
Embedding matplotlib Graphs in PyQt Interfaces
Enhancing PyQt4 user interfaces with graphical visualizations is a common requirement. matplotlib, a popular Python library for creating static and interactive graphs, offers a seamless integration with PyQt4.
To embed matplotlib graphs in PyQt4 GUIs, several approaches can be employed. Let's explore a step-by-step guide to create a basic example with a graph and a button.
Step 1: Import Required Modules
<code class="python">import sys from PyQt4 import QtGui from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg, NavigationToolbar2QT from matplotlib.figure import Figure</code>
Step 2: Define the Window Class
Create a PyQt4 window that will host the graph and buttons.
<code class="python">class Window(QtGui.QDialog):
def __init__(self, parent=None):
super(Window, self).__init__(parent)
# Create a Figure instance for plotting
self.figure = Figure()
# Create a FigureCanvasQTAgg object to display the figure
self.canvas = FigureCanvasQTAgg(self.figure)
# Add a NavigationToolbar2QT widget for interactive navigation
self.toolbar = NavigationToolbar2QT(self.canvas, self)
# Create a Plot button
self.button = QtGui.QPushButton('Plot')
self.button.clicked.connect(self.plot)
# Set the layout
layout = QtGui.QVBoxLayout()
layout.addWidget(self.toolbar)
layout.addWidget(self.canvas)
layout.addWidget(self.button)
self.setLayout(layout)</code>Step 3: Define the Plot Function
The Plot function generates random data and plots it on the graph.
<code class="python"> def plot(self):
# Generate random data
data = [random.random() for i in range(10)]
# Create an axis on the figure
ax = self.figure.add_subplot(111)
# Clear the existing plot
ax.clear()
# Plot the data
ax.plot(data, '*-')
# Update the canvas
self.canvas.draw()</code>Step 4: Main Application
Instantiate the Window class and launch the application.
<code class="python">if __name__ == '__main__':
app = QtGui.QApplication(sys.argv)
main = Window()
main.show()
sys.exit(app.exec_())</code>This script provides a simple yet effective example of embedding matplotlib graphs in PyQt4 user interfaces. By leveraging these powerful libraries, developers can enhance their applications with interactive visualizations.
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