Non-linear scales on image plots

:func:`imshow` now draws data at the requested points in data space after the

application of non-linear scales.

The image on the left demonstrates the new, correct behavior.

The old behavior can be recreated using :func:`pcolormesh` as

demonstrated on the right.

Non-linear scale example

.. plot::

import numpy as np

import matplotlib.pyplot as plt

data = np.arange(30).reshape(5, 6)

x = np.linspace(0, 6, 7)

y = 10**np.linspace(0, 5, 6)

X, Y = np.meshgrid(x, y)

fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(8, 4))

ax1.imshow(data, aspect="auto", extent=(0, 6, 1e0, 1e5), interpolation='nearest')

ax1.set_yscale('log')

ax1.set_title('Using ax.imshow')

ax2.pcolormesh(x, y, np.flipud(data))

ax2.set_yscale('log')

ax2.set_title('Using ax.pcolormesh')

ax2.autoscale('tight')

plt.show()

This can be understood by analogy to plotting a histogram with linearly spaced bins

with a logarithmic x-axis. Equal sized bins will be displayed as wider for small

*x* and narrower for large *x*.