geo-infer-risk

name	geo-infer-risk
description	Geospatial risk modeling including catastrophe models, exposure analysis, and underwriting. Use when assessing spatial risk, building catastrophe models, analyzing exposure/hazard/vulnerability, or computing portfolio risk metrics.
prerequisites	{"required":["geo-infer-space","geo-infer-data"],"recommended":["geo-infer-bayes","geo-infer-math"]}
difficulty	advanced
estimated_time	60min
examples_dir	../GEO-INFER-EXAMPLES/examples/

GEO-INFER-RISK

Instructions

Core Capabilities

• Catastrophe models: Cholesky-decomposition spatial correlation
• Risk engine: Moran's I, Geary C, Monte Carlo loss calculation
• Exposure modeling: Multi-source data loading (DB, file, stream, API)
• Hazard modeling: Spatial hazard assessment and mapping
• Vulnerability: Bayesian uncertainty quantification
• Underwriting: Rule-based fraud detection, env var API keys

Key Imports

from geo_infer_risk.core.risk_engine import RiskEngine
from geo_infer_risk.core.catastrophe_models import CatastropheModel
from geo_infer_risk.core.exposure_model import ExposureModel
from geo_infer_risk.core.hazard_model import HazardModel

Examples

from geo_infer_risk.core.risk_engine import RiskEngine

engine = RiskEngine()
result = engine.assess(
    hazard_raster=flood_depth,
    exposure_data=building_footprints,
    vulnerability_curve="residential_flood"
)
print(f"Expected loss: ${result.expected_loss:,.0f}")
print(f"Loss exceedance (100yr): ${result.loss_at_return_period(100):,.0f}")

from geo_infer_risk.core.catastrophe_models import CatastropheModel

cat_model = CatastropheModel(peril="earthquake", region="pacific_ring")
simulations = cat_model.run_monte_carlo(n_simulations=10_000)
print(f"Mean annual loss: ${simulations.mean_annual_loss:,.0f}")
print(f"99th percentile: ${simulations.percentile(99):,.0f}")

Guidelines

• All 18 former placeholder references verified clean (0 remaining)
• Spatial correlation uses Cholesky decomposition
• Risk aggregation uses real Moran's I and Monte Carlo
• Test: uv run python -m pytest GEO-INFER-RISK/tests/ -v

Integrations

• BAYES → Bayesian uncertainty quantification
• ECON → Economic loss and insurance modeling
• CLIMATE → Climate-driven hazard projections
• SPACE → Spatial correlation of hazards
• AG → Crop loss risk assessment