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//@version=6
indicator("combine", shorttitle=".", overlay=true,
     max_lines_count=400, max_boxes_count=50, max_labels_count=5)

// ── Enhanced Inputs
string GRP1 = "Core Pattern Matching"
string GRP2 = "Projection & Smoothing"
string GRP3 = "Quality & Filtering"
string GRP4 = "Visuals"

int   patLen   = input.int(20,   "Pattern Length",      minval=8,  maxval=200, group=GRP1)
int   fLen     = input.int(30,   "Forecast Bars",       minval=5,  maxval=300, group=GRP1)
int   depth    = input.int(2000, "Search Depth",        minval=200,maxval=6000,group=GRP1)
float minConf  = input.float(0.30,"Min Confidence",     minval=0.10,maxval=0.95,step=0.05,group=GRP1)

string scaling    = input.string("Adaptive","Scaling Method", options=["Fixed","Adaptive","Volatility","Z-Score"], group=GRP2)
string smoothing  = input.string("EMA","Projection Smoothing", options=["None","SMA","EMA","Adaptive"], group=GRP2)
int    smoothLen  = input.int(3, "Smoothing Length",     minval=2,  maxval=10, group=GRP2)

bool   useQualFilter = input.bool(true,  "Enable Quality Filter", group=GRP3)
float  minVariance   = input.float(0.001,"Min Pattern Variance", minval=0.0001, maxval=0.01, step=0.0001, group=GRP3)
int    trendCheck    = input.int(5,      "Trend Coherence Bars", minval=3, maxval=15, group=GRP3)

bool showProj   = input.bool(true,  "Show Projection", group=GRP4)
bool showBands  = input.bool(true,  "Show Bands",      group=GRP4)
bool showZones  = input.bool(true,  "Show Zones",      group=GRP4)

// Enhanced colors
color upColor   = input.color(#00FF88, "Uptrend (Green)",   group=GRP4)
color dnColor   = input.color(#FF4444, "Downtrend (Red)",   group=GRP4)
color swColor   = input.color(#FFAA00, "Sideways (Yellow)", group=GRP4)

// ── Enhanced Data buffers
var array<float> prices = array.new<float>()
var array<int>   times  = array.new<int>()
var array<float> highs  = array.new<float>()
var array<float> lows   = array.new<float>()

// handles
var array<line> hProj = array.new<line>()
var array<line> hBand = array.new<line>()
var array<box>  hBox  = array.new<box>()
var label       hLbl  = na

// ── Enhanced Helper Functions
safeDiv(float n, float d, float fb) => 
    d == 0.0 ? fb : n / d

// Enhanced cosine similarity with multiple normalization methods
cosineSim(array<float> arr, int startA, int startB, int len, string method = "returns") =>
    array<float> seqA = array.new<float>()
    array<float> seqB = array.new<float>()
    
    // Extract sequences
    for i = 0 to len - 1
        array.push(seqA, array.get(arr, startA + i))
        array.push(seqB, array.get(arr, startB + i))
    
    // Normalize based on method
    if method == "returns"
        // Return-based normalization (original method)
        float dp = 0.0, na2 = 0.0, nb2 = 0.0
        for k = 1 to len - 1
            float a0 = array.get(seqA, k - 1)
            float a1 = array.get(seqA, k)
            float b0 = array.get(seqB, k - 1)
            float b1 = array.get(seqB, k)
            float ra = safeDiv(a1 - a0, a0, 0.0)
            float rb = safeDiv(b1 - b0, b0, 0.0)
            dp  := dp + ra * rb
            na2 := na2 + ra * ra
            nb2 := nb2 + rb * rb
        float den = math.sqrt(na2) * math.sqrt(nb2)
        den == 0.0 ? 0.0 : dp / den
    else
        // Z-score normalization for more stable comparison
        float meanA = 0.0, meanB = 0.0
        for i = 0 to len - 1
            meanA := meanA + array.get(seqA, i)
            meanB := meanB + array.get(seqB, i)
        meanA := meanA / len
        meanB := meanB / len
        
        float stdA = 0.0, stdB = 0.0
        for i = 0 to len - 1
            float diffA = array.get(seqA, i) - meanA
            float diffB = array.get(seqB, i) - meanB
            stdA := stdA + diffA * diffA
            stdB := stdB + diffB * diffB
        stdA := math.sqrt(stdA / len)
        stdB := math.sqrt(stdB / len)
        
        if stdA == 0.0 or stdB == 0.0
            0.0
        else
            float dp = 0.0, na2 = 0.0, nb2 = 0.0
            for i = 0 to len - 1
                float za = (array.get(seqA, i) - meanA) / stdA
                float zb = (array.get(seqB, i) - meanB) / stdB
                dp  := dp + za * zb
                na2 := na2 + za * za
                nb2 := nb2 + zb * zb
            float den = math.sqrt(na2) * math.sqrt(nb2)
            den == 0.0 ? 0.0 : dp / den

// Pattern quality validation
patternQuality(array<float> arr, int start, int len) =>
    if start < 0 or start + len >= array.size(arr)
        0.0
    else
        // Calculate variance to ensure pattern has sufficient movement
        float mean = 0.0
        for i = 0 to len - 1
            mean := mean + array.get(arr, start + i)
        mean := mean / len
        
        float variance = 0.0
        for i = 0 to len - 1
            float diff = array.get(arr, start + i) - mean
            variance := variance + diff * diff
        variance := variance / len
        
        // Check trend coherence - avoid choppy patterns
        int trendChanges = 0
        bool lastUp = false
        bool firstCheck = true
        for i = 1 to len - 1
            bool currentUp = array.get(arr, start + i) > array.get(arr, start + i - 1)
            if not firstCheck and currentUp != lastUp
                trendChanges := trendChanges + 1
            lastUp := currentUp
            firstCheck := false
        
        float coherence = 1.0 - (trendChanges / (len - 1))
        math.sqrt(variance) * coherence

// Enhanced smoothing function
smoothProjection(array<float> proj, string method, int length) =>
    array<float> smoothed = array.new<float>()
    int size = array.size(proj)
    
    if method == "None"
        for i = 0 to size - 1
            array.push(smoothed, array.get(proj, i))
    else if method == "SMA"
        for i = 0 to size - 1
            float sum = 0.0
            int count = 0
            int start = math.max(0, i - length + 1)
            for j = start to i
                sum := sum + array.get(proj, j)
                count := count + 1
            array.push(smoothed, sum / count)
    else if method == "EMA"
        float alpha = 2.0 / (length + 1.0)
        array.push(smoothed, array.get(proj, 0))
        for i = 1 to size - 1
            float prev = array.get(smoothed, i - 1)
            float curr = array.get(proj, i)
            array.push(smoothed, alpha * curr + (1.0 - alpha) * prev)
    else // Adaptive
        for i = 0 to size - 1
            float sum = 0.0
            float weightSum = 0.0
            int adaptiveLen = i < length ? i + 1 : length
            for j = 0 to adaptiveLen - 1
                float weight = 1.0 / (j + 1.0)
                sum := sum + array.get(proj, i - j) * weight
                weightSum := weightSum + weight
            array.push(smoothed, sum / weightSum)
    
    smoothed

// Sample std of returns (enhanced for volatility scaling)
retStd(array<float> arr, int start, int len) =>
    if start < 1 or start + len >= array.size(arr)
        0.0
    else
        float s = 0.0
        float c = 0.0
        for k = start + 1 to start + len
            float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0)
            s := s + r
            c := c + 1.0
        float m = safeDiv(s, c, 0.0)
        float ss = 0.0
        for k = start + 1 to start + len
            float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0)
            float d = r - m
            ss := ss + d * d
        math.sqrt(safeDiv(ss, math.max(1.0, c - 1.0), 0.0))

// Array min/max over a range
arrMin(array<float> a, int start, int len) =>
    float m = na
    int stop = math.min(start + len, array.size(a))
    if start >= 0 and start < array.size(a)
        for i = start to stop - 1
            float v = array.get(a, i)
            m := na(m) ? v : math.min(m, v)
    m

arrMax(array<float> a, int start, int len) =>
    float m = na
    int stop = math.min(start + len, array.size(a))
    if start >= 0 and start < array.size(a)
        for i = start to stop - 1
            float v = array.get(a, i)
            m := na(m) ? v : math.max(m, v)
    m

// Draw cleanup
cleanup() =>
    for l in hProj
        line.delete(l)
    array.clear(hProj)
    for l in hBand
        line.delete(l)
    array.clear(hBand)
    for b in hBox
        box.delete(b)
    array.clear(hBox)
    if not na(hLbl)
        label.delete(hLbl)

// Keep arrays bounded
keep(int maxKeep) =>
    while array.size(prices) > maxKeep
        array.shift(prices)
        array.shift(times)
        array.shift(highs)
        array.shift(lows)

// ── Ingest
array.push(prices, close)
array.push(times,  time)
array.push(highs,  high)
array.push(lows,   low)
keep(depth + patLen + fLen + 50)

// ── Enhanced Engine
if barstate.islastconfirmedhistory and array.size(prices) > patLen * 2 + fLen
    cleanup()
    hLbl := na

    int N = array.size(prices)
    int recentStart = N - patLen
    int searchEnd   = N - patLen - fLen
    int searchStart = math.max(0, searchEnd - depth)

    float bestScore = -1.0
    int   bestIdx   = 0
    float bestQuality = 0.0

    // Enhanced pattern search with quality filtering
    for i = searchStart to searchEnd
        // Check pattern quality first if filtering enabled
        float quality = useQualFilter ? patternQuality(prices, i, patLen) : 1.0
        
        if quality >= minVariance
            string simMethod = scaling == "Z-Score" ? "zscore" : "returns"
            float s = cosineSim(prices, recentStart, i, patLen, simMethod)
            
            // Weight similarity by pattern quality
            float weightedScore = s * (0.7 + 0.3 * math.min(quality / (minVariance * 10.0), 1.0))
            
            if weightedScore > bestScore
                bestScore := weightedScore
                bestIdx := i
                bestQuality := quality

    bool have = bestScore >= minConf
    if have
        // Enhanced scaling methods
        float cur      = array.get(prices, N - 1)
        float baseHist = array.get(prices, bestIdx + patLen - 1)
        float scale    = 1.0
        
        if scaling == "Fixed"
            scale := 1.0
        else if scaling == "Adaptive"
            scale := safeDiv(cur, baseHist, 1.0)
        else if scaling == "Volatility"
            float cstd = retStd(prices, N - 1 - patLen, patLen)
            float hstd = retStd(prices, bestIdx, patLen)
            float vr   = safeDiv(cstd, hstd, 1.0)
            scale := safeDiv(cur, baseHist, 1.0) * vr
        else // Z-Score
            // Z-score based scaling for more stable projections
            float histMean = 0.0
            for i = 0 to patLen - 1
                histMean := histMean + array.get(prices, bestIdx + i)
            histMean := histMean / patLen
            
            float histStd = 0.0
            for i = 0 to patLen - 1
                float diff = array.get(prices, bestIdx + i) - histMean
                histStd := histStd + diff * diff
            histStd := math.sqrt(histStd / patLen)
            
            float currentStd = ta.stdev(close, patLen)
            scale := safeDiv(currentStd, histStd, 1.0)

        // Build raw projection path
        array<float> rawProj = array.new<float>()
        for k = 0 to fLen - 1
            float src = array.get(prices, bestIdx + patLen + k)
            float val = cur + (src - baseHist) * scale
            array.push(rawProj, val)

        // Apply smoothing to projection
        array<float> proj = smoothProjection(rawProj, smoothing, smoothLen)
        
        // Enhanced confidence bands
        float baseVol = ta.atr(20)
        float confMult = (1.0 - bestScore) * 2.0 + (1.0 - bestQuality / (minVariance * 20.0)) * 1.0
        
        array<float> up = array.new<float>()
        array<float> dn = array.new<float>()
        for i = 0 to array.size(proj) - 1
            float val = array.get(proj, i)
            float dynamicConf = baseVol * confMult * (1.0 + i * 0.1 / fLen) // Expanding confidence
            array.push(up, val + dynamicConf)
            array.push(dn, val - dynamicConf)

        // Directional analysis with smoothed values
        float last = array.get(proj, array.size(proj) - 1)
        float pct  = safeDiv(last - cur, cur, 0.0) * 100.0
        color lnColor = math.abs(pct) < 0.3 ? swColor : (pct > 0 ? upColor : dnColor)

        // Draw enhanced projection
        if showProj
            line l0 = line.new(bar_index, cur, bar_index + 1, array.get(proj, 0), color=lnColor, width=3)
            array.push(hProj, l0)
            for k = 0 to array.size(proj) - 2
                line lk = line.new(bar_index + k + 1, array.get(proj, k),
                                   bar_index + k + 2, array.get(proj, k + 1),
                                   color=lnColor, width=3)
                array.push(hProj, lk)

        // Enhanced bands
        if showBands
            color bc = color.new(lnColor, 70)
            line u0 = line.new(bar_index, cur + baseVol * confMult, bar_index + 1, array.get(up, 0), color=bc, style=line.style_dashed)
            line d0 = line.new(bar_index, cur - baseVol * confMult, bar_index + 1, array.get(dn, 0), color=bc, style=line.style_dashed)
            array.push(hBand, u0)
            array.push(hBand, d0)
            for k = 0 to array.size(up) - 2
                line uu = line.new(bar_index + k + 1, array.get(up, k), bar_index + k + 2, array.get(up, k + 1), color=bc, style=line.style_dashed)
                line dd = line.new(bar_index + k + 1, array.get(dn, k), bar_index + k + 2, array.get(dn, k + 1), color=bc, style=line.style_dashed)
                array.push(hBand, uu)
                array.push(hBand, dd)

        // Zones (unchanged)
        if showZones
            float hLow  = arrMin(lows,  bestIdx, patLen)
            float hHigh = arrMax(highs, bestIdx, patLen)
            if not na(hLow) and not na(hHigh)
                box b1 = box.new(array.get(times, bestIdx), hLow, array.get(times, bestIdx + patLen - 1), hHigh,
                                 xloc=xloc.bar_time, bgcolor=color.new(lnColor, 85), border_color=color.new(lnColor, 55))
                array.push(hBox, b1)
            float cLow  = ta.lowest(low,  patLen)
            float cHigh = ta.highest(high,patLen)
            box b2 = box.new(bar_index - patLen + 1, cLow, bar_index, cHigh,
                             bgcolor=color.new(color.blue, 85), border_color=color.new(color.blue, 55))
            array.push(hBox, b2)

        // Enhanced label with quality metrics
        string tname = math.abs(pct) < 0.3 ? "SIDEWAYS" : (pct > 0 ? "BULLISH" : "BEARISH")
        string emoji = math.abs(pct) < 0.3 ? "↔"        : (pct > 0 ? "▲"      : "▼")
        string lbl   = str.format("{0} ENHANCED PROJECTION ({1})\nConfidence: {2,number,#.0}% | Quality: {3,number,#.0}%\nTarget: {4,number,#.##} | Change: {5,number,#.1}%\nMethod: {6} | Smoothing: {7}",
                                  emoji, tname, bestScore*100.0, bestQuality*10000.0, last, pct, scaling, smoothing)
        hLbl := label.new(bar_index + math.round(array.size(proj)/2.0), math.max(cur, last) + ta.atr(10),
                          lbl, color=color.new(lnColor, 20), textcolor=color.white,
                          style=label.style_label_down, size=size.normal)

////////////////////
// UI Options for Auto Trend Detection and No Signal in Sideways Market
autoTrendDetection = input.bool(true, title = 'Auto Trend Detection')
noSignalSideways = input.bool(true, title = 'No Signal in Sideways Market')


// Color variables
upTrendColor = color.white
neutralColor = #90bff9
downTrendColor = color.blue


// Source
source = input(defval = close, title = 'Source')


// Sampling Period - Replaced with Sniper Machine
period = input.int(defval = 9, minval = 1, title = 'Sniper Machine Period')


// Trend Master - Replaced with Sniper Machine
multiplier = input.float(defval = 3.0, minval = 0.1, title = 'Sniper Machine Multiplier')


// Smooth Average Range
smoothRange(x, t, m) =>
    adjustedPeriod = t * 2 - 1
    avgRange = ta.ema(math.abs(x - x[1]), t)
    smoothRange = ta.ema(avgRange, adjustedPeriod) * m
    smoothRange
smoothedRange = smoothRange(source, period, multiplier)


// Trend Filter
trendFilter(x, r) =>
    filtered = x
    filtered := x > nz(filtered[1]) ? x - r < nz(filtered[1]) ? nz(filtered[1]) : x - r : x + r > nz(filtered[1]) ? nz(filtered[1]) : x + r
    filtered
filter = trendFilter(source, smoothedRange)


// Filter Direction
upCount = 0.0
upCount := filter > filter[1] ? nz(upCount[1]) + 1 : filter < filter[1] ? 0 : nz(upCount[1])
downCount = 0.0
downCount := filter < filter[1] ? nz(downCount[1]) + 1 : filter > filter[1] ? 0 : nz(downCount[1])


// Colors
filterColor = upCount > 0 ? upTrendColor : downCount > 0 ? downTrendColor : neutralColor


// Buy/Sell Signals - Adapted from Clear Trend Logic
trendUp = upCount > 0 // Equivalent to REMA_up in Clear Trend
newBuySignal = trendUp and not trendUp[1] and barstate.isconfirmed
newSellSignal = not trendUp and trendUp[1] and barstate.isconfirmed


initialCondition = 0
initialCondition := newBuySignal ? 1 : newSellSignal ? -1 : initialCondition[1]
longSignal = newBuySignal and initialCondition[1] == -1
shortSignal = newSellSignal and initialCondition[1] == 1


// Alerts and Signals
plotshape(longSignal, title = 'Buy Signal', text = '��', textcolor = #000000, style = shape.labelup, size = size.small, location = location.belowbar, color = #fae10400) // Bright yellow for Buy
plotshape(shortSignal, title = 'Sell Signal', text = '��', textcolor = #000000, style = shape.labeldown, size = size.small, location = location.abovebar, color = #fb020200) // Bright red for Sell


alertcondition(longSignal, title = 'Buy alert on Sniper Machine', message = 'Buy alert on Sniper Machine')
alertcondition(shortSignal, title = 'Sell alert on Sniper Machine', message = 'Sell alert on Sniper Machine')
///////////////

// Inputs
src     = input.source(hlc3, "Source")
emaLen  = input.int(15, "Center EMA")
spreadN = input.int(200, "Spread Length")
kMult   = input.float(3.0, "Multiplier", step=0.1)

upCol   = input.color(color.rgb(251, 5, 5), "Up Color")
dnCol   = input.color(color.rgb(26,221,127), "Down Color")

// Core calculation
mid    = ta.ema(src, emaLen)
spread = ta.sma(high - low, spreadN)
uBand  = mid + kMult * spread
lBand  = mid - kMult * spread

// Crawl bands
var float upC = na
var float dnC = na
upC := na(upC[1]) ? uBand : (src[1] > upC[1] ? uBand : math.min(uBand, upC[1]))
dnC := na(dnC[1]) ? lBand : (src[1] < dnC[1] ? lBand : math.max(lBand, dnC[1]))

// Direction & guide
var int dir = na
var float guide = na
if na(dir[1])
    dir := 1
else
    dir := guide[1] == upC[1] ? (src > upC ? -1 : 1) : (src < dnC ? 1 : -1)
guide := dir == 1 ? upC : dnC

// Background zone fill
bgcolor(dir==1 ? color.new(upCol, 85) : color.new(dnCol, 85), title="Trend Zone")

// Guide line
plot(guide, "Trs", color=color.new(dir==1?upCol:dnCol, 0), linewidth=1)

// Signals
trendUpbn    = not na(dir[1]) and dir == -1 and dir[1] != -1
trendDownbn  = not na(dir[1]) and dir == 1  and dir[1] != 1
pbUp       = dir==-1 and high >= upC
pbDown     = dir==1  and low <= dnC

dist = 0.25 * spread 
filteredPbUp   = pbUp   and (high - upC <= dist)
filteredPbDown = pbDown and (dnC - low <= dist)

firstPbUp   = filteredPbUp   and not filteredPbUp[1]
firstPbDown = filteredPbDown and not filteredPbDown[1]

// ATR for vertical spacing of signals
atrVal = ta.atr(14)
upY   = low - 15 * atrVal
downY = high + 10 * atrVal

// Plot BUY/SELL arrows as labels for vertical spacing
//if trendUpbn
    //label.new(bar_index, upY, text="BUY", style=label.style_triangleup, color=dnCol, textcolor=color.white, size=size.small, yloc=yloc.price)

//if trendDownbn
    //label.new(bar_index, downY, text="SELL", style=label.style_triangledown, color=upCol, textcolor=color.white, size=size.small, yloc=yloc.price)

// Pullback dots
//plotshape(firstPbUp,   style=shape.circle, location=location.belowbar, color=color.new(dnCol,0), size=size.small)
//plotshape(firstPbDown, style=shape.circle, location=location.abovebar, color=color.new(upCol,0), size=size.small)
//////////////////////

// --- User Inputs ---
// NEW: Added the "20/20 Profile (Ultra-Safe)" option.
profile = input.string('20/20 Profile (Ultra-Safe)', 'Select Profile', options = ['20/20 Profile (Ultra-Safe)', '16/16 Profile (Safe)', '12/12 Profile (Balanced)', '8/8 Profile (Aggressive)', 'Custom'], group = 'Grid Calculation')

// These inputs are now only used when "Custom" is selected.
customRangePercent = input.float(6.3, title = 'Custom Range as % of Price', group = 'Grid Calculation')
customGridCount = input.int(12, title = 'Custom Grid Count', group = 'Grid Calculation')

// Style Inputs
gridColor = input.color(color.new(color.gray, 60), title = 'Grid Line Color', group = 'Line Style')
gridWidth = input.int(1, title = 'Grid Line Width', minval = 1, maxval = 5, group = 'Line Style')
gridStyleString = input.string('Dotted', title = 'Grid Line Style', options = ['Solid', 'Dashed', 'Dotted'], group = 'Line Style')

// --- Variable Declarations ---
var array<line> gridLines = array.new_line()
var array<label> priceLabels = array.new_label()
var float finalRangePercent = 0.0
var int finalGridCount = 0

// --- Logic to select parameters based on profile ---
if profile == '20/20 Profile (Ultra-Safe)'
    finalRangePercent := 10.5
    finalGridCount := 20
    finalGridCount
else if profile == '16/16 Profile (Safe)'
    finalRangePercent := 8.4
    finalGridCount := 16
    finalGridCount
else if profile == '12/12 Profile (Balanced)'
    finalRangePercent := 6.3
    finalGridCount := 12
    finalGridCount
else if profile == '8/8 Profile (Aggressive)'
    finalRangePercent := 4.2
    finalGridCount := 8
    finalGridCount
else // Custom
    finalRangePercent := customRangePercent
    finalGridCount := customGridCount
    finalGridCount

// --- Helper Function ---
getLineStyle(styleString) =>
    styleString == 'Solid' ? line.style_solid : styleString == 'Dashed' ? line.style_dashed : line.style_dotted

// --- Drawing Logic ---
if barstate.islast
    // Delete old lines and labels
    if array.size(gridLines) > 0
        for lineId in gridLines
            line.delete(lineId)
        array.clear(gridLines)
    if array.size(priceLabels) > 0
        for labelId in priceLabels
            label.delete(labelId)
        array.clear(priceLabels)

    // Main Calculation
    currentPrice = close
    totalRange = currentPrice * (finalRangePercent / 100)
    halfRange = totalRange / 2.0
    upperLimit = currentPrice + halfRange
    lowerLimit = currentPrice - halfRange
    selectedGridStyle = getLineStyle(gridStyleString)

    // Draw Lines & Labels
    array.push(gridLines, line.new(bar_index - 99, upperLimit, bar_index, upperLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.green, 20), width = 2))
    array.push(gridLines, line.new(bar_index - 99, lowerLimit, bar_index, lowerLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.red, 20), width = 2))
    if finalGridCount > 1
        stepSize = totalRange / finalGridCount
        for i = 1 to finalGridCount - 1 by 1
            gridLevel = lowerLimit + i * stepSize
            array.push(gridLines, line.new(bar_index - 99, gridLevel, bar_index, gridLevel, xloc = xloc.bar_index, extend = extend.none, color = gridColor, width = gridWidth, style = selectedGridStyle))
    array.push(priceLabels, label.new(bar_index, upperLimit, text = str.tostring(upperLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.green, 70), textcolor = color.white, style = label.style_label_left))
    array.push(priceLabels, label.new(bar_index, lowerLimit, text = str.tostring(lowerLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.red, 70), textcolor = color.white, style = label.style_label_left))
///////////////////////////////// 

Eyvallah üstadım.
Kodu irdeleyemedim, back test vb. de yapamadım ama...
Çok iddialı

[KısaVade]

Eyvallah üstadım.
Kodu irdeleyemedim, back test vb. de yapamadım ama...
Çok iddialı

Hele şu projeksiyon doğru ise...
Tey, tey, teeeeyyyyy

[@yörük@]

Hele şu projeksiyon doğru ise...
Tey, tey, teeeeyyyyy

bilirsin üstadım.... projeksiyon doğrudur diyemem....

çünkü....
geriye doğru taradığın bar sayısı, aradığın pattern, volalite v.b....donelerle ileriye dönük istenilen bar sayısı kadar yapılıyor ki.....
her periyottaki farklılıkta cabası....

dediğin gibi...irdelemeden...test yapmadan....kullanmak
veya
kesin doğrudur...dememek lazım....

bence projeksiyon çalışmalarında....her meta için spesifik ayarlar kullanılması taraftarıyım....
endeks, btc, vadeli, hisse, usd gibi farklılıklarda...genel geçer durum yakalamak çok zor....
selamlar...

[@yörük@]

https://www.tradingview.com/x/cRLp7tSr/

ema3-atr5-sma10 kullanılarak yapılmış kombine örneği....

denemek isteyene kodu...

//@version=6
indicator(title = 'deneme', shorttitle = '.', overlay = true, max_lines_count = 100, max_labels_count=100, max_boxes_count = 100, max_bars_back = 100)

var params = "Parameters"
src55 = nz(input.source(close, title = "Source", group = params))
len55 = input.int(5, title = "ATR Len", group = params)
multi55 = input.float(1.5, title = "Multi", step = 0.25, minval = 0, group = params)

var cols = "Colors"
up_col = input.color(color.rgb(255, 255, 255, 00), title = "Yükseliş", group = cols)
down_col = input.color(color.rgb(247, 3, 3), title = "DÜşüş", group = cols)
flat_col = input.color(color.rgb(0, 0, 0, 00), title = "Flat ", inline = "3", group = cols)

rope_smoother(float _src55, float _threshold) =>

    var float _rope = _src55

    _move = _src55 - _rope //Movement from Rope

    _rope += math.max(math.abs(_move) - nz(_threshold), 0) * math.sign(_move) //Directional Movement beyond the Threshold
    
    [_rope,_rope+_threshold,_rope-_threshold] //[Rope, Upper, Lower]

///_____________________________________________________________________________________________________________________

//Calculating Rope
atr99 = ta.atr(len55)*multi55

[rope,upper,lower] = rope_smoother(src55,atr99)

//Directional Detection
var dir = 0

dir := rope > rope[1] ? 1 : rope < rope[1] ? -1 : dir

if ta.cross(src55,rope)
    dir := 0

//Directional Color Assignment    
col = dir > 0 ? up_col : dir < 0 ? down_col : flat_col

//High and Low Output Lines
var float c_hi = na
var float c_lo = na

//Counters for Accumulating Averages
var float h_sum = 0
var float l_sum = 0
var int c_count = 0

//Flip-Flop
var ff = 1

if dir == 0

    if dir[1] != 0
        h_sum := 0
        l_sum := 0
        c_count := 0
        ff := ff * -1

    h_sum += upper
    l_sum += lower
    c_count += 1
    c_hi := h_sum/c_count
    c_lo := l_sum/c_count

///
plot(rope, linewidth = 2, color = col, title = "ATR5", force_overlay = true)
////////////////
renk = input(true)
smaHigh = ta.sma(high, 10)
smaLow = ta.sma(low, 10)
mf=(smaHigh+smaLow)/2
//plot(mf, title = '@yörük@ ', color = #fd07f500, linewidth = 2)
plot(mf, title = 'sma10', style = plot.style_linebr, color = renk ? mf > close ? color.rgb(0, 0, 0, 100)  : color.rgb(255, 255, 255, 100) : color.silver, linewidth = 2)

//////////////////////////////////
type_ma = input.string("EMA", "Type", options = ["SMA", "EMA"], group = "MA")
length98 = input.int(3, "Length", inline = "ma", group = "MA")
source98 = input.source(close, "", inline = "ma", group = "MA")
grp98 = "MA Shift Oscillator"
osc_len = input.int(15, "Length", group = grp98, inline = "osc")
osc_threshold = input.float(0.5, "", step = 0.1, group = grp98, inline = "osc")

osc_col_up2 = input.color(color.rgb(255, 255, 255, 100), "", inline = "c", group = "color")
osc_col_dn2 = input.color(color.rgb(0, 0, 0, 100), "", inline = "c", group = "color")

ma(source98, length98, MAtype) =>
    switch MAtype
        "SMA"                   => ta.sma(source98, length98)
        "EMA"                   => ta.ema(source98, length98)
// MA 
MA = ma(source98, length98, type_ma) 
color98 = source98 >= MA ? osc_col_up2 : osc_col_dn2

plot(MA, "ema3", color=color98, force_overlay = true, linewidth = 1)

//////////////////////// 

[@yörük@]

ilave...mtf sar tablo....macd bar uyarılı... (yedekleme)
https://www.tradingview.com/x/m87JtZOz/

denemek ve geliştirmek isteyene....

//@version=6
indicator(title = 'deneme', shorttitle = '.', overlay = true, max_lines_count = 100, max_labels_count=100, max_boxes_count = 100, max_bars_back = 100)
//////////////////////////////////////////////////////////////////MTF SAR HESAPLAMASIDIR///////////////
start46 = input(0.)
increment46 = input(0.1)
maximum46 = input(0.9, "Max Value")
out55 = ta.sar(start46, increment46, maximum46)
plot_color = close > out55 ? color.rgb(5, 182, 64) : close < out55 ? color.rgb(169, 7, 7) : na

show_header = input(false, title="Show header?", group='Table Settings')
dashboard_position = input.string("Top center", title="Position", options=["Top right",  "Top center",  "Middle right"], group='Table Settings')
text_size = input.string('Normal', title="Size", options=["Tiny", "Small", "Normal", "Large"], group='Table Settings')
text_color = input.color(color.rgb(11, 68, 224), title="Text color", group='Table Settings')
table_color = input.color(color.purple, title="Border color", group='Table Settings')
uptrend_indicator = "🔵"
downtrend_indicator = "🟠"

tf11 = input.timeframe("1", title="Timeframe 1")
tf22 = input.timeframe("3", title="Timeframe 2")
tf33 = input.timeframe("5", title="Timeframe 3")
tf4 = input.timeframe("10", title="Timeframe 4")
tf5 = input.timeframe("15", title="Timeframe 5")
tf6 = input.timeframe("30", title="Timeframe 6")
tf7 = input.timeframe("60", title="Timeframe 7")
tf8 = input.timeframe("120", title="Timeframe 8")
tf9 = input.timeframe("240", title="Timeframe 9")
tf10 = input.timeframe("D", title="Timeframe 10")


var table_position = dashboard_position == 'Top center' ? position.middle_right :
  dashboard_position == 'Top center' ? position.middle_right :
  dashboard_position == 'Middle right' ? position.middle_right : position.middle_right
  
var table_text_size = text_size == 'Normal' ? size.normal :
  text_size == 'Small' ? size.small : size.normal

var t = table.new(position=table_position, columns=3, rows=20, frame_color=#cdcbcb, frame_width=5, border_color=table_color, border_width=1,bgcolor =color.rgb(21, 21, 21) )

get_trend_status(trend_value) =>
    is_uptrend = close > trend_value
    candle_now = is_uptrend ? uptrend_indicator : downtrend_indicator
    candle_now

//--------------------------------------------------------------------------------------

sar_1 = request.security(syminfo.tickerid, tf11, ta.sar(start46, increment46, maximum46))
sar_2 = request.security(syminfo.tickerid, tf22, ta.sar(start46, increment46, maximum46))
sar_3 = request.security(syminfo.tickerid, tf33, ta.sar(start46, increment46, maximum46))
sar_4 = request.security(syminfo.tickerid, tf4, ta.sar(start46, increment46, maximum46))
sar_5 = request.security(syminfo.tickerid, tf5, ta.sar(start46, increment46, maximum46))
sar_6 = request.security(syminfo.tickerid, tf6, ta.sar(start46, increment46, maximum46))
sar_7 = request.security(syminfo.tickerid, tf7, ta.sar(start46, increment46, maximum46))
sar_8 = request.security(syminfo.tickerid, tf8, ta.sar(start46, increment46, maximum46))
sar_9 = request.security(syminfo.tickerid, tf9, ta.sar(start46, increment46, maximum46))
sar_10 = request.security(syminfo.tickerid, tf10, ta.sar(start46, increment46, maximum46))


trend_indicator_1 = get_trend_status(sar_1)
trend_indicator_2 = get_trend_status(sar_2)
trend_indicator_3 = get_trend_status(sar_3)
trend_indicator_4 = get_trend_status(sar_4)
trend_indicator_5 = get_trend_status(sar_5)
trend_indicator_6 = get_trend_status(sar_6)
trend_indicator_7 = get_trend_status(sar_7)
trend_indicator_8 = get_trend_status(sar_8)
trend_indicator_9 = get_trend_status(sar_9)
trend_indicator_10 = get_trend_status(sar_10)

if tf11 == "60"
    tf11 := "1H"
if tf11 == "120"
    tf11 := "2H"
if tf11 == "180"
    tf11 := "3H"
if tf11 == "240"
    tf11 := "4H"

if tf22 == "60"
    tf22 := "1H"
if tf22 == "120"
    tf22 := "2H"
if tf22 == "180"
    tf22 := "3H"
if tf22 == "240"
    tf22 := "4H"

if tf33 == "60"
    tf33 := "1H"
if tf33 == "120"
    tf33 := "2H"
if tf33 == "180"
    tf33 := "3H"
if tf33 == "240"
    tf33 := "4H"

if tf4 == "60"
    tf4 := "1H"
if tf4 == "120"
    tf4 := "2H"
if tf4 == "180"
    tf4 := "3H"
if tf4 == "240"
    tf4 := "4H"

if tf5 == "60"
    tf5 := "1H"
if tf5 == "120"
    tf5 := "2H"
if tf5 == "180"
    tf5 := "3H"
if tf5 == "240"
    tf5 := "4H"

if tf6 == "60"
    tf6 := "1H"
if tf6 == "120"
    tf6 := "2H"
if tf6 == "180"
    tf6 := "3H"
if tf6 == "240"
    tf6 := "4H"

if tf7 == "60"
    tf7 := "1H"
if tf7 == "120"
    tf7 := "2H"
if tf7 == "180"
    tf7 := "3H"
if tf7 == "240"
    tf7 := "4H"

if tf8 == "60"
    tf8 := "1H"
if tf8 == "120"
    tf8 := "2H"
if tf8 == "180"
    tf8 := "3H"
if tf8 == "240"
    tf8 := "4H"

if tf9 == "60"
    tf9 := "1H"
if tf9 == "120"
    tf9 := "2H"
if tf9 == "180"
    tf9 := "3H"
if tf9 == "240"
    tf9 := "4H"

if tf10 == "60"
    tf10 := "1H"
if tf10 == "120"
    tf10 := "2H"
if tf10 == "180"
    tf10 := "3H"
if tf10 == "240"
    tf10 := "4H"


//---------------------------------------------------------------------------------------------
// Update table with trend data
//---------------------------------------------------------------------------------------------
if (barstate.islast)
   
    table.cell(t, 0, 1, tf11, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 1, text="●", text_color=trend_indicator_1==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 1, str.tostring(sar_1, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 2, tf22, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 2, text="●", text_color=trend_indicator_2==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 2, str.tostring(sar_2, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))
    
    table.cell(t, 0, 3, tf33, text_color=color.white, text_size=table_text_size,bgcolor= color.rgb(21, 21, 21))
    table.cell(t, 1, 3, text="●", text_color=trend_indicator_3==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 3, str.tostring(sar_3, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 4, tf4, text_color=color.white, text_size=table_text_size, bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 4, text="●", text_color=trend_indicator_4==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 4, str.tostring(sar_4, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 5, tf5, text_color=color.white, text_size=table_text_size, bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 5, text="●", text_color=trend_indicator_5==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 5, str.tostring(sar_5, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 6, tf6, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 6, text="●", text_color=trend_indicator_6==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 6, str.tostring(sar_6, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 7, tf7, text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))
    table.cell(t, 1, 7, text="●", text_color=trend_indicator_7==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 7, str.tostring(sar_7, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 8, tf8, text_color=color.white, text_size=table_text_size,bgcolor =  color.rgb(21, 21, 21))
    table.cell(t, 1, 8, text="●", text_color=trend_indicator_8==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 8, str.tostring(sar_8, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 9, tf9, text_color=color.white, text_size=table_text_size,bgcolor =  color.rgb(21, 21, 21))
    table.cell(t, 1, 9, text="●", text_color=trend_indicator_9==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 9, str.tostring(sar_9, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

    table.cell(t, 0, 10, tf10, text_color=color.white, text_size=table_text_size,bgcolor =  color.rgb(21, 21, 21))
    table.cell(t, 1, 10, text="●", text_color=trend_indicator_10==uptrend_indicator?color.lime:color.red,text_size = size.large)
    table.cell(t, 2, 10, str.tostring(sar_10, "#.##"), text_color=color.white, text_size=table_text_size,bgcolor = color.rgb(21, 21, 21))

 
table.cell(t,0,0,"Periyot",text_color = color.white,bgcolor = color.rgb(21, 21, 21))
table.cell(t,1,0,"Trend",text_color = color.white,bgcolor = color.rgb(21, 21, 21))
table.cell(t,2,0,"Fiyat",text_color = color.white,bgcolor = color.rgb(21, 21, 21))

lookback = input.int(5, "Line Lookback Period", minval=1)

//////////////////////
var params = "Parameters"
src55 = nz(input.source(close, title = "Source", group = params))
len55 = input.int(5, title = "ATR Len", group = params)
multi55 = input.float(1.5, title = "Multi", step = 0.25, minval = 0, group = params)

var cols = "Colors"
up_col = input.color(color.rgb(255, 255, 255, 00), title = "Yükseliş", group = cols)
down_col = input.color(color.rgb(247, 3, 3), title = "DÜşüş", group = cols)
flat_col = input.color(color.rgb(0, 0, 0, 00), title = "Flat ", inline = "3", group = cols)

rope_smoother(float _src55, float _threshold) =>

    var float _rope = _src55

    _move = _src55 - _rope //Movement from Rope

    _rope += math.max(math.abs(_move) - nz(_threshold), 0) * math.sign(_move) //Directional Movement beyond the Threshold
    
    [_rope,_rope+_threshold,_rope-_threshold] //[Rope, Upper, Lower]

///_____________________________________________________________________________________________________________________

//Calculating Rope
atr99 = ta.atr(len55)*multi55

[rope,upper,lower] = rope_smoother(src55,atr99)

//Directional Detection
var dir = 0

dir := rope > rope[1] ? 1 : rope < rope[1] ? -1 : dir

if ta.cross(src55,rope)
    dir := 0

//Directional Color Assignment    
col = dir > 0 ? up_col : dir < 0 ? down_col : flat_col

//High and Low Output Lines
var float c_hi = na
var float c_lo = na

//Counters for Accumulating Averages
var float h_sum = 0
var float l_sum = 0
var int c_count = 0

//Flip-Flop
var ff = 1

if dir == 0

    if dir[1] != 0
        h_sum := 0
        l_sum := 0
        c_count := 0
        ff := ff * -1

    h_sum += upper
    l_sum += lower
    c_count += 1
    c_hi := h_sum/c_count
    c_lo := l_sum/c_count

///
plot(rope, linewidth = 3, color = col, title = "ATR", force_overlay = true)
//////////////////////////////////////////////////////////////////////
groupFrames = 'Trend Monitoring Time Frames'

tf1 = input.timeframe('1', title='TF1 - Short', group=groupFrames)
tf2 = input.timeframe('5', title='TF2 - Medium', group=groupFrames)
tf3 = input.timeframe('15', title='TF3 - Long', group=groupFrames)

statusThreshold = input.int(4, title='Min Status Matches for Candle Color', options=[1, 2, 3, 4])

//-----------------------------------------
// User Inputs - Candle Color Settings
//-----------------------------------------
groupBody = 'Candle Color: Body'
sbBodyColor     = input.color(color.white, title='KESİN AL', group=groupBody)
bullBodyColor   = input.color(color.rgb(255, 255, 255, 100), title='AL', group=groupBody)
baseBodyColor   = input.color(color.rgb(4, 4, 4), title='DİKKAT ET', group=groupBody)
bearBodyColor   = input.color(color.rgb(255, 82, 82, 100), title='SAT', group=groupBody)
sbearBodyColor  = input.color(color.rgb(255, 82, 82, 100), title='KESİN SAT', group=groupBody)
ghostBodyColor  = input.color(color.rgb(223, 64, 251, 100), title='TREND YOK', group=groupBody)

groupBorder = 'Candle Color: Border & Wick'
sbBorderColor     = input.color(color.white, title='KESİN AL', group=groupBorder)
bullBorderColor   = input.color(color.rgb(255, 255, 255, 100), title='AL', group=groupBorder)
baseBorderColor   = input.color(color.rgb(4, 4, 4), title='DİKKAT ET', group=groupBorder)
bearBorderColor   = input.color(color.rgb(255, 82, 82, 100), title='SAT', group=groupBorder)
sbearBorderColor  = input.color(color.rgb(255, 82, 82, 100), title='KESİN SAT', group=groupBorder)
ghostBorderColor  = input.color(color.rgb(223, 64, 251, 100), title='TREND YOK', group=groupBorder)

//-----------------------------------------
// User Inputs - MACD Settings (at bottom per request)
//-----------------------------------------
groupMACD = 'MACD Settings'
macdFastLen = input.int(20, title='MACD Fast Length', minval=1, group=groupMACD)
macdSlowLen = input.int(40, title='MACD Slow Length', minval=1, group=groupMACD)
macdSignalLen = input.int(5, title='MACD Signal Smoothing', minval=1, group=groupMACD)
maType = input.string('EMA', title='MACD MA Type', options=['EMA', 'SMA', 'WMA'], group=groupMACD)

//-----------------------------------------
// MACD Calculation Function
//-----------------------------------------
calcMACD(_src, _fastLen, _slowLen, _signalLen) =>
    fastMA = maType == 'EMA' ? ta.ema(_src, _fastLen) : maType == 'SMA' ? ta.sma(_src, _fastLen) : ta.wma(_src, _fastLen)
    slowMA = maType == 'EMA' ? ta.ema(_src, _slowLen) : maType == 'SMA' ? ta.sma(_src, _slowLen) : ta.wma(_src, _slowLen)
    macdValue = fastMA - slowMA
    signalLine = maType == 'EMA' ? ta.ema(macdValue, _signalLen) : maType == 'SMA' ? ta.sma(macdValue, _signalLen) : ta.wma(macdValue, _signalLen)
    hist = macdValue - signalLine
    [macdValue, signalLine, hist, fastMA, slowMA]

//-----------------------------------------
// MACD (10m) Logic
//-----------------------------------------
[macdLine, signalLine, macdHist, _, _] = request.security(syminfo.tickerid, '10', calcMACD(close, macdFastLen, macdSlowLen, macdSignalLen))
macdBullish = macdLine > signalLine
macdStrong = macdBullish and macdLine > -0.25 and signalLine > -0.25
macdSuperBear = not macdBullish and macdLine < -0.25 and signalLine < -0.25
macdNeutral = not macdBullish and macdLine > -0.025 and signalLine > -0.025 and not macdSuperBear
macdText = macdStrong ? 'SUPERBULL' : macdSuperBear ? 'SUPERBEAR' : macdNeutral ? 'Basing' : macdBullish ? 'Bullish' : 'Bearish'

//-----------------------------------------
// Timeframe Status Function
//-----------------------------------------
f_getStatus(tf) =>
    [smaHigh, smaLow] = request.security(syminfo.tickerid, tf, [ta.sma(high, 20), ta.sma(low, 20)])
    [macdLine_tf, signalLine_tf, _, fastMA_tf, slowMA_tf] = request.security(syminfo.tickerid, tf, calcMACD(close, macdFastLen, macdSlowLen, macdSignalLen))
    price_tf = request.security(syminfo.tickerid, tf, close)
    macdBullish_tf = macdLine_tf > signalLine_tf
    aboveSMAs = price_tf > smaHigh and price_tf > smaLow
    belowSMAs = price_tf < smaHigh and price_tf < smaLow
    belowMAs = macdLine_tf < fastMA_tf and signalLine_tf < slowMA_tf
    status = ''
    statusColor = color.gray
    if aboveSMAs and macdBullish_tf and macdLine_tf > -0.025
        status := 'SUPERBULL'
    else if belowSMAs and not macdBullish_tf and macdLine_tf < -0.025 and belowMAs
        status := 'SUPERBEAR'
    else if macdLine_tf > -0.025 and not macdBullish_tf
        status := 'Basing'
    else if aboveSMAs and macdBullish_tf
        status := 'Bullish'
    else if not aboveSMAs and not macdBullish_tf
        status := 'Bearish'
    [status, statusColor]

//-----------------------------------------
// Timeframe Status Logic
//-----------------------------------------
[status1, color1] = f_getStatus(tf1)
[status5, color5] = f_getStatus(tf2)
[status15, color15] = f_getStatus(tf3)

//-----------------------------------------
// Status Match Count
//-----------------------------------------
superbullCount = (macdText == 'SUPERBULL' ? 1 : 0) + (status1 == 'SUPERBULL' ? 1 : 0) + (status5 == 'SUPERBULL' ? 1 : 0) + (status15 == 'SUPERBULL' ? 1 : 0)
superbearCount = (macdText == 'SUPERBEAR' ? 1 : 0) + (status1 == 'SUPERBEAR' ? 1 : 0) + (status5 == 'SUPERBEAR' ? 1 : 0) + (status15 == 'SUPERBEAR' ? 1 : 0)
basingCount = (macdText == 'Basing' ? 1 : 0) + (status1 == 'Basing' ? 1 : 0) + (status5 == 'Basing' ? 1 : 0) + (status15 == 'Basing' ? 1 : 0)
bullishCount = (macdText == 'Bullish' ? 1 : 0) + (status1 == 'Bullish' ? 1 : 0) + (status5 == 'Bullish' ? 1 : 0) + (status15 == 'Bullish' ? 1 : 0)
bearishCount = (macdText == 'Bearish' ? 1 : 0) + (status1 == 'Bearish' ? 1 : 0) + (status5 == 'Bearish' ? 1 : 0) + (status15 == 'Bearish' ? 1 : 0)

//-----------------------------------------
// Candle Coloring Logic
//-----------------------------------------
candleBodyColor = ghostBodyColor
candleBorderWickColor = ghostBorderColor

if superbullCount >= statusThreshold
    candleBodyColor := sbBodyColor
    candleBorderWickColor := sbBorderColor
else if superbearCount >= statusThreshold
    candleBodyColor := sbearBodyColor
    candleBorderWickColor := sbearBorderColor
else if basingCount >= statusThreshold
    candleBodyColor := baseBodyColor
    candleBorderWickColor := baseBorderColor
else if bullishCount >= statusThreshold
    candleBodyColor := bullBodyColor
    candleBorderWickColor := bullBorderColor
else if bearishCount >= statusThreshold
    candleBodyColor := bearBodyColor
    candleBorderWickColor := bearBorderColor

plotcandle(open, high, low, close,
     title='BAR',
     color=candleBodyColor,
     bordercolor=candleBorderWickColor,
     wickcolor=candleBorderWickColor)
//////////////////////////////////////////////////////
//@version=6
var table logo = table.new(position.bottom_center, 1, 1)
if barstate.islast
    table.cell(logo, 0, 0, 'deneme eğitim çalışması kod birleştirme örneği    ', text_size = size.normal, text_color = color.rgb(218, 241, 5))

//@version=6

smaHigh = ta.sma(high, 6)
smaLow = ta.sma(low, 6)
mf=(smaHigh+smaLow)/2
plot(mf, title = 'sma6 ', color = #fd07f500, linewidth = 2)

type_ma = input.string("EMA", "Type", options = ["SMA", "EMA"], group = "MA")
length98 = input.int(3, "Length", inline = "ma", group = "MA")
source98 = input.source(close, "", inline = "ma", group = "MA")
grp98 = "MA Shift Oscillator"
osc_len = input.int(15, "Length", group = grp98, inline = "osc")
osc_threshold = input.float(0.5, "", step = 0.1, group = grp98, inline = "osc")

osc_col_up2 = input.color(color.rgb(255, 255, 255, 100), "", inline = "c", group = "color")
osc_col_dn2 = input.color(color.rgb(0, 0, 0, 100), "", inline = "c", group = "color")

ma(source98, length98, MAtype) =>
    switch MAtype
        "SMA"                   => ta.sma(source98, length98)
        "EMA"                   => ta.ema(source98, length98)
// MA 
MA = ma(source98, length98, type_ma) 
color98 = source98 >= MA ? osc_col_up2 : osc_col_dn2

plot(MA, "ema", color=color98, force_overlay = true, linewidth = 1)

renk = input(true)
grp1 = "Indicator Settings"
src44 = input.source(hlc3, "Source", group=grp1, tooltip="Price source used for band calculations", display = display.data_window)
len44 = input.int(3, "Length", group=grp1, tooltip="Length for the basis calculation", display = display.data_window)
basis = ta.ema(ta.ema(src44, len44), len44)
plot(basis, title = 'ema3', style = plot.style_linebr, color = renk ? basis > close ? color.rgb(0, 0, 0, 100)  : color.rgb(255, 255, 255, 100) : color.silver, linewidth = 2)
/////////////////////////////// 

[@yörük@]

https://www.tradingview.com/x/kZ58kBwO/

denemek isteyene....

//@version=6
indicator("combine", shorttitle=".", overlay=true,
     max_lines_count=400, max_boxes_count=50, max_labels_count=5)

// ── Enhanced Inputs

///////////////

// Inputs
src     = input.source(hlc3, "Source")
emaLen  = input.int(1, "Center EMA")
spreadN = input.int(100, "Spread Length")
kMult   = input.float(3.0, "Multiplier", step=0.1)

upCol   = input.color(color.rgb(251, 5, 5), "Up Color")
dnCol   = input.color(color.rgb(26,221,127), "Down Color")

// Core calculation
mid    = ta.ema(src, emaLen)
spread = ta.sma(high - low, spreadN)
uBand  = mid + kMult * spread
lBand  = mid - kMult * spread

// Crawl bands
var float upC = na
var float dnC = na
upC := na(upC[1]) ? uBand : (src[1] > upC[1] ? uBand : math.min(uBand, upC[1]))
dnC := na(dnC[1]) ? lBand : (src[1] < dnC[1] ? lBand : math.max(lBand, dnC[1]))

// Direction & guide
var int dir = na
var float guide = na
if na(dir[1])
    dir := 1
else
    dir := guide[1] == upC[1] ? (src > upC ? -1 : 1) : (src < dnC ? 1 : -1)
guide := dir == 1 ? upC : dnC

// Background zone fill
//bgcolor(dir==1 ? color.new(upCol, 85) : color.new(dnCol, 85), title="Trend Zone")

// Guide line
plot(guide, "ema1", color=color.new(dir==1?upCol:dnCol, 0), linewidth=1)

// Signals
trendUpbn    = not na(dir[1]) and dir == -1 and dir[1] != -1
trendDownbn  = not na(dir[1]) and dir == 1  and dir[1] != 1
pbUp       = dir==-1 and high >= upC
pbDown     = dir==1  and low <= dnC

dist = 0.25 * spread 
filteredPbUp   = pbUp   and (high - upC <= dist)
filteredPbDown = pbDown and (dnC - low <= dist)

firstPbUp   = filteredPbUp   and not filteredPbUp[1]
firstPbDown = filteredPbDown and not filteredPbDown[1]

// ATR for vertical spacing of signals
atrVal = ta.atr(14)
upY   = low - 15 * atrVal
downY = high + 10 * atrVal

// Plot BUY/SELL arrows as labels for vertical spacing
//if trendUpbn
    //label.new(bar_index, upY, text="BUY", style=label.style_triangleup, color=dnCol, textcolor=color.white, size=size.small, yloc=yloc.price)

//if trendDownbn
    //label.new(bar_index, downY, text="SELL", style=label.style_triangledown, color=upCol, textcolor=color.white, size=size.small, yloc=yloc.price)

// Pullback dots
//plotshape(firstPbUp,   style=shape.circle, location=location.belowbar, color=color.new(dnCol,0), size=size.small)
//plotshape(firstPbDown, style=shape.circle, location=location.abovebar, color=color.new(upCol,0), size=size.small)
////////////////////// 

[@yörük@]

https://www.tradingview.com/x/JOJTMcEz/

farklı kodlarla yapılmış kombine örneği....

//@version=6
indicator("combine", shorttitle=".", overlay=true,
     max_lines_count=400, max_boxes_count=50, max_labels_count=5)

// ── Enhanced Inputs
string GRP1 = "Core Pattern Matching"
string GRP2 = "Projection & Smoothing"
string GRP3 = "Quality & Filtering"
string GRP4 = "Visuals"

int   patLen   = input.int(20,   "Pattern Length",      minval=8,  maxval=200, group=GRP1)
int   fLen     = input.int(30,   "Forecast Bars",       minval=5,  maxval=300, group=GRP1)
int   depth    = input.int(2000, "Search Depth",        minval=200,maxval=6000,group=GRP1)
float minConf  = input.float(0.30,"Min Confidence",     minval=0.10,maxval=0.95,step=0.05,group=GRP1)

string scaling    = input.string("Adaptive","Scaling Method", options=["Fixed","Adaptive","Volatility","Z-Score"], group=GRP2)
string smoothing  = input.string("EMA","Projection Smoothing", options=["None","SMA","EMA","Adaptive"], group=GRP2)
int    smoothLen  = input.int(3, "Smoothing Length",     minval=2,  maxval=10, group=GRP2)

bool   useQualFilter = input.bool(true,  "Enable Quality Filter", group=GRP3)
float  minVariance   = input.float(0.001,"Min Pattern Variance", minval=0.0001, maxval=0.01, step=0.0001, group=GRP3)
int    trendCheck    = input.int(5,      "Trend Coherence Bars", minval=3, maxval=15, group=GRP3)

bool showProj   = input.bool(true,  "Show Projection", group=GRP4)
bool showBands  = input.bool(true,  "Show Bands",      group=GRP4)
bool showZones  = input.bool(true,  "Show Zones",      group=GRP4)

// Enhanced colors
color upColor   = input.color(#00FF88, "Uptrend (Green)",   group=GRP4)
color dnColor   = input.color(#FF4444, "Downtrend (Red)",   group=GRP4)
color swColor   = input.color(#FFAA00, "Sideways (Yellow)", group=GRP4)

// ── Enhanced Data buffers
var array<float> prices = array.new<float>()
var array<int>   times  = array.new<int>()
var array<float> highs  = array.new<float>()
var array<float> lows   = array.new<float>()

// handles
var array<line> hProj = array.new<line>()
var array<line> hBand = array.new<line>()
var array<box>  hBox  = array.new<box>()
var label       hLbl  = na

// ── Enhanced Helper Functions
safeDiv(float n, float d, float fb) => 
    d == 0.0 ? fb : n / d

// Enhanced cosine similarity with multiple normalization methods
cosineSim(array<float> arr, int startA, int startB, int len, string method = "returns") =>
    array<float> seqA = array.new<float>()
    array<float> seqB = array.new<float>()
    
    // Extract sequences
    for i = 0 to len - 1
        array.push(seqA, array.get(arr, startA + i))
        array.push(seqB, array.get(arr, startB + i))
    
    // Normalize based on method
    if method == "returns"
        // Return-based normalization (original method)
        float dp = 0.0, na2 = 0.0, nb2 = 0.0
        for k = 1 to len - 1
            float a0 = array.get(seqA, k - 1)
            float a1 = array.get(seqA, k)
            float b0 = array.get(seqB, k - 1)
            float b1 = array.get(seqB, k)
            float ra = safeDiv(a1 - a0, a0, 0.0)
            float rb = safeDiv(b1 - b0, b0, 0.0)
            dp  := dp + ra * rb
            na2 := na2 + ra * ra
            nb2 := nb2 + rb * rb
        float den = math.sqrt(na2) * math.sqrt(nb2)
        den == 0.0 ? 0.0 : dp / den
    else
        // Z-score normalization for more stable comparison
        float meanA = 0.0, meanB = 0.0
        for i = 0 to len - 1
            meanA := meanA + array.get(seqA, i)
            meanB := meanB + array.get(seqB, i)
        meanA := meanA / len
        meanB := meanB / len
        
        float stdA = 0.0, stdB = 0.0
        for i = 0 to len - 1
            float diffA = array.get(seqA, i) - meanA
            float diffB = array.get(seqB, i) - meanB
            stdA := stdA + diffA * diffA
            stdB := stdB + diffB * diffB
        stdA := math.sqrt(stdA / len)
        stdB := math.sqrt(stdB / len)
        
        if stdA == 0.0 or stdB == 0.0
            0.0
        else
            float dp = 0.0, na2 = 0.0, nb2 = 0.0
            for i = 0 to len - 1
                float za = (array.get(seqA, i) - meanA) / stdA
                float zb = (array.get(seqB, i) - meanB) / stdB
                dp  := dp + za * zb
                na2 := na2 + za * za
                nb2 := nb2 + zb * zb
            float den = math.sqrt(na2) * math.sqrt(nb2)
            den == 0.0 ? 0.0 : dp / den

// Pattern quality validation
patternQuality(array<float> arr, int start, int len) =>
    if start < 0 or start + len >= array.size(arr)
        0.0
    else
        // Calculate variance to ensure pattern has sufficient movement
        float mean = 0.0
        for i = 0 to len - 1
            mean := mean + array.get(arr, start + i)
        mean := mean / len
        
        float variance = 0.0
        for i = 0 to len - 1
            float diff = array.get(arr, start + i) - mean
            variance := variance + diff * diff
        variance := variance / len
        
        // Check trend coherence - avoid choppy patterns
        int trendChanges = 0
        bool lastUp = false
        bool firstCheck = true
        for i = 1 to len - 1
            bool currentUp = array.get(arr, start + i) > array.get(arr, start + i - 1)
            if not firstCheck and currentUp != lastUp
                trendChanges := trendChanges + 1
            lastUp := currentUp
            firstCheck := false
        
        float coherence = 1.0 - (trendChanges / (len - 1))
        math.sqrt(variance) * coherence

// Enhanced smoothing function
smoothProjection(array<float> proj, string method, int length) =>
    array<float> smoothed = array.new<float>()
    int size = array.size(proj)
    
    if method == "None"
        for i = 0 to size - 1
            array.push(smoothed, array.get(proj, i))
    else if method == "SMA"
        for i = 0 to size - 1
            float sum = 0.0
            int count = 0
            int start = math.max(0, i - length + 1)
            for j = start to i
                sum := sum + array.get(proj, j)
                count := count + 1
            array.push(smoothed, sum / count)
    else if method == "EMA"
        float alpha = 2.0 / (length + 1.0)
        array.push(smoothed, array.get(proj, 0))
        for i = 1 to size - 1
            float prev = array.get(smoothed, i - 1)
            float curr = array.get(proj, i)
            array.push(smoothed, alpha * curr + (1.0 - alpha) * prev)
    else // Adaptive
        for i = 0 to size - 1
            float sum = 0.0
            float weightSum = 0.0
            int adaptiveLen = i < length ? i + 1 : length
            for j = 0 to adaptiveLen - 1
                float weight = 1.0 / (j + 1.0)
                sum := sum + array.get(proj, i - j) * weight
                weightSum := weightSum + weight
            array.push(smoothed, sum / weightSum)
    
    smoothed

// Sample std of returns (enhanced for volatility scaling)
retStd(array<float> arr, int start, int len) =>
    if start < 1 or start + len >= array.size(arr)
        0.0
    else
        float s = 0.0
        float c = 0.0
        for k = start + 1 to start + len
            float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0)
            s := s + r
            c := c + 1.0
        float m = safeDiv(s, c, 0.0)
        float ss = 0.0
        for k = start + 1 to start + len
            float r = safeDiv(array.get(arr, k) - array.get(arr, k - 1), array.get(arr, k - 1), 0.0)
            float d = r - m
            ss := ss + d * d
        math.sqrt(safeDiv(ss, math.max(1.0, c - 1.0), 0.0))

// Array min/max over a range
arrMin(array<float> a, int start, int len) =>
    float m = na
    int stop = math.min(start + len, array.size(a))
    if start >= 0 and start < array.size(a)
        for i = start to stop - 1
            float v = array.get(a, i)
            m := na(m) ? v : math.min(m, v)
    m

arrMax(array<float> a, int start, int len) =>
    float m = na
    int stop = math.min(start + len, array.size(a))
    if start >= 0 and start < array.size(a)
        for i = start to stop - 1
            float v = array.get(a, i)
            m := na(m) ? v : math.max(m, v)
    m

// Draw cleanup
cleanup() =>
    for l in hProj
        line.delete(l)
    array.clear(hProj)
    for l in hBand
        line.delete(l)
    array.clear(hBand)
    for b in hBox
        box.delete(b)
    array.clear(hBox)
    if not na(hLbl)
        label.delete(hLbl)

// Keep arrays bounded
keep(int maxKeep) =>
    while array.size(prices) > maxKeep
        array.shift(prices)
        array.shift(times)
        array.shift(highs)
        array.shift(lows)

// ── Ingest
array.push(prices, close)
array.push(times,  time)
array.push(highs,  high)
array.push(lows,   low)
keep(depth + patLen + fLen + 50)

// ── Enhanced Engine
if barstate.islastconfirmedhistory and array.size(prices) > patLen * 2 + fLen
    cleanup()
    hLbl := na

    int N = array.size(prices)
    int recentStart = N - patLen
    int searchEnd   = N - patLen - fLen
    int searchStart = math.max(0, searchEnd - depth)

    float bestScore = -1.0
    int   bestIdx   = 0
    float bestQuality = 0.0

    // Enhanced pattern search with quality filtering
    for i = searchStart to searchEnd
        // Check pattern quality first if filtering enabled
        float quality = useQualFilter ? patternQuality(prices, i, patLen) : 1.0
        
        if quality >= minVariance
            string simMethod = scaling == "Z-Score" ? "zscore" : "returns"
            float s = cosineSim(prices, recentStart, i, patLen, simMethod)
            
            // Weight similarity by pattern quality
            float weightedScore = s * (0.7 + 0.3 * math.min(quality / (minVariance * 10.0), 1.0))
            
            if weightedScore > bestScore
                bestScore := weightedScore
                bestIdx := i
                bestQuality := quality

    bool have = bestScore >= minConf
    if have
        // Enhanced scaling methods
        float cur      = array.get(prices, N - 1)
        float baseHist = array.get(prices, bestIdx + patLen - 1)
        float scale    = 1.0
        
        if scaling == "Fixed"
            scale := 1.0
        else if scaling == "Adaptive"
            scale := safeDiv(cur, baseHist, 1.0)
        else if scaling == "Volatility"
            float cstd = retStd(prices, N - 1 - patLen, patLen)
            float hstd = retStd(prices, bestIdx, patLen)
            float vr   = safeDiv(cstd, hstd, 1.0)
            scale := safeDiv(cur, baseHist, 1.0) * vr
        else // Z-Score
            // Z-score based scaling for more stable projections
            float histMean = 0.0
            for i = 0 to patLen - 1
                histMean := histMean + array.get(prices, bestIdx + i)
            histMean := histMean / patLen
            
            float histStd = 0.0
            for i = 0 to patLen - 1
                float diff = array.get(prices, bestIdx + i) - histMean
                histStd := histStd + diff * diff
            histStd := math.sqrt(histStd / patLen)
            
            float currentStd = ta.stdev(close, patLen)
            scale := safeDiv(currentStd, histStd, 1.0)

        // Build raw projection path
        array<float> rawProj = array.new<float>()
        for k = 0 to fLen - 1
            float src = array.get(prices, bestIdx + patLen + k)
            float val = cur + (src - baseHist) * scale
            array.push(rawProj, val)

        // Apply smoothing to projection
        array<float> proj = smoothProjection(rawProj, smoothing, smoothLen)
        
        // Enhanced confidence bands
        float baseVol = ta.atr(20)
        float confMult = (1.0 - bestScore) * 2.0 + (1.0 - bestQuality / (minVariance * 20.0)) * 1.0
        
        array<float> up = array.new<float>()
        array<float> dn = array.new<float>()
        for i = 0 to array.size(proj) - 1
            float val = array.get(proj, i)
            float dynamicConf = baseVol * confMult * (1.0 + i * 0.1 / fLen) // Expanding confidence
            array.push(up, val + dynamicConf)
            array.push(dn, val - dynamicConf)

        // Directional analysis with smoothed values
        float last = array.get(proj, array.size(proj) - 1)
        float pct  = safeDiv(last - cur, cur, 0.0) * 100.0
        color lnColor = math.abs(pct) < 0.3 ? swColor : (pct > 0 ? upColor : dnColor)

        // Draw enhanced projection
        if showProj
            line l0 = line.new(bar_index, cur, bar_index + 1, array.get(proj, 0), color=lnColor, width=3)
            array.push(hProj, l0)
            for k = 0 to array.size(proj) - 2
                line lk = line.new(bar_index + k + 1, array.get(proj, k),
                                   bar_index + k + 2, array.get(proj, k + 1),
                                   color=lnColor, width=3)
                array.push(hProj, lk)

        // Enhanced bands
        if showBands
            color bc = color.new(lnColor, 70)
            line u0 = line.new(bar_index, cur + baseVol * confMult, bar_index + 1, array.get(up, 0), color=bc, style=line.style_dashed)
            line d0 = line.new(bar_index, cur - baseVol * confMult, bar_index + 1, array.get(dn, 0), color=bc, style=line.style_dashed)
            array.push(hBand, u0)
            array.push(hBand, d0)
            for k = 0 to array.size(up) - 2
                line uu = line.new(bar_index + k + 1, array.get(up, k), bar_index + k + 2, array.get(up, k + 1), color=bc, style=line.style_dashed)
                line dd = line.new(bar_index + k + 1, array.get(dn, k), bar_index + k + 2, array.get(dn, k + 1), color=bc, style=line.style_dashed)
                array.push(hBand, uu)
                array.push(hBand, dd)

        // Zones (unchanged)
        if showZones
            float hLow  = arrMin(lows,  bestIdx, patLen)
            float hHigh = arrMax(highs, bestIdx, patLen)
            if not na(hLow) and not na(hHigh)
                box b1 = box.new(array.get(times, bestIdx), hLow, array.get(times, bestIdx + patLen - 1), hHigh,
                                 xloc=xloc.bar_time, bgcolor=color.new(lnColor, 85), border_color=color.new(lnColor, 55))
                array.push(hBox, b1)
            float cLow  = ta.lowest(low,  patLen)
            float cHigh = ta.highest(high,patLen)
            box b2 = box.new(bar_index - patLen + 1, cLow, bar_index, cHigh,
                             bgcolor=color.new(color.blue, 85), border_color=color.new(color.blue, 55))
            array.push(hBox, b2)

        // Enhanced label with quality metrics
        string tname = math.abs(pct) < 0.3 ? "SIDEWAYS" : (pct > 0 ? "BULLISH" : "BEARISH")
        string emoji = math.abs(pct) < 0.3 ? "↔"        : (pct > 0 ? "▲"      : "▼")
        string lbl   = str.format("{0} ENHANCED PROJECTION ({1})\nConfidence: {2,number,#.0}% | Quality: {3,number,#.0}%\nTarget: {4,number,#.##} | Change: {5,number,#.1}%\nMethod: {6} | Smoothing: {7}",
                                  emoji, tname, bestScore*100.0, bestQuality*10000.0, last, pct, scaling, smoothing)
        hLbl := label.new(bar_index + math.round(array.size(proj)/2.0), math.max(cur, last) + ta.atr(10),
                          lbl, color=color.new(lnColor, 20), textcolor=color.white,
                          style=label.style_label_down, size=size.normal)

////////////////////
// UI Options for Auto Trend Detection and No Signal in Sideways Market
autoTrendDetection = input.bool(true, title = 'Auto Trend Detection')
noSignalSideways = input.bool(true, title = 'No Signal in Sideways Market')


// Color variables
upTrendColor = color.white
neutralColor = #90bff9
downTrendColor = color.blue


// Source
source = input(defval = close, title = 'Source')


// Sampling Period - Replaced with Sniper Machine
period = input.int(defval = 9, minval = 1, title = 'Sniper Machine Period')


// Trend Master - Replaced with Sniper Machine
multiplier = input.float(defval = 3.0, minval = 0.1, title = 'Sniper Machine Multiplier')


// Smooth Average Range
smoothRange(x, t, m) =>
    adjustedPeriod = t * 2 - 1
    avgRange = ta.ema(math.abs(x - x[1]), t)
    smoothRange = ta.ema(avgRange, adjustedPeriod) * m
    smoothRange
smoothedRange = smoothRange(source, period, multiplier)


// Trend Filter
trendFilter(x, r) =>
    filtered = x
    filtered := x > nz(filtered[1]) ? x - r < nz(filtered[1]) ? nz(filtered[1]) : x - r : x + r > nz(filtered[1]) ? nz(filtered[1]) : x + r
    filtered
filter = trendFilter(source, smoothedRange)


// Filter Direction
upCount = 0.0
upCount := filter > filter[1] ? nz(upCount[1]) + 1 : filter < filter[1] ? 0 : nz(upCount[1])
downCount = 0.0
downCount := filter < filter[1] ? nz(downCount[1]) + 1 : filter > filter[1] ? 0 : nz(downCount[1])


// Colors
filterColor = upCount > 0 ? upTrendColor : downCount > 0 ? downTrendColor : neutralColor


// Buy/Sell Signals - Adapted from Clear Trend Logic
trendUp = upCount > 0 // Equivalent to REMA_up in Clear Trend
newBuySignal = trendUp and not trendUp[1] and barstate.isconfirmed
newSellSignal = not trendUp and trendUp[1] and barstate.isconfirmed


initialCondition = 0
initialCondition := newBuySignal ? 1 : newSellSignal ? -1 : initialCondition[1]
longSignal = newBuySignal and initialCondition[1] == -1
shortSignal = newSellSignal and initialCondition[1] == 1


// Alerts and Signals
plotshape(longSignal, title = 'Buy Signal', text = '🚀', textcolor = #000000, style = shape.labelup, size = size.small, location = location.belowbar, color = #fae10400) // Bright yellow for Buy
plotshape(shortSignal, title = 'Sell Signal', text = '🚨', textcolor = #000000, style = shape.labeldown, size = size.small, location = location.abovebar, color = #fb020200) // Bright red for Sell


alertcondition(longSignal, title = 'Buy alert on Sniper Machine', message = 'Buy alert on Sniper Machine')
alertcondition(shortSignal, title = 'Sell alert on Sniper Machine', message = 'Sell alert on Sniper Machine')
///////////////

// Inputs
src     = input.source(hlc3, "Source")
emaLen  = input.int(15, "Center EMA")
spreadN = input.int(200, "Spread Length")
kMult   = input.float(3.0, "Multiplier", step=0.1)

upCol   = input.color(color.rgb(251, 5, 5), "Up Color")
dnCol   = input.color(color.rgb(26,221,127), "Down Color")

// Core calculation
mid    = ta.ema(src, emaLen)
spread = ta.sma(high - low, spreadN)
uBand  = mid + kMult * spread
lBand  = mid - kMult * spread

// Crawl bands
var float upC = na
var float dnC = na
upC := na(upC[1]) ? uBand : (src[1] > upC[1] ? uBand : math.min(uBand, upC[1]))
dnC := na(dnC[1]) ? lBand : (src[1] < dnC[1] ? lBand : math.max(lBand, dnC[1]))

// Direction & guide
var int dir = na
var float guide = na
if na(dir[1])
    dir := 1
else
    dir := guide[1] == upC[1] ? (src > upC ? -1 : 1) : (src < dnC ? 1 : -1)
guide := dir == 1 ? upC : dnC

// Background zone fill
bgcolor(dir==1 ? color.new(upCol, 85) : color.new(dnCol, 85), title="Trend Zone")

// Guide line
plot(guide, "ema15", color=color.new(dir==1?upCol:dnCol, 0), linewidth=1)

// Signals
trendUpbn    = not na(dir[1]) and dir == -1 and dir[1] != -1
trendDownbn  = not na(dir[1]) and dir == 1  and dir[1] != 1
pbUp       = dir==-1 and high >= upC
pbDown     = dir==1  and low <= dnC

dist = 0.25 * spread 
filteredPbUp   = pbUp   and (high - upC <= dist)
filteredPbDown = pbDown and (dnC - low <= dist)

firstPbUp   = filteredPbUp   and not filteredPbUp[1]
firstPbDown = filteredPbDown and not filteredPbDown[1]

// ATR for vertical spacing of signals
atrVal = ta.atr(14)
upY   = low - 15 * atrVal
downY = high + 10 * atrVal

// Plot BUY/SELL arrows as labels for vertical spacing
//if trendUpbn
    //label.new(bar_index, upY, text="BUY", style=label.style_triangleup, color=dnCol, textcolor=color.white, size=size.small, yloc=yloc.price)

//if trendDownbn
    //label.new(bar_index, downY, text="SELL", style=label.style_triangledown, color=upCol, textcolor=color.white, size=size.small, yloc=yloc.price)

// Pullback dots
//plotshape(firstPbUp,   style=shape.circle, location=location.belowbar, color=color.new(dnCol,0), size=size.small)
//plotshape(firstPbDown, style=shape.circle, location=location.abovebar, color=color.new(upCol,0), size=size.small)
//////////////////////

// --- User Inputs ---
// NEW: Added the "20/20 Profile (Ultra-Safe)" option.
profile = input.string('20/20 Profile (Ultra-Safe)', 'Select Profile', options = ['20/20 Profile (Ultra-Safe)', '16/16 Profile (Safe)', '12/12 Profile (Balanced)', '8/8 Profile (Aggressive)', 'Custom'], group = 'Grid Calculation')

// These inputs are now only used when "Custom" is selected.
customRangePercent = input.float(6.3, title = 'Custom Range as % of Price', group = 'Grid Calculation')
customGridCount = input.int(12, title = 'Custom Grid Count', group = 'Grid Calculation')

// Style Inputs
gridColor = input.color(color.new(color.gray, 60), title = 'Grid Line Color', group = 'Line Style')
gridWidth = input.int(1, title = 'Grid Line Width', minval = 1, maxval = 5, group = 'Line Style')
gridStyleString = input.string('Dotted', title = 'Grid Line Style', options = ['Solid', 'Dashed', 'Dotted'], group = 'Line Style')

// --- Variable Declarations ---
var array<line> gridLines = array.new_line()
var array<label> priceLabels = array.new_label()
var float finalRangePercent = 0.0
var int finalGridCount = 0

// --- Logic to select parameters based on profile ---
if profile == '20/20 Profile (Ultra-Safe)'
    finalRangePercent := 10.5
    finalGridCount := 20
    finalGridCount
else if profile == '16/16 Profile (Safe)'
    finalRangePercent := 8.4
    finalGridCount := 16
    finalGridCount
else if profile == '12/12 Profile (Balanced)'
    finalRangePercent := 6.3
    finalGridCount := 12
    finalGridCount
else if profile == '8/8 Profile (Aggressive)'
    finalRangePercent := 4.2
    finalGridCount := 8
    finalGridCount
else // Custom
    finalRangePercent := customRangePercent
    finalGridCount := customGridCount
    finalGridCount

// --- Helper Function ---
getLineStyle(styleString) =>
    styleString == 'Solid' ? line.style_solid : styleString == 'Dashed' ? line.style_dashed : line.style_dotted

// --- Drawing Logic ---
if barstate.islast
    // Delete old lines and labels
    if array.size(gridLines) > 0
        for lineId in gridLines
            line.delete(lineId)
        array.clear(gridLines)
    if array.size(priceLabels) > 0
        for labelId in priceLabels
            label.delete(labelId)
        array.clear(priceLabels)

    // Main Calculation
    currentPrice = close
    totalRange = currentPrice * (finalRangePercent / 100)
    halfRange = totalRange / 2.0
    upperLimit = currentPrice + halfRange
    lowerLimit = currentPrice - halfRange
    selectedGridStyle = getLineStyle(gridStyleString)

    // Draw Lines & Labels
    array.push(gridLines, line.new(bar_index - 99, upperLimit, bar_index, upperLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.green, 20), width = 2))
    array.push(gridLines, line.new(bar_index - 99, lowerLimit, bar_index, lowerLimit, xloc = xloc.bar_index, extend = extend.none, color = color.new(color.red, 20), width = 2))
    if finalGridCount > 1
        stepSize = totalRange / finalGridCount
        for i = 1 to finalGridCount - 1 by 1
            gridLevel = lowerLimit + i * stepSize
            array.push(gridLines, line.new(bar_index - 99, gridLevel, bar_index, gridLevel, xloc = xloc.bar_index, extend = extend.none, color = gridColor, width = gridWidth, style = selectedGridStyle))
    array.push(priceLabels, label.new(bar_index, upperLimit, text = str.tostring(upperLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.green, 70), textcolor = color.white, style = label.style_label_left))
    array.push(priceLabels, label.new(bar_index, lowerLimit, text = str.tostring(lowerLimit, format.mintick), xloc = xloc.bar_index, color = color.new(color.red, 70), textcolor = color.white, style = label.style_label_left))
////////////////////son///////////// 

[@yörük@]

https://tr.tradingview.com/v/MbBYobih/ macd ve rsi kullanarak hesaplanmış... https://www.tradingview.com/x/K8gkA7Fb/

https://tr.tradingview.com/v/UEPdjqLf/ mum tesbiti için.... https://www.tradingview.com/x/x3lXlfdD/
eski köpekbalığı tekniği gibi..... blok olan mum kalıpları içinde... en tepe ve en diple...tek mum aralığı yakalamak gibi....

şimdi yazan kişi kodda.... son 20 barı...saatlik tarıyor...yani en dip ve tepe işaretliyor.....

bense...her zaman sadece son üç barı sürekli tarıyorum....

https://www.tradingview.com/x/4pE8dpui/ bu kodun ayarı değişmemiş hali....

https://www.tradingview.com/x/zVeRNR92/ bu kodun 15 dakkalık hali...kendi taramamla kıyaslamak için....

https://www.tradingview.com/x/Zryh1JLF/ bu da...kodu 3 barla taratınca görünüm....

kodu..kendimle kıyaslayınca...emeğe saygı gereği...nasıl kullanabilirim deseydim.....

kendi kalıbıma... https://www.tradingview.com/x/ZQdMWVbK/ böyle uyguladığımda... 1dk grafikte kendi kalıbımla tarar...
bu kodla 15 dk getirir.... destek direnç v.b kullanmaya çalışırdım....