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imshow no longer correctly handles 'bad' (nan) values #6069

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tacaswell opened this issue Feb 28, 2016 · 10 comments
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imshow no longer correctly handles 'bad' (nan) values #6069

tacaswell opened this issue Feb 28, 2016 · 10 comments
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@mdboom
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v2.0.0

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@tacaswell
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To help us understand and resolve your issue please check that you have provided
the information below.

  • [ v2.x ] Matplotlib version, Python version and Platform (Windows, OSX, Linux ...)
  • [ source ] How did you install Matplotlib and Python (pip, anaconda, from source ...)
  • If possible please supply a Short, Self Contained, Correct, Example
    that demonstrates the issue i.e a small piece of code which reproduces the issue
    and can be run with out any other (or as few as possible) external dependencies.
plt.imshow(np.ones((5, 5)) * np.nan)
  • If this is an image generation bug attach a screenshot demonstrating the issue.
    so

Also got some user warnings

 /home/tcaswell/.virtualenvs/dd_35/lib/python3.5/site-packages/numpy/ma/core.py:4089: UserWarning: Warning: converting a masked element to nan.
  warnings.warn("Warning: converting a masked element to nan.")
/home/tcaswell/source/p/matplotlib/lib/matplotlib/colors.py:581: RuntimeWarning: invalid value encountered in less
  cbook._putmask(xa, xa < 0.0, -1)
/home/tcaswell/source/p/matplotlib/lib/matplotlib/cm.py:275: RuntimeWarning: invalid value encountered in less
  rgba[:, :, 3][x < 0.0] = 0
  • [ always ] If this is a regression (Used to work in an earlier version of Matplotlib), please
    note where it used to work.
@tacaswell tacaswell added this to the 2.0 (style change major release) milestone Feb 28, 2016
@tacaswell
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It looks like new image re-sampling code loses the mask that gets added on the way into AxesImage which then does not propagate properly through norm / color map.

tacaswell added a commit to tacaswell/matplotlib that referenced this issue Feb 28, 2016
@tacaswell
FIX: do invalid masking in to_rgba not set_data
5a4bd76 
The way that color mapping used to work was:

 - mask invalid
 - normalize
 - cmap (which uses the mask information fill in 'bad' values)
 - interpolate

The new order is:

 - mask invalid
 - interpolate (converting mask -> nan)
 - normalize (which passes through nan)
 - cmap

which results in cmap seeing the `nan` which it seems to map to
0.

This does the masking on the interpolated array just prior to
normalizing and removes it on the way in.

Fixes matplotlib#6069
@tacaswell tacaswell mentioned this issue Feb 28, 2016
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@tacaswell tacaswell self-assigned this Feb 28, 2016
@mdboom mdboom assigned mdboom and tacaswell and unassigned tacaswell and mdboom Feb 29, 2016
@mdboom
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mdboom commented Feb 29, 2016

Lemme know if you need help with this one.

@mdboom mdboom assigned mdboom and unassigned tacaswell Mar 2, 2016
tacaswell added a commit that referenced this issue Mar 4, 2016
@tacaswell
Merge pull request #6099 from mdboom/masked-image
5c5a287 
Fix #6069.  Handle image masks correctly
tacaswell added a commit that referenced this issue Mar 4, 2016
@tacaswell
Merge pull request #6099 from mdboom/masked-image
1302606 
Fix #6069.  Handle image masks correctly
@mankoff
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mankoff commented May 17, 2016 •
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I think this bug still exists w/ RGB images. An MWE based on the test_image in the above fix.

fig, (ax1, ax2) = plt.subplots(1, 2)

foo = np.ones((5,5))
foo[1:2, 1:2] = np.nan
ax1.imshow(A)

bar = np.zeros((5,5,3))
bar[:,:,0] = 1
bar[:,:,1] = 0
bar[:,:,2] = 0
bar[1:2,1:2,:] = np.nan
ax2.imshow(bar)

screen shot 2016-05-17 at 16 14 08

@tacaswell
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In the case of RGBA there is no color mapping. The black coming through is a bit odd.

@mankoff What version of mpl and what backend are you using?

@mankoff
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mankoff commented May 17, 2016

mpl: 1.5.1
backend: Qt4Agg
OS: OS X.

I'm not sure what you mean by "no color mapping". Is it possible to have transparent values in an RGB displayed with imshow?

@tacaswell
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This original bug in this issue with the new image code which is only on 2.x/master (not released yet).

What I mean by 'no color mapping' is that if you pass a (M, N, 3) or (M, N, 4) array to imshow it does not get run through the normalization / color mapping code path. The [0,1] -> R3 step has a mapping, plus three special colors 'over', 'under', and 'bad'.

I am actually not sure what to expect for an RGB/RGBA input with nans in it. Did this used to do something different? In any case, can you make a new issue?

@efiring
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efiring commented May 18, 2016

Something might have gotten lost. We are using safe_masked_invalid in set_data, so I suspect that the mask was being handled prior to the big refactoring. What was being rendered in the masked locations, I don't know.

@efiring
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efiring commented May 18, 2016

Contrary to my last comment, I don't think anything has been lost. Looking at v1.4.1, I don't see any indication in the code or the docstring that invalid or masked data has ever been supported for RGB or RGBA arrays. Even though they get passed through safe_masked_invalid, their mask is never checked or used. Maybe the thing to do is to warn if any values are actually masked, and then use .filled(0) to turn them back into ordinary ndarrays. Or raise an exception if any values are masked. I think it should remain the responsibility of the supplier of RGB or RGBA arrays to handle bad values before passing the arrays in to imshow.

@anntzer anntzer mentioned this issue Jan 5, 2017
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@benjimin
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I think it is a useful feature that regions of NaN appear like holes when visualised by imshow. Unfortunately (in matplotlib 2.0.0) imshow raises ValueError if the raster array does not contain any finite values whatsoever.

@tacaswell
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Can you try with 2.0.2 or provide a MWE in a new issue?

I have a memory of fixing something like that recently.

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