import puppeteer from "puppeteer";
import fs from "fs-extra";
import path from "path";
import FormData from "form-data";
import axios from "axios"; // 导入 axios
import { colorSchemes } from "../colors.js";
export const getYewErrorBarChart = async (
data,
bucketName,
objectName,
analysisTypeCode
) => {
try {
// 提取机组编号和偏航误差值
const xData = data.map((item) => item.engine_name); // 机组编号
const yData = data.map((item) => item.yaw_error1); // 偏航误差值
// 为每个数据点分配颜色
const colors = yData.map((value) => {
if (value <= 3) {
return "#8AC8BE"; // (0, 3] 蓝色
} else if (value <= 5) {
return "#407DB3"; // (3, 5] 绿色
} else {
return "#1B2973"; // (5, ∞] 红色
}
});
const trace = {
x: xData, // 横坐标数据
y: yData, // 纵坐标数据
type: "bar", // 当前图表类型
marker: {
color: colors, // 每个点的颜色
},
name: "偏航误差值", // 图例名称
};
// 创建虚拟的 trace 以便显示图例
const legendTrace1 = {
x: [null],
y: [null],
name: "(0, 3]",
mode: "markers",
marker: { color: "#8AC8BE", size: 10 },
};
const legendTrace2 = {
x: [null],
y: [null],
name: "(3, 5]",
mode: "markers",
marker: { color: "#407DB3", size: 10 },
};
const legendTrace3 = {
x: [null],
y: [null],
name: "(5, ∞]",
mode: "markers",
marker: { color: "#1B2973", size: 10 },
};
const layout = {
title: {
text: "机组静态偏航误差值", // 图表标题
font: {
size: 16, // 设置标题字体大小（默认 16）
weight: "bold",
},
},
xaxis: {
title: {
text: "机组编号",
}, // 横坐标标题
tickmode: "array",
tickvals: xData, // 设置刻度值（机组编号）
ticktext: xData, // 设置刻度文本（机组编号）
gridcolor: "rgb(255,255,255)",
tickcolor: "rgb(255,255,255)",
backgroundcolor: "#e5ecf6",
},
yaxis: {
title: {
text: "静态偏航误差值（度）",
}, // 纵坐标标题
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", // 设置背景颜色
autosize: true, // 开启自适应
showlegend: true, // 显示图例
};
// 创建临时目录
const tempDir = path.join(process.cwd(), "images");
await fs.ensureDir(tempDir);
const tempFilePath = path.join(
tempDir,
`temp_yew_error_bar_chart_${Date.now()}.jpeg`
);
// 获取 plotly.js 的绝对路径
const plotlyPath = path.join(
process.cwd(),
"src",
"public",
"js",
"plotly-3.0.1.min.js"
);
const plotlyContent = await fs.readFile(plotlyPath, "utf-8");
// 使用 Puppeteer 生成图表的截图
const browser = await puppeteer.launch({
headless: "new",
executablePath: `${process.env.CHROME_PATH}`, // 根据系统改路径
args: ["--no-sandbox", "--disable-setuid-sandbox"],
});
try {
const page = await browser.newPage();
const traces = [trace, legendTrace1, legendTrace2, legendTrace3];
const htmlContent = `
机组静态偏航误差值
`;
await page.setContent(htmlContent, { waitUntil: "networkidle0" });
await page.waitForFunction(() => window.chartRendered === true, {
timeout: 60000,
});
// 截图并保存到临时文件
const chartElement = await page.$("#chart");
await chartElement.screenshot({ path: tempFilePath, type: "jpeg" });
// 上传图片到服务器
const formData = new FormData();
formData.append("file", fs.createReadStream(tempFilePath));
const response = await axios.post(
`${process.env.API_BASE_URL}/examples/upload`,
{
filePath: tempFilePath,
bucketName,
objectName,
}
);
console.log("上传成功:", response.data);
return response?.data?.url;
} catch (error) {
console.error("生成图表失败:", error);
} finally {
await browser.close();
}
} catch (error) {
console.error("发生错误:", error);
}
};