126 lines
4.2 KiB
Python
126 lines
4.2 KiB
Python
import json
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import os
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from pathlib import Path
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import pandas as pd
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# 定义结果目录
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data_dir = Path('./result')
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# 指定要分析的文件
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target_file = data_dir / 'backtest-result-2025-10-14_13-45-04.json'
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# 输出文件
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export_file = data_dir / 'backtest_trades_with_adjustments.csv'
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print(f"分析文件: {target_file}")
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print(f"文件大小: {target_file.stat().st_size / (1024 * 1024):.2f} MB")
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# 读取文件
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try:
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with open(target_file, 'r', encoding='utf-8') as f:
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data = json.load(f)
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print("文件加载成功")
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except Exception as e:
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print(f"文件加载失败: {e}")
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exit(1)
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# 检查数据结构
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if 'strategy' not in data:
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print("数据中没有 'strategy' 字段")
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exit(1)
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strategy_name = 'FreqaiPrimer'
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if strategy_name not in data['strategy']:
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print(f"策略 '{strategy_name}' 不在数据中")
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print(f"可用策略: {list(data['strategy'].keys())}")
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exit(1)
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strategy_data = data['strategy'][strategy_name]
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if 'trades' not in strategy_data:
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print("策略数据中没有 'trades' 字段")
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exit(1)
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trades = strategy_data['trades']
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print(f"总交易数: {len(trades)}")
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# 分析交易中的加仓情况
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results = []
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trades_with_adjustments = 0
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for i, trade in enumerate(trades):
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# 每1000笔交易显示进度
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if (i + 1) % 1000 == 0:
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print(f"已分析 {i + 1} 笔交易")
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pair = trade.get('pair', 'Unknown')
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open_date = trade.get('open_date', 'Unknown')
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open_rate = trade.get('open_rate', 0)
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profit_ratio = trade.get('profit_ratio', 0)
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# 检查是否有orders字段
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if 'orders' in trade:
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orders = trade['orders']
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# 筛选入场订单
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entry_orders = [order for order in orders if order.get('ft_is_entry', False)]
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# 按时间戳排序
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entry_orders.sort(key=lambda x: x.get('order_filled_timestamp', 0))
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# 统计加仓情况
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if len(entry_orders) > 1:
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trades_with_adjustments += 1
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base_price = entry_orders[0].get('safe_price', open_rate)
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for j in range(1, len(entry_orders)):
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current_order = entry_orders[j]
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current_price = current_order.get('safe_price', 0)
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if base_price > 0 and current_price > 0:
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# 计算降幅百分比
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price_drop_percent = ((base_price - current_price) / base_price) * 100
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# 保存结果
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results.append({
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'trade_index': i,
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'pair': pair,
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'open_date': open_date,
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'adjustment_number': j,
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'base_price': base_price,
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'current_price': current_price,
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'price_drop_percent': price_drop_percent,
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'open_rate': open_rate,
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'profit_ratio': profit_ratio
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})
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# 输出统计结果
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print(f"\n分析完成！")
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print(f"总交易数: {len(trades)}")
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print(f"包含加仓的交易数: {trades_with_adjustments}")
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print(f"总共分析到的加仓次数: {len(results)}")
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# 如果有结果，保存到CSV文件
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if results:
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df = pd.DataFrame(results)
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df.to_csv(export_file, index=False)
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print(f"\n加仓分析结果已保存到: {export_file}")
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# 显示统计信息
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print("\n加仓价格降幅统计:")
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print(f"平均降幅: {df['price_drop_percent'].mean():.2f}%")
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print(f"最大降幅: {df['price_drop_percent'].max():.2f}%")
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print(f"最小降幅: {df['price_drop_percent'].min():.2f}%")
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# 显示前10条记录
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print("\n前10条加仓记录:")
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print(df.head(10).to_string(index=False))
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else:
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print("\n未发现任何加仓记录")
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# 创建一个空的CSV文件，包含所有字段
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if not export_file.exists():
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empty_df = pd.DataFrame(columns=[
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'trade_index', 'pair', 'open_date', 'adjustment_number',
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'base_price', 'current_price', 'price_drop_percent',
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'open_rate', 'profit_ratio'
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])
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empty_df.to_csv(export_file, index=False)
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print(f"已创建空的结果文件: {export_file}") |