I use matplotlib.pyplot.pcolor() to plot a heatmap with matplotlib:
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(1)
data = np.sort(np.random.rand(8,12))
plt.figure()
c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap='RdBu', vmin=0.0, vmax=1.0)
plt.colorbar(c)
plt.show()

How can I change the intensity of the 'RdBu' colormap? E.g., if the color is (0, 0, 1), it should be transformed into (0, 0, 0.8). More generally,
if the color is (x, y, z), it should be transformed into (ax, ay, az), where a is some scalar between zero and one.
This is quite similar to Stanley R's (edit: now Serenity) answer, without the (in my opinion) unnecessary complexity of loops, appending to lists, et cetera:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
a = 0.5
# Get the colormap colors, multiply them with the factor "a", and create new colormap
my_cmap = plt.cm.RdBu(np.arange(plt.cm.RdBu.N))
my_cmap[:,0:3] *= a
my_cmap = ListedColormap(my_cmap)
np.random.seed(1)
data = np.sort(np.random.rand(8,12))
plt.figure()
plt.subplot(121)
c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap='RdBu', vmin=0.0, vmax=1.0)
plt.colorbar(c)
plt.subplot(122)
c = plt.pcolor(data, edgecolors='k', linewidths=4, cmap=my_cmap, vmin=0.0, vmax=1.0)
plt.colorbar(c)
plt.show()

You have to assembly new custom color map based on a standard.
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
np.random.seed(1)
data = np.sort(np.random.rand(8,12))
plt.figure()
cmap = cm.get_cmap('RdBu', len(data)) # set how many colors you want in color map
# modify colormap
alpha = .5
colors = []
for ind in xrange(cmap.N):
c = []
for x in cmap(ind)[:3]: c.append(x*alpha)
colors.append(tuple(c))
my_cmap = matplotlib.colors.ListedColormap(colors, name = 'my_name')
# plot with my new cmap
cb = plt.pcolor(data, edgecolors='k', linewidths=4, cmap=my_cmap, vmin=0.0, vmax=1.0)
plt.colorbar(cb)
plt.show()

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