def test_N4ITKBiasFieldCorrection_outputs(): output_map = dict(outputbiasfield=dict(), outputimage=dict(), ) outputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_outputs(): output_map = dict( outputbiasfield=dict(), outputimage=dict(), ) outputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_inputs(): input_map = dict( args=dict(argstr='%s', ), bsplineorder=dict(argstr='--bsplineorder %d', ), convergencethreshold=dict(argstr='--convergencethreshold %f', ), environ=dict( nohash=True, usedefault=True, ), histogramsharpening=dict( argstr='--histogramsharpening %s', sep=',', ), ignore_exception=dict( nohash=True, usedefault=True, ), inputimage=dict(argstr='--inputimage %s', ), iterations=dict( argstr='--iterations %s', sep=',', ), maskimage=dict(argstr='--maskimage %s', ), meshresolution=dict( argstr='--meshresolution %s', sep=',', ), outputbiasfield=dict( argstr='--outputbiasfield %s', hash_files=False, ), outputimage=dict( argstr='--outputimage %s', hash_files=False, ), shrinkfactor=dict(argstr='--shrinkfactor %d', ), splinedistance=dict(argstr='--splinedistance %f', ), terminal_output=dict( mandatory=True, nohash=True, ), weightimage=dict(argstr='--weightimage %s', ), ) inputs = N4ITKBiasFieldCorrection.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_N4ITKBiasFieldCorrection_inputs(): input_map = dict(args=dict(argstr='%s', ), bsplineorder=dict(argstr='--bsplineorder %d', ), convergencethreshold=dict(argstr='--convergencethreshold %f', ), environ=dict(nohash=True, usedefault=True, ), histogramsharpening=dict(argstr='--histogramsharpening %s', sep=',', ), ignore_exception=dict(nohash=True, usedefault=True, ), inputimage=dict(argstr='--inputimage %s', ), iterations=dict(argstr='--iterations %s', sep=',', ), maskimage=dict(argstr='--maskimage %s', ), meshresolution=dict(argstr='--meshresolution %s', sep=',', ), outputbiasfield=dict(argstr='--outputbiasfield %s', hash_files=False, ), outputimage=dict(argstr='--outputimage %s', hash_files=False, ), shrinkfactor=dict(argstr='--shrinkfactor %d', ), splinedistance=dict(argstr='--splinedistance %f', ), terminal_output=dict(mandatory=True, nohash=True, ), weightimage=dict(argstr='--weightimage %s', ), ) inputs = N4ITKBiasFieldCorrection.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value