# -*- coding: utf-8 -*-
#  This software and supporting documentation are distributed by
#      Institut Federatif de Recherche 49
#      CEA/NeuroSpin, Batiment 145,
#      91191 Gif-sur-Yvette cedex
#      France
#
# This software is governed by the CeCILL license version 2 under
# French law and abiding by the rules of distribution of free software.
# You can  use, modify and/or redistribute the software under the 
# terms of the CeCILL license version 2 as circulated by CEA, CNRS
# and INRIA at the following URL "http://www.cecill.info". 
#
# As a counterpart to the access to the source code and  rights to copy,
# modify and redistribute granted by the license, users are provided only
# with a limited warranty  and the software's author,  the holder of the
# economic rights,  and the successive licensors  have only  limited
# liability.
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# In this respect, the user's attention is drawn to the risks associated
# with loading,  using,  modifying and/or developing or reproducing the
# software by the user in light of its specific status of free software,
# that may mean  that it is complicated to manipulate,  and  that  also
# therefore means  that it is reserved for developers  and  experienced
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# same conditions as regards security.
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# knowledge of the CeCILL license version 2 and that you accept its terms.

from brainvisa.processes import *

name = 'Diffusion Bundles Analysis'
userLevel = 1

signature=Signature(
  'bundles', ReadDiskItem( 'Fascicles bundles', 'Aims bundles' ),
  'bundles_transformation', ReadDiskItem( 'Transformation matrix','Transformation matrix' ),
  'minimum_length', Float(),
  'slices', Integer(),
  'apparent_diffusion_coefficient', ReadDiskItem( 
                                               'Apparent Diffusion Coefficient',
                                               'Aims readable volume formats' ),
  'fractional_anisotropy', ReadDiskItem( 'Fractional Anisotropy',
                                          'Aims readable volume formats' ),
  'volume_ratio', ReadDiskItem( 'Volume Ratio', 'Aims readable volume formats' ),
  'standard_deviation', ReadDiskItem( 'Diffusion Standard Deviation',
                                       'Aims readable volume formats' ),
  'diffusion_weighted_t2', ReadDiskItem( 'Diffusion Weighted T2',
                                          'Aims readable volume formats' ),
  'statistics', WriteDiskItem( 'Bundles scalar features', 'Aims scalar features' ),
)


def initialization( self ):
  self.linkParameters( 'statistics', 'bundles' )
  self.setOptional( 'bundles_transformation' )
  self.slices = 50
  self.linkParameters( 'apparent_diffusion_coefficient', 'bundles' )
  self.linkParameters( 'fractional_anisotropy', 'bundles' )
  self.linkParameters( 'volume_ratio', 'bundles' )
  self.linkParameters( 'standard_deviation', 'bundles' )
  self.linkParameters( 'diffusion_weighted_t2', 'bundles' )
  self.setOptional( 'minimum_length',
                    'slices',
                    'apparent_diffusion_coefficient',
                    'fractional_anisotropy',
                    'volume_ratio',
                    'standard_deviation',
                    'diffusion_weighted_t2' )
 
def execution( self, context ):
  command = [ 'comistBundleAnalysis_old',
              '--verbose',
              '-i', self.bundles,
              '-o', self.statistics,
            ]
  if self.bundles_transformation is not None:
    command += [ '-t', self.bundles_transformation ]
  if self.minimum_length > 0:
    command += [ '--minimumLength', self.minimum_length ]
  imageStatistics = []
  if self.slices > 0:
    command += [ '--slices', self.slices ]
  if self.apparent_diffusion_coefficient is not None:
    imageStatistics += [ 'adc:' + self.apparent_diffusion_coefficient.fullPath() ]
  if self.fractional_anisotropy is not None:
    imageStatistics += [ 'fa:' + self.fractional_anisotropy.fullPath() ]
  if self.volume_ratio is not None:
    imageStatistics += [ 'vr:' + self.volume_ratio.fullPath() ]
  if self.standard_deviation is not None:
    imageStatistics += [ 'stddev:' + self.standard_deviation.fullPath() ]
  if self.diffusion_weighted_t2 is not None:
    imageStatistics += [ 'dwt2:' + self.diffusion_weighted_t2.fullPath() ]
  if imageStatistics:
    command += [ '--imageStatistics' ] + imageStatistics
  context.system( *command )