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Rounding scheme for neuroglancer fetching needs revision #642

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merged 3 commits into from
Mar 7, 2025
Merged

Rounding scheme for neuroglancer fetching needs revision #642

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8835d06
Take ceil of target shape instead maxpoint for ensuring minimum voxel…
dickscheid Feb 9, 2025
928eeca
Revert ng voxel selection method
AhmetNSimsek Feb 24, 2025
dff053b
ng debug info for selected and provided voi
AhmetNSimsek Feb 24, 2025
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15 changes: 6 additions & 9 deletions siibra/volumes/providers/neuroglancer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -529,14 +529,7 @@
if voi is None:
bbox_ = _boundingbox.BoundingBox((0, 0, 0), self.size, space=None)
else:
bbox_ = voi.transform(np.linalg.inv(self.affine))

for dim in range(3):
if bbox_.shape[dim] < 1:
logger.warning(
f"Bounding box in voxel space will be enlarged to by {self.res_mm[dim]} along axis {dim}."
)
bbox_.maxpoint[dim] = bbox_.maxpoint[dim] + self.res_mm[dim]
bbox_ = voi.transform(np.linalg.inv(self.affine), space=None)

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# extract minimum and maximum the chunk indices to be loaded
gx0, gy0, gz0 = self._point_to_lower_chunk_idx(tuple(bbox_.minpoint))
Expand All @@ -559,8 +552,12 @@
# exact bounding box requested, to cut off undesired borders
data_min = np.array([gx0, gy0, gz0]) * self.chunk_sizes
x0, y0, z0 = (np.array(bbox_.minpoint) - data_min).astype("int")
xd, yd, zd = np.ceil((np.array(bbox_.maxpoint))).astype(int) - np.floor((np.array(bbox_.minpoint))).astype(int)
xd, yd, zd = np.ceil(bbox_.maxpoint).astype(int) - np.floor(bbox_.minpoint).astype(int)
offset = tuple(bbox_.minpoint)
if voi is not None:
logger.debug(

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f"Input: {voi.minpoint.coordinate}, {voi.maxpoint.coordinate}.\nVoxel space: {bbox_.minpoint.coordinate}, {bbox_.maxpoint.coordinate}"
)

# build the nifti image
trans = np.identity(4)[[2, 1, 0, 3], :] # zyx -> xyz
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