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@ -82,7 +82,7 @@
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</el-scrollbar>
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</div>
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<div class="main-right">
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<el-scrollbar height="500px" ref="scrollbar" style="padding: 20px">
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<el-scrollbar height="590px" ref="scrollbar" style="padding: 20px">
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<div>
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<span style="font-weight: bold; font-size: 18px; color: #3596eb">分析数据：</span>
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<el-table :data="tableData2" style="width: 98%; margin-top: 10px" :header-cell-style="headerCellStyle" height="350">
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@ -103,6 +103,11 @@
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</el-table-column>
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</el-table>
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</div>
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<div class="pdfRef" id="pdfRef" style="margin-top: 20px; display: flex" v-show="flagUP">
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<div style="background: #ffffff">
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<div id="main" style="width: 550px; height: 500px"></div>
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</div>
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</div>
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</el-scrollbar>
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</div>
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</div>
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@ -313,9 +318,11 @@ import useAlgorithmStore from "@/store/modules/algorithm.js";
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const algorithmStore = useAlgorithmStore();
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import popModel from "@/views/components/popModal.vue";
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import * as echarts from "echarts";
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import { htmlPdf } from "@/utils/pdf.js";
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import * as API from "@/api/AI.js";
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import { getUserInfo } from "@/utils/auth";
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import * as XLSX from "XLSX";
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import JSZip from "jszip";
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import { onMounted, reactive } from "vue";
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const { proxy } = getCurrentInstance();
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const dialogVisible = ref(false);
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@ -398,10 +405,72 @@ const handleChange = (info) => {
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fileList.value.push(info);
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};
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const flag = ref(false);
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let myChart;
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const getRandomColorHex = () => {
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const randomValue = (min, max) => {
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// 生成 min 到 max 之间的随机整数
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const value = Math.floor(Math.random() * (max - min + 1)) + min;
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// 将整数转换为两位十六进制形式
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return value.toString(16).padStart(2, "0");
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};
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// 限制红色通道较低，绿色和蓝色通道较高
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const r = randomValue(0, 128); // 红色通道较低 (0-128)
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const g = randomValue(128, 255); // 绿色通道较高 (128-255)
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const b = randomValue(128, 255); // 蓝色通道较高 (128-255)
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return `#${r}${g}${b}`;
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};
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//图标添加数据
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const addData = (myChart, newData, color) => {
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// 获取当前的数据
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let currentData = myChart.getOption().series[0].data || [];
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// 添加新数据集，并为每个数据点单独设置颜色
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newData.forEach((dataPoint) => {
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currentData.push({
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value: [dataPoint[0], dataPoint[1]],
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itemStyle: { color: color },
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});
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});
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// 更新图表
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myChart.setOption({
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series: [
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{
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data: currentData,
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},
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],
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});
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};
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onMounted(() => {
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getList();
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optionData();
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var chartDom = document.getElementById("main");
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myChart = echarts.init(chartDom);
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var option = {
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dataset: [
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{
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source: [], // 初始时数据为空
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},
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],
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tooltip: {
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position: "top",
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},
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xAxis: {},
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yAxis: {},
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series: [
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{
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type: "line",
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encode: { tooltip: [0, 1] },
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symbolSize: 8,
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itemStyle: {
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borderColor: "#555",
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},
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},
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],
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};
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// 设置初始的配置
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myChart.setOption(option);
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});
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const optionData = () => {
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@ -532,35 +601,6 @@ const computation = () => {
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userId: JSON.parse(getUserInfo()).userId,
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};
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loading1.value = true;
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if (input4.value === "线性回归") {
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if (input5.value.length > 1) {
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proxy.$modal.msgError("y变量数量有误！");
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return;
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}
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if (input6.value.length != 2 || input6.value.length > 2) {
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proxy.$modal.msgError("x变量数量有误！");
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return;
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}
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flagColumn.value = true;
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tableData2.value.forEach((item) => {
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sendData.y.push(item[input5.value[0]]);
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sendData.x.push([item[input6.value[0]], item[input6.value[1]]]);
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});
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API.linearRegression(sendData).then((res) => {
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tableLabel2.length = 0;
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for (const key in res.data) {
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tableLabel2.push({
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label: key,
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prop: key,
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});
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}
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let data = res.data;
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data.slopes = data.slopes.join(",");
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tableData3.value = [data];
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predictionResults.value = "";
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loading1.value = false;
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});
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} else {
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if (input5.value.length > 1) {
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proxy.$modal.msgError("y变量数量有误！");
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return;
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@ -591,7 +631,33 @@ const computation = () => {
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predictionResults.value = "";
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loading1.value = true;
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});
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}
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//表格
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let sendData2={}
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if(input5.value[0]==="sales_volume"){
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sendData2={
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userId:JSON.parse(getUserInfo()).userId,
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y:tableData2.value.map(item=>item.sales_volume),
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x:tableData2.value.map(item=>item.sales_forehead)
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}
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}else{
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sendData2={
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userId:JSON.parse(getUserInfo()).userId,
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y:tableData2.value.map(item=>item.sales_forehead),
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x:tableData2.value.map(item=>item.sales_volume)
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}
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}
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API.regressionAnalysisTrendChart(sendData2).then((res)=>{
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myChart.setOption({
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series: [
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{
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data: [], // 清空数据
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},
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],
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});
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const bgColor = getRandomColorHex();
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addData(myChart,res.data,bgColor)
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})
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} else {
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proxy.$modal.msgWarning("请模型参数进行设置！");
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}
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@ -616,19 +682,6 @@ const handleClick = (item) => {
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};
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const predictionResults = ref("");
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const Forecasting = () => {
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// if (nowData.value.type === "线性回归") {
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// const sendData = {
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// intercept: nowData.value.intercept,
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// type: nowData.value.type,
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// slopes: nowData.value.slopes.split(",").map(Number),
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// raX: formInline2.user.split(",").map(Number),
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// };
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// API.logisticRegressionPrediction(sendData).then((res) => {
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// dialogVisible2.value = false;
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// predictionResults.value = res.data;
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// });
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// }
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// if (nowData.value.type === "逻辑回归") {
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const sendData = {
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intercept: nowData.value.intercept,
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slope: nowData.value.slope,
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@ -645,9 +698,22 @@ const upLoad = () => {
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if (!tableDom) {
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return;
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}
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const wb = XLSX.utils.table_to_book(tableDom);
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XLSX.writeFile(wb, "回归分析.xlsx");
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// XLSX.writeFile(wb, '聚类分析.xlsx');
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const zip = new JSZip();
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const excelBlob = XLSX.write(wb, { bookType: "xlsx", type: "array" });
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zip.file("回归分析.xlsx", new Blob([excelBlob], { type: "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" }));
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zip.file("回归分析图.pdf", handleExport());
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zip.generateAsync({ type: "blob" }).then((content) => {
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saveAs(content, "回归分析.zip");
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});
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};
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//图表导出pdf
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const handleExport = async (name) => {
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var fileName = "回归分析图";
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const fileList = document.getElementsByClassName("pdfRef"); // 很重要
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const pdfBlob = await htmlPdf(fileName, document.querySelector("#pdfRef"), fileList, true);
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return pdfBlob;
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};
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const startOver = () => {
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input.value = "";
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qinzhenpen
2 years ago