Context: Build a spatial risk assessment system correlating air quality data with children's respiratory disease incidence across Wuhan. Approach: FastAPI backend serving PostGIS spatial queries, React frontend with Deck.gl maps, and a PyTorch SpatialTemporalGCN pipeline for multi-day (1d/3d/7d) risk prediction. Changes: - backend/ — FastAPI API with auth (JWT), alerts, risk analysis, geocoded case data, grid statistics, and report endpoints - frontend/ — React dashboard with interactive risk maps, alert monitoring, district comparison charts, and timeline player - models/ — SpatialTemporalGCN model with trained weights and ONNX export for inference - scripts/ — ETL pipeline for weather + medical data, grid generation, feature engineering, training, and daily inference - deploy/ — Docker Compose configs for backend, frontend, and MLflow - docs/ — API docs, deployment guide, user guide, and code review Impact: Enables spatial risk visualization, alert monitoring, and ML-driven health risk forecasting for environmental health teams.
44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
"""
|
|
Geographic utilities: point-in-polygon testing via ray casting.
|
|
"""
|
|
|
|
|
|
def point_in_polygon(lat: float, lon: float, polygon_coords: list) -> bool:
|
|
"""Check if a point is inside a polygon (supports Polygon and MultiPolygon)."""
|
|
if not polygon_coords:
|
|
return False
|
|
|
|
# MultiPolygon: check each polygon
|
|
if isinstance(polygon_coords[0], list) and isinstance(polygon_coords[0][0], list):
|
|
for polygon in polygon_coords:
|
|
if polygon and isinstance(polygon[0], list):
|
|
ring = polygon[0] if isinstance(polygon[0][0], list) else polygon
|
|
if point_in_ring(lat, lon, ring):
|
|
return True
|
|
return False
|
|
|
|
# Single Polygon: use first ring (outer boundary)
|
|
ring = polygon_coords[0] if isinstance(polygon_coords[0], list) else polygon_coords
|
|
return point_in_ring(lat, lon, ring)
|
|
|
|
|
|
def point_in_ring(lat: float, lon: float, ring: list) -> bool:
|
|
"""Ray casting algorithm for point-in-ring test."""
|
|
n = len(ring)
|
|
inside = False
|
|
|
|
x, y = lon, lat
|
|
p1x, p1y = ring[0]
|
|
|
|
for i in range(1, n + 1):
|
|
p2x, p2y = ring[i % n]
|
|
if y > min(p1y, p2y):
|
|
if y <= max(p1y, p2y):
|
|
if x <= max(p1x, p2x):
|
|
xinters = (y - p1y) * (p2x - p1x) / (p2y - p1y) if p1y != p2y else p1x
|
|
if p1x == p2x or x <= xinters:
|
|
inside = not inside
|
|
p1x, p1y = p2x, p2y
|
|
|
|
return inside
|