Bonjour
Je suis en train de finir l’étude de la Vidya et j’aurai besoin d’un dernier coup de main pour traduire le code Trading View ci-dessous.
Merci d’avance !

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © loxx

//@version=5
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
//@version=5

indicator('STD-Stepped VIDYA w/ Quantile Bands [Loxx]', 
     shorttitle = "STDDVIDYAQB [Loxx]", 
     overlay = true, 
     timeframe="", 
     timeframe_gaps=true)
     
import loxx/loxxexpandedsourcetypes/3

greencolor = #2DD204
redcolor = #D2042D

SM02 = 'Slope'
SM03 = 'Middle Crossover'
SM04 = 'Levels Crossover'

_filt(src, len, filter)=>
    price = src
    filtdev = filter * ta.stdev(src, len)
    price := math.abs(price - price[1]) < filtdev ? price[1] : price
    price

smthtype = input.string("Kaufman", "Heikin-Ashi Better Caculation Type", options = ["AMA", "T3", "Kaufman"], group = "Basic Settings")

srcin = input.string("Close", "Source", group= "Basic Settings", 
     options = 
     ["Close", "Open", "High", "Low", "Median", "Typical", "Weighted", "Average", "Average Median Body", "Trend Biased", "Trend Biased (Extreme)", 
     "HA Close", "HA Open", "HA High", "HA Low", "HA Median", "HA Typical", "HA Weighted", "HA Average", "HA Average Median Body", "HA Trend Biased", "HA Trend Biased (Extreme)",
     "HAB Close", "HAB Open", "HAB High", "HAB Low", "HAB Median", "HAB Typical", "HAB Weighted", "HAB Average", "HAB Average Median Body", "HAB Trend Biased", "HAB Trend Biased (Extreme)"])

per = input(9, 'Period', group=  "Basic Settings")
histPer = input(30, 'Hist Period', group=  "Basic Settings")

filterop = input.string("Both", "Filter Options", options = ["Price", "VIDYA", "Both"], group=  "Filter Settings")
filter = input.float(0, "Filter Devaitions", minval = 0, group= "Filter Settings")
filterperiod = input.int(1, "Filter Period", minval = 0, group= "Filter Settings")

FlPeriod = input.int(25, "Levels Period", group = "Levels Settings") 
FlUp  = input.float(80 , "Up Level", group = "Levels Settings")
FlDn = input.float(20 , "Down Level", group = "Levels Settings")

sigtype = input.string(SM03, "Signal type", options = [SM02, SM03, SM04], group = "Signal Settings")

colorbars = input.bool(false, "Color bars?", group = "UI Options")
showsignals = input.bool(false, "Show signals?", group = "UI Options")

kfl=input.float(0.666, title="* Kaufman's Adaptive MA (KAMA) Only - Fast End", group = "Moving Average Inputs")
ksl=input.float(0.0645, title="* Kaufman's Adaptive MA (KAMA) Only - Slow End", group = "Moving Average Inputs")
amafl = input.int(2, title="* Adaptive Moving Average (AMA) Only - Fast", group = "Moving Average Inputs")
amasl = input.int(30, title="* Adaptive Moving Average (AMA) Only - Slow", group = "Moving Average Inputs")

haclose = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close)
haopen = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, open)
hahigh = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, high)
halow = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, low)
hamedian = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hl2)
hatypical = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hlc3)
haweighted = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, hlcc4)
haaverage = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, ohlc4)

src = switch srcin
	"Close" => loxxexpandedsourcetypes.rclose()
	"Open" => loxxexpandedsourcetypes.ropen()
	"High" => loxxexpandedsourcetypes.rhigh()
	"Low" => loxxexpandedsourcetypes.rlow()
	"Median" => loxxexpandedsourcetypes.rmedian()
	"Typical" => loxxexpandedsourcetypes.rtypical()
	"Weighted" => loxxexpandedsourcetypes.rweighted()
	"Average" => loxxexpandedsourcetypes.raverage()
    "Average Median Body" => loxxexpandedsourcetypes.ravemedbody()
	"Trend Biased" => loxxexpandedsourcetypes.rtrendb()
	"Trend Biased (Extreme)" => loxxexpandedsourcetypes.rtrendbext()
	"HA Close" => loxxexpandedsourcetypes.haclose(haclose)
	"HA Open" => loxxexpandedsourcetypes.haopen(haopen)
	"HA High" => loxxexpandedsourcetypes.hahigh(hahigh)
	"HA Low" => loxxexpandedsourcetypes.halow(halow)
	"HA Median" => loxxexpandedsourcetypes.hamedian(hamedian)
	"HA Typical" => loxxexpandedsourcetypes.hatypical(hatypical)
	"HA Weighted" => loxxexpandedsourcetypes.haweighted(haweighted)
	"HA Average" => loxxexpandedsourcetypes.haaverage(haaverage)
    "HA Average Median Body" => loxxexpandedsourcetypes.haavemedbody(haclose, haopen)
	"HA Trend Biased" => loxxexpandedsourcetypes.hatrendb(haclose, haopen, hahigh, halow)
	"HA Trend Biased (Extreme)" => loxxexpandedsourcetypes.hatrendbext(haclose, haopen, hahigh, halow)
	"HAB Close" => loxxexpandedsourcetypes.habclose(smthtype, amafl, amasl, kfl, ksl)
	"HAB Open" => loxxexpandedsourcetypes.habopen(smthtype, amafl, amasl, kfl, ksl)
	"HAB High" => loxxexpandedsourcetypes.habhigh(smthtype, amafl, amasl, kfl, ksl)
	"HAB Low" => loxxexpandedsourcetypes.hablow(smthtype, amafl, amasl, kfl, ksl)
	"HAB Median" => loxxexpandedsourcetypes.habmedian(smthtype, amafl, amasl, kfl, ksl)
	"HAB Typical" => loxxexpandedsourcetypes.habtypical(smthtype, amafl, amasl, kfl, ksl)
	"HAB Weighted" => loxxexpandedsourcetypes.habweighted(smthtype, amafl, amasl, kfl, ksl)
	"HAB Average" => loxxexpandedsourcetypes.habaverage(smthtype, amafl, amasl, kfl, ksl)
    "HAB Average Median Body" => loxxexpandedsourcetypes.habavemedbody(smthtype, amafl, amasl, kfl, ksl)
	"HAB Trend Biased" => loxxexpandedsourcetypes.habtrendb(smthtype, amafl, amasl, kfl, ksl)
	"HAB Trend Biased (Extreme)" => loxxexpandedsourcetypes.habtrendbext(smthtype, amafl, amasl, kfl, ksl)
	=> haclose

price = filterop == "Both" or filterop == "Price" and filter > 0 ? _filt(src, filterperiod, filter) : src

k = ta.stdev(price, per) / ta.stdev(price, histPer)
sc = 2 / (per + 1)
vidya = 0.0
vidya := nz(k * sc * price + (1 - k * sc) * vidya[1], 0)

out = filterop == "Both" or filterop == "VIDYA" and filter > 0 ? _filt(vidya, filterperiod, filter) : vidya
sig = out[1]

flhi = ta.percentile_linear_interpolation(out, FlPeriod, FlUp) 
mid = ta.percentile_linear_interpolation(out, FlPeriod, (FlUp+FlDn)/2.0)
fllo = ta.percentile_linear_interpolation(out, FlPeriod, FlDn)

state = 0.
if sigtype == SM02
    if (out<sig) 
        state :=-1
    if (out>sig) 
        state := 1
else if sigtype == SM03
    if (out<mid) 
        state :=-1
    if (out>mid)
        state := 1
else if sigtype == SM04
    if (out<fllo) 
        state :=-1
    if (out>flhi)
        state := 1

colorfish = state == -1 ? redcolor : state == 1 ? greencolor : color.gray

plot(out, color= colorfish, title="Fisher", linewidth = 3)

plot(flhi, "High Level", color = color.gray)
plot(fllo, "Low Level" ,color = color.gray)
plot(mid, "Middle", color = color.white)

barcolor(colorbars ? colorfish : na)

goLong = sigtype == SM02 ? ta.crossover(out, sig) : sigtype == SM03 ? ta.crossover(out, mid) : ta.crossover(out, flhi)
goShort = sigtype == SM02 ? ta.crossunder(out, sig) : sigtype == SM03 ? ta.crossunder(out, mid) :  ta.crossunder(out, fllo)

plotshape(goLong and showsignals, title = "Long", color = color.yellow, textcolor = color.yellow, text = "L", style = shape.triangleup, location = location.belowbar, size = size.tiny)
plotshape(goShort and showsignals, title = "Short", color = color.fuchsia, textcolor = color.fuchsia, text = "S", style = shape.triangledown, location = location.abovebar, size = size.tiny)

alertcondition(goLong, title="Long", message="STD-Stepped VIDYA w/ Quantile Bands [Loxx]: Long\nSymbol: {{ticker}}\nPrice: {{close}}")
alertcondition(goShort, title="Short", message="STD-Stepped VIDYA w/ Quantile Bands [Loxx]: Short\nSymbol: {{ticker}}\nPrice: {{close}}")

Capture-decran-2025-02-23-124013.png