Remove multiline descriptions

Author: chrisgorgo

fmriprep/info.py

@@ -17,28 +17,8 @@
 __status__ = 'Prototype'
 __url__ = 'https://github.com/poldracklab/fmriprep'
 __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.
-"""
+__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."
 
 DOWNLOAD_URL = (
     'https://pypi.python.org/packages/source/{name[0]}/{name}/{name}-{ver}.tar.gz'.format(