'i2 FddlmZmZmZmZddlmZmZmZGddeZ y))absolute_importdivisionprint_functionunicode_literals)SumNMovingAverageBaseExponentialSmoothingDynamicc.eZdZdZdZdZdZfdZxZS)AdaptiveMovingAveragea Defined by Perry Kaufman in his book `"Smarter Trading"`. It is A Moving Average with a continuously scaled smoothing factor by taking into account market direction and volatility. The smoothing factor is calculated from 2 ExponetialMovingAverage smoothing factors, a fast one and slow one. If the market trends the value will tend to the fast ema smoothing period. If the market doesn't trend it will move towards the slow EMA smoothing period. It is a subclass of SmoothingMovingAverage, overriding once to account for the live nature of the smoothing factor Formula: - direction = close - close_period - volatility = sumN(abs(close - close_n), period) - effiency_ratio = abs(direction / volatility) - fast = 2 / (fast_period + 1) - slow = 2 / (slow_period + 1) - smfactor = squared(efficienty_ratio * (fast - slow) + slow) - smfactor1 = 1.0 - smfactor - The initial seed value is a SimpleMovingAverage See also: - http://fxcodebase.com/wiki/index.php/Kaufman's_Adaptive_Moving_Average_(KAMA) - http://www.metatrader5.com/en/terminal/help/analytics/indicators/trend_indicators/ama - http://help.cqg.com/cqgic/default.htm#!Documents/adaptivemovingaverag2.htm )KAMAMovingAverageAdaptive)kama))fast)slowcD|j|j|jj z }tt |j|jdz |jj}t ||z }d|jj dzz }d|jj dzz }t|||z z|zd}t|j|jj||jd<tt|3y)N)periodg@g?r)ralphar) dataprrabsrrpowr linessuperr __init__)self direction volatilityerrrsc __class__s X/var/www/app/trading-bot/venv/lib/python3.12/site-packages/backtrader/indicators/kama.pyrzAdaptiveMovingAverage.__init__@sII 466==. 99 #dii$))B-78O Z' (dffkkC'(dffkkC'( "t $,a 03DII;?66==:<> 1  #T35) __name__ __module__ __qualname____doc__aliasrparamsr __classcell__)r$s@r%r r s$@ /E E (F66r&r N) __future__rrrrrr r r r&r%r1s%***ED66-66r&