@visx/delaunay

Overview

A Voronoi diagram partitions a two-dimensional plane into regions based on a set of input points. Each unique input point maps to a corresponding region, where each region represents all points that are closer to the input point than to any other input point.

Not only are Voronoi diagrams 😍, but they can be used to improve the interactive experience of a visualization. This is most often accomplished by overlaying an invisible voronoi grid on top of the visualization to increase the target area of interaction sites such as points on a scatter plot.

The @visx/delaunay package provides a wrapper around the existing d3-delaunay package with some react-specific utilities.

Installation

npm install --save @visx/delaunay

Usage

The @visx/delaunay package exports a wrapped version of the d3 voronoi and delaunay layouts for flexible usage, as well as a <Polygon /> component for rendering Voronoi and Delaunay regions.

import { voronoi, Polygon } from '@visx/delaunay';

const points = Array(n).fill(null).map(() => ({
  x: Math.random() * innerWidth,
  y: Math.random() * innerHeight,
}));

// width + height set an extent on the voronoi
// x + y set relevant accessors depending on the shape of your data
const voronoiDiagram = voronoi({
  data: points,
  x: d => d.x,
  y: d => d.y,
  width,
  height,
});

const polygons = Array.from(voronoiDiagram.cellPolygons());

return (
  <svg>
    <Group>
      {polygons.map((polygon) => (
        <Polygon key={...} polygon={polygon} />
      ))}
      {points.map(({ x, y }) => (
        <circle key={...} cx={x} cy={y} />
      )}
    </Group>
  </svg>
)

Additional information about the voronoi diagram API can be found in the d3-delaunay documentation.