Metadata-Version: 2.1
Name: fsl-pyfeeds
Version: 0.9.1
Summary: FSL testing framework
Home-page: https://git.fmrib.ox.ac.uk/fsl/pyfeeds
Author: Paul McCarthy
Author-email: pauldmccarthy@gmail.com
License: Apache License Version 2.0
Description: # `pyfeeds`
        
        
        [![PyPi version](https://img.shields.io/pypi/v/fsl-pyfeeds.svg)](https://pypi.python.org/pypi/fsl-pyfeeds/) [![Anaconda version](https://anaconda.org/conda-forge/fsl-pyfeeds/badges/version.svg)](https://anaconda.org/conda-forge/fsl-pyfeeds/)
        [![Coverage report](https://git.fmrib.ox.ac.uk/fsl/pyfeeds/badges/master/coverage.svg)](https://git.fmrib.ox.ac.uk/fsl/pyfeeds/commits/master)
        
        ## The FSL Evaluation and Example Data Suite (FEEDS), now in Python!
        
        
        `pyfeeds` (the FMRIB Evaluation and Example Data Suite) is a framework for
        running and managing tests for the FSL code base.
        
        
        ### Test writers
        
        If you want to write a test for your project, check out the page on [how to
        write a `pyfeeds` test](doc/writing_a_test.md).
        
        
        ### `pyfeeds` users
        
        
        If you are going to be running `pyfeeds` tests, or are just interested, check
        out these pages:
        
          - [Using `pyfeeds`](doc/using_pyfeeds.md)
          - [Configuring `pyfeeds`](doc/configuring_pyfeeds.md)
          - [How `pyfeeds` works](doc/how_pyfeeds_works.md)
        
        
        ### Running the example tests
        
        
        To run the examples included with `pyfeeds`, you will need
        [FSL](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/) 5.0.9 or newer installed, and
        you will need to download the example and benchmark data sets from the
        `pyfeeds` [git repository](https://git.fmrib.ox.ac.uk/fsl/pyfeeds).
        
        Use the following commands to run the tests:
        
            exprs="*.nii.gz=evalImage"
            exprs="$exprs:dti_V?.nii.gz=evalVectorImage"
            exprs="$exprs:*.txt=evalNumericalText"
            exprs="$exprs:*.mat=evalNumericalText"
            pyfeeds run -e "$exprs" \
                -i exampleInputData \
                -b exampleBenchmarkData \
                -o exampleOutput examples
        
        | Note that the FEAT example test may not pass for you, as different versions
        | of FSL may produce slightly different results.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: Free for non-commercial use
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
