From f6a39df3660ced2623ad007d56980f102595efff Mon Sep 17 00:00:00 2001 From: mytec Date: Sat, 31 Jan 2026 16:16:15 +0200 Subject: [PATCH] @mytec: iter2.2 ready for testing --- backend/app/api/routes/regions.py | 256 +++++++++++++++++++++ backend/app/main.py | 5 +- backend/app/services/buildings_service.py | 168 ++++++++------ backend/app/services/terrain_service.py | 192 ++++++++++------ backend/app/services/vegetation_service.py | 113 ++++++--- backend/app/services/water_service.py | 108 ++++++--- frontend/src/App.tsx | 27 +++ frontend/src/components/RegionWizard.tsx | 165 +++++++++++++ frontend/src/services/api.ts | 58 +++++ 9 files changed, 901 insertions(+), 191 deletions(-) create mode 100644 backend/app/api/routes/regions.py create mode 100644 frontend/src/components/RegionWizard.tsx diff --git a/backend/app/api/routes/regions.py b/backend/app/api/routes/regions.py new file mode 100644 index 0000000..08d2aba --- /dev/null +++ b/backend/app/api/routes/regions.py @@ -0,0 +1,256 @@ +from fastapi import APIRouter, BackgroundTasks, HTTPException +from pydantic import BaseModel +from typing import Optional +import asyncio +import uuid + +router = APIRouter() + +# Predefined regions +REGIONS = { + "ukraine": { + "name": "Ukraine", + "bbox": [44.0, 22.0, 52.5, 40.5], # min_lat, min_lon, max_lat, max_lon + "srtm_tiles": 120, + "estimated_size_gb": 3.0, + }, + "ukraine_east": { + "name": "Eastern Ukraine (Donbas)", + "bbox": [47.0, 34.0, 50.5, 40.5], + "srtm_tiles": 24, + "estimated_size_gb": 0.6, + }, + "ukraine_central": { + "name": "Central Ukraine", + "bbox": [48.0, 30.0, 51.0, 36.0], + "srtm_tiles": 18, + "estimated_size_gb": 0.5, + }, + "kyiv_region": { + "name": "Kyiv Region", + "bbox": [49.5, 29.5, 51.5, 32.5], + "srtm_tiles": 6, + "estimated_size_gb": 0.15, + }, +} + +# Download progress tracking (in-memory) +_download_tasks: dict[str, dict] = {} + + +class RegionInfo(BaseModel): + id: str + name: str + bbox: list[float] + srtm_tiles: int + estimated_size_gb: float + downloaded: bool = False + download_progress: float = 0.0 + + +class DownloadProgress(BaseModel): + task_id: str + region_id: str + status: str # queued, downloading_terrain, downloading_osm, done, error + progress: float # 0-100 + current_step: str + downloaded_mb: float + error: Optional[str] = None + + +@router.get("/available") +async def list_regions() -> list[RegionInfo]: + """List available regions for download""" + from app.services.terrain_service import terrain_service + + cached_tiles = set(terrain_service.get_cached_tiles()) + + result = [] + for region_id, info in REGIONS.items(): + min_lat, min_lon, max_lat, max_lon = info["bbox"] + needed_tiles = set() + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + tile = terrain_service.get_tile_name(lat, lon) + needed_tiles.add(tile) + + downloaded_tiles = needed_tiles & cached_tiles + progress = len(downloaded_tiles) / len(needed_tiles) * 100 if needed_tiles else 0 + + result.append(RegionInfo( + id=region_id, + name=info["name"], + bbox=info["bbox"], + srtm_tiles=info["srtm_tiles"], + estimated_size_gb=info["estimated_size_gb"], + downloaded=progress >= 100, + download_progress=progress + )) + + return result + + +@router.post("/download/{region_id}") +async def start_download(region_id: str, background_tasks: BackgroundTasks) -> dict: + """Start downloading a region in the background""" + if region_id not in REGIONS: + raise HTTPException(404, f"Region '{region_id}' not found") + + # Check if already downloading + for task_id, task in _download_tasks.items(): + if task["region_id"] == region_id and task["status"] not in ["done", "error"]: + return {"task_id": task_id, "status": "already_downloading"} + + task_id = str(uuid.uuid4())[:8] + + _download_tasks[task_id] = { + "region_id": region_id, + "status": "queued", + "progress": 0.0, + "current_step": "Starting...", + "downloaded_mb": 0.0, + "error": None + } + + background_tasks.add_task(_download_region_task, task_id, region_id) + + return {"task_id": task_id, "status": "started"} + + +async def _download_region_task(task_id: str, region_id: str): + """Background task to download region data""" + from app.services.terrain_service import terrain_service + from app.services.buildings_service import buildings_service + from app.services.water_service import water_service + from app.services.vegetation_service import vegetation_service + + task = _download_tasks[task_id] + region = REGIONS[region_id] + min_lat, min_lon, max_lat, max_lon = region["bbox"] + + try: + # Phase 1: Download SRTM tiles (0-70%) + task["status"] = "downloading_terrain" + task["current_step"] = "Downloading terrain data..." + + # Count total tiles + total_tiles = 0 + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + total_tiles += 1 + + downloaded_count = 0 + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + tile_name = terrain_service.get_tile_name(lat, lon) + await terrain_service.download_tile(tile_name) + downloaded_count += 1 + task["progress"] = (downloaded_count / total_tiles) * 70.0 + task["current_step"] = f"Terrain: {downloaded_count}/{total_tiles} tiles" + task["downloaded_mb"] = terrain_service.get_cache_size_mb() + + # Phase 2: Pre-cache OSM data (70-100%) + task["status"] = "downloading_osm" + task["current_step"] = "Downloading building data..." + + total_chunks = 0 + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + total_chunks += 1 + + done_chunks = 0 + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + chunk_min_lat = float(lat) + chunk_min_lon = float(lon) + chunk_max_lat = float(lat + 1) + chunk_max_lon = float(lon + 1) + + try: + await buildings_service.fetch_buildings( + chunk_min_lat, chunk_min_lon, + chunk_max_lat, chunk_max_lon + ) + except Exception as e: + print(f"[Region] Buildings chunk error: {e}") + + try: + await water_service.fetch_water_bodies( + chunk_min_lat, chunk_min_lon, + chunk_max_lat, chunk_max_lon + ) + except Exception as e: + print(f"[Region] Water chunk error: {e}") + + try: + await vegetation_service.fetch_vegetation( + chunk_min_lat, chunk_min_lon, + chunk_max_lat, chunk_max_lon + ) + except Exception as e: + print(f"[Region] Vegetation chunk error: {e}") + + done_chunks += 1 + task["progress"] = 70 + (done_chunks / total_chunks) * 30 + task["current_step"] = f"OSM data: {done_chunks}/{total_chunks} chunks" + + # Delay to avoid Overpass rate limiting + await asyncio.sleep(1.0) + + task["status"] = "done" + task["progress"] = 100.0 + task["current_step"] = "Complete!" + + except Exception as e: + task["status"] = "error" + task["error"] = str(e) + task["current_step"] = f"Error: {e}" + + +@router.get("/download/{task_id}/progress") +async def get_download_progress(task_id: str) -> DownloadProgress: + """Get download progress for a task""" + if task_id not in _download_tasks: + raise HTTPException(404, "Task not found") + + task = _download_tasks[task_id] + return DownloadProgress( + task_id=task_id, + region_id=task["region_id"], + status=task["status"], + progress=task["progress"], + current_step=task["current_step"], + downloaded_mb=task["downloaded_mb"], + error=task["error"] + ) + + +@router.delete("/cache") +async def clear_cache() -> dict: + """Clear all OSM cached data (keeps SRTM terrain)""" + from app.services.buildings_service import buildings_service + from app.services.water_service import water_service + from app.services.vegetation_service import vegetation_service + + buildings_service.cache.clear() + water_service.cache.clear() + vegetation_service.cache.clear() + + return {"status": "ok", "message": "OSM cache cleared"} + + +@router.get("/cache/stats") +async def get_cache_stats() -> dict: + """Get cache statistics""" + from app.services.terrain_service import terrain_service + from app.services.buildings_service import buildings_service + from app.services.water_service import water_service + from app.services.vegetation_service import vegetation_service + + return { + "terrain_mb": round(terrain_service.get_cache_size_mb(), 2), + "terrain_tiles": len(terrain_service.get_cached_tiles()), + "buildings_mb": round(buildings_service.cache.get_size_mb(), 2), + "water_mb": round(water_service.cache.get_size_mb(), 2), + "vegetation_mb": round(vegetation_service.cache.get_size_mb(), 2), + } diff --git a/backend/app/main.py b/backend/app/main.py index 0fb96da..0f04813 100644 --- a/backend/app/main.py +++ b/backend/app/main.py @@ -4,7 +4,7 @@ from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware from app.core.database import connect_to_mongo, close_mongo_connection -from app.api.routes import health, projects, terrain, coverage +from app.api.routes import health, projects, terrain, coverage, regions @asynccontextmanager @@ -24,7 +24,7 @@ app = FastAPI( # CORS for frontend app.add_middleware( CORSMiddleware, - allow_origins=["https://rfcp.eliah.one", "http://localhost:5173"], + allow_origins=["https://rfcp.eliah.one", "http://localhost:5173", "http://127.0.0.1:8888"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], @@ -35,6 +35,7 @@ app.include_router(health.router, prefix="/api/health", tags=["health"]) app.include_router(projects.router, prefix="/api/projects", tags=["projects"]) app.include_router(terrain.router, prefix="/api/terrain", tags=["terrain"]) app.include_router(coverage.router, prefix="/api/coverage", tags=["coverage"]) +app.include_router(regions.router, prefix="/api/regions", tags=["regions"]) @app.get("/") diff --git a/backend/app/services/buildings_service.py b/backend/app/services/buildings_service.py index df8e500..314e9ad 100644 --- a/backend/app/services/buildings_service.py +++ b/backend/app/services/buildings_service.py @@ -1,12 +1,11 @@ +import os import re import httpx -import asyncio +import json from typing import List, Optional from pydantic import BaseModel -from functools import lru_cache -import hashlib -import json from pathlib import Path +from datetime import datetime, timedelta class Building(BaseModel): @@ -20,24 +19,89 @@ class Building(BaseModel): tags: dict = {} # Store all OSM tags for material detection +class OSMCache: + """Local cache for OSM data with expiry""" + + CACHE_EXPIRY_DAYS = 30 + + def __init__(self, cache_type: str): + self.data_path = Path(os.environ.get('RFCP_DATA_PATH', './data')) + self.cache_path = self.data_path / 'osm' / cache_type + self.cache_path.mkdir(parents=True, exist_ok=True) + + def _get_cache_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str: + """Generate cache key from bbox (rounded to 0.01 degree grid)""" + return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}" + + def _get_cache_file(self, cache_key: str) -> Path: + return self.cache_path / f"{cache_key}.json" + + def get(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> Optional[dict]: + """Get cached data if available and not expired""" + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + if not cache_file.exists(): + return None + + try: + data = json.loads(cache_file.read_text()) + + # Check expiry + cached_at = datetime.fromisoformat(data.get('_cached_at', '2000-01-01')) + if datetime.now() - cached_at > timedelta(days=self.CACHE_EXPIRY_DAYS): + return None + + return data.get('data') + + except Exception as e: + print(f"[OSMCache] Failed to read cache: {e}") + return None + + def set(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float, data): + """Save data to cache""" + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + try: + cache_data = { + '_cached_at': datetime.now().isoformat(), + '_bbox': [min_lat, min_lon, max_lat, max_lon], + 'data': data + } + cache_file.write_text(json.dumps(cache_data)) + + except Exception as e: + print(f"[OSMCache] Failed to write cache: {e}") + + def clear(self): + """Clear all cached data""" + for f in self.cache_path.glob("*.json"): + f.unlink() + + def get_size_mb(self) -> float: + """Get cache size in MB""" + total = sum(f.stat().st_size for f in self.cache_path.glob("*.json")) + return total / (1024 * 1024) + + class BuildingsService: """ - OpenStreetMap buildings via Overpass API + OpenStreetMap buildings via Overpass API with local caching. """ OVERPASS_URL = "https://overpass-api.de/api/interpreter" DEFAULT_LEVEL_HEIGHT = 3.0 # meters per floor DEFAULT_BUILDING_HEIGHT = 9.0 # 3 floors if unknown - def __init__(self, cache_dir: str = "/opt/rfcp/backend/data/buildings"): - self.cache_dir = Path(cache_dir) - self.cache_dir.mkdir(exist_ok=True, parents=True) + def __init__(self): + self.cache = OSMCache('buildings') self._memory_cache: dict[str, List[Building]] = {} - self._max_cache_size = 50 # bbox regions + self._max_cache_size = 50 @staticmethod def _safe_int(value) -> Optional[int]: - """Safely parse int from OSM tag (handles '1а', '2-3', '5+', etc.)""" + """Safely parse int from OSM tag (handles '1a', '2-3', '5+', etc.)""" if not value: return None try: @@ -63,10 +127,8 @@ class BuildingsService: return None def _bbox_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str: - """Generate cache key for bbox""" - # Round to 0.01 degree (~1km) grid for cache efficiency - key = f"{min_lat:.2f},{min_lon:.2f},{max_lat:.2f},{max_lon:.2f}" - return hashlib.md5(key.encode()).hexdigest()[:12] + """Generate memory cache key for bbox""" + return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}" async def fetch_buildings( self, @@ -74,35 +136,25 @@ class BuildingsService: max_lat: float, max_lon: float, use_cache: bool = True ) -> List[Building]: - """ - Fetch buildings in bounding box from OSM - - Args: - min_lat, min_lon, max_lat, max_lon: Bounding box - use_cache: Whether to use cached results - - Returns: - List of Building objects with height estimates - """ - cache_key = self._bbox_key(min_lat, min_lon, max_lat, max_lon) + """Fetch buildings in bounding box from OSM, using cache if available""" + bbox_key = self._bbox_key(min_lat, min_lon, max_lat, max_lon) # Check memory cache - if use_cache and cache_key in self._memory_cache: - return self._memory_cache[cache_key] + if use_cache and bbox_key in self._memory_cache: + return self._memory_cache[bbox_key] - # Check disk cache - cache_file = self.cache_dir / f"{cache_key}.json" - if use_cache and cache_file.exists(): - try: - with open(cache_file, 'r') as f: - data = json.load(f) - buildings = [Building(**b) for b in data] - self._memory_cache[cache_key] = buildings + # Check disk cache (OSMCache with expiry) + if use_cache: + cached = self.cache.get(min_lat, min_lon, max_lat, max_lon) + if cached is not None: + print(f"[Buildings] Cache hit for bbox") + buildings = [Building(**b) for b in cached] + self._memory_cache[bbox_key] = buildings return buildings - except Exception: - pass # Fetch fresh if cache corrupted # Fetch from Overpass API + print(f"[Buildings] Fetching from Overpass API...") + query = f""" [out:json][timeout:30]; ( @@ -123,23 +175,21 @@ class BuildingsService: response.raise_for_status() data = response.json() except Exception as e: - print(f"Overpass API error: {e}") + print(f"[Buildings] Overpass API error: {e}") return [] - # Parse response buildings = self._parse_overpass_response(data) - # Cache results + # Save to disk cache if buildings: - # Disk cache - with open(cache_file, 'w') as f: - json.dump([b.model_dump() for b in buildings], f) + self.cache.set(min_lat, min_lon, max_lat, max_lon, + [b.model_dump() for b in buildings]) - # Memory cache (with size limit) - if len(self._memory_cache) >= self._max_cache_size: - oldest = next(iter(self._memory_cache)) - del self._memory_cache[oldest] - self._memory_cache[cache_key] = buildings + # Memory cache with size limit + if len(self._memory_cache) >= self._max_cache_size: + oldest = next(iter(self._memory_cache)) + del self._memory_cache[oldest] + self._memory_cache[bbox_key] = buildings return buildings @@ -162,19 +212,16 @@ class BuildingsService: if "building" not in tags: continue - # Get geometry geometry = [] for node_id in element.get("nodes", []): if node_id in nodes: geometry.append(list(nodes[node_id])) if len(geometry) < 3: - continue # Invalid polygon + continue - # Estimate height height = self._estimate_height(tags) - # Detect material from tags material_str = None if "building:material" in tags: material_str = tags["building:material"] @@ -195,19 +242,16 @@ class BuildingsService: def _estimate_height(self, tags: dict) -> float: """Estimate building height from OSM tags""" - # Explicit height tag if "height" in tags: h = self._safe_float(tags["height"]) if h is not None and h > 0: return h - # Calculate from levels if "building:levels" in tags: levels = self._safe_int(tags["building:levels"]) if levels is not None and levels > 0: return levels * self.DEFAULT_LEVEL_HEIGHT - # Default based on building type building_type = tags.get("building", "yes") type_heights = { "house": 6.0, @@ -254,18 +298,10 @@ class BuildingsService: lat2: float, lon2: float, height2: float, building: Building ) -> Optional[float]: - """ - Check if line segment intersects building - - Returns: - Distance along path where intersection occurs, or None - """ - # Simplified 2D check + height comparison - # For accurate 3D intersection, would need proper ray-polygon intersection - + """Check if line segment intersects building. + Returns distance along path where intersection occurs, or None.""" from app.services.terrain_service import TerrainService - # Sample points along line num_samples = 20 for i in range(num_samples): t = i / num_samples @@ -274,9 +310,7 @@ class BuildingsService: height = height1 + t * (height2 - height1) if self.point_in_building(lat, lon, building): - # Check if signal height is below building if height < building.height: - # Calculate distance dist = t * TerrainService.haversine_distance(lat1, lon1, lat2, lon2) return dist diff --git a/backend/app/services/terrain_service.py b/backend/app/services/terrain_service.py index 53fc9fc..7228e1b 100644 --- a/backend/app/services/terrain_service.py +++ b/backend/app/services/terrain_service.py @@ -1,34 +1,37 @@ +import os import struct import asyncio -import aiofiles +import gzip +import zipfile +import io +import numpy as np import httpx from pathlib import Path from typing import List, Optional, Tuple -import numpy as np class TerrainService: """ - SRTM elevation data service - - Downloads and caches .hgt tiles - - Provides elevation lookups - - Generates elevation profiles + SRTM elevation data service with local caching. + - Stores tiles in RFCP_DATA_PATH/terrain/ + - In-memory LRU cache (max 20 tiles) + - Auto-downloads from S3 mirror + - Supports both SRTM1 (3601x3601) and SRTM3 (1201x1201) """ - # SRTM tile dimensions (1 arc-second = 3601x3601, 3 arc-second = 1201x1201) - TILE_SIZE = 3601 # 1 arc-second (30m resolution) - - # Mirror URLs for SRTM data (USGS requires login, use mirrors) - SRTM_MIRRORS = [ + SRTM_SOURCES = [ "https://elevation-tiles-prod.s3.amazonaws.com/skadi/{lat_dir}/{tile_name}.hgt.gz", "https://s3.amazonaws.com/elevation-tiles-prod/skadi/{lat_dir}/{tile_name}.hgt.gz", ] - def __init__(self, cache_dir: str = "/opt/rfcp/backend/data/srtm"): - self.cache_dir = Path(cache_dir) - self.cache_dir.mkdir(exist_ok=True, parents=True) - self._tile_cache: dict[str, np.ndarray] = {} # In-memory cache - self._max_cached_tiles = 10 # Limit memory usage + def __init__(self): + self.data_path = Path(os.environ.get('RFCP_DATA_PATH', './data')) + self.terrain_path = self.data_path / 'terrain' + self.terrain_path.mkdir(parents=True, exist_ok=True) + + # In-memory cache for loaded tiles + self._tile_cache: dict[str, np.ndarray] = {} + self._max_cache_tiles = 20 # ~500MB max def get_tile_name(self, lat: float, lon: float) -> str: """Convert lat/lon to SRTM tile name (e.g., N48E035)""" @@ -42,73 +45,96 @@ class TerrainService: def get_tile_path(self, tile_name: str) -> Path: """Get local path for tile""" - return self.cache_dir / f"{tile_name}.hgt" + return self.terrain_path / f"{tile_name}.hgt" async def download_tile(self, tile_name: str) -> bool: - """Download SRTM tile from mirror""" - import gzip - + """Download SRTM tile if not cached locally""" tile_path = self.get_tile_path(tile_name) + if tile_path.exists(): return True lat_dir = tile_name[:3] # e.g., "N48" async with httpx.AsyncClient(timeout=60.0) as client: - for mirror in self.SRTM_MIRRORS: - url = mirror.format(lat_dir=lat_dir, tile_name=tile_name) + for source_url in self.SRTM_SOURCES: + url = source_url.format(lat_dir=lat_dir, tile_name=tile_name) try: response = await client.get(url) + if response.status_code == 200: - # Decompress gzip - decompressed = gzip.decompress(response.content) + data = response.content - async with aiofiles.open(tile_path, 'wb') as f: - await f.write(decompressed) + if url.endswith('.gz'): + data = gzip.decompress(data) + elif url.endswith('.zip'): + with zipfile.ZipFile(io.BytesIO(data)) as zf: + for name in zf.namelist(): + if name.endswith('.hgt'): + data = zf.read(name) + break - print(f"Downloaded {tile_name} from {mirror}") + tile_path.write_bytes(data) + print(f"[Terrain] Downloaded {tile_name} ({len(data)} bytes)") return True + except Exception as e: - print(f"Failed to download from {mirror}: {e}") + print(f"[Terrain] Failed from {url}: {e}") continue - print(f"Failed to download tile {tile_name}") + print(f"[Terrain] Could not download {tile_name}") return False - async def load_tile(self, tile_name: str) -> Optional[np.ndarray]: - """Load tile into memory (with caching)""" - # Check memory cache + def _load_tile(self, tile_name: str) -> Optional[np.ndarray]: + """Load tile from disk into memory cache""" + # Check memory cache first if tile_name in self._tile_cache: return self._tile_cache[tile_name] tile_path = self.get_tile_path(tile_name) - # Download if missing if not tile_path.exists(): + return None + + try: + data = tile_path.read_bytes() + + # SRTM HGT format: big-endian signed 16-bit integers + if len(data) == 3601 * 3601 * 2: + size = 3601 # SRTM1 (30m) + elif len(data) == 1201 * 1201 * 2: + size = 1201 # SRTM3 (90m) + else: + print(f"[Terrain] Unknown tile size: {len(data)} bytes for {tile_name}") + return None + + tile = np.frombuffer(data, dtype='>i2').reshape((size, size)) + + # Manage memory cache with LRU eviction + if len(self._tile_cache) >= self._max_cache_tiles: + oldest = next(iter(self._tile_cache)) + del self._tile_cache[oldest] + + self._tile_cache[tile_name] = tile + return tile + + except Exception as e: + print(f"[Terrain] Failed to load {tile_name}: {e}") + return None + + async def load_tile(self, tile_name: str) -> Optional[np.ndarray]: + """Load tile into memory, downloading if needed""" + # Check memory cache + if tile_name in self._tile_cache: + return self._tile_cache[tile_name] + + # Download if missing + if not self.get_tile_path(tile_name).exists(): success = await self.download_tile(tile_name) if not success: return None - # Read HGT file (big-endian signed 16-bit integers) - try: - async with aiofiles.open(tile_path, 'rb') as f: - data = await f.read() - - # Parse as numpy array - arr = np.frombuffer(data, dtype='>i2').reshape(self.TILE_SIZE, self.TILE_SIZE) - - # Manage cache size - if len(self._tile_cache) >= self._max_cached_tiles: - # Remove oldest entry - oldest = next(iter(self._tile_cache)) - del self._tile_cache[oldest] - - self._tile_cache[tile_name] = arr - return arr - - except Exception as e: - print(f"Error loading tile {tile_name}: {e}") - return None + return self._load_tile(tile_name) async def get_elevation(self, lat: float, lon: float) -> float: """Get elevation at specific coordinate (meters above sea level)""" @@ -116,7 +142,9 @@ class TerrainService: tile = await self.load_tile(tile_name) if tile is None: - return 0.0 # No data, assume sea level + return 0.0 + + size = tile.shape[0] # Calculate position within tile lat_int = int(lat) if lat >= 0 else int(lat) - 1 @@ -125,13 +153,12 @@ class TerrainService: lat_frac = lat - lat_int lon_frac = lon - lon_int - # Row 0 = north edge, row 3600 = south edge - row = int((1 - lat_frac) * (self.TILE_SIZE - 1)) - col = int(lon_frac * (self.TILE_SIZE - 1)) + # Row 0 = north edge, last row = south edge + row = int((1 - lat_frac) * (size - 1)) + col = int(lon_frac * (size - 1)) - # Clamp to valid range - row = max(0, min(row, self.TILE_SIZE - 1)) - col = max(0, min(col, self.TILE_SIZE - 1)) + row = max(0, min(row, size - 1)) + col = max(0, min(col, size - 1)) elevation = tile[row, col] @@ -147,15 +174,10 @@ class TerrainService: lat2: float, lon2: float, num_points: int = 100 ) -> List[dict]: - """ - Get elevation profile between two points - - Returns list of {lat, lon, elevation, distance} dicts - """ + """Get elevation profile between two points""" lats = np.linspace(lat1, lat2, num_points) lons = np.linspace(lon1, lon2, num_points) - # Calculate cumulative distances total_distance = self.haversine_distance(lat1, lon1, lat2, lon2) distances = np.linspace(0, total_distance, num_points) @@ -171,10 +193,46 @@ class TerrainService: return profile + async def ensure_tiles_for_bbox( + self, + min_lat: float, min_lon: float, + max_lat: float, max_lon: float + ) -> list[str]: + """Pre-download all tiles needed for a bounding box""" + tiles_needed = [] + + for lat in range(int(min_lat), int(max_lat) + 1): + for lon in range(int(min_lon), int(max_lon) + 1): + tile_name = self.get_tile_name(lat, lon) + tiles_needed.append(tile_name) + + # Download in parallel (batches of 5 to avoid overload) + downloaded = [] + batch_size = 5 + for i in range(0, len(tiles_needed), batch_size): + batch = tiles_needed[i:i + batch_size] + results = await asyncio.gather(*[ + self.download_tile(tile) for tile in batch + ]) + for tile, ok in zip(batch, results): + if ok: + downloaded.append(tile) + + return downloaded + + def get_cached_tiles(self) -> list[str]: + """List all locally cached tile names""" + return [f.stem for f in self.terrain_path.glob("*.hgt")] + + def get_cache_size_mb(self) -> float: + """Get total terrain cache size in MB""" + total = sum(f.stat().st_size for f in self.terrain_path.glob("*.hgt")) + return total / (1024 * 1024) + @staticmethod def haversine_distance(lat1: float, lon1: float, lat2: float, lon2: float) -> float: """Calculate distance between two points in meters""" - EARTH_RADIUS = 6371000 # meters + EARTH_RADIUS = 6371000 lat1, lon1, lat2, lon2 = map(np.radians, [lat1, lon1, lat2, lon2]) diff --git a/backend/app/services/vegetation_service.py b/backend/app/services/vegetation_service.py index 8b8e753..9550679 100644 --- a/backend/app/services/vegetation_service.py +++ b/backend/app/services/vegetation_service.py @@ -5,11 +5,13 @@ Forests and dense vegetation attenuate RF signals significantly. Uses ITU-R P.833 approximations for foliage loss. """ +import os import httpx +import json from typing import List, Tuple, Optional from pydantic import BaseModel -import json from pathlib import Path +from datetime import datetime, timedelta class VegetationArea(BaseModel): @@ -20,6 +22,62 @@ class VegetationArea(BaseModel): density: str # dense, sparse, mixed +class VegetationCache: + """Local cache for vegetation data with expiry""" + + CACHE_EXPIRY_DAYS = 30 + + def __init__(self): + self.data_path = Path(os.environ.get('RFCP_DATA_PATH', './data')) + self.cache_path = self.data_path / 'osm' / 'vegetation' + self.cache_path.mkdir(parents=True, exist_ok=True) + + def _get_cache_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str: + return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}" + + def _get_cache_file(self, cache_key: str) -> Path: + return self.cache_path / f"{cache_key}.json" + + def get(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> Optional[list]: + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + if not cache_file.exists(): + return None + + try: + data = json.loads(cache_file.read_text()) + cached_at = datetime.fromisoformat(data.get('_cached_at', '2000-01-01')) + if datetime.now() - cached_at > timedelta(days=self.CACHE_EXPIRY_DAYS): + return None + return data.get('data') + except Exception as e: + print(f"[VegetationCache] Failed to read cache: {e}") + return None + + def set(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float, data): + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + try: + cache_data = { + '_cached_at': datetime.now().isoformat(), + '_bbox': [min_lat, min_lon, max_lat, max_lon], + 'data': data + } + cache_file.write_text(json.dumps(cache_data)) + except Exception as e: + print(f"[VegetationCache] Failed to write cache: {e}") + + def clear(self): + for f in self.cache_path.glob("*.json"): + f.unlink() + + def get_size_mb(self) -> float: + total = sum(f.stat().st_size for f in self.cache_path.glob("*.json")) + return total / (1024 * 1024) + + class VegetationService: """OSM vegetation for signal attenuation""" @@ -44,33 +102,33 @@ class VegetationService: "autumn": 0.7, } - def __init__(self, cache_dir: str = "/opt/rfcp/backend/data/vegetation"): - self.cache_dir = Path(cache_dir) - self.cache_dir.mkdir(exist_ok=True, parents=True) - self._cache: dict[str, List[VegetationArea]] = {} + def __init__(self): + self.cache = VegetationCache() + self._memory_cache: dict[str, List[VegetationArea]] = {} async def fetch_vegetation( self, min_lat: float, min_lon: float, max_lat: float, max_lon: float ) -> List[VegetationArea]: - """Fetch vegetation areas in bounding box""" + """Fetch vegetation areas in bounding box, using cache if available""" 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] + # Memory cache + if cache_key in self._memory_cache: + return self._memory_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) - areas = [VegetationArea(**v) for v in data] - self._cache[cache_key] = areas - return areas - except Exception: - pass + # Disk cache with expiry + cached = self.cache.get(min_lat, min_lon, max_lat, max_lon) + if cached is not None: + print(f"[Vegetation] Cache hit for bbox") + areas = [VegetationArea(**v) for v in cached] + self._memory_cache[cache_key] = areas + return areas + + # Fetch from Overpass + print(f"[Vegetation] Fetching from Overpass API...") query = f""" [out:json][timeout:30]; @@ -91,17 +149,17 @@ class VegetationService: response.raise_for_status() data = response.json() except Exception as e: - print(f"Vegetation fetch error: {e}") + print(f"[Vegetation] Fetch error: {e}") return [] areas = self._parse_response(data) - # Cache + # Save to disk cache if areas: - with open(cache_file, 'w') as f: - json.dump([v.model_dump() for v in areas], f) - self._cache[cache_key] = areas + self.cache.set(min_lat, min_lon, max_lat, max_lon, + [v.model_dump() for v in areas]) + self._memory_cache[cache_key] = areas return areas def _parse_response(self, data: dict) -> List[VegetationArea]: @@ -128,7 +186,6 @@ class VegetationService: if len(geometry) < 3: continue - # Determine density from leaf_type tag leaf_type = tags.get("leaf_type", "mixed") density = "dense" if leaf_type == "needleleaved" else "mixed" @@ -151,7 +208,7 @@ class VegetationService: """ Calculate signal loss through vegetation along path. - Samples points along the TX→RX path and accumulates + Samples points along the TX->RX path and accumulates attenuation for each segment inside vegetation. Returns loss in dB (capped at 40 dB). @@ -163,7 +220,6 @@ class VegetationService: if path_length < 1: return 0.0 - # Sample points along path — every ~50m num_samples = max(10, int(path_length / 50)) segment_length = path_length / num_samples @@ -174,7 +230,6 @@ class VegetationService: lat = lat1 + t * (lat2 - lat1) lon = lon1 + t * (lon2 - lon1) - # Check if sample point is inside any vegetation area veg = self._point_in_vegetation(lat, lon, vegetation_areas) if veg: @@ -182,7 +237,7 @@ class VegetationService: seasonal = self.SEASONAL_FACTOR.get(season, 1.0) total_loss += (segment_length / 100) * attenuation * seasonal - return min(total_loss, 40.0) # Cap at 40 dB + return min(total_loss, 40.0) def _point_in_vegetation( self, @@ -199,7 +254,7 @@ class VegetationService: def _point_in_polygon( lat: float, lon: float, polygon: List[Tuple[float, float]] ) -> bool: - """Ray casting algorithm — polygon coords are (lon, lat)""" + """Ray casting algorithm -- polygon coords are (lon, lat)""" n = len(polygon) inside = False diff --git a/backend/app/services/water_service.py b/backend/app/services/water_service.py index 951bdf4..acdd8ee 100644 --- a/backend/app/services/water_service.py +++ b/backend/app/services/water_service.py @@ -5,11 +5,13 @@ Water surfaces produce strong specular reflections that can boost or create multipath interference for RF signals. """ +import os import httpx +import json from typing import List, Tuple, Optional from pydantic import BaseModel -import json from pathlib import Path +from datetime import datetime, timedelta class WaterBody(BaseModel): @@ -20,6 +22,62 @@ class WaterBody(BaseModel): name: Optional[str] = None +class WaterCache: + """Local cache for water body data with expiry""" + + CACHE_EXPIRY_DAYS = 30 + + def __init__(self): + self.data_path = Path(os.environ.get('RFCP_DATA_PATH', './data')) + self.cache_path = self.data_path / 'osm' / 'water' + self.cache_path.mkdir(parents=True, exist_ok=True) + + def _get_cache_key(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> str: + return f"{min_lat:.2f}_{min_lon:.2f}_{max_lat:.2f}_{max_lon:.2f}" + + def _get_cache_file(self, cache_key: str) -> Path: + return self.cache_path / f"{cache_key}.json" + + def get(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float) -> Optional[list]: + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + if not cache_file.exists(): + return None + + try: + data = json.loads(cache_file.read_text()) + cached_at = datetime.fromisoformat(data.get('_cached_at', '2000-01-01')) + if datetime.now() - cached_at > timedelta(days=self.CACHE_EXPIRY_DAYS): + return None + return data.get('data') + except Exception as e: + print(f"[WaterCache] Failed to read cache: {e}") + return None + + def set(self, min_lat: float, min_lon: float, max_lat: float, max_lon: float, data): + cache_key = self._get_cache_key(min_lat, min_lon, max_lat, max_lon) + cache_file = self._get_cache_file(cache_key) + + try: + cache_data = { + '_cached_at': datetime.now().isoformat(), + '_bbox': [min_lat, min_lon, max_lat, max_lon], + 'data': data + } + cache_file.write_text(json.dumps(cache_data)) + except Exception as e: + print(f"[WaterCache] Failed to write cache: {e}") + + def clear(self): + for f in self.cache_path.glob("*.json"): + f.unlink() + + def get_size_mb(self) -> float: + total = sum(f.stat().st_size for f in self.cache_path.glob("*.json")) + return total / (1024 * 1024) + + class WaterService: """OSM water bodies for reflection calculations""" @@ -34,33 +92,33 @@ class WaterService: "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]] = {} + def __init__(self): + self.cache = WaterCache() + self._memory_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""" + """Fetch water bodies in bounding box, using cache if available""" 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] + # Memory cache + if cache_key in self._memory_cache: + return self._memory_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 + # Disk cache with expiry + cached = self.cache.get(min_lat, min_lon, max_lat, max_lon) + if cached is not None: + print(f"[Water] Cache hit for bbox") + bodies = [WaterBody(**w) for w in cached] + self._memory_cache[cache_key] = bodies + return bodies + + # Fetch from Overpass + print(f"[Water] Fetching from Overpass API...") query = f""" [out:json][timeout:30]; @@ -80,17 +138,17 @@ class WaterService: response.raise_for_status() data = response.json() except Exception as e: - print(f"Water fetch error: {e}") + print(f"[Water] Fetch error: {e}") return [] bodies = self._parse_response(data) - # Cache + # Save to disk 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 + self.cache.set(min_lat, min_lon, max_lat, max_lon, + [w.model_dump() for w in bodies]) + self._memory_cache[cache_key] = bodies return bodies def _parse_response(self, data: dict) -> List[WaterBody]: @@ -106,8 +164,6 @@ class WaterService: continue tags = element.get("tags", {}) - - # Determine water type water_type = tags.get("water", tags.get("waterway", tags.get("natural", "water"))) geometry = [] @@ -144,7 +200,7 @@ class WaterService: def _point_in_polygon( lat: float, lon: float, polygon: List[Tuple[float, float]] ) -> bool: - """Ray casting algorithm — polygon coords are (lon, lat)""" + """Ray casting algorithm -- polygon coords are (lon, lat)""" n = len(polygon) inside = False diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index bbcf83c..43af176 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -27,6 +27,8 @@ import ThemeToggle from '@/components/ui/ThemeToggle.tsx'; import Button from '@/components/ui/Button.tsx'; import NumberInput from '@/components/ui/NumberInput.tsx'; import ConfirmDialog from '@/components/ui/ConfirmDialog.tsx'; +import { RegionWizard } from '@/components/RegionWizard.tsx'; +import { isDesktop } from '@/lib/desktop.ts'; /** * Restore a sites snapshot: replace all sites in IndexedDB + Zustand. @@ -117,6 +119,26 @@ export default function App() { const [showShortcuts, setShowShortcuts] = useState(false); const [kbDeleteTarget, setKbDeleteTarget] = useState<{ id: string; name: string } | null>(null); + // Region wizard for first-run (desktop mode only) + const [showWizard, setShowWizard] = useState(false); + + useEffect(() => { + if (!isDesktop()) return; + const skipped = localStorage.getItem('rfcp_region_wizard_skipped'); + if (skipped) return; + + api.getRegions() + .then((regions) => { + const hasDownloaded = regions.some((r) => r.downloaded); + if (!hasDownloaded) { + setShowWizard(true); + } + }) + .catch(() => { + // Backend not ready yet, skip wizard + }); + }, []); + // Resizable sidebar const PANEL_MIN = 300; const PANEL_MAX = 600; @@ -1084,6 +1106,11 @@ export default function App() { )} + + {/* First-run region download wizard (desktop only) */} + {showWizard && ( + setShowWizard(false)} /> + )} ); } diff --git a/frontend/src/components/RegionWizard.tsx b/frontend/src/components/RegionWizard.tsx new file mode 100644 index 0000000..34a11cb --- /dev/null +++ b/frontend/src/components/RegionWizard.tsx @@ -0,0 +1,165 @@ +import { useState, useEffect, useRef } from 'react'; +import { api } from '@/services/api.ts'; +import type { RegionInfo, DownloadProgress } from '@/services/api.ts'; + +export function RegionWizard({ onComplete }: { onComplete: () => void }) { + const [regions, setRegions] = useState([]); + const [selectedRegion, setSelectedRegion] = useState(null); + const [downloading, setDownloading] = useState(false); + const [progress, setProgress] = useState(null); + const [error, setError] = useState(null); + const pollRef = useRef | null>(null); + + useEffect(() => { + api.getRegions() + .then(setRegions) + .catch((err) => { + console.error('Failed to load regions:', err); + setError('Failed to connect to backend'); + }); + + return () => { + if (pollRef.current) clearInterval(pollRef.current); + }; + }, []); + + const startDownload = async () => { + if (!selectedRegion) return; + + setDownloading(true); + setError(null); + + try { + const { task_id } = await api.downloadRegion(selectedRegion); + + pollRef.current = setInterval(async () => { + try { + const prog = await api.getDownloadProgress(task_id); + setProgress(prog); + + if (prog.status === 'done') { + if (pollRef.current) clearInterval(pollRef.current); + setDownloading(false); + // Brief delay so user sees "Complete!" before closing + setTimeout(() => onComplete(), 1000); + } else if (prog.status === 'error') { + if (pollRef.current) clearInterval(pollRef.current); + setDownloading(false); + setError(prog.error || 'Download failed'); + } + } catch { + // Polling error, keep trying + } + }, 1000); + } catch (err) { + setDownloading(false); + setError(err instanceof Error ? err.message : 'Download failed'); + } + }; + + const skipDownload = () => { + localStorage.setItem('rfcp_region_wizard_skipped', 'true'); + onComplete(); + }; + + return ( +
+
+

+ Welcome to RFCP +

+

+ RF Coverage Planner +

+ +

+ Select a region to download for offline use. + This includes terrain elevation and building data. +

+ + {error && ( +
+ {error} +
+ )} + + {!downloading ? ( + <> + {/* Region list */} +
+ {regions.map((region) => ( + + ))} + + {regions.length === 0 && !error && ( +
+ Loading regions... +
+ )} +
+ + {/* Actions */} +
+ + +
+ + ) : ( + /* Download progress */ +
+
+
+
+
+ {progress?.current_step || 'Starting...'} +
+
+ {(progress?.downloaded_mb || 0).toFixed(1)} MB downloaded + {' '}·{' '} + {(progress?.progress || 0).toFixed(0)}% +
+
+ )} +
+
+ ); +} diff --git a/frontend/src/services/api.ts b/frontend/src/services/api.ts index c7c0eb7..646b3f9 100644 --- a/frontend/src/services/api.ts +++ b/frontend/src/services/api.ts @@ -147,6 +147,64 @@ class ApiService { const data = await response.json(); return data.elevation; } + + // === Region / Caching API === + + async getRegions(): Promise { + const response = await fetch(`${API_BASE}/api/regions/available`); + if (!response.ok) throw new Error('Failed to fetch regions'); + return response.json(); + } + + async downloadRegion(regionId: string): Promise<{ task_id: string; status: string }> { + const response = await fetch(`${API_BASE}/api/regions/download/${regionId}`, { + method: 'POST', + }); + if (!response.ok) throw new Error('Failed to start download'); + return response.json(); + } + + async getDownloadProgress(taskId: string): Promise { + const response = await fetch(`${API_BASE}/api/regions/download/${taskId}/progress`); + if (!response.ok) throw new Error('Failed to get progress'); + return response.json(); + } + + async getCacheStats(): Promise { + const response = await fetch(`${API_BASE}/api/regions/cache/stats`); + if (!response.ok) throw new Error('Failed to get cache stats'); + return response.json(); + } +} + +// === Region types === + +export interface RegionInfo { + id: string; + name: string; + bbox: number[]; + srtm_tiles: number; + estimated_size_gb: number; + downloaded: boolean; + download_progress: number; +} + +export interface DownloadProgress { + task_id: string; + region_id: string; + status: string; + progress: number; + current_step: string; + downloaded_mb: number; + error?: string; +} + +export interface CacheStats { + terrain_mb: number; + terrain_tiles: number; + buildings_mb: number; + water_mb: number; + vegetation_mb: number; } export const api = new ApiService();