i SSKJr SSKJrJr SSKJr SSKJrJ r SSK J r J r J r Jr \"SS9S5r\"SS9S 5rSS \S \ S \S\ S\S\4 Sjjrg ))njit)float64 zeros_like)Series)DictLikeInt)v_offset v_pos_defaultv_seriesv_strT)cachecURSSU- - p2[U[S9nUSUS'[SU5Hn[ SXXES- U-5XE'M U$Ng?)dtypersizerrrangemaxxnmrateresultis P/var/www/html/trading/venv/lib/python3.13/site-packages/pandas_ta/trend/decay.pynb_exponential_decayr sbffcS1Wot  )F!F1I 1a[14A!56  McURSU- p2[U[S9nUSUS'[SU5Hn[ SXXES- U- 5XE'M U$rrrs rnb_linear_decayr!s^ffcAgt  )F!F1I 1a[14A!56  MrNcloselengthmodeoffsetkwargsreturnc v[X5nUcg[US5n[US5n[U5nSUR 5peUS;aSn[ Xa5nO [ Xa5n[XpRS9nUS:waURU5nS U;aURUS S S 9 US U3Ul S Ul U$)aDecay This function creates a decay moving forward from prior signals. Sources: * [tulipindicators](https://tulipindicators.org/decay) Parameters: close (Series): ```close``` Series length (int): The period. Default: ```1``` mode (str): Either ```"linear"``` or ```"exp"``` (exponetional) Default: ```"linear"``` offset (int): Post shift. Default: ```0``` Other Parameters: fillna (value): ```pd.DataFrame.fillna(value)``` Returns: (Series): 1 column NrlinearL)exp exponentialEXP)indexrfillnaT)inplaceDECAY_trend) r r r r to_numpyrr!rr.shiftr/namecategory)r"r#r$r%r&_modenp_closers rdecayr9&s2 U #E } 61 %F x D f F5>>+8 %%%h7 2 F++ .F{f%6 fX& 5G6&*FKFO Mr)NNN)numbarnumpyrrpandasrpandas_ta._typingrrpandas_ta.utilsr r r r rr!strr9rrrAs%+DD D  D  489 99-09 9"*9 9r