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

小咪咪 2023-07-18 14:19 80阅读 0赞

### 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：

![2020032909534298.gif][]

![20200329095439363.gif][]

### 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][React_ArcGIS JS API 4.14]】，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：

[2020032909534298.gif]: /images/20230528/c7b9b485e16943e6b743b463cda800e6.png
[20200329095439363.gif]: /images/20230528/b3c16a68af4e4274a0e0eb35d91add5d.png
[React_ArcGIS JS API 4.14]: https://xuqwblog.blog.csdn.net/article/details/104003426