A framework for computing similarity between 2D gray-tone images

[onatlandsmyr]

Similarity Metrics for 2D gray-tone images of equal size

A framework for computing similarity metrics between 2D gray-tone images of equal size. Provides a wrapper for user-defined metrics for use in, soon to be pull requested, template matching and dictionary indexing.

Zero-mean Normalized Cross-Correlation and Normalized Dot Product are implemented for inputs being dask arrays.

Progress of the PR

• Docstrings for all functions
• Unit tests with pytest for all lines
• Clean style in as per black

Minimal example of the bug fix or new feature

>>> import numpy as np
>>> import kikuchipy as kp
>>> from kikuchipy.indexation import make_similiarity_metric
>>> s = kp.signals.EBSD(np.zeros((100, 200, 96, 96)),lazy=True)
>>> def sum_absolute_difference(p,t):
...     return np.sum(np.abs(p - t), axis=(2, 3))
>>> sad_metric = make_similarity_metric(sum_absolute_difference,scope=MetricScope.MANY_TO_ONE)
>>> sad = sad_metric(s.data, np.zeros((96, 96)))
array([[0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       ...,
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.],
       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)

For reviewers

• Check that the PR title is short, concise, and will make sense 1 year
  later.
• Check that new functions are imported in corresponding __init__.py.
• Check that new features, API changes, and deprecations are mentioned in
  the unreleased section in doc/changelog.rst.

[hakonanes]

This will be great additions, thank you @onatlandsmyr!

Do you wan't a review right away? If yes, I'll get to it today.

Also, do you want help with tests? And documentation? For this PR, I envision a module entry in the API reference documentation with all public classes/methods/functions fully documented from nice docstrings.

[onatlandsmyr]

A review would be good, sooner the better. Two more PRs are coming soon and they depend on this PR. I'll try to contribute more to the tests and docs, but any help is much appreciated.

[hakonanes]

A review would be good, sooner the better. Two more PRs are coming soon and they depend on this PR. I'll try to contribute more to the tests and docs, but any help is much appreciated.

Okay, great, will review soon and mention wherever I plan to contribute.

[hakonanes]

This looks great, the general approach looks easily extendable and customizable, which is very nice to have.

There are many comments, some questions, some proposals for changes. Many of the comments are related to docstring formatting... Do you wan't to tackle these, or should I? I will add the indexing module to the API reference and see that all docstrings behave nicely, if that's okay with you.

[hakonanes]

Yeah, the tests will fail since I didn't change the normalize() call in _ndp_einsum() to _normalize().

[hakonanes]

Will merge after tests pass. Great work, @onatlandsmyr!

[hakonanes]

Let's get this in and move on to the next PR! Let's change the SimilarityMetric class and related functions if necessary in that PR.