''' Make a colorbar as a separate figure. ''' from matplotlib import pyplot, mpl # Make a figure and axes with dimensions as desired. fig = pyplot.figure(figsize=(8,3)) ax1 = fig.add_axes([0.05, 0.65, 0.9, 0.15]) ax2 = fig.add_axes([0.05, 0.25, 0.9, 0.15]) # Set the colormap and norm to correspond to the data for which # the colorbar will be used. cmap = mpl.cm.cool norm = mpl.colors.Normalize(vmin=5, vmax=10) # ColorbarBase derives from ScalarMappable and puts a colorbar # in a specified axes, so it has everything needed for a # standalone colorbar. There are many more kwargs, but the # following gives a basic continuous colorbar with ticks # and labels. cb1 = mpl.colorbar.ColorbarBase(ax1, cmap=cmap, norm=norm, orientation='horizontal') cb1.set_label('Some Units') # The second example illustrates the use of a ListedColormap, a # BoundaryNorm, and extended ends to show the "over" and "under" # value colors. cmap = mpl.colors.ListedColormap(['r', 'g', 'b', 'c']) cmap.set_over('0.25') cmap.set_under('0.75') # If a ListedColormap is used, the length of the bounds array must be # one greater than the length of the color list. The bounds must be # monotonically increasing. bounds = [1, 2, 4, 7, 8] norm = mpl.colors.BoundaryNorm(bounds, cmap.N) cb2 = mpl.colorbar.ColorbarBase(ax2, cmap=cmap, norm=norm, # to use 'extend', you must # specify two extra boundaries: boundaries=[0]+bounds+[13], extend='both', ticks=bounds, # optional spacing='proportional', orientation='horizontal') cb2.set_label('Discrete intervals, some other units') pyplot.show()