old_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
  # vi: set ft=python sts=4 ts=4 sw=4 et:
  """
  This pipeline is developed by the Poldrack lab at Stanford University
  (https://poldracklab.stanford.edu/) for use at
  the Center for Reproducible Neuroscience (http://reproducibility.stanford.edu/),
  as well as for open-source software distribution.
  """
  
  from .workflows.base import fmri_preprocess
  
  __version__ = '0.0.2'
  
  
  __author__ = 'The CRN developers'
  __copyright__ = 'Copyright 2016, Center for Reproducible Neuroscience, Stanford University'
  __credits__ = ['Craig Moodie', 'Ross Blair', 'Oscar Esteban', 'Chris F. Gorgolewski',
                 'Russell A. Poldrack']
  __license__ = '3-clause BSD'
  __maintainer__ = 'Oscar Esteban'
  __email__ = 'crn.poldracklab@gmail.com'
  __status__ = 'Prototype'
  __url__ = 'https://github.com/poldracklab/preprocessing-workflow'
  __packagename__ = 'fmriprep'
  
  __description__ = """Fmriprep is a functional magnetic resonance image pre-processing pipeline that
  is designed to provide an easily accessible, state-of-the-art interface that is robust to differences
  in scan acquisition protocols and that requires minimal user input, while providing easily interpretable
  and comprehensive error and output reporting."""
  __longdesc__ = """
  This package is a functional magnetic resonance image preprocessing pipeline that is designed to
  provide an easily accessible, state-of-the-art interface that is robust to differences in scan
  acquisition protocols and that requires minimal user input, while providing easily interpretable
  and comprehensive error and output reporting. This open-source neuroimaging data processing tool
  is being developed as a part of the MRI image analysis and reproducibility platform offered by the
  CRN. This pipeline is heavily influenced by the `Human Connectome Project analysis pipelines
  <https://github.com/Washington-University/Pipelines>`_ and, as such, the backbone of this pipeline
  is a python reimplementation of the HCP `GenericfMRIVolumeProcessingPipeline.sh` script. However, a
  major difference is that this pipeline is executed using a `nipype workflow framework
  <http://nipype.readthedocs.io/en/latest/>`_. This allows for each call to a software module or binary
  to be controlled within the workflows, which removes the need for manual curation at every stage, while
  still providing all the output and error information that would be necessary for debugging and interpretation
  purposes. The fmriprep pipeline primarily utilizes FSL tools, but also utilizes ANTs tools at several stages
  such as skull stripping and template registration. This pipeline was designed to provide the best software
  implementation for each state of preprocessing, and will be updated as newer and better neuroimaging software
  become available.
  """
  
new_contents: #!/usr/bin/env python
  # -*- coding: utf-8 -*-
  # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
  # vi: set ft=python sts=4 ts=4 sw=4 et:
  """
  This pipeline is developed by the Poldrack lab at Stanford University
  (https://poldracklab.stanford.edu/) for use at
  the Center for Reproducible Neuroscience (http://reproducibility.stanford.edu/),
  as well as for open-source software distribution.
  """
  
  from .workflows.base import fmri_preprocess
  
  __version__ = '0.0.2'
  
  
  __author__ = 'The CRN developers'
  __copyright__ = 'Copyright 2016, Center for Reproducible Neuroscience, Stanford University'
  __credits__ = ['Craig Moodie', 'Ross Blair', 'Oscar Esteban', 'Chris F. Gorgolewski',
                 'Russell A. Poldrack']
  __license__ = '3-clause BSD'
  __maintainer__ = 'Ross Blair'
  __email__ = 'crn.poldracklab@gmail.com'
  __status__ = 'Prototype'
  __url__ = 'https://github.com/poldracklab/preprocessing-workflow'
  __packagename__ = 'fmriprep'
  
  __description__ = """Fmriprep is a functional magnetic resonance image pre-processing pipeline that
  is designed to provide an easily accessible, state-of-the-art interface that is robust to differences
  in scan acquisition protocols and that requires minimal user input, while providing easily interpretable
  and comprehensive error and output reporting."""
  __longdesc__ = """
  This package is a functional magnetic resonance image preprocessing pipeline that is designed to
  provide an easily accessible, state-of-the-art interface that is robust to differences in scan
  acquisition protocols and that requires minimal user input, while providing easily interpretable
  and comprehensive error and output reporting. This open-source neuroimaging data processing tool
  is being developed as a part of the MRI image analysis and reproducibility platform offered by the
  CRN. This pipeline is heavily influenced by the `Human Connectome Project analysis pipelines
  <https://github.com/Washington-University/Pipelines>`_ and, as such, the backbone of this pipeline
  is a python reimplementation of the HCP `GenericfMRIVolumeProcessingPipeline.sh` script. However, a
  major difference is that this pipeline is executed using a `nipype workflow framework
  <http://nipype.readthedocs.io/en/latest/>`_. This allows for each call to a software module or binary
  to be controlled within the workflows, which removes the need for manual curation at every stage, while
  still providing all the output and error information that would be necessary for debugging and interpretation
  purposes. The fmriprep pipeline primarily utilizes FSL tools, but also utilizes ANTs tools at several stages
  such as skull stripping and template registration. This pipeline was designed to provide the best software
  implementation for each state of preprocessing, and will be updated as newer and better neuroimaging software
  become available.
  """
  
subject: change maintainer