geoLine.html 15 KB

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  1. <html>
  2. <head>
  3. <meta charset='utf-8'>
  4. <script src='esl.js'></script>
  5. <script src='config.js'></script>
  6. <script src='lib/jquery.min.js'></script>
  7. <meta name="viewport" content="width=device-width, initial-scale=1" />
  8. </head>
  9. <body>
  10. <style>
  11. html, body, #main {
  12. width: 100%;
  13. height: 100%;
  14. margin: 0;
  15. }
  16. </style>
  17. <div id='main'></div>
  18. <script>
  19. require([
  20. 'echarts',
  21. 'echarts/chart/lines',
  22. 'echarts/chart/effectScatter',
  23. 'echarts/component/legend',
  24. 'echarts/component/geo'
  25. ], function (echarts) {
  26. var geoCoordMap = {
  27. '上海': [121.4648,31.2891],
  28. '东莞': [113.8953,22.901],
  29. '东营': [118.7073,37.5513],
  30. '中山': [113.4229,22.478],
  31. '临汾': [111.4783,36.1615],
  32. '临沂': [118.3118,35.2936],
  33. '丹东': [124.541,40.4242],
  34. '丽水': [119.5642,28.1854],
  35. '乌鲁木齐': [87.9236,43.5883],
  36. '佛山': [112.8955,23.1097],
  37. '保定': [115.0488,39.0948],
  38. '兰州': [103.5901,36.3043],
  39. '包头': [110.3467,41.4899],
  40. '北京': [116.4551,40.2539],
  41. '北海': [109.314,21.6211],
  42. '南京': [118.8062,31.9208],
  43. '南宁': [108.479,23.1152],
  44. '南昌': [116.0046,28.6633],
  45. '南通': [121.1023,32.1625],
  46. '厦门': [118.1689,24.6478],
  47. '台州': [121.1353,28.6688],
  48. '合肥': [117.29,32.0581],
  49. '呼和浩特': [111.4124,40.4901],
  50. '咸阳': [108.4131,34.8706],
  51. '哈尔滨': [127.9688,45.368],
  52. '唐山': [118.4766,39.6826],
  53. '嘉兴': [120.9155,30.6354],
  54. '大同': [113.7854,39.8035],
  55. '大连': [122.2229,39.4409],
  56. '天津': [117.4219,39.4189],
  57. '太原': [112.3352,37.9413],
  58. '威海': [121.9482,37.1393],
  59. '宁波': [121.5967,29.6466],
  60. '宝鸡': [107.1826,34.3433],
  61. '宿迁': [118.5535,33.7775],
  62. '常州': [119.4543,31.5582],
  63. '广州': [113.5107,23.2196],
  64. '廊坊': [116.521,39.0509],
  65. '延安': [109.1052,36.4252],
  66. '张家口': [115.1477,40.8527],
  67. '徐州': [117.5208,34.3268],
  68. '德州': [116.6858,37.2107],
  69. '惠州': [114.6204,23.1647],
  70. '成都': [103.9526,30.7617],
  71. '扬州': [119.4653,32.8162],
  72. '承德': [117.5757,41.4075],
  73. '拉萨': [91.1865,30.1465],
  74. '无锡': [120.3442,31.5527],
  75. '日照': [119.2786,35.5023],
  76. '昆明': [102.9199,25.4663],
  77. '杭州': [119.5313,29.8773],
  78. '枣庄': [117.323,34.8926],
  79. '柳州': [109.3799,24.9774],
  80. '株洲': [113.5327,27.0319],
  81. '武汉': [114.3896,30.6628],
  82. '汕头': [117.1692,23.3405],
  83. '江门': [112.6318,22.1484],
  84. '沈阳': [123.1238,42.1216],
  85. '沧州': [116.8286,38.2104],
  86. '河源': [114.917,23.9722],
  87. '泉州': [118.3228,25.1147],
  88. '泰安': [117.0264,36.0516],
  89. '泰州': [120.0586,32.5525],
  90. '济南': [117.1582,36.8701],
  91. '济宁': [116.8286,35.3375],
  92. '海口': [110.3893,19.8516],
  93. '淄博': [118.0371,36.6064],
  94. '淮安': [118.927,33.4039],
  95. '深圳': [114.5435,22.5439],
  96. '清远': [112.9175,24.3292],
  97. '温州': [120.498,27.8119],
  98. '渭南': [109.7864,35.0299],
  99. '湖州': [119.8608,30.7782],
  100. '湘潭': [112.5439,27.7075],
  101. '滨州': [117.8174,37.4963],
  102. '潍坊': [119.0918,36.524],
  103. '烟台': [120.7397,37.5128],
  104. '玉溪': [101.9312,23.8898],
  105. '珠海': [113.7305,22.1155],
  106. '盐城': [120.2234,33.5577],
  107. '盘锦': [121.9482,41.0449],
  108. '石家庄': [114.4995,38.1006],
  109. '福州': [119.4543,25.9222],
  110. '秦皇岛': [119.2126,40.0232],
  111. '绍兴': [120.564,29.7565],
  112. '聊城': [115.9167,36.4032],
  113. '肇庆': [112.1265,23.5822],
  114. '舟山': [122.2559,30.2234],
  115. '苏州': [120.6519,31.3989],
  116. '莱芜': [117.6526,36.2714],
  117. '菏泽': [115.6201,35.2057],
  118. '营口': [122.4316,40.4297],
  119. '葫芦岛': [120.1575,40.578],
  120. '衡水': [115.8838,37.7161],
  121. '衢州': [118.6853,28.8666],
  122. '西宁': [101.4038,36.8207],
  123. '西安': [109.1162,34.2004],
  124. '贵阳': [106.6992,26.7682],
  125. '连云港': [119.1248,34.552],
  126. '邢台': [114.8071,37.2821],
  127. '邯郸': [114.4775,36.535],
  128. '郑州': [113.4668,34.6234],
  129. '鄂尔多斯': [108.9734,39.2487],
  130. '重庆': [107.7539,30.1904],
  131. '金华': [120.0037,29.1028],
  132. '铜川': [109.0393,35.1947],
  133. '银川': [106.3586,38.1775],
  134. '镇江': [119.4763,31.9702],
  135. '长春': [125.8154,44.2584],
  136. '长沙': [113.0823,28.2568],
  137. '长治': [112.8625,36.4746],
  138. '阳泉': [113.4778,38.0951],
  139. '青岛': [120.4651,36.3373],
  140. '韶关': [113.7964,24.7028]
  141. };
  142. var BJData = [
  143. [{name:'北京'}, {name:'上海',value:95}],
  144. [{name:'北京'}, {name:'广州',value:90}],
  145. [{name:'北京'}, {name:'大连',value:80}],
  146. [{name:'北京'}, {name:'南宁',value:70}],
  147. [{name:'北京'}, {name:'南昌',value:60}],
  148. [{name:'北京'}, {name:'拉萨',value:50}],
  149. [{name:'北京'}, {name:'长春',value:40}],
  150. [{name:'北京'}, {name:'包头',value:30}],
  151. [{name:'北京'}, {name:'重庆',value:20}],
  152. [{name:'北京'}, {name:'常州',value:10}]
  153. ];
  154. var SHData = [
  155. [{name:'上海'},{name:'包头',value:95}],
  156. [{name:'上海'},{name:'昆明',value:90}],
  157. [{name:'上海'},{name:'广州',value:80}],
  158. [{name:'上海'},{name:'郑州',value:70}],
  159. [{name:'上海'},{name:'长春',value:60}],
  160. [{name:'上海'},{name:'重庆',value:50}],
  161. [{name:'上海'},{name:'长沙',value:40}],
  162. [{name:'上海'},{name:'北京',value:30}],
  163. [{name:'上海'},{name:'丹东',value:20}],
  164. [{name:'上海'},{name:'大连',value:10}]
  165. ];
  166. var GZData = [
  167. [{name:'广州'},{name:'福州',value:95}],
  168. [{name:'广州'},{name:'太原',value:90}],
  169. [{name:'广州'},{name:'长春',value:80}],
  170. [{name:'广州'},{name:'重庆',value:70}],
  171. [{name:'广州'},{name:'西安',value:60}],
  172. [{name:'广州'},{name:'成都',value:50}],
  173. [{name:'广州'},{name:'常州',value:40}],
  174. [{name:'广州'},{name:'北京',value:30}],
  175. [{name:'广州'},{name:'北海',value:20}],
  176. [{name:'广州'},{name:'海口',value:10}]
  177. ];
  178. 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';
  179. var convertData = function (data) {
  180. var res = [];
  181. for (var i = 0; i < data.length; i++) {
  182. var dataItem = data[i];
  183. var fromCoord = geoCoordMap[dataItem[0].name];
  184. var toCoord = geoCoordMap[dataItem[1].name];
  185. if (fromCoord && toCoord) {
  186. res.push([{
  187. coord: fromCoord
  188. }, {
  189. coord: toCoord
  190. }]);
  191. }
  192. }
  193. return res;
  194. };
  195. $.get('../map/json/china.json', function (chinaJson) {
  196. echarts.registerMap('china', chinaJson);
  197. var myChart = echarts.init(document.getElementById('main'));
  198. var color = ['#a6c84c', '#ffa022', '#46bee9'];
  199. var series = [];
  200. [['北京', BJData], ['上海', SHData], ['广州', GZData]].forEach(function (item, i) {
  201. series.push({
  202. name: item[0] + ' Top10',
  203. type: 'lines',
  204. zlevel: 1,
  205. effect: {
  206. show: true,
  207. period: 6,
  208. trailLength: 0.7,
  209. color: '#fff',
  210. symbolSize: 2
  211. },
  212. lineStyle: {
  213. normal: {
  214. color: color[i],
  215. width: 0,
  216. curveness: 0.2
  217. }
  218. },
  219. data: convertData(item[1])
  220. },
  221. {
  222. name: item[0] + ' Top10',
  223. type: 'lines',
  224. zlevel: 2,
  225. effect: {
  226. show: true,
  227. period: 6,
  228. trailLength: 0,
  229. symbol: planePath,
  230. symbolSize: 20
  231. },
  232. lineStyle: {
  233. normal: {
  234. color: color[i],
  235. width: 1,
  236. opacity: 0.4,
  237. curveness: 0.2
  238. }
  239. },
  240. data: convertData(item[1])
  241. },
  242. {
  243. name: item[0] + ' Top10',
  244. type: 'effectScatter',
  245. coordinateSystem: 'geo',
  246. zlevel: 2,
  247. rippleEffect: {
  248. brushType: 'stroke'
  249. },
  250. label: {
  251. normal: {
  252. show: true,
  253. position: 'right',
  254. formatter: '{b}'
  255. }
  256. },
  257. symbolSize: function (val) {
  258. return val[2] / 8;
  259. },
  260. itemStyle: {
  261. normal: {
  262. color: color[i]
  263. }
  264. },
  265. data: item[1].map(function (dataItem) {
  266. return {
  267. name: dataItem[1].name,
  268. value: geoCoordMap[dataItem[1].name].concat([dataItem[1].value])
  269. };
  270. })
  271. });
  272. });
  273. myChart.setOption({
  274. backgroundColor: '#404a59',
  275. title: {
  276. text: '全国主要城市空气质量',
  277. subtext: 'data from PM25.in',
  278. sublink: 'http://www.pm25.in',
  279. left: 'center',
  280. textStyle: {
  281. color: '#fff'
  282. }
  283. },
  284. tooltip : {
  285. trigger: 'item'
  286. },
  287. legend: {
  288. orient: 'vertical',
  289. top: 'bottom',
  290. left: 'right',
  291. data:['北京 Top10', '上海 Top10', '广州 Top10'],
  292. textStyle: {
  293. color: '#fff'
  294. },
  295. selectedMode: 'single'
  296. },
  297. geo: {
  298. map: 'china',
  299. label: {
  300. emphasis: {
  301. show: false
  302. }
  303. },
  304. roam: true,
  305. itemStyle: {
  306. normal: {
  307. areaColor: '#323c48',
  308. borderColor: '#404a59'
  309. },
  310. emphasis: {
  311. areaColor: '#2a333d'
  312. }
  313. }
  314. },
  315. series: series
  316. });
  317. });
  318. });
  319. </script>
  320. </body>
  321. </html>