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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。 标签： ECharts3Echarts2模拟迁徙百度地图引入 2016-10-24 16:21 10065人阅

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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。

标签： ECharts3Echarts2模拟迁徙百度地图引入
2016-10-24 16:21 10065人阅读 评论(67) 收藏 举报


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版权声明：本文为博主原创文章，未经博主允许不得转载。

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

___________________________________________________________________________________________________

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

[javascript] view
plain copy

<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。

[javascript] view
plain copy

<script sr
20000
c="echarts.js"></script>

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

[javascript] view
plain copy

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

完整的Demo代码：

[javascript] view
plain copy

<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

[javascript] view
plain copy

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：



[javascript] view
plain copy

<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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