def test_plot_img_comparison():
fig, axes = plt.subplots(2, 1)
axes = axes.ravel()
kwargs = {"shape": (3, 2, 4), "length": 5}
query_images, mask_img = data_gen.generate_fake_fmri(
rand_gen=np.random.RandomState(0), **kwargs)
# plot_img_comparison doesn't handle 4d images ATM
query_images = list(image.iter_img(query_images))
target_images, _ = data_gen.generate_fake_fmri(
rand_gen=np.random.RandomState(1), **kwargs)
target_images = list(image.iter_img(target_images))
target_images[0] = query_images[0]
masker = NiftiMasker(mask_img).fit()
correlations = plotting.plot_img_comparison(
target_images, query_images, masker, axes=axes, src_label="query")
assert len(correlations) == len(query_images)
assert correlations[0] == pytest.approx(1.)
ax_0, ax_1 = axes
# 5 scatterplots
assert len(ax_0.collections) == 5
assert len(ax_0.collections[0].get_edgecolors() == masker.transform(
target_images[0]).ravel().shape[0])
assert ax_0.get_ylabel() == "query"
assert ax_0.get_xlabel() == "image set 1"
# 5 regression lines
assert len(ax_0.lines) == 5
assert ax_0.lines[0].get_linestyle() == "--"
assert ax_1.get_title() == "Histogram of imgs values"
assert len(ax_1.patches) == 5 * 2 * 128
correlations_1 = plotting.plot_img_comparison(
target_images, query_images, masker, plot_hist=False)
assert np.allclose(correlations, correlations_1)
threshold=norm.isf(0.001),
title='Nilearn Z map of "StopSuccess - Go" (unc p<0.001)',
plot_abs=False,
display_mode='ortho')
plotting.plot_glass_brain(
fsl_z_map,
colorbar=True,
threshold=norm.isf(0.001),
title='FSL Z map of "StopSuccess - Go" (unc p<0.001)',
plot_abs=False,
display_mode='ortho')
plt.show()
from nilearn.plotting import plot_img_comparison
plot_img_comparison([z_map], [fsl_z_map],
model.masker_,
ref_label='Nilearn',
src_label='FSL')
plt.show()
#############################################################################
# Simple statistical report of thresholded contrast
# -----------------------------------------------------
# We display the contrast plot and table with cluster information
from nilearn.plotting import plot_contrast_matrix
plot_contrast_matrix('StopSuccess - Go', design_matrix)
plotting.plot_glass_brain(z_map,
colorbar=True,
threshold=norm.isf(0.001),
plot_abs=False,
display_mode='z',
figure=plt.figure(figsize=(4, 4)))