mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 01:37:43 +00:00
15f4bb90f3
New indicators: - HWC (Holt-Winters Channel) — channels, 27 tests - VWMACD (Volume-Weighted MACD) — momentum, 38 tests - Squeeze Pro — oscillators, 69 tests - BW_MFI (Bill Williams MFI) — oscillators - DSTOCH (Double Stochastic) — oscillators - ATRSTOP (ATR Trailing Stop) — reversals - VSTOP (Volatility Stop) — reversals - Convexity (Beta Convexity) — statistics, 23 tests Integration: - Python bridge: Exports.cs, _bridge.py, wrapper modules - Documentation: _sidebar.md, _index.md pages, SPEC.md - All analyzer warnings fixed (MA0074, xUnit2013, S2699) Build: 0 warnings, 0 errors | Tests: 15,933 passed, 0 failed
409 lines
13 KiB
C#
409 lines
13 KiB
C#
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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/// DSTOCH: Double Stochastic (Bressert DSS).
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/// Applies the Stochastic formula twice with EMA smoothing between stages.
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/// Stage 1: rawK = 100 * (close - LL) / (HH - LL) → smoothK = EMA(rawK, period)
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/// Stage 2: dsRaw = 100 * (smoothK - min(smoothK)) / (max(smoothK) - min(smoothK)) → output = EMA(dsRaw, period)
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/// Bounded [0, 100]. Uses MonotonicDeque for O(1) amortized min/max in both stages.
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/// </summary>
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[SkipLocalsInit]
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public sealed class Dstoch : ITValuePublisher
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{
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private readonly int _period;
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private readonly double _alpha;
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private readonly double _decay;
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// Stage 1: HLC stochastic
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private readonly double[] _hBuf;
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private readonly double[] _lBuf;
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private readonly MonotonicDeque _maxDeque;
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private readonly MonotonicDeque _minDeque;
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// Stage 2: smoothK stochastic
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private readonly double[] _skBuf;
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private readonly MonotonicDeque _skMaxDeque;
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private readonly MonotonicDeque _skMinDeque;
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private int _count;
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private long _index;
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[StructLayout(LayoutKind.Auto)]
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private record struct State(
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double SmK, double Dss,
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double LastValidHigh, double LastValidLow, double LastValidClose);
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private State _s;
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private State _ps;
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private readonly TBarPublishedHandler _barHandler;
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public string Name { get; }
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public int WarmupPeriod { get; }
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public TValue Last { get; private set; }
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public bool IsHot => _count >= _period;
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public event TValuePublishedHandler? Pub;
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public Dstoch(int period = 21)
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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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_period = period;
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_alpha = 2.0 / (period + 1);
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_decay = 1.0 - _alpha;
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_hBuf = new double[_period];
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_lBuf = new double[_period];
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_maxDeque = new MonotonicDeque(_period);
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_minDeque = new MonotonicDeque(_period);
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_skBuf = new double[_period];
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_skMaxDeque = new MonotonicDeque(_period);
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_skMinDeque = new MonotonicDeque(_period);
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_count = 0;
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_index = -1;
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_s = new State(double.NaN, double.NaN, double.NaN, double.NaN, double.NaN);
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_ps = _s;
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Name = $"Dstoch({period})";
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WarmupPeriod = period;
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_barHandler = HandleBar;
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}
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public Dstoch(TBarSeries source, int period = 21) : this(period)
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{
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Prime(source);
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source.Pub += _barHandler;
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}
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private void HandleBar(object? sender, in TBarEventArgs e) => Update(e.Value, e.IsNew);
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private void PubEvent(TValue value, bool isNew = true) =>
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Pub?.Invoke(this, new TValueEventArgs { Value = value, IsNew = isNew });
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public TValue Update(TBar input, bool isNew = true)
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{
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if (isNew)
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{
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_ps = _s;
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_index++;
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if (_count < _period)
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{
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_count++;
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}
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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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// Validate inputs — substitute last-valid on NaN/Infinity
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double high = input.High;
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double low = input.Low;
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double close = input.Close;
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if (double.IsFinite(high)) { s.LastValidHigh = high; }
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else { high = s.LastValidHigh; }
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if (double.IsFinite(low)) { s.LastValidLow = low; }
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else { low = s.LastValidLow; }
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if (double.IsFinite(close)) { s.LastValidClose = close; }
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else { close = s.LastValidClose; }
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if (double.IsNaN(high) || double.IsNaN(low) || double.IsNaN(close))
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{
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_s = s;
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Last = new TValue(input.Time, double.NaN);
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PubEvent(Last, isNew);
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return Last;
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}
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// Stage 1: Raw stochastic %K
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int bufIdx = _index < 0 ? 0 : (int)(_index % _period);
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_hBuf[bufIdx] = high;
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_lBuf[bufIdx] = low;
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if (isNew)
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{
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_maxDeque.PushMax(_index, high, _hBuf);
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_minDeque.PushMin(_index, low, _lBuf);
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}
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else
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{
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_maxDeque.RebuildMax(_hBuf, _index, _count);
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_minDeque.RebuildMin(_lBuf, _index, _count);
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}
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double highest = _maxDeque.GetExtremum(_hBuf);
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double lowest = _minDeque.GetExtremum(_lBuf);
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double range1 = highest - lowest;
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double rawK = range1 > 0.0 ? 100.0 * (close - lowest) / range1 : 0.0;
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// Stage 1 EMA: smooth rawK
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double smoothK = double.IsNaN(s.SmK)
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? rawK
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: Math.FusedMultiplyAdd(s.SmK, _decay, _alpha * rawK);
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s.SmK = smoothK;
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// Stage 2: Stochastic of smoothK
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_skBuf[bufIdx] = smoothK;
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if (isNew)
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{
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_skMaxDeque.PushMax(_index, smoothK, _skBuf);
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_skMinDeque.PushMin(_index, smoothK, _skBuf);
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}
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else
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{
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_skMaxDeque.RebuildMax(_skBuf, _index, _count);
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_skMinDeque.RebuildMin(_skBuf, _index, _count);
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}
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double skMax = _skMaxDeque.GetExtremum(_skBuf);
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double skMin = _skMinDeque.GetExtremum(_skBuf);
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double range2 = skMax - skMin;
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double dsRaw = range2 > 0.0 ? 100.0 * (smoothK - skMin) / range2 : 0.0;
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// Stage 2 EMA: smooth dsRaw
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double dss = double.IsNaN(s.Dss)
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? dsRaw
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: Math.FusedMultiplyAdd(s.Dss, _decay, _alpha * dsRaw);
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s.Dss = dss;
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_s = s;
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Last = new TValue(input.Time, dss);
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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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public TValue Update(TValue input, bool isNew = true) =>
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Update(new TBar(input.Time, input.Value, input.Value, input.Value, input.Value, 0), isNew);
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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 new TSeries([], []);
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}
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int len = source.Count;
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var times = new List<long>(len);
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var vals = new List<double>(len);
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CollectionsMarshal.SetCount(times, len);
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CollectionsMarshal.SetCount(vals, len);
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Batch(source.HighValues, source.LowValues, source.CloseValues,
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CollectionsMarshal.AsSpan(vals), _period);
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source.Times.CopyTo(CollectionsMarshal.AsSpan(times));
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Prime(source);
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var lastTime = new DateTime(source.Times[^1], DateTimeKind.Utc);
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Last = new TValue(lastTime, CollectionsMarshal.AsSpan(vals)[^1]);
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return new TSeries(times, vals);
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}
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public void Prime(TBarSeries source)
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{
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Reset();
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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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for (int i = 0; i < source.Count; i++)
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{
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Update(source[i], isNew: true);
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}
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}
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public void Reset()
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{
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Array.Clear(_hBuf);
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Array.Clear(_lBuf);
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Array.Clear(_skBuf);
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_maxDeque.Reset();
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_minDeque.Reset();
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_skMaxDeque.Reset();
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_skMinDeque.Reset();
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_count = 0;
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_index = -1;
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_s = new State(double.NaN, double.NaN, double.NaN, double.NaN, double.NaN);
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_ps = _s;
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Last = default;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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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 = 21)
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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 (high.Length != low.Length || high.Length != close.Length)
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{
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throw new ArgumentException("Input spans must have the same length", nameof(high));
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}
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if (output.Length < high.Length)
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{
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throw new ArgumentException("Output span must be at least as long as input", nameof(output));
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}
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int len = high.Length;
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if (len == 0)
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{
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return;
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}
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const int StackallocThreshold = 256;
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// Temporary buffers for Highest/Lowest results
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double[]? rentedUpper = null;
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double[]? rentedLower = null;
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double[]? rentedRawK = null;
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double[]? rentedSmK = null;
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double[]? rentedSmkUpper = null;
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double[]? rentedSmkLower = null;
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scoped Span<double> upperBuf;
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scoped Span<double> lowerBuf;
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scoped Span<double> rawKBuf;
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scoped Span<double> smKBuf;
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scoped Span<double> smkUpperBuf;
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scoped Span<double> smkLowerBuf;
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if (len <= StackallocThreshold)
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{
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upperBuf = stackalloc double[len];
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lowerBuf = stackalloc double[len];
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rawKBuf = stackalloc double[len];
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smKBuf = stackalloc double[len];
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smkUpperBuf = stackalloc double[len];
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smkLowerBuf = stackalloc double[len];
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}
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else
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{
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rentedUpper = ArrayPool<double>.Shared.Rent(len);
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rentedLower = ArrayPool<double>.Shared.Rent(len);
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rentedRawK = ArrayPool<double>.Shared.Rent(len);
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rentedSmK = ArrayPool<double>.Shared.Rent(len);
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rentedSmkUpper = ArrayPool<double>.Shared.Rent(len);
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rentedSmkLower = ArrayPool<double>.Shared.Rent(len);
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upperBuf = rentedUpper.AsSpan(0, len);
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lowerBuf = rentedLower.AsSpan(0, len);
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rawKBuf = rentedRawK.AsSpan(0, len);
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smKBuf = rentedSmK.AsSpan(0, len);
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smkUpperBuf = rentedSmkUpper.AsSpan(0, len);
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smkLowerBuf = rentedSmkLower.AsSpan(0, len);
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}
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try
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{
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// Stage 1: raw %K via Highest/Lowest
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Highest.Batch(high, upperBuf, period);
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Lowest.Batch(low, lowerBuf, period);
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double alpha = 2.0 / (period + 1);
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double decay = 1.0 - alpha;
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for (int i = 0; i < len; i++)
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{
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double range = upperBuf[i] - lowerBuf[i];
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rawKBuf[i] = range > 0.0 ? 100.0 * (close[i] - lowerBuf[i]) / range : 0.0;
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}
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// Stage 1 EMA: smooth rawK → smoothK
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smKBuf[0] = rawKBuf[0];
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for (int i = 1; i < len; i++)
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{
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smKBuf[i] = Math.FusedMultiplyAdd(smKBuf[i - 1], decay, alpha * rawKBuf[i]);
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}
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// Stage 2: Highest/Lowest of smoothK
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Highest.Batch(smKBuf.Slice(0, len), smkUpperBuf, period);
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Lowest.Batch(smKBuf.Slice(0, len), smkLowerBuf, period);
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// Stage 2: raw DS
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// Reuse rawKBuf for dsRaw
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for (int i = 0; i < len; i++)
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{
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double skRange = smkUpperBuf[i] - smkLowerBuf[i];
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rawKBuf[i] = skRange > 0.0
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? 100.0 * (smKBuf[i] - smkLowerBuf[i]) / skRange
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: 0.0;
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}
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// Stage 2 EMA: smooth dsRaw → output
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output[0] = rawKBuf[0];
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for (int i = 1; i < len; i++)
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{
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output[i] = Math.FusedMultiplyAdd(output[i - 1], decay, alpha * rawKBuf[i]);
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}
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}
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finally
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{
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if (rentedUpper != null) { ArrayPool<double>.Shared.Return(rentedUpper); }
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if (rentedLower != null) { ArrayPool<double>.Shared.Return(rentedLower); }
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if (rentedRawK != null) { ArrayPool<double>.Shared.Return(rentedRawK); }
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if (rentedSmK != null) { ArrayPool<double>.Shared.Return(rentedSmK); }
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if (rentedSmkUpper != null) { ArrayPool<double>.Shared.Return(rentedSmkUpper); }
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if (rentedSmkLower != null) { ArrayPool<double>.Shared.Return(rentedSmkLower); }
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}
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}
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public static TSeries Batch(TBarSeries source, int period = 21)
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{
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if (source == null || source.Count == 0)
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{
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return new TSeries([], []);
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}
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int len = source.Count;
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var times = new List<long>(len);
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var vals = new List<double>(len);
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CollectionsMarshal.SetCount(times, len);
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CollectionsMarshal.SetCount(vals, len);
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Batch(source.HighValues, source.LowValues, source.CloseValues,
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CollectionsMarshal.AsSpan(vals), period);
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source.Times.CopyTo(CollectionsMarshal.AsSpan(times));
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return new TSeries(times, vals);
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}
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public static (TSeries Results, Dstoch Indicator) Calculate(
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TBarSeries source, int period = 21)
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{
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var indicator = new Dstoch(period);
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var results = indicator.Update(source);
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return (results, indicator);
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}
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}
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