i} SSKJr SSKJr SSKJrJrJr SSKJ r SSK J r SSK J r JrJrJrJrJrJr SrSS \S \S \S \S \S\S\S\S\S\S\S\4Sjjrg))isnan)Series)DictLikeIntIntFloat)ma)stdev)unsigned_differencesv_boolv_driftv_mamodev_offset v_pos_defaultv_seriesc[X5n[X5upgXe-nXu-n [X8US9n [X9US9n X*-X-- n U $)N)length)r r r) sourcerscalarmodedriftstdposnegpos_stdneg_stdpos_avgneg_avgresults S/var/www/html/trading/venv/lib/python3.13/site-packages/pandas_ta/volatility/rvi.py_rvir sS  C#F2HCiGiGv.Gv.G  !2 3F MNclosehighlowrrrefinedthirdsmamoderoffsetkwargsreturnc  [US5n[XS-5nUcg[US5n[US5n[US5n[US5n[ U5n[ U 5n U(dU(a[U5n[U5nSn U(a$[ XXGU5n [ X#XGU5n SX--nS n OHU(a4[ XXGU5n [ X#XGU5n [ XXGU5nX-U-S - nS n O [ XXGU5n[[U55(agU S :waURU 5nS U ;aURU S SS9 SU SU3Ul SUl U$)a;Relative Volatility Index This indicator attempts to quantify volatility using standard deviation. Sources: * [motivewave](https://www.motivewave.com/studies/relative_volatility_index.htm) * [tradingview A](https://www.tradingview.com/script/mLZJqxKn-Relative-Volatility-Index/) * [tradingview B](https://www.tradingview.com/support/solutions/43000594684-relative-volatility-index/) Parameters: high (Series): ```high``` Series low (Series): ```low``` Series close (Series): ```close``` Series length (int): The period. Default: ```14``` scalar (float): Bands scalar. Default: ```100``` refined (bool): Use 'refined' calculation which is the average of RVI(high) and RVI(low) instead of RVI(close). Default: ```False``` thirds (bool): Average of ```high```, ```low``` and ```close```. Default: ```False``` mamode (str): See ```help(ta.ma)```. Default: ```"ema"``` offset (int): Post shift. Default: ```0``` Other Parameters: fillna (value): ```pd.DataFrame.fillna(value)``` Returns: (DataFrame): 3 columns NdFemag?rg@trfillnaT)inplaceRVI_ volatility) rrr r r rr allrshiftr3namecategory)r"r#r$rrr%r&r'rr(r)_modehigh_rvilow_rvirvi close_rvis rr?r?!ssH62 &F UQJ 'E } 63 'FWe$G FE "F fe $F ENE f F&~sm Efe<sFE:X'( fe<sFE:> !I-45&%8 5:{ii6 6(#T 2UG1VH%CHCL Jr!) NNNNNNNNN)numpyrpandasrpandas_ta._typingrrr pandas_ta.marpandas_ta.statisticsr pandas_ta.utilsr r r r rrrr boolstrr?r!rrJs55& 7;+/)-%) T TT-3T T (TT#'T  T # T  T #+ T  Tr!