.. _api-power_norm_demo:

api example code: power_norm_demo.py
====================================



.. plot:: /home/travis/build/jenshnielsen/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], [[2, 2], [2, 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`)