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踩坑ECharts(GL)地理位置散点图

踩坑ECharts(GL)地理位置散点图

作者: 赤色要塞满了 | 来源:发表于2019-05-22 00:29 被阅读0次

    散点图也可以叫做热点图、地理分布图等。

    目标


    画一个地图,上面星星点点的一些表示数据的热点。没想到这么简单的一个事儿,小坑无数,diss下百度。

    基于百度地图的散点图


    也就是scatter与bmap结合。主要参考官网的地理/地图例子,把那个矩形给去掉了。
    先写html,说明见注释。

    <!DOCTYPE html>
    <html lang="en">
    <head>
        <meta charset="UTF-8">
        <!--首先载入jQuery,不然无法使用$-->
        <script src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
    
        <script src="js/scatter-bmap.js"></script>
        <!--引入百度地图的api,这个必须去官网申请下,为了在https网站也能使用,选择了https以及在最后加个&s=1-->
        <script src="https://api.map.baidu.com/api?v=3.0&ak=g46ASxy66TjiPfNqFtaLM4f4OjDhG4tS&s=1"></script>
        <!--引入ECharts-->
        <script src="js/echarts.min.js"></script>
        <!--正文详述-->
        <script src="js/bmap.min.js"></script>
    
        <title>基于百度地图的散点图</title>
    </head>
    <body>
    <div id="scatter-bmap" style="height: 500px;">
    </div>
    </body>
    </html>
    

    首先,ECharts官网已经不提供地图文件直接下载了,只能采用与百度地图结合的形式。

    image.png
    其他都好说,引入bmap.js真是费周折。先从Echarts官网的最下面的扩展百度地图点进去,跳转到github,直接下载使用。
    <script src="js/bmap.js"></script>
    

    控制台报错Uncaught SyntaxError: Unexpected token <,不好使,页面也无法加载地图。然后我又看到github文档这么说:

    image.png
    你倒是告诉我,哪来的min版本?
    后来阴差阳错,在这个地址下载了min版本才可用了。
    js代码没什么好说的,参考了百度地图以及Echarts的官网。
    $(function () {
    
        var mp = new BMap.Map("scatter-bmap");
        mp.centerAndZoom(new BMap.Point(116.3964,39.9093), 10);
        mp.enableScrollWheelZoom();
    
    
        var canvasLayer = new BMap.CanvasLayer({
            update: update
        });
    
        function update() {
            var ctx = this.canvas.getContext("2d");
    
            if (!ctx) {
                return;
            }
    
            ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height);
    
            var temp = {};
            ctx.fillStyle = "rgba(50, 50, 255, 0.7)";
            ctx.beginPath();
            var data = [
                new BMap.Point(116.297047,39.979542),
                new BMap.Point(116.321768,39.88748),
                new BMap.Point(116.494243,39.956539)
            ];
    
            for (var i = 0, len = data.length; i < len; i++) {
                var pixel = mp.pointToPixel(data[i]);
                ctx.fillRect(pixel.x, pixel.y, 30, 30);
            }
        }
        mp.addOverlay(canvasLayer);
    
    
    
        // 初始化echarts示例mapChart
        var mapChart = echarts.init(document.getElementById('scatter-bmap'));
    
        var data = [
            {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}
        ];
    
        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]
        };
    
        var convertData = function (data) {
            var res = [];
            for (var i = 0; i < data.length; i++) {
                var geoCoord = geoCoordMap[data[i].name];
                if (geoCoord) {
                    res.push({
                        name: data[i].name,
                        value: geoCoord.concat(data[i].value)
                    });
                }
            }
            return res;
        };
    
        option = {
            title: {
                text: '全国空气质量',
                subtext: 'data from PM25.in',
                sublink: 'http://www.pm25.in',
                left: 'center',
                textStyle: {
                    color: '#fff'
                }
            },
            tooltip : {
                trigger: 'item'
            },
            bmap: {
                center: [104.114129, 37.550339],
                zoom: 5,
                roam: true,
                mapStyle: {
                    styleJson: [
                        {
                            "featureType": "water",
                            "elementType": "all",
                            "stylers": {
                                "color": "#044161"
                            }
                        },
                        {
                            "featureType": "land",
                            "elementType": "all",
                            "stylers": {
                                "color": "#004981"
                            }
                        },
                        {
                            "featureType": "boundary",
                            "elementType": "geometry",
                            "stylers": {
                                "color": "#064f85"
                            }
                        },
                        {
                            "featureType": "railway",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "highway",
                            "elementType": "geometry",
                            "stylers": {
                                "color": "#004981"
                            }
                        },
                        {
                            "featureType": "highway",
                            "elementType": "geometry.fill",
                            "stylers": {
                                "color": "#005b96",
                                "lightness": 1
                            }
                        },
                        {
                            "featureType": "highway",
                            "elementType": "labels",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "arterial",
                            "elementType": "geometry",
                            "stylers": {
                                "color": "#004981"
                            }
                        },
                        {
                            "featureType": "arterial",
                            "elementType": "geometry.fill",
                            "stylers": {
                                "color": "#00508b"
                            }
                        },
                        {
                            "featureType": "poi",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "green",
                            "elementType": "all",
                            "stylers": {
                                "color": "#056197",
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "subway",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "manmade",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "local",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "arterial",
                            "elementType": "labels",
                            "stylers": {
                                "visibility": "off"
                            }
                        },
                        {
                            "featureType": "boundary",
                            "elementType": "geometry.fill",
                            "stylers": {
                                "color": "#029fd4"
                            }
                        },
                        {
                            "featureType": "building",
                            "elementType": "all",
                            "stylers": {
                                "color": "#1a5787"
                            }
                        },
                        {
                            "featureType": "label",
                            "elementType": "all",
                            "stylers": {
                                "visibility": "off"
                            }
                        }
                    ]
                }
            },
            series : [
                {
                    name: '医院数量',
                    type: 'scatter',
                    coordinateSystem: 'bmap',
                    data: convertData(data),
                    symbolSize: function (val) {
                        return val[2] / 10;
                    },
                    label: {
                        normal: {
                            formatter: '{b}',
                            position: 'right',
                            show: false
                        },
                        emphasis: {
                            show: true
                        }
                    },
                    itemStyle: {
                        normal: {
                            color: '#ddb926'
                        }
                    }
                },
                {
                    name: 'Top 5',
                    type: 'effectScatter',
                    coordinateSystem: 'bmap',
                    data: convertData(data.sort(function (a, b) {
                        return b.value - a.value;
                    }).slice(0, 6)),
                    symbolSize: function (val) {
                        return val[2] / 10;
                    },
                    showEffectOn: 'emphasis',
                    rippleEffect: {
                        brushType: 'stroke'
                    },
                    hoverAnimation: true,
                    label: {
                        normal: {
                            formatter: '{b}',
                            position: 'right',
                            show: true
                        }
                    },
                    itemStyle: {
                        normal: {
                            color: '#f4e925',
                            shadowBlur: 10,
                            shadowColor: '#333'
                        }
                    },
                    zlevel: 1
                }
            ]
        };
    
        mapChart.setOption(option);
    
    
    });
    

    效果见图。


    image.png

    基于地图文件的GL散点图


    也就是scatterGL与map文件结合,主要参考官网这个例子。恶心的是,上一个例子,百度告诉我地图文件不能用了,要跟百度地图结合,然后这个例子还是用的地图文件,就没人好好维护下前后对的上么?只能自己多次尝试踩坑。
    先写html,去除了bmap相关文件,引入了gl库以及地图文件。

    <!DOCTYPE html>
    <html lang="en">
    <head>
        <meta charset="UTF-8">
        <script src="https://code.jquery.com/jquery-3.3.1.min.js"></script>
        <script src="js/scatter-gl.js"></script>
        <script src="js/echarts.min.js"></script>
        <!--引入gl库-->
        <script src="js/echarts-gl.min.js"></script>
        <!--引入中国地图文件-->
        <script src="js/china.js"></script>
    
        <title>基于地图文件的GL散点图</title>
    </head>
    <body>
    <div id="scatter-gl" style="height: 500px;">
    </div>
    </body>
    </html>
    

    地图文件去哪里下载呢?github的这个,我试过,好像是不能用的。阴差阳错的在这个文章里找到一个
    下载了,可用,感恩。
    官网的GL散点图例子的数据采用异步加载一个全世界gps信息什么的数据,有点复杂,自己研究发现,其实数据做出经纬度数值对数组就行了。

    $(function () {
    
        var mapScatter = echarts.init(document.getElementById('scatter-gl'));
        var option =  {
            backgroundColor: '#000',
            title: {
                text: '我的GL散点图',
                left: 'center',
                textStyle: {
                    color: '#fff'
                }
            },
            geo: {
                map: 'china',
                roam: true,
                label: {
                    emphasis: {
                        show: false
                    }
                },
                silent: true,
                itemStyle: {
                    normal: {
                        areaColor: '#323c48',
                        borderColor: '#111'
                    },
                    emphasis: {
                        areaColor: '#2a333d'
                    }
                }
            },
            series: [{
                name: '弱',
                type: 'scatterGL',
                progressive: 1e6,
                coordinateSystem: 'geo',
                symbolSize: 1,
                zoomScale: 0.002,
                blendMode: 'lighter',
                large: true,
                itemStyle: {
                    color: 'rgb(20, 15, 2)'
                },
                postEffect: {
                    enable: true
                },
                silent: true,
                dimensions: ['lng', 'lat'],
                data: [[116.37187, 39.9769], [116.47187, 40.0769], [116.57187, 40.1769], [116.67187, 40.2769], [116.77187, 40.3769], [116.87187, 40.4769], [116.97187, 40.5769], [117.07187, 40.6769], [117.17187, 40.7769], [117.27187, 40.8769], [117.37187, 40.9769], [117.47187, 41.0769], [117.57187, 41.1769], [117.67187, 41.2769], [117.77187, 41.3769], [117.87187, 41.4769], [117.97187, 41.5769], [118.07187, 41.6769], [118.17187, 41.7769], [118.27187, 41.8769], [118.37187, 41.9769], [118.47187, 42.0769], [118.57187, 42.1769], [118.67187, 42.2769], [118.77187, 42.3769], [118.87187, 42.4769], [118.97187, 42.5769], [119.07187, 42.6769], [119.17187, 42.7769], [119.27187, 42.8769], [119.37187, 42.9769], [119.47187, 43.0769], [119.57187, 43.1769], [119.67187, 43.2769], [119.77187, 43.3769], [119.87187, 43.4769], [119.97187, 43.5769], [120.07187, 43.6769], [120.17187, 43.7769], [120.27187, 43.8769], [120.37187, 43.9769], [120.47187, 44.0769], [120.57187, 44.1769], [120.67187, 44.2769], [120.77187, 44.3769], [120.87187, 44.4769], [120.97187, 44.5769], [121.07187, 44.6769], [121.17187, 44.7769], [121.27187, 44.8769], [121.37187, 44.9769], [121.47187, 45.0769], [121.57187, 45.1769], [121.67187, 45.2769], [121.77187, 45.3769], [121.87187, 45.4769], [121.97187, 45.5769], [122.07187, 45.6769], [122.17187, 45.7769], [122.27187, 45.8769], [122.37187, 45.9769], [122.47187, 46.0769], [122.57187, 46.1769], [122.67187, 46.2769], [122.77187, 46.3769], [122.87187, 46.4769], [122.97187, 46.5769], [123.07187, 46.6769], [123.17187, 46.7769], [123.27187, 46.8769], [123.37187, 46.9769], [123.47187, 47.0769], [123.57187, 47.1769], [123.67187, 47.2769], [123.77187, 47.3769], [123.87187, 47.4769], [123.97187, 47.5769], [124.07187, 47.6769], [124.17187, 47.7769], [124.27187, 47.8769], [124.37187, 47.9769], [124.47187, 48.0769], [124.57187, 48.1769], [124.67187, 48.2769], [124.77187, 48.3769], [124.87187, 48.4769], [124.97187, 48.5769], [125.07187, 48.6769], [125.17187, 48.7769], [125.27187, 48.8769], [125.37187, 48.9769], [125.47187, 49.0769], [125.57187, 49.1769], [125.67187, 49.2769], [125.77187, 49.3769], [125.87187, 49.4769], [125.97187, 49.5769], [126.07187, 49.6769], [126.17187, 49.7769], [126.27187, 49.8769]]
    
            }]
        };
    
        mapScatter.setOption(option);
    
    });
    
    

    看散点效果,有一道黄色的斜线,看到了吗?


    image.png

    总结

    • 采用百度地图会调用api、渲染、加载、还有配额等等,有点繁琐。
    • 采用地图文件比较简洁,就是显示的地图信息很少,就一些轮廓。
    • 第一个例子是scatter基于bmap,第二个例子是scatterGL基于map文件;我觉得换一下也是可以的,读者可以尝试。

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          本文标题:踩坑ECharts(GL)地理位置散点图

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