How to Plot in a Non-Blocking Way with Matplotlib: Why Does `show(block=False)` Not Always Work?

Plotting in a Non-Blocking Way with Matplotlib: Resolving Execution Issues

When attempting to plot a function with Matplotlib without halting execution, you may encounter difficulties related to the GUI and backend interactions. One common misunderstanding is the usage of show(block=False), which may not always work depending on the backend.

Your provided code demonstrates the use of show(block=False), but it appears that you are not using plt.ion() prior to calling show(). plt.ion() activates interactive mode, allowing for non-blocking plotting where you can draw and pause updates.

With plt.ion() enabled, you can call plt.show() to display the plot window. This window will remain open and non-blocking, allowing you to continue execution. However, to see the updated plots, you need to use plt.draw() to redraw the canvas and plt.pause(timeout) to pause the execution for a brief period. The timeout parameter in plt.pause() determines the length of the pause in seconds.

In your specific case, it is also crucial to note that each time you call plt.plot(), a new plot will be created in the same window. If you wish to update the existing plot instead, you should use plt.plot(x, y, color='r'). This will plot the new data points in red color, while preserving the existing plot.

Below is a revised version of your code that should resolve the non-blocking issue and update the existing plot:

<code class="python">import matplotlib.pyplot as plt
import numpy as np

def main():
    plt.ion()  # Activate interactive mode
    plt.show()  # Display the plot window

    plt.axis([-50,50,0,10000])
    x = np.arange(-50, 51)
    for pow in range(1,5):
        y = [Xi**pow for Xi in x]
        plt.plot(x, y, color='r')  # Update the plot in red color
        plt.draw()
        plt.pause(0.001)  # Pause for a brief period
        input("Press [enter] to continue.")

if __name__ == '__main__':
    main()</code>

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