perf(perception): reuse local surface cell observations

src/k1link/compute/lidar_local_surface_geometry.py

@@ -166,6 +166,16 @@ def update_cache(
     profile: K1LocalSurfaceProfile,
 ) -> None:
     keys, points = cloud_cell_observations(cloud, profile)
+    update_cache_observations(cache, keys, points, session_seconds)
+
+
+def update_cache_observations(
+    cache: dict[tuple[int, int], tuple[float, float]],
+    keys: npt.NDArray[np.int64],
+    points: npt.NDArray[np.float64],
+    session_seconds: float,
+) -> None:
+    """Update a surface cache from already aggregated cell observations."""
     for key, point in zip(keys, points, strict=True):
         cache[(int(key[0]), int(key[1]))] = (float(point[2]), session_seconds)
 

src/k1link/compute/lidar_local_surface_shadow.py

@@ -46,7 +46,7 @@ from .lidar_local_surface_geometry import (
     step_candidate_keys as _step_candidate_keys,
 )
 from .lidar_local_surface_geometry import (
-    update_cache as _update_cache,
+    update_cache_observations as _update_cache_observations,
 )
 from .live_perception import LatestWinsQueue
 
@@ -489,7 +489,7 @@ class K1LocalSurfaceShadowEstimator:
             position,
             self.profile,
         )
-        _, current_cell_points = _cloud_cell_observations(
+        current_cell_keys, current_cell_points = _cloud_cell_observations(
             local_cloud,
             self.profile,
         )
@@ -499,11 +499,11 @@ class K1LocalSurfaceShadowEstimator:
             position,
             self.profile,
         )
-        _update_cache(
+        _update_cache_observations(
             self._cache,
-            local_cloud,
+            current_cell_keys,
+            current_cell_points,
             value.session_seconds,
-            self.profile,
         )
         cell_keys, cell_points, cell_times = _local_cache_records(
             self._cache,