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| import networkx as nx | |
| import numpy as np | |
| class ResourceOptimizer: | |
| def __init__(self): | |
| pass | |
| def allocate_resources(self, impact_forecast): | |
| """ | |
| Calculates optimal manpower and barricades based on forecasted severity. | |
| """ | |
| duration = impact_forecast['predicted_duration_mins'] | |
| radius = impact_forecast['congestion_radius_meters'] | |
| # Base requirements | |
| manpower = 2 | |
| # Scale with radius (e.g., 1 cop per 400m radius) | |
| manpower += int(radius / 400) | |
| # Scale with duration (relief shifts) | |
| if duration > 180: | |
| manpower = int(manpower * 1.5) | |
| elif duration > 360: | |
| manpower = int(manpower * 2.0) | |
| barricades = manpower * 3 | |
| return { | |
| 'recommended_personnel': max(2, manpower), | |
| 'recommended_barricades': max(4, barricades) | |
| } | |
| def calculate_diversion(self, event_lat, event_lon, radius_meters): | |
| """ | |
| Simulates dynamic routing. Recommends alternative waypoints around the congestion. | |
| """ | |
| # 1 degree lat is approx 111 km. | |
| offset_deg = (radius_meters / 111000.0) * 1.3 # 30% margin around radius | |
| diversion_routes = [ | |
| {"lat": event_lat + offset_deg, "lon": event_lon + offset_deg, "instruction": "Divert North-East via alternative arterial"}, | |
| {"lat": event_lat + offset_deg, "lon": event_lon - offset_deg, "instruction": "Divert North-West via alternative arterial"}, | |
| {"lat": event_lat - offset_deg, "lon": event_lon + offset_deg, "instruction": "Divert South-East via alternative arterial"}, | |
| {"lat": event_lat - offset_deg, "lon": event_lon - offset_deg, "instruction": "Divert South-West via alternative arterial"}, | |
| ] | |
| return diversion_routes | |