.. _api-power_norm_demo: api example code: power_norm_demo.py ==================================== .. plot:: /home/tcaswell/other_source/matplotlib/doc/mpl_examples/api/power_norm_demo.py :: #!/usr/bin/python from matplotlib import pyplot as plt import matplotlib.colors as mcolors import numpy as np from numpy.random import multivariate_normal data = np.vstack([multivariate_normal([10, 10], [[3, 5],[4, 2]], size=100000), multivariate_normal([30, 20], [[2, 3],[1, 3]], size=1000) ]) gammas = [0.8, 0.5, 0.3] xgrid = np.floor((len(gammas) + 1.) / 2) ygrid = np.ceil((len(gammas) + 1.) / 2) plt.subplot(xgrid, ygrid, 1) plt.title('Linear normalization') plt.hist2d(data[:,0], data[:,1], bins=100) for i, gamma in enumerate(gammas): plt.subplot(xgrid, ygrid, i + 2) plt.title('Power law normalization\n$(\gamma=%1.1f)$' % gamma) plt.hist2d(data[:, 0], data[:, 1], bins=100, norm=mcolors.PowerNorm(gamma)) plt.subplots_adjust(hspace=0.39) plt.show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)