>>> """
============================
Contourf and log color scale
============================

Demonstrate use of a log color scale in contourf
"""
... 
... import matplotlib.pyplot as plt
... import numpy as np
... from numpy import ma
... from matplotlib import ticker, cm
... 
... N = 100
... x = np.linspace(-3.0, 3.0, N)
... y = np.linspace(-2.0, 2.0, N)
... 
... X, Y = np.meshgrid(x, y)
... 
... # A low hump with a spike coming out.
... # Needs to have z/colour axis on a log scale so we see both hump and spike.
... # linear scale only shows the spike.
... Z1 = np.exp(-X**2 - Y**2)
... Z2 = np.exp(-(X * 10)**2 - (Y * 10)**2)
... z = Z1 + 50 * Z2
... 
... # Put in some negative values (lower left corner) to cause trouble with logs:
... z[:5, :5] = -1
... 
... # The following is not strictly essential, but it will eliminate
... # a warning.  Comment it out to see the warning.
... z = ma.masked_where(z <= 0, z)
... 
... 
... # Automatic selection of levels works; setting the
... # log locator tells contourf to use a log scale:
... fig, ax = plt.subplots()
... cs = ax.contourf(X, Y, z, locator=ticker.LogLocator(), cmap=cm.PuBu_r)
... 
... # Alternatively, you can manually set the levels
... # and the norm:
... # lev_exp = np.arange(np.floor(np.log10(z.min())-1),
... #                    np.ceil(np.log10(z.max())+1))
... # levs = np.power(10, lev_exp)
... # cs = ax.contourf(X, Y, z, levs, norm=colors.LogNorm())
... 
... cbar = fig.colorbar(cs)
... 
... plt.show()
... 
... #############################################################################
... #
... # .. admonition:: References
... #
... #    The use of the following functions, methods, classes and modules is shown
... #    in this example:
... #
... #    - `matplotlib.axes.Axes.contourf` / `matplotlib.pyplot.contourf`
... #    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`
... #    - `matplotlib.axes.Axes.legend` / `matplotlib.pyplot.legend`
... #    - `matplotlib.ticker.LogLocator`
...