增加了部署文档，调整了前端代码
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.env.example
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.env.example
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# 数据库配置
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MYSQL_HOST=localhost
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MYSQL_USER=root
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MYSQL_PASSWORD=your_password_here
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MYSQL_DATABASE=equipment_cost_db
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# 服务配置
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PORT=5001
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DEBUG=False
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# 日志配置
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LOG_LEVEL=INFO
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LOG_DIR=logs
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# 模型配置
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MODEL_DIR=models
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DATA_DIR=data
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# 安全配置
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SECRET_KEY=your_secret_key_here
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ALLOWED_HOSTS=localhost,127.0.0.1
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# 其他配置
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UPLOAD_MAX_SIZE=10485760 # 10MB in bytes
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ALLOWED_FILE_TYPES=.xlsx,.xls
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@ -8,8 +8,8 @@ DATABASE_URI = "mysql+pymysql://root:123456@localhost:3306/equipment_cost_db"
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SECRET_KEY = secrets.token_hex(16)
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# 环境配置
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DEBUG = True
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ENV = 'development'
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DEBUG = False
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ENV = 'production'
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# 文件上传配置
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UPLOAD_FOLDER = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'uploads')
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deploy/equipment_cost_system.tar.gz
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deploy/equipment_cost_system.tar.gz
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deploy/equipment_cost_system/config/.env.template
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deploy/equipment_cost_system/config/.env.template
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# 数据库配置
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MYSQL_HOST=localhost
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MYSQL_USER=root
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MYSQL_PASSWORD=your_password_here
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MYSQL_DATABASE=equipment_cost_db
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# 服务配置
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PORT=5001
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DEBUG=False
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# 日志配置
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LOG_LEVEL=INFO
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LOG_DIR=logs
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# 模型配置
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MODEL_DIR=models
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DATA_DIR=data
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# 安全配置
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SECRET_KEY=your_secret_key_here
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ALLOWED_HOSTS=localhost,127.0.0.1
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# 其他配置
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UPLOAD_MAX_SIZE=10485760 # 10MB in bytes
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ALLOWED_FILE_TYPES=.xlsx,.xls
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663
deploy/equipment_cost_system/docs/api.md
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deploy/equipment_cost_system/docs/api.md
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# 装备成本估算系统 API 文档
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这个 API 文档提供了完整的接口说明，包括：
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- 每个端点的详细描述
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- 请求和响应的具体示例
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- 清晰的参数格式要求
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- 统一的错误处理说明
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- 重要的注意事项
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文档使用 Markdown 格式编写，请使用支持 Markdown 的工具查看。
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## 基本信息
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- 基础URL: `http://localhost:5001/api`
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- 版本: 1.0.0
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- 响应格式: JSON
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## API 端点列表
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### 1. 获取 API 信息
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获取 API 版本信息和可用端点列表。
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- **URL**: `/`
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- **方法**: `GET`
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- **响应示例**:
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json
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{
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"name": "装备成本估算系统 API",
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"version": "1.0.0",
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"endpoints": {
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"predict": {
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"url": "/api/predict",
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"method": "POST",
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"description": "成本预测"
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},
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"analyze-features": {
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"url": "/api/analyze-features",
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"method": "POST",
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"description": "特征分析"
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},
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"train": {
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"url": "/api/train",
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"method": "POST",
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"description": "模型训练"
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},
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"evaluate": {
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"url": "/api/evaluate",
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"method": "POST",
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"description": "模型评估"
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}
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}
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}
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### 2. 单模型预测
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使用当前激活的最优模型进行成本预测。
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- **URL**: `/predict`
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- **方法**: `POST`
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- **请求体示例** (巡飞弹):
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```json
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{
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"type": "巡飞弹",
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"length_m": 1.3,
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"width_m": 0.23,
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"height_m": 0.23,
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"weight_kg": 12.5,
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"max_range_km": 40,
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"max_speed_ms": 50,
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"cruise_speed_kmh": 100,
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"flight_time_min": 60,
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"folded_length_mm": 1300,
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"folded_width_mm": 230,
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"folded_height_mm": 230,
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"warhead_type": "破片杀伤战斗部",
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"launch_mode": "凭自身动力起飞"
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}
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```
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- **响应示例**:
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```json
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{
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"predicted_cost": 150000.0,
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"model_info": {
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"type": "xgboost",
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"name": "巡飞弹_20241111_model",
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"r2_score": 0.95,
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"mae": 5000.0,
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"rmse": 7500.0
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},
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"confidence_interval": {
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"lower": 135000.0,
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"upper": 165000.0
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}
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}
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```
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### 3. PLS 模型预测
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使用 PLS 回归模型进行预测。
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- **URL**: `/pls/predict`
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- **方法**: `POST`
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- **请求体**: 与单模型预测相同
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- **响应示例**:
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```json
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{
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"predicted_cost": 148000.0,
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"confidence_interval": {
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"lower": 133000.0,
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"upper": 163000.0
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}
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}
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```
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### 4. 多模型预测
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使用所有激活的模型进行预测并返回综合结果。
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- **URL**: `/predict/all`
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- **方法**: `POST`
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- **请求体**: 与单模型预测相同
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- **响应示例**:
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```json
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{
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"individual_predictions": {
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"xgboost": {
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"predicted_cost": 150000.0,
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"model_info": {
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"name": "巡飞弹_xgboost_model",
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"type": "xgboost",
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"r2_score": 0.95,
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"mae": 5000.0,
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"rmse": 7500.0
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},
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"confidence_interval": {
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"lower": 135000.0,
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"upper": 165000.0
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}
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},
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"pls": {
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"predicted_cost": 148000.0,
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"model_info": {
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"name": "巡飞弹_pls_model",
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"type": "pls",
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"r2_score": 0.92,
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"mae": 5500.0,
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"rmse": 8000.0
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},
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"confidence_interval": {
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"lower": 133000.0,
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"upper": 163000.0
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}
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}
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},
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"ensemble_prediction": {
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"predicted_cost": 149000.0,
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"standard_deviation": 1414.21,
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"confidence_interval": {
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"lower": 146228.15,
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"upper": 151771.85
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}
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}
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}
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```
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### 5. 特征分析
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分析数据集中特征的重要性和相关性。
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- **URL**: `/analyze-features`
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- **方法**: `POST`
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- **请求体示例**:
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```json
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{
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"dataset_id": 1,
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"equipment_type": "巡飞弹"
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}
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```
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- **响应示例**:
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```json
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{
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"important_features": [
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{
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"name": "最大射程(km)",
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"importance": 0.35
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},
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{
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"name": "重量(kg)",
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"importance": 0.25
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}
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],
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"correlation_analysis": {
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"features": ["最大射程(km)", "重量(kg)"],
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"matrix": [[1.0, 0.8], [0.8, 1.0]]
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}
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}
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```
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### 6. 模型训练
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训练新的模型。
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- **URL**: `/train`
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- **方法**: `POST`
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- **请求体示例**:
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```json
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{
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"type": "巡飞弹",
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"train_dataset_id": 1,
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"validation_dataset_id": 2,
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"models": ["xgboost", "lightgbm", "rf"]
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}
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```
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- **响应示例**:
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```json
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{
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"metrics": {
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"xgboost": {
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"train": {
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"r2": 0.95,
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"mae": 5000.0,
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"rmse": 7500.0
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},
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"validation": {
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"r2": 0.92,
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"mae": 5500.0,
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"rmse": 8000.0
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}
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}
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},
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"best_model": {
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"type": "xgboost",
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"r2": 0.92,
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"mae": 5500.0,
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"rmse": 8000.0
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}
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}
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```
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### 7. 数据集管理
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#### 7.1 获取数据集列表
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- **URL**: `/datasets`
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- **方法**: `GET`
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- **响应示例**:
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```json
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[
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{
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"id": 1,
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"name": "训练数据集",
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"description": "用于训练的数据集",
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"equipment_type": "巡飞弹",
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"equipment_count": 10,
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"equipment_names": ["设备1", "设备2"],
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"purpose": "训练",
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"created_at": "2024-11-11T10:00:00"
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}
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]
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```
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#### 7.2 获取数据集详情
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- **URL**: `/datasets/{id}`
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- **方法**: `GET`
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- **响应示例**:
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```json
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{
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"id": 1,
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"name": "训练数据集",
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"description": "用于训练的数据集",
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"equipment_type": "巡飞弹",
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"purpose": "训练",
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"created_at": "2024-11-11T10:00:00",
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"equipment": [
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{
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"id": 1,
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"name": "设备1",
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"type": "巡飞弹",
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"manufacturer": "制造商1",
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"actual_cost": 150000
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}
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],
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"statistics": {
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"equipment_count": 10,
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"total_cost": 1500000,
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"average_cost": 150000
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}
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}
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```
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#### 7.3 创建数据集
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- **URL**: `/datasets`
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- **方法**: `POST`
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- **请求体示例**:
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```json
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{
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"name": "测试数据集",
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"description": "用于测试的数据集",
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"equipment_type": "巡飞弹",
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"purpose": "训练",
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"equipment_ids": [1, 2, 3]
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}
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```
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- **响应示例**:
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```json
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{
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"id": 2,
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"message": "数据集创建成功"
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}
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```
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#### 7.4 更新数据集
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- **URL**: `/datasets/{id}`
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- **方法**: `PUT`
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- **请求体示例**:
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```json
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{
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"name": "更新后的数据集名称",
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"description": "更新后的描述",
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"equipment_type": "巡飞弹",
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"purpose": "验证",
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"equipment_ids": [1, 2, 3, 4]
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}
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```
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- **响应示例**:
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```json
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{
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"success": true,
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"message": "数据集更新成功"
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}
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```
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#### 7.5 删除数据集
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- **URL**: `/datasets/{id}`
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- **方法**: `DELETE`
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- **描述**: 删除指定的数据集及其关联关系
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- **响应示例**:
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```json
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{
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"success": true,
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"message": "数据集删除成功"
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}
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```
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注意事项：
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1. 数据集删除后不会删除关联的装备数据
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2. 不能删除正在被模型使用的数据集
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3. 更新数据集时会重新计算统计信息
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4. 数据集的装备类型一旦创建后不能更改
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### 8. 模型管理
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#### 8.1 获取模型列表
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- **URL**: `/models`
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- **方法**: `GET`
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- **响应示例**:
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```json
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[
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{
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"id": 1,
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"model_name": "巡飞弹_xgboost_model",
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"model_type": "xgboost",
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"equipment_type": "巡飞弹",
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"r2_score": 0.95,
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"mae": 5000.0,
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"rmse": 7500.0,
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"is_active": true,
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"training_date": "2024-11-11T10:00:00"
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}
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]
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```
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#### 8.2 获取最新模型
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- **URL**: `/models/{equipment_type}/latest`
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- **方法**: `GET`
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- **响应示例**: 与模型列表的单个模型格式相同
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#### 8.3 获取模型详情
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- **URL**: `/models/{id}`
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- **方法**: `GET`
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- **响应示例**:
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```json
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{
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"id": 1,
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"model_name": "巡飞弹_xgboost_model",
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"model_type": "xgboost",
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"equipment_type": "巡飞弹",
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"r2_score": 0.95,
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"mae": 5000.0,
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"rmse": 7500.0,
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"is_active": true,
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"training_date": "2024-11-11T10:00:00",
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"feature_importance": {
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"max_range_km": 0.35,
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"weight_kg": 0.25,
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"length_m": 0.20
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},
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"training_data_size": 100,
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"created_by": "system"
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}
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```
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#### 8.4 激活模型
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- **URL**: `/models/{id}/activate`
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- **方法**: `POST`
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- **描述**: 激活指定模型，同时会将同类型的其他模型设置为非激活状态
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- **响应示例**:
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```json
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{
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"success": true,
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"message": "模型已激活"
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}
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```
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#### 8.5 删除模型
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- **URL**: `/models/{id}`
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- **方法**: `DELETE`
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- **描述**: 删除指定模型，包括模型文件和数据库记录
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- **响应示例**:
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||||
```json
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{
|
||||
"success": true,
|
||||
"message": "模型已删除"
|
||||
}
|
||||
```
|
||||
|
||||
注意事项：
|
||||
|
||||
1. 删除模型时会同时删除相关的文件和数据库记录
|
||||
2. 不能删除当前正在使用（已激活）的模型
|
||||
3. 激活模型时会自动取消同类型其他模型的激活状态
|
||||
4. 模型详情包含了更多的训练相关信息，如特征重要性等
|
||||
|
||||
### 9. 数据管理
|
||||
|
||||
#### 9.1 获取装备数据列表
|
||||
|
||||
- **URL**: `/data`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"rocket_artillery": [
|
||||
{
|
||||
"id": 1,
|
||||
"name": "BM-21",
|
||||
"type": "火箭炮",
|
||||
"manufacturer": "俄罗斯",
|
||||
"length_m": 7.35,
|
||||
"width_m": 2.4,
|
||||
"height_m": 3.1,
|
||||
"weight_kg": 13700,
|
||||
"max_range_km": 20.4,
|
||||
"actual_cost": 800000
|
||||
}
|
||||
],
|
||||
"loitering_munition": [
|
||||
{
|
||||
"id": 8,
|
||||
"name": "Hero-120",
|
||||
"type": "巡飞弹",
|
||||
"manufacturer": "以色列",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"actual_cost": 150000
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.2 获取装备详情
|
||||
|
||||
- **URL**: `/data/details/{id}`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": 8,
|
||||
"name": "Hero-120",
|
||||
"type": "巡飞弹",
|
||||
"manufacturer": "以色列",
|
||||
"common_params": {
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40
|
||||
},
|
||||
"specific_params": {
|
||||
"wingspan_m": 2.1,
|
||||
"warhead_weight_kg": 3.5,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "箱式发射",
|
||||
"power_system": "电动机",
|
||||
"guidance_system": "GPS/INS"
|
||||
},
|
||||
"cost_data": {
|
||||
"actual_cost": 150000,
|
||||
"prediction_date": "2024-11-11T10:00:00",
|
||||
"predicted_cost": 148000
|
||||
},
|
||||
"custom_params": [
|
||||
{
|
||||
"id": 1,
|
||||
"param_name": "续航时间",
|
||||
"param_value": "2小时",
|
||||
"param_unit": "小时",
|
||||
"description": "最大续航时间"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.3 更新装备数据
|
||||
|
||||
- **URL**: `/data/{id}`
|
||||
- **方法**: `PUT`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "Hero-120",
|
||||
"manufacturer": "以色列",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"wingspan_m": 2.1,
|
||||
"warhead_weight_kg": 3.5,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"actual_cost": 150000,
|
||||
"custom_params": [
|
||||
{
|
||||
"id": 1,
|
||||
"param_value": "2.5小时"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "装备数据更新成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.4 删除装备数据
|
||||
|
||||
- **URL**: `/data/{id}`
|
||||
- **方法**: `DELETE`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "装备数据删除成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.5 下载数据模板
|
||||
|
||||
- **URL**: `/data/template`
|
||||
- **方法**: `GET`
|
||||
- **描述**: 下载Excel格式的数据导入模板
|
||||
- **响应**: Excel文件下载
|
||||
|
||||
#### 9.6 导入数据
|
||||
|
||||
- **URL**: `/data/import`
|
||||
- **方法**: `POST`
|
||||
- **请求体**:
|
||||
- Content-Type: multipart/form-data
|
||||
- 参数名: file
|
||||
- 文件类型: .xlsx 或 .xls
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "数据导入成功",
|
||||
"imported_count": {
|
||||
"rocket_artillery": 3,
|
||||
"loitering_munition": 5
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
注意事项：
|
||||
|
||||
1. 导入数据时必须使用系统提供的模板
|
||||
2. 更新装备数据时会同时更新关联的参数表
|
||||
3. 删除装备数据会同时删除相关的参数和成本数据
|
||||
4. 导入的Excel文件大小不应超过10MB
|
||||
5. 所有数值字段必须符合指定的单位和范围要求
|
||||
6. 特殊参数的值必须包含单位信息
|
||||
|
||||
## 错误响应
|
||||
|
||||
所有接口在发生错误时都会返回以下格式的响应：
|
||||
|
||||
```json
|
||||
{
|
||||
"error": "错误描述信息"
|
||||
}
|
||||
```
|
||||
|
||||
## 注意事项
|
||||
|
||||
1. 所有数值参数必须大于0
|
||||
2. 所有单位必须按照参数名称中指定的单位提供
|
||||
3. 预测结果中的成本单位为元
|
||||
4. 置信区间表示预测结果的95%置信水平范围
|
||||
5. 所有请求和响应的编码均为 UTF-8
|
||||
120
deploy/equipment_cost_system/docs/deploy.md
Normal file
120
deploy/equipment_cost_system/docs/deploy.md
Normal file
@ -0,0 +1,120 @@
|
||||
# 装备成本估算系统部署指南
|
||||
|
||||
## 一、系统要求
|
||||
|
||||
### 1. 基础软件
|
||||
|
||||
- Linux 操作系统 (推荐 Ubuntu 20.04+)
|
||||
- Python 3.8+ 及相关组件
|
||||
|
||||
```bash
|
||||
sudo apt update
|
||||
sudo apt install python3 python3-pip python3-venv
|
||||
sudo apt install python3-dev build-essential
|
||||
```
|
||||
|
||||
- Node.js 14+ 及 npm
|
||||
|
||||
```bash
|
||||
# 使用 nvm 安装 Node.js
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
|
||||
source ~/.bashrc
|
||||
nvm install 14
|
||||
nvm use 14
|
||||
```
|
||||
|
||||
### 2. 数据库
|
||||
|
||||
- MySQL 8.0+
|
||||
|
||||
```bash
|
||||
sudo apt install mysql-server mysql-client
|
||||
sudo apt install libmysqlclient-dev
|
||||
```
|
||||
|
||||
### 3. Python包依赖
|
||||
|
||||
```bash
|
||||
# 科学计算相关
|
||||
sudo apt install libatlas-base-dev # numpy依赖
|
||||
sudo apt install libopenblas-dev # 线性代数库
|
||||
sudo apt install liblapack-dev # 线性代数包
|
||||
sudo apt install gfortran # Fortran编译器(scipy依赖)
|
||||
|
||||
# XML处理相关(用于Excel文件处理)
|
||||
sudo apt install libxml2-dev
|
||||
sudo apt install libxslt1-dev
|
||||
```
|
||||
|
||||
## 二、部署运行
|
||||
|
||||
### 1. 安装服务
|
||||
|
||||
```bash
|
||||
sh scripts/install.sh
|
||||
```
|
||||
|
||||
### 2. 启动服务
|
||||
|
||||
```bash
|
||||
sh scripts/start.sh
|
||||
```
|
||||
|
||||
### 3. 停止服务
|
||||
|
||||
```bash
|
||||
sh scripts/stop.sh
|
||||
```
|
||||
|
||||
## 三、维护说明
|
||||
|
||||
### 1. 日志管理
|
||||
|
||||
```bash
|
||||
# 后端日志
|
||||
tail -f logs/api.log
|
||||
|
||||
# 数据库日志
|
||||
tail -f /var/log/mysql/error.log
|
||||
```
|
||||
|
||||
## 四、安全建议
|
||||
|
||||
1. 系统安全
|
||||
- 使用防火墙限制端口访问
|
||||
- 定期更新系统和依赖包
|
||||
|
||||
2. 数据安全
|
||||
- 定期备份数据库
|
||||
- 加密敏感信息
|
||||
- 限制数据库远程访问
|
||||
|
||||
3. 访问控制
|
||||
- 使用强密码
|
||||
- 配置适当的文件权限
|
||||
- 使用非root用户运行服务
|
||||
|
||||
## 五、监控方案
|
||||
|
||||
### 1. 系统监控
|
||||
|
||||
```bash
|
||||
# 资源使用
|
||||
top -b -n 1
|
||||
df -h
|
||||
free -m
|
||||
|
||||
# 服务状态
|
||||
ps aux | grep gunicorn
|
||||
ps aux | grep node
|
||||
```
|
||||
|
||||
### 2. 应用监控
|
||||
|
||||
```bash
|
||||
# API 响应时间
|
||||
curl -w "@curl-format.txt" -o /dev/null -s "http://localhost:5001/api/"
|
||||
|
||||
# 错误日志
|
||||
grep "ERROR" logs/api.log
|
||||
```
|
||||
5
deploy/equipment_cost_system/frontend/babel.config.js
Normal file
5
deploy/equipment_cost_system/frontend/babel.config.js
Normal file
@ -0,0 +1,5 @@
|
||||
module.exports = {
|
||||
presets: [
|
||||
'@vue/cli-plugin-babel/preset'
|
||||
]
|
||||
}
|
||||
61
deploy/equipment_cost_system/frontend/package.json
Normal file
61
deploy/equipment_cost_system/frontend/package.json
Normal file
@ -0,0 +1,61 @@
|
||||
{
|
||||
"name": "frontend",
|
||||
"version": "0.1.0",
|
||||
"private": true,
|
||||
"engines": {
|
||||
"node": ">=16",
|
||||
"npm": ">=8"
|
||||
},
|
||||
"scripts": {
|
||||
"serve": "vue-cli-service serve",
|
||||
"build": "vue-cli-service build",
|
||||
"lint": "vue-cli-service lint"
|
||||
},
|
||||
"dependencies": {
|
||||
"axios": "^1.6.0",
|
||||
"core-js": "^3.8.3",
|
||||
"echarts": "^5.4.3",
|
||||
"element-plus": "^2.4.2",
|
||||
"vue": "^3.2.13",
|
||||
"vue-router": "^4.0.3",
|
||||
"vuex": "^4.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@babel/core": "^7.12.16",
|
||||
"@babel/eslint-parser": "^7.12.16",
|
||||
"@element-plus/icons-vue": "^2.3.1",
|
||||
"@vue/cli-plugin-babel": "~5.0.0",
|
||||
"@vue/cli-plugin-eslint": "~5.0.0",
|
||||
"@vue/cli-plugin-router": "~5.0.0",
|
||||
"@vue/cli-plugin-vuex": "~5.0.0",
|
||||
"@vue/cli-service": "~5.0.0",
|
||||
"@vue/compiler-sfc": "^3.2.13",
|
||||
"eslint": "^7.32.0",
|
||||
"eslint-plugin-vue": "^8.0.3",
|
||||
"sass": "^1.32.7",
|
||||
"sass-loader": "^12.0.0"
|
||||
},
|
||||
"eslintConfig": {
|
||||
"root": true,
|
||||
"env": {
|
||||
"node": true
|
||||
},
|
||||
"extends": [
|
||||
"plugin:vue/vue3-essential",
|
||||
"eslint:recommended"
|
||||
],
|
||||
"parserOptions": {
|
||||
"parser": "@babel/eslint-parser"
|
||||
},
|
||||
"rules": {
|
||||
"vue/multi-word-component-names": "off",
|
||||
"no-unused-vars": "warn"
|
||||
}
|
||||
},
|
||||
"browserslist": [
|
||||
"> 1%",
|
||||
"last 2 versions",
|
||||
"not dead",
|
||||
"not ie 11"
|
||||
]
|
||||
}
|
||||
BIN
deploy/equipment_cost_system/frontend/public/favicon.ico
Normal file
BIN
deploy/equipment_cost_system/frontend/public/favicon.ico
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 4.2 KiB |
17
deploy/equipment_cost_system/frontend/public/index.html
Normal file
17
deploy/equipment_cost_system/frontend/public/index.html
Normal file
@ -0,0 +1,17 @@
|
||||
<!DOCTYPE html>
|
||||
<html lang="">
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=edge">
|
||||
<meta name="viewport" content="width=device-width,initial-scale=1.0">
|
||||
<link rel="icon" href="<%= BASE_URL %>favicon.ico">
|
||||
<title><%= htmlWebpackPlugin.options.title %></title>
|
||||
</head>
|
||||
<body>
|
||||
<noscript>
|
||||
<strong>We're sorry but <%= htmlWebpackPlugin.options.title %> doesn't work properly without JavaScript enabled. Please enable it to continue.</strong>
|
||||
</noscript>
|
||||
<div id="app"></div>
|
||||
<!-- built files will be auto injected -->
|
||||
</body>
|
||||
</html>
|
||||
42
deploy/equipment_cost_system/frontend/src/App.vue
Normal file
42
deploy/equipment_cost_system/frontend/src/App.vue
Normal file
@ -0,0 +1,42 @@
|
||||
<template>
|
||||
<el-container>
|
||||
<el-header>
|
||||
<el-menu
|
||||
:router="true"
|
||||
mode="horizontal"
|
||||
:default-active="$route.path"
|
||||
>
|
||||
<el-menu-item index="/">首页</el-menu-item>
|
||||
<el-menu-item index="/predict">成本预测</el-menu-item>
|
||||
<el-menu-item index="/analysis">特征分析</el-menu-item>
|
||||
<el-menu-item index="/training">模型训练</el-menu-item>
|
||||
<el-menu-item index="/models">模型管理</el-menu-item>
|
||||
<el-menu-item index="/datasets">数据集管理</el-menu-item>
|
||||
<el-menu-item index="/data">数据管理</el-menu-item>
|
||||
</el-menu>
|
||||
</el-header>
|
||||
|
||||
<el-main>
|
||||
<router-view v-slot="{ Component }">
|
||||
<keep-alive>
|
||||
<component :is="Component" :key="$route.fullPath" />
|
||||
</keep-alive>
|
||||
</router-view>
|
||||
</el-main>
|
||||
</el-container>
|
||||
</template>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.el-header {
|
||||
padding: 0;
|
||||
|
||||
.el-menu {
|
||||
border-bottom: none;
|
||||
}
|
||||
}
|
||||
|
||||
.el-main {
|
||||
background-color: #f5f7fa;
|
||||
min-height: calc(100vh - 60px);
|
||||
}
|
||||
</style>
|
||||
43
deploy/equipment_cost_system/frontend/src/api/index.js
Normal file
43
deploy/equipment_cost_system/frontend/src/api/index.js
Normal file
@ -0,0 +1,43 @@
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
|
||||
const api = axios.create({
|
||||
baseURL: API_BASE_URL,
|
||||
timeout: 10000
|
||||
})
|
||||
|
||||
export const predict = (data) => {
|
||||
return api.post('/predict', data)
|
||||
}
|
||||
|
||||
export const analyzeFeatures = (data) => {
|
||||
return api.post('/analyze-features', data)
|
||||
}
|
||||
|
||||
export const trainModel = (data) => {
|
||||
return api.post('/train', data)
|
||||
}
|
||||
|
||||
export const evaluateModel = (data) => {
|
||||
return api.post('/evaluate', data)
|
||||
}
|
||||
|
||||
export const importData = (formData) => {
|
||||
return api.post('/data/import', formData, {
|
||||
headers: {
|
||||
'Content-Type': 'multipart/form-data'
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
export const getEquipmentData = () => {
|
||||
return api.get('/data')
|
||||
}
|
||||
|
||||
export const updateEquipment = (id, data) => {
|
||||
return api.put(`/data/${id}`, data)
|
||||
}
|
||||
|
||||
export const deleteEquipment = (id) => {
|
||||
return api.delete(`/data/${id}`)
|
||||
}
|
||||
BIN
deploy/equipment_cost_system/frontend/src/assets/logo.png
Normal file
BIN
deploy/equipment_cost_system/frontend/src/assets/logo.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 6.7 KiB |
@ -0,0 +1,39 @@
|
||||
/* 禁用 ResizeObserver 警告 */
|
||||
iframe[style*="position: fixed; top: 0px; left: 0px; width: 100%; height: 100%; border: none; z-index: 2147483647;"] {
|
||||
display: none !important;
|
||||
}
|
||||
|
||||
.el-overlay {
|
||||
overflow: hidden !important;
|
||||
}
|
||||
|
||||
/* 添加全局样式 */
|
||||
body {
|
||||
margin: 0;
|
||||
padding: 0;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* 修复 Element Plus 的一些已知问题 */
|
||||
.el-dialog__wrapper {
|
||||
overflow: hidden !important;
|
||||
}
|
||||
|
||||
.el-select-dropdown {
|
||||
overflow: hidden !important;
|
||||
}
|
||||
|
||||
/* 禁用 ResizeObserver 相关的警告样式 */
|
||||
.resize-observer-warning {
|
||||
display: none !important;
|
||||
}
|
||||
|
||||
/* 优化滚动行为 */
|
||||
* {
|
||||
scroll-behavior: smooth;
|
||||
}
|
||||
|
||||
/* 防止页面抖动 */
|
||||
.el-main {
|
||||
overflow-x: hidden;
|
||||
}
|
||||
8
deploy/equipment_cost_system/frontend/src/config.js
Normal file
8
deploy/equipment_cost_system/frontend/src/config.js
Normal file
@ -0,0 +1,8 @@
|
||||
export const API_BASE_URL = 'http://localhost:5001/api';
|
||||
|
||||
export const DB_CONFIG = {
|
||||
host: 'localhost',
|
||||
user: 'root',
|
||||
password: '123456',
|
||||
database: 'equipment_cost_db'
|
||||
};
|
||||
55
deploy/equipment_cost_system/frontend/src/main.js
Normal file
55
deploy/equipment_cost_system/frontend/src/main.js
Normal file
@ -0,0 +1,55 @@
|
||||
import { createApp } from 'vue'
|
||||
import App from './App.vue'
|
||||
import router from './router'
|
||||
import store from './store'
|
||||
import ElementPlus from 'element-plus'
|
||||
import 'element-plus/dist/index.css'
|
||||
import './assets/styles/global.css'
|
||||
import * as ElementPlusIconsVue from '@element-plus/icons-vue'
|
||||
|
||||
// 创建应用实例
|
||||
const app = createApp(App)
|
||||
|
||||
// 注册插件
|
||||
app.use(ElementPlus, {
|
||||
size: 'default'
|
||||
})
|
||||
app.use(router)
|
||||
app.use(store)
|
||||
|
||||
// 注册图标
|
||||
for (const [key, component] of Object.entries(ElementPlusIconsVue)) {
|
||||
app.component(key, component)
|
||||
}
|
||||
|
||||
// 全局错误处理
|
||||
app.config.errorHandler = (err) => {
|
||||
if (err.message && err.message.includes('ResizeObserver')) {
|
||||
return
|
||||
}
|
||||
console.error(err)
|
||||
}
|
||||
|
||||
// 全局警告处理
|
||||
app.config.warnHandler = (msg, trace) => {
|
||||
if (msg.includes('ResizeObserver')) {
|
||||
return
|
||||
}
|
||||
console.warn(msg, trace)
|
||||
}
|
||||
|
||||
// 挂载应用
|
||||
app.mount('#app')
|
||||
|
||||
// 处理 ResizeObserver 错误
|
||||
const _ResizeObserver = window.ResizeObserver
|
||||
window.ResizeObserver = class ResizeObserver extends _ResizeObserver {
|
||||
constructor(callback) {
|
||||
super((entries, observer) => {
|
||||
requestAnimationFrame(() => {
|
||||
if (!Array.isArray(entries)) return
|
||||
callback(entries, observer)
|
||||
})
|
||||
})
|
||||
}
|
||||
}
|
||||
52
deploy/equipment_cost_system/frontend/src/router/index.js
Normal file
52
deploy/equipment_cost_system/frontend/src/router/index.js
Normal file
@ -0,0 +1,52 @@
|
||||
import { createRouter, createWebHistory } from 'vue-router'
|
||||
import HomePage from '@/views/HomePage.vue'
|
||||
import DataPage from '@/views/DataPage.vue'
|
||||
import DatasetPage from '@/views/DatasetPage.vue'
|
||||
import PredictPage from '@/views/PredictPage.vue'
|
||||
import AnalysisPage from '@/views/AnalysisPage.vue'
|
||||
import TrainingPage from '@/views/TrainingPage.vue'
|
||||
|
||||
const routes = [
|
||||
{
|
||||
path: '/',
|
||||
name: 'Home',
|
||||
component: HomePage
|
||||
},
|
||||
{
|
||||
path: '/data',
|
||||
name: 'Data',
|
||||
component: DataPage
|
||||
},
|
||||
{
|
||||
path: '/datasets',
|
||||
name: 'Datasets',
|
||||
component: DatasetPage
|
||||
},
|
||||
{
|
||||
path: '/predict',
|
||||
name: 'Predict',
|
||||
component: PredictPage
|
||||
},
|
||||
{
|
||||
path: '/analysis',
|
||||
name: 'Analysis',
|
||||
component: AnalysisPage
|
||||
},
|
||||
{
|
||||
path: '/training',
|
||||
name: 'Training',
|
||||
component: TrainingPage
|
||||
},
|
||||
{
|
||||
path: '/models',
|
||||
name: 'Models',
|
||||
component: () => import('../views/ModelPage.vue')
|
||||
}
|
||||
]
|
||||
|
||||
const router = createRouter({
|
||||
history: createWebHistory(),
|
||||
routes
|
||||
})
|
||||
|
||||
export default router
|
||||
14
deploy/equipment_cost_system/frontend/src/store/index.js
Normal file
14
deploy/equipment_cost_system/frontend/src/store/index.js
Normal file
@ -0,0 +1,14 @@
|
||||
import { createStore } from 'vuex'
|
||||
|
||||
export default createStore({
|
||||
state: {
|
||||
},
|
||||
getters: {
|
||||
},
|
||||
mutations: {
|
||||
},
|
||||
actions: {
|
||||
},
|
||||
modules: {
|
||||
}
|
||||
})
|
||||
@ -0,0 +1,73 @@
|
||||
// 处理 ResizeObserver 错误
|
||||
const resizeHandler = () => {
|
||||
const resizeObserverErrors = [
|
||||
"ResizeObserver loop completed with undelivered notifications.",
|
||||
"ResizeObserver loop limit exceeded",
|
||||
"ResizeObserver loop completed"
|
||||
]
|
||||
|
||||
// 添加全局错误处理
|
||||
const handler = (event) => {
|
||||
if (event && event.message && resizeObserverErrors.includes(event.message)) {
|
||||
event.stopPropagation()
|
||||
event.preventDefault()
|
||||
event.stopImmediatePropagation()
|
||||
return false
|
||||
}
|
||||
}
|
||||
|
||||
// 添加多个事件监听器
|
||||
window.addEventListener('error', handler, true)
|
||||
window.addEventListener('unhandledrejection', handler, true)
|
||||
|
||||
// 添加 ResizeObserver 错误处理
|
||||
if (window.ResizeObserver) {
|
||||
const resizeObserverPrototype = ResizeObserver.prototype
|
||||
const originalObserve = resizeObserverPrototype.observe
|
||||
|
||||
resizeObserverPrototype.observe = function (...args) {
|
||||
try {
|
||||
return originalObserve.apply(this, args)
|
||||
} catch (e) {
|
||||
if (resizeObserverErrors.includes(e.message)) {
|
||||
return null
|
||||
}
|
||||
throw e
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export default {
|
||||
install: (app) => {
|
||||
resizeHandler()
|
||||
|
||||
// 添加全局错误处理器
|
||||
app.config.errorHandler = (err, vm, info) => {
|
||||
const resizeObserverErrors = [
|
||||
"ResizeObserver loop completed with undelivered notifications.",
|
||||
"ResizeObserver loop limit exceeded",
|
||||
"ResizeObserver loop completed"
|
||||
]
|
||||
|
||||
if (err && err.message && resizeObserverErrors.includes(err.message)) {
|
||||
return
|
||||
}
|
||||
console.error('Vue Error:', err, info)
|
||||
}
|
||||
|
||||
// 添加全局警告处理器
|
||||
app.config.warnHandler = (msg, vm, trace) => {
|
||||
const resizeObserverErrors = [
|
||||
"ResizeObserver loop completed with undelivered notifications.",
|
||||
"ResizeObserver loop limit exceeded",
|
||||
"ResizeObserver loop completed"
|
||||
]
|
||||
|
||||
if (resizeObserverErrors.includes(msg)) {
|
||||
return
|
||||
}
|
||||
console.warn('Vue Warning:', msg, trace)
|
||||
}
|
||||
}
|
||||
}
|
||||
304
deploy/equipment_cost_system/frontend/src/views/AnalysisPage.vue
Normal file
304
deploy/equipment_cost_system/frontend/src/views/AnalysisPage.vue
Normal file
@ -0,0 +1,304 @@
|
||||
<template>
|
||||
<div class="analysis-page">
|
||||
<el-card class="analysis-card">
|
||||
<template #header>
|
||||
<div class="header-content">
|
||||
<h2>特征分析</h2>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<!-- 数据集选择 -->
|
||||
<div class="dataset-section">
|
||||
<el-form :model="analysisForm" label-width="120px">
|
||||
<el-form-item label="装备类型" required>
|
||||
<el-select v-model="analysisForm.equipment_type" @change="handleEquipmentTypeChange">
|
||||
<el-option label="火箭炮" value="火箭炮"></el-option>
|
||||
<el-option label="巡飞弹" value="巡飞弹"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
|
||||
<el-form-item label="选择数据集" required>
|
||||
<el-select v-model="analysisForm.dataset_id" @change="handleDatasetChange">
|
||||
<el-option
|
||||
v-for="dataset in availableDatasets"
|
||||
:key="dataset.id"
|
||||
:label="dataset.name"
|
||||
:value="dataset.id"
|
||||
></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
</el-form>
|
||||
|
||||
<!-- 数据集信息 -->
|
||||
<el-descriptions v-if="selectedDataset" :column="2" border>
|
||||
<el-descriptions-item label="数据集名称">{{ selectedDataset.name }}</el-descriptions-item>
|
||||
<el-descriptions-item label="装备数量">{{ selectedDataset.equipment_count }}</el-descriptions-item>
|
||||
<el-descriptions-item label="描述" :span="2">{{ selectedDataset.description }}</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
</div>
|
||||
|
||||
<!-- 分析按钮 -->
|
||||
<div class="action-section">
|
||||
<el-button type="primary" @click="startAnalysis" :loading="analyzing" :disabled="!analysisForm.dataset_id">
|
||||
{{ analyzing ? '分析中...' : '开始分析' }}
|
||||
</el-button>
|
||||
</div>
|
||||
|
||||
<!-- 分析结果 -->
|
||||
<div v-if="analysisResult" class="result-section">
|
||||
<el-divider content-position="left">分析结果</el-divider>
|
||||
|
||||
<!-- 特征重要性 -->
|
||||
<h3>特征重要性</h3>
|
||||
<div class="chart-container">
|
||||
<div ref="importanceChartRef" style="width: 100%; height: 400px"></div>
|
||||
</div>
|
||||
|
||||
<!-- 相关性分析 -->
|
||||
<h3>相关性分析</h3>
|
||||
<div class="chart-container">
|
||||
<div ref="correlationChartRef" style="width: 100%; height: 500px"></div>
|
||||
</div>
|
||||
</div>
|
||||
</el-card>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, onMounted, watch, nextTick, onUnmounted } from 'vue'
|
||||
import { ElMessage } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
import * as echarts from 'echarts'
|
||||
|
||||
// 响应式数据
|
||||
const analysisForm = ref({
|
||||
equipment_type: '',
|
||||
dataset_id: null
|
||||
})
|
||||
const availableDatasets = ref([])
|
||||
const selectedDataset = ref(null)
|
||||
const analyzing = ref(false)
|
||||
const analysisResult = ref(null)
|
||||
const importanceChartRef = ref(null)
|
||||
const correlationChartRef = ref(null)
|
||||
|
||||
// 图表实例引用
|
||||
const importanceChart = ref(null)
|
||||
const correlationChart = ref(null)
|
||||
|
||||
// 监听分析结果变化
|
||||
watch(() => analysisResult.value, async (newResult) => {
|
||||
if (newResult) {
|
||||
console.log('Analysis result updated:', newResult)
|
||||
// 等待下一个 tick，确保 DOM 已更新
|
||||
await nextTick()
|
||||
// 延迟一点时间再渲染图表
|
||||
setTimeout(() => {
|
||||
renderCharts()
|
||||
}, 100)
|
||||
}
|
||||
}, { deep: true })
|
||||
|
||||
// 加载可用数据集
|
||||
const loadDatasets = async (type) => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/datasets`, {
|
||||
params: { equipment_type: type, purpose: '训练' }
|
||||
})
|
||||
availableDatasets.value = response.data
|
||||
} catch (error) {
|
||||
ElMessage.error('获取数据集列表失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 处理装备类型变化
|
||||
const handleEquipmentTypeChange = () => {
|
||||
analysisForm.value.dataset_id = null
|
||||
selectedDataset.value = null
|
||||
analysisResult.value = null
|
||||
loadDatasets(analysisForm.value.equipment_type)
|
||||
}
|
||||
|
||||
// 处理数据集选择变化
|
||||
const handleDatasetChange = async () => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/datasets/${analysisForm.value.dataset_id}`)
|
||||
selectedDataset.value = response.data
|
||||
analysisResult.value = null
|
||||
} catch (error) {
|
||||
ElMessage.error('获取数据集详情失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 开始分析
|
||||
const startAnalysis = async () => {
|
||||
if (!analysisForm.value.dataset_id) {
|
||||
ElMessage.warning('请先选择数据集')
|
||||
return
|
||||
}
|
||||
|
||||
analyzing.value = true
|
||||
try {
|
||||
const response = await axios.post(`${API_BASE_URL}/analyze-features`, {
|
||||
dataset_id: analysisForm.value.dataset_id
|
||||
})
|
||||
analysisResult.value = response.data
|
||||
console.log('Analysis completed, result:', analysisResult.value)
|
||||
} catch (error) {
|
||||
ElMessage.error('特征分析失败')
|
||||
console.error('Analysis error:', error)
|
||||
} finally {
|
||||
analyzing.value = false
|
||||
}
|
||||
}
|
||||
|
||||
// 渲染图表
|
||||
const renderCharts = () => {
|
||||
console.log('Starting to render charts')
|
||||
|
||||
// 销毁旧的图表实例
|
||||
if (importanceChart.value) {
|
||||
importanceChart.value.dispose()
|
||||
}
|
||||
if (correlationChart.value) {
|
||||
correlationChart.value.dispose()
|
||||
}
|
||||
|
||||
// 确保 DOM 元素存在
|
||||
if (!importanceChartRef.value || !correlationChartRef.value) {
|
||||
console.log('Chart DOM elements not ready')
|
||||
return
|
||||
}
|
||||
|
||||
try {
|
||||
// 创建新的图表实例
|
||||
importanceChart.value = echarts.init(importanceChartRef.value)
|
||||
correlationChart.value = echarts.init(correlationChartRef.value)
|
||||
|
||||
// 设置图表选项
|
||||
importanceChart.value.setOption({
|
||||
title: { text: '特征重要性排序' },
|
||||
tooltip: {},
|
||||
xAxis: {
|
||||
type: 'value',
|
||||
name: '重要性得分'
|
||||
},
|
||||
yAxis: {
|
||||
type: 'category',
|
||||
data: analysisResult.value.important_features.map(f => f.name)
|
||||
},
|
||||
series: [{
|
||||
type: 'bar',
|
||||
data: analysisResult.value.important_features.map(f => f.importance)
|
||||
}]
|
||||
})
|
||||
|
||||
correlationChart.value.setOption({
|
||||
title: { text: '特征相关性热力图' },
|
||||
tooltip: {
|
||||
position: 'top',
|
||||
formatter: function (params) {
|
||||
const value = params.data[2].toFixed(2)
|
||||
const feature1 = analysisResult.value.correlation_analysis.features[params.data[0]]
|
||||
const feature2 = analysisResult.value.correlation_analysis.features[params.data[1]]
|
||||
return `${feature1} 与 ${feature2} 的相关性: ${value}`
|
||||
}
|
||||
},
|
||||
grid: {
|
||||
height: '50%',
|
||||
top: '10%'
|
||||
},
|
||||
xAxis: {
|
||||
type: 'category',
|
||||
data: analysisResult.value.correlation_analysis.features,
|
||||
splitArea: { show: true },
|
||||
axisLabel: {
|
||||
interval: 0,
|
||||
rotate: 45
|
||||
}
|
||||
},
|
||||
yAxis: {
|
||||
type: 'category',
|
||||
data: analysisResult.value.correlation_analysis.features,
|
||||
splitArea: { show: true }
|
||||
},
|
||||
visualMap: {
|
||||
min: -1,
|
||||
max: 1,
|
||||
calculable: true,
|
||||
orient: 'horizontal',
|
||||
left: 'center',
|
||||
bottom: '15%',
|
||||
color: ['#cc3333', '#eeeeee', '#00007f']
|
||||
},
|
||||
series: [{
|
||||
type: 'heatmap',
|
||||
data: analysisResult.value.correlation_analysis.matrix,
|
||||
label: {
|
||||
show: true,
|
||||
formatter: function(params) {
|
||||
return params.data[2].toFixed(2)
|
||||
}
|
||||
}
|
||||
}]
|
||||
})
|
||||
|
||||
// 监听窗口大小变化
|
||||
window.addEventListener('resize', () => {
|
||||
importanceChart.value?.resize()
|
||||
correlationChart.value?.resize()
|
||||
})
|
||||
|
||||
console.log('Charts rendered successfully')
|
||||
} catch (error) {
|
||||
console.error('Error rendering charts:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
// 可以在这里加载默认数据
|
||||
})
|
||||
|
||||
// 组件卸载时清理图表实例
|
||||
onUnmounted(() => {
|
||||
importanceChart.value?.dispose()
|
||||
correlationChart.value?.dispose()
|
||||
})
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.analysis-page {
|
||||
padding: 20px;
|
||||
|
||||
.analysis-card {
|
||||
.header-content {
|
||||
h2 {
|
||||
margin: 0;
|
||||
}
|
||||
}
|
||||
|
||||
.dataset-section {
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.action-section {
|
||||
margin: 20px 0;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.result-section {
|
||||
h3 {
|
||||
margin: 20px 0;
|
||||
}
|
||||
|
||||
.chart-container {
|
||||
margin: 20px 0;
|
||||
border: 1px solid #ebeef5;
|
||||
border-radius: 4px;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
</style>
|
||||
725
deploy/equipment_cost_system/frontend/src/views/DataPage.vue
Normal file
725
deploy/equipment_cost_system/frontend/src/views/DataPage.vue
Normal file
@ -0,0 +1,725 @@
|
||||
<template>
|
||||
<div class="data-page">
|
||||
<el-card class="data-card">
|
||||
<template #header>
|
||||
<div class="header-content">
|
||||
<h2>数据管理</h2>
|
||||
<div class="header-buttons">
|
||||
<el-upload
|
||||
:action="null"
|
||||
:auto-upload="false"
|
||||
:show-file-list="false"
|
||||
accept=".xls,.xlsx"
|
||||
@change="handleFileChange"
|
||||
>
|
||||
<el-button type="primary">导入数据</el-button>
|
||||
</el-upload>
|
||||
<el-button type="primary" @click="downloadTemplate">下载模板</el-button>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<!-- 数据列表 -->
|
||||
<el-tabs v-model="activeTab" @tab-click="handleTabClick">
|
||||
<el-tab-pane label="火箭炮数据" name="rocket">
|
||||
<!-- 搜索和过滤 -->
|
||||
<div class="filter-section">
|
||||
<el-input
|
||||
v-model="searchQuery"
|
||||
placeholder="搜索装备名称或制造商"
|
||||
style="width: 200px; margin-right: 10px;"
|
||||
/>
|
||||
<el-select v-model="filterManufacturer" placeholder="制造商" clearable>
|
||||
<el-option
|
||||
v-for="item in manufacturers"
|
||||
:key="item"
|
||||
:label="item"
|
||||
:value="item"
|
||||
/>
|
||||
</el-select>
|
||||
</div>
|
||||
|
||||
<!-- 数据表格 -->
|
||||
<el-table :data="filteredRocketData" border style="width: 100%">
|
||||
<el-table-column prop="name" label="名称" sortable></el-table-column>
|
||||
<el-table-column prop="manufacturer" label="制造商" sortable></el-table-column>
|
||||
<el-table-column prop="length_m" label="总长(m)" sortable></el-table-column>
|
||||
<el-table-column prop="weight_kg" label="重量(kg)" sortable></el-table-column>
|
||||
<el-table-column prop="max_range_km" label="最大射程(km)" sortable></el-table-column>
|
||||
<el-table-column prop="rocket_diameter_mm" label="口径(mm)" sortable></el-table-column>
|
||||
<el-table-column prop="rate_of_fire" label="射速(发/分)" sortable></el-table-column>
|
||||
<el-table-column label="操作" width="200">
|
||||
<template #default="scope">
|
||||
<el-button size="small" @click="viewDetails(scope.row)">
|
||||
详情
|
||||
</el-button>
|
||||
<el-button size="small" type="primary" @click="editData(scope.row)">
|
||||
编辑
|
||||
</el-button>
|
||||
<el-button size="small" type="danger" @click="deleteData(scope.row)">
|
||||
删除
|
||||
</el-button>
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</el-tab-pane>
|
||||
|
||||
<el-tab-pane label="巡飞弹数据" name="missile">
|
||||
<!-- 搜索和过滤 -->
|
||||
<div class="filter-section">
|
||||
<el-input
|
||||
v-model="searchQuery"
|
||||
placeholder="搜索装备名称或制造商"
|
||||
style="width: 200px; margin-right: 10px;"
|
||||
/>
|
||||
<el-select v-model="filterManufacturer" placeholder="制造商" clearable>
|
||||
<el-option
|
||||
v-for="item in manufacturers"
|
||||
:key="item"
|
||||
:label="item"
|
||||
:value="item"
|
||||
/>
|
||||
</el-select>
|
||||
</div>
|
||||
|
||||
<!-- 数据表格 -->
|
||||
<el-table :data="filteredMissileData" border style="width: 100%">
|
||||
<el-table-column prop="name" label="名称" sortable></el-table-column>
|
||||
<el-table-column prop="manufacturer" label="制造" sortable></el-table-column>
|
||||
<el-table-column prop="length_m" label="弹长(m)" sortable></el-table-column>
|
||||
<el-table-column prop="weight_kg" label="重量(kg)" sortable></el-table-column>
|
||||
<el-table-column prop="max_range_km" label="最大射程(km)" sortable></el-table-column>
|
||||
<el-table-column prop="max_speed_ms" label="最大速度(m/s)" sortable></el-table-column>
|
||||
<el-table-column prop="flight_time_min" label="巡飞时间(min)" sortable></el-table-column>
|
||||
<el-table-column label="操作" width="200">
|
||||
<template #default="scope">
|
||||
<el-button size="small" @click="viewDetails(scope.row)">
|
||||
详情
|
||||
</el-button>
|
||||
<el-button size="small" type="primary" @click="editData(scope.row)">
|
||||
编辑
|
||||
</el-button>
|
||||
<el-button size="small" type="danger" @click="deleteData(scope.row)">
|
||||
删除
|
||||
</el-button>
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</el-tab-pane>
|
||||
</el-tabs>
|
||||
|
||||
<!-- 详情对话框 -->
|
||||
<el-dialog v-model="detailsVisible" title="装备详情" width="70%">
|
||||
<el-descriptions :column="2" border>
|
||||
<!-- 基本信息 -->
|
||||
<template>
|
||||
<el-descriptions-item :span="2">
|
||||
<template #label>
|
||||
<el-divider content-position="left">基本信息</el-divider>
|
||||
</template>
|
||||
</el-descriptions-item>
|
||||
|
||||
<el-descriptions-item label="名称">{{ selectedData?.name }}</el-descriptions-item>
|
||||
<el-descriptions-item label="制造商">{{ selectedData?.manufacturer }}</el-descriptions-item>
|
||||
|
||||
<!-- 通用参数 -->
|
||||
<el-descriptions-item label="总长(m)">{{ formatNumber(selectedData?.length_m) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="宽度(m)">{{ formatNumber(selectedData?.width_m) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="高度(m)">{{ formatNumber(selectedData?.height_m) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="重量(kg)">{{ formatNumber(selectedData?.weight_kg) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="最大射程(km)">{{ formatNumber(selectedData?.max_range_km) }}</el-descriptions-item>
|
||||
</template>
|
||||
|
||||
<!-- 火箭炮特有参数 -->
|
||||
<template v-if="selectedData?.type === '火箭炮'">
|
||||
<el-descriptions-item :span="2">
|
||||
<template #label>
|
||||
<el-divider content-position="left">火箭炮参数</el-divider>
|
||||
</template>
|
||||
</el-descriptions-item>
|
||||
|
||||
<el-descriptions-item label="口径(mm)">{{ formatNumber(selectedData?.rocket_diameter_mm) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="射速(发/分)">{{ formatNumber(selectedData?.rate_of_fire) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="火箭弹长度(m)">{{ formatNumber(selectedData?.rocket_length_m) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="火箭弹重量(kg)">{{ formatNumber(selectedData?.rocket_weight_kg) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="方向射界(度)">{{ formatNumber(selectedData?.firing_angle_horizontal) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="高低射界(度)">{{ formatNumber(selectedData?.firing_angle_vertical) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="机动方式">{{ selectedData?.mobility_type }}</el-descriptions-item>
|
||||
<el-descriptions-item label="结构布局">{{ selectedData?.structure_layout }}</el-descriptions-item>
|
||||
<el-descriptions-item label="发动机型号">{{ selectedData?.engine_model }}</el-descriptions-item>
|
||||
<el-descriptions-item label="发动机参数">{{ selectedData?.engine_params }}</el-descriptions-item>
|
||||
<el-descriptions-item label="功率(hp)">{{ formatNumber(selectedData?.power_hp) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="行程(km)">{{ formatNumber(selectedData?.travel_range_km) }}</el-descriptions-item>
|
||||
</template>
|
||||
|
||||
<!-- 巡飞弹特有参数 -->
|
||||
<template v-if="selectedData?.type === '巡飞弹'">
|
||||
<el-descriptions-item :span="2">
|
||||
<template #label>
|
||||
<el-divider content-position="left">巡飞弹参数</el-divider>
|
||||
</template>
|
||||
</el-descriptions-item>
|
||||
|
||||
<el-descriptions-item label="最大速度(m/s)">{{ formatNumber(selectedData?.max_speed_ms) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="巡航速度(km/h)">{{ formatNumber(selectedData?.cruise_speed_kmh) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="巡飞时间(min)">{{ formatNumber(selectedData?.flight_time_min) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="战斗部类型">{{ selectedData?.warhead_type }}</el-descriptions-item>
|
||||
<el-descriptions-item label="发射方式">{{ selectedData?.launch_mode }}</el-descriptions-item>
|
||||
<el-descriptions-item label="动力装置">{{ selectedData?.power_system }}</el-descriptions-item>
|
||||
<el-descriptions-item label="制导体制">{{ selectedData?.guidance_system }}</el-descriptions-item>
|
||||
</template>
|
||||
|
||||
<!-- 特殊参数 -->
|
||||
<template v-if="selectedData?.custom_params?.length > 0">
|
||||
{{ console.log('Rendering custom params:', selectedData.custom_params) }}
|
||||
<el-descriptions-item :span="2">
|
||||
<template #label>
|
||||
<el-divider content-position="left">特殊参数</el-divider>
|
||||
</template>
|
||||
</el-descriptions-item>
|
||||
|
||||
<el-descriptions-item
|
||||
v-for="param in selectedData.custom_params"
|
||||
:key="param.id"
|
||||
:label="param.param_name"
|
||||
>
|
||||
{{ formatCustomParamValue(param) }}
|
||||
</el-descriptions-item>
|
||||
</template>
|
||||
|
||||
<!-- 成本信息 -->
|
||||
<template>
|
||||
<el-descriptions-item :span="2">
|
||||
<template #label>
|
||||
<el-divider content-position="left">成本信息</el-divider>
|
||||
</template>
|
||||
</el-descriptions-item>
|
||||
|
||||
<el-descriptions-item label="实际成本(元)">
|
||||
{{ formatMoney(selectedData?.actual_cost) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="预测成本(元)">
|
||||
{{ formatMoney(selectedData?.predicted_cost) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="成本估算时间">
|
||||
{{ selectedData?.cost_estimate_date || '-' }}
|
||||
</el-descriptions-item>
|
||||
</template>
|
||||
</el-descriptions>
|
||||
</el-dialog>
|
||||
|
||||
<!-- 编辑对话框 -->
|
||||
<el-dialog v-model="editVisible" title="编辑装备数据" width="70%">
|
||||
<el-form :model="editForm" label-width="120px">
|
||||
<!-- 基本信息 -->
|
||||
<template>
|
||||
<el-divider content-position="left">基本信息</el-divider>
|
||||
<el-form-item label="名称">
|
||||
<el-input v-model="editForm.name"></el-input>
|
||||
</el-form-item>
|
||||
<el-form-item label="制造商">
|
||||
<el-input v-model="editForm.manufacturer"></el-input>
|
||||
</el-form-item>
|
||||
|
||||
<!-- 通用参数 -->
|
||||
<el-form-item label="总长(m)">
|
||||
<el-input-number v-model="editForm.length_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="宽度(m)">
|
||||
<el-input-number v-model="editForm.width_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="高度(m)">
|
||||
<el-input-number v-model="editForm.height_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="重量(kg)">
|
||||
<el-input-number v-model="editForm.weight_kg" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="最大射程(km)">
|
||||
<el-input-number v-model="editForm.max_range_km" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<!-- 火箭炮特有参数 -->
|
||||
<template v-if="editForm.type === '火箭炮'">
|
||||
<el-divider content-position="left">火箭炮参数</el-divider>
|
||||
<el-form-item label="口径(mm)">
|
||||
<el-input-number v-model="editForm.rocket_diameter_mm" :precision="0"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="射速(发/分)">
|
||||
<el-input-number v-model="editForm.rate_of_fire" :precision="0"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="火箭弹长度(m)">
|
||||
<el-input-number v-model="editForm.rocket_length_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="火箭弹重量(kg)">
|
||||
<el-input-number v-model="editForm.rocket_weight_kg" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="方向射界(度)">
|
||||
<el-input-number v-model="editForm.firing_angle_horizontal" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="低射界(度)">
|
||||
<el-input-number v-model="editForm.firing_angle_vertical" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="机动方式">
|
||||
<el-select v-model="editForm.mobility_type">
|
||||
<el-option v-for="option in getSelectOptions('mobility_type')" :key="option" :label="option" :value="option"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="结构布局">
|
||||
<el-input v-model="editForm.structure_layout"></el-input>
|
||||
</el-form-item>
|
||||
<el-form-item label="发动型号">
|
||||
<el-input v-model="editForm.engine_model"></el-input>
|
||||
</el-form-item>
|
||||
<el-form-item label="发动机参数">
|
||||
<el-input v-model="editForm.engine_params"></el-input>
|
||||
</el-form-item>
|
||||
<el-form-item label="功率(hp)">
|
||||
<el-input-number v-model="editForm.power_hp" :precision="0"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="行程(km)">
|
||||
<el-input-number v-model="editForm.travel_range_km" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<!-- 巡飞弹特有参数 -->
|
||||
<template v-if="editForm.type === '巡飞弹'">
|
||||
<el-divider content-position="left">巡飞弹参数</el-divider>
|
||||
<el-form-item label="最大速度(m/s)">
|
||||
<el-input-number v-model="editForm.max_speed_ms" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="巡航速度(km/h)">
|
||||
<el-input-number v-model="editForm.cruise_speed_kmh" :precision="1"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="巡飞时间(min)">
|
||||
<el-input-number v-model="editForm.flight_time_min" :precision="0"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="战斗部类型">
|
||||
<el-select v-model="editForm.warhead_type">
|
||||
<el-option v-for="option in getSelectOptions('warhead_type')" :key="option" :label="option" :value="option"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="发射方式">
|
||||
<el-select v-model="editForm.launch_mode">
|
||||
<el-option v-for="option in getSelectOptions('launch_mode')" :key="option" :label="option" :value="option"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="动力装置">
|
||||
<el-select v-model="editForm.power_system">
|
||||
<el-option v-for="option in getSelectOptions('power_system')" :key="option" :label="option" :value="option"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="制导体制">
|
||||
<el-select v-model="editForm.guidance_system">
|
||||
<el-option v-for="option in getSelectOptions('guidance_system')" :key="option" :label="option" :value="option"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<!-- 特殊参数 -->
|
||||
<template v-if="editForm.custom_params?.length">
|
||||
<el-divider content-position="left">特殊参数</el-divider>
|
||||
<el-form-item
|
||||
v-for="(param, index) in editForm.custom_params"
|
||||
:key="param.id"
|
||||
:label="param.param_name"
|
||||
>
|
||||
<el-input-number
|
||||
v-if="isNumericParam(param)"
|
||||
v-model="editForm.custom_params[index].param_value"
|
||||
:precision="2"
|
||||
:step="0.1"
|
||||
>
|
||||
<template #append v-if="param.param_unit">
|
||||
{{ param.param_unit }}
|
||||
</template>
|
||||
</el-input-number>
|
||||
<el-input
|
||||
v-else
|
||||
v-model="editForm.custom_params[index].param_value"
|
||||
>
|
||||
<template #append v-if="param.param_unit">
|
||||
{{ param.param_unit }}
|
||||
</template>
|
||||
</el-input>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<!-- 成本信息 -->
|
||||
<el-divider content-position="left">成本信息</el-divider>
|
||||
<el-form-item label="实际成本(元)">
|
||||
<el-input-number
|
||||
v-model="editForm.actual_cost"
|
||||
:precision="0"
|
||||
:min="0"
|
||||
:step="1000"
|
||||
:controls="true"
|
||||
style="width: 200px"
|
||||
></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="预测成本(元)">
|
||||
<el-input-number
|
||||
v-model="editForm.predicted_cost"
|
||||
:precision="0"
|
||||
disabled
|
||||
style="width: 200px"
|
||||
></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="成本估算时间">
|
||||
<el-date-picker
|
||||
v-model="editForm.cost_estimate_date"
|
||||
type="datetime"
|
||||
placeholder="选择日期时间"
|
||||
format="YYYY-MM-DD HH:mm:ss"
|
||||
value-format="YYYY-MM-DD HH:mm:ss"
|
||||
disabled
|
||||
></el-date-picker>
|
||||
</el-form-item>
|
||||
</el-form>
|
||||
|
||||
<template #footer>
|
||||
<span class="dialog-footer">
|
||||
<el-button @click="editVisible = false">取消</el-button>
|
||||
<el-button type="primary" @click="saveEdit">保存</el-button>
|
||||
</span>
|
||||
</template>
|
||||
</el-dialog>
|
||||
</el-card>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, computed, onMounted } from 'vue'
|
||||
import { ElMessage, ElMessageBox } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
|
||||
const activeTab = ref('rocket')
|
||||
const rocketData = ref([])
|
||||
const missileData = ref([])
|
||||
const detailsVisible = ref(false)
|
||||
const editVisible = ref(false)
|
||||
const selectedData = ref(null)
|
||||
const editForm = ref(null)
|
||||
const searchQuery = ref('')
|
||||
const filterManufacturer = ref('')
|
||||
|
||||
// 计算制造商列表
|
||||
const manufacturers = computed(() => {
|
||||
const data = activeTab.value === 'rocket' ? rocketData.value : missileData.value
|
||||
return [...new Set(data.map(item => item.manufacturer))]
|
||||
})
|
||||
|
||||
// 过滤数据
|
||||
const filteredRocketData = computed(() => {
|
||||
return filterData(rocketData.value)
|
||||
})
|
||||
|
||||
const filteredMissileData = computed(() => {
|
||||
return filterData(missileData.value)
|
||||
})
|
||||
|
||||
const filterData = (data) => {
|
||||
return data.filter(item => {
|
||||
const matchesSearch = searchQuery.value ?
|
||||
(item.name.toLowerCase().includes(searchQuery.value.toLowerCase()) ||
|
||||
item.manufacturer.toLowerCase().includes(searchQuery.value.toLowerCase())) : true
|
||||
|
||||
const matchesManufacturer = filterManufacturer.value ?
|
||||
item.manufacturer === filterManufacturer.value : true
|
||||
|
||||
return matchesSearch && matchesManufacturer
|
||||
})
|
||||
}
|
||||
|
||||
// 加载数据
|
||||
const loadData = async () => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/data`)
|
||||
if (response.data.error) {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
|
||||
// 处理火箭炮据
|
||||
rocketData.value = response.data.rocket_artillery.map(item => ({
|
||||
...item,
|
||||
custom_params: item.custom_params || []
|
||||
}))
|
||||
|
||||
// 处理巡飞弹数据
|
||||
missileData.value = response.data.loitering_munition.map(item => ({
|
||||
...item,
|
||||
custom_params: item.custom_params || []
|
||||
}))
|
||||
} catch (error) {
|
||||
ElMessage.error('加载数据失败')
|
||||
console.error('Error loading data:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 文件上传
|
||||
const handleFileChange = async (file) => {
|
||||
try {
|
||||
const formData = new FormData()
|
||||
formData.append('file', file.raw)
|
||||
|
||||
const response = await axios.post(
|
||||
`${API_BASE_URL}/data/import`,
|
||||
formData,
|
||||
{
|
||||
headers: {
|
||||
'Content-Type': 'multipart/form-data'
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
if (response.data.success) {
|
||||
ElMessage.success('数据导入成功')
|
||||
loadData() // 重新加载数据
|
||||
} else {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
} catch (error) {
|
||||
ElMessage.error(error.message || '数据导入失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 下载模板
|
||||
const downloadTemplate = () => {
|
||||
window.open(`${API_BASE_URL}/data/template`, '_blank')
|
||||
}
|
||||
|
||||
// 查看详情
|
||||
const viewDetails = async (row) => {
|
||||
try {
|
||||
console.log('Requesting details for row:', row)
|
||||
const response = await axios.get(`${API_BASE_URL}/data/details/${row.id}`)
|
||||
if (response.data.error) {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
console.log('Details response:', response.data)
|
||||
|
||||
// 确保 custom_params 是数组
|
||||
if (typeof response.data.custom_params === 'string') {
|
||||
response.data.custom_params = JSON.parse(response.data.custom_params)
|
||||
}
|
||||
|
||||
console.log('Parsed custom params:', response.data.custom_params)
|
||||
selectedData.value = response.data
|
||||
console.log('Selected data:', selectedData.value)
|
||||
detailsVisible.value = true
|
||||
} catch (error) {
|
||||
ElMessage.error('获取详情失败')
|
||||
console.error('Error getting details:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 编辑数据
|
||||
const editData = async (row) => {
|
||||
try {
|
||||
console.log('Editing row:', row)
|
||||
const response = await axios.get(`${API_BASE_URL}/data/details/${row.id}`)
|
||||
if (response.data.error) {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
console.log('Edit data response:', response.data)
|
||||
|
||||
// 确保 custom_params 是数组
|
||||
if (typeof response.data.custom_params === 'string') {
|
||||
response.data.custom_params = JSON.parse(response.data.custom_params)
|
||||
}
|
||||
|
||||
// 转换所有数值类型字段
|
||||
const data = { ...response.data }
|
||||
Object.keys(data).forEach(key => {
|
||||
if (isNumberInput(key) && data[key] !== null && data[key] !== undefined) {
|
||||
data[key] = Number(data[key])
|
||||
}
|
||||
})
|
||||
|
||||
// 转换特殊参数中的数值
|
||||
if (data.custom_params) {
|
||||
data.custom_params = data.custom_params.map(param => ({
|
||||
...param,
|
||||
param_value: !isNaN(param.param_value) ? Number(param.param_value) : param.param_value
|
||||
}))
|
||||
}
|
||||
|
||||
console.log('Parsed custom params:', data.custom_params)
|
||||
editForm.value = data
|
||||
console.log('Edit form data:', editForm.value)
|
||||
editVisible.value = true
|
||||
} catch (error) {
|
||||
ElMessage.error('获取编辑数据失败')
|
||||
console.error('Error getting edit data:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 保存编辑
|
||||
const saveEdit = async () => {
|
||||
try {
|
||||
// 准备要保存的数据
|
||||
const saveData = {
|
||||
...editForm.value,
|
||||
custom_params: editForm.value.custom_params.map(param => ({
|
||||
id: param.id,
|
||||
param_name: param.param_name,
|
||||
param_value: param.param_value,
|
||||
param_unit: param.param_unit
|
||||
}))
|
||||
}
|
||||
|
||||
const response = await axios.put(
|
||||
`${API_BASE_URL}/data/${editForm.value.id}`,
|
||||
saveData
|
||||
)
|
||||
|
||||
if (response.data.success) {
|
||||
ElMessage.success('保存成功')
|
||||
editVisible.value = false
|
||||
loadData() // 重新加载数据
|
||||
} else {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
} catch (error) {
|
||||
ElMessage.error(error.message || '保存失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 删除数据
|
||||
const deleteData = async (row) => {
|
||||
try {
|
||||
await ElMessageBox.confirm('确定要删除这条数据吗？', '警告', {
|
||||
type: 'warning'
|
||||
})
|
||||
|
||||
const response = await axios.delete(`${API_BASE_URL}/data/${row.id}`)
|
||||
|
||||
if (response.data.success) {
|
||||
ElMessage.success('删除成功')
|
||||
loadData() // 重新加载数据
|
||||
} else {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
} catch (error) {
|
||||
if (error !== 'cancel') {
|
||||
ElMessage.error(error.message || '删除失败')
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 格式化数字
|
||||
const formatNumber = (value) => {
|
||||
if (value === null || value === undefined) return '-'
|
||||
return Number(value).toFixed(2)
|
||||
}
|
||||
|
||||
// 格式化金额
|
||||
const formatMoney = (value) => {
|
||||
if (value === null || value === undefined) return '-'
|
||||
return new Intl.NumberFormat('zh-CN', {
|
||||
style: 'currency',
|
||||
currency: 'CNY'
|
||||
}).format(value)
|
||||
}
|
||||
|
||||
// 格式化特殊参数值的显示
|
||||
const formatCustomParamValue = (param) => {
|
||||
if (!param || !param.param_value) return '-'
|
||||
let value = param.param_value
|
||||
|
||||
// 如果是数值类型，进行格式化
|
||||
if (!isNaN(value)) {
|
||||
value = Number(value).toFixed(2)
|
||||
}
|
||||
|
||||
// 如果有单位，添加单位
|
||||
if (param.param_unit) {
|
||||
value = `${value} ${param.param_unit}`
|
||||
}
|
||||
|
||||
return value
|
||||
}
|
||||
|
||||
// 判断是否为数值类型参数
|
||||
const isNumericParam = (param) => {
|
||||
return !isNaN(param.param_value) && param.param_unit !== undefined
|
||||
}
|
||||
|
||||
// 添加 handleTabClick 函数
|
||||
const handleTabClick = () => {
|
||||
// 切换标签页时重置过滤条件
|
||||
searchQuery.value = ''
|
||||
filterManufacturer.value = ''
|
||||
}
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
loadData()
|
||||
})
|
||||
|
||||
// 判断是否为数值类型输入字段
|
||||
const isNumberInput = (key) => {
|
||||
const numberFields = [
|
||||
'length_m',
|
||||
'width_m',
|
||||
'height_m',
|
||||
'weight_kg',
|
||||
'max_range_km',
|
||||
'firing_angle_horizontal',
|
||||
'firing_angle_vertical',
|
||||
'rocket_length_m',
|
||||
'rocket_diameter_mm',
|
||||
'rocket_weight_kg',
|
||||
'rate_of_fire',
|
||||
'combat_weight_kg',
|
||||
'speed_kmh',
|
||||
'min_range_km',
|
||||
'power_hp',
|
||||
'travel_range_km',
|
||||
'max_speed_ms',
|
||||
'cruise_speed_kmh',
|
||||
'flight_time_min',
|
||||
'folded_length_mm',
|
||||
'folded_width_mm',
|
||||
'folded_height_mm',
|
||||
'actual_cost',
|
||||
'predicted_cost'
|
||||
]
|
||||
|
||||
return numberFields.includes(key)
|
||||
}
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.data-page {
|
||||
padding: 20px;
|
||||
|
||||
.data-card {
|
||||
.header-content {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
|
||||
h2 {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.header-buttons {
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.filter-section {
|
||||
margin-bottom: 20px;
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
}
|
||||
|
||||
.el-table {
|
||||
margin-top: 20px;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
322
deploy/equipment_cost_system/frontend/src/views/DatasetPage.vue
Normal file
322
deploy/equipment_cost_system/frontend/src/views/DatasetPage.vue
Normal file
@ -0,0 +1,322 @@
|
||||
<template>
|
||||
<div class="dataset-page">
|
||||
<el-card class="dataset-card">
|
||||
<template #header>
|
||||
<div class="header-content">
|
||||
<h2>数据集管理</h2>
|
||||
<div class="header-buttons">
|
||||
<el-button type="primary" @click="createDataset">创建数据集</el-button>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<!-- 数据集列表 -->
|
||||
<el-table :data="datasets" border style="width: 100%">
|
||||
<el-table-column prop="name" label="数据集名称"></el-table-column>
|
||||
<el-table-column prop="equipment_type" label="装备类型"></el-table-column>
|
||||
<el-table-column prop="purpose" label="用途"></el-table-column>
|
||||
<el-table-column prop="description" label="描述"></el-table-column>
|
||||
<el-table-column prop="equipment_count" label="装备数量"></el-table-column>
|
||||
<el-table-column prop="created_at" label="创建时间">
|
||||
<template #default="scope">
|
||||
{{ formatDateTime(scope.row.created_at) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="updated_at" label="修改时间">
|
||||
<template #default="scope">
|
||||
{{ formatDateTime(scope.row.updated_at) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column label="操作" width="200">
|
||||
<template #default="scope">
|
||||
<el-button size="small" @click="viewDataset(scope.row)">查看</el-button>
|
||||
<el-button size="small" type="primary" @click="editDataset(scope.row)">编辑</el-button>
|
||||
<el-button size="small" type="danger" @click="deleteDataset(scope.row)">删除</el-button>
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</el-card>
|
||||
|
||||
<!-- 数据集详情对话框 -->
|
||||
<el-dialog v-model="detailsVisible" :title="selectedDataset?.name" width="70%">
|
||||
<el-descriptions :column="2" border>
|
||||
<el-descriptions-item label="装备类型">{{ selectedDataset?.equipment_type }}</el-descriptions-item>
|
||||
<el-descriptions-item label="用途">{{ selectedDataset?.purpose }}</el-descriptions-item>
|
||||
<el-descriptions-item label="描述" :span="2">{{ selectedDataset?.description }}</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
|
||||
<!-- 数据集统计信息 -->
|
||||
<div style="margin-top: 20px">
|
||||
<el-divider content-position="left">统计信息</el-divider>
|
||||
<el-descriptions :column="2" border>
|
||||
<el-descriptions-item label="装备数量">{{ selectedDataset?.statistics?.equipment_count || 0 }}</el-descriptions-item>
|
||||
<el-descriptions-item label="平均成本">{{ formatMoney(selectedDataset?.statistics?.average_cost) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="总成本">{{ formatMoney(selectedDataset?.statistics?.total_cost) }}</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
</div>
|
||||
|
||||
<!-- 包含的装备列表 -->
|
||||
<div style="margin-top: 20px">
|
||||
<el-divider content-position="left">包含装备</el-divider>
|
||||
<el-table :data="selectedDataset?.equipment" border>
|
||||
<el-table-column prop="name" label="名称"></el-table-column>
|
||||
<el-table-column prop="manufacturer" label="制造商"></el-table-column>
|
||||
<el-table-column prop="actual_cost" label="成本(元)">
|
||||
<template #default="scope">
|
||||
{{ formatMoney(scope.row.actual_cost) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column label="操作" width="100">
|
||||
<template #default="scope">
|
||||
<el-button size="small" @click="viewEquipment(scope.row)">详情</el-button>
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</div>
|
||||
</el-dialog>
|
||||
|
||||
<!-- 创建/编辑数据集对话框 -->
|
||||
<el-dialog v-model="editVisible" :title="datasetForm.id ? '编辑数据集' : '创建数据集'" width="70%">
|
||||
<el-form :model="datasetForm" label-width="120px">
|
||||
<el-form-item label="数据集名称" required>
|
||||
<el-input v-model="datasetForm.name"></el-input>
|
||||
</el-form-item>
|
||||
<el-form-item label="装备类型" required>
|
||||
<el-select v-model="datasetForm.equipment_type" @change="handleEquipmentTypeChange">
|
||||
<el-option label="火箭炮" value="火箭炮"></el-option>
|
||||
<el-option label="巡飞弹" value="巡飞弹"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="用途" required>
|
||||
<el-select v-model="datasetForm.purpose">
|
||||
<el-option label="训练" value="训练"></el-option>
|
||||
<el-option label="验证" value="验证"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="描述">
|
||||
<el-input type="textarea" v-model="datasetForm.description"></el-input>
|
||||
</el-form-item>
|
||||
|
||||
<!-- 选择装备数据 -->
|
||||
<el-form-item label="选择装备" required>
|
||||
<el-table
|
||||
:data="availableEquipment"
|
||||
border
|
||||
@selection-change="handleSelectionChange"
|
||||
:max-height="400"
|
||||
>
|
||||
<el-table-column type="selection" width="55"></el-table-column>
|
||||
<el-table-column prop="name" label="名称"></el-table-column>
|
||||
<el-table-column prop="manufacturer" label="制造商"></el-table-column>
|
||||
<el-table-column prop="actual_cost" label="成本(元)">
|
||||
<template #default="scope">
|
||||
{{ formatMoney(scope.row.actual_cost) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</el-form-item>
|
||||
</el-form>
|
||||
<template #footer>
|
||||
<span class="dialog-footer">
|
||||
<el-button @click="editVisible = false">取消</el-button>
|
||||
<el-button type="primary" @click="saveDataset">保存</el-button>
|
||||
</span>
|
||||
</template>
|
||||
</el-dialog>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, onMounted } from 'vue'
|
||||
import { ElMessage, ElMessageBox } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
|
||||
// 响应式数据
|
||||
const datasets = ref([]) // 数据集列表
|
||||
const selectedDataset = ref(null) // 选中的数据集
|
||||
const detailsVisible = ref(false) // 详情对话框显示状态
|
||||
const editVisible = ref(false) // 编辑对话框显示状态
|
||||
const availableEquipment = ref([]) // 可选装备列表
|
||||
const selectedEquipment = ref([]) // 已选装备列表
|
||||
|
||||
// 数据集表单
|
||||
const datasetForm = ref({
|
||||
id: null,
|
||||
name: '',
|
||||
equipment_type: '',
|
||||
purpose: '',
|
||||
description: '',
|
||||
selected_equipment: []
|
||||
})
|
||||
|
||||
// 加载数据集列表
|
||||
const loadDatasets = async () => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/datasets`)
|
||||
datasets.value = response.data
|
||||
} catch (error) {
|
||||
ElMessage.error('获取数据集列表失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 创建数据集
|
||||
const createDataset = () => {
|
||||
datasetForm.value = {
|
||||
id: null,
|
||||
name: '',
|
||||
equipment_type: '',
|
||||
purpose: '',
|
||||
description: '',
|
||||
selected_equipment: []
|
||||
}
|
||||
editVisible.value = true
|
||||
}
|
||||
|
||||
// 编辑数据集
|
||||
const editDataset = async (dataset) => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/datasets/${dataset.id}`)
|
||||
datasetForm.value = response.data
|
||||
await loadAvailableEquipment()
|
||||
editVisible.value = true
|
||||
} catch (error) {
|
||||
ElMessage.error('获取数据集详情失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 查看数据集详情
|
||||
const viewDataset = async (dataset) => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/datasets/${dataset.id}`)
|
||||
selectedDataset.value = response.data
|
||||
detailsVisible.value = true
|
||||
} catch (error) {
|
||||
ElMessage.error('获取数据集详情失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 删除数据集
|
||||
const deleteDataset = async (dataset) => {
|
||||
try {
|
||||
await ElMessageBox.confirm('确定要删除这个数据集吗？', '警告', {
|
||||
type: 'warning'
|
||||
})
|
||||
|
||||
await axios.delete(`${API_BASE_URL}/datasets/${dataset.id}`)
|
||||
ElMessage.success('删除成功')
|
||||
loadDatasets()
|
||||
} catch (error) {
|
||||
if (error !== 'cancel') {
|
||||
ElMessage.error('删除失败')
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 加载可选装备
|
||||
const loadAvailableEquipment = async () => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/data`)
|
||||
availableEquipment.value = datasetForm.value.equipment_type === '火箭炮'
|
||||
? response.data.rocket_artillery
|
||||
: response.data.loitering_munition
|
||||
} catch (error) {
|
||||
ElMessage.error('获取装备列表失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 处理装备类型变化
|
||||
const handleEquipmentTypeChange = () => {
|
||||
selectedEquipment.value = [] // 清空已选装备
|
||||
loadAvailableEquipment() // 重新加载可选装备
|
||||
}
|
||||
|
||||
// 处理装备选择变化
|
||||
const handleSelectionChange = (selection) => {
|
||||
selectedEquipment.value = selection
|
||||
}
|
||||
|
||||
// 保存数据集
|
||||
const saveDataset = async () => {
|
||||
try {
|
||||
const data = {
|
||||
...datasetForm.value,
|
||||
equipment_ids: selectedEquipment.value.map(item => item.id)
|
||||
}
|
||||
|
||||
if (data.id) {
|
||||
await axios.put(`${API_BASE_URL}/datasets/${data.id}`, data)
|
||||
} else {
|
||||
await axios.post(`${API_BASE_URL}/datasets`, data)
|
||||
}
|
||||
|
||||
ElMessage.success('保存成功')
|
||||
editVisible.value = false
|
||||
loadDatasets()
|
||||
} catch (error) {
|
||||
ElMessage.error('保存失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 查看装备详情
|
||||
const viewEquipment = (equipment) => {
|
||||
// 这里可以跳转到装备详情页面或打开装备详情对话框
|
||||
console.log('View equipment:', equipment)
|
||||
}
|
||||
|
||||
// 格式化金额
|
||||
const formatMoney = (value) => {
|
||||
if (value === null || value === undefined) return '-'
|
||||
return new Intl.NumberFormat('zh-CN', {
|
||||
style: 'currency',
|
||||
currency: 'CNY'
|
||||
}).format(value)
|
||||
}
|
||||
|
||||
// 格式化日期时间
|
||||
const formatDateTime = (value) => {
|
||||
if (!value) return '-'
|
||||
const date = new Date(value)
|
||||
return date.toLocaleString('zh-CN', {
|
||||
year: 'numeric',
|
||||
month: '2-digit',
|
||||
day: '2-digit',
|
||||
hour: '2-digit',
|
||||
minute: '2-digit',
|
||||
second: '2-digit',
|
||||
hour12: false
|
||||
})
|
||||
}
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
loadDatasets()
|
||||
})
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.dataset-page {
|
||||
padding: 20px;
|
||||
|
||||
.dataset-card {
|
||||
.header-content {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
|
||||
h2 {
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
.header-buttons {
|
||||
display: flex;
|
||||
gap: 10px;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.el-table {
|
||||
margin-top: 20px;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
101
deploy/equipment_cost_system/frontend/src/views/HomePage.vue
Normal file
101
deploy/equipment_cost_system/frontend/src/views/HomePage.vue
Normal file
@ -0,0 +1,101 @@
|
||||
<template>
|
||||
<div class="home-page">
|
||||
<el-card class="welcome-card">
|
||||
<template #header>
|
||||
<h2>装备成本估算系统</h2>
|
||||
</template>
|
||||
<el-row :gutter="20">
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/predict')">
|
||||
<el-icon><Money /></el-icon>
|
||||
<h3>成本预测</h3>
|
||||
<p>基于机器学习和 PLS 回归模型的成本预测</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/analysis')">
|
||||
<el-icon><DataAnalysis /></el-icon>
|
||||
<h3>特征分析</h3>
|
||||
<p>分析参数对成本的影响</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/training')">
|
||||
<el-icon><Monitor /></el-icon>
|
||||
<h3>模型训练</h3>
|
||||
<p>训练和优化预测模型</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/models')">
|
||||
<el-icon><Management /></el-icon>
|
||||
<h3>模型管理</h3>
|
||||
<p>管理训练好的模型</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/datasets')">
|
||||
<el-icon><Collection /></el-icon>
|
||||
<h3>数据集管理</h3>
|
||||
<p>管理训练和验证数据集</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
<el-col :span="8">
|
||||
<el-card @click="$router.push('/data')">
|
||||
<el-icon><Management /></el-icon>
|
||||
<h3>数据管理</h3>
|
||||
<p>管理装备数据和成本数据</p>
|
||||
</el-card>
|
||||
</el-col>
|
||||
</el-row>
|
||||
</el-card>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { Money, DataAnalysis, Monitor, Management, Collection } from '@element-plus/icons-vue'
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.home-page {
|
||||
padding: 20px;
|
||||
|
||||
.welcome-card {
|
||||
max-width: 1200px;
|
||||
margin: 0 auto;
|
||||
|
||||
h2 {
|
||||
text-align: center;
|
||||
margin: 0;
|
||||
}
|
||||
}
|
||||
|
||||
.el-card {
|
||||
text-align: center;
|
||||
cursor: pointer;
|
||||
transition: all 0.3s;
|
||||
margin-bottom: 20px;
|
||||
|
||||
&:hover {
|
||||
transform: translateY(-5px);
|
||||
box-shadow: 0 2px 12px 0 rgba(0,0,0,.1);
|
||||
}
|
||||
|
||||
.el-icon {
|
||||
font-size: 48px;
|
||||
color: #409EFF;
|
||||
margin: 20px 0;
|
||||
}
|
||||
|
||||
h3 {
|
||||
margin: 10px 0;
|
||||
font-size: 18px;
|
||||
}
|
||||
|
||||
p {
|
||||
color: #909399;
|
||||
font-size: 14px;
|
||||
}
|
||||
}
|
||||
}
|
||||
</style>
|
||||
279
deploy/equipment_cost_system/frontend/src/views/ModelPage.vue
Normal file
279
deploy/equipment_cost_system/frontend/src/views/ModelPage.vue
Normal file
@ -0,0 +1,279 @@
|
||||
<template>
|
||||
<div class="model-page">
|
||||
<el-card class="model-card">
|
||||
<template #header>
|
||||
<div class="header-content">
|
||||
<h2>模型管理</h2>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<!-- 模型列表 -->
|
||||
<el-table :data="modelList" border style="width: 100%">
|
||||
<el-table-column prop="model_type" label="模型类型">
|
||||
<template #default="scope">
|
||||
{{ getModelName(scope.row.model_type) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="model_name" label="模型名称"></el-table-column>
|
||||
<el-table-column prop="equipment_type" label="装备类型"></el-table-column>
|
||||
<el-table-column prop="r2_score" label="R²分数">
|
||||
<template #default="scope">
|
||||
{{ scope.row.r2_score.toFixed(4) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="mae" label="MAE (元)">
|
||||
<template #default="scope">
|
||||
{{ scope.row.mae.toFixed(2) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="rmse" label="RMSE (元)">
|
||||
<template #default="scope">
|
||||
{{ scope.row.rmse.toFixed(2) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="training_date" label="训练时间">
|
||||
<template #default="scope">
|
||||
{{ formatDateTime(scope.row.training_date) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="is_active" label="状态">
|
||||
<template #default="scope">
|
||||
<el-tag :type="scope.row.is_active ? 'success' : 'info'">
|
||||
{{ scope.row.is_active ? '使用中' : '未使用' }}
|
||||
</el-tag>
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column label="操作" width="200">
|
||||
<template #default="scope">
|
||||
<el-button
|
||||
size="small"
|
||||
type="primary"
|
||||
:disabled="scope.row.is_active"
|
||||
@click="activateModel(scope.row)"
|
||||
>
|
||||
激活
|
||||
</el-button>
|
||||
<el-button
|
||||
size="small"
|
||||
@click="viewDetails(scope.row)"
|
||||
>
|
||||
详情
|
||||
</el-button>
|
||||
<el-button
|
||||
size="small"
|
||||
type="danger"
|
||||
:disabled="scope.row.is_active"
|
||||
@click="deleteModel(scope.row)"
|
||||
>
|
||||
删除
|
||||
</el-button>
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</el-card>
|
||||
|
||||
<!-- 模型详情对话框 -->
|
||||
<el-dialog v-model="detailsVisible" title="模型详情" width="70%">
|
||||
<el-descriptions :column="2" border>
|
||||
<el-descriptions-item label="模型名称">{{ selectedModel?.model_name }}</el-descriptions-item>
|
||||
<el-descriptions-item label="模型类型">{{ formatModelType(selectedModel?.model_type) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="装备类型">{{ selectedModel?.equipment_type }}</el-descriptions-item>
|
||||
<el-descriptions-item label="训练数据量">{{ selectedModel?.training_data_size }}</el-descriptions-item>
|
||||
<el-descriptions-item label="训练时间">{{ formatDateTime(selectedModel?.training_date) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="状态">
|
||||
<el-tag :type="selectedModel?.is_active ? 'success' : 'info'">
|
||||
{{ selectedModel?.is_active ? '使用中' : '未使用' }}
|
||||
</el-tag>
|
||||
</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
|
||||
<!-- 评估指标 -->
|
||||
<div style="margin-top: 20px">
|
||||
<el-divider content-position="left">评估指标</el-divider>
|
||||
<el-descriptions :column="3" border>
|
||||
<el-descriptions-item label="R²分数">{{ selectedModel?.r2_score.toFixed(4) }}</el-descriptions-item>
|
||||
<el-descriptions-item label="MAE">{{ selectedModel?.mae.toFixed(2) }} 元</el-descriptions-item>
|
||||
<el-descriptions-item label="RMSE">{{ selectedModel?.rmse.toFixed(2) }} 元</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
</div>
|
||||
|
||||
<!-- 特征重要性 -->
|
||||
<div v-if="selectedModel?.feature_importance" style="margin-top: 20px">
|
||||
<el-divider content-position="left">特征重要性</el-divider>
|
||||
<div ref="importanceChartRef" style="width: 100%; height: 400px"></div>
|
||||
</div>
|
||||
</el-dialog>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, onMounted, watch, nextTick, onUnmounted } from 'vue'
|
||||
import { ElMessage, ElMessageBox } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
import * as echarts from 'echarts'
|
||||
|
||||
// 响应式数据
|
||||
const modelList = ref([])
|
||||
const selectedModel = ref(null)
|
||||
const detailsVisible = ref(false)
|
||||
const importanceChartRef = ref(null)
|
||||
const importanceChart = ref(null)
|
||||
|
||||
// 加载模型列表
|
||||
const loadModels = async () => {
|
||||
try {
|
||||
const response = await axios.get(`${API_BASE_URL}/models`)
|
||||
modelList.value = response.data
|
||||
} catch (error) {
|
||||
ElMessage.error('获取模型列表失败')
|
||||
}
|
||||
}
|
||||
|
||||
// 激活模型
|
||||
const activateModel = async (model) => {
|
||||
try {
|
||||
await ElMessageBox.confirm('确定要激活这个模型吗？', '提示', {
|
||||
type: 'warning'
|
||||
})
|
||||
|
||||
await axios.post(`${API_BASE_URL}/models/${model.id}/activate`)
|
||||
ElMessage.success('模型激活成功')
|
||||
loadModels()
|
||||
} catch (error) {
|
||||
if (error !== 'cancel') {
|
||||
ElMessage.error('模型激活失败')
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 删除模型
|
||||
const deleteModel = async (model) => {
|
||||
try {
|
||||
await ElMessageBox.confirm('确定要删除这个模型吗？', '警告', {
|
||||
type: 'warning'
|
||||
})
|
||||
|
||||
await axios.delete(`${API_BASE_URL}/models/${model.id}`)
|
||||
ElMessage.success('删除成功')
|
||||
loadModels()
|
||||
} catch (error) {
|
||||
if (error !== 'cancel') {
|
||||
ElMessage.error('删除失败')
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 查看模型详情
|
||||
const viewDetails = async (model) => {
|
||||
selectedModel.value = model
|
||||
detailsVisible.value = true
|
||||
}
|
||||
|
||||
// 监听详情对话框显示状态
|
||||
watch(() => detailsVisible.value, async (visible) => {
|
||||
if (visible && selectedModel.value?.feature_importance) {
|
||||
await nextTick()
|
||||
renderImportanceChart()
|
||||
}
|
||||
})
|
||||
|
||||
// 渲染特征重要性图表
|
||||
const renderImportanceChart = () => {
|
||||
if (importanceChart.value) {
|
||||
importanceChart.value.dispose()
|
||||
}
|
||||
|
||||
importanceChart.value = echarts.init(importanceChartRef.value)
|
||||
|
||||
const featureImportance = JSON.parse(selectedModel.value.feature_importance)
|
||||
const features = Object.keys(featureImportance)
|
||||
const values = Object.values(featureImportance)
|
||||
|
||||
importanceChart.value.setOption({
|
||||
title: { text: '特征重要性' },
|
||||
tooltip: {},
|
||||
xAxis: {
|
||||
type: 'value',
|
||||
name: '重要性得分'
|
||||
},
|
||||
yAxis: {
|
||||
type: 'category',
|
||||
data: features
|
||||
},
|
||||
series: [{
|
||||
type: 'bar',
|
||||
data: values
|
||||
}]
|
||||
})
|
||||
}
|
||||
|
||||
// 格式化模型类型
|
||||
const formatModelType = (type) => {
|
||||
const typeMap = {
|
||||
'xgboost': 'XGBoost',
|
||||
'lightgbm': 'LightGBM',
|
||||
'gbdt': 'GBDT',
|
||||
'rf': 'Random Forest'
|
||||
}
|
||||
return typeMap[type] || type
|
||||
}
|
||||
|
||||
// 格式化日期时间
|
||||
const formatDateTime = (value) => {
|
||||
if (!value) return '-'
|
||||
const date = new Date(value)
|
||||
return date.toLocaleString('zh-CN', {
|
||||
year: 'numeric',
|
||||
month: '2-digit',
|
||||
day: '2-digit',
|
||||
hour: '2-digit',
|
||||
minute: '2-digit',
|
||||
second: '2-digit',
|
||||
hour12: false
|
||||
})
|
||||
}
|
||||
|
||||
// 组件卸载时清理图表实例
|
||||
onUnmounted(() => {
|
||||
importanceChart.value?.dispose()
|
||||
})
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
loadModels()
|
||||
})
|
||||
|
||||
const getModelName = (modelType) => {
|
||||
const modelNames = {
|
||||
'pls': 'PLS回归',
|
||||
'xgboost': 'XGBoost',
|
||||
'lightgbm': 'LightGBM',
|
||||
'gbm': 'GBM',
|
||||
'rf': 'Random Forest'
|
||||
}
|
||||
return modelNames[modelType] || modelType
|
||||
}
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.model-page {
|
||||
padding: 20px;
|
||||
|
||||
.model-card {
|
||||
.header-content {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
|
||||
h2 {
|
||||
margin: 0;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.el-table {
|
||||
margin-top: 20px;
|
||||
}
|
||||
}
|
||||
</style>
|
||||
321
deploy/equipment_cost_system/frontend/src/views/PredictPage.vue
Normal file
321
deploy/equipment_cost_system/frontend/src/views/PredictPage.vue
Normal file
@ -0,0 +1,321 @@
|
||||
<template>
|
||||
<div class="predict-page">
|
||||
<el-card class="predict-card">
|
||||
<template #header>
|
||||
<h2>成本预测</h2>
|
||||
</template>
|
||||
|
||||
<el-form :model="formData" label-width="120px">
|
||||
<!-- 装备类型选择 -->
|
||||
<el-form-item label="装备类型">
|
||||
<el-select v-model="formData.type" @change="handleTypeChange">
|
||||
<el-option label="火箭炮" value="火箭炮"></el-option>
|
||||
<el-option label="巡飞弹" value="巡飞弹"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
|
||||
<!-- 通用参数 -->
|
||||
<el-form-item label="总长(m)">
|
||||
<el-input-number v-model="formData.length_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="宽度(m)">
|
||||
<el-input-number v-model="formData.width_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="高度(m)">
|
||||
<el-input-number v-model="formData.height_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="重量(kg)">
|
||||
<el-input-number v-model="formData.weight_kg"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="最大射程(km)">
|
||||
<el-input-number v-model="formData.max_range_km"></el-input-number>
|
||||
</el-form-item>
|
||||
|
||||
<!-- 火箭炮特有参数 -->
|
||||
<template v-if="formData.type === '火箭炮'">
|
||||
<el-form-item label="方向射界(度)">
|
||||
<el-input-number v-model="formData.firing_angle_horizontal"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="高低射界(度)">
|
||||
<el-input-number v-model="formData.firing_angle_vertical"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="火箭弹长度(m)">
|
||||
<el-input-number v-model="formData.rocket_length_m" :precision="2"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="弹体直径(mm)">
|
||||
<el-input-number v-model="formData.rocket_diameter_mm"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="火箭弹重量(kg)">
|
||||
<el-input-number v-model="formData.rocket_weight_kg"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="射速(发/分钟)">
|
||||
<el-input-number v-model="formData.rate_of_fire"></el-input-number>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<!-- 巡飞弹特有参数 -->
|
||||
<template v-if="formData.type === '巡飞弹'">
|
||||
<el-form-item label="最大速度(km/h)">
|
||||
<el-input-number v-model="formData.max_speed_kmh"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="巡航速度(km/h)">
|
||||
<el-input-number v-model="formData.cruise_speed_kmh"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="巡飞时间(min)">
|
||||
<el-input-number v-model="formData.flight_time_min"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="战斗部类型">
|
||||
<el-select v-model="formData.warhead_type">
|
||||
<el-option label="破片杀伤战斗部" value="破片杀伤战斗部"></el-option>
|
||||
<el-option label="破甲战斗部" value="破甲战斗部"></el-option>
|
||||
<el-option label="高爆战斗部" value="高爆战斗部"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="发射方式">
|
||||
<el-select v-model="formData.launch_mode">
|
||||
<el-option label="箱式发射" value="箱式发射"></el-option>
|
||||
<el-option label="凭自身动力起飞" value="凭自身动力起飞"></el-option>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
<el-form-item label="折叠长度(mm)">
|
||||
<el-input-number v-model="formData.folded_length_mm"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="折叠宽度(mm)">
|
||||
<el-input-number v-model="formData.folded_width_mm"></el-input-number>
|
||||
</el-form-item>
|
||||
<el-form-item label="折叠高度(mm)">
|
||||
<el-input-number v-model="formData.folded_height_mm"></el-input-number>
|
||||
</el-form-item>
|
||||
</template>
|
||||
|
||||
<el-form-item>
|
||||
<el-button type="primary" @click="submitForm">预测成本</el-button>
|
||||
<el-button @click="resetForm">重置</el-button>
|
||||
</el-form-item>
|
||||
</el-form>
|
||||
|
||||
<!-- 预测结果 -->
|
||||
<div v-if="predictionResults" class="prediction-results">
|
||||
<h3>预测结果</h3>
|
||||
|
||||
<!-- 机器学习模型预测结果 -->
|
||||
<div class="ml-prediction">
|
||||
<h4>机器学习模型预测</h4>
|
||||
<el-descriptions border>
|
||||
<el-descriptions-item label="模型类型">
|
||||
{{ getModelName(mlPrediction.model_info.type) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="模型名称">
|
||||
{{ mlPrediction.model_info.name }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="预测成本">
|
||||
{{ formatMoney(mlPrediction.predicted_cost) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="置信区间">
|
||||
{{ formatMoney(mlPrediction.confidence_interval.lower) }} ~
|
||||
{{ formatMoney(mlPrediction.confidence_interval.upper) }}
|
||||
</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
</div>
|
||||
|
||||
<!-- PLS回归预测结果 -->
|
||||
<div class="pls-prediction">
|
||||
<h4>PLS回归预测</h4>
|
||||
<el-descriptions border>
|
||||
<el-descriptions-item label="模型类型">
|
||||
{{ getModelName(plsPrediction.model_info.type) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="模型名称">
|
||||
{{ plsPrediction.model_info.name }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="预测成本">
|
||||
{{ formatMoney(plsPrediction.predicted_cost) }}
|
||||
</el-descriptions-item>
|
||||
<el-descriptions-item label="置信区间">
|
||||
{{ formatMoney(plsPrediction.confidence_interval.lower) }} ~
|
||||
{{ formatMoney(plsPrediction.confidence_interval.upper) }}
|
||||
</el-descriptions-item>
|
||||
</el-descriptions>
|
||||
</div>
|
||||
</div>
|
||||
</el-card>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, reactive } from 'vue'
|
||||
import { ElMessage } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
|
||||
const formData = reactive({
|
||||
type: '',
|
||||
length_m: null,
|
||||
width_m: null,
|
||||
height_m: null,
|
||||
weight_kg: null,
|
||||
max_range_km: null
|
||||
})
|
||||
|
||||
const predictionResults = ref(null)
|
||||
const mlPrediction = ref(null)
|
||||
const plsPrediction = ref(null)
|
||||
|
||||
const handleTypeChange = () => {
|
||||
// 重置特有参数
|
||||
if (formData.type === '火箭炮') {
|
||||
formData.firing_angle_horizontal = null
|
||||
formData.firing_angle_vertical = null
|
||||
formData.rocket_length_m = null
|
||||
formData.rocket_diameter_mm = null
|
||||
formData.rocket_weight_kg = null
|
||||
formData.rate_of_fire = null
|
||||
} else if (formData.type === '巡飞弹') {
|
||||
formData.max_speed_kmh = null
|
||||
formData.cruise_speed_kmh = null
|
||||
formData.flight_time_min = null
|
||||
formData.warhead_type = ''
|
||||
formData.launch_mode = ''
|
||||
formData.folded_length_mm = null
|
||||
formData.folded_width_mm = null
|
||||
formData.folded_height_mm = null
|
||||
}
|
||||
}
|
||||
|
||||
const submitForm = async () => {
|
||||
try {
|
||||
// 验证必填字段
|
||||
if (!formData.type) {
|
||||
throw new Error('请选择装备类型')
|
||||
}
|
||||
|
||||
// 验证通用参数
|
||||
const commonFields = ['length_m', 'width_m', 'height_m', 'weight_kg', 'max_range_km']
|
||||
for (const field of commonFields) {
|
||||
if (!formData[field]) {
|
||||
throw new Error(`请输入${formatFieldName(field)}`)
|
||||
}
|
||||
}
|
||||
|
||||
// 验证特有参数
|
||||
if (formData.type === '火箭炮') {
|
||||
const rocketFields = [
|
||||
'firing_angle_horizontal', 'firing_angle_vertical',
|
||||
'rocket_length_m', 'rocket_diameter_mm', 'rocket_weight_kg', 'rate_of_fire'
|
||||
]
|
||||
for (const field of rocketFields) {
|
||||
if (!formData[field]) {
|
||||
throw new Error(`请输入${formatFieldName(field)}`)
|
||||
}
|
||||
}
|
||||
} else if (formData.type === '巡飞弹') {
|
||||
const missileFields = [
|
||||
'max_speed_kmh', 'cruise_speed_kmh', 'flight_time_min',
|
||||
'folded_length_mm', 'folded_width_mm', 'folded_height_mm'
|
||||
]
|
||||
for (const field of missileFields) {
|
||||
if (!formData[field]) {
|
||||
throw new Error(`请输入${formatFieldName(field)}`)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 获取预测结果
|
||||
const [mlResponse, plsResponse] = await Promise.all([
|
||||
axios.post(`${API_BASE_URL}/predict`, formData),
|
||||
axios.post(`${API_BASE_URL}/pls/predict`, formData)
|
||||
])
|
||||
|
||||
mlPrediction.value = mlResponse.data
|
||||
plsPrediction.value = plsResponse.data
|
||||
predictionResults.value = true
|
||||
|
||||
} catch (error) {
|
||||
ElMessage.error(error.message || '预测失败')
|
||||
}
|
||||
}
|
||||
|
||||
const resetForm = () => {
|
||||
formData.type = ''
|
||||
formData.length_m = null
|
||||
formData.width_m = null
|
||||
formData.height_m = null
|
||||
formData.weight_kg = null
|
||||
formData.max_range_km = null
|
||||
predictionResults.value = null
|
||||
mlPrediction.value = null
|
||||
plsPrediction.value = null
|
||||
}
|
||||
|
||||
const formatFieldName = (field) => {
|
||||
const nameMap = {
|
||||
'length_m': '总长',
|
||||
'width_m': '宽度',
|
||||
'height_m': '高度',
|
||||
'weight_kg': '重量',
|
||||
'max_range_km': '最大射程',
|
||||
'firing_angle_horizontal': '方向射界',
|
||||
'firing_angle_vertical': '高低射界',
|
||||
'rocket_length_m': '火箭弹长度',
|
||||
'rocket_diameter_mm': '弹体直径',
|
||||
'rocket_weight_kg': '火箭弹重量',
|
||||
'rate_of_fire': '射速',
|
||||
'max_speed_kmh': '最大速度',
|
||||
'cruise_speed_kmh': '巡航速度',
|
||||
'flight_time_min': '巡飞时间',
|
||||
'folded_length_mm': '折叠长度',
|
||||
'folded_width_mm': '折叠宽度',
|
||||
'folded_height_mm': '折叠高度'
|
||||
}
|
||||
return nameMap[field] || field
|
||||
}
|
||||
|
||||
const formatMoney = (value) => {
|
||||
return new Intl.NumberFormat('zh-CN', {
|
||||
style: 'currency',
|
||||
currency: 'CNY'
|
||||
}).format(value)
|
||||
}
|
||||
|
||||
const getModelName = (modelType) => {
|
||||
const modelNames = {
|
||||
'pls': 'PLS回归',
|
||||
'xgboost': 'XGBoost',
|
||||
'lightgbm': 'LightGBM',
|
||||
'gbm': 'GBM',
|
||||
'rf': 'Random Forest'
|
||||
}
|
||||
return modelNames[modelType] || modelType
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.predict-page {
|
||||
padding: 20px;
|
||||
}
|
||||
|
||||
.predict-card {
|
||||
max-width: 800px;
|
||||
margin: 0 auto;
|
||||
}
|
||||
|
||||
.prediction-results {
|
||||
margin-top: 20px;
|
||||
|
||||
.ml-prediction, .pls-prediction {
|
||||
margin-top: 20px;
|
||||
padding: 20px;
|
||||
background-color: #f5f7fa;
|
||||
border-radius: 4px;
|
||||
}
|
||||
|
||||
h4 {
|
||||
margin-top: 0;
|
||||
margin-bottom: 15px;
|
||||
}
|
||||
}
|
||||
|
||||
.el-descriptions {
|
||||
margin-top: 10px;
|
||||
}
|
||||
</style>
|
||||
370
deploy/equipment_cost_system/frontend/src/views/TrainingPage.vue
Normal file
370
deploy/equipment_cost_system/frontend/src/views/TrainingPage.vue
Normal file
@ -0,0 +1,370 @@
|
||||
<template>
|
||||
<div class="training-page">
|
||||
<el-card class="training-card">
|
||||
<template #header>
|
||||
<h2>模型训练</h2>
|
||||
</template>
|
||||
|
||||
<!-- 训练配置 -->
|
||||
<el-form :model="trainingConfig" label-width="120px">
|
||||
<el-form-item label="装备类型">
|
||||
<el-select v-model="trainingConfig.type" placeholder="选择装备类型">
|
||||
<el-option label="火箭炮" value="火箭炮" />
|
||||
<el-option label="巡飞弹" value="巡飞弹" />
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
|
||||
<el-form-item label="训练数据集">
|
||||
<el-select v-model="trainingConfig.train_dataset_id" placeholder="选择训练数据集">
|
||||
<el-option
|
||||
v-for="dataset in trainingDatasets"
|
||||
:key="dataset.id"
|
||||
:label="dataset.name"
|
||||
:value="dataset.id"
|
||||
/>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
|
||||
<el-form-item label="验证数据集">
|
||||
<el-select v-model="trainingConfig.validation_dataset_id" placeholder="选择验证数据集">
|
||||
<el-option
|
||||
v-for="dataset in validationDatasets"
|
||||
:key="dataset.id"
|
||||
:label="dataset.name"
|
||||
:value="dataset.id"
|
||||
/>
|
||||
</el-select>
|
||||
</el-form-item>
|
||||
|
||||
<el-form-item label="选择模型">
|
||||
<el-checkbox-group v-model="trainingConfig.models">
|
||||
<el-checkbox label="pls" disabled>PLS回归</el-checkbox>
|
||||
<el-checkbox label="xgboost" checked>XGBoost</el-checkbox>
|
||||
<el-checkbox label="lightgbm" checked>LightGBM</el-checkbox>
|
||||
<el-checkbox label="gbm" checked>GBM</el-checkbox>
|
||||
<el-checkbox label="rf" checked>Random Forest</el-checkbox>
|
||||
</el-checkbox-group>
|
||||
</el-form-item>
|
||||
|
||||
<el-form-item>
|
||||
<el-button type="primary" @click="startTraining" :loading="isTraining">
|
||||
开始训练
|
||||
</el-button>
|
||||
</el-form-item>
|
||||
</el-form>
|
||||
|
||||
<!-- 训练结果 -->
|
||||
<div v-if="trainingResult" class="training-result">
|
||||
<h3>训练结果</h3>
|
||||
|
||||
<!-- 最佳模型信息 -->
|
||||
<div class="best-model-info" v-if="trainingResult.best_model">
|
||||
<h4>最佳模型: {{ getModelName(trainingResult.best_model.type) }}</h4>
|
||||
<p>R²分数: {{ formatNumber(trainingResult.best_model.r2) }}</p>
|
||||
<p>MAE: {{ formatNumber(trainingResult.best_model.mae) }} 元</p>
|
||||
<p>RMSE: {{ formatNumber(trainingResult.best_model.rmse) }} 元</p>
|
||||
</div>
|
||||
|
||||
<!-- 所有模型评估结果 -->
|
||||
<el-table :data="modelResults" border style="width: 100%; margin-top: 20px;">
|
||||
<el-table-column prop="model" label="模型" width="120">
|
||||
<template #default="scope">
|
||||
{{ getModelName(scope.row.model) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
|
||||
<!-- 训练集评估 -->
|
||||
<el-table-column label="训练集评估">
|
||||
<el-table-column prop="train.r2" label="R²分数" width="120">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.train.r2) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="train.mae" label="MAE (元)" width="150">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.train.mae) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="train.rmse" label="RMSE (元)" width="150">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.train.rmse) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table-column>
|
||||
|
||||
<!-- 验证集评估 -->
|
||||
<el-table-column label="验证集评估">
|
||||
<el-table-column prop="validation.r2" label="R²分数" width="120">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.validation.r2) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="validation.mae" label="MAE (元)" width="150">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.validation.mae) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
<el-table-column prop="validation.rmse" label="RMSE (元)" width="150">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.validation.rmse) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
|
||||
<!-- 特征重要性 -->
|
||||
<div v-if="trainingResult.feature_importance" class="feature-importance">
|
||||
<h4>特征重要性</h4>
|
||||
<el-table
|
||||
:data="featureImportanceData"
|
||||
border
|
||||
style="width: 100%; margin-top: 10px;"
|
||||
>
|
||||
<el-table-column prop="feature" label="特征" width="180" />
|
||||
<el-table-column prop="importance" label="重要性" width="120">
|
||||
<template #default="scope">
|
||||
{{ formatNumber(scope.row.importance) }}
|
||||
</template>
|
||||
</el-table-column>
|
||||
</el-table>
|
||||
</div>
|
||||
</div>
|
||||
</el-card>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup>
|
||||
import { ref, computed, onMounted, watch } from 'vue'
|
||||
import { ElMessage } from 'element-plus'
|
||||
import axios from 'axios'
|
||||
import { API_BASE_URL } from '@/config'
|
||||
|
||||
// 训练配置
|
||||
const trainingConfig = ref({
|
||||
type: '',
|
||||
train_dataset_id: null,
|
||||
validation_dataset_id: null,
|
||||
models: ['pls']
|
||||
})
|
||||
|
||||
// 数据集列表
|
||||
const trainingDatasets = ref([])
|
||||
const validationDatasets = ref([])
|
||||
|
||||
// 训练状态和结果
|
||||
const isTraining = ref(false)
|
||||
const trainingResult = ref(null)
|
||||
|
||||
// 加载数据集
|
||||
const loadDatasets = async () => {
|
||||
try {
|
||||
// 加载训练数据集
|
||||
const trainResponse = await axios.get(
|
||||
`${API_BASE_URL}/datasets`,
|
||||
{ params: { equipment_type: trainingConfig.value.type, purpose: '训练' } }
|
||||
)
|
||||
trainingDatasets.value = trainResponse.data
|
||||
|
||||
// 加载验证数据集
|
||||
const valResponse = await axios.get(
|
||||
`${API_BASE_URL}/datasets`,
|
||||
{ params: { equipment_type: trainingConfig.value.type, purpose: '验证' } }
|
||||
)
|
||||
validationDatasets.value = valResponse.data
|
||||
|
||||
} catch (error) {
|
||||
ElMessage.error('加载数据集失败')
|
||||
console.error('Error loading datasets:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 监听装备类型变化
|
||||
watch(() => trainingConfig.value.type, (newType) => {
|
||||
if (newType) {
|
||||
loadDatasets()
|
||||
}
|
||||
})
|
||||
|
||||
// 开始训练
|
||||
const startTraining = async () => {
|
||||
try {
|
||||
// 验证配置
|
||||
if (!trainingConfig.value.type) {
|
||||
ElMessage.warning('请选择装备类型')
|
||||
return
|
||||
}
|
||||
if (!trainingConfig.value.train_dataset_id) {
|
||||
ElMessage.warning('请选择训练数据集')
|
||||
return
|
||||
}
|
||||
if (!trainingConfig.value.validation_dataset_id) {
|
||||
ElMessage.warning('请选择验证数据集')
|
||||
return
|
||||
}
|
||||
if (trainingConfig.value.models.length === 0) {
|
||||
ElMessage.warning('请至少选择一个模型')
|
||||
return
|
||||
}
|
||||
|
||||
isTraining.value = true
|
||||
|
||||
// 发送训练请求
|
||||
const response = await axios.post(`${API_BASE_URL}/train`, trainingConfig.value)
|
||||
|
||||
if (response.data.error) {
|
||||
throw new Error(response.data.error)
|
||||
}
|
||||
|
||||
trainingResult.value = response.data
|
||||
ElMessage.success('训练完成')
|
||||
|
||||
} catch (error) {
|
||||
ElMessage.error(error.message || '训练失败')
|
||||
console.error('Training error:', error)
|
||||
} finally {
|
||||
isTraining.value = false
|
||||
}
|
||||
}
|
||||
|
||||
// 格式化数字
|
||||
const formatNumber = (value) => {
|
||||
if (value === null || value === undefined) return '-'
|
||||
if (typeof value === 'number') {
|
||||
if (Math.abs(value) >= 1000) {
|
||||
return value.toLocaleString('zh-CN', { maximumFractionDigits: 2 })
|
||||
}
|
||||
return value.toFixed(4)
|
||||
}
|
||||
return value
|
||||
}
|
||||
|
||||
// 获取模型中文名称
|
||||
const getModelName = (modelType) => {
|
||||
const modelNames = {
|
||||
'xgboost': 'XGBoost',
|
||||
'lightgbm': 'LightGBM',
|
||||
'gbm': 'GBM',
|
||||
'rf': 'Random Forest'
|
||||
}
|
||||
return modelNames[modelType] || modelType
|
||||
}
|
||||
|
||||
// 处理模型结果数据
|
||||
const modelResults = computed(() => {
|
||||
if (!trainingResult.value?.metrics) return []
|
||||
|
||||
return Object.entries(trainingResult.value.metrics).map(([model, metrics]) => ({
|
||||
model,
|
||||
train: metrics.train,
|
||||
validation: metrics.validation
|
||||
}))
|
||||
})
|
||||
|
||||
// 特征名称映射
|
||||
const featureNameMap = {
|
||||
// 通用参数
|
||||
'length_m': '总长(m)',
|
||||
'width_m': '宽度(m)',
|
||||
'height_m': '高度(m)',
|
||||
'weight_kg': '重量(kg)',
|
||||
'max_range_km': '最大射程(km)',
|
||||
|
||||
// 火箭炮特有参数
|
||||
'firing_angle_horizontal': '方向射界(度)',
|
||||
'firing_angle_vertical': '高低射界(度)',
|
||||
'rocket_length_m': '火箭弹长度(m)',
|
||||
'rocket_diameter_mm': '口径(mm)',
|
||||
'rocket_weight_kg': '火箭弹重量(kg)',
|
||||
'rate_of_fire': '射速(发/分)',
|
||||
'combat_weight_kg': '战斗重量(kg)',
|
||||
'speed_kmh': '速度(km/h)',
|
||||
'min_range_km': '最小射程(km)',
|
||||
'power_hp': '功率(hp)',
|
||||
|
||||
// 火箭炮衍生特征
|
||||
'fire_density': '火力密度',
|
||||
'mobility_index': '机动性指标',
|
||||
'range_ratio': '射程比',
|
||||
'power_weight_ratio': '功重比',
|
||||
'volume_density': '体积密度',
|
||||
|
||||
// 巡飞弹特有参数
|
||||
'wingspan_m': '翼展(m)',
|
||||
'warhead_weight_kg': '战斗部重量(kg)',
|
||||
'max_speed_ms': '最大速度(m/s)',
|
||||
'cruise_speed_kmh': '巡航速度(km/h)',
|
||||
'flight_time_min': '巡飞时间(min)',
|
||||
'folded_length_mm': '折叠长度(mm)',
|
||||
'folded_width_mm': '折叠宽度(mm)',
|
||||
'folded_height_mm': '折叠高度(mm)',
|
||||
|
||||
// 巡飞弹衍生特征
|
||||
'warhead_ratio': '战斗部比重',
|
||||
'speed_ratio': '速度比',
|
||||
'range_time_ratio': '射程时间比',
|
||||
'aspect_ratio': '展弦比'
|
||||
}
|
||||
|
||||
// 处理特征重要性数据
|
||||
const featureImportanceData = computed(() => {
|
||||
if (!trainingResult.value?.feature_importance || !trainingResult.value?.feature_names) return []
|
||||
|
||||
// 创建特征重要性数组
|
||||
const data = trainingResult.value.feature_importance
|
||||
.map((importance, index) => ({
|
||||
feature: featureNameMap[trainingResult.value.feature_names[index]] || trainingResult.value.feature_names[index],
|
||||
importance
|
||||
}))
|
||||
// 过滤掉重要性为0的特征
|
||||
.filter(item => item.importance > 0)
|
||||
// 按重要性降序排序
|
||||
.sort((a, b) => b.importance - a.importance)
|
||||
|
||||
return data
|
||||
})
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
if (trainingConfig.value.type) {
|
||||
loadDatasets()
|
||||
}
|
||||
})
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
.training-page {
|
||||
padding: 20px;
|
||||
|
||||
.training-card {
|
||||
.training-result {
|
||||
margin-top: 20px;
|
||||
|
||||
.best-model-info {
|
||||
background-color: #f5f7fa;
|
||||
padding: 15px;
|
||||
border-radius: 4px;
|
||||
margin-bottom: 20px;
|
||||
}
|
||||
|
||||
.feature-importance {
|
||||
margin-top: 20px;
|
||||
|
||||
.importance-bar {
|
||||
width: 100%;
|
||||
background-color: #f5f7fa;
|
||||
border-radius: 4px;
|
||||
|
||||
.importance-value {
|
||||
background-color: #409eff;
|
||||
color: white;
|
||||
padding: 4px 8px;
|
||||
border-radius: 4px;
|
||||
text-align: right;
|
||||
transition: width 0.3s ease;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
</style>
|
||||
5
deploy/equipment_cost_system/frontend/vue.config.js
Normal file
5
deploy/equipment_cost_system/frontend/vue.config.js
Normal file
@ -0,0 +1,5 @@
|
||||
module.exports = {
|
||||
devServer: {
|
||||
port: 8080
|
||||
}
|
||||
}
|
||||
12
deploy/equipment_cost_system/requirements.txt
Normal file
12
deploy/equipment_cost_system/requirements.txt
Normal file
@ -0,0 +1,12 @@
|
||||
flask==2.0.1
|
||||
flask-cors==3.0.10
|
||||
sqlalchemy==1.4.23
|
||||
pymysql==1.0.2
|
||||
cryptography==3.4.7 # MySQL 8.0+ 认证需要
|
||||
numpy==1.21.2
|
||||
pandas==1.3.3
|
||||
scikit-learn==0.24.2
|
||||
tensorflow==2.6.0
|
||||
urllib3<2.0.0 # 添加这一行，限制 urllib3 版本
|
||||
openpyxl==3.1.2 # 用于读取 .xlsx 文件
|
||||
xlrd==2.0.1 # 用于读取 .xls 文件
|
||||
60
deploy/equipment_cost_system/scripts/install.sh
Normal file
60
deploy/equipment_cost_system/scripts/install.sh
Normal file
@ -0,0 +1,60 @@
|
||||
#!/bin/bash
|
||||
|
||||
echo "开始安装装备成本估算系统..."
|
||||
|
||||
# 检查Python版本
|
||||
python3 -V || {
|
||||
echo "错误: 需要 Python 3.8+"
|
||||
exit 1
|
||||
}
|
||||
|
||||
# 检查Node.js版本
|
||||
node -v || {
|
||||
echo "错误: 需要 Node.js 14+"
|
||||
exit 1
|
||||
}
|
||||
|
||||
# 创建必要的目录
|
||||
echo "创建系统目录..."
|
||||
mkdir -p {logs,data,models}
|
||||
|
||||
# 安装后端依赖
|
||||
echo "安装后端依赖..."
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
pip install -r requirements.txt
|
||||
|
||||
# 安装前端依赖
|
||||
echo "安装前端依赖..."
|
||||
cd frontend
|
||||
npm install
|
||||
npm run build
|
||||
cd ..
|
||||
|
||||
# 配置文件
|
||||
if [ ! -f config/.env ]; then
|
||||
echo "创建配置文件..."
|
||||
cp config/.env.template config/.env
|
||||
echo "请修改 config/.env 中的配置"
|
||||
fi
|
||||
|
||||
# 初始化数据库
|
||||
echo "初始化数据库..."
|
||||
read -p "请输入MySQL root密码: " mysqlpass
|
||||
mysql -u root -p$mysqlpass < src/schema.sql
|
||||
|
||||
# 导入测试数据（可选）
|
||||
read -p "是否导入测试数据？(y/n) " import_test_data
|
||||
if [ "$import_test_data" = "y" ]; then
|
||||
mysql -u root -p$mysqlpass equipment_cost_db < src/init_data.sql
|
||||
fi
|
||||
|
||||
# 设置权限
|
||||
echo "设置文件权限..."
|
||||
chmod +x scripts/*.sh
|
||||
chmod 755 logs models data
|
||||
chmod 600 config/.env
|
||||
|
||||
echo "安装完成！"
|
||||
echo "请检查并修改 config/.env 中的配置"
|
||||
echo "使用 ./scripts/start.sh 启动服务"
|
||||
51
deploy/equipment_cost_system/scripts/start.sh
Normal file
51
deploy/equipment_cost_system/scripts/start.sh
Normal file
@ -0,0 +1,51 @@
|
||||
#!/bin/bash
|
||||
|
||||
echo "启动装备成本估算系统..."
|
||||
|
||||
# 检查配置文件
|
||||
if [ ! -f config/.env ]; then
|
||||
echo "错误: 配置文件不存在"
|
||||
echo "请先运行 install.sh"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# 检查日志目录
|
||||
if [ ! -d logs ]; then
|
||||
mkdir -p logs
|
||||
fi
|
||||
|
||||
# 激活虚拟环境
|
||||
source venv/bin/activate
|
||||
|
||||
# 导出环境变量
|
||||
export $(cat config/.env | xargs)
|
||||
|
||||
# 启动后端服务
|
||||
echo "启动后端服务..."
|
||||
gunicorn -w 4 -b 0.0.0.0:5001 "src.app:create_app()" \
|
||||
--daemon \
|
||||
--pid gunicorn.pid \
|
||||
--access-logfile logs/access.log \
|
||||
--error-logfile logs/error.log
|
||||
|
||||
# 等待后端服务启动
|
||||
sleep 2
|
||||
|
||||
# 检查后端服务是否成功启动
|
||||
if ! curl -s http://localhost:5001/api/ > /dev/null; then
|
||||
echo "错误: 后端服务启动失败"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# 启动前端服务
|
||||
echo "启动前端服务..."
|
||||
cd frontend
|
||||
npm run serve -- --port 8080 --host 0.0.0.0 &
|
||||
echo $! > ../frontend.pid
|
||||
cd ..
|
||||
|
||||
echo "服务已启动！"
|
||||
echo "后端API: http://localhost:5001"
|
||||
echo "前端界面: http://localhost:8080"
|
||||
echo "查看后端日志: tail -f logs/access.log"
|
||||
echo "查看前端日志: tail -f logs/frontend.log"
|
||||
44
deploy/equipment_cost_system/scripts/stop.sh
Normal file
44
deploy/equipment_cost_system/scripts/stop.sh
Normal file
@ -0,0 +1,44 @@
|
||||
#!/bin/bash
|
||||
|
||||
echo "停止装备成本估算系统..."
|
||||
|
||||
# 停止后端服务
|
||||
if [ -f gunicorn.pid ]; then
|
||||
echo "停止后端服务..."
|
||||
pid=$(cat gunicorn.pid)
|
||||
kill -TERM $pid
|
||||
rm gunicorn.pid
|
||||
echo "后端服务已停止 (PID: $pid)"
|
||||
else
|
||||
echo "未找到后端服务PID文件"
|
||||
# 尝试查找并停止所有gunicorn进程
|
||||
pkill -f gunicorn
|
||||
echo "已尝试停止所有gunicorn进程"
|
||||
fi
|
||||
|
||||
# 停止前端服务
|
||||
if [ -f frontend.pid ]; then
|
||||
echo "停止前端服务..."
|
||||
pid=$(cat frontend.pid)
|
||||
kill -TERM $pid
|
||||
rm frontend.pid
|
||||
echo "前端服务已停止 (PID: $pid)"
|
||||
else
|
||||
echo "未找到前端服务PID文件"
|
||||
# 尝试查找并停止前端服务进程
|
||||
pkill -f "vite preview"
|
||||
echo "已尝试停止所有前端服务进程"
|
||||
fi
|
||||
|
||||
# 检查是否还有相关进程在运行
|
||||
if pgrep -f gunicorn > /dev/null; then
|
||||
echo "警告: 仍有gunicorn进程在运行"
|
||||
ps aux | grep gunicorn | grep -v grep
|
||||
fi
|
||||
|
||||
if pgrep -f "vite preview" > /dev/null; then
|
||||
echo "警告: 仍有前端服务进程在运行"
|
||||
ps aux | grep "vite preview" | grep -v grep
|
||||
fi
|
||||
|
||||
echo "所有服务已停止"
|
||||
1
deploy/equipment_cost_system/src/__init__.py
Normal file
1
deploy/equipment_cost_system/src/__init__.py
Normal file
@ -0,0 +1 @@
|
||||
# 这个文件可以为空，但必须存在
|
||||
50
deploy/equipment_cost_system/src/app.py
Normal file
50
deploy/equipment_cost_system/src/app.py
Normal file
@ -0,0 +1,50 @@
|
||||
from flask import Flask
|
||||
from flask_cors import CORS
|
||||
from .routes import api_bp
|
||||
from .logger import setup_logger
|
||||
import os
|
||||
|
||||
# 获取logger
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
def create_app():
|
||||
"""
|
||||
创建并配置Flask应用
|
||||
"""
|
||||
try:
|
||||
# 创建必要的目录
|
||||
os.makedirs('logs', exist_ok=True)
|
||||
os.makedirs('data', exist_ok=True)
|
||||
os.makedirs('models', exist_ok=True)
|
||||
|
||||
logger.info("=== Server Starting ===")
|
||||
logger.info("Initializing directories...")
|
||||
|
||||
# 创建Flask应用
|
||||
app = Flask(__name__)
|
||||
|
||||
# 配置CORS
|
||||
CORS(app)
|
||||
logger.info("CORS enabled")
|
||||
|
||||
# 注册API蓝图
|
||||
app.register_blueprint(api_bp, url_prefix='/api')
|
||||
logger.info("API blueprint registered")
|
||||
|
||||
# 配置数据库连接
|
||||
app.config['MYSQL_HOST'] = 'localhost'
|
||||
app.config['MYSQL_USER'] = 'root'
|
||||
app.config['MYSQL_PASSWORD'] = '123456'
|
||||
app.config['MYSQL_DB'] = 'equipment_cost_db'
|
||||
|
||||
logger.info("Starting server...")
|
||||
|
||||
return app
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error creating app: {str(e)}")
|
||||
raise
|
||||
|
||||
if __name__ == '__main__':
|
||||
app = create_app()
|
||||
app.run(host='localhost', port=5001)
|
||||
342
deploy/equipment_cost_system/src/cost_prediction.py
Normal file
342
deploy/equipment_cost_system/src/cost_prediction.py
Normal file
@ -0,0 +1,342 @@
|
||||
import numpy as np
|
||||
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
|
||||
from sklearn.preprocessing import StandardScaler
|
||||
import tensorflow as tf
|
||||
from scipy import stats
|
||||
import joblib
|
||||
import os
|
||||
import pandas as pd
|
||||
from .feature_analysis import FeatureAnalysis
|
||||
import logging
|
||||
from src.model_trainer import ModelTrainer
|
||||
from src.database import get_db_connection
|
||||
from .logger import setup_logger
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
class CostPredictor:
|
||||
def __init__(self):
|
||||
self.scaler_X = StandardScaler()
|
||||
self.scaler_y = StandardScaler()
|
||||
self.model = None
|
||||
self.feature_analyzer = FeatureAnalysis()
|
||||
self.equipment_type = None
|
||||
|
||||
# 添加 TensorFlow 配置
|
||||
tf.config.run_functions_eagerly(False) # 启用图执行模式
|
||||
|
||||
# 创建预测函数
|
||||
@tf.function(reduce_retracing=True, jit_compile=True)
|
||||
def predict_fn(x):
|
||||
return self.model(x, training=False)
|
||||
|
||||
self._predict_fn = predict_fn
|
||||
|
||||
self.load_model()
|
||||
|
||||
def load_model(self):
|
||||
"""
|
||||
加载预训练型和标准化器
|
||||
"""
|
||||
try:
|
||||
model_dir = 'models'
|
||||
os.makedirs(model_dir, exist_ok=True)
|
||||
|
||||
# 创建默认模型
|
||||
self._create_default_model()
|
||||
|
||||
# 创建预测函数
|
||||
@tf.function(reduce_retracing=True, jit_compile=True)
|
||||
def predict_fn(x):
|
||||
return self.model(x, training=False)
|
||||
|
||||
self._predict_fn = predict_fn
|
||||
|
||||
except Exception as e:
|
||||
logging.error(f"Error loading model: {str(e)}")
|
||||
self._create_default_model()
|
||||
|
||||
def _create_default_model(self):
|
||||
"""
|
||||
创建默认模型并进行初始化训练
|
||||
"""
|
||||
# 创建输入层
|
||||
inputs = tf.keras.Input(shape=(11,))
|
||||
|
||||
# 创建隐藏层
|
||||
x = tf.keras.layers.Dense(64, activation='relu')(inputs)
|
||||
x = tf.keras.layers.Dense(32, activation='relu')(x)
|
||||
|
||||
# 创建输出层
|
||||
outputs = tf.keras.layers.Dense(1)(x)
|
||||
|
||||
# 创建模型
|
||||
self.model = tf.keras.Model(inputs=inputs, outputs=outputs)
|
||||
|
||||
# 编译模型
|
||||
self.model.compile(
|
||||
optimizer='adam',
|
||||
loss=tf.keras.losses.mean_squared_error,
|
||||
metrics=[tf.keras.metrics.mean_absolute_error]
|
||||
)
|
||||
|
||||
# 创建示例数据
|
||||
example_data = pd.DataFrame({
|
||||
'length_m': [7.35, 10.2],
|
||||
'width_m': [2.4, 2.8],
|
||||
'height_m': [3.1, 3.2],
|
||||
'weight_kg': [13700, 28500],
|
||||
'max_range_km': [20.4, 70],
|
||||
'firing_angle_horizontal': [102, 110],
|
||||
'firing_angle_vertical': [55, 60],
|
||||
'rocket_length_m': [2.87, 4.1],
|
||||
'rocket_diameter_mm': [122, 220],
|
||||
'rocket_weight_kg': [66.6, 150],
|
||||
'rate_of_fire': [40, 60]
|
||||
})
|
||||
|
||||
# 训练标准化器
|
||||
self.scaler_X.fit(example_data)
|
||||
self.scaler_y.fit(np.array([[800000], [4500000]])) # 使用正数成本范围
|
||||
|
||||
# 设置默认装备类型
|
||||
self.equipment_type = '火箭炮'
|
||||
|
||||
def _create_example_data(self):
|
||||
"""
|
||||
创建示例数据来训练标准化器
|
||||
"""
|
||||
# 火箭炮示例数据
|
||||
rocket_data = pd.DataFrame({
|
||||
'length_m': [7.35, 10.2],
|
||||
'width_m': [2.4, 2.8],
|
||||
'height_m': [3.1, 3.2],
|
||||
'weight_kg': [13700, 28500],
|
||||
'max_range_km': [20.4, 70],
|
||||
'firing_angle_horizontal': [102, 110],
|
||||
'firing_angle_vertical': [55, 60],
|
||||
'rocket_length_m': [2.87, 4.1],
|
||||
'rocket_diameter_mm': [122, 220],
|
||||
'rocket_weight_kg': [66.6, 150],
|
||||
'rate_of_fire': [40, 60]
|
||||
})
|
||||
|
||||
# 巡飞弹示例数据
|
||||
missile_data = pd.DataFrame({
|
||||
'length_m': [1.3, 2.5],
|
||||
'width_m': [0.23, 0.6],
|
||||
'height_m': [0.23, 0.6],
|
||||
'weight_kg': [12.5, 135],
|
||||
'max_range_km': [40, 250],
|
||||
'max_speed_kmh': [180, 185],
|
||||
'cruise_speed_kmh': [100, 110],
|
||||
'flight_time_min': [60, 120],
|
||||
'folded_length_mm': [1300, 2500],
|
||||
'folded_width_mm': [230, 600],
|
||||
'folded_height_mm': [230, 600]
|
||||
})
|
||||
|
||||
# 训练标准化器
|
||||
self.scaler_X.fit(rocket_data) # 使用火箭炮数据
|
||||
self.scaler_y.fit(np.array([[800000], [4500000]])) # 示例成本数据
|
||||
|
||||
# 设置默认装备类型
|
||||
self.equipment_type = '火箭炮'
|
||||
|
||||
def predict(self, data):
|
||||
"""
|
||||
使用训练好的最优模型进行预测
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Starting prediction for {data.get('type')}")
|
||||
equipment_type = data.get('type')
|
||||
|
||||
# 加载已训练的最优模型
|
||||
trainer = ModelTrainer()
|
||||
if not trainer.load_model(equipment_type):
|
||||
raise ValueError(f"No trained model found for {equipment_type}")
|
||||
|
||||
# 准备特征数据
|
||||
features = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
X = np.array([[data.get(feature) for feature in features]])
|
||||
|
||||
# 预测
|
||||
y_pred = trainer.predict(X)
|
||||
|
||||
# 计算置信区间
|
||||
confidence_interval = trainer._calculate_confidence_interval(y_pred[0])
|
||||
|
||||
# 获取模型类型
|
||||
model_type = trainer.get_model_type()
|
||||
|
||||
return {
|
||||
'predicted_cost': float(y_pred[0]),
|
||||
'model_type': model_type, # 返回使用的模型类型
|
||||
'confidence_interval': {
|
||||
'lower': float(confidence_interval[0]),
|
||||
'upper': float(confidence_interval[1])
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Prediction error: {str(e)}")
|
||||
raise
|
||||
|
||||
def _calculate_confidence_interval(self, prediction, confidence=0.95):
|
||||
"""
|
||||
计算预测值的置信区间
|
||||
"""
|
||||
try:
|
||||
# 使用预测值的20%作为标准差（增加不确定性）
|
||||
std = abs(prediction) * 0.2
|
||||
|
||||
# 计算置信区间
|
||||
from scipy import stats
|
||||
interval = stats.norm.interval(confidence, loc=prediction, scale=std)
|
||||
|
||||
# 确保区间值为正数且合理
|
||||
lower = max(1000, interval[0]) # 最小值设为1000元
|
||||
upper = max(prediction * 1.2, interval[1]) # 至少比预测值大20%
|
||||
|
||||
logging.info(f"Calculated confidence interval: [{lower:.2f}, {upper:.2f}]")
|
||||
|
||||
return [lower, upper]
|
||||
|
||||
except Exception as e:
|
||||
logging.error(f"Error calculating confidence interval: {str(e)}")
|
||||
# 如果计算失败，返回基于20%的简单区间
|
||||
lower = max(1000, prediction * 0.8)
|
||||
upper = prediction * 1.2
|
||||
return [lower, upper]
|
||||
|
||||
def evaluate(self, y_true, y_pred):
|
||||
"""
|
||||
模型评估
|
||||
"""
|
||||
return {
|
||||
'mae': float(mean_absolute_error(y_true, y_pred)),
|
||||
'mse': float(mean_squared_error(y_true, y_pred)),
|
||||
'rmse': float(np.sqrt(mean_squared_error(y_true, y_pred))),
|
||||
'r2': float(r2_score(y_true, y_pred))
|
||||
}
|
||||
|
||||
def predict_pls(self, data):
|
||||
"""
|
||||
使用 PLS <EFBFBD><EFBFBD><EFBFBD>型预测成本
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Starting PLS prediction for {data.get('type')}")
|
||||
equipment_type = data.get('type')
|
||||
|
||||
# 加载 PLS 模型
|
||||
trainer = ModelTrainer()
|
||||
if not trainer.load_model(equipment_type, model_type='pls'): # 指定加载 PLS 模型
|
||||
raise ValueError(f"No trained PLS model found for {equipment_type}")
|
||||
|
||||
# 准备特征数据
|
||||
features = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
X = np.array([[data.get(feature) for feature in features]])
|
||||
|
||||
# 预测
|
||||
y_pred = trainer.predict(X)
|
||||
|
||||
# 计算置信区间
|
||||
confidence_interval = trainer._calculate_confidence_interval(y_pred[0])
|
||||
|
||||
return {
|
||||
'predicted_cost': float(y_pred[0]),
|
||||
'confidence_interval': {
|
||||
'lower': float(confidence_interval[0]),
|
||||
'upper': float(confidence_interval[1])
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"PLS prediction error: {str(e)}")
|
||||
raise
|
||||
|
||||
def predict_all(self, data):
|
||||
"""
|
||||
使用所有可用模型进行预测
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Starting multi-model prediction for {data.get('type')}")
|
||||
equipment_type = data.get('type')
|
||||
results = {}
|
||||
|
||||
# 1. 获取所有激活的模型
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor(dictionary=True)
|
||||
cursor.execute("""
|
||||
SELECT id, model_type, model_name, r2_score, mae, rmse
|
||||
FROM trained_models
|
||||
WHERE equipment_type = %s AND is_active = TRUE
|
||||
""", (equipment_type,))
|
||||
active_models = cursor.fetchall()
|
||||
|
||||
if not active_models:
|
||||
raise ValueError(f"No active models found for {equipment_type}")
|
||||
|
||||
# 2. 使用每个模型进行预测
|
||||
trainer = ModelTrainer()
|
||||
for model_info in active_models:
|
||||
try:
|
||||
# 加载特定模型
|
||||
if not trainer.load_model(equipment_type, model_type=model_info['model_type']):
|
||||
logger.warning(f"Failed to load model: {model_info['model_name']}")
|
||||
continue
|
||||
|
||||
# 准备特征数据
|
||||
features = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
X = np.array([[data.get(feature) for feature in features]])
|
||||
|
||||
# 预测
|
||||
y_pred = trainer.predict(X)
|
||||
|
||||
# 计算置信区间
|
||||
confidence_interval = trainer._calculate_confidence_interval(y_pred[0])
|
||||
|
||||
# 保存结果
|
||||
results[model_info['model_type']] = {
|
||||
'predicted_cost': float(y_pred[0]),
|
||||
'model_info': {
|
||||
'name': model_info['model_name'],
|
||||
'type': model_info['model_type'],
|
||||
'r2_score': float(model_info['r2_score']),
|
||||
'mae': float(model_info['mae']),
|
||||
'rmse': float(model_info['rmse'])
|
||||
},
|
||||
'confidence_interval': {
|
||||
'lower': float(confidence_interval[0]),
|
||||
'upper': float(confidence_interval[1])
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error predicting with model {model_info['model_name']}: {str(e)}")
|
||||
continue
|
||||
|
||||
if not results:
|
||||
raise ValueError("No successful predictions from any model")
|
||||
|
||||
# 3. 计算综合预测结果
|
||||
all_predictions = [result['predicted_cost'] for result in results.values()]
|
||||
ensemble_prediction = float(np.mean(all_predictions))
|
||||
prediction_std = float(np.std(all_predictions))
|
||||
|
||||
# 4. 返回所有结果
|
||||
return {
|
||||
'individual_predictions': results,
|
||||
'ensemble_prediction': {
|
||||
'predicted_cost': ensemble_prediction,
|
||||
'standard_deviation': prediction_std,
|
||||
'confidence_interval': {
|
||||
'lower': float(ensemble_prediction - 1.96 * prediction_std),
|
||||
'upper': float(ensemble_prediction + 1.96 * prediction_std)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in multi-model prediction: {str(e)}")
|
||||
raise
|
||||
155
deploy/equipment_cost_system/src/create_template.py
Normal file
155
deploy/equipment_cost_system/src/create_template.py
Normal file
@ -0,0 +1,155 @@
|
||||
import pandas as pd
|
||||
import openpyxl
|
||||
from openpyxl.styles import PatternFill, Font, Alignment
|
||||
from openpyxl.worksheet.datavalidation import DataValidation
|
||||
import os
|
||||
from .logger import setup_logger
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
def create_excel_template():
|
||||
"""
|
||||
创建数据模板
|
||||
"""
|
||||
try:
|
||||
# 确保data目录存在
|
||||
data_dir = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'data')
|
||||
os.makedirs(data_dir, exist_ok=True)
|
||||
|
||||
# 创建完整的文件路径
|
||||
template_path = os.path.join(data_dir, 'equipment_data_template.xlsx')
|
||||
|
||||
# 创建 Excel 写入器
|
||||
writer = pd.ExcelWriter(template_path, engine='openpyxl')
|
||||
|
||||
# 火箭炮基本参数表
|
||||
rocket_artillery_columns = [
|
||||
'名称', '类型', '制造商', '口径_mm',
|
||||
'反射管数量', '乘员数', '总长_m',
|
||||
'宽度_m', '高度_m', '重量_kg',
|
||||
'战斗重_kg', '速度_km/h', '最大射程_km',
|
||||
'最小射程_km', '方向射界_度', '高低射界_度',
|
||||
'火箭弹长度_m', '火箭弹重量_kg',
|
||||
'火箭弹最大速度_m/s', '射速_发',
|
||||
'战斗部重量_kg', '行走方式',
|
||||
'结构布局', '发动机型号', '发动机参数',
|
||||
'功率_hp', '行程_km', '成本_元'
|
||||
]
|
||||
|
||||
# 巡飞弹基本参数表
|
||||
loitering_munition_columns = [
|
||||
'名称', '类型', '制造商', '目标类型',
|
||||
'弹长_m', '弹径_mm', '翼展_m',
|
||||
'重量_kg', '战斗部重量_kg',
|
||||
'最大射程_km', '最大速度_m/s',
|
||||
'巡航速度_kmh', '巡飞时间_min',
|
||||
'战斗部类型', '发射方式',
|
||||
'折叠长度_mm', '折叠宽度_mm',
|
||||
'折叠高度_mm', '动力装置',
|
||||
'制导体制', '成本_元'
|
||||
]
|
||||
|
||||
# 特殊参数表
|
||||
special_params_columns = [
|
||||
'装备名称', # 关联字段
|
||||
'参数名称',
|
||||
'参数值',
|
||||
'参数单位',
|
||||
'参数说明'
|
||||
]
|
||||
|
||||
# 创建工作表
|
||||
pd.DataFrame(columns=rocket_artillery_columns).to_excel(
|
||||
writer, sheet_name='火箭炮', index=False
|
||||
)
|
||||
pd.DataFrame(columns=loitering_munition_columns).to_excel(
|
||||
writer, sheet_name='巡飞弹', index=False
|
||||
)
|
||||
pd.DataFrame(columns=special_params_columns).to_excel(
|
||||
writer, sheet_name='特殊参数', index=False
|
||||
)
|
||||
|
||||
# 获取工作簿
|
||||
workbook = writer.book
|
||||
|
||||
# 设置火箭炮工作表格式
|
||||
rocket_sheet = workbook['火箭炮']
|
||||
for col in range(1, len(rocket_artillery_columns) + 1):
|
||||
cell = rocket_sheet.cell(row=1, column=col)
|
||||
cell.fill = PatternFill(start_color='CCCCCC', end_color='CCCCCC', fill_type='solid')
|
||||
cell.font = Font(bold=True)
|
||||
cell.alignment = Alignment(horizontal='center')
|
||||
|
||||
# 设置巡飞弹工作表格式
|
||||
missile_sheet = workbook['巡飞弹']
|
||||
for col in range(1, len(loitering_munition_columns) + 1):
|
||||
cell = missile_sheet.cell(row=1, column=col)
|
||||
cell.fill = PatternFill(start_color='CCCCCC', end_color='CCCCCC', fill_type='solid')
|
||||
cell.font = Font(bold=True)
|
||||
cell.alignment = Alignment(horizontal='center')
|
||||
|
||||
# 设置特殊参数工作表格式
|
||||
special_sheet = workbook['特殊参数']
|
||||
for col in range(1, len(special_params_columns) + 1):
|
||||
cell = special_sheet.cell(row=1, column=col)
|
||||
cell.fill = PatternFill(start_color='CCCCCC', end_color='CCCCCC', fill_type='solid')
|
||||
cell.font = Font(bold=True)
|
||||
cell.alignment = Alignment(horizontal='center')
|
||||
|
||||
# 添加数据验证
|
||||
for sheet in [rocket_sheet, missile_sheet]:
|
||||
# 数值验证
|
||||
number_validation = DataValidation(type="decimal", operator="greaterThan", formula1="0")
|
||||
number_validation.error = "请输入大于0的数值"
|
||||
number_validation.errorTitle = "输入错误"
|
||||
|
||||
# 应用到相应列
|
||||
for col in ['D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O']:
|
||||
number_validation.add(f"{col}2:{col}1000")
|
||||
|
||||
sheet.add_data_validation(number_validation)
|
||||
|
||||
# 添加说明
|
||||
rocket_sheet['AD1'] = "填写说明："
|
||||
rocket_sheet['AD2'] = "1. 所有数值必须大于0"
|
||||
rocket_sheet['AD3'] = "2. 单位必须按照表头要求填写"
|
||||
rocket_sheet['AD4'] = "3. 成本单位为元"
|
||||
|
||||
missile_sheet['V1'] = "填写说明："
|
||||
missile_sheet['V2'] = "1. 所有数值必须大于0"
|
||||
missile_sheet['V3'] = "2. 单位必须按照表头要求填写"
|
||||
missile_sheet['V4'] = "3. 成本单位为元"
|
||||
|
||||
special_sheet['G1'] = "填写说明："
|
||||
special_sheet['G2'] = "1. 装备名称必须与基本参数表中的名称一致"
|
||||
special_sheet['G3'] = "2. 参数值必须包含单位"
|
||||
special_sheet['G4'] = "3. 参数说明应简明扼要"
|
||||
|
||||
# 调整列宽
|
||||
for sheet in [rocket_sheet, missile_sheet, special_sheet]:
|
||||
for col in sheet.columns:
|
||||
max_length = 0
|
||||
column = col[0].column_letter
|
||||
for cell in col:
|
||||
try:
|
||||
if len(str(cell.value)) > max_length:
|
||||
max_length = len(str(cell.value))
|
||||
except:
|
||||
pass
|
||||
adjusted_width = (max_length + 2)
|
||||
sheet.column_dimensions[column].width = adjusted_width
|
||||
|
||||
# 保存文件
|
||||
writer.close()
|
||||
|
||||
return template_path
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"创建模板文件失败: {str(e)}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
template_path = create_excel_template()
|
||||
print(f"模板文件已创建: {template_path}")
|
||||
except Exception as e:
|
||||
print(f"错误: {str(e)}")
|
||||
233
deploy/equipment_cost_system/src/data_preparation.py
Normal file
233
deploy/equipment_cost_system/src/data_preparation.py
Normal file
@ -0,0 +1,233 @@
|
||||
from sklearn.preprocessing import StandardScaler
|
||||
from datetime import datetime
|
||||
import os
|
||||
import joblib
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
from src.feature_analysis import FeatureAnalysis
|
||||
from sklearn.ensemble import GradientBoostingRegressor, RandomForestRegressor
|
||||
from xgboost import XGBRegressor
|
||||
from lightgbm import LGBMRegressor
|
||||
from sklearn.model_selection import cross_val_score, LeaveOneOut
|
||||
import json
|
||||
import logging
|
||||
from src.database.db_connection import get_db_connection
|
||||
from sklearn.metrics import mean_absolute_error, mean_squared_error
|
||||
from .logger import setup_logger
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
class DataPreparation:
|
||||
def __init__(self):
|
||||
self.feature_analyzer = FeatureAnalysis()
|
||||
self.feature_scaler = StandardScaler()
|
||||
self.target_scaler = StandardScaler() # 添加目标值标准化器
|
||||
|
||||
def prepare_training_data(self, equipment_data, equipment_type):
|
||||
"""
|
||||
准备训练数据
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Preparing training data for {equipment_type}")
|
||||
logger.info(f"Raw data size: {len(equipment_data)}")
|
||||
|
||||
# 如果输入已经是 numpy 数组，直接返回
|
||||
if isinstance(equipment_data, np.ndarray):
|
||||
X = equipment_data
|
||||
logger.info(f"Input is already numpy array with shape: {X.shape}")
|
||||
|
||||
# 处理无效值
|
||||
X = np.nan_to_num(X, nan=0.0, posinf=0.0, neginf=0.0)
|
||||
|
||||
return {
|
||||
'X': X,
|
||||
'feature_names': self.feature_analyzer.get_equipment_specific_features(equipment_type),
|
||||
'feature_scaler': self.feature_scaler,
|
||||
'target_scaler': self.target_scaler
|
||||
}
|
||||
|
||||
# 从原始数据中提取特征和目标值
|
||||
feature_names = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
features = []
|
||||
targets = []
|
||||
|
||||
for item in equipment_data:
|
||||
# 提取特征值
|
||||
feature_values = []
|
||||
for name in feature_names:
|
||||
value = item.get(name)
|
||||
try:
|
||||
feature_values.append(float(value) if value is not None else 0.0)
|
||||
except (ValueError, TypeError):
|
||||
feature_values.append(0.0)
|
||||
features.append(feature_values)
|
||||
|
||||
# 提取目标值（成本）
|
||||
try:
|
||||
cost = float(item['actual_cost'])
|
||||
if cost > 0: # 只使用正数成本值
|
||||
targets.append(cost)
|
||||
else:
|
||||
logger.warning(f"Skipping non-positive cost value: {cost}")
|
||||
except (ValueError, TypeError, KeyError):
|
||||
logger.error(f"Invalid cost value: {item.get('actual_cost')}")
|
||||
continue
|
||||
|
||||
# 转换为numpy数组
|
||||
X = np.array(features, dtype=float)
|
||||
y = np.array(targets, dtype=float)
|
||||
|
||||
# 记录原始数据范围
|
||||
logger.info(f"Raw X range: min={X.min()}, max={X.max()}")
|
||||
logger.info(f"Raw y range: min={y.min()}, max={y.max()}")
|
||||
|
||||
# 标准化特征和目标值
|
||||
X_scaled = self.feature_scaler.fit_transform(X)
|
||||
y_scaled = self.target_scaler.fit_transform(y.reshape(-1, 1)).ravel()
|
||||
|
||||
# 记录标准化后的数据范围
|
||||
logger.info(f"Scaled X range: min={X_scaled.min()}, max={X_scaled.max()}")
|
||||
logger.info(f"Scaled y range: min={y_scaled.min()}, max={y_scaled.max()}")
|
||||
|
||||
# 记录标准化器参数
|
||||
logger.info("Feature scaler params:")
|
||||
logger.info(f"Mean: {self.feature_scaler.mean_}")
|
||||
logger.info(f"Scale: {self.feature_scaler.scale_}")
|
||||
|
||||
logger.info("Target scaler params:")
|
||||
logger.info(f"Mean: {self.target_scaler.mean_}")
|
||||
logger.info(f"Scale: {self.target_scaler.scale_}")
|
||||
|
||||
return {
|
||||
'X': X_scaled,
|
||||
'y': y_scaled,
|
||||
'feature_names': feature_names,
|
||||
'feature_scaler': self.feature_scaler,
|
||||
'target_scaler': self.target_scaler
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in data preparation: {str(e)}")
|
||||
raise Exception(f"Training error: {str(e)}")
|
||||
|
||||
def prepare_validation_data(self, validation_data, equipment_type, feature_names=None, scalers=None):
|
||||
"""
|
||||
准备验证数据
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Preparing validation data for {equipment_type}")
|
||||
logger.info(f"Raw validation data size: {len(validation_data)}")
|
||||
|
||||
# 如果输入已经是 numpy 数组，直接使用
|
||||
if isinstance(validation_data, np.ndarray):
|
||||
X = validation_data
|
||||
logger.info(f"Input is already numpy array with shape: {X.shape}")
|
||||
|
||||
# 处理无效值
|
||||
X = np.nan_to_num(X, nan=0.0, posinf=0.0, neginf=0.0)
|
||||
|
||||
# 使用训练数据的标准化器
|
||||
if scalers and 'feature_scaler' in scalers:
|
||||
X_scaled = scalers['feature_scaler'].transform(X)
|
||||
else:
|
||||
X_scaled = X
|
||||
|
||||
logger.info(f"Preprocessed data shape: {X_scaled.shape}")
|
||||
logger.info(f"Validation features shape: {X_scaled.shape}")
|
||||
logger.info(f"Validation features type: {X_scaled.dtype}")
|
||||
|
||||
return {
|
||||
'X': X_scaled,
|
||||
'y': None # 验证数据可能没有标签
|
||||
}
|
||||
|
||||
# 从原始数据中提取特征和目标值
|
||||
if not feature_names:
|
||||
feature_names = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
|
||||
features = []
|
||||
targets = []
|
||||
|
||||
for item in validation_data:
|
||||
# 提取特征值
|
||||
feature_values = []
|
||||
for name in feature_names:
|
||||
value = item.get(name)
|
||||
try:
|
||||
feature_values.append(float(value) if value is not None else 0.0)
|
||||
except (ValueError, TypeError):
|
||||
feature_values.append(0.0)
|
||||
features.append(feature_values)
|
||||
|
||||
# 提取目标值（成本）并验证范围
|
||||
try:
|
||||
cost = float(item['actual_cost'])
|
||||
logger.info(f"Raw cost value: {cost}")
|
||||
if cost > 0: # 只使用正数成本值
|
||||
targets.append(cost)
|
||||
else:
|
||||
logger.warning(f"Skipping non-positive cost value: {cost}")
|
||||
except (ValueError, TypeError):
|
||||
logger.error(f"Invalid cost value: {item.get('actual_cost')}")
|
||||
continue
|
||||
|
||||
# 转换为numpy数组
|
||||
X = np.array(features, dtype=float)
|
||||
y = np.array(targets, dtype=float)
|
||||
|
||||
# 记录数据范围
|
||||
logger.info(f"Features range: min={X.min()}, max={X.max()}")
|
||||
logger.info(f"Targets range: min={y.min()}, max={y.max()}")
|
||||
|
||||
# 处理无效值
|
||||
X = np.nan_to_num(X, nan=0.0, posinf=0.0, neginf=0.0)
|
||||
|
||||
# 使用训练数据的标准化器
|
||||
if scalers and 'feature_scaler' in scalers:
|
||||
X_scaled = scalers['feature_scaler'].transform(X)
|
||||
if 'target_scaler' in scalers:
|
||||
y_scaled = scalers['target_scaler'].transform(y.reshape(-1, 1)).ravel()
|
||||
else:
|
||||
y_scaled = y
|
||||
else:
|
||||
X_scaled = X
|
||||
y_scaled = y
|
||||
|
||||
logger.info(f"Preprocessed data shape: {X_scaled.shape}")
|
||||
logger.info(f"Validation features shape: {X_scaled.shape}")
|
||||
logger.info(f"Validation features type: {X_scaled.dtype}")
|
||||
|
||||
# 记录标准化后的数据范围
|
||||
logger.info(f"Scaled validation X range: min={X_scaled.min()}, max={X_scaled.max()}")
|
||||
logger.info(f"Scaled validation y range: min={y_scaled.min()}, max={y_scaled.max()}")
|
||||
|
||||
# 确保特征维度一致
|
||||
if not feature_names:
|
||||
feature_names = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
|
||||
logger.info(f"Expected features: {len(feature_names)}")
|
||||
logger.info(f"Actual features: {X_scaled.shape[1]}")
|
||||
|
||||
if X_scaled.shape[1] != len(feature_names):
|
||||
raise ValueError(f"Feature dimension mismatch: expected {len(feature_names)}, got {X_scaled.shape[1]}")
|
||||
|
||||
return {
|
||||
'X': X_scaled,
|
||||
'y': y_scaled # 返回标准化后的成本值
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in validation data preparation: {str(e)}")
|
||||
logger.error(f"Feature names: {feature_names}")
|
||||
logger.error(f"Equipment type: {equipment_type}")
|
||||
raise Exception(f"Validation error: {str(e)}")
|
||||
|
||||
def calculate_derived_features(self, data, equipment_type):
|
||||
"""
|
||||
计算衍生特征
|
||||
"""
|
||||
try:
|
||||
return self.feature_analyzer.calculate_derived_features(data, equipment_type)
|
||||
except Exception as e:
|
||||
logger.error(f"Error calculating derived features: {str(e)}")
|
||||
raise Exception(f"Feature calculation error: {str(e)}")
|
||||
1
deploy/equipment_cost_system/src/database/__init__.py
Normal file
1
deploy/equipment_cost_system/src/database/__init__.py
Normal file
@ -0,0 +1 @@
|
||||
from .db_connection import get_db_connection
|
||||
37
deploy/equipment_cost_system/src/database/db_connection.py
Normal file
37
deploy/equipment_cost_system/src/database/db_connection.py
Normal file
@ -0,0 +1,37 @@
|
||||
import mysql.connector
|
||||
from mysql.connector import Error
|
||||
from contextlib import contextmanager
|
||||
import os
|
||||
from dotenv import load_dotenv
|
||||
from ..logger import setup_logger
|
||||
|
||||
# 获取logger
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
# 加载环境变量
|
||||
load_dotenv()
|
||||
|
||||
@contextmanager
|
||||
def get_db_connection():
|
||||
"""
|
||||
数据库连接上下文管理器
|
||||
"""
|
||||
connection = None
|
||||
try:
|
||||
connection = mysql.connector.connect(
|
||||
host=os.getenv('MYSQL_HOST', 'localhost'),
|
||||
user=os.getenv('MYSQL_USER', 'root'),
|
||||
password=os.getenv('MYSQL_PASSWORD', '123456'),
|
||||
database=os.getenv('MYSQL_DATABASE', 'equipment_cost_db')
|
||||
)
|
||||
logger.info("Database connection established")
|
||||
yield connection
|
||||
|
||||
except Error as e:
|
||||
logger.error(f"Error connecting to MySQL: {str(e)}")
|
||||
raise
|
||||
|
||||
finally:
|
||||
if connection and connection.is_connected():
|
||||
connection.close()
|
||||
logger.info("Database connection closed")
|
||||
269
deploy/equipment_cost_system/src/feature_analysis.py
Normal file
269
deploy/equipment_cost_system/src/feature_analysis.py
Normal file
@ -0,0 +1,269 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from scipy import stats
|
||||
from sklearn.preprocessing import StandardScaler
|
||||
from sklearn.ensemble import RandomForestRegressor
|
||||
from sklearn.metrics import r2_score
|
||||
import logging
|
||||
from .logger import setup_logger
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
class FeatureAnalysis:
|
||||
def __init__(self):
|
||||
self.scaler = StandardScaler()
|
||||
self.important_features = []
|
||||
|
||||
# 添加特征名称映射
|
||||
self.feature_names_map = {
|
||||
# 通用参数
|
||||
'length_m': '总长(m)',
|
||||
'width_m': '宽度(m)',
|
||||
'height_m': '高度(m)',
|
||||
'weight_kg': '重量(kg)',
|
||||
'max_range_km': '最大射程(km)',
|
||||
|
||||
# 火箭炮特有参数
|
||||
'firing_angle_horizontal': '方向射界(度)',
|
||||
'firing_angle_vertical': '高低射界(度)',
|
||||
'rocket_length_m': '火箭弹长度(m)',
|
||||
'rocket_diameter_mm': '口径(mm)',
|
||||
'rocket_weight_kg': '火箭弹重量(kg)',
|
||||
'rate_of_fire': '射速(发/分)',
|
||||
'combat_weight_kg': '战斗重量(kg)',
|
||||
'speed_kmh': '速度(km/h)',
|
||||
'min_range_km': '最小射程(km)',
|
||||
'power_hp': '功率(hp)',
|
||||
|
||||
# 火箭炮衍生特征
|
||||
'fire_density': '火力密度',
|
||||
'mobility_index': '机动性指标',
|
||||
'range_ratio': '射程比',
|
||||
'power_weight_ratio': '功重比',
|
||||
'volume_density': '体积密度',
|
||||
|
||||
# 巡飞弹特有参数
|
||||
'wingspan_m': '翼展(m)',
|
||||
'warhead_weight_kg': '战斗部重量(kg)',
|
||||
'max_speed_ms': '最大速度(m/s)',
|
||||
'cruise_speed_kmh': '巡航速度(km/h)',
|
||||
'flight_time_min': '巡飞时间(min)',
|
||||
'folded_length_mm': '折叠长度(mm)',
|
||||
'folded_width_mm': '折叠宽度(mm)',
|
||||
'folded_height_mm': '折叠高度(mm)',
|
||||
|
||||
# 巡飞弹衍生特征
|
||||
'warhead_ratio': '战斗部比重',
|
||||
'speed_ratio': '速度比',
|
||||
'range_time_ratio': '射程时间比',
|
||||
'aspect_ratio': '展弦比',
|
||||
'volume_density': '体积密度'
|
||||
}
|
||||
|
||||
def get_equipment_specific_features(self, equipment_type):
|
||||
"""
|
||||
获取特定装备类型的特征列表
|
||||
"""
|
||||
# 通用参数
|
||||
common_features = [
|
||||
'length_m', # 总长(m)
|
||||
'width_m', # 宽度(m)
|
||||
'height_m', # 高度(m)
|
||||
'weight_kg', # 重量(kg)
|
||||
'max_range_km' # 最大射程(km)
|
||||
]
|
||||
|
||||
if equipment_type == '火箭炮':
|
||||
# 火箭炮特有参数
|
||||
specific_features = [
|
||||
'firing_angle_horizontal', # 方向射界(度)
|
||||
'firing_angle_vertical', # 高低射界(度)
|
||||
'rocket_length_m', # 火箭弹长度(m)
|
||||
'rocket_diameter_mm', # 口径(mm)
|
||||
'rocket_weight_kg', # 火箭弹重量(kg)
|
||||
'rate_of_fire', # 射速(发/分)
|
||||
'combat_weight_kg', # 战斗重量(kg)
|
||||
'speed_kmh', # 速度(km/h)
|
||||
'min_range_km', # 最小射程(km)
|
||||
'power_hp' # 功率(hp)
|
||||
]
|
||||
|
||||
# 火箭炮衍生特征
|
||||
derived_features = [
|
||||
'fire_density', # 火力密度 = 射速 * 火箭弹重量
|
||||
'mobility_index', # 机动性指标 = 速度 / 战斗重量
|
||||
'range_ratio', # 射程比 = 最大射程 / 最小射程
|
||||
'power_weight_ratio', # 功重比 = 功率 / 战斗重量
|
||||
'volume_density' # 体积密度 = 重量 / (长 * 宽 * 高)
|
||||
]
|
||||
|
||||
return common_features + specific_features + derived_features
|
||||
|
||||
else: # 巡飞弹
|
||||
# 巡飞弹特有参数
|
||||
specific_features = [
|
||||
'wingspan_m', # 翼展(m)
|
||||
'warhead_weight_kg', # 战斗部重量(kg)
|
||||
'max_speed_ms', # 最大速度(m/s)
|
||||
'cruise_speed_kmh', # 巡航速度(km/h)
|
||||
'flight_time_min', # 巡飞时间(min)
|
||||
'folded_length_mm', # 折叠长度(mm)
|
||||
'folded_width_mm', # 折叠宽度(mm)
|
||||
'folded_height_mm' # 折叠高度(mm)
|
||||
]
|
||||
|
||||
# 巡飞弹衍生特征
|
||||
derived_features = [
|
||||
'warhead_ratio', # 战斗部比重 = 战斗部重量 / 总重量
|
||||
'speed_ratio', # 速度比 = 巡航速度 / 最大速度
|
||||
'range_time_ratio', # 射程时间比 = 最大射程 / 巡飞时间
|
||||
'aspect_ratio', # 展弦比 = 翼展^2 / 参考面积
|
||||
'volume_density' # 体积密度 = 重量 / (长 * 宽 * 高)
|
||||
]
|
||||
|
||||
return common_features + specific_features + derived_features
|
||||
|
||||
def calculate_derived_features(self, data, equipment_type):
|
||||
"""
|
||||
计算衍生特征
|
||||
"""
|
||||
try:
|
||||
if equipment_type == '火箭炮':
|
||||
# 火箭炮衍生特征计算
|
||||
if 'rate_of_fire' in data.columns and 'rocket_weight_kg' in data.columns:
|
||||
data['fire_density'] = data['rate_of_fire'] * data['rocket_weight_kg']
|
||||
else:
|
||||
data['fire_density'] = 0 # 或者其他默认值
|
||||
|
||||
if 'speed_kmh' in data.columns and 'combat_weight_kg' in data.columns:
|
||||
data['mobility_index'] = data['speed_kmh'] / data['combat_weight_kg']
|
||||
else:
|
||||
data['mobility_index'] = 0
|
||||
|
||||
if 'max_range_km' in data.columns and 'min_range_km' in data.columns:
|
||||
data['range_ratio'] = data['max_range_km'] / data['min_range_km']
|
||||
else:
|
||||
data['range_ratio'] = 0
|
||||
|
||||
if 'power_hp' in data.columns and 'combat_weight_kg' in data.columns:
|
||||
data['power_weight_ratio'] = data['power_hp'] / data['combat_weight_kg']
|
||||
else:
|
||||
data['power_weight_ratio'] = 0
|
||||
|
||||
if all(col in data.columns for col in ['weight_kg', 'length_m', 'width_m', 'height_m']):
|
||||
data['volume_density'] = data['weight_kg'] / (data['length_m'] * data['width_m'] * data['height_m'])
|
||||
else:
|
||||
data['volume_density'] = 0
|
||||
|
||||
else: # 巡飞弹
|
||||
# 巡飞弹衍生特征计算
|
||||
if 'warhead_weight_kg' in data.columns and 'weight_kg' in data.columns:
|
||||
data['warhead_ratio'] = data['warhead_weight_kg'] / data['weight_kg']
|
||||
else:
|
||||
data['warhead_ratio'] = 0
|
||||
|
||||
if 'cruise_speed_kmh' in data.columns and 'max_speed_ms' in data.columns:
|
||||
data['speed_ratio'] = data['cruise_speed_kmh'] / (data['max_speed_ms'] * 3.6)
|
||||
else:
|
||||
data['speed_ratio'] = 0
|
||||
|
||||
if 'max_range_km' in data.columns and 'flight_time_min' in data.columns:
|
||||
data['range_time_ratio'] = data['max_range_km'] / data['flight_time_min']
|
||||
else:
|
||||
data['range_time_ratio'] = 0
|
||||
|
||||
if 'wingspan_m' in data.columns and 'length_m' in data.columns:
|
||||
data['aspect_ratio'] = (data['wingspan_m'] ** 2) / data['length_m']
|
||||
else:
|
||||
data['aspect_ratio'] = 0
|
||||
|
||||
if all(col in data.columns for col in ['weight_kg', 'length_m', 'width_m', 'height_m']):
|
||||
data['volume_density'] = data['weight_kg'] / (data['length_m'] * data['width_m'] * data['height_m'])
|
||||
else:
|
||||
data['volume_density'] = 0
|
||||
|
||||
return data
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error calculating derived features: {str(e)}")
|
||||
raise
|
||||
|
||||
def analyze_features(self, features, target, feature_names):
|
||||
"""
|
||||
分析特征重要性和相关性
|
||||
"""
|
||||
try:
|
||||
# 转换为numpy数组
|
||||
X = np.array(features)
|
||||
y = np.array(target)
|
||||
|
||||
# 数据标准化
|
||||
X_scaled = self.scaler.fit_transform(X)
|
||||
|
||||
# 特征重要性分析
|
||||
rf = RandomForestRegressor(n_estimators=100, random_state=42)
|
||||
rf.fit(X_scaled, y)
|
||||
importances = rf.feature_importances_
|
||||
|
||||
# 按重要性排序，使用中文特征名
|
||||
importance_indices = np.argsort(importances)[::-1]
|
||||
important_features = [
|
||||
{
|
||||
'name': self.feature_names_map.get(feature_names[i], feature_names[i]),
|
||||
'importance': float(importances[i])
|
||||
}
|
||||
for i in importance_indices
|
||||
]
|
||||
|
||||
# 相关性分析
|
||||
df = pd.DataFrame(X_scaled, columns=feature_names)
|
||||
correlation_matrix = df.corr().values
|
||||
|
||||
# 生成相关性分析数据，保留2位小数
|
||||
correlation_data = []
|
||||
chinese_feature_names = [self.feature_names_map.get(name, name) for name in feature_names]
|
||||
for i in range(len(feature_names)):
|
||||
for j in range(len(feature_names)):
|
||||
correlation_data.append([
|
||||
i, j,
|
||||
round(correlation_matrix[i][j], 2) # 修改为保留2位小数
|
||||
])
|
||||
|
||||
return {
|
||||
'important_features': important_features,
|
||||
'correlation_analysis': {
|
||||
'features': chinese_feature_names, # 使用中文特征名
|
||||
'matrix': correlation_data
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in feature analysis: {str(e)}")
|
||||
raise
|
||||
|
||||
def preprocess_features(self, equipment_data, equipment_type):
|
||||
"""
|
||||
预处理特征数据
|
||||
"""
|
||||
try:
|
||||
# 转换为 DataFrame
|
||||
df = pd.DataFrame(equipment_data)
|
||||
|
||||
# 计算衍生特征
|
||||
df = self.calculate_derived_features(df, equipment_type)
|
||||
|
||||
# 处理缺失值
|
||||
numeric_columns = df.select_dtypes(include=[np.number]).columns
|
||||
for col in numeric_columns:
|
||||
# 转换为数值类型
|
||||
df[col] = pd.to_numeric(df[col], errors='coerce')
|
||||
# 使用新的方式填充缺失值
|
||||
mean_value = df[col].mean()
|
||||
df[col] = df[col].fillna(mean_value)
|
||||
|
||||
logger.info(f"Preprocessed data shape: {df.shape}")
|
||||
return df
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error preprocessing features: {str(e)}")
|
||||
raise Exception(f"Feature preprocessing error: {str(e)}")
|
||||
255
deploy/equipment_cost_system/src/import_data.py
Normal file
255
deploy/equipment_cost_system/src/import_data.py
Normal file
@ -0,0 +1,255 @@
|
||||
import pandas as pd
|
||||
from .logger import setup_logger
|
||||
from src.database.db_connection import get_db_connection
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
def import_training_data(excel_file):
|
||||
"""
|
||||
从Excel导入训练数据到数据库
|
||||
"""
|
||||
try:
|
||||
# 读取所有sheet
|
||||
rocket_df = pd.read_excel(excel_file, sheet_name='火箭炮')
|
||||
missile_df = pd.read_excel(excel_file, sheet_name='巡飞弹')
|
||||
special_df = pd.read_excel(excel_file, sheet_name='特殊参数')
|
||||
|
||||
# 记录所有装备名称，用于后续检查
|
||||
equipment_names = set()
|
||||
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 1. 先导入火箭炮数据
|
||||
logger.info("开始导入火箭炮数据...")
|
||||
for _, row in rocket_df.iterrows():
|
||||
equipment_names.add(row['名称'])
|
||||
# 检查是否已存在相同名称的装备
|
||||
cursor.execute("""
|
||||
SELECT id FROM equipment
|
||||
WHERE name = %s AND type = '火箭炮'
|
||||
""", (row['名称'],))
|
||||
|
||||
existing_equipment = cursor.fetchone()
|
||||
if existing_equipment:
|
||||
logger.warning(f"火箭炮 '{row['名称']}' 已存在，跳过导入")
|
||||
continue
|
||||
|
||||
# 插入基本信息
|
||||
cursor.execute("""
|
||||
INSERT INTO equipment (name, type, manufacturer)
|
||||
VALUES (%s, %s, %s)
|
||||
""", (row['名称'], '火箭炮', row['制造商']))
|
||||
|
||||
equipment_id = cursor.lastrowid
|
||||
|
||||
# 插入通用参数
|
||||
cursor.execute("""
|
||||
INSERT INTO common_params
|
||||
(equipment_id, length_m, width_m, height_m, weight_kg, max_range_km)
|
||||
VALUES (%s, %s, %s, %s, %s, %s)
|
||||
""", (
|
||||
equipment_id,
|
||||
row['总长_m'] if pd.notna(row['总长_m']) else None,
|
||||
row['宽度_m'] if pd.notna(row['宽度_m']) else None,
|
||||
row['高度_m'] if pd.notna(row['高度_m']) else None,
|
||||
row['重量_kg'] if pd.notna(row['重量_kg']) else None,
|
||||
row['最大射程_km'] if pd.notna(row['最大射程_km']) else None
|
||||
))
|
||||
|
||||
# 插入火箭炮特有参数
|
||||
cursor.execute("""
|
||||
INSERT INTO rocket_artillery_params
|
||||
(equipment_id, firing_angle_horizontal, firing_angle_vertical,
|
||||
rocket_length_m, rocket_diameter_mm, rocket_weight_kg, rate_of_fire,
|
||||
combat_weight_kg, speed_kmh, min_range_km, mobility_type,
|
||||
structure_layout, engine_model, engine_params, power_hp,
|
||||
travel_range_km)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
|
||||
""", (
|
||||
equipment_id,
|
||||
row['方向射界_度'] if pd.notna(row['方向射界_度']) else None,
|
||||
row['高低射界_度'] if pd.notna(row['高低射界_度']) else None,
|
||||
row['火箭弹长度_m'] if pd.notna(row['火箭弹长度_m']) else None,
|
||||
row['口径_mm'] if pd.notna(row['口径_mm']) else None,
|
||||
row['火箭弹重量_kg'] if pd.notna(row['火箭弹重量_kg']) else None,
|
||||
row['射速_发'] if pd.notna(row['射速_发']) else None,
|
||||
row['战斗重_kg'] if pd.notna(row['战斗重_kg']) else None,
|
||||
row['速度_km/h'] if pd.notna(row['速度_km/h']) else None,
|
||||
row['最小射程_km'] if pd.notna(row['最小射程_km']) else None,
|
||||
row['行走方式'] if pd.notna(row['行走方式']) else None,
|
||||
row['结构布局'] if pd.notna(row['结构布局']) else None,
|
||||
row['发动机型号'] if pd.notna(row['发动机型号']) else None,
|
||||
row['发动机参数'] if pd.notna(row['发动机参数']) else None,
|
||||
row['功率_hp'] if pd.notna(row['功率_hp']) else None,
|
||||
row['行程_km'] if pd.notna(row['行程_km']) else None
|
||||
))
|
||||
|
||||
# 插入成本数据
|
||||
if pd.notna(row['成本_元']):
|
||||
cursor.execute("""
|
||||
INSERT INTO cost_data (equipment_id, actual_cost)
|
||||
VALUES (%s, %s)
|
||||
""", (equipment_id, row['成本_元']))
|
||||
|
||||
logger.info("火箭炮数据导入完成")
|
||||
|
||||
# 2. 导入巡飞弹数据
|
||||
logger.info("开始导入巡飞弹数据...")
|
||||
for index, row in missile_df.iterrows():
|
||||
# 记录每行数据的空值情况
|
||||
null_values = row[row.isna()].index.tolist()
|
||||
if null_values:
|
||||
logger.info(f"行 {index + 2} 中的空值字段: {null_values}")
|
||||
|
||||
equipment_names.add(row['名称'])
|
||||
# 检查是否已存在相同名称的装备
|
||||
cursor.execute("""
|
||||
SELECT id FROM equipment
|
||||
WHERE name = %s AND type = '巡飞弹'
|
||||
""", (row['名称'],))
|
||||
|
||||
existing_equipment = cursor.fetchone()
|
||||
if existing_equipment:
|
||||
logger.warning(f"巡飞弹 '{row['名称']}' 已存在，跳过导入")
|
||||
continue
|
||||
|
||||
# 插入基本信息
|
||||
cursor.execute("""
|
||||
INSERT INTO equipment (name, type, manufacturer)
|
||||
VALUES (%s, %s, %s)
|
||||
""", (
|
||||
row['名称'],
|
||||
'巡飞弹',
|
||||
row['制造商'] if pd.notna(row['制造商']) else None
|
||||
))
|
||||
|
||||
equipment_id = cursor.lastrowid
|
||||
|
||||
# 插入通用参数
|
||||
cursor.execute("""
|
||||
INSERT INTO common_params
|
||||
(equipment_id, length_m, width_m, height_m, weight_kg, max_range_km)
|
||||
VALUES (%s, %s, %s, %s, %s, %s)
|
||||
""", (
|
||||
equipment_id,
|
||||
float(row['弹长_m']) if pd.notna(row['弹长_m']) else None,
|
||||
float(row['弹径_mm'])/1000 if pd.notna(row['弹径_mm']) else None, # 转换为米
|
||||
float(row['弹径_mm'])/1000 if pd.notna(row['弹径_mm']) else None, # 转换为米
|
||||
float(row['重量_kg']) if pd.notna(row['重量_kg']) else None,
|
||||
float(row['最大射程_km']) if pd.notna(row['最大射程_km']) else None
|
||||
))
|
||||
|
||||
# 插入巡飞弹特有参数
|
||||
cursor.execute("""
|
||||
INSERT INTO loitering_munition_params
|
||||
(equipment_id, wingspan_m, warhead_weight_kg, max_speed_ms,
|
||||
cruise_speed_kmh, flight_time_min, warhead_type, launch_mode,
|
||||
folded_length_mm, folded_width_mm, folded_height_mm,
|
||||
power_system, guidance_system)
|
||||
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
|
||||
""", (
|
||||
equipment_id,
|
||||
float(row['翼展_m']) if pd.notna(row['翼展_m']) else None,
|
||||
float(row['战斗部重量_kg']) if pd.notna(row['战斗部重量_kg']) else None,
|
||||
float(row['最大速度_m/s']) if pd.notna(row['最大速度_m/s']) else None,
|
||||
float(row['巡航速度_km/h']) if pd.notna(row['巡航速度_km/h']) else None,
|
||||
float(row['巡飞时间_min']) if pd.notna(row['巡飞时间_min']) else None,
|
||||
str(row['战斗部类型']) if pd.notna(row['战斗部类型']) else None,
|
||||
str(row['发射方式']) if pd.notna(row['发射方式']) else None,
|
||||
float(row['折叠长度_mm']) if pd.notna(row['折叠长度_mm']) else None,
|
||||
float(row['折叠宽度_mm']) if pd.notna(row['折叠宽度_mm']) else None,
|
||||
float(row['折叠高度_mm']) if pd.notna(row['折叠高度_mm']) else None,
|
||||
str(row['动力装置']) if pd.notna(row['动力装置']) else None,
|
||||
str(row['制导体制']) if pd.notna(row['制导体制']) else None
|
||||
))
|
||||
|
||||
# 插入成本数据
|
||||
if pd.notna(row['成本_元']):
|
||||
cursor.execute("""
|
||||
INSERT INTO cost_data (equipment_id, actual_cost)
|
||||
VALUES (%s, %s)
|
||||
""", (equipment_id, float(row['成本_元'])))
|
||||
|
||||
logger.info("巡飞弹数据导入完成")
|
||||
|
||||
# 提交之前的更改并关闭原有游标
|
||||
cursor.close()
|
||||
conn.commit()
|
||||
|
||||
# 3. 导入特殊参数
|
||||
logger.info("开始导入特殊参数...")
|
||||
for index, row in special_df.iterrows():
|
||||
equipment_name = row['装备名称']
|
||||
param_name = row['参数名称']
|
||||
logger.info(f"处理第 {index + 1} 条记录: 装备='{equipment_name}', 参数='{param_name}'")
|
||||
|
||||
if equipment_name not in equipment_names:
|
||||
logger.warning(f"未找到装备: {equipment_name}，请检查名称是否正确")
|
||||
continue
|
||||
|
||||
# 获取装备ID - 使用新的游标
|
||||
logger.debug(f"查询装备ID: {equipment_name}")
|
||||
with conn.cursor() as id_cursor:
|
||||
id_cursor.execute("""
|
||||
SELECT id FROM equipment WHERE name = %s
|
||||
""", (equipment_name,))
|
||||
result = id_cursor.fetchone()
|
||||
|
||||
if not result:
|
||||
logger.warning(f"未找到装备: {equipment_name}")
|
||||
continue
|
||||
|
||||
equipment_id = result[0]
|
||||
logger.debug(f"找到装备ID: {equipment_id}")
|
||||
|
||||
# 检查参数是否存在 - 使用新的游标
|
||||
logger.debug(f"检查参数是否存在: equipment_id={equipment_id}, param_name='{param_name}'")
|
||||
with conn.cursor() as check_cursor:
|
||||
check_cursor.execute("""
|
||||
SELECT id FROM custom_params
|
||||
WHERE equipment_id = %s AND param_name = %s
|
||||
""", (equipment_id, param_name))
|
||||
exists = check_cursor.fetchone()
|
||||
|
||||
if exists:
|
||||
logger.warning(f"装备 '{equipment_name}' 的参数 '{param_name}' 已存在，跳过导入")
|
||||
continue
|
||||
|
||||
# 插入新的参数 - 使用新的游标
|
||||
param_value = str(row['参数值']) if pd.notna(row['参数值']) else None
|
||||
param_unit = row['参数单位'] if pd.notna(row['参数单位']) else None
|
||||
param_desc = row['参数说明'] if pd.notna(row['参数说明']) else None
|
||||
|
||||
logger.debug(f"插入新参数: value='{param_value}', unit='{param_unit}', desc='{param_desc}'")
|
||||
with conn.cursor() as insert_cursor:
|
||||
insert_cursor.execute("""
|
||||
INSERT INTO custom_params
|
||||
(equipment_id, param_name, param_value, param_unit, description)
|
||||
VALUES (%s, %s, %s, %s, %s)
|
||||
""", (
|
||||
equipment_id,
|
||||
param_name,
|
||||
param_value,
|
||||
param_unit,
|
||||
param_desc
|
||||
))
|
||||
logger.debug(f"成功插入参数记录")
|
||||
|
||||
# 最终提交
|
||||
conn.commit()
|
||||
logger.info("特殊参数导入完成")
|
||||
logger.info("所有数据导入成功")
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error importing data: {str(e)}")
|
||||
raise
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
excel_file = 'data/equipment_data_20241108.xlsx'
|
||||
import_training_data(excel_file)
|
||||
logger.info("All data imported successfully")
|
||||
except Exception as e:
|
||||
logger.error(f"Import failed: {str(e)}")
|
||||
319
deploy/equipment_cost_system/src/init_data.sql
Normal file
319
deploy/equipment_cost_system/src/init_data.sql
Normal file
@ -0,0 +1,319 @@
|
||||
/*
|
||||
这是用于开发和测试环境的示例数据。
|
||||
生产环境请使用系统的数据导入功能添加实际数据。
|
||||
|
||||
主要用途：
|
||||
1. 提供开发测试数据
|
||||
2. 作为数据格式参考
|
||||
3. 用于系统功能验证
|
||||
*/
|
||||
|
||||
-- 插入装备基本信息
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('终结者', '巡飞弹', '美国', '静止和移动的人员和轻型装甲车辆'),
|
||||
('胜利-2', '火箭炮', '伊朗', '地面固定目标');
|
||||
|
||||
-- 插入巡飞弹技术参数
|
||||
INSERT INTO technical_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_speed_kmh,
|
||||
cruise_speed_kmh,
|
||||
max_range_km,
|
||||
flight_time_min,
|
||||
warhead_type,
|
||||
launch_mode,
|
||||
folded_length_mm,
|
||||
folded_width_mm,
|
||||
folded_height_mm
|
||||
) VALUES (
|
||||
1, -- 终结者巡飞弹
|
||||
0.56,
|
||||
0.15,
|
||||
0.20,
|
||||
2.72,
|
||||
160.93,
|
||||
96.56,
|
||||
24,
|
||||
15,
|
||||
'破片杀伤战斗部',
|
||||
'凭自身动力起飞',
|
||||
560,
|
||||
150,
|
||||
200
|
||||
);
|
||||
|
||||
-- 插入火箭炮技术参数
|
||||
INSERT INTO technical_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_range_km
|
||||
) VALUES (
|
||||
2, -- 胜利-2火箭炮
|
||||
10,
|
||||
2.5,
|
||||
3.34,
|
||||
15000,
|
||||
23
|
||||
);
|
||||
|
||||
-- 插入成本数据（示例数据）
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
(1, 1000000), -- 终结者巡飞弹成本
|
||||
(2, 5000000); -- 胜利-2火箭炮成本
|
||||
|
||||
-- 插入更多巡飞弹变体数据用于训练
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('终结者-A', '巡飞弹', '美国', '静止和移动的人员和轻型装甲车辆'),
|
||||
('终结者-B', '巡飞弹', '美国', '静止和移动的人员和轻型装甲车辆'),
|
||||
('终结者-C', '巡飞弹', '美国', '静止和移动的人员和轻型装甲车辆');
|
||||
|
||||
-- 插入变体技术参数
|
||||
INSERT INTO technical_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_speed_kmh,
|
||||
cruise_speed_kmh,
|
||||
max_range_km,
|
||||
flight_time_min,
|
||||
warhead_type,
|
||||
launch_mode,
|
||||
folded_length_mm,
|
||||
folded_width_mm,
|
||||
folded_height_mm
|
||||
) VALUES
|
||||
-- 终结者-A（稍大型号）
|
||||
(3, 0.58, 0.16, 0.21, 2.85, 170, 100, 26, 16, '破片杀伤战斗部', '凭自身动力起飞', 580, 160, 210),
|
||||
-- 终结者-B（稍小型号）
|
||||
(4, 0.54, 0.14, 0.19, 2.60, 155, 93, 22, 14, '破片杀伤战斗部', '凭自身动力起飞', 540, 140, 190),
|
||||
-- 终结者-C（标准型号的改进版）
|
||||
(5, 0.56, 0.15, 0.20, 2.70, 165, 98, 25, 15, '破片杀伤战斗部', '凭自身动力起飞', 560, 150, 200);
|
||||
|
||||
-- 插入变体成本数据
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
(3, 1100000), -- 终结者-A成本（较高）
|
||||
(4, 900000), -- 终结者-B成本（较低）
|
||||
(5, 1050000); -- 终结者-C成本（中等）
|
||||
|
||||
-- 添加更多巡飞弹数据
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('哈比', '巡飞弹', '以色列', '防空系统和雷达站'),
|
||||
('游荡者', '巡飞弹', '以色列', '装甲车辆和防空系统'),
|
||||
('凤凰', '巡飞弹', '土耳其', '固定目标和装甲车辆'),
|
||||
('弹簧刀', '巡飞弹', '波兰', '装甲目标'),
|
||||
('彩虹-4', '巡飞弹', '中国', '地面固定目标');
|
||||
|
||||
-- 添加它们的技术参数
|
||||
INSERT INTO technical_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_speed_kmh,
|
||||
cruise_speed_kmh,
|
||||
max_range_km,
|
||||
flight_time_min,
|
||||
warhead_type,
|
||||
launch_mode,
|
||||
folded_length_mm,
|
||||
folded_width_mm,
|
||||
folded_height_mm
|
||||
) VALUES
|
||||
-- 哈比
|
||||
(6, 2.5, 0.6, 0.6, 135, 185, 110, 250, 120, '高爆战斗部', '箱式发射', 2500, 600, 600),
|
||||
-- 游荡者
|
||||
(7, 2.3, 0.4, 0.4, 30, 190, 120, 30, 30, '破片杀伤战斗部', '箱式发射', 2300, 400, 400),
|
||||
-- 凤凰
|
||||
(8, 2.0, 0.3, 0.3, 25, 170, 100, 20, 25, '破片杀伤战斗部', '箱式发射', 2000, 300, 300),
|
||||
-- 弹簧刀
|
||||
(9, 1.8, 0.35, 0.35, 28, 180, 110, 25, 30, '破片杀伤战斗部', '箱式发射', 1800, 350, 350),
|
||||
-- 彩虹-4
|
||||
(10, 3.5, 0.8, 0.8, 345, 210, 130, 300, 180, '高爆战斗部', '箱式发射', 3500, 800, 800);
|
||||
|
||||
-- 添加成本数据
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
(6, 800000), -- 哈比
|
||||
(7, 500000), -- 游荡者
|
||||
(8, 450000), -- 凤凰
|
||||
(9, 480000), -- 弹簧刀
|
||||
(10, 1500000); -- 彩虹-4
|
||||
|
||||
-- 火箭炮数据
|
||||
INSERT INTO equipment (name, type, manufacturer) VALUES
|
||||
('BM-21', '火箭炮', '俄罗斯'),
|
||||
('SR5', '火箭炮', '中国'),
|
||||
('HIMARS', '火箭炮', '美国'),
|
||||
('LAR-160', '火箭炮', '以色列'),
|
||||
('T-122', '火箭炮', '土耳其'),
|
||||
('RM-70', '火箭炮', '捷克'),
|
||||
('ASTROS II', '火箭炮', '巴西');
|
||||
|
||||
-- 火箭炮通用参数
|
||||
INSERT INTO common_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_range_km
|
||||
) VALUES
|
||||
-- BM-21
|
||||
(1, 7.35, 2.4, 3.1, 13700, 20.4),
|
||||
-- SR5
|
||||
(2, 10.2, 2.8, 3.2, 28500, 70),
|
||||
-- HIMARS
|
||||
(3, 7.0, 2.4, 3.2, 16250, 70),
|
||||
-- LAR-160
|
||||
(4, 6.7, 2.5, 2.8, 15000, 45),
|
||||
-- T-122
|
||||
(5, 7.2, 2.5, 2.9, 18000, 40),
|
||||
-- RM-70
|
||||
(6, 7.5, 2.5, 3.0, 17200, 20.3),
|
||||
-- ASTROS II
|
||||
(7, 8.0, 2.7, 3.1, 24500, 90);
|
||||
|
||||
-- 火箭炮特有参数
|
||||
INSERT INTO rocket_artillery_params (
|
||||
equipment_id,
|
||||
firing_angle_horizontal,
|
||||
firing_angle_vertical,
|
||||
rocket_length_m,
|
||||
rocket_diameter_mm,
|
||||
rocket_weight_kg,
|
||||
rate_of_fire,
|
||||
combat_weight_kg,
|
||||
speed_kmh,
|
||||
min_range_km,
|
||||
mobility_type,
|
||||
structure_layout,
|
||||
engine_model,
|
||||
engine_params,
|
||||
power_hp,
|
||||
travel_range_km
|
||||
) VALUES
|
||||
-- BM-21
|
||||
(1, 102, 55, 2.87, 122, 66.6, 40, 13700, 75, 1.6, '轮式', '前置驾驶舱', 'V8柴油', '240马力', 240, 500),
|
||||
-- SR5
|
||||
(2, 110, 60, 4.1, 220, 150, 60, 28500, 90, 2.0, '轮式', '前置驾驶舱', 'V6柴油', '320马力', 320, 650),
|
||||
-- HIMARS
|
||||
(3, 90, 65, 3.94, 227, 301, 6, 16250, 85, 2.0, '轮式', '前置驾驶舱', 'V8柴油', '290马力', 290, 480),
|
||||
-- LAR-160
|
||||
(4, 100, 58, 3.3, 160, 110, 18, 15000, 80, 1.8, '轮式', '前置驾驶舱', 'V6柴油', '260马力', 260, 550),
|
||||
-- T-122
|
||||
(5, 110, 65, 2.95, 122, 65.5, 40, 18000, 85, 1.5, '轮式', '前置驾驶舱', 'V8柴油', '280马力', 280, 600),
|
||||
-- RM-70
|
||||
(6, 100, 50, 2.87, 122, 66.6, 40, 17200, 70, 1.6, '轮式', '前置驾驶舱', 'V8柴油', '250马力', 250, 520),
|
||||
-- ASTROS II
|
||||
(7, 90, 65, 4.3, 300, 550, 30, 24500, 80, 2.2, '轮式', '前置驾驶舱', 'V8柴油', '350马力', 350, 700);
|
||||
|
||||
-- 巡飞弹数据
|
||||
INSERT INTO equipment (name, type, manufacturer) VALUES
|
||||
('Hero-120', '巡飞弹', '以色列'),
|
||||
('Switchblade 600', '巡飞弹', '美国'),
|
||||
('Warmate', '巡飞弹', '波兰'),
|
||||
('CH-901', '巡飞弹', '中国'),
|
||||
('HAROP', '巡飞弹', '以色列'),
|
||||
('Coyote', '巡飞弹', '美国'),
|
||||
('WS-43', '巡飞弹', '中国');
|
||||
|
||||
-- 巡飞弹通用参数
|
||||
INSERT INTO common_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
width_m,
|
||||
height_m,
|
||||
weight_kg,
|
||||
max_range_km
|
||||
) VALUES
|
||||
-- Hero-120
|
||||
(8, 1.3, 0.23, 0.23, 12.5, 40),
|
||||
-- Switchblade 600
|
||||
(9, 1.3, 0.22, 0.22, 15.0, 40),
|
||||
-- Warmate
|
||||
(10, 1.1, 0.15, 0.15, 5.7, 15),
|
||||
-- CH-901
|
||||
(11, 1.2, 0.18, 0.18, 9.0, 20),
|
||||
-- HAROP
|
||||
(12, 2.5, 0.43, 0.43, 135, 1000),
|
||||
-- Coyote
|
||||
(13, 0.9, 0.12, 0.12, 5.9, 20),
|
||||
-- WS-43
|
||||
(14, 1.8, 0.35, 0.35, 20, 60);
|
||||
|
||||
-- 巡飞弹特有参数
|
||||
INSERT INTO loitering_munition_params (
|
||||
equipment_id,
|
||||
wingspan_m,
|
||||
warhead_weight_kg,
|
||||
max_speed_ms,
|
||||
cruise_speed_kmh,
|
||||
flight_time_min,
|
||||
warhead_type,
|
||||
launch_mode,
|
||||
folded_length_mm,
|
||||
folded_width_mm,
|
||||
folded_height_mm,
|
||||
power_system,
|
||||
guidance_system
|
||||
) VALUES
|
||||
-- Hero-120
|
||||
(8, 2.1, 3.5, 50, 100, 60, '破片杀伤战斗部', '箱式发射', 1300, 230, 230, '电动机', 'GPS/INS'),
|
||||
-- Switchblade 600
|
||||
(9, 2.2, 4.0, 51.4, 115, 40, '破甲战斗部', '箱式发射', 1300, 220, 220, '电动机', 'GPS/INS/光电'),
|
||||
-- Warmate
|
||||
(10, 1.4, 1.4, 41.7, 90, 30, '破片杀伤战斗部', '箱式发射', 1100, 150, 150, '电动机', 'GPS/INS'),
|
||||
-- CH-901
|
||||
(11, 1.8, 2.0, 44.4, 95, 120, '破片杀伤战斗部', '箱式发射', 1200, 180, 180, '电动机', 'GPS/INS'),
|
||||
-- HAROP
|
||||
(12, 3.0, 23, 51.4, 110, 360, '高爆战斗部', '箱式发射', 2500, 430, 430, '活塞发动机', 'GPS/INS/光电/数据链'),
|
||||
-- Coyote
|
||||
(13, 1.2, 1.8, 41.7, 95, 30, '破片杀伤战斗部', '箱式发射', 900, 120, 120, '电动机', 'GPS/INS'),
|
||||
-- WS-43
|
||||
(14, 2.4, 3.8, 47.2, 100, 45, '破片杀伤战斗部', '箱式发射', 1800, 350, 350, '电动机', 'GPS/INS/光电');
|
||||
|
||||
-- 插入成本数据（示例成本）
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
-- 火箭炮
|
||||
(1, 800000), -- BM-21
|
||||
(2, 4500000), -- SR5
|
||||
(3, 5500000), -- HIMARS
|
||||
(4, 3500000), -- LAR-160
|
||||
(5, 2800000), -- T-122
|
||||
(6, 1500000), -- RM-70
|
||||
(7, 4800000), -- ASTROS II
|
||||
-- 巡飞弹
|
||||
(8, 150000), -- Hero-120
|
||||
(9, 180000), -- Switchblade 600
|
||||
(10, 80000), -- Warmate
|
||||
(11, 100000), -- CH-901
|
||||
(12, 850000), -- HAROP
|
||||
(13, 75000), -- Coyote
|
||||
(14, 120000); -- WS-43
|
||||
|
||||
-- 创建初始数据集
|
||||
INSERT INTO datasets (name, description, equipment_type, purpose) VALUES
|
||||
('火箭炮训练集', '用于训练火箭炮成本预测模型的数据集', '火箭炮', '训练'),
|
||||
('巡飞弹训练集', '用于训练巡飞弹成本预测模型的数据集', '巡飞弹', '训练'),
|
||||
('火箭炮验证集', '用于验证火箭炮成本预测模型的数据集', '火箭炮', '验证'),
|
||||
('巡飞弹验证集', '用于验证巡飞弹成本预测模型的数据集', '巡飞弹', '验证');
|
||||
|
||||
-- 关联装备到数据集
|
||||
INSERT INTO dataset_equipment (dataset_id, equipment_id) VALUES
|
||||
-- 火箭炮训练集
|
||||
(1, 1), (1, 2), (1, 3), (1, 4),
|
||||
-- 巡飞弹训练集
|
||||
(2, 8), (2, 9), (2, 10), (2, 11), (2, 12),
|
||||
-- 火箭炮验证集
|
||||
(3, 5), (3, 6), (3, 7),
|
||||
-- 巡飞弹验证集
|
||||
(4, 13), (4, 14);
|
||||
33
deploy/equipment_cost_system/src/logger.py
Normal file
33
deploy/equipment_cost_system/src/logger.py
Normal file
@ -0,0 +1,33 @@
|
||||
import logging
|
||||
import os
|
||||
from datetime import datetime
|
||||
|
||||
def setup_logger(name):
|
||||
"""
|
||||
创建并配置logger
|
||||
"""
|
||||
# 创建logger
|
||||
logger = logging.getLogger(name)
|
||||
|
||||
# 如果logger已经有处理器，直接返回
|
||||
if logger.handlers:
|
||||
return logger
|
||||
|
||||
# 设置日志级别
|
||||
logger.setLevel(logging.INFO)
|
||||
|
||||
# 确保日志目录存在
|
||||
os.makedirs('logs', exist_ok=True)
|
||||
|
||||
# 创建文件处理器
|
||||
file_handler = logging.FileHandler('logs/api.log')
|
||||
file_handler.setLevel(logging.INFO)
|
||||
|
||||
# 创建格式化器
|
||||
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
|
||||
file_handler.setFormatter(formatter)
|
||||
|
||||
# 添加处理器
|
||||
logger.addHandler(file_handler)
|
||||
|
||||
return logger
|
||||
612
deploy/equipment_cost_system/src/model_trainer.py
Normal file
612
deploy/equipment_cost_system/src/model_trainer.py
Normal file
@ -0,0 +1,612 @@
|
||||
import numpy as np
|
||||
import pandas as pd
|
||||
from sklearn.preprocessing import StandardScaler
|
||||
from sklearn.model_selection import cross_val_score
|
||||
from sklearn.ensemble import RandomForestRegressor, GradientBoostingRegressor
|
||||
from sklearn.impute import SimpleImputer
|
||||
import xgboost as xgb
|
||||
import lightgbm as lgb
|
||||
import logging
|
||||
import joblib
|
||||
import os
|
||||
from src.feature_analysis import FeatureAnalysis
|
||||
from datetime import datetime
|
||||
import json
|
||||
from src.database import get_db_connection
|
||||
from src.data_preparation import DataPreparation
|
||||
from sklearn.cross_decomposition import PLSRegression
|
||||
from .logger import setup_logger
|
||||
|
||||
logger = setup_logger(__name__)
|
||||
|
||||
class ModelTrainer:
|
||||
def __init__(self):
|
||||
"""
|
||||
初始化 ModelTrainer
|
||||
"""
|
||||
self.models = {
|
||||
'xgboost': self._create_xgboost_model(),
|
||||
'lightgbm': self._create_lightgbm_model(),
|
||||
'gbm': self._create_gbm_model(),
|
||||
'rf': self._create_rf_model(),
|
||||
'pls': self._create_pls_model()
|
||||
}
|
||||
self.best_model = None
|
||||
self.imputer = SimpleImputer(strategy='mean')
|
||||
self.feature_scaler = None
|
||||
self.target_scaler = None
|
||||
self.equipment_type = None
|
||||
self.feature_analyzer = FeatureAnalysis()
|
||||
|
||||
def fit_model(self, X_train, y_train, model_names, X_val=None, y_val=None, equipment_type=None):
|
||||
"""
|
||||
训练模型并返回评估结果
|
||||
"""
|
||||
try:
|
||||
self.equipment_type = equipment_type
|
||||
logger.info(f"Training data range - X: min={X_train.min()}, max={X_train.max()}")
|
||||
logger.info(f"Training data range - y: min={y_train.min()}, max={y_train.max()}")
|
||||
|
||||
results = {}
|
||||
best_score = -float('inf')
|
||||
best_model_info = None
|
||||
|
||||
# 首先训练 PLS 模型
|
||||
logger.info("Training pls...")
|
||||
pls_model = self.models['pls']
|
||||
pls_model.fit(X_train, y_train)
|
||||
pls_metrics = self._calculate_metrics(
|
||||
pls_model,
|
||||
X_train, y_train,
|
||||
X_val, y_val
|
||||
)
|
||||
results['pls'] = pls_metrics
|
||||
|
||||
# 训练其他机器学习模型
|
||||
for model_name in model_names:
|
||||
if model_name == 'pls': # 跳过 PLS 模型，因为已经训练过了
|
||||
continue
|
||||
|
||||
if model_name not in self.models:
|
||||
logger.warning(f"Unknown model: {model_name}")
|
||||
continue
|
||||
|
||||
logger.info(f"Training {model_name}...")
|
||||
model = self.models[model_name]
|
||||
|
||||
# 训练模型
|
||||
model.fit(X_train, y_train)
|
||||
|
||||
# 计算评估指标
|
||||
metrics = self._calculate_metrics(
|
||||
model,
|
||||
X_train, y_train,
|
||||
X_val, y_val
|
||||
)
|
||||
|
||||
results[model_name] = metrics
|
||||
|
||||
# 更新最佳模型（只在机器学习模型中比较）
|
||||
if metrics['validation']['r2'] > best_score:
|
||||
best_score = metrics['validation']['r2']
|
||||
best_model_info = {
|
||||
'type': model_name,
|
||||
'r2': metrics['validation']['r2'],
|
||||
'mae': metrics['validation']['mae'],
|
||||
'rmse': metrics['validation']['rmse']
|
||||
}
|
||||
self.best_model = model
|
||||
|
||||
# 保存最佳模型和 PLS 模型
|
||||
if equipment_type and best_model_info:
|
||||
self._save_best_model(equipment_type, best_model_info, X_train, y_train, X_val, y_val)
|
||||
|
||||
return {
|
||||
'metrics': results,
|
||||
'best_model': best_model_info
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in model training: {str(e)}")
|
||||
raise
|
||||
|
||||
def _calculate_metrics(self, model, X_train, y_train, X_val=None, y_val=None):
|
||||
"""
|
||||
计算模型评估指标
|
||||
"""
|
||||
from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error
|
||||
|
||||
# 训练集评估
|
||||
train_pred = model.predict(X_train)
|
||||
|
||||
# 如果使用了标准化，需要转换回原始范围
|
||||
if hasattr(self, 'target_scaler'):
|
||||
train_pred = self.target_scaler.inverse_transform(train_pred.reshape(-1, 1)).ravel()
|
||||
y_train_orig = self.target_scaler.inverse_transform(y_train.reshape(-1, 1)).ravel()
|
||||
else:
|
||||
y_train_orig = y_train
|
||||
|
||||
# 记录预测范围
|
||||
logger.info(f"Train predictions range: min={train_pred.min()}, max={train_pred.max()}")
|
||||
logger.info(f"Train actual range: min={y_train_orig.min()}, max={y_train_orig.max()}")
|
||||
|
||||
train_metrics = {
|
||||
'r2': r2_score(y_train_orig, train_pred),
|
||||
'mae': mean_absolute_error(y_train_orig, train_pred),
|
||||
'rmse': np.sqrt(mean_squared_error(y_train_orig, train_pred))
|
||||
}
|
||||
|
||||
# 验证集评估
|
||||
if X_val is not None and y_val is not None:
|
||||
val_pred = model.predict(X_val)
|
||||
|
||||
# 如果使用了标准化，需要转换回原始范围
|
||||
if hasattr(self, 'target_scaler'):
|
||||
val_pred = self.target_scaler.inverse_transform(val_pred.reshape(-1, 1)).ravel()
|
||||
y_val_orig = self.target_scaler.inverse_transform(y_val.reshape(-1, 1)).ravel()
|
||||
else:
|
||||
y_val_orig = y_val
|
||||
|
||||
# 记录预测范围
|
||||
logger.info(f"Validation predictions range: min={val_pred.min()}, max={val_pred.max()}")
|
||||
logger.info(f"Validation actual range: min={y_val_orig.min()}, max={y_val_orig.max()}")
|
||||
|
||||
val_metrics = {
|
||||
'r2': r2_score(y_val_orig, val_pred),
|
||||
'mae': mean_absolute_error(y_val_orig, val_pred),
|
||||
'rmse': np.sqrt(mean_squared_error(y_val_orig, val_pred))
|
||||
}
|
||||
else:
|
||||
# 使用交叉验证
|
||||
cv_scores = cross_val_score(model, X_train, y_train, cv=5)
|
||||
val_metrics = {
|
||||
'r2': cv_scores.mean(),
|
||||
'mae': None,
|
||||
'rmse': None
|
||||
}
|
||||
|
||||
return {
|
||||
'train': train_metrics,
|
||||
'validation': val_metrics
|
||||
}
|
||||
|
||||
def _create_xgboost_model(self):
|
||||
"""
|
||||
创建 XGBoost 模型，增强正则化
|
||||
"""
|
||||
return xgb.XGBRegressor(
|
||||
n_estimators=50, # 减少树的数量
|
||||
learning_rate=0.05, # 学习率
|
||||
max_depth=3, # 减小树的深
|
||||
min_child_weight=3, # 增加节点权重
|
||||
subsample=0.7, # 减小样本采样比例
|
||||
colsample_bytree=0.7, # 减小特征采样比例
|
||||
reg_alpha=0.1, # L1 正则化
|
||||
reg_lambda=1, # L2 正则化
|
||||
random_state=42
|
||||
)
|
||||
|
||||
def _create_lightgbm_model(self):
|
||||
"""
|
||||
创建 LightGBM 模型，增强正则化
|
||||
"""
|
||||
return lgb.LGBMRegressor(
|
||||
n_estimators=50,
|
||||
learning_rate=0.05,
|
||||
max_depth=3,
|
||||
num_leaves=7,
|
||||
min_data_in_leaf=3,
|
||||
min_sum_hessian_in_leaf=1e-3,
|
||||
subsample=0.7,
|
||||
colsample_bytree=0.7,
|
||||
reg_alpha=0.1,
|
||||
reg_lambda=1,
|
||||
random_state=42,
|
||||
verbose=-1
|
||||
)
|
||||
|
||||
def _create_gbm_model(self):
|
||||
"""
|
||||
创建 GBM 模型，增强正则化以减轻过拟合
|
||||
"""
|
||||
return GradientBoostingRegressor(
|
||||
n_estimators=100,
|
||||
learning_rate=0.1,
|
||||
max_depth=3,
|
||||
random_state=42,
|
||||
subsample=0.8,
|
||||
min_samples_split=3,
|
||||
min_samples_leaf=2
|
||||
)
|
||||
|
||||
def _create_rf_model(self):
|
||||
"""
|
||||
创建随机森林模型，针对小样本数据调整参数
|
||||
"""
|
||||
return RandomForestRegressor(
|
||||
n_estimators=100,
|
||||
max_depth=3,
|
||||
random_state=42,
|
||||
min_samples_split=3,
|
||||
min_samples_leaf=2
|
||||
)
|
||||
|
||||
def _create_pls_model(self):
|
||||
"""
|
||||
创建 PLS 模型，优化参数配置
|
||||
"""
|
||||
return PLSRegression(
|
||||
n_components=2, # 减少主成分数量，从5减到2
|
||||
scale=True, # 保持数据标准化
|
||||
max_iter=500, # 减少最大迭代次数，避免过拟合
|
||||
tol=1e-6 # 降低收敛精度，避免过拟合
|
||||
)
|
||||
|
||||
def _save_best_model(self, equipment_type, best_model_info, X_train, y_train, X_val=None, y_val=None):
|
||||
"""
|
||||
保存最佳模型和 PLS 模型
|
||||
"""
|
||||
try:
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
model_dir = 'models'
|
||||
os.makedirs(model_dir, exist_ok=True)
|
||||
|
||||
# 1. 保存最佳机器学习模型
|
||||
model_path = f'{model_dir}/{equipment_type}_{timestamp}'
|
||||
if isinstance(self.best_model, xgb.XGBRegressor):
|
||||
self.best_model.save_model(f'{model_path}.json')
|
||||
model_format = 'json'
|
||||
else:
|
||||
joblib.dump(self.best_model, f'{model_path}.joblib')
|
||||
model_format = 'joblib'
|
||||
|
||||
# 2. 保存 PLS 模型
|
||||
pls_model = self.models['pls']
|
||||
pls_path = f'{model_dir}/{equipment_type}_{timestamp}_pls.joblib'
|
||||
joblib.dump(pls_model, pls_path)
|
||||
|
||||
# 3. 保存标准化器
|
||||
scaler_path = f'{model_dir}/{equipment_type}_{timestamp}_scaler.joblib'
|
||||
joblib.dump({
|
||||
'feature_scaler': self.feature_scaler,
|
||||
'target_scaler': self.target_scaler
|
||||
}, scaler_path)
|
||||
|
||||
logger.info(f"Saved best model to {model_path}.{model_format}")
|
||||
logger.info(f"Saved PLS model to {pls_path}")
|
||||
logger.info(f"Saved scalers to {scaler_path}")
|
||||
|
||||
# 4. 更新数据库中的模型记录
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor()
|
||||
|
||||
# 将所有模型设置为非激活
|
||||
cursor.execute("""
|
||||
UPDATE trained_models
|
||||
SET is_active = FALSE
|
||||
WHERE equipment_type = %s
|
||||
""", (equipment_type,))
|
||||
|
||||
# 获取 PLS 模型的评估指标
|
||||
pls_metrics = self._calculate_metrics(
|
||||
self.models['pls'],
|
||||
X_train,
|
||||
y_train,
|
||||
X_val,
|
||||
y_val
|
||||
)
|
||||
|
||||
# 保存最佳机器学习模型记录
|
||||
self.best_model.equipment_type = equipment_type # 设置装备类型
|
||||
ml_feature_importance = self._get_feature_importance(self.best_model)
|
||||
|
||||
cursor.execute("""
|
||||
INSERT INTO trained_models (
|
||||
model_name, model_type, equipment_type, model_path, scaler_path,
|
||||
r2_score, mae, rmse, feature_importance, training_data_size,
|
||||
training_date, is_active, created_by
|
||||
) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), TRUE, %s)
|
||||
""", (
|
||||
f"{equipment_type}_{timestamp}", # model_name
|
||||
best_model_info['type'], # model_type
|
||||
equipment_type, # equipment_type
|
||||
f"{model_path}.{model_format}", # model_path
|
||||
scaler_path, # scaler_path
|
||||
best_model_info['r2'], # r2_score
|
||||
best_model_info['mae'], # mae
|
||||
best_model_info['rmse'], # rmse
|
||||
json.dumps(ml_feature_importance), # feature_importance
|
||||
len(X_train), # training_data_size
|
||||
'system' # created_by
|
||||
))
|
||||
|
||||
# 保存 PLS 模型记录
|
||||
pls_model.equipment_type = equipment_type # 设置装备类型
|
||||
pls_feature_importance = self._get_feature_importance(pls_model)
|
||||
|
||||
cursor.execute("""
|
||||
INSERT INTO trained_models (
|
||||
model_name, model_type, equipment_type, model_path, scaler_path,
|
||||
r2_score, mae, rmse, feature_importance, training_data_size,
|
||||
training_date, is_active, created_by
|
||||
) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, NOW(), TRUE, %s)
|
||||
""", (
|
||||
f"{equipment_type}_{timestamp}_pls", # model_name
|
||||
'pls', # model_type
|
||||
equipment_type, # equipment_type
|
||||
pls_path, # model_path
|
||||
scaler_path, # scaler_path
|
||||
float(pls_metrics['validation']['r2']), # r2_score
|
||||
float(pls_metrics['validation']['mae']), # mae
|
||||
float(pls_metrics['validation']['rmse']), # rmse
|
||||
json.dumps(pls_feature_importance), # feature_importance
|
||||
len(X_train), # training_data_size
|
||||
'system' # created_by
|
||||
))
|
||||
|
||||
conn.commit()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error saving models: {str(e)}")
|
||||
logger.error("Detailed traceback:", exc_info=True)
|
||||
raise
|
||||
|
||||
def load_model(self, equipment_type, model_type='ml'):
|
||||
"""
|
||||
加载已训练的模型
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Loading {model_type} model for {equipment_type}")
|
||||
|
||||
# 从数据库获取激活的模型
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor(dictionary=True)
|
||||
|
||||
# 构建查询语句
|
||||
if model_type == 'pls':
|
||||
query = """
|
||||
SELECT * FROM trained_models
|
||||
WHERE equipment_type = %s
|
||||
AND model_type = 'pls'
|
||||
AND is_active = TRUE
|
||||
LIMIT 1
|
||||
"""
|
||||
params = (equipment_type,)
|
||||
else:
|
||||
query = """
|
||||
SELECT * FROM trained_models
|
||||
WHERE equipment_type = %s
|
||||
AND model_type != 'pls'
|
||||
AND is_active = TRUE
|
||||
LIMIT 1
|
||||
"""
|
||||
params = (equipment_type,)
|
||||
|
||||
# 记录查询信息
|
||||
logger.info(f"Executing query: {query}")
|
||||
logger.info(f"Query params: {params}")
|
||||
|
||||
cursor.execute(query, params)
|
||||
model_record = cursor.fetchone()
|
||||
|
||||
# 记录查询结果
|
||||
if model_record:
|
||||
logger.info(f"Found model record: {model_record}")
|
||||
else:
|
||||
logger.warning(f"No active model found for type {model_type}")
|
||||
return False
|
||||
|
||||
# 检查文件是否存在
|
||||
logger.info(f"Checking model file: {model_record['model_path']}")
|
||||
logger.info(f"Checking scaler file: {model_record['scaler_path']}")
|
||||
|
||||
if not os.path.exists(model_record['model_path']):
|
||||
logger.error(f"Model file not found: {model_record['model_path']}")
|
||||
raise FileNotFoundError(f"Model file not found: {model_record['model_path']}")
|
||||
|
||||
if not os.path.exists(model_record['scaler_path']):
|
||||
logger.error(f"Scaler file not found: {model_record['scaler_path']}")
|
||||
raise FileNotFoundError(f"Scaler file not found: {model_record['scaler_path']}")
|
||||
|
||||
# 加载模型文件
|
||||
logger.info(f"Loading model from {model_record['model_path']}")
|
||||
if model_type == 'pls':
|
||||
self.best_model = joblib.load(model_record['model_path'])
|
||||
logger.info("Loaded PLS model")
|
||||
else:
|
||||
if model_record['model_type'] == 'xgboost':
|
||||
self.best_model = xgb.XGBRegressor()
|
||||
self.best_model.load_model(model_record['model_path'])
|
||||
logger.info("Loaded XGBoost model")
|
||||
else:
|
||||
self.best_model = joblib.load(model_record['model_path'])
|
||||
logger.info(f"Loaded {model_record['model_type']} model")
|
||||
|
||||
# 加载标准化器
|
||||
logger.info(f"Loading scalers from {model_record['scaler_path']}")
|
||||
scalers = joblib.load(model_record['scaler_path'])
|
||||
self.feature_scaler = scalers['feature_scaler']
|
||||
self.target_scaler = scalers['target_scaler']
|
||||
logger.info("Loaded scalers successfully")
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error loading model: {str(e)}")
|
||||
logger.error(f"Detailed traceback:", exc_info=True)
|
||||
return False
|
||||
|
||||
def predict(self, features):
|
||||
"""
|
||||
使用加载的模型进行预测
|
||||
"""
|
||||
try:
|
||||
if not self.best_model:
|
||||
raise ValueError("No model loaded")
|
||||
|
||||
if not self.feature_scaler:
|
||||
raise ValueError("Feature scaler not loaded")
|
||||
|
||||
if not self.target_scaler:
|
||||
raise ValueError("Target scaler not loaded")
|
||||
|
||||
logger.info("Starting prediction")
|
||||
logger.info(f"Input features shape: {features.shape}")
|
||||
logger.info(f"Input features: \n{features}")
|
||||
|
||||
# 处理缺失值
|
||||
features_filled = np.array(features, dtype=float)
|
||||
features_filled[np.isnan(features_filled)] = 0
|
||||
features_filled = np.nan_to_num(features_filled, 0)
|
||||
|
||||
logger.info(f"Filled features: \n{features_filled}")
|
||||
|
||||
# 标准化特征
|
||||
X = self.feature_scaler.transform(features_filled)
|
||||
logger.info(f"Transformed features shape: {X.shape}")
|
||||
logger.info(f"Transformed features: \n{X}")
|
||||
|
||||
# 预测
|
||||
y_pred_scaled = self.best_model.predict(X)
|
||||
logger.info(f"Scaled prediction shape: {y_pred_scaled.shape}")
|
||||
logger.info(f"Scaled prediction: {y_pred_scaled}")
|
||||
|
||||
# <20><>标准化
|
||||
y_pred = self.target_scaler.inverse_transform(y_pred_scaled.reshape(-1, 1))
|
||||
logger.info(f"Final prediction shape: {y_pred.shape}")
|
||||
logger.info(f"Final prediction: {y_pred}")
|
||||
|
||||
# 记录标准化器的参数
|
||||
logger.info("Target scaler params:")
|
||||
logger.info(f"Mean: {self.target_scaler.mean_}")
|
||||
logger.info(f"Scale: {self.target_scaler.scale_}")
|
||||
|
||||
return y_pred.ravel()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in prediction: {str(e)}")
|
||||
raise
|
||||
|
||||
def _get_feature_importance(self, model):
|
||||
"""
|
||||
获取特征重要性
|
||||
"""
|
||||
try:
|
||||
if not model:
|
||||
return {}
|
||||
|
||||
# 获取特征名称
|
||||
feature_analyzer = FeatureAnalysis()
|
||||
feature_names = feature_analyzer.get_equipment_specific_features(self.equipment_type)
|
||||
|
||||
# 获取特<E58F96><E789B9><EFBFBD>重要性
|
||||
if hasattr(model, 'feature_importances_'):
|
||||
importances = model.feature_importances_
|
||||
elif hasattr(model, 'coef_'):
|
||||
if len(model.coef_.shape) > 1: # 如果是二维数组
|
||||
importances = np.abs(model.coef_[0]) # 取第一行
|
||||
else:
|
||||
importances = np.abs(model.coef_)
|
||||
else:
|
||||
return {}
|
||||
|
||||
# 创建特征重要性字典
|
||||
importance_dict = {}
|
||||
for name, importance in zip(feature_names, importances):
|
||||
importance_dict[name] = float(importance) # 确保转换为 Python 标量
|
||||
|
||||
# 按重要性降序排序
|
||||
sorted_dict = dict(sorted(
|
||||
importance_dict.items(),
|
||||
key=lambda x: x[1],
|
||||
reverse=True
|
||||
))
|
||||
|
||||
# 过滤掉重要性为0的特征
|
||||
return {k: v for k, v in sorted_dict.items() if v > 0}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting feature importance: {str(e)}")
|
||||
return {}
|
||||
|
||||
def _calculate_confidence_interval(self, prediction, confidence=0.95):
|
||||
"""
|
||||
计算预测值的置信区间
|
||||
"""
|
||||
try:
|
||||
# 使用预测值的20%作为标准差（增加不确定性）
|
||||
std = abs(prediction) * 0.2
|
||||
|
||||
# 计算置信区间
|
||||
from scipy import stats
|
||||
interval = stats.norm.interval(confidence, loc=prediction, scale=std)
|
||||
|
||||
# 确保区间值为正数且合理
|
||||
lower = max(1000, interval[0]) # 最小值设为1000元
|
||||
upper = max(prediction * 1.2, interval[1]) # 至少比预测值大20%
|
||||
|
||||
logger.info(f"Calculated confidence interval: [{lower:.2f}, {upper:.2f}]")
|
||||
|
||||
return [lower, upper]
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error calculating confidence interval: {str(e)}")
|
||||
# 如果计算失败，返回基于20%的简单区间
|
||||
lower = max(1000, prediction * 0.8)
|
||||
upper = prediction * 1.2
|
||||
return [lower, upper]
|
||||
|
||||
def get_model_type(self):
|
||||
"""
|
||||
获取当前模型的类型
|
||||
"""
|
||||
if isinstance(self.best_model, xgb.XGBRegressor):
|
||||
return 'xgboost'
|
||||
elif isinstance(self.best_model, lgb.LGBMRegressor):
|
||||
return 'lightgbm'
|
||||
elif isinstance(self.best_model, GradientBoostingRegressor):
|
||||
return 'gbm'
|
||||
elif isinstance(self.best_model, RandomForestRegressor):
|
||||
return 'rf'
|
||||
else:
|
||||
return 'unknown'
|
||||
|
||||
def _get_pls_feature_importance(self):
|
||||
"""
|
||||
获取 PLS 模型的特征重要性
|
||||
"""
|
||||
try:
|
||||
if not self.models['pls']:
|
||||
return {}
|
||||
|
||||
# 获取特征名称
|
||||
feature_analyzer = FeatureAnalysis()
|
||||
feature_names = feature_analyzer.get_equipment_specific_features(self.equipment_type)
|
||||
|
||||
# 获取 PLS 模型的系数作为特征重要性
|
||||
pls_model = self.models['pls']
|
||||
if hasattr(pls_model, 'coef_'):
|
||||
# 使用绝对值作为重要性指标
|
||||
importances = np.abs(pls_model.coef_.ravel()) # 使用 ravel() 展平数组
|
||||
else:
|
||||
return {}
|
||||
|
||||
# 创建特征重要性字典
|
||||
importance_dict = {}
|
||||
for name, importance in zip(feature_names, importances):
|
||||
importance_dict[name] = float(importance) # 确保转换为 Python 标量
|
||||
|
||||
# 按重要性降序排序
|
||||
sorted_dict = dict(sorted(
|
||||
importance_dict.items(),
|
||||
key=lambda x: x[1],
|
||||
reverse=True
|
||||
))
|
||||
|
||||
# 过滤掉重要性为0的特征
|
||||
return {k: v for k, v in sorted_dict.items() if v > 0}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting PLS feature importance: {str(e)}")
|
||||
logger.error("Detailed traceback:", exc_info=True)
|
||||
return {}
|
||||
1254
deploy/equipment_cost_system/src/routes.py
Normal file
1254
deploy/equipment_cost_system/src/routes.py
Normal file
File diff suppressed because it is too large
Load Diff
140
deploy/equipment_cost_system/src/schema.sql
Normal file
140
deploy/equipment_cost_system/src/schema.sql
Normal file
@ -0,0 +1,140 @@
|
||||
-- 如果数据库已存在则删除
|
||||
DROP DATABASE IF EXISTS equipment_cost_db;
|
||||
|
||||
-- 创建数据库
|
||||
CREATE DATABASE equipment_cost_db
|
||||
DEFAULT CHARACTER SET utf8mb4
|
||||
COLLATE utf8mb4_unicode_ci;
|
||||
|
||||
-- 使用数据库
|
||||
USE equipment_cost_db;
|
||||
|
||||
-- 装备基本信息表
|
||||
CREATE TABLE equipment (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
name VARCHAR(100), -- 名称
|
||||
type VARCHAR(50), -- 类型（火箭炮/巡飞弹）
|
||||
manufacturer VARCHAR(100), -- 制造商
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 通用参数表
|
||||
CREATE TABLE common_params (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
equipment_id INT,
|
||||
length_m FLOAT, -- 总长(m)
|
||||
width_m FLOAT, -- 宽度(m)
|
||||
height_m FLOAT, -- 高度(m)
|
||||
weight_kg FLOAT, -- 重量(kg)
|
||||
max_range_km FLOAT, -- 最大射程(km)
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 火箭炮特有参数表
|
||||
CREATE TABLE rocket_artillery_params (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
equipment_id INT,
|
||||
firing_angle_horizontal FLOAT, -- 方向射界(度)
|
||||
firing_angle_vertical FLOAT, -- 高低射界(度)
|
||||
rocket_length_m FLOAT, -- 火箭弹长度(m)
|
||||
rocket_diameter_mm FLOAT, -- 弹体直径(mm)
|
||||
rocket_weight_kg FLOAT, -- 火箭弹重量(kg)
|
||||
rate_of_fire FLOAT, -- 射速(发/分钟)
|
||||
combat_weight_kg FLOAT, -- 战斗重量(kg)
|
||||
speed_kmh FLOAT, -- 速度(km/h)
|
||||
min_range_km FLOAT, -- 最小射程(km)
|
||||
mobility_type VARCHAR(50), -- 行走方式
|
||||
structure_layout VARCHAR(100), -- 结构布局
|
||||
engine_model VARCHAR(100), -- 发动机型号
|
||||
engine_params TEXT, -- 发动机参数
|
||||
power_hp FLOAT, -- 功率(hp)
|
||||
travel_range_km FLOAT, -- 行程(km)
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 巡飞弹特有参数表
|
||||
CREATE TABLE loitering_munition_params (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
equipment_id INT,
|
||||
wingspan_m FLOAT, -- 翼展(m)
|
||||
warhead_weight_kg FLOAT, -- 战斗部重量(kg)
|
||||
max_speed_ms FLOAT, -- 最大速度(m/s)
|
||||
cruise_speed_kmh FLOAT, -- 巡航速度(km/h)
|
||||
flight_time_min FLOAT, -- 巡飞时间(min)
|
||||
warhead_type VARCHAR(50), -- 战斗部类型
|
||||
launch_mode VARCHAR(50), -- 发射方式
|
||||
folded_length_mm FLOAT, -- 折叠长度(mm)
|
||||
folded_width_mm FLOAT, -- 折叠宽度(mm)
|
||||
folded_height_mm FLOAT, -- 折叠高度(mm)
|
||||
power_system VARCHAR(100), -- 动力装置
|
||||
guidance_system VARCHAR(100), -- 制导体制
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 成本数据表
|
||||
CREATE TABLE cost_data (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
equipment_id INT,
|
||||
actual_cost DECIMAL(15,2), -- 实际成本(元)
|
||||
predicted_cost DECIMAL(15,2), -- 预测成本(元)
|
||||
prediction_date TIMESTAMP, -- 预测日期
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 特殊参数表
|
||||
CREATE TABLE custom_params (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
equipment_id INT,
|
||||
param_name VARCHAR(100), -- 参数名称
|
||||
param_value VARCHAR(255), -- 参数值
|
||||
param_unit VARCHAR(50), -- 参数单位
|
||||
description TEXT, -- 参数说明
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 添加索引
|
||||
CREATE INDEX idx_equipment_type ON equipment(type);
|
||||
CREATE INDEX idx_equipment_name ON equipment(name);
|
||||
CREATE INDEX idx_cost_data_equipment ON cost_data(equipment_id);
|
||||
|
||||
-- 数据集表
|
||||
CREATE TABLE datasets (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
name VARCHAR(100) NOT NULL, -- 数据集名称
|
||||
description TEXT, -- 数据集描述
|
||||
equipment_type VARCHAR(50) NOT NULL, -- 装备类型
|
||||
purpose VARCHAR(50) NOT NULL, -- 用途(训练/验证)
|
||||
created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
|
||||
);
|
||||
|
||||
-- 数据集-装备关联表
|
||||
CREATE TABLE dataset_equipment (
|
||||
dataset_id INT NOT NULL,
|
||||
equipment_id INT NOT NULL,
|
||||
PRIMARY KEY (dataset_id, equipment_id),
|
||||
FOREIGN KEY (dataset_id) REFERENCES datasets(id),
|
||||
FOREIGN KEY (equipment_id) REFERENCES equipment(id)
|
||||
);
|
||||
|
||||
-- 训练模型表
|
||||
CREATE TABLE trained_models (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
model_name VARCHAR(100) NOT NULL, -- 模型名称
|
||||
model_type VARCHAR(50) NOT NULL, -- 模型类型
|
||||
equipment_type VARCHAR(50) NOT NULL, -- 装备类型
|
||||
model_path VARCHAR(255) NOT NULL, -- 模型文件路径
|
||||
scaler_path VARCHAR(255) NOT NULL, -- 标准化器路径
|
||||
r2_score FLOAT, -- R²分数
|
||||
mae FLOAT, -- 平均绝对误差
|
||||
rmse FLOAT, -- 均方根误差
|
||||
feature_importance JSON, -- 特征重要性
|
||||
training_data_size INT, -- 训练数据量
|
||||
training_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP, -- 训练时间
|
||||
is_active BOOLEAN DEFAULT FALSE, -- 是否为当前激活模型
|
||||
created_by VARCHAR(50) -- 创建者
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
|
||||
-- 添加索引
|
||||
CREATE INDEX idx_model_equipment_type ON trained_models(equipment_type);
|
||||
CREATE INDEX idx_model_active ON trained_models(is_active);
|
||||
191
deploy/equipment_cost_system/src/test_api.py
Normal file
191
deploy/equipment_cost_system/src/test_api.py
Normal file
@ -0,0 +1,191 @@
|
||||
import requests
|
||||
import json
|
||||
import logging
|
||||
from datetime import datetime
|
||||
import os
|
||||
import sys
|
||||
|
||||
# 添加项目根目录到 Python 路径
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
project_root = os.path.dirname(current_dir)
|
||||
if project_root not in sys.path:
|
||||
sys.path.insert(0, project_root)
|
||||
|
||||
# 配置基本日志
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
|
||||
handlers=[
|
||||
logging.FileHandler('logs/test_api.log'),
|
||||
logging.StreamHandler()
|
||||
]
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def test_api_endpoints():
|
||||
"""
|
||||
测试 API 各个端点
|
||||
"""
|
||||
base_url = 'http://localhost:5001/api'
|
||||
|
||||
try:
|
||||
# 1. 测试根路由
|
||||
logger.info("\n1. 测试 API 根路由")
|
||||
response = requests.get(f'{base_url}/')
|
||||
print_response(response, "API 根路由")
|
||||
|
||||
# 2. 测试机器学习预测接口
|
||||
logger.info("\n2. 测试机器学习预测接口")
|
||||
predict_data = {
|
||||
"type": "巡飞弹",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"folded_length_mm": 1300,
|
||||
"folded_width_mm": 230,
|
||||
"folded_height_mm": 230,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "凭自身动力起飞"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "机器学习预测")
|
||||
|
||||
# 3. 测试 PLS 预测接口
|
||||
logger.info("\n3. 测试 PLS 预测接口")
|
||||
response = requests.post(
|
||||
f'{base_url}/pls/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "PLS 预测")
|
||||
|
||||
# 4. 测试特征分析接口
|
||||
logger.info("\n4. 测试特征分析接口")
|
||||
analysis_data = {
|
||||
"dataset_id": 1, # 假设数据集 ID 为 1
|
||||
"equipment_type": "巡飞弹"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/analyze-features',
|
||||
json=analysis_data
|
||||
)
|
||||
print_response(response, "特征分析")
|
||||
|
||||
# 5. 测试机器学习模型训练接口
|
||||
logger.info("\n5. 测试机器学习模型训练接口")
|
||||
training_data = {
|
||||
"type": "巡飞弹",
|
||||
"train_dataset_id": 1, # 训练数据集 ID
|
||||
"validation_dataset_id": 2, # 验证数据集 ID
|
||||
"models": ["xgboost", "lightgbm", "rf"] # 要训练的模型类型
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/train',
|
||||
json=training_data
|
||||
)
|
||||
print_response(response, "模型训练")
|
||||
|
||||
# 6. 测试数据集相关接口
|
||||
logger.info("\n6. 测试数据集相关接口")
|
||||
|
||||
# 6.1 获取数据集列表
|
||||
response = requests.get(f'{base_url}/datasets')
|
||||
print_response(response, "获取数据集列表")
|
||||
|
||||
# 6.2 获取可用的装备列表
|
||||
response = requests.get(f'{base_url}/data')
|
||||
equipment_data = response.json()
|
||||
|
||||
# 获取巡飞弹类型的装备ID
|
||||
available_equipment_ids = []
|
||||
if 'loitering_munition' in equipment_data:
|
||||
available_equipment_ids = [
|
||||
item['id']
|
||||
for item in equipment_data['loitering_munition']
|
||||
if item['id'] is not None
|
||||
][:3] # 取前3个可用的ID
|
||||
|
||||
if not available_equipment_ids:
|
||||
logger.warning("没有找到可用的装备ID，跳过创建数据集测试")
|
||||
else:
|
||||
# 6.3 创建新数据集
|
||||
new_dataset = {
|
||||
"name": "测试数据集",
|
||||
"description": "用于测试的数据集",
|
||||
"equipment_type": "巡飞弹",
|
||||
"purpose": "训练",
|
||||
"equipment_ids": available_equipment_ids
|
||||
}
|
||||
|
||||
logger.info(f"创建数据集使用的装备IDs: {available_equipment_ids}")
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/datasets',
|
||||
json=new_dataset
|
||||
)
|
||||
print_response(response, "创建数据集")
|
||||
|
||||
# 7. 测试模型相关接口
|
||||
logger.info("\n7. 测试模型相关接口")
|
||||
|
||||
# 7.1 获取模型列表
|
||||
response = requests.get(f'{base_url}/models')
|
||||
print_response(response, "获取模型列表")
|
||||
|
||||
# 7.2 获取最新模型
|
||||
response = requests.get(f'{base_url}/models/巡飞弹/latest')
|
||||
print_response(response, "获取最新模型")
|
||||
|
||||
# 8. 测试多模型预测接口
|
||||
logger.info("\n8. 测试多模型预测接口")
|
||||
response = requests.post(
|
||||
f'{base_url}/predict/all',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "多模型预测")
|
||||
|
||||
logger.info("所有测试完成")
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"API 请求错误: {str(e)}")
|
||||
except Exception as e:
|
||||
logger.error(f"测试过程中出现错误: {str(e)}")
|
||||
|
||||
def print_response(response, endpoint_name):
|
||||
"""
|
||||
打印响应结果
|
||||
"""
|
||||
try:
|
||||
logger.info(f"\n=== {endpoint_name} 测试结果 ===")
|
||||
logger.info(f"状态码: {response.status_code}")
|
||||
|
||||
if response.status_code == 200:
|
||||
result = response.json()
|
||||
logger.info(f"响应数据:\n{json.dumps(result, indent=2, ensure_ascii=False)}")
|
||||
else:
|
||||
logger.error(f"错误响应:\n{response.text}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理响应时出错: {str(e)}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
# 确保日志目录存在
|
||||
os.makedirs('logs', exist_ok=True)
|
||||
|
||||
logger.info(f"=== API 测试开始 - {datetime.now()} ===")
|
||||
test_api_endpoints()
|
||||
logger.info(f"=== API 测试结束 - {datetime.now()} ===")
|
||||
except Exception as e:
|
||||
logger.error(f"测试执行失败: {str(e)}")
|
||||
0
deploy/equipment_cost_system/venv
Normal file
0
deploy/equipment_cost_system/venv
Normal file
34
deploy/setup.md
Normal file
34
deploy/setup.md
Normal file
@ -0,0 +1,34 @@
|
||||
# 安装说明
|
||||
|
||||
## 1. 系统要求
|
||||
|
||||
- Linux 服务器 (推荐 Ubuntu 20.04+)
|
||||
- Python 3.8+
|
||||
- MySQL 8.0+
|
||||
|
||||
## 2. 安装部署
|
||||
|
||||
```bash
|
||||
# 解压部署包
|
||||
tar -xzf equipment_cost_prediction.tar.gz
|
||||
cd equipment_cost_prediction
|
||||
|
||||
# 运行安装脚本
|
||||
bash scripts/install.sh
|
||||
|
||||
# 修改配置文件
|
||||
vim config/.env
|
||||
|
||||
# 启动服务
|
||||
bash scripts/start.sh
|
||||
```
|
||||
|
||||
## 3. 验证部署
|
||||
|
||||
```bash
|
||||
# 检查服务状态
|
||||
curl http://localhost:5001/api/
|
||||
|
||||
# 检查日志
|
||||
tail -f logs/api.log
|
||||
```
|
||||
663
docs/deploy/api.md
Normal file
663
docs/deploy/api.md
Normal file
@ -0,0 +1,663 @@
|
||||
# 装备成本估算系统 API 文档
|
||||
|
||||
这个 API 文档提供了完整的接口说明，包括：
|
||||
|
||||
- 每个端点的详细描述
|
||||
- 请求和响应的具体示例
|
||||
- 清晰的参数格式要求
|
||||
- 统一的错误处理说明
|
||||
- 重要的注意事项
|
||||
|
||||
文档使用 Markdown 格式编写，请使用支持 Markdown 的工具查看。
|
||||
|
||||
## 基本信息
|
||||
|
||||
- 基础URL: `http://localhost:5001/api`
|
||||
- 版本: 1.0.0
|
||||
- 响应格式: JSON
|
||||
|
||||
## API 端点列表
|
||||
|
||||
### 1. 获取 API 信息
|
||||
|
||||
获取 API 版本信息和可用端点列表。
|
||||
|
||||
- **URL**: `/`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
json
|
||||
{
|
||||
"name": "装备成本估算系统 API",
|
||||
"version": "1.0.0",
|
||||
"endpoints": {
|
||||
"predict": {
|
||||
"url": "/api/predict",
|
||||
"method": "POST",
|
||||
"description": "成本预测"
|
||||
},
|
||||
"analyze-features": {
|
||||
"url": "/api/analyze-features",
|
||||
"method": "POST",
|
||||
"description": "特征分析"
|
||||
},
|
||||
"train": {
|
||||
"url": "/api/train",
|
||||
"method": "POST",
|
||||
"description": "模型训练"
|
||||
},
|
||||
"evaluate": {
|
||||
"url": "/api/evaluate",
|
||||
"method": "POST",
|
||||
"description": "模型评估"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
### 2. 单模型预测
|
||||
|
||||
使用当前激活的最优模型进行成本预测。
|
||||
|
||||
- **URL**: `/predict`
|
||||
- **方法**: `POST`
|
||||
- **请求体示例** (巡飞弹):
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "巡飞弹",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"folded_length_mm": 1300,
|
||||
"folded_width_mm": 230,
|
||||
"folded_height_mm": 230,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "凭自身动力起飞"
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"predicted_cost": 150000.0,
|
||||
"model_info": {
|
||||
"type": "xgboost",
|
||||
"name": "巡飞弹_20241111_model",
|
||||
"r2_score": 0.95,
|
||||
"mae": 5000.0,
|
||||
"rmse": 7500.0
|
||||
},
|
||||
"confidence_interval": {
|
||||
"lower": 135000.0,
|
||||
"upper": 165000.0
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 3. PLS 模型预测
|
||||
|
||||
使用 PLS 回归模型进行预测。
|
||||
|
||||
- **URL**: `/pls/predict`
|
||||
- **方法**: `POST`
|
||||
- **请求体**: 与单模型预测相同
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"predicted_cost": 148000.0,
|
||||
"confidence_interval": {
|
||||
"lower": 133000.0,
|
||||
"upper": 163000.0
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 4. 多模型预测
|
||||
|
||||
使用所有激活的模型进行预测并返回综合结果。
|
||||
|
||||
- **URL**: `/predict/all`
|
||||
- **方法**: `POST`
|
||||
- **请求体**: 与单模型预测相同
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"individual_predictions": {
|
||||
"xgboost": {
|
||||
"predicted_cost": 150000.0,
|
||||
"model_info": {
|
||||
"name": "巡飞弹_xgboost_model",
|
||||
"type": "xgboost",
|
||||
"r2_score": 0.95,
|
||||
"mae": 5000.0,
|
||||
"rmse": 7500.0
|
||||
},
|
||||
"confidence_interval": {
|
||||
"lower": 135000.0,
|
||||
"upper": 165000.0
|
||||
}
|
||||
},
|
||||
"pls": {
|
||||
"predicted_cost": 148000.0,
|
||||
"model_info": {
|
||||
"name": "巡飞弹_pls_model",
|
||||
"type": "pls",
|
||||
"r2_score": 0.92,
|
||||
"mae": 5500.0,
|
||||
"rmse": 8000.0
|
||||
},
|
||||
"confidence_interval": {
|
||||
"lower": 133000.0,
|
||||
"upper": 163000.0
|
||||
}
|
||||
}
|
||||
},
|
||||
"ensemble_prediction": {
|
||||
"predicted_cost": 149000.0,
|
||||
"standard_deviation": 1414.21,
|
||||
"confidence_interval": {
|
||||
"lower": 146228.15,
|
||||
"upper": 151771.85
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 5. 特征分析
|
||||
|
||||
分析数据集中特征的重要性和相关性。
|
||||
|
||||
- **URL**: `/analyze-features`
|
||||
- **方法**: `POST`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"dataset_id": 1,
|
||||
"equipment_type": "巡飞弹"
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"important_features": [
|
||||
{
|
||||
"name": "最大射程(km)",
|
||||
"importance": 0.35
|
||||
},
|
||||
{
|
||||
"name": "重量(kg)",
|
||||
"importance": 0.25
|
||||
}
|
||||
],
|
||||
"correlation_analysis": {
|
||||
"features": ["最大射程(km)", "重量(kg)"],
|
||||
"matrix": [[1.0, 0.8], [0.8, 1.0]]
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 6. 模型训练
|
||||
|
||||
训练新的模型。
|
||||
|
||||
- **URL**: `/train`
|
||||
- **方法**: `POST`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"type": "巡飞弹",
|
||||
"train_dataset_id": 1,
|
||||
"validation_dataset_id": 2,
|
||||
"models": ["xgboost", "lightgbm", "rf"]
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"metrics": {
|
||||
"xgboost": {
|
||||
"train": {
|
||||
"r2": 0.95,
|
||||
"mae": 5000.0,
|
||||
"rmse": 7500.0
|
||||
},
|
||||
"validation": {
|
||||
"r2": 0.92,
|
||||
"mae": 5500.0,
|
||||
"rmse": 8000.0
|
||||
}
|
||||
}
|
||||
},
|
||||
"best_model": {
|
||||
"type": "xgboost",
|
||||
"r2": 0.92,
|
||||
"mae": 5500.0,
|
||||
"rmse": 8000.0
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 7. 数据集管理
|
||||
|
||||
#### 7.1 获取数据集列表
|
||||
|
||||
- **URL**: `/datasets`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
[
|
||||
{
|
||||
"id": 1,
|
||||
"name": "训练数据集",
|
||||
"description": "用于训练的数据集",
|
||||
"equipment_type": "巡飞弹",
|
||||
"equipment_count": 10,
|
||||
"equipment_names": ["设备1", "设备2"],
|
||||
"purpose": "训练",
|
||||
"created_at": "2024-11-11T10:00:00"
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
#### 7.2 获取数据集详情
|
||||
|
||||
- **URL**: `/datasets/{id}`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": 1,
|
||||
"name": "训练数据集",
|
||||
"description": "用于训练的数据集",
|
||||
"equipment_type": "巡飞弹",
|
||||
"purpose": "训练",
|
||||
"created_at": "2024-11-11T10:00:00",
|
||||
"equipment": [
|
||||
{
|
||||
"id": 1,
|
||||
"name": "设备1",
|
||||
"type": "巡飞弹",
|
||||
"manufacturer": "制造商1",
|
||||
"actual_cost": 150000
|
||||
}
|
||||
],
|
||||
"statistics": {
|
||||
"equipment_count": 10,
|
||||
"total_cost": 1500000,
|
||||
"average_cost": 150000
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
#### 7.3 创建数据集
|
||||
|
||||
- **URL**: `/datasets`
|
||||
- **方法**: `POST`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "测试数据集",
|
||||
"description": "用于测试的数据集",
|
||||
"equipment_type": "巡飞弹",
|
||||
"purpose": "训练",
|
||||
"equipment_ids": [1, 2, 3]
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": 2,
|
||||
"message": "数据集创建成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 7.4 更新数据集
|
||||
|
||||
- **URL**: `/datasets/{id}`
|
||||
- **方法**: `PUT`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "更新后的数据集名称",
|
||||
"description": "更新后的描述",
|
||||
"equipment_type": "巡飞弹",
|
||||
"purpose": "验证",
|
||||
"equipment_ids": [1, 2, 3, 4]
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "数据集更新成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 7.5 删除数据集
|
||||
|
||||
- **URL**: `/datasets/{id}`
|
||||
- **方法**: `DELETE`
|
||||
- **描述**: 删除指定的数据集及其关联关系
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "数据集删除成功"
|
||||
}
|
||||
```
|
||||
|
||||
注意事项：
|
||||
|
||||
1. 数据集删除后不会删除关联的装备数据
|
||||
2. 不能删除正在被模型使用的数据集
|
||||
3. 更新数据集时会重新计算统计信息
|
||||
4. 数据集的装备类型一旦创建后不能更改
|
||||
|
||||
### 8. 模型管理
|
||||
|
||||
#### 8.1 获取模型列表
|
||||
|
||||
- **URL**: `/models`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
[
|
||||
{
|
||||
"id": 1,
|
||||
"model_name": "巡飞弹_xgboost_model",
|
||||
"model_type": "xgboost",
|
||||
"equipment_type": "巡飞弹",
|
||||
"r2_score": 0.95,
|
||||
"mae": 5000.0,
|
||||
"rmse": 7500.0,
|
||||
"is_active": true,
|
||||
"training_date": "2024-11-11T10:00:00"
|
||||
}
|
||||
]
|
||||
```
|
||||
|
||||
#### 8.2 获取最新模型
|
||||
|
||||
- **URL**: `/models/{equipment_type}/latest`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**: 与模型列表的单个模型格式相同
|
||||
|
||||
#### 8.3 获取模型详情
|
||||
|
||||
- **URL**: `/models/{id}`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": 1,
|
||||
"model_name": "巡飞弹_xgboost_model",
|
||||
"model_type": "xgboost",
|
||||
"equipment_type": "巡飞弹",
|
||||
"r2_score": 0.95,
|
||||
"mae": 5000.0,
|
||||
"rmse": 7500.0,
|
||||
"is_active": true,
|
||||
"training_date": "2024-11-11T10:00:00",
|
||||
"feature_importance": {
|
||||
"max_range_km": 0.35,
|
||||
"weight_kg": 0.25,
|
||||
"length_m": 0.20
|
||||
},
|
||||
"training_data_size": 100,
|
||||
"created_by": "system"
|
||||
}
|
||||
```
|
||||
|
||||
#### 8.4 激活模型
|
||||
|
||||
- **URL**: `/models/{id}/activate`
|
||||
- **方法**: `POST`
|
||||
- **描述**: 激活指定模型，同时会将同类型的其他模型设置为非激活状态
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "模型已激活"
|
||||
}
|
||||
```
|
||||
|
||||
#### 8.5 删除模型
|
||||
|
||||
- **URL**: `/models/{id}`
|
||||
- **方法**: `DELETE`
|
||||
- **描述**: 删除指定模型，包括模型文件和数据库记录
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "模型已删除"
|
||||
}
|
||||
```
|
||||
|
||||
注意事项：
|
||||
|
||||
1. 删除模型时会同时删除相关的文件和数据库记录
|
||||
2. 不能删除当前正在使用（已激活）的模型
|
||||
3. 激活模型时会自动取消同类型其他模型的激活状态
|
||||
4. 模型详情包含了更多的训练相关信息，如特征重要性等
|
||||
|
||||
### 9. 数据管理
|
||||
|
||||
#### 9.1 获取装备数据列表
|
||||
|
||||
- **URL**: `/data`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"rocket_artillery": [
|
||||
{
|
||||
"id": 1,
|
||||
"name": "BM-21",
|
||||
"type": "火箭炮",
|
||||
"manufacturer": "俄罗斯",
|
||||
"length_m": 7.35,
|
||||
"width_m": 2.4,
|
||||
"height_m": 3.1,
|
||||
"weight_kg": 13700,
|
||||
"max_range_km": 20.4,
|
||||
"actual_cost": 800000
|
||||
}
|
||||
],
|
||||
"loitering_munition": [
|
||||
{
|
||||
"id": 8,
|
||||
"name": "Hero-120",
|
||||
"type": "巡飞弹",
|
||||
"manufacturer": "以色列",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"actual_cost": 150000
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.2 获取装备详情
|
||||
|
||||
- **URL**: `/data/details/{id}`
|
||||
- **方法**: `GET`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"id": 8,
|
||||
"name": "Hero-120",
|
||||
"type": "巡飞弹",
|
||||
"manufacturer": "以色列",
|
||||
"common_params": {
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40
|
||||
},
|
||||
"specific_params": {
|
||||
"wingspan_m": 2.1,
|
||||
"warhead_weight_kg": 3.5,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "箱式发射",
|
||||
"power_system": "电动机",
|
||||
"guidance_system": "GPS/INS"
|
||||
},
|
||||
"cost_data": {
|
||||
"actual_cost": 150000,
|
||||
"prediction_date": "2024-11-11T10:00:00",
|
||||
"predicted_cost": 148000
|
||||
},
|
||||
"custom_params": [
|
||||
{
|
||||
"id": 1,
|
||||
"param_name": "续航时间",
|
||||
"param_value": "2小时",
|
||||
"param_unit": "小时",
|
||||
"description": "最大续航时间"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.3 更新装备数据
|
||||
|
||||
- **URL**: `/data/{id}`
|
||||
- **方法**: `PUT`
|
||||
- **请求体示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"name": "Hero-120",
|
||||
"manufacturer": "以色列",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"wingspan_m": 2.1,
|
||||
"warhead_weight_kg": 3.5,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"actual_cost": 150000,
|
||||
"custom_params": [
|
||||
{
|
||||
"id": 1,
|
||||
"param_value": "2.5小时"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "装备数据更新成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.4 删除装备数据
|
||||
|
||||
- **URL**: `/data/{id}`
|
||||
- **方法**: `DELETE`
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "装备数据删除成功"
|
||||
}
|
||||
```
|
||||
|
||||
#### 9.5 下载数据模板
|
||||
|
||||
- **URL**: `/data/template`
|
||||
- **方法**: `GET`
|
||||
- **描述**: 下载Excel格式的数据导入模板
|
||||
- **响应**: Excel文件下载
|
||||
|
||||
#### 9.6 导入数据
|
||||
|
||||
- **URL**: `/data/import`
|
||||
- **方法**: `POST`
|
||||
- **请求体**:
|
||||
- Content-Type: multipart/form-data
|
||||
- 参数名: file
|
||||
- 文件类型: .xlsx 或 .xls
|
||||
- **响应示例**:
|
||||
|
||||
```json
|
||||
{
|
||||
"success": true,
|
||||
"message": "数据导入成功",
|
||||
"imported_count": {
|
||||
"rocket_artillery": 3,
|
||||
"loitering_munition": 5
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
注意事项：
|
||||
|
||||
1. 导入数据时必须使用系统提供的模板
|
||||
2. 更新装备数据时会同时更新关联的参数表
|
||||
3. 删除装备数据会同时删除相关的参数和成本数据
|
||||
4. 导入的Excel文件大小不应超过10MB
|
||||
5. 所有数值字段必须符合指定的单位和范围要求
|
||||
6. 特殊参数的值必须包含单位信息
|
||||
|
||||
## 错误响应
|
||||
|
||||
所有接口在发生错误时都会返回以下格式的响应：
|
||||
|
||||
```json
|
||||
{
|
||||
"error": "错误描述信息"
|
||||
}
|
||||
```
|
||||
|
||||
## 注意事项
|
||||
|
||||
1. 所有数值参数必须大于0
|
||||
2. 所有单位必须按照参数名称中指定的单位提供
|
||||
3. 预测结果中的成本单位为元
|
||||
4. 置信区间表示预测结果的95%置信水平范围
|
||||
5. 所有请求和响应的编码均为 UTF-8
|
||||
120
docs/deploy/deploy.md
Normal file
120
docs/deploy/deploy.md
Normal file
@ -0,0 +1,120 @@
|
||||
# 装备成本估算系统部署指南
|
||||
|
||||
## 一、系统要求
|
||||
|
||||
### 1. 基础软件
|
||||
|
||||
- Linux 操作系统 (推荐 Ubuntu 20.04+)
|
||||
- Python 3.8+ 及相关组件
|
||||
|
||||
```bash
|
||||
sudo apt update
|
||||
sudo apt install python3 python3-pip python3-venv
|
||||
sudo apt install python3-dev build-essential
|
||||
```
|
||||
|
||||
- Node.js 14+ 及 npm
|
||||
|
||||
```bash
|
||||
# 使用 nvm 安装 Node.js
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
|
||||
source ~/.bashrc
|
||||
nvm install 14
|
||||
nvm use 14
|
||||
```
|
||||
|
||||
### 2. 数据库
|
||||
|
||||
- MySQL 8.0+
|
||||
|
||||
```bash
|
||||
sudo apt install mysql-server mysql-client
|
||||
sudo apt install libmysqlclient-dev
|
||||
```
|
||||
|
||||
### 3. Python包依赖
|
||||
|
||||
```bash
|
||||
# 科学计算相关
|
||||
sudo apt install libatlas-base-dev # numpy依赖
|
||||
sudo apt install libopenblas-dev # 线性代数库
|
||||
sudo apt install liblapack-dev # 线性代数包
|
||||
sudo apt install gfortran # Fortran编译器(scipy依赖)
|
||||
|
||||
# XML处理相关(用于Excel文件处理)
|
||||
sudo apt install libxml2-dev
|
||||
sudo apt install libxslt1-dev
|
||||
```
|
||||
|
||||
## 二、部署运行
|
||||
|
||||
### 1. 安装服务
|
||||
|
||||
```bash
|
||||
sh scripts/install.sh
|
||||
```
|
||||
|
||||
### 2. 启动服务
|
||||
|
||||
```bash
|
||||
sh scripts/start.sh
|
||||
```
|
||||
|
||||
### 3. 停止服务
|
||||
|
||||
```bash
|
||||
sh scripts/stop.sh
|
||||
```
|
||||
|
||||
## 三、维护说明
|
||||
|
||||
### 1. 日志管理
|
||||
|
||||
```bash
|
||||
# 后端日志
|
||||
tail -f logs/api.log
|
||||
|
||||
# 数据库日志
|
||||
tail -f /var/log/mysql/error.log
|
||||
```
|
||||
|
||||
## 四、安全建议
|
||||
|
||||
1. 系统安全
|
||||
- 使用防火墙限制端口访问
|
||||
- 定期更新系统和依赖包
|
||||
|
||||
2. 数据安全
|
||||
- 定期备份数据库
|
||||
- 加密敏感信息
|
||||
- 限制数据库远程访问
|
||||
|
||||
3. 访问控制
|
||||
- 使用强密码
|
||||
- 配置适当的文件权限
|
||||
- 使用非root用户运行服务
|
||||
|
||||
## 五、监控方案
|
||||
|
||||
### 1. 系统监控
|
||||
|
||||
```bash
|
||||
# 资源使用
|
||||
top -b -n 1
|
||||
df -h
|
||||
free -m
|
||||
|
||||
# 服务状态
|
||||
ps aux | grep gunicorn
|
||||
ps aux | grep node
|
||||
```
|
||||
|
||||
### 2. 应用监控
|
||||
|
||||
```bash
|
||||
# API 响应时间
|
||||
curl -w "@curl-format.txt" -o /dev/null -s "http://localhost:5001/api/"
|
||||
|
||||
# 错误日志
|
||||
grep "ERROR" logs/api.log
|
||||
```
|
||||
250
docs/dev/deployment.md
Normal file
250
docs/dev/deployment.md
Normal file
@ -0,0 +1,250 @@
|
||||
# 装备成本估算系统部署指南
|
||||
|
||||
## 一、系统打包
|
||||
|
||||
### 1. 创建部署包结构
|
||||
|
||||
```bash
|
||||
mkdir -p deploy/equipment_cost_system/{backend,frontend,docs}
|
||||
```
|
||||
|
||||
### 2. 准备部署文件
|
||||
|
||||
#### 2.1 后端文件
|
||||
|
||||
```bash
|
||||
cd deploy/equipment_cost_system/backend
|
||||
mkdir -p {src,scripts,config,data,logs,models}
|
||||
cp -r ../../../src/* src/
|
||||
cp ../../../requirements.txt ./
|
||||
cp ../../../.env.example config/.env.template
|
||||
```
|
||||
|
||||
#### 2.2 前端文件
|
||||
|
||||
```bash
|
||||
cd ../frontend
|
||||
mkdir -p {src,public,dist}
|
||||
cp -r ../../frontend/src/* src/
|
||||
cp -r ../../frontend/public/* public/
|
||||
cp ../../../frontend/package.json ./
|
||||
cp ../../../frontend/vite.config.js ./
|
||||
cp ../../../frontend/.env.production ./
|
||||
```
|
||||
|
||||
#### 2.3 复制文档
|
||||
|
||||
```bash
|
||||
cd ../docs
|
||||
cp -r ../../docs/deploy/* ./
|
||||
```
|
||||
|
||||
#### 2.4 创建部署脚本
|
||||
|
||||
```bash
|
||||
touch scripts/{install.sh,start.sh,stop.sh}
|
||||
```
|
||||
|
||||
### 3. 部署脚本内容
|
||||
|
||||
#### 3.1 安装脚本 (install.sh)
|
||||
|
||||
```bash
|
||||
#!/bin/bash
|
||||
|
||||
# 安装 Python 依赖
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate
|
||||
pip install -r requirements.txt
|
||||
|
||||
# 创建必要的目录
|
||||
mkdir -p logs
|
||||
mkdir -p data
|
||||
mkdir -p models
|
||||
|
||||
# 配置文件
|
||||
if [ ! -f config/.env ]; then
|
||||
cp config/.env.template config/.env
|
||||
echo "请修改 config/.env 中的配置"
|
||||
fi
|
||||
|
||||
# 初始化数据库
|
||||
read -p "请输入MySQL root密码: " mysqlpass
|
||||
mysql -u root -p$mysqlpass < src/schema.sql
|
||||
|
||||
# 设置权限
|
||||
chmod +x scripts/*.sh
|
||||
```
|
||||
|
||||
#### 3.2 启动脚本 (start.sh)
|
||||
|
||||
```bash
|
||||
#!/bin/bash
|
||||
|
||||
# 激活虚拟环境
|
||||
source venv/bin/activate
|
||||
|
||||
# 检查配置文件
|
||||
if [ ! -f config/.env ]; then
|
||||
echo "错误: 配置文件不存在"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
# 启动服务
|
||||
export $(cat config/.env | xargs)
|
||||
gunicorn -w 4 -b 0.0.0.0:5001 "src.app:create_app()" --daemon
|
||||
|
||||
echo "服务已启动，访问 http://localhost:5001"
|
||||
```
|
||||
|
||||
#### 3.3 停止脚本 (stop.sh)
|
||||
|
||||
```bash
|
||||
#!/bin/bash
|
||||
|
||||
# 查找并停止 gunicorn 进程
|
||||
pkill -f gunicorn
|
||||
|
||||
echo "服务已停止"
|
||||
```
|
||||
|
||||
### 4. 创建部署包
|
||||
|
||||
```bash
|
||||
cd ..
|
||||
tar -czf equipment_cost_system.tar.gz equipment_cost_system/
|
||||
```
|
||||
|
||||
## 二、部署步骤
|
||||
|
||||
### 1. 系统要求
|
||||
|
||||
- Linux 服务器 (推荐 Ubuntu 20.04+)
|
||||
- Python 3.8+
|
||||
- MySQL 8.0+
|
||||
|
||||
### 2. 安装部署
|
||||
|
||||
```bash
|
||||
# 解压部署包
|
||||
tar -xzf equipment_cost_system.tar.gz
|
||||
cd equipment_cost_system
|
||||
|
||||
# 运行安装脚本
|
||||
bash scripts/install.sh
|
||||
|
||||
# 修改配置文件
|
||||
vim config/.env
|
||||
|
||||
# 启动服务
|
||||
bash scripts/start.sh
|
||||
```
|
||||
|
||||
### 3. 验证部署
|
||||
|
||||
```bash
|
||||
# 检查服务状态
|
||||
curl http://localhost:5001/api/
|
||||
|
||||
# 检查日志
|
||||
tail -f logs/api.log
|
||||
```
|
||||
|
||||
## 三、维护说明
|
||||
|
||||
### 1. 日常维护
|
||||
|
||||
```bash
|
||||
# 查看日志
|
||||
tail -f logs/api.log
|
||||
|
||||
# 备份数据库
|
||||
mysqldump -u root -p equipment_cost_db > backup/$(date +%Y%m%d).sql
|
||||
|
||||
# 清理旧日志
|
||||
find logs/ -name "*.log" -mtime +30 -delete
|
||||
```
|
||||
|
||||
### 2. 更新部署
|
||||
|
||||
```bash
|
||||
# 停止服务
|
||||
bash scripts/stop.sh
|
||||
|
||||
# 备份数据
|
||||
cp -r data data_backup_$(date +%Y%m%d)
|
||||
|
||||
# 更新代码
|
||||
# ... 更新相关文件 ...
|
||||
|
||||
# 重启服务
|
||||
bash scripts/start.sh
|
||||
```
|
||||
|
||||
### 3. 故障处理
|
||||
|
||||
```bash
|
||||
# 检查服务状态
|
||||
ps aux | grep gunicorn
|
||||
|
||||
# 检查数据库连接
|
||||
mysql -u root -p -e "show databases;"
|
||||
|
||||
# 重启服务
|
||||
bash scripts/stop.sh
|
||||
bash scripts/start.sh
|
||||
```
|
||||
|
||||
## 四、安全建议
|
||||
|
||||
1. 文件权限设置
|
||||
|
||||
```bash
|
||||
# 设置适当的文件权限
|
||||
chmod 755 scripts/*.sh
|
||||
chmod 600 config/.env
|
||||
chmod 700 logs models data
|
||||
```
|
||||
|
||||
2. 数据库安全
|
||||
|
||||
- 使用强密码
|
||||
- 限制数据库访问IP
|
||||
- 定期备份数据
|
||||
|
||||
3. 服务器配置
|
||||
|
||||
- 配置防火墙规则
|
||||
- 启用 SSL/TLS
|
||||
- 定期更新系统
|
||||
|
||||
## 五、监控方案
|
||||
|
||||
### 1. 系统监控
|
||||
|
||||
```bash
|
||||
# 检查CPU和内存使用
|
||||
top -b -n 1
|
||||
|
||||
# 检查磁盘使用
|
||||
df -h
|
||||
|
||||
# 检查网络连接
|
||||
netstat -tunlp
|
||||
```
|
||||
|
||||
### 2. 应用监控
|
||||
|
||||
```bash
|
||||
# 检查API响应时间
|
||||
curl -w "@curl-format.txt" -o /dev/null -s "http://localhost:5001/api/"
|
||||
|
||||
# 检查错误日志
|
||||
grep "ERROR" logs/api.log
|
||||
```
|
||||
|
||||
### 3. 告警设置
|
||||
|
||||
- 配置日志告警
|
||||
- 设置资源使用阈值告警
|
||||
- 配置服务可用性监控
|
||||
@ -16,11 +16,11 @@
|
||||
（2）线性相关分析：对于特征和标签皆为连续值的回归问题，要检测二者的相关性，最直接的做法就是求相关系数rxy，本质是建立协方差矩阵，分析数据和成本之间相关关系的类型和程度，筛选出影响特征
|
||||
（3）互信息 (mutual information)： 用于特征选择，可以从两个角度进行解释：(1)、基于 KL 散度和 (2)、基于信息增益。
|
||||
2. 数据一致性分析：对特征数据分层分组，计算组内一致性,目标是选择比较合适的一组数据，以此产生一个进行成本估算和分析的虚拟量.大部分的研究中报告的三个数据：rwg、ICC(1)、ICC(2)，要符合3个条件，rwg>0.7、ICC(1)>0.05、ICC(2)>0.5
|
||||
RWG值：打分一致性；
|
||||
ICC1：组内一致性；
|
||||
ICC2：组间一致性。
|
||||
RWG值：打分一致性；
|
||||
ICC1：组内一致性；
|
||||
ICC2：组间一致性。
|
||||
3. 回归模型：偏最小二乘回归(partial Least Squares，PLS)
|
||||
4. 神经网络模型：采用 BP 网络
|
||||
4. 神经网络模型：采用适用的神经网络模型
|
||||
|
||||
### 数据准备
|
||||
|
||||
164
docs/dev/run.md
Normal file
164
docs/dev/run.md
Normal file
@ -0,0 +1,164 @@
|
||||
# 装备成本估算系统运行说明
|
||||
|
||||
## 一、开发环境配置
|
||||
|
||||
### 1. 系统要求
|
||||
|
||||
- Linux/macOS/Windows
|
||||
- Python 3.8+
|
||||
- MySQL 8.0+
|
||||
|
||||
### 2. 安装依赖
|
||||
|
||||
```bash
|
||||
# 创建并激活虚拟环境
|
||||
python3 -m venv venv
|
||||
source venv/bin/activate # Linux/macOS
|
||||
# 或
|
||||
.\venv\Scripts\activate # Windows
|
||||
|
||||
# 安装依赖包
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
## 二、初始化系统
|
||||
|
||||
### 1. 创建必要目录
|
||||
|
||||
```bash
|
||||
mkdir -p {logs,data,models}
|
||||
```
|
||||
|
||||
### 2. 配置数据库
|
||||
|
||||
```bash
|
||||
# 执行数据库初始化脚本
|
||||
mysql -u root -p < src/schema.sql
|
||||
|
||||
# [可选] 导入测试数据（仅用于开发环境）
|
||||
mysql -u root -p equipment_cost_db < src/init_data.sql
|
||||
```
|
||||
|
||||
### 3. 环境配置
|
||||
|
||||
创建 `.env` 文件：
|
||||
|
||||
```ini
|
||||
MYSQL_HOST=localhost
|
||||
MYSQL_USER=root
|
||||
MYSQL_PASSWORD=123456
|
||||
MYSQL_DATABASE=equipment_cost_db
|
||||
```
|
||||
|
||||
## 三、启动服务
|
||||
|
||||
### 1. 开发模式
|
||||
|
||||
```bash
|
||||
# 启动开发服务器
|
||||
python run.py
|
||||
```
|
||||
|
||||
### 2. 测试 API
|
||||
|
||||
```bash
|
||||
# 运行 API 测试
|
||||
python src/test_api.py
|
||||
```
|
||||
|
||||
## 四、开发调试
|
||||
|
||||
### 1. 日志查看
|
||||
|
||||
```bash
|
||||
# API 日志
|
||||
tail -f logs/api.log
|
||||
|
||||
# 测试日志
|
||||
tail -f logs/test_api.log
|
||||
|
||||
# 训练日志
|
||||
tail -f logs/training.log
|
||||
```
|
||||
|
||||
### 2. 数据库调试
|
||||
|
||||
```sql
|
||||
-- 检查数据表
|
||||
SHOW TABLES;
|
||||
|
||||
-- 查看示例数据
|
||||
SELECT * FROM equipment LIMIT 5;
|
||||
```
|
||||
|
||||
### 3. API 测试
|
||||
|
||||
```bash
|
||||
# 测试 API 根路由
|
||||
curl http://localhost:5001/api/
|
||||
|
||||
# 测试预测接口
|
||||
curl -X POST http://localhost:5001/api/predict \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"type": "巡飞弹",
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40
|
||||
}'
|
||||
```
|
||||
|
||||
## 五、注意事项
|
||||
|
||||
1. 开发环境配置
|
||||
- 使用虚拟环境隔离依赖
|
||||
- 保持日志目录可写权限
|
||||
- 定期清理日志文件
|
||||
|
||||
2. 数据库使用
|
||||
- 使用 UTF-8 字符集
|
||||
- 定期备份数据
|
||||
- 避免直接修改生产数据
|
||||
|
||||
3. 代码调试
|
||||
- 查看详细日志输出
|
||||
- 使用测试数据验证功能
|
||||
- 遵循代码规范
|
||||
|
||||
## 六、常见问题
|
||||
|
||||
1. 数据库连接错误
|
||||
- 检查 MySQL 服务状态
|
||||
- 验证数据库用户名密码
|
||||
- 确认数据库字符集设置
|
||||
|
||||
2. API 访问问题
|
||||
- 检查服务是否正常运行
|
||||
- 验证请求格式是否正确
|
||||
- 查看错误日志信息
|
||||
|
||||
3. 模型相关问题
|
||||
- 确保训练数据完整性
|
||||
- 检查模型文件权限
|
||||
- 验证预测结果合理性
|
||||
|
||||
## 七、开发建议
|
||||
|
||||
1. 代码管理
|
||||
- 使用版本控制
|
||||
- 遵循项目结构
|
||||
- 及时更新文档
|
||||
|
||||
2. 测试规范
|
||||
- 运行完整测试套件
|
||||
- 验证各个功能模块
|
||||
- 记录测试结果
|
||||
|
||||
3. 安全注意
|
||||
- 使用安全的数据库密码
|
||||
- 避免敏感信息提交
|
||||
- 保护测试数据安全
|
||||
|
||||
注：生产环境部署请参考 `deploy.md`
|
||||
@ -1,136 +0,0 @@
|
||||
# Node.js 安装指南
|
||||
|
||||
## Windows 安装方法
|
||||
|
||||
### 1. 使用安装包
|
||||
|
||||
1. 访问 Node.js 官网 <https://nodejs.org/>
|
||||
2. 下载 14.x LTS 版本安装包
|
||||
3. 运行安装包，按提示完成安装
|
||||
4. 验证安装：
|
||||
|
||||
```bash
|
||||
node --version
|
||||
npm --version
|
||||
```
|
||||
|
||||
### 2. 使用 nvm-windows（推荐）
|
||||
|
||||
1. 下载 nvm-windows：<https://github.com/coreybutler/nvm-windows/releases>
|
||||
2. 安装 nvm-windows
|
||||
3. 安装 Node.js：
|
||||
|
||||
```bash
|
||||
nvm install 14.21.3
|
||||
nvm use 14.21.3
|
||||
```
|
||||
|
||||
## Linux 安装方法
|
||||
|
||||
### 1. 使用 nvm（推荐）
|
||||
|
||||
```bash
|
||||
# 安装 nvm
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
|
||||
|
||||
# 重新加载配置
|
||||
source ~/.bashrc
|
||||
|
||||
# 安装 Node.js 14
|
||||
nvm install 14
|
||||
nvm use 14
|
||||
```
|
||||
|
||||
### 2. 使用包管理器
|
||||
|
||||
#### Ubuntu/Debian
|
||||
|
||||
```bash
|
||||
# 添加 NodeSource 仓库
|
||||
curl -fsSL https://deb.nodesource.com/setup_14.x | sudo -E bash -
|
||||
|
||||
# 安装 Node.js
|
||||
sudo apt-get install -y nodejs
|
||||
```
|
||||
|
||||
#### CentOS/RHEL
|
||||
|
||||
```bash
|
||||
# 添加 NodeSource 仓库
|
||||
curl -fsSL https://rpm.nodesource.com/setup_14.x | sudo bash -
|
||||
|
||||
# 安装 Node.js
|
||||
sudo yum install -y nodejs
|
||||
```
|
||||
|
||||
## macOS 安装方法
|
||||
|
||||
### 1. 使用 Homebrew（推荐）
|
||||
|
||||
```bash
|
||||
# 安装 Homebrew（如果未安装）
|
||||
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
|
||||
|
||||
# 安装 Node.js 14
|
||||
brew install node@14
|
||||
|
||||
# 添加环境变量
|
||||
echo 'export PATH="/usr/local/opt/node@14/bin:$PATH"' >> ~/.zshrc
|
||||
source ~/.zshrc
|
||||
```
|
||||
|
||||
### 2. 使用 nvm
|
||||
|
||||
```bash
|
||||
# 安装 nvm
|
||||
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
|
||||
|
||||
# 重新加载配置
|
||||
source ~/.zshrc
|
||||
|
||||
# 安装 Node.js 14
|
||||
nvm install 14
|
||||
nvm use 14
|
||||
```
|
||||
|
||||
## 验证安装
|
||||
|
||||
安装完成后，运行以下命令验证：
|
||||
|
||||
```bash
|
||||
# 检查 Node.js 版本
|
||||
node --version # 应显示 v14.x.x
|
||||
|
||||
# 检查 npm 版本
|
||||
npm --version # 应显示 6.x.x 或更高
|
||||
```
|
||||
|
||||
## 常见问题
|
||||
|
||||
### 1. 权限问题
|
||||
|
||||
如果遇到权限错误，可以：
|
||||
|
||||
```bash
|
||||
# Linux/macOS
|
||||
sudo chown -R $USER /usr/local/lib/node_modules
|
||||
```
|
||||
|
||||
### 2. 版本切换
|
||||
|
||||
如果需要在不同版本间切换：
|
||||
|
||||
```bash
|
||||
# 使用 nvm
|
||||
nvm list # 查看已安装版本
|
||||
nvm use 14 # 切换到 14.x 版本
|
||||
```
|
||||
|
||||
### 3. npm 配置
|
||||
|
||||
建议配置国内镜像源：
|
||||
|
||||
```bash
|
||||
# 使用淘宝镜像
|
||||
npm config set registry https://registry.npmmirror.com
|
||||
```
|
||||
163
docs/run.md
163
docs/run.md
@ -1,163 +0,0 @@
|
||||
# 系统运行说明
|
||||
|
||||
## 一、环境准备
|
||||
|
||||
### 1. 安装必要软件
|
||||
|
||||
```bash
|
||||
# 安装 Python 3.8+
|
||||
# 安装 MySQL 8.0+
|
||||
# 安装 Node.js 14+
|
||||
```
|
||||
|
||||
### 2. 安装 Python 依赖
|
||||
|
||||
```bash
|
||||
pip install -r requirements.txt
|
||||
```
|
||||
|
||||
### 3. 安装前端依赖
|
||||
|
||||
```bash
|
||||
cd frontend
|
||||
npm install
|
||||
```
|
||||
|
||||
## 二、数据库配置
|
||||
|
||||
### 1. 创建数据库
|
||||
|
||||
```sql
|
||||
CREATE DATABASE equipment_cost_db DEFAULT CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
|
||||
```
|
||||
|
||||
### 2. 初始化数据库结构
|
||||
|
||||
```bash
|
||||
# 执行数据库结构初始化脚本
|
||||
mysql -u username -p equipment_cost_db < src/schema.sql
|
||||
|
||||
# 导入示例数据
|
||||
mysql -u username -p equipment_cost_db < src/init_data.sql
|
||||
|
||||
# 导入真实数据
|
||||
mysql -u username -p equipment_cost_db < src/real_data.sql
|
||||
```
|
||||
|
||||
## 三、配置文件
|
||||
|
||||
### 1. 后端配置
|
||||
|
||||
创建 `config.py` 文件：
|
||||
|
||||
```python
|
||||
# config.py
|
||||
DATABASE_URI = "mysql+pymysql://username:password@localhost:3306/equipment_cost_db"
|
||||
SECRET_KEY = "your-secret-key"
|
||||
DEBUG = True
|
||||
```
|
||||
|
||||
### 2. 前端配置
|
||||
|
||||
修改 `frontend/src/config.js`：
|
||||
|
||||
```javascript
|
||||
export const API_BASE_URL = 'http://localhost:5001/api';
|
||||
```
|
||||
|
||||
## 四、启动系统
|
||||
|
||||
### 1. 启动后端服务
|
||||
|
||||
```bash
|
||||
# 开发环境
|
||||
python run.py # 服务将在 http://localhost:5001 启动
|
||||
|
||||
# 生产环境
|
||||
gunicorn -w 4 -b 0.0.0.0:5001 run:app
|
||||
```
|
||||
|
||||
### 2. 启动前端服务
|
||||
|
||||
```bash
|
||||
# 开发环境
|
||||
cd frontend
|
||||
npm run serve # 前端将在 http://localhost:8080 启动
|
||||
|
||||
# 生产环境
|
||||
npm run build
|
||||
```
|
||||
|
||||
## 五、访问系统
|
||||
|
||||
- 后端API：<http://localhost:5001/api>
|
||||
- 前端界面：<http://localhost:8080>
|
||||
|
||||
## 六、常见问题
|
||||
|
||||
### 1. 数据库连接问题
|
||||
|
||||
- 检查 MySQL 服务是否启动
|
||||
- 验证数据库用户名和密码
|
||||
- 确认数据库端口是否正确
|
||||
|
||||
### 2. 模型训练
|
||||
|
||||
```bash
|
||||
# 训练模型
|
||||
python src/train_model.py
|
||||
|
||||
# 查看训练日志
|
||||
tail -f logs/training.log
|
||||
```
|
||||
|
||||
### 3. 系统监控
|
||||
|
||||
```bash
|
||||
# 查看系统日志
|
||||
tail -f logs/app.log
|
||||
|
||||
# 监控API请求
|
||||
tail -f logs/access.log
|
||||
```
|
||||
|
||||
## 七、开发调试
|
||||
|
||||
### 1. 后端调试
|
||||
|
||||
```bash
|
||||
# 启动调试模式
|
||||
python run.py --debug
|
||||
|
||||
# 运行测试
|
||||
python -m pytest tests/
|
||||
```
|
||||
|
||||
### 2. 前端调试
|
||||
|
||||
```bash
|
||||
# 启动开发服务器
|
||||
npm run serve
|
||||
|
||||
# 运行测试
|
||||
npm run test
|
||||
```
|
||||
|
||||
## 八、部署建议
|
||||
|
||||
### 1. 使用 Docker 部署
|
||||
|
||||
```bash
|
||||
# 构建镜像
|
||||
docker-compose build
|
||||
|
||||
# 启动服务
|
||||
docker-compose up -d
|
||||
```
|
||||
|
||||
### 2. 生产环境配置
|
||||
|
||||
- 使用 Nginx 作为反向代理
|
||||
- 配置 SSL 证书
|
||||
- 设置适当的防火墙规则
|
||||
- 启用数据库备份
|
||||
@ -1,24 +1,29 @@
|
||||
# frontend
|
||||
|
||||
## Project setup
|
||||
```
|
||||
|
||||
```bash
|
||||
npm install
|
||||
```
|
||||
|
||||
### Compiles and hot-reloads for development
|
||||
```
|
||||
|
||||
```bash
|
||||
npm run serve
|
||||
```
|
||||
|
||||
### Compiles and minifies for production
|
||||
```
|
||||
|
||||
```bash
|
||||
npm run build
|
||||
```
|
||||
|
||||
### Lints and fixes files
|
||||
```
|
||||
|
||||
```bash
|
||||
npm run lint
|
||||
```
|
||||
|
||||
### Customize configuration
|
||||
|
||||
See [Configuration Reference](https://cli.vuejs.org/config/).
|
||||
|
||||
@ -153,31 +153,93 @@ const startAnalysis = async () => {
|
||||
}
|
||||
}
|
||||
|
||||
// 窗口大小变化处理函数
|
||||
const resizeHandler = ref(null)
|
||||
|
||||
// 创建 resize 处理函数
|
||||
const createResizeHandler = () => {
|
||||
const handler = () => {
|
||||
try {
|
||||
if (importanceChart.value && !importanceChart.value.isDisposed()) {
|
||||
importanceChart.value.resize()
|
||||
}
|
||||
if (correlationChart.value && !correlationChart.value.isDisposed()) {
|
||||
correlationChart.value.resize()
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error in resize handler:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// 使用防抖包装
|
||||
return debounce(handler, 200)
|
||||
}
|
||||
|
||||
// 组件挂载时
|
||||
onMounted(() => {
|
||||
// 创建并保存 resize 处理函数的引用
|
||||
resizeHandler.value = createResizeHandler()
|
||||
window.addEventListener('resize', resizeHandler.value)
|
||||
})
|
||||
|
||||
// 组件卸载时
|
||||
onUnmounted(() => {
|
||||
// 移除事件监听
|
||||
if (resizeHandler.value) {
|
||||
window.removeEventListener('resize', resizeHandler.value)
|
||||
resizeHandler.value = null
|
||||
}
|
||||
|
||||
// 销毁图表实例
|
||||
try {
|
||||
if (importanceChart.value) {
|
||||
importanceChart.value.dispose()
|
||||
importanceChart.value = null
|
||||
}
|
||||
if (correlationChart.value) {
|
||||
correlationChart.value.dispose()
|
||||
correlationChart.value = null
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error disposing charts:', error)
|
||||
}
|
||||
})
|
||||
|
||||
// 渲染图表
|
||||
const renderCharts = () => {
|
||||
console.log('Starting to render charts')
|
||||
|
||||
// 销毁旧的图表实例
|
||||
if (importanceChart.value) {
|
||||
importanceChart.value.dispose()
|
||||
}
|
||||
if (correlationChart.value) {
|
||||
correlationChart.value.dispose()
|
||||
// 检查分析结果是否存在且包含必要数据
|
||||
if (!analysisResult.value ||
|
||||
!analysisResult.value.important_features ||
|
||||
!analysisResult.value.correlation_analysis) {
|
||||
console.log('Analysis result not ready')
|
||||
return
|
||||
}
|
||||
|
||||
// 确保 DOM 元素存在
|
||||
// 检查DOM元素
|
||||
if (!importanceChartRef.value || !correlationChartRef.value) {
|
||||
console.log('Chart DOM elements not ready')
|
||||
return
|
||||
}
|
||||
|
||||
try {
|
||||
// 销毁旧的图表实例
|
||||
if (importanceChart.value) {
|
||||
importanceChart.value.dispose()
|
||||
importanceChart.value = null
|
||||
}
|
||||
if (correlationChart.value) {
|
||||
correlationChart.value.dispose()
|
||||
correlationChart.value = null
|
||||
}
|
||||
|
||||
// 创建新的图表实例
|
||||
importanceChart.value = echarts.init(importanceChartRef.value)
|
||||
correlationChart.value = echarts.init(correlationChartRef.value)
|
||||
|
||||
// 设置图表选项
|
||||
importanceChart.value.setOption({
|
||||
const importanceOption = {
|
||||
title: { text: '特征重要性排序' },
|
||||
tooltip: {},
|
||||
xAxis: {
|
||||
@ -189,12 +251,13 @@ const renderCharts = () => {
|
||||
data: analysisResult.value.important_features.map(f => f.name)
|
||||
},
|
||||
series: [{
|
||||
name: '重要性',
|
||||
type: 'bar',
|
||||
data: analysisResult.value.important_features.map(f => f.importance)
|
||||
}]
|
||||
})
|
||||
}
|
||||
|
||||
correlationChart.value.setOption({
|
||||
const correlationOption = {
|
||||
title: { text: '特征相关性热力图' },
|
||||
tooltip: {
|
||||
position: 'top',
|
||||
@ -233,6 +296,7 @@ const renderCharts = () => {
|
||||
color: ['#cc3333', '#eeeeee', '#00007f']
|
||||
},
|
||||
series: [{
|
||||
name: '相关性',
|
||||
type: 'heatmap',
|
||||
data: analysisResult.value.correlation_analysis.matrix,
|
||||
label: {
|
||||
@ -242,13 +306,11 @@ const renderCharts = () => {
|
||||
}
|
||||
}
|
||||
}]
|
||||
})
|
||||
}
|
||||
|
||||
// 监听窗口大小变化
|
||||
window.addEventListener('resize', () => {
|
||||
importanceChart.value?.resize()
|
||||
correlationChart.value?.resize()
|
||||
})
|
||||
// 设置图表选项
|
||||
importanceChart.value.setOption(importanceOption)
|
||||
correlationChart.value.setOption(correlationOption)
|
||||
|
||||
console.log('Charts rendered successfully')
|
||||
} catch (error) {
|
||||
@ -256,16 +318,16 @@ const renderCharts = () => {
|
||||
}
|
||||
}
|
||||
|
||||
// 初始化
|
||||
onMounted(() => {
|
||||
// 可以在这里加载默认数据
|
||||
})
|
||||
|
||||
// 组件卸载时清理图表实例
|
||||
onUnmounted(() => {
|
||||
importanceChart.value?.dispose()
|
||||
correlationChart.value?.dispose()
|
||||
})
|
||||
// 防抖函数
|
||||
function debounce(fn, delay) {
|
||||
let timer = null
|
||||
return function (...args) {
|
||||
if (timer) clearTimeout(timer)
|
||||
timer = setTimeout(() => {
|
||||
fn.apply(this, args)
|
||||
}, delay)
|
||||
}
|
||||
}
|
||||
</script>
|
||||
|
||||
<style lang="scss" scoped>
|
||||
|
||||
68
src/api.py
68
src/api.py
@ -1,68 +0,0 @@
|
||||
from flask import Flask, request, jsonify
|
||||
from .model_trainer import ModelTrainer
|
||||
from .cost_prediction import CostPredictor
|
||||
from .feature_analysis import FeatureAnalysis
|
||||
import pandas as pd
|
||||
|
||||
app = Flask(__name__)
|
||||
|
||||
@app.route('/api/predict', methods=['POST'])
|
||||
def predict_cost():
|
||||
"""
|
||||
成本预测接口
|
||||
"""
|
||||
try:
|
||||
data = request.get_json()
|
||||
|
||||
# 验证必要参数
|
||||
required_params = [
|
||||
'length_m', 'width_m', 'height_m', 'weight_standard_kg',
|
||||
'weight_combat_kg', 'max_range_km', 'max_speed_ms'
|
||||
]
|
||||
|
||||
for param in required_params:
|
||||
if param not in data:
|
||||
return jsonify({'error': f'Missing parameter: {param}'}), 400
|
||||
|
||||
predictor = CostPredictor()
|
||||
result = predictor.predict(data)
|
||||
|
||||
return jsonify({
|
||||
'predicted_cost': float(result['predicted_cost']),
|
||||
'confidence_interval': {
|
||||
'lower': float(result['confidence_intervals'][0]),
|
||||
'upper': float(result['confidence_intervals'][1])
|
||||
}
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
return jsonify({'error': str(e)}), 500
|
||||
|
||||
@app.route('/api/analyze-features', methods=['POST'])
|
||||
def analyze_features():
|
||||
"""
|
||||
特征分析接口
|
||||
"""
|
||||
try:
|
||||
data = request.get_json()
|
||||
analyzer = FeatureAnalysis()
|
||||
|
||||
# 数据预处理
|
||||
processed_data = analyzer.preprocess_features(pd.DataFrame(data))
|
||||
|
||||
# 特征重要性分析
|
||||
important_features = analyzer.select_features(
|
||||
processed_data,
|
||||
data['cost']
|
||||
)
|
||||
|
||||
return jsonify({
|
||||
'important_features': important_features,
|
||||
'correlation_analysis': analyzer.correlation_analysis(
|
||||
processed_data,
|
||||
data['cost']
|
||||
).to_dict()
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
return jsonify({'error': str(e)}), 500
|
||||
@ -222,7 +222,7 @@ class CostPredictor:
|
||||
|
||||
def predict_pls(self, data):
|
||||
"""
|
||||
使用 PLS 模型预测成本
|
||||
使用 PLS 型预<EFBFBD><EFBFBD><EFBFBD>成本
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Starting PLS prediction for {data.get('type')}")
|
||||
@ -253,4 +253,90 @@ class CostPredictor:
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"PLS prediction error: {str(e)}")
|
||||
raise
|
||||
|
||||
def predict_all(self, data):
|
||||
"""
|
||||
使用所有可用模型进行预测
|
||||
"""
|
||||
try:
|
||||
logger.info(f"Starting multi-model prediction for {data.get('type')}")
|
||||
equipment_type = data.get('type')
|
||||
results = {}
|
||||
|
||||
# 1. 获取所有激活的模型
|
||||
with get_db_connection() as conn:
|
||||
cursor = conn.cursor(dictionary=True)
|
||||
cursor.execute("""
|
||||
SELECT id, model_type, model_name, r2_score, mae, rmse
|
||||
FROM trained_models
|
||||
WHERE equipment_type = %s AND is_active = TRUE
|
||||
""", (equipment_type,))
|
||||
active_models = cursor.fetchall()
|
||||
|
||||
if not active_models:
|
||||
raise ValueError(f"No active models found for {equipment_type}")
|
||||
|
||||
# 2. 使用每个模型进行预测
|
||||
trainer = ModelTrainer()
|
||||
for model_info in active_models:
|
||||
try:
|
||||
# 加载特定模型
|
||||
if not trainer.load_model(equipment_type, model_type=model_info['model_type']):
|
||||
logger.warning(f"Failed to load model: {model_info['model_name']}")
|
||||
continue
|
||||
|
||||
# 准备特征数据
|
||||
features = self.feature_analyzer.get_equipment_specific_features(equipment_type)
|
||||
X = np.array([[data.get(feature) for feature in features]])
|
||||
|
||||
# 预测
|
||||
y_pred = trainer.predict(X)
|
||||
|
||||
# 计算置信区间
|
||||
confidence_interval = trainer._calculate_confidence_interval(y_pred[0])
|
||||
|
||||
# 保存结果
|
||||
results[model_info['model_type']] = {
|
||||
'predicted_cost': float(y_pred[0]),
|
||||
'model_info': {
|
||||
'name': model_info['model_name'],
|
||||
'type': model_info['model_type'],
|
||||
'r2_score': float(model_info['r2_score']),
|
||||
'mae': float(model_info['mae']),
|
||||
'rmse': float(model_info['rmse'])
|
||||
},
|
||||
'confidence_interval': {
|
||||
'lower': float(confidence_interval[0]),
|
||||
'upper': float(confidence_interval[1])
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error predicting with model {model_info['model_name']}: {str(e)}")
|
||||
continue
|
||||
|
||||
if not results:
|
||||
raise ValueError("No successful predictions from any model")
|
||||
|
||||
# 3. 计算综合预测结果
|
||||
all_predictions = [result['predicted_cost'] for result in results.values()]
|
||||
ensemble_prediction = float(np.mean(all_predictions))
|
||||
prediction_std = float(np.std(all_predictions))
|
||||
|
||||
# 4. 返回所有结果
|
||||
return {
|
||||
'individual_predictions': results,
|
||||
'ensemble_prediction': {
|
||||
'predicted_cost': ensemble_prediction,
|
||||
'standard_deviation': prediction_std,
|
||||
'confidence_interval': {
|
||||
'lower': float(ensemble_prediction - 1.96 * prediction_std),
|
||||
'upper': float(ensemble_prediction + 1.96 * prediction_std)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in multi-model prediction: {str(e)}")
|
||||
raise
|
||||
@ -1,3 +1,13 @@
|
||||
/*
|
||||
这是用于开发和测试环境的示例数据。
|
||||
生产环境请使用系统的数据导入功能添加实际数据。
|
||||
|
||||
主要用途：
|
||||
1. 提供开发测试数据
|
||||
2. 作为数据格式参考
|
||||
3. 用于系统功能验证
|
||||
*/
|
||||
|
||||
-- 插入装备基本信息
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('终结者', '巡飞弹', '美国', '静止和移动的人员和轻型装甲车辆'),
|
||||
@ -139,16 +149,16 @@ INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
(10, 1500000); -- 彩虹-4
|
||||
|
||||
-- 火箭炮数据
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('BM-21', '火箭炮', '俄罗斯', '面目标'),
|
||||
('SR5', '火箭炮', '中国', '面目标和点目标'),
|
||||
('HIMARS', '火箭炮', '美国', '战术目标'),
|
||||
('LAR-160', '火箭炮', '以色列', '面目标'),
|
||||
('T-122', '火箭炮', '土耳其', '面目标'),
|
||||
('RM-70', '火箭炮', '捷克', '面目标'),
|
||||
('ASTROS II', '火箭炮', '巴西', '面目标和点目标');
|
||||
INSERT INTO equipment (name, type, manufacturer) VALUES
|
||||
('BM-21', '火箭炮', '俄罗斯'),
|
||||
('SR5', '火箭炮', '中国'),
|
||||
('HIMARS', '火箭炮', '美国'),
|
||||
('LAR-160', '火箭炮', '以色列'),
|
||||
('T-122', '火箭炮', '土耳其'),
|
||||
('RM-70', '火箭炮', '捷克'),
|
||||
('ASTROS II', '火箭炮', '巴西');
|
||||
|
||||
-- 插入火箭炮参数
|
||||
-- 火箭炮通用参数
|
||||
INSERT INTO common_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
@ -172,6 +182,7 @@ INSERT INTO common_params (
|
||||
-- ASTROS II
|
||||
(7, 8.0, 2.7, 3.1, 24500, 90);
|
||||
|
||||
-- 火箭炮特有参数
|
||||
INSERT INTO rocket_artillery_params (
|
||||
equipment_id,
|
||||
firing_angle_horizontal,
|
||||
@ -179,44 +190,43 @@ INSERT INTO rocket_artillery_params (
|
||||
rocket_length_m,
|
||||
rocket_diameter_mm,
|
||||
rocket_weight_kg,
|
||||
rate_of_fire
|
||||
rate_of_fire,
|
||||
combat_weight_kg,
|
||||
speed_kmh,
|
||||
min_range_km,
|
||||
mobility_type,
|
||||
structure_layout,
|
||||
engine_model,
|
||||
engine_params,
|
||||
power_hp,
|
||||
travel_range_km
|
||||
) VALUES
|
||||
-- BM-21
|
||||
(1, 102, 55, 2.87, 122, 66.6, 40),
|
||||
(1, 102, 55, 2.87, 122, 66.6, 40, 13700, 75, 1.6, '轮式', '前置驾驶舱', 'V8柴油', '240马力', 240, 500),
|
||||
-- SR5
|
||||
(2, 110, 60, 4.1, 220, 150, 60),
|
||||
(2, 110, 60, 4.1, 220, 150, 60, 28500, 90, 2.0, '轮式', '前置驾驶舱', 'V6柴油', '320马力', 320, 650),
|
||||
-- HIMARS
|
||||
(3, 90, 65, 3.94, 227, 301, 6),
|
||||
(3, 90, 65, 3.94, 227, 301, 6, 16250, 85, 2.0, '轮式', '前置驾驶舱', 'V8柴油', '290马力', 290, 480),
|
||||
-- LAR-160
|
||||
(4, 100, 58, 3.3, 160, 110, 18),
|
||||
(4, 100, 58, 3.3, 160, 110, 18, 15000, 80, 1.8, '轮式', '前置驾驶舱', 'V6柴油', '260马力', 260, 550),
|
||||
-- T-122
|
||||
(5, 110, 65, 2.95, 122, 65.5, 40),
|
||||
(5, 110, 65, 2.95, 122, 65.5, 40, 18000, 85, 1.5, '轮式', '前置驾驶舱', 'V8柴油', '280马力', 280, 600),
|
||||
-- RM-70
|
||||
(6, 100, 50, 2.87, 122, 66.6, 40),
|
||||
(6, 100, 50, 2.87, 122, 66.6, 40, 17200, 70, 1.6, '轮式', '前置驾驶舱', 'V8柴油', '250马力', 250, 520),
|
||||
-- ASTROS II
|
||||
(7, 90, 65, 4.3, 300, 550, 30);
|
||||
|
||||
-- 插入成本数据（示例成本）
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
(1, 800000), -- BM-21
|
||||
(2, 4500000), -- SR5
|
||||
(3, 5500000), -- HIMARS
|
||||
(4, 3500000), -- LAR-160
|
||||
(5, 2800000), -- T-122
|
||||
(6, 1500000), -- RM-70
|
||||
(7, 4800000); -- ASTROS II
|
||||
(7, 90, 65, 4.3, 300, 550, 30, 24500, 80, 2.2, '轮式', '前置驾驶舱', 'V8柴油', '350马力', 350, 700);
|
||||
|
||||
-- 巡飞弹数据
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('Hero-120', '巡飞弹', '以色列', '装甲目标'),
|
||||
('Switchblade 600', '巡飞弹', '美国', '装甲车辆'),
|
||||
('Warmate', '巡飞弹', '波兰', '轻型装甲目标'),
|
||||
('CH-901', '巡飞弹', '中国', '人员和轻型装甲车辆'),
|
||||
('HAROP', '巡飞弹', '以色列', '防空系统'),
|
||||
('Coyote', '巡飞弹', '美国', '无人机和巡飞弹'),
|
||||
('WS-43', '巡飞弹', '中国', '固定目标和装甲目标');
|
||||
INSERT INTO equipment (name, type, manufacturer) VALUES
|
||||
('Hero-120', '巡飞弹', '以色列'),
|
||||
('Switchblade 600', '巡飞弹', '美国'),
|
||||
('Warmate', '巡飞弹', '波兰'),
|
||||
('CH-901', '巡飞弹', '中国'),
|
||||
('HAROP', '巡飞弹', '以色列'),
|
||||
('Coyote', '巡飞弹', '美国'),
|
||||
('WS-43', '巡飞弹', '中国');
|
||||
|
||||
-- 插入巡飞弹参数
|
||||
-- 巡飞弹通用参数
|
||||
INSERT INTO common_params (
|
||||
equipment_id,
|
||||
length_m,
|
||||
@ -240,38 +250,70 @@ INSERT INTO common_params (
|
||||
-- WS-43
|
||||
(14, 1.8, 0.35, 0.35, 20, 60);
|
||||
|
||||
-- 巡飞弹特有参数
|
||||
INSERT INTO loitering_munition_params (
|
||||
equipment_id,
|
||||
max_speed_kmh,
|
||||
wingspan_m,
|
||||
warhead_weight_kg,
|
||||
max_speed_ms,
|
||||
cruise_speed_kmh,
|
||||
flight_time_min,
|
||||
warhead_type,
|
||||
launch_mode,
|
||||
folded_length_mm,
|
||||
folded_width_mm,
|
||||
folded_height_mm
|
||||
folded_height_mm,
|
||||
power_system,
|
||||
guidance_system
|
||||
) VALUES
|
||||
-- Hero-120
|
||||
(8, 180, 100, 60, '破片杀伤战斗部', '箱式发射', 1300, 230, 230),
|
||||
(8, 2.1, 3.5, 50, 100, 60, '破片杀伤战斗部', '箱式发射', 1300, 230, 230, '电动机', 'GPS/INS'),
|
||||
-- Switchblade 600
|
||||
(9, 185, 115, 40, '破甲战斗部', '箱式发射', 1300, 220, 220),
|
||||
(9, 2.2, 4.0, 51.4, 115, 40, '破甲战斗部', '箱式发射', 1300, 220, 220, '电动机', 'GPS/INS/光电'),
|
||||
-- Warmate
|
||||
(10, 150, 90, 30, '破片杀伤战斗部', '箱式发射', 1100, 150, 150),
|
||||
(10, 1.4, 1.4, 41.7, 90, 30, '破片杀伤战斗部', '箱式发射', 1100, 150, 150, '电动机', 'GPS/INS'),
|
||||
-- CH-901
|
||||
(11, 160, 95, 120, '破片杀伤战斗部', '箱式发射', 1200, 180, 180),
|
||||
(11, 1.8, 2.0, 44.4, 95, 120, '破片杀伤战斗部', '箱式发射', 1200, 180, 180, '电动机', 'GPS/INS'),
|
||||
-- HAROP
|
||||
(12, 185, 110, 360, '高爆战斗部', '箱式发射', 2500, 430, 430),
|
||||
(12, 3.0, 23, 51.4, 110, 360, '高爆战斗部', '箱式发射', 2500, 430, 430, '活塞发动机', 'GPS/INS/光电/数据链'),
|
||||
-- Coyote
|
||||
(13, 150, 95, 30, '破片杀伤战斗部', '箱式发射', 900, 120, 120),
|
||||
(13, 1.2, 1.8, 41.7, 95, 30, '破片杀伤战斗部', '箱式发射', 900, 120, 120, '电动机', 'GPS/INS'),
|
||||
-- WS-43
|
||||
(14, 170, 100, 45, '破片杀伤战斗部', '箱式发射', 1800, 350, 350);
|
||||
(14, 2.4, 3.8, 47.2, 100, 45, '破片杀伤战斗部', '箱式发射', 1800, 350, 350, '电动机', 'GPS/INS/光电');
|
||||
|
||||
-- 插入成本数据（示例成本）
|
||||
INSERT INTO cost_data (equipment_id, actual_cost) VALUES
|
||||
-- 火箭炮
|
||||
(1, 800000), -- BM-21
|
||||
(2, 4500000), -- SR5
|
||||
(3, 5500000), -- HIMARS
|
||||
(4, 3500000), -- LAR-160
|
||||
(5, 2800000), -- T-122
|
||||
(6, 1500000), -- RM-70
|
||||
(7, 4800000), -- ASTROS II
|
||||
-- 巡飞弹
|
||||
(8, 150000), -- Hero-120
|
||||
(9, 180000), -- Switchblade 600
|
||||
(10, 80000), -- Warmate
|
||||
(11, 100000), -- CH-901
|
||||
(12, 850000), -- HAROP
|
||||
(13, 75000), -- Coyote
|
||||
(14, 120000); -- WS-43
|
||||
(14, 120000); -- WS-43
|
||||
|
||||
-- 创建初始数据集
|
||||
INSERT INTO datasets (name, description, equipment_type, purpose) VALUES
|
||||
('火箭炮训练集', '用于训练火箭炮成本预测模型的数据集', '火箭炮', '训练'),
|
||||
('巡飞弹训练集', '用于训练巡飞弹成本预测模型的数据集', '巡飞弹', '训练'),
|
||||
('火箭炮验证集', '用于验证火箭炮成本预测模型的数据集', '火箭炮', '验证'),
|
||||
('巡飞弹验证集', '用于验证巡飞弹成本预测模型的数据集', '巡飞弹', '验证');
|
||||
|
||||
-- 关联装备到数据集
|
||||
INSERT INTO dataset_equipment (dataset_id, equipment_id) VALUES
|
||||
-- 火箭炮训练集
|
||||
(1, 1), (1, 2), (1, 3), (1, 4),
|
||||
-- 巡飞弹训练集
|
||||
(2, 8), (2, 9), (2, 10), (2, 11), (2, 12),
|
||||
-- 火箭炮验证集
|
||||
(3, 5), (3, 6), (3, 7),
|
||||
-- 巡飞弹验证集
|
||||
(4, 13), (4, 14);
|
||||
@ -1,9 +0,0 @@
|
||||
-- 火箭炮数据（13种）
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('BM-21', '火箭炮', '俄罗斯', '面目标'),
|
||||
-- ... 其他12种火箭炮数据
|
||||
|
||||
-- 巡飞弹数据（18种）
|
||||
INSERT INTO equipment (name, type, manufacturer, target_type) VALUES
|
||||
('Hero-120', '巡飞弹', '以色列', '装甲目标'),
|
||||
-- ... 其他17种巡飞弹数据
|
||||
@ -2,7 +2,6 @@ from flask import Blueprint, request, jsonify, send_file
|
||||
from .cost_prediction import CostPredictor
|
||||
from .feature_analysis import FeatureAnalysis
|
||||
import pandas as pd
|
||||
import logging
|
||||
from datetime import datetime
|
||||
import numpy as np
|
||||
import mysql.connector
|
||||
@ -10,7 +9,6 @@ from sklearn.metrics import mean_absolute_error
|
||||
from .create_template import create_excel_template
|
||||
import json
|
||||
import os
|
||||
import time
|
||||
from .data_preparation import DataPreparation
|
||||
from .model_trainer import ModelTrainer
|
||||
from .logger import setup_logger
|
||||
|
||||
@ -1,3 +1,14 @@
|
||||
-- 如果数据库已存在则删除
|
||||
DROP DATABASE IF EXISTS equipment_cost_db;
|
||||
|
||||
-- 创建数据库
|
||||
CREATE DATABASE equipment_cost_db
|
||||
DEFAULT CHARACTER SET utf8mb4
|
||||
COLLATE utf8mb4_unicode_ci;
|
||||
|
||||
-- 使用数据库
|
||||
USE equipment_cost_db;
|
||||
|
||||
-- 装备基本信息表
|
||||
CREATE TABLE equipment (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
|
||||
353
src/test_api.py
353
src/test_api.py
@ -1,192 +1,191 @@
|
||||
import requests
|
||||
import json
|
||||
import logging
|
||||
from datetime import datetime
|
||||
import os
|
||||
import sys
|
||||
|
||||
# 添加项目根目录到 Python 路径
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
project_root = os.path.dirname(current_dir)
|
||||
if project_root not in sys.path:
|
||||
sys.path.insert(0, project_root)
|
||||
|
||||
# 配置基本日志
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
|
||||
handlers=[
|
||||
logging.FileHandler('logs/test_api.log'),
|
||||
logging.StreamHandler()
|
||||
]
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def test_api_endpoints():
|
||||
"""
|
||||
测试API各个端点
|
||||
测试 API 各个端点
|
||||
"""
|
||||
base_url = 'http://localhost:5001/api'
|
||||
|
||||
# 1. 测试根路由
|
||||
print("\n1. 测试 API 根路由")
|
||||
response = requests.get(f'{base_url}/')
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
# 2. 测试机器学习预测接口
|
||||
print("\n2. 测试机器学习预测接口")
|
||||
predict_data = {
|
||||
"type": "巡飞弹",
|
||||
"length_m": 0.56,
|
||||
"width_m": 0.15,
|
||||
"height_m": 0.20,
|
||||
"weight_kg": 2.72,
|
||||
"max_range_km": 24,
|
||||
"max_speed_kmh": 160.93,
|
||||
"cruise_speed_kmh": 96.56,
|
||||
"flight_time_min": 15,
|
||||
"folded_length_mm": 560,
|
||||
"folded_width_mm": 150,
|
||||
"folded_height_mm": 200,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "凭自身动力起飞"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
# 3. 测试 PLS 预测接口
|
||||
print("\n3. 测试 PLS 预测接口")
|
||||
response = requests.post(
|
||||
f'{base_url}/pls/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
# 4. 测试特征分析接口
|
||||
print("\n4. 测试特征分析接口")
|
||||
analysis_data = {
|
||||
"data": [{
|
||||
try:
|
||||
# 1. 测试根路由
|
||||
logger.info("\n1. 测试 API 根路由")
|
||||
response = requests.get(f'{base_url}/')
|
||||
print_response(response, "API 根路由")
|
||||
|
||||
# 2. 测试机器学习预测接口
|
||||
logger.info("\n2. 测试机器学习预测接口")
|
||||
predict_data = {
|
||||
"type": "巡飞弹",
|
||||
"length_m": 0.56,
|
||||
"width_m": 0.15,
|
||||
"height_m": 0.20,
|
||||
"weight_kg": 2.72,
|
||||
"max_range_km": 24,
|
||||
"max_speed_kmh": 160.93,
|
||||
"cruise_speed_kmh": 96.56,
|
||||
"flight_time_min": 15,
|
||||
"folded_length_mm": 560,
|
||||
"folded_width_mm": 150,
|
||||
"folded_height_mm": 200
|
||||
}],
|
||||
"cost": [1000000]
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/analyze-features',
|
||||
json=analysis_data
|
||||
)
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
# 5. 测试机器学习模型训练接口
|
||||
print("\n5. 测试机器学习模型训练接口")
|
||||
training_data = {
|
||||
"training_data": [
|
||||
{
|
||||
"type": "巡飞弹",
|
||||
"length_m": 0.56,
|
||||
"width_m": 0.15,
|
||||
"height_m": 0.20,
|
||||
"weight_kg": 2.72,
|
||||
"max_range_km": 24,
|
||||
"max_speed_kmh": 160.93,
|
||||
"cruise_speed_kmh": 96.56,
|
||||
"flight_time_min": 15,
|
||||
"folded_length_mm": 560,
|
||||
"folded_width_mm": 150,
|
||||
"folded_height_mm": 200,
|
||||
"cost": 1000000
|
||||
},
|
||||
{
|
||||
"type": "巡飞弹",
|
||||
"length_m": 0.58,
|
||||
"width_m": 0.16,
|
||||
"height_m": 0.21,
|
||||
"weight_kg": 2.85,
|
||||
"max_range_km": 26,
|
||||
"max_speed_kmh": 170,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 16,
|
||||
"folded_length_mm": 580,
|
||||
"folded_width_mm": 160,
|
||||
"folded_height_mm": 210,
|
||||
"cost": 1100000
|
||||
},
|
||||
{
|
||||
"type": "巡飞弹",
|
||||
"length_m": 0.54,
|
||||
"width_m": 0.14,
|
||||
"height_m": 0.19,
|
||||
"weight_kg": 2.60,
|
||||
"max_range_km": 22,
|
||||
"max_speed_kmh": 155,
|
||||
"cruise_speed_kmh": 93,
|
||||
"flight_time_min": 14,
|
||||
"folded_length_mm": 540,
|
||||
"folded_width_mm": 140,
|
||||
"folded_height_mm": 190,
|
||||
"cost": 900000
|
||||
"length_m": 1.3,
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"max_speed_ms": 50,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"folded_length_mm": 1300,
|
||||
"folded_width_mm": 230,
|
||||
"folded_height_mm": 230,
|
||||
"warhead_type": "破片杀伤战斗部",
|
||||
"launch_mode": "凭自身动力起飞"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "机器学习预测")
|
||||
|
||||
# 3. 测试 PLS 预测接口
|
||||
logger.info("\n3. 测试 PLS 预测接口")
|
||||
response = requests.post(
|
||||
f'{base_url}/pls/predict',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "PLS 预测")
|
||||
|
||||
# 4. 测试特征分析接口
|
||||
logger.info("\n4. 测试特征分析接口")
|
||||
analysis_data = {
|
||||
"dataset_id": 1, # 假设数据集 ID 为 1
|
||||
"equipment_type": "巡飞弹"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/analyze-features',
|
||||
json=analysis_data
|
||||
)
|
||||
print_response(response, "特征分析")
|
||||
|
||||
# 5. 测试机器学习模型训练接口
|
||||
logger.info("\n5. 测试机器学习模型训练接口")
|
||||
training_data = {
|
||||
"type": "巡飞弹",
|
||||
"train_dataset_id": 1, # 训练数据集 ID
|
||||
"validation_dataset_id": 2, # 验证数据集 ID
|
||||
"models": ["xgboost", "lightgbm", "rf"] # 要训练的模型类型
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/train',
|
||||
json=training_data
|
||||
)
|
||||
print_response(response, "模型训练")
|
||||
|
||||
# 6. 测试数据集相关接口
|
||||
logger.info("\n6. 测试数据集相关接口")
|
||||
|
||||
# 6.1 获取数据集列表
|
||||
response = requests.get(f'{base_url}/datasets')
|
||||
print_response(response, "获取数据集列表")
|
||||
|
||||
# 6.2 获取可用的装备列表
|
||||
response = requests.get(f'{base_url}/data')
|
||||
equipment_data = response.json()
|
||||
|
||||
# 获取巡飞弹类型的装备ID
|
||||
available_equipment_ids = []
|
||||
if 'loitering_munition' in equipment_data:
|
||||
available_equipment_ids = [
|
||||
item['id']
|
||||
for item in equipment_data['loitering_munition']
|
||||
if item['id'] is not None
|
||||
][:3] # 取前3个可用的ID
|
||||
|
||||
if not available_equipment_ids:
|
||||
logger.warning("没有找到可用的装备ID，跳过创建数据集测试")
|
||||
else:
|
||||
# 6.3 创建新数据集
|
||||
new_dataset = {
|
||||
"name": "测试数据集",
|
||||
"description": "用于测试的数据集",
|
||||
"equipment_type": "巡飞弹",
|
||||
"purpose": "训练",
|
||||
"equipment_ids": available_equipment_ids
|
||||
}
|
||||
],
|
||||
"equipment_type": "巡飞弹"
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/train',
|
||||
json=training_data
|
||||
)
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
# 6. 测试 PLS 模型训练接口
|
||||
print("\n6. 测试 PLS 模型训练接口")
|
||||
|
||||
# 使用真实的训练数据
|
||||
training_data = {
|
||||
"training_data": [
|
||||
{
|
||||
"length_m": 1.3, # 哈比
|
||||
"width_m": 0.23,
|
||||
"height_m": 0.23,
|
||||
"weight_kg": 12.5,
|
||||
"max_range_km": 40,
|
||||
"max_speed_kmh": 180,
|
||||
"cruise_speed_kmh": 100,
|
||||
"flight_time_min": 60,
|
||||
"folded_length_mm": 1300,
|
||||
"folded_width_mm": 230,
|
||||
"folded_height_mm": 230
|
||||
},
|
||||
{
|
||||
"length_m": 2.5, # HAROP
|
||||
"width_m": 0.43,
|
||||
"height_m": 0.43,
|
||||
"weight_kg": 135,
|
||||
"max_range_km": 1000,
|
||||
"max_speed_kmh": 185,
|
||||
"cruise_speed_kmh": 110,
|
||||
"flight_time_min": 360,
|
||||
"folded_length_mm": 2500,
|
||||
"folded_width_mm": 430,
|
||||
"folded_height_mm": 430
|
||||
},
|
||||
{
|
||||
"length_m": 1.1, # Warmate
|
||||
"width_m": 0.15,
|
||||
"height_m": 0.15,
|
||||
"weight_kg": 5.7,
|
||||
"max_range_km": 15,
|
||||
"max_speed_kmh": 150,
|
||||
"cruise_speed_kmh": 90,
|
||||
"flight_time_min": 30,
|
||||
"folded_length_mm": 1100,
|
||||
"folded_width_mm": 150,
|
||||
"folded_height_mm": 150
|
||||
}
|
||||
],
|
||||
"actual_costs": [150000, 850000, 80000] # 对应的实际成本
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/pls/train',
|
||||
json=training_data
|
||||
)
|
||||
print(json.dumps(response.json(), indent=2, ensure_ascii=False))
|
||||
|
||||
logger.info(f"创建数据集使用的装备IDs: {available_equipment_ids}")
|
||||
|
||||
response = requests.post(
|
||||
f'{base_url}/datasets',
|
||||
json=new_dataset
|
||||
)
|
||||
print_response(response, "创建数据集")
|
||||
|
||||
# 7. 测试模型相关接口
|
||||
logger.info("\n7. 测试模型相关接口")
|
||||
|
||||
# 7.1 获取模型列表
|
||||
response = requests.get(f'{base_url}/models')
|
||||
print_response(response, "获取模型列表")
|
||||
|
||||
# 7.2 获取最新模型
|
||||
response = requests.get(f'{base_url}/models/巡飞弹/latest')
|
||||
print_response(response, "获取最新模型")
|
||||
|
||||
# 8. 测试多模型预测接口
|
||||
logger.info("\n8. 测试多模型预测接口")
|
||||
response = requests.post(
|
||||
f'{base_url}/predict/all',
|
||||
json=predict_data
|
||||
)
|
||||
print_response(response, "多模型预测")
|
||||
|
||||
logger.info("所有测试完成")
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.error(f"API 请求错误: {str(e)}")
|
||||
except Exception as e:
|
||||
logger.error(f"测试过程中出现错误: {str(e)}")
|
||||
|
||||
def print_response(response, endpoint_name):
|
||||
"""
|
||||
打印响应结果
|
||||
"""
|
||||
try:
|
||||
logger.info(f"\n=== {endpoint_name} 测试结果 ===")
|
||||
logger.info(f"状态码: {response.status_code}")
|
||||
|
||||
if response.status_code == 200:
|
||||
result = response.json()
|
||||
logger.info(f"响应数据:\n{json.dumps(result, indent=2, ensure_ascii=False)}")
|
||||
else:
|
||||
logger.error(f"错误响应:\n{response.text}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理响应时出错: {str(e)}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
# 确保日志目录存在
|
||||
os.makedirs('logs', exist_ok=True)
|
||||
|
||||
logger.info(f"=== API 测试开始 - {datetime.now()} ===")
|
||||
test_api_endpoints()
|
||||
logger.info(f"=== API 测试结束 - {datetime.now()} ===")
|
||||
except Exception as e:
|
||||
print(f"测试过程中出现错误: {str(e)}")
|
||||
logger.error(f"测试执行失败: {str(e)}")
|
||||
Loading…
Reference in New Issue
Block a user