def test_ModelFit_outputs():
output_map = dict(fitted_data=dict(), )
outputs = ModelFit.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_ModelFit_outputs():
output_map = dict(fitted_data=dict(),
)
outputs = ModelFit.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_ModelFit_inputs():
input_map = dict(args=dict(argstr='%s',
),
bgmask=dict(argstr='-bgmask %s',
),
bgthresh=dict(argstr='-bgthresh %G',
),
cfthresh=dict(argstr='-csfthresh %G',
),
environ=dict(nohash=True,
usedefault=True,
),
fixedbvalue=dict(argstr='-fixedbvalue %s',
),
fixedmodq=dict(argstr='-fixedmod %s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='-inputfile %s',
mandatory=True,
),
inputdatatype=dict(argstr='-inputdatatype %s',
),
model=dict(argstr='-model %s',
mandatory=True,
),
noisemap=dict(argstr='-noisemap %s',
),
out_file=dict(argstr='> %s',
genfile=True,
position=-1,
),
outlier=dict(argstr='-outliermap %s',
),
outputfile=dict(argstr='-outputfile %s',
),
residualmap=dict(argstr='-residualmap %s',
),
scheme_file=dict(argstr='-schemefile %s',
mandatory=True,
),
sigma=dict(argstr='-sigma %G',
),
tau=dict(argstr='-tau %G',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = ModelFit.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_ModelFit_inputs():
input_map = dict(
args=dict(argstr='%s', ),
bgmask=dict(argstr='-bgmask %s', ),
bgthresh=dict(argstr='-bgthresh %G', ),
cfthresh=dict(argstr='-csfthresh %G', ),
environ=dict(
nohash=True,
usedefault=True,
),
fixedbvalue=dict(argstr='-fixedbvalue %s', ),
fixedmodq=dict(argstr='-fixedmod %s', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='-inputfile %s',
mandatory=True,
),
inputdatatype=dict(argstr='-inputdatatype %s', ),
model=dict(
argstr='-model %s',
mandatory=True,
),
noisemap=dict(argstr='-noisemap %s', ),
out_file=dict(
argstr='> %s',
genfile=True,
position=-1,
),
outlier=dict(argstr='-outliermap %s', ),
outputfile=dict(argstr='-outputfile %s', ),
residualmap=dict(argstr='-residualmap %s', ),
scheme_file=dict(
argstr='-schemefile %s',
mandatory=True,
),
sigma=dict(argstr='-sigma %G', ),
tau=dict(argstr='-tau %G', ),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = ModelFit.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
