f816b2d21de51ea97a45d8cbece6a528848c56e4,examples/03_connectivity/plot_compare_decomposition.py,,,#,33

Before Change

names = {dict_learning: "DictionaryLearning", canica: "CanICA"}
estimators = [canica, dict_learning]
components_imgs = [canica_components_img, dictlearning_components_img]

// Selecting specific maps to display: maps were manually chosen to be similar
indices = {dict_learning: 8, canica: 14}
// We select relevant cut coordinates for displaying
cut_component = index_img(components_imgs[0], indices[dict_learning])
cut_coords = find_xyz_cut_coords(cut_component)
for estimator, components in zip(estimators, components_imgs):
    // 4D plotting
    plot_prob_atlas(components, view_type="filled_contours",
                    title="%s" % names[estimator],
                    cut_coords=cut_coords, colorbar=False)
    // 3D plotting
    plot_stat_map(index_img(components, indices[estimator]),
                  title="%s" % names[estimator],
                  cut_coords=cut_coords, colorbar=False)
show()
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// .. note::
//

After Change

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// One plot of each component

for i, cur_img in enumerate(iter_img(dictlearning_components_img)):
    plot_stat_map(cur_img, display_mode="z", title="Comp %d" % i,
                  cut_coords=1, colorbar=False)


show()
////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// .. note::
//

Instances