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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