SYMBOL INDEX (329 symbols across 73 files) FILE: bertopic/_bertopic.py class BERTopic (line 88) | class BERTopic: method __init__ (line 145) | def __init__( method _outliers (line 318) | def _outliers(self): method topic_labels_ (line 329) | def topic_labels_(self): method fit (line 350) | def fit( method fit_transform (line 395) | def fit_transform( method transform (line 545) | def transform( method partial_fit (line 649) | def partial_fit( method topics_over_time (line 797) | def topics_over_time( method topics_per_class (line 956) | def topics_per_class( method hierarchical_topics (line 1035) | def hierarchical_topics( method approximate_distribution (line 1204) | def approximate_distribution( method find_topics (line 1431) | def find_topics( method update_topics (line 1488) | def update_topics( method get_topics (line 1598) | def get_topics(self, full: bool = False) -> Mapping[str, Tuple[str, fl... method get_topic (line 1622) | def get_topic(self, topic: int, full: bool = False) -> Union[Mapping[s... method get_topic_info (line 1650) | def get_topic_info(self, topic: int | None = None) -> pd.DataFrame: method get_topic_freq (line 1703) | def get_topic_freq(self, topic: int | None = None) -> Union[pd.DataFra... method get_document_info (line 1734) | def get_document_info( method get_representative_docs (line 1826) | def get_representative_docs(self, topic: int | None = None) -> List[str]: method get_topic_tree (line 1872) | def get_topic_tree( method set_topic_labels (line 1979) | def set_topic_labels(self, topic_labels: Union[List[str], Mapping[int,... method generate_topic_labels (line 2042) | def generate_topic_labels( method merge_topics (line 2101) | def merge_topics( method delete_topics (line 2177) | def delete_topics( method reduce_topics (line 2313) | def reduce_topics( method reduce_outliers (line 2380) | def reduce_outliers( method visualize_topics (line 2541) | def visualize_topics( method visualize_documents (line 2595) | def visualize_documents( method visualize_document_datamap (line 2694) | def visualize_document_datamap( method visualize_hierarchical_documents (line 2805) | def visualize_hierarchical_documents( method visualize_term_rank (line 2925) | def visualize_term_rank( method visualize_topics_over_time (line 2988) | def visualize_topics_over_time( method visualize_topics_per_class (line 3044) | def visualize_topics_per_class( method visualize_distribution (line 3100) | def visualize_distribution( method visualize_approximate_distribution (line 3147) | def visualize_approximate_distribution( method visualize_hierarchy (line 3201) | def visualize_hierarchy( method visualize_heatmap (line 3301) | def visualize_heatmap( method visualize_barchart (line 3361) | def visualize_barchart( method save (line 3416) | def save( method load (line 3534) | def load(cls, path: str, embedding_model=None): method merge_models (line 3590) | def merge_models(cls, models, min_similarity: float = 0.7, embedding_m... method push_to_hf_hub (line 3751) | def push_to_hf_hub( method get_params (line 3821) | def get_params(self, deep: bool = False) -> Mapping[str, Any]: method _extract_embeddings (line 3844) | def _extract_embeddings( method _images_to_text (line 3884) | def _images_to_text(self, documents: pd.DataFrame, embeddings: np.ndar... method _map_predictions (line 3901) | def _map_predictions(self, predictions: List[int]) -> List[int]: method _reduce_dimensionality (line 3907) | def _reduce_dimensionality( method _cluster_embeddings (line 3958) | def _cluster_embeddings( method _zeroshot_topic_modeling (line 4010) | def _zeroshot_topic_modeling( method _is_zeroshot (line 4068) | def _is_zeroshot(self): method _combine_zeroshot_topics (line 4078) | def _combine_zeroshot_topics( method _guided_topic_modeling (line 4137) | def _guided_topic_modeling(self, embeddings: np.ndarray) -> Tuple[List... method _extract_topics (line 4177) | def _extract_topics( method _save_representative_docs (line 4217) | def _save_representative_docs(self, documents: pd.DataFrame): method _extract_representative_docs (line 4235) | def _extract_representative_docs( method _create_topic_vectors (line 4315) | def _create_topic_vectors( method _c_tf_idf (line 4398) | def _c_tf_idf( method _update_topic_size (line 4455) | def _update_topic_size(self, documents: pd.DataFrame): method _extract_words_per_topic (line 4464) | def _extract_words_per_topic( method _reduce_topics (line 4565) | def _reduce_topics(self, documents: pd.DataFrame, use_ctfidf: bool = F... method _reduce_to_n_topics (line 4598) | def _reduce_to_n_topics(self, documents: pd.DataFrame, use_ctfidf: boo... method _auto_reduce_topics (line 4655) | def _auto_reduce_topics(self, documents: pd.DataFrame, use_ctfidf: boo... method _sort_mappings_by_frequency (line 4726) | def _sort_mappings_by_frequency(self, documents: pd.DataFrame) -> pd.D... method _map_probabilities (line 4767) | def _map_probabilities( method _preprocess_text (line 4804) | def _preprocess_text(self, documents: np.ndarray) -> List[str]: method _top_n_idx_sparse (line 4819) | def _top_n_idx_sparse(matrix: csr_matrix, n: int) -> np.ndarray: method _top_n_values_sparse (line 4841) | def _top_n_values_sparse(matrix: csr_matrix, indices: np.ndarray) -> n... method _get_param_names (line 4858) | def _get_param_names(cls): method __str__ (line 4870) | def __str__(self): class TopicMapper (line 4887) | class TopicMapper: method __init__ (line 4913) | def __init__(self, topics: List[int]): method get_mappings (line 4923) | def get_mappings(self, original_topics: bool = True) -> Mapping[int, i... method add_mappings (line 4950) | def add_mappings(self, mappings: Mapping[int, int], topic_model: BERTo... method add_new_topics (line 5006) | def add_new_topics(self, mappings: Mapping[int, int]): function _create_model_from_files (line 5018) | def _create_model_from_files( FILE: bertopic/_save_utils.py function push_to_hf_hub (line 106) | def push_to_hf_hub( function load_local_files (line 174) | def load_local_files(path): function load_files_from_hf (line 224) | def load_files_from_hf(path): function generate_readme (line 271) | def generate_readme(model, repo_id: str): function save_hf (line 318) | def save_hf(model, save_directory, serialization: str): function save_ctfidf (line 331) | def save_ctfidf(model, save_directory: str, serialization: str): function save_ctfidf_config (line 360) | def save_ctfidf_config(model, path): function save_config (line 385) | def save_config(model, path: str, embedding_model): function check_has_visual_aspect (line 401) | def check_has_visual_aspect(model): function save_images (line 409) | def save_images(model, path: str): function save_topics (line 424) | def save_topics(model, path: str): function load_cfg_from_json (line 453) | def load_cfg_from_json(json_file: Union[str, os.PathLike]): class NumpyEncoder (line 460) | class NumpyEncoder(json.JSONEncoder): method default (line 461) | def default(self, obj): function get_package_versions (line 469) | def get_package_versions(): function load_safetensors (line 521) | def load_safetensors(path): function save_safetensors (line 531) | def save_safetensors(path, tensors): FILE: bertopic/_utils.py class MyLogger (line 10) | class MyLogger: method __init__ (line 11) | def __init__(self): method configure (line 14) | def configure(self, level): method info (line 19) | def info(self, message): method warning (line 22) | def warning(self, message): method set_level (line 25) | def set_level(self, level): method _add_handler (line 30) | def _add_handler(self): function check_documents_type (line 40) | def check_documents_type(documents): function check_embeddings_shape (line 51) | def check_embeddings_shape(embeddings, docs): function check_is_fitted (line 65) | def check_is_fitted(topic_model): class NotInstalled (line 83) | class NotInstalled: method __init__ (line 88) | def __init__(self, tool, dep, custom_msg=None): method __getattr__ (line 99) | def __getattr__(self, *args, **kwargs): method __call__ (line 102) | def __call__(self, *args, **kwargs): function validate_distance_matrix (line 106) | def validate_distance_matrix(X, n_samples): function get_unique_distances (line 155) | def get_unique_distances(dists: np.array, noise_max=1e-7) -> np.array: function select_topic_representation (line 179) | def select_topic_representation( class MockPlotlyModule (line 231) | class MockPlotlyModule: method __getattr__ (line 234) | def __getattr__(self, name: str) -> Any: FILE: bertopic/backend/_base.py class BaseEmbedder (line 5) | class BaseEmbedder: method __init__ (line 17) | def __init__(self, embedding_model=None, word_embedding_model=None): method embed (line 21) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... method embed_words (line 35) | def embed_words(self, words: List[str], verbose: bool = False) -> np.n... method embed_documents (line 50) | def embed_documents(self, document: List[str], verbose: bool = False) ... FILE: bertopic/backend/_cohere.py class CohereBackend (line 8) | class CohereBackend(BaseEmbedder): method __init__ (line 43) | def __init__( method embed (line 63) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... method _chunks (line 92) | def _chunks(self, documents): FILE: bertopic/backend/_fastembed.py class FastEmbedBackend (line 8) | class FastEmbedBackend(BaseEmbedder): method __init__ (line 27) | def __init__(self, embedding_model: str = "BAAI/bge-small-en-v1.5"): method embed (line 41) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_flair.py class FlairBackend (line 10) | class FlairBackend(BaseEmbedder): method __init__ (line 33) | def __init__(self, embedding_model: Union[TokenEmbeddings, DocumentEmb... method embed (line 55) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_gensim.py class GensimBackend (line 8) | class GensimBackend(BaseEmbedder): method __init__ (line 27) | def __init__(self, embedding_model: Word2VecKeyedVectors): method embed (line 39) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_hftransformers.py class HFTransformerBackend (line 12) | class HFTransformerBackend(BaseEmbedder): method __init__ (line 34) | def __init__(self, embedding_model: Pipeline): method embed (line 45) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... method _embed (line 69) | def _embed(self, document: str, features: np.ndarray) -> np.ndarray: class MyDataset (line 94) | class MyDataset(Dataset): method __init__ (line 97) | def __init__(self, docs): method __len__ (line 100) | def __len__(self): method __getitem__ (line 103) | def __getitem__(self, idx): FILE: bertopic/backend/_langchain.py class LangChainBackend (line 8) | class LangChainBackend(BaseEmbedder): method __init__ (line 25) | def __init__(self, embedding_model: Embeddings): method embed (line 28) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_model2vec.py class Model2VecBackend (line 9) | class Model2VecBackend(BaseEmbedder): method __init__ (line 54) | def __init__( method embed (line 90) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... method _check_model2vec_installation (line 125) | def _check_model2vec_installation(self): FILE: bertopic/backend/_multimodal.py class MultiModalBackend (line 10) | class MultiModalBackend(BaseEmbedder): method __init__ (line 45) | def __init__( method embed (line 87) | def embed(self, documents: List[str], images: List[str] | None = None,... method embed_documents (line 125) | def embed_documents(self, documents: List[str], verbose: bool = False)... method embed_words (line 141) | def embed_words(self, words: List[str], verbose: bool = False) -> np.n... method embed_images (line 156) | def embed_images(self, images, verbose): method _truncate_document (line 188) | def _truncate_document(self, document): FILE: bertopic/backend/_openai.py class OpenAIBackend (line 9) | class OpenAIBackend(BaseEmbedder): method __init__ (line 34) | def __init__( method embed (line 54) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... method _chunks (line 86) | def _chunks(self, documents): FILE: bertopic/backend/_sentencetransformers.py class SentenceTransformerBackend (line 9) | class SentenceTransformerBackend(BaseEmbedder): method __init__ (line 53) | def __init__(self, embedding_model: Union[str, SentenceTransformer], m... method embed (line 72) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_sklearn.py class SklearnEmbedder (line 5) | class SklearnEmbedder(BaseEmbedder): method __init__ (line 46) | def __init__(self, pipe): method embed (line 50) | def embed(self, documents, verbose=False): FILE: bertopic/backend/_spacy.py class SpacyBackend (line 7) | class SpacyBackend(BaseEmbedder): method __init__ (line 53) | def __init__(self, embedding_model): method embed (line 64) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_use.py class USEBackend (line 8) | class USEBackend(BaseEmbedder): method __init__ (line 27) | def __init__(self, embedding_model): method embed (line 40) | def embed(self, documents: List[str], verbose: bool = False) -> np.nda... FILE: bertopic/backend/_utils.py function select_backend (line 71) | def select_backend(embedding_model, language: str | None = None, verbose... FILE: bertopic/backend/_word_doc.py class WordDocEmbedder (line 7) | class WordDocEmbedder(BaseEmbedder): method __init__ (line 10) | def __init__(self, embedding_model, word_embedding_model): method embed_words (line 16) | def embed_words(self, words: List[str], verbose: bool = False) -> np.n... method embed_documents (line 31) | def embed_documents(self, document: List[str], verbose: bool = False) ... FILE: bertopic/cluster/_base.py class BaseCluster (line 4) | class BaseCluster: method fit (line 33) | def fit(self, X, y=None): method transform (line 40) | def transform(self, X: np.ndarray) -> np.ndarray: FILE: bertopic/cluster/_utils.py function hdbscan_delegator (line 4) | def hdbscan_delegator(model, func: str, embeddings: np.ndarray = None): function is_supported_hdbscan (line 67) | def is_supported_hdbscan(model): FILE: bertopic/dimensionality/_base.py class BaseDimensionalityReduction (line 4) | class BaseDimensionalityReduction: method fit (line 22) | def fit(self, X: np.ndarray = None, y: np.ndarray = None): method transform (line 25) | def transform(self, X: np.ndarray) -> np.ndarray: FILE: bertopic/plotting/_approximate_distribution.py function visualize_approximate_distribution (line 12) | def visualize_approximate_distribution( FILE: bertopic/plotting/_barchart.py function visualize_barchart (line 9) | def visualize_barchart( FILE: bertopic/plotting/_datamap.py class Figure (line 13) | class Figure(object): function visualize_document_datamap (line 17) | def visualize_document_datamap( FILE: bertopic/plotting/_distribution.py function visualize_distribution (line 6) | def visualize_distribution( FILE: bertopic/plotting/_documents.py function visualize_documents (line 8) | def visualize_documents( FILE: bertopic/plotting/_heatmap.py function visualize_heatmap (line 11) | def visualize_heatmap( FILE: bertopic/plotting/_hierarchical_documents.py function visualize_hierarchical_documents (line 9) | def visualize_hierarchical_documents( FILE: bertopic/plotting/_hierarchy.py function visualize_hierarchy (line 16) | def visualize_hierarchy( function _get_annotations (line 230) | def _get_annotations( FILE: bertopic/plotting/_term_rank.py function visualize_term_rank (line 6) | def visualize_term_rank( FILE: bertopic/plotting/_topics.py function visualize_topics (line 18) | def visualize_topics( function _plotly_topic_visualization (line 123) | def _plotly_topic_visualization(df: pd.DataFrame, topic_list: List[str],... FILE: bertopic/plotting/_topics_over_time.py function visualize_topics_over_time (line 7) | def visualize_topics_over_time( FILE: bertopic/plotting/_topics_per_class.py function visualize_topics_per_class (line 7) | def visualize_topics_per_class( FILE: bertopic/representation/_base.py class BaseRepresentation (line 7) | class BaseRepresentation(BaseEstimator): method extract_topics (line 10) | def extract_topics( FILE: bertopic/representation/_cohere.py class Cohere (line 41) | class Cohere(BaseRepresentation): method __init__ (line 111) | def __init__( method extract_topics (line 138) | def extract_topics( method _create_prompt (line 184) | def _create_prompt(self, docs, topic, topics): method _replace_documents (line 204) | def _replace_documents(prompt, docs): FILE: bertopic/representation/_keybert.py class KeyBERTInspired (line 12) | class KeyBERTInspired(BaseRepresentation): method __init__ (line 13) | def __init__( method extract_topics (line 68) | def extract_topics( method _extract_candidate_words (line 112) | def _extract_candidate_words( method _extract_embeddings (line 156) | def _extract_embeddings( method _extract_top_words (line 194) | def _extract_top_words( FILE: bertopic/representation/_langchain.py class LangChain (line 12) | class LangChain(BaseRepresentation): method __init__ (line 133) | def __init__( method extract_topics (line 153) | def extract_topics( FILE: bertopic/representation/_litellm.py class LiteLLM (line 20) | class LiteLLM(BaseRepresentation): method __init__ (line 79) | def __init__( method extract_topics (line 103) | def extract_topics( method _create_prompt (line 146) | def _create_prompt(self, docs, topic, topics): method _replace_documents (line 166) | def _replace_documents(prompt, docs): function chat_completions_with_backoff (line 174) | def chat_completions_with_backoff(**kwargs): FILE: bertopic/representation/_llamacpp.py class LlamaCPP (line 41) | class LlamaCPP(BaseRepresentation): method __init__ (line 115) | def __init__( method extract_topics (line 149) | def extract_topics( method _create_prompt (line 190) | def _create_prompt(self, docs, topic, topics): method _replace_documents (line 210) | def _replace_documents(prompt, docs): FILE: bertopic/representation/_mmr.py class MaximalMarginalRelevance (line 10) | class MaximalMarginalRelevance(BaseRepresentation): method __init__ (line 39) | def __init__(self, diversity: float = 0.1, top_n_words: int = 10): method extract_topics (line 43) | def extract_topics( function mmr (line 86) | def mmr( FILE: bertopic/representation/_openai.py class OpenAI (line 50) | class OpenAI(BaseRepresentation): method __init__ (line 133) | def __init__( method extract_topics (line 182) | def extract_topics( method _create_prompt (line 242) | def _create_prompt(self, docs, topic, topics): method _replace_documents (line 262) | def _replace_documents(prompt, docs): function chat_completions_with_backoff (line 270) | def chat_completions_with_backoff(client, **kwargs): FILE: bertopic/representation/_pos.py class PartOfSpeech (line 15) | class PartOfSpeech(BaseRepresentation): method __init__ (line 66) | def __init__( method extract_topics (line 94) | def extract_topics( FILE: bertopic/representation/_textgeneration.py class TextGeneration (line 17) | class TextGeneration(BaseRepresentation): method __init__ (line 85) | def __init__( method extract_topics (line 119) | def extract_topics( method _create_prompt (line 169) | def _create_prompt(self, docs, topic, topics): FILE: bertopic/representation/_utils.py function truncate_document (line 6) | def truncate_document(topic_model, doc_length: Union[int, None], tokeniz... function validate_truncate_document_parameters (line 62) | def validate_truncate_document_parameters(tokenizer, doc_length) -> Unio... function retry_with_exponential_backoff (line 74) | def retry_with_exponential_backoff( FILE: bertopic/representation/_visual.py class VisualRepresentation (line 14) | class VisualRepresentation(BaseRepresentation): method __init__ (line 48) | def __init__( method extract_topics (line 76) | def extract_topics( method _convert_image_to_text (line 131) | def _convert_image_to_text(self, images: List[str], verbose: bool = Fa... method image_to_text (line 156) | def image_to_text(self, documents: pd.DataFrame, embeddings: np.ndarra... method _chunks (line 204) | def _chunks(self, images): function get_concat_h_multi_resize (line 209) | def get_concat_h_multi_resize(im_list): function get_concat_v_multi_resize (line 227) | def get_concat_v_multi_resize(im_list): function get_concat_tile_resize (line 241) | def get_concat_tile_resize(im_list_2d, image_height=600, image_squares=F... FILE: bertopic/representation/_zeroshot.py class ZeroShotClassification (line 9) | class ZeroShotClassification(BaseRepresentation): method __init__ (line 38) | def __init__( method extract_topics (line 59) | def extract_topics( FILE: bertopic/vectorizers/_ctfidf.py class ClassTfidfTransformer (line 9) | class ClassTfidfTransformer(TfidfTransformer): method __init__ (line 41) | def __init__( method fit (line 54) | def fit(self, X: sp.csr_matrix, multiplier: np.ndarray = None): method transform (line 98) | def transform(self, X: sp.csr_matrix): FILE: bertopic/vectorizers/_online_cv.py class OnlineCountVectorizer (line 11) | class OnlineCountVectorizer(CountVectorizer): method __init__ (line 71) | def __init__(self, decay: float | None = None, delete_min_df: float | ... method partial_fit (line 76) | def partial_fit(self, raw_documents: List[str]) -> None: method update_bow (line 102) | def update_bow(self, raw_documents: List[str]) -> csr_matrix: method _clean_bow (line 144) | def _clean_bow(self) -> None: FILE: tests/conftest.py function embedding_model (line 17) | def embedding_model(): function document_embeddings (line 23) | def document_embeddings(documents, embedding_model): function reduced_embeddings (line 29) | def reduced_embeddings(document_embeddings): function documents (line 37) | def documents(): function targets (line 43) | def targets(): function base_topic_model (line 50) | def base_topic_model(documents, document_embeddings, embedding_model): function zeroshot_topic_model (line 59) | def zeroshot_topic_model(documents, document_embeddings, embedding_model): function custom_topic_model (line 74) | def custom_topic_model(documents, document_embeddings, embedding_model): function representation_topic_model (line 92) | def representation_topic_model(documents, document_embeddings, embedding... function reduced_topic_model (line 115) | def reduced_topic_model(custom_topic_model, documents): function merged_topic_model (line 122) | def merged_topic_model(custom_topic_model, documents): function kmeans_pca_topic_model (line 136) | def kmeans_pca_topic_model(documents, document_embeddings): function supervised_topic_model (line 148) | def supervised_topic_model(documents, document_embeddings, embedding_mod... function online_topic_model (line 161) | def online_topic_model(documents, document_embeddings, embedding_model): function cuml_base_topic_model (line 181) | def cuml_base_topic_model(documents, document_embeddings, embedding_model): FILE: tests/test_bertopic.py function cuml_available (line 7) | def cuml_available(): function test_full_model (line 32) | def test_full_model(model, documents, request): FILE: tests/test_other.py function test_load_save_model (line 10) | def test_load_save_model(): function test_get_params (line 20) | def test_get_params(): function test_no_plotly (line 31) | def test_no_plotly(): FILE: tests/test_plotting/test_approximate.py function test_approximate_distribution (line 17) | def test_approximate_distribution(batch_size, padding, model, documents,... FILE: tests/test_plotting/test_bar.py function test_barchart (line 16) | def test_barchart(model, request): function test_barchart_outlier (line 42) | def test_barchart_outlier(model, request): FILE: tests/test_plotting/test_documents.py function test_documents (line 15) | def test_documents(model, reduced_embeddings, documents, request): FILE: tests/test_plotting/test_dynamic.py function test_dynamic (line 16) | def test_dynamic(model, documents, request): FILE: tests/test_plotting/test_heatmap.py function test_heatmap (line 15) | def test_heatmap(model, request): FILE: tests/test_plotting/test_term_rank.py function test_term_rank (line 6) | def test_term_rank(model, request): FILE: tests/test_plotting/test_topics.py function test_topics (line 16) | def test_topics(model, request): function test_topics_outlier (line 40) | def test_topics_outlier(model, request): FILE: tests/test_reduction/test_delete.py function test_delete (line 16) | def test_delete(model, request): FILE: tests/test_reduction/test_merge.py function test_merge (line 16) | def test_merge(model, documents, request): FILE: tests/test_representation/test_get.py function test_get_topic (line 18) | def test_get_topic(model, request): function test_get_topics (line 41) | def test_get_topics(model, request): function test_get_topic_freq (line 60) | def test_get_topic_freq(model, request): function test_get_representative_docs (line 85) | def test_get_representative_docs(model, request): function test_get_topic_info (line 114) | def test_get_topic_info(model, request): FILE: tests/test_representation/test_labels.py function test_generate_topic_labels (line 16) | def test_generate_topic_labels(model, request): function test_set_labels (line 40) | def test_set_labels(model, request): FILE: tests/test_representation/test_representations.py function test_update_topics (line 18) | def test_update_topics(model, documents, request): function test_extract_topics (line 51) | def test_extract_topics(model, documents, request): function test_extract_topics_custom_cv (line 84) | def test_extract_topics_custom_cv(model, documents, request): function test_topic_reduction (line 121) | def test_topic_reduction(model, reduced_topics, documents, request): function test_topic_reduction_edge_cases (line 149) | def test_topic_reduction_edge_cases(model, documents, request): function test_find_topics (line 179) | def test_find_topics(model, request): FILE: tests/test_sub_models/test_cluster.py function test_hdbscan_cluster_embeddings (line 23) | def test_hdbscan_cluster_embeddings(cluster_model, samples, features, ce... function test_custom_hdbscan_cluster_embeddings (line 58) | def test_custom_hdbscan_cluster_embeddings(cluster_model, samples, featu... FILE: tests/test_sub_models/test_dim_reduction.py function test_reduce_dimensionality (line 19) | def test_reduce_dimensionality(dim_model, embeddings, shape, n_components): function test_custom_reduce_dimensionality (line 36) | def test_custom_reduce_dimensionality(model, request): FILE: tests/test_sub_models/test_embeddings.py function test_extract_embeddings (line 19) | def test_extract_embeddings(model, request): function test_extract_embeddings_compare (line 50) | def test_extract_embeddings_compare(model, embedding_model, request): function test_extract_incorrect_embeddings (line 62) | def test_extract_incorrect_embeddings(): FILE: tests/test_utils.py function test_logger (line 15) | def test_logger(): function test_check_documents_type (line 31) | def test_check_documents_type(docs): function test_check_embeddings_shape (line 36) | def test_check_embeddings_shape(): function test_make_unique_distances (line 42) | def test_make_unique_distances(): function test_select_topic_representation (line 57) | def test_select_topic_representation(): FILE: tests/test_variations/test_class.py function test_class (line 19) | def test_class(model, documents, request): FILE: tests/test_variations/test_dynamic.py function test_dynamic (line 15) | def test_dynamic(model, documents, request): FILE: tests/test_variations/test_hierarchy.py function test_hierarchy (line 16) | def test_hierarchy(model, documents, request): function test_linkage (line 36) | def test_linkage(model, documents, request): function test_tree (line 59) | def test_tree(model, documents, request): FILE: tests/test_vectorizers/test_ctfidf.py function test_ctfidf (line 23) | def test_ctfidf(model, documents, request): function test_ctfidf_custom_cv (line 68) | def test_ctfidf_custom_cv(model, documents, request): FILE: tests/test_vectorizers/test_online_cv.py function test_online_cv (line 16) | def test_online_cv(model, documents, request): function test_clean_bow (line 30) | def test_clean_bow(model, request):