#  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.
#
# 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
# professionals having in-depth computer knowledge. Users are therefore
# encouraged to load and test the software's suitability as regards their
# requirements in conditions enabling the security of their systems and/or 
# data to be ensured and,  more generally, to use and operate it in the 
# same conditions as regards security.
#
# The fact that you are presently reading this means that you have had
# knowledge of the CeCILL license version 2 and that you accept its terms.

from brainvisa.processes import *
import registration

name ='Diffusion tensor'
userLevel = 1

fixedDT = 1

signature = Signature(
  't2_diffusion', ReadDiskItem( 'T2 Diffusion MR',
                                'Aims readable volume formats' ),
  'dw_diffusion', ReadDiskItem( 'DW Diffusion MR',
                                'Aims readable volume formats' ),
  'mask', ReadDiskItem( 'Diffusion Mask', 'Aims readable volume formats' ),
  'diffusion_model', WriteDiskItem( 'DTI Model', 'Bucket' ),
  'error_mask', WriteDiskItem( 'Error Mask', 'Aims writable volume formats' ),
)

def initialization( self ):
  self.linkParameters( 'dw_diffusion', 't2_diffusion' )
  self.linkParameters( 'mask', 't2_diffusion' )
  self.linkParameters( 'diffusion_model', 't2_diffusion' )
  self.linkParameters( 'error_mask', 'diffusion_model')
  
  self.setOptional( 'mask', 'error_mask' )

def execution( self, context ):
  command = [
   'comistFixedDTModel',
    '-verbose',
    '-t2', self.t2_diffusion,
    '-dw', self.dw_diffusion,
    '-o', self.diffusion_model,
  ]
  if self.mask is not None:
    command += [ '-m', self.mask ]
  if self.error_mask is not None:
    command += [ '-e', self.error_mask ]
  context.system( *command )
  volume_dimension = self.dw_diffusion.get( 'volume_dimension' )
  if volume_dimension is not None:
    self.diffusion_model.setMinf( 'volume_dimension', volume_dimension )
  else:
    raise AttributeError( 
                  _t_('No <em>volume_dimension</em> attribute in <em>%s</em>') %
                   ( self.dw_diffusion.fullPath(),) )

  # Set referentials of new objects
  trManager = registration.getTransformationManager()
  trManager.copyReferential( self.t2_diffusion, self.diffusion_model )
  trManager.copyReferential( self.t2_diffusion, self.error_mask )