mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-30 02:27:43 +00:00
67ad6f0cba
Comprehensive refactor across all indicators replacing the periodic ResyncInterval-based drift correction (every 1000 ticks recalculate from scratch) with Kahan compensated summation for running sums. Key changes: - Remove ResyncInterval constants and TickCount fields from all State records - Add Kahan compensation fields (SumComp, SumSqComp, etc.) to State records - Replace naive sum += val - removed with Kahan delta pattern - Remove Resync()/RecalculateSum() methods that did O(N) recalculation - Update batch/SIMD paths to use Kahan compensation instead of resync loops - IIR filters (EMA, REMA, RGMA) simplified: inherently self-correcting - Version bump to 0.8.7 - Build system: README version stamping via Directory.Build.props - Minor doc/test tolerance adjustments for new numerical characteristics Affected modules: channels, core, cycles, dynamics, errors, momentum, oscillators, statistics, trends_FIR, trends_IIR, volatility, volume
541 lines
15 KiB
C#
541 lines
15 KiB
C#
using System;
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using System.Buffers;
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using System.Runtime.CompilerServices;
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using System.Runtime.InteropServices;
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namespace QuanTAlib;
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/// <summary>
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/// GHLA: Gann High-Low Activator
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/// SMA-based trailing stop with three-state hysteresis trend detection.
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/// Output follows SMA(Low) during uptrends and SMA(High) during downtrends.
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/// </summary>
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/// <remarks>
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/// <b>Calculation steps:</b>
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/// <list type="number">
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/// <item>SMA_high = running sum of last N highs / N</item>
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/// <item>SMA_low = running sum of last N lows / N</item>
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/// <item>Close > SMA_high → trend = +1 (bullish), output = SMA_low</item>
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/// <item>Close < SMA_low → trend = -1 (bearish), output = SMA_high</item>
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/// <item>Between both SMAs → retain previous trend (hysteresis)</item>
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/// </list>
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///
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/// <b>Sources:</b>
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/// Robert Krausz (1998). "The New Gann Swing Chartist" — Stocks & Commodities V.16:1
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/// </remarks>
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/// <seealso href="Ghla.md">Detailed documentation</seealso>
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[SkipLocalsInit]
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public sealed class Ghla : AbstractBase
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{
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private readonly RingBuffer _highBuffer;
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private readonly RingBuffer _lowBuffer;
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[StructLayout(LayoutKind.Auto)]
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private record struct State(
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double HighSum,
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double LowSum,
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double HighSumComp,
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double LowSumComp,
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int Trend,
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double LastValidHigh,
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double LastValidLow,
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double LastValidClose
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);
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private State _s;
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private State _ps;
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/// <summary>
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/// Creates GHLA with specified SMA period.
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/// </summary>
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/// <param name="period">SMA lookback period (must be > 0, default 13)</param>
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public Ghla(int period = 13)
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{
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if (period <= 0)
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{
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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}
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_highBuffer = new RingBuffer(period);
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_lowBuffer = new RingBuffer(period);
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Name = $"Ghla({period})";
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WarmupPeriod = period;
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_s = default;
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_ps = _s;
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}
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/// <summary>
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/// Creates GHLA with specified source and period.
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/// </summary>
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public Ghla(ITValuePublisher source, int period = 13) : this(period)
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{
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source.Pub += Handle;
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}
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private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
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/// <summary>
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/// True when both SMA buffers are full.
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/// </summary>
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public override bool IsHot => _highBuffer.IsFull;
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/// <summary>
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/// The current trend direction: +1 bullish, -1 bearish, 0 undetermined.
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/// </summary>
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public int Trend => _s.Trend;
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/// <summary>
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/// Updates the indicator with a TBar input (preferred method).
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public TValue Update(TBar bar, bool isNew = true)
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{
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return UpdateCore(bar.Time, bar.High, bar.Low, bar.Close, isNew);
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}
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/// <summary>
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/// Updates the indicator with a TValue input.
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/// Treats the value as H=L=C (degenerate case, always neutral zone).
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/// Prefer Update(TBar) for standard OHLC data.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override TValue Update(TValue input, bool isNew = true)
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{
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return UpdateCore(input.Time, input.Value, input.Value, input.Value, isNew);
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}
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/// <summary>
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/// Updates the indicator with a bar series.
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/// </summary>
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public TSeries Update(TBarSeries source)
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{
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if (source.Count == 0)
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{
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return [];
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}
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int len = source.Count;
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var t = new List<long>(len);
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var v = new List<double>(len);
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CollectionsMarshal.SetCount(t, len);
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CollectionsMarshal.SetCount(v, len);
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var tSpan = CollectionsMarshal.AsSpan(t);
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var vSpan = CollectionsMarshal.AsSpan(v);
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for (int i = 0; i < len; i++)
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{
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tSpan[i] = source[i].Time;
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}
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for (int i = 0; i < len; i++)
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{
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var result = Update(source[i], isNew: true);
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vSpan[i] = result.Value;
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}
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return new TSeries(t, v);
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}
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/// <inheritdoc/>
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public override TSeries Update(TSeries source)
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{
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// TSeries has no OHLC — treat values as H=L=C (degenerate case)
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int len = source.Count;
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var t = new List<long>(len);
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var v = new List<double>(len);
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CollectionsMarshal.SetCount(t, len);
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CollectionsMarshal.SetCount(v, len);
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var tSpan = CollectionsMarshal.AsSpan(t);
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var vSpan = CollectionsMarshal.AsSpan(v);
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var values = source.Values;
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var times = source.Times;
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for (int i = 0; i < len; i++)
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{
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tSpan[i] = times[i];
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var result = Update(new TValue(times[i], values[i]), isNew: true);
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vSpan[i] = result.Value;
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}
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return new TSeries(t, v);
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}
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/// <inheritdoc/>
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public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
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{
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for (int i = 0; i < source.Length; i++)
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{
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Update(new TValue(DateTime.UtcNow, source[i]), isNew: true);
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}
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}
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/// <inheritdoc/>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override void Reset()
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{
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_highBuffer.Clear();
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_lowBuffer.Clear();
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_s = default;
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_ps = _s;
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Last = default;
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}
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/// <summary>
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/// Calculates GHLA for the entire bar series using a new instance.
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/// </summary>
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public static TSeries Batch(TBarSeries source, int period = 13)
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{
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var ghla = new Ghla(period);
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return ghla.Update(source);
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}
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/// <summary>
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/// Span-based batch calculation for high, low, and close arrays.
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/// </summary>
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/// <param name="high">High prices.</param>
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/// <param name="low">Low prices.</param>
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/// <param name="close">Close prices.</param>
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/// <param name="output">Output activator values.</param>
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/// <param name="period">SMA lookback period.</param>
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public static void Batch(
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ReadOnlySpan<double> high,
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ReadOnlySpan<double> low,
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ReadOnlySpan<double> close,
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Span<double> output,
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int period = 13)
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{
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int len = high.Length;
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if (low.Length != len)
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{
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throw new ArgumentException("High and low spans must have the same length", nameof(low));
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}
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if (close.Length != len)
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{
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throw new ArgumentException("High and close spans must have the same length", nameof(close));
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}
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if (output.Length < len)
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{
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throw new ArgumentException("Output span must be at least as long as input spans", nameof(output));
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}
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if (period <= 0)
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{
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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}
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if (len == 0)
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{
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return;
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}
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CalculateScalarCore(high, low, close, output, period);
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}
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/// <summary>
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/// Calculates GHLA and returns both results and the indicator instance.
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/// </summary>
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public static (TSeries Results, Ghla Indicator) Calculate(TBarSeries source, int period = 13)
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{
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var indicator = new Ghla(period);
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TSeries results = indicator.Update(source);
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return (results, indicator);
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}
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// ---- Private implementation ----
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private TValue UpdateCore(long timeTicks, double high, double low, double close, bool isNew)
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{
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// Snapshot/restore for bar correction
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if (isNew)
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{
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_ps = _s;
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}
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else
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{
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_s = _ps;
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}
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var s = _s;
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// Handle non-finite values — use last valid per component
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if (!double.IsFinite(high))
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{
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high = s.LastValidHigh;
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}
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else
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{
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s.LastValidHigh = high;
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}
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if (!double.IsFinite(low))
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{
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low = s.LastValidLow;
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}
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else
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{
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s.LastValidLow = low;
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}
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if (!double.IsFinite(close))
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{
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close = s.LastValidClose;
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}
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else
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{
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s.LastValidClose = close;
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}
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// Update running SMA sums via ring buffers
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if (isNew)
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{
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// High buffer — Kahan compensated
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double highRemoved = _highBuffer.Count == _highBuffer.Capacity ? _highBuffer.Oldest : 0.0;
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double hDelta = high - highRemoved - s.HighSumComp;
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double hNewSum = s.HighSum + hDelta;
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s.HighSumComp = (hNewSum - s.HighSum) - hDelta;
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s.HighSum = hNewSum;
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_highBuffer.Add(high);
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// Low buffer — Kahan compensated
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double lowRemoved = _lowBuffer.Count == _lowBuffer.Capacity ? _lowBuffer.Oldest : 0.0;
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double lDelta = low - lowRemoved - s.LowSumComp;
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double lNewSum = s.LowSum + lDelta;
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s.LowSumComp = (lNewSum - s.LowSum) - lDelta;
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s.LowSum = lNewSum;
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_lowBuffer.Add(low);
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}
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else
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{
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// Bar correction: update newest value in both buffers
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_highBuffer.UpdateNewest(high);
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s.HighSum = _highBuffer.Sum;
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s.HighSumComp = 0;
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_lowBuffer.UpdateNewest(low);
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s.LowSum = _lowBuffer.Sum;
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s.LowSumComp = 0;
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}
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// Compute SMAs
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int count = _highBuffer.Count;
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double smaHigh = count > 0 ? s.HighSum / count : 0.0;
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double smaLow = count > 0 ? s.LowSum / count : 0.0;
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// Three-state hysteresis trend detection
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if (s.Trend == 0)
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{
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// Seed: classify first bar
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if (close >= smaHigh)
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{
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s.Trend = 1;
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}
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else if (close <= smaLow)
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{
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s.Trend = -1;
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}
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else
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{
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s.Trend = 1; // default bullish per Pine reference
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}
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}
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if (close > smaHigh)
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{
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s.Trend = 1;
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}
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else if (close < smaLow)
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{
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s.Trend = -1;
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}
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// else: retain previous trend (hysteresis zone)
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// Select activator: bullish → SMA(Low), bearish → SMA(High)
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double activator = s.Trend == 1 ? smaLow : smaHigh;
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_s = s;
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Last = new TValue(timeTicks, activator);
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PubEvent(Last, isNew);
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return Last;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static void CalculateScalarCore(
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ReadOnlySpan<double> high,
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ReadOnlySpan<double> low,
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ReadOnlySpan<double> close,
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Span<double> output,
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int period)
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{
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int len = high.Length;
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const int StackAllocThreshold = 256;
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// High circular buffer
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double[]? rentedHigh = period > StackAllocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
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Span<double> highBuf = rentedHigh != null
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? rentedHigh.AsSpan(0, period)
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: stackalloc double[period];
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// Low circular buffer
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double[]? rentedLow = period > StackAllocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
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Span<double> lowBuf = rentedLow != null
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? rentedLow.AsSpan(0, period)
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: stackalloc double[period];
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try
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{
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double highSum = 0;
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double highSumComp = 0;
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double lowSum = 0;
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double lowSumComp = 0;
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double lastValidHigh = 0;
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double lastValidLow = 0;
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double lastValidClose = 0;
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int highIdx = 0;
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int lowIdx = 0;
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int filled = 0;
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int trend = 0;
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// Seed lastValid values
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(high[k]))
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{
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lastValidHigh = high[k];
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break;
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}
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}
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(low[k]))
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{
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lastValidLow = low[k];
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break;
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}
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}
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(close[k]))
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{
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lastValidClose = close[k];
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break;
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}
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}
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for (int i = 0; i < len; i++)
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{
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double h = high[i];
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double l = low[i];
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double c = close[i];
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if (double.IsFinite(h))
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{
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lastValidHigh = h;
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}
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else
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{
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h = lastValidHigh;
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}
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if (double.IsFinite(l))
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{
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lastValidLow = l;
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}
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else
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{
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l = lastValidLow;
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}
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if (double.IsFinite(c))
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{
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lastValidClose = c;
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}
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else
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{
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c = lastValidClose;
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}
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// Kahan-compensated update for high buffer
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{
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double deltaH = h - (filled >= period ? highBuf[highIdx] : 0);
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double yH = deltaH - highSumComp;
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double tH = highSum + yH;
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highSumComp = (tH - highSum) - yH;
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highSum = tH;
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}
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highBuf[highIdx] = h;
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highIdx++;
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if (highIdx >= period)
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{
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highIdx = 0;
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}
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// Kahan-compensated update for low buffer
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{
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double deltaL = l - (filled >= period ? lowBuf[lowIdx] : 0);
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double yL = deltaL - lowSumComp;
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double tL = lowSum + yL;
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lowSumComp = (tL - lowSum) - yL;
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lowSum = tL;
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}
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lowBuf[lowIdx] = l;
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lowIdx++;
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if (lowIdx >= period)
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{
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lowIdx = 0;
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}
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if (filled < period)
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{
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filled++;
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}
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double smaH = highSum / filled;
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double smaL = lowSum / filled;
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// Hysteresis
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if (trend == 0)
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{
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if (c >= smaH)
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{
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trend = 1;
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}
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else if (c <= smaL)
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{
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trend = -1;
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}
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else
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{
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trend = 1; // default bullish per Pine reference
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}
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}
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if (c > smaH)
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{
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trend = 1;
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}
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else if (c < smaL)
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{
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trend = -1;
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}
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output[i] = trend == 1 ? smaL : smaH;
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}
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}
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finally
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{
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if (rentedHigh != null)
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{
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ArrayPool<double>.Shared.Return(rentedHigh);
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}
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if (rentedLow != null)
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{
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ArrayPool<double>.Shared.Return(rentedLow);
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}
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}
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}
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}
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