feat(lidar): admit and benchmark GOOSE baseline

tests/test_lidar_ground.py

@@ -157,6 +157,48 @@ def test_local_percentile_ground_is_point_aligned_and_non_mutating() -> None:
     np.testing.assert_array_equal(xyzi, unchanged)
 
 
+def test_local_percentile_grid_index_preserves_exact_radius_result() -> None:
+    random = np.random.default_rng(42)
+    xyzi = random.normal(size=(240, 4)).astype(np.float32)
+    xyzi[:, :2] *= 4
+    profile = GroundBenchmarkProfile(
+        current_cell_size_m=0.6,
+        current_local_radius_m=1.7,
+        current_lower_percentile=11,
+        current_maximum_below_ground_m=0.2,
+        current_maximum_above_ground_m=0.18,
+        current_minimum_local_points=5,
+    )
+
+    actual = LocalPercentileGroundSegmenter(profile=profile).segment(xyzi)
+
+    xyz = xyzi[:, :3].astype(np.float64)
+    cell_keys = np.floor(xyz[:, :2] / profile.current_cell_size_m).astype(np.int64)
+    unique_cells, inverse = np.unique(cell_keys, axis=0, return_inverse=True)
+    expected = np.zeros(xyzi.shape[0], dtype=np.bool_)
+    global_ground_z = float(np.percentile(xyz[:, 2], profile.current_lower_percentile))
+    for cell_index in range(unique_cells.shape[0]):
+        point_indices = np.flatnonzero(inverse == cell_index)
+        center_xy = np.median(xyz[point_indices, :2], axis=0)
+        delta_xy = xyz[:, :2] - center_xy
+        local = xyz[
+            np.einsum("ij,ij->i", delta_xy, delta_xy)
+            <= profile.current_local_radius_m**2,
+            2,
+        ]
+        ground_z = (
+            float(np.percentile(local, profile.current_lower_percentile))
+            if local.size >= profile.current_minimum_local_points
+            else global_ground_z
+        )
+        z = xyz[point_indices, 2]
+        expected[point_indices] = (
+            z >= ground_z - profile.current_maximum_below_ground_m
+        ) & (z <= ground_z + profile.current_maximum_above_ground_m)
+
+    np.testing.assert_array_equal(actual.ground_mask, expected)
+
+
 def test_ground_benchmark_is_immutable_diagnostic_evidence(tmp_path: Path) -> None:
     replay = _Replay()
     output = build_lidar_ground_benchmark(