2d to 3d chunking

pyproject.toml

@@ -27,7 +27,7 @@ authors = [
 # Required Python version and dependencies
 requires-python = ">=3.10"
 dependencies = [
-    "fractal-tasks-core==1.4.0","ngio==0.1.4",
+    "fractal-tasks-core==1.4.2","ngio==0.1.6",
 ]
 
 # Optional dependencies (e.g. for `pip install -e ".[dev]"`, see

src/fractal_helper_tasks/__FRACTAL_MANIFEST__.json

@@ -49,6 +49,9 @@
       "input_types": {
         "is_3D": false
       },
+      "output_types": {
+        "is_3D": true
+      },
       "tags": [
         "Mixed modality",
         "2D to 3D workflows"
@@ -113,6 +116,11 @@
             "type": "string",
             "description": "If the image name between 2D & 3D don't match, this is the suffix that should be added to the 3D image. If the 2D image is in \"/path/to/my_plate_mip.zarr/B/03/0\" and the 3D image is in \"/path/to/my_plate.zarr/B/03/0_illum_corr\", the value should be \"_illum_corr\"."
           },
+          "z_chunks": {
+            "title": "Z Chunks",
+            "type": "integer",
+            "description": "Chunking for the Z dimension. Set this parameter if you want the label image to be chunked differently from the 3D image in the Z dimension."
+          },
           "overwrite": {
             "default": false,
             "title": "Overwrite",

src/fractal_helper_tasks/convert_2D_segmentation_to_3D.py

@@ -99,6 +99,7 @@ def convert_2D_segmentation_to_3D(
     plate_suffix: str = "_mip",
     image_suffix_2D_to_remove: Optional[str] = None,
     image_suffix_3D_to_add: Optional[str] = None,
+    z_chunks: Optional[int] = None,
     overwrite: bool = False,
 ) -> None:
     """Convert 2D segmentation to 3D segmentation.
@@ -141,6 +142,9 @@ def convert_2D_segmentation_to_3D(
             If the 2D image is in "/path/to/my_plate_mip.zarr/B/03/0" and the
             3D image is in "/path/to/my_plate.zarr/B/03/0_illum_corr", the
             value should be "_illum_corr".
+        z_chunks: Chunking for the Z dimension. Set this parameter if you want
+            the label image to be chunked differently from the 3D image in
+            the Z dimension.
         overwrite: If `True`, overwrite existing label and ROI tables in the
             3D OME-Zarr
     """
@@ -173,12 +177,20 @@ def convert_2D_segmentation_to_3D(
 
     # 1a) Load a 2D label image
     label_img = da.from_zarr(f"{zarr_url}/labels/{label_name}/{level}")
-    chunks = label_img.chunksize
+    chunks = list(label_img.chunksize)
 
     # 1b) Get number z planes & Z spacing from 3D OME-Zarr file
     with zarr.open(zarr_3D_url, mode="rw+") as zarr_img:
         zarr_3D = da.from_zarr(zarr_img[0])
         new_z_planes = zarr_3D.shape[-3]
+        z_chunk_3d = zarr_3D.chunksize[-3]
+
+    # TODO: Improve axis detection in ngio refactor?
+    if z_chunks:
+        chunks[-3] = z_chunks
+    else:
+        chunks[-3] = z_chunk_3d
+    chunks = tuple(chunks)
 
     image_meta = load_NgffImageMeta(zarr_3D_url)
     z_pixel_size = image_meta.get_pixel_sizes_zyx(level=0)[0]
@@ -249,12 +261,15 @@ def convert_2D_segmentation_to_3D(
 
     logger.info("Finished 2D to 3D conversion")
 
-    output_dict = dict(
-        filters=dict(
-            types=dict(is_3D=True),
-        )
+    # Give the 3D image as an output so that filters are applied correctly
+    image_list_updates = dict(
+        image_list_updates=[
+            dict(
+                zarr_url=zarr_3D_url,
+            )
+        ]
     )
-    return output_dict
+    return image_list_updates
 
 
 if __name__ == "__main__":

src/fractal_helper_tasks/dev/task_list.py

@@ -13,6 +13,7 @@
     ),
     ParallelTask(
         input_types=dict(is_3D=False),
+        output_types=dict(is_3D=True),
         name="Convert 2D segmentation to 3D",
         executable="convert_2D_segmentation_to_3D.py",
         meta={"cpus_per_task": 2, "mem": 8000},

src/fractal_helper_tasks/rechunk_zarr.py

@@ -131,7 +131,6 @@ def rechunk_zarr(
                     types=dict(rechunked=True),
                 )
             ],
-            filters=dict(types=dict(rechunked=True)),
         )
         return output
 

tests/test_rechunk_zarr.py

@@ -119,7 +119,6 @@ def test_rechunk_no_overwrite_input(tmp_zenodo_zarr: list[str]):
                 types=dict(rechunked=True),
             )
         ],
-        filters=dict(types=dict(rechunked=True)),
     )
     assert expected_output == output