From: Jérôme Benoit <jerome.benoit@piment-noir.org>
Date: Sun, 11 May 2025 17:53:47 +0000 (+0200)
Subject: refactor(qav3): cleanup functions namespace
X-Git-Url: https://git.piment-noir.org/?a=commitdiff_plain;h=35c545eddd11fea36488482b59f9f82bd51cb3fc;p=freqai-strategies.git

refactor(qav3): cleanup functions namespace

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

diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py
index dbf59aa..d3eb88d 100644
--- a/quickadapter/user_data/strategies/QuickAdapterV3.py
+++ b/quickadapter/user_data/strategies/QuickAdapterV3.py
@@ -20,7 +20,7 @@ from Utils import (
     bottom_change_percent,
     zigzag,
     ewo,
-    non_zero_range,
+    non_zero_diff,
     price_retracement_percent,
     vwapb,
     top_change_percent,
@@ -260,7 +260,7 @@ class QuickAdapterV3(IStrategy):
             dataframe["bb_upperband"] - dataframe["bb_lowerband"]
         ) / dataframe["bb_middleband"]
         dataframe["%-ibs"] = (dataframe["close"] - dataframe["low"]) / (
-            non_zero_range(dataframe["high"], dataframe["low"])
+            non_zero_diff(dataframe["high"], dataframe["low"])
         )
         dataframe["jaw"], dataframe["teeth"], dataframe["lips"] = alligator(
             dataframe, pricemode="median", zero_lag=True
diff --git a/quickadapter/user_data/strategies/Utils.py b/quickadapter/user_data/strategies/Utils.py
index daf7d7e..3047968 100644
--- a/quickadapter/user_data/strategies/Utils.py
+++ b/quickadapter/user_data/strategies/Utils.py
@@ -14,7 +14,7 @@ def get_distance(
     return abs(p1 - p2)
 
 
-def non_zero_range(s1: pd.Series, s2: pd.Series) -> pd.Series:
+def non_zero_diff(s1: pd.Series, s2: pd.Series) -> pd.Series:
     """Returns the difference of two series and adds epsilon to any zero values."""
     diff = s1 - s2
     diff = diff.mask(diff == 0, other=diff + np.finfo(float).eps)
@@ -112,7 +112,7 @@ def price_retracement_percent(dataframe: pd.DataFrame, period: int) -> pd.Series
     )
 
     return (dataframe["close"] - previous_close_low) / (
-        non_zero_range(previous_close_high, previous_close_low)
+        non_zero_diff(previous_close_high, previous_close_low)
     )