def test_nodemaker_tools_masking_parlistfile_RSN(): """ Test nodemaker_tools_masking_parlistfile_RSN functionality """ # Set example inputs base_dir = str(Path(__file__).parent/"examples") dir_path = base_dir + '/002/fmri' func_file = dir_path + '/002.nii.gz' parlistfile = base_dir + '/whole_brain_cluster_labels_PCA200.nii.gz' roi = base_dir + '/pDMN_3_bin.nii.gz' network = 'Default' ID = '002' perc_overlap = 0.10 parc = True start_time = time.time() [coords, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile) print("%s%s%s" % ('get_names_and_coords_of_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) labels = np.arange(len(coords) + 1)[np.arange(len(coords) + 1) != 0].tolist() start_time = time.time() parcel_list = nodemaker.gen_img_list(parlistfile) [net_coords, net_parcel_list, net_labels, network] = nodemaker.get_node_membership(network, func_file, coords, labels, parc, parcel_list) print("%s%s%s" % ('get_node_membership --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_coords_masked, net_labels_masked, net_parcel_list_masked] = nodemaker.parcel_masker(roi, net_coords, net_parcel_list, net_labels, dir_path, ID, perc_overlap) print("%s%s%s" % ('parcel_masker --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(net_parcel_list_masked) print("%s%s%s" % ('create_parcel_atlas --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() out_path = nodemaker.gen_network_parcels(parlistfile, network, net_labels_masked, dir_path) print("%s%s%s" % ('gen_network_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) assert coords is not None assert net_coords is not None assert net_labels is not None assert net_parcel_list is not None assert net_coords_masked is not None assert net_labels_masked is not None assert net_parcel_list_masked is not None assert out_path is not None assert net_parcels_map_nifti is not None assert parcel_list_exp is not None assert network is not None
def test_nodemaker_tools_masking_parlistfile_WB(): """ Test nodemaker_tools_masking_parlistfile_WB functionality """ # Set example inputs base_dir = str(Path(__file__).parent / "examples") dir_path = f"{base_dir}/BIDS/sub-0025427/ses-1/func" parlistfile = f"{base_dir}/miscellaneous/whole_brain_cluster_labels_PCA200.nii.gz" atlas = 'whole_brain_cluster_labels_PCA200' roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz" ID = '002' parc = True perc_overlap = 0.10 start_time = time.time() [WB_coords, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile) print("%s%s%s" % ( 'get_names_and_coords_of_parcels (Masking whole-brain version) --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) WB_labels = np.arange(len(WB_coords) + 1)[np.arange(len(WB_coords) + 1) != 0].tolist() start_time = time.time() WB_parcel_list = nodemaker.gen_img_list(parlistfile) [_, _, WB_parcel_list_masked ] = nodemaker.parcel_masker(roi, WB_coords, WB_parcel_list, WB_labels, dir_path, ID, perc_overlap) print("%s%s%s" % ('parcel_masker (Masking whole-brain version) --> finished: ', np.round(time.time() - start_time, 1), 's')) start_time = time.time() [WB_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(WB_parcel_list_masked) print("%s%s%s" % ('create_parcel_atlas (Masking whole-brain version) --> finished: ', np.round(time.time() - start_time, 1), 's')) start_time = time.time() [WB_net_parcels_map_nifti_unmasked, WB_coords_unmasked, _, _, _, dir_path] = nodemaker.node_gen(WB_coords, WB_parcel_list, WB_labels, dir_path, ID, parc, atlas, parlistfile) print("%s%s%s" % ('node_gen (Masking whole-brain version) --> finished: ', np.round(time.time() - start_time, 1), 's')) start_time = time.time() [ WB_net_parcels_map_nifti_masked, WB_coords_masked, WB_labels_masked, _, _, _ ] = nodemaker.node_gen_masking(roi, WB_coords, WB_parcel_list, WB_labels, dir_path, ID, parc, atlas, parlistfile) print("%s%s%s" % ('node_gen_masking (Masking whole-brain version) --> finished: ', np.round(time.time() - start_time, 1), 's')) assert WB_coords is not None assert WB_labels is not None assert WB_parcel_list is not None assert WB_coords_masked is not None assert WB_labels_masked is not None assert WB_parcel_list_masked is not None assert WB_parcels_map_nifti is not None assert parcel_list_exp is not None assert WB_net_parcels_map_nifti_unmasked is not None assert WB_coords_unmasked is not None assert WB_net_parcels_map_nifti_masked is not None assert WB_coords_masked is not None
def test_nodemaker_tools_masking_parlistfile_RSN(): """ Test nodemaker_tools_masking_parlistfile_RSN functionality """ # Set example inputs base_dir = str(Path(__file__).parent / "examples") func_file = f"{base_dir}/BIDS/sub-0025427/ses-1/func/sub-0025427_ses-1_task-rest_space-MNI152NLin2009cAsym_desc-smoothAROMAnonaggr_bold.nii.gz" dir_path = f"{base_dir}/BIDS/sub-0025427/ses-1/func" parlistfile = f"{base_dir}/miscellaneous/whole_brain_cluster_labels_PCA200.nii.gz" roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz" network = 'Default' ID = '002' perc_overlap = 0.10 parc = True start_time = time.time() [coords, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile) print("%s%s%s" % ('get_names_and_coords_of_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) labels = np.arange(len(coords) + 1)[np.arange(len(coords) + 1) != 0].tolist() start_time = time.time() parcel_list = nodemaker.gen_img_list(parlistfile) [net_coords, net_parcel_list, net_labels, network] = nodemaker.get_node_membership(network, func_file, coords, labels, parc, parcel_list) print("%s%s%s" % ('get_node_membership --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_coords_masked, net_labels_masked, net_parcel_list_masked ] = nodemaker.parcel_masker(roi, net_coords, net_parcel_list, net_labels, dir_path, ID, perc_overlap) print("%s%s%s" % ('parcel_masker --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(net_parcel_list_masked) print("%s%s%s" % ('create_parcel_atlas --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() out_path = nodemaker.gen_network_parcels(parlistfile, network, net_labels_masked, dir_path) print("%s%s%s" % ('gen_network_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) assert coords is not None assert net_coords is not None assert net_labels is not None assert net_parcel_list is not None assert net_coords_masked is not None assert net_labels_masked is not None assert net_parcel_list_masked is not None assert out_path is not None assert net_parcels_map_nifti is not None assert parcel_list_exp is not None assert network is not None
def test_nodemaker_tools_masking_parlistfile_RSN(): """ Test nodemaker_tools_masking_parlistfile_RSN functionality """ # Set example inputs import pkg_resources base_dir = str(Path(__file__).parent / "examples") template = pkg_resources.resource_filename( "pynets", f"templates/MNI152_T1_brain_2mm.nii.gz") dir_path = f"{base_dir}/BIDS/sub-25659/ses-1/func" parlistfile = f"{base_dir}/miscellaneous/whole_brain_cluster_labels_PCA200.nii.gz" roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz" network = 'Default' ID = '002' perc_overlap = 0.10 parc = True start_time = time.time() [coords, _, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile) print("%s%s%s" % ('get_names_and_coords_of_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) labels = np.arange(len(coords) + 1)[np.arange(len(coords) + 1) != 0].tolist() start_time = time.time() parcel_list = nodemaker.gen_img_list(parlistfile) [net_coords, net_parcel_list, net_labels, network] = nodemaker.get_node_membership(network, template, coords, labels, parc, parcel_list) print("%s%s%s" % ('get_node_membership --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_coords_masked, net_labels_masked, net_parcel_list_masked] = nodemaker.parcel_masker(roi, net_coords, net_parcel_list, net_labels, dir_path, ID, perc_overlap, vox_size='2mm') print("%s%s%s" % ('parcel_masker --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() [net_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(net_parcel_list_masked) print("%s%s%s" % ('create_parcel_atlas --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) start_time = time.time() out_path = nodemaker.gen_network_parcels(parlistfile, network, net_labels_masked, dir_path) print("%s%s%s" % ('gen_network_parcels --> finished: ', str(np.round(time.time() - start_time, 1)), 's')) assert coords is not None assert net_coords is not None assert net_labels is not None assert net_parcel_list is not None assert net_coords_masked is not None assert net_labels_masked is not None assert net_parcel_list_masked is not None assert out_path is not None assert net_parcels_map_nifti is not None assert parcel_list_exp is not None assert network is not None
def node_gen_masking(roi, coords, parcel_list, labels, dir_path, ID, parc, atlas, uatlas, perc_overlap=0.75, error=2): """ In the case that masking was applied, this function generate nodes based on atlas definitions established by fetch_nodes_and_labels. Parameters ---------- roi : str File path to binarized/boolean region-of-interest Nifti1Image file. coords : list List of (x, y, z) tuples in mm-space corresponding to a coordinate atlas used or which represent the center-of-mass of each parcellation node. parcel_list : list List of 3D boolean numpy arrays or binarized Nifti1Images corresponding to ROI masks. labels : list List of string labels corresponding to ROI nodes. dir_path : str Path to directory containing subject derivative data for given run. ID : str A subject id or other unique identifier. parc : bool Indicates whether to use parcels instead of coordinates as ROI nodes. atlas : str Name of a Nilearn-hosted coordinate or parcellation/label-based atlas supported for fetching. See Nilearn's datasets.atlas module for more detailed reference. uatlas : str File path to atlas parcellation Nifti1Image in MNI template space. perc_overlap : float Value 0-1 indicating a threshold of spatial overlap to use as a spatial error cushion in the case of evaluating mask/RSN membership from a given list of parcel masks. Default is 0.75. error : int Rounded euclidean distance, in units of voxel number, to use as a spatial error cushion in the case of evaluating mask/RSN membership from a given list of coordinates. Default is 4. Returns ------- net_parcels_map_nifti : Nifti1Image A nibabel-based nifti image consisting of a 3D array with integer voxel intensities corresponding to ROI membership. coords : list List of (x, y, z) tuples in mm-space corresponding to a coordinate atlas used or which represent the center-of-mass of each parcellation node. labels : list List of string labels corresponding to ROI nodes. atlas : str Name of a Nilearn-hosted coordinate or parcellation/label-based atlas supported for fetching. See Nilearn's datasets.atlas module for more detailed reference. uatlas : str File path to atlas parcellation Nifti1Image in MNI template space. dir_path : str Path to directory containing subject derivative data for given run. """ from pynets.core import nodemaker import os.path as op try: import cPickle as pickle except ImportError: import _pickle as pickle # Mask Parcels if parc is True: # For parcel masking, specify overlap thresh and error cushion in mm voxels [coords, labels, parcel_list_masked ] = nodemaker.parcel_masker(roi, coords, parcel_list, labels, dir_path, ID, perc_overlap) [net_parcels_map_nifti, _] = nodemaker.create_parcel_atlas(parcel_list_masked) # Mask Coordinates else: [coords, labels] = nodemaker.coords_masker(roi, coords, labels, error) # Save coords to pickle coords_path = f"{dir_path}/atlas_coords_{op.basename(roi).split('.')[0]}.pkl" with open(coords_path, 'wb') as f: pickle.dump(coords, f, protocol=2) net_parcels_map_nifti = None # Save labels to pickle labels_path = f"{dir_path}/atlas_labelnames_{op.basename(roi).split('.')[0]}.pkl" with open(labels_path, 'wb') as f: pickle.dump(labels, f, protocol=2) return net_parcels_map_nifti, coords, labels, atlas, uatlas, dir_path
def test_nodemaker_tools_masking_parlistfile_WB(): """ Test nodemaker_tools_masking_parlistfile_WB functionality """ # Set example inputs parlistfile = pkg_resources.resource_filename( "pynets", "templates/atlases/whole_brain_cluster_labels_PCA200.nii.gz") dir_path = str(tempfile.TemporaryDirectory().name) os.makedirs(dir_path, exist_ok=True) shutil.copy2(parlistfile, f"{dir_path}/{os.path.basename(parlistfile)}") parlistfile = f"{dir_path}/{os.path.basename(parlistfile)}" atlas = "whole_brain_cluster_labels_PCA200" roi = tempfile.NamedTemporaryFile(mode="w+", suffix=".nii.gz").name data_gen.generate_mni_space_img()[1].to_filename(roi) ID = "002" parc = True perc_overlap = 0.10 start_time = time.time() [WB_coords, _, _, _] = nodemaker.get_names_and_coords_of_parcels(parlistfile) print("%s%s%s" % ( "get_names_and_coords_of_parcels (Masking whole-brain " "version) --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) WB_labels = np.arange(len(WB_coords) + 1)[np.arange(len(WB_coords) + 1) != 0].tolist() start_time = time.time() WB_parcel_list = nodemaker.three_to_four_parcellation(parlistfile) start_time = time.time() [ WB_net_parcels_map_nifti_unmasked, WB_coords_unmasked, _, _, _, dir_path, ] = nodemaker.node_gen(WB_coords, WB_parcel_list, WB_labels, dir_path, ID, parc, atlas, parlistfile) print("%s%s%s" % ( "node_gen (Masking whole-brain version) --> finished: ", np.round(time.time() - start_time, 1), "s", )) start_time = time.time() WB_parcel_list = nodemaker.three_to_four_parcellation(parlistfile) [WB_parcels_map_nifti, parcel_list_exp] = nodemaker.create_parcel_atlas(WB_parcel_list) print("%s%s%s" % ( "create_parcel_atlas (Masking whole-brain version) --> finished: ", np.round(time.time() - start_time, 1), "s", )) start_time = time.time() WB_parcel_list = nodemaker.three_to_four_parcellation(parlistfile) [ WB_net_parcels_map_nifti_masked, WB_coords_masked, WB_labels_masked, _, _, _, ] = nodemaker.node_gen_masking( roi, WB_coords, WB_parcel_list, WB_labels, dir_path, ID, parc, atlas, parlistfile, vox_size="2mm", ) WB_parcel_list = nodemaker.three_to_four_parcellation(parlistfile) WB_parcel_list_masked = nodemaker.parcel_masker( roi, WB_coords, WB_parcel_list, WB_labels, dir_path, ID, perc_overlap, vox_size="2mm", )[2] print("%s%s%s" % ( "parcel_masker (Masking whole-brain version) --> " "finished: ", np.round(time.time() - start_time, 1), "s", )) print("%s%s%s" % ( "node_gen_masking (Masking whole-brain version) --> " "finished: ", np.round(time.time() - start_time, 1), "s", )) assert WB_coords is not None assert WB_labels is not None assert WB_parcel_list is not None assert WB_coords_masked is not None assert WB_labels_masked is not None assert WB_parcel_list_masked is not None assert WB_parcels_map_nifti is not None assert parcel_list_exp is not None assert WB_net_parcels_map_nifti_unmasked is not None assert WB_coords_unmasked is not None assert WB_net_parcels_map_nifti_masked is not None assert WB_coords_masked is not None
def test_nodemaker_tools_masking_parlistfile_RSN(): """ Test nodemaker_tools_masking_parlistfile_RSN functionality """ # Set example inputs template = pkg_resources.resource_filename( "pynets", f"templates/standard/MNI152_T1_brain_2mm.nii.gz") tmp = tempfile.TemporaryDirectory() dir_path = str(tmp.name) os.makedirs(dir_path, exist_ok=True) parlistfile = pkg_resources.resource_filename( "pynets", "templates/atlases/whole_brain_cluster_labels_PCA200.nii.gz") shutil.copy2(parlistfile, f"{dir_path}/{os.path.basename(parlistfile)}") parlistfile = f"{dir_path}/{os.path.basename(parlistfile)}" roi = tempfile.NamedTemporaryFile(mode="w+", suffix=".nii.gz").name data_gen.generate_mni_space_img()[1].to_filename(roi) subnet = "Default" ID = "002" perc_overlap = 0.75 parc = True start_time = time.time() coords = nodemaker.get_names_and_coords_of_parcels(parlistfile)[0] print("%s%s%s" % ( "get_names_and_coords_of_parcels --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) labels = np.arange(len(coords) + 1)[np.arange(len(coords) + 1) != 0].tolist() start_time = time.time() parcels_4d_img = nodemaker.three_to_four_parcellation(parlistfile) [net_coords, net_parcels_4d_img, net_labels, subnet] = \ nodemaker.get_node_membership( subnet, template, coords, labels, parc, parcels_4d_img ) print("%s%s%s" % ( "get_node_membership --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) start_time = time.time() [ net_coords_masked, net_labels_masked, net_parcels_4d_img_masked, ] = nodemaker.parcel_masker( roi, net_coords, net_parcels_4d_img, net_labels, dir_path, ID, perc_overlap, vox_size="2mm", ) print("%s%s%s" % ( "parcel_masker --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) start_time = time.time() [net_parcels_map_nifti, parcel_list_exp ] = nodemaker.create_parcel_atlas(net_parcels_4d_img_masked) print("%s%s%s" % ( "create_parcel_atlas --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) start_time = time.time() out_path = nodemaker.gen_network_parcels(parlistfile, subnet, net_labels_masked, dir_path) print("%s%s%s" % ( "gen_network_parcels --> finished: ", str(np.round(time.time() - start_time, 1)), "s", )) assert coords is not None assert net_coords is not None assert net_labels is not None assert net_parcels_4d_img is not None assert net_coords_masked is not None assert net_labels_masked is not None assert net_parcels_4d_img_masked is not None assert out_path is not None assert net_parcels_map_nifti is not None assert parcel_list_exp is not None assert subnet is not None tmp.cleanup()