Files
QuanTAlib/lib/oscillators/dstoch/Dstoch.cs
T
Miha Kralj 15f4bb90f3 feat: add 8 new indicators with full integration
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
2026-03-17 08:35:29 -07:00

409 lines
13 KiB
C#

using System.Buffers;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
/// <summary>
/// DSTOCH: Double Stochastic (Bressert DSS).
/// Applies the Stochastic formula twice with EMA smoothing between stages.
/// Stage 1: rawK = 100 * (close - LL) / (HH - LL) → smoothK = EMA(rawK, period)
/// Stage 2: dsRaw = 100 * (smoothK - min(smoothK)) / (max(smoothK) - min(smoothK)) → output = EMA(dsRaw, period)
/// Bounded [0, 100]. Uses MonotonicDeque for O(1) amortized min/max in both stages.
/// </summary>
[SkipLocalsInit]
public sealed class Dstoch : ITValuePublisher
{
private readonly int _period;
private readonly double _alpha;
private readonly double _decay;
// Stage 1: HLC stochastic
private readonly double[] _hBuf;
private readonly double[] _lBuf;
private readonly MonotonicDeque _maxDeque;
private readonly MonotonicDeque _minDeque;
// Stage 2: smoothK stochastic
private readonly double[] _skBuf;
private readonly MonotonicDeque _skMaxDeque;
private readonly MonotonicDeque _skMinDeque;
private int _count;
private long _index;
[StructLayout(LayoutKind.Auto)]
private record struct State(
double SmK, double Dss,
double LastValidHigh, double LastValidLow, double LastValidClose);
private State _s;
private State _ps;
private readonly TBarPublishedHandler _barHandler;
public string Name { get; }
public int WarmupPeriod { get; }
public TValue Last { get; private set; }
public bool IsHot => _count >= _period;
public event TValuePublishedHandler? Pub;
public Dstoch(int period = 21)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
_period = period;
_alpha = 2.0 / (period + 1);
_decay = 1.0 - _alpha;
_hBuf = new double[_period];
_lBuf = new double[_period];
_maxDeque = new MonotonicDeque(_period);
_minDeque = new MonotonicDeque(_period);
_skBuf = new double[_period];
_skMaxDeque = new MonotonicDeque(_period);
_skMinDeque = new MonotonicDeque(_period);
_count = 0;
_index = -1;
_s = new State(double.NaN, double.NaN, double.NaN, double.NaN, double.NaN);
_ps = _s;
Name = $"Dstoch({period})";
WarmupPeriod = period;
_barHandler = HandleBar;
}
public Dstoch(TBarSeries source, int period = 21) : this(period)
{
Prime(source);
source.Pub += _barHandler;
}
private void HandleBar(object? sender, in TBarEventArgs e) => Update(e.Value, e.IsNew);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private void PubEvent(TValue value, bool isNew = true) =>
Pub?.Invoke(this, new TValueEventArgs { Value = value, IsNew = isNew });
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public TValue Update(TBar input, bool isNew = true)
{
if (isNew)
{
_ps = _s;
_index++;
if (_count < _period)
{
_count++;
}
}
else
{
_s = _ps;
}
var s = _s;
// Validate inputs — substitute last-valid on NaN/Infinity
double high = input.High;
double low = input.Low;
double close = input.Close;
if (double.IsFinite(high)) { s.LastValidHigh = high; }
else { high = s.LastValidHigh; }
if (double.IsFinite(low)) { s.LastValidLow = low; }
else { low = s.LastValidLow; }
if (double.IsFinite(close)) { s.LastValidClose = close; }
else { close = s.LastValidClose; }
if (double.IsNaN(high) || double.IsNaN(low) || double.IsNaN(close))
{
_s = s;
Last = new TValue(input.Time, double.NaN);
PubEvent(Last, isNew);
return Last;
}
// Stage 1: Raw stochastic %K
int bufIdx = _index < 0 ? 0 : (int)(_index % _period);
_hBuf[bufIdx] = high;
_lBuf[bufIdx] = low;
if (isNew)
{
_maxDeque.PushMax(_index, high, _hBuf);
_minDeque.PushMin(_index, low, _lBuf);
}
else
{
_maxDeque.RebuildMax(_hBuf, _index, _count);
_minDeque.RebuildMin(_lBuf, _index, _count);
}
double highest = _maxDeque.GetExtremum(_hBuf);
double lowest = _minDeque.GetExtremum(_lBuf);
double range1 = highest - lowest;
double rawK = range1 > 0.0 ? 100.0 * (close - lowest) / range1 : 0.0;
// Stage 1 EMA: smooth rawK
double smoothK = double.IsNaN(s.SmK)
? rawK
: Math.FusedMultiplyAdd(s.SmK, _decay, _alpha * rawK);
s.SmK = smoothK;
// Stage 2: Stochastic of smoothK
_skBuf[bufIdx] = smoothK;
if (isNew)
{
_skMaxDeque.PushMax(_index, smoothK, _skBuf);
_skMinDeque.PushMin(_index, smoothK, _skBuf);
}
else
{
_skMaxDeque.RebuildMax(_skBuf, _index, _count);
_skMinDeque.RebuildMin(_skBuf, _index, _count);
}
double skMax = _skMaxDeque.GetExtremum(_skBuf);
double skMin = _skMinDeque.GetExtremum(_skBuf);
double range2 = skMax - skMin;
double dsRaw = range2 > 0.0 ? 100.0 * (smoothK - skMin) / range2 : 0.0;
// Stage 2 EMA: smooth dsRaw
double dss = double.IsNaN(s.Dss)
? dsRaw
: Math.FusedMultiplyAdd(s.Dss, _decay, _alpha * dsRaw);
s.Dss = dss;
_s = s;
Last = new TValue(input.Time, dss);
PubEvent(Last, isNew);
return Last;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public TValue Update(TValue input, bool isNew = true) =>
Update(new TBar(input.Time, input.Value, input.Value, input.Value, input.Value, 0), isNew);
public TSeries Update(TBarSeries source)
{
if (source.Count == 0)
{
return new TSeries([], []);
}
int len = source.Count;
var times = new List<long>(len);
var vals = new List<double>(len);
CollectionsMarshal.SetCount(times, len);
CollectionsMarshal.SetCount(vals, len);
Batch(source.HighValues, source.LowValues, source.CloseValues,
CollectionsMarshal.AsSpan(vals), _period);
source.Times.CopyTo(CollectionsMarshal.AsSpan(times));
Prime(source);
var lastTime = new DateTime(source.Times[^1], DateTimeKind.Utc);
Last = new TValue(lastTime, CollectionsMarshal.AsSpan(vals)[^1]);
return new TSeries(times, vals);
}
public void Prime(TBarSeries source)
{
Reset();
if (source.Count == 0)
{
return;
}
for (int i = 0; i < source.Count; i++)
{
Update(source[i], isNew: true);
}
}
public void Reset()
{
Array.Clear(_hBuf);
Array.Clear(_lBuf);
Array.Clear(_skBuf);
_maxDeque.Reset();
_minDeque.Reset();
_skMaxDeque.Reset();
_skMinDeque.Reset();
_count = 0;
_index = -1;
_s = new State(double.NaN, double.NaN, double.NaN, double.NaN, double.NaN);
_ps = _s;
Last = default;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Batch(
ReadOnlySpan<double> high,
ReadOnlySpan<double> low,
ReadOnlySpan<double> close,
Span<double> output,
int period = 21)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
if (high.Length != low.Length || high.Length != close.Length)
{
throw new ArgumentException("Input spans must have the same length", nameof(high));
}
if (output.Length < high.Length)
{
throw new ArgumentException("Output span must be at least as long as input", nameof(output));
}
int len = high.Length;
if (len == 0)
{
return;
}
const int StackallocThreshold = 256;
// Temporary buffers for Highest/Lowest results
double[]? rentedUpper = null;
double[]? rentedLower = null;
double[]? rentedRawK = null;
double[]? rentedSmK = null;
double[]? rentedSmkUpper = null;
double[]? rentedSmkLower = null;
scoped Span<double> upperBuf;
scoped Span<double> lowerBuf;
scoped Span<double> rawKBuf;
scoped Span<double> smKBuf;
scoped Span<double> smkUpperBuf;
scoped Span<double> smkLowerBuf;
if (len <= StackallocThreshold)
{
upperBuf = stackalloc double[len];
lowerBuf = stackalloc double[len];
rawKBuf = stackalloc double[len];
smKBuf = stackalloc double[len];
smkUpperBuf = stackalloc double[len];
smkLowerBuf = stackalloc double[len];
}
else
{
rentedUpper = ArrayPool<double>.Shared.Rent(len);
rentedLower = ArrayPool<double>.Shared.Rent(len);
rentedRawK = ArrayPool<double>.Shared.Rent(len);
rentedSmK = ArrayPool<double>.Shared.Rent(len);
rentedSmkUpper = ArrayPool<double>.Shared.Rent(len);
rentedSmkLower = ArrayPool<double>.Shared.Rent(len);
upperBuf = rentedUpper.AsSpan(0, len);
lowerBuf = rentedLower.AsSpan(0, len);
rawKBuf = rentedRawK.AsSpan(0, len);
smKBuf = rentedSmK.AsSpan(0, len);
smkUpperBuf = rentedSmkUpper.AsSpan(0, len);
smkLowerBuf = rentedSmkLower.AsSpan(0, len);
}
try
{
// Stage 1: raw %K via Highest/Lowest
Highest.Batch(high, upperBuf, period);
Lowest.Batch(low, lowerBuf, period);
double alpha = 2.0 / (period + 1);
double decay = 1.0 - alpha;
for (int i = 0; i < len; i++)
{
double range = upperBuf[i] - lowerBuf[i];
rawKBuf[i] = range > 0.0 ? 100.0 * (close[i] - lowerBuf[i]) / range : 0.0;
}
// Stage 1 EMA: smooth rawK → smoothK
smKBuf[0] = rawKBuf[0];
for (int i = 1; i < len; i++)
{
smKBuf[i] = Math.FusedMultiplyAdd(smKBuf[i - 1], decay, alpha * rawKBuf[i]);
}
// Stage 2: Highest/Lowest of smoothK
Highest.Batch(smKBuf.Slice(0, len), smkUpperBuf, period);
Lowest.Batch(smKBuf.Slice(0, len), smkLowerBuf, period);
// Stage 2: raw DS
// Reuse rawKBuf for dsRaw
for (int i = 0; i < len; i++)
{
double skRange = smkUpperBuf[i] - smkLowerBuf[i];
rawKBuf[i] = skRange > 0.0
? 100.0 * (smKBuf[i] - smkLowerBuf[i]) / skRange
: 0.0;
}
// Stage 2 EMA: smooth dsRaw → output
output[0] = rawKBuf[0];
for (int i = 1; i < len; i++)
{
output[i] = Math.FusedMultiplyAdd(output[i - 1], decay, alpha * rawKBuf[i]);
}
}
finally
{
if (rentedUpper != null) { ArrayPool<double>.Shared.Return(rentedUpper); }
if (rentedLower != null) { ArrayPool<double>.Shared.Return(rentedLower); }
if (rentedRawK != null) { ArrayPool<double>.Shared.Return(rentedRawK); }
if (rentedSmK != null) { ArrayPool<double>.Shared.Return(rentedSmK); }
if (rentedSmkUpper != null) { ArrayPool<double>.Shared.Return(rentedSmkUpper); }
if (rentedSmkLower != null) { ArrayPool<double>.Shared.Return(rentedSmkLower); }
}
}
public static TSeries Batch(TBarSeries source, int period = 21)
{
if (source == null || source.Count == 0)
{
return new TSeries([], []);
}
int len = source.Count;
var times = new List<long>(len);
var vals = new List<double>(len);
CollectionsMarshal.SetCount(times, len);
CollectionsMarshal.SetCount(vals, len);
Batch(source.HighValues, source.LowValues, source.CloseValues,
CollectionsMarshal.AsSpan(vals), period);
source.Times.CopyTo(CollectionsMarshal.AsSpan(times));
return new TSeries(times, vals);
}
public static (TSeries Results, Dstoch Indicator) Calculate(
TBarSeries source, int period = 21)
{
var indicator = new Dstoch(period);
var results = indicator.Update(source);
return (results, indicator);
}
}