Firestation Clustering

How to run

1. Install https://python-poetry.org/docs/
2. Copy config-example.yaml to config.yaml
3. Insert api-key in config.yaml
4. poetry install
5. poetry run x

ToDo

• Switch everything to mapbox
• Probabilistic fire spawning
• Log all relevant data in every iteration
  • Firestation locations
  • Fire locations
  • Driving times /euclid distance
• Add kmeans_driving_time results output
• Run experiments
• Calculate final average driving time for all experiments

Experiments

• euclid uniform
• euclid weighted probabilities
• haversine uniform
• haversine weighted probabilities
• driving_time uniform
• driving_time weighted probabilities

Let's assume we have 1000 fires for the final metric. How many matrix elements do we need? -> 1000 * 4 * 6 = 24000

For driving_time training we need -> 2 * 20 * 400 * 4 = 64000

Total matrix elements: 88000