openlayers6结合echarts4实现迁徙图
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效果图如下：
参考GitHub来实现的，更详细的源码以及参数说明见：GitHub
- 本篇文章的html源码：
<!DOCTYPE html> <html> <head> <title>openlayers6结合echarts4实现迁徙图</title> <link rel="stylesheet" href="lib/ol.css"> <script src="lib/ol.js"></script> <script src="lib/echarts.js"></script> <script src="lib/ol-echarts.js"></script> <!--<script src="https://cdn.jsdelivr.net/npm/echarts/dist/echarts.js"></script> <script src="https://unpkg.com/ol-echarts/dist/ol-echarts.js"></script>--> <style> html, body, #map { height: 100%; margin: 0; padding: 0; } </style> </head> <body> <div id="map"></div> <script> /** * 地图创建初始化 */ var map = new ol.Map({ target: ‘map‘, layers: [ new ol.layer.Tile({ source: new ol.source.XYZ({ url: ‘http://cache1.arcgisonline.cn/arcgis/rest/services/ChinaOnline‘ + ‘StreetPurplishBlue/MapServer/tile/{z}/{y}/{x}‘ }) }) ], view: new ol.View({ center: [116.55406673632812, 39.94828066015626], projection: ‘EPSG:4326‘, zoom: 10 }) }); //迁徙图图层初始化 var echartslayer = new EChartsLayer(getOption()); echartslayer.appendTo(map) function getOption () { var geoCoordMap = { ‘上海‘: [121.4648, 31.2891], ‘东莞‘: [113.8953, 22.901], ‘东营‘: [118.7073, 37.5513], ‘中山‘: [113.4229, 22.478], ‘临汾‘: [111.4783, 36.1615], ‘临沂‘: [118.3118, 35.2936], ‘丹东‘: [124.541, 40.4242], ‘丽水‘: [119.5642, 28.1854], ‘乌鲁木齐‘: [87.9236, 43.5883], ‘佛山‘: [112.8955, 23.1097], ‘保定‘: [115.0488, 39.0948], ‘兰州‘: [103.5901, 36.3043], ‘包头‘: [110.3467, 41.4899], ‘北京‘: [116.4551, 40.2539], ‘北海‘: [109.314, 21.6211], ‘南京‘: [118.8062, 31.9208], ‘南宁‘: [108.479, 23.1152], ‘南昌‘: [116.0046, 28.6633], ‘南通‘: [121.1023, 32.1625], ‘厦门‘: [118.1689, 24.6478], ‘台州‘: [121.1353, 28.6688], ‘合肥‘: [117.29, 32.0581], ‘呼和浩特‘: [111.4124, 40.4901], ‘咸阳‘: [108.4131, 34.8706], ‘哈尔滨‘: [127.9688, 45.368], ‘唐山‘: [118.4766, 39.6826], ‘嘉兴‘: [120.9155, 30.6354], ‘大同‘: [113.7854, 39.8035], ‘大连‘: [122.2229, 39.4409], ‘天津‘: [117.4219, 39.4189], ‘太原‘: [112.3352, 37.9413], ‘威海‘: [121.9482, 37.1393], ‘宁波‘: [121.5967, 29.6466], ‘宝鸡‘: [107.1826, 34.3433], ‘宿迁‘: [118.5535, 33.7775], ‘常州‘: [119.4543, 31.5582], ‘广州‘: [113.5107, 23.2196], ‘廊坊‘: [116.521, 39.0509], ‘延安‘: [109.1052, 36.4252], ‘张家口‘: [115.1477, 40.8527], ‘徐州‘: [117.5208, 34.3268], ‘德州‘: [116.6858, 37.2107], ‘惠州‘: [114.6204, 23.1647], ‘成都‘: [103.9526, 30.7617], ‘扬州‘: [119.4653, 32.8162], ‘承德‘: [117.5757, 41.4075], ‘拉萨‘: [91.1865, 30.1465], ‘无锡‘: [120.3442, 31.5527], ‘日照‘: [119.2786, 35.5023], ‘昆明‘: [102.9199, 25.4663], ‘杭州‘: [119.5313, 29.8773], ‘枣庄‘: [117.323, 34.8926], ‘柳州‘: [109.3799, 24.9774], ‘株洲‘: [113.5327, 27.0319], ‘武汉‘: [114.3896, 30.6628], ‘汕头‘: [117.1692, 23.3405], ‘江门‘: [112.6318, 22.1484], ‘沈阳‘: [123.1238, 42.1216], ‘沧州‘: [116.8286, 38.2104], ‘河源‘: [114.917, 23.9722], ‘泉州‘: [118.3228, 25.1147], ‘泰安‘: [117.0264, 36.0516], ‘泰州‘: [120.0586, 32.5525], ‘济南‘: [117.1582, 36.8701], ‘济宁‘: [116.8286, 35.3375], ‘海口‘: [110.3893, 19.8516], ‘淄博‘: [118.0371, 36.6064], ‘淮安‘: [118.927, 33.4039], ‘深圳‘: [114.5435, 22.5439], ‘清远‘: [112.9175, 24.3292], ‘温州‘: [120.498, 27.8119], ‘渭南‘: [109.7864, 35.0299], ‘湖州‘: [119.8608, 30.7782], ‘湘潭‘: [112.5439, 27.7075], ‘滨州‘: [117.8174, 37.4963], ‘潍坊‘: [119.0918, 36.524], ‘烟台‘: [120.7397, 37.5128], ‘玉溪‘: [101.9312, 23.8898], ‘珠海‘: [113.7305, 22.1155], ‘盐城‘: [120.2234, 33.5577], ‘盘锦‘: [121.9482, 41.0449], ‘石家庄‘: [114.4995, 38.1006], ‘福州‘: [119.4543, 25.9222], ‘秦皇岛‘: [119.2126, 40.0232], ‘绍兴‘: [120.564, 29.7565], ‘聊城‘: [115.9167, 36.4032], ‘肇庆‘: [112.1265, 23.5822], ‘舟山‘: [122.2559, 30.2234], ‘苏州‘: [120.6519, 31.3989], ‘莱芜‘: [117.6526, 36.2714], ‘菏泽‘: [115.6201, 35.2057], ‘营口‘: [122.4316, 40.4297], ‘葫芦岛‘: [120.1575, 40.578], ‘衡水‘: [115.8838, 37.7161], ‘衢州‘: [118.6853, 28.8666], ‘西宁‘: [101.4038, 36.8207], ‘西安‘: [109.1162, 34.2004], ‘贵阳‘: [106.6992, 26.7682], ‘连云港‘: [119.1248, 34.552], ‘邢台‘: [114.8071, 37.2821], ‘邯郸‘: [114.4775, 36.535], ‘郑州‘: [113.4668, 34.6234], ‘鄂尔多斯‘: [108.9734, 39.2487], ‘重庆‘: [107.7539, 30.1904], ‘金华‘: [120.0037, 29.1028], ‘铜川‘: [109.0393, 35.1947], ‘银川‘: [106.3586, 38.1775], ‘镇江‘: [119.4763, 31.9702], ‘长春‘: [125.8154, 44.2584], ‘长沙‘: [113.0823, 28.2568], ‘长治‘: [112.8625, 36.4746], ‘阳泉‘: [113.4778, 38.0951], ‘青岛‘: [120.4651, 36.3373], ‘韶关‘: [113.7964, 24.7028] }; var BJData = [ [{name: ‘北京‘}, {name: ‘上海‘, value: 95}], [{name: ‘北京‘}, {name: ‘广州‘, value: 90}], [{name: ‘北京‘}, {name: ‘大连‘, value: 80}], [{name: ‘北京‘}, {name: ‘南宁‘, value: 70}], [{name: ‘北京‘}, {name: ‘南昌‘, value: 60}], [{name: ‘北京‘}, {name: ‘拉萨‘, value: 50}], [{name: ‘北京‘}, {name: ‘长春‘, value: 40}], [{name: ‘北京‘}, {name: ‘包头‘, value: 30}], [{name: ‘北京‘}, {name: ‘重庆‘, value: 20}], [{name: ‘北京‘}, {name: ‘常州‘, value: 10}] ]; var SHData = [ [{name: ‘上海‘}, {name: ‘包头‘, value: 95}], [{name: ‘上海‘}, {name: ‘昆明‘, value: 90}], [{name: ‘上海‘}, {name: ‘广州‘, value: 80}], [{name: ‘上海‘}, {name: ‘郑州‘, value: 70}], [{name: ‘上海‘}, {name: ‘长春‘, value: 60}], [{name: ‘上海‘}, {name: ‘重庆‘, value: 50}], [{name: ‘上海‘}, {name: ‘长沙‘, value: 40}], [{name: ‘上海‘}, {name: ‘北京‘, value: 30}], [{name: ‘上海‘}, {name: ‘丹东‘, value: 20}], [{name: ‘上海‘}, {name: ‘大连‘, value: 10}] ]; var GZData = [ [{name: ‘广州‘}, {name: ‘福州‘, value: 95}], [{name: ‘广州‘}, {name: ‘太原‘, value: 90}], [{name: ‘广州‘}, {name: ‘长春‘, value: 80}], [{name: ‘广州‘}, {name: ‘重庆‘, value: 70}], [{name: ‘广州‘}, {name: ‘西安‘, value: 60}], [{name: ‘广州‘}, {name: ‘成都‘, value: 50}], [{name: ‘广州‘}, {name: ‘常州‘, value: 40}], [{name: ‘广州‘}, {name: ‘北京‘, value: 30}], [{name: ‘广州‘}, {name: ‘北海‘, value: 20}], [{name: ‘广州‘}, {name: ‘海口‘, value: 10}] ]; var planePath = ‘path://M1705.06,1318.313v-89.254l-319.9-221.799l0.073-208.063c0.521-84.662-26.629-121.796-63.961-121.491c-37.332-0.305-64.482,36.829-63.961,121.491l0.073,208.063l-319.9,221.799v89.254l330.343-157.288l12.238,241.308l-134.449,92.931l0.531,42.034l175.125-42.917l175.125,42.917l0.531-42.034l-134.449-92.931l12.238-241.308L1705.06,1318.313z‘; var convertData = function (data) { var res = []; for (var i = 0; i < data.length; i++) { var dataItem = data[i]; var fromCoord = geoCoordMap[dataItem[0].name]; var toCoord = geoCoordMap[dataItem[1].name]; if (fromCoord && toCoord) { res.push({ fromName: dataItem[0].name, toName: dataItem[1].name, coords: [fromCoord, toCoord] }); } } return res; }; var color = [‘#a6c84c‘, ‘#ffa022‘, ‘#46bee9‘]; var series = []; [ [‘北京‘, BJData], [‘上海‘, SHData], [‘广州‘, GZData]].forEach( function (item, i) { series.push({ name: item[0] + ‘ Top10‘, type: ‘lines‘, zlevel: 1, effect: { show: true, period: 6, trailLength: 0.7, color: ‘#fff‘, symbolSize: 3 }, lineStyle: { normal: { color: color[i], width: 0, curveness: 0.2 } }, data: convertData(item[1]) }, { name: item[0] + ‘ Top10‘, type: ‘lines‘, zlevel: 2, effect: { show: true, period: 6, trailLength: 0, symbol: planePath, symbolSize: 15 }, lineStyle: { normal: { color: color[i], width: 1, opacity: 0.4, curveness: 0.2 } }, data: convertData(item[1]) }, { name: item[0] + ‘ Top10‘, type: ‘effectScatter‘, coordinateSystem: ‘geo‘, zlevel: 2, rippleEffect: { brushType: ‘stroke‘ }, label: { normal: { show: true, position: ‘right‘, formatter: ‘{b}‘ } }, symbolSize: function (val) { return val[2] / 8; }, itemStyle: { normal: { color: color[i] } }, data: item[1].map(function (dataItem) { return { name: dataItem[1].name, value: geoCoordMap[dataItem[1].name].concat([dataItem[1].value]) }; }) }); }); return { tooltip: { trigger: ‘item‘ }, /*title: { text: ‘模拟迁徙图‘, subtext: ‘‘, left: ‘center‘, textStyle: { color: ‘#fff‘ } },*/ series: series }; } </script> </body> </html>
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