Convert Pine & Create cBot

Convert a TradingView indicator in pine script and then create a trading cBot based on the indicator. Parameter options for trailing stop, take profit, lot size, trading time (hours).

Source code;

// 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

indicator("STD-Filtered, N-Pole Gaussian Filter [Loxx]",

     shorttitle="STDFNPGF [Loxx]",

     overlay = true)

     

import loxx/loxxexpandedsourcetypes/4

 

greencolor = #2DD204  

redcolor = #D2042D

 

//factorial calc

fact(int n)=>

    float a = 1

    for i = 1 to n

        a *= i

    a

 

//alpha calc

_alpha(int period, int poles)=>

    w = 2.0 * math.pi / period

    float b = (1.0 - math.cos(w)) / (math.pow(1.414, 2.0 / poles) - 1.0)

    float a = - b + math.sqrt(b * b + 2.0 * b)

    a

   

//n-pole calc

_makeCoeffs(simple int period, simple int order)=>

    coeffs = matrix.new<float>(order + 1, 3, 0.)

    float a = _alpha(period, order)

    for r = 0 to order

        out = nz(fact(order) / (fact(order - r) * fact(r)), 1)

        matrix.set(coeffs, r, 0, out)

        matrix.set(coeffs, r, 1, math.pow(a, r))

        matrix.set(coeffs, r, 2, math.pow(1.0 - a, r))

    coeffs

   

//n-pole calc

_npolegf(float src, simple int period, simple int order)=>

    var coeffs = _makeCoeffs(period, order)

    float filt = src * matrix.get(coeffs, order, 1)

    int sign = 1

    for r = 1 to order

        filt += sign * matrix.get(coeffs, r, 0) * matrix.get(coeffs, r, 2) * nz(filt[r])

        sign *= -1

    filt

 

//std filter

_filt(float src, int len, float filter)=>

    float price = src

    float filtdev = filter * ta.stdev(src, len)

    price := math.abs(price - nz(price[1])) < filtdev ? nz(price[1]) : price

    price

   

smthtype = input.string("Kaufman", "Heiken-Ashi Better Smoothing", options = ["AMA", "T3", "Kaufman"], group=  "Source Settings")

srcoption = input.string("Close", "Source", group= "Source 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)"])

 

period = input.int(25,'Period', group = "Basic Settings")

order = input.int(5,'Order', group = "Basic Settings", minval = 1)

 

filterop = input.string("Gaussian Filter", "Filter Options", options = ["Price", "Gaussian Filter", "Both", "None"], group=  "Filter Settings")

filter = input.float(1, "Filter Devaitions", minval = 0, group= "Filter Settings")

filterperiod = input.int(10, "Filter Period", minval = 0, group= "Filter Settings")

 

colorbars = input.bool(true, "Color bars?", group = "UI Options")

showSigs = input.bool(true, "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, haopen, hahigh, halow, hamedian, hatypical, haweighted, haaverage] = request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, [close, open, high, low, hl2, hlc3, hlcc4, ohlc4])

 

float src = switch srcoption

    "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

 

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

 

out = _npolegf(src, period, order)

 

out := filterop == "Both" or filterop == "Gaussian Filter" and filter > 0 ? _filt(out, filterperiod, filter) : out

 

sig = nz(out[1])

 

state = 0

if (out > sig)

    state := 1

if (out < sig)

    state := -1

 

pregoLong = out > sig and (nz(out[1]) < nz(sig[1]) or nz(out[1]) == nz(sig[1]))

pregoShort = out < sig and (nz(out[1]) > nz(sig[1]) or nz(out[1]) == nz(sig[1]))

 

contsw = 0

contsw := nz(contsw[1])

contsw := pregoLong ? 1 : pregoShort ? -1 : nz(contsw[1])

 

goLong = pregoLong and nz(contsw[1]) == -1

goShort = pregoShort and nz(contsw[1]) == 1

 

var color colorout = na

colorout := state == -1 ? redcolor : state == 1 ? greencolor : nz(colorout[1])

 

plot(out, "N-Pole GF", color = colorout, linewidth = 3)

barcolor(colorbars ? colorout : na)

 

plotshape(showSigs and goLong, title = "Long", color = color.black, textcolor = color.black, text = "L", style = shape.triangleup, location = location.belowbar, size = size.tiny)

plotshape(showSigs and goShort, title = "Short", color = color.black, textcolor = color.black, text = "S", style = shape.triangledown, location = location.abovebar, size = size.tiny)

 

alertcondition(goLong, title = "Long", message = "STD-Filtered, N-Pole Gaussian Filter [Loxx]: Long\nSymbol: {{ticker}}\nPrice: {{close}}")

alertcondition(goShort, title = "Short", message = "STD-Filtered, N-Pole Gaussian Filter [Loxx]: Short\nSymbol: {{ticker}}\nPrice: {{close}}")