chore: comply with ruff by ignoring napari specific import errors

Author: 404Simon

vesskel/_napari.py

@@ -15,7 +15,7 @@
 if TYPE_CHECKING:
     # These imports are only used for annotations and are therefore
     # guarded by TYPE_CHECKING to avoid runtime import-time coupling.
-    from napari.layers import Image
+    from napari.layers import Image  # noqa: F401
 
 from vesskel.config import (
     ExtractionConfig,
@@ -40,7 +40,7 @@ def __init__(self, napari_viewer):
     def _setup_ui(self):
         # ---------- extraction parameters (magicgui) ----------
         def _extraction_params(
-            image: "napari.layers.Image",
+            image: "napari.layers.Image",  # noqa: F821
             extract_branches: bool = False,
             extract_branch_text: bool = False,
             extract_nodes: bool = False,
@@ -347,9 +347,7 @@ def _on_analyze(self) -> None:
 
             n_fg = int((img.data > 0).sum())
             n_skel = int(result.skeleton.sum())
-            show_info(
-                f"Analysis: {n_fg} → {n_skel} skeleton pixels " f"in {elapsed:.3f}s"
-            )
+            show_info(f"Analysis: {n_fg} → {n_skel} skeleton pixels in {elapsed:.3f}s")
 
             # Always add skeleton layer first.
             self.viewer.add_layer(
@@ -379,7 +377,7 @@ def _on_analyze(self) -> None:
                     self.viewer.add_layer(layer)
                 except Exception as e:
                     show_info(
-                        f"Failed to add layer " f"{meta.get('name', '<unnamed>')}: {e}"
+                        f"Failed to add layer {meta.get('name', '<unnamed>')}: {e}"
                     )
         except (ValueError, RuntimeError, OSError) as e:
             show_error(f"Analysis failed: {e}")

vesskel/cli.py

@@ -68,13 +68,17 @@ def _make_parser() -> argparse.ArgumentParser:
         "init",
         help="Create a starter config JSON.",
     )
-    init_parser.add_argument("out", nargs="?", default="vesskel.json", help="Output config path.")
+    init_parser.add_argument(
+        "out", nargs="?", default="vesskel.json", help="Output config path."
+    )
 
     validate_parser = subparsers.add_parser(
         "validate",
         help="Validate and print a normalised config JSON.",
     )
-    validate_parser.add_argument("config", nargs="?", default="vesskel.json", help="Config JSON path.")
+    validate_parser.add_argument(
+        "config", nargs="?", default="vesskel.json", help="Config JSON path."
+    )
 
     completions_parser = subparsers.add_parser(
         "completions",

vesskel/napari_layers.py

@@ -9,7 +9,7 @@
 from vesskel.features import compute_tortuosity, extract_node_features
 
 if TYPE_CHECKING:
-    from napari.types import LayerDataTuple
+    from napari.types import LayerDataTuple  # noqa: F401
 
 
 def extract_skeleton_layers(
@@ -20,7 +20,7 @@ def extract_skeleton_layers(
     config: ExtractionConfig | None = None,
     features: dict[str, float] | None = None,
     radius_matrix: np.ndarray | None = None,
-) -> list["napari.types.LayerDataTuple"]:
+) -> list["napari.types.LayerDataTuple"]:  # noqa: F821
     """Extract visualization layers from a binary skeleton.
 
     Parameters
@@ -56,15 +56,15 @@ def extract_skeleton_layers(
                 layers.append(text_layer)
 
     if config.nodes:
-        node_layer = _extract_node_features_layer(base_name, graph, branch_data, radius_matrix=radius_matrix)
+        node_layer = _extract_node_features_layer(
+            base_name, graph, branch_data, radius_matrix=radius_matrix
+        )
         if node_layer is not None:
             layers.append(node_layer)
 
     if config.summary:
         if features is None:
-            raise ValueError(
-                "features is required when summary is enabled"
-            )
+            raise ValueError("features is required when summary is enabled")
         summary_layer = _extract_summary_features_layer(
             skeleton,
             base_name,
@@ -84,7 +84,7 @@ def _extract_radius_layer(
     radius_matrix: np.ndarray,
     skeleton: np.ndarray,
     base_name: str,
-) -> "napari.types.LayerDataTuple | None":
+) -> "napari.types.LayerDataTuple | None":  # noqa: F821
     """Create an image layer showing per-pixel vessel radius on the skeleton."""
     if not np.any(radius_matrix):
         return None
@@ -103,7 +103,7 @@ def _extract_branch_features_layer(
     base_name: str,
     graph: Skeleton,
     branch_data,
-) -> "napari.types.LayerDataTuple | None":
+) -> "napari.types.LayerDataTuple | None":  # noqa: F821
     """Extract branch features and generate paths layer.
 
     Parameters
@@ -161,9 +161,9 @@ def _extract_branch_features_layer(
 
 
 def _extract_branch_text_layer(
-    branch_layer: "napari.types.LayerDataTuple",
+    branch_layer: "napari.types.LayerDataTuple",  # noqa: F821
     base_name: str,
-) -> "napari.types.LayerDataTuple":
+) -> "napari.types.LayerDataTuple":  # noqa: F821
     path_data = branch_layer[0]
     branch_data = branch_layer[1]["properties"]
 
@@ -197,7 +197,7 @@ def _extract_summary_features_layer(
     skeleton: np.ndarray,
     base_name: str,
     features: dict[str, float],
-) -> "napari.types.LayerDataTuple":
+) -> "napari.types.LayerDataTuple":  # noqa: F821
     """Create a summary point layer displaying global skeleton features.
 
     Parameters
@@ -242,17 +242,24 @@ def _extract_node_features_layer(
     graph: Skeleton,
     branch_data,
     radius_matrix: np.ndarray | None = None,
-) -> "napari.types.LayerDataTuple | None":
+) -> "napari.types.LayerDataTuple | None":  # noqa: F821
     """Create a points layer showing graph nodes colored by degree."""
-    node_records = extract_node_features(graph, branch_data, radius_matrix=radius_matrix)
+    node_records = extract_node_features(
+        graph, branch_data, radius_matrix=radius_matrix
+    )
     if not node_records:
         return None
 
     ndim = graph.coordinates.shape[1]
-    points = np.array([tuple(r[f"coord_{d}"] for d in range(ndim)) for r in node_records], dtype=float)
-
-    props = {k: [r[k] for r in node_records] for k in node_records[0].keys()
-             if not k.startswith("coord_")}
+    points = np.array(
+        [tuple(r[f"coord_{d}"] for d in range(ndim)) for r in node_records], dtype=float
+    )
+
+    props = {
+        k: [r[k] for r in node_records]
+        for k in node_records[0].keys()
+        if not k.startswith("coord_")
+    }
 
     meta = {
         "name": f"{base_name}_nodes",

vesskel/pipeline.py

@@ -24,15 +24,15 @@
 from vesskel.thin import lee94_thin
 
 if TYPE_CHECKING:
-    from napari.types import LayerDataTuple
+    from napari.types import LayerDataTuple  # noqa: F401
 
 
 @dataclass
 class AnalysisResult:
     """Container for single-image analysis outputs."""
 
     skeleton: np.ndarray
-    layers: list["napari.types.LayerDataTuple"]
+    layers: list["napari.types.LayerDataTuple"]  # noqa: F821
     summary_features: dict[str, float]
     branch_records: list[dict[str, object]]
     node_records: list[dict[str, object]]
@@ -121,8 +121,12 @@ def analyze_binary_image(
             branch_data[key] = arr
 
         if radius_stats is not None:
-            radius_stats["mean_segment_volume"] = float(np.nanmean(branch_data["volume"]))
-            radius_stats["mean_surface_area"] = float(np.nanmean(branch_data["surface_area"]))
+            radius_stats["mean_segment_volume"] = float(
+                np.nanmean(branch_data["volume"])
+            )
+            radius_stats["mean_surface_area"] = float(
+                np.nanmean(branch_data["surface_area"])
+            )
 
     if not branch_data.empty:
         euclidean = branch_data["euclidean-distance"].to_numpy(dtype=float)