chore(qav3): bump version

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 a00392eee19545a2bf2e5634d8ba96aa093f1f35..6d00e6809c5b6093e4422e26546b13683a1ef083 100644 (file)
--- a/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
+++ b/quickadapter/user_data/freqaimodels/QuickAdapterRegressorV3.py
@@ -45,7 +45,7 @@ class QuickAdapterRegressorV3(BaseRegressionModel):
     https://github.com/sponsors/robcaulk
     """
 
-    version = "3.7.55"
+    version = "3.7.56"
 
     @cached_property
     def _optuna_config(self) -> dict:
@@ -1064,9 +1064,10 @@ def zigzag(
             if np.isclose(log_next_closes_std, 0):
                 next_slope_strength = 0
             else:
-                weights = np.linspace(0.5, 1.5, len(log_next_closes))
+                log_next_closes_length = len(log_next_closes)
+                weights = np.linspace(0.5, 1.5, log_next_closes_length)
                 log_next_slope = np.polyfit(
-                    range(len(log_next_closes)), log_next_closes, 1, w=weights
+                    range(log_next_closes_length), log_next_closes, 1, w=weights
                 )[0]
                 next_slope_strength = log_next_slope / log_next_closes_std
             min_slope_strength = calculate_min_slope_strength(candidate_pivot_pos)

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index 74cfa2725a8379c370f10e008a83ecb94c1835bf..ecb1b4a56145cf7df701a02472865c805be1fe5c 100644 (file)
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -60,7 +60,7 @@ class QuickAdapterV3(IStrategy):
     INTERFACE_VERSION = 3
 
     def version(self) -> str:
-        return "3.3.55"
+        return "3.3.56"
 
     timeframe = "5m"
 

diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py
index 7f9d78416cc96959b9bd58153d9a083f249e724f..1d4d6c6993c5be038873002ed8ff1cda3a5af88e 100644 (file)
--- a/quickadapter/user_data/strategies/Utils.py
+++ b/quickadapter/user_data/strategies/Utils.py
@@ -318,8 +318,9 @@ def find_fractals(
 
     fractal_candidate_indices = np.arange(fractal_period, n - fractal_period)
 
-    is_fractal_high = np.ones(len(fractal_candidate_indices), dtype=bool)
-    is_fractal_low = np.ones(len(fractal_candidate_indices), dtype=bool)
+    fractal_candidate_indices_length = len(fractal_candidate_indices)
+    is_fractal_high = np.ones(fractal_candidate_indices_length, dtype=bool)
+    is_fractal_low = np.ones(fractal_candidate_indices_length, dtype=bool)
 
     for i in range(1, fractal_period + 1):
         is_fractal_high &= (
@@ -547,9 +548,10 @@ def zigzag(
             if np.isclose(log_next_closes_std, 0):
                 next_slope_strength = 0
             else:
-                weights = np.linspace(0.5, 1.5, len(log_next_closes))
+                log_next_closes_length = len(log_next_closes)
+                weights = np.linspace(0.5, 1.5, log_next_closes_length)
                 log_next_slope = np.polyfit(
-                    range(len(log_next_closes)), log_next_closes, 1, w=weights
+                    range(log_next_closes_length), log_next_closes, 1, w=weights
                 )[0]
                 next_slope_strength = log_next_slope / log_next_closes_std
             min_slope_strength = calculate_min_slope_strength(candidate_pivot_pos)