Metadata-Version: 1.1
Name: niprov
Version: 0.3
Summary: provenance for neuroimaging data
Home-page: https://github.com/ilogue/niprov
Author: Jasper J.F. van den Bosch
Author-email: japsai@gmail.com
License: BSD
Description: niprov
        ======
        
        provenance for neuroimaging data
        
        |PyPI version| |Build| |Docs| |Coverage| |DOI| |Twitter|
        
        See the `full online documentation <http://niprov.readthedocs.org/>`__
        (or
        `pdf <https://media.readthedocs.org/pdf/niprov/latest/niprov.pdf>`__)
        and `PyPi package <https://pypi.python.org/pypi/niprov>`__ and follow
        `niprov on twitter <https://twitter.com/niprovenance>`__!
        
        To inspect image files, install ``nibabel``,\ ``mne`` and/or
        ``pydicom``.
        
        A list with all provenance attributes collected can be found
        `here <http://niprov.readthedocs.org/en/latest/provenance-fields.html>`__.
        
        Commandline Usage
        -----------------
        
        *Look for image files below the current directory, inspect them and
        store the obtained provenance metadata:*
        
        .. code:: shell
        
            provenance discover .
        
        *Run a transformation command and log it as provenance for the new
        file:*
        
        .. code:: shell
        
            provenance record mcflirt -in t1flip_all_orig -out t1all_reg -refvol 0
        
        *Alternatively, log the provenance after running the command:*
        
        .. code:: shell
        
            provenance log 'motion correction' --new fmri-3dmc.nii --parent fmri.nii 
        
        *Publish provenance of known files for subject 'John Doe' as an html
        file:*
        
        .. code:: shell
        
            provenance report --subject "John Doe" --html
        
        Python API
        ----------
        
        .. code:: python
        
            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')
        
        .. |PyPI version| image:: https://badge.fury.io/py/niprov.svg
           :target: http://badge.fury.io/py/niprov
        .. |Build| image:: https://travis-ci.org/ilogue/niprov.svg?branch=master
           :target: https://travis-ci.org/ilogue/niprov
        .. |Docs| image:: https://readthedocs.org/projects/niprov/badge/?version=latest
           :target: http://niprov.readthedocs.org/
        .. |Coverage| image:: https://img.shields.io/coveralls/ilogue/niprov.svg
           :target: https://coveralls.io/r/ilogue/niprov
        .. |DOI| image:: https://zenodo.org/badge/7344/ilogue/niprov.svg
           :target: http://dx.doi.org/10.5281/zenodo.13683
        .. |Twitter| image:: https://img.shields.io/twitter/follow/niprovenance.svg?style=social
           :target: https://twitter.com/niprovenance
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
