using System.Buffers; using System.Runtime.CompilerServices; using System.Runtime.InteropServices; namespace QuanTAlib; /// /// SWMA: Symmetric Weighted Moving Average /// /// /// FIR filter with triangular (symmetric) weights peaking at the center. /// Weight formula: w(i) = half + 1 - |i - half| where half = (period-1)/2.0 /// All weights are non-negative; output is a convex combination bounded by input range. /// Equivalent to SMA of SMA (double rectangular convolution). /// /// Default period=4 (PineScript ta.swma uses fixed period=4 with weights [1,2,2,1]/6). /// Minimum period=2. /// /// Detailed documentation [SkipLocalsInit] public sealed class Swma : AbstractBase { private readonly int _period; private readonly double[] _weights; private readonly RingBuffer _buffer; private readonly ITValuePublisher? _source; private readonly TValuePublishedHandler? _pubHandler; private bool _isNew = true; private bool _disposed; private double _lastValidValue = double.NaN; private double _p_lastValidValue = double.NaN; public bool IsNew => _isNew; public override bool IsHot => _buffer.IsFull; /// /// Creates SWMA with specified period. /// /// Lookback period (must be >= 2) [MethodImpl(MethodImplOptions.AggressiveInlining)] public Swma(int period = 4) { if (period < 2) { throw new ArgumentException("Period must be at least 2", nameof(period)); } _period = period; Name = $"Swma({_period})"; WarmupPeriod = _period; _buffer = new RingBuffer(_period); _weights = new double[_period]; ComputeTriangularWeights(_weights, _period); } /// /// Creates SWMA connected to a data source for event-based updates. /// [MethodImpl(MethodImplOptions.AggressiveInlining)] public Swma(ITValuePublisher source, int period = 4) : this(period) { _source = source; _pubHandler = Handle; _source.Pub += _pubHandler; } /// /// Computes symmetric triangular weights. /// w(i) = half + 1 - |i - half| where half = (period-1)/2.0 /// Normalized to sum=1.0. /// [MethodImpl(MethodImplOptions.AggressiveInlining)] private static void ComputeTriangularWeights(Span weights, int period) { double half = (period - 1) * 0.5; double wsum = 0.0; for (int i = 0; i < period; i++) { double w = half + 1.0 - Math.Abs(i - half); weights[i] = w; wsum += w; } // Normalize to sum=1.0 if (wsum > double.Epsilon) { double inv = 1.0 / wsum; for (int i = 0; i < period; i++) { weights[i] *= inv; } } } [MethodImpl(MethodImplOptions.AggressiveInlining)] public override TValue Update(TValue input, bool isNew = true) { _isNew = isNew; return Update(input, isNew, publish: true); } [MethodImpl(MethodImplOptions.AggressiveInlining)] private TValue Update(TValue input, bool isNew, bool publish) { if (isNew) { _p_lastValidValue = _lastValidValue; } else { _lastValidValue = _p_lastValidValue; } double val = GetValidValue(input.Value); if (!double.IsFinite(val)) { Last = new TValue(input.Time, double.NaN); if (publish) { PubEvent(Last, isNew); } return Last; } if (isNew) { _lastValidValue = val; _buffer.Add(val); int count = _buffer.Count; double result; if (count < _period) { result = val; } else { result = ConvolveFull(_buffer, _weights); } Last = new TValue(input.Time, result); if (publish) { PubEvent(Last, isNew); } return Last; } else { // Bar correction: snapshot, compute, restore _buffer.Snapshot(); double prevLast = _lastValidValue; double prevPLast = _p_lastValidValue; _lastValidValue = val; _buffer.UpdateNewest(val); int count = _buffer.Count; double result; if (count < _period) { result = val; } else { result = ConvolveFull(_buffer, _weights); } Last = new TValue(input.Time, result); // Restore buffer and state _buffer.Restore(); _lastValidValue = prevLast; _p_lastValidValue = prevPLast; if (publish) { PubEvent(Last, isNew); } return Last; } } public override TSeries Update(TSeries source) { if (source.Count == 0) { return new TSeries([], []); } int len = source.Count; var t = new List(len); var v = new List(len); CollectionsMarshal.SetCount(t, len); CollectionsMarshal.SetCount(v, len); var tSpan = CollectionsMarshal.AsSpan(t); var vSpan = CollectionsMarshal.AsSpan(v); Batch(source.Values, vSpan, _period); source.Times.CopyTo(tSpan); // Restore state by replaying last period bars Reset(); int startIndex = Math.Max(0, len - _period); for (int i = startIndex; i < len; i++) { Update(source[i], isNew: true, publish: false); } return new TSeries(t, v); } [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)) { return input; } return double.IsFinite(_lastValidValue) ? _lastValidValue : double.NaN; } /// /// FIR convolution using SIMD DotProduct over circular buffer. /// Weight[0] corresponds to oldest bar, Weight[period-1] to newest. /// [MethodImpl(MethodImplOptions.AggressiveInlining)] private static double ConvolveFull(RingBuffer buffer, double[] weights) { ReadOnlySpan internalBuf = buffer.InternalBuffer; int head = buffer.StartIndex; int period = buffer.Capacity; int part1Len = period - head; double sum1 = internalBuf.Slice(head, part1Len).DotProduct(weights.AsSpan(0, part1Len)); double sum2 = internalBuf[..head].DotProduct(weights.AsSpan(part1Len)); return sum1 + sum2; } public override void Prime(ReadOnlySpan source, TimeSpan? step = null) { foreach (var value in source) { Update(new TValue(DateTime.MinValue, value)); } } /// /// Calculates SWMA from a TSeries using streaming updates. /// public static TSeries Batch(TSeries source, int period = 4) { var swma = new Swma(period); return swma.Update(source); } /// /// Calculates Symmetric Weighted Moving Average over a span of values. /// /// Input values /// Output buffer (must be same length as source) /// Period for weight calculation (must be >= 2) /// Value to use for NaN substitution (default: NaN) [MethodImpl(MethodImplOptions.AggressiveInlining)] public static void Batch(ReadOnlySpan source, Span output, int period = 4, double nanValue = double.NaN) { if (period < 2) { throw new ArgumentException("Period must be at least 2", nameof(period)); } if (source.Length != output.Length) { throw new ArgumentException("Source and output must have the same length", nameof(output)); } if (source.Length == 0) { return; } int len = source.Length; const int StackallocThreshold = 256; // Allocate weights double[]? weightsRented = period > StackallocThreshold ? ArrayPool.Shared.Rent(period) : null; Span weights = period <= StackallocThreshold ? stackalloc double[period] : weightsRented!.AsSpan(0, period); // Allocate ring buffer double[]? ringRented = period > StackallocThreshold ? ArrayPool.Shared.Rent(period) : null; Span ring = period <= StackallocThreshold ? stackalloc double[period] : ringRented!.AsSpan(0, period); // Allocate NaN-corrected values array double[]? cleanRented = len > StackallocThreshold ? ArrayPool.Shared.Rent(len) : null; Span clean = len <= StackallocThreshold ? stackalloc double[len] : cleanRented!.AsSpan(0, len); ComputeTriangularWeights(weights, period); try { // Build NaN-corrected values array double lastValid = nanValue; for (int i = 0; i < len; i++) { double val = source[i]; if (double.IsFinite(val)) { lastValid = val; clean[i] = val; } else if (double.IsFinite(lastValid)) { clean[i] = lastValid; } else { clean[i] = double.NaN; } } // Apply SWMA FIR convolution int ringIdx = 0; int count = 0; for (int i = 0; i < len; i++) { double val = clean[i]; ring[ringIdx] = val; ringIdx++; if (ringIdx >= period) { ringIdx = 0; } if (count < period) { count++; } if (count < period) { // Warmup: return raw value output[i] = val; continue; } // Full window: DotProduct convolution over circular buffer // ringIdx points to next-write = oldest entry int part1Len = period - ringIdx; ReadOnlySpan ringRo = ring; double sum = ringRo.Slice(ringIdx, part1Len).DotProduct(weights.Slice(0, part1Len)) + ringRo[..ringIdx].DotProduct(weights.Slice(part1Len)); output[i] = sum; } } finally { if (weightsRented != null) { ArrayPool.Shared.Return(weightsRented); } if (ringRented != null) { ArrayPool.Shared.Return(ringRented); } if (cleanRented != null) { ArrayPool.Shared.Return(cleanRented); } } } /// /// Creates a SWMA indicator and calculates results from source. /// public static (TSeries Results, Swma Indicator) Calculate(TSeries source, int period = 4) { var indicator = new Swma(period); TSeries results = indicator.Update(source); return (results, indicator); } public override void Reset() { _buffer.Clear(); _lastValidValue = double.NaN; _p_lastValidValue = double.NaN; Last = default; } protected override void Dispose(bool disposing) { if (!_disposed) { if (disposing && _source != null && _pubHandler != null) { _source.Pub -= _pubHandler; } _disposed = true; } base.Dispose(disposing); } }