/** * @license Highcharts JS v11.2.0 (2023-10-30) * * Marker clusters module for Highcharts * * (c) 2010-2021 Wojciech Chmiel * * License: www.highcharts.com/license */ (function (factory) { if (typeof module === 'object' && module.exports) { factory['default'] = factory; module.exports = factory; } else if (typeof define === 'function' && define.amd) { define('highcharts/modules/marker-clusters', ['highcharts'], function (Highcharts) { factory(Highcharts); factory.Highcharts = Highcharts; return factory; }); } else { factory(typeof Highcharts !== 'undefined' ? Highcharts : undefined); } }(function (Highcharts) { 'use strict'; var _modules = Highcharts ? Highcharts._modules : {}; function _registerModule(obj, path, args, fn) { if (!obj.hasOwnProperty(path)) { obj[path] = fn.apply(null, args); if (typeof CustomEvent === 'function') { window.dispatchEvent(new CustomEvent( 'HighchartsModuleLoaded', { detail: { path: path, module: obj[path] } } )); } } } _registerModule(_modules, 'Extensions/MarkerClusters/MarkerClusterDefaults.js', [], function () { /* * * * Marker clusters module. * * (c) 2010-2021 Torstein Honsi * * Author: Wojciech Chmiel * * License: www.highcharts.com/license * * !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!! * * */ /* * * * API Options * * */ /** * Options for marker clusters, the concept of sampling the data * values into larger blocks in order to ease readability and * increase performance of the JavaScript charts. * * Note: marker clusters module is not working with `boost` * and `draggable-points` modules. * * The marker clusters feature requires the marker-clusters.js * file to be loaded, found in the modules directory of the download * package, or online at [code.highcharts.com/modules/marker-clusters.js * ](code.highcharts.com/modules/marker-clusters.js). * * @sample maps/marker-clusters/europe * Maps marker clusters * @sample highcharts/marker-clusters/basic * Scatter marker clusters * @sample maps/marker-clusters/optimized-kmeans * Marker clusters with colorAxis * * @product highcharts highmaps * @since 8.0.0 * @optionparent plotOptions.scatter.cluster * * @private */ var cluster = { /** * Whether to enable the marker-clusters module. * * @sample maps/marker-clusters/basic * Maps marker clusters * @sample highcharts/marker-clusters/basic * Scatter marker clusters */ enabled: false, /** * When set to `false` prevent cluster overlapping - this option * works only when `layoutAlgorithm.type = "grid"`. * * @sample highcharts/marker-clusters/grid * Prevent overlapping */ allowOverlap: true, /** * Options for the cluster marker animation. * @type {boolean|Partial} * @default { "duration": 500 } */ animation: { /** @ignore-option */ duration: 500 }, /** * Zoom the plot area to the cluster points range when a cluster is clicked. */ drillToCluster: true, /** * The minimum amount of points to be combined into a cluster. * This value has to be greater or equal to 2. * * @sample highcharts/marker-clusters/basic * At least three points in the cluster */ minimumClusterSize: 2, /** * Options for layout algorithm. Inside there * are options to change the type of the algorithm, gridSize, * distance or iterations. */ layoutAlgorithm: { /** * Type of the algorithm used to combine points into a cluster. * There are three available algorithms: * * 1) `grid` - grid-based clustering technique. Points are assigned * to squares of set size depending on their position on the plot * area. Points inside the grid square are combined into a cluster. * The grid size can be controlled by `gridSize` property * (grid size changes at certain zoom levels). * * 2) `kmeans` - based on K-Means clustering technique. In the * first step, points are divided using the grid method (distance * property is a grid size) to find the initial amount of clusters. * Next, each point is classified by computing the distance between * each cluster center and that point. When the closest cluster * distance is lower than distance property set by a user the point * is added to this cluster otherwise is classified as `noise`. The * algorithm is repeated until each cluster center not change its * previous position more than one pixel. This technique is more * accurate but also more time consuming than the `grid` algorithm, * especially for big datasets. * * 3) `optimizedKmeans` - based on K-Means clustering technique. This * algorithm uses k-means algorithm only on the chart initialization * or when chart extremes have greater range than on initialization. * When a chart is redrawn the algorithm checks only clustered points * distance from the cluster center and rebuild it when the point is * spaced enough to be outside the cluster. It provides performance * improvement and more stable clusters position yet can be used rather * on small and sparse datasets. * * By default, the algorithm depends on visible quantity of points * and `kmeansThreshold`. When there are more visible points than the * `kmeansThreshold` the `grid` algorithm is used, otherwise `kmeans`. * * The custom clustering algorithm can be added by assigning a callback * function as the type property. This function takes an array of * `processedXData`, `processedYData`, `processedXData` indexes and * `layoutAlgorithm` options as arguments and should return an object * with grouped data. * * The algorithm should return an object like that: *
{
                 *  clusterId1: [{
                 *      x: 573,
                 *      y: 285,
                 *      index: 1 // point index in the data array
                 *  }, {
                 *      x: 521,
                 *      y: 197,
                 *      index: 2
                 *  }],
                 *  clusterId2: [{
                 *      ...
                 *  }]
                 *  ...
                 * }
* * `clusterId` (example above - unique id of a cluster or noise) * is an array of points belonging to a cluster. If the * array has only one point or fewer points than set in * `cluster.minimumClusterSize` it won't be combined into a cluster. * * @sample maps/marker-clusters/optimized-kmeans * Optimized K-Means algorithm * @sample highcharts/marker-clusters/kmeans * K-Means algorithm * @sample highcharts/marker-clusters/grid * Grid algorithm * @sample maps/marker-clusters/custom-alg * Custom algorithm * * @type {string|Function} * @see [cluster.minimumClusterSize](#plotOptions.scatter.cluster.minimumClusterSize) * @apioption plotOptions.scatter.cluster.layoutAlgorithm.type */ /** * When `type` is set to the `grid`, * `gridSize` is a size of a grid square element either as a number * defining pixels, or a percentage defining a percentage * of the plot area width. * * @type {number|string} */ gridSize: 50, /** * When `type` is set to `kmeans`, * `iterations` are the number of iterations that this algorithm will be * repeated to find clusters positions. * * @type {number} * @apioption plotOptions.scatter.cluster.layoutAlgorithm.iterations */ /** * When `type` is set to `kmeans`, * `distance` is a maximum distance between point and cluster center * so that this point will be inside the cluster. The distance * is either a number defining pixels or a percentage * defining a percentage of the plot area width. * * @type {number|string} */ distance: 40, /** * When `type` is set to `undefined` and there are more visible points * than the kmeansThreshold the `grid` algorithm is used to find * clusters, otherwise `kmeans`. It ensures good performance on * large datasets and better clusters arrangement after the zoom. */ kmeansThreshold: 100 }, /** * Options for the cluster marker. * @type {Highcharts.PointMarkerOptionsObject} * @extends plotOptions.series.marker * @excluding enabledThreshold, states */ marker: { /** @internal */ symbol: 'cluster', /** @internal */ radius: 15, /** @internal */ lineWidth: 0, /** @internal */ lineColor: "#ffffff" /* Palette.backgroundColor */ }, /** * Fires when the cluster point is clicked and `drillToCluster` is enabled. * One parameter, `event`, is passed to the function. The default action * is to zoom to the cluster points range. This can be prevented * by calling `event.preventDefault()`. * * @type {Highcharts.MarkerClusterDrillCallbackFunction} * @product highcharts highmaps * @see [cluster.drillToCluster](#plotOptions.scatter.cluster.drillToCluster) * @apioption plotOptions.scatter.cluster.events.drillToCluster */ /** * An array defining zones within marker clusters. * * In styled mode, the color zones are styled with the * `.highcharts-cluster-zone-{n}` class, or custom * classed from the `className` * option. * * @sample highcharts/marker-clusters/basic * Marker clusters zones * @sample maps/marker-clusters/custom-alg * Zones on maps * * @type {Array<*>} * @product highcharts highmaps * @apioption plotOptions.scatter.cluster.zones */ /** * Styled mode only. A custom class name for the zone. * * @sample highcharts/css/color-zones/ * Zones styled by class name * * @type {string} * @apioption plotOptions.scatter.cluster.zones.className */ /** * Settings for the cluster marker belonging to the zone. * * @see [cluster.marker](#plotOptions.scatter.cluster.marker) * @extends plotOptions.scatter.cluster.marker * @product highcharts highmaps * @apioption plotOptions.scatter.cluster.zones.marker */ /** * The value where the zone starts. * * @type {number} * @product highcharts highmaps * @apioption plotOptions.scatter.cluster.zones.from */ /** * The value where the zone ends. * * @type {number} * @product highcharts highmaps * @apioption plotOptions.scatter.cluster.zones.to */ /** * The fill color of the cluster marker in hover state. When * `undefined`, the series' or point's fillColor for normal * state is used. * * @type {Highcharts.ColorType} * @apioption plotOptions.scatter.cluster.states.hover.fillColor */ /** * Options for the cluster data labels. * @type {Highcharts.DataLabelsOptions} */ dataLabels: { /** @internal */ enabled: true, /** @internal */ format: '{point.clusterPointsAmount}', /** @internal */ verticalAlign: 'middle', /** @internal */ align: 'center', /** @internal */ style: { color: 'contrast' }, /** @internal */ inside: true } }; var tooltip = { /** * The HTML of the cluster point's in the tooltip. Works only with * marker-clusters module and analogously to * [pointFormat](#tooltip.pointFormat). * * The cluster tooltip can be also formatted using * `tooltip.formatter` callback function and `point.isCluster` flag. * * @sample highcharts/marker-clusters/grid * Format tooltip for cluster points. * * @sample maps/marker-clusters/europe/ * Format tooltip for clusters using tooltip.formatter * * @type {string} * @default Clustered points: {point.clusterPointsAmount} * @apioption tooltip.clusterFormat */ clusterFormat: 'Clustered points: ' + '{point.clusterPointsAmount}
' }; /* * * * Default Export * * */ var MarkerClusterDefaults = { cluster: cluster, tooltip: tooltip }; return MarkerClusterDefaults; }); _registerModule(_modules, 'Extensions/MarkerClusters/MarkerClusterScatter.js', [_modules['Core/Animation/AnimationUtilities.js'], _modules['Extensions/MarkerClusters/MarkerClusterDefaults.js'], _modules['Core/Utilities.js']], function (A, MarkerClusterDefaults, U) { /* * * * Marker clusters module. * * (c) 2010-2021 Torstein Honsi * * Author: Wojciech Chmiel * * License: www.highcharts.com/license * * !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!! * * */ var animObject = A.animObject; var clusterDefaults = MarkerClusterDefaults.cluster; var addEvent = U.addEvent, defined = U.defined, error = U.error, isArray = U.isArray, isFunction = U.isFunction, isObject = U.isObject, isNumber = U.isNumber, merge = U.merge, objectEach = U.objectEach, pushUnique = U.pushUnique, relativeLength = U.relativeLength, syncTimeout = U.syncTimeout; /* * * * Constants * * */ var composedMembers = []; var markerClusterAlgorithms = { grid: function (dataX, dataY, dataIndexes, options) { var series = this, grid = {}, gridOffset = this.getGridOffset(); var x, y, gridX, gridY, key, i; // drawGridLines(series, options); var scaledGridSize = series.getScaledGridSize(options); for (i = 0; i < dataX.length; i++) { var p = valuesToPixels(series, { x: dataX[i], y: dataY[i] }); x = p.x - gridOffset.plotLeft; y = p.y - gridOffset.plotTop; gridX = Math.floor(x / scaledGridSize); gridY = Math.floor(y / scaledGridSize); key = gridY + '-' + gridX; if (!grid[key]) { grid[key] = []; } grid[key].push({ dataIndex: dataIndexes[i], x: dataX[i], y: dataY[i] }); } return grid; }, kmeans: function (dataX, dataY, dataIndexes, options) { var series = this, clusters = [], noise = [], group = {}, pointMaxDistance = options.processedDistance || clusterDefaults.layoutAlgorithm.distance, iterations = options.iterations, // Max pixel difference beetwen new and old cluster position. maxClusterShift = 1; var currentIteration = 0, repeat = true, pointX = 0, pointY = 0, tempPos, pointClusterDistance = []; options.processedGridSize = options.processedDistance; // Use grid method to get groupedData object. var groupedData = series.markerClusterAlgorithms ? series.markerClusterAlgorithms.grid.call(series, dataX, dataY, dataIndexes, options) : {}; // Find clusters amount and its start positions // based on grid grouped data. for (var key in groupedData) { if (groupedData[key].length > 1) { tempPos = getClusterPosition(groupedData[key]); clusters.push({ posX: tempPos.x, posY: tempPos.y, oldX: 0, oldY: 0, startPointsLen: groupedData[key].length, points: [] }); } } // Start kmeans iteration process. while (repeat) { for (var _i = 0, clusters_1 = clusters; _i < clusters_1.length; _i++) { var c = clusters_1[_i]; c.points.length = 0; } noise.length = 0; for (var i = 0; i < dataX.length; i++) { pointX = dataX[i]; pointY = dataY[i]; pointClusterDistance = series.getClusterDistancesFromPoint(clusters, pointX, pointY); if (pointClusterDistance.length && pointClusterDistance[0].distance < pointMaxDistance) { clusters[pointClusterDistance[0].clusterIndex].points.push({ x: pointX, y: pointY, dataIndex: dataIndexes[i] }); } else { noise.push({ x: pointX, y: pointY, dataIndex: dataIndexes[i] }); } } // When cluster points array has only one point the // point should be classified again. for (var i = 0; i < clusters.length; i++) { if (clusters[i].points.length === 1) { pointClusterDistance = series.getClusterDistancesFromPoint(clusters, clusters[i].points[0].x, clusters[i].points[0].y); if (pointClusterDistance[1].distance < pointMaxDistance) { // Add point to the next closest cluster. clusters[pointClusterDistance[1].clusterIndex].points .push(clusters[i].points[0]); // Clear points array. clusters[pointClusterDistance[0].clusterIndex] .points.length = 0; } } } // Compute a new clusters position and check if it // is different than the old one. repeat = false; for (var i = 0; i < clusters.length; i++) { tempPos = getClusterPosition(clusters[i].points); clusters[i].oldX = clusters[i].posX; clusters[i].oldY = clusters[i].posY; clusters[i].posX = tempPos.x; clusters[i].posY = tempPos.y; // Repeat the algorithm if at least one cluster // is shifted more than maxClusterShift property. if (clusters[i].posX > clusters[i].oldX + maxClusterShift || clusters[i].posX < clusters[i].oldX - maxClusterShift || clusters[i].posY > clusters[i].oldY + maxClusterShift || clusters[i].posY < clusters[i].oldY - maxClusterShift) { repeat = true; } } // If iterations property is set repeat the algorithm // specified amount of times. if (iterations) { repeat = currentIteration < iterations - 1; } currentIteration++; } for (var i = 0, iEnd = clusters.length; i < iEnd; ++i) { group['cluster' + i] = clusters[i].points; } for (var i = 0, iEnd = noise.length; i < iEnd; ++i) { group['noise' + i] = [noise[i]]; } return group; }, optimizedKmeans: function (processedXData, processedYData, dataIndexes, options) { var series = this, pointMaxDistance = options.processedDistance || clusterDefaults.layoutAlgorithm.gridSize, extremes = series.getRealExtremes(), clusterMarkerOptions = (series.options.cluster || {}).marker; var distance, group = {}, offset, radius; if (!series.markerClusterInfo || (series.initMaxX && series.initMaxX < extremes.maxX || series.initMinX && series.initMinX > extremes.minX || series.initMaxY && series.initMaxY < extremes.maxY || series.initMinY && series.initMinY > extremes.minY)) { series.initMaxX = extremes.maxX; series.initMinX = extremes.minX; series.initMaxY = extremes.maxY; series.initMinY = extremes.minY; group = series.markerClusterAlgorithms ? series.markerClusterAlgorithms.kmeans.call(series, processedXData, processedYData, dataIndexes, options) : {}; series.baseClusters = null; } else { if (!series.baseClusters) { series.baseClusters = { clusters: series.markerClusterInfo.clusters, noise: series.markerClusterInfo.noise }; } for (var _i = 0, _a = series.baseClusters.clusters; _i < _a.length; _i++) { var cluster = _a[_i]; cluster.pointsOutside = []; cluster.pointsInside = []; for (var _b = 0, _c = cluster.data; _b < _c.length; _b++) { var dataPoint = _c[_b]; var dataPointPx = valuesToPixels(series, dataPoint), clusterPx = valuesToPixels(series, cluster); distance = Math.sqrt(Math.pow(dataPointPx.x - clusterPx.x, 2) + Math.pow(dataPointPx.y - clusterPx.y, 2)); if (cluster.clusterZone && cluster.clusterZone.marker && cluster.clusterZone.marker.radius) { radius = cluster.clusterZone.marker.radius; } else if (clusterMarkerOptions && clusterMarkerOptions.radius) { radius = clusterMarkerOptions.radius; } else { radius = clusterDefaults.marker.radius; } offset = pointMaxDistance - radius >= 0 ? pointMaxDistance - radius : radius; if (distance > radius + offset && defined(cluster.pointsOutside)) { cluster.pointsOutside.push(dataPoint); } else if (defined(cluster.pointsInside)) { cluster.pointsInside.push(dataPoint); } } if (cluster.pointsInside.length) { group[cluster.id] = cluster.pointsInside; } var i = 0; for (var _d = 0, _e = cluster.pointsOutside; _d < _e.length; _d++) { var p = _e[_d]; group[cluster.id + '_noise' + i++] = [p]; } } for (var _f = 0, _g = series.baseClusters.noise; _f < _g.length; _f++) { var noise = _g[_f]; group[noise.id] = noise.data; } } return group; } }; /* * * * Variables * * */ var baseGeneratePoints; /** * Points that ids are included in the oldPointsStateId array are hidden before * animation. Other ones are destroyed. * @private */ var oldPointsStateId = []; var stateIdCounter = 0; /* * * * Functions * * */ /** @private */ function compose(highchartsDefaultOptions, ScatterSeriesClass) { if (pushUnique(composedMembers, ScatterSeriesClass)) { var scatterProto = ScatterSeriesClass.prototype; baseGeneratePoints = scatterProto.generatePoints; scatterProto.markerClusterAlgorithms = markerClusterAlgorithms; scatterProto.animateClusterPoint = seriesAnimateClusterPoint; scatterProto.destroyClusteredData = seriesDestroyClusteredData; scatterProto.generatePoints = seriesGeneratePoints; scatterProto.getClusterDistancesFromPoint = seriesGetClusterDistancesFromPoint; scatterProto.getClusteredData = seriesGetClusteredData; scatterProto.getGridOffset = seriesGetGridOffset; scatterProto.getPointsState = seriesGetPointsState; scatterProto.getRealExtremes = seriesGetRealExtremes; scatterProto.getScaledGridSize = seriesGetScaledGridSize; scatterProto.hideClusteredData = seriesHideClusteredData; scatterProto.isValidGroupedDataObject = seriesIsValidGroupedDataObject; scatterProto.preventClusterCollisions = seriesPreventClusterCollisions; // Destroy grouped data on series destroy. addEvent(ScatterSeriesClass, 'destroy', scatterProto.destroyClusteredData); } if (pushUnique(composedMembers, highchartsDefaultOptions)) { (highchartsDefaultOptions.plotOptions || {}).series = merge((highchartsDefaultOptions.plotOptions || {}).series, MarkerClusterDefaults); } } /** * Util function. * @private */ function destroyOldPoints(oldState) { if (oldState) { var state = void 0; for (var _i = 0, _a = Object.keys(oldState); _i < _a.length; _i++) { var key = _a[_i]; state = oldState[key]; if (state.point && state.point.destroy) { state.point.destroy(); } } } } /** * Util function. * @private */ function fadeInElement(elem, opacity, animation) { elem .attr({ opacity: opacity }) .animate({ opacity: 1 }, animation); } /** * Util function. * @private */ function fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, opacity) { // Fade in new point. fadeInStatePoint(newPointObj, opacity, animation, true, true); // Destroy old animated points. for (var _i = 0, oldPoints_1 = oldPoints; _i < oldPoints_1.length; _i++) { var p = oldPoints_1[_i]; if (p.point && p.point.destroy) { p.point.destroy(); } } } /** * Util function. * @private */ function fadeInStatePoint(stateObj, opacity, animation, fadeinGraphic, fadeinDataLabel) { if (stateObj.point) { if (fadeinGraphic && stateObj.point.graphic) { stateObj.point.graphic.show(); fadeInElement(stateObj.point.graphic, opacity, animation); } if (fadeinDataLabel && stateObj.point.dataLabel) { stateObj.point.dataLabel.show(); fadeInElement(stateObj.point.dataLabel, opacity, animation); } } } /** * Util function. * @private */ function getClusterPosition(points) { var pointsLen = points.length; var sumX = 0, sumY = 0; for (var i = 0; i < pointsLen; i++) { sumX += points[i].x; sumY += points[i].y; } return { x: sumX / pointsLen, y: sumY / pointsLen }; } /** * Util function.Prepare array with sorted data objects to be compared in * getPointsState method. * @private */ function getDataState(clusteredData, stateDataLen) { var state = []; state.length = stateDataLen; clusteredData.clusters.forEach(function (cluster) { cluster.data.forEach(function (elem) { state[elem.dataIndex] = elem; }); }); clusteredData.noise.forEach(function (noise) { state[noise.data[0].dataIndex] = noise.data[0]; }); return state; } /** * Util function. Generate unique stateId for a state element. * @private */ function getStateId() { return Math.random().toString(36).substring(2, 7) + '-' + stateIdCounter++; } /** * Util function. * @private */ function hideStatePoint(stateObj, hideGraphic, hideDataLabel) { if (stateObj.point) { if (hideGraphic && stateObj.point.graphic) { stateObj.point.graphic.hide(); } if (hideDataLabel && stateObj.point.dataLabel) { stateObj.point.dataLabel.hide(); } } } /** @private */ function onPointDrillToCluster(event) { var point = event.point || event.target; point.firePointEvent('drillToCluster', event, function (e) { var point = e.point || e.target, series = point.series, xAxis = point.series.xAxis, yAxis = point.series.yAxis, chart = point.series.chart, mapView = chart.mapView, clusterOptions = series.options.cluster, drillToCluster = (clusterOptions || {}).drillToCluster; if (drillToCluster && point.clusteredData) { var sortedDataX = point.clusteredData .map(function (data) { return data.x; }) .sort(function (a, b) { return a - b; }), sortedDataY = point.clusteredData .map(function (data) { return data.y; }) .sort(function (a, b) { return a - b; }), minX = sortedDataX[0], maxX = sortedDataX[sortedDataX.length - 1], minY = sortedDataY[0], maxY = sortedDataY[sortedDataY.length - 1], offsetX = Math.abs((maxX - minX) * 0.1), offsetY = Math.abs((maxY - minY) * 0.1), x1 = Math.min(minX, maxX) - offsetX, x2 = Math.max(minX, maxX) + offsetX, y1 = Math.min(minY, maxY) - offsetY, y2 = Math.max(minY, maxY) + offsetY; if (mapView) { mapView.fitToBounds({ x1: x1, x2: x2, y1: y1, y2: y2 }); } else if (xAxis && yAxis) { chart.pointer.zoomX = true; chart.pointer.zoomY = true; chart.zoom({ originalEvent: e, xAxis: [{ axis: xAxis, min: x1, max: x2 }], yAxis: [{ axis: yAxis, min: y1, max: y2 }] }); } } }); } /** * Util function. * @private */ function pixelsToValues(series, pos) { var chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis; if (chart.mapView) { return chart.mapView.pixelsToProjectedUnits(pos); } return { x: xAxis ? xAxis.toValue(pos.x) : 0, y: yAxis ? yAxis.toValue(pos.y) : 0 }; } /** @private */ function seriesAnimateClusterPoint(clusterObj) { var series = this, chart = series.chart, mapView = chart.mapView, clusterOptions = series.options.cluster, animation = animObject((clusterOptions || {}).animation), animDuration = animation.duration || 500, pointsState = (series.markerClusterInfo || {}).pointsState, newState = (pointsState || {}).newState, oldState = (pointsState || {}).oldState, oldPoints = []; var parentId, oldPointObj, newPointObj, newPointBBox, offset = 0, newX = 0, newY = 0, isOldPointGrahic = false, isCbHandled = false; if (oldState && newState) { newPointObj = newState[clusterObj.stateId]; var newPos = valuesToPixels(series, newPointObj); newX = newPos.x - (mapView ? 0 : chart.plotLeft); newY = newPos.y - (mapView ? 0 : chart.plotTop); // Point has one ancestor. if (newPointObj.parentsId.length === 1) { parentId = (newState || {})[clusterObj.stateId].parentsId[0]; oldPointObj = oldState[parentId]; // If old and new poistions are the same do not animate. if (newPointObj.point && newPointObj.point.graphic && oldPointObj && oldPointObj.point && oldPointObj.point.plotX && oldPointObj.point.plotY && oldPointObj.point.plotX !== newPointObj.point.plotX && oldPointObj.point.plotY !== newPointObj.point.plotY) { newPointBBox = newPointObj.point.graphic.getBBox(); // Marker image does not have the offset (#14342). offset = (newPointObj.point.graphic && newPointObj.point.graphic.isImg) ? 0 : newPointBBox.width / 2; newPointObj.point.graphic.attr({ x: oldPointObj.point.plotX - offset, y: oldPointObj.point.plotY - offset }); newPointObj.point.graphic.animate({ x: newX - (newPointObj.point.graphic.radius || 0), y: newY - (newPointObj.point.graphic.radius || 0) }, animation, function () { isCbHandled = true; // Destroy old point. if (oldPointObj.point && oldPointObj.point.destroy) { oldPointObj.point.destroy(); } }); // Data label animation. if (newPointObj.point.dataLabel && newPointObj.point.dataLabel.alignAttr && oldPointObj.point.dataLabel && oldPointObj.point.dataLabel.alignAttr) { newPointObj.point.dataLabel.attr({ x: oldPointObj.point.dataLabel.alignAttr.x, y: oldPointObj.point.dataLabel.alignAttr.y }); newPointObj.point.dataLabel.animate({ x: newPointObj.point.dataLabel.alignAttr.x, y: newPointObj.point.dataLabel.alignAttr.y }, animation); } } } else if (newPointObj.parentsId.length === 0) { // Point has no ancestors - new point. // Hide new point. hideStatePoint(newPointObj, true, true); syncTimeout(function () { // Fade in new point. fadeInStatePoint(newPointObj, 0.1, animation, true, true); }, animDuration / 2); } else { // Point has many ancestors. // Hide new point before animation. hideStatePoint(newPointObj, true, true); newPointObj.parentsId.forEach(function (elem) { if (oldState && oldState[elem]) { oldPointObj = oldState[elem]; oldPoints.push(oldPointObj); if (oldPointObj.point && oldPointObj.point.graphic) { isOldPointGrahic = true; oldPointObj.point.graphic.show(); oldPointObj.point.graphic.animate({ x: newX - (oldPointObj.point.graphic.radius || 0), y: newY - (oldPointObj.point.graphic.radius || 0), opacity: 0.4 }, animation, function () { isCbHandled = true; fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, 0.7); }); if (oldPointObj.point.dataLabel && oldPointObj.point.dataLabel.y !== -9999 && newPointObj.point && newPointObj.point.dataLabel && newPointObj.point.dataLabel.alignAttr) { oldPointObj.point.dataLabel.show(); oldPointObj.point.dataLabel.animate({ x: newPointObj.point.dataLabel.alignAttr.x, y: newPointObj.point.dataLabel.alignAttr.y, opacity: 0.4 }, animation); } } } }); // Make sure point is faded in. syncTimeout(function () { if (!isCbHandled) { fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, 0.85); } }, animDuration); if (!isOldPointGrahic) { syncTimeout(function () { fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, 0.1); }, animDuration / 2); } } } } /** * Destroy clustered data points. * @private */ function seriesDestroyClusteredData() { var clusteredSeriesData = this.markerClusterSeriesData; // Clear previous groups. (clusteredSeriesData || []).forEach(function (point) { if (point && point.destroy) { point.destroy(); } }); this.markerClusterSeriesData = null; } /** * Override the generatePoints method by adding a reference to grouped data. * @private */ function seriesGeneratePoints() { var series = this, chart = series.chart, mapView = chart.mapView, xData = series.xData, yData = series.yData, clusterOptions = series.options.cluster, realExtremes = series.getRealExtremes(), visibleXData = [], visibleYData = [], visibleDataIndexes = []; var oldPointsState, oldDataLen, oldMarkerClusterInfo, kmeansThreshold, cropDataOffsetX, cropDataOffsetY, seriesMinX, seriesMaxX, seriesMinY, seriesMaxY, type, algorithm, clusteredData, groupedData, layoutAlgOptions, point, i; // For map point series, we need to resolve lon, lat and geometry options // and project them on the plane in order to get x and y. In the regular // series flow, this is not done until the `translate` method because the // resulting [x, y] position depends on inset positions in the MapView. if (mapView && series.is('mappoint') && xData && yData) { (series.options.data || []).forEach(function (p, i) { var xy = series.projectPoint(p); if (xy) { xData[i] = xy.x; yData[i] = xy.y; } }); } if (clusterOptions && clusterOptions.enabled && xData && xData.length && yData && yData.length && !chart.polar) { type = clusterOptions.layoutAlgorithm.type; layoutAlgOptions = clusterOptions.layoutAlgorithm; // Get processed algorithm properties. layoutAlgOptions.processedGridSize = relativeLength(layoutAlgOptions.gridSize || clusterDefaults.layoutAlgorithm.gridSize, chart.plotWidth); layoutAlgOptions.processedDistance = relativeLength(layoutAlgOptions.distance || clusterDefaults.layoutAlgorithm.distance, chart.plotWidth); kmeansThreshold = layoutAlgOptions.kmeansThreshold || clusterDefaults.layoutAlgorithm.kmeansThreshold; // Offset to prevent cluster size changes. var halfGrid = layoutAlgOptions.processedGridSize / 2, p1 = pixelsToValues(series, { x: 0, y: 0 }), p2 = pixelsToValues(series, { x: halfGrid, y: halfGrid }); cropDataOffsetX = Math.abs(p1.x - p2.x); cropDataOffsetY = Math.abs(p1.y - p2.y); // Get only visible data. for (i = 0; i < xData.length; i++) { if (!series.dataMaxX) { if (!defined(seriesMaxX) || !defined(seriesMinX) || !defined(seriesMaxY) || !defined(seriesMinY)) { seriesMaxX = seriesMinX = xData[i]; seriesMaxY = seriesMinY = yData[i]; } else if (isNumber(yData[i]) && isNumber(seriesMaxY) && isNumber(seriesMinY)) { seriesMaxX = Math.max(xData[i], seriesMaxX); seriesMinX = Math.min(xData[i], seriesMinX); seriesMaxY = Math.max(yData[i] || seriesMaxY, seriesMaxY); seriesMinY = Math.min(yData[i] || seriesMinY, seriesMinY); } } // Crop data to visible ones with appropriate offset to prevent // cluster size changes on the edge of the plot area. if (xData[i] >= (realExtremes.minX - cropDataOffsetX) && xData[i] <= (realExtremes.maxX + cropDataOffsetX) && (yData[i] || realExtremes.minY) >= (realExtremes.minY - cropDataOffsetY) && (yData[i] || realExtremes.maxY) <= (realExtremes.maxY + cropDataOffsetY)) { visibleXData.push(xData[i]); visibleYData.push(yData[i]); visibleDataIndexes.push(i); } } // Save data max values. if (defined(seriesMaxX) && defined(seriesMinX) && isNumber(seriesMaxY) && isNumber(seriesMinY)) { series.dataMaxX = seriesMaxX; series.dataMinX = seriesMinX; series.dataMaxY = seriesMaxY; series.dataMinY = seriesMinY; } if (isFunction(type)) { algorithm = type; } else if (series.markerClusterAlgorithms) { if (type && series.markerClusterAlgorithms[type]) { algorithm = series.markerClusterAlgorithms[type]; } else { algorithm = visibleXData.length < kmeansThreshold ? series.markerClusterAlgorithms.kmeans : series.markerClusterAlgorithms.grid; } } else { algorithm = function () { return false; }; } groupedData = algorithm.call(this, visibleXData, visibleYData, visibleDataIndexes, layoutAlgOptions); clusteredData = groupedData ? series.getClusteredData(groupedData, clusterOptions) : groupedData; // When animation is enabled get old points state. if (clusterOptions.animation && series.markerClusterInfo && series.markerClusterInfo.pointsState && series.markerClusterInfo.pointsState.oldState) { // Destroy old points. destroyOldPoints(series.markerClusterInfo.pointsState.oldState); oldPointsState = series.markerClusterInfo.pointsState.newState; } else { oldPointsState = {}; } // Save points old state info. oldDataLen = xData.length; oldMarkerClusterInfo = series.markerClusterInfo; if (clusteredData) { series.processedXData = clusteredData.groupedXData; series.processedYData = clusteredData.groupedYData; series.hasGroupedData = true; series.markerClusterInfo = clusteredData; series.groupMap = clusteredData.groupMap; } baseGeneratePoints.apply(this); if (clusteredData && series.markerClusterInfo) { // Mark cluster points. Safe point reference in the cluster object. (series.markerClusterInfo.clusters || []).forEach(function (cluster) { point = series.points[cluster.index]; point.isCluster = true; point.clusteredData = cluster.data; point.clusterPointsAmount = cluster.data.length; cluster.point = point; // Add zoom to cluster range. addEvent(point, 'click', onPointDrillToCluster); }); // Safe point reference in the noise object. (series.markerClusterInfo.noise || []).forEach(function (noise) { noise.point = series.points[noise.index]; }); // When animation is enabled save points state. if (clusterOptions.animation && series.markerClusterInfo) { series.markerClusterInfo.pointsState = { oldState: oldPointsState, newState: series.getPointsState(clusteredData, oldMarkerClusterInfo, oldDataLen) }; } // Record grouped data in order to let it be destroyed the next time // processData runs. if (!clusterOptions.animation) { this.destroyClusteredData(); } else { this.hideClusteredData(); } this.markerClusterSeriesData = this.hasGroupedData ? this.points : null; } } else { baseGeneratePoints.apply(this); } } /** @private */ function seriesGetClusterDistancesFromPoint(clusters, pointX, pointY) { var pointClusterDistance = []; for (var clusterIndex = 0; clusterIndex < clusters.length; clusterIndex++) { var p1 = valuesToPixels(this, { x: pointX, y: pointY }), p2 = valuesToPixels(this, { x: clusters[clusterIndex].posX, y: clusters[clusterIndex].posY }), distance = Math.sqrt(Math.pow(p1.x - p2.x, 2) + Math.pow(p1.y - p2.y, 2)); pointClusterDistance.push({ clusterIndex: clusterIndex, distance: distance }); } return pointClusterDistance.sort(function (a, b) { return a.distance - b.distance; }); } /** @private */ function seriesGetClusteredData(groupedData, options) { var series = this, groupedXData = [], groupedYData = [], clusters = [], // Container for clusters. noise = [], // Container for points not belonging to any cluster. groupMap = [], // Prevent minimumClusterSize lower than 2. minimumClusterSize = Math.max(2, options.minimumClusterSize || 2); var index = 0, stateId, point, points, pointUserOptions, pointsLen, marker, clusterPos, pointOptions, clusterTempPos, zoneOptions, clusterZone, clusterZoneClassName, i, k; // Check if groupedData is valid when user uses a custom algorithm. if (isFunction(options.layoutAlgorithm.type) && !series.isValidGroupedDataObject(groupedData)) { error('Highcharts marker-clusters module: ' + 'The custom algorithm result is not valid!', false, series.chart); return false; } for (k in groupedData) { if (groupedData[k].length >= minimumClusterSize) { points = groupedData[k]; stateId = getStateId(); pointsLen = points.length; // Get zone options for cluster. if (options.zones) { for (i = 0; i < options.zones.length; i++) { if (pointsLen >= options.zones[i].from && pointsLen <= options.zones[i].to) { clusterZone = options.zones[i]; clusterZone.zoneIndex = i; zoneOptions = options.zones[i].marker; clusterZoneClassName = options.zones[i].className; } } } clusterTempPos = getClusterPosition(points); if (options.layoutAlgorithm.type === 'grid' && !options.allowOverlap) { marker = series.options.marker || {}; clusterPos = series.preventClusterCollisions({ x: clusterTempPos.x, y: clusterTempPos.y, key: k, groupedData: groupedData, gridSize: series.getScaledGridSize(options.layoutAlgorithm), defaultRadius: marker.radius || 3 + (marker.lineWidth || 0), clusterRadius: (zoneOptions && zoneOptions.radius) ? zoneOptions.radius : (options.marker || {}).radius || clusterDefaults.marker.radius }); } else { clusterPos = { x: clusterTempPos.x, y: clusterTempPos.y }; } for (i = 0; i < pointsLen; i++) { points[i].parentStateId = stateId; } clusters.push({ x: clusterPos.x, y: clusterPos.y, id: k, stateId: stateId, index: index, data: points, clusterZone: clusterZone, clusterZoneClassName: clusterZoneClassName }); groupedXData.push(clusterPos.x); groupedYData.push(clusterPos.y); groupMap.push({ options: { formatPrefix: 'cluster', dataLabels: options.dataLabels, marker: merge(options.marker, { states: options.states }, zoneOptions || {}) } }); // Save cluster data points options. if (series.options.data && series.options.data.length) { for (i = 0; i < pointsLen; i++) { if (isObject(series.options.data[points[i].dataIndex])) { points[i].options = series.options.data[points[i].dataIndex]; } } } index++; zoneOptions = null; } else { for (i = 0; i < groupedData[k].length; i++) { // Points not belonging to any cluster. point = groupedData[k][i]; stateId = getStateId(); pointOptions = null; pointUserOptions = ((series.options || {}).data || [])[point.dataIndex]; groupedXData.push(point.x); groupedYData.push(point.y); point.parentStateId = stateId; noise.push({ x: point.x, y: point.y, id: k, stateId: stateId, index: index, data: groupedData[k] }); if (pointUserOptions && typeof pointUserOptions === 'object' && !isArray(pointUserOptions)) { pointOptions = merge(pointUserOptions, { x: point.x, y: point.y }); } else { pointOptions = { userOptions: pointUserOptions, x: point.x, y: point.y }; } groupMap.push({ options: pointOptions }); index++; } } } return { clusters: clusters, noise: noise, groupedXData: groupedXData, groupedYData: groupedYData, groupMap: groupMap }; } /** @private */ function seriesGetGridOffset() { var series = this, chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis; var plotLeft = 0, plotTop = 0; if (xAxis && series.dataMinX && series.dataMaxX) { plotLeft = xAxis.reversed ? xAxis.toPixels(series.dataMaxX) : xAxis.toPixels(series.dataMinX); } else { plotLeft = chart.plotLeft; } if (yAxis && series.dataMinY && series.dataMaxY) { plotTop = yAxis.reversed ? yAxis.toPixels(series.dataMinY) : yAxis.toPixels(series.dataMaxY); } else { plotTop = chart.plotTop; } return { plotLeft: plotLeft, plotTop: plotTop }; } /** * Point state used when animation is enabled to compare and bind old points * with new ones. * @private */ function seriesGetPointsState(clusteredData, oldMarkerClusterInfo, dataLength) { var oldDataStateArr = oldMarkerClusterInfo ? getDataState(oldMarkerClusterInfo, dataLength) : [], newDataStateArr = getDataState(clusteredData, dataLength), state = {}; // Clear global array before populate with new ids. oldPointsStateId = []; // Build points state structure. clusteredData.clusters.forEach(function (cluster) { state[cluster.stateId] = { x: cluster.x, y: cluster.y, id: cluster.stateId, point: cluster.point, parentsId: [] }; }); clusteredData.noise.forEach(function (noise) { state[noise.stateId] = { x: noise.x, y: noise.y, id: noise.stateId, point: noise.point, parentsId: [] }; }); var newState, oldState; // Bind new and old state. for (var i = 0; i < newDataStateArr.length; i++) { newState = newDataStateArr[i]; oldState = oldDataStateArr[i]; if (newState && oldState && newState.parentStateId && oldState.parentStateId && state[newState.parentStateId] && state[newState.parentStateId].parentsId.indexOf(oldState.parentStateId) === -1) { state[newState.parentStateId].parentsId.push(oldState.parentStateId); if (oldPointsStateId.indexOf(oldState.parentStateId) === -1) { oldPointsStateId.push(oldState.parentStateId); } } } return state; } /** @private */ function seriesGetRealExtremes() { var chart = this.chart, x = chart.mapView ? 0 : chart.plotLeft, y = chart.mapView ? 0 : chart.plotTop, p1 = pixelsToValues(this, { x: x, y: y }), p2 = pixelsToValues(this, { x: x + chart.plotWidth, y: x + chart.plotHeight }), realMinX = p1.x, realMaxX = p2.x, realMinY = p1.y, realMaxY = p2.y; return { minX: Math.min(realMinX, realMaxX), maxX: Math.max(realMinX, realMaxX), minY: Math.min(realMinY, realMaxY), maxY: Math.max(realMinY, realMaxY) }; } /** @private */ function seriesGetScaledGridSize(options) { var series = this, xAxis = series.xAxis, mapView = this.chart.mapView, processedGridSize = options.processedGridSize || clusterDefaults.layoutAlgorithm.gridSize; var search = true, k = 1, divider = 1; if (!series.gridValueSize) { if (mapView) { series.gridValueSize = processedGridSize / mapView.getScale(); } else { series.gridValueSize = Math.abs(xAxis.toValue(processedGridSize) - xAxis.toValue(0)); } } var gridSize = mapView ? series.gridValueSize * mapView.getScale() : xAxis.toPixels(series.gridValueSize) - xAxis.toPixels(0); var scale = +(processedGridSize / gridSize).toFixed(14); // Find the level and its divider. while (search && scale !== 1) { var level = Math.pow(2, k); if (scale > 0.75 && scale < 1.25) { search = false; } else if (scale >= (1 / level) && scale < 2 * (1 / level)) { search = false; divider = level; } else if (scale <= level && scale > level / 2) { search = false; divider = 1 / level; } k++; } return (processedGridSize / divider) / scale; } /** * Hide clustered data points. * @private */ function seriesHideClusteredData() { var series = this, clusteredSeriesData = this.markerClusterSeriesData, oldState = ((series.markerClusterInfo || {}).pointsState || {}).oldState || {}, oldPointsId = oldPointsStateId.map(function (elem) { return (oldState[elem].point || {}).id || ''; }); (clusteredSeriesData || []).forEach(function (point) { // If an old point is used in animation hide it, otherwise destroy. if (point && oldPointsId.indexOf(point.id) !== -1) { if (point.graphic) { point.graphic.hide(); } if (point.dataLabel) { point.dataLabel.hide(); } } else { if (point && point.destroy) { point.destroy(); } } }); } /** * Check if user algorithm result is valid groupedDataObject. * @private */ function seriesIsValidGroupedDataObject(groupedData) { var result = false, i; if (!isObject(groupedData)) { return false; } objectEach(groupedData, function (elem) { result = true; if (!isArray(elem) || !elem.length) { result = false; return; } for (i = 0; i < elem.length; i++) { if (!isObject(elem[i]) || (!elem[i].x || !elem[i].y)) { result = false; return; } } }); return result; } /** @private */ function seriesPreventClusterCollisions(props) { var _a; var series = this, _b = props.key.split('-').map(parseFloat), gridY = _b[0], gridX = _b[1], gridSize = props.gridSize, groupedData = props.groupedData, defaultRadius = props.defaultRadius, clusterRadius = props.clusterRadius, gridXPx = gridX * gridSize, gridYPx = gridY * gridSize, propsPx = valuesToPixels(series, props), gridsToCheckCollision = [], clusterMarkerOptions = (series.options.cluster || {}).marker, zoneOptions = (series.options.cluster || {}).zones, gridOffset = series.getGridOffset(); var xPixel = propsPx.x, yPixel = propsPx.y, pointsLen = 0, radius = 0, nextXPixel, nextYPixel, signX, signY, cornerGridX, cornerGridY, i, j, itemX, itemY, nextClusterPos, maxDist, keys; // Distance to the grid start. xPixel -= gridOffset.plotLeft; yPixel -= gridOffset.plotTop; for (i = 1; i < 5; i++) { signX = i % 2 ? -1 : 1; signY = i < 3 ? -1 : 1; cornerGridX = Math.floor((xPixel + signX * clusterRadius) / gridSize); cornerGridY = Math.floor((yPixel + signY * clusterRadius) / gridSize); keys = [ cornerGridY + '-' + cornerGridX, cornerGridY + '-' + gridX, gridY + '-' + cornerGridX ]; for (j = 0; j < keys.length; j++) { if (gridsToCheckCollision.indexOf(keys[j]) === -1 && keys[j] !== props.key) { gridsToCheckCollision.push(keys[j]); } } } for (var _i = 0, gridsToCheckCollision_1 = gridsToCheckCollision; _i < gridsToCheckCollision_1.length; _i++) { var item = gridsToCheckCollision_1[_i]; if (groupedData[item]) { // Cluster or noise position is already computed. if (!groupedData[item].posX) { nextClusterPos = getClusterPosition(groupedData[item]); groupedData[item].posX = nextClusterPos.x; groupedData[item].posY = nextClusterPos.y; } var pos_1 = valuesToPixels(series, { x: groupedData[item].posX || 0, y: groupedData[item].posY || 0 }); nextXPixel = pos_1.x - gridOffset.plotLeft; nextYPixel = pos_1.y - gridOffset.plotTop; _a = item.split('-').map(parseFloat), itemY = _a[0], itemX = _a[1]; if (zoneOptions) { pointsLen = groupedData[item].length; for (i = 0; i < zoneOptions.length; i++) { if (pointsLen >= zoneOptions[i].from && pointsLen <= zoneOptions[i].to) { if (defined((zoneOptions[i].marker || {}).radius)) { radius = zoneOptions[i].marker.radius || 0; } else if (clusterMarkerOptions && clusterMarkerOptions.radius) { radius = clusterMarkerOptions.radius; } else { radius = clusterDefaults.marker.radius; } } } } if (groupedData[item].length > 1 && radius === 0 && clusterMarkerOptions && clusterMarkerOptions.radius) { radius = clusterMarkerOptions.radius; } else if (groupedData[item].length === 1) { radius = defaultRadius; } maxDist = clusterRadius + radius; radius = 0; if (itemX !== gridX && Math.abs(xPixel - nextXPixel) < maxDist) { xPixel = itemX - gridX < 0 ? gridXPx + clusterRadius : gridXPx + gridSize - clusterRadius; } if (itemY !== gridY && Math.abs(yPixel - nextYPixel) < maxDist) { yPixel = itemY - gridY < 0 ? gridYPx + clusterRadius : gridYPx + gridSize - clusterRadius; } } } var pos = pixelsToValues(series, { x: xPixel + gridOffset.plotLeft, y: yPixel + gridOffset.plotTop }); groupedData[props.key].posX = pos.x; groupedData[props.key].posY = pos.y; return pos; } /** * Util function. * @private */ function valuesToPixels(series, pos) { var chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis; if (chart.mapView) { return chart.mapView.projectedUnitsToPixels(pos); } return { x: xAxis ? xAxis.toPixels(pos.x) : 0, y: yAxis ? yAxis.toPixels(pos.y) : 0 }; } /* * * * Default Export * * */ var MarkerClusterScatter = { compose: compose }; return MarkerClusterScatter; }); _registerModule(_modules, 'Extensions/MarkerClusters/MarkerClusters.js', [_modules['Core/Animation/AnimationUtilities.js'], _modules['Core/Defaults.js'], _modules['Extensions/MarkerClusters/MarkerClusterDefaults.js'], _modules['Extensions/MarkerClusters/MarkerClusterScatter.js'], _modules['Core/Utilities.js']], function (A, D, MarkerClusterDefaults, MarkerClusterScatter, U) { /* * * * Marker clusters module. * * (c) 2010-2021 Torstein Honsi * * Author: Wojciech Chmiel * * License: www.highcharts.com/license * * !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!! * * */ var animObject = A.animObject; var defaultOptions = D.defaultOptions; var addEvent = U.addEvent, defined = U.defined, error = U.error, isFunction = U.isFunction, merge = U.merge, pushUnique = U.pushUnique, syncTimeout = U.syncTimeout; /* * * * Constants * * */ var composedMembers = []; (defaultOptions.plotOptions || {}).series = merge((defaultOptions.plotOptions || {}).series, MarkerClusterDefaults); /* * * * Functions * * */ /** @private */ function compose(AxisClass, ChartClass, highchartsDefaultOptions, SeriesClass) { var PointClass = SeriesClass.prototype.pointClass; if (pushUnique(composedMembers, AxisClass)) { addEvent(AxisClass, 'setExtremes', onAxisSetExtremes); } if (pushUnique(composedMembers, ChartClass)) { addEvent(ChartClass, 'render', onChartRender); } if (pushUnique(composedMembers, PointClass)) { addEvent(PointClass, 'drillToCluster', onPointDrillToCluster); addEvent(PointClass, 'update', onPointUpdate); } if (pushUnique(composedMembers, SeriesClass)) { addEvent(SeriesClass, 'afterRender', onSeriesAfterRender); } var ScatterSeries = SeriesClass.types.scatter; if (ScatterSeries) { MarkerClusterScatter.compose(highchartsDefaultOptions, ScatterSeries); } } /** * Destroy the old tooltip after zoom. * @private */ function onAxisSetExtremes() { var chart = this.chart; var animationDuration = 0; for (var _i = 0, _a = chart.series; _i < _a.length; _i++) { var series = _a[_i]; if (series.markerClusterInfo) { animationDuration = (animObject((series.options.cluster || {}).animation).duration || 0); } } syncTimeout(function () { if (chart.tooltip) { chart.tooltip.destroy(); } }, animationDuration); } /** * Handle animation. * @private */ function onChartRender() { var chart = this; for (var _i = 0, _a = (chart.series || []); _i < _a.length; _i++) { var series = _a[_i]; if (series.markerClusterInfo) { var options = series.options.cluster, pointsState = (series.markerClusterInfo || {}).pointsState, oldState = (pointsState || {}).oldState; if ((options || {}).animation && series.markerClusterInfo && series.chart.pointer.pinchDown.length === 0 && ((series.xAxis || {}).eventArgs || {}).trigger !== 'pan' && oldState && Object.keys(oldState).length) { for (var _b = 0, _c = series.markerClusterInfo.clusters; _b < _c.length; _b++) { var cluster = _c[_b]; series.animateClusterPoint(cluster); } for (var _d = 0, _e = series.markerClusterInfo.noise; _d < _e.length; _d++) { var noise = _e[_d]; series.animateClusterPoint(noise); } } } } } /** @private */ function onPointDrillToCluster(event) { var point = event.point || event.target, series = point.series, clusterOptions = series.options.cluster, onDrillToCluster = ((clusterOptions || {}).events || {}).drillToCluster; if (isFunction(onDrillToCluster)) { onDrillToCluster.call(this, event); } } /** * Override point prototype to throw a warning when trying to update * clustered point. * @private */ function onPointUpdate() { var point = this; if (point.dataGroup) { error('Highcharts marker-clusters module: ' + 'Running `Point.update` when point belongs to clustered series' + ' is not supported.', false, point.series.chart); return false; } } /** * Add classes, change mouse cursor. * @private */ function onSeriesAfterRender() { var series = this, clusterZoomEnabled = (series.options.cluster || {}).drillToCluster; if (series.markerClusterInfo && series.markerClusterInfo.clusters) { for (var _i = 0, _a = series.markerClusterInfo.clusters; _i < _a.length; _i++) { var cluster = _a[_i]; if (cluster.point && cluster.point.graphic) { cluster.point.graphic.addClass('highcharts-cluster-point'); // Change cursor to pointer when drillToCluster is enabled. if (clusterZoomEnabled && cluster.point) { cluster.point.graphic.css({ cursor: 'pointer' }); if (cluster.point.dataLabel) { cluster.point.dataLabel.css({ cursor: 'pointer' }); } } if (defined(cluster.clusterZone)) { cluster.point.graphic.addClass(cluster.clusterZoneClassName || 'highcharts-cluster-zone-' + cluster.clusterZone.zoneIndex); } } } } } /* * * * Default Export * * */ var MarkerClusters = { compose: compose }; /* * * * API Options * * */ /** * Function callback when a cluster is clicked. * * @callback Highcharts.MarkerClusterDrillCallbackFunction * * @param {Highcharts.Point} this * The point where the event occured. * * @param {Highcharts.PointClickEventObject} event * Event arguments. */ ''; // keeps doclets above in JS file return MarkerClusters; }); _registerModule(_modules, 'Extensions/MarkerClusters/MarkerClusterSymbols.js', [_modules['Core/Utilities.js']], function (U) { /* * * * Marker clusters module. * * (c) 2010-2021 Torstein Honsi * * Author: Wojciech Chmiel * * License: www.highcharts.com/license * * !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!! * * */ var pushUnique = U.pushUnique; /* * * * Constants * * */ var modifiedMembers = []; /* * * * Variables * * */ var symbols; /* * * * Functions * * */ /** * Cluster symbol. * @private */ function cluster(x, y, width, height) { var w = width / 2, h = height / 2, outerWidth = 1, space = 1, inner = symbols.arc(x + w, y + h, w - space * 4, h - space * 4, { start: Math.PI * 0.5, end: Math.PI * 2.5, open: false }), outer1 = symbols.arc(x + w, y + h, w - space * 3, h - space * 3, { start: Math.PI * 0.5, end: Math.PI * 2.5, innerR: w - outerWidth * 2, open: false }), outer2 = symbols.arc(x + w, y + h, w - space, h - space, { start: Math.PI * 0.5, end: Math.PI * 2.5, innerR: w, open: false }); return outer2.concat(outer1, inner); } /** * @private */ function compose(SVGRendererClass) { if (pushUnique(modifiedMembers, SVGRendererClass)) { symbols = SVGRendererClass.prototype.symbols; symbols.cluster = cluster; } } /* * * * Default Export * * */ var MarkerClusterSymbols = { compose: compose }; return MarkerClusterSymbols; }); _registerModule(_modules, 'masters/modules/marker-clusters.src.js', [_modules['Core/Globals.js'], _modules['Extensions/MarkerClusters/MarkerClusters.js'], _modules['Extensions/MarkerClusters/MarkerClusterSymbols.js']], function (Highcharts, MarkerClusters, MarkerClusterSymbols) { var G = Highcharts; MarkerClusters.compose(G.Axis, G.Chart, G.defaultOptions, G.Series); MarkerClusterSymbols.compose(G.SVGRenderer); }); }));