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