Files

396 lines
12 KiB
C#
Raw Permalink Normal View History

using System.Buffers;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
/// <summary>
/// HOLT: Holt Exponential Moving Average (Double Exponential Smoothing)
/// </summary>
/// <remarks>
/// Holt's (1957) double exponential smoothing tracks both level and trend,
/// producing a 1-step-ahead forecast that adapts to trending data.
///
/// Calculation:
/// <c>L_t = α·y_t + (1-α)·(L_{t-1} + B_{t-1})</c> (Level)
/// <c>B_t = γ·(L_t - L_{t-1}) + (1-γ)·B_{t-1}</c> (Trend)
/// <c>HOLT_t = L_t + B_t</c> (1-step-ahead forecast)
///
/// When gamma=0, degenerates to standard EMA (no trend correction).
/// When gamma=alpha, provides balanced level/trend tracking.
/// </remarks>
/// <seealso href="Holt.md">Detailed documentation</seealso>
/// <seealso href="holt.pine">Reference Pine Script implementation</seealso>
[SkipLocalsInit]
public sealed class Holt : AbstractBase
{
[StructLayout(LayoutKind.Auto)]
private record struct State(double Level, double Trend, int Count, bool IsHot, bool Initialized)
{
public static State New() => new() { Level = 0, Trend = 0, Count = 0, IsHot = false, Initialized = false };
}
private readonly double _alpha;
private readonly double _decay;
private readonly double _gamma;
private readonly double _gammaDecay;
private State _state = State.New();
private State _p_state = State.New();
private double _lastValidValue;
private double _p_lastValidValue;
/// <summary>
/// Creates Holt with specified period and trend smoothing factor.
/// Alpha = 2 / (period + 1). Gamma defaults to alpha when 0.
/// </summary>
/// <param name="period">Smoothing period (must be &gt; 0)</param>
/// <param name="gamma">Trend smoothing factor [0..1]. 0 = auto (uses alpha)</param>
public Holt(int period, double gamma = 0)
{
ArgumentOutOfRangeException.ThrowIfNegativeOrZero(period);
if (gamma < 0 || gamma > 1)
{
throw new ArgumentException("Gamma must be between 0 and 1", nameof(gamma));
}
_alpha = 2.0 / (period + 1.0);
_decay = 1.0 - _alpha;
_gamma = gamma > 0 ? gamma : _alpha;
_gammaDecay = 1.0 - _gamma;
Name = gamma > 0 ? $"Holt({period},{gamma:F2})" : $"Holt({period})";
WarmupPeriod = period;
}
/// <summary>
/// Creates Holt with specified source and parameters.
/// Subscribes to source.Pub event.
/// </summary>
public Holt(ITValuePublisher source, int period, double gamma = 0) : this(period, gamma)
{
source.Pub += Handle;
}
/// <summary>
/// Creates Holt from a TSeries source with specified parameters.
/// Primes from history and subscribes to source.Pub event.
/// </summary>
public Holt(TSeries source, int period, double gamma = 0) : this(period, gamma)
{
Prime(source.Values);
if (source.Count > 0)
{
Last = new TValue(source.LastTime, Last.Value);
}
source.Pub += Handle;
}
/// <summary>
/// True when the Holt indicator has received enough data for valid output.
/// </summary>
public override bool IsHot => _state.IsHot;
private const int StackAllocThreshold = 512;
/// <summary>
/// Initializes the indicator state using the provided history.
/// </summary>
public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
{
if (source.Length == 0)
{
return;
}
_state = State.New();
_p_state = State.New();
_lastValidValue = 0;
_p_lastValidValue = 0;
int len = source.Length;
bool foundValid = false;
for (int k = 0; k < len; k++)
{
if (double.IsFinite(source[k]))
{
_lastValidValue = source[k];
foundValid = true;
break;
}
}
if (!foundValid)
{
Last = new TValue(DateTime.MinValue, double.NaN);
_p_state = _state;
_p_lastValidValue = _lastValidValue;
return;
}
double[]? rented = len > StackAllocThreshold ? ArrayPool<double>.Shared.Rent(len) : null;
Span<double> tempOutput = rented != null
? rented.AsSpan(0, len)
: stackalloc double[len];
try
{
CalculateCore(source, tempOutput, _alpha, _decay, _gamma, _gammaDecay, WarmupPeriod, ref _state, ref _lastValidValue);
Last = new TValue(DateTime.MinValue, tempOutput[len - 1]);
_p_state = _state;
_p_lastValidValue = _lastValidValue;
}
finally
{
if (rented != null)
{
ArrayPool<double>.Shared.Return(rented);
}
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double GetValidValue(double input)
{
if (double.IsFinite(input))
{
_lastValidValue = input;
return input;
}
return _lastValidValue;
}
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
public override TValue Update(TValue input, bool isNew = true)
{
if (isNew)
{
_p_state = _state;
_p_lastValidValue = _lastValidValue;
}
else
{
_state = _p_state;
_lastValidValue = _p_lastValidValue;
}
double val = GetValidValue(input.Value);
val = Compute(val, _alpha, _decay, _gamma, _gammaDecay, WarmupPeriod, ref _state);
Last = new TValue(input.Time, val);
PubEvent(Last, isNew);
return Last;
}
[MethodImpl(MethodImplOptions.AggressiveOptimization)]
public override TSeries Update(TSeries source)
{
if (source.Count == 0)
{
return [];
}
int len = source.Count;
var t = new List<long>(len);
var v = new List<double>(len);
CollectionsMarshal.SetCount(t, len);
CollectionsMarshal.SetCount(v, len);
var tSpan = CollectionsMarshal.AsSpan(t);
var vSpan = CollectionsMarshal.AsSpan(v);
var sourceValues = source.Values;
var sourceTimes = source.Times;
State state = _state;
double lastValidValue = _lastValidValue;
CalculateCore(sourceValues, vSpan, _alpha, _decay, _gamma, _gammaDecay, WarmupPeriod, ref state, ref lastValidValue);
_state = state;
_lastValidValue = lastValidValue;
sourceTimes.CopyTo(tSpan);
_p_state = _state;
_p_lastValidValue = _lastValidValue;
Last = new TValue(tSpan[len - 1], vSpan[len - 1]);
return new TSeries(t, v);
}
/// <summary>
/// Core computation: Holt double exponential smoothing.
/// Level and trend equations use FMA for precision.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private static double Compute(double input, double alpha, double decay, double gamma, double gammaDecay, int warmup, ref State state)
{
if (!state.Initialized)
{
// First bar: initialize level to input, trend to 0
state.Level = input;
state.Trend = 0;
state.Initialized = true;
state.Count = 1;
if (warmup <= 1)
{
state.IsHot = true;
}
return input;
}
double prevLevel = state.Level;
// Level: alpha * input + (1 - alpha) * (prevLevel + trend)
// = FMA(alpha, input, decay * (prevLevel + trend))
state.Level = Math.FusedMultiplyAdd(alpha, input, decay * (prevLevel + state.Trend));
// Trend: gamma * (level - prevLevel) + (1 - gamma) * trend
// = FMA(gamma, level - prevLevel, gammaDecay * trend)
state.Trend = Math.FusedMultiplyAdd(gamma, state.Level - prevLevel, gammaDecay * state.Trend);
state.Count++;
if (!state.IsHot && state.Count >= warmup)
{
state.IsHot = true;
}
// Output: level + trend (1-step-ahead forecast)
return state.Level + state.Trend;
}
/// <summary>
/// Core batch calculation with NaN handling.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveOptimization)]
private static void CalculateCore(ReadOnlySpan<double> source, Span<double> output,
double alpha, double decay, double gamma, double gammaDecay,
int warmup, ref State state, ref double lastValidValue)
{
int len = source.Length;
ref double srcRef = ref MemoryMarshal.GetReference(source);
ref double outRef = ref MemoryMarshal.GetReference(output);
for (int i = 0; i < len; i++)
{
double val = Unsafe.Add(ref srcRef, i);
if (!double.IsFinite(val))
{
val = lastValidValue;
}
else
{
lastValidValue = val;
}
if (!state.Initialized)
{
state.Level = val;
state.Trend = 0;
state.Initialized = true;
state.Count = 1;
if (warmup <= 1)
{
state.IsHot = true;
}
Unsafe.Add(ref outRef, i) = val;
continue;
}
double prevLevel = state.Level;
state.Level = Math.FusedMultiplyAdd(alpha, val, decay * (prevLevel + state.Trend));
state.Trend = Math.FusedMultiplyAdd(gamma, state.Level - prevLevel, gammaDecay * state.Trend);
state.Count++;
if (!state.IsHot && state.Count >= warmup)
{
state.IsHot = true;
}
Unsafe.Add(ref outRef, i) = state.Level + state.Trend;
}
}
/// <summary>
/// Calculates Holt for the entire series using a new instance.
/// </summary>
public static TSeries Batch(TSeries source, int period, double gamma = 0)
{
var holt = new Holt(period, gamma);
return holt.Update(source);
}
/// <summary>
/// Calculates Holt in-place using pre-allocated output span. Zero-allocation.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveOptimization)]
public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period, double gamma = 0)
{
if (source.Length != output.Length)
{
throw new ArgumentException("Source and output must have the same length", nameof(output));
}
ArgumentOutOfRangeException.ThrowIfNegativeOrZero(period);
if (gamma < 0 || gamma > 1)
{
throw new ArgumentException("Gamma must be between 0 and 1", nameof(gamma));
}
if (source.Length == 0)
{
return;
}
double alpha = 2.0 / (period + 1.0);
double decay = 1.0 - alpha;
double g = gamma > 0 ? gamma : alpha;
double gDecay = 1.0 - g;
var state = State.New();
double lastValid = 0;
bool foundValid = false;
for (int k = 0; k < source.Length; k++)
{
if (double.IsFinite(source[k]))
{
lastValid = source[k];
foundValid = true;
break;
}
}
if (!foundValid)
{
output.Fill(double.NaN);
return;
}
CalculateCore(source, output, alpha, decay, g, gDecay, period, ref state, ref lastValid);
}
/// <summary>
/// Runs a high-performance batch and returns a hot Holt instance.
/// </summary>
public static (TSeries Results, Holt Indicator) Calculate(TSeries source, int period, double gamma = 0)
{
var holt = new Holt(period, gamma);
TSeries results = holt.Update(source);
return (results, holt);
}
/// <summary>
/// Resets the Holt filter state.
/// </summary>
public override void Reset()
{
_state = State.New();
_p_state = _state;
_lastValidValue = 0;
_p_lastValidValue = 0;
Last = default;
}
}