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Optimizing Subplot Heights and Spacing for Extensive Plots
Creating multiple vertically stacked plots in Matplotlib can be challenging when space constraints become an issue. This becomes particularly evident when saving the resultant image for viewing on webpages. To address this problem, it is crucial to optimize the subplot heights and spacing effectively.
One solution to this issue is to utilize the matplotlib.pyplot.tight_layout function. This function automatically adjusts the layout of the subplots within a figure to prevent overlap, regardless of the figure size. It does this by dynamically calculating the appropriate spacing between subplots based on their respective contents.
To illustrate the usage of matplotlib.pyplot.tight_layout, consider the following code:
import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(8, 8)) fig.tight_layout() # Automatically adjusts subplot spacing and heights plt.show()
In this example, the tight_layout function is applied to a figure comprising a grid of 4 rows and 4 columns. As the figure size is fixed at 8 by 8, the subplots will automatically resize and adjust their heights to fit within the figure without overlapping.
The effect of using tight_layout is evident in the comparison between plots created without and with the function. The original plots often exhibit overlapping subplots, while the ones generated with tight_layout have their subplots neatly arranged within the figure.
Without Tight Layout: [Image of overlapping subplots] With Tight Layout: [Image of non-overlapping subplots]
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