Change locations for zarr image in single image workflows

Adds nesting for zarr file locations for single image workflows (Closes #343) Previously, zarr directory structure was affected by `scale-format-string` argument in bf2raw command which has been removed. Update SEM neuroglancer metadata to new format (Closes #342)
niaid · Oct 5, 2023 · 46ee92d · 46ee92d
1 parent eea099d
commit 46ee92d
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Showing 3 changed files with 22 additions and 15 deletions.
diff --git a/em_workflows/brt/flow.py b/em_workflows/brt/flow.py
@@ -503,16 +503,16 @@ def gen_zarr(fp_in: FilePath):
 def gen_ng_metadata(fp_in: FilePath) -> Dict:
     file_path = fp_in
     asset_fp = Path(f"{file_path.assets_dir}/{file_path.base}.zarr")
-    zarr_fp = Path(f"{file_path.working_dir}/{file_path.base}.zarr")
-    hw_images = HedwigZarrImages(zarr_fp)
+    hw_images = HedwigZarrImages(asset_fp)
     _, hw_image = next(hw_images.series())
 
+    first_zarr_arr = Path(asset_fp.as_posix() + "/0/0")
     ng_asset = file_path.gen_asset(
-        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=asset_fp
+        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=first_zarr_arr
     )
     metadata = {
-        "shader": "Grayscale",
-        "dimensions": "XYZ",
+        "shader": hw_image.shader_type,
+        "dimensions": hw_image.dimensions,
         "shaderParameters": hw_image.neuroglancer_shader_parameters(),
     }
     ng_asset["metadata"] = metadata

diff --git a/em_workflows/lrg_2d_rgb/flow.py b/em_workflows/lrg_2d_rgb/flow.py
@@ -59,15 +59,16 @@ def gen_zarr(file_path: FilePath) -> None:
 
 @task
 def generate_ng_asset(file_path: FilePath) -> Dict:
-    output_zarr = Path(f"{file_path.assets_dir}/{file_path.base}.zarr")
-    zarr_images = HedwigZarrImages(zarr_path=output_zarr, read_only=False)
-    zarr_image = zarr_images[list(zarr_images.get_series_keys())[0]]
+    asset_fp = Path(f"{file_path.assets_dir}/{file_path.base}.zarr")
+    hw_images = HedwigZarrImages(zarr_path=asset_fp, read_only=False)
+    hw_image = hw_images[list(hw_images.get_series_keys())[0]]
+    first_zarr_arr = Path(asset_fp.as_posix() + "/0/0")
     ng_asset = file_path.gen_asset(
-        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=output_zarr
+        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=first_zarr_arr
     )
     ng_asset["metadata"] = dict(
-        shader=zarr_image.shader_type,
-        dimensions=zarr_image.dims,
+        shader=hw_image.shader_type,
+        dimensions=hw_image.dims,
         # shaderParameters=zarr_image.neuroglancer_shader_parameters()
     )
     return ng_asset

diff --git a/em_workflows/sem_tomo/flow.py b/em_workflows/sem_tomo/flow.py
@@ -5,7 +5,7 @@
 from typing import Dict
 from prefect import Flow, task, Parameter, unmapped
 from prefect.run_configs import LocalRun
-from pytools.workflow_functions import visual_min_max
+from pytools.HedwigZarrImages import HedwigZarrImages
 
 from em_workflows.utils import utils
 from em_workflows.utils import neuroglancer as ng
@@ -234,13 +234,19 @@ def gen_zarr(fp_in: FilePath) -> None:
 def gen_ng_metadata(fp_in: FilePath) -> Dict:
     file_path = fp_in
     asset_fp = Path(f"{file_path.assets_dir}/{file_path.base}.zarr")
+    output_zarr = Path(f"{file_path.assets_dir}/{file_path.base}.zarr")
+    hw_images = HedwigZarrImages(zarr_path=output_zarr, read_only=False)
+    hw_image = hw_images[list(hw_images.get_series_keys())[0]]
 
     first_zarr_arr = Path(asset_fp.as_posix() + "/0/0")
-
     ng_asset = file_path.gen_asset(
-        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=asset_fp
+        asset_type=AssetType.NEUROGLANCER_ZARR, asset_fp=first_zarr_arr
+    )
+    ng_asset["metadata"] = dict(
+        shader=hw_image.shader_type,
+        dimensions=hw_image.dims,
+        shaderParameters=hw_image.neuroglancer_shader_parameters(),
     )
-    ng_asset["metadata"] = visual_min_max(mad_scale=5, input_image=first_zarr_arr)
     return ng_asset