def test_brain_atlas(self):
brain_atlas = BrainAtlas(self.atlas_name, "vec", rois=self.roi_list)
new_data = brain_atlas.transform(self.X)
self.assertTrue(len(self.X), len(brain_atlas.rois))
brain_atlas_mean = BrainAtlas(self.atlas_name, "mean", rois="all")
brain_atlas_mean.transform(self.X)
# Todo: how to compare?
debug = True
def test_brain_masker(self):
affine, shape = BrainMask.get_format_info_from_first_image(self.X)
atlas_obj = AtlasLibrary().get_atlas(self.atlas_name, affine, shape)
roi_objects = BrainAtlas._get_rois(atlas_obj, which_rois=self.roi_list, background_id=0)
for roi in roi_objects:
masker = BrainMask(mask_image=roi, affine=affine, shape=shape, extract_mode="vec")
own_calculation = masker.transform(self.X[0])
nilearn_func = NiftiMasker(mask_img=roi.mask, target_affine=affine, target_shape=shape, dtype='float32')
nilearn_calculation = nilearn_func.fit_transform(self.X[0])
self.assertTrue(np.array_equal(own_calculation, nilearn_calculation))
def test_validity_check_roi_extraction(self):
for atlas in AtlasLibrary().ATLAS_DICTIONARY.keys():
print("Checking atlas {}".format(atlas))
rois = AtlasLibrary().get_atlas(atlas).roi_list[1:3]
rois = [roi.label for roi in rois]
brain_atlas = BrainAtlas(atlas_name=atlas)
brain_atlas.rois = rois
X_t = brain_atlas.transform(self.X[0:2])
"-".join(rois)
name = os.path.join(self.test_folder, atlas + "_" + "-".join(rois))
brain_atlas._validity_check_roi_extraction(X_t[0], filename=name)
def _find_rois(element):
roi_list = element.base_element.rois
atlas_obj = AtlasLibrary().get_atlas(element.base_element.atlas_name)
roi_objects = BrainAtlas._get_rois(atlas_obj, roi_list)
return [roi.label for roi in roi_objects], atlas_obj