def test_DTITracker_outputs(): output_map = dict(track_file=dict(), mask_file=dict(), ) outputs = DTITracker.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_DTITracker_outputs(): output_map = dict(mask_file=dict(), track_file=dict(), ) outputs = DTITracker.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_DTITracker_inputs(): input_map = dict( angle_threshold=dict(argstr='-at %f', ), angle_threshold_weight=dict(argstr='-atw %f', ), args=dict(argstr='%s', ), environ=dict( nohash=True, usedefault=True, ), ignore_exception=dict( nohash=True, usedefault=True, ), input_data_prefix=dict( argstr='%s', position=0, usedefault=True, ), input_type=dict(argstr='-it %s', ), invert_x=dict(argstr='-ix', ), invert_y=dict(argstr='-iy', ), invert_z=dict(argstr='-iz', ), mask1_file=dict( argstr='-m %s', mandatory=True, position=2, ), mask1_threshold=dict(position=3, ), mask2_file=dict( argstr='-m2 %s', position=4, ), mask2_threshold=dict(position=5, ), output_file=dict( argstr='%s', position=1, usedefault=True, ), output_mask=dict(argstr='-om %s', ), primary_vector=dict(argstr='-%s', ), random_seed=dict(argstr='-rseed', ), step_length=dict(argstr='-l %f', ), swap_xy=dict(argstr='-sxy', ), swap_yz=dict(argstr='-syz', ), swap_zx=dict(argstr='-szx', ), tensor_file=dict(), terminal_output=dict(nohash=True, ), tracking_method=dict(argstr='-%s', ), ) inputs = DTITracker.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_DTITracker_inputs(): input_map = dict(mask2_threshold=dict(position=5, ), input_data_prefix=dict(position=0, usedefault=True, argstr='%s', ), mask2_file=dict(position=4, argstr='-m2 %s', ), invert_y=dict(argstr='-iy', ), invert_x=dict(argstr='-ix', ), invert_z=dict(argstr='-iz', ), tensor_file=dict(), input_type=dict(argstr='-it %s', ), mask1_threshold=dict(position=3, ), output_file=dict(position=1, usedefault=True, argstr='%s', ), tracking_method=dict(argstr='-%s', ), step_length=dict(argstr='-l %f', ), output_mask=dict(argstr='-om %s', ), primary_vector=dict(argstr='-%s', ), ignore_exception=dict(nohash=True, usedefault=True, ), random_seed=dict(argstr='-rseed', ), args=dict(argstr='%s', ), angle_threshold_weight=dict(argstr='-atw %f', ), terminal_output=dict(mandatory=True, nohash=True, ), mask1_file=dict(position=2, mandatory=True, argstr='-m %s', ), angle_threshold=dict(argstr='-at %f', ), swap_zx=dict(argstr='-szx', ), swap_xy=dict(argstr='-sxy', ), environ=dict(nohash=True, usedefault=True, ), swap_yz=dict(argstr='-syz', ), ) inputs = DTITracker.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value