threshold=norm.isf(0.001),
title='Nistats 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 nistats.reporting import compare_niimgs
compare_niimgs([z_map], [fsl_z_map],
model.masker_,
ref_label='Nistats',
src_label='FSL')
plt.show()
#############################################################################
# Simple statistical report of thresholded contrast
# -----------------------------------------------------
# We display the contrast plot and table with cluster information.
from nistats.reporting 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)))
os.path.join(data_dir, 'derivatives', 'task', subject, 'stopsignal.feat',
'stats', 'zstat12.nii.gz'))
from nilearn import plotting
import matplotlib.pyplot as plt
from scipy.stats import norm
plotting.plot_glass_brain(z_map, colorbar=True, threshold=norm.isf(0.001),
title='Nistats 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 nistats.reporting import compare_niimgs
compare_niimgs([z_map], [fsl_z_map], model.masker_,
ref_label='Nistats', src_label='FSL')
plt.show()
#############################################################################
# Simple statistical report of thresholded contrast
# -----------------------------------------------------
# We display the contrast plot and table with cluster information
from nistats.reporting 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)))
plt.show()
###############################################################################
# We can get a latex table from a Pandas Dataframe for display and publication