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 @vx/voronoi package provides a wrapper around the existing d3-voronoi
package.
The @vx/voronoi package exports a wrapped version of the d3 voronoi layout for flexible usage,
as well as a <VoronoiPolygon /> component for rendering Voronoi regions.
import { voronoi, VoronoiPolygon } from '@vx/voronoi';
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 voronoiLayout = voronoi({
x: d => d.x, // maybe pass a scale here?
y: d => d.y,
width,
height,
});
const voronoiDiagram = voronoiLayout(data);
const polygons = voronoiLayout.polygons(points); // equivalent to voronoiDiagram.polygons()
return (
<svg>
<Group>
{polygons.map((polygon) => (
<VoronoiPolygon key={...} polygon={polygon} />
))}
{points.map(({ x, y }) => (
<circle key={...} cx={x} cy={y} />
)}
</Group>
</svg>
)For more advanced usage with events, see this example. Additional information about the voronoi layout + diagram can be found in the d3-voronoi documentation.