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()
