"""单元测试：组合级 Walk-Forward 引擎（PortfolioWalkForwardEngine，v1.31）。""" from __future__ import annotations import json from typing import Any import numpy as np import pandas as pd from easy_tdx.backtest.portfolio_engine import StockData from easy_tdx.backtest.strategy import Strategy from easy_tdx.backtest.walkforward import PortfolioWalkForwardEngine class PeriodicStrategy(Strategy): """每 10 根切换一次持仓，保证窗口内有成交（与单标的 WF 测试同思路）。""" def init(self) -> None: self._holding = False def next(self) -> None: if self._bar_index % 10 == 0 and not self._holding: self.buy(size=0) self._holding = True elif self._bar_index % 10 == 5 and self._holding: self.sell(size=0) self._holding = False def _make_df(n: int = 400, seed: int = 42, start: str = "2023-01-01") -> pd.DataFrame: rng = np.random.default_rng(seed) close = 100.0 + np.cumsum(rng.normal(0, 1, n)) high = close + rng.uniform(0, 1, n) low = close - rng.uniform(0, 1, n) open_ = low + rng.uniform(0, high - low, n) vol = rng.integers(1_000_000, 10_000_000, n).astype(float) return pd.DataFrame( { "datetime": pd.date_range(start, periods=n, freq="D"), "open": open_, "high": high, "low": low, "close": close, "vol": vol, "amount": vol * close, } ) def _stocks() -> list[StockData]: return [ StockData("000001", "SZ", _make_df(400, seed=42)), StockData("600000", "SH", _make_df(400, seed=99)), ] class TestPortfolioWalkForward: def test_basic_structure(self) -> None: """切窗数量、窗口字段与聚合指标齐全。""" wf = PortfolioWalkForwardEngine( strategy=PeriodicStrategy, stocks=_stocks(), n_windows=4, total_cash=200_000 ).run() assert len(wf.windows) == 4 for i, w in enumerate(wf.windows): assert w.index == i assert w.start <= w.end assert w.bars > 0 # 窗口时间升序且不重叠 starts = [pd.Timestamp(w.start) for w in wf.windows] assert starts == sorted(starts) assert wf.total_trades > 0 def test_aggregates_consistency_and_chained(self) -> None: """consistency = 盈利窗占比，chained = 各窗连乘 - 1。""" wf = PortfolioWalkForwardEngine( strategy=PeriodicStrategy, stocks=_stocks(), n_windows=5 ).run() rets = [w.total_return for w in wf.windows] assert wf.consistency == sum(1 for r in rets if r > 0) / len(rets) chained = float(np.prod([1.0 + r for r in rets]) - 1.0) assert wf.chained_return == pd.Series([chained]).iloc[0] def test_insufficient_data_returns_empty(self) -> None: """数据不足以切窗时返回空结果（windows 为空、聚合指标为 0）。""" stocks = [StockData("000001", "SZ", _make_df(50, seed=1))] wf = PortfolioWalkForwardEngine(strategy=PeriodicStrategy, stocks=stocks, n_windows=7).run() assert wf.windows == [] assert wf.consistency == 0.0 def test_empty_stocks_returns_empty(self) -> None: wf = PortfolioWalkForwardEngine(strategy=PeriodicStrategy, stocks=[], n_windows=3).run() assert wf.windows == [] def test_late_listing_stock_tolerated(self) -> None: """晚上市的标的不该拖垮整窗（该窗跳过它，其余照常）。""" stocks = [ StockData("000001", "SZ", _make_df(400, seed=42)), StockData("688981", "SH", _make_df(100, seed=7, start="2024-02-01")), ] wf = PortfolioWalkForwardEngine(strategy=PeriodicStrategy, stocks=stocks, n_windows=4).run() assert len(wf.windows) == 4 assert all(w.total_trades > 0 for w in wf.windows) def test_window_independent_opening(self) -> None: """每窗独立开仓：窗口总交易数应等于窗内各标的回合数（无跨窗结转）。""" stocks = _stocks() n_windows = 4 wf = PortfolioWalkForwardEngine( strategy=PeriodicStrategy, stocks=stocks, n_windows=n_windows ).run() # PeriodicStrategy 每 10 根一个回合，窗长约 56 根 → 每标的每窗 5 回合上下， # 总交易数应为正且与窗口长度量级一致（防止持仓跨窗导致的重复/丢失计数）。 assert wf.total_trades > 0 assert wf.total_trades == sum(w.total_trades for w in wf.windows) def test_to_dict_serializable(self) -> None: wf = PortfolioWalkForwardEngine( strategy=PeriodicStrategy, stocks=_stocks(), n_windows=3 ).run() d = wf.to_dict() assert len(d["windows"]) == len(wf.windows) # JSON 兼容（numpy 标量已清洗） json.dumps(d) # 每窗 performance 为完整指标 dict（含 SQN 等深度指标） assert "sqn" in d["windows"][0]["performance"] assert "max_consecutive_wins" in d["windows"][0]["performance"] def test_min_windows_guard(self) -> None: """n_windows < 2 至少取 2（与单标的 WF 同保护）。""" wf = PortfolioWalkForwardEngine( strategy=PeriodicStrategy, stocks=_stocks(), n_windows=0 ).run() assert wf.n_windows == 2 # ── MultiStrategyWalkForwardEngine（v1.31.1：多策略组合槽位 WF）─────────────── def _slots() -> list[Any]: from easy_tdx.backtest.multi_strategy_engine import StrategySlot return [ StrategySlot( label="双均线交叉", symbol="SH:601088", strategy=PeriodicStrategy(), df=_make_df(400, seed=42), ), StrategySlot( label="RSI反转", symbol="SZ:000001", strategy=PeriodicStrategy(), df=_make_df(400, seed=99), ), ] def test_multi_strategy_wf_basic_structure() -> None: from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine wf = MultiStrategyWalkForwardEngine(strategies=_slots(), n_windows=4, total_cash=200_000).run() assert len(wf.windows) == 4 assert wf.total_trades > 0 assert wf.total_trades == sum(w.total_trades for w in wf.windows) # 窗口时间升序 starts = [pd.Timestamp(w.start) for w in wf.windows] assert starts == sorted(starts) def test_multi_strategy_wf_matches_portfolio_structure() -> None: """与 PortfolioWalkForwardEngine 输出同构（前端面板可复用）。""" from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine wf = MultiStrategyWalkForwardEngine(strategies=_slots(), n_windows=3).run() d = wf.to_dict() json.dumps(d) assert "sqn" in d["windows"][0]["performance"] assert "max_consecutive_wins" in d["windows"][0]["performance"] def test_multi_strategy_wf_empty_slots() -> None: from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine wf = MultiStrategyWalkForwardEngine(strategies=[], n_windows=3).run() assert wf.windows == [] def test_combo_slot_failure_logs_warning(caplog): """单槽位回测异常记 warning（含槽位标识），不拖垮整窗（旧码静默 continue）。""" import logging from easy_tdx.backtest.multi_strategy_engine import StrategySlot from easy_tdx.backtest.walkforward import MultiStrategyWalkForwardEngine class Boom(Strategy): def init(self) -> None: raise RuntimeError("slot-boom") def next(self) -> None: pass slots = [ StrategySlot( label="正常", symbol="SH:601088", strategy=PeriodicStrategy(), df=_make_df(400, seed=42) ), StrategySlot(label="炸裂", symbol="SZ:000001", strategy=Boom(), df=_make_df(400, seed=99)), ] with caplog.at_level(logging.WARNING, logger="easy_tdx.backtest.walkforward"): wf = MultiStrategyWalkForwardEngine(strategies=slots, n_windows=3).run() assert len(wf.windows) == 3 # 正常槽位照常出窗 assert wf.total_trades > 0 assert any("炸裂" in r.getMessage() for r in caplog.records if r.levelno >= logging.WARNING)