Conversion of Jurik DMX Histogram Indicator from Trading View

Forums ProRealTime English forum ProBuilder support Conversion of Jurik DMX Histogram Indicator from Trading View

  • This topic has 2 replies, 2 voices, and was last updated 6 months ago by avatarΞ3.
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  • #226461
    Ξ3

    Please could you convert the below Trading View code found on the following website: Jurik DMX Histogram [Loxx] — Indicator by loxx — TradingView

    Jurik DMX Histogram is the ultra-smooth, low lag version of your classic DMI indicator.

    //@version=5
    indicator(title=”Jurik DMX Histogram [Loxx]”, shorttitle=”JDMXH [Loxx]”, timeframe=””, timeframe_gaps=true, overlay = false)

    greencolor = #2DD204
    redcolor = #D2042D
    bluecolor = #042dd2

    lightgreencolor = #96E881
    lightredcolor = #DF4F6C
    lightbluecolor = #4f6cdf

    darkGreenColor = #1B7E02
    darkRedColor = #93021F
    darkBlueColor = #021f93

    _f_hp(_src, max_len) =>
    var c = 360 * math.pi / 180
    _alpha = (1 – math.sin(c / max_len)) / math.cos(c / max_len)
    _hp = 0.0
    _hp := 0.5 * (1 + _alpha) * (_src – nz(_src[1])) + _alpha * nz(_hp[1])
    _hp

    _f_ess(_src, _len) =>
    var s = 1.414
    _a = math.exp(-s * math.pi / _len)
    _b = 2 * _a * math.cos(s * math.pi / _len)
    _c2 = _b
    _c3 = -_a * _a
    _c1 = 1 – _c2 – _c3
    _out = 0.0
    _out := _c1 * (_src + nz(_src[1])) / 2 + _c2 * nz(_out[1], nz(_src[1], _src)) + _c3 * nz(_out[2], nz(_src[2], nz(_src[1], _src)))
    _out

    _auto_dom(src, min_len, max_len, ave_len) =>
    var c = 2 * math.pi
    var s = 1.414
    avglen = ave_len

    filt = _f_ess(_f_hp(src, max_len), min_len)
    arr_size = max_len * 2

    var corr = array.new_float(arr_size, initial_value=0)
    var cospart = array.new_float(arr_size, initial_value=0)
    var sinpart = array.new_float(arr_size, initial_value=0)
    var sqsum = array.new_float(arr_size, initial_value=0)
    var r1 = array.new_float(arr_size, initial_value=0)
    var r2 = array.new_float(arr_size, initial_value=0)
    var pwr = array.new_float(arr_size, initial_value=0)

    for lag = 0 to max_len by 1
    m = avglen == 0 ? lag : avglen
    Sx = 0.0, Sy = 0.0, Sxx = 0.0, Syy = 0.0, Sxy = 0.0
    for i = 0 to m – 1 by 1
    x = nz(filt[i])
    y = nz(filt[lag + i])
    Sx += x
    Sy += y
    Sxx += x * x
    Sxy += x * y
    Syy += y * y
    Syy
    if (m * Sxx – Sx * Sx) * (m * Syy – Sy * Sy) > 0
    array.set(corr, lag, (m * Sxy – Sx * Sy) / math.sqrt((m * Sxx – Sx * Sx) * (m * Syy – Sy * Sy)))

    for period = min_len to max_len by 1
    array.set(cospart, period, 0)
    array.set(sinpart, period, 0)
    for n = ave_len to max_len by 1
    array.set(cospart, period, nz(array.get(cospart, period)) + nz(array.get(corr, n)) * math.cos(c * n / period))
    array.set(sinpart, period, nz(array.get(sinpart, period)) + nz(array.get(corr, n)) * math.sin(c * n / period))
    array.set(sqsum, period, math.pow(nz(array.get(cospart, period)), 2) + math.pow(nz(array.get(sinpart, period)), 2))

    for period = min_len to max_len by 1
    array.set(r2, period, nz(array.get(r1, period)))
    array.set(r1, period, 0.2 * math.pow(nz(array.get(sqsum, period)), 2) + 0.8 * nz(array.get(r2, period)))

    maxpwr = 0.0

    for period = min_len to max_len by 1
    if nz(array.get(r1, period)) > maxpwr
    maxpwr := nz(array.get(r1, period))

    for period = ave_len to max_len by 1
    array.set(pwr, period, nz(array.get(r1, period)) / maxpwr)

    dominantcycle = 0.0, peakpwr = 0.0

    for period = min_len to max_len by 1
    if nz(array.get(pwr, period)) > peakpwr
    peakpwr := nz(array.get(pwr, period))

    spx = 0.0, sp = 0.0

    for period = min_len to max_len by 1
    if peakpwr >= 0.25 and nz(array.get(pwr, period)) >= 0.25
    spx += period * nz(array.get(pwr, period))
    sp += nz(array.get(pwr, period))

    dominantcycle := sp != 0 ? spx / sp : dominantcycle
    dominantcycle := sp < 0.25 ? dominantcycle[1] : dominantcycle
    dominantcycle := dominantcycle < 1 ? 1 : dominantcycle
    dom_in = math.min(math.max(dominantcycle, min_len), max_len)
    dom_in

    _a_jurik_filt(src, len, phase) =>
    len1 = math.max(math.log(math.sqrt(0.5 * (len-1))) / math.log(2.0) + 2.0, 0)
    pow1 = math.max(len1 – 2.0, 0.5)
    volty = 7.0, avolty = 9.0, vsum = 8.0, bsmax = 5.0, bsmin = 6.0, avgLen = 65

    del1 = src – nz(bsmax[1])
    del2 = src – nz(bsmin[1])

    div = 1.0 / (10.0 + 10.0 * (math.min(math.max(len-10, 0), 100)) / 100)
    volty := math.abs(del1) > math.abs(del2) ? math.abs(del1) : math.abs(del2)
    vsum := nz(vsum[1]) + div * (volty – nz(volty[10]))

    temp_avg = ta.sma(vsum, avgLen)

    y = bar_index + 1
    if(y <= avgLen + 1)
    avolty := nz(avolty[1]) + 2.0 * (vsum – nz(avolty[1])) / (avgLen + 1)
    else
    avolty := temp_avg

    dVolty = avolty > 0 ? volty / avolty : 0
    dVolty := dVolty > math.pow(len1, 1.0/pow1) ? math.pow(len1, 1.0/pow1) : dVolty
    dVolty := dVolty < 1 ? 1 : dVolty
    pow2 = math.pow(dVolty, pow1)
    len2 = math.sqrt(0.5 * (len – 1)) * len1
    Kv = math.pow(len2 / (len2 + 1), math.sqrt(pow2))

    bsmax := del1 > 0 ? src : src – Kv * del1
    bsmin := del2 < 0 ? src : src – Kv * del2

    phaseRatio = phase < -100 ? 0.5 : phase > 100 ? 2.5 : phase / 100 + 1.5
    beta = 0.45 * (len – 1) / (0.45 * (len – 1) + 2)
    alpha = math.pow(beta, pow2)
    jma1 = 0.0, e0 = 0.0, e1 = 0.0, e2 = 0.0
    e0 := (1 – alpha) * src + alpha * nz(e0[1])
    e1 := (src – e0) * (1 – beta) + beta * nz(e1[1])
    e2 := (e0 + phaseRatio * e1 – nz(jma1[1])) * math.pow(1 – alpha, 2) + math.pow(alpha, 2) * nz(e2[1])
    jma1 := e2 + nz(jma1[1])
    jma1

    adapt = input.string(“Fixed”, “Calculation type”, options = [“Fixed”, “Autocorrelation Adaptive”], group = “Basic Settings”)

    len = input.int(32, minval=1, title=”Length”, group = “Basic Settings”)
    phs = input.int(0, title= “Jurik Phase”, group = “Basic Settings”)
    siglen = input.int(5, minval=1, title=”Signal Smoothing Length”, group = “Basic Settings”)

    auto_src = input.source(close, title=’JMA Source’, group = “Autocorrelation Periodgram Algorithm”)
    auto_min = input.int(8, minval = 1, title=’JMA Min Length’, group = “Autocorrelation Periodgram Algorithm”)
    auto_max = input.int(50, minval = 1, title=’JMA Max Length’, group = “Autocorrelation Periodgram Algorithm”)
    auto_avg = input.int(32, minval = 1, title=’JMA Average Length’, group = “Autocorrelation Periodgram Algorithm”)

    colorbars = input.bool(false, “Color bars?”, group = “UI Options”)

    auto = _auto_dom(auto_src, auto_min, auto_max, auto_avg)
    out = adapt == “Fixed” ? len : int(auto) < 1 ? 1 : int(auto)

    up = ta.change(high)
    down = -ta.change(low)

    plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
    minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)

    trur = _a_jurik_filt(ta.tr, out, phs)

    plus = fixnan(100 * _a_jurik_filt(plusDM, out, phs) / trur)
    minus = fixnan(100 * _a_jurik_filt(minusDM, out, phs) / trur)

    trigger = plus-minus
    signal = _a_jurik_filt(trigger, siglen, phs)

    colorout =
    trigger >= 0 and trigger >= signal ? greencolor :
    trigger >= 0 and trigger < signal ? lightgreencolor :
    trigger < 0 and trigger < signal ? redcolor :
    lightredcolor

    plot(trigger, color=colorout, title = “DMX”, style = plot.style_histogram)
    plot(trigger, color = trigger >= 0 ? darkGreenColor : darkRedColor , title = “DMX”, linewidth = 1)
    plot(signal, color = color.white, title = “Signal”, linewidth = 2)

    barcolor(colorbars ? colorout : na)

    #229698

    Hi,
    Here it’s the code: https://www.prorealcode.com/prorealtime-indicators/jurik-dmx-histogram-indicator/

    1 user thanked author for this post.
    avatar Ξ3
    #229742
    Ξ3

    Much appreciated!

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