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import numpy as np
import pandas as pd
DAMAGE_STATES = ['none', 'minor', 'severe', 'collapse']
def generate_buildings(n_buildings, diameter_km, seed=42):
np.random.seed(seed)
buildings = []
radius = diameter_km / 2
for i in range(n_buildings):
angle = np.random.uniform(0, 2 * np.pi)
r = np.random.uniform(0.5, radius)
x = r * np.cos(angle)
y = r * np.sin(angle)
distance = r
building_type = np.random.choice(
['wood', 'concrete', 'steel'],
p=[0.5, 0.3, 0.2]
)
if building_type == 'wood':
occupancy = int(np.random.uniform(10, 100))
elif building_type == 'concrete':
occupancy = int(np.random.uniform(50, 300))
else:
occupancy = int(np.random.uniform(100, 500))
buildings.append({
'building_id': i,
'x': round(x, 2),
'y': round(y, 2),
'distance_km': round(distance, 2),
'building_type': building_type,
'occupancy': occupancy
})
return pd.DataFrame(buildings)
def compute_damage_probabilities(distance, building_type, magnitude, alpha_params):
magnitude_scale = (magnitude - 5.0) / 3.0
magnitude_scale = max(0.1, min(magnitude_scale, 2.0))
base_damage = np.exp(-distance / (15.0 * magnitude_scale))
alpha = alpha_params[building_type]
p_collapse = alpha * base_damage * 0.30 * magnitude_scale
p_severe = alpha * base_damage * 0.25 * magnitude_scale
p_minor = alpha * base_damage * 0.20 * magnitude_scale
total = p_collapse + p_severe + p_minor
if total > 0.95:
scale = 0.95 / total
p_collapse *= scale
p_severe *= scale
p_minor *= scale
p_none = 1 - (p_collapse + p_severe + p_minor)
return np.array([p_none, p_minor, p_severe, p_collapse])
def simulate_damage(buildings_df, magnitude, alpha_params, seed=42):
np.random.seed(seed)
buildings = buildings_df.copy()
for idx, building in buildings.iterrows():
probs = compute_damage_probabilities(
building['distance_km'],
building['building_type'],
magnitude,
alpha_params
)
damage_state = np.random.choice(DAMAGE_STATES, p=probs)
buildings.at[idx, 'true_damage'] = damage_state
buildings.at[idx, 'p_none'] = round(probs[0], 4)
buildings.at[idx, 'p_minor'] = round(probs[1], 4)
buildings.at[idx, 'p_severe'] = round(probs[2], 4)
buildings.at[idx, 'p_collapse'] = round(probs[3], 4)
return buildings
def create_scenario(n_buildings=100, diameter_km=40, magnitude=6.5,
alpha_params=None, seed=42):
if alpha_params is None:
alpha_params = {'wood': 1.5, 'concrete': 1.0, 'steel': 0.7}
buildings = generate_buildings(n_buildings, diameter_km, seed)
scenario = simulate_damage(buildings, magnitude, alpha_params, seed)
return scenario |