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fix(backtest): _find_bar_index 用 to_numpy().argmax() 取真实位置
idxmax() 返回 index label,后续 iloc[] 按位置取行;当 df.index 非默认 RangeIndex 时 label != position,撮合会取错 K 线。两处分支统一改为位置索引。 新增 2 例非连续 index 回归测试。
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@@ -144,19 +144,22 @@ class OrderSimulator:
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dt_col = self.df["datetime"]
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# 尝试直接比较(如果是 int 类型)
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# 注意:用 to_numpy().argmax() 取位置索引,而非 idxmax()(返回 label),
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# 因为后续 self.df.iloc[...] 按位置取行;若 df.index 非默认 RangeIndex,
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# label != position 会导致撮合取错 bar。
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try:
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idx = (dt_col == datetime_val).idxmax() if (dt_col == datetime_val).any() else None
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if idx is not None:
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return int(idx)
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mask = (dt_col == datetime_val).to_numpy()
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if mask.any():
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return int(mask.argmax())
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except (TypeError, ValueError):
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pass
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# 如果是 datetime 对象,转为 int 比较
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if pd.api.types.is_datetime64_any_dtype(dt_col):
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dt_ints = dt_col.dt.strftime("%Y%m%d").astype(int)
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mask = dt_ints == datetime_val
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if mask.any():
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return int(mask.idxmax())
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mask_arr = (dt_ints == datetime_val).to_numpy()
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if mask_arr.any():
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return int(mask_arr.argmax())
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return None
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return None
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@@ -464,3 +464,41 @@ class TestSlippageModelIntegration:
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trades = sim.simulate(signals, cash=20000, position=0)
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assert len(trades) == 1
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assert trades[0].slippage == pytest.approx(5.0)
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# ── Test Non-Continuous Index ─────────────────────────────────────────────────
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class TestNonContinuousIndex:
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"""df.index 非默认 RangeIndex 时,撮合应按位置(iloc)而非 label 取 bar。
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回归 _find_bar_index 旧实现在非连续 index 下用 idxmax() 返回 label 当位置用,
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导致 iloc 取错 bar / 越界。
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"""
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def test_next_open_with_non_continuous_index(self) -> None:
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"""信号在 bar 0(label=10),应在 bar 1(position)open 成交。"""
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df = _make_df(10)
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df.index = [10 * (i + 1) for i in range(len(df))] # [10,20,...,100]
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sim = OrderSimulator(df, execution="next_open")
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signals = [_buy_signal(0, size=100)]
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trades = sim.simulate(signals, cash=20000, position=0)
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assert len(trades) == 1
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# position 1 的 open = 101.0;旧代码会用 label 10 当位置 → iloc[10] 越界
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assert trades[0].price == 101.0
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assert trades[0].rejected is False
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def test_this_close_with_non_continuous_index(self) -> None:
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"""this_close 模式下信号在 bar 2(label=30),应在同根 close 成交。"""
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df = _make_df(10)
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df.index = [10 * (i + 1) for i in range(len(df))]
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sim = OrderSimulator(df, execution="this_close")
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signals = [_buy_signal(2, size=100)]
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trades = sim.simulate(signals, cash=20000, position=0)
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assert len(trades) == 1
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# position 2 的 close = 103.0
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assert trades[0].price == 103.0
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