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shy3130
ef59df4a67
后端: - #225 自定义源分钟K字符串 datetime 不再被 cast 成 null: _normalize_minute 对 Utf8 列按常见格式链式解析 (参照 kline_sync 口径) - #226 自定义源日K/除权因子单批失败只隔离该批 (重试 1 次 + 跳过 + warning 汇总), 不再丢弃已成功批次的全部进度 - #201 旧信号回测 _load_panel 加指标 warmup 窗口 (120 交易日保守日历日), 计算后裁回 [start,end]; 数据不足时自然退化 前端: - #188 因子回测单标的不再整面板空白: 外层条件改 !error, IC 卡片 单独守卫并给出需 >=2 只的提示 - #200 因子回测支持调仓频率 (日/周/月) 与滑点 (bp) 配置 - #196 自选页板块筛选新增 ETF 分类, 旧偏好加载时补 ETF 键保持默认可见
67 lines
2.3 KiB
Python
67 lines
2.3 KiB
Python
"""#201 回归: 旧信号回测的 _load_panel 必须带指标 warmup 窗口。
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直接按 [start,end] 过滤后 compute_all, 区间头部的 MA/MACD/RSI 会因缺
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历史窗口而失真 (回测起始段信号不可信)。
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"""
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from __future__ import annotations
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from datetime import date, timedelta
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from unittest.mock import MagicMock
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import polars as pl
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from app.services.backtest import BacktestService
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def _synthetic_enriched(n_days: int) -> pl.DataFrame:
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base = date(2026, 1, 1)
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days = [base + timedelta(days=i) for i in range(n_days)]
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n = len(days)
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closes = [10.0 + (i % 7) * 0.3 + i * 0.01 for i in range(n)]
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return pl.DataFrame(
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{
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"symbol": ["600000.SH"] * n,
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"date": days,
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"open": [c - 0.05 for c in closes],
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"high": [c + 0.1 for c in closes],
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"low": [c - 0.1 for c in closes],
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"close": closes,
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"volume": [10000.0] * n,
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"amount": [c * 10000.0 for c in closes],
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"raw_close": closes,
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"raw_high": [c + 0.1 for c in closes],
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"raw_low": [c - 0.1 for c in closes],
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}
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)
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def test_load_panel_warms_up_indicators(monkeypatch) -> None:
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df = _synthetic_enriched(250)
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monkeypatch.setattr(
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"app.services.backtest.scan_enriched_parquet", lambda glob: df.lazy()
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)
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svc = BacktestService(repo=MagicMock())
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start = df["date"][-30]
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end = df["date"][-1]
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panel = svc._load_panel(["600000.SH"], start, end)
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# warmup 行不进入结果面板 (pandas datetime64 与 date 直接比较会类型不符)
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assert str(panel["date"].min())[:10] == start.isoformat()
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assert str(panel["date"].max())[:10] == end.isoformat()
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# 区间首日的指标已有历史窗口可用, 不再是 NaN
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first = panel.iloc[0]
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assert first["rsi_14"] == first["rsi_14"] # NaN != NaN
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def test_load_panel_insufficient_history_degrades_gracefully(monkeypatch) -> None:
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# 数据起点晚于 warmup 起点时自然退化: 有多少算多少, 不抛异常
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df = _synthetic_enriched(20)
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monkeypatch.setattr(
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"app.services.backtest.scan_enriched_parquet", lambda glob: df.lazy()
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)
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svc = BacktestService(repo=MagicMock())
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panel = svc._load_panel(["600000.SH"], df["date"][0], df["date"][-1])
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assert len(panel) == 20
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