This example displays the difference between interpolation methods for imshow.
If interpolation is None, it defaults to the rcParams["image.interpolation"] (default: 'auto'). If the interpolation is 'none', then no interpolation is performed for the Agg, ps and pdf backends. Other backends will default to 'auto'.
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.
See Image resampling for a discussion on the default interpolation='auto' option.
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, 6),
subplot_kw={'xticks': [], 'yticks': []})
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()
Total running time of the script: (0 minutes 4.703 seconds)
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