Not to steal @ianilis's answer, but I wanted to add an example...
There are multiple ways, but the simplest is just to specify the vmin
and vmax
kwargs to imshow
. Alternately, you can make a matplotlib.cm.Colormap
instance and specify it, but that's more complicated than necessary for simple cases.
Here's a quick example with a single colorbar for all images:
import numpy as np
import matplotlib.pyplot as plt
# Generate some data that where each slice has a different range
# (The overall range is from 0 to 2)
data = np.random.random((4,10,10))
data *= np.array([0.5, 1.0, 1.5, 2.0])[:,None,None]
# Plot each slice as an independent subplot
fig, axes = plt.subplots(nrows=2, ncols=2)
for dat, ax in zip(data, axes.flat):
# The vmin and vmax arguments specify the color limits
im = ax.imshow(dat, vmin=0, vmax=2)
# Make an axis for the colorbar on the right side
cax = fig.add_axes([0.9, 0.1, 0.03, 0.8])
fig.colorbar(im, cax=cax)
plt.show()
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