def test_masker_attributes_with_fit():
# Test base module at sub-class
data, mask_img, components, rng = _make_canica_test_data(n_subjects=3)
# Passing mask_img
canica = CanICA(n_components=3, mask=mask_img, random_state=0)
canica.fit(data)
assert canica.mask_img_ == mask_img
assert canica.mask_img_ == canica.masker_.mask_img_
# Passing masker
masker = MultiNiftiMasker(mask_img=mask_img)
canica = CanICA(n_components=3, mask=masker, random_state=0)
canica.fit(data)
assert canica.mask_img_ == canica.masker_.mask_img_
canica = CanICA(mask=mask_img, n_components=3)
with pytest.raises(ValueError,
match="Object has no components_ attribute. "
"This is probably because fit has not been called"):
canica.transform(data)
# Test if raises an error when empty list of provided.
with pytest.raises(ValueError,
match='Need one or more Niimg-like objects as input, '
'an empty list was given.'):
canica.fit([])
# Test passing masker arguments to estimator
canica = CanICA(n_components=3,
target_affine=np.eye(4),
target_shape=(6, 8, 10),
mask_strategy='background')
canica.fit(data)
for ii in range(1, n_timecourses)
]
print("Fitting data for subject %d..." % si)
subj_canica = CanICA(n_components=n_components,
smoothing_fwhm=6.,
memory="nilearn_cache",
memory_level=5,
max_iter=max_iter,
threshold=3.,
verbose=10,
random_state=0)
subj_canica.fit(subj_img_list)
print("Projecting subject data into computed components...")
subj_loadings = subj_canica.transform(subj_img)
subj_component_imgs = subj_canica.masker_.inverse_transform(
subj_canica.components_)
subj_loadings_imgs = []
for time_series, component_volume in zip(subj_loadings.T,
subj_component_imgs.get_data()):
tiled_img_data = np.tile(component_volume[..., np.newaxis],
len(time_series))
loaded_time_series = tiled_img_data * time_series
loading_img = nibabel.Nifti1Image(loaded_time_series,
subj_img.get_affine())
subj_loadings_imgs.append(loading_img)
loadings_imgs.append(subj_loadings_imgs)
all_loadings_images = [
img for subj_images in loadings_imgs for img in subj_loadings_imgs
