fix: Oriented point rendering in Neuroglancer (#358)

* Fixing oriented point rendering

* Refactor pytest fixture name

* Adding tests

* reverting config change

* updating oriented point layer name

* addresing pr feedback

ingestion_tools/scripts/importers/visualization_config.py

@@ -75,9 +75,9 @@ def _to_segmentation_mask_layer(
         **kwargs,
     ) -> dict[str, Any]:
         return state_generator.generate_segmentation_mask_layer(
-            source_path,
-            f"{name_prefix} segmentation",
-            self.config.https_prefix,
+            source=source_path,
+            name=f"{name_prefix} segmentation",
+            url=self.config.https_prefix,
             color=color,
             scale=resolution,
             is_visible=file_metadata.get("is_visualization_default"),
@@ -90,18 +90,23 @@ def _to_point_layer(
         name_prefix: str,
         color: str,
         resolution: tuple[float, float, float],
-        is_instance_segmentation: bool,
+        shape: str,
         **kwargs,
     ) -> dict[str, Any]:
-        return state_generator.generate_point_layer(
-            source_path,
-            f"{name_prefix} point",
-            self.config.https_prefix,
-            color=color,
-            scale=resolution,
-            is_visible=file_metadata.get("is_visualization_default"),
-            is_instance_segmentation=is_instance_segmentation,
-        )
+        is_instance_segmentation = shape == "InstanceSegmentation"
+        args = {
+            "source": source_path,
+            "url": self.config.https_prefix,
+            "color": color,
+            "scale": resolution,
+            "is_visible": file_metadata.get("is_visualization_default"),
+            "is_instance_segmentation": is_instance_segmentation,
+        }
+        if shape == "OrientedPoint":
+            args["name"] = f"{name_prefix} orientedpoint"
+            return state_generator.generate_oriented_point_layer(**args)
+        args["name"] = f"{name_prefix} point"
+        return state_generator.generate_point_layer(**args)
 
     def get_annotation_layer_info(self, alignment_metadata_path: str) -> dict[str, Any]:
         precompute_path = self.config.resolve_output_path("annotation_viz", self)
@@ -155,7 +160,7 @@ def get_annotation_layer_info(self, alignment_metadata_path: str) -> dict[str, A
                         "file_metadata": file,
                         "name_prefix": name_prefix,
                         "color": hex_colors[0],
-                        "is_instance_segmentation": is_instance_seg,
+                        "shape": shape,
                     },
                 }
 
@@ -180,7 +185,6 @@ def _create_config(self, alignment_metadata_path: str) -> dict[str, Any]:
                 layers.append(self._to_segmentation_mask_layer(**args))
             elif info["shape"] in {"Point", "OrientedPoint", "InstanceSegmentation"}:
                 layers.append(self._to_point_layer(**args))
-
         return state_generator.combine_json_layers(layers, scale=resolution)
 
     @classmethod

ingestion_tools/scripts/tests/s3_import/test_alignments.py

@@ -80,7 +80,7 @@ def validate(expected: dict, prefix: str) -> None:
 
 
 @pytest.fixture
-def create_config(
+def config_generator(
     s3_fs: FileSystemApi,
     test_output_bucket: str,
     input_bucket: str,
@@ -102,15 +102,15 @@ def _create(path: str) -> DepositionImportConfig:
     ],
 )
 def test_alignment_import_item(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     add_alignment_metadata: Callable[[str, int], None],
     validate_dataframe: Callable[[str, str], None],
     validate_metadata: Callable[[dict, str], None],
     test_output_bucket: str,
     deposition_id: int,
     id_prefix: int,
 ) -> None:
-    config = create_config("dataset1.yaml")
+    config = config_generator("dataset1.yaml")
     parents = get_parents(config)
     dataset_name = parents.get("dataset").name
     run_name = parents.get("run").name
@@ -182,15 +182,15 @@ def test_alignment_import_item(
     ],
 )
 def test_alignment_import_item_aretomo(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     add_alignment_metadata: Callable[[str, int], None],
     validate_dataframe: Callable[[str, str], None],
     validate_metadata: Callable[[dict, str], None],
     test_output_bucket: str,
     deposition_id: int,
     id_prefix: int,
 ) -> None:
-    config = create_config("dataset2.yaml")
+    config = config_generator("dataset2.yaml")
     parents = get_parents(config)
     dataset_name = parents.get("dataset").name
     run_name = parents.get("run").name
@@ -251,12 +251,12 @@ def test_alignment_import_item_aretomo(
 
 
 def test_default_alignment_import_with_tomograms(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     s3_client: S3Client,
     test_output_bucket: str,
     validate_metadata: Callable[[dict, str], None],
 ) -> None:
-    config = create_config("alignments/alignment1.yaml")
+    config = config_generator("alignments/alignment1.yaml")
     parents = get_parents(config)
 
     alignments = list(AlignmentImporter.finder(config, **parents))
@@ -289,11 +289,11 @@ def test_default_alignment_import_with_tomograms(
 
 
 def test_default_alignment_import_without_tomograms(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     s3_client: S3Client,
     test_output_bucket: str,
 ) -> None:
-    config = create_config("alignments/alignment2.yaml")
+    config = config_generator("alignments/alignment2.yaml")
     parents = get_parents(config)
 
     alignments = list(AlignmentImporter.finder(config, **parents))
@@ -309,11 +309,11 @@ def test_default_alignment_import_without_tomograms(
 
 
 def test_custom_alignment_import_without_tomograms(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     s3_client: S3Client,
     test_output_bucket: str,
 ) -> None:
-    config = create_config("alignments/alignment3.yaml")
+    config = config_generator("alignments/alignment3.yaml")
     parents = get_parents(config)
 
     alignments = list(AlignmentImporter.finder(config, **parents))
@@ -329,12 +329,12 @@ def test_custom_alignment_import_without_tomograms(
 
 
 def test_custom_alignment_with_dimensions_import_without_tomograms(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     test_output_bucket: str,
     validate_dataframe: Callable[[str, str, int], None],
     validate_metadata: Callable[[dict, str, int], None],
 ) -> None:
-    config = create_config("alignments/alignment4.yaml")
+    config = config_generator("alignments/alignment4.yaml")
     parents = get_parents(config)
 
     alignments = list(AlignmentImporter.finder(config, **parents))
@@ -389,11 +389,11 @@ def test_custom_alignment_with_dimensions_import_without_tomograms(
 
 
 def test_allow_import_is_false(
-    create_config: Callable[[str], DepositionImportConfig],
+    config_generator: Callable[[str], DepositionImportConfig],
     test_output_bucket: str,
     s3_client: S3Client,
 ) -> None:
-    config = create_config("alignments/alignment4.yaml")
+    config = config_generator("alignments/alignment4.yaml")
     parents = get_parents(config)
 
     alignments = list(AlignmentImporter.finder(config, **parents))