Interpolations for imshow/matshow

This example displays the difference between interpolation methods for imshow() and matshow().

If interpolation is None, it defaults to the image.interpolation rc parameter. If the interpolation is 'none', then no interpolation is performed for the Agg, ps and pdf backends. Other backends will default to 'nearest'.

For the Agg, ps and pdf backends, interpolation = 'none' works well when a big image is scaled down, while interpolation = 'nearest' works well when a small image is scaled up.

import matplotlib.pyplot as plt
import numpy as np

methods = [None, 'none', 'nearest', 'bilinear', 'bicubic', 'spline16',
           'spline36', 'hanning', 'hamming', 'hermite', 'kaiser', 'quadric',
           'catrom', 'gaussian', 'bessel', 'mitchell', 'sinc', 'lanczos']

# Fixing random state for reproducibility
np.random.seed(19680801)

grid = np.random.rand(4, 4)

fig, axs = plt.subplots(nrows=3, ncols=6, figsize=(9.3, 6),
                        subplot_kw={'xticks': [], 'yticks': []})

fig.subplots_adjust(left=0.03, right=0.97, hspace=0.3, wspace=0.05)

for ax, interp_method in zip(axs.flat, methods):
    ax.imshow(grid, interpolation=interp_method, cmap='viridis')
    ax.set_title(str(interp_method))

plt.tight_layout()
plt.show()

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References

The use of the following functions and methods is shown in this example:

import matplotlib
matplotlib.axes.Axes.imshow
matplotlib.pyplot.imshow