利用ECharts3来实现ECharts2实例中的模拟迁徙效果，即背景地图为百度地图。

来源：互联网发布：淘宝服务.com 编辑：程序博客网时间：2024/05/19 17:47

很多小伙伴都来要demo源码，现在我把demo放在我的GitHub上了。
https://github.com/lixinGiting/echarts3_map_demo
希望大家能给我个star鼓励一下。

效果预览：http://htmlpreview.github.io/?https://github.com/lixinGiting/echarts3_map_demo/blob/master/index.html

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工作需要，想通过ECharts3来制作类似于ECharts2实例中模拟迁徙地图的效果，本来认为很简单，后来发现并不好做，上网查找了相关问题，翻来覆去只有相关的问题，却没有一个合适的答案，后来费心尽力，终于做出一点成果，分享给大家。

在ECharts2中模拟迁徙地图为：点击打开链接

在ECharts3中模拟迁徙地图为：点击打开链接

发现有以下要注意的事项，首先与echarts2相比echarts3有很大的改动：

第一点：ECharts2推荐模块化单文件引入；由于echarts依赖底层zrender，你需要同时下载zrender到本地。

ECharts 3 开始不再强制使用 AMD 的方式按需引入，代码里也不再内置 AMD 加载器。因此引入方式简单了很多，只需要像普通的 JavaScript 库一样用 script 标签引入。

第二点：ECharts3中因为地图精度的提高，不再内置地图数据增大代码体积，你可以在地图下载界面下载到需要的地图文件引入并注册到 ECharts 中。

如果采用echarts3官方给的地图加载方式即

<script src="echarts.js"></script><script src="map/js/china.js"></script><script>var chart = echarts.init(document.getElementById('main'));chart.setOption({    series: [{        type: 'map',        map: 'china'    }]});</script>

那么会得到和echarts3官方实例一样的黑色背景的地图。

echarts2中的模拟迁徙之所以能显示百度地图的背景，是因为它引入了百度地图。

百度地图和echarts2的结合比较简单，官方也有很多百度地图的扩展实例。具体查看请点击

重点是echart3和百度地图的结合

需要引入百度开发者密钥，还要引入bmap文件，否则会报错。百度开发者密钥去百度地图API官网申请即可，很简单。

<script src="echarts.js"></script><script src="bmap.js"></script>

<script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=0UqXGL98FSmi22w2Rl6HK56I"></script>

完整的Demo代码：

<html><head>    <meta charset="utf-8">    <style type="text/css">        body {            margin: 0;        }        #main {            height: 100%;        }    </style></head><body><div id="main"></div><script src="echarts.js"></script><script src="bmap.js"></script><script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=0UqXGL98FSmi22w2Rl6HK56I"></script><script>var myChart = echarts.init(document.getElementById('main'));var option = {        bmap: {        center: [113.65,34.76],        zoom: 5,        roam: true,        },         series: [{            type: 'map',            coordinateSystem: 'bmap'        }]};myChart.setOption(option);</script></body></html>

值得注意的是series中的坐标系

coordinateSystem: 'bmap'

然后我们就可以参考着echarts3中的模拟迁徙图补全代码，最终就可以得到以百度地图为背景的echarts模拟迁徙地图，和echrts2中的模拟迁徙实例非常类似。

官方实例图：

效果图：

<html><head>    <meta charset="utf-8">    <style type="text/css">        body {            margin: 0;        }        #main {            height: 100%;        }    </style></head><body><div id="main"></div><script src="echarts.js"></script><script src="bmap.js"></script><script src="china.js"></script><script src="world.js"></script><script src="http://libs.baidu.com/jquery/2.0.0/jquery.js"></script><script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=0UqXGL98FSmi22w2Rl6HK56I"></script><script>var myChart = echarts.init(document.getElementById('main'));var geoCoordMap = {    '上海': [121.4648,31.2891],    '东莞': [113.8953,22.901],    '东营': [118.7073,37.5513],    '中山': [113.4229,22.478],    '临汾': [111.4783,36.1615],    '临沂': [118.3118,35.2936],    '丹东': [124.541,40.4242],    '丽水': [119.5642,28.1854],    '乌鲁木齐': [87.9236,43.5883],    '佛山': [112.8955,23.1097],    '保定': [115.0488,39.0948],    '兰州': [103.5901,36.3043],    '包头': [110.3467,41.4899],    '北京': [116.4551,40.2539],    '北海': [109.314,21.6211],    '南京': [118.8062,31.9208],    '南宁': [108.479,23.1152],    '南昌': [116.0046,28.6633],    '南通': [121.1023,32.1625],    '厦门': [118.1689,24.6478],    '台州': [121.1353,28.6688],    '合肥': [117.29,32.0581],    '呼和浩特': [111.4124,40.4901],    '咸阳': [108.4131,34.8706],    '哈尔滨': [127.9688,45.368],    '唐山': [118.4766,39.6826],    '嘉兴': [120.9155,30.6354],    '大同': [113.7854,39.8035],    '大连': [122.2229,39.4409],    '天津': [117.4219,39.4189],    '太原': [112.3352,37.9413],    '威海': [121.9482,37.1393],    '宁波': [121.5967,29.6466],    '宝鸡': [107.1826,34.3433],    '宿迁': [118.5535,33.7775],    '常州': [119.4543,31.5582],    '广州': [113.5107,23.2196],    '廊坊': [116.521,39.0509],    '延安': [109.1052,36.4252],    '张家口': [115.1477,40.8527],    '徐州': [117.5208,34.3268],    '德州': [116.6858,37.2107],    '惠州': [114.6204,23.1647],    '成都': [103.9526,30.7617],    '扬州': [119.4653,32.8162],    '承德': [117.5757,41.4075],    '拉萨': [91.1865,30.1465],    '无锡': [120.3442,31.5527],    '日照': [119.2786,35.5023],    '昆明': [102.9199,25.4663],    '杭州': [119.5313,29.8773],    '枣庄': [117.323,34.8926],    '柳州': [109.3799,24.9774],    '株洲': [113.5327,27.0319],    '武汉': [114.3896,30.6628],    '汕头': [117.1692,23.3405],    '江门': [112.6318,22.1484],    '沈阳': [123.1238,42.1216],    '沧州': [116.8286,38.2104],    '河源': [114.917,23.9722],    '泉州': [118.3228,25.1147],    '泰安': [117.0264,36.0516],    '泰州': [120.0586,32.5525],    '济南': [117.1582,36.8701],    '济宁': [116.8286,35.3375],    '海口': [110.3893,19.8516],    '淄博': [118.0371,36.6064],    '淮安': [118.927,33.4039],    '深圳': [114.5435,22.5439],    '清远': [112.9175,24.3292],    '温州': [120.498,27.8119],    '渭南': [109.7864,35.0299],    '湖州': [119.8608,30.7782],    '湘潭': [112.5439,27.7075],    '滨州': [117.8174,37.4963],    '潍坊': [119.0918,36.524],    '烟台': [120.7397,37.5128],    '玉溪': [101.9312,23.8898],    '珠海': [113.7305,22.1155],    '盐城': [120.2234,33.5577],    '盘锦': [121.9482,41.0449],    '石家庄': [114.4995,38.1006],    '福州': [119.4543,25.9222],    '秦皇岛': [119.2126,40.0232],    '绍兴': [120.564,29.7565],    '聊城': [115.9167,36.4032],    '肇庆': [112.1265,23.5822],    '舟山': [122.2559,30.2234],    '苏州': [120.6519,31.3989],    '莱芜': [117.6526,36.2714],    '菏泽': [115.6201,35.2057],    '营口': [122.4316,40.4297],    '葫芦岛': [120.1575,40.578],    '衡水': [115.8838,37.7161],    '衢州': [118.6853,28.8666],    '西宁': [101.4038,36.8207],    '西安': [109.1162,34.2004],    '贵阳': [106.6992,26.7682],    '连云港': [119.1248,34.552],    '邢台': [114.8071,37.2821],    '邯郸': [114.4775,36.535],    '郑州': [113.4668,34.6234],    '鄂尔多斯': [108.9734,39.2487],    '重庆': [107.7539,30.1904],    '金华': [120.0037,29.1028],    '铜川': [109.0393,35.1947],    '银川': [106.3586,38.1775],    '镇江': [119.4763,31.9702],    '长春': [125.8154,44.2584],    '长沙': [113.0823,28.2568],    '长治': [112.8625,36.4746],    '阳泉': [113.4778,38.0951],    '青岛': [120.4651,36.3373],    '韶关': [113.7964,24.7028]};var BJData = [    [{name:'北京'}, {name:'上海',value:95}],    [{name:'北京'}, {name:'广州',value:90}],    [{name:'北京'}, {name:'大连',value:80}],    [{name:'北京'}, {name:'南宁',value:70}],    [{name:'北京'}, {name:'南昌',value:60}],    [{name:'北京'}, {name:'拉萨',value:50}],    [{name:'北京'}, {name:'长春',value:40}],    [{name:'北京'}, {name:'包头',value:30}],    [{name:'北京'}, {name:'重庆',value:20}],    [{name:'北京'}, {name:'常州',value:10}]];var SHData = [    [{name:'上海'},{name:'包头',value:95}],    [{name:'上海'},{name:'昆明',value:90}],    [{name:'上海'},{name:'广州',value:80}],    [{name:'上海'},{name:'郑州',value:70}],    [{name:'上海'},{name:'长春',value:60}],    [{name:'上海'},{name:'重庆',value:50}],    [{name:'上海'},{name:'长沙',value:40}],    [{name:'上海'},{name:'北京',value:30}],    [{name:'上海'},{name:'丹东',value:20}],    [{name:'上海'},{name:'大连',value:10}]];var GZData = [    [{name:'广州'},{name:'福州',value:95}],    [{name:'广州'},{name:'太原',value:90}],    [{name:'广州'},{name:'长春',value:80}],    [{name:'广州'},{name:'重庆',value:70}],    [{name:'广州'},{name:'西安',value:60}],    [{name:'广州'},{name:'成都',value:50}],    [{name:'广州'},{name:'常州',value:40}],    [{name:'广州'},{name:'北京',value:30}],    [{name:'广州'},{name:'北海',value:20}],    [{name:'广州'},{name:'海口',value:10}]];var planePath = 'path://M1705.06,1318.313v-89.254l-319.9-221.799l0.073-208.063c0.521-84.662-26.629-121.796-63.961-121.491c-37.332-0.305-64.482,36.829-63.961,121.491l0.073,208.063l-319.9,221.799v89.254l330.343-157.288l12.238,241.308l-134.449,92.931l0.531,42.034l175.125-42.917l175.125,42.917l0.531-42.034l-134.449-92.931l12.238-241.308L1705.06,1318.313z';var convertData = function (data) {    var res = [];    for (var i = 0; i < data.length; i++) {        var dataItem = data[i];        var fromCoord = geoCoordMap[dataItem[0].name];        var toCoord = geoCoordMap[dataItem[1].name];        if (fromCoord && toCoord) {            res.push({                fromName: dataItem[0].name,                toName: dataItem[1].name,                coords: [fromCoord, toCoord]            });        }    }    return res;};var color = ['#a6c84c', '#ffa022', '#46bee9'];var series = [];[['北京', BJData], ['上海', SHData], ['广州', GZData]].forEach(function (item, i) {    series.push({            name: item[0] + ' Top10',            type: 'lines',            coordinateSystem: 'bmap',            zlevel: 1,            effect: {                show: true,                period: 6,                trailLength: 0.7,                color: '#fff',                symbolSize: 3            },            lineStyle: {                normal: {                    color: color[i],                    width: 0,                    curveness: 0.2                }            },            data: convertData(item[1])        },        {            name: item[0] + ' Top10',            type: 'lines',            coordinateSystem: 'bmap',            zlevel: 2,            effect: {                show: true,                period: 6,                trailLength: 0,                symbol: planePath,                symbolSize: 15            },            lineStyle: {                normal: {                    color: color[i],                    width: 1,                    opacity: 0.4,                    curveness: 0.2                }            },            data: convertData(item[1])        },        {            name: item[0] + ' Top10',            type: 'effectScatter',            coordinateSystem: 'bmap',            zlevel: 2,            rippleEffect: {                brushType: 'stroke'            },            label: {                normal: {                    show: true,                    position: 'right',                    formatter: '{b}'                }            },            symbolSize: function (val) {                return val[2] / 8;            },            itemStyle: {                normal: {                    color: color[i]                }            },            data: item[1].map(function (dataItem) {                return {                    name: dataItem[1].name,                    value: geoCoordMap[dataItem[1].name].concat([dataItem[1].value])                };            })        });});option = {    backgroundColor: '#404a59',    title : {        text: '模拟迁徙',        subtext: '数据纯属虚构',        left: 'center',        textStyle : {            color: '#fff'        }    },    tooltip : {        trigger: 'item'    },    legend: {        orient: 'vertical',        top: 'bottom',        left: 'right',        data:['北京 Top10', '上海 Top10', '广州 Top10'],        textStyle: {            color: '#fff'        },        selectedMode: 'single'    },    dataRange: {        min: 0,        max: 100,        x: 'right',        calculable: true,        color: ['#ff3333', 'orange', 'yellow', 'lime', 'aqua'],        textStyle: {            color: '#fff'        }    },    bmap: {        center: [115.97, 29.71],        zoom: 5,        roam: true    },    series: series};myChart.setOption(option);</script></body></html>

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