rui.jiang
/
performance-test


			
				
					
						
						
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							import puppeteer from "puppeteer";
import fs from "fs-extra";
import path from "path";
import FormData from "form-data";
import { colorSchemes } from "../colors.js";
import axios from "axios";

/**
 * 生成折线图并上传
 * @param {Object} options - 配置选项
 * @param {string} options.fileAddr - 数据文件地址
 * @param {string[]} options.color1 - 颜色数组1
 * @param {string[]} options.colors - 颜色数组2
 * @returns {Promise<String>} - 返回图片URL
 */
export const generateLineAndChildLine = async (
  chartData,
  bucketName,
  objectName
) => {
  try {
    const colorSchemesItem = colorSchemes[0].colors;
    // 获取数据
    // 准备图表数据
    const data = [];
    const newData =
      chartData.analysisTypeCode === "风电机组叶尖速比和风速分析"
        ? chartData &&
          chartData.data &&
          JSON.parse(JSON.stringify(chartData.data)).sort((a, b) => {
            return a.engineName.localeCompare(b.engineName);
          })
        : JSON.parse(JSON.stringify(chartData.data));

    newData.forEach((turbine, index) => {
      const chartConfig = {
        x: turbine.xData,
        y: turbine.yData,
        name: turbine.engineName,
        mode: "lines",
        line: {
          color: colorSchemesItem[index % colorSchemesItem.length],
        },
        marker: {
          color: colorSchemesItem[index % colorSchemesItem.length],
        },
        hovertemplate:
          `${chartData.xaixs}:` +
          ` %{x} <br> ` +
          `${chartData.yaixs}:` +
          "%{y} <br>",
      };
      if (chartData.yaixs === "概率密度函数") {
        chartConfig.line.color = colorSchemesItem[7];
      }
      data.push(chartConfig);
    });

    // 准备布局配置
    const layout = {
      title: {
        text: chartData.title || chartData.data[0].title,
        font: {
          size: 16,
          weight: "bold",
        },
      },
      xaxis: {
        title: chartData.xaixs || "X轴",
        gridcolor: "rgb(255,255,255)",
        tickcolor: "rgb(255,255,255)",
        backgroundcolor: "#e5ecf6",
      },
      yaxis: {
        title: chartData.yaixs || "Y轴",
        gridcolor: "rgb(255,255,255)",
        tickcolor: "rgb(255,255,255)",
        backgroundcolor: "#e5ecf6",
      },
      margin: {
        l: 50,
        r: 50,
        t: 50,
        b: 50,
      },
      plot_bgcolor: "#e5ecf6",
      gridcolor: "#fff",
      bgcolor: "#e5ecf6",
      autosize: true,
      barmode: "group",
    };

    if (
      chartData.contract_Cp_curve_yData &&
      chartData.contract_Cp_curve_yData.length > 0
    ) {
      data.push({
        x: chartData.contract_Cp_curve_xData,
        y: chartData.contract_Cp_curve_yData,
        mode: "lines+markers",
        name: "合同功率曲线",
        line: {
          color: "red",
          width: 1,
        },
        marker: { color: "red", size: 4 },
      });
    }

    // 创建临时目录
    const tempDir = path.join(process.cwd(), "images");
    await fs.ensureDir(tempDir);
    const tempFilePath = path.join(
      tempDir,
      `temp_line_chart_${Date.now()}.jpeg`
    );

    // 获取 plotly.js 的绝对路径
    const plotlyPath = path.join(
      process.cwd(),
      "src",
      "public",
      "js",
      "plotly-latest.min.js"
    );
    const plotlyContent = await fs.readFile(plotlyPath, "utf-8");

    // 创建浏览器实例
    const browser = await puppeteer.launch({
      headless: "new",
      // 根据系统改路径
      executablePath: `${process.env.CHROME_PATH}`, // 根据系统改路径

      args: ["--no-sandbox", "--disable-setuid-sandbox"],
    });

    try {
      const page = await browser.newPage();

      // 创建HTML内容
      const htmlContent = `
                <!DOCTYPE html>
                <html>
                  <head>
                    <script>${plotlyContent}</script>
                    <style>
                      body { margin: 0; }
                      #chart { width: 800px; height: 600px; }
                    </style>
                  </head>
                  <body>
                    <div id="chart"></div>
                    <script>
                      window.onload = function() {
                        const data = ${JSON.stringify(data)};
                        const layout = ${JSON.stringify(layout)};
                        Plotly.newPlot('chart', data, layout, {
                          responsive: true
                        }).then(() => {
                          window.chartRendered = true;
                        });
                      };
                    </script>
                  </body>
                </html>
            `;

      // 设置页面内容
      await page.setContent(htmlContent, {
        waitUntil: "networkidle0",
      });

      // 等待图表渲染完成
      await page.waitForFunction(() => window.chartRendered === true, {
        timeout: 60000,
      });

      // 截图并保存到临时文件
      const chartElement = await page.$("#chart");
      await chartElement.screenshot({
        path: tempFilePath,
        type: "jpeg",
      });

      // 上传图片到服务器
      const formData = new FormData();
      formData.append("file", fs.createReadStream(tempFilePath));
      formData.append("type", "chart");
      // 这里假设需要从 chartData 中获取 engineCode 和 analysisTypeCode，根据实际情况调整
      formData.append("engineCode", chartData.engineCode || "");
      formData.append("analysisTypeCode", chartData.analysisTypeCode || "");

      // 发送上传请求
      const response = await axios.post(
        `${process.env.API_BASE_URL}/examples/upload`,
        { filePath: tempFilePath, bucketName, objectName }
      );
      return response?.data?.url;
    } finally {
      await browser.close();
    }
  } catch (error) {
    throw error;
  }
};