'i4ddlmZmZmZmZddlZddlZddlZddlm Z m Z ddl m Z Gdde Z Gd d e ZGd d eZGd deZGddeZGddeZGddeZGddeZGddeZGddeZGddeZGddeZGdd eZGd!d"eZGd#d$eZGd%d&eZGd'd(e ZGd)d*e ZGd+d,eZGd-d.eZ Gd/d0e Z!y)1)absolute_importdivisionprint_functionunicode_literalsN)maprange) Indicatorc&eZdZdZdZfdZxZS)PeriodNz Base class for indicators which take a period (__init__ has to be called either via super or explicitly) This class has no defined lines ))periodr cttt| |j|jj yN)superr __init__ addminperiodprself __class__s \/var/www/app/trading-bot/venv/lib/python3.12/site-packages/backtrader/indicators/basicops.pyrzPeriodN.__init__*s& gt%' $&&--(__name__ __module__ __qualname____doc__paramsr __classcell__rs@rr r !s F))rr ceZdZdZdZdZy) OperationNa Calculates "func" for a given period Serves as a base for classes that work with a period and can express the logic in a callable object Note: Base classes must provide a "func" attribute which is a callable Formula: - line = func(data, period) c|j|jj|jj|j d<yN)sizer)funcdatagetrrliners rnextzOperationN.next<s/yyDFFMM!BC ! rc|jj}|jj}|jj}|j }t ||D]}||||z dz|dz||<yNr )r*arrayr(rrr'r )rstartenddstsrcrr'is roncezOperationN.once?siiiooiiooyyuc" 6A#a&j1na!e45CF 6rN)rrrrr,r5rrr#r#/s D6rr#c&eZdZdZdZfdZxZS) BaseApplyNay Base class for ApplyN and others which may take a ``func`` as a parameter but want to define the lines in the indicator. Calculates ``func`` for a given period where func is given as a parameter, aka named argument or ``kwarg`` Formula: - lines[0] = func(data, period) Any extra lines defined beyond the first (index 0) are not calculated ))r'Nc`|jj|_tt|yr)rr'rr8rrs rrzBaseApplyN.__init__XsFFKK  j$(*rrr!s@rr8r8Is F++rr8ceZdZdZdZy)ApplyNz` Calculates ``func`` for a given period Formula: - line = func(data, period) )applyN)rrrrlinesr6rrr;r;]s Err;ceZdZdZdZdZeZy)Highestz Calculates the highest value for the data in a given period Uses the built-in ``max`` for the calculation Formula: - highest = max(data, period) )MaxN)highestN)rrrraliasr=maxr'r6rrr?r?gs E E Drr?ceZdZdZdZdZeZy)Lowestz Calculates the lowest value for the data in a given period Uses the built-in ``min`` for the calculation Formula: - lowest = min(data, period) )MinN)lowestN)rrrrrBr=minr'r6rrrErEus E E DrrEc>eZdZdZdZej ZfdZxZ S)ReduceNa Calculates the Reduced value of the ``period`` data points applying ``function`` Uses the built-in ``reduce`` for the calculation plus the ``func`` that subclassess define Formula: - reduced = reduce(function(data, period)), initializer=initializer) Notes: - In order to mimic the python ``reduce``, this indicator takes a ``function`` non-named argument as the 1st argument, unlike other Indicators which take only named arguments )reducedc d|vr&tj|j||_n*tj|j||d|_tt|y)N initializer)rM) functoolspartialr'rrJr)rfunctionkwargsrs rrzReduceN.__init__sU  &!))$))X>DI!))$))X6<]6KMDI gt%'r) rrrrr=rNreducer'rr r!s@rrJrJs$ E   D((rrJc,eZdZdZdZej Zy)SumNz Calculates the Sum of the data values over a given period Uses ``math.fsum`` for the calculation rather than the built-in ``sum`` to avoid precision errors Formula: - sumn = sum(data, period) )sumnN)rrrrr=mathfsumr'r6rrrTrTs E 99DrrTceZdZdZdZeZy)AnyNz Has a value of ``True`` (stored as ``1.0`` in the lines) if *any* of the values in the ``period`` evaluates to non-zero (ie: ``True``) Uses the built-in ``any`` for the calculation Formula: - anyn = any(data, period) )anynN)rrrrr=anyr'r6rrrYrY E DrrYceZdZdZdZeZy)AllNz Has a value of ``True`` (stored as ``1.0`` in the lines) if *all* of the values in the ``period`` evaluates to non-zero (ie: ``True``) Uses the built-in ``all`` for the calculation Formula: - alln = all(data, period) )allnN)rrrrr=allr'r6rrr^r^r\rr^ceZdZdZdZdZdZy)FindFirstIndexa7 Returns the index of the last data that satisfies equality with the condition generated by the parameter _evalfunc Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = first for which data[index] == _evalfunc(data) index) _evalfuncNc|jj|tfdtt |DS)Nc34K|]\}}|k(s |ywrr6.0r4vms r z&FindFirstIndex.func..sJ$!Q16AJ )rrfr, enumeratereversed)riterablerls @rr'zFindFirstIndex.funcs2 FF  X &J)HX,>"?JJJrNrrrrr=rr'r6rrrbrbs  E #FKrrbceZdZdZdeffZy)FindFirstIndexHighesta Returns the index of the first data that is the highest in the period Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = index of first data which is the highest rfNrrrrrCrr6rrrtrt C "FrrtceZdZdZdeffZy)FindFirstIndexLowestz Returns the index of the first data that is the lowest in the period Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = index of first data which is the lowest rfNrrrrrHrr6rrrxrxrvrrxceZdZdZdZdZdZy) FindLastIndexa6 Returns the index of the last data that satisfies equality with the condition generated by the parameter _evalfunc Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = last for which data[index] == _evalfunc(data) rcrec|jj|tfdt|D}|jj|z dz S)Nc34K|]\}}|k(s |ywrr6ris rrmz%FindLastIndex.func.. sA41a!q&QArnr )rrfr,ror)rrqrdrls @rr'zFindLastIndex.func sF FF  X &A9X#6AAvv}}u$q((rNrrr6rrr{r{s  E #F)rr{ceZdZdZdeffZy)FindLastIndexHighestz Returns the index of the last data that is the highest in the period Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = index of last data which is the highest rfNrur6rrrrrvrrceZdZdZdeffZy)FindLastIndexLowestz Returns the index of the last data that is the lowest in the period Note: Returned indexes look backwards. 0 is the current index and 1 is the previous bar. Formula: - index = index of last data which is the lowest rfNryr6rrrr!rvrrc4eZdZdZdZdZdZdZdZdZ dZ y ) AccumzP Cummulative sum of the data values Formula: - accum += data )CumSum CumulativeSum)accum))seedgcj|jj|jdz|jd<yNr)rrr(r*r+s r nextstartzAccum.nextstart>s$vv{{TYYq\1 ! rc\|jd|jdz|jd<yNr)r*r(r+s rr,z Accum.nextAs$yy}tyy|3 ! rc|jj}|jj}|jj}t ||D]}|||zx||<}yr)r*r/r(rrr rr0r1r2r3prevr4s r oncestartzAccum.oncestartDsUiiooiioovv{{uc" *A 3q6M )CFT *rc|jj}|jj}||dz }t||D]}|||zx||<}yr.)r*r/r(r rs rr5z Accum.onceLsUiiooiioo519~uc" *A 3q6M )CFT *rN) rrrrrBr=rrr,rr5r6rrrr/s, )E E F 24**rrc$eZdZdZdZdZdZdZy)Averagez Averages a given data arithmetically over a period Formula: - av = data(period) / period See also: - https://en.wikipedia.org/wiki/Arithmetic_mean )ArithmeticMeanMeanavctj|jj|jj |jj z |j d<yr%)rVrWr(r)rrr*r+s rr,z Average.nextbs? IIdiimmm7 8466== H ! rc|jj}|jj}|jj}t ||D])}t j|||z dz|dz|z ||<+yr.)r(r/r*rrr rVrW)rr0r1r3r2rr4s rr5z Average.oncefskiiooiioouc" CAYYs1v:>!a%89FBCF CrN)rrrrrBr=r,r5r6rrrrUs (E EICrrcJeZdZdZdZdZfdZfdZdZfdZ dZ xZ S) ExponentialSmoothingaC Averages a given data over a period using exponential smoothing A regular ArithmeticMean (Average) is used as the seed value considering the first period values of data Formula: - av = prev * (1 - alpha) + data * alpha See also: - https://en.wikipedia.org/wiki/Exponential_smoothing ) ExpSmoothing))alphaNc|jj|_|j!dd|jjzz |_d|jz |_tt |y)Ng@?)rrralpha1rrrrs rrzExponentialSmoothing.__init__sSVV\\ :: dffmm 34DJDJJ&  "D24rc*tt| yr)rrr,rs rrzExponentialSmoothing.nextstarts "D.0rc|jd|jz|jd|jzz|jd<yrr*rr(rr+s rr,zExponentialSmoothing.nexts6yy}t{{2TYYq\DJJ5NN ! rc.tt| ||yr)rrr5)rr0r1rs rrzExponentialSmoothing.oncestarts "D.uc:rc|jj}|jj}|j}|j}||dz }t ||D]}||z|||zzx||<}yr.r(r/r*rrr rr0r1darraylarrayrrrr4s rr5zExponentialSmoothing.oncesv eai uc" AA#f}vay5/@@ @F1I Ar) rrrrrBrrrr,rr5r r!s@rrros/  E F51O; Arrc2eZdZdZdZfdZdZdZxZS)ExponentialSmoothingDynamica Averages a given data over a period using exponential smoothing A regular ArithmeticMean (Average) is used as the seed value considering the first period values of data Note: - alpha is an array of values which can be calculated dynamically Formula: - av = prev * (1 - alpha) + data * alpha See also: - https://en.wikipedia.org/wiki/Exponential_smoothing )ExpSmoothingDynamicctt| td|jj |j jz }|jdj|yr) rrrrCr _minperiodrrr= incminperiod)r minperioddiffrs rrz$ExponentialSmoothingDynamic.__init__sL )49; Atzz44tvv}}DE  1 ""=1rc|jd|jdz|jd|jdzz|jd<yrrr+s rr,z ExponentialSmoothingDynamic.nextsA IIbMDKKN *TYYq\DJJqM-I I ! rc|jj}|jj}|jj}|jj}||dz }t ||D]}|||z||||zzx||<}yr.rrs rr5z ExponentialSmoothingDynamic.onces   ""eai uc" GA#fQi/&)eAh2FF FF1I Gr) rrrrrBrr,r5r r!s@rrrs  %E2J GrrcLeZdZdZdZdZddeffZfdZdZ dZ xZ S) WeightedAverageaw Calculates the weighted average of the given data over a period The default weights (if none are provided) are linear to assigne more weight to the most recent data The result will be multiplied by a given "coef" Formula: - av = coef * sum(mul(data, period), weights) See: - https://en.wikipedia.org/wiki/Weighted_arithmetic_mean )AverageWeightedr)coefrweightsc*tt| yr)rrrrs rrzWeightedAverage.__init__s ot-/rc4|jj|jj}t t j ||jj}|jjtj|z|jd<yr%) r(r)rrroperatormulrrrVrWr*)rr( dataweighteds rr,zWeightedAverage.nexts[yy}}$&&--}08<<tvv~~> vv{{TYY|%<< ! rc |jj}|jj}|jj}|jj }|jj }t||D]D}|||z dz|dz} |tjttj| |z||<Fyr.) r(r/r*rrrrr rVrWrrr) rr0r1rrrrrr4r(s rr5zWeightedAverage.oncesvv{{&&..uc" KA!f*q.!a%0DtyyX\\4)IJJF1I Kr) rrrrrBr=tuplerrr,r5r r!s@rrrs5  !E Ei1 3F0= Krr)" __future__rrrrrNrVr utils.py3rr r r r#r8r;r?rErJrTrYr^rbrtrxr{rrrrrrrr6rrrs**** " )i )664++(Z j  Z (j(< :  :  : KZK( #N # #> #)J)0 #= # #- ##*I#*LCgC4-A7-A`(G"6(GV$Kg$Kr