Write OME-Zarr 0.5

docs/examples/run_update_ome_zarr.py

@@ -0,0 +1,81 @@
+"""
+Update OME-Zarr Version
+=======================
+
+This script shows how to write the same OME-Zarr image
+using a new version.
+"""
+
+# %%
+from pathlib import Path
+from tempfile import TemporaryDirectory
+
+import numpy as np
+
+from iohub.ngff import TransformationMeta, open_ome_zarr
+
+# %%
+# Set storage path
+tmp_dir = TemporaryDirectory()
+old_store_path = Path(tmp_dir.name) / "old.zarr"
+new_store_path = Path(tmp_dir.name) / "new.zarr"
+
+# %%
+# Create a version 0.4 OME-Zarr dataset
+random_image = np.random.randint(
+    0, np.iinfo(np.uint16).max, size=(10, 2, 32, 128, 128), dtype=np.uint16
+)
+scale = [2.0, 3.0, 4.0, 5.0, 6.0]
+
+
+with open_ome_zarr(
+    old_store_path,
+    layout="hcs",
+    mode="w-",
+    channel_names=["DAPI", "GFP"],
+    version="0.4",
+) as old_dataset:
+    position = old_dataset.create_position("A", "1", "0")
+    image = position.create_image(
+        "0",
+        random_image,
+        chunks=(1, 1, 4, 32, 32),
+        transform=[TransformationMeta(type="scale", scale=scale)],
+    )
+
+# %%
+# Write the same image with version 0.5 and sharding
+
+with open_ome_zarr(old_store_path, mode="r", layout="hcs") as old_dataset:
+    with open_ome_zarr(
+        new_store_path,
+        layout="hcs",
+        mode="w",
+        channel_names=old_dataset.channel_names,
+        version="0.5",
+    ) as new_dataset:
+        for name, old_position in old_dataset.positions():
+            row, col, fov = name.split("/")
+            new_position = new_dataset.create_position(row, col, fov)
+            old_image = old_position["0"]
+            new_image = new_position.create_image(
+                "0",
+                data=old_image.numpy(),
+                chunks=(1, 1, 4, 32, 32),
+                shards_ratio=(2, 1, 8, 4, 4),
+                transform=old_position.metadata.multiscales[0]
+                .datasets[0]
+                .coordinate_transformations,
+            )
+
+# %%
+# Read the new FOV to verify it was written correctly
+with open_ome_zarr(new_store_path / "A/1/0", mode="r") as dataset:
+    assert dataset.scale == scale
+    image = dataset["0"]
+    assert image.shards == (2, 1, 32, 128, 128)
+    assert np.array_equal(image.numpy(), random_image)
+
+# %%
+# Clean up
+tmp_dir.cleanup()

iohub/ngff/models.py

@@ -219,9 +219,7 @@ class VersionMeta(MetaBase):
     """OME-NGFF spec version. Default is the current version (0.4)."""
 
     # SHOULD
-    version: Literal["0.1", "0.2", "0.3", "0.4", "0.5"] | None = Field(
-        default=None, exclude=lambda v: v is None
-    )
+    version: Literal["0.1", "0.2", "0.3", "0.4", "0.5"] | None = None
 
 
 class MultiScaleMeta(VersionMeta):
@@ -302,6 +300,9 @@ class ImagesMeta(MetaBase):
     multiscales: list[MultiScaleMeta]
     # transitional, optional
     omero: OMEROMeta | None = None
+    # only for OME-NGFF v0.5
+    version: Literal["0.5"] | None = None
+    model_config = ConfigDict(extra="allow")
 
 
 class LabelsMeta(MetaBase):