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ENH: Enable models for sparsely sampled fMRI series
Initial commit is all but the Convolve
portions of #376 squashed onto master @ 4315865375a6eb811ba9f7eadbc1d621ecb2de96. There may be some parts that are no longer appropriate.
Supersedes and closes #376 (leaving open for now for reference). Closes #252.
Codecov Report
Merging #414 into master will decrease coverage by
0.29%
. The diff coverage is44.23%
.
@@ Coverage Diff @@
## master #414 +/- ##
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- Coverage 62.37% 62.08% -0.3%
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Files 27 27
Lines 4564 4602 +38
Branches 1174 1185 +11
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+ Hits 2847 2857 +10
- Misses 1433 1455 +22
- Partials 284 290 +6
Flag | Coverage Δ | |
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#unittests | 62.08% <44.23%> (-0.3%) |
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Impacted Files | Coverage Δ | |
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bids/variables/kollekshuns.py | 83.57% <100%> (ø) |
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bids/variables/entities.py | 87.77% <100%> (+0.13%) |
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bids/variables/variables.py | 83.54% <36.36%> (-4.85%) |
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bids/variables/io.py | 72.24% <37.5%> (-3.01%) |
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bids/analysis/analysis.py | 86.91% <50%> (-1.87%) |
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Ah, saw you said we should set up a call. Looking at this again, I agree. Hacking sparse sampling into or next to the current approach is probably not worth it, and we should work out a strategy for resampling more broadly, with discontinuous integration windows in mind. Might also be worth thinking through the clustered acquisition approach at the same time, to avoid settling on a solution that will need to be refactored again when we get around to that.
@satra Do you think you or anyone in your group should be on the call?
@satra Bump.
Any status update on this, post resampling changes? (Fine if not, this is a low priority from my perspective.)
@tyarkoni - i haven't had a look at this in a while. can you point me to where the design matrix is being built and i can backtrack from there?