iV SSKJrJr SSKJrJr SSKJrJr SSK J r J r J r SSK J r SS\S \S \S \S \S \S\S\4Sjjrg)) DataFrameSeries)DictLikeInt)hlc3sma)v_offset v_pos_defaultv_series)atrNhighlowcloselength atr_lengthoffsetkwargsreturnc [US5n[US5n[XC5S-n[X5n[X5n[X'5nUbUbUcg[U5n[ XX$S9n[ XUS9n [ X5n X-n X- n US:waDU RU5n U RU5n U RU5n URU5nSU;aLU RUSS S 9 U RUSS S 9 U RUSS S 9 URUSS S 9 S US U3n S U 3U l S U 3U l SU 3U l SU 3Ul S=U l U l U R=U l Ul U RXRXRXRU0n[XRS9nSU 3Ul U RUl U$)aAberration Similar to Keltner Channels. Sources: * [Request #46](https://github.com/twopirllc/pandas-ta/issues/46) Parameters: high (Series): ```high``` Series low (Series): ```low``` Series close (Series): ```close``` Series length (int): The period. Default: ```5``` atr_length (int): ATR period. Default: ```15``` offset (int): Post shift. Default: ```0``` Other Parameters: fillna (value): ```pd.DataFrame.fillna(value)``` Returns: (DataFrame): 4 columns r N)rrrr)rrrrfillnaT)inplace_ABER_ZGABER_SGABER_XGABER_ATR volatility)indexABER) r maxr r r rrshiftrnamecategoryrr!)rrrrrrr_lengthatr_jgzgsgxg_propsdatadfs Z/var/www/html/trading/venv/lib/python3.13/site-packages/pandas_ta/volatility/aberration.py aberrationr1 s661 %Fz2.J*%)G D "D 3 C U $E |s{em f F D BD 4 .B RB B B{ XXf  XXf  XXf zz&!6 &"D 1 &"D 1 &"D 1 F8$d 3* &Fx BGx BGx BG6(#DI ,,BK"+"$++-BK$- GGR"ggr99d CD 4{{ +BVHoBG++BK I)NNN)pandasrrpandas_ta._typingrrpandas_ta.overlaprrpandas_ta.utilsr r r r r1r2r0r8ss$+'== +/K KK&,K K$'K K#+K Kr2