.. _images_contours_and_fields-contourf_log: images_contours_and_fields example code: contourf_log.py ======================================================== .. plot:: /home/tcaswell/source/p/matplotlib/doc/mpl_examples/images_contours_and_fields/contourf_log.py :: ''' 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 colors, ticker, cm from matplotlib.mlab import bivariate_normal 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 of the top right. # Needs to have z/colour axis on a log scale so we see both hump and spike. # linear scale only shows the spike. z = (bivariate_normal(X, Y, 0.1, 0.2, 1.0, 1.0) + 0.1 * bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)) # 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 = P.contourf(X, Y, z, levs, norm=colors.LogNorm()) # The 'extend' kwarg does not work yet with a log scale. cbar = fig.colorbar(cs) plt.show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)