/**
 * @license Highcharts JS v9.1.1 (2021-06-03)
 *
 * Marker clusters module for Highcharts
 *
 * (c) 2010-2021 Wojciech Chmiel
 *
 * License: www.highcharts.com/license
 */
'use strict';
(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) {
    var _modules = Highcharts ? Highcharts._modules : {};
    function _registerModule(obj, path, args, fn) {
        if (!obj.hasOwnProperty(path)) {
            obj[path] = fn.apply(null, args);
        }
    }
    _registerModule(_modules, 'Extensions/MarkerClusters.js', [_modules['Core/Animation/AnimationUtilities.js'], _modules['Core/Chart/Chart.js'], _modules['Core/DefaultOptions.js'], _modules['Core/Color/Palette.js'], _modules['Core/Series/Point.js'], _modules['Core/Series/Series.js'], _modules['Core/Series/SeriesRegistry.js'], _modules['Core/Renderer/SVG/SVGRenderer.js'], _modules['Core/Utilities.js'], _modules['Core/Axis/Axis.js']], function (A, Chart, D, palette, Point, Series, SeriesRegistry, SVGRenderer, U, Axis) {
        /* *
         *
         *  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 seriesTypes = SeriesRegistry.seriesTypes;
        var symbols = SVGRenderer.prototype.symbols;
        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,
            relativeLength = U.relativeLength,
            syncTimeout = U.syncTimeout;
        /**
         * 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.
         */
        ''; // detach doclets from following code
        /* eslint-disable no-invalid-this */
        var Scatter = seriesTypes.scatter,
            baseGeneratePoints = Series.prototype.generatePoints,
            stateIdCounter = 0, 
            // Points that ids are included in the oldPointsStateId array
            // are hidden before animation. Other ones are destroyed.
            oldPointsStateId = [];
        /**
         * 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 clusterDefaultOptions = {
                /**
                 * 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<Highcharts.AnimationOptionsObject>}
                 * @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:
                     * <pre>{
                     *  clusterId1: [{
                     *      x: 573,
                     *      y: 285,
                     *      index: 1 // point index in the data array
                     *  }, {
                     *      x: 521,
                     *      y: 197,
                     *      index: 2
                     *  }],
                     *  clusterId2: [{
                     *      ...
                     *  }]
                     *  ...
                     * }</pre>
                     *
                     * `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.marker.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.
                 * @extends   plotOptions.series.marker
                 * @excluding enabledThreshold,
            states
                 * @type      {Highcharts.PointMarkerOptionsObject}
                 */
                marker: {
                    /** @internal */
                    symbol: 'cluster',
                    /** @internal */
                    radius: 15,
                    /** @internal */
                    lineWidth: 0,
                    /** @internal */
                    lineColor: 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.marker.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
                }
            };
        (defaultOptions.plotOptions || {}).series = merge((defaultOptions.plotOptions || {}).series, {
            cluster: clusterDefaultOptions,
            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
                 *
                 * @apioption tooltip.clusterFormat
                 */
                clusterFormat: '<span>Clustered points: ' +
                    '{point.clusterPointsAmount}</span><br/>'
            }
        });
        // Utils.
        /* eslint-disable require-jsdoc */
        function getClusterPosition(points) {
            var pointsLen = points.length,
                sumX = 0,
                sumY = 0,
                i;
            for (i = 0; i < pointsLen; i++) {
                sumX += points[i].x;
                sumY += points[i].y;
            }
            return {
                x: sumX / pointsLen,
                y: sumY / pointsLen
            };
        }
        // Prepare array with sorted data objects to be
        // compared in getPointsState method.
        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;
        }
        function fadeInElement(elem, opacity, animation) {
            elem
                .attr({
                opacity: opacity
            })
                .animate({
                opacity: 1
            }, animation);
        }
        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);
                }
            }
        }
        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();
                }
            }
        }
        function destroyOldPoints(oldState) {
            if (oldState) {
                objectEach(oldState, function (state) {
                    if (state.point && state.point.destroy) {
                        state.point.destroy();
                    }
                });
            }
        }
        function fadeInNewPointAndDestoryOld(newPointObj, oldPoints, animation, opacity) {
            // Fade in new point.
            fadeInStatePoint(newPointObj, opacity, animation, true, true);
            // Destroy old animated points.
            oldPoints.forEach(function (p) {
                if (p.point && p.point.destroy) {
                    p.point.destroy();
                }
            });
        }
        // Generate unique stateId for a state element.
        function getStateId() {
            return Math.random().toString(36).substring(2, 7) + '-' + stateIdCounter++;
        }
        // Cluster symbol.
        symbols.cluster = function (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);
        };
        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();
                        // 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);
                    }
                }
            }
        };
        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 = [realMinX, realMaxX], realMaxX = _a[0], realMinX = _a[1];
            }
            if (realMinY > realMaxY) {
                _b = [realMinY, realMaxY], 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 = [maxX, minX], minX = _a[0], maxX = _a[1];
                    }
                    if (minY > maxY) {
                        _b = [maxY, minY], 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 = props.key.split('-').map(parseFloat),
                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 = 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 = 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.xData.length &&
                series.yData &&
                series.yData.length &&
                !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(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(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 () {


    });
}));