contrasts['EV1>EV2'] = contrasts['EV1'] - contrasts['EV2']
contrasts['EV2>EV1'] = contrasts['EV2'] - contrasts['EV1']
contrasts['effects_of_interest'] = contrasts['EV1'] + contrasts['EV2']
"""fit GLM"""
print('\r\nFitting a GLM (this takes time) ..')
fmri_glm = FMRILinearModel(fmri_files, matrix, mask='compute')
fmri_glm.fit(do_scaling=True, model='ar1')
"""save computed mask"""
mask_path = os.path.join(subject_data.output_dir, "mask.nii.gz")
print "Saving mask image %s" % mask_path
nibabel.save(fmri_glm.mask, mask_path)
# compute bg unto which activation will be projected
mean_fmri_files = compute_mean_3D_image(fmri_files)
print "Computing contrasts .."
z_maps = {}
for contrast_id, contrast_val in contrasts.iteritems():
print "\tcontrast id: %s" % contrast_id
z_map, t_map, eff_map, var_map = fmri_glm.contrast(
contrasts[contrast_id],
con_id=contrast_id,
output_z=True,
output_stat=True,
output_effects=True,
output_variance=True,
)
# store stat maps to disk
for dtype, out_map in zip(['z', 't', 'effects', 'variance'],
contrasts['EV1>EV2'] = contrasts['EV1'] - contrasts['EV2']
contrasts['EV2>EV1'] = contrasts['EV2'] - contrasts['EV1']
contrasts['effects_of_interest'] = contrasts['EV1'] + contrasts['EV2']
"""fit GLM"""
print('\r\nFitting a GLM (this takes time) ..')
fmri_glm = FirstLevelGLM()
fmri_glm.fit(fmri_files, design_matrix)
"""save computed mask"""
mask_path = os.path.join(subject_data.output_dir, "mask.nii.gz")
print "Saving mask image %s" % mask_path
nibabel.save(fmri_glm.masker_.mask_img_, mask_path)
# compute bg unto which activation will be projected
mean_fmri_files = compute_mean_3D_image(fmri_files)
print "Computing contrasts .."
z_maps = {}
for contrast_id, contrast_val in contrasts.iteritems():
print "\tcontrast id: %s" % contrast_id
z_map, t_map, eff_map, var_map = fmri_glm.transform(
con_vals=contrasts[contrast_id],
contrast_name=contrast_id,
output_z=True,
output_stat=True,
output_effects=True,
output_variance=True,
)
# store stat maps to disk
for dtype, out_map in zip(['z', 't', 'effects', 'variance'],