Point clustering with visual variables

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This sample demonstrates how point clustering can be used to group points into clusters based on their spatial proximity to one another. Clustering is enabled on the layer's featureReduction property.

Since featureReduction is independent of the renderer, the symbol and popupTemplate of each cluster graphic can be used to summarize features within the cluster. See Clustering styles and configurations for more information about the various ways clusters can summarize the points they represent.

The layer's renderer in this sample visualizes weather data with three visual variables, each representing a different attribute:

Color: TEMP
Size: WIND_SPEED
Rotation: WIND_DIRECT

The renderer object looks like the the following:

Calculate cluster statistics
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      const renderer = {
        type: "simple", // autocasts as new SimpleRenderer()
        symbol: {
          type: "simple-marker", // autocasts as new SimpleMarkerSymbol()
          // Arrow marker
          path: "M14.5,29 23.5,0 14.5,9 5.5,0z",
          color: [50, 50, 50],
          outline: {
            color: [0, 0, 0, 0.7],
            width: 0.5
          },
          angle: 180,
          size: 15
        },
        visualVariables: [
          {
            type: "rotation",
            // Use {cluster_avg_WIND_DIRECT} in the
            // featureReudction.popupTemplate to
            // display the average temperature of all
            // features within the cluster
            field: "WIND_DIRECT",
            rotationType: "geographic"
          },
          {
            type: "size",
            // Use {cluster_avg_WIND_SPEED} in the
            // featureReudction.popupTemplate to
            // display the average temperature of all
            // features within the cluster
            field: "WIND_SPEED",
            minDataValue: 0,
            maxDataValue: 60,
            minSize: 8,
            maxSize: 40
          },
          {
            type: "color",
            // Use {cluster_avg_TEMP} in the
            // featureReudction.popupTemplate to
            // display the average temperature of all
            // features within the cluster
            field: "TEMP",
            stops: [
              { value: 20, color: "#2b83ba" },
              { value: 35, color: "#abdda4" },
              { value: 50, color: "#ffffbf" },
              { value: 65, color: "#fdae61" },
              { value: 80, color: "#d7191c" }
            ]
          }
        ]
      };

To enable clustering on the layer, you simply have to set the featureReduction property to type cluster,

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layer.featureReduction = {
  type: "cluster"
};

This will cluster the points using the default clusterRadius (80px), and assign a symbol to each cluster conforming to the visualVariables in the renderer in the following manner:

Color: average TEMP of all features in the cluster
Size: average WIND_SPEED of all features in the cluster
Rotation: average WIND_DIRECT of all features in the cluster

No feature reduction	Clustered features
	)

If a UniqueValueRenderer were used, the symbol of the predominant uniqueValueInfo among the features in the cluster would be used to represent the cluster.

To provide more meaning to the app, you can configure a popupTemplate to display the average values of all the fields used by the renderer when the user clicks or taps the cluster.

Configure clustering based on renderer
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      const clusterConfig = {
        type: "cluster",
        popupTemplate: {
          content: [{
            type: "text",
            text: "This cluster represents <b>{cluster_count}</b> weather stations."
          }, {
            type: "fields",
            fieldInfos: [{
              fieldName: "cluster_avg_WIND_SPEED",
              label: "Average wind speed (km/h)",
              format: {
                places: 0
              }
            }, {
              fieldName: "cluster_avg_WIND_DIRECT",
              label: "Average wind direction (degrees)",
              format: {
                places: 0
              }
            }, {
              fieldName: "cluster_avg_TEMP",
              label: "Average temperature (°F)",
              format: {
                places: 0
              }
            }]
          }]
        }
      };

Enabling clustering on layers with spatial references other than Web Mercator and WGS-84 is experimental and may not work for every projection. Clustered layers that have spatial references other than Web Mercator or WGS-84 have the same limitations listed in the projection engine documentation.

Click here to read more information about clustering limitations.