STD-Filtered, ATR-Adaptive Laguerre Filter [Loxx]
// 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, ATR-Adaptive Laguerre Filter [Loxx]", 
     shorttitle = "STDFATRALF [Loxx]", 
     overlay = true, 
     timeframe="", 
     timeframe_gaps = true)
     
import loxx/loxxexpandedsourcetypes/4

greencolor = #2DD204
redcolor = #D2042D 

_lagfiltosc(float src, float per) =>
    float _gamma = 1.0 - 10.0 / (per + 9.0)
    float L0 = 0.0, float L1 = 0.0, float L2 = 0.0, float L3 = 0.0
    L0 := (1 - _gamma) * src + _gamma * nz(L0[1])
    L1 := -_gamma * L0 + nz(L0[1]) + _gamma * nz(L1[1])
    L2 := -_gamma * L1 + nz(L1[1]) + _gamma * nz(L2[1])
    L3 := -_gamma * L2 + nz(L2[1]) + _gamma * nz(L3[1])
    float out = (L0 + 2.0 * L1 + 2.0 * L2 + L3)/6.0
    out

//std filter
_filt(float src, simple 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)"])

per = input.int(20, "Laguerre/ATR Period", group = "Basic Settings")

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

filterop = input.string("Both", "Filter Options", options = ["Price", "Laguerre Filter", "Both", "None"], group=  "Filter Settings")
filter = input.float(2, "Filter Devaitions", minval = 0, group= "Filter Settings")
filterperiod = input.int(10, "Filter Period", minval = 0, group= "Filter Settings")

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

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

//apply ATR adaptivity 
atr = ta.atr(per)
fmax = ta.highest(atr, per)        
fmin = ta.lowest(atr, per)       
coeff = (fmin != fmax) ? 1 - (atr - fmin)/(fmax - fmin) : 0.5
val = _lagfiltosc(src, per * (coeff + 1.0) / 2.0)

//apply standard devaition filter
out = val
out := filterop == "Both" or filterop == "Laguerre 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, ATR-Adaptive Laguerre Filter [Loxx]: Long\nSymbol: {{ticker}}\nPrice: {{close}}")
alertcondition(goShort, title = "Short", message = "STD-Filtered, ATR-Adaptive Laguerre Filter [Loxx]: Short\nSymbol: {{ticker}}\nPrice: {{close}}")
