03 【ArcGIS JS API + eCharts系列】实现二、三维散点图的绘制

概述

上一篇文章中我们介绍了如何使用ArcGIS JS API和eCharts结合，在二维和三维场景下绘制迁徙图。这篇文章我们来介绍下如何在二维和三维场景下绘制散点图，其实散点图跟迁徙图一样，它的绘制也跟地理坐标系有关，所以实现思路跟迁徙图的绘制是一样的，我们来看下最终效果：

实现思路

迁徙图、散点图这种图表跟地理坐标关系紧密，所以仅仅通过二维普通图表绘制的方式是无法实现这类图表绘制的，所以就需要我们来扩展eCharts的相关功能，使其能够够结合最新版的ArcGIS JS API来完成地图上这类图表的绘制，eCharts官网也提供了相应的扩展插件，但这种插件并不能很好地支持我们ArcGIS JS API的高版本，所以我们在这篇文章里直接扩展了一个图层类，下面是具体的实现思路：

实现ArcGIS JS API和eCharts的结合，最最关键的是要实现两个插件库里的坐标系转换，这是重点，只要搞清楚了这一点，我们完全可以脱离地图API库的束缚，理论上可以实现eCharts跟任意地图库的结合。在此处转换坐标时我们使用了eCharts提供的registerCoordinateSystem方法，通过这个方法我们注册了一个名为"arcgis"的坐标系，里面对eCharts中的dataToPoint、pointToData等方法进行了重写，然后将这些所有内容封装为了一个EchartsLayer图层类。至于这个文件的源码，文章结尾会提供，接下来我们看一下具体的实现步骤。

实现步骤

1、本文所用的demo同样是基于React框架搭建的，所以我们首先基于React框架搭建一个初始化项目，然后改写src目录下的App.js这个主文件，实例化出一张二维地图，这中间用到了esri-loader插件，具体的实现过程可查看我的这篇文章【【番外】 React中使用ArcGIS JS API 4.14开发】，里面有具体的实现步骤。

2、通过上述操作实例化完一张二维地图后，我们接下来就要进行散点图的绘制操作了，在开始之前我们需要一些数据，首先是散点图中所要用到的各个城市坐标，我在此处将它们单独抽出来作为一个js文件，源文件如下：

let 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]
};export default geoCoordMap;

除了上述的城市坐标之外，我们还需要一份跟城市坐标相对应的权重数据，用来表示某个指标在各个城市的值，同样的是一份单独的js文件，源代码如下：

let dataValue = [{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}
];export default dataValue;

3、完成了以上操作之后，我们接下来就要进行散点图的配置信息初始化，在此处其实就是实例化series这个属性，代码如下：

    //初始化图表参数_initCharts=() => {const _self = this;_self.state.series = [{name: 'pm2.5',type: 'scatter',coordinateSystem: 'arcgis',data: _self._convertData(dataValue),symbolSize: function (val) {return val[2] / 10;},label: {formatter: '{b}',position: 'right',show: false},itemStyle: {color: '#00FFFF'},emphasis: {label: {show: true}}},{name: 'Top 5',type: 'effectScatter',coordinateSystem: 'arcgis',data: _self._convertData(dataValue.sort(function (a, b) {return b.value - a.value;}).slice(0, 6)),symbolSize: function (val) {return val[2] / 10;},showEffectOn: 'render',rippleEffect: {brushType: 'stroke'},hoverAnimation: true,label: {formatter: '{b}',position: 'right',show: true},itemStyle: {color: '#00FFFF',shadowBlur: 10,shadowColor: '#333'},zlevel: 1}];}

上述代码中用到了数据转换这个方法，代码如下：

    _convertData=(data) => {let res = [];for (let i = 0; i < data.length; i++) {let geoCoord = geoCoordMap[data[i].name];if (geoCoord) {res.push({name: data[i].name,value: geoCoord.concat(data[i].value)});}}return res;}

4、图表信息初始化之后，接下来监听地图的绘制完成事件，然后调用绘制图表函数来进行图表的绘制，代码如下：

view.when(function() {_self.state.mapview = view;_self._drawCharts();
});

    //绘制图表_drawCharts=() => {const _self = this;const options = {url: 'https://js.arcgis.com/4.14/dojo/dojo.js',};loadModules(['http://localhost/test/EchartsLayer.min.js'], options).then(([echartsLayer]) => {console.log(_self.state.mapview)//_self.state.mapview.when(function(){let chart = new echartsLayer(_self.state.mapview);let option = {title: {text: 'ArcGIS API for Javascript4.14扩展Echarts4之散点图',subtext: 'Develop By X北辰北',left: 'center',textStyle: {color: '#fff'}},series: _self.state.series};chart.setChartOption(option);//});}).catch((err) => {console.log('图表绘制失败，' + err);});}

5、通过以上操作过程就实现了散点图的绘制，如果需要绘制三维场景下的散点图，只需要将mapview更改为sceneview即可。

总结

本文在上一篇文章的基础之上跟大家介绍了一下使用ArcGIS JS API和eCharts来绘制二维和三维场景下的散点图的过程，为了便于代码组织，这篇文章中的代码是在src目录下新建了一个scatterDiagram的组件，如果大家觉得麻烦，可将此组件中的代码直接拷贝到App.js文件里进行学习和参考，中间没有任何问题。

附：

散点图绘制全部源码：

import React,{Component} from 'react';
import {loadModules} from 'esri-loader';
import './scatterDiagram.css';import dataValue from './data/dataValue';
import geoCoordMap from './data/geoCoordMap';class ScatterDiagram extends Component {state = {series: null,mapview: null,}componentDidMount=() => {this._initMapView();this._initCharts();}//实例化地图_initMapView=() => {const _self = this;const options = {url: 'https://js.arcgis.com/4.14/',css: 'https://js.arcgis.com/4.14/esri/themes/light/main.css'};loadModules(['esri/Map','esri/Basemap','esri/layers/TileLayer','esri/views/MapView','esri/views/SceneView',], options).then(([Map, Basemap,TileLayer,MapView,SceneView,]) => {let basemap = new Basemap({baseLayers: [new TileLayer({url: "http://map.geoq.cn/arcgis/rest/services/ChinaOnlineStreetPurplishBlue/MapServer",title: "Basemap"})],title: "basemap",id: "basemap"});let map = new Map({basemap: basemap});let view = new MapView({container: "mapview", map: map, zoom: 5, center: [107.246152,34.414465] });// let view = new SceneView({//     container: "mapview", //     map: map, //     scale: 50000000, //     center: [107.246152,34.414465] // });view.when(function() {_self.state.mapview = view;_self._drawCharts();});}).catch((err) => {console.log('底图创建失败，' + err);});}//初始化图表参数_initCharts=() => {const _self = this;_self.state.series = [{name: 'pm2.5',type: 'scatter',coordinateSystem: 'arcgis',data: _self._convertData(dataValue),symbolSize: function (val) {return val[2] / 10;},label: {formatter: '{b}',position: 'right',show: false},itemStyle: {color: '#00FFFF'},emphasis: {label: {show: true}}},{name: 'Top 5',type: 'effectScatter',coordinateSystem: 'arcgis',data: _self._convertData(dataValue.sort(function (a, b) {return b.value - a.value;}).slice(0, 6)),symbolSize: function (val) {return val[2] / 10;},showEffectOn: 'render',rippleEffect: {brushType: 'stroke'},hoverAnimation: true,label: {formatter: '{b}',position: 'right',show: true},itemStyle: {color: '#00FFFF',shadowBlur: 10,shadowColor: '#333'},zlevel: 1}];}_convertData=(data) => {let res = [];for (let i = 0; i < data.length; i++) {let geoCoord = geoCoordMap[data[i].name];if (geoCoord) {res.push({name: data[i].name,value: geoCoord.concat(data[i].value)});}}return res;}//绘制图表_drawCharts=() => {const _self = this;const options = {url: 'https://js.arcgis.com/4.14/dojo/dojo.js',};loadModules(['http://localhost/test/EchartsLayer.min.js'], options).then(([echartsLayer]) => {console.log(_self.state.mapview)//_self.state.mapview.when(function(){let chart = new echartsLayer(_self.state.mapview);let option = {title: {text: 'ArcGIS API for Javascript4.14扩展Echarts4之散点图',subtext: 'Develop By X北辰北',left: 'center',textStyle: {color: '#fff'}},series: _self.state.series};chart.setChartOption(option);//});}).catch((err) => {console.log('图表绘制失败，' + err);});}render() {return (<div id="mapview"></div>)}
}export default  ScatterDiagram;

EchartsLayer.min.js源码：

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