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PrometheusPi opened this issue Dec 22, 2016 · 5 comments
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document that imshow now respects scale #7661

PrometheusPi opened this issue Dec 22, 2016 · 5 comments
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v2.0.0

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@PrometheusPi
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PrometheusPi commented Dec 22, 2016 •
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With the introduction of matplotlib 2.0.0 using plt.imshow() together with plt.yscale('log') changed its behavior.

The following example code:

import numpy as np
import matplotlib.pyplot as plt

tmp = np.random.random((5,5))
plt.imshow(tmp, aspect="auto", extent=(0,5, 1e0, 1e5), interpolation='nearest')
plt.yscale("log")

plt.show()

produces with python 3.4.3 and matplotlib 1.5.1
plt_imshow_2

and the following warning:

../.local/lib/python3.4/site-packages/matplotlib/image.py:375: UserWarning: Images are not supported on non-linear axes.
  warnings.warn("Images are not supported on non-linear axes.")

With python 3.4.3 and matplotlib 2.0.0rc1 it produces
index2

Thus, 2.0.0 assumes that underneath the linear bin id of the numpy array tmp lies a linear data extend (y-axis) scaling.

If however my logarithmic extent is mapped correctly onto the linear bin id of the numpy array - the old behavior is exactly what represents the data.

Is it possible to reproduce the old behavior without relabeling the y-axis by hand?
Is there an option, the tell imshow directly that a specify data axis is already log-scaled?
and if so:
Is it possible to have the same behavior independent of the matplotlib version used?

System:
Ubuntu 14.04.5 - Linux-Kernel 4.4.0-38
Matplotlib and Python are available via the HPC module system (probably via pip)

cc'ing: @s0vereign
@PrometheusPi PrometheusPi mentioned this issue Dec 22, 2016
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@tacaswell tacaswell added this to the 2.0 (style change major release) milestone Dec 22, 2016
@tacaswell
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To be clear, you were relying on a bug / undefined behavior. The new behavior is in arguably correct.

I think you want to be using http://matplotlib.org/examples/pylab_examples/image_nonuniform.html in 2.0+ but not sure if that will work as expected in <2.0.

I think pcolor and friends will work in all cases, see http://matplotlib.org/examples/pylab_examples/pcolor_demo.html

@phobson
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phobson commented Dec 22, 2016

Agree with @tacaswell about pcolor. This works in 1.5 and the 2.0 RC:
http://stackoverflow.com/a/20844584/1552748

@efiring
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efiring commented Dec 22, 2016

Don't use pcolor--it's slow, and has no advantages in most cases. Use pcolormesh. Supply the cell boundaries explicitly:

import numpy as np
import matplotlib.pyplot as plt

tmp = 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, ax = plt.subplots()
ax.set_yscale('log')
ax.pcolormesh(x, y, tmp)
ax.autoscale('tight')

plt.show()

It should be possible to do this more efficiently with Axes.pcolorfast, but it doesn't work with a log scale. That's a bug.
When testing this sort of thing, use a rectangular array (not a square), and a regular pattern, so you can be sure you are getting the orientation the way you intend it.

@tacaswell tacaswell changed the title imhow with yscale('log') changes scaling with 2.0.0 document that imshow now respects scale Dec 22, 2016
phobson added a commit to phobson/matplotlib that referenced this issue Jan 11, 2017
@phobson
DOC: explain logscales and imshow (closes matplotlib#7661)
6c407a4
@phobson phobson mentioned this issue Jan 11, 2017
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phobson added a commit to phobson/matplotlib that referenced this issue Jan 11, 2017
@phobson
DOC: explain logscales and imshow (closes matplotlib#7661)
25158c2
efiring added a commit that referenced this issue Jan 16, 2017
@efiring
Merge pull request #7800 from phobson/doc-imshow-logscale
54b120f 
DOC: explain non-linear scales and imshow (closes #7661)
tacaswell pushed a commit that referenced this issue Jan 16, 2017
@efiring @tacaswell
Merge pull request #7800 from phobson/doc-imshow-logscale
cfafd3d 
DOC: explain non-linear scales and imshow (closes #7661)
@PrometheusPi PrometheusPi mentioned this issue Feb 15, 2017
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@PrometheusPi
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Thanks a lot for your help. I finally had the time to implement the pcolormesh approach in our code. It works like a charm.

@mforbes
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mforbes commented Feb 12, 2018

What about when loading an RGB image from file? pcolormesh does not obviously accept RGB data...

@mforbes mforbes mentioned this issue Sep 23, 2018
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@alurban alurban mentioned this issue Jan 21, 2019
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@quantumsteve quantumsteve mentioned this issue May 3, 2019
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