def test_nodemaker_tools_masking_coords_WB(atlas):
"""
Test nodemaker_tools_masking_coords_WB functionality
"""
# Set example inputs
roi = tempfile.NamedTemporaryFile(mode="w+", suffix=".nii.gz").name
data_gen.generate_mni_space_img()[1].to_filename(roi)
error = 2
start_time = time.time()
[WB_coords, _, _, WB_labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" % (
"fetch_nilearn_atlas_coords (Masking whole-brain "
"coords version) --> finished: ",
str(np.round(time.time() - start_time, 1)),
"s",
))
start_time = time.time()
[WB_coords_masked,
WB_labels_masked] = nodemaker.coords_masker(roi, WB_coords, WB_labels,
error)
print("%s%s%s" % (
"coords_masker (Masking whole-brain coords version) "
"--> finished: ",
str(np.round(time.time() - start_time, 1)),
"s",
))
assert WB_coords is not None
assert WB_coords is not None
assert WB_coords_masked is not None
assert WB_labels is not None
assert WB_labels_masked is not None
def test_nodemaker_tools_masking_coords_WB(atlas):
"""
Test nodemaker_tools_masking_coords_WB functionality
"""
# Set example inputs
base_dir = str(Path(__file__).parent / "examples")
roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz"
error = 2
start_time = time.time()
[WB_coords, _, _, WB_labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" % (
'fetch_nilearn_atlas_coords (Masking whole-brain coords version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[WB_coords_masked,
WB_labels_masked] = nodemaker.coords_masker(roi, WB_coords, WB_labels,
error)
print("%s%s%s" %
('coords_masker (Masking whole-brain coords version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
assert WB_coords is not None
assert WB_coords is not None
assert WB_coords_masked is not None
assert WB_labels is not None
assert WB_labels_masked is not None
def test_nodemaker_tools_masking_coords_RSN(atlas):
"""
Test nodemaker_tools_masking_coords_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'
roi = base_dir + '/pDMN_3_bin.nii.gz'
network = 'Default'
parc = False
parcel_list = None
error = 2
start_time = time.time()
[coords, _, _, labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" % ('fetch_nilearn_atlas_coords (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords, _, net_labels, network] = nodemaker.get_node_membership(network, func_file, coords, labels, parc,
parcel_list)
print("%s%s%s" % ('get_node_membership (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords_masked, net_labels_masked] = nodemaker.coords_masker(roi, net_coords, net_labels, error)
print("%s%s%s" % ('coords_masker (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
assert coords is not None
assert net_coords is not None
assert net_coords_masked is not None
assert net_labels is not None
assert net_labels_masked is not None
assert network is not None
def test_nodemaker_tools_masking_coords_RSN(atlas):
"""
Test nodemaker_tools_masking_coords_RSN functionality
"""
# Set example inputs
template = pkg_resources.resource_filename(
"pynets", f"templates/standard/MNI152_T1_brain_2mm.nii.gz")
dir_path = str(tempfile.TemporaryDirectory().name)
os.makedirs(dir_path, exist_ok=True)
roi = tempfile.NamedTemporaryFile(mode="w+", suffix=".nii.gz").name
data_gen.generate_mni_space_img()[1].to_filename(roi)
subnet = "Default"
parc = False
parcels_4d_img = None
error = 2
start_time = time.time()
[coords, _, _, labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" % (
"fetch_nilearn_atlas_coords (Masking subnet version) --> "
"finished: ",
str(np.round(time.time() - start_time, 1)),
"s",
))
start_time = time.time()
[net_coords, _, net_labels,
subnet] = nodemaker.get_node_membership(subnet, template, coords, labels,
parc, parcels_4d_img)
print("%s%s%s" % (
"get_node_membership (Masking subnet version) --> "
"finished: ",
str(np.round(time.time() - start_time, 1)),
"s",
))
start_time = time.time()
[net_coords_masked,
net_labels_masked] = nodemaker.coords_masker(roi, net_coords, net_labels,
error)
print("%s%s%s" % (
"coords_masker (Masking subnet version) --> finished: ",
str(np.round(time.time() - start_time, 1)),
"s",
))
assert coords is not None
assert net_coords is not None
assert net_coords_masked is not None
assert net_labels is not None
assert net_labels_masked is not None
assert subnet is not None
def test_nodemaker_tools_masking_coords_RSN(atlas):
"""
Test nodemaker_tools_masking_coords_RSN functionality
"""
import pkg_resources
# Set example inputs
base_dir = str(Path(__file__).parent / "examples")
template = pkg_resources.resource_filename(
"pynets", f"templates/MNI152_T1_brain_2mm.nii.gz")
roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz"
network = 'Default'
parc = False
parcel_list = None
error = 2
start_time = time.time()
[coords, _, _, labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" %
('fetch_nilearn_atlas_coords (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords, _, net_labels,
network] = nodemaker.get_node_membership(network, template, coords,
labels, parc, parcel_list)
print("%s%s%s" %
('get_node_membership (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords_masked,
net_labels_masked] = nodemaker.coords_masker(roi, net_coords, net_labels,
error)
print("%s%s%s" % ('coords_masker (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
assert coords is not None
assert net_coords is not None
assert net_coords_masked is not None
assert net_labels is not None
assert net_labels_masked is not None
assert network is not None
def test_nodemaker_tools_masking_coords_RSN(atlas):
"""
Test nodemaker_tools_masking_coords_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"
roi = f"{base_dir}/miscellaneous/pDMN_3_bin.nii.gz"
network = 'Default'
parc = False
parcel_list = None
error = 2
start_time = time.time()
[coords, _, _, labels] = nodemaker.fetch_nilearn_atlas_coords(atlas)
print("%s%s%s" %
('fetch_nilearn_atlas_coords (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords, _, net_labels,
network] = nodemaker.get_node_membership(network, func_file, coords,
labels, parc, parcel_list)
print("%s%s%s" %
('get_node_membership (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
start_time = time.time()
[net_coords_masked,
net_labels_masked] = nodemaker.coords_masker(roi, net_coords, net_labels,
error)
print("%s%s%s" % ('coords_masker (Masking RSN version) --> finished: ',
str(np.round(time.time() - start_time, 1)), 's'))
assert coords is not None
assert net_coords is not None
assert net_coords_masked is not None
assert net_labels is not None
assert net_labels_masked 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
