def individual_tcorr_clustering(func_file, clust_mask, ID, k, thresh=0.5):
import os
from pynets import utils
from pynets.clustools import make_image_from_bin_renum, binfile_parcellate, make_local_connectivity_tcorr
mask_name = os.path.basename(clust_mask).split('.nii.gz')[0]
atlas_select = mask_name + '_k' + str(k)
print('\nCreating atlas at cluster level ' + str(k) + ' for ' +
str(atlas_select) + '...\n')
working_dir = os.path.dirname(func_file) + '/' + atlas_select
outfile = working_dir + '/rm_tcorr_conn_' + str(ID) + '.npy'
outfile_parc = working_dir + '/rm_tcorr_indiv_cluster_' + str(ID)
binfile = working_dir + '/rm_tcorr_indiv_cluster_' + str(ID) + '_' + str(
k) + '.npy'
dir_path = utils.do_dir_path(atlas_select, func_file)
parlistfile = dir_path + '/' + mask_name + '_k' + str(k) + '.nii.gz'
make_local_connectivity_tcorr(func_file, clust_mask, outfile, thresh)
binfile_parcellate(outfile, outfile_parc, int(k))
##write out for group mean clustering
make_image_from_bin_renum(parlistfile, binfile, clust_mask)
return (parlistfile, atlas_select, dir_path)
def individual_tcorr_clustering(func_file, clust_mask, ID, k, clust_type, thresh=0.5):
import os
from pynets import utils, clustools
nilearn_clust_list = ['kmeans', 'ward', 'complete', 'average']
mask_name = os.path.basename(clust_mask).split('.nii.gz')[0]
atlas_select = "%s%s%s%s%s" % (mask_name, '_', clust_type, '_k', str(k))
print("%s%s%s%s%s%s%s" % ('\nCreating atlas using ', clust_type, ' at cluster level ', str(k),
' for ', str(atlas_select), '...\n'))
dir_path = utils.do_dir_path(atlas_select, func_file)
uatlas_select = "%s%s%s%s%s%s%s%s" % (dir_path, '/', mask_name, '_', clust_type, '_k', str(k), '.nii.gz')
if clust_type in nilearn_clust_list:
clustools.nil_parcellate(func_file, clust_mask, k, clust_type, ID, dir_path, uatlas_select)
elif clust_type == 'ncut':
working_dir = "%s%s%s" % (os.path.dirname(func_file), '/', atlas_select)
outfile = "%s%s%s%s" % (working_dir, '/rm_tcorr_conn_', str(ID), '.npy')
outfile_parc = "%s%s%s" % (working_dir, '/rm_tcorr_indiv_cluster_', str(ID))
binfile = "%s%s%s%s%s%s" % (working_dir, '/rm_tcorr_indiv_cluster_', str(ID), '_', str(k), '.npy')
clustools.make_local_connectivity_tcorr(func_file, clust_mask, outfile, thresh)
clustools.binfile_parcellate(outfile, outfile_parc, int(k))
clustools.make_image_from_bin_renum(uatlas_select, binfile, clust_mask)
clustering = True
return uatlas_select, atlas_select, clustering, clust_mask, k, clust_type
def individual_tcorr_clustering(func_file, clust_mask, ID, k, thresh=0.5):
import os
from pynets import utils
from pynets.clustools import make_image_from_bin_renum, binfile_parcellate, make_local_connectivity_tcorr
mask_name = os.path.basename(clust_mask).split('.nii.gz')[0]
atlas_select = "%s%s%s" % (mask_name, '_k', str(k))
print("%s%s%s%s%s" % ('\nCreating atlas at cluster level ', str(k),
' for ', str(atlas_select), '...\n'))
working_dir = "%s%s%s" % (os.path.dirname(func_file), '/', atlas_select)
outfile = "%s%s%s%s" % (working_dir, '/rm_tcorr_conn_', str(ID), '.npy')
outfile_parc = "%s%s%s" % (working_dir, '/rm_tcorr_indiv_cluster_',
str(ID))
binfile = "%s%s%s%s%s%s" % (working_dir, '/rm_tcorr_indiv_cluster_',
str(ID), '_', str(k), '.npy')
dir_path = utils.do_dir_path(atlas_select, func_file)
parlistfile = "%s%s%s%s%s%s" % (dir_path, '/', mask_name, '_k', str(k),
'.nii.gz')
make_local_connectivity_tcorr(func_file, clust_mask, outfile, thresh)
binfile_parcellate(outfile, outfile_parc, int(k))
# write out for group mean clustering
make_image_from_bin_renum(parlistfile, binfile, clust_mask)
return parlistfile, atlas_select, dir_path