@mytec: 1.4iter ready for testing
This commit is contained in:
@@ -1,3 +1,5 @@
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import time
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from fastapi import APIRouter, HTTPException, BackgroundTasks
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from typing import List, Optional
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from pydantic import BaseModel
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@@ -5,7 +7,9 @@ from app.services.coverage_service import (
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coverage_service,
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CoverageSettings,
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SiteParams,
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CoveragePoint
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CoveragePoint,
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apply_preset,
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PRESETS,
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)
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router = APIRouter()
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@@ -23,6 +27,8 @@ class CoverageResponse(BaseModel):
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count: int
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settings: CoverageSettings
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stats: dict
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computation_time: float # seconds
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models_used: List[str] # which models were active
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@router.post("/calculate")
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@@ -30,7 +36,8 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
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"""
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Calculate RF coverage for one or more sites
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Returns grid of RSRP values with terrain and building effects
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Returns grid of RSRP values with terrain and building effects.
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Supports propagation model presets: fast, standard, detailed, full.
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"""
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if not request.sites:
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raise HTTPException(400, "At least one site required")
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@@ -45,6 +52,13 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
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if request.settings.resolution < 50:
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raise HTTPException(400, "Minimum resolution 50m")
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# Apply preset and determine active models
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effective_settings = apply_preset(request.settings.model_copy())
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models_used = _get_active_models(effective_settings)
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# Time the calculation
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start_time = time.time()
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# Calculate
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if len(request.sites) == 1:
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points = await coverage_service.calculate_coverage(
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@@ -57,6 +71,8 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
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request.settings
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)
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computation_time = time.time() - start_time
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# Calculate stats
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rsrp_values = [p.rsrp for p in points]
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los_count = sum(1 for p in points if p.has_los)
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@@ -68,16 +84,48 @@ async def calculate_coverage(request: CoverageRequest) -> CoverageResponse:
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"los_percentage": (los_count / len(points) * 100) if points else 0,
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"points_with_buildings": sum(1 for p in points if p.building_loss > 0),
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"points_with_terrain_loss": sum(1 for p in points if p.terrain_loss > 0),
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"points_with_reflection_gain": sum(1 for p in points if p.reflection_gain > 0),
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}
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return CoverageResponse(
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points=points,
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count=len(points),
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settings=request.settings,
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stats=stats
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settings=effective_settings,
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stats=stats,
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computation_time=round(computation_time, 2),
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models_used=models_used
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)
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@router.get("/presets")
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async def get_presets():
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"""Get available propagation model presets"""
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return {
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"presets": {
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"fast": {
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"description": "Quick calculation - terrain only",
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**PRESETS["fast"],
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"estimated_speed": "~5 seconds for 5km radius"
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},
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"standard": {
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"description": "Balanced - terrain + buildings with materials",
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**PRESETS["standard"],
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"estimated_speed": "~30 seconds for 5km radius"
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},
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"detailed": {
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"description": "Accurate - adds dominant path analysis",
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**PRESETS["detailed"],
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"estimated_speed": "~2 minutes for 5km radius"
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},
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"full": {
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"description": "Maximum realism - all models enabled",
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**PRESETS["full"],
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"estimated_speed": "~5 minutes for 5km radius"
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}
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}
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}
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@router.get("/buildings")
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async def get_buildings(
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min_lat: float,
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@@ -102,3 +150,23 @@ async def get_buildings(
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"count": len(buildings),
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"buildings": [b.model_dump() for b in buildings]
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}
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def _get_active_models(settings: CoverageSettings) -> List[str]:
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"""Determine which propagation models are active"""
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models = ["okumura_hata"] # Always active as base model
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if settings.use_terrain:
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models.append("terrain_los")
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if settings.use_buildings:
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models.append("buildings")
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if settings.use_materials:
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models.append("materials")
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if settings.use_dominant_path:
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models.append("dominant_path")
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if settings.use_street_canyon:
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models.append("street_canyon")
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if settings.use_reflections:
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models.append("reflections")
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return models
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@@ -17,7 +17,7 @@ async def lifespan(app: FastAPI):
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app = FastAPI(
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title="RFCP Backend API",
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description="RF Coverage Planning Backend",
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version="1.3.0",
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version="1.4.0",
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lifespan=lifespan,
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)
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@@ -39,7 +39,7 @@ app.include_router(coverage.router, prefix="/api/coverage", tags=["coverage"])
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@app.get("/")
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async def root():
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return {"message": "RFCP Backend API", "version": "1.3.0"}
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return {"message": "RFCP Backend API", "version": "1.4.0"}
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if __name__ == "__main__":
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@@ -15,6 +15,8 @@ class Building(BaseModel):
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height: float # meters
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levels: Optional[int] = None
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building_type: Optional[str] = None
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material: Optional[str] = None # Detected material type
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tags: dict = {} # Store all OSM tags for material detection
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class BuildingsService:
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@@ -144,12 +146,21 @@ class BuildingsService:
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# Estimate height
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height = self._estimate_height(tags)
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# Detect material from tags
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material_str = None
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if "building:material" in tags:
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material_str = tags["building:material"]
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elif "building:facade:material" in tags:
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material_str = tags["building:facade:material"]
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buildings.append(Building(
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id=element["id"],
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geometry=geometry,
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height=height,
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levels=int(tags.get("building:levels", 0)) or None,
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building_type=tags.get("building")
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building_type=tags.get("building"),
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material=material_str,
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tags=tags
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))
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return buildings
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@@ -5,6 +5,10 @@ from pydantic import BaseModel
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from app.services.terrain_service import terrain_service, TerrainService
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from app.services.los_service import los_service
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from app.services.buildings_service import buildings_service, Building
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from app.services.materials_service import materials_service
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from app.services.dominant_path_service import dominant_path_service
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from app.services.street_canyon_service import street_canyon_service, Street
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from app.services.reflection_service import reflection_service
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class CoveragePoint(BaseModel):
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@@ -15,14 +19,69 @@ class CoveragePoint(BaseModel):
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has_los: bool
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terrain_loss: float # dB
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building_loss: float # dB
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reflection_gain: float = 0.0 # dB (NEW)
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class CoverageSettings(BaseModel):
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radius: float = 10000 # meters
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resolution: float = 200 # meters
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min_signal: float = -120 # dBm threshold
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# Layer toggles
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use_terrain: bool = True
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use_buildings: bool = True
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use_materials: bool = True
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use_dominant_path: bool = False
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use_street_canyon: bool = False
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use_reflections: bool = False
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# Preset
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preset: Optional[str] = None # fast, standard, detailed, full
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# Propagation model presets
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PRESETS = {
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"fast": {
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"use_terrain": True,
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"use_buildings": False,
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"use_materials": False,
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"use_dominant_path": False,
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"use_street_canyon": False,
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"use_reflections": False,
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},
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"standard": {
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"use_terrain": True,
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"use_buildings": True,
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"use_materials": True,
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"use_dominant_path": False,
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"use_street_canyon": False,
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"use_reflections": False,
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},
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"detailed": {
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"use_terrain": True,
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"use_buildings": True,
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"use_materials": True,
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"use_dominant_path": True,
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"use_street_canyon": False,
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"use_reflections": False,
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},
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"full": {
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"use_terrain": True,
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"use_buildings": True,
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"use_materials": True,
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"use_dominant_path": True,
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"use_street_canyon": True,
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"use_reflections": True,
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},
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}
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def apply_preset(settings: CoverageSettings) -> CoverageSettings:
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"""Apply preset configuration to settings"""
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if settings.preset and settings.preset in PRESETS:
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for key, value in PRESETS[settings.preset].items():
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setattr(settings, key, value)
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return settings
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class SiteParams(BaseModel):
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@@ -38,7 +97,8 @@ class SiteParams(BaseModel):
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class CoverageService:
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"""
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RF Coverage calculation with terrain and buildings
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RF Coverage calculation with terrain, buildings, materials,
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dominant path, street canyon, and reflections
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"""
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EARTH_RADIUS = 6371000
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@@ -58,6 +118,9 @@ class CoverageService:
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Returns list of CoveragePoint with RSRP values
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"""
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# Apply preset if specified
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settings = apply_preset(settings)
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points = []
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# Generate grid
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@@ -67,23 +130,31 @@ class CoverageService:
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settings.resolution
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)
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# Fetch buildings for coverage area (if enabled)
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buildings = []
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if settings.use_buildings:
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# Calculate bbox with margin
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lat_delta = settings.radius / 111000 # ~111km per degree
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# Calculate bbox for data fetching
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lat_delta = settings.radius / 111000
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lon_delta = settings.radius / (111000 * np.cos(np.radians(site.lat)))
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# Fetch buildings for coverage area (if enabled)
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buildings: List[Building] = []
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if settings.use_buildings:
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buildings = await self.buildings.fetch_buildings(
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site.lat - lat_delta, site.lon - lon_delta,
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site.lat + lat_delta, site.lon + lon_delta
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)
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# Fetch streets (if street canyon enabled)
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streets: List[Street] = []
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if settings.use_street_canyon:
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streets = await street_canyon_service.fetch_streets(
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site.lat - lat_delta, site.lon - lon_delta,
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site.lat + lat_delta, site.lon + lon_delta
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)
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# Calculate coverage for each point
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for lat, lon in grid:
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point = await self._calculate_point(
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site, lat, lon,
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settings, buildings
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settings, buildings, streets
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)
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if point.rsrp >= settings.min_signal:
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@@ -103,6 +174,9 @@ class CoverageService:
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if not sites:
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return []
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# Apply preset once
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settings = apply_preset(settings)
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# Get all individual coverages
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all_coverages = await asyncio.gather(*[
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self.calculate_coverage(site, settings)
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@@ -155,9 +229,10 @@ class CoverageService:
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site: SiteParams,
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lat: float, lon: float,
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settings: CoverageSettings,
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buildings: List[Building]
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buildings: List[Building],
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streets: List[Street]
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) -> CoveragePoint:
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"""Calculate RSRP at a single point"""
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"""Calculate RSRP at a single point with all propagation models"""
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# Distance
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distance = TerrainService.haversine_distance(site.lat, site.lon, lat, lon)
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@@ -194,10 +269,12 @@ class CoverageService:
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clearance = los_result["clearance"]
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terrain_loss = self._diffraction_loss(clearance, site.frequency)
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# Building loss
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# Building loss (with optional material awareness)
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building_loss = 0.0
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if settings.use_buildings and buildings:
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if settings.use_materials:
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# Material-aware building loss
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for building in buildings:
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intersection = self.buildings.line_intersects_building(
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site.lat, site.lon, site.height + await self.terrain.get_elevation(site.lat, site.lon),
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@@ -205,14 +282,72 @@ class CoverageService:
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building
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)
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if intersection is not None:
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# Building penetration loss (~20dB for concrete)
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building_loss += 20.0
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material = materials_service.detect_material(building.tags)
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building_loss += materials_service.get_penetration_loss(
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material, site.frequency
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)
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has_los = False
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break # One building is enough
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else:
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# Simple building loss (legacy behavior)
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for building in buildings:
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intersection = self.buildings.line_intersects_building(
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site.lat, site.lon, site.height + await self.terrain.get_elevation(site.lat, site.lon),
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lat, lon, 1.5 + await self.terrain.get_elevation(lat, lon),
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building
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)
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if intersection is not None:
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building_loss += 20.0 # Default concrete
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has_los = False
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break
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# Calculate RSRP
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# RSRP = Tx Power + Tx Gain - Path Loss - Antenna Loss - Terrain Loss - Building Loss
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rsrp = site.power + site.gain - path_loss - antenna_loss - terrain_loss - building_loss
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# Dominant path analysis (find best route)
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if settings.use_dominant_path and buildings:
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paths = await dominant_path_service.find_dominant_paths(
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site.lat, site.lon, site.height,
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lat, lon, 1.5,
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site.frequency, buildings
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)
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if paths:
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best_path = paths[0]
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# Use best path's loss if it's better
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if best_path.is_valid and best_path.path_loss < (path_loss + terrain_loss + building_loss):
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path_loss = best_path.path_loss
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terrain_loss = 0
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building_loss = 0
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has_los = best_path.path_type == "direct" and not best_path.materials_crossed
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# Street canyon model
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if settings.use_street_canyon and streets:
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canyon_loss, street_path = await street_canyon_service.calculate_street_canyon_loss(
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site.lat, site.lon, site.height,
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lat, lon, 1.5,
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site.frequency, streets
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)
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# Use canyon loss if better than current total
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if canyon_loss < (path_loss + terrain_loss + building_loss):
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path_loss = canyon_loss
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terrain_loss = 0
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building_loss = 0
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# Reflections
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reflection_gain = 0.0
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if settings.use_reflections and buildings:
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reflection_paths = await reflection_service.find_reflection_paths(
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site.lat, site.lon, site.height,
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lat, lon, 1.5,
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site.frequency, buildings
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)
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if reflection_paths:
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# Combine direct and reflected signals
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direct_rsrp = site.power + site.gain - path_loss - antenna_loss - terrain_loss - building_loss
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combined_rsrp = reflection_service.combine_paths(
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direct_rsrp, reflection_paths, site.power + site.gain
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)
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reflection_gain = max(0, combined_rsrp - direct_rsrp)
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# Final RSRP
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rsrp = site.power + site.gain - path_loss - antenna_loss - terrain_loss - building_loss + reflection_gain
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return CoveragePoint(
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lat=lat,
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@@ -221,7 +356,8 @@ class CoverageService:
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distance=distance,
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has_los=has_los,
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terrain_loss=terrain_loss,
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building_loss=building_loss
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building_loss=building_loss,
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reflection_gain=reflection_gain
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)
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def _okumura_hata(
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@@ -311,9 +447,6 @@ class CoverageService:
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return 0.0 # No obstruction
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# Fresnel parameter approximation
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# v ~ clearance * sqrt(2 / (lambda * d))
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# Simplified: use clearance directly
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v = abs(clearance) / 10 # Normalize
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# Knife-edge loss approximation
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394
backend/app/services/dominant_path_service.py
Normal file
394
backend/app/services/dominant_path_service.py
Normal file
@@ -0,0 +1,394 @@
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import numpy as np
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from typing import List, Tuple, Optional
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from dataclasses import dataclass
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from app.services.terrain_service import terrain_service
|
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from app.services.buildings_service import buildings_service, Building
|
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from app.services.materials_service import materials_service, BuildingMaterial
|
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||||
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||||
@dataclass
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||||
class RayPath:
|
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"""Single ray path from TX to RX"""
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path_type: str # "direct", "reflected", "diffracted", "street"
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total_distance: float # meters
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path_loss: float # dB
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||||
reflection_points: List[Tuple[float, float]] # [(lat, lon), ...]
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||||
materials_crossed: List[BuildingMaterial]
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is_valid: bool # Does this path exist?
|
||||
|
||||
|
||||
class DominantPathService:
|
||||
"""
|
||||
Find dominant propagation paths (2-3 strongest)
|
||||
|
||||
Path types:
|
||||
1. Direct (LoS if available)
|
||||
2. Single reflection off building
|
||||
3. Over-roof diffraction
|
||||
4. Around-corner diffraction
|
||||
"""
|
||||
|
||||
MAX_REFLECTIONS = 2
|
||||
MAX_PATHS = 3
|
||||
|
||||
async def find_dominant_paths(
|
||||
self,
|
||||
tx_lat: float, tx_lon: float, tx_height: float,
|
||||
rx_lat: float, rx_lon: float, rx_height: float,
|
||||
frequency_mhz: float,
|
||||
buildings: List[Building]
|
||||
) -> List[RayPath]:
|
||||
"""Find the dominant propagation paths"""
|
||||
|
||||
paths = []
|
||||
|
||||
# 1. Try direct path
|
||||
direct = await self._check_direct_path(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz, buildings
|
||||
)
|
||||
if direct:
|
||||
paths.append(direct)
|
||||
|
||||
# 2. Try single-bounce reflections
|
||||
reflections = await self._find_reflection_paths(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz, buildings
|
||||
)
|
||||
paths.extend(reflections[:2]) # Max 2 reflection paths
|
||||
|
||||
# 3. Try over-roof diffraction (if direct blocked)
|
||||
if not direct or not direct.is_valid:
|
||||
diffracted = await self._find_diffraction_path(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz, buildings
|
||||
)
|
||||
if diffracted:
|
||||
paths.append(diffracted)
|
||||
|
||||
# Sort by path loss (best first) and return top N
|
||||
paths.sort(key=lambda p: p.path_loss)
|
||||
return paths[:self.MAX_PATHS]
|
||||
|
||||
async def _check_direct_path(
|
||||
self,
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz,
|
||||
buildings: List[Building]
|
||||
) -> Optional[RayPath]:
|
||||
"""Check if direct LoS path exists"""
|
||||
from app.services.los_service import los_service
|
||||
|
||||
# Check terrain LoS
|
||||
los_result = await los_service.check_line_of_sight(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height
|
||||
)
|
||||
|
||||
if not los_result["has_los"]:
|
||||
distance = terrain_service.haversine_distance(tx_lat, tx_lon, rx_lat, rx_lon)
|
||||
return RayPath(
|
||||
path_type="direct",
|
||||
total_distance=distance,
|
||||
path_loss=float('inf'),
|
||||
reflection_points=[],
|
||||
materials_crossed=[],
|
||||
is_valid=False
|
||||
)
|
||||
|
||||
# Check building intersections
|
||||
materials_crossed = []
|
||||
for building in buildings:
|
||||
intersection = self._line_intersects_building_3d(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
building
|
||||
)
|
||||
if intersection:
|
||||
material = materials_service.detect_material(building.tags)
|
||||
materials_crossed.append(material)
|
||||
|
||||
# Calculate path loss
|
||||
distance = terrain_service.haversine_distance(tx_lat, tx_lon, rx_lat, rx_lon)
|
||||
path_loss = self._calculate_path_loss(distance, frequency_mhz, tx_height, rx_height)
|
||||
|
||||
# Add material penetration losses
|
||||
for material in materials_crossed:
|
||||
path_loss += materials_service.get_penetration_loss(material, frequency_mhz)
|
||||
|
||||
return RayPath(
|
||||
path_type="direct",
|
||||
total_distance=distance,
|
||||
path_loss=path_loss,
|
||||
reflection_points=[],
|
||||
materials_crossed=materials_crossed,
|
||||
is_valid=len(materials_crossed) < 3 # Too many walls = not viable
|
||||
)
|
||||
|
||||
async def _find_reflection_paths(
|
||||
self,
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz,
|
||||
buildings: List[Building]
|
||||
) -> List[RayPath]:
|
||||
"""Find viable single-bounce reflection paths"""
|
||||
|
||||
reflection_paths = []
|
||||
|
||||
for building in buildings:
|
||||
# Find potential reflection points on building walls
|
||||
reflection_point = self._find_reflection_point(
|
||||
tx_lat, tx_lon, rx_lat, rx_lon, building
|
||||
)
|
||||
|
||||
if not reflection_point:
|
||||
continue
|
||||
|
||||
ref_lat, ref_lon = reflection_point
|
||||
|
||||
# Check if both segments are clear
|
||||
# TX -> Reflection point
|
||||
dist1 = terrain_service.haversine_distance(tx_lat, tx_lon, ref_lat, ref_lon)
|
||||
# Reflection point -> RX
|
||||
dist2 = terrain_service.haversine_distance(ref_lat, ref_lon, rx_lat, rx_lon)
|
||||
|
||||
total_distance = dist1 + dist2
|
||||
|
||||
# Don't consider if much longer than direct path
|
||||
direct_distance = terrain_service.haversine_distance(tx_lat, tx_lon, rx_lat, rx_lon)
|
||||
if total_distance > direct_distance * 2:
|
||||
continue
|
||||
|
||||
# Calculate path loss
|
||||
path_loss = self._calculate_path_loss(total_distance, frequency_mhz, tx_height, rx_height)
|
||||
|
||||
# Add reflection loss
|
||||
material = materials_service.detect_material(building.tags)
|
||||
path_loss += materials_service.get_reflection_loss(material)
|
||||
|
||||
reflection_paths.append(RayPath(
|
||||
path_type="reflected",
|
||||
total_distance=total_distance,
|
||||
path_loss=path_loss,
|
||||
reflection_points=[(ref_lat, ref_lon)],
|
||||
materials_crossed=[],
|
||||
is_valid=True
|
||||
))
|
||||
|
||||
return reflection_paths
|
||||
|
||||
async def _find_diffraction_path(
|
||||
self,
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz,
|
||||
buildings: List[Building]
|
||||
) -> Optional[RayPath]:
|
||||
"""Find over-roof diffraction path"""
|
||||
|
||||
# Find highest obstacle between TX and RX
|
||||
max_height = 0
|
||||
obstacle_lat, obstacle_lon = None, None
|
||||
|
||||
# Sample points along direct path
|
||||
num_samples = 20
|
||||
for i in range(1, num_samples - 1):
|
||||
t = i / num_samples
|
||||
lat = tx_lat + t * (rx_lat - tx_lat)
|
||||
lon = tx_lon + t * (rx_lon - tx_lon)
|
||||
|
||||
# Check terrain
|
||||
terrain_elev = await terrain_service.get_elevation(lat, lon)
|
||||
if terrain_elev > max_height:
|
||||
max_height = terrain_elev
|
||||
obstacle_lat, obstacle_lon = lat, lon
|
||||
|
||||
# Check buildings at this point
|
||||
for building in buildings:
|
||||
if buildings_service.point_in_building(lat, lon, building):
|
||||
if building.height > max_height:
|
||||
max_height = building.height
|
||||
obstacle_lat, obstacle_lon = lat, lon
|
||||
|
||||
if not obstacle_lat:
|
||||
return None
|
||||
|
||||
# Calculate diffraction loss (simplified knife-edge)
|
||||
distance = terrain_service.haversine_distance(tx_lat, tx_lon, rx_lat, rx_lon)
|
||||
|
||||
# Fresnel parameter
|
||||
tx_elev = await terrain_service.get_elevation(tx_lat, tx_lon)
|
||||
rx_elev = await terrain_service.get_elevation(rx_lat, rx_lon)
|
||||
|
||||
tx_total = tx_elev + tx_height
|
||||
rx_total = rx_elev + rx_height
|
||||
|
||||
# Height of LoS at obstacle point
|
||||
d1 = terrain_service.haversine_distance(tx_lat, tx_lon, obstacle_lat, obstacle_lon)
|
||||
los_height = tx_total + (rx_total - tx_total) * (d1 / distance) if distance > 0 else tx_total
|
||||
|
||||
clearance = los_height - max_height
|
||||
|
||||
# Knife-edge diffraction loss
|
||||
diffraction_loss = self._knife_edge_loss(clearance, frequency_mhz, distance, d1)
|
||||
|
||||
path_loss = self._calculate_path_loss(distance, frequency_mhz, tx_height, rx_height)
|
||||
path_loss += diffraction_loss
|
||||
|
||||
return RayPath(
|
||||
path_type="diffracted",
|
||||
total_distance=distance,
|
||||
path_loss=path_loss,
|
||||
reflection_points=[(obstacle_lat, obstacle_lon)],
|
||||
materials_crossed=[],
|
||||
is_valid=True
|
||||
)
|
||||
|
||||
def _find_reflection_point(
|
||||
self,
|
||||
tx_lat: float, tx_lon: float,
|
||||
rx_lat: float, rx_lon: float,
|
||||
building: Building
|
||||
) -> Optional[Tuple[float, float]]:
|
||||
"""Find specular reflection point on building wall"""
|
||||
|
||||
# Simplified: find closest wall segment and calculate reflection
|
||||
geometry = building.geometry
|
||||
|
||||
best_point = None
|
||||
best_score = float('inf')
|
||||
|
||||
for i in range(len(geometry) - 1):
|
||||
wall_start = geometry[i]
|
||||
wall_end = geometry[i + 1]
|
||||
|
||||
# Find reflection point on this wall segment
|
||||
ref_point = self._specular_reflection(
|
||||
tx_lon, tx_lat, rx_lon, rx_lat,
|
||||
wall_start[0], wall_start[1],
|
||||
wall_end[0], wall_end[1]
|
||||
)
|
||||
|
||||
if ref_point:
|
||||
# Score by total path length
|
||||
d1 = np.sqrt((ref_point[0] - tx_lon)**2 + (ref_point[1] - tx_lat)**2)
|
||||
d2 = np.sqrt((ref_point[0] - rx_lon)**2 + (ref_point[1] - rx_lat)**2)
|
||||
score = d1 + d2
|
||||
|
||||
if score < best_score:
|
||||
best_score = score
|
||||
best_point = (ref_point[1], ref_point[0]) # Return as (lat, lon)
|
||||
|
||||
return best_point
|
||||
|
||||
def _specular_reflection(
|
||||
self,
|
||||
tx_x, tx_y, rx_x, rx_y,
|
||||
wall_x1, wall_y1, wall_x2, wall_y2
|
||||
) -> Optional[Tuple[float, float]]:
|
||||
"""Calculate specular reflection point on wall segment"""
|
||||
|
||||
# Wall vector
|
||||
wall_dx = wall_x2 - wall_x1
|
||||
wall_dy = wall_y2 - wall_y1
|
||||
wall_len = np.sqrt(wall_dx**2 + wall_dy**2)
|
||||
|
||||
if wall_len < 1e-10:
|
||||
return None
|
||||
|
||||
# Wall normal
|
||||
normal_x = -wall_dy / wall_len
|
||||
normal_y = wall_dx / wall_len
|
||||
|
||||
# Mirror TX across wall
|
||||
# Project TX onto wall
|
||||
tx_rel_x = tx_x - wall_x1
|
||||
tx_rel_y = tx_y - wall_y1
|
||||
|
||||
dot = tx_rel_x * normal_x + tx_rel_y * normal_y
|
||||
|
||||
mirror_x = tx_x - 2 * dot * normal_x
|
||||
mirror_y = tx_y - 2 * dot * normal_y
|
||||
|
||||
# Find intersection of (mirror -> RX) with wall
|
||||
# Parametric line: mirror + t * (rx - mirror)
|
||||
dx = rx_x - mirror_x
|
||||
dy = rx_y - mirror_y
|
||||
|
||||
# Wall parametric: wall1 + s * (wall2 - wall1)
|
||||
denom = dx * wall_dy - dy * wall_dx
|
||||
|
||||
if abs(denom) < 1e-10:
|
||||
return None # Parallel
|
||||
|
||||
t = ((wall_x1 - mirror_x) * wall_dy - (wall_y1 - mirror_y) * wall_dx) / denom
|
||||
s = ((wall_x1 - mirror_x) * dy - (wall_y1 - mirror_y) * dx) / (-denom)
|
||||
|
||||
# Check if intersection is on wall segment and between mirror and RX
|
||||
if 0 <= s <= 1 and 0 <= t <= 1:
|
||||
ref_x = mirror_x + t * dx
|
||||
ref_y = mirror_y + t * dy
|
||||
return (ref_x, ref_y)
|
||||
|
||||
return None
|
||||
|
||||
def _line_intersects_building_3d(
|
||||
self,
|
||||
lat1, lon1, height1,
|
||||
lat2, lon2, height2,
|
||||
building: Building
|
||||
) -> bool:
|
||||
"""Check if 3D line intersects building volume"""
|
||||
# Sample along line
|
||||
for t in np.linspace(0, 1, 20):
|
||||
lat = lat1 + t * (lat2 - lat1)
|
||||
lon = lon1 + t * (lon2 - lon1)
|
||||
height = height1 + t * (height2 - height1)
|
||||
|
||||
if buildings_service.point_in_building(lat, lon, building):
|
||||
if height < building.height:
|
||||
return True
|
||||
return False
|
||||
|
||||
def _calculate_path_loss(self, distance, frequency_mhz, tx_height, rx_height) -> float:
|
||||
"""Okumura-Hata path loss"""
|
||||
d_km = max(distance / 1000, 0.1)
|
||||
|
||||
a_hm = (1.1 * np.log10(frequency_mhz) - 0.7) * rx_height - (1.56 * np.log10(frequency_mhz) - 0.8)
|
||||
|
||||
L = (69.55 + 26.16 * np.log10(frequency_mhz) - 13.82 * np.log10(tx_height) - a_hm +
|
||||
(44.9 - 6.55 * np.log10(tx_height)) * np.log10(d_km))
|
||||
|
||||
return L
|
||||
|
||||
def _knife_edge_loss(self, clearance, frequency_mhz, total_distance, d1) -> float:
|
||||
"""Knife-edge diffraction loss"""
|
||||
if clearance >= 0:
|
||||
return 0.0
|
||||
|
||||
wavelength = 300 / frequency_mhz
|
||||
d2 = total_distance - d1
|
||||
|
||||
if d1 <= 0 or d2 <= 0 or wavelength <= 0:
|
||||
return 0.0
|
||||
|
||||
# Fresnel parameter v
|
||||
v = abs(clearance) * np.sqrt(2 * (d1 + d2) / (wavelength * d1 * d2))
|
||||
|
||||
# Lee's approximation
|
||||
if v <= -0.78:
|
||||
return 0
|
||||
elif v < 0:
|
||||
return 6.02 + 9.11 * v - 1.27 * v**2
|
||||
elif v < 2.4:
|
||||
return 6.02 + 9.11 * v + 1.27 * v**2
|
||||
else:
|
||||
return 13 + 20 * np.log10(v)
|
||||
|
||||
|
||||
dominant_path_service = DominantPathService()
|
||||
128
backend/app/services/materials_service.py
Normal file
128
backend/app/services/materials_service.py
Normal file
@@ -0,0 +1,128 @@
|
||||
import math
|
||||
from enum import Enum
|
||||
from typing import Optional
|
||||
|
||||
|
||||
class BuildingMaterial(Enum):
|
||||
"""Building materials with RF properties"""
|
||||
CONCRETE = "concrete"
|
||||
BRICK = "brick"
|
||||
GLASS = "glass"
|
||||
WOOD = "wood"
|
||||
METAL = "metal"
|
||||
STONE = "stone"
|
||||
PLASTER = "plaster"
|
||||
UNKNOWN = "unknown"
|
||||
|
||||
|
||||
# ITU-R P.2040 based attenuation (dB per wall at 1-3 GHz)
|
||||
MATERIAL_LOSS = {
|
||||
BuildingMaterial.CONCRETE: 15.0,
|
||||
BuildingMaterial.BRICK: 10.0,
|
||||
BuildingMaterial.GLASS: 3.0,
|
||||
BuildingMaterial.WOOD: 5.0,
|
||||
BuildingMaterial.METAL: 25.0, # Or full reflection
|
||||
BuildingMaterial.STONE: 12.0,
|
||||
BuildingMaterial.PLASTER: 4.0,
|
||||
BuildingMaterial.UNKNOWN: 10.0, # Default assumption
|
||||
}
|
||||
|
||||
# Reflection coefficient (0-1, portion of signal reflected)
|
||||
MATERIAL_REFLECTION = {
|
||||
BuildingMaterial.CONCRETE: 0.6,
|
||||
BuildingMaterial.BRICK: 0.5,
|
||||
BuildingMaterial.GLASS: 0.3,
|
||||
BuildingMaterial.WOOD: 0.2,
|
||||
BuildingMaterial.METAL: 0.9,
|
||||
BuildingMaterial.STONE: 0.55,
|
||||
BuildingMaterial.PLASTER: 0.3,
|
||||
BuildingMaterial.UNKNOWN: 0.4,
|
||||
}
|
||||
|
||||
|
||||
class MaterialsService:
|
||||
"""Building material detection and RF properties"""
|
||||
|
||||
# OSM building:material tag mapping
|
||||
OSM_MATERIAL_MAP = {
|
||||
"concrete": BuildingMaterial.CONCRETE,
|
||||
"brick": BuildingMaterial.BRICK,
|
||||
"glass": BuildingMaterial.GLASS,
|
||||
"wood": BuildingMaterial.WOOD,
|
||||
"metal": BuildingMaterial.METAL,
|
||||
"steel": BuildingMaterial.METAL,
|
||||
"stone": BuildingMaterial.STONE,
|
||||
"plaster": BuildingMaterial.PLASTER,
|
||||
"cement_block": BuildingMaterial.CONCRETE,
|
||||
"timber": BuildingMaterial.WOOD,
|
||||
}
|
||||
|
||||
# Fallback by building type
|
||||
BUILDING_TYPE_MATERIAL = {
|
||||
"industrial": BuildingMaterial.METAL,
|
||||
"warehouse": BuildingMaterial.METAL,
|
||||
"garage": BuildingMaterial.METAL,
|
||||
"shed": BuildingMaterial.WOOD,
|
||||
"house": BuildingMaterial.BRICK,
|
||||
"residential": BuildingMaterial.CONCRETE,
|
||||
"apartments": BuildingMaterial.CONCRETE,
|
||||
"commercial": BuildingMaterial.GLASS, # Often glass facades
|
||||
"office": BuildingMaterial.GLASS,
|
||||
"retail": BuildingMaterial.GLASS,
|
||||
"church": BuildingMaterial.STONE,
|
||||
"cathedral": BuildingMaterial.STONE,
|
||||
"school": BuildingMaterial.BRICK,
|
||||
"hospital": BuildingMaterial.CONCRETE,
|
||||
"university": BuildingMaterial.CONCRETE,
|
||||
}
|
||||
|
||||
def detect_material(self, building_tags: dict) -> BuildingMaterial:
|
||||
"""Detect building material from OSM tags"""
|
||||
|
||||
# Direct material tag
|
||||
if "building:material" in building_tags:
|
||||
material_str = building_tags["building:material"].lower()
|
||||
if material_str in self.OSM_MATERIAL_MAP:
|
||||
return self.OSM_MATERIAL_MAP[material_str]
|
||||
|
||||
# Facade material (often more relevant for RF)
|
||||
if "building:facade:material" in building_tags:
|
||||
material_str = building_tags["building:facade:material"].lower()
|
||||
if material_str in self.OSM_MATERIAL_MAP:
|
||||
return self.OSM_MATERIAL_MAP[material_str]
|
||||
|
||||
# Fallback by building type
|
||||
building_type = building_tags.get("building", "yes").lower()
|
||||
if building_type in self.BUILDING_TYPE_MATERIAL:
|
||||
return self.BUILDING_TYPE_MATERIAL[building_type]
|
||||
|
||||
return BuildingMaterial.UNKNOWN
|
||||
|
||||
def get_penetration_loss(self, material: BuildingMaterial, frequency_mhz: float = 1800) -> float:
|
||||
"""
|
||||
Get RF penetration loss through wall
|
||||
|
||||
Frequency correction: +2dB per octave above 1GHz
|
||||
"""
|
||||
base_loss = MATERIAL_LOSS[material]
|
||||
|
||||
# Frequency correction (simplified)
|
||||
freq_factor = max(0, (frequency_mhz - 1000) / 1000) * 2
|
||||
|
||||
return base_loss + freq_factor
|
||||
|
||||
def get_reflection_coefficient(self, material: BuildingMaterial) -> float:
|
||||
"""Get reflection coefficient (0-1)"""
|
||||
return MATERIAL_REFLECTION[material]
|
||||
|
||||
def get_reflection_loss(self, material: BuildingMaterial) -> float:
|
||||
"""Get loss due to reflection (dB)"""
|
||||
coeff = MATERIAL_REFLECTION[material]
|
||||
if coeff <= 0:
|
||||
return 30.0 # Effectively no reflection
|
||||
|
||||
# Reflection loss in dB = -10 * log10(coefficient)
|
||||
return -10 * math.log10(coeff)
|
||||
|
||||
|
||||
materials_service = MaterialsService()
|
||||
265
backend/app/services/reflection_service.py
Normal file
265
backend/app/services/reflection_service.py
Normal file
@@ -0,0 +1,265 @@
|
||||
import numpy as np
|
||||
from typing import List, Tuple, Optional
|
||||
from dataclasses import dataclass
|
||||
from app.services.buildings_service import Building
|
||||
from app.services.materials_service import materials_service
|
||||
|
||||
|
||||
@dataclass
|
||||
class ReflectionPath:
|
||||
"""A reflection path with one or more bounces"""
|
||||
points: List[Tuple[float, float]] # [TX, reflection1, reflection2, ..., RX]
|
||||
total_distance: float
|
||||
total_loss: float
|
||||
reflection_count: int
|
||||
materials: List[str]
|
||||
|
||||
|
||||
class ReflectionService:
|
||||
"""
|
||||
Calculate reflection paths for RF propagation
|
||||
|
||||
- Single bounce (most common)
|
||||
- Double bounce (around corners)
|
||||
- Ground reflection
|
||||
"""
|
||||
|
||||
MAX_BOUNCES = 2
|
||||
GROUND_REFLECTION_COEFF = 0.3 # Depends on surface
|
||||
|
||||
async def find_reflection_paths(
|
||||
self,
|
||||
tx_lat: float, tx_lon: float, tx_height: float,
|
||||
rx_lat: float, rx_lon: float, rx_height: float,
|
||||
frequency_mhz: float,
|
||||
buildings: List[Building],
|
||||
include_ground: bool = True
|
||||
) -> List[ReflectionPath]:
|
||||
"""Find all viable reflection paths"""
|
||||
|
||||
paths = []
|
||||
|
||||
# Single-bounce building reflections
|
||||
for building in buildings:
|
||||
path = self._find_single_bounce(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz, building
|
||||
)
|
||||
if path:
|
||||
paths.append(path)
|
||||
|
||||
# Ground reflection
|
||||
if include_ground:
|
||||
ground_path = self._calculate_ground_reflection(
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz
|
||||
)
|
||||
if ground_path:
|
||||
paths.append(ground_path)
|
||||
|
||||
# Sort by loss (best first)
|
||||
paths.sort(key=lambda p: p.total_loss)
|
||||
|
||||
return paths[:5] # Return top 5
|
||||
|
||||
def _find_single_bounce(
|
||||
self,
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz,
|
||||
building: Building
|
||||
) -> Optional[ReflectionPath]:
|
||||
"""Find single-bounce reflection off building"""
|
||||
|
||||
# Find reflection point on building walls
|
||||
geometry = building.geometry
|
||||
|
||||
for i in range(len(geometry) - 1):
|
||||
wall_start = geometry[i]
|
||||
wall_end = geometry[i + 1]
|
||||
|
||||
ref_point = self._specular_reflection_point(
|
||||
(tx_lon, tx_lat), (rx_lon, rx_lat),
|
||||
wall_start, wall_end
|
||||
)
|
||||
|
||||
if not ref_point:
|
||||
continue
|
||||
|
||||
ref_lat, ref_lon = ref_point[1], ref_point[0]
|
||||
|
||||
# Calculate distances
|
||||
from app.services.terrain_service import TerrainService
|
||||
d1 = TerrainService.haversine_distance(tx_lat, tx_lon, ref_lat, ref_lon)
|
||||
d2 = TerrainService.haversine_distance(ref_lat, ref_lon, rx_lat, rx_lon)
|
||||
total_dist = d1 + d2
|
||||
|
||||
# Direct distance check - reflection shouldn't be much longer
|
||||
direct_dist = TerrainService.haversine_distance(tx_lat, tx_lon, rx_lat, rx_lon)
|
||||
if total_dist > direct_dist * 1.5:
|
||||
continue
|
||||
|
||||
# Path loss
|
||||
path_loss = self._free_space_loss(total_dist, frequency_mhz)
|
||||
|
||||
# Reflection loss
|
||||
material = materials_service.detect_material(building.tags)
|
||||
reflection_loss = materials_service.get_reflection_loss(material)
|
||||
|
||||
total_loss = path_loss + reflection_loss
|
||||
|
||||
return ReflectionPath(
|
||||
points=[(tx_lat, tx_lon), (ref_lat, ref_lon), (rx_lat, rx_lon)],
|
||||
total_distance=total_dist,
|
||||
total_loss=total_loss,
|
||||
reflection_count=1,
|
||||
materials=[material.value]
|
||||
)
|
||||
|
||||
return None
|
||||
|
||||
def _calculate_ground_reflection(
|
||||
self,
|
||||
tx_lat, tx_lon, tx_height,
|
||||
rx_lat, rx_lon, rx_height,
|
||||
frequency_mhz
|
||||
) -> Optional[ReflectionPath]:
|
||||
"""Calculate ground reflection path"""
|
||||
|
||||
from app.services.terrain_service import TerrainService
|
||||
|
||||
# Reflection point (simplified - midpoint for flat ground)
|
||||
mid_lat = (tx_lat + rx_lat) / 2
|
||||
mid_lon = (tx_lon + rx_lon) / 2
|
||||
|
||||
# Path lengths
|
||||
d1 = TerrainService.haversine_distance(tx_lat, tx_lon, mid_lat, mid_lon)
|
||||
d2 = TerrainService.haversine_distance(mid_lat, mid_lon, rx_lat, rx_lon)
|
||||
|
||||
# Actual path length considering heights
|
||||
path1 = np.sqrt(d1**2 + tx_height**2)
|
||||
path2 = np.sqrt(d2**2 + rx_height**2)
|
||||
total_dist = path1 + path2
|
||||
|
||||
# Path loss
|
||||
path_loss = self._free_space_loss(total_dist, frequency_mhz)
|
||||
|
||||
# Ground reflection loss (~5-10 dB typically)
|
||||
ground_reflection_loss = -10 * np.log10(self.GROUND_REFLECTION_COEFF)
|
||||
|
||||
# Phase difference can cause constructive or destructive interference
|
||||
# Simplified: assume average case
|
||||
total_loss = path_loss + ground_reflection_loss
|
||||
|
||||
return ReflectionPath(
|
||||
points=[(tx_lat, tx_lon), (mid_lat, mid_lon), (rx_lat, rx_lon)],
|
||||
total_distance=total_dist,
|
||||
total_loss=total_loss,
|
||||
reflection_count=1,
|
||||
materials=["ground"]
|
||||
)
|
||||
|
||||
def _specular_reflection_point(
|
||||
self,
|
||||
tx: Tuple[float, float], # (lon, lat)
|
||||
rx: Tuple[float, float],
|
||||
wall_start: List[float], # [lon, lat]
|
||||
wall_end: List[float]
|
||||
) -> Optional[Tuple[float, float]]:
|
||||
"""Calculate specular reflection point on wall"""
|
||||
|
||||
# Wall vector
|
||||
wx = wall_end[0] - wall_start[0]
|
||||
wy = wall_end[1] - wall_start[1]
|
||||
wall_len = np.sqrt(wx**2 + wy**2)
|
||||
|
||||
if wall_len < 1e-10:
|
||||
return None
|
||||
|
||||
# Normalize
|
||||
wx /= wall_len
|
||||
wy /= wall_len
|
||||
|
||||
# Wall normal (perpendicular)
|
||||
nx = -wy
|
||||
ny = wx
|
||||
|
||||
# Vector from wall start to TX
|
||||
tx_rel_x = tx[0] - wall_start[0]
|
||||
tx_rel_y = tx[1] - wall_start[1]
|
||||
|
||||
# Distance from TX to wall line
|
||||
dist_to_wall = tx_rel_x * nx + tx_rel_y * ny
|
||||
|
||||
# Mirror TX across wall
|
||||
mirror_x = tx[0] - 2 * dist_to_wall * nx
|
||||
mirror_y = tx[1] - 2 * dist_to_wall * ny
|
||||
|
||||
# Line from mirror to RX
|
||||
dx = rx[0] - mirror_x
|
||||
dy = rx[1] - mirror_y
|
||||
|
||||
# Find intersection with wall
|
||||
# Parametric: wall_start + t * wall_dir
|
||||
# Parametric: mirror + s * (rx - mirror)
|
||||
|
||||
denom = dx * wy - dy * wx
|
||||
if abs(denom) < 1e-10:
|
||||
return None
|
||||
|
||||
t = ((wall_start[0] - mirror_x) * wy - (wall_start[1] - mirror_y) * wx) / denom
|
||||
s = ((wall_start[0] - mirror_x) * dy - (wall_start[1] - mirror_y) * dx) / (-denom) if denom != 0 else 0
|
||||
|
||||
# Check if on wall segment and between mirror and RX
|
||||
if 0 <= s <= 1 and 0 <= t <= 1:
|
||||
ref_x = mirror_x + t * dx
|
||||
ref_y = mirror_y + t * dy
|
||||
return (ref_x, ref_y)
|
||||
|
||||
return None
|
||||
|
||||
def _free_space_loss(self, distance: float, frequency_mhz: float) -> float:
|
||||
"""Free space path loss (dB)"""
|
||||
if distance <= 0:
|
||||
distance = 1
|
||||
|
||||
# FSPL = 20*log10(d) + 20*log10(f) + 20*log10(4*pi/c)
|
||||
# Simplified: FSPL = 32.45 + 20*log10(f_MHz) + 20*log10(d_km)
|
||||
d_km = distance / 1000
|
||||
return 32.45 + 20 * np.log10(frequency_mhz) + 20 * np.log10(d_km + 0.001)
|
||||
|
||||
def combine_paths(
|
||||
self,
|
||||
direct_power_dbm: float,
|
||||
reflection_paths: List[ReflectionPath],
|
||||
tx_power_dbm: float
|
||||
) -> float:
|
||||
"""
|
||||
Combine direct and reflected signals (power sum)
|
||||
|
||||
Returns total received power in dBm
|
||||
"""
|
||||
|
||||
# Convert to linear power
|
||||
powers = []
|
||||
|
||||
if direct_power_dbm > -150: # Valid direct signal
|
||||
powers.append(10 ** (direct_power_dbm / 10))
|
||||
|
||||
for path in reflection_paths:
|
||||
reflected_power_dbm = tx_power_dbm - path.total_loss
|
||||
if reflected_power_dbm > -150:
|
||||
powers.append(10 ** (reflected_power_dbm / 10))
|
||||
|
||||
if not powers:
|
||||
return -150.0 # No signal
|
||||
|
||||
# Sum powers (incoherent addition - conservative estimate)
|
||||
total_power = sum(powers)
|
||||
|
||||
return 10 * np.log10(total_power)
|
||||
|
||||
|
||||
reflection_service = ReflectionService()
|
||||
363
backend/app/services/street_canyon_service.py
Normal file
363
backend/app/services/street_canyon_service.py
Normal file
@@ -0,0 +1,363 @@
|
||||
import numpy as np
|
||||
from typing import List, Tuple, Optional
|
||||
from dataclasses import dataclass
|
||||
import httpx
|
||||
from pathlib import Path
|
||||
import json
|
||||
|
||||
|
||||
@dataclass
|
||||
class Street:
|
||||
"""Street segment from OSM"""
|
||||
id: int
|
||||
name: Optional[str]
|
||||
geometry: List[Tuple[float, float]] # [(lat, lon), ...]
|
||||
width: float # meters
|
||||
highway_type: str # residential, primary, secondary, etc.
|
||||
|
||||
|
||||
class StreetCanyonService:
|
||||
"""
|
||||
Street canyon propagation model (ITU-R P.1411)
|
||||
|
||||
Signal propagates along streets with reflections from building walls.
|
||||
Loss increases at corners/turns.
|
||||
"""
|
||||
|
||||
OVERPASS_URL = "https://overpass-api.de/api/interpreter"
|
||||
|
||||
# Default street widths by type
|
||||
STREET_WIDTHS = {
|
||||
"motorway": 25.0,
|
||||
"trunk": 20.0,
|
||||
"primary": 15.0,
|
||||
"secondary": 12.0,
|
||||
"tertiary": 10.0,
|
||||
"residential": 8.0,
|
||||
"unclassified": 6.0,
|
||||
"service": 5.0,
|
||||
"footway": 2.0,
|
||||
"path": 1.5,
|
||||
}
|
||||
|
||||
# Corner/turn loss
|
||||
CORNER_LOSS_90 = 10.0 # dB for 90-degree turn
|
||||
CORNER_LOSS_45 = 4.0 # dB for 45-degree turn
|
||||
|
||||
def __init__(self, cache_dir: str = "/opt/rfcp/backend/data/streets"):
|
||||
self.cache_dir = Path(cache_dir)
|
||||
self.cache_dir.mkdir(exist_ok=True, parents=True)
|
||||
self._cache: dict[str, List[Street]] = {}
|
||||
|
||||
async def fetch_streets(
|
||||
self,
|
||||
min_lat: float, min_lon: float,
|
||||
max_lat: float, max_lon: float
|
||||
) -> List[Street]:
|
||||
"""Fetch street network from OSM"""
|
||||
|
||||
cache_key = f"{min_lat:.3f}_{min_lon:.3f}_{max_lat:.3f}_{max_lon:.3f}"
|
||||
|
||||
# Check cache
|
||||
if cache_key in self._cache:
|
||||
return self._cache[cache_key]
|
||||
|
||||
cache_file = self.cache_dir / f"{cache_key}.json"
|
||||
if cache_file.exists():
|
||||
with open(cache_file) as f:
|
||||
data = json.load(f)
|
||||
streets = [Street(**s) for s in data]
|
||||
self._cache[cache_key] = streets
|
||||
return streets
|
||||
|
||||
# Fetch from Overpass
|
||||
query = f"""
|
||||
[out:json][timeout:30];
|
||||
way["highway"]({min_lat},{min_lon},{max_lat},{max_lon});
|
||||
out body;
|
||||
>;
|
||||
out skel qt;
|
||||
"""
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=60.0) as client:
|
||||
response = await client.post(self.OVERPASS_URL, data={"data": query})
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
except Exception as e:
|
||||
print(f"Street fetch error: {e}")
|
||||
return []
|
||||
|
||||
streets = self._parse_streets(data)
|
||||
|
||||
# Cache
|
||||
with open(cache_file, 'w') as f:
|
||||
json.dump([{
|
||||
"id": s.id,
|
||||
"name": s.name,
|
||||
"geometry": s.geometry,
|
||||
"width": s.width,
|
||||
"highway_type": s.highway_type
|
||||
} for s in streets], f)
|
||||
|
||||
self._cache[cache_key] = streets
|
||||
return streets
|
||||
|
||||
def _parse_streets(self, data: dict) -> List[Street]:
|
||||
"""Parse Overpass response into Street objects"""
|
||||
|
||||
nodes = {}
|
||||
for element in data.get("elements", []):
|
||||
if element["type"] == "node":
|
||||
nodes[element["id"]] = (element["lat"], element["lon"])
|
||||
|
||||
streets = []
|
||||
for element in data.get("elements", []):
|
||||
if element["type"] != "way":
|
||||
continue
|
||||
|
||||
tags = element.get("tags", {})
|
||||
if "highway" not in tags:
|
||||
continue
|
||||
|
||||
highway_type = tags["highway"]
|
||||
|
||||
# Skip non-road types
|
||||
if highway_type in ["bus_stop", "crossing", "traffic_signals"]:
|
||||
continue
|
||||
|
||||
geometry = []
|
||||
for node_id in element.get("nodes", []):
|
||||
if node_id in nodes:
|
||||
geometry.append(nodes[node_id])
|
||||
|
||||
if len(geometry) < 2:
|
||||
continue
|
||||
|
||||
# Get width
|
||||
width = self._get_street_width(tags)
|
||||
|
||||
streets.append(Street(
|
||||
id=element["id"],
|
||||
name=tags.get("name"),
|
||||
geometry=geometry,
|
||||
width=width,
|
||||
highway_type=highway_type
|
||||
))
|
||||
|
||||
return streets
|
||||
|
||||
def _get_street_width(self, tags: dict) -> float:
|
||||
"""Estimate street width from OSM tags"""
|
||||
|
||||
# Explicit width
|
||||
if "width" in tags:
|
||||
try:
|
||||
return float(tags["width"].replace("m", "").strip())
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
# Calculate from lanes
|
||||
if "lanes" in tags:
|
||||
try:
|
||||
lanes = int(tags["lanes"])
|
||||
return lanes * 3.5 # ~3.5m per lane
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
# Default by highway type
|
||||
highway_type = tags.get("highway", "residential")
|
||||
return self.STREET_WIDTHS.get(highway_type, 8.0)
|
||||
|
||||
async def calculate_street_canyon_loss(
|
||||
self,
|
||||
tx_lat: float, tx_lon: float, tx_height: float,
|
||||
rx_lat: float, rx_lon: float, rx_height: float,
|
||||
frequency_mhz: float,
|
||||
streets: List[Street]
|
||||
) -> Tuple[float, List[Tuple[float, float]]]:
|
||||
"""
|
||||
Calculate path loss through street canyon
|
||||
|
||||
Returns:
|
||||
(path_loss_db, street_path as list of points)
|
||||
"""
|
||||
|
||||
# Find path along streets from TX to RX
|
||||
street_path = self._find_street_path(tx_lat, tx_lon, rx_lat, rx_lon, streets)
|
||||
|
||||
if not street_path:
|
||||
return float('inf'), [] # No street path found
|
||||
|
||||
# Calculate loss along path
|
||||
total_loss = 0.0
|
||||
total_distance = 0.0
|
||||
|
||||
for i in range(len(street_path) - 1):
|
||||
p1 = street_path[i]
|
||||
p2 = street_path[i + 1]
|
||||
|
||||
# Segment distance
|
||||
from app.services.terrain_service import TerrainService
|
||||
segment_dist = TerrainService.haversine_distance(p1[0], p1[1], p2[0], p2[1])
|
||||
total_distance += segment_dist
|
||||
|
||||
# Street canyon loss (ITU-R P.1411 simplified)
|
||||
# L = 32.4 + 20*log10(f_MHz) + 20*log10(d_km)
|
||||
if segment_dist > 0:
|
||||
segment_loss = 32.4 + 20 * np.log10(frequency_mhz) + 20 * np.log10(segment_dist / 1000 + 0.001)
|
||||
total_loss += segment_loss * (segment_dist / total_distance) if total_distance > 0 else 0
|
||||
|
||||
# Corner loss
|
||||
if i > 0:
|
||||
corner_angle = self._calculate_corner_angle(
|
||||
street_path[i - 1], p1, p2
|
||||
)
|
||||
corner_loss = self._corner_loss(corner_angle)
|
||||
total_loss += corner_loss
|
||||
|
||||
return total_loss, street_path
|
||||
|
||||
def _find_street_path(
|
||||
self,
|
||||
start_lat: float, start_lon: float,
|
||||
end_lat: float, end_lon: float,
|
||||
streets: List[Street]
|
||||
) -> List[Tuple[float, float]]:
|
||||
"""
|
||||
Find path along streets (simplified A* / greedy)
|
||||
|
||||
Returns list of (lat, lon) waypoints
|
||||
"""
|
||||
|
||||
# Find nearest street point to start and end
|
||||
start_point = self._nearest_street_point(start_lat, start_lon, streets)
|
||||
end_point = self._nearest_street_point(end_lat, end_lon, streets)
|
||||
|
||||
if not start_point or not end_point:
|
||||
return []
|
||||
|
||||
# Simplified: just return direct street segments
|
||||
# Full implementation would use A* pathfinding
|
||||
path = [(start_lat, start_lon), start_point]
|
||||
|
||||
# Add intermediate points along streets toward destination
|
||||
current = start_point
|
||||
visited = set()
|
||||
|
||||
for _ in range(50): # Max iterations
|
||||
if self._distance(current, end_point) < 50: # Within 50m
|
||||
break
|
||||
|
||||
# Find next street segment toward destination
|
||||
next_point = self._next_street_point(current, end_point, streets, visited)
|
||||
if not next_point:
|
||||
break
|
||||
|
||||
path.append(next_point)
|
||||
visited.add((round(current[0], 5), round(current[1], 5)))
|
||||
current = next_point
|
||||
|
||||
path.append(end_point)
|
||||
path.append((end_lat, end_lon))
|
||||
|
||||
return path
|
||||
|
||||
def _nearest_street_point(
|
||||
self,
|
||||
lat: float, lon: float,
|
||||
streets: List[Street]
|
||||
) -> Optional[Tuple[float, float]]:
|
||||
"""Find nearest point on any street"""
|
||||
|
||||
best_point = None
|
||||
best_dist = float('inf')
|
||||
|
||||
for street in streets:
|
||||
for point in street.geometry:
|
||||
dist = self._distance((lat, lon), point)
|
||||
if dist < best_dist:
|
||||
best_dist = dist
|
||||
best_point = point
|
||||
|
||||
return best_point if best_dist < 200 else None # Max 200m to street
|
||||
|
||||
def _next_street_point(
|
||||
self,
|
||||
current: Tuple[float, float],
|
||||
target: Tuple[float, float],
|
||||
streets: List[Street],
|
||||
visited: set
|
||||
) -> Optional[Tuple[float, float]]:
|
||||
"""Find next street point toward target"""
|
||||
|
||||
best_point = None
|
||||
best_score = float('inf')
|
||||
|
||||
for street in streets:
|
||||
for i, point in enumerate(street.geometry):
|
||||
if (round(point[0], 5), round(point[1], 5)) in visited:
|
||||
continue
|
||||
|
||||
dist_from_current = self._distance(current, point)
|
||||
dist_to_target = self._distance(point, target)
|
||||
|
||||
# Must be close to current position
|
||||
if dist_from_current > 100:
|
||||
continue
|
||||
|
||||
# Score: prefer points closer to target
|
||||
score = dist_to_target + dist_from_current * 0.5
|
||||
|
||||
if score < best_score:
|
||||
best_score = score
|
||||
best_point = point
|
||||
|
||||
return best_point
|
||||
|
||||
def _distance(self, p1: Tuple[float, float], p2: Tuple[float, float]) -> float:
|
||||
"""Quick distance approximation (meters)"""
|
||||
lat_diff = (p1[0] - p2[0]) * 111000
|
||||
lon_diff = (p1[1] - p2[1]) * 111000 * np.cos(np.radians(p1[0]))
|
||||
return np.sqrt(lat_diff**2 + lon_diff**2)
|
||||
|
||||
def _calculate_corner_angle(
|
||||
self,
|
||||
p1: Tuple[float, float],
|
||||
p2: Tuple[float, float],
|
||||
p3: Tuple[float, float]
|
||||
) -> float:
|
||||
"""Calculate angle at corner (degrees)"""
|
||||
|
||||
v1 = (p1[0] - p2[0], p1[1] - p2[1])
|
||||
v2 = (p3[0] - p2[0], p3[1] - p2[1])
|
||||
|
||||
dot = v1[0] * v2[0] + v1[1] * v2[1]
|
||||
mag1 = np.sqrt(v1[0]**2 + v1[1]**2)
|
||||
mag2 = np.sqrt(v2[0]**2 + v2[1]**2)
|
||||
|
||||
if mag1 * mag2 < 1e-10:
|
||||
return 180.0
|
||||
|
||||
cos_angle = dot / (mag1 * mag2)
|
||||
cos_angle = max(-1, min(1, cos_angle))
|
||||
|
||||
return np.degrees(np.arccos(cos_angle))
|
||||
|
||||
def _corner_loss(self, angle_degrees: float) -> float:
|
||||
"""Calculate loss due to corner/turn"""
|
||||
|
||||
# Straight = 180 deg, right angle = 90 deg
|
||||
turn_angle = abs(180 - angle_degrees)
|
||||
|
||||
if turn_angle < 15:
|
||||
return 0.0
|
||||
elif turn_angle < 45:
|
||||
return self.CORNER_LOSS_45 * (turn_angle / 45)
|
||||
elif turn_angle < 90:
|
||||
return self.CORNER_LOSS_45 + (self.CORNER_LOSS_90 - self.CORNER_LOSS_45) * ((turn_angle - 45) / 45)
|
||||
else:
|
||||
return self.CORNER_LOSS_90 + (turn_angle - 90) * 0.2 # Extra loss for sharp turns
|
||||
|
||||
|
||||
street_canyon_service = StreetCanyonService()
|
||||
Reference in New Issue
Block a user