我正在尝试在下面实现一个 openlayers 热图示例：
https://openlayers.org/en/latest/examples/heatmap-earthquakes.html
是否可以显示数量而不是数量（同一区域中有多少点）？
编辑：指针计数并在缩小时显示：
问问题
1122 次
1 回答
2
如果您的意思是将聚类特征显示为热图，则可以这样做。这是集群特征示例和热图示例的组合。
<!DOCTYPE html>
<html>
<head>
<title>Clustered Features</title>
<link rel="stylesheet" href="https://openlayers.org/en/v4.6.5/css/ol.css" type="text/css">
<!-- The line below is only needed for old environments like Internet Explorer and Android 4.x -->
<script src="https://cdn.polyfill.io/v2/polyfill.min.js?features=requestAnimationFrame,Element.prototype.classList,URL"></script>
<script src="https://openlayers.org/en/v4.6.5/build/ol.js"></script>
</head>
<body>
<div id="map" class="map"></div>
<form>
<label>cluster distance</label>
<input id="distance" type="range" min="0" max="100" step="1" value="40"/>
<label>radius size</label>
<input id="radius" type="range" min="1" max="50" step="1" value="5"/>
<label>blur size</label>
<input id="blur" type="range" min="1" max="50" step="1" value="15"/>
</form>
<script>
var distance = document.getElementById('distance');
var blur = document.getElementById('blur');
var radius = document.getElementById('radius');
var count = 20000;
var features = new Array(count);
var e = 4500000;
for (var i = 0; i < count; ++i) {
var coordinates = [2 * e * Math.random() - e, 2 * e * Math.random() - e];
features[i] = new ol.Feature(new ol.geom.Point(coordinates));
}
var source = new ol.source.Vector({
features: features
});
var clusterSource = new ol.source.Cluster({
distance: parseInt(distance.value, 10),
source: source
});
var styleCache = {};
var vector = new ol.layer.Heatmap({
source: clusterSource,
weight: function(feature) { return feature.get('features').length/1000; },
blur: parseInt(blur.value, 10),
radius: parseInt(radius.value, 10)
});
var raster = new ol.layer.Tile({
source: new ol.source.OSM()
});
var map = new ol.Map({
layers: [raster, vector],
target: 'map',
view: new ol.View({
center: [0, 0],
zoom: 2
})
});
distance.addEventListener('input', function() {
clusterSource.setDistance(parseInt(distance.value, 10));
});
blur.addEventListener('input', function() {
vector.setBlur(parseInt(blur.value, 10));
});
radius.addEventListener('input', function() {
vector.setRadius(parseInt(radius.value, 10));
});
</script>
</body>
</html>
此版本显示缩放级别为 0、1 和 2 的普通集群图层以及缩放级别 3 或更高级别的热图
<!DOCTYPE html>
<html>
<head>
<title>Clustered Features</title>
<link rel="stylesheet" href="https://openlayers.org/en/v4.6.5/css/ol.css" type="text/css">
<!-- The line below is only needed for old environments like Internet Explorer and Android 4.x -->
<script src="https://cdn.polyfill.io/v2/polyfill.min.js?features=requestAnimationFrame,Element.prototype.classList,URL"></script>
<script src="https://openlayers.org/en/v4.6.5/build/ol.js"></script>
</head>
<body>
<div id="map" class="map"></div>
<form>
<label>cluster distance</label>
<input id="distance" type="range" min="0" max="100" step="1" value="60"/>
<label>radius size</label>
<input id="radius" type="range" min="1" max="50" step="1" value="40"/>
<label>blur size</label>
<input id="blur" type="range" min="1" max="50" step="1" value="15"/>
</form>
<script>
var distance = document.getElementById('distance');
var blur = document.getElementById('blur');
var radius = document.getElementById('radius');
var count = 20000;
var features = new Array(count);
var e = 4500000;
for (var i = 0; i < count; ++i) {
var coordinates = [2 * e * Math.random() - e, 2 * e * Math.random() - e];
features[i] = new ol.Feature(new ol.geom.Point(coordinates));
}
var source = new ol.source.Vector({
features: features
});
var clusterSource = new ol.source.Cluster({
distance: parseInt(distance.value, 10),
source: source
});
var styleCache = {};
var clusters = new ol.layer.Vector({
source: clusterSource,
style: function(feature) {
var size = feature.get('features').length;
var style = styleCache[size];
if (!style) {
style = new ol.style.Style({
image: new ol.style.Circle({
radius: 15,
stroke: new ol.style.Stroke({
color: '#fff'
}),
fill: new ol.style.Fill({
color: '#3399CC'
})
}),
text: new ol.style.Text({
text: size.toString(),
fill: new ol.style.Fill({
color: '#fff'
})
})
});
styleCache[size] = style;
}
return style;
},
minResolution: ol.tilegrid.createXYZ().getResolution(3) + 1
});
var vector = new ol.layer.Heatmap({
source: clusterSource,
weight: function(feature) { return feature.get('features').length/500; },
blur: parseInt(blur.value, 10),
radius: parseInt(radius.value, 10),
maxResolution: ol.tilegrid.createXYZ().getResolution(3) + 1
});
var raster = new ol.layer.Tile({
source: new ol.source.OSM()
});
var map = new ol.Map({
layers: [raster, clusters, vector],
target: 'map',
view: new ol.View({
center: [0, 0],
zoom: 3
})
});
distance.addEventListener('input', function() {
clusterSource.setDistance(parseInt(distance.value, 10));
});
blur.addEventListener('input', function() {
vector.setBlur(parseInt(blur.value, 10));
});
radius.addEventListener('input', function() {
vector.setRadius(parseInt(radius.value, 10));
});
</script>
</body>
</html>
如果您的数据是随机的，您可以找到当前最大的集群大小并在划分时使用它来计算权重：
weight: function(feature) {
var maxSize = 0;
clusterSource.forEachFeature( function(feature) { maxSize = Math.max(maxSize, feature.get('features').length); } );
return feature.get('features').length/maxSize;
},
于 2018-11-03T14:53:33.097 回答