def test_TCorrMap_outputs():
output_map = dict(absolute_threshold=dict(),
zmean=dict(),
var_absolute_threshold_normalize=dict(),
correlation_maps_masked=dict(),
var_absolute_threshold=dict(),
mean_file=dict(),
pmean=dict(),
histogram=dict(),
sum_expr=dict(),
average_expr_nonzero=dict(),
average_expr=dict(),
correlation_maps=dict(),
qmean=dict(),
)
outputs = TCorrMap.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_TCorrMap_outputs():
output_map = dict(absolute_threshold=dict(),
average_expr=dict(),
average_expr_nonzero=dict(),
correlation_maps=dict(),
correlation_maps_masked=dict(),
histogram=dict(),
mean_file=dict(),
pmean=dict(),
qmean=dict(),
sum_expr=dict(),
var_absolute_threshold=dict(),
var_absolute_threshold_normalize=dict(),
zmean=dict(),
)
outputs = TCorrMap.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_TCorrMap_inputs():
input_map = dict(
absolute_threshold=dict(
argstr='-Thresh %f %s',
name_source='in_file',
suffix='_thresh',
xor=('absolute_threshold', 'var_absolute_threshold',
'var_absolute_threshold_normalize'),
),
args=dict(argstr='%s', ),
automask=dict(argstr='-automask', ),
average_expr=dict(
argstr='-Aexpr %s %s',
name_source='in_file',
suffix='_aexpr',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
),
average_expr_nonzero=dict(
argstr='-Cexpr %s %s',
name_source='in_file',
suffix='_cexpr',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
),
bandpass=dict(argstr='-bpass %f %f', ),
blur_fwhm=dict(argstr='-Gblur %f', ),
correlation_maps=dict(
argstr='-CorrMap %s',
name_source='in_file',
),
correlation_maps_masked=dict(
argstr='-CorrMask %s',
name_source='in_file',
),
environ=dict(
nohash=True,
usedefault=True,
),
expr=dict(),
histogram=dict(
argstr='-Hist %d %s',
name_source='in_file',
suffix='_hist',
),
histogram_bin_numbers=dict(),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='-input %s',
copyfile=False,
mandatory=True,
),
mask=dict(argstr='-mask %s', ),
mean_file=dict(
argstr='-Mean %s',
name_source='in_file',
suffix='_mean',
),
out_file=dict(
argstr='-prefix %s',
name_source=['in_file'],
name_template='%s_afni',
),
outputtype=dict(),
pmean=dict(
argstr='-Pmean %s',
name_source='in_file',
suffix='_pmean',
),
polort=dict(argstr='-polort %d', ),
qmean=dict(
argstr='-Qmean %s',
name_source='in_file',
suffix='_qmean',
),
regress_out_timeseries=dict(argstr='-ort %s', ),
seeds=dict(
argstr='-seed %s',
xor='seeds_width',
),
seeds_width=dict(
argstr='-Mseed %f',
xor='seeds',
),
sum_expr=dict(
argstr='-Sexpr %s %s',
name_source='in_file',
suffix='_sexpr',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
thresholds=dict(),
var_absolute_threshold=dict(
argstr='-VarThresh %f %f %f %s',
name_source='in_file',
suffix='_varthresh',
xor=('absolute_threshold', 'var_absolute_threshold',
'var_absolute_threshold_normalize'),
),
var_absolute_threshold_normalize=dict(
argstr='-VarThreshN %f %f %f %s',
name_source='in_file',
suffix='_varthreshn',
xor=('absolute_threshold', 'var_absolute_threshold',
'var_absolute_threshold_normalize'),
),
zmean=dict(
argstr='-Zmean %s',
name_source='in_file',
suffix='_zmean',
),
)
inputs = TCorrMap.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_TCorrMap_inputs():
input_map = dict(
polort=dict(argstr="-polort %d"),
zmean=dict(name_source="in_file", suffix="_zmean", argstr="-Zmean %s"),
correlation_maps_masked=dict(name_source="in_file", argstr="-CorrMask %s"),
thresholds=dict(),
outputtype=dict(),
average_expr_nonzero=dict(
name_source="in_file",
xor=("average_expr", "average_expr_nonzero", "sum_expr"),
suffix="_cexpr",
argstr="-Cexpr %s %s",
),
seeds_width=dict(xor="seeds", argstr="-Mseed %f"),
qmean=dict(name_source="in_file", suffix="_qmean", argstr="-Qmean %s"),
pmean=dict(name_source="in_file", suffix="_pmean", argstr="-Pmean %s"),
in_file=dict(copyfile=False, mandatory=True, argstr="-input %s"),
ignore_exception=dict(nohash=True, usedefault=True),
var_absolute_threshold=dict(
name_source="in_file",
xor=("absolute_threshold", "var_absolute_threshold", "var_absolute_threshold_normalize"),
suffix="_varthresh",
argstr="-VarThresh %f %f %f %s",
),
absolute_threshold=dict(
name_source="in_file",
xor=("absolute_threshold", "var_absolute_threshold", "var_absolute_threshold_normalize"),
suffix="_thresh",
argstr="-Thresh %f %s",
),
automask=dict(argstr="-automask"),
args=dict(argstr="%s"),
histogram=dict(name_source="in_file", suffix="_hist", argstr="-Hist %d %s"),
terminal_output=dict(mandatory=True, nohash=True),
average_expr=dict(
name_source="in_file",
xor=("average_expr", "average_expr_nonzero", "sum_expr"),
suffix="_aexpr",
argstr="-Aexpr %s %s",
),
blur_fwhm=dict(argstr="-Gblur %f"),
var_absolute_threshold_normalize=dict(
name_source="in_file",
xor=("absolute_threshold", "var_absolute_threshold", "var_absolute_threshold_normalize"),
suffix="_varthreshn",
argstr="-VarThreshN %f %f %f %s",
),
out_file=dict(name_source=["in_file"], name_template="%s_afni", argstr="-prefix %s"),
expr=dict(),
mask=dict(argstr="-mask %s"),
mean_file=dict(name_source="in_file", suffix="_mean", argstr="-Mean %s"),
sum_expr=dict(
name_source="in_file",
xor=("average_expr", "average_expr_nonzero", "sum_expr"),
suffix="_sexpr",
argstr="-Sexpr %s %s",
),
regress_out_timeseries=dict(argstr="-ort %s"),
seeds=dict(xor="seeds_width", argstr="-seed %s"),
environ=dict(nohash=True, usedefault=True),
correlation_maps=dict(name_source="in_file", argstr="-CorrMap %s"),
histogram_bin_numbers=dict(),
bandpass=dict(argstr="-bpass %f %f"),
)
inputs = TCorrMap.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_TCorrMap_inputs():
input_map = dict(polort=dict(argstr='-polort %d',
),
zmean=dict(name_source='in_file',
suffix='_zmean',
argstr='-Zmean %s',
),
correlation_maps_masked=dict(name_source='in_file',
argstr='-CorrMask %s',
),
thresholds=dict(),
outputtype=dict(),
average_expr_nonzero=dict(name_source='in_file',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
suffix='_cexpr',
argstr='-Cexpr %s %s',
),
seeds_width=dict(xor='seeds',
argstr='-Mseed %f',
),
qmean=dict(name_source='in_file',
suffix='_qmean',
argstr='-Qmean %s',
),
pmean=dict(name_source='in_file',
suffix='_pmean',
argstr='-Pmean %s',
),
in_file=dict(mandatory=True,
argstr='-input %s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
var_absolute_threshold=dict(name_source='in_file',
xor=('absolute_threshold', 'var_absolute_threshold', 'var_absolute_threshold_normalize'),
suffix='_varthresh',
argstr='-VarThresh %f %f %f %s',
),
absolute_threshold=dict(name_source='in_file',
xor=('absolute_threshold', 'var_absolute_threshold', 'var_absolute_threshold_normalize'),
suffix='_thresh',
argstr='-Thresh %f %s',
),
automask=dict(argstr='-automask',
),
args=dict(argstr='%s',
),
histogram=dict(name_source='in_file',
suffix='_hist',
argstr='-Hist %d %s',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
average_expr=dict(name_source='in_file',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
suffix='_aexpr',
argstr='-Aexpr %s %s',
),
blur_fwhm=dict(argstr='-Gblur %f',
),
var_absolute_threshold_normalize=dict(name_source='in_file',
xor=('absolute_threshold', 'var_absolute_threshold', 'var_absolute_threshold_normalize'),
suffix='_varthreshn',
argstr='-VarThreshN %f %f %f %s',
),
out_file=dict(name_source=['in_file'],
name_template='%s_afni',
argstr='-prefix %s',
),
expr=dict(),
mask=dict(argstr='-mask %s',
),
mean_file=dict(name_source='in_file',
suffix='_mean',
argstr='-Mean %s',
),
sum_expr=dict(name_source='in_file',
xor=('average_expr', 'average_expr_nonzero', 'sum_expr'),
suffix='_sexpr',
argstr='-Sexpr %s %s',
),
regress_out_timeseries=dict(argstr='-ort %s',
),
seeds=dict(xor='seeds_width',
argstr='-seed %s',
),
environ=dict(nohash=True,
usedefault=True,
),
correlation_maps=dict(name_source='in_file',
argstr='-CorrMap %s',
),
histogram_bin_numbers=dict(),
bandpass=dict(argstr='-bpass %f %f',
),
)
inputs = TCorrMap.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value