Metadata-Version: 2.1
Name: arcana
Version: 2.0b0.dev7
Summary: Abstraction of Repository-Centric ANAlysis framework
Home-page: https://github.com/australian-imaging-service/arcana
Author: Thomas G. Close
Author-email: tom.g.close@gmail.com
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License
Description: Arcana
        ======
        .. image:: https://github.com/australian-imaging-service/arcana/actions/workflows/tests.yml/badge.svg
           :target: https://github.com/australian-imaging-service/arcana/actions/workflows/tests.yml
        .. image:: https://codecov.io/gh/australian-imaging-service/arcana/branch/main/graph/badge.svg?token=UIS0OGPST7
           :target: https://codecov.io/gh/australian-imaging-service/arcana
        .. .. image:: https://img.shields.io/pypi/pyversions/arcana.svg
        ..    :target: https://pypi.python.org/pypi/arcana/
        ..    :alt: Supported Python versions
        .. .. image:: https://img.shields.io/pypi/v/arcana.svg
        ..    :target: https://pypi.python.org/pypi/arcana/
        ..    :alt: Latest Version
        .. image:: https://readthedocs.org/projects/arcana/badge/?version=latest
          :target: http://arcana.readthedocs.io/en/latest/?badge=latest
          :alt: Documentation Status
        
        
        Abstraction of Repository-Centric ANAlysis (Arcana_) is Python framework
        for "repository-centric" analyses of study groups (e.g. NeuroImaging
        studies) built on Pydra_.
        
        Arcana_ interacts closely with a data store (e.g. XNAT repository or BIDS dataset),
        storing intermediate outputs, along with the parameters used to derive them,
        for reuse by subsequent analyses.
        
        Analysis workflows are constructed and executed using the Pydra_
        package, and can either be run locally or submitted to HPC
        schedulers using Pydra_'s execution plugins. For a requested analysis
        output, Arcana determines the required processing steps by querying
        the repository to check for missing intermediate outputs before
        constructing the workflow graph.
        
        Documentation
        -------------
        
        Detailed documentation on Arcana can be found at https://arcana.readthedocs.io
        
        Quick Installation
        ------------------
        
        Arcana can be installed for Python 3 using *pip*::
        
            $ pip3 install arcana
        
        .. _Arcana: http://arcana.readthedocs.io
        .. _Pydra: http://pydra.readthedocs.io
        .. _XNAT: http://xnat.org
        .. _BIDS: http://bids.neuroimaging.io/
        .. _`Environment Modules`: http://modules.sourceforge.net
        
        
        License
        -------
        
        This work is licensed under a
        `Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License <http://creativecommons.org/licenses/by-nc-sa/4.0/>`_
        
        .. image:: https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png
          :target: http://creativecommons.org/licenses/by-nc-sa/4.0/
          :alt: Creative Commons License: Attribution-NonCommercial-ShareAlike 4.0 International
        
        |
        
        *Note: For the legacy version of Arcana as described in
        Close TG, et. al. Neuroinformatics. 2020 18(1):109-129. doi:* `<10.1007/s12021-019-09430-1>`_
        *please see* `<https://github.com/MonashBI/arcana-legacy>`_.
        *Conceptually, the legacy version and the versions in this repository (>=2) are similar.
        However, instead of Nipype, v2 uses the Pydra workflow engine (Nipype's successor)
        and the syntax has been rewritten from scratch to make it more streamlined and intuitive.*
        
Keywords: repository analysis neuroimaging workflows pipelines
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Provides-Extra: test
Provides-Extra: dev
