Files
rfcp/backend/app/services/water_service.py

164 lines
4.8 KiB
Python

"""
OSM water bodies service for RF reflection calculations.
Water surfaces produce strong specular reflections that can boost
or create multipath interference for RF signals.
"""
import httpx
from typing import List, Tuple, Optional
from pydantic import BaseModel
import json
from pathlib import Path
class WaterBody(BaseModel):
"""Water body from OSM"""
id: int
geometry: List[Tuple[float, float]] # [(lon, lat), ...]
water_type: str # river, lake, pond, reservoir
name: Optional[str] = None
class WaterService:
"""OSM water bodies for reflection calculations"""
OVERPASS_URL = "https://overpass-api.de/api/interpreter"
# Reflection coefficients by water type
REFLECTION_COEFF = {
"lake": 0.8,
"reservoir": 0.8,
"river": 0.7,
"pond": 0.75,
"water": 0.7,
}
def __init__(self, cache_dir: str = "/opt/rfcp/backend/data/water"):
self.cache_dir = Path(cache_dir)
self.cache_dir.mkdir(exist_ok=True, parents=True)
self._cache: dict[str, List[WaterBody]] = {}
async def fetch_water_bodies(
self,
min_lat: float, min_lon: float,
max_lat: float, max_lon: float
) -> List[WaterBody]:
"""Fetch water bodies in bounding box"""
cache_key = f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}"
if cache_key in self._cache:
return self._cache[cache_key]
cache_file = self.cache_dir / f"{cache_key}.json"
if cache_file.exists():
try:
with open(cache_file) as f:
data = json.load(f)
bodies = [WaterBody(**w) for w in data]
self._cache[cache_key] = bodies
return bodies
except Exception:
pass
query = f"""
[out:json][timeout:30];
(
way["natural"="water"]({min_lat},{min_lon},{max_lat},{max_lon});
relation["natural"="water"]({min_lat},{min_lon},{max_lat},{max_lon});
way["waterway"]({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"Water fetch error: {e}")
return []
bodies = self._parse_response(data)
# Cache
if bodies:
with open(cache_file, 'w') as f:
json.dump([w.model_dump() for w in bodies], f)
self._cache[cache_key] = bodies
return bodies
def _parse_response(self, data: dict) -> List[WaterBody]:
"""Parse Overpass response"""
nodes = {}
for element in data.get("elements", []):
if element["type"] == "node":
nodes[element["id"]] = (element["lon"], element["lat"])
bodies = []
for element in data.get("elements", []):
if element["type"] != "way":
continue
tags = element.get("tags", {})
# Determine water type
water_type = tags.get("water", tags.get("waterway", tags.get("natural", "water")))
geometry = []
for node_id in element.get("nodes", []):
if node_id in nodes:
geometry.append(nodes[node_id])
if len(geometry) < 3:
continue
bodies.append(WaterBody(
id=element["id"],
geometry=geometry,
water_type=water_type,
name=tags.get("name")
))
return bodies
def get_reflection_coefficient(self, water_type: str) -> float:
"""Get reflection coefficient for water type"""
return self.REFLECTION_COEFF.get(water_type, 0.7)
def point_over_water(
self, lat: float, lon: float, water_bodies: List[WaterBody]
) -> Optional[WaterBody]:
"""Check if point is over water"""
for body in water_bodies:
if self._point_in_polygon(lat, lon, body.geometry):
return body
return None
@staticmethod
def _point_in_polygon(
lat: float, lon: float, polygon: List[Tuple[float, float]]
) -> bool:
"""Ray casting algorithm — polygon coords are (lon, lat)"""
n = len(polygon)
inside = False
j = n - 1
for i in range(n):
xi, yi = polygon[i] # lon, lat
xj, yj = polygon[j]
if ((yi > lat) != (yj > lat)) and (lon < (xj - xi) * (lat - yi) / (yj - yi) + xi):
inside = not inside
j = i
return inside
water_service = WaterService()