这几天,看了一下ECharts官网的API和Demo发现很有意思,于是就利用模型预测产生的数据做一个伪实时的动态数据显示 。
首先,创建一个index.html的文件,我用的vscode打开的,进行编写。
1.插入一个标签
<div id="main" style="600px;height:400px;"></div>
设置他的一些style(可自行美化,我很懒!!!)。
2.在body下建一个<script>脚本(为什么要在body下写js脚本呢?因为这是提高用户体验,可自行百度深层次的原因~~~)。
3.脚本写啥呢?别急,慢慢来啊~~
(1)首先,我们来建一个echarts的对象,就叫他MyChart吧
var myChart = echarts.init(document.getElementById('main'));
(2)建一个setoption这是初始化图的,填一些基本参数(可通过此链接飞到Echarts官网的配置参考一下)
(3)初始化了之后,我们就可以ajax异步读取本地文件了~~~~
其中不懂堆栈的(链接在此这个是我Google的,有可能被墙~~)不懂push,shift操作数据的(链接在此这个应该不会被墙~~)
1 $.ajax({ 2 type:"get", 3 // async:true, 4 url:"test_data.json", 5 data:{}, 6 dataType:"json", 7 success:function(result){ 8 var datas=result 9 if(result){ 10 11 var m=0; 12 for(var i=0;i<result.length;i++){ 13 if(m<1000){ 14 datas.shift(); 15 date.push(result[i]["time"]); 16 data.push(result[i]["AM23SIG0206.AV"]); 17 m+=1; 18 } 19 else{ 20 break; 21 22 } 23 myChart.hideLoading(); 24 25 setInterval(function(){ 26 for(var n=0;n<2;n++){ 27 28 date.shift(); 29 date.push(datas[n]["time"]); 30 data.shift(); 31 data.push(datas[n]["AM23SIG0206.AV"]); 32 } 33 myChart.setOption({ 34 xAxis:{ 35 data:date 36 }, 37 series:[ 38 { 39 name:"参数", 40 data:data 41 } 42 ]}); 43 44 for(var nn=0;nn<2;nn++){ 45 datas.shift() 46 } 47 48 },2000); 49 50 51 52 } 53 } 54 }, 55 error:function(errorMsg){ 56 alert("图表请求数据失败!"); 57 myChart.hideLoading(); 58 myChart_2.hideLoading(); 59 } 60 })
我来解释一下,这个异步加载的原理是这样子的:
(1)我们现在加载一个.json文件,存在一个变量result里,开始进行数据的操作,利用堆栈的概念先存一个图上要显示的数据量,假设是1000个点,存到data里(这是一个队列)你如果要实现动态的实时的数据,看着数据他会动~~~~你需要存一个数据进去,但是呢这个队列只有1000个容量,放不下怎么办,没关系啊,你先取一个出来不就行了嘛,就这样循环下去~~~~
(2)但是啊,取一个存一个太麻烦了,我们在设置一个定时器setInterval()在这个里面,每过2s更新2个点(怎么更新呢,就是data.shift()
data.push()
模拟了堆栈~~~~
这样就达到了动态数据了~~~~
好吧,如果只是这样也太low了,我要实现一个框架+数据库+前端的真正数据动起来~~~~让我在研究几天~~~~~~
好了,不废话了,下面是源码,有需要的童鞋可以自己跑一下,看看可不可以动~~~~~
1 <!DOCTYPE html> 2 <html lang="en"> 3 <head> 4 <meta charset="UTF-8"> 5 <title>Charts</title> 6 <script type="text/javascript" src="echarts.min.js"></script> 7 <script type="text/javascript" src="http://ajax.googleapis.com/ajax/libs/jquery/1.2.6/jquery.min.js"></script> 8 </head> 9 <body> 10 <div id="main" style="600px;height:400px;"></div> 11 <div id="main_2" style="600px;height:400px;"></div> 12 </body> 13 <script type="text/javascript"> 14 var myChart = echarts.init(document.getElementById('main')); 15 var myChart_2 = echarts.init(document.getElementById('main_2')); 16 myChart.setOption({ 17 title:{ 18 text:'异步数据加载' 19 }, 20 tooltip:{ 21 show:true, 22 23 }, 24 25 xAxis:{ 26 type:'category', 27 boundaryGap:false, 28 data:[], 29 splitLine: { 30 show: false 31 }, 32 }, 33 yAxis:{ 34 boundaryGap:[0,'100%'], 35 type:'value', 36 min:'dataMin', 37 max:'dataMax', 38 splitLine: { 39 show: false 40 }, 41 42 }, 43 series:[{ 44 name:'参数', 45 type:'line', 46 data:[] 47 }] 48 }); 49 myChart_2.setOption({ 50 title:{ 51 text:'异步数据加载' 52 }, 53 tooltip:{ 54 show:true, 55 56 }, 57 58 xAxis:{ 59 type:'category', 60 boundaryGap:false, 61 data:[], 62 splitLine: { 63 show: false 64 }, 65 }, 66 yAxis:{ 67 boundaryGap:[0,'100%'], 68 type:'value', 69 min:'dataMin', 70 max:'dataMax', 71 splitLine: { 72 show: false 73 }, 74 75 }, 76 series:[{ 77 name:'参数', 78 type:'line', 79 data:[] 80 }] 81 }); 82 myChart.showLoading(); 83 myChart_2.showLoading(); 84 var date = []; 85 var data = []; 86 $.ajax({ 87 type:"get", 88 // async:true, 89 url:"test_data.json", 90 data:{}, 91 dataType:"json", 92 success:function(result){ 93 var datas=result 94 if(result){ 95 96 var m=0; 97 for(var i=0;i<result.length;i++){ 98 if(m<1000){ 99 datas.shift(); 100 date.push(result[i]["time"]); 101 data.push(result[i]["AM23SIG0206.AV"]); 102 m+=1; 103 } 104 else{ 105 break; 106 107 } 108 myChart.hideLoading(); 109 myChart_2.hideLoading(); 110 setInterval(function(){ 111 for(var n=0;n<2;n++){ 112 113 date.shift(); 114 date.push(datas[n]["time"]); 115 data.shift(); 116 data.push(datas[n]["AM23SIG0206.AV"]); 117 } 118 myChart.setOption({ 119 xAxis:{ 120 data:date 121 }, 122 series:[ 123 { 124 name:"参数", 125 data:data 126 } 127 ]}); 128 myChart_2.setOption({ 129 xAxis:{ 130 data:date 131 }, 132 series:[ 133 { 134 name:"参数", 135 data:data 136 } 137 ]}); 138 for(var nn=0;nn<2;nn++){ 139 datas.shift() 140 } 141 142 },2000); 143 144 145 146 } 147 } 148 }, 149 error:function(errorMsg){ 150 alert("图表请求数据失败!"); 151 myChart.hideLoading(); 152 myChart_2.hideLoading(); 153 } 154 }) 155 </script> 156 </html>
1 [ 2 { 3 "AM23SIG0206.AV": "594.4071", 4 "time": "2016-05-01 00:00:01" 5 }, 6 { 7 "AM23SIG0206.AV": "594.4207", 8 "time": "2016-05-01 00:00:04" 9 }, 10 { 11 "AM23SIG0206.AV": "594.3883", 12 "time": "2016-05-01 00:00:07" 13 }, 14 { 15 "AM23SIG0206.AV": "594.3586", 16 "time": "2016-05-01 00:00:10" 17 }, 18 { 19 "AM23SIG0206.AV": "594.3883", 20 "time": "2016-05-01 00:00:13" 21 }, 22 { 23 "AM23SIG0206.AV": "594.3398", 24 "time": "2016-05-01 00:00:16" 25 }, 26 { 27 "AM23SIG0206.AV": "594.3398", 28 "time": "2016-05-01 00:00:19" 29 }, 30 { 31 "AM23SIG0206.AV": "594.3075", 32 "time": "2016-05-01 00:00:22" 33 }, 34 { 35 "AM23SIG0206.AV": "594.3076", 36 "time": "2016-05-01 00:00:25" 37 }, 38 { 39 "AM23SIG0206.AV": "594.2753", 40 "time": "2016-05-01 00:00:28" 41 }, 42 { 43 "AM23SIG0206.AV": "594.2753", 44 "time": "2016-05-01 00:00:31" 45 }, 46 { 47 "AM23SIG0206.AV": "594.2429", 48 "time": "2016-05-01 00:00:34" 49 }, 50 { 51 "AM23SIG0206.AV": "594.2753", 52 "time": "2016-05-01 00:00:37" 53 }, 54 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}, 106 { 107 "AM23SIG0206.AV": "594.2402", 108 "time": "2016-05-01 00:01:19" 109 }, 110 { 111 "AM23SIG0206.AV": "594.1918", 112 "time": "2016-05-01 00:01:22" 113 }, 114 { 115 "AM23SIG0206.AV": "594.2241", 116 "time": "2016-05-01 00:01:25" 117 }, 118 { 119 "AM23SIG0206.AV": "594.1918", 120 "time": "2016-05-01 00:01:28" 121 }, 122 { 123 "AM23SIG0206.AV": "594.1595", 124 "time": "2016-05-01 00:01:31" 125 }, 126 { 127 "AM23SIG0206.AV": "594.0975", 128 "time": "2016-05-01 00:01:34" 129 }, 130 { 131 "AM23SIG0206.AV": "594.1272", 132 "time": "2016-05-01 00:01:37" 133 }, 134 { 135 "AM23SIG0206.AV": "594.111", 136 "time": "2016-05-01 00:01:40" 137 }, 138 { 139 "AM23SIG0206.AV": "594.1136", 140 "time": "2016-05-01 00:01:43" 141 }, 142 { 143 "AM23SIG0206.AV": "594.0787", 144 "time": "2016-05-01 00:01:46" 145 }, 146 { 147 "AM23SIG0206.AV": "594.0813", 148 "time": "2016-05-01 00:01:49" 149 }, 150 { 151 "AM23SIG0206.AV": "594.0464", 152 "time": "2016-05-01 00:01:52" 153 }, 154 { 155 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00:03:07" 253 }, 254 { 255 "AM23SIG0206.AV": "593.9481", 256 "time": "2016-05-01 00:03:10" 257 }, 258 { 259 "AM23SIG0206.AV": "593.8997", 260 "time": "2016-05-01 00:03:13" 261 }, 262 { 263 "AM23SIG0206.AV": "593.8997", 264 "time": "2016-05-01 00:03:16" 265 }, 266 { 267 "AM23SIG0206.AV": "593.8673", 268 "time": "2016-05-01 00:03:19" 269 }, 270 { 271 "AM23SIG0206.AV": "593.835", 272 "time": "2016-05-01 00:03:22" 273 }, 274 { 275 "AM23SIG0206.AV": "593.8027", 276 "time": "2016-05-01 00:03:25" 277 }, 278 { 279 "AM23SIG0206.AV": "593.7704", 280 "time": "2016-05-01 00:03:28" 281 }, 282 { 283 "AM23SIG0206.AV": "593.7704", 284 "time": "2016-05-01 00:03:31" 285 }, 286 { 287 "AM23SIG0206.AV": "593.7193", 288 "time": "2016-05-01 00:03:34" 289 }, 290 { 291 "AM23SIG0206.AV": "593.7193", 292 "time": "2016-05-01 00:03:37" 293 }, 294 { 295 "AM23SIG0206.AV": "593.6735", 296 "time": "2016-05-01 00:03:40" 297 }, 298 { 299 "AM23SIG0206.AV": "593.625", 300 "time": "2016-05-01 00:03:43" 301 }, 302 { 303 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这个是.json文件(python的大数据模型预测产生的数据我拿来用一哈)
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