ENH: Add a test for large image serialization with tensorstore

test/test_to_ngff_zarr_tensorstore.py

@@ -3,8 +3,16 @@
 
 import pytest
 import zarr
+from dask_image import imread
 
-from ngff_zarr import Methods, to_multiscales, to_ngff_zarr, from_ngff_zarr
+from ngff_zarr import (
+    Methods,
+    to_multiscales,
+    to_ngff_zarr,
+    from_ngff_zarr,
+    config,
+    to_ngff_image,
+)
 
 from ._data import verify_against_baseline
 
@@ -47,3 +55,24 @@ def test_gaussian_isotropic_scale_factors(input_images):
         to_ngff_zarr(tmpdir, multiscales, use_tensorstore=True)
         multiscales = from_ngff_zarr(tmpdir)
         verify_against_baseline(dataset_name, baseline_name, multiscales)
+
+
+def test_large_image_serialization(input_images):
+    pytest.importorskip("tensorstore")
+
+    default_mem_target = config.memory_target
+    config.memory_target = int(1e6)
+
+    dataset_name = "lung_series"
+    data = imread.imread(input_images[dataset_name])
+    image = to_ngff_image(
+        data=data,
+        dims=("z", "y", "x"),
+        scale={"z": 2.5, "y": 1.40625, "x": 1.40625},
+        translation={"z": 332.5, "y": 360.0, "x": 0.0},
+        name="LIDC2",
+    )
+    multiscales = to_multiscales(image)
+    with tempfile.TemporaryDirectory() as tmpdir:
+        to_ngff_zarr(tmpdir, multiscales, use_tensorstore=True)
+        config.memory_target = default_mem_target