Echarts使用一：在地图上将特定城市显示高亮

来源：互联网发布：ubuntu sudo反应很慢编辑：程序博客网时间：2024/04/30 07:10

最近项目要使用echarts进行数据可视化。主要用到中国和各省市地图，第一次用也是遇到了很多问题，在这里记录一下，方便以后回顾。
首先将第一个需求说一下，就是根据传入的一条数据在地图上将两个城市连线并显示高亮。在介绍代码之前先说一下echarts的一个大致流程。以地图为例：
1，标签里面一般会将要使用到的js文件引入进来，这里的js文件可以是在线的，比如说下面例子中所使用的链接；也可以是本地的，也就是把echarts官网提供的文件下载下来，把本机文件存储路径写上也是可以的，目的就是把地图要使用到的数据导入进来。
2，进入body之后会为地图生成一个div，用于放置所生成的地图。就是下面这句话：

var myChart = echarts.init(document.getElementById('main'));

3，为要生成的地图配置参数，这里也是最重要的部分，要按照自己的需求生成想要的地图就要定制自己的option，这部分就要自己去深入了解了。
4，把参数传入之前定义的myChart变量，把地图显示出来。
myChart.setOption(option);
恩，一个最简的流程就是这样，我这个demo本来是要连接数据库查询数据的，但是这里为了简单就定义一个数据然后循环读取。

<!DOCTYPE html><html><head>    <meta charset="utf-8">    <title>echarts使用一</title><link rel="stylesheet" href="../css/main.css" type="text/css"/>    <!-- 引入 echarts.js --><script type="text/javascript" src="http://echarts.baidu.com/gallery/vendors/echarts/echarts-all-3.js"></script>       <script type="text/javascript" src="http://echarts.baidu.com/gallery/vendors/echarts/extension/dataTool.min.js"></script>       <script type="text/javascript" src="http://echarts.baidu.com/gallery/vendors/echarts/map/js/china.js"></script>       <script type="text/javascript" src="http://echarts.baidu.com/gallery/vendors/echarts/map/js/world.js"></script>       <script type="text/javascript" src="http://api.map.baidu.com/api?v=2.0&ak=ZUONbpqGBsYGXNIYHicvbAbM"></script>       <script type="text/javascript" src="http://echarts.baidu.com/gallery/vendors/echarts/extension/bmap.min.js"></script></head><body>    <!-- 为ECharts准备一个具备大小（宽高）的Dom -->    <div id="main" style="width: 600px;height:400px;"></div>    <script type="text/javascript">    // 基于准备好的dom，初始化echarts实例    var myChart = echarts.init(document.getElementById('main'));    var data = [         {name: '广州', value: '北京'}    ];    //这里记录每个城市的坐标信息（不全）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]};//根据data得到每个data中城市的坐标var convertData = function (data) {    var res = [];    for (var i = 0; i < data.length; i++) {        var fromCoord = geoCoordMap[data[i].name];//获取城市的坐标 source        var toCoord = geoCoordMap[data[i].value];//获取城市的坐标 destination        if (fromCoord && toCoord) {            res.push({                fromName: data[i].name,                toName: data[i].value,                coords: [fromCoord, toCoord]            });        }    }    return res;};//根据data得到放射光标效果图。如果起始城市没有值的话，就只显示目的城市var convertData1 = function (data) {    var res = [];    for (var i = 0; i < data.length; i++) {        var geoCoord = geoCoordMap[data[i].name];        var geoCoord1 = geoCoordMap[data[i].value];        if (geoCoord)         {            res.push({                name: data[i].name,                value: geoCoord.concat(data[i].value)            });        }        if(geoCoord1)        {            res.push({                name: data[i].value,                value: geoCoord1.concat(data[i].name)            })        }    }    return res;};//设置一些可选的参数option = {    //设置背景颜色    backgroundColor: '#f3f3f3',    //设置图片标题、子标题、文本颜色等等    title: {        text: 'echarts使用1',        subtext: 'made by 刘冲',        left: 'center',        textStyle: {            color: '#000'        }    },    tooltip : {        trigger: 'item'    },    geo: {        map: 'china',        label: {            emphasis: {                show: true            }        },        //是否可以点击鼠标、滚轮缩放        roam: true,    },    //series就是要绘制的地图的主体。是一个数组，也就是说可以有多个数据进行绘制。这里有两个，一个是两个城市的连线，一个是对两个城市进行高亮显示。其中的type是很重要的参数，主要有饼图、条形图、线、地图等等。具体的可以去参考官网上的配置手册。    series :     [        {            name: 'rode',            type: 'lines',            coordinateSystem: 'geo',            data: convertData(data),            effect: {                show: true,                period: 6,                trailLength: 0,            },            lineStyle: {                normal: {                    color: '#389BB7',                    width: 1,                    opacity: 0.4,                    curveness: 0.2                }            }        },        {            name: 'city',            type: 'effectScatter',            coordinateSystem: 'geo',            rippleEffect: {                brushType: 'stroke'            },            label: {                normal: {                    show: true,                    position: 'right',                    formatter: '{b}'                }            },            symbolSize: 8,            itemStyle: {                normal: {                    color: '#389BB7'                }            },            data: convertData1(data)        },    ]};        // 使用刚指定的配置项和数据显示图表。        myChart.setOption(option);//定义数据var dataArray=new Array();dataArray[0]=[{name:'上海',value:'广州'}];dataArray[1]=[{name:'上海',value:'北京'}];dataArray[2]=[{value:'深圳'}];dataArray[3]=[{name:'上海',value:'天津'}];dataArray[4]=[{name:'上海',value:'唐山'}];var globalIndex=0;//一直要执行的函数function nocease(){    //随机取1-5    data=dataArray[globalIndex%5];    globalIndex++;    var option = myChart.getOption();    if(data[0].name)    {    option.series[0].data = convertData(data);    option.series[1].data = convertData1(data);    }    else{    option.series[0].data = null;    option.series[1].data = convertData1(data);     }    myChart.setOption(option);}setInterval("nocease()","2000");</script></body></html>

好了，代码介绍完毕，那就看一下效果图，
这里写图片描述
恩，还是挺好看的吧。

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