def test_StreamlineTrack_outputs(): output_map = dict(tracked=dict(), ) outputs = StreamlineTrack.output_spec() for key, metadata in output_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_StreamlineTrack_inputs(): input_map = dict(do_not_precompute=dict(argstr='-noprecomputed', ), maximum_number_of_tracks=dict(argstr='-maxnum %d', ), exclude_file=dict(position=2, argstr='-exclude %s', ), cutoff_value=dict(units='NA', argstr='-cutoff %s', ), seed_file=dict(position=2, argstr='-seed %s', ), step_size=dict(units='mm', argstr='-step %s', ), in_file=dict(position=-2, mandatory=True, argstr='%s', ), environ=dict(nohash=True, usedefault=True, ), no_mask_interpolation=dict(argstr='-nomaskinterp', ), ignore_exception=dict(nohash=True, usedefault=True, ), include_file=dict(position=2, argstr='-include %s', ), maximum_tract_length=dict(units='mm', argstr='-length %s', ), args=dict(argstr='%s', ), stop=dict(argstr='-gzip', ), minimum_radius_of_curvature=dict(units='mm', argstr='-curvature %s', ), inputmodel=dict(position=-3, usedefault=True, argstr='%s', ), initial_direction=dict(units='voxels', argstr='-initdirection %s', ), exclude_spec=dict(sep=',', units='mm', position=2, argstr='-seed %s', ), desired_number_of_tracks=dict(argstr='-number %d', ), seed_spec=dict(sep=',', units='mm', position=2, argstr='-seed %s', ), initial_cutoff_value=dict(units='NA', argstr='-initcutoff %s', ), minimum_tract_length=dict(units='mm', argstr='-minlength %s', ), mask_spec=dict(sep=',', units='mm', position=2, argstr='-seed %s', ), out_file=dict(position=-1, genfile=True, argstr='%s', ), include_spec=dict(sep=',', units='mm', position=2, argstr='-seed %s', ), terminal_output=dict(mandatory=True, nohash=True, ), unidirectional=dict(argstr='-unidirectional', ), mask_file=dict(position=2, argstr='-exclude %s', ), ) inputs = StreamlineTrack.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_StreamlineTrack_inputs(): input_map = dict( args=dict(argstr='%s', ), cutoff_value=dict( argstr='-cutoff %s', units='NA', ), desired_number_of_tracks=dict(argstr='-number %d', ), do_not_precompute=dict(argstr='-noprecomputed', ), environ=dict( nohash=True, usedefault=True, ), exclude_file=dict( argstr='-exclude %s', xor=['exclude_file', 'exclude_spec'], ), exclude_spec=dict( argstr='-exclude %s', position=2, sep=',', units='mm', xor=['exclude_file', 'exclude_spec'], ), ignore_exception=dict( nohash=True, usedefault=True, ), in_file=dict( argstr='%s', mandatory=True, position=-2, ), include_file=dict( argstr='-include %s', xor=['include_file', 'include_spec'], ), include_spec=dict( argstr='-include %s', position=2, sep=',', units='mm', xor=['include_file', 'include_spec'], ), initial_cutoff_value=dict( argstr='-initcutoff %s', units='NA', ), initial_direction=dict( argstr='-initdirection %s', units='voxels', ), inputmodel=dict( argstr='%s', position=-3, usedefault=True, ), mask_file=dict( argstr='-mask %s', xor=['mask_file', 'mask_spec'], ), mask_spec=dict( argstr='-mask %s', position=2, sep=',', units='mm', xor=['mask_file', 'mask_spec'], ), maximum_number_of_tracks=dict(argstr='-maxnum %d', ), maximum_tract_length=dict( argstr='-length %s', units='mm', ), minimum_radius_of_curvature=dict( argstr='-curvature %s', units='mm', ), minimum_tract_length=dict( argstr='-minlength %s', units='mm', ), no_mask_interpolation=dict(argstr='-nomaskinterp', ), out_file=dict( argstr='%s', name_source=['in_file'], name_template='%s_tracked.tck', output_name='tracked', position=-1, ), seed_file=dict( argstr='-seed %s', xor=['seed_file', 'seed_spec'], ), seed_spec=dict( argstr='-seed %s', position=2, sep=',', units='mm', xor=['seed_file', 'seed_spec'], ), step_size=dict( argstr='-step %s', units='mm', ), stop=dict(argstr='-stop', ), terminal_output=dict( mandatory=True, nohash=True, ), unidirectional=dict(argstr='-unidirectional', ), ) inputs = StreamlineTrack.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value