Metadata-Version: 1.1
Name: niprov
Version: 0.5
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| |Code Quality|
        
        |Research software impact| |DOI| |Twitter|
        
        Ever encountered a file of which you weren’t sure what analysis steps it
        had gone through? Ever wanted to know what types of data you have
        available for a subject in one overview? Automatically document an
        analysis pipeline?
        
        Provenance is meta-data that tracks the ‘history’ of a file, and niprov
        is a python program to create, store and publish provenance for brain
        imaging files.
        
        A list with all provenance attributes collected can be found
        `here <http://niprov.readthedocs.org/en/latest/provenance-fields.html>`__.
        Read more in the `full online
        documentation <http://niprov.readthedocs.org/>`__ (or
        `pdf <https://media.readthedocs.org/pdf/niprov/latest/niprov.pdf>`__).
        For additional detailed information on image files, install
        ``nibabel``,\ ``mne`` and/or ``pydicom``.
        
        Commandline Usage
        -----------------
        
        Install niprov:
        
        .. code:: shell
        
            pip install niprov
        
        Look for existing image files in your data directory:
        
        .. code:: shell
        
            provenance discover /my/data/directory
        
        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
        
        Store provenance of known MEG files as an xml file:
        
        .. code:: shell
        
            provenance export --modality "MEG" --xml
        
        Python API
        ----------
        
        .. code:: python
        
            import niprov
            provenance = niprov.ProvenanceContext()
        
            # Log an analysis step:
            someAnalysisPackage.correctmotion(input='JD-fmri.nii', output='JD-fmri-3dmc.nii')
            provenance.log('JD-fmri.nii', 'motion correction', ['JD-fmri-3dmc.nii'])
        
            # Loop over images of John Smith and display a preview:
            for image in provenance.get().bySubject('John Smith'):
                image.viewSnapshot() 
        
            # Make sure two files were acquired with the same parameters:
            img1.compare(img2).assertEqualProtocol()
        
        Web browser
        -----------
        
        By running the command ``provenance serve`` you can start a mini
        webserver in the background, and browse images in your webbrowser:
        
        |niprov\_search| |niprov\_details| |niprov\_pipeline|
        
        .. |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
        .. |Code Quality| image:: https://scrutinizer-ci.com/g/ilogue/niprov/badges/quality-score.png?b=master
           :target: https://scrutinizer-ci.com/g/ilogue/niprov/?branch=master
        .. |Research software impact| image:: http://depsy.org/api/package/pypi/niprov/badge.svg
           :target: http://depsy.org/package/python/niprov
        .. |DOI| image:: https://zenodo.org/badge/doi/10.5281/zenodo.46136.svg
           :target: http://dx.doi.org/10.5281/zenodo.46136
        .. |Twitter| image:: https://img.shields.io/twitter/follow/niprovenance.svg?style=social
           :target: https://twitter.com/niprovenance
        .. |niprov\_search| image:: https://cloud.githubusercontent.com/assets/1508492/16635983/2c4c78fe-438a-11e6-868d-51d26c9956cf.png
        .. |niprov\_details| image:: https://cloud.githubusercontent.com/assets/1508492/16635948/f962ff1c-4389-11e6-958b-59a8fd9de9cd.png
        .. |niprov\_pipeline| image:: https://cloud.githubusercontent.com/assets/1508492/16635949/faa0c8b4-4389-11e6-87ae-87dce26c9973.png
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
