i0SSKJr SSKJrJrJr SSKJrJrJ r J r SSK J r SSK JrJrJrJr SSSSSS .r\"S S 9S 5r\"S S 9S 5r\"S S 9S5r\"S S 9S5r\"S S 9S5r\"S S 9S5rSS\ S\ S\ S\ S\S\S\ S\4Sjjrg))njit)greaternan zeros_like) DataFrame DateOffsetSeries infer_freq)DictLike)nb_nonzero_rangev_datetime_orderedv_seriesv_stryearsmonthsdays)YYEMMEDT)cachec X-U-S- n[X5nUSU-- nUSU-- nUSU-- nUSU-- nUSU--n USU--n USU--n USU--n X5XgXXU 4 $)Ngwwwwww?gwwwwww?g?g?r highlowclosetphl_ranges1s2s3s4r1r2r3r4s S/var/www/html/trading/venv/lib/python3.13/site-packages/pandas_ta/overlap/pivots.pypivot_camarillar+s *u  !B*H H$ $B 8# #B ! !B  B H$ $B 8# #B ! !B  B 2222 --c X-U-S- n[X5nSU-U- nX4- nUSU-- nUSU-- nSU-U- n X4-n USU--n USU--n X5XgXXU 4 $Nrrrs r* pivot_classicr0*s *u  !B*H R$B B a(l B a(l B R#B B a(l B a(l B 2222 --r,cX:HR5(aSX-SU---nO;[X05R5(aSSU-U-U--nOSUSU--U--nSU-U- nSU-U- nXEU4$)Ng?r/)allr)open_rrrr r"r&s r* pivot_demarkr4<s  TZ!e)+ ,   " " $ $ QX^e+ , TAG^e+ , R$B R#B 2:r,cX-U-S- n[X5nUSU-- nUSU-- nX4- nUSU--nUSU--n X4-n X5XgXU 4$)Nrg r?g-?r) rrrr r!r"r#r$r&r'r(s r*pivot_fibonaccir6Ksv *u  !B*H eh B eh B B eh B eh B B 222 %%r,c X-U-S- n[X5nSU-U- nX4- nUSU-- nUSU-- nSU-U- n X4-n USU--n USU--n X5XgXXU 4 $r.rrs r*pivot_traditionalr8[s *u  !B*H R$B B a(l B a(l B R#B B a(l B a(l B 2222 --r,c SU-U-U-S- n[X5nSU-U- nX4- nUSX- -- nXt- nSU-U- n X4-n USX2- --n X-n X5XgXXU 4 $)Nr/r) r3rrr r!r"r#r$r%r&r'r(r)s r* pivot_woodier;ms e)d S A %B*H R$B B qDI B B R#B B RX B B 2222 --r,Nr3rrrmethodanchorkwargsreturnc [U5n[U5n[U5n[U5nUb UbUbUcg/SQn[XGS5nURRS:ag[ U5(d [ S5 gURn[ U5n U(a5[U[5(a [U5S:aUR5nOSnXLa[URU5R5URU5R5URU5R5URU5R!5S.S 9n U R#S S 9 O [XX#S.US 9n U R$R'5n U R(R'5n U R*R'5n U R,R'5n[/U5n[0USS&U=n=n=n=n=n=n=n=nnUS :Xa[3XU5u nnnnnnnnnOUS:Xa[5XU5u nnnnnnnnnOeUS:Xa[7XX5unnnONUS:Xa[9XU5unnnnnnnO3US:Xa[;XU 5u nnnnnnnnnO[=XU5u nnnnnnnnnSUSSR5SU3nUU US3'UUsU US3'U US3'UUsU US3'U US3'UUsU US3'U US3'UUsU US3'U US3'[>RAUR5S5nU(a"[CS%0US0D6nU RU-U lO[ SUS35 XLaU REUS S!9n U RFSS2SS24n US";aNU RIU RJVs/sH(n[MU URO55(dM&UPM* snS S#9 UU l(S$U l)U $s snf)&a}Pivot Points Pivot Points attempt to identify support and resistance levels. There are many different methods of calculating Pivot Points. The most common (and default) method is: Traditional. Other methods include: Camarilla, Classic, Demark, Fibonacci, and Woodie. Sources: * [sierrachart](https://www.sierrachart.com/index.php?page=doc/PivotPoints.html) Parameters: open_ (Series): ```open``` Series high (Series): ```high``` Series low (Series): ```low``` Series close (Series): ```close``` Series method (str): Pivot methode. Default: ```'traditional'``` anchor (str): Anchor frequency. Default: ```'D'``` Other Parameters: fillna (value): ```pd.DataFrame.fillna(value)``` Returns: (DataFrame): 3, 7 or 9 columns Note: [Pandas Offset Aliases](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#timeseries-offset-aliases) N) traditional fibonacciwoodieclassicdemark camarillarrz-[!] Pivots requires an ordered DatetimeIndex.r)openrrr)dataT)inplace)rIindexrFrDrErBrCPIVOTS_r:__P_S1_S2_S3_S4_R1_R2_R3_R4z[!] Unsupported time anchor .ffill)r<)rErB)columnsrJoverlap)*rrrKsizer printr isinstancestrlenupperrresamplefirstmaxminlastdropnarHto_numpyrrrrrr+r0r4r6r;r8 td_mappinggetrreindexilocdroprYr2isnanamecategory)r3rrrr<r=r>methodsdt_indexfreqdfnp_opennp_highnp_lownp_close _nan_arrayr r"r#r$r%r&r'r(r)_props time_unit time_deltaxs r*pivotsr~sAD UOE D>D 3-C UOE }  u}G61: &F {{! e $ $ =>{{H h D *VS))c&kQ.>  v.446 f-113||F+//1/446   $  cJ  gg Ggg G VV__ Fxx  "HH%JJqM1;;B;;b;2;;R;";rB GX 6 +BBBB 9  '8 4 +BBBB 8 !'FE B ; %4Wh%O"BBB 8  6 2 +BBBB gx 8 +BBBBvbqz'')*!F8 4FB&}-/*B&~fXS>*-/*B&~fXS>*-/*B&~fXS>*-/*B&~fXS>*v||~t4I19a.1 88j( ,VHA67  ZZZ 1 12B (( BJJDJq#bejjl2CJDdSBGBK I Es 1%O6O6)NN)numbarnumpyrrrpandasrrr r pandas_ta._typingr pandas_ta.utilsr r rrrir+r0r4r6r8r;r_r~r[r,r*rs***<<&       D.."D.."D  D & &D.."D..('+I II II I!$I I  Ir,