HT local subregions testing - #1
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htregidgo
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May 14, 2026
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- Add local subregions test config profiles
- Document subregions smoke-test outputs
Refactor the shared subregions smoke-test harness so Henry and Jackson can run it without editing hard-coded paths in the script. The script now looks for repo-relative JSON profile pairs and uses the first one whose required FreeSurfer, subject, segmentation, and DTI paths exist. Add Henry-specific DTI and multichannel JSON files while leaving Jackson's existing JSON files as the fallback profile. Keep temp and output locations separate for DTI, standard thalamus, and multichannel runs so results remain inspectable and avoid filename collisions. Replace the hard-coded means_groupings.json path in thalamusDTI.py with a path derived from the module location, so the support file is loaded from the repo on either machine.
Add notes to the local subregions test harness explaining the three objects it drives: the DTI-aware run, the standard thalamus run, and the multi-channel DTI/FA run. Annotate each process.py-style command group with the temp files or final outputs it writes. This keeps the dirty shared harness easier to inspect after long local smoke tests without changing runtime behavior.
jnolan14
marked this pull request as ready for review
May 27, 2026 14:22
Add shared Gaussian helpers for diagonal and full-covariance subregions fitting, including likelihoods, posterior parameter updates, covariance conversion for GEMS, and validation for covariance-mode inputs. Wire covariance_mode through MeshModel and ThalamicNucleiDTI while preserving diagonal mode as the default. Refactor image fitting and final posterior extraction to use the shared helpers, and pass full covariance matrices to GEMS in both covariance modes. Update DTI hyperparameter estimation so multi-channel runs produce channel-aware meanHyper arrays while keeping nHyper one-dimensional. Add focused pytest coverage for the helper math, covariance shape handling, low-mass fallbacks, singular covariance rejection, and the full mean-prior cost.
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