performance-test/downLoadServer/src/server/utils/chartsCom/TwoDMarkersChart1.js

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";

export const generateTwoDMarkersChart1 = async (
  data,
  bucketName,
  objectName
) => {
  try {
    // 创建临时目录
    const tempDir = path.join(process.cwd(), "images");
    await fs.ensureDir(tempDir);
    const tempFilePath = path.join(
      tempDir,
      `temp_scatter_chart_${Date.now()}.jpeg`
    );

    // 获取 plotly.js 的绝对路径
    const plotlyPath = path.join(
      process.cwd(),
      "src",
      "public",
      "js",
      "plotly-3.0.1.min.js"
    );
    const plotlyContent = await fs.readFile(plotlyPath, "utf-8");

    // 创建浏览器实例
    const browser = await puppeteer.launch({
      headless: "new",
      args: ["--no-sandbox", "--disable-setuid-sandbox"],
    });

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

      // 提取散点数据和线数据
      const scatterData = data.data.filter(
        (item) => item.engineName !== "合同功率曲线"
      )[0]; // 点数据

      const lineData = data.data.filter(
        (item) =>
          item.engineName === "合同功率曲线" ||
          item.enginName === "合同功率曲线"
      )[0]; // 线数据

      // 提取唯一时间标签，并计算 tickvals 和 ticktext
      const uniqueTimeLabels = scatterData.colorbar
        ? [...new Set(scatterData.colorbar)]
        : [...new Set(scatterData.color)];
      const tickvals = uniqueTimeLabels.map((_, index) => index + 1);
      const ticktext = uniqueTimeLabels.map((dateStr) => {
        const date = new Date(dateStr);
        return date.toLocaleDateString("en-CA", {
          year: "numeric",
          month: "2-digit",
        });
      });

      const timeMapping = uniqueTimeLabels.reduce((acc, curr, index) => {
        acc[curr] = index + 1;
        return acc;
      }, {});

      // 计算颜色值映射
      let colorValues = scatterData.colorbar
        ? scatterData.colorbar.map((date) => timeMapping[date])
        : scatterData.color.map((date) => timeMapping[date]);

      // 绘制散点图
      const scatterTrace = {
        x: scatterData.xData,
        y: scatterData.yData,
        mode: "markers",
        type: "scattergl", // 使用 scattergl 提高性能
        text: scatterData.engineName, // 提示文本
        marker: {
          color: colorValues,
          colorscale: [
            [0, "#F9FDD2"],
            [0.15, "#E9F6BD"],
            [0.3, "#C2E3B9"],
            [0.45, "#8AC8BE"],
            [0.6, "#5CA8BF"],
            [0.75, "#407DB3"],
            [0.9, "#2E4C9A"],
            [1, "#1B2973"],
          ],
          size: new Array(scatterData.xData.length).fill(6), // 点的大小
        },
        hovertemplate: `${data.xaixs}: %{x} <br> ${data.yaixs}: %{y} <br> 时间: %{customdata}<extra></extra>`,
        customdata: scatterData.colorbar || scatterData.color, // 将格式化后的时间存入 customdata
      };

      // 绘制线图
      let lineTrace = {};
      if (lineData) {
        lineTrace = {
          x: lineData.xData,
          y: lineData.yData,
          mode: "lines+markers", // 线和点同时显示
          type: "scattergl", // 使用 scattergl 类型
          text: lineData.engineName, // 提示文本
          line: {
            color: "red", // 线条颜色
          },
        };
      }
      console.log(lineData, lineTrace, "2222");
      // 图表布局
      const layout = {
        title: {
          text: scatterData.title,
          font: {
            size: 16,
            weight: "bold",
          },
        },
        xaxis: {
          title: {
            text: data.xaixs,
          },
          gridcolor: "rgb(255,255,255)",
          tickcolor: "rgb(255,255,255)",
          backgroundcolor: "#e5ecf6",
          showbackground: true,
        },
        yaxis: {
          title: {
            text: data.yaixs,
          },
          gridcolor: "rgb(255,255,255)",
          tickcolor: "rgb(255,255,255)",
          backgroundcolor: "#e5ecf6",
          showbackground: true,
        },
        showlegend: false,
        plot_bgcolor: "#e5ecf6",
        gridcolor: "#fff",
      };

      // 准备 HTML 内容
      const htmlContent = `
        <!DOCTYPE html>
        <html>
        <head>
          <meta charset="UTF-8">
          <title>2D 散点图</title>
          <script>${plotlyContent}</script>
        </head>
        <body>
          <div id="chart" style="width: 100%; height: 600px"></div>
          <script>
            const traces = [${JSON.stringify(scatterTrace)}${
        lineTrace ? `, ${JSON.stringify(lineTrace)}` : ""
      }];
            const layout = ${JSON.stringify(layout)};
            Plotly.newPlot('chart', traces, layout, { responsive: true }).then(() => {
              window.chartRendered = true; // 确保在图表渲染完成后设置
              console.log("图表渲染完成");
            }).catch((error) => {
              console.error("图表渲染错误:", error); // 捕获渲染错误
            });
          </script>
        </body>
        </html>
      `;

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

      // 等待图表渲染完成，延长超时时间
      await page.waitForFunction(() => window.chartRendered === true, {
        timeout: 150000, // 延长到 150 秒
      });

      // 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));
      // return formData;
      // 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;
    } catch (error) {
      console.error("生成2D散点图失败:", error);
      throw error;
    } finally {
      await browser.close();
    }
  } catch (error) {
    console.error("生成2D散点图失败:", error);
    throw error;
  }
};