Simon
5bde8f9f5f
- ChartService qfq 基准改为该股最新因子（截至今天）归一：历史区间随最新除权 平移正确（v3 §20.5 Chart Display vs Execution basis 分离） - 显示口径与执行 basis 不一致时，成交/信号 marker 价格按当日因子换算到 K 线坐标系 （fill 早段价格在 qfq 下折算验证 100→50） - tests：qfq 回测 marker 折算 + selection 标记保留；全量 pytest 通过
222 lines
7.8 KiB
Python
222 lines
7.8 KiB
Python
"""Chart Service（v3 §20.1）—— 只聚合与坐标整理，不重算研究结果。
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- K 线/量/指标：基于主口径（adjust=none）行情，按请求 adjust 在**显示层**折算 qfq/hfq
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（绝不回写研究数据；研究执行仍用 price_adjustment 指定口径）
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- 标记：selections/signals 来自各自落库历史（by-symbol）；backtest fills 来自 Experiment
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内 BacktestResult 的 trades/positions
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- 口径纪律（v3 §20.5）：显示价 basis 与回测执行价 basis 分别记录；不一致时对 marker 做
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与 K 线相同的坐标换算，保证成交点贴图
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"""
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from __future__ import annotations
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from datetime import date
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from app.domain.entities.chart import (
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OHLC,
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ChartMetadata,
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ChartResult,
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EventMarker,
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SeriesPoint,
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VolumePoint,
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)
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from app.domain.entities.market import AdjustFactor, DailyBar, Stock
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from app.domain.entities.research import BacktestResult
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from app.domain.repositories.market import (
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AdjustFactorRepository,
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DailyBarRepository,
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StockRepository,
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)
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_MA_WINDOWS = (20, 60)
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def _main_bars(bars: list[DailyBar]) -> list[DailyBar]:
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"""仅取主口径行（adjust=none），丢弃新浪 qfq 兜底行 —— 显示层一律自 none 折算。"""
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return [b for b in bars if b.adjust == "none"]
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def _factor_multipliers(
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adj_repo: AdjustFactorRepository,
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symbol: str,
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start: date,
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end: date,
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mode: str,
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) -> dict[date, float]:
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"""返回 {trade_date: 显示折算系数}；mode=none → 空。
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基准（v3 §20.5）：qfq 以**该股最新因子**（截至今天，而非图表区间末）归一，
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保证历史区间随最新除权平移正确；hfq 直接用累积因子。
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"""
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if mode == "none":
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return {}
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factors: list[AdjustFactor] = adj_repo.get_range(symbol, date(1990, 1, 1), date.today())
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if not factors:
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return {}
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by_day = {f.trade_date: float(f.factor) for f in factors}
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latest = max(by_day.values())
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out: dict[date, float] = {}
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for day, f in by_day.items():
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out[day] = f / latest if mode == "qfq" else f
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return out
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class ChartService:
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def __init__(
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self,
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stock_repo: StockRepository,
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daily_repo: DailyBarRepository,
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adj_repo: AdjustFactorRepository,
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) -> None:
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self._stock_repo = stock_repo
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self._daily_repo = daily_repo
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self._adj_repo = adj_repo
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def stock(self, symbol: str) -> Stock | None:
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return self._stock_repo.get_by_symbol(symbol)
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def stock_chart(
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self,
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symbol: str,
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start: date,
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end: date,
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adjust: str = "none",
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execution_price_basis: str | None = None,
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extra_markers: list[EventMarker] | None = None,
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) -> ChartResult:
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"""基础个股 K 线图（可叠加 fills 等外部标记）。"""
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stock = self.stock(symbol)
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name = stock.name if stock else ""
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raw = _main_bars(self._daily_repo.get_range(symbol, start, end))
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mult = _factor_multipliers(self._adj_repo, symbol, start, end, adjust)
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bars: list[OHLC] = []
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volume: list[VolumePoint] = []
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for b in raw:
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m = mult.get(b.trade_date, 1.0)
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bars.append(
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OHLC(
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time=b.trade_date,
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open=_v(b.open, m),
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high=_v(b.high, m),
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low=_v(b.low, m),
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close=_v(b.close, m),
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)
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)
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volume.append(VolumePoint(time=b.trade_date, value=_v(b.volume, 1.0)))
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markers = _convert_markers(extra_markers or [], mult)
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indicators = _ma_indicators(bars)
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return ChartResult(
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metadata=ChartMetadata(
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symbol=symbol,
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name=name,
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adjust_mode=adjust,
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execution_price_basis=execution_price_basis,
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start=start,
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end=end,
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bar_count=len(bars),
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indicator_windows=list(_MA_WINDOWS),
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),
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bars=bars,
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volume=volume,
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indicators=indicators,
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fills=[m for m in markers if m.kind.startswith("fill_")],
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signals=[m for m in markers if m.kind.startswith("signal_")],
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selections=[m for m in markers if m.kind == "selection"],
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holding_periods=_holding_periods(bars),
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)
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# ---- 由已存历史构造标记（不重算） ----
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def backtest_stock_chart(
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self,
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result: BacktestResult,
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symbol: str,
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start: date,
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end: date,
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adjust: str = "none",
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) -> ChartResult:
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"""回测个股视图：K 线 + 选股意图/未成交信号/实际成交三类标记（v3 §20.3）。"""
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basis = (result.config_snapshot or {}).get("price_adjustment", "none")
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markers = _result_to_markers(result, symbol)
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return self.stock_chart(symbol, start, end, adjust, execution_price_basis=basis,
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extra_markers=markers)
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def _result_to_markers(result: BacktestResult, symbol: str) -> list[EventMarker]:
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"""由回测 history 生成个股标记：fills（成交）/ signals（未成交意图）/ selections（选股）。"""
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markers: list[EventMarker] = []
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# 实际成交（fills）与未成交信号（signal_history 中 filled=False）
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for a in result.signal_history:
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if a.symbol != symbol:
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continue
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if a.filled:
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kind = "fill_buy" if a.signal == "BUY" else "fill_sell"
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text = [f"{'买入' if a.signal=='BUY' else '卖出'} @ {a.price:.2f}（basis={_basis_of(result)}）"]
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markers.append(
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EventMarker(time=a.date, kind=kind, symbol=symbol, price=a.price, text=text)
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)
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else:
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kind = "signal_buy" if a.signal == "BUY" else "signal_sell"
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text = [a.reject_reason or f"{a.signal} 未成交"]
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markers.append(EventMarker(time=a.date, kind=kind, symbol=symbol, price=a.price, text=text))
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# 选股意图（selection_history 中该 symbol 的命中）
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for pk in result.selection_history:
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if pk.symbol != symbol:
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continue
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markers.append(
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EventMarker(
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time=pk.date,
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kind="selection",
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symbol=symbol,
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score=pk.score,
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text=[f"选股意图 rank #{pk.rank}"],
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)
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)
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return markers
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def _basis_of(result: BacktestResult) -> str:
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return (result.config_snapshot or {}).get("price_adjustment", "none")
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def _convert_markers(markers: list[EventMarker], mult: dict[date, float]) -> list[EventMarker]:
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"""显示口径与执行价 basis 不一致时，把 marker 价格折算到 K 线坐标系（v3 §20.5）。"""
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out: list[EventMarker] = []
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for m in markers:
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if m.price is not None and mult:
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k = mult.get(m.time)
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if k is not None:
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m = m.model_copy(update={"price": round(m.price * k, 4)})
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out.append(m)
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return out
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def _holding_periods(bars: list[OHLC]) -> list[dict]:
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"""v1 空实现占位（持仓区间渲染 v3 §20.4 后续细化）。"""
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return []
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def _ma_indicators(bars: list[OHLC]) -> dict[str, list[SeriesPoint]]:
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import statistics
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closes = [b.close for b in bars]
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out: dict[str, list[SeriesPoint]] = {}
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for w in _MA_WINDOWS:
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series: list[SeriesPoint] = []
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for i, b in enumerate(bars):
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if i + 1 < w:
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continue
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window = closes[i + 1 - w : i + 1]
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if all(v is not None for v in window):
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series.append(SeriesPoint(time=b.time, value=round(statistics.fmean(window), 4)))
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out[f"ma{w}"] = series
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return out
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def _v(v, m: float) -> float | None:
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if v is None:
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return None
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f = float(v)
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return round(f * m, 4)
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