8000 WIP: Neuroscout related changes by adelavega · Pull Request #1 · effigies/fitlins · GitHub
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Merged
merged 4 commits into from
Dec 3, 2018

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adelavega
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@adelavega adelavega commented Nov 30, 2018
  • ModelSpecLoader is not working working when the model was specified as a string, rather than extract from the filesystem using BIDSLayout. I fix that here
    Not sure this will work w/ auto_model. Doesn't that return a dictionary (not a path, or json in string format)?
  • I need to be able to specify more than a single derivatives dir (neuroscout event files, fmriprep files) Changing fitlins to allow multiple derivatives, as in BIDSLayout

@adelavega adelavega changed the title Extract model paths from BIDSFile objects WIP: Neuroscout related changes Nov 30, 2018
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adelavega commented Dec 1, 2018

@effigies Let me know what you think about specifying arbitrary derivatives directories. They way I did it here is that you can keep passing derivatives to be indexed by pybids.

E.g. fitlins [other args] --derivatives = /my/fmriprep --derivatives= /my/events --derivatives = /maybe/something else
Those argument are put together into a list that is passed to BIDSLayout. If none is specified, the default is True, and all derivatives in bids_dir/derivatives are indexed. I suppose we can also allow None if the user doesn't want any derivatives to be indexed (although when would that be the case)?

Also, it would be syntactically nicer if we didn't have to repeated the --derivatives argument and just pass a list, but Im not sure how to do that w/ argparse.

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LGTM. One comment on the argument parser.

Co-Authored-By: adelavega <aleph4@gmail.com>
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If you want go ahead and merge and I can open up a new PR for any forthcoming changes... or I can keep going here up to you.

@effigies effigies merged commit 39f912f into effigies:mnt/dependency_updates Dec 3, 2018
@adelavega adelavega deleted the fix/modelstring branch December 3, 2018 18:33
effigies pushed a commit that referenced this pull request Mar 6, 2019
Sketch implementation of smoothing kernel in nistats
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