From 29d32d92cc96d4a30c1043ab16f594d2ad1d6647 Mon Sep 17 00:00:00 2001 From: =?utf8?q?J=C3=A9r=C3=B4me=20Benoit?= Date: Mon, 24 Mar 2025 14:03:30 +0100 Subject: [PATCH] perf(qav3): integrate new features MIME-Version: 1.0 Content-Type: text/plain; charset=utf8 Content-Transfer-Encoding: 8bit Signed-off-by: Jérôme Benoit --- .../user_data/strategies/QuickAdapterV3.py | 39 ++++++++++--------- 1 file changed, 21 insertions(+), 18 deletions(-) diff --git a/quickadapter/user_data/strategies/QuickAdapterV3.py b/quickadapter/user_data/strategies/QuickAdapterV3.py index ea4d31e..b769722 100644 --- a/quickadapter/user_data/strategies/QuickAdapterV3.py +++ b/quickadapter/user_data/strategies/QuickAdapterV3.py @@ -18,8 +18,11 @@ import numpy as np import pandas_ta as pta from Utils import ( + alligator, + bottom_change_percent, ewo, non_zero_range, + price_retracement_percent, vwapb, top_change_percent, get_distance, @@ -56,7 +59,7 @@ class QuickAdapterV3(IStrategy): INTERFACE_VERSION = 3 def version(self) -> str: - return "3.1.15" + return "3.2.0" timeframe = "5m" @@ -197,8 +200,8 @@ class QuickAdapterV3(IStrategy): length=period, ) dataframe["%-tcp-period"] = top_change_percent(dataframe, period=period) - # dataframe["%-bcp-period"] = bottom_change_percent(dataframe, period=period) - # dataframe["%-prp-period"] = price_retracement_percent(dataframe, period=period) + dataframe["%-bcp-period"] = bottom_change_percent(dataframe, period=period) + dataframe["%-prp-period"] = price_retracement_percent(dataframe, period=period) dataframe["%-cti-period"] = pta.cti(dataframe["close"], length=period) dataframe["%-chop-period"] = pta.chop( dataframe["high"], @@ -255,21 +258,21 @@ class QuickAdapterV3(IStrategy): dataframe["%-ibs"] = (dataframe["close"] - dataframe["low"]) / ( non_zero_range(dataframe["high"], dataframe["low"]) ) - # dataframe["jaw"], dataframe["teeth"], dataframe["lips"] = alligator( - # dataframe, mamode="ema", zero_lag=True - # ) - # dataframe["%-dist_to_jaw"] = get_distance(dataframe["close"], dataframe["jaw"]) - # dataframe["%-dist_to_teeth"] = get_distance( - # dataframe["close"], dataframe["teeth"] - # ) - # dataframe["%-dist_to_lips"] = get_distance( - # dataframe["close"], dataframe["lips"] - # ) - # dataframe["%-spread_jaw_teeth"] = dataframe["jaw"] - dataframe["teeth"] - # dataframe["%-spread_teeth_lips"] = dataframe["teeth"] - dataframe["lips"] - # dataframe["%-alligator_trend_strength"] = ( - # dataframe["lips"] - dataframe["teeth"] - # ) + (non_zero_range(dataframe["teeth"], dataframe["jaw"])) + dataframe["jaw"], dataframe["teeth"], dataframe["lips"] = alligator( + dataframe, mamode="ema", zero_lag=True + ) + dataframe["%-dist_to_jaw"] = get_distance(dataframe["close"], dataframe["jaw"]) + dataframe["%-dist_to_teeth"] = get_distance( + dataframe["close"], dataframe["teeth"] + ) + dataframe["%-dist_to_lips"] = get_distance( + dataframe["close"], dataframe["lips"] + ) + dataframe["%-spread_jaw_teeth"] = dataframe["jaw"] - dataframe["teeth"] + dataframe["%-spread_teeth_lips"] = dataframe["teeth"] - dataframe["lips"] + dataframe["%-alligator_trend_strength"] = ( + dataframe["lips"] - dataframe["teeth"] + ) + (non_zero_range(dataframe["teeth"], dataframe["jaw"])) dataframe["zlema_50"] = pta.zlma(dataframe["close"], length=50, mamode="ema") dataframe["zlema_12"] = pta.zlma(dataframe["close"], length=12, mamode="ema") dataframe["zlema_26"] = pta.zlma(dataframe["close"], length=26, mamode="ema") -- 2.43.0