Can matplotlib Plots Remain Interactive During Computation?

Maintaining Matplotlib Plot Interactivity During Continued Computation

When performing complex calculations in Python, it can be beneficial to monitor intermediate results through interactive visualizations. However, calling matplotlib.pyplot.show() typically blocks further computations until the figure is closed. This can hinder the efficiency of long-running tasks.

Can This Blocking Behavior Be Circumvented?

Yes, it is possible to detach matplotlib plots from the computation process, allowing both to proceed concurrently. This enables the interactive exploration of results while the program continues with its calculations.

Utilizing Non-Blocking Methods

Two non-blocking functions provided by matplotlib can be implemented to achieve this:

• draw(): Updates the figure without displaying it, allowing the program to proceed without blocking.

Example:

from matplotlib.pyplot import plot, draw, show
plot([1,2,3])
draw()
print('continue computation')

# Display the plot after computation completes
show()

• ion() (interactive mode): Activates interactive mode, where all figure updates are displayed immediately.

Example:

from matplotlib.pyplot import plot, ion, show
ion() # Enables interactive mode
plot([1,2,3]) # Figure updates immediately

print('continue computation')

# Display the plot after computation completes
show()

In conclusion, by leveraging draw() or activating interactive mode with ion(), it becomes possible to maintain the interactivity of matplotlib plots while the computation proceeds in the background. This technique significantly enhances the efficiency of workflows involving complex calculations and interactive data visualization.

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