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Output RMSE map and time series for decay model fit
Closes #861. @madisoth, what kind of outputs do you think would be useful? I was thinking (1) a mean RMSE map and (2) maybe a mean RMSE time series, so users could flag volumes with bad model fits?
I could probably convert the RMSE map to a more meaningful unit, like percent?
Changes proposed in this pull request:
- Add a function to calculate RMSE 4D time series from monoexponential model fit.
Codecov Report
Attention: Patch coverage is 94.25287%
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in your changes are missing coverage. Please review.
Project coverage is 89.91%. Comparing base (
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Files | Patch % | Lines |
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tedana/decay.py | 93.33% | 1 Missing and 1 partial :warning: |
tedana/io.py | 84.61% | 1 Missing and 1 partial :warning: |
tedana/workflows/tedana.py | 80.00% | 0 Missing and 1 partial :warning: |
Additional details and impacted files
@@ Coverage Diff @@
## main #1044 +/- ##
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+ Coverage 89.80% 89.91% +0.11%
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Files 26 26
Lines 3540 3621 +81
Branches 621 629 +8
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- Misses 212 214 +2
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@madisoth gave me the thumbs up on this offline, so I'm opening it up for review.
Here's the mean RMSE image for the 3-echo dataset:
Here's the timeseries plot (with +/- 1 SD) for the same dataset:
The results are now substantially different:
The results are now substantially different:
I do expect the values to be non-trivially lower because you were including voxels with 1 good echo, which meant fit coefficients of 0 (i.e. the residual error would be the entire time series).
Ah, okay. That's a relief then.
That's fixed in my most recent commit.
@handwerkerd I think everything should be good now. Would you mind taking another look?
Thanks @handwerkerd!
Here's what the updated 3-echo timeseries plot looks like, for posterity.