forked from qwerty/tupali
1553 lines
76 KiB
JavaScript
1553 lines
76 KiB
JavaScript
/**
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* @license Highcharts JS v8.1.0 (2020-05-05)
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*
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* Marker clusters module for Highcharts
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*
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* (c) 2010-2019 Wojciech Chmiel
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*
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* License: www.highcharts.com/license
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*/
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'use strict';
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(function (factory) {
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if (typeof module === 'object' && module.exports) {
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factory['default'] = factory;
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module.exports = factory;
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} else if (typeof define === 'function' && define.amd) {
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define('highcharts/modules/marker-clusters', ['highcharts'], function (Highcharts) {
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factory(Highcharts);
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factory.Highcharts = Highcharts;
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return factory;
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});
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} else {
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factory(typeof Highcharts !== 'undefined' ? Highcharts : undefined);
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}
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}(function (Highcharts) {
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var _modules = Highcharts ? Highcharts._modules : {};
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function _registerModule(obj, path, args, fn) {
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if (!obj.hasOwnProperty(path)) {
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obj[path] = fn.apply(null, args);
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}
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}
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_registerModule(_modules, 'modules/marker-clusters.src.js', [_modules['parts/Globals.js'], _modules['parts/Point.js'], _modules['parts/Utilities.js']], function (H, Point, U) {
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/* *
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*
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* Marker clusters module.
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*
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* (c) 2010-2020 Torstein Honsi
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*
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* Author: Wojciech Chmiel
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*
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* License: www.highcharts.com/license
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*
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* !!!!!!! SOURCE GETS TRANSPILED BY TYPESCRIPT. EDIT TS FILE ONLY. !!!!!!!
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*
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* */
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var __read = (this && this.__read) || function (o, n) {
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var m = typeof Symbol === "function" && o[Symbol.iterator];
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if (!m) return o;
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var i = m.call(o), r, ar = [], e;
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try {
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while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);
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}
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catch (error) { e = { error: error }; }
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finally {
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try {
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if (r && !r.done && (m = i["return"])) m.call(i);
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}
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finally { if (e) throw e.error; }
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}
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return ar;
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};
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/**
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* Function callback when a cluster is clicked.
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*
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* @callback Highcharts.MarkerClusterDrillCallbackFunction
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*
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* @param {Highcharts.Point} this
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* The point where the event occured.
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*
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* @param {Highcharts.PointClickEventObject} event
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* Event arguments.
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*/
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''; // detach doclets from following code
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var addEvent = U.addEvent, animObject = U.animObject, defined = U.defined, error = U.error, isArray = U.isArray, isFunction = U.isFunction, isObject = U.isObject, isNumber = U.isNumber, merge = U.merge, objectEach = U.objectEach, relativeLength = U.relativeLength, syncTimeout = U.syncTimeout;
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/* eslint-disable no-invalid-this */
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var Series = H.Series, Scatter = H.seriesTypes.scatter, SvgRenderer = H.SVGRenderer, baseGeneratePoints = Series.prototype.generatePoints, stateIdCounter = 0,
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// Points that ids are included in the oldPointsStateId array
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// are hidden before animation. Other ones are destroyed.
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oldPointsStateId = [];
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/**
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* Options for marker clusters, the concept of sampling the data
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* values into larger blocks in order to ease readability and
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* increase performance of the JavaScript charts.
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*
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* Note: marker clusters module is not working with `boost`
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* and `draggable-points` modules.
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*
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* The marker clusters feature requires the marker-clusters.js
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* file to be loaded, found in the modules directory of the download
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* package, or online at [code.highcharts.com/modules/marker-clusters.js
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* ](code.highcharts.com/modules/marker-clusters.js).
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*
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* @sample maps/marker-clusters/europe
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* Maps marker clusters
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* @sample highcharts/marker-clusters/basic
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* Scatter marker clusters
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* @sample maps/marker-clusters/optimized-kmeans
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* Marker clusters with colorAxis
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*
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* @product highcharts highmaps
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* @since 8.0.0
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* @optionparent plotOptions.scatter.cluster
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*
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* @private
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*/
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var clusterDefaultOptions = {
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/**
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* Whether to enable the marker-clusters module.
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*
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* @sample maps/marker-clusters/basic
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* Maps marker clusters
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* @sample highcharts/marker-clusters/basic
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* Scatter marker clusters
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*/
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enabled: false,
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/**
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* When set to `false` prevent cluster overlapping - this option
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* works only when `layoutAlgorithm.type = "grid"`.
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*
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* @sample highcharts/marker-clusters/grid
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* Prevent overlapping
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*/
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allowOverlap: true,
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/**
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* Options for the cluster marker animation.
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* @type {boolean|Highcharts.AnimationOptionsObject}
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* @default { "duration": 500 }
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*/
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animation: {
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/** @ignore-option */
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duration: 500
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},
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/**
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* Zoom the plot area to the cluster points range when a cluster is clicked.
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*/
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drillToCluster: true,
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/**
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* The minimum amount of points to be combined into a cluster.
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* This value has to be greater or equal to 2.
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*
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* @sample highcharts/marker-clusters/basic
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* At least three points in the cluster
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*/
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minimumClusterSize: 2,
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/**
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* Options for layout algorithm. Inside there
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* are options to change the type of the algorithm, gridSize,
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* distance or iterations.
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*/
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layoutAlgorithm: {
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/**
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* Type of the algorithm used to combine points into a cluster.
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* There are three available algorithms:
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*
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* 1) `grid` - grid-based clustering technique. Points are assigned
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* to squares of set size depending on their position on the plot
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* area. Points inside the grid square are combined into a cluster.
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* The grid size can be controlled by `gridSize` property
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* (grid size changes at certain zoom levels).
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*
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* 2) `kmeans` - based on K-Means clustering technique. In the
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* first step, points are divided using the grid method (distance
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* property is a grid size) to find the initial amount of clusters.
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* Next, each point is classified by computing the distance between
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* each cluster center and that point. When the closest cluster
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* distance is lower than distance property set by a user the point
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* is added to this cluster otherwise is classified as `noise`. The
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* algorithm is repeated until each cluster center not change its
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* previous position more than one pixel. This technique is more
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* accurate but also more time consuming than the `grid` algorithm,
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* especially for big datasets.
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*
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* 3) `optimizedKmeans` - based on K-Means clustering technique. This
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* algorithm uses k-means algorithm only on the chart initialization
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* or when chart extremes have greater range than on initialization.
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* When a chart is redrawn the algorithm checks only clustered points
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* distance from the cluster center and rebuild it when the point is
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* spaced enough to be outside the cluster. It provides performance
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* improvement and more stable clusters position yet can be used rather
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* on small and sparse datasets.
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*
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* By default, the algorithm depends on visible quantity of points
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* and `kmeansThreshold`. When there are more visible points than the
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* `kmeansThreshold` the `grid` algorithm is used, otherwise `kmeans`.
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*
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* The custom clustering algorithm can be added by assigning a callback
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* function as the type property. This function takes an array of
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* `processedXData`, `processedYData`, `processedXData` indexes and
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* `layoutAlgorithm` options as arguments and should return an object
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* with grouped data.
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*
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* The algorithm should return an object like that:
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* <pre>{
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* clusterId1: [{
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* x: 573,
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* y: 285,
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* index: 1 // point index in the data array
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* }, {
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* x: 521,
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* y: 197,
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* index: 2
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* }],
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* clusterId2: [{
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* ...
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* }]
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* ...
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* }</pre>
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*
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* `clusterId` (example above - unique id of a cluster or noise)
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* is an array of points belonging to a cluster. If the
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* array has only one point or fewer points than set in
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* `cluster.minimumClusterSize` it won't be combined into a cluster.
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*
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* @sample maps/marker-clusters/optimized-kmeans
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* Optimized K-Means algorithm
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* @sample highcharts/marker-clusters/kmeans
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* K-Means algorithm
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* @sample highcharts/marker-clusters/grid
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* Grid algorithm
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* @sample maps/marker-clusters/custom-alg
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* Custom algorithm
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*
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* @type {string|Function}
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* @see [cluster.minimumClusterSize](#plotOptions.scatter.marker.cluster.minimumClusterSize)
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* @apioption plotOptions.scatter.cluster.layoutAlgorithm.type
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*/
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/**
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* When `type` is set to the `grid`,
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* `gridSize` is a size of a grid square element either as a number
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* defining pixels, or a percentage defining a percentage
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* of the plot area width.
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*
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* @type {number|string}
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*/
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gridSize: 50,
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/**
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* When `type` is set to `kmeans`,
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* `iterations` are the number of iterations that this algorithm will be
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* repeated to find clusters positions.
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*
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* @type {number}
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* @apioption plotOptions.scatter.cluster.layoutAlgorithm.iterations
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*/
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/**
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* When `type` is set to `kmeans`,
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* `distance` is a maximum distance between point and cluster center
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* so that this point will be inside the cluster. The distance
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* is either a number defining pixels or a percentage
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* defining a percentage of the plot area width.
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*
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* @type {number|string}
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*/
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distance: 40,
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/**
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* When `type` is set to `undefined` and there are more visible points
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* than the kmeansThreshold the `grid` algorithm is used to find
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* clusters, otherwise `kmeans`. It ensures good performance on
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* large datasets and better clusters arrangement after the zoom.
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*/
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kmeansThreshold: 100
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},
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/**
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* Options for the cluster marker.
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* @extends plotOptions.series.marker
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* @excluding enabledThreshold, states
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* @type {Highcharts.PointMarkerOptionsObject}
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*/
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marker: {
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/** @internal */
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symbol: 'cluster',
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/** @internal */
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radius: 15,
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/** @internal */
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lineWidth: 0,
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/** @internal */
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lineColor: '#ffffff'
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},
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/**
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* Fires when the cluster point is clicked and `drillToCluster` is enabled.
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* One parameter, `event`, is passed to the function. The default action
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* is to zoom to the cluster points range. This can be prevented
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* by calling `event.preventDefault()`.
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*
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* @type {Highcharts.MarkerClusterDrillCallbackFunction}
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* @product highcharts highmaps
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* @see [cluster.drillToCluster](#plotOptions.scatter.marker.cluster.drillToCluster)
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* @apioption plotOptions.scatter.cluster.events.drillToCluster
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*/
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/**
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* An array defining zones within marker clusters.
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*
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* In styled mode, the color zones are styled with the
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* `.highcharts-cluster-zone-{n}` class, or custom
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* classed from the `className`
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* option.
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*
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* @sample highcharts/marker-clusters/basic
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* Marker clusters zones
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* @sample maps/marker-clusters/custom-alg
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* Zones on maps
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*
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* @type {Array<*>}
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* @product highcharts highmaps
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* @apioption plotOptions.scatter.cluster.zones
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*/
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/**
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* Styled mode only. A custom class name for the zone.
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*
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* @sample highcharts/css/color-zones/
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* Zones styled by class name
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*
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* @type {string}
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* @apioption plotOptions.scatter.cluster.zones.className
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*/
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/**
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* Settings for the cluster marker belonging to the zone.
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*
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* @see [cluster.marker](#plotOptions.scatter.cluster.marker)
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* @extends plotOptions.scatter.cluster.marker
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* @product highcharts highmaps
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* @apioption plotOptions.scatter.cluster.zones.marker
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*/
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/**
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* The value where the zone starts.
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*
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* @type {number}
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* @product highcharts highmaps
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* @apioption plotOptions.scatter.cluster.zones.from
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*/
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/**
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* The value where the zone ends.
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*
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* @type {number}
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* @product highcharts highmaps
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* @apioption plotOptions.scatter.cluster.zones.to
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*/
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/**
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* The fill color of the cluster marker in hover state. When
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* `undefined`, the series' or point's fillColor for normal
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* state is used.
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*
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* @type {Highcharts.ColorType}
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* @apioption plotOptions.scatter.cluster.states.hover.fillColor
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*/
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/**
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* Options for the cluster data labels.
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* @type {Highcharts.DataLabelsOptions}
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*/
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dataLabels: {
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/** @internal */
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enabled: true,
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/** @internal */
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format: '{point.clusterPointsAmount}',
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/** @internal */
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verticalAlign: 'middle',
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/** @internal */
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align: 'center',
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/** @internal */
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style: {
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color: 'contrast'
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},
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/** @internal */
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inside: true
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}
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};
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(H.defaultOptions.plotOptions || {}).series = merge((H.defaultOptions.plotOptions || {}).series, {
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cluster: clusterDefaultOptions,
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tooltip: {
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/**
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* The HTML of the cluster point's in the tooltip. Works only with
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* marker-clusters module and analogously to
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* [pointFormat](#tooltip.pointFormat).
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*
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* The cluster tooltip can be also formatted using
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* `tooltip.formatter` callback function and `point.isCluster` flag.
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*
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* @sample highcharts/marker-clusters/grid
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* Format tooltip for cluster points.
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*
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* @sample maps/marker-clusters/europe/
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* Format tooltip for clusters using tooltip.formatter
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*
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* @apioption tooltip.clusterFormat
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*/
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clusterFormat: '<span>Clustered points: ' +
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'{point.clusterPointsAmount}</span><br/>'
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}
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});
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// Utils.
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/* eslint-disable require-jsdoc */
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function getClusterPosition(points) {
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var pointsLen = points.length, sumX = 0, sumY = 0, i;
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for (i = 0; i < pointsLen; i++) {
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sumX += points[i].x;
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sumY += points[i].y;
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}
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return {
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x: sumX / pointsLen,
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y: sumY / pointsLen
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};
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}
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// Prepare array with sorted data objects to be
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// compared in getPointsState method.
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function getDataState(clusteredData, stateDataLen) {
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var state = [];
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state.length = stateDataLen;
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clusteredData.clusters.forEach(function (cluster) {
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cluster.data.forEach(function (elem) {
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state[elem.dataIndex] = elem;
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});
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});
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clusteredData.noise.forEach(function (noise) {
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state[noise.data[0].dataIndex] = noise.data[0];
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});
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return state;
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}
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function fadeInElement(elem, opacity, animation) {
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elem
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.attr({
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opacity: opacity
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})
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.animate({
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opacity: 1
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}, animation);
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}
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function fadeInStatePoint(stateObj, opacity, animation, fadeinGraphic, fadeinDataLabel) {
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if (stateObj.point) {
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if (fadeinGraphic && stateObj.point.graphic) {
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stateObj.point.graphic.show();
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fadeInElement(stateObj.point.graphic, opacity, animation);
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}
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if (fadeinDataLabel && stateObj.point.dataLabel) {
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stateObj.point.dataLabel.show();
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fadeInElement(stateObj.point.dataLabel, opacity, animation);
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}
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}
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}
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function hideStatePoint(stateObj, hideGraphic, hideDataLabel) {
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if (stateObj.point) {
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if (hideGraphic && stateObj.point.graphic) {
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stateObj.point.graphic.hide();
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}
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if (hideDataLabel && stateObj.point.dataLabel) {
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stateObj.point.dataLabel.hide();
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}
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}
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}
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function destroyOldPoints(oldState) {
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if (oldState) {
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objectEach(oldState, function (state) {
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if (state.point && state.point.destroy) {
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state.point.destroy();
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}
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});
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}
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}
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function fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, opacity) {
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// Fade in new point.
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fadeInStatePoint(newPointObj, opacity, animation, true, true);
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// Destroy old animated points.
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oldPoints.forEach(function (p) {
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if (p.point && p.point.destroy) {
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p.point.destroy();
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}
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});
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}
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// Generate unique stateId for a state element.
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function getStateId() {
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return Math.random().toString(36).substring(2, 7) + '-' + stateIdCounter++;
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}
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|
// Useful for debugging.
|
|
// function drawGridLines(
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// series: Highcharts.Series,
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// options: Highcharts.MarkerClusterLayoutAlgorithmOptions
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// ): void {
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// var chart = series.chart,
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// xAxis = series.xAxis,
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// yAxis = series.yAxis,
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// xAxisLen = series.xAxis.len,
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// yAxisLen = series.yAxis.len,
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// i, j, elem, text,
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// currentX = 0,
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// currentY = 0,
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// scaledGridSize = 50,
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// gridX = 0,
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// gridY = 0,
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// gridOffset = series.getGridOffset(),
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// mapXSize, mapYSize;
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// if (series.debugGridLines && series.debugGridLines.length) {
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// series.debugGridLines.forEach(function (gridItem): void {
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// if (gridItem && gridItem.destroy) {
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// gridItem.destroy();
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// }
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// });
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// }
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// series.debugGridLines = [];
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// scaledGridSize = series.getScaledGridSize(options);
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// mapXSize = Math.abs(
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// xAxis.toPixels(xAxis.dataMax || 0) -
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// xAxis.toPixels(xAxis.dataMin || 0)
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// );
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// mapYSize = Math.abs(
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// yAxis.toPixels(yAxis.dataMax || 0) -
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// yAxis.toPixels(yAxis.dataMin || 0)
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// );
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// gridX = Math.ceil(mapXSize / scaledGridSize);
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// gridY = Math.ceil(mapYSize / scaledGridSize);
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// for (i = 0; i < gridX; i++) {
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// currentX = i * scaledGridSize;
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// if (
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|
// gridOffset.plotLeft + currentX >= 0 &&
|
|
// gridOffset.plotLeft + currentX < xAxisLen
|
|
// ) {
|
|
// for (j = 0; j < gridY; j++) {
|
|
// currentY = j * scaledGridSize;
|
|
// if (
|
|
// gridOffset.plotTop + currentY >= 0 &&
|
|
// gridOffset.plotTop + currentY < yAxisLen
|
|
// ) {
|
|
// if (j % 2 === 0 && i % 2 === 0) {
|
|
// var rect = chart.renderer
|
|
// .rect(
|
|
// gridOffset.plotLeft + currentX,
|
|
// gridOffset.plotTop + currentY,
|
|
// scaledGridSize * 2,
|
|
// scaledGridSize * 2
|
|
// )
|
|
// .attr({
|
|
// stroke: series.color,
|
|
// 'stroke-width': '2px'
|
|
// })
|
|
// .add()
|
|
// .toFront();
|
|
// series.debugGridLines.push(rect);
|
|
// }
|
|
// elem = chart.renderer
|
|
// .rect(
|
|
// gridOffset.plotLeft + currentX,
|
|
// gridOffset.plotTop + currentY,
|
|
// scaledGridSize,
|
|
// scaledGridSize
|
|
// )
|
|
// .attr({
|
|
// stroke: series.color,
|
|
// opacity: 0.3,
|
|
// 'stroke-width': '1px'
|
|
// })
|
|
// .add()
|
|
// .toFront();
|
|
// text = chart.renderer
|
|
// .text(
|
|
// j + '-' + i,
|
|
// gridOffset.plotLeft + currentX + 2,
|
|
// gridOffset.plotTop + currentY + 7
|
|
// )
|
|
// .css({
|
|
// fill: 'rgba(0, 0, 0, 0.7)',
|
|
// fontSize: '7px'
|
|
// })
|
|
// .add()
|
|
// .toFront();
|
|
// series.debugGridLines.push(elem);
|
|
// series.debugGridLines.push(text);
|
|
// }
|
|
// }
|
|
// }
|
|
// }
|
|
// }
|
|
/* eslint-enable require-jsdoc */
|
|
// Cluster symbol.
|
|
SvgRenderer.prototype.symbols.cluster = function (x, y, width, height) {
|
|
var w = width / 2, h = height / 2, outerWidth = 1, space = 1, inner, outer1, outer2;
|
|
inner = this.arc(x + w, y + h, w - space * 4, h - space * 4, {
|
|
start: Math.PI * 0.5,
|
|
end: Math.PI * 2.5,
|
|
open: false
|
|
});
|
|
outer1 = this.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 = this.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);
|
|
};
|
|
Scatter.prototype.animateClusterPoint = function (clusterObj) {
|
|
var series = this, xAxis = series.xAxis, yAxis = series.yAxis, chart = series.chart, clusterOptions = series.options.cluster, animation = animObject((clusterOptions || {}).animation), animDuration = animation.duration || 500, pointsState = (series.markerClusterInfo || {}).pointsState, newState = (pointsState || {}).newState, oldState = (pointsState || {}).oldState, parentId, oldPointObj, newPointObj, oldPoints = [], newPointBBox, offset = 0, newX = 0, newY = 0, isOldPointGrahic = false, isCbHandled = false;
|
|
if (oldState && newState) {
|
|
newPointObj = newState[clusterObj.stateId];
|
|
newX = xAxis.toPixels(newPointObj.x) - chart.plotLeft;
|
|
newY = yAxis.toPixels(newPointObj.y) - 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();
|
|
offset = 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,
|
|
y: newY - newPointObj.point.graphic.radius
|
|
}, 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,
|
|
y: newY - oldPointObj.point.graphic.radius,
|
|
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);
|
|
}
|
|
}
|
|
}
|
|
};
|
|
Scatter.prototype.getGridOffset = function () {
|
|
var series = this, chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis, plotLeft = 0, plotTop = 0;
|
|
if (series.dataMinX && series.dataMaxX) {
|
|
plotLeft = xAxis.reversed ?
|
|
xAxis.toPixels(series.dataMaxX) : xAxis.toPixels(series.dataMinX);
|
|
}
|
|
else {
|
|
plotLeft = chart.plotLeft;
|
|
}
|
|
if (series.dataMinY && series.dataMaxY) {
|
|
plotTop = yAxis.reversed ?
|
|
yAxis.toPixels(series.dataMinY) : yAxis.toPixels(series.dataMaxY);
|
|
}
|
|
else {
|
|
plotTop = chart.plotTop;
|
|
}
|
|
return { plotLeft: plotLeft, plotTop: plotTop };
|
|
};
|
|
Scatter.prototype.getScaledGridSize = function (options) {
|
|
var series = this, xAxis = series.xAxis, search = true, k = 1, divider = 1, processedGridSize = options.processedGridSize ||
|
|
clusterDefaultOptions.layoutAlgorithm.gridSize, gridSize, scale, level;
|
|
if (!series.gridValueSize) {
|
|
series.gridValueSize = Math.abs(xAxis.toValue(processedGridSize) - xAxis.toValue(0));
|
|
}
|
|
gridSize = xAxis.toPixels(series.gridValueSize) - xAxis.toPixels(0);
|
|
scale = +(processedGridSize / gridSize).toFixed(14);
|
|
// Find the level and its divider.
|
|
while (search && scale !== 1) {
|
|
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;
|
|
};
|
|
Scatter.prototype.getRealExtremes = function () {
|
|
var _a, _b;
|
|
var series = this, chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis, realMinX = xAxis ? xAxis.toValue(chart.plotLeft) : 0, realMaxX = xAxis ?
|
|
xAxis.toValue(chart.plotLeft + chart.plotWidth) : 0, realMinY = yAxis ? yAxis.toValue(chart.plotTop) : 0, realMaxY = yAxis ?
|
|
yAxis.toValue(chart.plotTop + chart.plotHeight) : 0;
|
|
if (realMinX > realMaxX) {
|
|
_a = __read([realMinX, realMaxX], 2), realMaxX = _a[0], realMinX = _a[1];
|
|
}
|
|
if (realMinY > realMaxY) {
|
|
_b = __read([realMinY, realMaxY], 2), realMaxY = _b[0], realMinY = _b[1];
|
|
}
|
|
return {
|
|
minX: realMinX,
|
|
maxX: realMaxX,
|
|
minY: realMinY,
|
|
maxY: realMaxY
|
|
};
|
|
};
|
|
Scatter.prototype.onDrillToCluster = function (event) {
|
|
var point = event.point || event.target;
|
|
point.firePointEvent('drillToCluster', event, function (e) {
|
|
var _a, _b;
|
|
var point = e.point || e.target, series = point.series, xAxis = point.series.xAxis, yAxis = point.series.yAxis, chart = point.series.chart, clusterOptions = series.options.cluster, drillToCluster = (clusterOptions || {}).drillToCluster, offsetX, offsetY, sortedDataX, sortedDataY, minX, minY, maxX, maxY;
|
|
if (drillToCluster && point.clusteredData) {
|
|
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);
|
|
chart.pointer.zoomX = true;
|
|
chart.pointer.zoomY = true;
|
|
// Swap when minus values.
|
|
if (minX > maxX) {
|
|
_a = __read([maxX, minX], 2), minX = _a[0], maxX = _a[1];
|
|
}
|
|
if (minY > maxY) {
|
|
_b = __read([maxY, minY], 2), minY = _b[0], maxY = _b[1];
|
|
}
|
|
chart.zoom({
|
|
originalEvent: e,
|
|
xAxis: [{
|
|
axis: xAxis,
|
|
min: minX - offsetX,
|
|
max: maxX + offsetX
|
|
}],
|
|
yAxis: [{
|
|
axis: yAxis,
|
|
min: minY - offsetY,
|
|
max: maxY + offsetY
|
|
}]
|
|
});
|
|
}
|
|
});
|
|
};
|
|
Scatter.prototype.getClusterDistancesFromPoint = function (clusters, pointX, pointY) {
|
|
var series = this, xAxis = series.xAxis, yAxis = series.yAxis, pointClusterDistance = [], j, distance;
|
|
for (j = 0; j < clusters.length; j++) {
|
|
distance = Math.sqrt(Math.pow(xAxis.toPixels(pointX) -
|
|
xAxis.toPixels(clusters[j].posX), 2) +
|
|
Math.pow(yAxis.toPixels(pointY) -
|
|
yAxis.toPixels(clusters[j].posY), 2));
|
|
pointClusterDistance.push({
|
|
clusterIndex: j,
|
|
distance: distance
|
|
});
|
|
}
|
|
return pointClusterDistance.sort(function (a, b) { return a.distance - b.distance; });
|
|
};
|
|
// Point state used when animation is enabled to compare
|
|
// and bind old points with new ones.
|
|
Scatter.prototype.getPointsState = function (clusteredData, oldMarkerClusterInfo, dataLength) {
|
|
var oldDataStateArr = oldMarkerClusterInfo ?
|
|
getDataState(oldMarkerClusterInfo, dataLength) : [], newDataStateArr = getDataState(clusteredData, dataLength), state = {}, newState, oldState, i;
|
|
// 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: []
|
|
};
|
|
});
|
|
// Bind new and old state.
|
|
for (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;
|
|
};
|
|
Scatter.prototype.markerClusterAlgorithms = {
|
|
grid: function (dataX, dataY, dataIndexes, options) {
|
|
var series = this, xAxis = series.xAxis, yAxis = series.yAxis, grid = {}, gridOffset = series.getGridOffset(), scaledGridSize, x, y, gridX, gridY, key, i;
|
|
// drawGridLines(series, options);
|
|
scaledGridSize = series.getScaledGridSize(options);
|
|
for (i = 0; i < dataX.length; i++) {
|
|
x = xAxis.toPixels(dataX[i]) - gridOffset.plotLeft;
|
|
y = yAxis.toPixels(dataY[i]) - 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 ||
|
|
clusterDefaultOptions.layoutAlgorithm.distance, iterations = options.iterations,
|
|
// Max pixel difference beetwen new and old cluster position.
|
|
maxClusterShift = 1, currentIteration = 0, repeat = true, pointX = 0, pointY = 0, tempPos, pointClusterDistance = [], groupedData, key, i, j;
|
|
options.processedGridSize = options.processedDistance;
|
|
// Use grid method to get groupedData object.
|
|
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 (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) {
|
|
clusters.map(function (c) {
|
|
c.points.length = 0;
|
|
return c;
|
|
});
|
|
noise.length = 0;
|
|
for (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 (j = 0; j < clusters.length; j++) {
|
|
if (clusters[j].points.length === 1) {
|
|
pointClusterDistance = series.getClusterDistancesFromPoint(clusters, clusters[j].points[0].x, clusters[j].points[0].y);
|
|
if (pointClusterDistance[1].distance < pointMaxDistance) {
|
|
// Add point to the next closest cluster.
|
|
clusters[pointClusterDistance[1].clusterIndex].points
|
|
.push(clusters[j].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 (j = 0; j < clusters.length; j++) {
|
|
tempPos = getClusterPosition(clusters[j].points);
|
|
clusters[j].oldX = clusters[j].posX;
|
|
clusters[j].oldY = clusters[j].posY;
|
|
clusters[j].posX = tempPos.x;
|
|
clusters[j].posY = tempPos.y;
|
|
// Repeat the algorithm if at least one cluster
|
|
// is shifted more than maxClusterShift property.
|
|
if (clusters[j].posX > clusters[j].oldX + maxClusterShift ||
|
|
clusters[j].posX < clusters[j].oldX - maxClusterShift ||
|
|
clusters[j].posY > clusters[j].oldY + maxClusterShift ||
|
|
clusters[j].posY < clusters[j].oldY - maxClusterShift) {
|
|
repeat = true;
|
|
}
|
|
}
|
|
// If iterations property is set repeat the algorithm
|
|
// specified amount of times.
|
|
if (iterations) {
|
|
repeat = currentIteration < iterations - 1;
|
|
}
|
|
currentIteration++;
|
|
}
|
|
clusters.forEach(function (cluster, i) {
|
|
group['cluster' + i] = cluster.points;
|
|
});
|
|
noise.forEach(function (noise, i) {
|
|
group['noise' + i] = [noise];
|
|
});
|
|
return group;
|
|
},
|
|
optimizedKmeans: function (processedXData, processedYData, dataIndexes, options) {
|
|
var series = this, xAxis = series.xAxis, yAxis = series.yAxis, pointMaxDistance = options.processedDistance ||
|
|
clusterDefaultOptions.layoutAlgorithm.gridSize, group = {}, extremes = series.getRealExtremes(), clusterMarkerOptions = (series.options.cluster || {}).marker, offset, distance, 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
|
|
};
|
|
}
|
|
series.baseClusters.clusters.forEach(function (cluster) {
|
|
cluster.pointsOutside = [];
|
|
cluster.pointsInside = [];
|
|
cluster.data.forEach(function (dataPoint) {
|
|
distance = Math.sqrt(Math.pow(xAxis.toPixels(dataPoint.x) -
|
|
xAxis.toPixels(cluster.x), 2) +
|
|
Math.pow(yAxis.toPixels(dataPoint.y) -
|
|
yAxis.toPixels(cluster.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 = clusterDefaultOptions.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;
|
|
}
|
|
cluster.pointsOutside.forEach(function (p, i) {
|
|
group[cluster.id + '_noise' + i] = [p];
|
|
});
|
|
});
|
|
series.baseClusters.noise.forEach(function (noise) {
|
|
group[noise.id] = noise.data;
|
|
});
|
|
}
|
|
return group;
|
|
}
|
|
};
|
|
Scatter.prototype.preventClusterCollisions = function (props) {
|
|
var series = this, xAxis = series.xAxis, yAxis = series.yAxis, _a = __read(props.key.split('-').map(parseFloat), 2), gridY = _a[0], gridX = _a[1], gridSize = props.gridSize, groupedData = props.groupedData, defaultRadius = props.defaultRadius, clusterRadius = props.clusterRadius, gridXPx = gridX * gridSize, gridYPx = gridY * gridSize, xPixel = xAxis.toPixels(props.x), yPixel = yAxis.toPixels(props.y), gridsToCheckCollision = [], pointsLen = 0, radius = 0, clusterMarkerOptions = (series.options.cluster || {}).marker, zoneOptions = (series.options.cluster || {}).zones, gridOffset = series.getGridOffset(), nextXPixel, nextYPixel, signX, signY, cornerGridX, cornerGridY, i, j, itemX, itemY, nextClusterPos, maxDist, keys, x, y;
|
|
// 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]);
|
|
}
|
|
}
|
|
}
|
|
gridsToCheckCollision.forEach(function (item) {
|
|
var _a;
|
|
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;
|
|
}
|
|
nextXPixel = xAxis.toPixels(groupedData[item].posX || 0) -
|
|
gridOffset.plotLeft;
|
|
nextYPixel = yAxis.toPixels(groupedData[item].posY || 0) -
|
|
gridOffset.plotTop;
|
|
_a = __read(item.split('-').map(parseFloat), 2), 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 = clusterDefaultOptions.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;
|
|
}
|
|
}
|
|
});
|
|
x = xAxis.toValue(xPixel + gridOffset.plotLeft);
|
|
y = yAxis.toValue(yPixel + gridOffset.plotTop);
|
|
groupedData[props.key].posX = x;
|
|
groupedData[props.key].posY = y;
|
|
return { x: x, y: y };
|
|
};
|
|
// Check if user algorithm result is valid groupedDataObject.
|
|
Scatter.prototype.isValidGroupedDataObject = function (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;
|
|
};
|
|
Scatter.prototype.getClusteredData = function (groupedData, options) {
|
|
var series = this, groupedXData = [], groupedYData = [], clusters = [], // Container for clusters.
|
|
noise = [], // Container for points not belonging to any cluster.
|
|
groupMap = [], index = 0,
|
|
// Prevent minimumClusterSize lower than 2.
|
|
minimumClusterSize = Math.max(2, options.minimumClusterSize || 2), 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 ||
|
|
clusterDefaultOptions.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
|
|
};
|
|
};
|
|
// Destroy clustered data points.
|
|
Scatter.prototype.destroyClusteredData = function () {
|
|
var clusteredSeriesData = this.markerClusterSeriesData;
|
|
// Clear previous groups.
|
|
(clusteredSeriesData || []).forEach(function (point) {
|
|
if (point && point.destroy) {
|
|
point.destroy();
|
|
}
|
|
});
|
|
this.markerClusterSeriesData = null;
|
|
};
|
|
// Hide clustered data points.
|
|
Scatter.prototype.hideClusteredData = function () {
|
|
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();
|
|
}
|
|
}
|
|
});
|
|
};
|
|
// Override the generatePoints method by adding a reference to grouped data.
|
|
Scatter.prototype.generatePoints = function () {
|
|
var series = this, chart = series.chart, xAxis = series.xAxis, yAxis = series.yAxis, clusterOptions = series.options.cluster, realExtremes = series.getRealExtremes(), visibleXData = [], visibleYData = [], visibleDataIndexes = [], oldPointsState, oldDataLen, oldMarkerClusterInfo, kmeansThreshold, cropDataOffsetX, cropDataOffsetY, seriesMinX, seriesMaxX, seriesMinY, seriesMaxY, type, algorithm, clusteredData, groupedData, layoutAlgOptions, point, i;
|
|
if (clusterOptions &&
|
|
clusterOptions.enabled &&
|
|
series.xData &&
|
|
series.yData &&
|
|
!chart.polar) {
|
|
type = clusterOptions.layoutAlgorithm.type;
|
|
layoutAlgOptions = clusterOptions.layoutAlgorithm;
|
|
// Get processed algorithm properties.
|
|
layoutAlgOptions.processedGridSize = relativeLength(layoutAlgOptions.gridSize ||
|
|
clusterDefaultOptions.layoutAlgorithm.gridSize, chart.plotWidth);
|
|
layoutAlgOptions.processedDistance = relativeLength(layoutAlgOptions.distance ||
|
|
clusterDefaultOptions.layoutAlgorithm.distance, chart.plotWidth);
|
|
kmeansThreshold = layoutAlgOptions.kmeansThreshold ||
|
|
clusterDefaultOptions.layoutAlgorithm.kmeansThreshold;
|
|
// Offset to prevent cluster size changes.
|
|
cropDataOffsetX = Math.abs(xAxis.toValue(layoutAlgOptions.processedGridSize / 2) -
|
|
xAxis.toValue(0));
|
|
cropDataOffsetY = Math.abs(yAxis.toValue(layoutAlgOptions.processedGridSize / 2) -
|
|
yAxis.toValue(0));
|
|
// Get only visible data.
|
|
for (i = 0; i < series.xData.length; i++) {
|
|
if (!series.dataMaxX) {
|
|
if (!defined(seriesMaxX) ||
|
|
!defined(seriesMinX) ||
|
|
!defined(seriesMaxY) ||
|
|
!defined(seriesMinY)) {
|
|
seriesMaxX = seriesMinX = series.xData[i];
|
|
seriesMaxY = seriesMinY = series.yData[i];
|
|
}
|
|
else if (isNumber(series.yData[i]) &&
|
|
isNumber(seriesMaxY) &&
|
|
isNumber(seriesMinY)) {
|
|
seriesMaxX = Math.max(series.xData[i], seriesMaxX);
|
|
seriesMinX = Math.min(series.xData[i], seriesMinX);
|
|
seriesMaxY = Math.max(series.yData[i] || seriesMaxY, seriesMaxY);
|
|
seriesMinY = Math.min(series.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 (series.xData[i] >= (realExtremes.minX - cropDataOffsetX) &&
|
|
series.xData[i] <= (realExtremes.maxX + cropDataOffsetX) &&
|
|
(series.yData[i] || realExtremes.minY) >=
|
|
(realExtremes.minY - cropDataOffsetY) &&
|
|
(series.yData[i] || realExtremes.maxY) <=
|
|
(realExtremes.maxY + cropDataOffsetY)) {
|
|
visibleXData.push(series.xData[i]);
|
|
visibleYData.push(series.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 = series.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', series.onDrillToCluster);
|
|
});
|
|
// 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);
|
|
}
|
|
};
|
|
// Handle animation.
|
|
addEvent(H.Chart, 'render', function () {
|
|
var chart = this;
|
|
(chart.series || []).forEach(function (series) {
|
|
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) {
|
|
series.markerClusterInfo.clusters.forEach(function (cluster) {
|
|
series.animateClusterPoint(cluster);
|
|
});
|
|
series.markerClusterInfo.noise.forEach(function (noise) {
|
|
series.animateClusterPoint(noise);
|
|
});
|
|
}
|
|
}
|
|
});
|
|
});
|
|
// Override point prototype to throw a warning when trying to update
|
|
// clustered point.
|
|
addEvent(Point, 'update', function () {
|
|
if (this.dataGroup) {
|
|
error('Highcharts marker-clusters module: ' +
|
|
'Running `Point.update` when point belongs to clustered series' +
|
|
' is not supported.', false, this.series.chart);
|
|
return false;
|
|
}
|
|
});
|
|
// Destroy grouped data on series destroy.
|
|
addEvent(Series, 'destroy', Scatter.prototype.destroyClusteredData);
|
|
// Add classes, change mouse cursor.
|
|
addEvent(Series, 'afterRender', function () {
|
|
var series = this, clusterZoomEnabled = (series.options.cluster || {}).drillToCluster;
|
|
if (series.markerClusterInfo && series.markerClusterInfo.clusters) {
|
|
series.markerClusterInfo.clusters.forEach(function (cluster) {
|
|
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);
|
|
}
|
|
}
|
|
});
|
|
}
|
|
});
|
|
addEvent(Point, 'drillToCluster', function (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);
|
|
}
|
|
});
|
|
// Destroy the old tooltip after zoom.
|
|
addEvent(H.Axis, 'setExtremes', function () {
|
|
var chart = this.chart, animationDuration = 0, animation;
|
|
chart.series.forEach(function (series) {
|
|
if (series.markerClusterInfo) {
|
|
animation = animObject((series.options.cluster || {}).animation);
|
|
animationDuration = animation.duration || 0;
|
|
}
|
|
});
|
|
syncTimeout(function () {
|
|
if (chart.tooltip) {
|
|
chart.tooltip.destroy();
|
|
}
|
|
}, animationDuration);
|
|
});
|
|
|
|
});
|
|
_registerModule(_modules, 'masters/modules/marker-clusters.src.js', [], function () {
|
|
|
|
|
|
});
|
|
})); |