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Update NDTIFF reader #145

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merged 1 commit into from
Jun 20, 2023
Merged

Update NDTIFF reader #145

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27 changes: 8 additions & 19 deletions iohub/ndtiff.py
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Original file line number Diff line number Diff line change
Expand Up @@ -140,32 +140,21 @@ def get_zarr(self, position: int) -> zarr.array:
# TODO: try casting the dask array into a zarr array
# using `dask.array.to_zarr()`.
# Currently this call brings the data into memory
Comment on lines 140 to 142
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I believe now as_array returns a dask array without bring the data into memory, I think you can test and remove this comment

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I think this means that dask.array.to_zarr() brings data to memory if the store is a MemoryStore so this method cannot be consistent with other get_zarr() methods.

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Hopefully this won't be a problem anymore after #132 and we refactor this.


ax = [
ax_
for ax_ in ["position", "time", "channel", "z"]
if ax_ in self._axes
]

if "position" in self._axes.keys():
# da is Dask array
da = self.dataset.as_array(axes=ax, position=position)
else:
if position not in (0, None):
warnings.warn(
f"Position index {position} is not part of this dataset."
f" Returning data at default position."
)
da = self.dataset.as_array(axes=ax)

if "position" not in self._axes.keys() and position not in (0, None):
warnings.warn(
f"Position index {position} is not part of this dataset. "
"Returning data at the default position."
)
position = None
da = self.dataset.as_array(position=position)
shape = (
self.frames,
self.channels,
self.slices,
self.height,
self.width,
)

# add singleton axes so output is 5D
return da.reshape(shape)

def get_array(self, position: int) -> np.ndarray:
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2 changes: 1 addition & 1 deletion setup.cfg
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Expand Up @@ -33,7 +33,7 @@ install_requires =
pydantic>=1.10.2
tifffile>=2023.2.3, <2023.3.15
natsort>=7.1.1
ndtiff>=1.9.0
ndtiff>=2.1.0
zarr>=2.13
tqdm
pillow>=9.4.0
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