From 6d39f573cfc41af7013144a11f2eec8ee2a10918 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Wed, 21 May 2025 17:44:13 +0200 Subject: [PATCH] refactor(qav3): trivial cleanup MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 4 ++-- quickadapter/user_data/strategies/QuickAdapterV3.py | 6 +++--- quickadapter/user_data/strategies/Utils.py | 2 +- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 78b747e..16f70b5 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -885,7 +885,7 @@ def zigzag( def get_natr_values(period: int) -> np.ndarray: if period not in natr_values_cache: natr_values_cache[period] = ( - ta.NATR(df, timeperiod=period).fillna(method="bfill") / 100 + ta.NATR(df, timeperiod=period).fillna(method="bfill") / 100.0 ).values return natr_values_cache[period] @@ -1194,7 +1194,7 @@ def label_objective( return -np.inf, -np.inf scaled_natr_label_period_candles = ( - ta.NATR(df, timeperiod=label_period_candles).fillna(method="bfill") / 100 + ta.NATR(df, timeperiod=label_period_candles).fillna(method="bfill") / 100.0 ) * label_natr_ratio return scaled_natr_label_period_candles.median(), n diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py index b18f08b..fc05aea 100644 --- a/quickadapter/user_data/strategies/QuickAdapterV3.py +++ b/quickadapter/user_data/strategies/QuickAdapterV3.py @@ -496,7 +496,7 @@ class QuickAdapterV3(IStrategy): return None return ( current_rate - * (current_natr / 100) + * (current_natr / 100.0) * self.get_stoploss_natr_ratio(trade.pair) * (1 / math.log10(3.75 + 0.25 * trade_duration_candles)) ) @@ -525,7 +525,7 @@ class QuickAdapterV3(IStrategy): ) return ( trade.open_rate - * (take_profit_natr / 100) + * (take_profit_natr / 100.0) * self.get_take_profit_natr_ratio(trade.pair) * math.log10(9.75 + 0.25 * trade_duration_candles) ) @@ -640,7 +640,7 @@ class QuickAdapterV3(IStrategy): return False lower_bound = 0 upper_bound = 0 - price_deviation = (last_candle_natr / 100) * self.get_entry_natr_ratio(pair) + price_deviation = (last_candle_natr / 100.0) * self.get_entry_natr_ratio(pair) if side == "long": lower_bound = last_candle_low * (1 - price_deviation) upper_bound = last_candle_close * (1 + price_deviation) diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index 0a90334..8ccc00c 100644 --- a/quickadapter/user_data/strategies/Utils.py +++ b/quickadapter/user_data/strategies/Utils.py @@ -376,7 +376,7 @@ def zigzag( def get_natr_values(period: int) -> np.ndarray: if period not in natr_values_cache: natr_values_cache[period] = ( - ta.NATR(df, timeperiod=period).fillna(method="bfill") / 100 + ta.NATR(df, timeperiod=period).fillna(method="bfill") / 100.0 ).values return natr_values_cache[period] -- 2.43.0