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shy3130
697c27bb02
- 市场环境: 新增情绪周期6阶段(冰点/启动/主升/高潮/退潮/修复, 连板梯队驱动, EMA平滑+2日确认+弱档否决, 平均段长9.7天)与概念/行业主线排名(涨停梯队聚合, 可配置宽基/风格标签过滤); 市场环境页重构, regime 透明加列, 与5档state并存 - 挖掘: 因子与策略挖掘全链路(API/worker/进程锁/候选库/前端工作台/文档), 周度调度默认关闭且永不自动发布 - 回测: 财务快照因子(点时口径), 批量回测预计算共享下期收益, 信号路径矩阵列依赖展开修复(consecutive_limit_ups 缺列报错) - 数据/性能: enriched 生成与预热治理, 重任务限流, 行情/K线缓存复用, 时区修复 - 测试: 后端全量 914 通过; GUI 黑盒验证截图存证 gui-test-screenshots/
66 lines
2.3 KiB
Python
66 lines
2.3 KiB
Python
"""每日信号路径的字段依赖展开回归测试。
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挖掘发布的 FactorRankResearchMatrixStrategy 把因子权重放在类级 SCORING,
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META["scoring"] 为空。每日信号/实时矩阵路径通过 _matrix_field_columns 决定
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矩阵字段, 必须展开 required_fields_for_params 的虚拟因子依赖
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(limit_up_count_* -> consecutive_limit_ups), 否则 compute_signals 抛
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"MarketDataMatrix missing field: consecutive_limit_ups"。
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"""
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from __future__ import annotations
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import types
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from datetime import date, timedelta
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import polars as pl
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from app.backtest.matrix import build_market_data_matrix
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from app.strategy.builtin.factor_rank_research import FactorRankResearchMatrixStrategy
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from app.strategy.engine import StrategyEngine
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def _mined_limit_up_strategy() -> types.SimpleNamespace:
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strategy = FactorRankResearchMatrixStrategy(
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{"amplitude": 2.0, "limit_up_count_60d": 1.0},
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{"amplitude": "low", "limit_up_count_60d": "low"},
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)
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return types.SimpleNamespace(
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matrix_strategy=strategy,
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basic_filter=None,
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meta={"scoring": {}},
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)
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def test_matrix_field_columns_expand_parameter_scoring_dependencies():
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strategy = _mined_limit_up_strategy()
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fields = StrategyEngine._matrix_field_columns(strategy, None, {})
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assert "consecutive_limit_ups" in fields
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assert "amplitude" in fields
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def test_mined_limit_up_strategy_signals_build_from_panel_fields():
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rows = []
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start = date(2024, 1, 1)
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for offset in range(80):
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close = 10.0 + offset * 0.04
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rows.append({
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"symbol": "000001.SZ",
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"date": start + timedelta(days=offset),
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"open": close - 0.05,
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"high": close + 0.15,
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"low": close - 0.15,
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"close": close,
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"volume": 1000.0 + offset * 5.0,
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"amount": 100000.0,
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"amplitude": 1.5,
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"turnover_rate": 5.0,
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"consecutive_limit_ups": (offset % 17) + 1 if offset % 17 == 0 else 0,
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})
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panel = pl.DataFrame(rows)
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strategy = _mined_limit_up_strategy()
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market = build_market_data_matrix(
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panel,
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field_columns=StrategyEngine._matrix_field_columns(strategy, None, {}),
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)
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signals = strategy.matrix_strategy.compute_signals(market, {})
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assert signals.shape == market.shape
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