def _generate_report(self):
from niworkflows.viz.utils import plot_segs
plot_segs(image_nii=self._anat_file,
seg_niis=self._seg_files,
mask_nii=self._mask_file,
out_file=self.inputs.out_report,
masked=self._masked,
title=self._report_title,
compress=self.inputs.compress_report)
def _generate_report(self):
'''
Construct a parcellation overlay image
'''
import niworkflows.viz.utils as nwviz
from ..patches.niworkflows import _3d_in_file, _plot_anat_with_contours
'''
MONKEY PATCH:
_3d_in_file in niworkflows.viz.utils cannot accept Nifti1Images
as inputs.
This is a small patch that will stop it from failing when this is
the case
'''
# _3d_in_file more robust to accepting a Nifti1Image
nwviz._3d_in_file = _3d_in_file
# plot_anat_with_contours accepts filled
nwviz._plot_anat_with_contours = _plot_anat_with_contours
segs = _parcel2segs(self._parcellation)
nwviz.compose_view(
nwviz.plot_segs(
image_nii=self._bg_nii,
seg_niis=segs,
bbox_nii=self._mask_nii,
out_file=None, # this arg doesn't matter
colors=self._colors,
filled=True,
alpha=0.3),
fg_svgs=None,
out_file=self._out_report)
def make_brain(*, anatomical, mask, out_file):
"""
Creates `out_file`.svg of brain `mask` on input `anatomical`
Parameters
----------
anatomical : str
Path to anatomical T1w image (*with skull*)
mask : str
Path to brain mask file
out_file : str
Path to where svg will be saved
Returns
-------
out_file : str
Where svg was saved
"""
if not out_file.endswith('.svg'): out_file += '.svg'
compose_view(
plot_segs(image_nii=anatomical,
seg_niis=[mask],
bbox_nii=mask,
out_file='reports.svg',
masked=False,
compress='auto'),
fg_svgs=None,
out_file=out_file
)
return out_file
def _generate_report(self):
from niworkflows.viz.utils import plot_segs
compose_view(plot_segs(image_nii=self._anat_file,
seg_niis=self._seg_files,
bbox_nii=self._mask_file,
out_file=self.inputs.out_report,
masked=self._masked,
compress=self.inputs.compress_report),
fg_svgs=None,
out_file=self._out_report)
def _generate_report(self):
from seaborn import color_palette
from niworkflows.viz.utils import plot_segs, compose_view
seg_files = self.inputs.in_rois
mask_file = None if not isdefined(self.inputs.in_mask) else self.inputs.in_mask
# Remove trait decoration and replace None with []
levels = [level for level in self.inputs.levels or []]
colors = [c for c in self.inputs.colors or []]
if len(seg_files) == 1: # in_rois is a segmentation
nsegs = len(levels)
if nsegs == 0:
levels = np.unique(
np.round(nb.load(seg_files[0]).get_fdata(dtype="float32"))
)
levels = (levels[levels > 0] - 0.5).tolist()
nsegs = len(levels)
levels = [levels]
missing = nsegs - len(colors)
if missing > 0:
colors = colors + color_palette("husl", missing)
colors = [colors]
else: # in_rois is a list of masks
nsegs = len(seg_files)
levels = [[0.5]] * nsegs
missing = nsegs - len(colors)
if missing > 0:
colors = [[c] for c in colors + color_palette("husl", missing)]
if mask_file:
seg_files.insert(0, mask_file)
if levels:
levels.insert(0, [0.5])
colors.insert(0, [self.inputs.mask_color])
nsegs += 1
self._out_report = os.path.abspath(self.inputs.out_report)
compose_view(
plot_segs(
image_nii=self.inputs.in_file,
seg_niis=seg_files,
bbox_nii=mask_file,
levels=levels,
colors=colors,
out_file=self.inputs.out_report,
masked=self.inputs.masked,
compress=self.inputs.compress_report,
),
fg_svgs=None,
out_file=self._out_report,
)
def _generate_report(self):
from niworkflows.viz.utils import plot_segs, compose_view
seg_files = self.inputs.in_rois
mask_file = None if not isdefined(self.inputs.in_mask) \
else self.inputs.in_mask
# Remove trait decoration and replace None with []
levels = [l for l in self.inputs.levels or []]
colors = [c for c in self.inputs.colors or []]
if len(seg_files) == 1: # in_rois is a segmentation
nsegs = len(levels)
if nsegs == 0:
levels = np.unique(np.round(
nb.load(seg_files[0]).get_data()).astype(int))
levels = (levels[levels > 0] - 0.5).tolist()
nsegs = len(levels)
levels = [levels]
missing = nsegs - len(colors)
if missing > 0:
colors = colors + color_palette("husl", missing)
colors = [colors]
else: # in_rois is a list of masks
nsegs = len(seg_files)
levels = [[0.5]] * nsegs
missing = nsegs - len(colors)
if missing > 0:
colors = [[c] for c in colors + color_palette("husl", missing)]
if mask_file:
seg_files.insert(0, mask_file)
if levels:
levels.insert(0, [0.5])
colors.insert(0, [self.inputs.mask_color])
nsegs += 1
self._out_report = os.path.abspath(self.inputs.out_report)
compose_view(
plot_segs(
image_nii=self.inputs.in_file,
seg_niis=seg_files,
bbox_nii=mask_file,
levels=levels,
colors=colors,
out_file=self.inputs.out_report,
masked=self.inputs.masked,
compress=self.inputs.compress_report,
),
fg_svgs=None,
out_file=self._out_report
)
def _generate_report(self):
from niworkflows.viz.utils import plot_segs
compose_view(
plot_segs(
image_nii=self._anat_file,
seg_niis=self._seg_files,
bbox_nii=self._mask_file,
out_file=self.inputs.out_report,
masked=self._masked,
compress=self.inputs.compress_report
),
fg_svgs=None,
out_file=self._out_report
)
def _generate_report(self):
from niworkflows.viz.utils import plot_segs, compose_view
seg_files = self.inputs.in_rois
mask_file = None
if isdefined(self.inputs.in_mask):
mask_file = self.inputs.in_mask
seg_files.insert(0, self.inputs.in_mask)
self._out_report = os.path.abspath(self.inputs.out_report)
compose_view(plot_segs(image_nii=self.inputs.in_file,
seg_niis=seg_files,
bbox_nii=mask_file,
out_file=self.inputs.out_report,
masked=self.inputs.masked,
colors=self.inputs.colors,
compress=self.inputs.compress_report),
fg_svgs=None,
out_file=self._out_report)
def _run_interface(self, runtime):
""" there is not inner interface to run """
from niworkflows.viz.utils import plot_segs, compose_view
seg_files = self.inputs.in_rois
mask_file = None
if isdefined(self.inputs.in_mask):
mask_file = self.inputs.in_mask
seg_files.insert(0, self.inputs.in_mask)
self._out_report = os.path.abspath(self.inputs.out_report)
compose_view(plot_segs(image_nii=self.inputs.in_file,
seg_niis=seg_files,
bbox_nii=mask_file,
out_file=self.inputs.out_report,
masked=self.inputs.masked,
colors=self.inputs.colors,
compress=self.inputs.compress_report),
fg_svgs=None,
out_file=self._out_report)
return runtime
def make_segmentation(*, anatomical, segmentation, mask, out_file):
"""
Creates `out_file`.svg of `segmentation` countours on input `anatomical`
Parameters
----------
anatomical : str
Path to anatomical T1w image (*without skull*)
segmentation : str
Path to segmentation file with tissue types (1-6)
mask : str
Path to brain mask file
out_file : str
Path to where svg will be saved
Returns
-------
out_file : str
Where svg was saved
"""
if not out_file.endswith('.svg'): out_file += '.svg'
segs = segmentation_to_files(segmentation)
compose_view(
plot_segs(image_nii=anatomical,
seg_niis=[mask] + segs,
bbox_nii=mask,
out_file='reports.svg',
masked=False,
compress='auto'),
fg_svgs=None,
out_file=out_file
)
for fname in segs: os.remove(fname)
return out_file