.. _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`)