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Does anyone have the thinkscript code for Ehlers RocketRSI that’s in Stocks & Commodities May 2018 issue?

Instantaneous TrendLine by John Ehlers Note: This indicator was written in EasyLanguage. Please refer to your users manual for importation instructions. Your comments and rating of this indicator is appreciated. Instantaneous TrendLine.txt

{Adaptive CCI From the book 'Rocket Science for Traders' by John Ehlers modified with new cycle measurement method from 'Cybernetic Analysis for Stocks and Futures' mmillar, July 2004 Price - the current price - only used by the Cycle Period measurement, not by the CCI calculation Length - used by the Cycle Period measurement - John Ehlers uses alpha but I have replaced it with the more intuitive Length, where alpha=2/(Length+1) CycPart - allows you to change how much of the cycle period should be used in the CCI calculation - usually 1 } Inputs: Price((H+L)/2), Length(19), CycPart(1); Vars: oResult1(0), oResult2(0); value1=_Oscillators(18, Price, Length, CycPart, 1, 0, 1, oResult1, oResult2); Plot1(oResult1, "AdaptCCI"); _Oscillators function: {A collection of oscillators by John Ehlers by mmillar, July 2004 1-15 are taken from 'Cybernetic Analysis for Stocks and Futures' 16-18 are taken from 'Rocket Science for Traders' and updated using a new cycle period measurement method This function calls the function '_CyclePeriod' to calculate the Dominant Cycle for use in adaptive strategies Oscillator Types 1 - Cyber Cycle 2 - CG Oscillator 3 - Relative Vigor Index (RVI) 4 - Stochastic RSI 5 - Stochastic Cyber Cycle 6 - Stochastic CG 7 - Stochastic RVI 8 - Fisher Cyber Cycle 9 - Fisher CG 10 - Fisher RVI 11 - Adaptive Cyber Cycle 12 - Adaptive CG 13 - Adaptive RVI 14 - Sinewave Indicator 15 - Laguerre RSI 16 - Adaptive RSI 17 - Adaptive Stochastic 18 - Adaptive CCI This function is called with OscType - one of the above Price - some indicators can use a price input e.g. (H+L)/2, Close etc, otherwise this can be set to 0 Length - the length or period that you wish to measure. In some instances John Ehlers uses 'alpha' as his input but I have standardised all inputs using Length and then converted, where necessary, with alpha=2/(Length+1) Length2 - this is a catch all used when an additional input variable is needed (just because everything is done in one function) RSILength, StocLength, WMALength - only used by Stochastic RSI (OscType=4) oResult1, oResult2 - are the results returned by the function } Inputs: OscType(Numeric), Price(Numeric), Length(Numeric), Length2(Numeric), {general inputs} RSILength(Numeric), StocLength(Numeric), WMALength(Numeric), {only used by OscType=4} oResult1(NumericRef), oResult2(NumericRef); {results to return} Vars: alpha(0), count(0), Num(0), Denom(0), Smooth(0), Cycle(0), {for OscType=1, 5, 8, 11} CG(0), {for OscType=2, 6, 9, 12} RVI(0), {for OscType=3, 7, 10, 13} MaxVal(0), MinVal(0), {for OscType=5-10} Period(0), {for OscType=11-18} Cycle1(0), {for OscType=11-18 but only used in 14} Smooth1(0), {for OscType=11-18 but only used in 11} DCPeriod(0), RealPart(0), ImagPart(0), DCPhase(0), {for OscType=14} L0(0), L1(0), L2(0), L3(0), {for OscType=15} vRSI(0), CU(0), CD(0), {for OscType=15, 16} vStoch(0), HH(0), LL(0), {for OscType=17} vCCI(0), Avg(0), MD(0), MPrice(0); {for OscType=18} If ( OscType=1 ) then Begin {Cyber Cycle} alpha=2/(Length+1); Smooth=(Price+2*Price[1]+2*Price[2]+Price[3])/6; Cycle=(1-0.5*alpha)*(1-0.5*alpha)*(Smooth-2*Smooth[1]+Smooth[2])+2*(1-alpha)*Cycle[1]-(1-alpha)*( 1-alpha)*Cycle[2]; If currentbar<7 then Cycle=(Price-2*Price[1]+Price[2])/4; oResult1=Cycle; oResult2=Cycle[1]; end else If ( OscType=2 ) then Begin {CG Oscillator} Num=0; Denom=0; For count=0 to Length-1 Begin Num=Num+(1+count)*Price[count]; Denom=Denom+Price[count]; end; If Denom<>0 then CG=-Num/Denom+(Length+1)/2; oResult1=CG; oResult2=CG[1]; end else If ( OscType=3 ) then Begin {Relative Vigor Index} Value1=((Close-Open)+2*(Close[1]-Open[1])+2*(Close[2]-Open[2])+(Close[3]-Open[3]))/6; Value2=((High-Low)+2*(High[1]-Low[1])+2*(High[2]-Low[2])+(High[3]-Low[3]))/6; Num=0; Denom=0; For count=0 to Length-1 Begin Num=Num+Value1[count]; Denom=Denom+Value2[count]; end; If Denom<>0 then RVI=Num/Denom; oResult1=RVI; oResult2=RVI[1]; end else If ( OscType=4 ) then Begin {Stochastic RSI} Value1=RSI(Close, RSILength)-Lowest(RSI(Close, RSILength), StocLength); Value2=Highest(RSI(Close, RSILength), StocLength)-Lowest(RSI(Close, RSILength), StocLength); If Value2<>0 then Value3=Value1/Value2; Value4=2*(WAverage(Value3, WMALength)-0.5); oResult1=Value4; oResult2=Value4[1]; end else If ( OscType=5 ) then Begin {Stochastic Cyber Cycle} alpha=2/(Length+1); Smooth=(Price+2*Price[1]+2*Price[2]+Price[3])/6; Cycle=(1-0.5*alpha)*(1-0.5*alpha)*(Smooth-2*Smooth[1]+Smooth[2])+2*(1-alpha)*Cycle[1]-(1-alpha)*(1-alpha)*Cycle[2]; If currentbar<7 then Cycle=(Price-2*Price[1]+Price[2])/4; MaxVal=Highest(Cycle, StocLength); MinVal=Lowest(Cycle, StocLength); If MaxVal<>MinVal then Value1=(Cycle-MinVal)/(MaxVal-MinVal); Value2=(4*Value1+3*Value1[1]+2*Value1[2]+Value1[3])/10; Value2=2*(Value2-0.5); oResult1=Value2; oResult2=0.96*(Value2[1]+0.02); end else If ( OscType=6 ) then Begin {Stochastic CG} Num=0; Denom=0; For count=0 to Length-1 Begin Num=Num+(1+count)*Price[count]; Denom=Denom+Price[count]; end; If Denom<>0 then CG=-Num/Denom+(Length+1)/2; MaxVal=Highest(CG, Length); MinVal=Lowest(CG, Length); If MaxVal<>MinVal then Value1=(CG-MinVal)/(MaxVal-MinVal); Value2=(4*Value1+3*Value1[1]+2*Value1[2]+Value1[3])/10; Value2=2*(Value2-0.5); oResult1=Value2; oResult2=0.96*(Value2[1]+0.02); end else If ( OscType=7 ) then Begin {Stochastic RVI} Value1=((Close-Open)+2*(Close[1]-Open[1])+2*(Close[2]-Open[2])+(Close[3]-Open[3]))/6; Value2=((High-Low)+2*(High[1]-Low[1])+2*(High[2]-Low[2])+(High[3]-Low[3]))/6; Num=0; Denom=0; For count=0 to Length-1 Begin Num=Num+Value1[count]; Denom=Denom+Value2[count]; end; If Denom<>0 then RVI=Num/Denom; MaxVal=Highest(RVI, Length); MinVal=Lowest(RVI, Length); If MaxVal<>MinVal then Value3=(RVI-MinVal)/(MaxVal-MinVal); Value4=(4*Value3+3*Value3[1]+2*Value3[2]+Value3[3])/10; Value4=2*(Value4-0.5); oResult1=Value4; oResult2=0.96*(Value4[1]+0.02); end else If ( OscType=8 ) then Begin {Fisher Cyber Cycle} alpha=2/(Length+1); Smooth=(Price+2*Price[1]+2*Price[2]+Price[3])/6; Cycle=(1-0.5*alpha)*(1-0.5*alpha)*(Smooth-2*Smooth[1]+Smooth[2])+2*(1-alpha)*Cycle[1]-(1-alpha)*(1-alpha)*Cycle[2]; If currentbar<7 then Cycle=(Price-2*Price[1]+Price[2])/4; MaxVal=Highest(Cycle, Length2); MinVal=Lowest(Cycle, Length2); If MaxVal<>MinVal then Value1=(Cycle-MinVal)/(MaxVal-MinVal); Value2=(4*Value1+3*Value1[1]+2*Value1[2]+Value1[3])/10; Value3=0.5*Log((1+1.98*(Value2-0.5))/(1-1.98*(Value2-0.5))); oResult1=Value3; oResult2=Value3[1]; end else If ( OscType=9 ) then Begin {Fisher CG} Num=0; Denom=0; For count=0 to length-1 Begin Num=Num+(1+count)*(Price[count]); Denom=Denom+(Price[count]); end; If Denom<>0 then CG=-Num/Denom+(Length+1)/2; MaxVal=Highest(CG, Length); MinVal=Lowest(CG, Length); If MaxVal<>MinVal then Value1=(CG-MinVal)/(MaxVal-MinVal); Value2=(4*Value1+3*Value1[1]+2*Value1[2]+Value1[3])/10; Value3=0.5*Log((1+1.98*(Value2-0.5))/(1-1.98*(Value2-0.5))); oResult1=Value3; oResult2=Value3[1]; end else If ( OscType=10 ) then Begin {Fisher RVI} Value1=((Close-Open)+2*(Close[1]-Open[1])+2*(Close[2]-Open[2])+(Close[3]-Open[3]))/6; Value2=((High-Low)+2*(High[1]-Low[1])+2*(High[2]-Low[2])+(High[3]-Low[3]))/6; Num=0; Denom=0; For count=0 to Length-1 Begin Num=Num+Value1[count]; Denom=Denom+Value2[count]; end; If Denom<>0 then RVI=Num/Denom; MaxVal=Highest(RVI, Length); MinVal=Lowest(RVI, Length); If MaxVal<>MinVal then Value3=(RVI-MinVal)/(MaxVal-MinVal); Value4=(4*Value3+3*Value3[1]+2*Value3[2]+Value3[3])/10; Value5=0.5*Log((1+1.98*(Value4-0.5))/(1-1.98*(Value4-0.5))); oResult1=Value5; oResult2=Value5[1]; end else If ( OscType=11 ) then Begin {Adaptive Cyber Cycle} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); alpha=2/(Period+1); Cycle=(1-0.5*alpha)*(1-0.5*alpha)*(Smooth1-2*Smooth1[1]+Smooth1[2])+2*(1-alpha)*Cycle[1]-(1-alpha)*(1-alpha)*Cycle[2]; If currentbar<7 then Cycle=(Price-2*Price[1]+Price[2])/4; oResult1=Cycle; oResult2=Cycle[1]; end else If ( OscType=12 ) then Begin {Adaptive CG} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); Value1=IntPortion(Period/2); {use half the cycle period} Num=0; Denom=0; For count=0 to Value1-1 Begin Num=Num+(1+count)*(Price[count]); Denom=Denom+(Price[count]); end; If Denom<>0 then CG=-Num/Denom+(Value1+1)/2; oResult1=CG; oResult2=CG[1]; end else If ( OscType=13 ) then Begin {Adaptive RVI} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); Value3=IntPortion((4*Period+3*Period[1]+2*Period[3]+Period[4])/20); Value1=((Close-Open)+2*(Close[1]-Open[1])+2*(Close[2]-Open[2])+(Close[3]-Open[3]))/6; Value2=((High-Low)+2*(High[1]-Low[1])+2*(High[2]-Low[2])+(High[3]-Low[3]))/6; Num=0; Denom=0; For count=0 to Value3-1 Begin Num=Num+Value1[count]; Denom=Denom+Value2[count]; end; If Denom<>0 then RVI=Num/Denom; oResult1=RVI; oResult2=RVI[1]; end else If ( OscType=14 ) then Begin {Sinewave Indicator} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); DCPeriod=IntPortion(Period); RealPart=0; ImagPart=0; For count=0 to DCPeriod-1 Begin RealPart=RealPart+Sine(360*count/DCPeriod)*(Cycle1[count]); ImagPart=ImagPart+Cosine(360*count/DCPeriod)*(Cycle1[count]); end; If AbsValue(ImagPart)>0.001 then DCPhase=Arctangent(RealPart/ImagPart); If AbsValue(ImagPart)<=0.001 then DCPhase=90*Sign(RealPart); DCPhase=DCPhase+90; If ImagPart<0 then DCPhase=DCPhase+180; If DCPhase>315 then DCPhase=DCPhase-360; oResult1=Sine(DCPhase); oResult2=Sine(DCPhase+45); end else If ( OscType=15 ) then Begin {Laguerre RSI} L0=(1-Length2)*Close+Length2*L0[1]; L1=-Length2*L0+L0[1]+Length2*L1[1]; L2=-Length2*L1+L1[1]+Length2*L2[1]; L3=-Length2*L2+L2[1]+Length2*L3[1]; CU=0; CD=0; If L0>=L1 then CU=L0-L1 else CD=L1-L0; If L1>=L2 then CU=CU+L1-L2 else CD=CD+L2-L1; If L2>=L3 then CU=CU+L2-L3 else CD=CD+L3-L2; If CU+CD<>0 then vRSI=CU/(CU+CD); oResult1=vRSI; oResult2=0; end else If ( OscType=16 ) then Begin {Adaptive RSI} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); CU=0; CD=0; For count=0 to (Period*Length2)-1 Begin If Close[count]-Close[count+1]>0 then CU=CU+(Close[count]-Close[count+1]); If Close[count]-Close[count+1]<0 then CD=CD+(Close[count+1]-Close[count]); end; If CU+CD<>0 then vRSI=100*CU/(CU+CD); oResult1=vRSI; oResult2=0; end else If ( OscType=17 ) then Begin {Adaptive Stochastic} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); HH=High; LL=Low; For count=0 to IntPortion(Period*Length2)-1 Begin If High[count]>HH then HH=High[count]; If Low[count]<LL then LL=Low[count]; end; If HH-LL<>0 then vStoch=(Close-LL)/(HH-LL); oResult1=vStoch; oResult2=0; end else If ( OscType=18 ) then Begin {Adaptive CCI} alpha=2/(Length+1); Period=_CyclePeriod(Price, alpha, Cycle1, Smooth1); Value1=IntPortion(Period*Length2); MPrice=(High+Low+Close)/3; Avg=0; For count=0 to Value1-1 Begin Avg=Avg+MPrice[count]; end; If Value1<>0 then Avg=Avg/Value1; MD=0; For count=0 to Value1-1 Begin MD=MD+AbsValue(MPrice[count]-Avg); end; If Value1<>0 then MD=MD/Value1; If MD<>0 then vCCI=(MPrice-Avg)/(0.015*MD); oResult1=vCCI; oResult2=0; end; _Oscillators=1; _cycleperiod function {Cycle Period Measurement From the book 'Cybernetic Analysis for Stocks and Futures' by John Ehlers mmillar, July 2004 This function is called with Price - the current price, such as (H+L)/2 or Close alpha - the alpha (which is related to the measurement period/length) oCycle - a return variable that is needed by some indicators } Inputs: Price(numeric), alpha(numeric), oCycle(numericref), oSmooth(numericref); Vars: Smooth(0), Cycle(0), Q1(0), I1(0), DC(0), DeltaPhase(0), MedianDelta(0), InstPeriod(0), Period(0); Smooth=(Price+2*Price[1]+2*Price[2]+Price[3])/6; Cycle=(1-0.5*alpha)*(1-0.5*alpha)*(Smooth-2*Smooth[1]+Smooth[2])+2*(1-alpha)*Cycle[1]-(1-alpha)*(1 -alpha)*Cycle[2]; If currentbar<7 then Cycle=(Price-2*Price[1]+Price[2])/4; Q1=(0.0962*Cycle+0.5769*Cycle[2]-0.5769*Cycle[4]-0.0962*Cycle[6])*(0.5+0.08*InstPeriod[1]); I1=Cycle[3]; If Q1<>0 and Q1[1]<>0 then DeltaPhase=(I1/Q1-I1[1]/Q1[1])/(1+I1*I1[1]/(Q1*Q1[1])); If DeltaPhase<0.1 then DeltaPhase=0.1; If DeltaPhase>1.1 then DeltaPhase=1.1; MedianDelta=Median(DeltaPhase, 5); If MedianDelta=0 then DC=15 else DC=6.28318/MedianDelta+0.5; InstPeriod=0.33*DC+0.67*InstPeriod[1]; Period=0.15*InstPeriod+0.85*Period[1]; oCycle=Cycle; oSmooth=Smooth; _CyclePeriod=Period;

After enjoying some indicators posted by fellow traders, i just want to give my participation and bring this interesting indicators created by John Ehlers ; i am still new to this studies but will be nice if someone already advance with the "corona charts" can give us they views. CORONACHARTS.ELD CoronaCharts.pdf

Fisher Transform by John Ehlers The fisher transform indicator by John Ehlers is a range oscillator showing where today's price is within the past N-days highest and lowest. It has some smoothing, plus what's known in mathematics as a fisher transform. The range position is similar to Stochastics and to Williams %R. The fisher transformation stretches out values near the N-day high and low to make large peaks so as to help highlight those extremes. The calculation is as follows: The prices used are the midpoint between the day's high and low (as in most of Ehlers' indicators). Today's price is located within the highest and lowest of those midpoints from the past N days, scaled to -1 for the low and 1 for the high. price = (high + low) / 2 price - Ndaylow raw = 2 * ----------------------- - 1 Ndayhigh - Ndaylow This raw position is smoothed by a 5-day EMA (see Exponential Moving Average) then a log form which is the fisher transform, before a final further 3-day EMA smoothing. smoothed = EMA[5] of raw 1 + smoothed fisher = EMA[3] of log ------------------ 1 - smoothed The effect of the logarithm is to make “smoothed” values near 0 remain near there, but values near 1 and -1 grow greatly, thus highlighting extremities. A “smoothed” value of exactly +/-1 would transform to +/-infinity, so a clamp of 0.999 is applied, effectively limiting the final result to about +/-7.5. Source: Kevin Ryde FisherTransform.txt FisherTransform_(MultiCharts).pla

Fourier Transform by John F. Ehlers Have fun with colors... This is as much an exercise in programming as a psychoanalytical experience. Feel free to share your signaling enlightenments. Fourier_Transform_(MultiCharts).pla Fourier_Transform.txt