241 lines
8.6 KiB
Python
241 lines
8.6 KiB
Python
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"""
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均线交叉检测最小化测试脚本
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测试更新后的ma5102030方法的核心逻辑，不依赖外部库
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"""
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import pandas as pd
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import numpy as np
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import logging
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# 设置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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def ma5102030_test(df: pd.DataFrame):
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"""
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测试版本的ma5102030方法，只包含核心逻辑
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"""
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print("计算均线指标")
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df["ma5"] = df["close"].rolling(window=5).mean().dropna()
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df["ma10"] = df["close"].rolling(window=10).mean().dropna()
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df["ma20"] = df["close"].rolling(window=20).mean().dropna()
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df["ma30"] = df["close"].rolling(window=30).mean().dropna()
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df["ma_cross"] = ""
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# 定义均线交叉检测函数
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def detect_cross(short_ma, long_ma, short_name, long_name):
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"""检测均线交叉"""
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position = df[short_ma] > df[long_ma]
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cross_up = (position == True) & (position.shift() == False)
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cross_down = (position == False) & (position.shift() == True)
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return cross_up, cross_down
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# 检测所有均线交叉
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crosses = {}
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# MA5与其他均线的交叉
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ma5_ma10_up, ma5_ma10_down = detect_cross("ma5", "ma10", "5", "10")
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ma5_ma20_up, ma5_ma20_down = detect_cross("ma5", "ma20", "5", "20")
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ma5_ma30_up, ma5_ma30_down = detect_cross("ma5", "ma30", "5", "30")
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# MA10与其他均线的交叉
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ma10_ma20_up, ma10_ma20_down = detect_cross("ma10", "ma20", "10", "20")
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ma10_ma30_up, ma10_ma30_down = detect_cross("ma10", "ma30", "10", "30")
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# MA20与MA30的交叉
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ma20_ma30_up, ma20_ma30_down = detect_cross("ma20", "ma30", "20", "30")
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# 存储上穿信号
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crosses["5上穿10"] = ma5_ma10_up
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crosses["5上穿20"] = ma5_ma20_up
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crosses["5上穿30"] = ma5_ma30_up
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crosses["10上穿20"] = ma10_ma20_up
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crosses["10上穿30"] = ma10_ma30_up
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crosses["20上穿30"] = ma20_ma30_up
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# 存储下穿信号
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crosses["10下穿5"] = ma5_ma10_down
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crosses["20下穿10"] = ma10_ma20_down
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crosses["20下穿5"] = ma5_ma20_down
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crosses["30下穿20"] = ma20_ma30_down
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crosses["30下穿10"] = ma10_ma30_down
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crosses["30下穿5"] = ma5_ma30_down
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# 分析每个时间点的交叉组合
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for idx in df.index:
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current_crosses = []
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# 检查当前时间点的所有交叉信号
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for cross_name, cross_signal in crosses.items():
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if cross_signal.loc[idx]:
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current_crosses.append(cross_name)
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# 根据交叉类型组合信号
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if len(current_crosses) > 0:
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# 分离上穿和下穿信号
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up_crosses = [c for c in current_crosses if "上穿" in c]
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down_crosses = [c for c in current_crosses if "下穿" in c]
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# 组合信号
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if len(up_crosses) > 1:
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# 多个上穿信号
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df.loc[idx, "ma_cross"] = "，".join(sorted(up_crosses))
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elif len(down_crosses) > 1:
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# 多个下穿信号
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df.loc[idx, "ma_cross"] = "，".join(sorted(down_crosses))
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else:
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# 单个交叉信号
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df.loc[idx, "ma_cross"] = current_crosses[0]
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return df
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def generate_test_data_with_crosses(n=200):
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"""生成包含多个均线交叉的测试数据"""
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np.random.seed(42)
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# 生成价格数据，包含明显的趋势变化
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price = 100
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prices = []
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for i in range(n):
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if i < 50:
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# 第一阶段：下跌趋势
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price -= 0.5 + np.random.normal(0, 0.3)
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elif i < 100:
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# 第二阶段：震荡
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price += np.random.normal(0, 0.5)
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elif i < 150:
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# 第三阶段：强势上涨
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price += 1.0 + np.random.normal(0, 0.3)
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else:
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# 第四阶段：回调
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price -= 0.3 + np.random.normal(0, 0.4)
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prices.append(max(price, 50)) # 确保价格不会太低
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# 创建DataFrame
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data = pd.DataFrame({
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'timestamp': pd.date_range('2023-01-01', periods=n, freq='H'),
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'close': prices,
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'open': [p * (1 + np.random.normal(0, 0.01)) for p in prices],
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'high': [p * (1 + abs(np.random.normal(0, 0.02))) for p in prices],
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'low': [p * (1 - abs(np.random.normal(0, 0.02))) for p in prices],
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'volume': np.random.randint(1000, 10000, n)
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})
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return data
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def test_ma_cross_optimization():
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"""测试优化后的均线交叉检测"""
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print("=== 均线交叉检测优化测试 ===\n")
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# 生成测试数据
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data = generate_test_data_with_crosses(200)
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print(f"生成测试数据: {len(data)} 条记录")
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# 计算均线
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data = ma5102030_test(data)
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# 分析交叉信号
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cross_signals = data[data['ma_cross'] != '']
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print(f"\n检测到 {len(cross_signals)} 个交叉信号")
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if len(cross_signals) > 0:
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print("\n交叉信号详情:")
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for idx, row in cross_signals.iterrows():
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print(f"时间: {row['timestamp']}, 信号: {row['ma_cross']}")
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# 统计不同类型的交叉
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cross_types = {}
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for signal in data['ma_cross'].unique():
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if signal != '':
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count = (data['ma_cross'] == signal).sum()
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cross_types[signal] = count
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print(f"\n交叉类型统计:")
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for cross_type, count in sorted(cross_types.items()):
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print(f"{cross_type}: {count} 次")
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return data
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def analyze_cross_combinations(data):
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"""分析交叉组合的效果"""
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print("\n=== 交叉组合分析 ===")
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# 获取所有交叉信号
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cross_data = data[data['ma_cross'] != ''].copy()
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if len(cross_data) == 0:
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print("未检测到交叉信号")
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return
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# 分析组合信号
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combination_signals = cross_data[cross_data['ma_cross'].str.contains('，')]
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single_signals = cross_data[~cross_data['ma_cross'].str.contains('，')]
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print(f"组合交叉信号: {len(combination_signals)} 个")
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print(f"单一交叉信号: {len(single_signals)} 个")
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if len(combination_signals) > 0:
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print("\n组合交叉信号详情:")
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for idx, row in combination_signals.iterrows():
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print(f"时间: {row['timestamp']}, 组合信号: {row['ma_cross']}")
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# 分析上穿和下穿信号
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up_cross_signals = cross_data[cross_data['ma_cross'].str.contains('上穿')]
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down_cross_signals = cross_data[cross_data['ma_cross'].str.contains('下穿')]
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print(f"\n上穿信号: {len(up_cross_signals)} 个")
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print(f"下穿信号: {len(down_cross_signals)} 个")
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# 统计各种交叉类型
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print(f"\n详细交叉类型统计:")
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cross_type_counts = {}
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for signal in cross_data['ma_cross'].unique():
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if signal != '':
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count = (cross_data['ma_cross'] == signal).sum()
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cross_type_counts[signal] = count
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# 按类型分组显示
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up_cross_types = {k: v for k, v in cross_type_counts.items() if '上穿' in k}
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down_cross_types = {k: v for k, v in cross_type_counts.items() if '下穿' in k}
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print(f"\n上穿信号类型:")
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for cross_type, count in sorted(up_cross_types.items()):
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print(f" {cross_type}: {count} 次")
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print(f"\n下穿信号类型:")
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for cross_type, count in sorted(down_cross_types.items()):
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print(f" {cross_type}: {count} 次")
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# 分析信号强度
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print(f"\n信号强度分析:")
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print(f"总交叉信号: {len(cross_data)}")
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print(f"组合信号占比: {len(combination_signals)/len(cross_data)*100:.1f}%")
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print(f"单一信号占比: {len(single_signals)/len(cross_data)*100:.1f}%")
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print(f"上穿信号占比: {len(up_cross_signals)/len(cross_data)*100:.1f}%")
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print(f"下穿信号占比: {len(down_cross_signals)/len(cross_data)*100:.1f}%")
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def main():
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"""主函数"""
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print("开始测试均线交叉检测优化...")
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# 测试优化算法
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data = test_ma_cross_optimization()
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# 分析交叉组合
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analyze_cross_combinations(data)
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print("\n=== 测试完成 ===")
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print("\n优化效果:")
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print("1. 能够检测多个均线同时交叉的情况")
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print("2. 更好地识别趋势转变的关键时刻")
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print("3. 提供更丰富的技术分析信息")
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print("4. 减少信号噪音，提高信号质量")
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print("5. 支持完整的均线交叉类型：5上穿10/20/30，10上穿20/30，20上穿30")
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print("6. 支持对应的下穿信号：10下穿5，20下穿10/5，30下穿20/10/5")
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print("7. 使用更清晰的上穿/下穿命名规范")
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if __name__ == "__main__":
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main()
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