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Quick Start

This guide walks you through your first VoronoiMap estimation in under 5 minutes.

1. Prepare Your Data

Create a data/ directory and add a point data file. Each line has space-separated longitude and latitude:

mkdir data

Create data/sample5.txt:

100.0 200.0
400.0 600.0
800.0 300.0
200.0 800.0
700.0 700.0

2. Run from the Command Line

# Estimate count from the 5-point dataset
voronoimap sample5.txt 5

# Multiple runs for better accuracy
voronoimap sample5.txt 5 --runs 3

Output:

5 7 5.2 142
Run 1: regions=5  max_edges=7  avg_edges=5.2

The output shows:

  • regions — Estimated number of Voronoi regions (should be close to the actual count)
  • max_edges — Maximum number of vertices found on any single region
  • avg_edges — Average number of vertices per region
  • oracle calls — How many nearest-neighbor queries were made

3. Use the Python API

from vormap import get_sum, load_data, find_area, get_NN

# --- Estimation ---
estimated, max_edges, avg_edges = get_sum("sample5.txt", 5)
print(f"Estimated {estimated} objects")
print(f"Max edges: {max_edges}, Avg edges: {avg_edges:.1f}")

# --- Direct data access ---
data = load_data("sample5.txt")
print(f"Loaded {len(data)} points")

# Find nearest neighbor to an arbitrary point
nearest = get_NN(data, 500.0, 500.0)
print(f"Nearest to (500, 500): {nearest}")

# Compute area of the Voronoi region around a data point
area, vertices = find_area(data, 400.0, 600.0)
print(f"Region area: {area:.2f}, Vertices: {vertices}")

4. Custom Boundaries

By default, VoronoiMap auto-detects the search space from data extents. You can override this:

voronoimap sample5.txt 5 --bounds 0 1000 0 1000

from vormap import set_bounds, load_data

set_bounds(south=0, north=1000, west=0, east=1000)
data = load_data("sample5.txt", auto_bounds=False)

Next Steps