Buongiorno, vorrei proporre traduzione di questo codice che sembra interessante, in quanto evidenzia molto chiaramente le fasi di stallo del mercato, potenzialmente propedeutiche a successivi movimenti. Grazie come sempre https://www.tradingview.com/script/OCl780V6-Machine-Learning-Momentum-Oscillator-ChartPrime/ // This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © ChartPrime //@version=5 indicator(“Machine Learning Momentum Oscillator [ChartPrime]”,shorttitle = “Machine Learning Momentum Oscillator [ChartPrime]” , overlay=false) string Core = “➞ ML Core Settings 🔸” int ShortPriod = input.int (26, ‘Short Period’, 1,group=Core) int LongPriod = input.int (14, ‘Long Period’, 2,group=Core) int Smooth = input.int (13, ‘Smoothing Period’, 2,group=Core) int Neighbours = math.floor(input.int (50,’Neighbours Count’, 5,group=Core)) bool showLines = input.bool(false,”Show prediction lines”) float prediction = 0.0 float small = 0.0 float BIG = 0.0 int Class = 0 //——– { type MachineLearning array<float> D1 array<float> D2 array<float> D3 array<int> dir array<int> Preds array<float> PerD type MLData float Prime1 float Prime2 float Prime3 float prediction float Smoothed float Band var ML = MachineLearning.new( array.new_float(0), array.new_float(0), array.new_float(), array.new_int(0), array.new_int(0), array.new_float() ) MData = MLData.new() method _Band(int len)=> math.min (ta.atr (len) * 0.3, close * (0.3/100)) [20] /2 method RawData(int x,z) => WS = ta.ema(hlc3 – hlc3[1], x) WQ = ta.ema(math.abs(hlc3 – hlc3[1]), x) Out = ta.ema(WS, z) Outs = ta.ema(WQ, z) Z = 100 * (Out / Outs) Z MData.Prime1 := RawData(LongPriod,Smooth) MData.Prime2 := RawData(ShortPriod,Smooth) MData.Band := _Band(30) * 2.5 max = MData.Prime2 + MData.Band min = MData.Prime2 – MData.Band for i = 0 to math.max(LongPriod,ShortPriod,Neighbours) Class := MData.Prime1[2] < MData.Prime1[0] ? -1 : MData.Prime1[2] > MData.Prime1[0] ? 1 : 0 ML.D1.push(MData.Prime1) ML.D2.push(MData.Prime2) ML.dir.push(Class) // if Algo.dir.size() > 10000 // Algo.dir.shift() // method MLCalculation(float x ,float y) => method MLCalculation(float x ,float y , float q , float z) => math.abs(x – y) + math.abs(q – z) // math.sqrt(math.abs(x – y) * math.abs(q – z)) // math.abs(x – y)) // Nearest Neighbor Calculations method Knn(MachineLearning MS) => float Minz = -1e-6 for i = 0 to MS.dir.size() – 1 MData.Prime3 := MLCalculation(MData.Prime1,MS.D1.get(i),MData.Prime2 ,MS.D2.get(i)) // MData.Prime3 := MLCalculation(MData.Prime1,ML.data.get(i)) if MData.Prime3 > Minz Minz := MData.Prime3 if MS.Preds.size() >= Neighbours MS.Preds.shift() MS.Preds.push(MS.dir.get(i)) float(MS.Preds.sum() * 5 ) // break MData.prediction := Knn(ML) MData.Smoothed := ta.sma(MData.prediction,Smooth) ML.PerD.push(MData.Smoothed) // if ML.PerD.size() > 1000 // ML.PerD.shift() small := ML.PerD.min() BIG := ML.PerD.max() Which = MData.prediction > 0 ? small:BIG Greeny = color.from_gradient(MData.prediction,small,BIG,color.rgb(7, 187, 37), color.rgb(0, 107, 43)) Reddy = color.from_gradient(MData.prediction,small,BIG,color.rgb(153, 0, 0),color.rgb(255, 82, 82)) con = MData.prediction == MData.Smoothed ? color.from_gradient(MData.prediction,small,BIG,color.rgb(164, 175, 10, 70), color.rgb(87, 61, 0, 70)): na pred = plot(MData.prediction,color =color.new(color.black,100),style = plot.style_line,title = “ML”,editable = false) SmoothP = plot(MData.Smoothed,color =color.new(color.black,100),style = plot.style_linebr,title = “Smoothed ML”,editable = false) _Which = plot(Which,color = color.new(color.black,100),editable = false) CONA = MData.prediction > MData.Smoothed ? Greeny:Reddy topLine = plot(BIG,color = color.new(color.white, 78),title = “T-TOP”) botLine = plot(small,color = color.new(color.white, 78),title = “T-BOT”) Top = plot(BIG + 15 ,color = color.new(color.white, 78),title = “B-TOP”) Bot = plot(small – 15,color = color.new(color.white, 78),title = “B-BOT”) _Center = plot(showLines ? MData.Prime1: na,color = color.new(#efb906, 70),linewidth = 2,editable = false) Center = plot(showLines ? MData.Prime2: na,color = color.new(#08d3ed, 70),linewidth = 2,editable = false) alpha = color.new(color.black, 100) TOP = plot(showLines ? max : na ,color = alpha,linewidth = 2,editable = false) BOT = plot(showLines ? min: na ,color = alpha,linewidth = 2,editable = false) plot(showLines ? MData.Prime1: na , “”, color.new(#efb906, 70), 2, editable = false) plot(showLines ? MData.Prime1: na , “”, color.new(#efb906, 90), 4, editable = false) plot(showLines ? MData.Prime2: na , “”, color.new(#08d3ed, 70), 2, editable = false) plot(showLines ? MData.Prime2: na , “”, color.new(#08d3ed, 90), 4, editable = false) fill(pred,_Which,color = con) fill(topLine,Top,color = color.rgb(255, 255, 255, 91)) fill(botLine,Bot,color = color.rgb(255, 255, 255, 91)) fill(topLine, botLine, BIG, small, color.rgb(255, 82, 82, 75), color.rgb(33, 149, 243, 82)) plotcandle(MData.prediction,MData.prediction,MData.Smoothed,MData.Smoothed,color=color.new(CONA,20),bordercolor = color.new(CONA,10)) fill(TOP, Center, top_value = max, bottom_value = MData.Prime2, bottom_color = color.new(#08edda, 75), top_color = alpha, editable = true) fill(Center, BOT, top_value = MData.Prime2, bottom_value = min, bottom_color = alpha, top_color = color.new(#08edda, 75), editable = true) fill(TOP, _Center, top_value = max, bottom_value = MData.Prime1, bottom_color = color.new(#efb906, 75), top_color = alpha, editable = true) fill(_Center, BOT, top_value = MData.Prime1, bottom_value = min, bottom_color = alpha, top_color = color.new(#efb906, 75), editable = true)
.
