def looping((sub, hemi, sess)):
print 'running', sub, hemi, sess
label_file = '/scr/ilz3/myelinconnect/all_data_on_simple_surf/labels/%s_%s_highres2lowres_labels.npy'%(sub, hemi)
rest_file = '/scr/ilz3/myelinconnect/resting/final/%s_rest%s_denoised.nii.gz'%(sub, sess)
highres_file = '/scr/ilz3/myelinconnect/struct/surf_%s/orig2func/rest%s/%s_%s_mid_groupavgsurf.vtk'%(hemi, sess, sub, hemi)
data_file = '/scr/ilz3/myelinconnect/all_data_on_simple_surf/rest/%s_%s_rest%s_smooth_3.npy'%(sub, hemi, sess)
# load data
labels = np.load(label_file)[:,1]
highres_v, highres_f, highres_d = read_vtk(highres_file)
# sample resting state time series on highres mesh
rest_highres = sample_volume(rest_file, highres_v)
# average across highres vertices that map to the same lowres vertex
rest_lowres = sample_simple(rest_highres, labels)
# save data
np.save(data_file, rest_lowres)
if os.path.isfile(data_file):
print sub+' '+hemi+' ' +sess+' finished'
return data_file
tsnr_count = 0
for sub in subjects:
labels = np.load(label_file%(sub, hemi))[:,1]
inv2prob_highres_v, inv2prob_highres_f, inv2prob_highres_d = read_vtk(inv2prob_highres_file%(sub, hemi))
# average across highres vertices that map to the same lowres vertex
inv2prob[:,inv2prob_count] = np.squeeze(sample_simple(inv2prob_highres_d, labels))
inv2prob_count += 1
for sess in sessions:
print sub, sess
highres_func_v, highres_func_f, highres_func_d = read_vtk(highres_func_file%(hemi, sess, sub, hemi))
# sample resting state time series on highres mesh
tsnr_highres = sample_volume(tsnr_file%(sub, sess, sub, sess), highres_func_v)
# average across highres vertices that map to the same lowres vertex
tsnr[:,tsnr_count] = np.squeeze(sample_simple(tsnr_highres[:,np.newaxis], labels))
tsnr_count += 1
print 'saving'
#save the minimum snr across all subjects and sessions
np.save(tsnr_full_file%(hemi), tsnr)
np.save(tsnr_min_file%(hemi), np.min(tsnr, axis=1))
np.save(inv2prob_full_file%(hemi), inv2prob)
np.save(inv2prob_min_file%(hemi), np.min(inv2prob, axis=1))
