Screener Super Trend AI Clustering

• 09/11/2025 at 4:55 PM #250715
  Alai-n

  Bonjour,

  Je souhaiterais modifier ce code disponible dans la bibliothèque des Indicateurs, le Super Trend AI Clustering.

  Seulement, lorsque je fais une tentative j’ai des erreurs de syntaxe en pagaille que je n’arrive pas à régler!

  Serait-il possible de simplifier l’écriture de ce code afin de pouvoir l’utiliser dans un Screener ?

  Merci

  Super Trend AI Clustering

  //---------------------------------------------------------------// //SuperTrend AI Clustering //version = 2 //02.06.2025 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //---------------------------------------------------------------// //-----Inputs----------------------------------------------------// //---------------------------------------------------------------// //length=10 // ATR length //minMult=1 //maxMult=5 //step=0.5 //perfAlpha=10 // Performance memory //fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //---------------------------------------------------------------// //-----Average True Range----------------------------------------// //---------------------------------------------------------------// atr=averagetruerange[length](close) //---------------------------------------------------------------// //-----Supertrend cálculo múltiple-------------------------------// //---------------------------------------------------------------// $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2 k=0 for factor=0 to floor((maxMult-minMult)/step) do up=(high+low)/2+atr*factor dn=(high+low)/2-atr*factor if close > $holderUpper[k] then $holderTrend[k]=1 elsif close < $holderUpper[k] then $holderTrend[k]=0 else $holderTrend[k]=$holderTrend[k] endif if close[1]<$holderUpper[k] then $holderUpper[k]=min(up,$holderUpper[k]) else $holderUpper[k]=up endif if close[1]>$holderLower[k] then $holderLower[k]=max(dn,$holderLower[k]) else $holderLower[k]=dn endif if (close[1]-$holderOutput[k])>0 then diff=1 elsif (close[1]-$holderOutput[k])<0 then diff=-1 else diff=0 endif $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)]) if $holderTrend[k]=1 then $holderOutput[k]=$holderLower[k] else $holderOutput[k]=$holderUpper[k] endif $holderFactor[k] = (minMult+k*step) k=k+1 next //---------------------------------------------------------------// //-----K-means con convergencia----------------------------------// //---------------------------------------------------------------// centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k FOR i = 0 TO count - 1 DO IF i < count / 3 THEN centroid1 = centroid1 + $holderPerf[i] ELSIF i < 2 * count / 3 THEN centroid2 = centroid2 + $holderPerf[i] ELSE centroid3 = centroid3 + $holderPerf[i] ENDIF NEXT centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3) converged = 0 iter = 0 WHILE iter < maxiter AND converged = 0 DO old1 = centroid1 old2 = centroid2 old3 = centroid3 $cluster1Perf[0] = 0 $cluster2Perf[0] = 0 $cluster3Perf[0] = 0 $cluster1Factors[0] = 0 $cluster2Factors[0] = 0 $cluster3Factors[0] = 0 FOR i = 0 TO count - 1 DO dist1 = abs($holderPerf[i] - centroid1) dist2 = abs($holderPerf[i] - centroid2) dist3 = abs($holderPerf[i] - centroid3) IF dist1 <= dist2 AND dist1 <= dist3 THEN $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i] $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i] $cluster1Perf[0] = $cluster1Perf[0] + 1 $cluster1Factors[0] = $cluster1Factors[0] + 1 ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i] $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i] $cluster2Perf[0] = $cluster2Perf[0] + 1 $cluster2Factors[0] = $cluster2Factors[0] + 1 ELSE $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i] $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i] $cluster3Perf[0] = $cluster3Perf[0] + 1 $cluster3Factors[0] = $cluster3Factors[0] + 1 ENDIF NEXT centroid1 = 0 centroid2 = 0 centroid3 = 0 IF $cluster1Perf[0] > 0 THEN FOR i = 1 TO $cluster1Perf[0] DO centroid1 = centroid1 + $cluster1Perf[i] NEXT centroid1 = centroid1 / $cluster1Perf[0] ENDIF IF $cluster2Perf[0] > 0 THEN FOR i = 1 TO $cluster2Perf[0] DO centroid2 = centroid2 + $cluster2Perf[i] NEXT centroid2 = centroid2 / $cluster2Perf[0] ENDIF IF $cluster3Perf[0] > 0 THEN FOR i = 1 TO $cluster3Perf[0] DO centroid3 = centroid3 + $cluster3Perf[i] NEXT centroid3 = centroid3 / $cluster3Perf[0] ENDIF IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN converged = 1 ENDIF iter = iter + 1 WEND //---------------------------------------------------------------// //-----Cluster seleccionado y nuevo Supertrend-------------------// //---------------------------------------------------------------// finalFactor = 0 finalPerf = 0 perf = 0 fact = 0 IF fromCluster = 1 THEN // Best IF centroid1 > max(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 > max(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF ELSIF fromCluster = 2 THEN // Average IF centroid1 > centroid2 AND centroid1 < centroid3 THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 > centroid1 AND centroid2 < centroid3 THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF ELSIF fromCluster = 3 THEN // Worst IF centroid1 < min(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 < min(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF ENDIF //---------------------------------------------------------------// //-----Renderizado final del Supertrend--------------------------// //---------------------------------------------------------------// newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor if close[1] < newupper then newupper = min(newup, newupper) else newupper = newup endif if close[1] > newlower then newlower = max(newdown, newlower) else newlower = newdown endif if close > newupper then newOS = 1 elsif close < newlower then newOS = 0 else newOS = newOS endif if newOS and newOS[1]=0 then newST = newlower r = 0 g = 255 transp=0 elsif newOS then newST = newlower r = 0 g = 255 transp=255 elsif newOS=0 and newOS[1] then newST = newupper r = 255 g = 0 transp=0 else newST = newupper r = 255 g = 0 transp=255 endif //---------------------------------------------------------------// return newST style(line,2) coloured(r,g,0,transp)

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  //---------------------------------------------------------------// //SuperTrend AI Clustering //version = 2 //02.06.2025 //Iván González @ www.prorealcode.com //Sharing ProRealTime knowledge //---------------------------------------------------------------// //-----Inputs----------------------------------------------------// //---------------------------------------------------------------// //length=10 // ATR length //minMult=1 //maxMult=5 //step=0.5 //perfAlpha=10 // Performance memory //fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //---------------------------------------------------------------// //-----Average True Range----------------------------------------// //---------------------------------------------------------------// atr=averagetruerange[length](close) //---------------------------------------------------------------// //-----Supertrend cálculo múltiple-------------------------------// //---------------------------------------------------------------// $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2   k=0 for factor=0 to floor((maxMult-minMult)/step) do up=(high+low)/2+atr*factor dn=(high+low)/2-atr*factor   if close > $holderUpper[k] then $holderTrend[k]=1 elsif close < $holderUpper[k] then $holderTrend[k]=0 else $holderTrend[k]=$holderTrend[k] endif   if close[1]<$holderUpper[k] then $holderUpper[k]=min(up,$holderUpper[k]) else $holderUpper[k]=up endif   if close[1]>$holderLower[k] then $holderLower[k]=max(dn,$holderLower[k]) else $holderLower[k]=dn endif   if (close[1]-$holderOutput[k])>0 then diff=1 elsif (close[1]-$holderOutput[k])<0 then diff=-1 else diff=0 endif   $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)])   if $holderTrend[k]=1 then $holderOutput[k]=$holderLower[k] else $holderOutput[k]=$holderUpper[k] endif   $holderFactor[k] = (minMult+k*step)   k=k+1 next //---------------------------------------------------------------// //-----K-means con convergencia----------------------------------// //---------------------------------------------------------------// centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k   FOR i = 0 TO count - 1 DO IF i < count / 3 THEN centroid1 = centroid1 + $holderPerf[i] ELSIF i < 2 * count / 3 THEN centroid2 = centroid2 + $holderPerf[i] ELSE centroid3 = centroid3 + $holderPerf[i] ENDIF NEXT   centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3)   converged = 0 iter = 0   WHILE iter < maxiter AND converged = 0 DO old1 = centroid1 old2 = centroid2 old3 = centroid3   $cluster1Perf[0] = 0 $cluster2Perf[0] = 0 $cluster3Perf[0] = 0 $cluster1Factors[0] = 0 $cluster2Factors[0] = 0 $cluster3Factors[0] = 0   FOR i = 0 TO count - 1 DO dist1 = abs($holderPerf[i] - centroid1) dist2 = abs($holderPerf[i] - centroid2) dist3 = abs($holderPerf[i] - centroid3)   IF dist1 <= dist2 AND dist1 <= dist3 THEN $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i] $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i] $cluster1Perf[0] = $cluster1Perf[0] + 1 $cluster1Factors[0] = $cluster1Factors[0] + 1 ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i] $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i] $cluster2Perf[0] = $cluster2Perf[0] + 1 $cluster2Factors[0] = $cluster2Factors[0] + 1 ELSE $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i] $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i] $cluster3Perf[0] = $cluster3Perf[0] + 1 $cluster3Factors[0] = $cluster3Factors[0] + 1 ENDIF NEXT   centroid1 = 0 centroid2 = 0 centroid3 = 0   IF $cluster1Perf[0] > 0 THEN FOR i = 1 TO $cluster1Perf[0] DO centroid1 = centroid1 + $cluster1Perf[i] NEXT centroid1 = centroid1 / $cluster1Perf[0] ENDIF IF $cluster2Perf[0] > 0 THEN FOR i = 1 TO $cluster2Perf[0] DO centroid2 = centroid2 + $cluster2Perf[i] NEXT centroid2 = centroid2 / $cluster2Perf[0] ENDIF IF $cluster3Perf[0] > 0 THEN FOR i = 1 TO $cluster3Perf[0] DO centroid3 = centroid3 + $cluster3Perf[i] NEXT centroid3 = centroid3 / $cluster3Perf[0] ENDIF   IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN converged = 1 ENDIF   iter = iter + 1 WEND //---------------------------------------------------------------// //-----Cluster seleccionado y nuevo Supertrend-------------------// //---------------------------------------------------------------// finalFactor = 0 finalPerf = 0 perf = 0 fact = 0   IF fromCluster = 1 THEN // Best IF centroid1 > max(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 > max(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF   ELSIF fromCluster = 2 THEN // Average IF centroid1 > centroid2 AND centroid1 < centroid3 THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 > centroid1 AND centroid2 < centroid3 THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF   ELSIF fromCluster = 3 THEN // Worst IF centroid1 < min(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) if lastset($cluster1Perf) > 0 then finalPerf = perf / lastset($cluster1Perf) else finalPerf = 0 endif ELSIF centroid2 < min(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) if lastset($cluster2Perf) > 0 then finalPerf = perf / lastset($cluster2Perf) else finalPerf = 0 endif ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) if lastset($cluster3Perf) > 0 then finalPerf = perf / lastset($cluster3Perf) else finalPerf = 0 endif ENDIF ENDIF //---------------------------------------------------------------// //-----Renderizado final del Supertrend--------------------------// //---------------------------------------------------------------// newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor   if close[1] < newupper then newupper = min(newup, newupper) else newupper = newup endif   if close[1] > newlower then newlower = max(newdown, newlower) else newlower = newdown endif   if close > newupper then newOS = 1 elsif close < newlower then newOS = 0 else newOS = newOS endif   if newOS and newOS[1]=0 then newST = newlower r = 0 g = 255 transp=0 elsif newOS then newST = newlower r = 0 g = 255 transp=255 elsif newOS=0 and newOS[1] then newST = newupper r = 255 g = 0 transp=0 else newST = newupper r = 255 g = 0 transp=255 endif //---------------------------------------------------------------// return newST style(line,2) coloured(r,g,0,transp)

   

  

  Alai-n

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  09/11/2025 at 5:19 PM #250724
  robertogozzi

  Les lignes 156 et 157 étaient séparées, alors qu’elles auraient dû être une seule ligne :

  IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN

  1	IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN

   

  

  robertogozzi

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  09/12/2025 at 8:53 AM #250743
  Iván

  Bonjour. Tu dois supprimer toutes les variables qui ne sont pas utilisées dans le code.

  //-----Inputs length=10 minMult=1 maxMult=5 step=0.5 perfAlpha=10 // Performance memory fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //-----Average True Range atr=averagetruerange[length](close) //-----Supertrend cálculo múltiple $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2 k=0 for factor=0 to floor((maxMult-minMult)/step) do up=(high+low)/2+atr*factor dn=(high+low)/2-atr*factor if close > $holderUpper[k] then $holderTrend[k]=1 elsif close < $holderUpper[k] then $holderTrend[k]=0 else $holderTrend[k]=$holderTrend[k] endif if close[1]<$holderUpper[k] then $holderUpper[k]=min(up,$holderUpper[k]) else $holderUpper[k]=up endif if close[1]>$holderLower[k] then $holderLower[k]=max(dn,$holderLower[k]) else $holderLower[k]=dn endif if (close[1]-$holderOutput[k])>0 then diff=1 elsif (close[1]-$holderOutput[k])<0 then diff=-1 else diff=0 endif $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)]) if $holderTrend[k]=1 then $holderOutput[k]=$holderLower[k] else $holderOutput[k]=$holderUpper[k] endif $holderFactor[k] = (minMult+k*step) k=k+1 next //-----K-means con convergencia centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k FOR i = 0 TO count - 1 DO IF i < count / 3 THEN centroid1 = centroid1 + $holderPerf[i] ELSIF i < 2 * count / 3 THEN centroid2 = centroid2 + $holderPerf[i] ELSE centroid3 = centroid3 + $holderPerf[i] ENDIF NEXT centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3) converged = 0 iter = 0 WHILE iter < maxiter AND converged = 0 DO old1 = centroid1 old2 = centroid2 old3 = centroid3 $cluster1Perf[0] = 0 $cluster2Perf[0] = 0 $cluster3Perf[0] = 0 $cluster1Factors[0] = 0 $cluster2Factors[0] = 0 $cluster3Factors[0] = 0 FOR i = 0 TO count - 1 DO dist1 = abs($holderPerf[i] - centroid1) dist2 = abs($holderPerf[i] - centroid2) dist3 = abs($holderPerf[i] - centroid3) IF dist1 <= dist2 AND dist1 <= dist3 THEN $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i] $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i] $cluster1Perf[0] = $cluster1Perf[0] + 1 $cluster1Factors[0] = $cluster1Factors[0] + 1 ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i] $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i] $cluster2Perf[0] = $cluster2Perf[0] + 1 $cluster2Factors[0] = $cluster2Factors[0] + 1 ELSE $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i] $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i] $cluster3Perf[0] = $cluster3Perf[0] + 1 $cluster3Factors[0] = $cluster3Factors[0] + 1 ENDIF NEXT centroid1 = 0 centroid2 = 0 centroid3 = 0 IF $cluster1Perf[0] > 0 THEN FOR i = 1 TO $cluster1Perf[0] DO centroid1 = centroid1 + $cluster1Perf[i] NEXT centroid1 = centroid1 / $cluster1Perf[0] ENDIF IF $cluster2Perf[0] > 0 THEN FOR i = 1 TO $cluster2Perf[0] DO centroid2 = centroid2 + $cluster2Perf[i] NEXT centroid2 = centroid2 / $cluster2Perf[0] ENDIF IF $cluster3Perf[0] > 0 THEN FOR i = 1 TO $cluster3Perf[0] DO centroid3 = centroid3 + $cluster3Perf[i] NEXT centroid3 = centroid3 / $cluster3Perf[0] ENDIF IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN converged = 1 ENDIF iter = iter + 1 WEND //-----Cluster seleccionado y nuevo Supertrend finalFactor = 0 perf = 0 fact = 0 IF fromCluster = 1 THEN // Best IF centroid1 > max(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) ELSIF centroid2 > max(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) ENDIF ELSIF fromCluster = 2 THEN // Average IF centroid1 > centroid2 AND centroid1 < centroid3 THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) ELSIF centroid2 > centroid1 AND centroid2 < centroid3 THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) ENDIF ELSIF fromCluster = 3 THEN // Worst IF centroid1 < min(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) ELSIF centroid2 < min(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) ENDIF ENDIF //-----Renderizado final del Supertrend newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor if close[1] < newupper then newupper = min(newup, newupper) else newupper = newup endif if close[1] > newlower then newlower = max(newdown, newlower) else newlower = newdown endif if close > newupper then newOS = 1 elsif close < newlower then newOS = 0 else newOS = newOS endif screener[newOS<>newOS[1]]

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  //-----Inputs length=10 minMult=1 maxMult=5 step=0.5 perfAlpha=10 // Performance memory fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //-----Average True Range atr=averagetruerange[length](close) //-----Supertrend cálculo múltiple $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2   k=0 for factor=0 to floor((maxMult-minMult)/step) do    up=(high+low)/2+atr*factor    dn=(high+low)/2-atr*factor       if close > $holderUpper[k] then       $holderTrend[k]=1    elsif close < $holderUpper[k] then       $holderTrend[k]=0    else       $holderTrend[k]=$holderTrend[k]    endif       if close[1]<$holderUpper[k] then       $holderUpper[k]=min(up,$holderUpper[k])    else       $holderUpper[k]=up    endif       if close[1]>$holderLower[k] then       $holderLower[k]=max(dn,$holderLower[k])    else       $holderLower[k]=dn    endif       if (close[1]-$holderOutput[k])>0 then       diff=1    elsif (close[1]-$holderOutput[k])<0 then       diff=-1    else       diff=0    endif       $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)])       if $holderTrend[k]=1 then       $holderOutput[k]=$holderLower[k]    else       $holderOutput[k]=$holderUpper[k]    endif       $holderFactor[k] = (minMult+k*step)       k=k+1 next //-----K-means con convergencia centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k   FOR i = 0 TO count - 1 DO    IF i < count / 3 THEN       centroid1 = centroid1 + $holderPerf[i]    ELSIF i < 2 * count / 3 THEN       centroid2 = centroid2 + $holderPerf[i]    ELSE       centroid3 = centroid3 + $holderPerf[i]    ENDIF NEXT   centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3)   converged = 0 iter = 0   WHILE iter < maxiter AND converged = 0 DO    old1 = centroid1    old2 = centroid2    old3 = centroid3       $cluster1Perf[0] = 0    $cluster2Perf[0] = 0    $cluster3Perf[0] = 0    $cluster1Factors[0] = 0    $cluster2Factors[0] = 0    $cluster3Factors[0] = 0       FOR i = 0 TO count - 1 DO       dist1 = abs($holderPerf[i] - centroid1)       dist2 = abs($holderPerf[i] - centroid2)       dist3 = abs($holderPerf[i] - centroid3)              IF dist1 <= dist2 AND dist1 <= dist3 THEN          $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i]          $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i]          $cluster1Perf[0] = $cluster1Perf[0] + 1          $cluster1Factors[0] = $cluster1Factors[0] + 1       ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN          $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i]          $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i]          $cluster2Perf[0] = $cluster2Perf[0] + 1          $cluster2Factors[0] = $cluster2Factors[0] + 1       ELSE          $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i]          $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i]          $cluster3Perf[0] = $cluster3Perf[0] + 1          $cluster3Factors[0] = $cluster3Factors[0] + 1       ENDIF    NEXT       centroid1 = 0    centroid2 = 0    centroid3 = 0       IF $cluster1Perf[0] > 0 THEN       FOR i = 1 TO $cluster1Perf[0] DO          centroid1 = centroid1 + $cluster1Perf[i]       NEXT       centroid1 = centroid1 / $cluster1Perf[0]    ENDIF    IF $cluster2Perf[0] > 0 THEN       FOR i = 1 TO $cluster2Perf[0] DO          centroid2 = centroid2 + $cluster2Perf[i]       NEXT       centroid2 = centroid2 / $cluster2Perf[0]    ENDIF    IF $cluster3Perf[0] > 0 THEN       FOR i = 1 TO $cluster3Perf[0] DO          centroid3 = centroid3 + $cluster3Perf[i]       NEXT       centroid3 = centroid3 / $cluster3Perf[0]    ENDIF       IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN       converged = 1    ENDIF       iter = iter + 1 WEND   //-----Cluster seleccionado y nuevo Supertrend finalFactor = 0 perf = 0 fact = 0   IF fromCluster = 1 THEN    // Best    IF centroid1 > max(centroid2, centroid3) THEN       FOR j = 1 TO lastset($cluster1Perf) DO          perf = perf + $cluster1Perf[j]          fact = fact + $cluster1Factors[j]       NEXT       finalFactor = fact / lastset($cluster1Factors)           ELSIF centroid2 > max(centroid1, centroid3) THEN       FOR j = 1 TO lastset($cluster2Perf) DO          perf = perf + $cluster2Perf[j]          fact = fact + $cluster2Factors[j]       NEXT       finalFactor = fact / lastset($cluster2Factors)           ELSE       FOR j = 1 TO lastset($cluster3Perf) DO          perf = perf + $cluster3Perf[j]          fact = fact + $cluster3Factors[j]       NEXT       finalFactor = fact / lastset($cluster3Factors)           ENDIF    ELSIF fromCluster = 2 THEN    // Average    IF centroid1 > centroid2 AND centroid1 < centroid3 THEN       FOR j = 1 TO lastset($cluster1Perf) DO          perf = perf + $cluster1Perf[j]          fact = fact + $cluster1Factors[j]       NEXT       finalFactor = fact / lastset($cluster1Factors)           ELSIF centroid2 > centroid1 AND centroid2 < centroid3 THEN       FOR j = 1 TO lastset($cluster2Perf) DO          perf = perf + $cluster2Perf[j]          fact = fact + $cluster2Factors[j]       NEXT       finalFactor = fact / lastset($cluster2Factors)           ELSE       FOR j = 1 TO lastset($cluster3Perf) DO          perf = perf + $cluster3Perf[j]          fact = fact + $cluster3Factors[j]       NEXT       finalFactor = fact / lastset($cluster3Factors)           ENDIF    ELSIF fromCluster = 3 THEN    // Worst    IF centroid1 < min(centroid2, centroid3) THEN       FOR j = 1 TO lastset($cluster1Perf) DO          perf = perf + $cluster1Perf[j]          fact = fact + $cluster1Factors[j]       NEXT       finalFactor = fact / lastset($cluster1Factors)           ELSIF centroid2 < min(centroid1, centroid3) THEN       FOR j = 1 TO lastset($cluster2Perf) DO          perf = perf + $cluster2Perf[j]          fact = fact + $cluster2Factors[j]       NEXT       finalFactor = fact / lastset($cluster2Factors)           ELSE       FOR j = 1 TO lastset($cluster3Perf) DO          perf = perf + $cluster3Perf[j]          fact = fact + $cluster3Factors[j]       NEXT       finalFactor = fact / lastset($cluster3Factors)           ENDIF ENDIF //-----Renderizado final del Supertrend newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor   if close[1] < newupper then    newupper = min(newup, newupper) else    newupper = newup endif   if close[1] > newlower then    newlower = max(newdown, newlower) else    newlower = newdown endif   if close > newupper then    newOS = 1 elsif close < newlower then    newOS = 0 else    newOS = newOS endif   screener[newOS<>newOS[1]]

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  Alai-n

  

  Iván

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  09/22/2025 at 2:31 PM #251264
  Alai-n

  Bonjour,

  J’ai un problème pour terminer ce Screener, les résultats retournés ne sont pas juste! Ici sur la photo jointe, pour se rendre compte du problème, je l’ai posé comme un indicateur dans une fenêtre sous le prix.

  L’idée initiale est de mettre en évidence la tendance haussière ou baissière du SuperTrend AI Clustering ligne 204 à 230 dans le code. Mais on peut voir clairement qu’il y a une différence notable entre l’indicateur sur le graphique et l’indicateur dans la fenêtre sous le prix…

  Je ne trouve pas la solution !

  //-----Inputs length=10 minMult=1 maxMult=5 step=0.5 perfAlpha=10 // Performance memory fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //-----Average True Range atr=averagetruerange[length](close) //-----Supertrend cálculo múltiple $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2 k=0 for factor=0 to floor((maxMult-minMult)/step) do up=(high+low)/2+atr*factor dn=(high+low)/2-atr*factor if close > $holderUpper[k] then $holderTrend[k]=1 elsif close < $holderUpper[k] then $holderTrend[k]=0 else $holderTrend[k]=$holderTrend[k] endif if close[1]<$holderUpper[k] then $holderUpper[k]=min(up,$holderUpper[k]) else $holderUpper[k]=up endif if close[1]>$holderLower[k] then $holderLower[k]=max(dn,$holderLower[k]) else $holderLower[k]=dn endif if (close[1]-$holderOutput[k])>0 then diff=1 elsif (close[1]-$holderOutput[k])<0 then diff=-1 else diff=0 endif $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)]) if $holderTrend[k]=1 then $holderOutput[k]=$holderLower[k] else $holderOutput[k]=$holderUpper[k] endif $holderFactor[k] = (minMult+k*step) k=k+1 next //-----K-means con convergencia centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k FOR i = 0 TO count - 1 DO IF i < count / 3 THEN centroid1 = centroid1 + $holderPerf[i] ELSIF i < 2 * count / 3 THEN centroid2 = centroid2 + $holderPerf[i] ELSE centroid3 = centroid3 + $holderPerf[i] ENDIF NEXT centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3) converged = 0 iter = 0 WHILE iter < maxiter AND converged = 0 DO old1 = centroid1 old2 = centroid2 old3 = centroid3 $cluster1Perf[0] = 0 $cluster2Perf[0] = 0 $cluster3Perf[0] = 0 $cluster1Factors[0] = 0 $cluster2Factors[0] = 0 $cluster3Factors[0] = 0 FOR i = 0 TO count - 1 DO dist1 = abs($holderPerf[i] - centroid1) dist2 = abs($holderPerf[i] - centroid2) dist3 = abs($holderPerf[i] - centroid3) IF dist1 <= dist2 AND dist1 <= dist3 THEN $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i] $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i] $cluster1Perf[0] = $cluster1Perf[0] + 1 $cluster1Factors[0] = $cluster1Factors[0] + 1 ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i] $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i] $cluster2Perf[0] = $cluster2Perf[0] + 1 $cluster2Factors[0] = $cluster2Factors[0] + 1 ELSE $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i] $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i] $cluster3Perf[0] = $cluster3Perf[0] + 1 $cluster3Factors[0] = $cluster3Factors[0] + 1 ENDIF NEXT centroid1 = 0 centroid2 = 0 centroid3 = 0 IF $cluster1Perf[0] > 0 THEN FOR i = 1 TO $cluster1Perf[0] DO centroid1 = centroid1 + $cluster1Perf[i] NEXT centroid1 = centroid1 / $cluster1Perf[0] ENDIF IF $cluster2Perf[0] > 0 THEN FOR i = 1 TO $cluster2Perf[0] DO centroid2 = centroid2 + $cluster2Perf[i] NEXT centroid2 = centroid2 / $cluster2Perf[0] ENDIF IF $cluster3Perf[0] > 0 THEN FOR i = 1 TO $cluster3Perf[0] DO centroid3 = centroid3 + $cluster3Perf[i] NEXT centroid3 = centroid3 / $cluster3Perf[0] ENDIF IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN converged = 1 ENDIF iter = iter + 1 WEND //-----Cluster seleccionado y nuevo Supertrend finalFactor = 0 perf = 0 fact = 0 IF fromCluster = 1 THEN // Best IF centroid1 > max(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors) ELSIF centroid2 > max(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors) ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) ENDIF ENDIF //-----Renderizado final del Supertrend newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor if close[1] < newupper then newupper = min(newup, newupper) else newupper = newup endif if close[1] > newlower then newlower = max(newdown, newlower) else newlower = newdown endif if close > newupper then newOS = 1 elsif close < newlower then newOS = 0 else newOS = newOS endif ///////////////////////////////////////////////////////////////////////////////////////////////////////////////// if newOS[0]>newOS[1] then haussier = 1 endif if newOS[0]<newOS[1] then haussier = 0 endif // if newOS[0]<newOS[1] then baissier = 1 endif if newOS[0]>newOS[1] then baissier = 0 endif Signal = 0 If Haussier Then Signal = 1 Endif If Baissier Then Signal = -1 Endif ///////////////////////////////////////////////////////////////////////////////////////////////////////////////// ///////////////////////////////////////////////////////////////////////////////////////////////////////////////// Return Signal as "Signal" /////////////////////////////////////////////////////////////////////////////////////////////////////////////////

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  //-----Inputs length=10 minMult=1 maxMult=5 step=0.5 perfAlpha=10 // Performance memory fromCluster=1 // 1=best 2=average 3=worst maxiter=10 // Número máximo de iteraciones de clustering epsilon=0.0001 // Precisión para simular convergencia //-----Average True Range atr=averagetruerange[length](close) //-----Supertrend cálculo múltiple $holderUpper[0]=(high+low)/2 $holderLower[0]=(high+low)/2   k=0 for factor=0 to floor((maxMult-minMult)/step) do up=(high+low)/2+atr*factor dn=(high+low)/2-atr*factor    if close > $holderUpper[k] then $holderTrend[k]=1 elsif close < $holderUpper[k] then $holderTrend[k]=0 else $holderTrend[k]=$holderTrend[k] endif    if close[1]<$holderUpper[k] then $holderUpper[k]=min(up,$holderUpper[k]) else $holderUpper[k]=up endif    if close[1]>$holderLower[k] then $holderLower[k]=max(dn,$holderLower[k]) else $holderLower[k]=dn endif    if (close[1]-$holderOutput[k])>0 then diff=1 elsif (close[1]-$holderOutput[k])<0 then diff=-1 else diff=0 endif    $holderPerf[k]=$holderPerf[max(0,k-1)]+2/(perfAlpha+1)*((close-close[1])*diff-$holderPerf[max(0,k-1)])    if $holderTrend[k]=1 then $holderOutput[k]=$holderLower[k] else $holderOutput[k]=$holderUpper[k] endif    $holderFactor[k] = (minMult+k*step)    k=k+1 next //-----K-means con convergencia centroid1 = 0 centroid2 = 0 centroid3 = 0 count = k   FOR i = 0 TO count - 1 DO IF i < count / 3 THEN centroid1 = centroid1 + $holderPerf[i] ELSIF i < 2 * count / 3 THEN centroid2 = centroid2 + $holderPerf[i] ELSE centroid3 = centroid3 + $holderPerf[i] ENDIF NEXT   centroid1 = centroid1 / (count / 3) centroid2 = centroid2 / (count / 3) centroid3 = centroid3 / (count / 3)   converged = 0 iter = 0   WHILE iter < maxiter AND converged = 0 DO old1 = centroid1 old2 = centroid2 old3 = centroid3    $cluster1Perf[0] = 0 $cluster2Perf[0] = 0 $cluster3Perf[0] = 0 $cluster1Factors[0] = 0 $cluster2Factors[0] = 0 $cluster3Factors[0] = 0    FOR i = 0 TO count - 1 DO dist1 = abs($holderPerf[i] - centroid1) dist2 = abs($holderPerf[i] - centroid2) dist3 = abs($holderPerf[i] - centroid3)        IF dist1 <= dist2 AND dist1 <= dist3 THEN $cluster1Perf[$cluster1Perf[0]+1] = $holderPerf[i] $cluster1Factors[$cluster1Factors[0]+1] = $holderFactor[i] $cluster1Perf[0] = $cluster1Perf[0] + 1 $cluster1Factors[0] = $cluster1Factors[0] + 1 ELSIF dist2 <= dist1 AND dist2 <= dist3 THEN $cluster2Perf[$cluster2Perf[0]+1] = $holderPerf[i] $cluster2Factors[$cluster2Factors[0]+1] = $holderFactor[i] $cluster2Perf[0] = $cluster2Perf[0] + 1 $cluster2Factors[0] = $cluster2Factors[0] + 1 ELSE $cluster3Perf[$cluster3Perf[0]+1] = $holderPerf[i] $cluster3Factors[$cluster3Factors[0]+1] = $holderFactor[i] $cluster3Perf[0] = $cluster3Perf[0] + 1 $cluster3Factors[0] = $cluster3Factors[0] + 1 ENDIF NEXT    centroid1 = 0 centroid2 = 0 centroid3 = 0    IF $cluster1Perf[0] > 0 THEN FOR i = 1 TO $cluster1Perf[0] DO centroid1 = centroid1 + $cluster1Perf[i] NEXT centroid1 = centroid1 / $cluster1Perf[0] ENDIF IF $cluster2Perf[0] > 0 THEN FOR i = 1 TO $cluster2Perf[0] DO centroid2 = centroid2 + $cluster2Perf[i] NEXT centroid2 = centroid2 / $cluster2Perf[0] ENDIF IF $cluster3Perf[0] > 0 THEN FOR i = 1 TO $cluster3Perf[0] DO centroid3 = centroid3 + $cluster3Perf[i] NEXT centroid3 = centroid3 / $cluster3Perf[0] ENDIF    IF abs(centroid1 - old1) < epsilon AND abs(centroid2 - old2) < epsilon AND abs(centroid3 - old3) < epsilon THEN converged = 1 ENDIF    iter = iter + 1 WEND   //-----Cluster seleccionado y nuevo Supertrend finalFactor = 0 perf = 0 fact = 0   IF fromCluster = 1 THEN // Best IF centroid1 > max(centroid2, centroid3) THEN FOR j = 1 TO lastset($cluster1Perf) DO perf = perf + $cluster1Perf[j] fact = fact + $cluster1Factors[j] NEXT finalFactor = fact / lastset($cluster1Factors)        ELSIF centroid2 > max(centroid1, centroid3) THEN FOR j = 1 TO lastset($cluster2Perf) DO perf = perf + $cluster2Perf[j] fact = fact + $cluster2Factors[j] NEXT finalFactor = fact / lastset($cluster2Factors)        ELSE FOR j = 1 TO lastset($cluster3Perf) DO perf = perf + $cluster3Perf[j] fact = fact + $cluster3Factors[j] NEXT finalFactor = fact / lastset($cluster3Factors) ENDIF ENDIF   //-----Renderizado final del Supertrend newup = (high + low) / 2 + atr * finalFactor newdown = (high + low) / 2 - atr * finalFactor   if close[1] < newupper then newupper = min(newup, newupper) else newupper = newup endif   if close[1] > newlower then newlower = max(newdown, newlower) else newlower = newdown endif   if close > newupper then newOS = 1 elsif close < newlower then newOS = 0 else newOS = newOS endif     ///////////////////////////////////////////////////////////////////////////////////////////////////////////////// if newOS[0]>newOS[1] then haussier = 1 endif if newOS[0]<newOS[1] then haussier = 0 endif // if newOS[0]<newOS[1] then baissier = 1 endif if newOS[0]>newOS[1] then baissier = 0 endif   Signal = 0   If Haussier Then Signal = 1 Endif   If Baissier Then Signal = -1 Endif /////////////////////////////////////////////////////////////////////////////////////////////////////////////////     ///////////////////////////////////////////////////////////////////////////////////////////////////////////////// Return Signal as "Signal" /////////////////////////////////////////////////////////////////////////////////////////////////////////////////

  

  Alai-n

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  10/14/2025 at 11:25 AM #252578
  Alai-n

  UP

  @Iván je n’arrive pas à finir ce Screener de tendance, post précédent #251264 !

  Je souhaiterais de plus, pouvoir identifier lorsque l’on passe d’une situation haussière à une situation baissière(image ci-jointe) sur l’indicateur “Super Trend AI Clustering”, pour pouvoir l’incorporer dans une approche Multi TimeFrame et je ne m’en sors pas avec NewOs ou Newupper ou Newlower !!!

  

  Alai-n

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