python - Can a PyQt Embedded MatPlotLib Graph Be Interactive?

Python - Can a PyQt Embedded MatPlotLib Graph Be Interactive?

Yes, it's possible to create an interactive Matplotlib graph embedded within a PyQt application. You can achieve this by embedding a Matplotlib figure canvas within a PyQt GUI application using Matplotlib's FigureCanvasQTAgg backend.

Here's a simple example demonstrating how to create an interactive Matplotlib graph embedded within a PyQt application:

import sys import numpy as np import matplotlib.pyplot as plt from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget, QPushButton class MainWindow(QMainWindow): def __init__(self): super().__init__() self.setWindowTitle('Interactive Matplotlib in PyQt') self.setGeometry(100, 100, 800, 600) # Create a button to update the plot self.button = QPushButton('Update Plot') self.button.clicked.connect(self.update_plot) # Create a layout for the main window layout = QVBoxLayout() layout.addWidget(self.button) # Create a Matplotlib figure and canvas self.figure, self.ax = plt.subplots() self.canvas = FigureCanvas(self.figure) layout.addWidget(self.canvas) # Create a central widget to hold the layout central_widget = QWidget() central_widget.setLayout(layout) self.setCentralWidget(central_widget) # Plot initial data self.x = np.linspace(0, 10, 100) self.y = np.sin(self.x) self.ax.plot(self.x, self.y) self.canvas.draw() def update_plot(self): # Update the plot with new data self.y = np.sin(self.x + np.random.rand()) self.ax.clear() self.ax.plot(self.x, self.y) self.canvas.draw() if __name__ == '__main__': app = QApplication(sys.argv) window = MainWindow() window.show() sys.exit(app.exec_())

In this example:

  • We create a QMainWindow as the main window of the application.
  • Inside the main window, we create a button (QPushButton) to update the plot.
  • We create a Matplotlib figure and canvas using FigureCanvasQTAgg.
  • The Matplotlib plot is embedded within the PyQt application's GUI layout.
  • Initially, a sinusoidal plot is displayed.
  • When the "Update Plot" button is clicked, the plot is updated with new random data.

This example demonstrates how to create a simple interactive Matplotlib graph embedded within a PyQt application. You can further customize the plot and add additional interactive features as needed.

Examples

  1. Create Interactive Matplotlib Plot in PyQt: Description: Explore how to embed a Matplotlib plot in a PyQt application and make it interactive using mpl_connect.

    import sys from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.plot(np.random.rand(10)) self.canvas.mpl_connect('button_press_event', self.on_click) def on_click(self, event): print('You clicked on point:', event.xdata, event.ydata) app = QApplication(sys.argv) mainWindow = MainWindow() mainWindow.show() sys.exit(app.exec_())

  2. Matplotlib PyQt Graph with Interactive Zoom: Description: Implement a PyQt application with a Matplotlib plot that supports interactive zooming.

    from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.plot(np.random.rand(10)) self.toolbar = NavigationToolbar(self.canvas, self) self.addToolBar(self.toolbar) app = QApplication([]) mainWindow = MainWindow() mainWindow.show() app.exec_()

  3. PyQt Matplotlib Interactive Scatter Plot: Description: Build a PyQt application with a Matplotlib scatter plot that responds to mouse clicks.

    from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.scatter(np.random.rand(10), np.random.rand(10)) self.canvas.mpl_connect('button_press_event', self.on_click) def on_click(self, event): print('You clicked on point:', event.xdata, event.ydata) app = QApplication([]) mainWindow = MainWindow() mainWindow.show() app.exec_()

  4. Interactive Matplotlib Plot in PyQt5 Application: Description: Develop a PyQt5 application with an embedded Matplotlib plot that allows interactive panning and zooming.

    import sys from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.plot(np.random.rand(10)) app = QApplication(sys.argv) mainWindow = MainWindow() mainWindow.show() sys.exit(app.exec_())

  5. Embed Interactive Matplotlib Plot in PyQt Application: Description: Embed an interactive Matplotlib plot in a PyQt application by connecting mouse events to Python functions.

    from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.plot(np.random.rand(10)) self.canvas.mpl_connect('button_press_event', self.on_click) def on_click(self, event): print('You clicked on point:', event.xdata, event.ydata) app = QApplication([]) mainWindow = MainWindow() mainWindow.show() app.exec_()

  6. PyQt5 Interactive Matplotlib Graph with Pan and Zoom: Description: Create a PyQt5 application with an embedded Matplotlib plot that supports panning and zooming.

    import sys from PyQt5.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas from matplotlib.figure import Figure from matplotlib.backends.backend_qt5 import NavigationToolbar2QT as NavigationToolbar import numpy as np class MainWindow(QMainWindow): def __init__(self): super().__init__() self.figure = Figure() self.canvas = FigureCanvas(self.figure) layout = QVBoxLayout() layout.addWidget(self.canvas) widget = QWidget() widget.setLayout(layout) self.setCentralWidget(widget) self.ax = self.figure.add_subplot(111) self.ax.plot(np.random.rand(10)) self.toolbar = NavigationToolbar(self.canvas, self) self.addToolBar(self.toolbar) app = QApplication(sys.argv) mainWindow = MainWindow() mainWindow.show() sys.exit(app.exec_())

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