lovetotrade
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- Thinkorswim
- NinjaTrader
hello gangs, i need your help to convert this trading view indicator into TOS, i really been following this indicator so far so good, i will like to have on TOS so i can use. thanks in advance to barbaros and the others great coder here.
// 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
_npolegf(float src, int period, 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))
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 - price[1]) < filtdev ? 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 = 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)
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.yellow, textcolor = color.yellow, text = "L", style = shape.triangleup, location = location.belowbar, size = size.tiny)
plotshape(showSigs and goShort, 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-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}}")
// 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
_npolegf(float src, int period, 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))
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 - price[1]) < filtdev ? 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 = 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)
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.yellow, textcolor = color.yellow, text = "L", style = shape.triangleup, location = location.belowbar, size = size.tiny)
plotshape(showSigs and goShort, 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-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}}")