def test_Tensor2ApparentDiffusion_outputs(): output_map = dict(ADC=dict(), ) outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs(): input_map = dict(args=dict(argstr='%s', ), debug=dict(argstr='-debug', position=1, ), environ=dict(nohash=True, usedefault=True, ), ignore_exception=dict(nohash=True, usedefault=True, ), in_file=dict(argstr='%s', mandatory=True, position=-2, ), out_filename=dict(argstr='%s', genfile=True, position=-1, ), quiet=dict(argstr='-quiet', position=1, ), terminal_output=dict(mandatory=True, nohash=True, ), ) inputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_outputs(): output_map = dict(ADC=dict(), ) outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs(): input_map = dict( args=dict(argstr='%s', ), debug=dict( argstr='-debug', position=1, ), environ=dict( nohash=True, usedefault=True, ), ignore_exception=dict( nohash=True, usedefault=True, ), in_file=dict( argstr='%s', mandatory=True, position=-2, ), out_filename=dict( argstr='%s', genfile=True, position=-1, ), quiet=dict( argstr='-quiet', position=1, ), terminal_output=dict( mandatory=True, nohash=True, ), ) inputs = Tensor2ApparentDiffusion.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value