openlayer4加载echart3的地理位置scatter图-全国主要城市空气质量
在github上下载了ol3-Echarts-master，原数据是加载echart的迁徙图，我对作者的类进行了改造，编写了一个类EchartLayer，加载饼图。代码如下：
说明：没有用到偏移量的计算，拖拽、缩放的时候，每次保存原数据（深度克隆），重新计算地理位置所对应的屏幕位置
/**
* echarts 百度地图扩展，必须在echarts初始化前使用
*
* @desc echarts基于Canvas，纯Javascript图表库，提供直观，生动，可交互，可个性化定制的数据统计图表。
*/
//**************js深度克隆*****************//
function deepClone(obj){
var result;
var oClass=isClass(obj);
if(oClass==="Object"){
result={};
}else if(oClass==="Array"){
result=[];
}else{
return obj;
}
for(var key in obj){
var copy=obj[key];
if(isClass(copy)=="Object"){
result[key]=arguments.callee(copy);//递归调用
}else if(isClass(copy)=="Array"){
result[key]=arguments.callee(copy);
}else{
result[key]=obj[key];
}
}
return result;
}
//判断对象的数据类型
function isClass(o){
if(o===null) return "Null";
if(o===undefined) return "Undefined";
return Object.prototype.toString.call(o).slice(8,-1);
}
/**
* 构造函数
*
* @param {String|HTMLElement|ol.Map} obj
* @param {echarts} ec
* @constructor
*/
function EchartLayer(map,ec) {
this._map=map;
var size = map.getSize();
var div = this._echartsContainer = document.createElement('div');
div.style.position = 'absolute';
div.style.height = size[1] + 'px';
div.style.width = size[0] + 'px';
div.style.top = 0;
div.style.left = 0;
map.getViewport().appendChild(div);
this._init(map,ec);
};
/**
* echarts 容器元素
*
* @type {HTMLElement}
* @private
*/
EchartLayer.prototype._echartsContainer = null;
/**
* ol地图实例
*
* @type {BMap.Map}
* @private
*/
EchartLayer.prototype._map = null;
/**
* 使用的echarts实例
*
* @type {ECharts}
* @private
*/
EchartLayer.prototype._ec = null;
/**
* geoCoord
*
* @type {Object}
* @private
*/
EchartLayer.prototype._geoCoord = [];
/**
* 记录地图的便宜量
*
* @type {Array.<number>}
* @private
*/
EchartLayer.prototype._mapOffset = [0, 0];
/**
* 初始化方法
*
* @param {String|HTMLElement|ol.Map} obj
* @param {BMap} BMap
* @param {echarts} ec
* @private
*/
EchartLayer.prototype._init = function (map,ec) {
var self = this;
self._map = map;
/**
* 获取echarts容器
*
* @return {HTMLElement}
* @public
*/
self.getEchartsContainer = function () {
return self._echartsContainer;
};
/**
* 获取map实例
*
* @return {BMap.Map}
* @public
*/
self.getMap = function () {
return self._map;
}
/**
* 经纬度转换为屏幕像素
*
* @param {Array.<number>} geoCoord 经纬度
* @return {Array.<number>}
* @public
*/
self.geoCoord2Pixel = function (geoCoord) {
return self._map.getPixelFromCoordinate(ol.proj.fromLonLat(geoCoord));
};
/**
* 屏幕像素转换为经纬度
*
* @param {Array.<number>} pixel 像素坐标
* @return {Array.<number>}
* @public
*/
self.pixel2GeoCoord = function (pixel) {
return self._map.getCoordinateFromPixel(pixel);
};
/**
* 初始化echarts实例
*
* @return {ECharts}
* @public
*/
self.initECharts = function () {
self._ec = ec.init.apply(self, arguments);
self._bindEvent();
self._addMarkWrap();
return self._ec;
};
// addMark wrap for get position from baidu map by geo location
// by kener at 2015.01.08
self._addMarkWrap = function () {
function _addMark(seriesIdx, markData, markType) {
if (markType == 'markPoint') {
var data = markData.data;
if (data && data.length) {
for (var k = 0, len = data.length; k < len; k++) {
self._AddPos(data[k]);
}
}
}
else {
data = markData.data;
if (data && data.length) {
for (var k = 0, len = data.length; k < len; k++) {
self._AddPos(data[k][0]);
self._AddPos(data[k][1]);
}
}
}
self._ec._addMarkOri(seriesIdx, markData, markType);
}
self._ec._addMarkOri = self._ec._addMark;
self._ec._addMark = _addMark;
};
/**
* 获取ECharts实例
*
* @return {ECharts}
* @public
*/
self.getECharts = function () {
return self._ec;
};
/**
* 获取地图的偏移量
*
* @return {Array.<number>}
* @public
*/
self.getMapOffset = function () {
return self._mapOffset;
};
/**
* 对echarts的setOption加一次处理
* 用来为markPoint、markLine中添加x、y坐标，需要name与geoCoord对应
*
* @param {Object}
* @public
*/
self.setOption = function (option, notMerge) {
if(!option){
return;
}
self._option = deepClone(option);
var series = option.series || {};
//data的数据类型[{name:"北京","value":[x,y,value]}],
//将x,y转为屏幕坐标
// var coordinates=option.series[0].data || option.series || {};
for(var i=0;i<series.length;i++){
var iseries=series[i];
var tempdata=iseries.data;
var resultdata=[];
if(tempdata){
for(var j=0;j<tempdata.length;j++){
var latlon=tempdata[j].value.slice(0,2);
var pixelcoordinates=self.geoCoord2Pixel(latlon);
var value=tempdata[j].value[2];
var resultValue=pixelcoordinates.push(value);
var item={"name":tempdata[j].name,"value":pixelcoordinates};
resultdata.push(item);
}
series[i].data=resultdata;
}
}
// 记录所有的geoCoord
/* for (var i = 0, item; item = coordinates[i++];) {
var geoCoord = item.geoCoord || item.value.slice(0,2);
console.log(geoCoord);
if (geoCoord) {
self._geoCoord[item.name] = geoCoord;
}
}
// 添加x、y
for (var i = 0, item; item = series[i++];) {
var markPoint = item.markPoint || {};
var markLine = item.markLine || {};
var data = markPoint.data;
if (data && data.length) {
for (var k = 0, len = data.length; k < len; k++) {
self._AddPos(data[k]);
}
}
data = markLine.data;
if (data && data.length) {
for (var k = 0, len = data.length; k < len; k++) {
self._AddPos(data[k][0]);
self._AddPos(data[k][1]);
}
}
}*/
//data
option.series=series;
self._ec.setOption(option, notMerge);
};
/**
* 增加x、y坐标
*
* @param {Object} obj markPoint、markLine data中的项，必须有name
* @param {Object} geoCoord
*/
self._AddPos = function (obj) {
var coord = this._geoCoord[obj.name];
var pos = this.geoCoord2Pixel(coord);
obj.x = pos[0] ;//- self._mapOffset[0];
obj.y = pos[1] ;//- self._mapOffset[1];
};
/**
* 绑定地图事件的处理方法
*
* @private
*/
self._bindEvent = function () {
//self._map.getView().on('change:resolution', _zoomChangeHandler('zoom'));
/* self._map.getView().on('change:center', _moveHandler('moving'));
self._map.on('moveend', _moveHandler('moveend'));
self._ec.getZr().on('dragstart', _dragZrenderHandler(true));
self._ec.getZr().on('dragend', _dragZrenderHandler(false));*/
self._map.getView().on('change:resolution', function (e) {
self.setOption(self._option);
});
self._map.on('moveend', function (e) {
self._echartsContainer.style.display='block';
self.setOption(self._option);
});
self._map.on('movestart', function (e) {
self._echartsContainer.style.display='none';
});
}
/**
* 地图缩放触发事件
*
* @private
*/
function _zoomChangeHandler(type) {
_fireEvent(type);
}
/**
* 地图移动、如拖拽触发事件
*
* @param {string} type moving | moveend 移动中|移动结束
* @return {Function}
* @private
*/
function _moveHandler(type) {
return function (e) {
// 记录偏移量
var offsetEle =
self._echartsContainer.parentNode.parentNode.parentNode;
self._mapOffset = [
-parseInt(offsetEle.style.left) || 0,
-parseInt(offsetEle.style.top) || 0
];
self._echartsContainer.style.left = self._mapOffset[0] + 'px';
self._echartsContainer.style.top = self._mapOffset[1] + 'px';
_fireEvent(type);
}
}
/**
* Zrender拖拽触发事件
*
* @param {boolean} isStart
* @return {Function}
* @private
*/
function _dragZrenderHandler(isStart) {
return function () {
self._map.dragging = isStart;
}
}
/**
* 触发事件
*
* @param {stirng} type 事件类型
* @private
*/
function _fireEvent(type) {
var func = self['on' + type];
if (func) {
func();
} else {
self.refresh();
}
}
/**
* 刷新页面
*
* @public
*/
self.refresh = function () {
if (self._ec) {
var option = self._ec.getOption();
var component = self._ec.component || {};
var legend = component.legend;
var dataRange = component.dataRange;
if (legend) {
option.legend.selected = legend.getSelectedMap();
}
if (dataRange) {
option.dataRange.range = dataRange._range;
}
self._ec.clear();
self.setOption(option);
}
};
return EchartLayer;
}
调用示例：
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>ol3-Echarts</title>
<style>
html, body, #map {
height: 100%;
padding: 0;
margin: 0;
background-color: #0f0f0f;
}
</style>
<link rel="stylesheet" href="plugin/ol3/ol.css" type="text/css">
</head>
<body>
<div id="map">
</div>
<script src="plugin/ol3/ol.js"></script>
<script src="js/main.js"></script>
<script src="plugin/jquery-2.1.1.min.js"></script>
<script src="plugin/echarts.min-3.2.3.js"></script>
<script src="js/EchartLayer.js"></script>
<script>
$(document).ready(function () {
var map = new ol.Map({
target: 'map',
controls: [],
layers: [
new ol.layer.Tile({
source: new ol.source.OSM()
})
/* new ol.layer.Vector({
source:new ol.source.Vector({
url:'china_line.json',
format:new ol.format.GeoJSON()
})
}),
new ol.layer.Vector({
source:new ol.source.Vector({
url:'china.geojson',
format:new ol.format.GeoJSON()
})
})*/
],
view: new ol.View({
center: [0, 0],
zoom: 2
})
})
var data = [
{name: '海门', value: 9},
{name: '鄂尔多斯', value: 12},
{name: '招远', value: 12},
{name: '舟山', value: 12},
{name: '齐齐哈尔', value: 14},
{name: '盐城', value: 15},
{name: '赤峰', value: 16},
{name: '青岛', value: 18},
{name: '乳山', value: 18},
{name: '金昌', value: 19},
{name: '泉州', value: 21},
{name: '莱西', value: 21},
{name: '日照', value: 21},
{name: '胶南', value: 22},
{name: '南通', value: 23},
{name: '拉萨', value: 24},
{name: '云浮', value: 24},
{name: '梅州', value: 25},
{name: '文登', value: 25},
{name: '上海', value: 25},
{name: '攀枝花', value: 25},
{name: '威海', value: 25},
{name: '承德', value: 25},
{name: '厦门', value: 26},
{name: '汕尾', value: 26},
{name: '潮州', value: 26},
{name: '丹东', value: 27},
{name: '太仓', value: 27},
{name: '曲靖', value: 27},
{name: '烟台', value: 28},
{name: '福州', value: 29},
{name: '瓦房店', value: 30},
{name: '即墨', value: 30},
{name: '抚顺', value: 31},
{name: '玉溪', value: 31},
{name: '张家口', value: 31},
{name: '阳泉', value: 31},
{name: '莱州', value: 32},
{name: '湖州', value: 32},
{name: '汕头', value: 32},
{name: '昆山', value: 33},
{name: '宁波', value: 33},
{name: '湛江', value: 33},
{name: '揭阳', value: 34},
{name: '荣成', value: 34},
{name: '连云港', value: 35},
{name: '葫芦岛', value: 35},
{name: '常熟', value: 36},
{name: '东莞', value: 36},
{name: '河源', value: 36},
{name: '淮安', value: 36},
{name: '泰州', value: 36},
{name: '南宁', value: 37},
{name: '营口', value: 37},
{name: '惠州', value: 37},
{name: '江阴', value: 37},
{name: '蓬莱', value: 37},
{name: '韶关', value: 38},
{name: '嘉峪关', value: 38},
{name: '广州', value: 38},
{name: '延安', value: 38},
{name: '太原', value: 39},
{name: '清远', value: 39},
{name: '中山', value: 39},
{name: '昆明', value: 39},
{name: '寿光', value: 40},
{name: '盘锦', value: 40},
{name: '长治', value: 41},
{name: '深圳', value: 41},
{name: '珠海', value: 42},
{name: '宿迁', value: 43},
{name: '咸阳', value: 43},
{name: '铜川', value: 44},
{name: '平度', value: 44},
{name: '佛山', value: 44},
{name: '海口', value: 44},
{name: '江门', value: 45},
{name: '章丘', value: 45},
{name: '肇庆', value: 46},
{name: '大连', value: 47},
{name: '临汾', value: 47},
{name: '吴江', value: 47},
{name: '石嘴山', value: 49},
{name: '沈阳', value: 50},
{name: '苏州', value: 50},
{name: '茂名', value: 50},
{name: '嘉兴', value: 51},
{name: '长春', value: 51},
{name: '胶州', value: 52},
{name: '银川', value: 52},
{name: '张家港', value: 52},
{name: '三门峡', value: 53},
{name: '锦州', value: 54},
{name: '南昌', value: 54},
{name: '柳州', value: 54},
{name: '三亚', value: 54},
{name: '自贡', value: 56},
{name: '吉林', value: 56},
{name: '阳江', value: 57},
{name: '泸州', value: 57},
{name: '西宁', value: 57},
{name: '宜宾', value: 58},
{name: '呼和浩特', value: 58},
{name: '成都', value: 58},
{name: '大同', value: 58},
{name: '镇江', value: 59},
{name: '桂林', value: 59},
{name: '张家界', value: 59},
{name: '宜兴', value: 59},
{name: '北海', value: 60},
{name: '西安', value: 61},
{name: '金坛', value: 62},
{name: '东营', value: 62},
{name: '牡丹江', value: 63},
{name: '遵义', value: 63},
{name: '绍兴', value: 63},
{name: '扬州', value: 64},
{name: '常州', value: 64},
{name: '潍坊', value: 65},
{name: '重庆', value: 66},
{name: '台州', value: 67},
{name: '南京', value: 67},
{name: '滨州', value: 70},
{name: '贵阳', value: 71},
{name: '无锡', value: 71},
{name: '本溪', value: 71},
{name: '克拉玛依', value: 72},
{name: '渭南', value: 72},
{name: '马鞍山', value: 72},
{name: '宝鸡', value: 72},
{name: '焦作', value: 75},
{name: '句容', value: 75},
{name: '北京', value: 79},
{name: '徐州', value: 79},
{name: '衡水', value: 80},
{name: '包头', value: 80},
{name: '绵阳', value: 80},
{name: '乌鲁木齐', value: 84},
{name: '枣庄', value: 84},
{name: '杭州', value: 84},
{name: '淄博', value: 85},
{name: '鞍山', value: 86},
{name: '溧阳', value: 86},
{name: '库尔勒', value: 86},
{name: '安阳', value: 90},
{name: '开封', value: 90},
{name: '济南', value: 92},
{name: '德阳', value: 93},
{name: '温州', value: 95},
{name: '九江', value: 96},
{name: '邯郸', value: 98},
{name: '临安', value: 99},
{name: '兰州', value: 99},
{name: '沧州', value: 100},
{name: '临沂', value: 103},
{name: '南充', value: 104},
{name: '天津', value: 105},
{name: '富阳', value: 106},
{name: '泰安', value: 112},
{name: '诸暨', value: 112},
{name: '郑州', value: 113},
{name: '哈尔滨', value: 114},
{name: '聊城', value: 116},
{name: '芜湖', value: 117},
{name: '唐山', value: 119},
{name: '平顶山', value: 119},
{name: '邢台', value: 119},
{name: '德州', value: 120},
{name: '济宁', value: 120},
{name: '荆州', value: 127},
{name: '宜昌', value: 130},
{name: '义乌', value: 132},
{name: '丽水', value: 133},
{name: '洛阳', value: 134},
{name: '秦皇岛', value: 136},
{name: '株洲', value: 143},
{name: '石家庄', value: 147},
{name: '莱芜', value: 148},
{name: '常德', value: 152},
{name: '保定', value: 153},
{name: '湘潭', value: 154},
{name: '金华', value: 157},
{name: '岳阳', value: 169},
{name: '长沙', value: 175},
{name: '衢州', value: 177},
{name: '廊坊', value: 193},
{name: '菏泽', value: 194},
{name: '合肥', value: 229},
{name: '武汉', value: 273},
{name: '大庆', value: 279}
];
var geoCoordMap = {
'海门':[121.15,31.89],
'鄂尔多斯':[109.781327,39.608266],
'招远':[120.38,37.35],
'舟山':[122.207216,29.985295],
'齐齐哈尔':[123.97,47.33],
'盐城':[120.13,33.38],
'赤峰':[118.87,42.28],
'青岛':[120.33,36.07],
'乳山':[121.52,36.89],
'金昌':[102.188043,38.520089],
'泉州':[118.58,24.93],
'莱西':[120.53,36.86],
'日照':[119.46,35.42],
'胶南':[119.97,35.88],
'南通':[121.05,32.08],
'拉萨':[91.11,29.97],
'云浮':[112.02,22.93],
'梅州':[116.1,24.55],
'文登':[122.05,37.2],
'上海':[121.48,31.22],
'攀枝花':[101.718637,26.582347],
'威海':[122.1,37.5],
'承德':[117.93,40.97],
'厦门':[118.1,24.46],
'汕尾':[115.375279,22.786211],
'潮州':[116.63,23.68],
'丹东':[124.37,40.13],
'太仓':[121.1,31.45],
'曲靖':[103.79,25.51],
'烟台':[121.39,37.52],
'福州':[119.3,26.08],
'瓦房店':[121.979603,39.627114],
'即墨':[120.45,36.38],
'抚顺':[123.97,41.97],
'玉溪':[102.52,24.35],
'张家口':[114.87,40.82],
'阳泉':[113.57,37.85],
'莱州':[119.942327,37.177017],
'湖州':[120.1,30.86],
'汕头':[116.69,23.39],
'昆山':[120.95,31.39],
'宁波':[121.56,29.86],
'湛江':[110.359377,21.270708],
'揭阳':[116.35,23.55],
'荣成':[122.41,37.16],
'连云港':[119.16,34.59],
'葫芦岛':[120.836932,40.711052],
'常熟':[120.74,31.64],
'东莞':[113.75,23.04],
'河源':[114.68,23.73],
'淮安':[119.15,33.5],
'泰州':[119.9,32.49],
'南宁':[108.33,22.84],
'营口':[122.18,40.65],
'惠州':[114.4,23.09],
'江阴':[120.26,31.91],
'蓬莱':[120.75,37.8],
'韶关':[113.62,24.84],
'嘉峪关':[98.289152,39.77313],
'广州':[113.23,23.16],
'延安':[109.47,36.6],
'太原':[112.53,37.87],
'清远':[113.01,23.7],
'中山':[113.38,22.52],
'昆明':[102.73,25.04],
'寿光':[118.73,36.86],
'盘锦':[122.070714,41.119997],
'长治':[113.08,36.18],
'深圳':[114.07,22.62],
'珠海':[113.52,22.3],
'宿迁':[118.3,33.96],
'咸阳':[108.72,34.36],
'铜川':[109.11,35.09],
'平度':[119.97,36.77],
'佛山':[113.11,23.05],
'海口':[110.35,20.02],
'江门':[113.06,22.61],
'章丘':[117.53,36.72],
'肇庆':[112.44,23.05],
'大连':[121.62,38.92],
'临汾':[111.5,36.08],
'吴江':[120.63,31.16],
'石嘴山':[106.39,39.04],
'沈阳':[123.38,41.8],
'苏州':[120.62,31.32],
'茂名':[110.88,21.68],
'嘉兴':[120.76,30.77],
'长春':[125.35,43.88],
'胶州':[120.03336,36.264622],
'银川':[106.27,38.47],
'张家港':[120.555821,31.875428],
'三门峡':[111.19,34.76],
'锦州':[121.15,41.13],
'南昌':[115.89,28.68],
'柳州':[109.4,24.33],
'三亚':[109.511909,18.252847],
'自贡':[104.778442,29.33903],
'吉林':[126.57,43.87],
'阳江':[111.95,21.85],
'泸州':[105.39,28.91],
'西宁':[101.74,36.56],
'宜宾':[104.56,29.77],
'呼和浩特':[111.65,40.82],
'成都':[104.06,30.67],
'大同':[113.3,40.12],
'镇江':[119.44,32.2],
'桂林':[110.28,25.29],
'张家界':[110.479191,29.117096],
'宜兴':[119.82,31.36],
'北海':[109.12,21.49],
'西安':[108.95,34.27],
'金坛':[119.56,31.74],
'东营':[118.49,37.46],
'牡丹江':[129.58,44.6],
'遵义':[106.9,27.7],
'绍兴':[120.58,30.01],
'扬州':[119.42,32.39],
'常州':[119.95,31.79],
'潍坊':[119.1,36.62],
'重庆':[106.54,29.59],
'台州':[121.420757,28.656386],
'南京':[118.78,32.04],
'滨州':[118.03,37.36],
'贵阳':[106.71,26.57],
'无锡':[120.29,31.59],
'本溪':[123.73,41.3],
'克拉玛依':[84.77,45.59],
'渭南':[109.5,34.52],
'马鞍山':[118.48,31.56],
'宝鸡':[107.15,34.38],
'焦作':[113.21,35.24],
'句容':[119.16,31.95],
'北京':[116.46,39.92],
'徐州':[117.2,34.26],
'衡水':[115.72,37.72],
'包头':[110,40.58],
'绵阳':[104.73,31.48],
'乌鲁木齐':[87.68,43.77],
'枣庄':[117.57,34.86],
'杭州':[120.19,30.26],
'淄博':[118.05,36.78],
'鞍山':[122.85,41.12],
'溧阳':[119.48,31.43],
'库尔勒':[86.06,41.68],
'安阳':[114.35,36.1],
'开封':[114.35,34.79],
'济南':[117,36.65],
'德阳':[104.37,31.13],
'温州':[120.65,28.01],
'九江':[115.97,29.71],
'邯郸':[114.47,36.6],
'临安':[119.72,30.23],
'兰州':[103.73,36.03],
'沧州':[116.83,38.33],
'临沂':[118.35,35.05],
'南充':[106.110698,30.837793],
'天津':[117.2,39.13],
'富阳':[119.95,30.07],
'泰安':[117.13,36.18],
'诸暨':[120.23,29.71],
'郑州':[113.65,34.76],
'哈尔滨':[126.63,45.75],
'聊城':[115.97,36.45],
'芜湖':[118.38,31.33],
'唐山':[118.02,39.63],
'平顶山':[113.29,33.75],
'邢台':[114.48,37.05],
'德州':[116.29,37.45],
'济宁':[116.59,35.38],
'荆州':[112.239741,30.335165],
'宜昌':[111.3,30.7],
'义乌':[120.06,29.32],
'丽水':[119.92,28.45],
'洛阳':[112.44,34.7],
'秦皇岛':[119.57,39.95],
'株洲':[113.16,27.83],
'石家庄':[114.48,38.03],
'莱芜':[117.67,36.19],
'常德':[111.69,29.05],
'保定':[115.48,38.85],
'湘潭':[112.91,27.87],
'金华':[119.64,29.12],
'岳阳':[113.09,29.37],
'长沙':[113,28.21],
'衢州':[118.88,28.97],
'廊坊':[116.7,39.53],
'菏泽':[115.480656,35.23375],
'合肥':[117.27,31.86],
'武汉':[114.31,30.52],
'大庆':[125.03,46.58]
};
var option = {
title: {
text: '全国主要城市空气质量',
subtext: 'data from PM25.in',
sublink: 'http://www.pm25.in',
left: 'center',
textStyle: {
color: '#fff'
}
},
tooltip : {
trigger: 'item'
},
legend: {
orient: 'vertical',
y: 'bottom',
x:'right',
data:['pm2.5'],
textStyle: {
color: '#fff'
}
},
geo: {
map: '',
label: {
emphasis: {
show: false
}
},
roam: true,
itemStyle: {
normal: {
areaColor: '#323c48',
borderColor: '#111'
},
emphasis: {
areaColor: '#2a333d'
}
}
},
series : [
{
name: 'pm2.5',
type: 'scatter',
coordinateSystem: 'geo',
data: convertData(),
symbolSize: function (val) {
return val[2] / 10;
},
label: {
normal: {
formatter: '{b}',
position: 'right',
show: false
},
emphasis: {
show: true
}
},
itemStyle: {
normal: {
color: '#ddb926'
}
}
},
{
name: 'Top 5',
type: 'effectScatter',
coordinateSystem: 'geo',
data: convertData2(),
symbolSize: function (val) {
return val[2] / 10;
},
showEffectOn: 'render',
rippleEffect: {
brushType: 'stroke'
},
hoverAnimation: true,
label: {
normal: {
formatter: '{b}',
position: 'right',
show: true
}
},
itemStyle: {
normal: {
color: '#f4e925',
shadowBlur: 10,
shadowColor: '#333'
}
},
zlevel: 1
}
]
};
// chart.setOption(option);
//将地图坐标与值结合
function convertData() {
var res=[];
for(var i=0;i<data.length;i++){
var singledata=data[i];
var geoCoord=geoCoordMap[data[i].name];
if(geoCoord){
res.push({
name:data[i].name,
value:geoCoord.concat(data[i].value)
});
}
}
return res;
}
function convertData2() {
var res=[];
var tempdata=data.sort(function (a, b) {
return b.value - a.value;
}).slice(0, 6);
for(var i=0;i<tempdata.length;i++){
var singledata=tempdata[i];
var geoCoord=geoCoordMap[singledata.name];
if(geoCoord){
res.push({
name:data[i].name,
value:geoCoord.concat(singledata.value)
});
}
}
return res;
}
// window.onresize = chart.resize;
var olMapExt;
map.once('postrender', function (e) {
if (olMapExt !== undefined)
return;
olMapExt = new EchartLayer(map, echarts);
var container = olMapExt.getEchartsContainer();
var myChart = olMapExt.initECharts(container);
window.onresize = myChart.resize;
olMapExt.setOption(option, true);
// var chart = echarts.init(container);
//chart.setOption(option);
});
});
</script>
</body>
</html>
转载自：https://blog.csdn.net/u011394175/article/details/81075113
