area_echarts.js 11 KB

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  1. /*大屏*/
  2. $.getJSON('js/map.json', function(data){
  3. $.each(data, function (infoIndex, info){
  4. var city = info.children;
  5. for(var i =0;i<city.length;i++){
  6. var citydetail = new Array();
  7. var name = city[i].name;
  8. geoCoordMap[name]= citydetail;
  9. var lat = parseFloat(city[i].lat);
  10. var log = parseFloat(city[i].log);
  11. citydetail.push(log);
  12. citydetail.push(lat);
  13. }
  14. })
  15. map_1_option.series[0].data = convertData(data2.sort(function (a, b) {
  16. return b.value - a.value;
  17. })),
  18. /* }).slice(0, 6)),
  19. */ map_1.setOption(map_1_option);
  20. });
  21. var geoCoordMap = {
  22. };
  23. var data2 = [
  24. {name: '商丘', value: 9},
  25. {name: '鄂尔多斯', value: 12},
  26. {name: '招远', value: 12},
  27. {name: '舟山', value: 12},
  28. {name: '齐齐哈尔', value: 14},
  29. {name: '盐城', value: 15},
  30. {name: '赤峰', value: 16},
  31. {name: '青岛', value: 18},
  32. {name: '乳山', value: 18},
  33. {name: '金昌', value: 19},
  34. {name: '泉州', value: 21},
  35. {name: '莱西', value: 21},
  36. {name: '日照', value: 21},
  37. {name: '胶南', value: 22},
  38. {name: '南通', value: 23},
  39. {name: '拉萨', value: 24},
  40. {name: '云浮', value: 24},
  41. {name: '梅州', value: 25},
  42. {name: '文登', value: 25},
  43. {name: '上海', value: 25},
  44. {name: '攀枝花', value: 25},
  45. {name: '威海', value: 25},
  46. {name: '承德', value: 25},
  47. {name: '厦门', value: 26},
  48. {name: '汕尾', value: 26},
  49. {name: '潮州', value: 26},
  50. {name: '丹东', value: 27},
  51. {name: '太仓', value: 27},
  52. {name: '曲靖', value: 27},
  53. {name: '烟台', value: 28},
  54. {name: '福州', value: 29},
  55. {name: '瓦房店', value: 30},
  56. {name: '即墨', value: 30},
  57. {name: '抚顺', value: 31},
  58. {name: '玉溪', value: 31},
  59. {name: '张家口', value: 31},
  60. {name: '阳泉', value: 31},
  61. {name: '莱州', value: 32},
  62. {name: '湖州', value: 32},
  63. {name: '汕头', value: 32},
  64. {name: '昆山', value: 33},
  65. {name: '宁波', value: 33},
  66. {name: '湛江', value: 33},
  67. {name: '揭阳', value: 34},
  68. {name: '荣成', value: 34},
  69. {name: '连云港', value: 35},
  70. {name: '葫芦岛', value: 35},
  71. {name: '常熟', value: 36},
  72. {name: '东莞', value: 36},
  73. {name: '河源', value: 36},
  74. {name: '淮安', value: 36},
  75. {name: '泰州', value: 36},
  76. {name: '南宁', value: 37},
  77. {name: '营口', value: 37},
  78. {name: '惠州', value: 37},
  79. {name: '江阴', value: 37},
  80. {name: '蓬莱', value: 37},
  81. {name: '韶关', value: 38},
  82. {name: '嘉峪关', value: 38},
  83. {name: '广州', value: 38},
  84. {name: '延安', value: 38},
  85. {name: '太原', value: 39},
  86. {name: '清远', value: 39},
  87. {name: '中山', value: 39},
  88. {name: '昆明', value: 39},
  89. {name: '寿光', value: 40},
  90. {name: '盘锦', value: 40},
  91. {name: '长治', value: 41},
  92. {name: '深圳', value: 41},
  93. {name: '珠海', value: 42},
  94. {name: '宿迁', value: 43},
  95. {name: '咸阳', value: 43},
  96. {name: '铜川', value: 44},
  97. {name: '平度', value: 44},
  98. {name: '佛山', value: 44},
  99. {name: '海口', value: 44},
  100. {name: '江门', value: 45},
  101. {name: '章丘', value: 45},
  102. {name: '肇庆', value: 46},
  103. {name: '大连', value: 47},
  104. {name: '临汾', value: 47},
  105. {name: '吴江', value: 47},
  106. {name: '石嘴山', value: 49},
  107. {name: '沈阳', value: 50},
  108. {name: '苏州', value: 50},
  109. {name: '茂名', value: 50},
  110. {name: '嘉兴', value: 51},
  111. {name: '长春', value: 51},
  112. {name: '胶州', value: 52},
  113. {name: '银川', value: 52},
  114. {name: '张家港', value: 52},
  115. {name: '三门峡', value: 53},
  116. {name: '锦州', value: 54},
  117. {name: '南昌', value: 54},
  118. {name: '柳州', value: 54},
  119. {name: '三亚', value: 54},
  120. {name: '自贡', value: 56},
  121. {name: '吉林', value: 56},
  122. {name: '阳江', value: 57},
  123. {name: '泸州', value: 57},
  124. {name: '西宁', value: 57},
  125. {name: '宜宾', value: 58},
  126. {name: '呼和浩特', value: 58},
  127. {name: '成都', value: 58},
  128. {name: '大同', value: 58},
  129. {name: '镇江', value: 59},
  130. {name: '桂林', value: 59},
  131. {name: '张家界', value: 59},
  132. {name: '宜兴', value: 59},
  133. {name: '北海', value: 60},
  134. {name: '西安', value: 61},
  135. {name: '金坛', value: 62},
  136. {name: '东营', value: 62},
  137. {name: '牡丹江', value: 63},
  138. {name: '遵义', value: 63},
  139. {name: '绍兴', value: 63},
  140. {name: '扬州', value: 64},
  141. {name: '常州', value: 64},
  142. {name: '潍坊', value: 65},
  143. {name: '重庆', value: 66},
  144. {name: '台州', value: 67},
  145. {name: '南京', value: 67},
  146. {name: '滨州', value: 70},
  147. {name: '贵阳', value: 71},
  148. {name: '无锡', value: 71},
  149. {name: '本溪', value: 71},
  150. {name: '克拉玛依', value: 72},
  151. {name: '渭南', value: 72},
  152. {name: '马鞍山', value: 72},
  153. {name: '宝鸡', value: 72},
  154. {name: '焦作', value: 75},
  155. {name: '句容', value: 75},
  156. {name: '北京', value: 79},
  157. {name: '徐州', value: 79},
  158. {name: '衡水', value: 80},
  159. {name: '包头', value: 80},
  160. {name: '绵阳', value: 80},
  161. {name: '乌鲁木齐', value: 84},
  162. {name: '枣庄', value: 84},
  163. {name: '杭州', value: 84},
  164. {name: '淄博', value: 85},
  165. {name: '鞍山', value: 86},
  166. {name: '溧阳', value: 86},
  167. {name: '库尔勒', value: 86},
  168. {name: '安阳', value: 90},
  169. {name: '开封', value: 90},
  170. {name: '济南', value: 92},
  171. {name: '德阳', value: 93},
  172. {name: '温州', value: 95},
  173. {name: '九江', value: 96},
  174. {name: '邯郸', value: 98},
  175. {name: '临安', value: 99},
  176. {name: '兰州', value: 99},
  177. {name: '沧州', value: 100},
  178. {name: '临沂', value: 103},
  179. {name: '南充', value: 104},
  180. {name: '天津', value: 105},
  181. {name: '富阳', value: 106},
  182. {name: '泰安', value: 112},
  183. {name: '诸暨', value: 112},
  184. {name: '郑州', value: 113},
  185. {name: '哈尔滨', value: 114},
  186. {name: '聊城', value: 116},
  187. {name: '芜湖', value: 117},
  188. {name: '唐山', value: 119},
  189. {name: '平顶山', value: 119},
  190. {name: '邢台', value: 119},
  191. {name: '德州', value: 120},
  192. {name: '济宁', value: 120},
  193. {name: '荆州', value: 127},
  194. {name: '宜昌', value: 130},
  195. {name: '义乌', value: 132},
  196. {name: '丽水', value: 133},
  197. {name: '洛阳', value: 134},
  198. {name: '秦皇岛', value: 136},
  199. {name: '株洲', value: 143},
  200. {name: '石家庄', value: 147},
  201. {name: '莱芜', value: 148},
  202. {name: '常德', value: 152},
  203. {name: '保定', value: 153},
  204. {name: '湘潭', value: 154},
  205. {name: '金华', value: 157},
  206. {name: '岳阳', value: 169},
  207. {name: '长沙', value: 175},
  208. {name: '衢州', value: 177},
  209. {name: '廊坊', value: 193},
  210. {name: '菏泽', value: 194},
  211. {name: '合肥', value: 229},
  212. {name: '武汉', value: 273},
  213. {name: '大庆', value: 279}
  214. ];
  215. var convertData = function (data) {
  216. var res = [];
  217. for (var i = 0; i < data.length; i++) {
  218. var geoCoord = geoCoordMap[data[i].name];
  219. if (geoCoord) {
  220. res.push({
  221. name: data[i].name,
  222. value: geoCoord.concat(data[i].value)
  223. });
  224. }
  225. }
  226. return res;
  227. };
  228. //地图容器
  229. var map_1 = echarts.init(document.getElementById('map_1'));
  230. //地图容器
  231. //34个省、市、自治区的名字拼音映射数组
  232. //网络零售当期分布
  233. var map_1_option = {
  234. /* title: {
  235. text: '全国主要城市空气质量',
  236. subtext: 'data from PM25.in',
  237. left: 'center',
  238. textStyle: {
  239. color: '#fff'
  240. }
  241. },*/
  242. grid: {
  243. top: '0',
  244. left: '0',
  245. right: '0',
  246. bottom: '0',
  247. containLabel: true
  248. },
  249. tooltip : {
  250. trigger: 'item'
  251. },
  252. /* legend: {
  253. orient: 'vertical',
  254. y: 'bottom',
  255. x:'right',
  256. data:['pm2.5'],
  257. textStyle: {
  258. color: '#fff'
  259. }
  260. },*/
  261. geo: {
  262. map: 'china',
  263. label: {
  264. emphasis: {
  265. show: false
  266. }
  267. },
  268. roam: false,
  269. itemStyle: {
  270. normal: {
  271. areaColor: '#4c60ff',
  272. borderColor: '#000f4c',
  273. },
  274. emphasis: {
  275. areaColor: '#293fff'
  276. }
  277. }
  278. },
  279. series : [
  280. {
  281. name: 'pm2.5',
  282. type: 'scatter',
  283. coordinateSystem: 'geo',
  284. data: convertData(data2),
  285. symbolSize: function (val) {
  286. return val[2] / 20;
  287. },
  288. label: {
  289. normal: {
  290. formatter: '{b}',
  291. position: 'right',
  292. show: false
  293. },
  294. emphasis: {
  295. show: true
  296. }
  297. },
  298. itemStyle: {
  299. normal: {
  300. color: '#ecf500'
  301. }
  302. }
  303. },
  304. {
  305. name: 'Top 5',
  306. type: 'effectScatter',
  307. coordinateSystem: 'geo',
  308. symbolSize: function (val) {
  309. return val[2] / 10;
  310. },
  311. showEffectOn: 'render',
  312. rippleEffect: {
  313. brushType: 'stroke'
  314. },
  315. hoverAnimation: true,
  316. /* label: {
  317. normal: {
  318. formatter: '{b}',
  319. position: 'right',
  320. show: true,
  321. color:'#333'
  322. },
  323. emphasis:{
  324. color:'#333'
  325. }
  326. },*/
  327. itemStyle: {
  328. normal: {
  329. color: '#f75749',
  330. shadowBlur: 10,
  331. shadowColor: '#333'
  332. }
  333. },
  334. zlevel: 1
  335. }
  336. ]
  337. };
  338. $(document).ready(function(){
  339.   map_1.resize();
  340. })
  341. window.addEventListener("resize", function () {
  342.   map_1.resize();
  343. });