def extract_eigenv_roi(bold_image, mask, csvpath, sub, run):
"""
Use fsl.ImageMeants to extract eigenvariate
"""
if not os.path.exists(csvpath):
os.makedirs(csvpath)
extract_eigv = ImageMeants(in_file=bold_image,
terminal_output='file',
eig=True,
mask=mask,
out_file=os.path.join(
csvpath, '{}_{}_{}.csv'.format(
sub, run,
mask.replace('_mask.nii.gz', '')[-4:])))
extract_eigv.run()
#sets necessary inputs
wf_reg.inputs.input_node.realign_movpar_txt = root_path + '/fmri2standard/{subject_id}/realign_fmri2SBref/{subject_id}_ses-01_run-01_rest_bold_ap_roi_mcf.nii.gz.par'.format(
subject_id=subject_id)
wf_reg.inputs.input_node.rfmri_unwarped_imgs = root_path + '/fmri2standard/{subject_id}/spm_coregister2T1_bold/{subject_id}_ses-01_run-01_rest_bold_ap_roi_mcf_corrected_coregistered2T1.nii.gz'.format(
subject_id=subject_id)
#wf_reg.inputs.input_node.masks_imgs = root_path+'/nuisance_correction/{subject_id}/masks_csf_wm/wm_binmask.nii.gz'.format(subject_id=subject_id)
wf_reg.inputs.input_node.mask_wm = root_path + '/nuisance_correction/{subject_id}/masks_csf_wm/wm_binmask.nii.gz'.format(
subject_id=subject_id)
wf_reg.inputs.input_node.mask_csf = root_path + '/nuisance_correction/{subject_id}/masks_csf_wm/csf_binmask.nii.gz'.format(
subject_id=subject_id)
#CONNECT WITH fmri2standard WF
wf_reg.inputs.input_node.bold_img = root_path + '/fmri2standard/{subject_id}/spm_coregister2T1_bold/{subject_id}_ses-01_run-01_rest_bold_ap_roi_mcf_corrected_coregistered2T1.nii.gz'.format(
subject_id=subject_id)
#writes WF graph and runs it
#wf_reg.write_graph()
#wf_reg.run()
print("Extracting...")
extraction.inputs.in_file = root_path + '/nuisance_correction/{subject_id}/filter_regressors_bold/{subject_id}_ses-01_run-01_rest_bold_ap_roi_mcf_corrected_coregistered2T1_regfilt.nii.gz'.format(
subject_id=subject_id)
extraction.inputs.out_file = root_path + '/timeseries/{subject_id}/{subject_id}_ses-01_run-01_rest_bold_glasser_timeseries.txt'.format(
subject_id=subject_id)
#extraction.inputs.out_file=root_path+'/timeseries/{subject_id}/{subject_id}_ses-01_run-01_rest_bold_glasser_timeseries_leftV1.txt'.format(subject_id=subject_id)
extraction.inputs.mask = root_path + '/glasser/{subject_id}/glasser_volumetric_T1_boldT1.nii.gz'.format(
subject_id=subject_id)
#extraction.inputs.mask=root_path+'/glasser/{subject_id}/left_V1_mask.nii.gz'.format(subject_id=subject_id)
extraction.run()
