>>> """
=======================
Colorbar Tick Labelling
=======================

Produce custom labelling for a colorbar.

Contributed by Scott Sinclair
"""
... 
... import matplotlib.pyplot as plt
... import numpy as np
... from matplotlib import cm
... from numpy.random import randn
... 
... 
... # Fixing random state for reproducibility
... np.random.seed(19680801)
... 
... ###############################################################################
... # Make plot with vertical (default) colorbar
... 
... fig, ax = plt.subplots()
... 
... data = np.clip(randn(250, 250), -1, 1)
... 
... cax = ax.imshow(data, cmap=cm.coolwarm)
... ax.set_title('Gaussian noise with vertical colorbar')
... 
... # Add colorbar, make sure to specify tick locations to match desired ticklabels
... cbar = fig.colorbar(cax, ticks=[-1, 0, 1])
... cbar.ax.set_yticklabels(['< -1', '0', '> 1'])  # vertically oriented colorbar
... 
... ###############################################################################
... # Make plot with horizontal colorbar
... 
... fig, ax = plt.subplots()
... 
... data = np.clip(randn(250, 250), -1, 1)
... 
... cax = ax.imshow(data, cmap=cm.afmhot)
... ax.set_title('Gaussian noise with horizontal colorbar')
... 
... cbar = fig.colorbar(cax, ticks=[-1, 0, 1], orientation='horizontal')
... cbar.ax.set_xticklabels(['Low', 'Medium', 'High'])  # horizontal colorbar
... 
... plt.show()
...