Cannot minimize matplotlib window

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Summary

The issue of a matplotlib window not staying minimized is a common problem encountered when creating dashboards using matplotlib. The root cause of this issue lies in the way matplotlib handles window events and the infinite loop used to update the plot. In this article, we will explore the root cause, real-world impact, and provide a solution to fix this issue.

Root Cause

The root cause of this issue is the infinite loop used to update the plot, which prevents the window from staying minimized. The loop continuously updates the plot, causing the window to jump back up. Additionally, the plt.pause(0.0001) function is used to introduce a delay, but it is not sufficient to allow the window to stay minimized.

Why This Happens in Real Systems

This issue occurs in real systems because of the following reasons:

  • Infinite loops are commonly used to update plots in real-time
  • Matplotlib does not handle window events properly when used in conjunction with infinite loops
  • plt.pause() function is not designed to handle window minimization events

Real-World Impact

The real-world impact of this issue is:

  • Poor user experience: The window jumping back up can be frustrating for users
  • Increased CPU usage: The infinite loop can consume high CPU resources, leading to performance issues
  • Difficulty in debugging: The issue can be challenging to debug, especially for junior engineers

Example or Code

import matplotlib.pyplot as plt
import numpy as np

def on_close(event):
    event.canvas.figure.axes[0].has_been_closed = True
    print('The Figure is Closed!')

fig, ax = plt.subplots(2, 3)
ax[0,0].has_been_closed = False
fig.canvas.mpl_connect('close_event', on_close)
fig.set_size_inches(15, 8)

while True:
    for i in range(ax.shape[0]):
        for j in range(ax.shape[1]):
            ax[i,j].clear()
    ax[0, 0].plot(range(10), np.random.rand(10,1), 'r')
    ax[1, 0].plot(np.random.rand(10,1), 'b')
    ax[0, 1].plot(np.random.rand(10,1), 'g')
    ax[1, 1].plot(np.random.rand(10,1), 'k')
    ax[0, 2].plot(np.random.rand(10,1), 'g')
    ax[1, 2].plot(np.random.rand(10,1), 'k')
    plt.pause(0.0001)
    if ax[0,0].has_been_closed:
        break

How Senior Engineers Fix It

Senior engineers fix this issue by:

  • Using a more efficient plotting library, such as PyQt or wxPython, which handle window events properly
  • Implementing a more efficient update mechanism, such as using timers or threads, to reduce CPU usage
  • Using matplotlib in conjunction with other libraries, such as PyQt, to handle window events properly

Why Juniors Miss It

Junior engineers may miss this issue because:

  • Lack of experience with matplotlib and its limitations
  • Insufficient understanding of window events and how they are handled in matplotlib
  • Overreliance on plt.pause() function, which is not designed to handle window minimization events

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