From 23ccc27d59a91f6020b64e0c796c01c265247060 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Fri, 13 Jun 2025 23:36:37 +0200 Subject: [PATCH] refactor(qav3): cleanup zigzag() MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../user_data/freqaimodels/QuickAdapterRegressorV3.py | 11 ++++------- quickadapter/user_data/strategies/Utils.py | 11 ++++------- 2 files changed, 8 insertions(+), 14 deletions(-) diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py index 0e81df5..d5f6bd6 100644 --- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py +++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py @@ -1394,15 +1394,12 @@ def zigzag( log_next_moving_closes = np.log(next_moving_closes) log_next_moving_closes_std = np.std(log_next_moving_closes) if np.isclose(log_next_moving_closes_std, 0): - next_moving_slope_strength = ( - np.sign(log_next_moving_closes[-1] - log_next_moving_closes[0]) - * 0.01 - ) + next_moving_slope_strength = 0 else: - log_next_closes_moving_length = len(log_next_moving_closes) - weights = np.linspace(0.5, 1.5, log_next_closes_moving_length) + log_next_moving_closes_length = len(log_next_moving_closes) + weights = np.linspace(0.5, 1.5, log_next_moving_closes_length) log_next_moving_slope = np.polyfit( - range(log_next_closes_moving_length), + range(log_next_moving_closes_length), log_next_moving_closes, 1, w=weights, diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py index 4f9aa52..f03547e 100644 --- a/quickadapter/user_data/strategies/Utils.py +++ b/quickadapter/user_data/strategies/Utils.py @@ -566,15 +566,12 @@ def zigzag( log_next_moving_closes = np.log(next_moving_closes) log_next_moving_closes_std = np.std(log_next_moving_closes) if np.isclose(log_next_moving_closes_std, 0): - next_moving_slope_strength = ( - np.sign(log_next_moving_closes[-1] - log_next_moving_closes[0]) - * 0.01 - ) + next_moving_slope_strength = 0 else: - log_next_closes_moving_length = len(log_next_moving_closes) - weights = np.linspace(0.5, 1.5, log_next_closes_moving_length) + log_next_moving_closes_length = len(log_next_moving_closes) + weights = np.linspace(0.5, 1.5, log_next_moving_closes_length) log_next_moving_slope = np.polyfit( - range(log_next_closes_moving_length), + range(log_next_moving_closes_length), log_next_moving_closes, 1, w=weights, -- 2.43.0