@mytec: iter3.2.2 ready for test

backend/app/services/coverage_service.py

@@ -47,6 +47,7 @@ from app.services.materials_service import materials_service
 from app.services.dominant_path_service import (
     dominant_path_service, find_dominant_paths_vectorized,
     get_lod_level, LODLevel, SIMPLIFIED_MAX_BUILDINGS,
+    _filter_buildings_by_distance,
 )
 from app.services.street_canyon_service import street_canyon_service, Street
 from app.services.reflection_service import reflection_service
@@ -853,6 +854,16 @@ class CoverageService:
             if spatial_idx else buildings
         )
 
+        # Cap building count for the intersection loop — query_line can
+        # return hundreds of buildings; sort by proximity so the first
+        # intersecting building is found faster (loop breaks early).
+        if len(nearby_buildings) > 50:
+            nearby_buildings = _filter_buildings_by_distance(
+                nearby_buildings,
+                (site.lat, site.lon), (lat, lon),
+                max_count=50, max_distance=500,
+            )
+
         if settings.use_buildings and nearby_buildings:
             site_total_h = site.height + site_elevation
             point_total_h = 1.5 + point_elevation
@@ -897,22 +908,22 @@ class CoverageService:
                 try:
                     # LOD_SIMPLIFIED: limit buildings for mid-range points (1.5-3km)
                     dp_buildings = nearby_buildings
-                    dp_spatial = spatial_idx
                     if lod == LODLevel.SIMPLIFIED:
                         timing.setdefault("lod_simplified", 0)
                         timing["lod_simplified"] += 1
                         if len(nearby_buildings) > SIMPLIFIED_MAX_BUILDINGS:
                             dp_buildings = nearby_buildings[:SIMPLIFIED_MAX_BUILDINGS]
-                            dp_spatial = None  # Skip spatial queries, use filtered list only
                     else:
                         timing.setdefault("lod_full", 0)
                         timing["lod_full"] += 1
 
+                    # nearby_buildings already filtered via spatial index —
+                    # don't pass spatial_idx to avoid redundant query_line()
+                    # and query_point() inside the vectorized function.
                     dominant = find_dominant_paths_vectorized(
                         site.lat, site.lon, site.height,
                         lat, lon, 1.5,
                         site.frequency, dp_buildings,
-                        spatial_idx=dp_spatial,
                     )
                     if dominant['path_type'] == 'direct':
                         has_los = True