provenance for neuroimaging data
See the full online documentation (or pdf) and PyPi package.
To inspect image files, install nibabel,mne and/or pydicom.
A list with all provenance attributes collected can be found here.
Commandline Usage
Look for image files below the current directory, inspect them and store the obtained provenance metadata:
provenance discover .Run a transformation command and log it as provenance for the new file:
provenance record mcflirt -in t1flip_all_orig -out t1all_reg -refvol 0Alternatively, log the provenance after running the command:
provenance log 'motion correction' --new fmri-3dmc.nii --parent fmri.niiPublish provenance of known files for subject ‘John Doe’ as an html file:
provenance report --subject "John Doe" --htmlPython API
import niprov
niprov.discover('.')
analysispackage.correctmotion(input='JD-fmri.nii', output='JD-fmri-3dmc.nii')
niprov.log('JD-fmri.nii', 'motion correction', ['JD-fmri-3dmc.nii'])
niprov.record('mcflirt -in t1flip_all_orig -out t1all_reg -refvol 0')
files = niprov.report(forSubject='John Doe')1 maintainer
Metadata
1 maintainer
Release files for niprov 0.1.post6
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| niprov-0.1.post6.tar.gz | 29.5 kB | Details |
Release files / niprov-0.1.post6.tar.gz
| Download URL | niprov-0.1.post6.tar.gz |
|---|---|
| Size | 29.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
0f1968b1c39aef5504bb579fa608edfc0543a5fe861e5499c1da0850a679bdf3
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BLAKE2b-256 checksum How to use checksums |
a8ecf322b9c1f63fd4f6e84ad5e44c08d34a3215d4cd50b17021a62eb51bd8dc
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