STD- and Clutter-Filtered, Non-Lag Moving Average [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- and Clutter-Filtered, Non-Lag Moving Average [Loxx]",
     shorttitle = "STFDFNLMA [Loxx]",
     overlay = true, 
     timeframe="", 
     timeframe_gaps = true)

import loxx/loxxexpandedsourcetypes/4

greencolor = #2DD204
redcolor = #D2042D 

nonlagma(float src, int len)=>
    float cycle = 4.0
    float coeff = 3.0 * math.pi
    float phase = len - 1.0
    int _len = int(len * cycle + phase)
    float weight = 0., float alfa = 0., float out = 0.
    float[] alphas = array.new_float(_len, 0.)
    for k = 0 to _len - 1
        float t = 0.
        t := k <= phase - 1 ?  1.0 * k / (phase - 1) : 1.0 + (k - phase + 1) * (2.0 * cycle - 1.0) / (cycle * len -1.0)
        float beta = math.cos(math.pi * t)
        float g = 1.0/(coeff * t + 1)
        g := t <= 0.5  ? 1 : g
        array.set(alphas, k, g * beta)
        weight += array.get(alphas, k)
    if (weight > 0)  
        float sum = 0.
        for k = 0 to _len - 1
            sum += array.get(alphas, k) * nz(src[k])
        out := (sum / weight)
    out
    
clutterFilt(float src, float threshold)=>
    bool out = math.abs(ta.roc(src, 1)) > threshold
    out
    
stdFilter(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("HAB Median", "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(25, "Period", group = "Basic Settings")
sth = input.float(0.1, "Clutter Filter Threshold", group = "Basic Settings", step = 0.001)

filterop = input.string("Both", "Filter Options", options = ["Price", "STFDFNLMA", "Both", "None"], group=  "Filter Settings")
filter = input.float(0, "Filter Devaitions", minval = 0, group= "Filter Settings")
filterperiod = input.int(15, "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")
showdeadzones = input.bool(false, "Show dead zones?", 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 ? stdFilter(src, filterperiod, filter) : src
out = nonlagma(src, per)
out := filterop == "Both" or filterop == "ULLMA" and filter > 0 ? stdFilter(out, filterperiod, filter) : out
sig = nz(out[1])

filtTrend = clutterFilt(out, sth)
state = filtTrend ? (out > sig ? 1 : out < sig ? -1 : 0) : 0

pregoLong = state == 1
pregoShort =state == -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 

color colorout = na
colorout := filtTrend ? (state == 1 ? greencolor : state == -1 ? redcolor : showdeadzones ? color.gray : colorout[1]) : showdeadzones ? color.gray : colorout[1]

plot(out, "STFDFNLMA MA", 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- and Clutter-Filtered, Non-Lag Moving Average [Loxx]: Long\nSymbol: {{ticker}}\nPrice: {{close}}")
alertcondition(goShort, title = "Short", message = "STD- and Clutter-Filtered, Non-Lag Moving Average [Loxx]: Short\nSymbol: {{ticker}}\nPrice: {{close}}")

