my-home/zhixing-system
2
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

style(selection): apply ruff format to gold_brick module

Browse Source
This commit is contained in:
yuxuanhui
2026-09-05 19:48:41 +08:00
parent 12642f3c2d
commit 3e0aa496f3
1 changed files with 6 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
zhixing-server/src/zhixing_server/modules/selection/domain/gold_brick.py
+6 -15
View File
@@ -19,9 +19,7 @@ from .zhixing_b1 import compute_signal_masks, prepare_zhixing_b1_indicators
GOLD_BRICK_MINIMUM_HISTORY = 200 GOLD_BRICK_MINIMUM_HISTORY = 200
GOLD_BRICK_TURNOVER_RATE_THRESHOLD = 0.99 GOLD_BRICK_TURNOVER_RATE_THRESHOLD = 0.99
GOLD_BRICK_SIGNAL_ORDER: tuple[GoldBrickCategory, ...] = ( GOLD_BRICK_SIGNAL_ORDER: tuple[GoldBrickCategory, ...] = (GoldBrickCategory.RESONANCE,)
GoldBrickCategory.RESONANCE,
)
def _safe_ratio(numerator: pd.Series, denominator: pd.Series) -> pd.Series: def _safe_ratio(numerator: pd.Series, denominator: pd.Series) -> pd.Series:
@@ -90,9 +88,7 @@ def prepare_gold_brick_indicators(frame: pd.DataFrame, code: str) -> pd.DataFram
) )
multiple_volume_bonus = pd.Series( multiple_volume_bonus = pd.Series(
np.where( np.where(
(close > open_price) (close > open_price) & (close > previous_close) & (volume > previous_volume * 1.8),
& (close > previous_close)
& (volume > previous_volume * 1.8),
multiple_volume_coefficient, multiple_volume_coefficient,
1.0, 1.0,
), ),
@@ -115,13 +111,9 @@ def prepare_gold_brick_indicators(frame: pd.DataFrame, code: str) -> pd.DataFram
) )
result["j_momentum"] = j_momentum result["j_momentum"] = j_momentum
result["rsi_momentum"] = rsi_momentum result["rsi_momentum"] = rsi_momentum
result["yellow_column"] = ( result["yellow_column"] = momentum_sum.div(2).mul(shadow_coefficient).mul(multiple_volume_bonus)
momentum_sum.div(2).mul(shadow_coefficient).mul(multiple_volume_bonus)
)
x_condition = ( x_condition = (
(close > open_price) (close > open_price) & (close > previous_close) & (momentum_sum > previous_momentum_sum)
& (close > previous_close)
& (momentum_sum > previous_momentum_sum)
) )
result["x_momentum"] = ( result["x_momentum"] = (
momentum_sum.sub(previous_momentum_sum) momentum_sum.sub(previous_momentum_sum)
@@ -163,9 +155,8 @@ def prepare_gold_brick_indicators(frame: pd.DataFrame, code: str) -> pd.DataFram
high - close, high - close,
high - upper_shadow_floor, high - upper_shadow_floor,
) )
result["upper_shadow_condition"] = ( result["upper_shadow_condition"] = ((close >= open_price) | (close > previous_close)) & (
((close >= open_price) | (close > previous_close)) result["upper_shadow_strength"] > 0.618
& (result["upper_shadow_strength"] > 0.618)
) )
long = result["long_oscillator"] long = result["long_oscillator"]