def test_CoherenceAnalyzer_outputs():
output_map = dict(coherence_array=dict(),
coherence_csv=dict(),
coherence_fig=dict(),
timedelay_array=dict(),
timedelay_csv=dict(),
timedelay_fig=dict(),
)
outputs = CoherenceAnalyzer.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_CoherenceAnalyzer_outputs():
output_map = dict(
coherence_array=dict(),
coherence_csv=dict(),
coherence_fig=dict(),
timedelay_array=dict(),
timedelay_csv=dict(),
timedelay_fig=dict(),
)
outputs = CoherenceAnalyzer.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_CoherenceAnalyzer_inputs():
input_map = dict(
NFFT=dict(usedefault=True, ),
TR=dict(),
figure_type=dict(usedefault=True, ),
frequency_range=dict(usedefault=True, ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_TS=dict(),
in_file=dict(requires=('TR', ), ),
n_overlap=dict(usedefault=True, ),
output_csv_file=dict(),
output_figure_file=dict(),
)
inputs = CoherenceAnalyzer.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_CoherenceAnalyzer_inputs():
input_map = dict(NFFT=dict(usedefault=True,
),
TR=dict(),
figure_type=dict(usedefault=True,
),
frequency_range=dict(usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_TS=dict(),
in_file=dict(requires=('TR',),
),
n_overlap=dict(usedefault=True,
),
output_csv_file=dict(),
output_figure_file=dict(),
)
inputs = CoherenceAnalyzer.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value