414 lines
14 KiB
Python
414 lines
14 KiB
Python
"""
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高光谱分析工具包输出处理模块
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提供统一的输出格式化和结果摘要功能
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"""
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import os
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import json
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import pandas as pd
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import numpy as np
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from pathlib import Path
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from typing import Dict, Any, List, Optional, Union, Tuple
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from datetime import datetime
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import matplotlib.pyplot as plt
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import warnings
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warnings.filterwarnings('ignore')
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class OutputFormatter:
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"""输出格式化器"""
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@staticmethod
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def format_task_result(task_name: str, result: Any) -> Dict[str, Any]:
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"""格式化任务结果"""
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formatted = {
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'task_name': task_name,
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'timestamp': datetime.now().isoformat(),
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'success': True,
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'result_type': type(result).__name__,
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'summary': {}
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}
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if result is None:
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formatted['summary'] = {'message': '任务完成，无返回结果'}
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elif isinstance(result, dict):
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formatted['summary'] = OutputFormatter._summarize_dict_result(result)
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elif isinstance(result, (list, tuple)):
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formatted['summary'] = OutputFormatter._summarize_list_result(result)
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elif isinstance(result, np.ndarray):
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formatted['summary'] = OutputFormatter._summarize_array_result(result)
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elif isinstance(result, pd.DataFrame):
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formatted['summary'] = OutputFormatter._summarize_dataframe_result(result)
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else:
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formatted['summary'] = {'value': str(result)}
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return formatted
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@staticmethod
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def _summarize_dict_result(result: Dict) -> Dict[str, Any]:
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"""汇总字典结果"""
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summary = {
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'keys_count': len(result),
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'keys': list(result.keys())[:10] # 只显示前10个键
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}
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# 尝试提取数值信息
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numeric_values = {}
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for key, value in result.items():
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if isinstance(value, (int, float)):
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numeric_values[key] = value
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elif isinstance(value, np.ndarray) and value.ndim == 0:
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numeric_values[key] = float(value)
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elif isinstance(value, np.ndarray) and value.size == 1:
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numeric_values[key] = float(value.item())
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if numeric_values:
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summary['numeric_metrics'] = numeric_values
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return summary
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@staticmethod
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def _summarize_list_result(result: Union[List, Tuple]) -> Dict[str, Any]:
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"""汇总列表/元组结果"""
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summary = {
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'length': len(result),
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'element_types': list(set(type(x).__name__ for x in result[:10]))
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}
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# 如果是数值列表，计算统计信息
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if len(result) > 0 and all(isinstance(x, (int, float, np.number)) for x in result):
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numeric_result = [float(x) for x in result]
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summary['statistics'] = {
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'mean': np.mean(numeric_result),
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'std': np.std(numeric_result),
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'min': np.min(numeric_result),
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'max': np.max(numeric_result)
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}
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return summary
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@staticmethod
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def _summarize_array_result(result: np.ndarray) -> Dict[str, Any]:
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"""汇总数组结果"""
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summary = {
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'shape': result.shape,
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'dtype': str(result.dtype),
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'dimensions': result.ndim
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}
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if result.size > 0:
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summary['statistics'] = {
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'mean': float(np.mean(result)),
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'std': float(np.std(result)),
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'min': float(np.min(result)),
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'max': float(np.max(result))
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}
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# 检查是否有NaN或Inf
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if np.any(np.isnan(result)):
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summary['has_nan'] = True
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if np.any(np.isinf(result)):
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summary['has_inf'] = True
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return summary
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@staticmethod
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def _summarize_dataframe_result(result: pd.DataFrame) -> Dict[str, Any]:
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"""汇总DataFrame结果"""
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summary = {
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'shape': result.shape,
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'columns': list(result.columns),
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'dtypes': result.dtypes.astype(str).to_dict()
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}
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# 数值列统计
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numeric_cols = result.select_dtypes(include=[np.number]).columns
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if len(numeric_cols) > 0:
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summary['numeric_statistics'] = {}
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for col in numeric_cols:
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summary['numeric_statistics'][col] = {
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'mean': float(result[col].mean()),
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'std': float(result[col].std()),
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'min': float(result[col].min()),
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'max': float(result[col].max())
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}
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return summary
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class ResultExporter:
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"""结果导出器"""
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@staticmethod
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def save_task_summary(summary: Dict[str, Any], output_dir: str, prefix: str = "task_summary"):
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"""保存任务摘要"""
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output_path = Path(output_dir) / f"{prefix}.json"
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try:
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(summary, f, indent=2, ensure_ascii=False, default=str)
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return str(output_path)
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except Exception as e:
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print(f"警告: 无法保存任务摘要: {e}")
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return None
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@staticmethod
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def save_execution_log(task_name: str, args: Dict[str, Any], result: Any,
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output_dir: str, success: bool = True):
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"""保存执行日志"""
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log_entry = {
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'timestamp': datetime.now().isoformat(),
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'task_name': task_name,
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'parameters': args,
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'success': success,
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'result_summary': OutputFormatter.format_task_result(task_name, result)
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}
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log_path = Path(output_dir) / "execution_log.json"
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try:
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# 读取现有日志
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if log_path.exists():
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with open(log_path, 'r', encoding='utf-8') as f:
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logs = json.load(f)
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else:
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logs = []
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# 添加新日志
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logs.append(log_entry)
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# 保存日志
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with open(log_path, 'w', encoding='utf-8') as f:
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json.dump(logs, f, indent=2, ensure_ascii=False, default=str)
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return str(log_path)
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except Exception as e:
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print(f"警告: 无法保存执行日志: {e}")
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return None
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class SummaryGenerator:
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"""摘要生成器"""
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@staticmethod
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def generate_task_summary(task_name: str, args, result: Any,
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execution_time: Optional[float] = None) -> str:
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"""生成任务摘要文本"""
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lines = []
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lines.append("=" * 60)
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lines.append(f"任务执行摘要 - {task_name}")
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lines.append("=" * 60)
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# 基本信息
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lines.append(f"执行时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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if execution_time:
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lines.append(f"运行时长: {execution_time:.2f} 秒")
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# 输入参数
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lines.append(f"\n输入参数:")
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for key, value in vars(args).items():
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if not key.startswith('_'):
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lines.append(f" {key}: {value}")
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# 结果摘要
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lines.append(f"\n结果摘要:")
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formatted_result = OutputFormatter.format_task_result(task_name, result)
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summary = formatted_result['summary']
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if 'statistics' in summary:
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stats = summary['statistics']
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lines.append(f" 数据统计:")
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lines.append(f" 均值: {stats.get('mean', 'N/A'):.4f}")
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lines.append(f" 标准差: {stats.get('std', 'N/A'):.4f}")
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lines.append(f" 最小值: {stats.get('min', 'N/A'):.4f}")
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lines.append(f" 最大值: {stats.get('max', 'N/A'):.4f}")
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if 'shape' in summary:
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lines.append(f" 数据形状: {summary['shape']}")
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if 'keys_count' in summary:
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lines.append(f" 结果包含 {summary['keys_count']} 个项目")
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if 'numeric_metrics' in summary:
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lines.append(f" 数值指标:")
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for key, value in summary['numeric_metrics'].items():
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lines.append(f" {key}: {value}")
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# 输出文件
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if hasattr(args, 'output_dir') and hasattr(args, 'output_prefix'):
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output_dir = Path(args.output_dir)
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lines.append(f"\n输出文件:")
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lines.append(f" 输出目录: {output_dir.absolute()}")
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# 列出可能的输出文件
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possible_files = [
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f"{args.output_prefix}.dat",
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f"{args.output_prefix}.hdr",
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f"{args.output_prefix}.csv",
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f"{args.output_prefix}.png",
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f"{args.output_prefix}.json"
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]
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for filename in possible_files:
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filepath = output_dir / filename
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if filepath.exists():
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lines.append(f" ✓ {filename} ({filepath.stat().st_size} bytes)")
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lines.append("=" * 60)
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return "\n".join(lines)
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@staticmethod
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def print_colored_summary(summary_text: str, success: bool = True):
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"""打印彩色摘要"""
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try:
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from colorama import Fore, Style, init
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init()
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if success:
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color = Fore.GREEN
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else:
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color = Fore.RED
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print(color + summary_text + Style.RESET_ALL)
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except ImportError:
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# 如果没有colorama，直接打印
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print(summary_text)
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class ReportGenerator:
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"""报告生成器"""
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@staticmethod
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def generate_html_report(task_name: str, args, result: Any,
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output_dir: str, execution_time: Optional[float] = None) -> str:
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"""生成HTML报告"""
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html_content = f"""
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<!DOCTYPE html>
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<html>
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<head>
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<title>高光谱分析报告 - {task_name}</title>
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<meta charset="utf-8">
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<style>
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body {{ font-family: Arial, sans-serif; margin: 40px; }}
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.header {{ background: #f0f0f0; padding: 20px; border-radius: 5px; }}
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.section {{ margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 5px; }}
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.success {{ border-color: #4CAF50; background: #f9fff9; }}
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.metric {{ display: inline-block; margin: 10px; padding: 10px; background: #e8f4f8; border-radius: 3px; }}
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table {{ border-collapse: collapse; width: 100%; }}
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th, td {{ border: 1px solid #ddd; padding: 8px; text-align: left; }}
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th {{ background-color: #f2f2f2; }}
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</style>
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</head>
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<body>
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<div class="header">
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<h1>高光谱分析执行报告</h1>
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<p><strong>任务:</strong> {task_name}</p>
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<p><strong>执行时间:</strong> {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
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{"<p><strong>运行时长:</strong> " + f"{execution_time:.2f} 秒</p>" if execution_time else ""}
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</div>
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<div class="section">
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<h2>输入参数</h2>
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<table>
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<tr><th>参数</th><th>值</th></tr>
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"""
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# 添加参数
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for key, value in vars(args).items():
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if not key.startswith('_'):
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html_content += f" <tr><td>{key}</td><td>{value}</td></tr>\n"
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html_content += """
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</table>
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</div>
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<div class="section success">
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<h2>执行结果</h2>
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"""
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# 添加结果摘要
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formatted_result = OutputFormatter.format_task_result(task_name, result)
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summary = formatted_result['summary']
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if 'statistics' in summary:
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stats = summary['statistics']
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html_content += """
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<h3>数据统计</h3>
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<div class="metric">均值: {:.4f}</div>
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<div class="metric">标准差: {:.4f}</div>
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<div class="metric">最小值: {:.4f}</div>
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<div class="metric">最大值: {:.4f}</div>
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""".format(
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stats.get('mean', 0),
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stats.get('std', 0),
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stats.get('min', 0),
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stats.get('max', 0)
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)
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if 'shape' in summary:
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html_content += f"""
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<h3>数据信息</h3>
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<p>形状: {summary['shape']}</p>
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<p>数据类型: {summary.get('dtype', 'unknown')}</p>
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"""
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html_content += """
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</div>
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</body>
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</html>
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"""
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# 保存HTML报告
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report_path = Path(output_dir) / f"{task_name}_report.html"
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try:
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with open(report_path, 'w', encoding='utf-8') as f:
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f.write(html_content)
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return str(report_path)
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except Exception as e:
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print(f"警告: 无法生成HTML报告: {e}")
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return None
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def create_unified_output(task_name: str, args, result: Any,
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output_dir: str, execution_time: Optional[float] = None,
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success: bool = True) -> Dict[str, str]:
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"""
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创建统一的输出
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Returns:
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输出文件路径字典
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"""
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output_files = {}
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# 生成并打印摘要
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summary_text = SummaryGenerator.generate_task_summary(
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task_name, args, result, execution_time
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)
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SummaryGenerator.print_colored_summary(summary_text, success)
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# 保存任务摘要
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formatted_result = OutputFormatter.format_task_result(task_name, result)
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summary_path = ResultExporter.save_task_summary(
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formatted_result, output_dir, f"{task_name}_summary"
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)
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if summary_path:
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output_files['summary'] = summary_path
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# 保存执行日志
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log_path = ResultExporter.save_execution_log(
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task_name, vars(args), result, output_dir, success
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)
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if log_path:
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output_files['log'] = log_path
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# 生成HTML报告
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html_path = ReportGenerator.generate_html_report(
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task_name, args, result, output_dir, execution_time
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)
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if html_path:
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output_files['report'] = html_path
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return output_files
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