diff --git a/API/ome_zarr_io.html b/API/ome_zarr_io.html index 4612fc8..ae66bd0 100644 --- a/API/ome_zarr_io.html +++ b/API/ome_zarr_io.html @@ -123,13 +123,20 @@
cvpl_tools.ome_zarr.io.load_dask_array_from_path(path: str, mode: str | None = None, use_zip: bool | None = None, level: int | None = None) → Array
-

Loads either a zarr folder or zarr zip file into a zarr group.

+

Loads either a zarr folder or zarr zip file into a dask array.

Compared to load_zarr_group_from_path, this function allows specifying which slice and channel to read using a query string syntax (idea thanks to Davis Bennett in the thread https://forum.image.sc/t/loading-only-one-channel-from-an-ome-zarr/97798)

-

Examples

-

load_dask_array_from_path(‘C://path/to/image.ome.zarr?slices=[1]’) # use channel 1 -load_dask_array_from_path(‘/path/to/image.ome.zarr?slices=[:, :100]’) # all channels, 0-99 on the second axis

+

Example

+

Loading an ome zarr array of shape (2, 200, 1000, 1000) using different slices:

+
arr_original = load_dask_array_from_path('file.ome.zarr', level=0)  # shape=(2, 200, 1000, 1000)
+arr1 = load_dask_array_from_path('file.ome.zarr?slices=[0]', level=0)  # shape=(200, 1000, 1000)
+arr2 = load_dask_array_from_path('file.ome.zarr?slices=[:, :100]', level=0)  # shape=(2, 100, 1000, 1000)
+arr3 = load_dask_array_from_path('file.ome.zarr?slices=[0:1, 0, -1:, ::2]', level=0)  # shape=(1, 1, 500)
+
+
+

Essentially, Python multi-index slicing can be done and the effect is similar to torch or numpy indexing using +slices.

Parameters:
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