def gen_mapped_prior_stim_sites(subject_id, localization, paths,
setup_status) -> FilePaths:
""" Map prior stim site locations into this subject's coordinate space
Parameters
----------
subject_id: str
Subject ID
localization: str
Localization number to use
paths: :class:`cml_pipelines.paths.FilePaths`
Container for various file paths needed by the task
setup_status: bool
Status of the setup task. Indicates that this task is dependent on
setup completing successfully
Returns
-------
exp_paths: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by this task
"""
subject_localization = _combine_subject_localization(
subject_id, localization)
output_file = build_prior_stim_location_mapping(subject_localization,
paths.base, paths.image)
exp_paths = FilePaths(root="/", prior_stim=output_file)
return exp_paths
def test_initialize(self, root, basedir):
paths = FilePaths(root, base=basedir)
basedir = basedir.lstrip("/").rstrip("/")
assert paths.root == os.path.expanduser(root)
assert paths.base == os.path.join(os.path.expanduser(root), basedir)
return
def avg_hcp_to_subject(subject_id: str, localization: int, paths: FilePaths,
setup_status: bool) -> FilePaths:
""" Convert HCP atlas annotation file into subject-specific space
Parameters
----------
subject_id: str
ID of subject
localization: str
Localization number to use
paths: :class:`cml_pipelines.paths.FilePaths`
Container for various file paths produced by the task
setup_status: bool
True if the setup task completed successfully. The presence of this
boolean in the function signature is used to notify the pipeline
framework that this task depends on the result of the setup task
Returns
-------
exp_files: :class:`cml_pipelines.paths.FilePaths`
File path container object containing files produced by this task
"""
subject_localization = _combine_subject_localization(
subject_id, localization)
subprocess.run(" ".join([
"mri_surf2surf", "--srcsubject fsaverage_temp",
"--sval-annot HCP-MMP1.annot",
"--trgsubject {}".format(subject_localization),
"--trgsurfval HCP-MMP1.annot", "--hemi lh"
]),
shell=True,
check=True)
subprocess.run(" ".join([
"mri_surf2surf", "--srcsubject fsaverage_temp",
"--sval-annot HCP-MMP1.annot",
"--trgsubject {}".format(subject_localization),
"--trgsurfval HCP-MMP1.annot", "--hemi rh"
]),
shell=True,
check=True)
shutil.copy(os.path.join(paths.base, "label/lh.HCP-MMP1.annot"),
paths.cortex)
shutil.copy(os.path.join(paths.base, "label/rh.HCP-MMP1.annot"),
paths.cortex)
exp_files = FilePaths(root="/",
rh_hcp=os.path.join(paths.cortex,
"rh.HCP-MMP1.annot"),
lh_hcp=os.path.join(paths.cortex,
"lh.HCP-MMP1.annot"))
return exp_files
def setup_class(cls):
cls.paths = FilePaths(datafile("R1291M_1/"),
base="",
cortex="surf/roi/",
image="imaging/autoloc/",
tal="tal/",
output="blender_scene/",
avg_prior_stim="")
cls.subject_id = "R1291M"
cls.localization = 1
def test_gen_blender_scene(self):
prior_stim_output = FilePaths(root="/",
prior_stim=os.path.join(
self.paths.base,
"prior_stim/R1291M_1_allcords.csv"))
# Most of the FilePaths objects that are passed are only used to
# denote dependencies and are not actually used, which is why it is
# okay to pass self.paths multiple times for testing
returned_paths = gen_blender_scene(self.subject_id, self.localization,
self.paths, True, prior_stim_output,
self.paths, self.paths, self.paths)
assert os.path.exists(returned_paths.blender_file)
def gen_blender_scene(subject_id: str, localization: int, paths: FilePaths,
build_site_status, prior_stim_paths: FilePaths,
split_hcp_files: FilePaths, split_dk_files: FilePaths,
electrode_coord_files: FilePaths) -> FilePaths:
""" Creates the Blender-based 3D brain standalone brain visualization
Parameters
----------
subject_id: str
Subject ID
localization: str
Localization number to use
paths: :class:`cml_pipelines.paths.FilePaths`
File path container for files needed by this task
build_site_status: bool
Status of the setup_standalone_blender_scene task, indicating a
dependency on this task
prior_stim_paths: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the
gen_mapped_prior_stim_sites task, indicating a dependency on this task
split_hcp_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the split_hcp_surface task,
indicating a dependency on this task
split_dk_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the split_dk_surface,
indicating a dependency on this task
electrode_coord_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the save_coords_for_blender
task, indicating a dependency on this task
Returns
-------
exp_output: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by this task
"""
prior_stim_sites = prior_stim_paths.prior_stim
subject_localiztion = _combine_subject_localization(
subject_id, localization)
subprocess.run([
"/usr/global/blender-2.78c-linux-glibc219-x86_64/blender", "-b",
datafile("iEEG_surface_template/empty.blend"), "-b", "--python",
code_files("create_scene.py"), "--", subject_localiztion, paths.cortex,
paths.tal, paths.output, prior_stim_sites
],
check=True)
exp_output = FilePaths(root="/",
blender_file=os.path.join(paths.output,
'iEEG_surface.json'))
return exp_output
def freesurfer_to_wavefront(paths: FilePaths, setup_status: bool) -> FilePaths:
""" Convert Freesurfer brain piece models to wavefront format
Parameters
----------
paths: :class:`cml_pipelines.paths.FilePaths
File path container
setup_status: bool
If true, setup step was succesful. Indicates that this task is
dependent on the setup completing successfully
Returns
-------
exp_files: :class:`cml_pipelines.paths.FilePaths`
File path container with files produced by the task
"""
subprocess.run("mris_convert " + os.path.join(paths.cortex, "lh.pial ") +
os.path.join(paths.cortex, "lh.pial.asc"),
shell=True,
check=True)
subprocess.run("mris_convert " + os.path.join(paths.cortex, "rh.pial ") +
os.path.join(paths.cortex, "rh.pial.asc"),
shell=True,
check=True)
shutil.move(os.path.join(paths.cortex, "lh.pial.asc"),
os.path.join(paths.cortex, "lh.pial.srf"))
shutil.move(os.path.join(paths.cortex, "rh.pial.asc"),
os.path.join(paths.cortex, "rh.pial.srf"))
subprocess.run(" ".join([
bin_files("srf2obj"),
os.path.join(paths.cortex, "lh.pial.srf "), ">",
os.path.join(paths.cortex, "lh.pial.obj")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("srf2obj"),
os.path.join(paths.cortex, "rh.pial.srf"), ">",
os.path.join(paths.cortex, "rh.pial.obj")
]),
shell=True,
check=True)
exp_files = FilePaths(root="/",
rh_obj=os.path.join(paths.cortex, "rh.pial.obj"),
lh_obj=os.path.join(paths.cortex, "lh.pial.obj"))
return exp_files
def test_gen_avg_brain():
""" Black-box test for generating average brain """
paths = FilePaths(datafile("average"),
avg_roi="surf/roi/",
output="blender_scene/",
avg_prior_stim="")
generate_average_brain(paths=paths, blender=True, force_rerun=True)
assert os.path.exists(paths.output + '/iEEG_surface.blend')
assert os.path.exists(paths.output + '/iEEG_surface.bin')
assert os.path.exists(paths.output + '/iEEG_surface.json')
assert os.path.exists(paths.root + "/fsaverage_joel_allcords.csv")
if os.path.exists(paths.output):
shutil.rmtree(paths.output, ignore_errors=True)
if os.path.exists(paths.root + "fsaverage_joel_allcords.csv"):
os.remove(paths.root + "fsaverage_joel_allcords.csv")
def setup_paths(subject_id: str,
localization: str,
rhino_root: Optional[str] = "/"):
"""
Helper function to produce a `cml_pipelines.paths.FilePaths` object
with production paths for building a subject-specific 3D brain
visualization
Parameters
----------
subject_id: str
ID of subject to generate the brain visualization
localization: str
Localization number as a string to use. Typically this is 0.
rhino_root: str, default: "/"
Mount point for RHINO
"""
subject_localization = _combine_subject_localization(
subject_id, localization)
subject_num = _extract_subject_num(subject_id)
# Common paths used throughout the pipeline
BASE = "/data10/eeg/freesurfer/subjects/{}".format(subject_localization)
CORTEX = "/data10/eeg/freesurfer/subjects/{}/surf/roi".format(
subject_localization)
CONTACT = "/data10/RAM/subjects/{}/tal/coords".format(subject_localization)
TAL = "/data10/RAM/subjects/{}/tal".format(subject_localization)
IMAGE = "/data10/RAM/subjects/{}/imaging/autoloc/".format(
subject_localization)
OUTPUT = "/reports/r1/subjects/{}/reports/iEEG_surface".format(subject_num)
paths = FilePaths(
rhino_root,
base=BASE,
cortex=CORTEX,
contact=CONTACT,
tal=TAL,
image=IMAGE,
output=OUTPUT,
avg_prior_stim=
"data10/eeg/freesurfer/subjects/fsaverage_joel/prior_stim/")
return paths
def setup_avg_paths(rhino_root: Optional[str] = "/") -> FilePaths:
""" Create default paths for building average brain visualization
Parameters
----------
rhino_root: str
Mount point for RHINO
Returns
-------
paths: :class:`cml_pipelines.paths.FilePaths`
File path container
"""
paths = FilePaths(
rhino_root,
avg_prior_stim=
"data10/eeg/freesurfer/subjects/fsaverage_joel/prior_stim/",
output="reports/r1/subjects/avg/iEEG_surface",
avg_roi="data10/eeg/freesurfer/subjects/average/surf/roi/")
return paths
def setup_class(cls):
cls.paths = FilePaths(datafile("R1291M_1/"), base="",
workdir="prior_stim/",
baselinedir="prior_stim_baseline/",
imagedir="imaging/autoloc/")
cls.subject_id = "R1291M_1"
def split_hcp_surface(paths: FilePaths, hcp_subj_files: FilePaths,
fs_to_wav_files: FilePaths) -> FilePaths:
""" Creates individual brain objects based on the HCP atlas
Parameters
----------
paths: :class:`cml_pipelines.paths.FilePaths`
File path container for files needed by this task
hcp_subj_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the avg_hcp_to_subject task,
indicating a dependency on this task
fs_to_wav_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the freesurfer_to_wavefront
task, indicating a dependency on this task
Returns
-------
exp_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by this task
"""
subprocess.run(" ".join([
bin_files("annot2dpv"),
os.path.join(paths.cortex, "lh.HCP-MMP1.annot"),
os.path.join(paths.cortex, "lh.HCP-MMP1.annot.dpv")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("annot2dpv"),
os.path.join(paths.cortex, "rh.HCP-MMP1.annot"),
os.path.join(paths.cortex, "rh.HCP-MMP1.annot.dpv")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("splitsrf"),
os.path.join(paths.cortex, "lh.pial.srf"),
os.path.join(paths.cortex, "lh.HCP-MMP1.annot.dpv"),
os.path.join(paths.cortex, "lh.hcp")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("splitsrf"),
os.path.join(paths.cortex, "rh.pial.srf"),
os.path.join(paths.cortex, "rh.HCP-MMP1.annot.dpv"),
os.path.join(paths.cortex, "rh.hcp")
]),
shell=True,
check=True)
hcp_surfaces = glob.glob(os.path.join(paths.cortex, "*.hcp.*.srf"))
for surface in hcp_surfaces:
subprocess.run(" ".join([
bin_files("srf2obj"), surface, ">",
surface.replace(".srf", ".obj")
]),
shell=True,
check=True)
exp_files = FilePaths(root="/",
lh_hcp=os.path.join(paths.cortex, "lh.hcp.0001.obj"),
rh_hcp=os.path.join(paths.cortex, "rh.hcp.0001.obj"))
return exp_files
def split_dk_surface(paths: FilePaths,
fs_to_wav_files: FilePaths) -> FilePaths:
""" Creates individual brain objects based on Desikan-Killiany atlas
Parameters
----------
paths: :class:`cml_pipelines.paths.FilePaths`
File path container for files needed by this task
fs_to_wav_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by the freesurfer_to_wavefront,
which also indicates a dependency on this task
Returns
-------
exp_files: :class:`cml_pipelines.paths.FilePaths`
File path container for files produced by this task
"""
subprocess.run(" ".join([
bin_files("annot2dpv"),
os.path.join(paths.cortex, "rh.aparc.annot"),
os.path.join(paths.cortex, "rh.aparc.annot.dpv")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("annot2dpv"),
os.path.join(paths.cortex, "lh.aparc.annot"),
os.path.join(paths.cortex, "lh.aparc.annot.dpv")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("splitsrf"),
os.path.join(paths.cortex, "rh.pial.srf"),
os.path.join(paths.cortex, "rh.aparc.annot.dpv"),
os.path.join(paths.cortex, "rh.pial_roi")
]),
shell=True,
check=True)
subprocess.run(" ".join([
bin_files("splitsrf"),
os.path.join(paths.cortex, "lh.pial.srf"),
os.path.join(paths.cortex, "lh.aparc.annot.dpv"),
os.path.join(paths.cortex, "lh.pial_roi")
]),
shell=True,
check=True)
# Mapping between the default numeric number and the name of the brain
# region
surf_num_dict = {
"0001": "Unmeasured.obj",
"0002": "BanksSuperiorTemporal.obj",
"0003": "CACingulate.obj",
"0004": "MiddleFrontalCaudal.obj",
"0005": "Cuneus.obj",
"0006": "Entorhinal.obj",
"0007": "Fusiform.obj",
"0008": "InferiorParietal.obj",
"0009": "InferiorTemporal.obj",
"0010": "Isthmus.obj",
"0011": "LateralOccipital.obj",
"0012": "OrbitalFrontal.obj",
"0013": "Lingual.obj",
"0014": "MedialOrbitalFrontal.obj",
"0015": "MiddleTemporal.obj",
"0016": "Parahippocampal.obj",
"0017": "ParacentralLobule.obj",
"0018": "InfFrontalParsOpercularis.obj",
"0019": "InfFrontalParsOrbitalis.obj",
"0020": "InfFrontalParsTriangularis.obj",
"0021": "Pericalcarine.obj",
"0022": "Post-Central.obj",
"0023": "PosteriorCingulate.obj",
"0024": "Pre-Central.obj",
"0025": "PreCuneus.obj",
"0026": "RACingulate.obj",
"0027": "MiddleFrontalRostral.obj",
"0028": "SuperiorFrontal.obj",
"0029": "SuperiorParietal.obj",
"0030": "SuperiorTemporal.obj",
"0031": "Supra-Marginal.obj",
"0032": "FrontalPole.obj",
"0033": "TemporalPole.obj",
"0034": "TransverseTemporal.obj",
"0035": "Insula.obj"
}
base_input_file = paths.cortex + "/{hemisphere}.pial_roi.{surface_num}.srf"
base_output_file = paths.cortex + "/{hemisphere}.{surface_name}"
exp_files = FilePaths(root="/")
for hemisphere in ["lh", "rh"]:
for surface in surf_num_dict.keys():
subprocess.run(" ".join([
bin_files("srf2obj"),
base_input_file.format(hemisphere=hemisphere,
surface_num=surface), ">",
base_output_file.format(hemisphere=hemisphere,
surface_name=surf_num_dict[surface])
]),
shell=True,
check=True)
# Adding the output file to the set of paths
setattr(
exp_files, "".join([hemisphere, surface]),
base_output_file.format(hemisphere=hemisphere,
surface_name=surf_num_dict[surface]))
return exp_files
def setup_class(cls):
cls.test_paths = FilePaths("/mnt/mount_point/",
dir1="/base/",
dir2="dir2/")