Repository: csmailis/NPYViewer
Branch: master
Commit: 7345ca418bd1
Files: 16
Total size: 19.9 KB

Directory structure:
gitextract_h7azvspx/

├── LICENSE.md
├── NPYViewer.py
├── README.md
├── code_for_generating_npy_samples/
│   ├── .gitkeep
│   ├── 3dSpiral_Example.py
│   ├── gaussian_example.py
│   ├── graph.py
│   └── heightmap_example.py
├── requirements.txt
├── sample_npy_files/
│   ├── .gitkeep
│   ├── 3DSpiral.npy
│   ├── gaussian.npy
│   ├── graph.npy
│   ├── heightmap.npy
│   └── timeseries.npy
└── screenshots/
    └── .gitkeep

================================================
FILE CONTENTS
================================================

================================================
FILE: LICENSE.md
================================================
MIT License

Copyright (c) 2023 csmailis

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files ("NPYViewer"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


================================================
FILE: NPYViewer.py
================================================
#!/usr/bin/env python3
import os.path
import sys
from PyQt5.QtWidgets import *
from PyQt5.QtGui import QIcon
from PyQt5.QtCore import *
from pathlib import Path
import numpy as np
from numpy import asarray
from numpy import savetxt
import pandas as pd
import csv
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import os
from scipy.io import savemat
import networkx as nx


version="1.28"

def isint(s):
    try:
        print(int(s))
        return True
    except ValueError:
        return False


def isfloat(s):
    try:
        print(float(s))
        return True
    except ValueError:
        return False



def openNPY_CLI_noGUI (filename):

        if ".npy" in filename:
            data = np.load(filename, allow_pickle=True)
        else:
            data = np.array(pd.read_csv(filename).values.tolist())

        npyfile = NPYfile(data, filename)
        print(npyfile)
        print(data)


class NPYfile():
    def __init__(self, data, filename):
        self.data = data
        self.filename = filename

    def __str__(self):
        if hasattr(self.data, 'dtype'):
            return "Filename = " + str(self.filename) + " \nDtype = " + str(self.data.dtype) + "\nShape = " + str(
                self.data.shape)
        else:
            return "Filename = " + str(self.filename) + " \nDtype = " + "\nShape = " + str(self.data.shape)



            
class MainApp(QMainWindow):

    def __init__(self):
        super().__init__()
        self.left = 0
        self.top = 0
        self.width = 800
        self.height = 640
        # np.save('/home/user/tst.npy', np.array([255.0,50.0,10.0,5.0]))
        self.npyfile = None
        self.initUI()

    def saveAs(self):
        home = str(Path.home())
        if self.npyfile is not None:
            home = os.path.dirname(self.npyfile.filename)
        path = QFileDialog.getSaveFileName(
            self, 'Save File', home, 'NPY (*.npy);;CSV(*.csv);;MAT(*.mat)')[0]
        # path = QFileDialog.getSaveFileName(
        #    self, 'Save File', home, 'CSV(*.csv)')[0]
        if path != "" and ".csv" in path:
            with open((path.replace(".csv", "") + ".csv"), 'w') as stream:
                writer = csv.writer(stream)
                for row in range(self.tableWidget.rowCount()):
                    rowdata = []
                    for column in range(self.tableWidget.columnCount()):
                        item = self.tableWidget.item(row, column)
                        if item is not None:
                            rowdata.append(item.text())

                        else:
                            rowdata.append('')
                    writer.writerow(rowdata)
        else:
            OutMatrix = []
            for row in range(self.tableWidget.rowCount()):
                rowdata = []
                for column in range(self.tableWidget.columnCount()):
                    item = self.tableWidget.item(row, column)
                    if item is not None:
                        #if item.text().isnumeric():
                        rowdata.append(float(item.text()))

                if rowdata != []:
                    OutMatrix.append(rowdata)
            OutMatrix = np.array(OutMatrix)
            if ".csv" in path:
                np.save(path, np.array(OutMatrix))
            if ".mat" in path:
                mdic = {"ans": OutMatrix}
                print(OutMatrix)
                savemat(path, mdic)

    def openNPY(self):
        if os.path.exists("lastpath.npy"):
            home = str(np.load("lastpath.npy"))
            print(home)
        else:
            home = str(Path.home())
        if self.npyfile is not None:
            home = os.path.dirname(self.npyfile.filename)
        filename = QFileDialog.getOpenFileName(self, 'Open .NPY file', home, ".NPY files (*.npy);;.CSV files (*.csv)")[
            0]
        if filename != "":
            if ".npy" in filename:
                data = np.load(filename, allow_pickle=True)
            else:
                data = np.array(pd.read_csv(filename).values.tolist())

            npyfile = NPYfile(data, filename)
            print(npyfile)
            self.setWindowTitle("NPYViewer v." +version+": "+ npyfile.filename)
            self.infoLb.setText("NPY Properties:\n" + str(npyfile))
            self.tableWidget.clear()

            # initialise table
            self.tableWidget.setRowCount(data.shape[0])
            dtype_dim = len(npyfile.data.dtype)  # 0, if plain dtype, 1 or bigger if compound dtype
            if data.ndim > 1:
                self.tableWidget.setColumnCount(data.shape[1])
            elif dtype_dim > 0:
                self.tableWidget.setColumnCount(dtype_dim)
            else:
                self.tableWidget.setColumnCount(1)

            # fill data
            if data.ndim > 1:
                for i, value1 in enumerate(npyfile.data):  # loop over items in first column
                    for j, value in enumerate(value1):
                        self.tableWidget.setItem(i, j, QTableWidgetItem(str(value)))
            elif dtype_dim > 0:
                for i, value1 in enumerate(npyfile.data):
                    for j, col_name in enumerate(npyfile.data.dtype.names):
                        self.tableWidget.setItem(i, j, QTableWidgetItem(str(value1[col_name])))
            else:
                for i, value1 in enumerate(npyfile.data):  # loop over items in first column
                    self.tableWidget.setItem(i, 0, QTableWidgetItem(str(value1)))

            self.npyfile = npyfile
            path = os.path.dirname(filename)
            np.save("lastpath.npy", path)


    def openNPY_CLI(self,filename):

            if ".npy" in filename:
                data = np.load(filename, allow_pickle=True)
            else:
                data = np.array(pd.read_csv(filename).values.tolist())

            npyfile = NPYfile(data, filename)
            print(npyfile)
            self.setWindowTitle("NPYViewer v." +version+": " +npyfile.filename)
            self.infoLb.setText("NPY Properties:\n" + str(npyfile))
            self.tableWidget.clear()

            # initialise table
            self.tableWidget.setRowCount(data.shape[0])
            dtype_dim = len(npyfile.data.dtype)  # 0, if plain dtype, 1 or bigger if compound dtype
            if data.ndim > 1:
                self.tableWidget.setColumnCount(data.shape[1])
            elif dtype_dim > 0:
                self.tableWidget.setColumnCount(dtype_dim)
            else:
                self.tableWidget.setColumnCount(1)

            # fill data
            if data.ndim > 1:
                for i, value1 in enumerate(npyfile.data):  # loop over items in first column
                    for j, value in enumerate(value1):
                        self.tableWidget.setItem(i, j, QTableWidgetItem(str(value)))
            elif dtype_dim > 0:
                for i, value1 in enumerate(npyfile.data):
                    for j, col_name in enumerate(npyfile.data.dtype.names):
                        self.tableWidget.setItem(i, j, QTableWidgetItem(str(value1[col_name])))
            else:
                for i, value1 in enumerate(npyfile.data):  # loop over items in first column
                    self.tableWidget.setItem(i, 0, QTableWidgetItem(str(value1)))

            self.npyfile = npyfile
            path = os.path.dirname(filename)
            np.save("lastpath.npy", path)


            
    def createMenu(self):

        exitAct = QAction(QIcon('exit.png'), '&Exit', self)
        exitAct.setShortcut('Ctrl+Q')
        exitAct.setStatusTip('Exit application')
        exitAct.triggered.connect(qApp.quit)

        openAct = QAction(QIcon('Open.png'), '&Open', self)
        openAct.setShortcut('Ctrl+O')
        openAct.setStatusTip('Open .NPY file')
        openAct.triggered.connect(self.openNPY)
        self.statusBar()

        saveAct = QAction(QIcon('Save.png'), '&Save As', self)
        saveAct.setShortcut('Ctrl+S')
        saveAct.setStatusTip('Save As')
        saveAct.triggered.connect(self.saveAs)
        self.statusBar()

        grayscalevVewAct = QAction(QIcon(None), '&View as Grayscale Image', self)
        grayscalevVewAct.setShortcut('Ctrl+V')
        grayscalevVewAct.setStatusTip('View as Grayscale')
        grayscalevVewAct.triggered.connect(self.grayscaleView)
        self.statusBar()

        View3dAct = QAction(QIcon(None), 'View &3D Point Cloud', self)
        View3dAct.setShortcut('Ctrl+3')
        View3dAct.setStatusTip('View 3D Point Cloud')
        View3dAct.triggered.connect(self.View3dPoints)
        self.statusBar()

        View3dImgAct = QAction(QIcon(None), 'View as &HeightMap', self)
        View3dImgAct.setShortcut('Ctrl+H')
        View3dImgAct.setStatusTip('View as HeightMap')
        View3dImgAct.triggered.connect(self.ViewImageHeightMap)
        self.statusBar()

        ViewTimeSeriesAct= QAction(QIcon(None), 'View as &Time Series', self)
        ViewTimeSeriesAct.setShortcut('Ctrl+S')
        ViewTimeSeriesAct.setStatusTip('View as TimeSeries')
        ViewTimeSeriesAct.triggered.connect(self.ViewTimeseries)
        self.statusBar()

        ViewGraphSeriesAct= QAction(QIcon(None), 'View as Directional &Graph', self)
        ViewGraphSeriesAct.setShortcut('Ctrl+G')
        ViewGraphSeriesAct.setStatusTip('View as Graph')
        ViewGraphSeriesAct.triggered.connect(self.ViewGraphSeriesAct)
        self.statusBar()
        
        menubar = self.menuBar()
        fileMenu = menubar.addMenu('&Functionalities')
        fileMenu.addAction(openAct)
        fileMenu.addAction(saveAct)
        fileMenu.addAction(grayscalevVewAct)
        fileMenu.addAction(View3dAct)
        fileMenu.addAction(View3dImgAct)
        fileMenu.addAction(ViewTimeSeriesAct)
        fileMenu.addAction(ViewGraphSeriesAct)
        fileMenu.addAction(exitAct)

    def grayscaleView(self):
        OutMatrix = []
        for row in range(self.tableWidget.rowCount()):
            rowdata = []
            for column in range(self.tableWidget.columnCount()):
                item = self.tableWidget.item(row, column)
                # print(item.text())
                if item is not None:
                    rowdata.append(np.float32(item.text()))

            if len(rowdata) > 0 and rowdata != None:
                OutMatrix.append(rowdata)

        OutMatrix = np.array(OutMatrix)
        plt.imshow(OutMatrix, cmap='gray')
        plt.show()
        return

    def ViewGraphSeriesAct(self):
        OutMatrix = []
        for row in range(self.tableWidget.rowCount()):
            rowdata = []
            for column in range(self.tableWidget.columnCount()):
                item = self.tableWidget.item(row, column)
                # print(item.text())
                if item is not None:
                    rowdata.append(np.float32(item.text()))

            if len(rowdata) > 0 and rowdata != None:
                OutMatrix.append(rowdata)

        OutMatrix = np.array(OutMatrix)


        G = nx.DiGraph(OutMatrix)

        # Set the position of the nodes in the graph
        pos = nx.spring_layout(G)

        # Draw the graph with labels and edges
        labels = {node: str(int(node)+1) for node in G.nodes()}

        nx.draw_networkx_labels(G, pos,labels=labels)
        nx.draw_networkx_edges(G, pos)

        nx.draw_networkx_edge_labels(G, pos, edge_labels={(i, j): OutMatrix[i][j] for i, j in G.edges()})

        # Draw the nodes with the same color
        nx.draw_networkx_nodes(G, pos, node_color='b')


        # Set the title and show the plot
        plt.title("Directional Graph")
        plt.show()

    def ViewImageHeightMap(self):
        OutMatrix = []
        for row in range(self.tableWidget.rowCount()):
            rowdata = []
            for column in range(self.tableWidget.columnCount()):
                item = self.tableWidget.item(row, column)

                if item is not None:
                    if item.text():
                        rowdata.append(np.float32(item.text()))
            if len(rowdata) > 0 and rowdata != None:
                OutMatrix.append(rowdata)
        # print(OutMatrix)
        HeightMap = []
        for x, row in enumerate(OutMatrix):
            for y, val in enumerate(row):
                HeightMap.append([x, y, val])
        OutMatrix = np.array(HeightMap)

        fig = plt.figure()
        ax = fig.add_subplot(111, projection='3d')

        xs = OutMatrix[:, 0]

        ys = OutMatrix[:, 1]
        zs = OutMatrix[:, 2]
        ax.plot_trisurf(xs, ys, zs,
                        cmap='Greys_r', edgecolor='none');

        ax.set_xlabel('X Axis')
        ax.set_ylabel('Y Axis')
        ax.set_zlabel('Z Axis')

        plt.show()
        return

    def View3dPoints(self):
        OutMatrix = []
        for row in range(self.tableWidget.rowCount()):
            rowdata = []
            for column in range(self.tableWidget.columnCount()):
                item = self.tableWidget.item(row, column)

                if item is not None:
                    if item.text():
                        rowdata.append(np.float32(item.text()))
            if len(rowdata) > 0 and rowdata != None:
                OutMatrix.append(rowdata)
        # print(OutMatrix)
        OutMatrix = np.array(OutMatrix)

        fig = plt.figure()
        ax = fig.add_subplot(111, projection='3d')

        xs = OutMatrix[:, 0]

        ys = OutMatrix[:, 1]
        zs = OutMatrix[:, 2]
        ax.scatter(xs, ys, zs, c='r', marker='o')

        ax.set_xlabel('X Axis')
        ax.set_ylabel('Y Axis')
        ax.set_zlabel('Z Axis')

        plt.show()
        return
    
    def ViewTimeseries(self):
        OutMatrix = []
        for row in range(self.tableWidget.rowCount()):
            rowdata = []
            for column in range(self.tableWidget.columnCount()):
                item = self.tableWidget.item(row, column)

                if item is not None:
                    if item.text():
                        rowdata.append(np.float32(item.text()))
            if len(rowdata) > 0 and rowdata != None:
                OutMatrix.append(rowdata)
        # print(OutMatrix)
        #OutMatrix = np.array(OutMatrix)

        fig = plt.figure()
        ax = fig.add_subplot(111)
        indices=range(0,len(OutMatrix))
        plt.plot(indices, OutMatrix, label='values', linewidth=3)

        ax.set_xlabel('Time Unit')
        ax.set_ylabel('Values')

        plt.show()
        return

    
    def initUI(self):
        self.createMenu()

        self.infoLb = QLabel("NPY Properties:")
        self.tableWidget = QTableWidget()
        self.tableWidget.setRowCount(100)
        self.tableWidget.setColumnCount(100)

        # table selection change
        # self.tableWidget.doubleClicked.connect(self.on_click)

        self.setGeometry(0, 0, 800, 600)
        self.setWindowTitle("NPYViewer v."+version)

        self.widget = QWidget(self)
        layout = QGridLayout()
        layout.addWidget(self.infoLb)
        layout.addWidget(self.tableWidget)
        self.widget.setLayout(layout)
        self.setCentralWidget(self.widget)
        # self.tableWidget.setItesetTextAlignmentmDelegate(AlignDelegate())

        self.layout = QVBoxLayout()

        self.setLayout(self.layout)
        self.setWindowIcon(QIcon('npyviewer_128x128.png'))

        self.show()


def main():
    if "-noGUI" not in sys.argv:
        app = QApplication(sys.argv)
        ex = MainApp()
        if len(sys.argv) ==2:
            ex.openNPY_CLI(sys.argv[1])
        sys.exit(app.exec_())
    if len(sys.argv) ==3:
        if sys.argv[2]=="-noGUI":
            print("GUI not displayed")
            openNPY_CLI_noGUI(sys.argv[1])



if __name__ == '__main__':
    main()


================================================
FILE: README.md
================================================

<p align="center">
  <img src="npyviewer_128x128.png" alt="screenshot">
</p>

# NPYViewer 1.28
###  A simple GUI tool that provides multiple ways to load and view the contents of .npy files containing 2D and 1D NumPy arrays.

#### Plot 3-column 2D numpy arrays containing 3D coordinates as 3D point clouds
![screenshot](screenshots/ScreenShot1.png)
#### Plot 2D numpy arrays as grayscale images
![screenshot](screenshots/ScreenShot2.png)
#### Visualize heightmaps stored as 2D numpy arrays
![screenshot](screenshots/ScreenShot3.png) 
![screenshot](screenshots/ScreenShot4.png)
#### Visualize time series data stored as 1D numpy arrays
![screenshot](screenshots/ScreenShot5.png)
#### Visualize adjacency matrices (saved in .npy arrays) as directional edge weighted graphs
![screenshot](screenshots/ScreenShot7.png)
#### Print numpy arrays in terminal
![screenshot](screenshots/ScreenShot6.png)


### Installation:
* Original development in Ubuntu 20.04 and Python 3.8.8
* Also tested on Windows 10 and Ubuntu 22.04
* pip3 install -r requirements.txt


### Execution:
* python3 NPYViewer.py


### Current Features:
* Open and view .npy files that contain 2D NumPy arrays and lists, as spreadsheets
* Convert .npy files to .csv format
* Convert .csv files to .npy format
* Export .npy files as .mat files (compatible with MATLAB and Octave)
* Plot 2D numpy arrays as grayscale images
* Plot 2D numpy arrays containing 3D coordinates as 3D point clouds
* Visualize heightmaps stored as 2D numpy arrays
* Visualize time series data stored as 1D numpy arrays
* Supports loading .npy files as command line arguments (e.g., python3 NPYViewer.py sample_npy_files/timeseries.npy)
* Visualize adjacency matrices (saved in .npy arrays) as directional edge weighted graphs
* Print numpy arrays in terminal through the use of the -noGUI argument (e.g., python NPYViewer.py sample_npy_files/timeseries.npy -noGUI)
* GUI developed using PyQT5


### TODO:
* Add/Remove Rows & Columns
* Copy/Paste Rows & Columns
* Data search and filtering
* Modify content datatypes 
* Handle data with more than 2 dimensions



### Changes since last version:
* Added application icon
* Fixed Bug: "View as Time Series" option was hidden in the "Functionalities" menu

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details.



================================================
FILE: code_for_generating_npy_samples/.gitkeep
================================================



================================================
FILE: code_for_generating_npy_samples/3dSpiral_Example.py
================================================

import numpy as np
import matplotlib.pyplot as plt



ax = plt.axes(projection='3d')

# Data for a three-dimensional line
zline = np.linspace(0, 64, 64)
xline = np.sin(zline)
yline = np.cos(zline)

# Data for three-dimensional scattered points
zdata = 15 * np.random.random(100)
xdata = np.sin(zdata) + 0.1 * np.random.randn(100)
ydata = np.cos(zdata) + 0.1 * np.random.randn(100)
temp=np.array([xdata,ydata,zdata])
temp=temp.T
print(np.shape(temp))
np.save("3DSpiral.npy",temp)
ax.scatter3D(xdata,ydata,zdata, c='r');



================================================
FILE: code_for_generating_npy_samples/gaussian_example.py
================================================

import numpy as np
import matplotlib.pyplot as plt
size = 24
sigma_x = 10.
sigma_y = 10.

x = np.linspace(-10, 10, size)
y = np.linspace(-10, 10, size)

x, y = np.meshgrid(x, y)
z = (1/(2*np.pi*sigma_x*sigma_y) * np.exp(-(x**2/(2*sigma_x**2)
     + y**2/(2*sigma_y**2))))
z *= (255.0/z.max()).astype(int)
np.save("gaussian.npy",z)
plt.imshow(z, cmap='gray')
plt.show()




================================================
FILE: code_for_generating_npy_samples/graph.py
================================================
import numpy as np

# Create a random numpy array
arr = np.random.randint(low=0, high=2, size=(5, 5))

# Save the numpy array to an .npy file
np.save("graph.npy", arr)


================================================
FILE: code_for_generating_npy_samples/heightmap_example.py
================================================

from PIL import Image
import numpy as np
heightmap = Image.open("Heightmap.png")

np.save("heightmap.npy",heightmap)


================================================
FILE: requirements.txt
================================================
PyQt5==5.12.3
numpy
pandas
matplotlib
scipy
networkx


================================================
FILE: sample_npy_files/.gitkeep
================================================



================================================
FILE: screenshots/.gitkeep
================================================