refactor(qav3): cleanup zigzag()

Signed-off-by: Jérôme Benoit <jerome.benoit@piment-noir.org>

diff --git a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
index 0e81df5545c946abbc257f4b5bdcf41e5f98dc24..d5f6bd6f98681614005bb6fd2ec6d5514a95f412 100644 (file)
--- 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 4f9aa52ee5315c4a2d20b8823fdc014da1803e31..f03547ef64d557ebaba571f555d63795c12e4da2 100644 (file)
--- 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,