REF: Remove PET estimator#426
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #426 +/- ##
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- Coverage 83.91% 83.37% -0.54%
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Files 37 37
Lines 2138 2093 -45
Branches 235 231 -4
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- Hits 1794 1745 -49
- Misses 303 309 +6
+ Partials 41 39 -2 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
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Remove the PET estimator: the `NiFreeze` estimator design is modality-agnostic, so a PET-specific estimator is not required. Remove the PET-specific integration test: checking that motion estimation with PET data yields the identity matrix when monkey patching the transformation computation when the estimator runs the registration step is covered by the `test_estimator:test_estimator_iterator_index_match` test function. Update the notebook accordingly: - Avoid trying to fit on all data, as it is not implemented yet following commit a468d76. - Call `.matrix` on the `Affine` instances to get the affine transformation as a `NumPy` array.
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@oesteban @mnoergaard Runs from beginning to end now. The estimation is still not good, but that is independent of the patch set I'd say. |
oesteban
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This is great. We can now work on making the general estimator work properly, but having a net decrease of ~2400 lines is a substantial complexity reduction. Thanks!
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One thing that came to my mind yesterday was nipy/nitransforms#286 (comment). Maybe we are not extracting the motion parameters correctly, and hence, our results do not seem to be correct. May not be the only reason. |
Remove the PET estimator: the
NiFreezeestimator design is modality-agnostic, so a PET-specific estimator is not required.Remove the PET-specific integration test: checking that motion estimation with PET data yields the identity matrix when monkey patching the transformation computation when the estimator runs the registration step is covered by the
test_estimator:test_estimator_iterator_index_matchtest function.Update the notebook accordingly:
following commit a468d76.
.matrixon theAffineinstances to get the affine transformation as aNumPyarray.