def test_BrainMapDecoder_failure(testdata_laird):
"""
Smoke test for discrete.BrainMapDecoder where there are no features left.
"""
decoder = discrete.BrainMapDecoder(features=["doggy"])
with pytest.raises(Exception):
decoder.fit(testdata_laird)
def test_BrainMapDecoder(testdata_laird):
"""Smoke test for discrete.BrainMapDecoder."""
ids = testdata_laird.ids[:5]
labels = testdata_laird.get_labels(ids=testdata_laird.ids)
decoder = discrete.BrainMapDecoder(features=labels)
decoder.fit(testdata_laird)
decoded_df = decoder.transform(ids=ids)
assert isinstance(decoded_df, pd.DataFrame)
assert decoded_df.shape == (len(labels), 6)
def test_BrainMapDecoder(testdata_laird):
"""
Smoke test for discrete.BrainMapDecoder
"""
ids = testdata_laird.ids[:5]
decoder = discrete.BrainMapDecoder()
decoder.fit(testdata_laird)
decoded_df = decoder.transform(ids=ids)
assert isinstance(decoded_df, pd.DataFrame)
arr[65:75, 50:60, 50:60] = 1 mask_img = nib.Nifti1Image(arr, dset.masker.mask_img.affine) plot_roi(mask_img, draw_cross=False) # Get studies with voxels in the mask ids = dset.get_studies_by_mask(mask_img) ############################################################################### # # .. _brain-map-decoder-example: # # Decode an ROI image using the BrainMap method # ----------------------------------------------------------------------------- # Run the decoder decoder = discrete.BrainMapDecoder(correction=None) decoder.fit(dset) decoded_df = decoder.transform(ids=ids) decoded_df.sort_values(by="probReverse", ascending=False).head() ############################################################################### # # .. _neurosynth-chi2-decoder-example: # # Decode an ROI image using the Neurosynth chi-square method # ----------------------------------------------------------------------------- # Run the decoder decoder = discrete.NeurosynthDecoder(correction=None) decoder.fit(dset) decoded_df = decoder.transform(ids=ids)