# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
#
# Copyright 2021 The NiPreps Developers <nipreps@gmail.com>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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"""Handling surfaces."""
import os
import re
from pathlib import Path
from collections import defaultdict
import numpy as np
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
from nipype.interfaces.base import (
BaseInterfaceInputSpec,
TraitedSpec,
DynamicTraitedSpec,
SimpleInterface,
CommandLine,
CommandLineInputSpec,
File,
traits,
isdefined,
InputMultiPath,
OutputMultiPath,
Undefined,
)
SECONDARY_ANAT_STRUC = {
"smoothwm": "GrayWhite",
"white": "GrayWhite",
"pial": "Pial",
"midthickness": "GrayMid",
}
class _NormalizeSurfInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, exists=True, desc="Freesurfer-generated GIFTI file")
transform_file = File(exists=True, desc="FSL or LTA affine transform file")
class _NormalizeSurfOutputSpec(TraitedSpec):
out_file = File(desc="output file with re-centered GIFTI coordinates")
[docs]
class NormalizeSurf(SimpleInterface):
"""
Normalize a FreeSurfer-generated GIFTI image.
FreeSurfer includes an offset to the center of the brain volume that is not
respected by all software packages.
Normalization involves adding this offset to the coordinates of all
vertices, and zeroing out that offset, to ensure consistent behavior
across software packages.
In particular, this normalization is consistent with the Human Connectome
Project pipeline (see `AlgorithmSurfaceApplyAffine`_ and
`FreeSurfer2CaretConvertAndRegisterNonlinear`_), although the the HCP
may not zero out the offset.
GIFTI files with ``midthickness``/``graymid`` in the name are also updated
to include the following metadata entries::
{
AnatomicalStructureSecondary: MidThickness,
GeometricType: Anatomical
}
This interface is intended to be applied uniformly to GIFTI surface files
generated from the ``?h.white``/``?h.smoothwm`` and ``?h.pial`` surfaces,
as well as externally-generated ``?h.midthickness``/``?h.graymid`` files.
In principle, this should apply safely to any other surface, although it is
less relevant to surfaces that don't describe an anatomical structure.
.. _AlgorithmSurfaceApplyAffine: https://github.com/Washington-University/workbench\
/blob/1b79e56/src/Algorithms/AlgorithmSurfaceApplyAffine.cxx#L73-L91
.. _FreeSurfer2CaretConvertAndRegisterNonlinear: https://github.com/Washington-University/\
Pipelines/blob/ae69b9a/PostFreeSurfer/scripts/FreeSurfer2CaretConvertAndRegisterNonlinear.sh\
#L147-154
"""
input_spec = _NormalizeSurfInputSpec
output_spec = _NormalizeSurfOutputSpec
def _run_interface(self, runtime):
transform_file = self.inputs.transform_file
if not isdefined(transform_file):
transform_file = None
self._results["out_file"] = normalize_surfs(
self.inputs.in_file, transform_file, newpath=runtime.cwd
)
return runtime
class _Path2BIDSInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, desc="input GIFTI file")
class _Path2BIDSOutputSpec(DynamicTraitedSpec):
extension = traits.Str()
[docs]
class Path2BIDS(SimpleInterface):
"""
Extract BIDS entities from paths using a pattern.
Default pattern is given for Gifti surfaces.
>>> Path2BIDS(in_file='_fix_surfs0/rh.pial.surf.gii').run().outputs
<BLANKLINE>
extension = .surf.gii
hemi = R
suffix = pial
<BLANKLINE>
>>> Path2BIDS(in_file='_fix_surfs0/rh.pial.gii').run().outputs
<BLANKLINE>
extension = .gii
hemi = R
suffix = pial
<BLANKLINE>
>>> Path2BIDS(in_file='_fix_surfs0/rh.smoothwm_converted.gii').run().outputs
<BLANKLINE>
extension = .gii
hemi = R
suffix = smoothwm
<BLANKLINE>
>>> Path2BIDS(in_file='_fix_surfs0/rh.smoothwm_converted.func.gii').run().outputs
<BLANKLINE>
extension = .func.gii
hemi = R
suffix = smoothwm
<BLANKLINE>
>>> Path2BIDS(in_file='lh.sulc_converted.gii').run().outputs
<BLANKLINE>
extension = .gii
hemi = L
suffix = sulc
<BLANKLINE>
"""
input_spec = _Path2BIDSInputSpec
output_spec = _Path2BIDSOutputSpec
_pattern = re.compile(
r"(?P<hemi>[lr])h.(?P<suffix>(white|smoothwm|pial|midthickness|"
r"inflated|vinflated|sphere|flat|sulc|curv|thickness))[\w\d_-]*(?P<extprefix>\.\w+)?"
)
_excluded = ("extprefix",)
def __init__(self, pattern=None, **inputs):
"""Initialize the interface."""
super().__init__(**inputs)
if pattern:
self._pattern = re.compile(pattern)
def _outputs(self):
outputs = self.output_spec()
outputs.trait_set(
trait_change_notify=False,
**{
entity: Undefined
for entity in self._pattern.groupindex.keys()
if entity not in self._excluded
},
)
return outputs
def _run_interface(self, runtime):
in_file = Path(self.inputs.in_file)
extension = "".join(in_file.suffixes[-((in_file.suffixes[-1] == ".gz") + 1):])
info = self._pattern.match(in_file.name[: -len(extension)]).groupdict()
self._results["extension"] = f"{info.pop('extprefix', None) or ''}{extension}"
self._results.update(info)
if "hemi" in self._results:
self._results["hemi"] = self._results["hemi"].upper()
return runtime
class _GiftiNameSourceInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, exists=True, desc="input GIFTI file")
pattern = traits.Str(
mandatory=True, desc='input file name pattern (must capture named group "LR")'
)
template = traits.Str(mandatory=True, desc="output file name template")
template_kwargs = traits.Dict(desc="additional template keyword value pairs")
class _GiftiNameSourceOutputSpec(TraitedSpec):
out_name = traits.Str(desc="(partial) filename formatted according to template")
[docs]
class GiftiNameSource(SimpleInterface):
r"""
Construct a new filename for a GIFTI file.
Construct a new filename based on an input filename, a matching pattern,
and a related template, with optionally additional keywords.
This interface is intended for use with GIFTI files, to generate names
conforming to Section 9.0 of the `GIFTI Standard`_.
Patterns are expected to have named groups, including one named "LR" that
matches "l" or "r".
These groups must correspond to named format elements in the template.
.. testsetup::
>>> open('lh.pial.gii', 'w').close()
>>> open('rh.fsaverage.gii', 'w').close()
Examples
--------
>>> surf_namer = GiftiNameSource()
>>> surf_namer.inputs.pattern = r'(?P<LR>[lr])h.(?P<surf>\w+).gii'
>>> surf_namer.inputs.template = r'{surf}.{LR}.surf'
>>> surf_namer.inputs.in_file = 'lh.pial.gii'
>>> res = surf_namer.run()
>>> res.outputs.out_name
'pial.L.surf'
>>> func_namer = GiftiNameSource()
>>> func_namer.inputs.pattern = r'(?P<LR>[lr])h.(?P<space>\w+).gii'
>>> func_namer.inputs.template = r'space-{space}.{LR}.func'
>>> func_namer.inputs.in_file = 'rh.fsaverage.gii'
>>> res = func_namer.run()
>>> res.outputs.out_name
'space-fsaverage.R.func'
>>> namer = GiftiNameSource()
>>> namer.inputs.pattern = r'(?P<LR>[lr])h.(?P<space>\w+).gii'
>>> namer.inputs.template = r'space-{space}_density-{density}_hemi-{LR}.func'
>>> namer.inputs.in_file = 'rh.fsaverage.gii'
>>> namer.inputs.template_kwargs = {'density': '10k'}
>>> res = namer.run()
>>> res.outputs.out_name
'space-fsaverage_density-10k_hemi-R.func'
.. testcleanup::
>>> import os
>>> os.unlink('lh.pial.gii')
>>> os.unlink('rh.fsaverage.gii')
.. _GIFTI Standard: https://www.nitrc.org/frs/download.php/2871/GIFTI_Surface_Format.pdf
"""
input_spec = _GiftiNameSourceInputSpec
output_spec = _GiftiNameSourceOutputSpec
def _run_interface(self, runtime):
in_format = re.compile(self.inputs.pattern)
in_file = os.path.basename(self.inputs.in_file)
info = in_format.match(in_file).groupdict()
info["LR"] = info["LR"].upper()
if self.inputs.template_kwargs:
info.update(self.inputs.template_kwargs)
filefmt = self.inputs.template
self._results["out_name"] = filefmt.format(**info)
return runtime
class _GiftiSetAnatomicalStructureInputSpec(BaseInterfaceInputSpec):
in_file = File(
mandatory=True, exists=True, desc='GIFTI file beginning with "lh." or "rh."'
)
class _GiftiSetAnatomicalStructureOutputSpec(TraitedSpec):
out_file = File(desc="output file with updated AnatomicalStructurePrimary entry")
[docs]
class GiftiSetAnatomicalStructure(SimpleInterface):
"""
Set AnatomicalStructurePrimary attribute of GIFTI image based on filename.
For files that begin with ``lh.`` or ``rh.``, update the metadata to
include::
{
AnatomicalStructurePrimary: (CortexLeft | CortexRight),
}
If ``AnatomicalStructurePrimary`` is already set, this function has no
effect.
"""
input_spec = _GiftiSetAnatomicalStructureInputSpec
output_spec = _GiftiSetAnatomicalStructureOutputSpec
def _run_interface(self, runtime):
img = nb.load(self.inputs.in_file)
if any(nvpair.name == "AnatomicalStruturePrimary" for nvpair in img.meta.data):
out_file = self.inputs.in_file
else:
fname = os.path.basename(self.inputs.in_file)
if fname[:3] in ("lh.", "rh."):
asp = "CortexLeft" if fname[0] == "l" else "CortexRight"
else:
raise ValueError(
"AnatomicalStructurePrimary cannot be derived from filename"
)
img.meta.data.insert(
0, nb.gifti.GiftiNVPairs("AnatomicalStructurePrimary", asp)
)
out_file = os.path.join(runtime.cwd, fname)
img.to_filename(out_file)
self._results["out_file"] = out_file
return runtime
class _GiftiToCSVInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, exists=True, desc="GIFTI file")
itk_lps = traits.Bool(False, usedefault=True, desc="flip XY axes")
class _GiftiToCSVOutputSpec(TraitedSpec):
out_file = File(desc="output csv file")
[docs]
class GiftiToCSV(SimpleInterface):
"""Converts GIfTI files to CSV to make them ammenable to use with
``antsApplyTransformsToPoints``."""
input_spec = _GiftiToCSVInputSpec
output_spec = _GiftiToCSVOutputSpec
def _run_interface(self, runtime):
gii = nb.load(self.inputs.in_file)
data = gii.darrays[0].data
if self.inputs.itk_lps: # ITK: flip X and Y around 0
data[:, :2] *= -1
# antsApplyTransformsToPoints requires 5 cols with headers
csvdata = np.hstack((data, np.zeros((data.shape[0], 3))))
out_file = fname_presuffix(
self.inputs.in_file, newpath=runtime.cwd, use_ext=False, suffix="points.csv"
)
np.savetxt(
out_file,
csvdata,
delimiter=",",
header="x,y,z,t,label,comment",
fmt=["%.5f"] * 4 + ["%d"] * 2,
)
self._results["out_file"] = out_file
return runtime
class _CSVToGiftiInputSpec(BaseInterfaceInputSpec):
in_file = File(mandatory=True, exists=True, desc="CSV file")
gii_file = File(mandatory=True, exists=True, desc="reference GIfTI file")
itk_lps = traits.Bool(False, usedefault=True, desc="flip XY axes")
class _CSVToGiftiOutputSpec(TraitedSpec):
out_file = File(desc="output GIfTI file")
[docs]
class CSVToGifti(SimpleInterface):
"""Converts CSV files back to GIfTI, after moving vertices with
``antsApplyTransformToPoints``."""
input_spec = _CSVToGiftiInputSpec
output_spec = _CSVToGiftiOutputSpec
def _run_interface(self, runtime):
gii = nb.load(self.inputs.gii_file)
data = np.loadtxt(
self.inputs.in_file, delimiter=",", skiprows=1, usecols=(0, 1, 2)
)
if self.inputs.itk_lps: # ITK: flip X and Y around 0
data[:, :2] *= -1
gii.darrays[0].data = data[:, :3].astype(gii.darrays[0].data.dtype)
out_file = fname_presuffix(
self.inputs.gii_file, newpath=runtime.cwd, suffix=".transformed"
)
gii.to_filename(out_file)
self._results["out_file"] = out_file
return runtime
class _SurfacesToPointCloudInputSpec(BaseInterfaceInputSpec):
in_files = InputMultiPath(
File(exists=True), mandatory=True, desc="input GIfTI files"
)
out_file = File("pointcloud.ply", usedefault=True, desc="output file name")
class _SurfacesToPointCloudOutputSpec(TraitedSpec):
out_file = File(desc="output pointcloud in PLY format")
[docs]
class SurfacesToPointCloud(SimpleInterface):
"""Converts multiple surfaces into a pointcloud with corresponding normals
to then apply Poisson reconstruction"""
input_spec = _SurfacesToPointCloudInputSpec
output_spec = _SurfacesToPointCloudOutputSpec
def _run_interface(self, runtime):
from pathlib import Path
giis = [nb.load(g) for g in self.inputs.in_files]
vertices = np.vstack([g.darrays[0].data for g in giis])
norms = np.vstack(
[vertex_normals(g.darrays[0].data, g.darrays[1].data) for g in giis]
)
out_file = Path(self.inputs.out_file).resolve()
pointcloud2ply(vertices, norms, out_file=out_file)
self._results["out_file"] = str(out_file)
return runtime
class _PoissonReconInputSpec(CommandLineInputSpec):
in_file = File(
exists=True,
mandatory=True,
argstr="--in %s",
desc="input PLY pointcloud (vertices + normals)",
)
out_file = File(
argstr="--out %s",
keep_extension=True,
name_source=["in_file"],
name_template="%s_avg",
desc="output PLY triangular mesh",
)
class _PoissonReconOutputSpec(TraitedSpec):
out_file = File(exists=True, desc="output PLY triangular mesh")
[docs]
class PoissonRecon(CommandLine):
"""Runs Poisson Reconstruction on a cloud of points + normals
given in PLY format.
See https://github.com/mkazhdan/PoissonRecon
"""
input_spec = _PoissonReconInputSpec
output_spec = _PoissonReconOutputSpec
_cmd = "PoissonRecon"
class _PLYtoGiftiInputSpec(BaseInterfaceInputSpec):
in_file = File(exists=True, mandatory=True, desc="input PLY file")
surf_key = traits.Str(mandatory=True, desc="reference GIfTI file")
class _PLYtoGiftiOutputSpec(TraitedSpec):
out_file = File(desc="output GIfTI file")
[docs]
class PLYtoGifti(SimpleInterface):
"""Convert surfaces from PLY to GIfTI"""
input_spec = _PLYtoGiftiInputSpec
output_spec = _PLYtoGiftiOutputSpec
def _run_interface(self, runtime):
from pathlib import Path
meta = {
"GeometricType": "Anatomical",
"VolGeomWidth": "256",
"VolGeomHeight": "256",
"VolGeomDepth": "256",
"VolGeomXsize": "1.0",
"VolGeomYsize": "1.0",
"VolGeomZsize": "1.0",
"VolGeomX_R": "-1.0",
"VolGeomX_A": "0.0",
"VolGeomX_S": "0.0",
"VolGeomY_R": "0.0",
"VolGeomY_A": "0.0",
"VolGeomY_S": "-1.0",
"VolGeomZ_R": "0.0",
"VolGeomZ_A": "1.0",
"VolGeomZ_S": "0.0",
"VolGeomC_R": "0.0",
"VolGeomC_A": "0.0",
"VolGeomC_S": "0.0",
}
meta["AnatomicalStructurePrimary"] = "Cortex%s" % (
"Left" if self.inputs.surf_key.startswith("lh") else "Right"
)
meta["AnatomicalStructureSecondary"] = SECONDARY_ANAT_STRUC[
self.inputs.surf_key.split(".")[-1]
]
meta["Name"] = "%s_average.gii" % self.inputs.surf_key
out_file = Path(runtime.cwd) / meta["Name"]
out_file = ply2gii(self.inputs.in_file, meta, out_file=out_file)
self._results["out_file"] = str(out_file)
return runtime
class _UnzipJoinedSurfacesInputSpec(BaseInterfaceInputSpec):
in_files = traits.List(
InputMultiPath(File(exists=True), mandatory=True, desc="input GIfTI files")
)
class _UnzipJoinedSurfacesOutputSpec(TraitedSpec):
out_files = traits.List(
OutputMultiPath(File(exists=True), desc="output pointcloud in PLY format")
)
surf_keys = traits.List(traits.Str, desc="surface identifier keys")
[docs]
class UnzipJoinedSurfaces(SimpleInterface):
"""Unpack surfaces by identifier keys"""
input_spec = _UnzipJoinedSurfacesInputSpec
output_spec = _UnzipJoinedSurfacesOutputSpec
def _run_interface(self, runtime):
from pathlib import Path
groups = defaultdict(list)
in_files = [it for items in self.inputs.in_files for it in items]
for f in in_files:
bname = Path(f).name
groups[bname.split("_")[0]].append(f)
self._results["out_files"] = [sorted(els) for els in groups.values()]
self._results["surf_keys"] = list(groups.keys())
return runtime
class CreateSurfaceROIInputSpec(TraitedSpec):
subject_id = traits.Str(desc='subject ID')
hemisphere = traits.Enum(
"L",
"R",
mandatory=True,
desc='hemisphere',
)
thickness_file = File(exists=True, mandatory=True, desc='input GIFTI file')
class CreateSurfaceROIOutputSpec(TraitedSpec):
roi_file = File(desc='output GIFTI file')
[docs]
class CreateSurfaceROI(SimpleInterface):
"""Prepare GIFTI shape file for use in cortical masking
Distilled from the FreeSurfer2CaretConvertAndRegisterNonlinear.sh script in
DCAN-HCP PostFreeSurfer scripts (as of commit 9291324). The relevant lines
are 277-290.
"""
input_spec = CreateSurfaceROIInputSpec
output_spec = CreateSurfaceROIOutputSpec
def _run_interface(self, runtime):
subject, hemi = self.inputs.subject_id, self.inputs.hemisphere
if not isdefined(subject):
subject = 'sub-XYZ'
img = nb.GiftiImage.from_filename(self.inputs.thickness_file)
# wb_command -set-structure (L282)
img.meta["AnatomicalStructurePrimary"] = {'L': 'CortexLeft', 'R': 'CortexRight'}[hemi]
darray = img.darrays[0]
# wb_command -set-map-names (L284)
meta = darray.meta
meta['Name'] = f"{subject}_{hemi}_ROI"
# wb_command -metric-palette calls (L285, L289) have no effect on ROI files
# Compiling an odd sequence of math operations (L283, L288, L290) that work out to:
# wb_command -metric-math "abs(var * -1) > 0"
roi = np.abs(darray.data) > 0
darray = nb.gifti.GiftiDataArray(
roi,
intent=darray.intent,
datatype=darray.datatype,
encoding=darray.encoding,
endian=darray.endian,
coordsys=darray.coordsys,
ordering=darray.ind_ord,
meta=meta,
)
out_filename = os.path.join(runtime.cwd, f"{subject}.{hemi}.roi.native.shape.gii")
img.to_filename(out_filename)
self._results["roi_file"] = out_filename
return runtime
[docs]
def normalize_surfs(in_file, transform_file, newpath=None):
"""
Re-center GIFTI coordinates to fit align to native T1w space.
For midthickness surfaces, add MidThickness metadata
Coordinate update based on:
https://github.com/Washington-University/workbench/blob/1b79e56/src/Algorithms/AlgorithmSurfaceApplyAffine.cxx#L73-L91
and
https://github.com/Washington-University/Pipelines/blob/ae69b9a/PostFreeSurfer/scripts/FreeSurfer2CaretConvertAndRegisterNonlinear.sh#L147
"""
img = nb.load(in_file)
transform = load_transform(transform_file)
pointset = img.get_arrays_from_intent("NIFTI_INTENT_POINTSET")[0]
coords = pointset.data.T
c_ras_keys = ("VolGeomC_R", "VolGeomC_A", "VolGeomC_S")
ras = np.array([[float(pointset.metadata[key])] for key in c_ras_keys])
ones = np.ones((1, coords.shape[1]), dtype=coords.dtype)
# Apply C_RAS translation to coordinates, then transform
pointset.data = transform.dot(np.vstack((coords + ras, ones)))[:3].T.astype(
coords.dtype
)
secondary = nb.gifti.GiftiNVPairs("AnatomicalStructureSecondary", "MidThickness")
geom_type = nb.gifti.GiftiNVPairs("GeometricType", "Anatomical")
has_ass = has_geo = False
for nvpair in pointset.meta.data:
# Remove C_RAS translation from metadata to avoid double-dipping in FreeSurfer
if nvpair.name in c_ras_keys:
nvpair.value = "0.000000"
# Check for missing metadata
elif nvpair.name == secondary.name:
has_ass = True
elif nvpair.name == geom_type.name:
has_geo = True
fname = os.path.basename(in_file)
# Update metadata for MidThickness/graymid surfaces
if "midthickness" in fname.lower() or "graymid" in fname.lower():
if not has_ass:
pointset.meta.data.insert(1, secondary)
if not has_geo:
pointset.meta.data.insert(2, geom_type)
if newpath is not None:
newpath = os.getcwd()
out_file = os.path.join(newpath, fname)
img.to_filename(out_file)
return out_file
[docs]
def vertex_normals(vertices, faces):
"""Calculates the normals of a triangular mesh"""
def normalize_v3(arr):
""" Normalize a numpy array of 3 component vectors shape=(n,3) """
lens = np.sqrt(arr[:, 0] ** 2 + arr[:, 1] ** 2 + arr[:, 2] ** 2)
arr /= lens[:, np.newaxis]
tris = vertices[faces]
facenorms = np.cross(tris[::, 1] - tris[::, 0], tris[::, 2] - tris[::, 0])
normalize_v3(facenorms)
norm = np.zeros(vertices.shape, dtype=vertices.dtype)
norm[faces[:, 0]] += facenorms
norm[faces[:, 1]] += facenorms
norm[faces[:, 2]] += facenorms
normalize_v3(norm)
return norm
[docs]
def pointcloud2ply(vertices, normals, out_file=None):
"""Converts the file to PLY format"""
from pathlib import Path
import pandas as pd
from pyntcloud import PyntCloud
df = pd.DataFrame(np.hstack((vertices, normals)))
df.columns = ["x", "y", "z", "nx", "ny", "nz"]
cloud = PyntCloud(df)
if out_file is None:
out_file = Path("pointcloud.ply").resolve()
cloud.to_file(str(out_file))
return out_file
[docs]
def ply2gii(in_file, metadata, out_file=None):
"""Convert from ply to GIfTI"""
from pathlib import Path
from numpy import eye
from nibabel.gifti import (
GiftiMetaData,
GiftiCoordSystem,
GiftiImage,
GiftiDataArray,
)
from pyntcloud import PyntCloud
in_file = Path(in_file)
surf = PyntCloud.from_file(str(in_file))
# Update centroid metadata
metadata.update(
zip(
("SurfaceCenterX", "SurfaceCenterY", "SurfaceCenterZ"),
["%.4f" % c for c in surf.centroid],
)
)
# Prepare data arrays
da = (
GiftiDataArray(
data=surf.xyz.astype("float32"),
datatype="NIFTI_TYPE_FLOAT32",
intent="NIFTI_INTENT_POINTSET",
meta=GiftiMetaData.from_dict(metadata),
coordsys=GiftiCoordSystem(xform=eye(4), xformspace=3),
),
GiftiDataArray(
data=surf.mesh.values,
datatype="NIFTI_TYPE_INT32",
intent="NIFTI_INTENT_TRIANGLE",
coordsys=None,
),
)
surfgii = GiftiImage(darrays=da)
if out_file is None:
out_file = fname_presuffix(
in_file.name, suffix=".gii", use_ext=False, newpath=str(Path.cwd())
)
surfgii.to_filename(str(out_file))
return out_file