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
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
if do_surface:
for hemi in ['lh', 'rh']:
z_maps = [
pjoin(work_dir, acq, 'z_surf',
'effects_interest_%s.gii' % hemi) for acq in acqs
]
mean_z = np.mean([
np.ravel([darrays.data for darrays in load(z_map).darrays])
for z_map in z_maps
], 0)
n_maps = len(z_maps)
fixed_effects = mean_z * np.sqrt(n_maps)
gii = GiftiImage(
darrays=[GiftiDataArray().from_array(fixed_effects, 't test')])
gii.to_filename(pjoin(write_dir, 'retinotopicity_%s.gii' % hemi))
fixed_effects[np.isnan(fixed_effects)] = 0
bh = fdr_threshold(fixed_effects, alpha)
print(bh)
mask = fixed_effects > bh
# todo: plot on a surface
"""
output_file = pjoin(write_dir, 'retinotopicity_%s.png' % hemi)
if hemi == 'lh':
plot_surf_stat_map(
lh_inflated, fixed_effects, bg_map=sulc_left, output_file=output_file,
hemi='left', view='medial', bg_on_data=True, darkness=1, alpha=1,
threshold=THRESHOLD)
else:
plot_surf_stat_map(
