plot residual

[HanHsuanWu]

Description of the change

A few sentences and/or a bulleted list to describe and motivate the change:

As suggested by @thomasaarholt on gitter, I added a plot_residual argument to model1d.plot.
This argument will plot a residual signal (Signal - Model) to the signal plot.
Currently, it has a bug when the size of signal and model are not the same. I am not sure what's the best way to do this so any help is appreciated.

Progress of the PR

• Change implemented (can be split into several points),
• update docstring (if appropriate),
• update user guide (if appropriate),
• add an changelog entry in the upcoming_changes folder (see upcoming_changes/README.rst),
• Check formatting changelog entry in the readthedocs doc build of this PR (link in github checks)
• add tests,
• ready for review.

Minimal example of the bug fix or the new feature

import hyperspy.api as hs
import numpy as np
s = hs.signals.Signal1D(np.tile(np.arctan(np.arange(-500, 500)), (10, 1)),dtype='float64')
s.add_gaussian_noise(std=0.1)
m = s.create_model()
line  = hs.model.components1D.Polynomial(order=2)
m.append(line)
m.fit()
m.plot(plot_residual=True)

[codecov]

Codecov Report

Patch coverage: 100.00% and project coverage change: +0.01% 🎉

Comparison is base (aeae846) 81.25% compared to head (18a019a) 81.27%.

Additional details and impacted files

@@                  Coverage Diff                   @@
##           RELEASE_next_major    #3186      +/-   ##
======================================================
+ Coverage               81.25%   81.27%   +0.01%     
======================================================
  Files                     173      173              
  Lines                   24192    24203      +11     
  Branches                 5621     5622       +1     
======================================================
+ Hits                    19657    19670      +13     
+ Misses                   3236     3234       -2     
  Partials                 1299     1299              

Files Changed	Coverage Δ
hyperspy/models/model1d.py	88.67% <100.00%> (+0.27%)	⬆️

... and 1 file with indirect coverage changes

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[thomasaarholt]

Thanks for the PR! I've added some general linting comments below as well as a few suggestions.

[thomasaarholt]

Could you document what happens here?

[HanHsuanWu]

I have added documentation for _residual_for_plot.

[HanHsuanWu]

Hey @thomasaarholt thanks for reviewing.
I have addressed your comments and ended up deleting the out_of_range2nans part.
I added a new argument for model1d.call() to ignore the channel_switches, so that it always plots the residual for the whole spectrum. We can add another argument to turn this on or off if needed. What do you think?

[ericpre]

Thank you @HanHsuanWu, this works well and is a long overdue!

I have suggested some simplification.

This would need a changelog entry.

[HanHsuanWu]

Thank you @HanHsuanWu, this works well and is a long overdue!

I have suggested some simplification.

This would need a changelog entry.

What is a changelog entry and where do I add this?

[ericpre]

See https://github.com/hyperspy/hyperspy/blob/RELEASE_next_minor/upcoming_changes/README.rst as per checklist of the first comment of the PR.
It is a note to describe the changes of this PR and will be added automatically to the list of changes (also called changelog) for each release.

[HanHsuanWu]

See https://github.com/hyperspy/hyperspy/blob/RELEASE_next_minor/upcoming_changes/README.rst as per checklist of the first comment of the PR. It is a note to describe the changes of this PR and will be added automatically to the list of changes (also called changelog) for each release.

Thanks Eric. I have added the changelog. Got a bit confused before.

[HanHsuanWu]

@ericpre any further comments for this pull request?

[ericpre]

Sorry, I don't have time at the minute, I will come back to it very soon.

[ericpre]

Thanks @HanHsuanWu, this looks good.
In 18a019a I added a test and an example. I have also rebased on the RELEASE_next_major branch as the next release will be the 2.0.