def test_ConstrainedSphericalDeconvolution_outputs(): output_map = dict(spherical_harmonics_image=dict(), ) outputs = ConstrainedSphericalDeconvolution.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_ConstrainedSphericalDeconvolution_inputs(): input_map = dict( args=dict(argstr='%s', ), debug=dict(argstr='-debug', ), directions_file=dict( argstr='-directions %s', position=-2, ), encoding_file=dict( argstr='-grad %s', position=1, ), environ=dict( nohash=True, usedefault=True, ), filter_file=dict( argstr='-filter %s', position=-2, ), ignore_exception=dict( nohash=True, usedefault=True, ), in_file=dict( argstr='%s', mandatory=True, position=-3, ), iterations=dict(argstr='-niter %s', ), lambda_value=dict(argstr='-lambda %s', ), mask_image=dict( argstr='-mask %s', position=2, ), maximum_harmonic_order=dict(argstr='-lmax %s', ), normalise=dict( argstr='-normalise', position=3, ), out_filename=dict( argstr='%s', genfile=True, position=-1, ), response_file=dict( argstr='%s', mandatory=True, position=-2, ), terminal_output=dict(nohash=True, ), threshold_value=dict(argstr='-threshold %s', ), ) inputs = ConstrainedSphericalDeconvolution.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_ConstrainedSphericalDeconvolution_inputs(): input_map = dict(args=dict(argstr='%s', ), debug=dict(argstr='-debug', ), directions_file=dict(argstr='-directions %s', position=-2, ), encoding_file=dict(argstr='-grad %s', position=1, ), environ=dict(nohash=True, usedefault=True, ), filter_file=dict(argstr='-filter %s', position=-2, ), ignore_exception=dict(nohash=True, usedefault=True, ), in_file=dict(argstr='%s', mandatory=True, position=-3, ), iterations=dict(argstr='-niter %s', ), lambda_value=dict(argstr='-lambda %s', ), mask_image=dict(argstr='-mask %s', position=2, ), maximum_harmonic_order=dict(argstr='-lmax %s', ), normalise=dict(argstr='-normalise', position=3, ), out_filename=dict(argstr='%s', genfile=True, position=-1, ), response_file=dict(argstr='%s', mandatory=True, position=-2, ), terminal_output=dict(mandatory=True, nohash=True, ), threshold_value=dict(argstr='-threshold %s', ), ) inputs = ConstrainedSphericalDeconvolution.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value