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ENH: Add a Bandpass
filter interface under algorithms.filters
#2915
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Codecov Report
@@ Coverage Diff @@
## master #2915 +/- ##
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- Coverage 67.57% 64.17% -3.4%
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Files 343 342 -1
Lines 43645 43637 -8
Branches 5428 5430 +2
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- Hits 29494 28005 -1489
- Misses 13447 14552 +1105
- Partials 704 1080 +376
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Thumbs up? |
@oesteban - this looks good. could we add a real test to this perhaps generating a random (white noise) nifti timeseries file and filtering it with this code in _bandpass_filter? also could we add a pointer to the discussion on neurostars (or at least the wording about ringing artifacts with this method)? |
will do |
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Seems reasonable. Couple comments.
Parameters | ||
---------- | ||
files : str | ||
4D NIfTI file |
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Necessarily NIfTI?
the default of 0 sets low pass cutoff to Nyquist | ||
freq_hi : float | ||
cutoff frequency for the high pass filter (in Hz) | ||
the default of 0 sets high pass cutoff to 0 |
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This seems wrong...
Co-Authored-By: Chris Markiewicz <[email protected]>
@oesteban You're going to need to merge/rebase master to fix the Docker builds. |
@oesteban Do you want to try to finish this up with Satra's suggestions this weekend, or just push off to another release? |
This pull request is "orphaned," which means it has been deemed to be abandoned by its original author. Orphaned pull requests have not been rejected, and we hope that if a user sees one that will meet their needs with a little work, that they will fork it and open a new pull request (or, in the case of the original author, reopen the original PR). We ask that all adopted PRs be updated to merge or rebase the current master. If you would like to adopt a PR and need help getting started, any of a number of contributors will be happy to help. |
Upranks the
bandpass_filter
implementation that we had within the example workflows to a fully fledged Nipype Interface.