14 changed files with 431 additions and 288 deletions
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Before Width: | Height: | Size: 1005 B |
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Before Width: | Height: | Size: 1013 B |
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Before Width: | Height: | Size: 88 KiB |
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Before Width: | Height: | Size: 1.4 KiB |
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Before Width: | Height: | Size: 20 KiB |
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Before Width: | Height: | Size: 3.6 KiB |
@ -1,253 +1,304 @@ |
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var dom1 = document.getElementById('container1'); |
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// pressure(dom1, 1);
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|
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/** |
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* 绘制图 |
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* @param dom |
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* @param item |
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*/ |
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function pressure(dom, item){ |
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var myChart = echarts.init(dom, null, { |
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renderer: 'canvas', |
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useDirtyRect: false |
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}); |
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var app = {}; |
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var dom2 = document.getElementById('container2'); |
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lineGraph(dom1, '温度', '℃') |
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lineGraph2(dom2, '血氧', '%') |
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var option; |
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function lineGraph(dom, title, unit){ |
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var myChart = echarts.init(dom, null, { |
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renderer: 'canvas', |
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useDirtyRect: false |
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}); |
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var app = {}; |
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var ROOT_PATH = ''; |
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var option; |
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var dataAll = []; |
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|
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let noise = getNoiseHelper(); |
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let xData = []; |
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let yData = []; |
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noise.seed(Math.random()); |
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function generateData(theta, min, max) { |
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let data = []; |
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for (let i = 0; i <= 100; i++) { |
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xData.push(i); |
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} |
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for (let j = 0; j < 100; j++) { |
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yData.push(j); |
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} |
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return data; |
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$.get( |
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ROOT_PATH + '/loraData', |
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function (_rawData) { |
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_rawData.forEach(value => dataAll.push(value)); |
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run(_rawData); |
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} |
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let data = generateData(2, -5, 5); |
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setTimer(); |
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function setTimer () { |
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let timer = null |
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$.get('/tabularData?item=' + item).done(function(data) { |
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if(data){//根据返回状态判断
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let pressure = data.pressure |
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myChart.setOption({ |
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series: [ |
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{ |
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data: pressure |
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} |
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); |
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function run(_rawData) { |
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_rawData.unshift(["Income","Life Expectancy","Population","Country","Year"]) |
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// var countries = ['Australia', 'Canada', 'China', 'Cuba', 'Finland', 'France', 'Germany', 'Iceland', 'India', 'Japan', 'North Korea', 'South Korea', 'New Zealand', 'Norway', 'Poland', 'Russia', 'Turkey', 'United Kingdom', 'United States'];
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const countries = [title]; |
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const datasetWithFilters = []; |
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const seriesList = []; |
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echarts.util.each(countries, function (country) { |
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var datasetId = 'dataset_' + country; |
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datasetWithFilters.push({ |
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id: datasetId, |
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fromDatasetId: 'dataset_raw', |
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transform: { |
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type: 'filter', |
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config: { |
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and: [ |
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// { dimension: 'Year', gte: 1950 },
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{ dimension: 'Country', '=': country } |
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] |
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}); |
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var myDate = new Date(); |
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var mytime = myDate.toLocaleTimeString(); |
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let original = mytime + ' '; |
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pressure.forEach((elem, index) => { |
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original += elem[2] * 64 + ' ' |
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}) |
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$(".sound-code-chunk-default-content").html(original); |
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$("#foot-content1").html(data['foot'][0] + '℃'); |
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$("#foot-content2").html(data['foot'][1] + '%'); |
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$("#foot-content3").html(data['foot'][2] + '℃'); |
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$("#foot-content4").html(data['foot'][3] + '%'); |
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$("#foot-content5").html(data['foot'][4] + '℃'); |
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$("#foot-content6").html(data['foot'][5] + '%'); |
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$("#foot-content7").html(data['foot'][6] + '℃'); |
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$("#foot-content8").html(data['foot'][7] + '%'); |
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timer = setTimeout(()=>{ |
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setTimer () |
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},5000)//2秒查一下
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} else { |
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clearTimeout(timer);//清理定时任务
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} |
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} |
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}); |
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} |
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seriesList.push({ |
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type: 'line', |
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datasetId: datasetId, |
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showSymbol: false, |
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smooth: true, |
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name: country, |
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endLabel: { |
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show: true, |
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formatter: function (params) { |
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return params.value[3] + ': ' + params.value[0] + unit; |
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} |
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}, |
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labelLayout: { |
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moveOverlap: 'shiftY' |
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}, |
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emphasis: { |
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focus: 'series' |
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}, |
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encode: { |
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x: 'Year', |
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y: 'Income', |
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label: ['Country', 'Income'], |
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itemName: 'Year', |
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tooltip: ['Income'] |
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} |
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}); |
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}); |
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option = { |
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tooltip: {}, |
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animationDuration: 10000, |
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dataset: [ |
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{ |
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id: 'dataset_raw', |
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source: _rawData |
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}, |
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...datasetWithFilters |
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], |
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tooltip: { |
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order: 'valueDesc', |
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trigger: 'axis' |
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}, |
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xAxis: { |
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type: 'category', |
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data: xData |
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nameLocation: 'middle' |
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}, |
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yAxis: { |
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type: 'category', |
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data: yData |
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scale: false, |
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name: 'Income', |
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min: 30, |
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max: 40, |
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}, |
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visualMap: { |
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show:false, |
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min: 0, |
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max: 1, |
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calculable: true, |
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realtime: false, |
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inRange: { |
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color: [ |
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// '#313695',
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// '#4575b4',
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// '#74add1',
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// '#abd9e9',
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// '#e0f3f8',
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// '#ffffbf',
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// '#fee090',
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// '#fdae61',
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// '#f46d43',
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// '#d73027',
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// '#a50026'
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'#ffffdc', |
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'#ffffbf', |
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'#ffff71', |
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'#fee090', |
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'#ffc993', |
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'#fdae61', |
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'#f87f59', |
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'#f46d43', |
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'#e34d45', |
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'#d73027', |
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'#a50026', |
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] |
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} |
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grid: { |
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right: 140 |
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}, |
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series: [ |
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{ |
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name: 'Gaussian', |
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type: 'heatmap', |
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data: data, |
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emphasis: { |
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itemStyle: { |
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borderColor: '#333', |
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borderWidth: 1 |
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} |
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}, |
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progressive: 1000, |
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animation: false |
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} |
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] |
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series: seriesList |
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}; |
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///////////////////////////////////////////////////////////////////////////
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// perlin noise helper from https://github.com/josephg/noisejs
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///////////////////////////////////////////////////////////////////////////
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function getNoiseHelper() { |
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class Grad { |
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constructor(x, y, z) { |
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this.x = x; |
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this.y = y; |
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this.z = z; |
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} |
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dot2(x, y) { |
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return this.x * x + this.y * y; |
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} |
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dot3(x, y, z) { |
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return this.x * x + this.y * y + this.z * z; |
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} |
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} |
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const grad3 = [ |
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new Grad(1, 1, 0), |
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new Grad(-1, 1, 0), |
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new Grad(1, -1, 0), |
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new Grad(-1, -1, 0), |
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new Grad(1, 0, 1), |
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new Grad(-1, 0, 1), |
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new Grad(1, 0, -1), |
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new Grad(-1, 0, -1), |
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new Grad(0, 1, 1), |
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new Grad(0, -1, 1), |
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new Grad(0, 1, -1), |
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new Grad(0, -1, -1) |
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]; |
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const p = [ |
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151, 160, 137, 91, 90, 15, 131, 13, 201, 95, 96, 53, 194, 233, 7, 225, 140, |
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36, 103, 30, 69, 142, 8, 99, 37, 240, 21, 10, 23, 190, 6, 148, 247, 120, |
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234, 75, 0, 26, 197, 62, 94, 252, 219, 203, 117, 35, 11, 32, 57, 177, 33, |
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88, 237, 149, 56, 87, 174, 20, 125, 136, 171, 168, 68, 175, 74, 165, 71, |
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134, 139, 48, 27, 166, 77, 146, 158, 231, 83, 111, 229, 122, 60, 211, 133, |
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230, 220, 105, 92, 41, 55, 46, 245, 40, 244, 102, 143, 54, 65, 25, 63, 161, |
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1, 216, 80, 73, 209, 76, 132, 187, 208, 89, 18, 169, 200, 196, 135, 130, |
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116, 188, 159, 86, 164, 100, 109, 198, 173, 186, 3, 64, 52, 217, 226, 250, |
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124, 123, 5, 202, 38, 147, 118, 126, 255, 82, 85, 212, 207, 206, 59, 227, |
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47, 16, 58, 17, 182, 189, 28, 42, 223, 183, 170, 213, 119, 248, 152, 2, 44, |
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154, 163, 70, 221, 153, 101, 155, 167, 43, 172, 9, 129, 22, 39, 253, 19, 98, |
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108, 110, 79, 113, 224, 232, 178, 185, 112, 104, 218, 246, 97, 228, 251, 34, |
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242, 193, 238, 210, 144, 12, 191, 179, 162, 241, 81, 51, 145, 235, 249, 14, |
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239, 107, 49, 192, 214, 31, 181, 199, 106, 157, 184, 84, 204, 176, 115, 121, |
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50, 45, 127, 4, 150, 254, 138, 236, 205, 93, 222, 114, 67, 29, 24, 72, 243, |
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141, 128, 195, 78, 66, 215, 61, 156, 180 |
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]; |
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// To remove the need for index wrapping, double the permutation table length
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let perm = new Array(512); |
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let gradP = new Array(512); |
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// This isn't a very good seeding function, but it works ok. It supports 2^16
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// different seed values. Write something better if you need more seeds.
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function seed(seed) { |
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if (seed > 0 && seed < 1) { |
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// Scale the seed out
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seed *= 65536; |
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} |
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seed = Math.floor(seed); |
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if (seed < 256) { |
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seed |= seed << 8; |
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myChart.setOption(option); |
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} |
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setInterval(function () { |
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$.get( |
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ROOT_PATH + '/loraData?item=' + title, |
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function (_rawData2) { |
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|
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if (dataAll.length > 40){ |
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dataAll.shift(); |
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dataAll.shift(); |
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} |
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for (let i = 0; i < 256; i++) { |
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let v; |
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if (i & 1) { |
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v = p[i] ^ (seed & 255); |
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_rawData2.forEach(value => dataAll.push(value)); |
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_rawData = [["Income","Life Expectancy","Population","Country","Year"]]; |
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dataAll.forEach(value => _rawData.push(value)); |
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myChart.setOption({ |
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dataset: [ |
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{ |
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source: _rawData |
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} |
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], |
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}); |
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|
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let original = ''; |
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dataAll.forEach((elem, index) => { |
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original += elem[3] + elem[0]; |
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if (elem[3] == "血氧") { |
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original += '%' |
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} else { |
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v = p[i] ^ ((seed >> 8) & 255); |
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original += '℃' |
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} |
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perm[i] = perm[i + 256] = v; |
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gradP[i] = gradP[i + 256] = grad3[v % 12]; |
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} |
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} |
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seed(0); |
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// ##### Perlin noise stuff
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function fade(t) { |
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return t * t * t * (t * (t * 6 - 15) + 10); |
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} |
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function lerp(a, b, t) { |
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return (1 - t) * a + t * b; |
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original += ' ' |
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}) |
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$(".sound-code-chunk-default-content").html(original); |
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} |
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// 2D Perlin Noise
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function perlin2(x, y) { |
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// Find unit grid cell containing point
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let X = Math.floor(x), |
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Y = Math.floor(y); |
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// Get relative xy coordinates of point within that cell
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x = x - X; |
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y = y - Y; |
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// Wrap the integer cells at 255 (smaller integer period can be introduced here)
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X = X & 255; |
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Y = Y & 255; |
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// Calculate noise contributions from each of the four corners
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let n00 = gradP[X + perm[Y]].dot2(x, y); |
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let n01 = gradP[X + perm[Y + 1]].dot2(x, y - 1); |
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let n10 = gradP[X + 1 + perm[Y]].dot2(x - 1, y); |
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let n11 = gradP[X + 1 + perm[Y + 1]].dot2(x - 1, y - 1); |
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// Compute the fade curve value for x
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let u = fade(x); |
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// Interpolate the four results
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return lerp(lerp(n00, n10, u), lerp(n01, n11, u), fade(y)); |
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); |
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}, 1000); |
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if (option && typeof option === 'object') { |
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myChart.setOption(option); |
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} |
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window.addEventListener('resize', myChart.resize); |
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} |
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function lineGraph2(dom, title, unit){ |
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var myChart = echarts.init(dom, null, { |
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renderer: 'canvas', |
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useDirtyRect: false |
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}); |
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var app = {}; |
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var ROOT_PATH = ''; |
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var option; |
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var dataAll = []; |
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|
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$.get( |
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ROOT_PATH + '/loraData', |
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function (_rawData) { |
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_rawData.forEach(value => dataAll.push(value)); |
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run(_rawData); |
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} |
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return { |
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seed, |
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perlin2 |
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); |
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function run(_rawData) { |
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_rawData.unshift(["Income","Life Expectancy","Population","Country","Year"]) |
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// var countries = ['Australia', 'Canada', 'China', 'Cuba', 'Finland', 'France', 'Germany', 'Iceland', 'India', 'Japan', 'North Korea', 'South Korea', 'New Zealand', 'Norway', 'Poland', 'Russia', 'Turkey', 'United Kingdom', 'United States'];
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const countries = [title]; |
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const datasetWithFilters = []; |
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const seriesList = []; |
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echarts.util.each(countries, function (country) { |
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var datasetId = 'dataset_' + country; |
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datasetWithFilters.push({ |
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id: datasetId, |
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fromDatasetId: 'dataset_raw', |
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transform: { |
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type: 'filter', |
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config: { |
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and: [ |
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// { dimension: 'Year', gte: 1950 },
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{ dimension: 'Country', '=': country } |
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] |
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} |
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} |
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}); |
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seriesList.push({ |
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type: 'line', |
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datasetId: datasetId, |
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showSymbol: false, |
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smooth: true, |
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name: country, |
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endLabel: { |
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show: true, |
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formatter: function (params) { |
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return params.value[3] + ': ' + params.value[0] + unit; |
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} |
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}, |
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labelLayout: { |
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moveOverlap: 'shiftY' |
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}, |
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emphasis: { |
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focus: 'series' |
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}, |
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encode: { |
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x: 'Year', |
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y: 'Income', |
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label: ['Country', 'Income'], |
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itemName: 'Year', |
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tooltip: ['Income'] |
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} |
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}); |
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}); |
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option = { |
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animationDuration: 10000, |
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dataset: [ |
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{ |
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id: 'dataset_raw', |
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source: _rawData |
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}, |
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...datasetWithFilters |
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], |
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tooltip: { |
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order: 'valueDesc', |
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trigger: 'axis' |
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}, |
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xAxis: { |
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type: 'category', |
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nameLocation: 'middle' |
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}, |
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yAxis: { |
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scale: false, |
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name: 'Income' |
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}, |
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grid: { |
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right: 140 |
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}, |
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color:[ |
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'rgba(231,82,27,0.94)' |
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], |
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series: seriesList |
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}; |
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myChart.setOption(option); |
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} |
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|
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setInterval(function () { |
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$.get( |
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ROOT_PATH + '/loraData?item=' + title, |
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function (_rawData2) { |
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|
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if (dataAll.length > 40){ |
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dataAll.shift(); |
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dataAll.shift(); |
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} |
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_rawData2.forEach(value => dataAll.push(value)); |
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_rawData = [["Income","Life Expectancy","Population","Country","Year"]]; |
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dataAll.forEach(value => _rawData.push(value)); |
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|
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myChart.setOption({ |
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dataset: [ |
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{ |
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source: _rawData |
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} |
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], |
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}); |
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|
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let original = ''; |
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dataAll.forEach((elem, index) => { |
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original += elem[3] + elem[0]; |
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if (elem[3] == "血氧") { |
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original += '%' |
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} else { |
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original += '℃' |
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} |
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original += ' ' |
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}) |
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$(".sound-code-chunk-default-content").html(original); |
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} |
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); |
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}, 1000); |
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if (option && typeof option === 'object') { |
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myChart.setOption(option); |
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} |
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window.addEventListener('resize', myChart.resize); |
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} |
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|
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} |
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