.. _scales-scales:

scales example code: scales.py
==============================



.. plot:: /home/tcaswell/src/p/matplotlib/doc/mpl_examples/scales/scales.py

::

    """
    Illustrate the scale transformations applied to axes, e.g. log, symlog, logit.
    """
    import numpy as np
    import matplotlib.pyplot as plt
    from matplotlib.ticker import NullFormatter
    
    np.random.seed(1)
    # make up some data in the interval ]0, 1[
    y = np.random.normal(loc=0.5, scale=0.4, size=1000)
    y = y[(y > 0) & (y < 1)]
    y.sort()
    x = np.arange(len(y))
    
    # plot with various axes scales
    fig, axs = plt.subplots(2, 2, sharex=True)
    fig.subplots_adjust(left=0.08, right=0.98, wspace=0.3)
    
    # linear
    ax = axs[0, 0]
    ax.plot(x, y)
    ax.set_yscale('linear')
    ax.set_title('linear')
    ax.grid(True)
    
    
    # log
    ax = axs[0, 1]
    ax.plot(x, y)
    ax.set_yscale('log')
    ax.set_title('log')
    ax.grid(True)
    
    
    # symmetric log
    ax = axs[1, 1]
    ax.plot(x, y - y.mean())
    ax.set_yscale('symlog', linthreshy=0.02)
    ax.set_title('symlog')
    ax.grid(True)
    
    # logit
    ax = axs[1, 0]
    ax.plot(x, y)
    ax.set_yscale('logit')
    ax.set_title('logit')
    ax.grid(True)
    ax.yaxis.set_minor_formatter(NullFormatter())
    
    
    plt.show()
    

Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)