Find centre of rotation (tentative 2)

[lauraporta]

Tentative 2 with squashed commits

Description

What is this PR

• Bug fix
• Addition of a new feature
• Other

Why is this PR needed?
See #12

What does this PR do?

Creates methods and pipeline to find the centre of rotation in the incremental dataset.

⚠️ It does not fix the wobbling issues. The pipeline works well with simulated data but worsens the real datasets.

Pipeline

Find the centre

Find the centre of rotation using the incremental rotations datasets, in which the sample was rotated at discrete angles with 10deg intervals. Centre of rotation is found by fitting an ellipse to the brightest ROI location at each of the 10deg configurations.
New methods include:

• find_center_of_rotation
• get_coords_of_largest_blob
• plot_blob_detection
• fit_ellipse_to_points
• plot_ellipse_fit_and_centers

Use the new centre

In order to use the new centre of rotation, the derotate_an_image_array_line_by_line needed to be totally rewritten. I am discarding the usage of scipy.ndimage.rotate and using classic linear algebra to rotate the matrices. With this new implementation the derotation is so much faster! 🚀

How has this PR been tested?

The performance of the de-rotation when the centre of rotation is shifted has been tested with simulated data generated by the class Rotator.

I created a stepwise array of angles to imitate the incremental rotation dataset, and a sinusoidal array as the main experimental session dataset.

I then rotated a sample image that has two blobs that imitate two ROIs (one brighter than the other).

Ellipse fit works well with a shifted centre:

And derotation works smothly. This is the proof that in principle my derotation with shifted centres works.

I added tests to cover this new functionality and the pipeline.

Is this a breaking change?

No

Checklist:

• The code has been tested locally
• Tests have been added to cover all new functionality
• The documentation has been updated to reflect any changes
• The code has been formatted with pre-commit

[lauraporta]

From previous PR:

Improve tests, suggestions from @JoeZiminski in #25 :

• explain better the strategy of regression tests. Comments 1, 2
• path of the pre-computed images. Comments 3
• naming of the images. Comments 4
• expand tests on Rotator constructor. Comments 5
• move fixtures to conftest.py. Comments 6
• more notes on why did I made certain choices. Comments 7

[codecov]

Codecov Report

Attention: Patch coverage is 55.17241% with 65 lines in your changes missing coverage. Please review.

Project coverage is 43.89%. Comparing base (dd0bfab) to head (a1ece6a).
Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
...tation/analysis/incremental_derotation_pipeline.py	51.48%	49 Missing ⚠️
derotation/analysis/full_derotation_pipeline.py	12.50%	14 Missing ⚠️
derotation/derotate_by_line.py	90.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #30      +/-   ##
==========================================
- Coverage   48.54%   43.89%   -4.65%     
==========================================
  Files           5        6       +1     
  Lines         377      631     +254     
==========================================
+ Hits          183      277      +94     
- Misses        194      354     +160     

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[JoeZiminski]

Hey @lauraporta this looks great, very easy to follow and super clean! The tests and plots are really nice, it's super useful for understanding and very convincing that the algorithm is working well. I don't really have any major feedback, just a few things that came to mind. The only thing is the pattern (assuming I understand correctly) to re-generate the regression test data by running the test script as main vs. just testing with pytest. It seems it could be easy to accidentally run the script and regenerate the data, which would then nullify all tests. I don't think this is that major for now but might be something to think about in future.

I am super curious as to why incorporating the centre of rotation is making the real-world case worse 🤔 but I guess outside the scope of this PR!