Defining a discrete colormap for imshow in matplotlib

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You can use a ListedColormap to specify the white and red as the only colors in the color map, and the bounds determine where the transition is from one color to the next:

import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np

np.random.seed(101)
zvals = np.random.rand(100, 100) * 10

# make a color map of fixed colors
cmap = colors.ListedColormap(['white', 'red'])
bounds=[0,5,10]
norm = colors.BoundaryNorm(bounds, cmap.N)

# tell imshow about color map so that only set colors are used
img = plt.imshow(zvals, interpolation='nearest', origin='lower',
                    cmap=cmap, norm=norm)

# make a color bar
plt.colorbar(img, cmap=cmap, norm=norm, boundaries=bounds, ticks=[0, 5, 10])

plt.savefig('redwhite.png')
plt.show()

The resulting figure has only two colors:

enter image description here

I proposed essentially the same thing for a somewhat different question: 2D grid data visualization in Python

The solution is inspired by a matplotlib example. The example explains that the bounds must be one more than the number of colors used.

The BoundaryNorm is a normalization that maps a series of values to integers, which are then used to assign the corresponding colors. cmap.N, in the example above, just defines the number of colors.

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