Example of using ol/source/Cluster.
This example shows how to do clustering on point features.
import Feature from 'ol/Feature.js';
import Map from 'ol/Map.js';
import Point from 'ol/geom/Point.js';
import View from 'ol/View.js';
import {
Circle as CircleStyle,
Fill,
Stroke,
Style,
Text,
} from 'ol/style.js';
import {Cluster, OSM, Vector as VectorSource} from 'ol/source.js';
import {Tile as TileLayer, Vector as VectorLayer} from 'ol/layer.js';
import {boundingExtent} from 'ol/extent.js';
const distanceInput = document.getElementById('distance');
const minDistanceInput = document.getElementById('min-distance');
const count = 20000;
const features = new Array(count);
const e = 4500000;
for (let i = 0; i < count; ++i) {
const coordinates = [2 * e * Math.random() - e, 2 * e * Math.random() - e];
features[i] = new Feature(new Point(coordinates));
}
const source = new VectorSource({
features: features,
});
const clusterSource = new Cluster({
distance: parseInt(distanceInput.value, 10),
minDistance: parseInt(minDistanceInput.value, 10),
source: source,
});
const styleCache = {};
const clusters = new VectorLayer({
source: clusterSource,
style: function (feature) {
const size = feature.get('features').length;
let style = styleCache[size];
if (!style) {
style = new Style({
image: new CircleStyle({
radius: 10,
stroke: new Stroke({
color: '#fff',
}),
fill: new Fill({
color: '#3399CC',
}),
}),
text: new Text({
text: size.toString(),
fill: new Fill({
color: '#fff',
}),
}),
});
styleCache[size] = style;
}
return style;
},
});
const raster = new TileLayer({
source: new OSM(),
});
const map = new Map({
layers: [raster, clusters],
target: 'map',
view: new View({
center: [0, 0],
zoom: 2,
}),
});
distanceInput.addEventListener('input', function () {
clusterSource.setDistance(parseInt(distanceInput.value, 10));
});
minDistanceInput.addEventListener('input', function () {
clusterSource.setMinDistance(parseInt(minDistanceInput.value, 10));
});
map.on('click', (e) => {
clusters.getFeatures(e.pixel).then((clickedFeatures) => {
if (clickedFeatures.length) {
// Get clustered Coordinates
const features = clickedFeatures[0].get('features');
if (features.length > 1) {
const extent = boundingExtent(
features.map((r) => r.getGeometry().getCoordinates()),
);
map.getView().fit(extent, {duration: 1000, padding: [50, 50, 50, 50]});
}
}
});
});
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>Clustered Features</title>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css">
<link rel="stylesheet" href="node_modules/ol/ol.css">
<style>
.map {
width: 100%;
height: 400px;
}
</style>
</head>
<body>
<div id="map" class="map"></div>
<form>
<div class="form-group">
<label for="distance" class="col-form-label pb-0">Cluster distance</label>
<input id="distance" class="form-range" type="range" min="0" max="200" step="1" value="40"/>
<small class="form-text text-muted">
The distance within which features will be clustered together.
</small>
</div>
<div class="form-group">
<label for="min-distance" class="col-form-label pb-0">Minimum distance</label>
<input id="min-distance" class="form-range" type="range" min="0" max="200" step="1" value="20"/>
<small class="form-text text-muted">
The minimum distance between clusters. Can't be larger than the configured distance.
</small>
</div>
</form>
<script type="module" src="main.js"></script>
</body>
</html>
{
"name": "cluster",
"dependencies": {
"ol": "10.2.1"
},
"devDependencies": {
"vite": "^3.2.3"
},
"scripts": {
"start": "vite",
"build": "vite build"
}
}