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Construct affine transforms from point-pairs #87

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merged 4 commits into from
May 7, 2023

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@timholy timholy commented Apr 29, 2023

Given a set of point pairs from => to, compute the affine
transformation that best reproduces the observed mapping.

Closes #30

timholy added 2 commits April 29, 2023 07:01
Given a set of point pairs `from => to`, compute the affine
transformation that best reproduces the observed mapping.

Closes #30
@timholy timholy closed this Apr 29, 2023
@timholy timholy reopened this Apr 29, 2023
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codecov bot commented Apr 29, 2023

Codecov Report

Merging #87 (9e67de2) into master (78f5a5c) will increase coverage by 2.63%.
The diff coverage is 58.82%.

❗ Current head 9e67de2 differs from pull request most recent head ff37a34. Consider uploading reports for the commit ff37a34 to get more accurate results

@@            Coverage Diff             @@
##           master      #87      +/-   ##
==========================================
+ Coverage   63.90%   66.54%   +2.63%     
==========================================
  Files           4        4              
  Lines         266      275       +9     
==========================================
+ Hits          170      183      +13     
+ Misses         96       92       -4     
Impacted Files Coverage Δ
src/affine.jl 56.97% <53.33%> (+8.87%) ⬆️
src/coordinatesystems.jl 79.28% <100.00%> (+0.30%) ⬆️

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Looks good to me.

@timholy timholy merged commit a2c7197 into master May 7, 2023
@timholy timholy deleted the teh/affine_from_points branch May 7, 2023 21:43
timholy added a commit that referenced this pull request Jan 15, 2025
Given two sets of points, this constructs rigid (rotation
+ translation) and similarity (rotation, translation, and scaling)
transformations that align the first set to the second in the
least-squares sense. Similar to #87, but with constraints on the nature
of the transformation.

Co-authored by: Tom McGrath <[email protected]>
timholy added a commit that referenced this pull request Feb 4, 2025
Given two sets of points, this constructs rigid (rotation
+ translation) and similarity (rotation, translation, and scaling)
transformations that align the first set to the second in the
least-squares sense. Similar to #87, but with constraints on the nature
of the transformation.

Co-authored by: Tom McGrath <[email protected]>
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Set of measured points to known coordinates
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