ['123.4123.4 -2120ab34100 '], ['123.46-b4565'], ['125,000-20004'], ['123.4'], [' 12ab324 1 1 '], ['!790@'], ['-b412ab123-53415b6'], ['123.5'], ['0 -2000 '], [' 12ab324 1 1 '], ['11,0'], ['444'], ['6-b 12ab13235123.4 -200 4 341 1 2 456'], ['12aab13235123.4'], ['123.4 -206-b 1 2 1235 4560 '], ['-2123.5132ab341012ab3240'], ['-200'], ['-212a123.4 -212ab34100 34100'], [' 15'], [' 12ab324 a123.45 1 1 2 '], ['@@7678'], ['6-b 1 2 1235 456!790@'], ['15'], ['0 -2000 0 '], ['--55'], [' 1 2 '], ['141,045623.5'], ['1123.4 1 2 5'], ['12ab123512312a2b1235123.4.4'], ['0 -2000 0 -100'], [' 12ab324 a123.4 12ab324 1 1 2 '], ['12a1123.4 1 2 5b123.4..54'], ['6-b VuNmzvmS1 2 1235 456'], ['456!790@'], ['12ab212351,000341'], ['b-b45b6'], ['1123.4 VuNmzvmS 1 2 5'], ['12ab133235123.4'], ['12ab3-b 12ab324 a123.45 1 1 2 4564'], ['12a1123.4'], ['2ab34 1 2 5'], ['2 5 '], ['DJm'], ['3VuNmzvmS1'], ['12136-b 1 -2002 12355 456a'], ['b-b456'], ['6-b VuNmzNvmS1 2 1235 456'], ['125,00 150004'], ['12136-b 1-2000 -2002 12355 456a'], ['0 -2000 '], ['115']]
results = [False, True, True, None, True, True, True, True, True, True, True, False, False, False, False, False, False, False, False, True, True, False, False, None, False, None, False, False, False, False, False, False, False, False, False, False, True, False, True, False, True, False, True, False, False, False, False, True, False, False, False, False, False, False, False, False, False, True, False, False, False, True, False, False, True, False, True, False, False, None, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True, False, False, False, False, True, False, True, False, False, False, True, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, False, True]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(check_integer(*inp), exp, 0)
| OK=False
==================== Problem #65 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a given tuple of positive integers into a single integer.
Your answer will be tested on test cases like:
assert tuple_to_int((1,2,3))==123
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a given tuple of positive integers into a single integer.
Your answer will be tested on test cases like:
assert tuple_to_int((1,2,3))==123
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a given tuple of positive integers into a single integer.
Your answer will be tested on test cases like:
assert tuple_to_int((1,2,3))==123
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a given tuple of positive integers into a single integer.
Your answer will be tested on test cases like:
assert tuple_to_int((1,2,3))==123
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a given tuple of positive integers into a single integer.
Your answer will be tested on test cases like:
assert tuple_to_int((1,2,3))==123
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called tuple_to_int that takes a tuple of positive integers and converts them into a single integer. Let's see, for example, (1,2,3) becomes 123. So how do I approach this?
Hmm, the tuple elements are digits, right? So each element is a single digit. Wait, but the problem says positive integers. Oh, wait, but the example given is (1,2,3) which are single digits. But what if the tuple has numbers with more than one digit? Wait, the problem says "positive integers", but the example uses single digits. Wait, maybe the tuple is meant to represent digits of a number. But the problem statement says "given tuple of positive integers", so perhaps each element is a positive integer, but when combined, they form a number. For example, (1, 23, 4) would become 1234? Or maybe each element is a single digit. Wait, the example given is (1,2,3) becomes 123, which suggests that each element is a digit. But the problem says "positive integers", which could be numbers like 10, etc. But maybe the problem expects that each element is a single digit. But the problem statement isn't clear. However, the test case given is (1,2,3) which is 123, so perhaps the function is supposed to concatenate the digits. But how to handle numbers with multiple digits?
Wait, maybe the problem is that the tuple is a sequence of digits. So each element is a single digit. So the function should concatenate them. But the problem says "positive integers", which could be numbers like 1, 2, etc. So maybe the function is supposed to take each element as a digit and combine them into a number. For example, (1, 2, 3) becomes 123. So how to do that?
So the approach would be to take each element in the tuple, convert them to strings, concatenate them, then convert the result to an integer. That seems straightforward. Let's test this approach with the example. For (1,2,3), the string would be '123', then converting to int gives 123. That works.
But what if the tuple is empty? Well, the problem says "given tuple of positive integers", so perhaps the input is always a non-empty tuple. But maybe the function should handle empty tuples? However, the test case given is for a non-empty tuple. So perhaps we can assume that the input is a non-empty tuple of positive integers.
So the steps for the function:
1. Iterate over each element in the tuple.
2. Convert each element to a string.
3. Concatenate all the strings.
4. Convert the concatenated string to an integer.
5. Return that integer.
So the code would be something like:
def tuple_to_int(t):
return int(''.join(map(str, t)))
Wait, that's simple. Let's test with the example. (1,2,3) becomes '123' which is 123. That works. What if there's a number with multiple digits? Like (10, 2) would become '102' which is 102. But according to the problem statement, the input is a tuple of positive integers, which could include numbers like 10. But the problem says "convert into a single integer", so this approach would work regardless of the elements being single-digit or not. So this function would handle that.
So the code would be as simple as that. Let me check the test case. The assert statement would be assert tuple_to_int((1,2,3)) == 123. Which would pass.
But what about leading zeros? For example, if the tuple is (0, 1, 2), but the problem says "positive integers", so zero is not allowed. The problem says "positive integers", so the elements are all positive integers. So no leading zeros. So the function is safe.
So the code is straightforward. So the Python function is:
def tuple_to_int(t):
return int(''.join(map(str, t)))
But wait, what if the tuple is empty? But the problem says "given tuple of positive integers", so perhaps the input is always valid. So the code should work.
So the final answer is that function.
```python
def tuple_to_int(t):
return int(''.join(map(str, t)))
```
----------------------------------------------
Result: Pred=def tuple_to_int(t):
return int(''.join(map(str, t))) | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[(1, 2, 3)], [(4, 5, 6)], [(5, 6, 7)], [(123, 456, 789)], [(987, 654, 321)], [(999, 888, 777)], [(10000000000000000000, 9999999999999999999, 8888888888888888888)], [(1234567891011121314, 9876543210987654321, 1111111111111111111)], [(999999999999999999, 999999999999999998, 999999999999999997)], [(123456789123456789, 987654321987654321, 123456789123456789)], [(77777777777777777777, 88888888888888888888, 99999999999999999999)], [(123456789123456789123456789, 987654321987654321987654321, 123456789123456789123456789)], [(9999999999999999998, 9876543210987654321, 1111111111111111111)], [(123456789123456789, 987654321987654321, 123456789123456789, 123456789123456789)], [(789, 1234567891011121314, 9876543210987654321, 1111111111111111111)], [(10000000000000000000, 8888888888888888888)], [(10000000000000000000, 8888888888888888888, 10000000000000000000)], [(123456789123456789, 987654321987654321, 123456789123456789, 9999999999999999999)], [(123456789123456789, 999999999999999998, 77777777777777777777)], [(123456789123456789, 123456789123456789)], [(999, 888, 1234567891011121314)], [(987654321987654321,)], [(123456789123456789, 123456789123456789, 123456789123456789)], [(1234567891011121314, 9876543210987654321, 1234567891011121314, 1111111111111111111)], [(456, 789)], [(10000000000000000000, 8888888888888888888, 10000000000000000000, 77777777777777777777, 10000000000000000000)], [(987, 321)], [(321, 322)], [(1111111111111111111,)], [(1111111111111111110, 1234567891011121314, 9876543210987654321, 1234567891011121314, 1111111111111111111)], [(999, 888)], [(1111111111111111112,)], [(10000000000000000000, 9999999999999999999, 322, 77777777777777777777, 10000000000000000000)], [(999, 654, 888, 777, 888)], [(987, 321, 987)], [(10000000000000000000, 9999999999999999999, 8888888888888888889, 8888888888888888887, 8888888888888888888)], [(10000000000000000000, 8888888888888888889, 8888888888888888888)], [(987, 321, 321)], [(987, 77777777777777777777, 321)], [(999999999999999999, 654)], [(888, 123456789123456789, 123456789123456789)], [(10000000000000000000, 1111111111111111110, 8888888888888888889, 8888888888888888887, 8888888888888888888)], [(1234567891011121314, 9876543210987654321, 1234567891011121314, 1111111111111111111, 1234567891011121314, 1234567891011121314)], [(788, 789, 1234567891011121314, 9876543210987654321, 1111111111111111111)], [(987654321987654321, 987654321987654321)], [(123456789123456789, 8888888888888888887)], [(123, 456, 122, 789)], [(987, 321, 987, 987, 987)], [(789, 1234567891011121314, 9876543210987654321, 1234567891011121314, 1111111111111111111)], [(987,)], [(987654321987654321, 987654321987654321, 987654321987654321)], [(999999999999999998, 123456789123456789, 123456789123456789, 123456789123456789)], [(788, 789, 1234567891011121314, 9876543210987654321, 1111111111111111111, 789)], [(124, 456, 789)], [(123, 456, 789, 123)], [(10000000000000000000,)], [(9876543210987654321, 987, 321)], [(999999999999999999, 987654321987654321, 987654321987654321)], [(88888888888888888888, 77777777777777777777, 88888888888888888888, 99999999999999999999, 88888888888888888888)], [(123456789123456788, 123456789123456789, 123456789123456789123456789)], [(1111111111111111111, 1111111111111111111)], [(999, 888, 1234567891011121314, 999)], [(999, 987654321987654321987654321, 888)], [(77777777777777777777, 88888888888888888887, 99999999999999999999)], [(123, 456, 1234567891011121314, 123)], [(123, 456, 123)], [(777, 8888888888888888889, 8888888888888888888)], [(9999999999999999999, 10000000000000000000)], [(88888888888888888888, 987654321987654321, 987654321987654321)], [(123456789123456789, 9999999999999999999, 123456789123456789)], [(999, 123456789123456789, 987654321987654321, 998, 123456789123456789, 123456789123456789)], [(987, 321, 987, 987, 986, 987)], [(123456789123456789, 987654321987654321, 123456789123456789, 123456789123456789, 123456789123456789)], [(9876543210987654321, 654, 321)], [(123456789123456789, 999999999999999998, 77777777777777777777, 123456789123456789)], [(9999999999999999998, 9876543210987654321)], [(1234567891011121314, 9876543210987654321, 1234567891011121314, 1111111111111111111, 9999999999999999998, 1234567891011121313, 1234567891011121314)], [(788, 789, 9876543210987654321, 1111111111111111111, 789, 789)], [(987, 987)], [(123456789123456789, 987654321987654321, 123456789123456788, 123456789123456789, 123456789123456789)], [(123456789123456789, 987654321987654321, 77777777777777777777, 123456789123456789)], [(123456789123456789, 88888888888888888887, 987654321987654321, 123456789123456789, 123456789123456789, 123456789123456789, 88888888888888888887)], [(123456789123456789, 987654321987654321, 123456789123456788, 123456789123456789)], [(123456789123456790, 987654321987654321, 123456789123456789, 9999999999999999999)], [(321,)], [(987, 8888888888888888888, 321)], [(88888888888888888888, 77777777777777777777, 88888888888888888888, 99999999999999999999, 9876543210987654321, 99999999999999999998, 88888888888888888888)], [(123456789123456789, 123456789123456788, 8888888888888888887)], [(88888888888888888888, 987654321987654321, 987654321987654321, 987654321987654321)], [(1000000000000000000, 999999999999999998, 456)], [(88888888888888888888, 987654321987654321, 987654321987654321, 987654321987654321, 987654321987654321)], [(9876543210987654321, 987, 321, 321)], [(999, 1000, 888, 1234567891011121314)], [(999, 123456789123456789, 987654321987654321, 998, 987654321987654321, 123456789123456789, 123456789123456789)], [(123456789123456789, 987654321987654321, 8888888888888888888, 123456789123456789, 123456789123456789)], [(123, 456, 124, 789, 789, 123)], [(987, 987, 654, 321)], [(999999999999999999, 999999999999999998, 999999999999999997, 999999999999999999)], [(999, 888, 999)], [(1000000000000000000, 124, 456, 789, 789)], [(888, 123456789123456789, 123456789123456789, 123456789123456789)], [(88888888888888888888, 77777777777777777777, 88888888888888888888, 99999999999999999998, 88888888888888888888)], [(999999999999999999, 999999999999999998, 999999999999999997, 999999999999999999, 999999999999999999)], [(1234567891011121314, 9876543210987654321, 888, 1111111111111111111, 9999999999999999998, 1234567891011121313, 1234567891011121314)], [(123456789123456789, 999999999999999999, 8888888888888888887)], [(10000000000000000000, 8888888888888888889, 8888888888888888888, 10000000000000000000)], [(9876543210987654321, 986, 986, 321)], [(123, 124, 456, 789)], [(10000000000000000001, 123456789123456788, 10000000000000000000, 9999999999999999999, 8888888888888888888)], [(1234567891011121314, 9876543210987654322, 1234567891011121314, 1111111111111111111, 1234567891011121314, 1234567891011121314)], [(999999999999999999, 999999999999999998, 999999999999999999)], [(788, 789, 9876543210987654321, 1111111111111111111, 789, 789, 9876543210987654321)]]
results = [123, 456, 567, 123456789, 987654321, 999888777, 1000000000000000000099999999999999999998888888888888888888, 123456789101112131498765432109876543211111111111111111111, 999999999999999999999999999999999998999999999999999997, 123456789123456789987654321987654321123456789123456789, 777777777777777777778888888888888888888899999999999999999999, 123456789123456789123456789987654321987654321987654321123456789123456789123456789, 999999999999999999898765432109876543211111111111111111111, 123456789123456789987654321987654321123456789123456789123456789123456789, 789123456789101112131498765432109876543211111111111111111111, 100000000000000000008888888888888888888, 10000000000000000000888888888888888888810000000000000000000, 1234567891234567899876543219876543211234567891234567899999999999999999999, 12345678912345678999999999999999999877777777777777777777, 123456789123456789123456789123456789, 9998881234567891011121314, 987654321987654321, 123456789123456789123456789123456789123456789123456789, 1234567891011121314987654321098765432112345678910111213141111111111111111111, 456789, 100000000000000000008888888888888888888100000000000000000007777777777777777777710000000000000000000, 987321, 321322, 1111111111111111111, 11111111111111111101234567891011121314987654321098765432112345678910111213141111111111111111111, 999888, 1111111111111111112, 1000000000000000000099999999999999999993227777777777777777777710000000000000000000, 999654888777888, 987321987, 100000000000000000009999999999999999999888888888888888888988888888888888888878888888888888888888, 1000000000000000000088888888888888888898888888888888888888, 987321321, 98777777777777777777777321, 999999999999999999654, 888123456789123456789123456789123456789, 100000000000000000001111111111111111110888888888888888888988888888888888888878888888888888888888, 123456789101112131498765432109876543211234567891011121314111111111111111111112345678910111213141234567891011121314, 788789123456789101112131498765432109876543211111111111111111111, 987654321987654321987654321987654321, 1234567891234567898888888888888888887, 123456122789, 987321987987987, 7891234567891011121314987654321098765432112345678910111213141111111111111111111, 987, 987654321987654321987654321987654321987654321987654321, 999999999999999998123456789123456789123456789123456789123456789123456789, 788789123456789101112131498765432109876543211111111111111111111789, 124456789, 123456789123, 10000000000000000000, 9876543210987654321987321, 999999999999999999987654321987654321987654321987654321, 8888888888888888888877777777777777777777888888888888888888889999999999999999999988888888888888888888, 123456789123456788123456789123456789123456789123456789123456789, 11111111111111111111111111111111111111, 9998881234567891011121314999, 999987654321987654321987654321888, 777777777777777777778888888888888888888799999999999999999999, 1234561234567891011121314123, 123456123, 77788888888888888888898888888888888888888, 999999999999999999910000000000000000000, 88888888888888888888987654321987654321987654321987654321, 1234567891234567899999999999999999999123456789123456789, 999123456789123456789987654321987654321998123456789123456789123456789123456789, 987321987987986987, 123456789123456789987654321987654321123456789123456789123456789123456789123456789123456789, 9876543210987654321654321, 12345678912345678999999999999999999877777777777777777777123456789123456789, 99999999999999999989876543210987654321, 1234567891011121314987654321098765432112345678910111213141111111111111111111999999999999999999812345678910111213131234567891011121314, 78878998765432109876543211111111111111111111789789, 987987, 123456789123456789987654321987654321123456789123456788123456789123456789123456789123456789, 12345678912345678998765432198765432177777777777777777777123456789123456789, 1234567891234567898888888888888888888798765432198765432112345678912345678912345678912345678912345678912345678988888888888888888887, 123456789123456789987654321987654321123456789123456788123456789123456789, 1234567891234567909876543219876543211234567891234567899999999999999999999, 321, 9878888888888888888888321, 8888888888888888888877777777777777777777888888888888888888889999999999999999999998765432109876543219999999999999999999888888888888888888888, 1234567891234567891234567891234567888888888888888888887, 88888888888888888888987654321987654321987654321987654321987654321987654321, 1000000000000000000999999999999999998456, 88888888888888888888987654321987654321987654321987654321987654321987654321987654321987654321, 9876543210987654321987321321, 99910008881234567891011121314, 999123456789123456789987654321987654321998987654321987654321123456789123456789123456789123456789, 1234567891234567899876543219876543218888888888888888888123456789123456789123456789123456789, 123456124789789123, 987987654321, 999999999999999999999999999999999998999999999999999997999999999999999999, 999888999, 1000000000000000000124456789789, 888123456789123456789123456789123456789123456789123456789, 8888888888888888888877777777777777777777888888888888888888889999999999999999999888888888888888888888, 999999999999999999999999999999999998999999999999999997999999999999999999999999999999999999, 123456789101112131498765432109876543218881111111111111111111999999999999999999812345678910111213131234567891011121314, 1234567891234567899999999999999999998888888888888888887, 100000000000000000008888888888888888889888888888888888888810000000000000000000, 9876543210987654321986986321, 123124456789, 100000000000000000011234567891234567881000000000000000000099999999999999999998888888888888888888, 123456789101112131498765432109876543221234567891011121314111111111111111111112345678910111213141234567891011121314, 999999999999999999999999999999999998999999999999999999, 788789987654321098765432111111111111111111117897899876543210987654321]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(tuple_to_int(*inp), exp, 0)
| OK=True
==================== Problem #66 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a string to a list of strings split on the space character.
Your answer will be tested on test cases like:
assert string_to_list("python programming")==['python','programming']
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a string to a list of strings split on the space character.
Your answer will be tested on test cases like:
assert string_to_list("python programming")==['python','programming']
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a string to a list of strings split on the space character.
Your answer will be tested on test cases like:
assert string_to_list("python programming")==['python','programming']
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a string to a list of strings split on the space character.
Your answer will be tested on test cases like:
assert string_to_list("python programming")==['python','programming']
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to convert a string to a list of strings split on the space character.
Your answer will be tested on test cases like:
assert string_to_list("python programming")==['python','programming']
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called string_to_list that takes a string and splits it into a list of strings based on spaces. Let me think about how to do this.
Wait, the problem says split on the space character. So, the default split method in Python splits on whitespace, which includes spaces, tabs, newlines, etc. But maybe the question specifically wants splitting only on spaces, not other whitespace. But the example given is "python programming" which is split into two elements. Using the default split() would work here because splitting on spaces would split the string into parts separated by spaces.
Wait, the split() method without any arguments splits on any whitespace, so if there are multiple spaces, it would treat them as a single separator. But the problem says to split on the space character. So maybe using split(' ') would be better? Wait, no. Because if you split on a single space, then consecutive spaces would result in empty strings in the list. For example, "a b" (two spaces) would split into ['a', '', 'b'] if using split(' '). But the default split() would split into ['a', 'b'], which is probably the intended behavior.
But the problem says to split on the space character. So maybe the question expects splitting on each space, but perhaps the test cases don't have multiple spaces. Let me check the example given. The example is "python programming" which has one space, so splitting with split() or split(' ') would both result in the same output. However, if the input has multiple spaces, like "hello world", the split() method would return ['hello', 'world'], whereas split(' ') would return ['hello', '', '', 'world'].
But the problem's test case uses a single space. So maybe the intended solution is to use the split() method without any arguments, which splits on any whitespace. However, the problem says "split on the space character", which might mean that only spaces are considered, not other whitespace. But in practice, the split() method with no arguments splits on any whitespace, which includes spaces, tabs, newlines, etc. However, if the problem specifically wants to split only on space characters, then perhaps using split(' ') is needed. But that would include empty strings if there are multiple spaces.
But the example given is "python programming" which splits into two elements. Let's think: if the input is "python programming", then using split() would split into ['python', 'programming'], which is correct. Using split(' ') would also split into the same result. So for that test case, both approaches work.
But what about if there are multiple spaces? For example, "a b" (two spaces). The split() method would return ['a', 'b'], but split(' ') would return ['a', '', 'b'].
But the problem's test case doesn't have such a scenario. However, the problem says that the function should split on the space character. So perhaps the correct approach is to split on the space character, which would mean using split(' '). However, that would result in empty strings if there are multiple spaces. But maybe the problem expects that. Or perhaps the problem expects splitting on any whitespace, which is the default split().
Wait, the problem says "split on the space character". So the split should occur wherever a space character is. So, for example, "hello world" would split into ["hello", "world"], and "hello world" (three spaces) would split into ["hello", "", "", "world"] if using split(' '). However, if the problem expects that multiple spaces are treated as a single separator, then split() is better. But the problem's wording says "split on the space character", which could imply that each space is a separator, but perhaps the intended solution is to use split().
But the example given uses a single space. So perhaps the intended solution is to use the split() method. Let me check the test case. The test case is assert string_to_list("python programming")==['python','programming'], which would be satisfied by both split() and split(' '). However, if the input is "python programming" (two spaces), then split() would return ['python', 'programming'], while split(' ') would return ['python', '', 'programming'].
But the problem's description may not have such cases, so perhaps the intended solution is to use split().
Alternatively, perhaps the problem expects splitting on the space character, which is the same as using split(' '). But that's not the case. Because split(' ') splits on each space, but split() splits on any whitespace.
But the problem says "split on the space character", so perhaps the correct approach is to split on the space character. So the function would be:
def string_to_list(s):
return s.split(' ')
But then, if the input is "a b c", it would split into ['a', 'b', 'c'], which is correct. But if the input is "a b", it would split into ['a', '', 'b'].
But maybe the problem expects that. However, the example given uses a single space. But the problem's test case may not have such cases. However, the problem says that the function should split on the space character, so perhaps using split(' ') is correct.
But wait, the default split() method splits on any whitespace, which includes spaces, tabs, newlines, etc. But the problem says to split on the space character. So perhaps the correct approach is to split on the space character, not on other whitespace. However, in that case, the split(' ') would split on each space, but that would include empty strings for multiple spaces.
But maybe the problem expects that. For example, if the input is "hello world", the split on space would produce ['hello', '', '', 'world'].
But perhaps the problem expects that the split is done on any whitespace, which is the default split().
But the problem says "split on the space character". So perhaps the correct answer is to split on the space character, which would be s.split(' '). However, that's not the standard way. For example, the standard way to split on spaces (ignoring multiple spaces) is to use split().
But the problem says "split on the space character", which may imply that each space is a separator, but perhaps the problem is expecting split().
This is a bit ambiguous. However, the example given is "python programming" which would split into ['python', 'programming'] with either split() or split(' '). So perhaps the intended solution is to use split().
But the problem says "split on the space character", which is a bit ambiguous. However, in Python, the split() method with no arguments splits on any whitespace, which includes spaces, tabs, newlines, etc. So if the problem wants to split on the space character specifically, perhaps the split(' ') is needed. But that's not the standard approach.
Alternatively, perhaps the problem is using "split on the space character" to mean splitting on whitespace, and the intended solution is split().
But given that the test case uses a single space, and the expected output is a list of the words, the split() method would be the correct approach. Because if you have multiple spaces, split() would collapse them into one separator, but split(' ') would not. However, the problem's test case may not require handling such cases.
But the problem says that the function should split on the space character. So perhaps the correct answer is to split on the space character, which is split(' ').
But in that case, the test case would pass, but for other cases, like multiple spaces, it would return empty strings. However, the problem's test case is only checking for the case with one space.
But perhaps the problem expects split().
This is a bit of a problem. However, the example given is "python programming" which is split into two elements. Both split() and split(' ') would work here. So perhaps the intended solution is to use split().
But the problem says "split on the space character", which might mean that the split is done on each individual space. But that's not the case. For example, the split(' ') method would split on each space, but when there are multiple spaces, it would create empty strings. However, the problem may not have such test cases.
But given that the problem's test case is passing, perhaps the intended solution is to use split().
But to be safe, perhaps the problem expects split().
So the function would be:
def string_to_list(s):
return s.split()
But wait, the split() method without any arguments splits on any whitespace, which includes spaces, tabs, etc. So if the input is "python\tprogramming" (tab), then split() would split into ['python', 'programming'], which is correct. But the problem says split on the space character. But maybe the problem is using "space" as a general term for whitespace. However, the problem's wording is not clear.
But the example given uses a space, and the test case is for that. So the function s.split() would work.
But the problem says "split on the space character", which is a bit more specific. However, in practice, the split() method is the standard way to split strings into words, and the test case would pass.
Therefore, the correct function is to return s.split().
But let me check the example. For "python programming", s.split() returns ['python', 'programming'], which matches the test case. So that's correct.
Therefore, the function can be written as:
def string_to_list(s):
return s.split()
But wait, the problem says "split on the space character", but the split() method splits on any whitespace. However, the problem's test case is satisfied by this function.
But maybe the problem expects that the split is done on the space character, not other whitespace. For example, if the input is "hello\tworld", then split() would split into ['hello', 'world'], but split(' ') would split into ['hello\tworld'] (since the tab is not a space). But the problem says to split on the space character, so the split(' ') would be the correct approach. However, that would not split on tabs, which may be intended.
But the problem's test case uses a space, and the function is supposed to split on the space character. So perhaps the correct approach is to split on the space character, which would be split(' ').
But then, if the input is "hello world", split(' ') returns ['hello', 'world'], which is correct. But if the input is "hello world", split(' ') returns ['hello', '', '', 'world'].
But perhaps the problem expects that. However, the problem's test case doesn't have such a scenario.
But the problem says to split on the space character, so the correct approach is to split on the space character, which is achieved by split(' ').
But why would the problem's test case use split() then? Well, the test case is given as "python programming" which would work with either method.
But the problem's wording is ambiguous. However, the problem's test case may not have such edge cases, and the expected answer is to use split().
But how to decide?
Well, the problem says "split on the space character", which in Python, the split(' ') would split on each space. However, the default split() splits on any whitespace. So the problem's wording may be intending to split on the space character, not other whitespace. So perhaps the correct code is to use split(' ').
But then, for the test case, it would work. But what about leading or trailing spaces? For example, " hello world " would split into ['', '', 'hello', 'world', '', ''] using split(' '). But using split() would split into ['hello', 'world'].
But the problem's test case may not require handling those cases. However, the problem says that the function should split on the space character. So perhaps the correct approach is to use split(' ').
But the problem's test case is "python programming" which would split into ['python', 'programming'] with both methods.
But the problem may have other test cases. For example, if the input is "a b c", then split(' ') would split into ['a', 'b', 'c'], which is correct. If the input is "a b", split(' ') would return ['a', '', '', 'b'].
But the problem's test case may not have such cases. However, the problem says to split on the space character, which would be the case with split(' ').
But the problem says "split on the space character", which is a bit ambiguous. However, the standard way to split a string into words, splitting on any whitespace, is split(). But the problem's wording is different.
But given that the test case uses split() and the problem says to split on the space character, perhaps the intended solution is to use split(' ').
But I'm not sure. However, the problem's test case is:
assert string_to_list("python programming")==['python','programming']
Which would be satisfied by both split() and split(' ').
But perhaps the problem expects the split() method. Because in most cases, when someone says "split on spaces", they mean split into words, which is what split() does.
But the problem says "split on the space character", which could be interpreted as splitting the string into parts wherever a space occurs. For example, "a b c" would split into ['a', 'b', 'c'], which is the same as split().
But the split(' ') would split on each space. So, for example, "a b c" would split into ['a', 'b', 'c'], which is the same as split(). However, for "a b", split(' ') would give ['a', '', 'b'], while split() would give ['a', 'b'].
But the problem's test case is for a single space. So perhaps the intended solution is to use split(' ').
But why would the problem mention the space character? Because split(' ') splits on the space character. So maybe that's what they want.
But the problem's wording is ambiguous. However, given that the test case passes with both methods, but the problem says "split on the space character", I think the intended answer is to use split(' ').
But I'm not sure. However, in Python, the split() method is the standard way to split a string into words. So maybe the intended answer is to use split().
But given the problem's wording, I think the correct answer is to use split(' ').
But perhaps the problem is expecting the split() method. Because the problem's example is the same for both.
But I need to choose one. Let me think again: the problem says to split on the space character. So the split should occur wherever there is a space. So the split(' ') is the correct method.
But in that case, the test case would pass. So I think the answer is to use split(' ').
Wait, but in Python, the split(' ') method will split on each space, including multiple spaces. But the problem's example is correct.
So the function would be:
def string_to_list(s):
return s.split(' ')
But then, if the input is "hello world", it returns ['hello', 'world'], which is correct.
But what if the input is empty? Well, the problem may not have such test cases.
But the problem says to write a function that splits on the space character. So the code would be as above.
But perhaps the problem expects that leading or trailing spaces are handled. For example, " hello world " would split into ['', '', 'hello', 'world', '', ''] with split(' '). But the problem's test case may not require that.
But given that the problem's test case is correct, I think the function is correct.
But the problem's test case uses split() and expects the list to be split on whitespace. But the problem says to split on the space character. So I think the answer is to use split(' ').
But I'm not 100% sure. However, given the problem's wording, I'll proceed with split(' ').
Wait, but in Python, the split() method without any arguments splits on any whitespace, which includes spaces, tabs, newlines, etc. So if the problem says to split on the space character, then the correct method would be to split on the space character, which is split(' ').
But then, if there are tabs, they would not be split. But the problem says to split on the space character, so that's correct.
So the function is:
def string_to_list(s):
return s.split(' ')
But then, the test case would pass.
But I'm not sure if this is the intended solution. However, given the problem's wording, this is the correct approach.
But perhaps the problem expects the split() method. Let me think again.
The problem's test case is:
assert string_to_list("python programming") == ['python', 'programming']
Which is satisfied by both methods. So which one is the correct answer?
The problem says "split on the space character". The split() method splits on any whitespace, which is more than just the space character. So if the problem wants to split only on the space character, then split(' ') is correct. Otherwise, split() is correct.
But the wording is "split on the space character", which suggests that the split is done on the space character, not other whitespace. So the answer is split(' ').
So the code is:
def string_to_list(s):
return s.split(' ')
But then, for the input " a b ", the result would be ['', '', 'a', 'b', '', ''].
But the problem's test case is correct.
But I think that's the correct approach based on the problem's wording.
```python
def string_to_list(s):
return s.split(' ')
```
----------------------------------------------
Result: Pred=def string_to_list(s):
return s.split(' ') | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['python programming'], ['lists tuples strings'], ['write a program'], [''], [' python programming '], ['1234 5678 9101'], ['string1,string2,string3'], ['My favorite programming language is Python'], ['string1, string2, string3'], ['string1,string2,strin3'], ['language'], ['1234 5678 91string1,string2,string301'], ['string1,string2,3'], ['My'], ['1234'], ['l'], ['5678'], ['192314 5678 9101'], ['python'], ['12314'], [' ng '], ['56678'], ['favorite'], ['string2,'], ['AeFmnNDd'], ['56'], ['programming'], ['pronggrammin12314g'], ['prog'], ['5striing1,stringg2,strin3'], ['language ng '], ['favorit'], ['gvZn'], ['languPythonage ng '], ['Python'], ['SfDBdGHKU'], ['is'], ['5stprogriing1,stringg2,strin3'], ['fvorrite'], ['porog'], ['pAeFmnNDdor'], ['propg'], ['languag5678e ng '], ['My favorite programming lamnguage is Python'], ['12My favorite programming language is Python34 5678 9101'], ['programmming'], ['My favorite prolanguPythonagegramminlg language is Python'], ['te'], ['fvorrrite'], ['string1, string2, sstring3'], ['1234 5678 9101'], ['556is78'], ['My favorite prol anguPythonagegramminlg lanage is Python'], ['vksoeiMq'], ['12My favorite programming language is Python34 5678string2,'], ['5striing1,My favorite proMye ythonpstringg2,strin3'], ['1234 5678 91string1,sPython342,string301'], ['fvorofrite'], ['fvorrreite'], ['favoritprogrammming'], ['Python34'], ['556iss78'], ['peMsMC'], ['ffvorrreite'], ['5striing1,My favorite proMylanguagee ythonpstringg2,strin3'], ['556iss788'], ['spythonring2'], ['string3'], ['Pstring3ython'], ['My favorit5678e prol anguPythonagegramminlg lanage is Pgython'], ['12334 5678 9101'], ['prol'], ['langua g5678e ng '], ['rfvorrrite'], ['PlanguPythonage'], ['123My favorite prolanguPythonagegramminlg language is Python4 5678 9101'], ['12 334 5678 9101'], ['fvorofritre'], ['192314'], ['string1, st ring2,, string3'], ['lanage'], ['gprolanguPythonagegramminlgvZ12n'], ['fvoorrite'], ['st'], ['anguPythonagegramminlg'], ['12My favorite programming glanguage is Python34 5678string2,'], ['12python3My'], ['languPythonage ngn '], ['gg5678e'], ['rfvorrtristring1, st ring2,, string3te'], ['languag5678e'], ['string1, st ring2,languag5678e ng string3'], ['5stprogriing1,stiringg2,strin3'], ['My favorite programming language is PytlanguPythonagehon'], ['programmmipng'], ['flvorofrite'], ['tt'], ['1212314M3y'], ['pronggrrammin12314g'], ['string1, st ring2,, string3'], ['123My favorite prolanguPythonagegramminlg language is Pythstring1, string2, string3on4 5678 9101'], ['fvsstring3e'], ['Pst3ring3ython'], ['string1, st ring2,languag5678e ng string'], ['lan12334 5678 9101gua g5678e ng '], ['faorite'], ['91nstring1,string2,string301'], ['prrfvorrtristring1, st ring2,, string3teol'], ['556667string1,string2,string3']]
results = [['python', 'programming'], ['lists', 'tuples', 'strings'], ['write', 'a', 'program'], [''], ['', '', '', 'python', '', '', '', '', '', 'programming', '', '', '', ''], ['1234', '5678', '9101'], ['string1,string2,string3'], ['My', 'favorite', 'programming', 'language', 'is', 'Python'], ['string1,', '', '', '', '', 'string2,', '', '', '', '', '', '', 'string3'], ['string1,string2,strin3'], ['language'], ['1234', '5678', '91string1,string2,string301'], ['string1,string2,3'], ['My'], ['1234'], ['l'], ['5678'], ['192314', '5678', '9101'], ['python'], ['12314'], ['', '', '', 'ng', '', '', '', ''], ['56678'], ['favorite'], ['string2,'], ['AeFmnNDd'], ['56'], ['programming'], ['pronggrammin12314g'], ['prog'], ['5striing1,stringg2,strin3'], ['language', '', 'ng', '', '', '', ''], ['favorit'], ['gvZn'], ['languPythonage', '', 'ng', '', '', '', ''], ['Python'], ['SfDBdGHKU'], ['is'], ['5stprogriing1,stringg2,strin3'], ['fvorrite'], ['porog'], ['pAeFmnNDdor'], ['propg'], ['languag5678e', '', 'ng', '', '', '', ''], ['My', 'favorite', 'programming', 'lamnguage', 'is', 'Python'], ['12My', 'favorite', 'programming', 'language', 'is', 'Python34', '5678', '9101'], ['programmming'], ['My', 'favorite', 'prolanguPythonagegramminlg', 'language', 'is', 'Python'], ['te'], ['fvorrrite'], ['string1,', '', '', '', '', 'string2,', '', '', '', '', '', '', 'sstring3'], ['1234', '5678', '', '9101'], ['556is78'], ['My', 'favorite', 'prol', 'anguPythonagegramminlg', 'lanage', 'is', 'Python'], ['vksoeiMq'], ['12My', 'favorite', 'programming', 'language', 'is', 'Python34', '5678string2,'], ['5striing1,My', 'favorite', 'proMye', 'ythonpstringg2,strin3'], ['1234', '5678', '91string1,sPython342,string301'], ['fvorofrite'], ['fvorrreite'], ['favoritprogrammming'], ['Python34'], ['556iss78'], ['peMsMC'], ['ffvorrreite'], ['5striing1,My', 'favorite', 'proMylanguagee', 'ythonpstringg2,strin3'], ['556iss788'], ['spythonring2'], ['string3'], ['Pstring3ython'], ['My', 'favorit5678e', 'prol', 'anguPythonagegramminlg', 'lanage', 'is', 'Pgython'], ['12334', '5678', '', '9101'], ['prol'], ['langua', 'g5678e', '', 'ng', '', '', '', ''], ['rfvorrrite'], ['PlanguPythonage'], ['123My', 'favorite', 'prolanguPythonagegramminlg', 'language', 'is', 'Python4', '5678', '9101'], ['12', '334', '5678', '', '9101'], ['fvorofritre'], ['192314'], ['string1,', '', '', '', '', 'st', 'ring2,,', '', '', '', '', '', '', 'string3'], ['lanage'], ['gprolanguPythonagegramminlgvZ12n'], ['fvoorrite'], ['st'], ['anguPythonagegramminlg'], ['12My', 'favorite', 'programming', 'glanguage', 'is', 'Python34', '5678string2,'], ['12python3My'], ['languPythonage', '', 'ngn', '', '', '', ''], ['gg5678e'], ['rfvorrtristring1,', '', '', '', '', 'st', 'ring2,,', '', '', '', '', '', '', 'string3te'], ['languag5678e'], ['string1,', '', '', '', '', 'st', 'ring2,languag5678e', '', 'ng', '', '', '', '', '', 'string3'], ['5stprogriing1,stiringg2,strin3'], ['My', 'favorite', 'programming', 'language', 'is', 'PytlanguPythonagehon'], ['programmmipng'], ['flvorofrite'], ['tt'], ['1212314M3y'], ['pronggrrammin12314g'], ['string1,', '', '', '', '', 'st', 'ring2,,', '', '', '', '', '', '', '', 'string3'], ['123My', 'favorite', 'prolanguPythonagegramminlg', 'language', 'is', 'Pythstring1,', '', '', '', '', 'string2,', '', '', '', '', '', '', 'string3on4', '5678', '9101'], ['fvsstring3e'], ['Pst3ring3ython'], ['string1,', '', '', '', '', 'st', 'ring2,languag5678e', '', 'ng', '', '', '', '', '', 'string'], ['lan12334', '5678', '', '9101gua', 'g5678e', '', 'ng', '', '', '', ''], ['faorite'], ['91nstring1,string2,string301'], ['prrfvorrtristring1,', '', '', '', '', 'st', 'ring2,,', '', '', '', '', '', '', 'string3teol'], ['556667string1,string2,string3']]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(string_to_list(*inp), exp, 0)
| OK=True
==================== Problem #67 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the element that appears only once in a sorted array.
Your answer will be tested on test cases like:
assert search([1,1,2,2,3]) == 3
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the element that appears only once in a sorted array.
Your answer will be tested on test cases like:
assert search([1,1,2,2,3]) == 3
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the element that appears only once in a sorted array.
Your answer will be tested on test cases like:
assert search([1,1,2,2,3]) == 3
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the element that appears only once in a sorted array.
Your answer will be tested on test cases like:
assert search([1,1,2,2,3]) == 3
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the element that appears only once in a sorted array.
Your answer will be tested on test cases like:
assert search([1,1,2,2,3]) == 3
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function that finds the element appearing only once in a sorted array. Let's think about the problem. The array is sorted, so duplicates are next to each other. The example given is [1,1,2,2,3], and the answer is 3. So the function should return the element that's not duplicated.
Hmm, how do I approach this? Well, since the array is sorted, maybe I can iterate through it and check pairs. For each element, if it's the same as the next one, skip both. If not, then the current element is the unique one. But wait, what about the last element? Like if the array ends with the unique element. For example, [1,2,2,3,3], the unique is 1. Wait, no, that example would have 1 as the first element. Wait, in that case, the code would check the first element, compare with the next. Since 1 != 2, return 1. That works.
But what if the array has even number of elements? Wait, the problem says that there is exactly one element that appears once. So the array length must be odd. Because all others are in pairs. So for example, the sample input has 5 elements. So the unique element is at an even index? Or maybe not. Let's think.
Another approach: since the array is sorted, the unique element will be the one where the previous element is different. But for the first element, there's no previous. So maybe we can check each element. For example, in the sample [1,1,2,2,3], the first element is 1. The next element is same, so move. Then 2, next same. Then 3, next is nothing. So return 3.
Alternatively, maybe using binary search. Because the array is sorted. Let me think. The unique element will be the first element where the next element is different. But how to find that efficiently.
Wait, but for a sorted array with duplicates, the unique element will be the one where the index is even? Or maybe not. Let's think. Let's take the example [1,1,2,2,3]. The indices are 0,1,2,3,4. The unique element is at index 4. Which is even. Another example: [1,2,2,3,3]. The unique is 1 at index 0. Which is even. Another example: [1,1,2,3,3]. The unique is 2 at index 2. Also even. Hmm, maybe the unique element is always at an even index? Wait, what if the array is [1,2,3,3,4]. Then the unique is 1 at index 0 (even), but the array is sorted. Wait, but the array is [1,2,3,3,4], the unique is 1 and 2 and 4? No, no. Wait the problem states that there is exactly one element that appears once. So the array must have all others in pairs. So the array length is 2n+1. So the unique element is in the middle? Or not necessarily. For example, [1,2,2,3,3]. The unique is 1. So the middle index is 2, which is 2. But the unique is at index 0. So that idea is wrong.
So maybe the approach is to iterate through the array and check for the element that is not equal to its neighbor. But how to handle that.
Let me think of the steps:
For each element in the array, check if it's the same as the next element. If not, return it. But if it is, then move to the next element. But since the array is sorted, the unique element will be the first one that doesn't have a duplicate. So for example, in [1,1,2,2,3], the first element is 1, compare with next (1). Same, so move to index 2. Then compare 2 with next (2). Same, move to index 4. Compare with next, which is beyond the array. So return 3.
But how to implement this. Let's think of the code:
def search(arr):
for i in range(0, len(arr)-1, 2):
if arr[i] != arr[i+1]:
return arr[i]
return arr[-1]
Wait, this would work for the sample. Let's test:
For [1,1,2,2,3], the loop steps:
i=0: check arr[0] and arr[1]. 1 == 1, so continue.
i=2: check arr[2] and arr[3]. 2 == 2, continue.
i=4: len(arr)-1 is 4, so range is 0 to 4-1=3, step 2. So the loop runs for i=0, 2. Then after that, return arr[-1], which is 3. Correct.
Another test case: [1,2,2,3,3]. The loop starts at i=0. arr[0] is 1, compare with arr[1] which is 2. Not equal, return 1. Correct.
Another test case: [1,1,2,3,3]. The loop i=0: compare 1 and 1. Same, move to i=2. Compare 2 and 3. Not same. Return 2. Correct.
Another case: [1,2,3,3,4]. The loop i=0: compare 1 and 2. Not same, return 1. Correct.
What if the unique element is in the middle? Like [1,2,3,4,4]. Then the loop i=0: 1 and 2 are different. Return 1. Which is correct.
But wait, what if the array is [1,1,2,3,3,4,4]. Then the unique is 2. Let's see. The loop steps:
i=0: compare 1 and 1. Same. i becomes 2. Compare 2 and 3. Not same. Return 2. Correct.
So this approach seems to work. So the code would be:
def search(arr):
for i in range(0, len(arr)-1, 2):
if arr[i] != arr[i+1]:
return arr[i]
return arr[-1]
But wait, what if the array has only one element? Like [5]. Then len(arr)-1 is 0, so the loop runs from 0 to -1, which is not executed. Then returns arr[-1], which is 5. Correct.
Another case: [1,1,2]. The loop runs i=0. Compare arr[0] and arr[1], same. Then i=2, which is len(arr)-1=2. So the loop runs for i=0, then returns arr[-1], which is 2. Correct.
So this code should handle all cases. So the function is as written.
Now, the problem says that the function is to be written. So the code would be:
def search(arr):
for i in range(0, len(arr)-1, 2):
if arr[i] != arr[i+1]:
return arr[i]
return arr[-1]
But wait, the problem says that the array is sorted. So this code works because the duplicates are adjacent. So this approach works.
Testing the sample input:
assert search([1,1,2,2,3]) == 3. Which would return 3. Correct.
Another test case: [1,2,2,3,3] returns 1. Correct.
Another test case: [1,1,2] returns 2. Correct.
So the code should work. So the Python function is as above.
```python
def search(arr):
for i in range(0, len(arr)-1, 2):
if arr[i] != arr[i+1]:
return arr[i]
return arr[-1]
```
----------------------------------------------
Result: Pred=def search(arr):
for i in range(0, len(arr)-1, 2):
if arr[i] != arr[i+1]:
return arr[i]
return arr[-1] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[1, 1, 2, 2, 3]], [[1, 1, 3, 3, 4, 4, 5, 5, 7, 7, 8]], [[1, 2, 2, 3, 3, 4, 4]], [[]], [[2, 2, 2, 2, 2, 2]], [[1, 1, 1, 1, 1, 1]], [[6]], [[1, 2, 3, 4, 5, 6]], [[1, 1, 2, 2, 3, 3, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14, 15]], [[5]], [[1, 1, 4, 4, 5, 6]], [[0, 1, 4, 4, 5, 6]], [[4, 5, 5]], [[4, 4, 5]], [[1, 1, 4, 4, 6]], [[0, 1, 4, 4, 5]], [[2, 2, 2, 2, 2]], [[1, 1, 4, 6]], [[0, 4, 4, 5, 6]], [[4, 5]], [[1, 1, 4, 4, 5]], [[1, 1, 1, 1, 1]], [[1, 2, 4, 6]], [[5, 5]], [[4, 5, 5, 5]], [[1, 1, 1, 1, 1, 1, 1]], [[1, 1, 1, 1, 1, 1, 1, 1]], [[2, 2, 2, 2, 2, 2, 2, 2]], [[2, 2, 2, 2, 2, 2, 2, 2, 2]], [[1, 1, 1]], [[1, 1, 4, 4]], [[0, 1, 4, 4, 8]], [[2, 2, 2, 2, 2, 2, 2, 15]], [[4, 4, 4]], [[1, 1, 2, 2, 3, 3, 4, 5, 5, 6, 6, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 14, 15]], [[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]], [[False, False]], [[6, 6, 6]], [[1, 4, 4]], [[5, 5, 5]], [[4, 5, 5, 5, 5]], [[1, 4]], [[1, 1]], [[6, 6]], [[1, 1, 1, 1, 1, 1, 1, 1, 1]], [[2, 2, 2, 2, 2, 2, 2, 2, 15]], [[1, 2, 3, 3, 4, 5, 6]], [[0, 4, 4, 8]], [[1, 1, 4]], [[1, 4, 6]], [[0, 1, 1, 1, 1, 1, 1, 1, 1]], [[4, 6]], [[False, True]], [[1, 1, 11]], [[1, 1, 2]], [[0, 1, 4, 8]], [[0, 4, 4, 4, 6, 6]], [[2, 2, 2, 2, 2, 2, 2, 2, 2, 15]], [[1, 5]], [[4, 4, 4, 4, 4]], [[3, 5, 5]], [[5, 5, 5, 5]], [[1, 1, 2, 2, 3, 3, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13, 13, 14, 15, 15]], [[1, 3, 5, 5, 6]], [[0, 4, 8]], [[4, 4, 6]], [[0, 1, 4, 4, 6]], [[1, 1, 4, 4, 5, 5]], [[1, 1, 2, 2]], [[0, 1, 1, 1, 1, 1, 1, 1, 1, 1]], [[1, 1, 11, 11]], [[True]], [[4, 4]], [[False, True, True, True, True, True]], [[5, 11]], [[1, 1, 1, 4, 4]], [[4, 4, 4, 4]], [[2, 2, 2, 2, 2, 2, 2]], [[1, 2, 4, 6, 6]], [[4, 4, 8]], [[0, 2, 2, 2, 2]], [[1, 2, 3, 3, 11]], [[4, 4, 6, 6]], [[3, 5]], [[2, 5]], [[0, 1, 1, 1, 1, 1, 1, 1]], [[3, 6]], [[1, 4, 4, 6]], [[0, 2, 2, 2]], [[0, 1, 1]], [[1, 3, 4, 7]], [[1, 4, 6, 6]], [[1, 4, 4, 4]], [[False]], [[1, 1, 10, 11, 11]], [[0, 4, 5, 5]], [[0, 1, 4, 5, 6]], [[1, 4, 4, 5, 6]], [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], [[1, 1, 6, 6, 6]], [[4]], [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], [[1, 1, 12]], [[0, 2, 6, 6]], [[9]], [[1, 1, 1, 4, 4, 4]], [[1, 11, 11]], [[1, 1, 4, 4, 5, 9]], [[3, 6, 6]], [[1, 3, 3, 5, 13]]]
results = [3, 8, 1, 0, 0, 0, 6, 7, 11, 5, 3, 2, 4, 5, 6, 4, 2, 2, 3, 1, 5, 1, 1, 0, 1, 1, 0, 0, 2, 1, 0, 9, 13, 4, 12, 2, 0, 6, 1, 5, 4, 5, 0, 0, 1, 15, 4, 8, 4, 3, 0, 2, 1, 11, 2, 13, 4, 13, 4, 4, 3, 0, 10, 4, 12, 6, 7, 0, 0, 1, 0, 1, 0, 1, 14, 1, 0, 2, 7, 8, 0, 8, 0, 6, 7, 1, 5, 7, 2, 0, 1, 5, 5, 0, 10, 4, 6, 2, 1, 6, 4, 0, 12, 2, 9, 5, 1, 12, 3, 9]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(search(*inp), exp, 0)
| OK=False
==================== Problem #68 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum absolute product between numbers in pairs of tuples within a given list.
Your answer will be tested on test cases like:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)] )==36
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum absolute product between numbers in pairs of tuples within a given list.
Your answer will be tested on test cases like:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)] )==36
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum absolute product between numbers in pairs of tuples within a given list.
Your answer will be tested on test cases like:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)] )==36
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum absolute product between numbers in pairs of tuples within a given list.
Your answer will be tested on test cases like:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)] )==36
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum absolute product between numbers in pairs of tuples within a given list.
Your answer will be tested on test cases like:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)] )==36
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called max_product_tuple that takes a list of tuples and returns the maximum absolute product between numbers in pairs of tuples. Let me think about how to approach this.
The problem says the input is a list of tuples, like [(2,7), (2,6), etc.]. For each tuple, I need to calculate the product of the two numbers. Then take the absolute value of that product. Then find the maximum among all those absolute products.
Wait, but the question says "between numbers in pairs of tuples". Wait, maybe I need to consider pairs of tuples? Or is it the product of the two numbers within each tuple?
Looking at the example given: the input is [(2,7), (2,6), (1,8), (4,9)]. The expected output is 36. Let's check each tuple's product:
(2,7) product is 14, absolute is 14. (2,6) is 12. (1,8) is 8. (4,9) is 36. So the maximum is 36. So the example matches that. So the problem is to compute the product of the two elements in each tuple, take absolute value, and find the maximum.
So the function needs to iterate through each tuple in the list, compute the product of the two elements, take absolute value, and track the maximum.
So steps for the function:
1. Initialize a variable to hold the maximum product, maybe start with negative infinity.
2. Iterate over each tuple in the input list.
3. For each tuple, calculate the product of the two elements. Then take the absolute value.
4. Compare this value with the current maximum, and update the maximum if it's larger.
5. After processing all tuples, return the maximum.
Now, how to implement this in Python.
The function definition would be def max_product_tuple(lst):, where lst is the list of tuples.
Wait, but the example uses the function name max_product_tuple. So the code should have that function.
So code steps:
Initialize max_prod as -infinity.
For each pair in the list:
product = pair[0] * pair[1]
abs_product = abs(product)
if abs_product > max_prod:
max_prod = abs_product
Then return max_prod.
That seems straightforward.
Testing the example: [(2,7), (2,6), (1,8), (4,9)].
Calculations:
2*7=14 → abs 14 → max is 14.
Then 2*6=12 → 12 <14 → no change.
Then 1*8=8 → same.
Then 4*9=36 → 36>14 → max becomes 36. So returns 36. Which matches the example.
What about edge cases?
What if the list is empty? Well, the problem probably assumes that the input is a valid list of tuples with two elements each. But maybe the function should handle empty lists? But according to the example, the function is called with a non-empty list. However, in practice, perhaps we should handle that. But since the problem's test case doesn't include that, maybe we can assume the input is valid.
Another case: tuples with negative numbers. For example, (-3, -4) → product is 12, absolute is 12. Or (-3, 4) → product -12, absolute 12. So the code handles that correctly.
So the code should be:
def max_product_tuple(lst):
max_prod = float('-inf')
for pair in lst:
product = pair[0] * pair[1]
abs_product = abs(product)
if abs_product > max_prod:
max_prod = abs_product
return max_prod
Wait, but what if the list is empty? Then it would return -inf, which is not correct. However, the problem's test case probably expects that the input is a non-empty list. But maybe the function should handle that. However, since the problem's example doesn't have that, perhaps we can proceed as such.
So the code should work for the given test case. Let's check the sample input:
assert max_product_tuple([(2, 7), (2, 6), (1, 8), (4, 9)]) == 36 → yes.
Another test case: [( -5, 3 ), (2, -4)] → products are -15 (abs 15) and -8 (abs 8). Max is 15.
So the code would return 15.
Yes.
So the code seems correct.
```python
def max_product_tuple(lst):
max_prod = float('-inf')
for pair in lst:
product = pair[0] * pair[1]
abs_product = abs(product)
if abs_product > max_prod:
max_prod = abs_product
return max_prod
```
----------------------------------------------
Result: Pred=def max_product_tuple(lst):
max_prod = float('-inf')
for pair in lst:
product = pair[0] * pair[1]
abs_product = abs(product)
if abs_product > max_prod:
max_prod = abs_product
return max_prod | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[[(2, 7), (2, 6), (1, 8), (4, 9)]], [[(10, 20), (15, 2), (5, 10)]], [[(11, 44), (10, 15), (20, 5), (12, 9)]], [[(-10, 20), (15, -2), (-5, 10)]], [[(1000000, 500000), (2000000, 1000000), (3000000, 1500000)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(-10, 0), (0, 5)]], [[(-100, 100), (0, 10)]], [[(0, -100), (0, 100)]], [[(-1000000, 1000000), (0, 100000)]], [[(1, 0), (-0.5, 0.5), (2, -2)]], [[(0.1, 0.1), (0.5, -0.5), (0.2, 0.2)]], [[(-9999999, 9999999), (1e-06, 1000000)]], [[(1000000, -1000000000), (-1000000000, 1000000)]], [[(-1000000, -1000000), (-999, 0)]], [[(0, 0)]], [[(-1000000, 1000000), (0, 99999)]], [[(-10, 20), (15, -2)]], [[(0.5, -0.5), (0.2, 0.2)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000)]], [[(-1000001, -1000000), (0, 100000)]], [[(-999, 0)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(-10, 20), (15, -2), (-5, 9), (-5, 10)]], [[(0.5, -0.5), (0.2, 0.2), (0.5, -0.5)]], [[(10, -1000000)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(-10, 20)]], [[(0.1, 0.1), (0.5, 0.1), (0.2, 0.2)]], [[(-10, 0), (0, 100000)]], [[(-10, 20), (100000, -2)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000)]], [[(3000000, 1500000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000)]], [[(-10, 20), (-10, 20)]], [[(-10, 20), (15, -2), (15, -2)]], [[(-9, 20)]], [[(-100, 100), (0, 10), (0, 10)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000001, 1000000), (-1000000000, 1000000), (1000000, -1000000000)]], [[(0.5, -0.5), (0.2, 0.2), (0.5, -0.5), (0.2, 0.2)]], [[(-100, 100)]], [[(0.1, 0.1), (0.5, 0.1), (0.2, 0.2), (0.1, 0.1)]], [[(-999, 0), (-999, 0)]], [[(10, -1000001)]], [[(-1000000000, 1000000)]], [[(-10, 20), (15, -2), (-5, 9), (-5, 10), (-5, 9)]], [[(-2, 0), (0, 5)]], [[(-1000000000, 1000000), (-1000000000, 1000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (1000000, -1000000000)]], [[(-10, 20), (100000, -2), (-10, 20)]], [[(0.1, 0.1), (0.5, -0.5), (0.1, 0.1), (0.1, 0.1)]], [[(0, -101), (0, -100), (0, 100), (0, -100), (0, 100)]], [[(1000000, -1000000000), (9999999, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000)]], [[(-10, 20), (15, -2), (-5, 9), (-5, 10), (-5, 9), (-5, 9)]], [[(0, 100000), (0, 100000)]], [[(1000000, 9999999), (1000000, 500000), (2000000, 1000000), (3000000, 1500000), (3000000, 1500000)]], [[(-10, 20), (15, -2), (-5, 9)]], [[(15, -2), (-5, 9), (-5, 10), (-5, 9), (-5, 9)]], [[(-10, 20), (-10, 20), (-10, 20)]], [[(1000000, -1000000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (3000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000)]], [[(-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, 0), (1, -1), (1, -1)]], [[(15, -2), (-5, 9)]], [[(0.1, 0.1), (0.5, 0.1), (0.2, 0.2), (0.1, 0.1), (0.5, 0.1)]], [[(0.2, 0.2), (0.2, 0.2)]], [[(0.1, 0.1), (0.5, 0.1), (0.1, 0.14655870166177412), (0.2, 0.2)]], [[(0, 100000)]], [[(0.1, 0.1), (0.2, 0.2), (0.1, 0.1), (0.2, 0.2)]], [[(0.1, 0.1), (0.2, 0.2), (0.1, 0.1), (0.2, 0.2), (0.1, 0.1)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000001, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (-1000000001, 1000000)]], [[(0.5, -0.5)]], [[(1, 0), (-0.5, 0.5), (2, -2), (2, -2)]], [[(1000000, 500000), (2000000, 1000000), (3000000, 1500000), (2000000, 1000000)]], [[(0.2, 0.2)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000001, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (-1000000001, 1000000), (-1000000001, 1000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -999), (1000000, -1000000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000001, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (1000000, -1000000000)]], [[(0.1, 0.1), (0.5, -0.5), (0.1, 0.1), (0.1, 0.1), (0.5, -0.5)]], [[(0.1, 0.1), (0.5, 1e-06), (0.5, -0.5), (0.1, 0.1), (0.1, 0.1), (0.5, -0.5)]], [[(-2, 0), (0, 5), (0, 5)]], [[(1000000, -1000000000), (9999999, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (9999999, 10), (-1000000000, 1000000), (1000000, -1000000000)]], [[(-10, 0), (-10, 0)]], [[(1000000, -1000000000), (-1000000000, 1000000), (3000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (1000000, -1000000000)]], [[(0.14228615811571196, 0.1), (0.5, 0.1), (0.2, 0.2)]], [[(10, -1000000), (10, -1000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 999999), (-1000000001, 1000000), (-1000000000, 1000000), (1000000, -1000000000)]], [[(-1000000, 1000000), (0, 99999), (-1000000, 1000000)]], [[(-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000)]], [[(0.2, 0.2), (0.2, 0.2), (0.2, 0.2), (0.2, 0.2)]], [[(-10, 20), (15, -2), (14, -2)]], [[(0, 10), (-100, 100), (0, 10), (0, 10)]], [[(0.1, 0.1), (0.5, -0.5), (0.1, 0.1), (0.1, 0.1), (0.5, -0.5), (0.1, 0.1)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(-10, 20), (15, -2), (-5, 9), (-5, 9)]], [[(100000, -2), (-10, 20)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 0)]], [[(0, 99999), (-1000000, 1000000)]], [[(1000000, -1000000000), (-1000000000, 1000000), (1000000, -999999999), (-1000000000, 0)]], [[(0.14228615811571196, 0.1), (0.5, 0.1), (0.2, 0.2), (0.14228615811571196, 0.1)]], [[(0.2, 0.2), (0.1, 0.1), (0.2, 0.2)]], [[(1000000, -1000000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -999), (1000000, -1000000000)]], [[(100000, -2), (-10, 3000000), (100000, -2)]], [[(0.2, 0.2), (0.2, 0.2), (0.2, 0.2)]], [[(15, -2), (-5, 9), (-5, 10), (-5, 9), (-5, 9), (15, -2)]], [[(15, -2), (-5, 9), (-5, 10), (-5, 9), (-5, 9), (15, -2), (-5, 9)]], [[(1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1), (1, -1)]], [[(100000, -2), (-10, 3000000), (100000, -2), (100000, -2)]], [[(0.1, 0.1), (0.1, 0.1), (0.2, 0.2)]], [[(-999, 0), (-999, 0), (-999, 0)]], [[(0.1, 0.1), (0.5, -0.5), (0.1, 0.1)]], [[(-1000000000, 1000000), (3000000, 1000000), (-1000000000, 1000000), (-1000000000, 1000000), (1000000, -1000000000), (1000000, -1000000000), (-1000000000, 1000000)]], [[(0.1, 0.1), (0.2, 0.2), (0.1, 0.1), (0.2, 0.2), (0.1, 0.1), (0.2, 0.2)]], [[(-10, 20), (15, -2), (-10, 21), (15, -2)]]]
results = [36, 200, 484, 200, 4500000000000, 1, 0, 10000, 0, 1000000000000, 4, 0.25, 99999980000001, 1000000000000000, 1000000000000, 0, 1000000000000, 200, 0.25, 1, 1, 1000000000000000, 1000001000000, 0, 1, 200, 0.25, 10000000, 1, 200, 0.05, 0, 200000, 1000000000000000, 4500000000000, 1000000000000000, 200, 200, 180, 10000, 1000000001000000, 0.25, 10000, 0.05, 0, 10000010, 1000000000000000, 200, 0, 1000000000000000, 1000000000000000, 200000, 0.25, 0, 9999999000000000, 200, 0, 9999999000000, 200, 50, 200, 1000000000000000, 1000000000000000, 1000000000000000, 1, 45, 0.05, 0.04000000000000001, 0.05, 0, 0.04000000000000001, 0.04000000000000001, 1000000001000000, 0.25, 4, 4500000000000, 0.04000000000000001, 1000000001000000, 1000000000000000, 1000000001000000, 0.25, 0.25, 0, 9999999000000000, 0, 1000000000000000, 0.05, 10000000, 1000000001000000, 1000000000000, 1000000000000000, 0.04000000000000001, 200, 10000, 0.25, 1, 200, 200000, 1000000000000000, 1000000000000, 1000000000000000, 0.05, 0.04000000000000001, 1000000000000000, 30000000, 0.04000000000000001, 50, 50, 1, 30000000, 0.04000000000000001, 0, 0.25, 1000000000000000, 0.04000000000000001, 210]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(max_product_tuple(*inp), exp, 0.0001)
| OK=True
==================== Problem #69 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sum all amicable numbers from 1 to a specified number.
Your answer will be tested on test cases like:
assert amicable_numbers_sum(999)==504
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sum all amicable numbers from 1 to a specified number.
Your answer will be tested on test cases like:
assert amicable_numbers_sum(999)==504
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sum all amicable numbers from 1 to a specified number.
Your answer will be tested on test cases like:
assert amicable_numbers_sum(999)==504
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sum all amicable numbers from 1 to a specified number.
Your answer will be tested on test cases like:
assert amicable_numbers_sum(999)==504
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to sum all amicable numbers from 1 to a specified number.
Your answer will be tested on test cases like:
assert amicable_numbers_sum(999)==504
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function that sums all amicable numbers up to a given number. Let me think about what amicable numbers are. Oh right, amicable pairs are two distinct numbers where the sum of the proper divisors of each equals the other. Like 220 and 284. So, for each number up to N, I need to check if it's part of such a pair and sum them.
First, I need a way to find the sum of proper divisors of a number. Proper divisors are numbers less than the number that divide it. For example, for 220, the sum is 1 + 2 + 4 + ... etc. So, how to calculate that efficiently?
Hmm, for a number n, I can iterate from 1 to sqrt(n) and add the divisors. Wait, but I need to avoid counting the number itself. Wait, the proper divisors exclude the number itself. So for each n, the sum of proper divisors would be the sum of all divisors except n.
So, maybe a helper function called sum_of_divisors(n) that returns the sum of proper divisors. Let me think about how to implement that.
Let me think of the helper function. For n, iterate from 1 to sqrt(n), check if i divides n. If i is a divisor, add i and n/i. But need to be careful with perfect squares to avoid adding the square root twice. Also, subtract n itself if it's included. Wait, for example, for n=6, the proper divisors are 1, 2, 3. Sum is 6. So the function should return 6. So the helper function should calculate the sum of all divisors except the number itself.
So, here's a way: initialize sum as 1 (since 1 is a proper divisor for all n > 1). Then iterate from 2 to sqrt(n). For each i that divides n, add i and n/i if they are different. But wait, for n=6, sqrt(n) is about 2.45. So i would be 2. 6 divided by 2 is 3. So add 2 and 3. So sum would be 1 + 2 + 3 = 6. That works.
But for n=1, the sum is 0, since there are no proper divisors. So the helper function needs to handle that.
So the helper function:
def sum_of_proper_divisors(n):
if n == 1:
return 0
total = 1 # 1 is a proper divisor for n > 1
sqrt_n = int(math.sqrt(n))
for i in range(2, sqrt_n + 1):
if n % i == 0:
total += i
other = n // i
if other != i:
total += other
return total
Wait, but for numbers like 6, this would loop from 2 to 2 (sqrt(6) is ~2.45, so sqrt_n is 2). So i=2, 6%2 is 0. Add 2 and 3. So total is 1 + 2 + 3 = 6. Correct.
Another example: n=220. Let's see. The sum of proper divisors is 284. But I don't need to check that now. The helper function should return that.
Once I have this helper function, I can check for amicable pairs. So, for each number a in 1 to N, compute b = sum_of_proper_divisors(a). Then check if sum_of_proper_divisors(b) equals a, and also that a != b. Also, need to ensure that each pair is only counted once. For example, if a and b are a pair, then when we check a, we find b, and when we check b, we find a. So if we just add both, we would count them twice. So how to avoid that?
The problem says to sum all amicable numbers from 1 to N. So for each pair (a, b), both a and b are amicable numbers. But when we process a, we check if it's part of a pair. However, if we process both a and b, we might add both to the sum. But we need to make sure that each pair is only counted once. Wait, the problem says to sum all amicable numbers. So for example, if the pair is (a, b), then both a and b are amicable numbers. So if N is large enough to include both, then both should be added to the sum. However, if we check for each number whether it's part of a pair, but we need to avoid adding both a and b twice. Wait, no. Because for example, when a is 220, and b is 284, when we check 220, we find that its sum is 284, and then check if sum of 284's divisors is 220. If yes, then 220 and 284 are a pair. So, in that case, we need to add both numbers to the sum, but only once each. So the approach is to check for each a, if it's part of a pair, and if so, add both a and b to the sum, but ensuring that we don't process the same pair twice. For example, when a is 220, and b is 284, when we process a, we check if b is within N, and if so, add both. But when we process b, we check if a is within N, and then add again. Which would result in adding both twice. So that's a problem.
So how to avoid that? One way is to check if a < b, and then add both if they are within the limit. So for example, when processing a, if a is part of a pair (a, b), and a < b, then add both a and b to the sum. But then, when processing b, we would check if it's part of a pair, which would be a, but since a < b, we would have already added them. So to avoid processing the same pair twice, we can check if a < b. So, the algorithm would be:
Initialize sum to 0.
For each a from 2 to N:
compute b = sum_of_proper_divisors(a)
if b > N: continue
if b == a: continue (since it's a perfect number, not part of an amicable pair)
compute c = sum_of_proper_divisors(b)
if c == a and a < b:
sum += a + b
So, in this way, each pair is considered once. Because when a is processed, and if a < b, then we add both. When b is processed, since b > a, the condition a < b is not met (since a is now b, and b is a, but in that case, the code would check if a < b, which would be false). Wait, maybe not. Let me think.
Let me think: For a pair (a, b), where a < b. When processing a, we check if b is within N. Then check if sum_of_proper_divisors(b) is a. If yes, then add a and b. When processing b, the sum_of_proper_divisors(b) is a. So then, we check if a is within N. Then check if sum_of_proper_divisors(a) is b. Which it is. Then check if a < b. Since a is less than b, but in this case, the code would check if a < b, which is true. But then, we would add a and b again. Which would result in duplicates.
Wait, no. Because when processing a, we check if a < b. Then, when processing b, we check if b < a? No. Because when processing b, the code would compute c = sum_of_proper_divisors(b) which is a. Then check if c == a (which is true), and then check if b < a? No, because a < b. So the condition would be false. So the code would not add again.
Wait, let me rephrase. For each a in the loop, we check if b is sum of divisors of a. Then check if sum of divisors of b is a. Then, if a < b, then add a and b to the sum. So when a is 220, and b is 284, the code would check if 220 < 284 (yes), and add them. Then, when a is 284, compute b as sum of divisors of 284, which is 220. Then check if sum of divisors of 220 is 284 (yes). Then check if 284 < 220? No. So the code would not add them again. So this way, each pair is added once.
So that's the approach. So the steps are:
- For each a from 2 to N:
- compute b = sum_of_proper_divisors(a)
- if b is equal to a, skip (perfect numbers, not part of amicable pairs)
- if b is greater than N, skip
- compute c = sum_of_proper_divisors(b)
- if c == a and a < b, then add a + b to the sum.
So that's the plan.
Now, let's think about the helper function. For example, the sum_of_proper_divisors(220) should be 284. Let me test that.
But first, the helper function. Let's see for n=220.
The code for sum_of_proper_divisors(220):
n=220, which is greater than 1. So total starts at 1.
sqrt(220) is about 14.83, so sqrt_n is 14.
Loop from 2 to 14.
Check for each i:
i=2: 220 % 2 == 0. So add 2 and 220/2=110. total becomes 1 + 2 + 110 = 113.
i=3: 220%3 is 220/3 is 73.333. 3*73=219, remainder 1. So no.
i=4: 220%4 is 220-4*55=0. So yes. Add 4 and 55. total is 113 + 4 +55 = 172.
i=5: 220%5 is 0. Add 5 and 44. total is 172 +5 +44 = 221.
i=6: 220/6 is 36.666. 6*36=216. remainder 4. No.
i=7: 220/7 is 31.428... 7*31=217, remainder 3. No.
i=8: 220/8=27.5. No.
i=9: 220/9 is 24.444... no.
i=10: 220%10 is 0. Add 10 and 22. total is 221 + 10 +22 = 253.
i=11: 220%11 is 0. 11 and 20. Add them. total 253 +11+20= 284.
i=12: 220/12 is 18.333. No.
i=13: 220/13 is 16.923. No.
i=14: 220/14 is 15.714... no.
So the total is 284. Which is correct. So the helper function returns 284 for 220.
Then, for 284, sum_of_proper_divisors(284) would be 220. So that's correct.
Now, the code for the amicable_numbers_sum function.
The function needs to take a number N and return the sum of all amicable numbers up to N.
So the steps:
Initialize sum_amicable = 0
Loop a from 2 to N:
b = sum_of_proper_divisors(a)
if b == a: continue
if b > N: continue
c = sum_of_proper_divisors(b)
if c == a and a < b:
sum_amicable += a + b
Return sum_amicable
But wait, what if a is 6? sum_of_proper_divisors(6) is 6. So it's a perfect number. So it's skipped. So that's correct.
Now, testing the example given: assert amicable_numbers_sum(999) == 504.
Let me think. What's the amicable pairs under 1000?
The first pair is 220 and 284. Are there others?
Another pair is 1184 and 1210, but those are above 999. So in the range up to 999, the only pair is 220 and 284. So the sum is 220 + 284 = 504. Which matches the test case. So the code should return 504.
So, the code should work.
Now, implement this in Python.
But first, the helper function. Need to import math.
Now, code:
def amicable_numbers_sum(n):
def sum_of_proper_divisors(num):
if num == 1:
return 0
total = 1
sqrt_num = int(math.sqrt(num))
for i in range(2, sqrt_num + 1):
if num % i == 0:
total += i
other = num // i
if other != i:
total += other
return total
sum_amicable = 0
for a in range(2, n + 1):
b = sum_of_proper_divisors(a)
if b == a:
continue
if b > n:
continue
c = sum_of_proper_divisors(b)
if c == a and a < b:
sum_amicable += a + b
return sum_amicable
Wait, but in the code, for a in range(2, n+1). Because the upper limit is n.
But let's test for n=999. The code would process a from 2 to 999. For a=220, b=284. Then check if 284 is <= 999. Yes. Then compute c = sum_of_proper_divisors(284) which is 220. Then check if c == a (220 == 220, yes) and a < b (220 < 284, yes). So add 220+284=504. That's the sum. So the code returns 504. Which is correct.
Another test case: if n is 284, then the code would process a=220 (if 220 is <=284). So when a=220, b=284. Then check if 284 is <=284 (yes). Then compute c = sum_of_proper_divisors(284) = 220. Then check if 220 == a (220) and a < b (220 < 284). So add 220+284. But if n is 284, then the sum would be 504. But if the code is called with n=284, then the sum would include 220 and 284. But if the code is called with n=220, then b=284 is larger than n, so it's skipped. So the code would return 0 for n=220.
But for the test case given, the code works.
But what about other pairs? Let me think. Are there any other amicable pairs under 1000?
Yes, there's another pair: 1184 and 1210, but they are over 1000. So in the range up to 999, only 220 and 284. So the code works.
But what about other pairs? For example, 69660 and 876360, but those are way larger. So the code seems correct.
Now, code needs to import math. So the code should have import math.
So the full code would be:
import math
def amicable_numbers_sum(n):
def sum_of_proper_divisors(num):
if num == 1:
return 0
total = 1
sqrt_num = int(math.sqrt(num))
for i in range(2, sqrt_num + 1):
if num % i == 0:
total += i
other = num // i
if other != i:
total += other
return total
sum_amicable = 0
for a in range(2, n + 1):
b = sum_of_proper_divisors(a)
if b == a:
continue
if b > n:
continue
c = sum_of_proper_divisors(b)
if c == a and a < b:
sum_amicable += a + b
return sum_amicable
Wait, but what about when a is 284 and b is 220. Then, when a is 284, the code checks for b = sum_of_proper_divisors(284) which is 220. Then, since 220 is <=n (assuming n is 999), then compute c = sum_of_proper_divisors(220) which is 284. Then check if c == a (284 == 284, yes) and a < b (284 < 220? No). So the condition is false, so it's not added again. So the code adds the pair once.
Yes, that's correct.
Now, test case: amicable_numbers_sum(999) returns 504. Which is correct.
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[999], [9999], [99], [10000], [5000], [4999], [4998], [5001], [90], [92], [89], [91], [10001], [93], [5002], [4997], [True], [94], [4996], [4995], [10002], [88], [10003], [5003], [5004], [21], [87], [22], [4994], [95], [86], [96], [20], [9998], [4993], [23], [47], [97], [5005], [10004], [9], [9997], [10005], [85], [8], [46], [9996], [84], [7], [19], [9995], [98], [10006], [18], [100], [101], [24], [68], [61], [69], [44], [43], [17], [5006], [16], [6], [10], [45], [10007], [66], [15], [83], [48], [9994], [81], [60], [74], [5007], [67], [28], [80], [72], [79], [70], [29], [49], [9993], [65], [4992], [4991], [11], [10008], [73], [12], [62], [71], [4990], [5008], [78], [50], [59], [77], [10009]]
results = [504, 31626, 0, 31626, 8442, 8442, 8442, 8442, 0, 0, 0, 0, 31626, 0, 8442, 8442, 0, 0, 8442, 8442, 31626, 0, 31626, 8442, 8442, 0, 0, 0, 8442, 0, 0, 0, 0, 31626, 8442, 0, 0, 0, 8442, 31626, 0, 31626, 31626, 0, 0, 0, 31626, 0, 0, 0, 31626, 0, 31626, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8442, 0, 0, 0, 0, 31626, 0, 0, 0, 0, 31626, 0, 0, 0, 8442, 0, 0, 0, 0, 0, 0, 0, 0, 31626, 0, 8442, 8442, 0, 31626, 0, 0, 0, 0, 8442, 8442, 0, 0, 0, 0, 31626]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(amicable_numbers_sum(*inp), exp, 0)
| OK=False
==================== Problem #70 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the angle of a complex number.
Your answer will be tested on test cases like:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the angle of a complex number.
Your answer will be tested on test cases like:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the angle of a complex number.
Your answer will be tested on test cases like:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the angle of a complex number.
Your answer will be tested on test cases like:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to get the angle of a complex number.
Your answer will be tested on test cases like:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called angle_complex that takes two arguments, which are the real and imaginary parts of a complex number, and returns its angle. Hmm, right. The angle of a complex number is calculated using the arctangent of the imaginary part over the real part. But wait, I remember that Python's math module has a function called atan2 that takes y and x as arguments, which is exactly this case. Oh right, because the regular arctangent might not account for the correct quadrant, but atan2 does. So using math.atan2 would be better here.
Wait, the problem says that the test case is checking for the angle of 0 + 1j, which is π/2 radians, approximately 1.5707963267948966. So if I use math.atan2(imaginary, real), then for (0,1), that should give me π/2. Let me think: math.atan2(y, x) returns the correct angle. So for a complex number represented as (real, imaginary), the angle is atan2(imaginary, real). So the function should take the real and imaginary parts as inputs, then compute math.atan2(imaginary, real).
Wait, but in Python, the complex number's angle can be found using the cmath.phase function. But maybe the problem expects me to compute it using math.atan2. Because if the user passes in the real and imaginary parts as separate arguments, then using math.atan2 is the way to go.
So the function would be:
import math
def angle_complex(real, imag):
return math.atan2(imag, real)
Wait, but wait, the test case is using 0 and 1j. Wait, in the test case, the first argument is 0, and the second is 1j. So in the function, the real part is 0, and the imaginary part is 1. So math.atan2(1, 0) should return pi/2. Which it does. Because math.atan2(y, x) returns the angle theta such that x = r cos(theta), y = r sin(theta). So yes, when x is 0 and y is positive, the angle is pi/2.
So the function should take real and imaginary parts as parameters. So the code would be:
import math
def angle_complex(real, imag):
return math.atan2(imag, real)
But wait, what about when the real part is zero? Like in the test case. Let me check. For example, math.atan2(1, 0) returns pi/2, which is correct. So that's exactly what the test case is checking. So the code should work.
But wait, the parameters for the function: when the user passes 0 and 1j, but in the function, the real part is 0, and the imaginary part is 1. So the code is correct.
So the code should be as follows. Also, the function needs to be self-contained. So the code should import math, define the function, and return the correct value.
So the final code would be:
import math
def angle_complex(real, imag):
return math.atan2(imag, real)
Yes. That's the solution. Let me test with the given test case. The test case is assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001). Wait, but 1j is the imaginary part. So in the function, the imag parameter is 1.0? Because 1j is a complex number, but when you pass it as the second argument, maybe the function is expecting a float. Wait, wait, in Python, if you pass 1j as the imag argument, but math.atan2 expects a float. Wait, but 1j is a complex number. Oh wait, no. Wait, the function is called with (0, 1j), which would be real=0, imag=1j. But math.atan2 takes two floats. Wait, but 1j is a complex number. So this would be a problem. Wait, but in Python, if you pass 1j as the second argument, which is a complex number, but math.atan2 expects a float. Oh, wait, that's a problem. Wait, but the test case is written as angle_complex(0,1j), but the function is expecting real and imag as parameters. But 1j is a complex number. So perhaps the function should take the real and imaginary parts as separate parameters. Wait, but in the test case, the second argument is 1j. But that's a complex number. So maybe the function is supposed to take a complex number as input. Wait, but the problem says that the function is to get the angle of a complex number, but the parameters are given as real and imaginary parts. Wait, the problem says: "Write a function to get the angle of a complex number." But the parameters are given as (0,1j), which seems like the real and imaginary parts. Wait, but 0 is a real part, and 1j is the imaginary part. But in Python, the imaginary part is a float. Wait, perhaps the function is supposed to take two arguments: the real part and the imaginary part. But in the test case, the second argument is 1j, which is a complex number. Wait, but that would be incorrect. Because if the function is supposed to take real and imaginary parts as separate parameters, then the test case is passing 0 (real part) and 1j (imaginary part). But 1j is a complex number. Wait, perhaps the test case is written in a way that the function is supposed to take a complex number as input. Wait, maybe the function is supposed to take a single complex number as input. But the problem says to write a function that takes the real and imaginary parts. Wait, the problem's test case is written as angle_complex(0,1j). So the function has two parameters, real and imag. But 1j is a complex number. So perhaps the test case is incorrect, but maybe the function is supposed to take two arguments: the real part and the imaginary part. But in that case, the test case is passing 0 (real) and 1j (imaginary part). But 1j is a complex number. Wait, but perhaps the test case is written in a way that the function is supposed to take a complex number as input. Wait, maybe the function should take a single complex number as input, but the problem says to write a function that takes real and imaginary parts. This is confusing.
Wait, the problem says: "Write a function to get the angle of a complex number." So perhaps the function should take a complex number as input, like angle_complex(z), where z is a complex number. But the test case is written as angle_complex(0,1j), which would imply that the function takes two arguments. So maybe the function is supposed to take two arguments: real and imaginary parts. But in that case, the test case is passing 0 (real) and 1j (imaginary part). But 1j is a complex number. Wait, but maybe the function is supposed to take two parameters, which are the real and imaginary parts. So for example, for the complex number 0 + 1j, the real part is 0, and the imaginary part is 1. So the function is called with real=0, imag=1. But in the test case, the code is angle_complex(0,1j), which would pass imag=1j. But that would be a problem. Because math.atan2 expects two floats. So if the function is called with imag=1j, then math.atan2 would get a complex number, which would cause an error.
Wait, this seems to be a contradiction. Let me re-examine the problem.
The test case given is:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
So the function angle_complex is called with two arguments: 0 and 1j. But 1j is a complex number. However, the function is supposed to return the angle of a complex number. So perhaps the function is supposed to take two arguments, real and imaginary parts, which are floats. But in the test case, the second argument is 1j, which is a complex number. That would be a problem. Unless the function is supposed to take a complex number as input. Wait, maybe the function is supposed to take a single complex number, but the test case is written with two arguments. That doesn't make sense. Alternatively, perhaps the function is supposed to take two arguments, real and imaginary parts, which are floats, and the test case is written with 0 and 1j, but that's a mistake. But perhaps the test case is correct, and the function should accept two arguments, which can be complex numbers. But that's not possible. Because math.atan2 requires two floats.
Wait, maybe the test case is written incorrectly. Because 1j is a complex number. But in Python, if you pass 1j as the imaginary part, then the function would need to extract the real and imaginary parts. But perhaps the function is supposed to take a single complex number as input. For example, the function could be written as:
def angle_complex(z):
return math.atan2(z.imag, z.real)
Then, for z = 0 + 1j, it would return math.atan2(1, 0) which is pi/2. But then the test case is written as angle_complex(0, 1j), which would not match. So that's a problem.
Alternatively, maybe the test case is written with a mistake. Perhaps the function is supposed to take a single complex number as input, and the test case should be angle_complex(1j). But the test case shows angle_complex(0, 1j), which would imply that the function has two parameters.
Alternatively, perhaps the function is supposed to take two parameters, real and imaginary parts, which are floats, and the test case is passing 0 and 1j as real and imaginary parts. But that's not correct. Because 1j is a complex number. The imaginary part is 1.0, not 1j. So perhaps the test case is written incorrectly. But the user says that the answer will be tested on that test case. So the function must accept those parameters.
Wait, but in Python, if you pass 1j as the imaginary part, then in the function, the imag variable would be 1j. Then, math.atan2(imag, real) would be math.atan2(1j, 0). But math.atan2 expects two floats. So that would raise a TypeError. Therefore, the test case must be wrong, but perhaps the user made a mistake. Or perhaps the function is supposed to take a complex number as input. Let me think again.
Alternatively, maybe the test case is written in a way that the function is supposed to take two parameters, real and imaginary parts, but the test case is passing 0 as the real part and 1j as the imaginary part. But that's not correct. Because the imaginary part should be a float. So the test case should be angle_complex(0, 1), not 1j. But the user provided the test case as angle_complex(0,1j). So perhaps the user made a mistake in the test case. But I have to write the function to pass that test case.
Alternatively, perhaps the test case is written with 1j as the imaginary part, but in reality, the function is supposed to take a complex number. For example, if the function is written as:
def angle_complex(z):
return math.atan2(z.imag, z.real)
Then, when called with z=1j, it would return the correct angle. But the test case is written as angle_complex(0, 1j), which would not match. So this is confusing.
Alternatively, maybe the test case is written with a mistake, and the function should take a single complex number as input. But the problem says that the function is supposed to get the angle of a complex number, which is usually done via cmath.phase(z) or math.atan2(z.imag, z.real). But the test case is written with two arguments.
Wait, perhaps the user made a mistake in the test case. For example, the test case may have intended to pass (0, 1) instead of (0, 1j). But the user provided the test case as is. So I need to make sure that the function works with that test case.
But if the function is written to take two arguments, real and imag, and the test case passes 0 and 1j, then the imag argument is 1j, which is a complex number. So in the function, math.atan2(imag, real) would be math.atan2(1j, 0), which is invalid. Because math.atan2 expects two floats. So this would raise a TypeError. Therefore, the test case is incorrect, but the user says that the answer will be tested on that test case. Therefore, perhaps the function should take a single complex number as input.
Wait, maybe the function is supposed to take two arguments, but they are real and imaginary parts, which are floats. So the test case is wrong, but I need to write the function to work with that. But how?
Alternatively, perhaps the test case is written with a mistake, and the correct call is angle_complex(0, 1), not 1j. Because 1j is a complex number, but the imaginary part is 1. So in that case, the function would be:
def angle_complex(real, imag):
return math.atan2(imag, real)
Then, when called with (0, 1), it would return pi/2. But the test case is passing 1j as the second argument, which would be a problem.
Hmm, this is a problem. How to reconcile this? Maybe the user made a mistake in the test case. But since the user says that the function will be tested on that test case, I have to make sure that the function passes it.
Wait, maybe the function is supposed to take two arguments, which are complex numbers. But that doesn't make sense. Or perhaps the function is supposed to take a complex number and return its angle. So the function signature would be def angle_complex(z), and the test case is written incorrectly. But the user's test case shows angle_complex(0, 1j). So this is conflicting.
Alternatively, perhaps the function is supposed to take two arguments, which are the real and imaginary parts. So for the complex number 0 + 1j, the real part is 0 and the imaginary part is 1. So the function is called with real=0, imag=1. But in the test case, the user is passing 1j as the second argument, which is a complex number. That would be incorrect. But perhaps the user made a mistake in the test case, and the correct code is to pass 1 as the second argument. In that case, the function would be correct.
But since the user provided the test case as is, I have to make sure that the function works with it. So perhaps the test case is incorrect, but I need to proceed.
Alternatively, maybe the test case is written correctly, and the function should take two arguments, real and imaginary parts, which are complex numbers. But that doesn't make sense. Because the angle is calculated using the real and imaginary parts as floats.
This is a bit of a puzzle. Let me think about the possible scenarios.
If the function is defined as taking two arguments, real and imag, which are floats, then the test case angle_complex(0, 1j) is passing 1j as the imag parameter. But 1j is a complex number. So in that case, the code would fail because math.atan2 expects two floats. But the test case is expecting it to return a value. So this implies that the function is supposed to take a single complex number as input. For example, the function could be defined as:
def angle_complex(z):
return math.atan2(z.imag, z.real)
Then, when called with z=1j, it would return math.atan2(1.0, 0.0), which is pi/2. But the test case is written as angle_complex(0, 1j), which would not match this function signature.
So this is confusing. But the user's test case is:
assert math.isclose(angle_complex(0,1j), 1.5707963267948966, rel_tol=0.001)
So the function is called with two arguments, 0 and 1j. So the function must have two parameters. So the function is supposed to take real and imaginary parts as arguments. But the imaginary part is passed as 1j, which is a complex number. So perhaps the function should extract the imaginary part from the complex number. But that would require the function to handle complex numbers as inputs. So for example, the function could be:
def angle_complex(real, imag):
return math.atan2(imag.imag, real.real)
But that would be if real and imag are complex numbers. But that seems unlikely.
Alternatively, perhaps the test case is incorrect, and the correct call should be angle_complex(0, 1), and the user made a mistake in writing 1j instead of 1. In that case, the function would work as expected.
But since the user says that the function will be tested on that test case, I have to assume that the test case is correct. So how can I make the function work with that test case?
Wait, in Python, the complex number 1j has a real part of 0 and an imaginary part of 1. So if the function is called with real=0 and imag=1j, then the imaginary part is 1j. But that's a complex number. How can I get the angle from that?
Wait, maybe the function is supposed to take two complex numbers, but that doesn't make sense. Or maybe the function is supposed to take a real part and a complex number as the imaginary part, but that's not standard.
Alternatively, perhaps the test case is written incorrectly, and the function is supposed to take a single complex number as input. So the function should be:
def angle_complex(z):
return math.atan2(z.imag, z.real)
Then, for z = 1j, this would return the correct value. But the test case is written as angle_complex(0, 1j), which would not match this function signature. So this is a problem.
But the user's test case is written as angle_complex(0,1j). So I have to make the function take two arguments. So the function is supposed to take two arguments, real and imaginary parts. But in the test case, the second argument is 1j, which is a complex number. But that would imply that the imaginary part is 1j, which is a complex number. But how to compute the angle from
----------------------------------------------
Result: Pred=None | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [(0.0, 1j), (2.0, 1j), (0.0, 2j), (0.0, 0j), (1e-100, 1e-100j), (1.0, (-0-1j)), (-3.0, 4j), (-1.0, 0.5j), (-1.0, (-0-2j)), (5.0, (-0-3j)), (1.0, (-0-1e-16j)), (-1000000.0, 1j), (0.001, 0.001j), (-0.002, 0.003j), (5000.0, (-0-5000j)), (2.0, 2j), (5.0, (-0-1e-16j)), (-1000000.0, 1e-100j), (-1.0, -0.2094810906938558j), (0.001, 1.0104890444966959j), (0.0, 0.003j), (0.0, (-0-1e-16j)), (0.001, 1e-100j), (5.0, 2j), (1.0, 2.016370180069777j), (5.0, 0.003j), (-1000000.0, 0.003j), (-1.0, -1.1516856344430004j), (0.001, 0.6725319152086964j), (0.0, -0.010355262258335274j), (2.0, (-0-1j)), (-3.0, 1j), (5000.0, 0j), (0.0, 0.975464332791085j), (1.0, 1j), (0.0, 1.9698673032096357j), (0.001, 1.0219314567339677j), (5000.0, 0.003j), (5000.0, 0.3936790862469757j), (-1.0, 0j), (1e-100, 1.0219314567339677j), (0.0, 0.6725319152086964j), (0.001, -0.8400056138335225j), (0.0, 1.0623785268964003j), (-2.0, (-0-2j)), (-1.0, (-0-1e-16j)), (-2.0, -1.4466815811938807j), (-0.420215439612294, 1.0219314567339677j), (0.0, -0.8400056138335225j), (-1.0, 0.003j), (2.0, (-0-3j)), (0.0, -0.7464229304074054j), (5.0, (-0-1j)), (-1.0, 0.7612695873124079j), (2.0, -2.62106615192279j), (1.0, 4j), (1.0, -0.24099175426302122j), (1.0, 1.0623785268964003j), (5001.0, 0.003j), (-3.0, 0.7612695873124079j), (1.0, 1.0104890444966959j), (0.001, (-0-3j)), (1.0, 0.6725319152086964j), (0.001, -0.8715172340818781j), (1.0, 3.2198297580460986j), (-0.24387354740075257, 1.0219314567339677j), (0.001, -1.1516856344430004j), (1e-100, -0.1029778505874197j), (5.0, -0.2094810906938558j), (-763284.5778121873, 1j), (2.0, 0.8691541649826418j), (0.0, -4999.924286520318j), (2.0, (-0-1e-16j)), (5000.0, (-0-1j)), (5000.0, -0.2094810906938558j), (1.0, -0.1029778505874197j), (5000.0, -0.010355262258335274j), (0.0007807920872595409, 0.6725319152086964j), (5001.0, 0.975464332791085j), (2.0, 0.975464332791085j), (0.0007732910823548642, 0.001j), (5000.0, 0.5697754263979038j), (3.0, 1j), (0.0007732910823548642, -0.6005568184440887j), (5.0, (-0-2j)), (-0.24387354740075257, 1e-100j), (-1.0, 2.016370180069777j), (5.0, 1j), (-3.0, -0.24099175426302122j), (5001.0, -0.2094810906938558j), (1.0, 0.746539818763773j), (1.0, 0.6430961891723811j), (1.0, 3.0401020209872165j), (1.0, 0.5697754263979038j), (3.0, 0j), (5.0, 0.975464332791085j), (1.0, -0.010355262258335274j), (1.0, 1.2472534570917213j), (0.001, 0.2808016878272164j), (-0.24387354740075257, -0.6005568184440887j), (0.0, 1.6394342209431512j), (7.0, (-0-1j)), (-0.24387354740075257, 0.11629069822069693j), (5000.0, -4999.787677780481j), (0.0, -0.6005568184440887j), (-1.0, 1j), (5.0, -0.7272148602507602j), (5001.0, 1.628767403187359j), (0.001, 0.6755064392822638j), (7.0, 1.2472534570917213j), (1.0, 0.8045352400481771j), (0.0, (-0-1j))]
results = [1.5707963267948966, 0.4636476090008061, 1.5707963267948966, 0.0, 0.7853981633974483, -0.7853981633974483, 2.214297435588181, 2.677945044588987, -2.0344439357957027, -0.5404195002705842, -1e-16, 3.1415916535897934, 0.7853981633974483, 2.158798930342464, -0.7853981633974483, 0.7853981633974483, -1.9999999999999998e-17, 3.141592653589793, -2.935097503165345, 1.5698067072844257, 1.5707963267948966, -1.5707963267948966, 1e-97, 0.3805063771123649, 1.1104014431812392, 0.0005999999280000155, 3.1415926505897933, -2.285814737388355, 1.5693094096086464, -1.5707963267948966, -0.4636476090008061, 2.819842099193151, 0.0, 1.5707963267948966, 0.7853981633974483, 1.5707963267948966, 1.5698177878975654, 5.99999999999928e-07, 7.873581708669206e-05, 3.141592653589793, 1.5707963267948966, 1.5707963267948966, -1.569605859122863, 1.5707963267948966, -2.356194490192345, -3.141592653589793, -2.515372879526448, 1.960918111233556, -1.5707963267948966, 3.1385926625897445, -0.982793723247329, -1.5707963267948966, -0.19739555984988075, 2.490917937562239, -0.9189964914877319, 1.3258176636680326, -0.23648250986307637, 0.8156348609311445, 5.998800239951291e-07, 2.8930815706323374, 0.7906152767961402, -1.570462993473909, 0.5920521756892685, -1.5696489030584135, 1.2696657660459925, 1.8050548184065056, -1.5699280345120177, -1.5707963267948966, -0.04187173054255484, 3.1415913434624447, 0.4099544764199125, -1.5707963267948966, -5e-17, -0.0001999999973333334, -4.1896218114257775e-05, -0.10261614184321532, -2.0710524516640937e-06, 1.569635353287464, 0.00019505385331338622, 0.4537852644763088, 0.9125547986768521, 0.00011395508478631625, 0.3217505543966422, -1.569508703990125, -0.3805063771123649, 3.141592653589793, 2.031191210408554, 0.19739555984988075, -3.061434194054647, -4.1887840546158345e-05, 0.6412829122604286, 0.5715066061270702, 1.2530082821139132, 0.517899009776432, 0.0, 0.1926727405632964, -0.0103548921455297, 0.8949821254321993, 1.5672351096942738, -1.9565322614534364, 1.5707963267948966, -0.14189705460416394, 2.696637311690111, -0.7853769307246828, -1.5707963267948966, 2.356194490192345, -0.14443024473721994, 0.0003256883314533101, 1.5693159570880375, 0.17632859194255202, 0.6775002210922619, -1.5707963267948966]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(angle_complex(*inp), exp, 0.0001)
| OK=False
==================== Problem #71 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between the number of 0s and number of 1s in any sub-string of the given binary string.
Your answer will be tested on test cases like:
assert find_length("11000010001") == 6
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between the number of 0s and number of 1s in any sub-string of the given binary string.
Your answer will be tested on test cases like:
assert find_length("11000010001") == 6
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between the number of 0s and number of 1s in any sub-string of the given binary string.
Your answer will be tested on test cases like:
assert find_length("11000010001") == 6
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between the number of 0s and number of 1s in any sub-string of the given binary string.
Your answer will be tested on test cases like:
assert find_length("11000010001") == 6
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find the maximum difference between the number of 0s and number of 1s in any sub-string of the given binary string.
Your answer will be tested on test cases like:
assert find_length("11000010001") == 6
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, let's see. I need to write a Python function called find_length that takes a binary string and returns the maximum difference between the number of 0s and 1s in any substring. The example given is "11000010001" which should return 6. Hmm, how do I approach this?
First, I need to understand what exactly the problem is asking. The maximum difference between 0s and 1s in any substring. So for any substring, calculate (number of 0s - number of 1s), and find the maximum value of that.
Wait, but how do I efficiently compute that for all possible substrings? Because checking every possible substring would be O(n^2) time, which might be acceptable for small strings, but maybe there's a smarter way.
Alternatively, think about transforming the problem. Let's consider each character as +1 for 0 and -1 for 1. Then the problem becomes finding the maximum difference between the sum of a subarray. Because the difference (0s - 1s) is equivalent to sum of (1 for 0, -1 for 1) over the substring. So the problem reduces to finding the maximum sum subarray. Oh right! Because the maximum sum subarray would correspond to the maximum (0s - 1s) difference.
Wait, but the maximum sum subarray can be found using Kadane's algorithm. That's O(n) time. So that's efficient. So the problem is equivalent to converting the binary string into an array of +1 and -1, then finding the maximum subarray sum.
But wait, let me confirm. Let's take the example given: "11000010001". Let's convert each character to -1 (for 1) and +1 (for 0). Let's see:
Original string: 1 1 0 0 0 0 1 0 0 0 1
Converted to: -1 -1 +1 +1 +1 +1 -1 +1 +1 +1 -1
Now, the maximum subarray sum would be the maximum sum of any contiguous subarray. Let's see. For example, the substring from index 2 to 5 (0s) would be four 0s. Their sum is 4. But the example says the answer is 6. Wait, maybe I'm missing something here. Let me check the example again.
The example says find_length("11000010001") returns 6. Let's think: what substring gives a difference of 6?
Let me count. Suppose there's a substring with 6 more 0s than 1s. Let's see the string:
Original string is "11000010001". Let's look for substrings. For example, the substring "0000" (positions 2-5) has 4 zeros and 0 ones. Difference is 4-0 = 4. But the answer is 6. Hmm. Another substring: maybe "00001000" ?
Wait, let's think again. Let me try to find a substring where the difference is 6. Let's take the substring from index 2 to 6 (assuming 0-based or 1-based? Let's check the original string. Let me write the string as indexes:
Let's index from 0:
Indices 0: '1', 1: '1', 2: '0', 3: '0', 4: '0', 5: '0', 6: '1', 7: '0', 8: '0', 9: '0', 10: '1'.
So the substring from index 2 to 5 (0-based) is '0000', which is 4 zeros, difference is 4-0=4. What about from index 2 to 8? That's 00001000. Let's count:
Number of 0s: 0s are at 2,3,4,5,7,8. So 6 zeros. 1s are at 6. So difference is 6-1=5. Not 6.
Wait, maybe the substring from 2 to 9? That would be 00001000. Wait, index 2 to 9 is 0,0,0,0,1,0,0,0. So 0s count is 7 (positions 2,3,4,5,7,8,9?), wait, index 9 is 0. So that's 7 zeros and 1 one. Difference is 6. Oh right! So that substring has 7 zeros and 1 one. 7-1=6. So that's the answer.
So how does this translate into the transformed array? Let's see the transformed array for that substring. The substring is from index 2 to 9 (assuming 0-based). The converted values are:
Original substring: 0,0,0,0,1,0,0,0. Converted to +1, +1, +1, +1, -1, +1, +1, +1. The sum is (4*1) + (-1) + 3*1 = 4 -1 +3 = 6. So the maximum sum is 6. So using Kadane's algorithm on the transformed array would give the correct answer.
So the problem reduces to converting the binary string into an array of +1 and -1, then finding the maximum subarray sum. So the solution is to use Kadane's algorithm.
So the steps are:
1. Convert the binary string into an array where each '0' is +1 and '1' is -1.
2. Apply Kadane's algorithm to find the maximum subarray sum.
But wait, what if the string is all 1s? Then the maximum difference would be 0 (since all substrings have 0s - 1s as negative, but the maximum would be the least negative. Wait, but the problem says "maximum difference between the number of 0s and number of 1s". So if the substring has more 1s than 0s, the difference would be negative. But the maximum could be negative. However, the problem says "maximum difference", which could be a positive value. But perhaps the problem expects the maximum possible value, even if it's negative. Wait, but in the example, the answer is 6. So the maximum is positive.
But in the case where the string is all 1s, the maximum difference would be 0 (if the substring is empty?), but the problem requires any substring. Wait, but the substring must be non-empty. So for example, if the string is "111", then the maximum difference is (number of 0s - number of 1s) for any substring. For any substring, that's 0 - len(substring). So the maximum is -1 (for a substring of length 1). But according to the problem statement, is that acceptable? But the problem says "maximum difference", which would be -1 in that case. However, the problem's example returns a positive value. So perhaps the problem expects that the maximum is the maximum possible (could be negative). However, in the problem's test case, the answer is 6. So the function must return the maximum value possible.
But how to handle this with Kadane's algorithm. Because Kadane's algorithm finds the maximum sum subarray, which would be the maximum difference between 0s and 1s.
So the approach is correct.
Now, how to implement Kadane's algorithm in Python.
But let's think about the code. Let's write a function that converts the string into the array of +1 and -1, then applies Kadane's algorithm.
Let me think about the code.
First, the function:
def find_length(s):
Then, create the transformed array. For each character in s:
transformed = [1 if c == '0' else -1 for c in s]
Then, apply Kadane's algorithm on this array.
But what about the case where the array is all negative? For example, if the string is all 1s, then the transformed array is all -1. The maximum subarray sum would be -1 (the maximum is the single element). But according to the problem, that would be the maximum difference (0s - 1s) for any substring, which would be -1 for a substring of length 1.
But the problem's test case expects a positive value. So the code would return the correct value.
So the code needs to compute the maximum subarray sum.
Now, implementing Kadane's algorithm.
Initialize current_max and max_so_far to the first element. Then iterate from the second element.
But what if the array is empty? Well, the problem says that the input is a binary string, which is non-empty? Well, the problem's test case has a string of length 11. So assuming that the input is a non-empty string.
But in the code, need to handle the case when the string is empty? Probably not, since the problem says "given binary string", which I assume is non-empty.
So, code steps:
Initialize current_max = transformed[0]
max_so_far = transformed[0]
for i in range(1, len(transformed)):
current_max = max(transformed[i], current_max + transformed[i])
max_so_far = max(max_so_far, current_max)
At the end, return max_so_far.
But let's test with the example.
For the example, transformed array is:
Original string: "11000010001"
transformed = [-1, -1, 1, 1, 1, 1, -1, 1, 1, 1, -1]
Let's compute Kadane's algorithm on this array.
Let's walk through:
Initialize current_max = -1, max_so_far = -1.
i=1 (value -1):
current_max = max(-1, -1 + (-1) = -2) => -1. So current_max is -1. max_so_far is max(-1, -1) remains -1.
i=2 (value 1):
current_max = max(1, -1 + 1=0) => 1. max_so_far is now 1.
i=3 (value 1):
current_max = max(1, 1 + 1=2) => 2. max_so_far is 2.
i=4 (value 1):
current_max = 2 + 1=3. max_so_far is 3.
i=5 (value 1): current_max = 3 +1=4. max_so_far 4.
i=6 (value -1): current_max = max(-1, 4-1=3) => 3. max_so_far remains 4.
i=7 (value 1): current_max = 3 +1=4. max_so_far is 4. (since 4 is same as current max_so_far)
i=8 (value 1): current_max = 4 +1=5. max_so_far is 5.
i=9 (value 1): current_max = 5+1=6. max_so_far is 6.
i=10 (value -1): current_max = max(-1, 6-1=5) =>5. max_so_far remains 6.
So the final max_so_far is 6, which matches the example. So the code works.
So the code is correct.
Now, code in Python:
def find_length(s):
transformed = [1 if c == '0' else -1 for c in s]
if not transformed:
return 0 # though input is non-empty
current_max = max_so_far = transformed[0]
for num in transformed[1:]:
current_max = max(num, current_max + num)
max_so_far = max(max_so_far, current_max)
return max_so_far
But wait, what if the string is empty? Well, the problem's test case has a string, so perhaps we can assume that the input is non-empty. So the code should handle that.
Testing the example, the code returns 6. So that's correct.
Another test case: if the string is "0000", then the transformed array is [1,1,1,1]. Kadane's algorithm returns 4, which is the correct difference (4-0=4).
Another test case: "111" → transformed is [-1, -1, -1]. The maximum subarray sum is -1. So the function returns -1. But according to the problem, the maximum difference is (number of 0s - 1s). For any substring, that's 0 - len(substring). So for substring of length 1, it's -1. Which is the maximum. So the code returns -1, which is correct.
But the problem says "maximum difference between the number of 0s and number of 1s in any sub-string". So the code is correct.
So the code should be correct. Now, write this as a Python function inside the markdown code block.
But the problem says that the function is called find_length and the test case is assert find_length("11000010001") == 6. So the code should work.
So the final code is:
def find_length(s):
transformed = [1 if c == '0' else -1 for c in s]
current_max = max_so_far = transformed[0]
for num in transformed[1:]:
current_max = max(num, current_max + num)
max_so_far = max(max_so_far, current_max)
return max_so_far
Wait, but what if the string is empty? Well, the problem probably expects that the input is non-empty, so the code is okay.
Yes, that's the code.
```python
def find_length(s):
transformed = [1 if c == '0' else -1 for c in s]
current_max = max_so_far = transformed[0]
for num in transformed[1:]:
current_max = max(num, current_max + num)
max_so_far = max(max_so_far, current_max)
return max_so_far
```
----------------------------------------------
Result: Pred=def find_length(s):
transformed = [1 if c == '0' else -1 for c in s]
current_max = max_so_far = transformed[0]
for num in transformed[1:]:
current_max = max(num, current_max + num)
max_so_far = max(max_so_far, current_max)
return max_so_far | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [['11000010001'], ['10111'], ['11011101100101'], [''], ['0000000011111111'], ['000000111111'], ['0000001110000001111111'], ['00000011110000001111111'], ['000000000000111111111111'], ['00000000000011111111110000001111000000111111111'], ['00000011100000101111111'], ['000000100000011110000001111111110000001111111'], ['0000000000000111111111111'], ['100000011100000000111111111000000011111101'], ['0000000000001111111111000000111100000011110000001111000000111111111111'], ['0000000000001111111101111'], ['000000000000011111111110000001111000000111111111'], ['0000001000000001111111111111'], ['00000000000011111111110000000000000000001111111111111111000000111111111'], ['0000001111000000000000111100000011111111111111'], ['0000000000001111111111111'], ['00000000111000001011111111111111'], ['0000001011111'], ['0000000000111100000011111111111111'], ['00000001111111111110000000010000000000001111111111000000111100000011110000001111000000111111111111111111111111'], ['0000000111111101111'], ['000000011111111111100000000100000000000001111111111000000111100000011110000001111000000111111111111111111111111'], ['000000111110000001111111'], ['0000000000000000011111111110000000000000000001111111111111111000000111111111011110000001111111'], ['00000000000011111111111111'], ['00000000000000000111111111100000000000000000011111111111111110000001111111110111100000011111100000010000000011111111111111'], ['00000000011111111'], ['0000000100000011110000001111111110000001111111000000000001111111101111'], ['000000000000111111111100000000000000000011111111111111110000001'], ['000000111000001001111111'], ['000000000010111111100000001111111111111'], ['0000000100000011100000000111111111000000011111101000111100000011111111111111'], ['000011'], ['0000000111111111111000000001000000000000111111111100000011110000000000000000000001111111111000000000000000000111111111111111100000011111111101111000000111111111'], ['0000011'], ['00000011'], ['000000111100000010111111'], ['0000001110000010011111111'], ['00000000000000010000001111000000111111111000000111111111111111'], ['00000011100000010011111111'], ['000000111000000010011111111'], ['00000001111111111110000000010000000000000000000000001111111111000000000000000000111111111111111100000011111111101111111111000000111100000011110000001111000000111111111111111111111111'], ['1000000111000000001111111111000000011111101'], ['000000000000111000000111111110000001111000000111111111'], ['000000000000000111000000010011111111000111111111111'], ['00000001111111111110000000010000000000001111111111000000111100000000000000000000011111111110000000000000000001111101111111111100000011111111101111000000111111111'], ['000000100000011111111101000001111111'], ['0000000000001111111110000001110000000011111111110000000111111011111'], ['0000000111111111111000000001000000000000111111111100000011110000001111000000111100000011111111000000001110000010111111111111111111111111111111'], ['00000011100000110011111111'], ['00000011010000010011111111'], ['00000000000000111111111100000000000000000011111111111111110000001000011110000001111111'], ['0000000111111111111000000001000000000000011111111110000001111000000111100000011110000001111111111111111111'], ['00000000001111000000011111111111111'], ['000000001110000010111110000000111111111111000000001000000000000000000000000111111111100000000000000000011111111111111110000001111111110111111111100000011110000001111000000111111111111111111111111111111'], ['00000000000000011111111110000000011111111111100000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111'], ['00000000111000001011111000000011111111111100000000100000000000000000000000011111111110000000000000000001111111111111111000000111111111101111111111000000111100000011110000001111111111111111111111111111111'], ['000000000000000000000111111111111000111111111100000000000000000011111111111111111000000111111111'], ['00001001110000001111111'], ['00000001111111111110000000010000000000000000011111111111100000000100000000000011111111110000001111000000000000000000000111111111100000000000000000011111011111111111000000111111111011110000001111111110001111111111000000111100000011110000001111000000111111111111111111111111'], ['10000001110000000010000000000000001000000111100000011111111100000011111111111111111111111000000000001111100000011111110011111101'], ['00000000000000011111111110000000011100000011111000000111111111111111100000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111'], ['0000001110000001000000001111111111110000000010000000000001111111111000000111100000000000000000000011111111110000000000000000001111101111111111100000011111111101111000000111111111011111111'], ['0000001110000001001111111'], ['00000011110000000000001111000000111111000000111100000000000011110000001111111111111111111111'], ['0000000000001111111111000000000000000000111111011111111110000001'], ['0000001111000000000001111111111111'], ['0000001110000010011111'], ['000000011111111111100000000100000000000011111111110000000001111111111000000000000000000111111111111111100000011111111101111000000111111111'], ['0000001110000010111111'], ['0000000000000001111111111000000001110000000000011100000101111111011111000000111111111111111100000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111'], ['00000000000010000000011100000101111100000001111111111110000000010000000000000000000000001111111111000000000000000000111111111111111100000011111111101111111111000000111100000011110000001111111111111111111111111111111111111111111'], ['00000011110000000000111111111111000000001000000000000111111111100000011110000001111000000111100000011111111000000001110000010111111111111111111111111111111000000001111111111111'], ['000000111000100110011111111'], ['00000010100000001111111011111111'], ['00000010000000011111111111000000000000111111111100000000000000000011111101111111111000000111'], ['00000000000011111111100000010000000011111111111111000000111100000011110000001111000000111111111111'], ['0000001010000000111111'], ['000000000000011111111100000010000000011111111111111000000111100000011110000001111000000111111111111'], ['0000000000000000000001111111111110001111111111000000000000000000111111111111111110000001111101111'], ['00000000000000000000011111111111100011111111110000000000000000001111111111111111110000001111101111'], ['0000000000000001111111111000000001110000000000011100000101111110000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111'], ['000000000000011111111111'], ['0000001010000000000111000001011111111111111000001111111011111111'], ['0000000111111111111000000001000000000000111111111100000000011111111110000000000000000001111111111111111100000011111111101111000000111111111'], ['000000000000000111111111100000000111111111111100000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111'], ['0000001111000000000011111111111100000000100000000000011111111110000001111000000111100000011110000001111111100000000111000001011111111111111111111111111111100000000111111000000000000100000000111000001011111000000011111111111100000000100000000000000000000000011111111110000000000000000001111111111111111000000111111111011111111110000001111000000111100000011111111111111111111111111111111111111111111111111'], ['000000000000111111111000000111000000001111111111000000001111000000000011111111111100000000100000000000011111111110000001111000000111100000011110000001111111100000000111000001011111111111111111111111111111100000000111111111111100000111111011111'], ['00000001111111111110000000010000000000001111111111000000111100000000000000000000011111111110000000000000000001111111111111111000000111111111011110000100111111111'], ['0000000011100000101111100000001111111111110000000010000000000000000000000001111111111000000000000000000111111111111111100000011111111101111111111000000111100000011110100000111111111111111111111111111111'], ['000000000111111111'], ['00000000000000000000000000111111111111000111111111100000000000000000011111111111111111000000111110111100000000000000000011111111111111110000001000011110000001111111'], ['00000111111'], ['0000000000000111000001011111111111111000011111111'], ['00000001111111111110000000010000000000001111111111000000111100000000000000000000000000000000001111111111000000001110000000000011100000101111110000000100000000000011111111110000001111000000111100000011110000001111111111111111111111110000011110000001111111110000111000000010011111111111101111111111100000011111111101111000000111111111'], ['0000001110000001001000000000000011111111000000000000000000000111111111111000111111111100000000000000000011111111111111111000000111110111111000000111100000010111111111111111'], ['1110000001010000000000111000001011111111111111000001111111011111111'], ['0000000000001111111110000000000000000000001111111111110001111111111000000000000000000111111111111111110000001111101111111'], ['0000001110000001111'], ['000000101101011']]
results = [6, 1, 2, 0, 8, 6, 9, 8, 12, 12, 8, 13, 13, 11, 14, 12, 13, 13, 20, 16, 12, 10, 6, 12, 21, 7, 22, 7, 25, 12, 25, 9, 15, 20, 9, 10, 17, 4, 40, 5, 6, 8, 9, 22, 10, 11, 39, 11, 15, 20, 40, 11, 14, 23, 8, 10, 22, 22, 13, 39, 22, 39, 21, 8, 52, 32, 22, 44, 10, 26, 20, 13, 9, 26, 8, 23, 50, 23, 7, 12, 22, 16, 12, 17, 21, 21, 37, 13, 17, 26, 21, 52, 29, 40, 39, 9, 26, 5, 15, 67, 35, 17, 24, 9, 6]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(find_length(*inp), exp, 0)
| OK=False
==================== Problem #72 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the sum of common divisors of two given numbers.
Your answer will be tested on test cases like:
assert sum(10,15) == 6
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the sum of common divisors of two given numbers.
Your answer will be tested on test cases like:
assert sum(10,15) == 6
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the sum of common divisors of two given numbers.
Your answer will be tested on test cases like:
assert sum(10,15) == 6
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the sum of common divisors of two given numbers.
Your answer will be tested on test cases like:
assert sum(10,15) == 6
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a python function to find the sum of common divisors of two given numbers.
Your answer will be tested on test cases like:
assert sum(10,15) == 6
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function that finds the sum of common divisors of two numbers. Let's think about how to approach this.
First, what's a common divisor? It's a number that divides both numbers without leaving a remainder. So for example, for 10 and 15, their common divisors are 1 and 5, and the sum is 6. The test case given is assert sum(10,15) == 6, which matches that.
So the steps I need to take are:
1. Find all the divisors of each number.
2. Find the common divisors between the two sets.
3. Sum those common divisors.
Wait, but how do I efficiently find the common divisors? Well, maybe there's a smarter way than generating all divisors for each number and then finding the intersection. Because for large numbers, generating all divisors could be time-consuming.
Alternatively, the greatest common divisor (GCD) of the two numbers will be the largest number that divides both. Then, all common divisors are the divisors of the GCD. So, for example, GCD of 10 and 15 is 5. The divisors of 5 are 1 and 5, which sum to 6. So that's correct.
So the plan is:
- Compute the GCD of the two numbers.
- Find all divisors of the GCD.
- Sum those divisors.
That's more efficient, especially for larger numbers.
So first, how to compute the GCD in Python? Oh right, the math module has a gcd function. But wait, in Python versions before 3.5, math.gcd might not be available. However, assuming that the environment uses a recent Python version, that's acceptable. Also, note that math.gcd returns the absolute value, but since the inputs are positive integers (as they are numbers for which divisors are considered), that's okay.
Wait, but the problem says "two given numbers"—but divisors are for positive integers. So I should assume that the inputs are positive integers. So the function can take two integers, and compute their GCD.
Once I have the GCD, I need to find all its divisors and sum them.
So how to find the divisors of a number. Let's take the GCD value, say g. Then, find all numbers that divide g.
To find the divisors of g, I can loop from 1 to sqrt(g), check if i divides g. If so, add both i and g/i to the list, but avoid duplicates when g is a perfect square.
Alternatively, for each number from 1 to g, check if it divides g. But that's O(n) time, which for small numbers is acceptable. However, for very large g, the first method is better.
But given that the problem is for a programming problem, perhaps the numbers aren't too big, so even a simple approach would work.
So let's think of the steps for the function:
Function sum_common_divisors(a, b):
1. Compute the GCD of a and b. Let's call it g.
2. Find all divisors of g.
3. Sum those divisors.
So, for example, for a=10, b=15, GCD is 5. Divisors of 5 are 1,5. Sum is 6.
Now, how to implement this in Python.
First, import math and compute the GCD.
But wait, what if one of the numbers is zero? Well, the problem says "given numbers"—probably positive integers. But the function needs to handle cases where a or b is zero? Well, the problem's test case uses 10 and 15, so perhaps the function is intended for positive integers. But let's think: if either a or b is zero, then the GCD is the other number. But for example, if a is zero and b is non-zero, then the GCD is b. But divisors of zero? Well, in mathematics, zero can't have divisors because any number divides zero. But in this problem, perhaps the inputs are positive integers. So the function can assume that a and b are positive integers.
So the code can proceed under that assumption.
So, code steps:
def sum_common_divisors(a, b):
import math
g = math.gcd(a, b)
# Now find all divisors of g and sum them.
# How to find divisors of g?
# Initialize sum as 0
total = 0
# Iterate from 1 to sqrt(g) + 1?
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
# i is a divisor, and so is g//i
if i == g // i:
total += i
else:
total += i + g//i
return total
Wait, but this code would work for numbers where the square root is not an integer. Let me test with g=5. The square root is ~2.236. So the loop runs from 1 to 2+1=3? Wait, range(1, int(5**0.5) +1) is range(1, 2+1) = range(1,3), which is 1 and 2.
For i=1: 5%1 ==0. So add 1 and 5//1=5. So total becomes 1+5=6. Then i=2: 5%2 is 1, so no addition. So total is 6. Which is correct.
Another test case: g=6. Divisors are 1, 2, 3, 6. Sum is 12.
Let's see:
sqrt(6) is ~2.449. So int(2.449) is 2. So range(1, 2+1) is 1,2.
i=1: 6%1=0. So add 1 and 6. total is 7.
i=2: 6%2=0. So 2 and 3. Add 2+3=5. total becomes 7+5=12. Correct.
Another example: g=4. Divisors are 1,2,4. Sum is 7.
Loop runs from 1 to 2 (sqrt(4) is 2, so int(2) +1 is 3? Wait, range(1, int(4**0.5) +1) is range(1, 2 +1) = 1, 2.
i=1: 4%1=0. Add 1 and 4. total is 5.
i=2: 4%2=0. 2 and 4//2=2. Since i and g//i are same, add 2. total is 5+2=7. Correct.
So the code works.
But what if g is 0? Well, if a and b are both zero, then their GCD is zero. But divisors of zero? Well, in that case, the code would have g=0. Then, in the loop, trying to compute sqrt(0) is zero. So the loop runs from 1 to 0+1=1, which is range(1,1), which is empty. So total remains zero. But the sum of divisors of zero is undefined, but perhaps the function is intended for positive integers. So the problem's test cases probably don't have zero. So the code is okay.
But the problem says "given numbers"—so perhaps the function should handle cases where a or b is zero? But the problem's test case uses 10 and 15. So maybe the function is intended for positive integers. So the code is okay.
So putting it all together.
But wait, the code has to be a self-contained function. So the code would be:
import math
def sum_common_divisors(a, b):
g = math.gcd(a, b)
total = 0
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
if i == g // i:
total += i
else:
total += i + g // i
return total
Wait, but what if g is 0? For example, if a=0 and b=0. Then math.gcd(0,0) returns 0. Then the loop runs from 1 to 0 +1 = 1. So range(1,1) is empty. So returns 0. But the sum of common divisors of 0 and 0 is undefined, but the code returns 0. However, perhaps the problem expects that the inputs are positive integers. So the code is okay.
Testing the sample input:
sum_common_divisors(10,15) → GCD is 5. Sum of divisors is 1+5=6. Which matches the test case.
Another test case: a=12, b=18. GCD is 6. Divisors of 6: 1,2,3,6. Sum is 12. So function returns 12. Let's see:
Loop for i from 1 to 2 (sqrt(6) is ~2.449, so int is 2. range(1, 3) is 1,2.
i=1: 6%1=0 → add 1 +6 → total 7.
i=2: 6%2=0 → add 2 + 3 → total 7+5=12. Correct.
Another test case: a=1, b=1. GCD is 1. Sum is 1. The code returns 1.
Another case: a=2, b=4. GCD is 2. Divisors are 1,2. Sum is 3. The code would loop from 1 to 1 (sqrt(2) is ~1.414, int is 1. range(1, 2) → i=1. 2%1=0. So add 1 + 2 → total 3. Correct.
So the code seems correct.
But wait, in the code, when g is 0, the loop is not entered. So returns 0. But if a and b are 0, then the sum of common divisors would be undefined. But the problem's test cases probably don't include that. So the code is okay.
So the function should be written as such.
Now, the code needs to be written in a markdown code block as a self-contained Python function. The user's example shows that the code should be inside a markdown code block with triple backticks.
So the final code would be:
import math
def sum(a, b):
g = math.gcd(a, b)
total = 0
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
if i == g // i:
total += i
else:
total += i + g // i
return total
Wait, but the function is named 'sum'? But the user's test case uses sum(10,15) == 6. However, in Python, 'sum' is a built-in function. So renaming the function to something else would be better. But the user's test case uses 'sum' as the function name. So perhaps the user's code is expecting the function to be named 'sum'.
But the problem says "write a python function to find the sum...". So the function name is up to the user. However, the test case uses sum(10,15) == 6. So the function must be named 'sum'.
But in Python, using 'sum' as a function name is not a good idea because it shadows the built-in sum function. However, the user's test case uses that, so the code must have the function named 'sum'.
But the code as written would have the function named 'sum', which is allowed. However, in Python, the code may raise a warning, but it's allowed.
So the code would be:
import math
def sum(a, b):
g = math.gcd(a, b)
total = 0
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
if i == g // i:
total += i
else:
total += i + g // i
return total
But wait, what about when a and b are zero? For example, sum(0,0) would return 0. But that's not a valid case. But the problem's test case is for positive integers.
But the code should work for all positive integers.
So the code should be correct. Let me check the sample input.
Testing sum(10,15) → returns 6. Which is correct.
Another test case: sum(12, 18) → returns 12. Which is correct.
Another case: sum(5,5) → GCD is 5, sum of divisors 1+5=6. So returns 6.
Yes.
So the code is correct.
```python
import math
def sum(a, b):
g = math.gcd(a, b)
total = 0
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
if i == g // i:
total += i
else:
total += i + g // i
return total
```
----------------------------------------------
Result: Pred=import math
def sum(a, b):
g = math.gcd(a, b)
total = 0
for i in range(1, int(g**0.5) + 1):
if g % i == 0:
if i == g // i:
total += i
else:
total += i + g // i
return total | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10, 15], [100, 150], [4, 6], [27, 81], [12, 18], [123, 456], [555, 1111], [987, 654], [10, 3], [987654321, 123456789], [555, 456], [987654322, 81], [555, 987654322], [3, 987654321], [555, 555], [123, 1111], [987654321, 987654321], [456, 456], [81, 555], [123456790, 123456790], [123456789, 987654322], [123, 3], [12, 1111], [123456789, 81], [555, 554], [81, 456], [455, 456], [81, 457], [555, 987654323], [556, 553], [80, 456], [555, 553], [123456789, 456], [456, 987654323], [987, 986], [987654320, 987654321], [987654323, 987654322], [987654323, 987654323], [987654322, 987654321], [987654323, 10], [455, 987654320], [987654322, 987654322], [123456789, 123456790], [554, 457], [26, 82], [11, 3], [986, 987654323], [123, 123], [555, 81], [987654324, 987], [987654321, 18], [987654319, 987654318], [654, 654], [123456790, 455], [3, 987654322], [80, 987654321], [553, 553], [556, 457], [988, 654], [455, 123456789], [654, 987654321], [123456790, 654], [11, 123], [556, 1111], [27, 26], [80, 124], [556, 456], [987, 987], [457, 456], [553, 80], [81, 458], [123456789, 123456789], [457, 457], [457, 3], [123456789, 986], [985, 987], [986, 986], [987654320, 987654320], [456, 458], [2, 3], [124, 987654323], [987654320, 81], [12, 12], [987654321, 987654320], [125, 555], [81, 2], [654, 81], [654, 123456788], [987654319, 80], [81, 554], [457, 554], [987654323, 456], [456, 26], [81, 81], [556, 556], [654, 80], [987654319, 986], [123, 4], [556, 987654320], [456, 556], [987654320, 456], [987654321, 2], [126, 2], [556, 987654322], [18, 123456789], [2, 654], [457, 987654323], [985, 456], [2, 18], [3, 556]]
results = [6.0, 93.0, 3.0, 40.0, 12.0, 4.0, 1, 4.0, 1, 13.0, 4.0, 1, 1, 4.0, 912.0, 1, 1515470502.0, 1200.0, 4.0, 228228912.0, 1, 4.0, 1, 13.0, 1, 4.0, 1, 1, 1, 1, 15.0, 1, 4.0, 1, 1, 1, 1, 987654324.0, 1, 1, 6.0, 1483596972.0, 1, 1, 3.0, 1, 1, 168.0, 4.0, 4.0, 13.0, 1, 1320.0, 6.0, 1, 1, 640.0, 1, 3.0, 1, 4.0, 3.0, 1, 1, 1, 7.0, 7.0, 1536.0, 1, 1, 1, 178422816.0, 458.0, 1, 1, 1, 1620.0, 2358365424.0, 3.0, 1, 1, 1, 28.0, 1, 6.0, 1, 4.0, 3.0, 1, 1, 1, 1, 3.0, 121.0, 980.0, 3.0, 1, 1, 7.0, 7.0, 15.0, 1, 3.0, 3.0, 13.0, 3.0, 1, 1, 3.0, 1]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(sum(*inp), exp, 0)
| OK=True
==================== Problem #73 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply two integers.
Your answer will be tested on test cases like:
assert multiply_int(10,20)==200
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply two integers.
Your answer will be tested on test cases like:
assert multiply_int(10,20)==200
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply two integers.
Your answer will be tested on test cases like:
assert multiply_int(10,20)==200
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply two integers.
Your answer will be tested on test cases like:
assert multiply_int(10,20)==200
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to multiply two integers.
Your answer will be tested on test cases like:
assert multiply_int(10,20)==200
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called multiply_int that takes two integers and returns their product. Let's think about how to approach this.
First, the function needs to take two parameters, a and b. Then, multiply them. Oh right, in Python, the multiplication operator is *. So the function can be as simple as returning a * b.
Wait, but what about the test case? The example given is assert multiply_int(10,20) == 200. So when a is 10 and b is 20, the result should be 200. That's exactly what 10 * 20 gives. So the function should just return the product of the two parameters.
I should make sure that the function is named correctly, and the parameters are properly defined. Let me structure the code.
The code should be a self-contained function. So the code block would start with def multiply_int(a, b): and then return a * b.
I don't see any edge cases mentioned here. The problem says integers, so negative numbers, zero, etc., should be handled naturally by Python's multiplication.
So the code is straightforward. Let me write that.
```python
def multiply_int(a, b):
return a * b
```
----------------------------------------------
Result: Pred=def multiply_int(a, b):
return a * b | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[10, 20], [5, 10], [4, 8], [10000000000000000, 9999999999999999], [999999999999999999, 999999999999999999], [0, 999999999999999999], [-999999999999999999, 999999999999999999], [9999999999999999, -999999999999999999], [9999999999999999, 9999999999999999], [0, 0], [10000000000000000, 9999999999999998], [999999999999999998, 999999999999999998], [999999999999999999, 999999999999999998], [-999999999999999999, -999999999999999999], [-999999999999999999, -1000000000000000000], [0, 9999999999999999], [-999999999999999999, -999999999999999998], [10000000000000000, 999999999999999999], [10000000000000000, 10000000000000000], [1000000000000000000, 999999999999999999], [10000000000000001, -999999999999999999], [1000000000000000000, 0], [10000000000000000, -999999999999999998], [999999999999999999, 10000000000000001], [10000000000000001, 10000000000000001], [9999999999999999, 999999999999999999], [10000000000000000, -999999999999999999], [9999999999999999, 9999999999999998], [1, 0], [9999999999999999, 10000000000000000], [999999999999999998, 0], [9999999999999999, 0], [-2, 0], [-999999999999999997, -999999999999999998], [10000000000000000, 999999999999999998], [0, 9999999999999998], [-1, -1], [9999999999999999, -999999999999999998], [-999999999999999999, -1], [-999999999999999999, 0], [-1000000000000000000, 0], [-999999999999999999, 10000000000000000], [9999999999999998, 10000000000000000], [-1000000000000000000, 1000000000000000000], [1, 10000000000000001], [-2, 999999999999999999], [9999999999999998, 9999999999999999], [10000000000000001, 10000000000000000], [-999999999999999999, 999999999999999998], [999999999999999997, 999999999999999998], [10000000000000000, 999999999999999997], [9999999999999997, 9999999999999997], [9999999999999998, 1000000000000000000], [0, -1], [10000000000000001, 0], [9999999999999999, -2], [9999999999999999, 1], [10000000000000000, 10000000000000001], [10000000000000001, -1], [10000000000000001, 9999999999999998], [9999999999999998, 9999999999999998], [-1, 0], [-999999999999999997, -999999999999999997], [1000000000000000000, -999999999999999998], [-3, -1], [999999999999999997, 10000000000000000], [1000000000000000000, 1000000000000000000], [10000000000000000, -1], [1000000000000000001, -999999999999999998], [999999999999999998, -999999999999999999], [-3, 9999999999999997], [1, 1], [1000000000000000000, 9999999999999997], [False, False], [10000000000000000, 0], [1, 999999999999999999], [-999999999999999999, 999999999999999997], [1000000000000000000, -999999999999999997], [1, 1000000000000000001], [1, -999999999999999998], [999999999999999998, 10000000000000000], [0, 10000000000000001], [1, 2], [999999999999999996, 999999999999999998], [-999999999999999998, -3], [9999999999999999, 10000000000000001], [999999999999999998, 10000000000000001], [-999999999999999998, -999999999999999999], [10000000000000000, 1000000000000000000], [-1, 1000000000000000001], [-999999999999999998, -999999999999999998], [1, -1], [10000000000000002, -2], [9999999999999999, 1000000000000000001], [-999999999999999997, 999999999999999998], [-999999999999999998, 0], [10000000000000000, -2], [-1, -999999999999999998], [9999999999999997, -1], [9999999999999997, -999999999999999998], [2, 1], [-1, 1], [999999999999999997, 1000000000000000001], [9999999999999998, 9999999999999997], [-999999999999999998, 10000000000000000], [999999999999999999, -999999999999999998], [-3, -999999999999999998]]
results = [200, 50, 32, 99999999999999990000000000000000, 999999999999999998000000000000000001, 0, -999999999999999998000000000000000001, -9999999999999998990000000000000001, 99999999999999980000000000000001, 0, 99999999999999980000000000000000, 999999999999999996000000000000000004, 999999999999999997000000000000000002, 999999999999999998000000000000000001, 999999999999999999000000000000000000, 0, 999999999999999997000000000000000002, 9999999999999999990000000000000000, 100000000000000000000000000000000, 999999999999999999000000000000000000, -10000000000000000989999999999999999, 0, -9999999999999999980000000000000000, 10000000000000000989999999999999999, 100000000000000020000000000000001, 9999999999999998990000000000000001, -9999999999999999990000000000000000, 99999999999999970000000000000002, 0, 99999999999999990000000000000000, 0, 0, 0, 999999999999999995000000000000000006, 9999999999999999980000000000000000, 0, 1, -9999999999999998980000000000000002, 999999999999999999, 0, 0, -9999999999999999990000000000000000, 99999999999999980000000000000000, -1000000000000000000000000000000000000, 10000000000000001, -1999999999999999998, 99999999999999970000000000000002, 100000000000000010000000000000000, -999999999999999997000000000000000002, 999999999999999995000000000000000006, 9999999999999999970000000000000000, 99999999999999940000000000000009, 9999999999999998000000000000000000, 0, 0, -19999999999999998, 9999999999999999, 100000000000000010000000000000000, -10000000000000001, 99999999999999989999999999999998, 99999999999999960000000000000004, 0, 999999999999999994000000000000000009, -999999999999999998000000000000000000, 3, 9999999999999999970000000000000000, 1000000000000000000000000000000000000, -10000000000000000, -999999999999999998999999999999999998, -999999999999999997000000000000000002, -29999999999999991, 1, 9999999999999997000000000000000000, 0, 0, 999999999999999999, -999999999999999996000000000000000003, -999999999999999997000000000000000000, 1000000000000000001, -999999999999999998, 9999999999999999980000000000000000, 0, 2, 999999999999999994000000000000000008, 2999999999999999994, 99999999999999999999999999999999, 10000000000000000979999999999999998, 999999999999999997000000000000000002, 10000000000000000000000000000000000, -1000000000000000001, 999999999999999996000000000000000004, -1, -20000000000000004, 9999999999999999009999999999999999, -999999999999999995000000000000000006, 0, -20000000000000000, 999999999999999998, -9999999999999997, -9999999999999996980000000000000006, 2, -1, 999999999999999997999999999999999997, 99999999999999950000000000000006, -9999999999999999980000000000000000, -999999999999999997000000000000000002, 2999999999999999994]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(multiply_int(*inp), exp, 0)
| OK=True
==================== Problem #74 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find words that are longer than n characters from a given list of words.
Your answer will be tested on test cases like:
assert long_words(3,"python is a programming language")==['python','programming','language']
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find words that are longer than n characters from a given list of words.
Your answer will be tested on test cases like:
assert long_words(3,"python is a programming language")==['python','programming','language']
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find words that are longer than n characters from a given list of words.
Your answer will be tested on test cases like:
assert long_words(3,"python is a programming language")==['python','programming','language']
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find words that are longer than n characters from a given list of words.
Your answer will be tested on test cases like:
assert long_words(3,"python is a programming language")==['python','programming','language']
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Judger (judger) -----
[To Tokenize]
<|im_start|>user
Target Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to find words that are longer than n characters from a given list of words.
Your answer will be tested on test cases like:
assert long_words(3,"python is a programming language")==['python','programming','language']
You are a helpful assistant. You are provided with latent information for reference and a target question to solve.
The latent information might contain irrelevant contents. Ignore it if it is not helpful for solving the target question.
Your must reason step-by-step to solve the **provided Target Question** witout outputing other irrelevant inforamtion.
You must put all python code as self-contained Python function in markdown code blocks. For example ```python
import math
def add(a, b):
return a + b```. Do not add any other contents inside the markdown code block.
Now, reason step by step and output the final answer inside ```python
YOUR_PYTHON_CODE
```.
<|im_end|>
<|im_start|>assistant
[Output]
Okay, I need to write a Python function called long_words that takes two parameters: n and a string of words. The goal is to return a list of words from the string that are longer than n characters. Let me think about how to approach this.
First, the input is a string like "python is a programming language". So I need to split this string into individual words. The split() method without arguments splits on any whitespace, which should work here.
Once I have the list of words, I need to filter them based on their length. For each word in the list, check if its length is greater than n. So, using a list comprehension would be efficient here. Something like [word for word in words if len(word) > n].
Wait, the function parameters: the first argument is n, then the string. So the function definition should be def long_words(n, words_string):.
Let me test with the sample input. The sample call is long_words(3, "python is a programming language"). The words are ["python", "is", "a", "programming", "language"]. The lengths are 6, 2, 1, 11, 8. So words longer than 3 are python (6>3), programming (11>3), language (8>3). The expected output is ['python','programming','language'], which matches the sample assertion.
But wait, the sample assertion uses the string "python is a programming language" and the output includes 'python' which is 6 letters. So yes, longer than 3. So the code should split the string into words, check each length, collect those longer than n.
So putting it all together:
Split the input string into words. Then filter each word where len(word) > n. Return that list.
Now, code steps:
Define the function with parameters n and the string. Split the string into words. Use list comprehension to filter. Return the list.
Potential edge cases: words with exactly n characters should not be included. What if the input string is empty? Then return an empty list. Also, if there are punctuation marks? But the problem says it's a list of words, so perhaps the input is a simple string with words separated by spaces, no punctuation. So we don't need to handle that.
Another thing: the function is supposed to return a list of the words, in the same order as they appear in the input string. The list comprehension will preserve the order.
So the code would be:
def long_words(n, words):
return [word for word in words.split() if len(word) > n]
Wait, but the parameters: the second argument is the string. So in the function definition, the parameters are n and the string. So the code should be:
def long_words(n, words_string):
return [word for word in words_string.split() if len(word) > n]
But the sample test case is assert long_words(3,"python is a programming language")==['python','programming','language'].
Testing this code with that input: the split would create the list of words, and the list comprehension would select those with len>3. Which works.
So that's the function. But wait, the function name is long_words, and the parameters are n and the string. So that's correct.
So the Python code should be:
def long_words(n, words):
return [word for word in words.split() if len(word) > n]
Wait, but in the sample test case, the second argument is the string. So the function is called with (3, "python is..."), which would split into words. So this code should work.
Yes, that's the solution. Let me write that as the code.
```python
def long_words(n, words):
return [word for word in words.split() if len(word) > n]
```
----------------------------------------------
Result: Pred=def long_words(n, words):
return [word for word in words.split() if len(word) > n] | Gold=import numpy as np
from math import inf
def is_floats(x) -> bool:
# check if it is float; List[float]; Tuple[float]
if isinstance(x, float):
return True
if isinstance(x, (list, tuple)):
return all(isinstance(i, float) for i in x)
if isinstance(x, np.ndarray):
return x.dtype == np.float64 or x.dtype == np.float32
return False
def assertion(out, exp, atol):
if atol == 0 and is_floats(exp):
atol = 1e-6
if out != exp and atol != 0:
assert np.allclose(out, exp, rtol=1e-07, atol=atol)
else:
assert out == exp, f"out: {out}, exp: {exp}"
inputs = [[3, 'python is a programming language'], [2, 'writing a program'], [5, 'sorting list'], [0, 'abc def ghi jklm nopqrs tuvwxyz'], [0, ''], [10, 'thisisaverylongword testing wordlengths'], [100, 'hello python is a programming language'], [0, 'is'], [100, 'thisisaverylongwordw testing wordlengths'], [0, 'jklm'], [100, 'thisisaverylongwordw teseting wordlengths'], [0, 'thisisaverylongword testing wordlengths'], [10, 'is'], [10, 'hello python is a programming language'], [1, 'thisisaverylongword testing wordlengths'], [0, 'jklam'], [100, 'tuvwxyz'], [0, 'hello'], [0, 'jkjlam'], [100, ''], [1, 'jklam'], [100, 'thisisaverylongwordnopqrsw teseting wordlengths'], [10, 'heogramming language'], [10, ''], [100, 'i'], [11, 'thisisaverylongword testing wordlengths'], [100, 'thisisaverylongword'], [2, ''], [2, 'heogramming language'], [2, 'hello python is a programming language'], [100, 'ii'], [1, 'thisisaverylongwordw teseting wordlengths'], [100, 'thisisaveriylongwordw testing wordlengths'], [9, 'jklm'], [100, 'is'], [10, 'helloh python is a programming language'], [100, 'abc def ghi jklm nopqrs tuvwxyz'], [2, 'heogramming laneguage'], [0, 'ajklamteseting'], [100, 'thisisaveriylongwordw'], [100, 'thisisaverylongwordw testheogramming languageing wordlengths'], [0, 'thisisaverylongwordnopqrsw teseting wordlengths'], [99, 'thisisaveriylongwordw'], [0, 'a'], [0, 'hello python is a programming language'], [0, 'aa'], [0, 'thisisaveriylongwordw'], [10, 'python'], [10, 'jkl'], [1, 'hello python is a programming language'], [1, 'jkllm'], [100, 'thisisaverylongwordnopqrsw teseting wordlengthsi'], [101, 'thisisaverylongwordw testing wordlengths'], [99, 'thisisaverylongwordw teseting wordlengths'], [99, 'heogramming langualaneguagege'], [0, 'ii'], [101, 'thisisaverylongwordw testheogramming languageing wordlengths'], [11, 'jkl'], [1, ''], [101, 'abc def ghi jklm nopqrs tuvwx yz'], [0, 'thisisaveriylongwoordw'], [0, 'hlello'], [0, 'heogramming language'], [1, 'heogramming language'], [101, 'is'], [9, 'thisisaverylongwordnopqrsw teseting wordlengths'], [99, 'hello python is a programming language'], [1, 'thisisalanguageverylongwordw teseting wordleths'], [10, 'jkjlam'], [0, 'hlelllo'], [100, 'yz'], [0, 'ajheogramming languageklamteseting'], [9, 'helloh python is a programminlaneguageg language'], [11, 'thisisaveriylongwordw'], [2, 'thisisaverylongwordw teseting wordlengths'], [2, 'hlelllo'], [1, 'hello python is a prthisisaverylongwordnopqrsw teseting wordlengthsiogramming language'], [0, 'abc def ghi jklm thisisaveriylongwordwnopqrs tuvwxyz'], [101, 'aaa'], [11, 'heogramming language'], [2, 'wordlengthsiogramming'], [1, 'thisisalanguageverylthisisaverylongwordnopqrsw teseting wordlengthsiongwordw teseting wordleths'], [11, 'wordlengthsiongwordw'], [1, 'heogramminghelloh python is a programming languagelanguage'], [11, 'thisisaverylongword'], [11, 'ljkl'], [99, 'thisisalanguageverylongwordw'], [1, 'ajheogramming languageklamteseting'], [0, 'wordlengthsi'], [100, 'thisisaveriylongwordwnopqrs'], [102, 'aaa'], [102, 'aaaa'], [10, 'thisisaveriylongwordw testing wordlengths'], [0, 'jkl'], [10, 'thisisaverylongwordnopqrsw teseting wordlengths'], [10, 'jk'], [100, 'thisisaverylongwordnopqrsw tegseting wordlengthsi'], [101, 'thisisajklmverylongwordw testing wordlengths'], [1, 'heogramming laneguage'], [1, 'ajklamteseting'], [100, 'thisisaverylongwordw testheogramming languagein wordlengths'], [102, 'thisisaveriylongwordw testing wordlengths'], [100, 'thisisavongwordw'], [100, 'hlello'], [0, 'hello python is heogramming laneguagea programming language'], [10, 'wlengthsiongwordw'], [99, 'hello pylanguage']]
results = [['python', 'programming', 'language'], ['writing', 'program'], ['sorting'], ['abc', 'def', 'ghi', 'jklm', 'nopqrs', 'tuvwxyz'], [], ['thisisaverylongword', 'wordlengths'], [], ['is'], [], ['jklm'], [], ['thisisaverylongword', 'testing', 'wordlengths'], [], ['programming'], ['thisisaverylongword', 'testing', 'wordlengths'], ['jklam'], [], ['hello'], ['jkjlam'], [], ['jklam'], [], ['heogramming'], [], [], ['thisisaverylongword'], [], [], ['heogramming', 'language'], ['hello', 'python', 'programming', 'language'], [], ['thisisaverylongwordw', 'teseting', 'wordlengths'], [], [], [], ['programming'], [], ['heogramming', 'laneguage'], ['ajklamteseting'], [], [], ['thisisaverylongwordnopqrsw', 'teseting', 'wordlengths'], [], ['a'], ['hello', 'python', 'is', 'a', 'programming', 'language'], ['aa'], ['thisisaveriylongwordw'], [], [], ['hello', 'python', 'is', 'programming', 'language'], ['jkllm'], [], [], [], [], ['ii'], [], [], [], [], ['thisisaveriylongwoordw'], ['hlello'], ['heogramming', 'language'], ['heogramming', 'language'], [], ['thisisaverylongwordnopqrsw', 'wordlengths'], [], ['thisisalanguageverylongwordw', 'teseting', 'wordleths'], [], ['hlelllo'], [], ['ajheogramming', 'languageklamteseting'], ['programminlaneguageg'], ['thisisaveriylongwordw'], ['thisisaverylongwordw', 'teseting', 'wordlengths'], ['hlelllo'], ['hello', 'python', 'is', 'prthisisaverylongwordnopqrsw', 'teseting', 'wordlengthsiogramming', 'language'], ['abc', 'def', 'ghi', 'jklm', 'thisisaveriylongwordwnopqrs', 'tuvwxyz'], [], [], ['wordlengthsiogramming'], ['thisisalanguageverylthisisaverylongwordnopqrsw', 'teseting', 'wordlengthsiongwordw', 'teseting', 'wordleths'], ['wordlengthsiongwordw'], ['heogramminghelloh', 'python', 'is', 'programming', 'languagelanguage'], ['thisisaverylongword'], [], [], ['ajheogramming', 'languageklamteseting'], ['wordlengthsi'], [], [], [], ['thisisaveriylongwordw', 'wordlengths'], ['jkl'], ['thisisaverylongwordnopqrsw', 'wordlengths'], [], [], [], ['heogramming', 'laneguage'], ['ajklamteseting'], [], [], [], [], ['hello', 'python', 'is', 'heogramming', 'laneguagea', 'programming', 'language'], ['wlengthsiongwordw'], []]
for i, (inp, exp) in enumerate(zip(inputs, results)):
assertion(long_words(*inp), exp, 0)
| OK=True
==================== Problem #75 ====================
Question:
Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate whether the matrix is a magic square.
Your answer will be tested on test cases like:
assert magic_square_test([[7, 12, 1, 14], [2, 13, 8, 11], [16, 3, 10, 5], [9, 6, 15, 4]])==True
----- Agent: Planner (planner) -----
[To Tokenize]
<|im_start|>user
You are a Planner Agent. Given an input question, design a clear, step-by-step plan for how to solve the question.
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate whether the matrix is a magic square.
Your answer will be tested on test cases like:
assert magic_square_test([[7, 12, 1, 14], [2, 13, 8, 11], [16, 3, 10, 5], [9, 6, 15, 4]])==True
Your outlined plan should be concise with a few bulletpoints for each step. Do not produce the final answer.
Now output your plan to solve the question below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Critic (critic) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate whether the matrix is a magic square.
Your answer will be tested on test cases like:
assert magic_square_test([[7, 12, 1, 14], [2, 13, 8, 11], [16, 3, 10, 5], [9, 6, 15, 4]])==True
You are a Critic Agent to evaluate the correctness of the input plan for the given question and provide helpful feedback for improving the plan.
The plan information is provided in latent KV representation format. Review the plan and question and output:
(1) original plan contents
(2) constructive feedback on the original plan.
Format your response as follows:
Original Plan: [Copy the provided Planner Agent's plan here]
Feedback: [Your detailed feedback to improve the plan here]
Now, output your response below:
<|im_end|>
<|im_start|>assistant
[Latent Steps]
0
[Output]
----------------------------------------------
----- Agent: Refiner (refiner) -----
[To Tokenize]
<|im_start|>user
Question: Please provide a self-contained Python script that solves the following problem in a markdown code block:
```python
YOUR_PYTHON_CODE
```:
Write a function to calculate whether the matrix is a magic square.
Your answer will be tested on test cases like:
assert magic_square_test([[7, 12, 1, 14], [2, 13, 8, 11], [16, 3, 10, 5], [9, 6, 15, 4]])==True
You are a Refiner Agent to provide a refined step-by-step plan for solving the given question.
You are provided with:
(1) latent-format information: a previous plan with feedback
(2) text-format information: the input question you need to solve.
Based on the input, write a refined and improved plan to solve the question. Make sure your output plan is correct and concise.
Now, output your refined plan below:
<|im_end|>
<|im_start|>assistant
