Bagaimana untuk Mencegah Cut-off Legend dalam Matplotlib dan Mengekalkan Keterlihatan Data?

Addressing Cut-off Legend in Matplotlib by Resizing the Figure Box

In Matplotlib, moving the legend outside the plot axis often results in its cutoff by the figure box. While shrinking the axis has been suggested as a solution, it diminishes data visibility, especially when presenting complex plots with numerous legend entries.

A more effective approach, as highlighted in Benjamin Root's response on the Matplotlib mailing list, involves modifying the savefig call to incorporate the legend as an extra artist:

fig.savefig('samplefigure', bbox_extra_artists=(lgd,), bbox_inches='tight')

This method, similar to using tight_layout, enables savefig to consider the legend when calculating the figure box size.

The following enhanced code sample demonstrates the solution:

import matplotlib.pyplot as plt
import numpy as np

plt.gcf().clear()
x = np.arange(-2*np.pi, 2*np.pi, 0.1)
fig = plt.figure(1)
ax = fig.add_subplot(111)
ax.plot(x, np.sin(x), label='Sine')
ax.plot(x, np.cos(x), label='Cosine')
ax.plot(x, np.arctan(x), label='Inverse tan')
handles, labels = ax.get_legend_handles_labels()
lgd = ax.legend(handles, labels, loc='upper center', bbox_to_anchor=(0.5,-0.1))
text = ax.text(-0.2,1.05, "Aribitrary text", transform=ax.transAxes)
ax.set_title("Trigonometry")
ax.grid('on')
fig.savefig('samplefigure', bbox_extra_artists=(lgd,text), bbox_inches='tight')

This now dynamically adjusts the figure box size to accommodate the legend, preventing its cutoff while maintaining data visibility.

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