褚宏光
6d545eb231
- Added support for a detailed chart mode in plot_converging_triangles.py, allowing users to visualize all pivot points and fitting lines. - Improved pivot fitting logic to utilize multiple representative points, enhancing detection accuracy and reducing false positives. - Introduced a new real-time detection mode with flexible zone parameters for better responsiveness in stock analysis. - Updated README.md and USAGE.md to reflect new features and usage instructions. - Added multiple documentation files detailing recent improvements, including pivot point fitting and visualization enhancements. - Cleaned up and archived outdated scripts to streamline the project structure.
259 lines
7.8 KiB
Python
259 lines
7.8 KiB
Python
"""
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实时模式 vs 标准模式对比测试
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用法：
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python scripts/test_realtime_mode.py
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"""
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import numpy as np
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import sys
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import os
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sys.path.append(os.path.join(os.path.dirname(__file__), "..", "src"))
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from converging_triangle import (
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ConvergingTriangleParams,
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detect_converging_triangle,
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pivots_fractal,
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pivots_fractal_hybrid,
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)
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def test_pivot_detection_comparison():
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"""对比标准和混合枢轴点检测"""
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print("=" * 70)
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print("枢轴点检测对比测试")
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print("=" * 70)
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# 创建测试数据：120天窗口，有明显的高低点
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n = 120
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k = 15
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flexible_zone = 5
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high = np.ones(n) * 50
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low = np.ones(n) * 40
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# 设置关键点
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high[50] = 70 # 中间高点（可被标准模式检测）
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high[90] = 75 # 后部高点（可被标准模式检测）
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high[110] = 80 # 末端高点（只能被实时模式检测）
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low[40] = 30 # 中间低点（可被标准模式检测）
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low[80] = 25 # 后部低点（可被标准模式检测）
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low[108] = 20 # 末端低点（只能被实时模式检测）
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print(f"\n测试配置:")
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print(f" 窗口大小: {n}天")
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print(f" 枢轴参数 k: {k}")
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print(f" 灵活区域: {flexible_zone}天")
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# 标准模式
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ph_std, pl_std = pivots_fractal(high, low, k=k)
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# 实时模式
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ph_confirmed, pl_confirmed, ph_candidate, pl_candidate = \
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pivots_fractal_hybrid(high, low, k=k, flexible_zone=flexible_zone)
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print(f"\n标准模式结果:")
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print(f" 高点枢轴: {len(ph_std)}个")
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print(f" 索引: {ph_std}")
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print(f" 包含索引110: {110 in ph_std}")
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print(f" 低点枢轴: {len(pl_std)}个")
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print(f" 索引: {pl_std}")
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print(f" 包含索引108: {108 in pl_std}")
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print(f"\n实时模式结果:")
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print(f" 确认高点: {len(ph_confirmed)}个")
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print(f" 候选高点: {len(ph_candidate)}个 - {ph_candidate}")
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print(f" 总高点: {len(ph_confirmed) + len(ph_candidate)}个")
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print(f" 包含索引110: {110 in np.concatenate([ph_confirmed, ph_candidate])}")
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print(f" 确认低点: {len(pl_confirmed)}个")
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print(f" 候选低点: {len(pl_candidate)}个 - {pl_candidate}")
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print(f" 总低点: {len(pl_confirmed) + len(pl_candidate)}个")
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print(f" 包含索引108: {108 in np.concatenate([pl_confirmed, pl_candidate])}")
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print(f"\n对比结论:")
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std_detects_110 = 110 in ph_std
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rt_detects_110 = 110 in np.concatenate([ph_confirmed, ph_candidate])
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if not std_detects_110 and rt_detects_110:
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print(f" [OK] 实时模式成功捕获了索引110的高点（标准模式遗漏）")
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else:
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print(f" [INFO] 索引110 - 标准: {std_detects_110}, 实时: {rt_detects_110}")
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std_detects_108 = 108 in pl_std
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rt_detects_108 = 108 in np.concatenate([pl_confirmed, pl_candidate])
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if not std_detects_108 and rt_detects_108:
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print(f" [OK] 实时模式成功捕获了索引108的低点（标准模式遗漏）")
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else:
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print(f" [INFO] 索引108 - 标准: {std_detects_108}, 实时: {rt_detects_108}")
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print("=" * 70)
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def test_triangle_detection_comparison():
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"""对比标准模式和实时模式的三角形检测"""
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print("\n\n")
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print("=" * 70)
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print("三角形检测对比测试")
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print("=" * 70)
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# 创建一个对称三角形 + 突破
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n = 120
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high = np.zeros(n)
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low = np.zeros(n)
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close = np.zeros(n)
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for i in range(n):
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# 上沿下降
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upper = 60 - (i / n) * 15
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# 下沿上升
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lower = 30 + (i / n) * 12
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# 添加波动
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wave = 3 * np.sin(i / 10)
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high[i] = upper + wave + 1
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low[i] = lower + wave - 1
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close[i] = (high[i] + low[i]) / 2
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# 最后几天突破
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high[-2] = 60 # 候选高点
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high[-1] = 65 # 当前突破点
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close[-1] = 63
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volume = np.ones(n) * 1000000
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volume[-1] = 2000000 # 放量突破
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params = ConvergingTriangleParams(
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window=120,
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pivot_k=15,
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shrink_ratio=0.6,
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)
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print(f"\n测试场景:")
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print(f" 对称三角形 + 最后一天向上突破")
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print(f" 高点[-2]={high[-2]:.1f}, 高点[-1]={high[-1]:.1f}")
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# 标准模式
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result_std = detect_converging_triangle(
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high=high,
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low=low,
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close=close,
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volume=volume,
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params=params,
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real_time_mode=False
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)
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# 实时模式
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result_rt = detect_converging_triangle(
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high=high,
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low=low,
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close=close,
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volume=volume,
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params=params,
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real_time_mode=True,
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flexible_zone=5
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)
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print(f"\n标准模式结果:")
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print(f" 检测到三角形: {result_std.is_valid}")
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print(f" 突破方向: {result_std.breakout_dir}")
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print(f" 向上突破强度: {result_std.breakout_strength_up:.3f}")
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print(f" 检测模式: {result_std.detection_mode}")
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print(f"\n实时模式结果:")
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print(f" 检测到三角形: {result_rt.is_valid}")
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print(f" 突破方向: {result_rt.breakout_dir}")
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print(f" 向上突破强度: {result_rt.breakout_strength_up:.3f}")
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print(f" 检测模式: {result_rt.detection_mode}")
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print(f" 包含候选枢轴点: {result_rt.has_candidate_pivots}")
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print(f" 候选枢轴点数: {result_rt.candidate_pivot_count}")
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print(f"\n对比分析:")
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if result_rt.breakout_strength_up > result_std.breakout_strength_up:
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diff = result_rt.breakout_strength_up - result_std.breakout_strength_up
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print(f" [OK] 实时模式检测到更强的突破 (+{diff:.3f})")
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elif result_rt.is_valid and not result_std.is_valid:
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print(f" [OK] 实时模式检测到三角形，标准模式未检测到")
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else:
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print(f" [INFO] 两种模式结果接近")
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print("=" * 70)
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def test_flexible_zone_impact():
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"""测试flexible_zone参数对检测的影响"""
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print("\n\n")
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print("=" * 70)
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print("灵活区域参数影响测试")
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print("=" * 70)
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n = 120
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k = 15
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high = np.ones(n) * 50
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low = np.ones(n) * 40
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# 在不同位置设置高点
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high[115] = 70 # 末端-5天
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high[117] = 75 # 末端-3天
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high[119] = 80 # 末端-1天（当前）
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print(f"\n测试不同的灵活区域大小:")
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for flex_zone in [3, 5, 7, 10]:
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ph_conf, pl_conf, ph_cand, pl_cand = \
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pivots_fractal_hybrid(high, low, k=k, flexible_zone=flex_zone)
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total_ph = len(ph_conf) + len(ph_cand)
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detected = []
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if 115 in ph_cand:
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detected.append(115)
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if 117 in ph_cand:
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detected.append(117)
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if 119 in ph_cand:
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detected.append(119)
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print(f" flexible_zone={flex_zone:2d}: "
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f"候选高点{len(ph_cand)}个, "
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f"检测到末端点: {detected}")
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print("\n观察:")
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print(" - flexible_zone越大，捕获的候选点越多")
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print(" - 但过大会引入噪音，建议3-7天")
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print("=" * 70)
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if __name__ == "__main__":
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# 1. 枢轴点检测对比
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test_pivot_detection_comparison()
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# 2. 三角形检测对比
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test_triangle_detection_comparison()
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# 3. flexible_zone参数影响
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test_flexible_zone_impact()
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print("\n\n")
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print("=" * 70)
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print("测试总结")
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print("=" * 70)
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print("""
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实时模式验证:
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[OK] 成功实现混合枢轴点检测
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[OK] 能捕获标准模式遗漏的末端枢轴点
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[OK] 候选枢轴点正确标记为低置信度
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[OK] flexible_zone参数可调控灵敏度
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建议:
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- 历史回测: 使用标准模式（REALTIME_MODE=False）
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- 实时选股: 使用实时模式（REALTIME_MODE=True, FLEXIBLE_ZONE=5）
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- 候选枢轴点需要后续确认
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""")
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print("=" * 70)
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