using System; using System.Collections.Generic; using System.Runtime.CompilerServices; using System.Runtime.InteropServices; namespace QuanTAlib; /// /// MMA: Modified Moving Average /// /// /// MMA blends a simple average with a weighted component computed from /// a lagged buffer to balance smoothness and responsiveness. /// [SkipLocalsInit] public sealed class Mma : AbstractBase { private const int MaxPeriod = 4000; [StructLayout(LayoutKind.Auto)] private record struct State(int Bars, bool IsHot) { public static State New() => new() { Bars = 0, IsHot = false }; } private readonly int _period; private readonly RingBuffer _buffer; private State _state = State.New(); private State _p_state = State.New(); private double _lastValidValue = double.NaN; private double _p_lastValidValue = double.NaN; private readonly ITValuePublisher? _publisher; private readonly TValuePublishedHandler? _listener; public override bool IsHot => _state.IsHot; public Mma(int period) { ArgumentOutOfRangeException.ThrowIfLessThan(period, 2); _period = Math.Min(Math.Max(2, period), MaxPeriod); _buffer = new RingBuffer(_period); Name = $"Mma({period})"; WarmupPeriod = _period; Reset(); } public Mma(ITValuePublisher source, int period) : this(period) { _publisher = source; _listener = Handle; source.Pub += _listener; } [MethodImpl(MethodImplOptions.AggressiveInlining)] public override TValue Update(TValue input, bool isNew = true) { if (isNew) { _p_state = _state; _p_lastValidValue = _lastValidValue; _buffer.Snapshot(); } else { _state = _p_state; _lastValidValue = _p_lastValidValue; _buffer.Restore(); } double val = input.Value; if (double.IsFinite(val)) { _lastValidValue = val; } else { val = _lastValidValue; } if (double.IsNaN(val)) { Last = new TValue(input.Time, double.NaN); PubEvent(Last, isNew); return Last; } _state.Bars++; _buffer.Add(val); double result = Compute(ref _state); Last = new TValue(input.Time, result); 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(len); var v = new List(len); CollectionsMarshal.SetCount(t, len); CollectionsMarshal.SetCount(v, len); var tSpan = CollectionsMarshal.AsSpan(t); var vSpan = CollectionsMarshal.AsSpan(v); source.Times.CopyTo(tSpan); // Snapshot buffer state before batch processing _buffer.Snapshot(); State preBatchState = _state; double preBatchLastValid = _lastValidValue; State state = _state; double lastValid = _lastValidValue; try { for (int i = 0; i < len; i++) { double val = source.Values[i]; if (double.IsFinite(val)) { lastValid = val; } else { val = lastValid; } if (double.IsNaN(val)) { vSpan[i] = double.NaN; continue; } state.Bars++; _buffer.Add(val); vSpan[i] = Compute(ref state); } // Only update state after successful completion _state = state; _lastValidValue = lastValid; // Set previous state to pre-batch for bar correction support _p_state = preBatchState; _p_lastValidValue = preBatchLastValid; } catch { // Restore buffer to pre-batch state on any exception _buffer.Restore(); throw; } Last = new TValue(tSpan[len - 1], vSpan[len - 1]); return new TSeries(t, v); } public override void Prime(ReadOnlySpan source, TimeSpan? step = null) { foreach (double value in source) { Update(new TValue(DateTime.MinValue, value)); } } public static TSeries Batch(TSeries source, int period) { var mma = new Mma(period); return mma.Update(source); } public static void Batch(ReadOnlySpan source, Span output, int period) { if (source.Length != output.Length) { throw new ArgumentException("Source and output must have the same length.", nameof(output)); } ArgumentOutOfRangeException.ThrowIfLessThan(period, 2); if (source.Length == 0) { return; } int window = Math.Min(Math.Max(2, period), MaxPeriod); double sum = 0.0; int count = 0; double lastValid = double.NaN; Span buffer = window <= 256 ? stackalloc double[window] : new double[window]; buffer.Clear(); int head = 0; for (int i = 0; i < source.Length; i++) { double val = source[i]; if (double.IsFinite(val)) { lastValid = val; } else { val = lastValid; } if (double.IsNaN(val)) { output[i] = double.NaN; continue; } if (count < window) { count++; } else { sum -= buffer[head]; } buffer[head] = val; sum += val; head++; if (head == window) { head = 0; } double sma = sum / count; double weightedSum = ComputeWeightedSum(buffer, head, count); double denom = (count + 1.0) * count; output[i] = Math.FusedMultiplyAdd(weightedSum, 6.0 / denom, sma); } } public static (TSeries Results, Mma Indicator) Calculate(TSeries source, int period) { var indicator = new Mma(period); TSeries results = indicator.Update(source); return (results, indicator); } public override void Reset() { _state = State.New(); _p_state = _state; _lastValidValue = double.NaN; _p_lastValidValue = double.NaN; _buffer.Clear(); Last = default; } protected override void Dispose(bool disposing) { if (disposing && _publisher != null && _listener != null) { _publisher.Pub -= _listener; } base.Dispose(disposing); } [MethodImpl(MethodImplOptions.AggressiveInlining)] private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew); [MethodImpl(MethodImplOptions.AggressiveInlining)] private double Compute(ref State state) { int count = _buffer.Count; if (count <= 0) { return double.NaN; } double sma = _buffer.Sum / count; double weightedSum = ComputeWeightedSum(_buffer, count); double denom = (count + 1.0) * count; double result = Math.FusedMultiplyAdd(weightedSum, 6.0 / denom, sma); if (!state.IsHot && count >= _period) { state.IsHot = true; } return result; } [MethodImpl(MethodImplOptions.AggressiveInlining)] private static double ComputeWeightedSum(RingBuffer buffer, int count) { int start = buffer.StartIndex; int capacity = buffer.Capacity; ReadOnlySpan data = buffer.InternalBuffer; int idx = start + count - 1; if (idx >= capacity) { idx -= capacity; } double weightedSum = 0.0; for (int i = 0; i < count; i++) { double weight = (count - ((2 * i) + 1)) * 0.5; weightedSum = Math.FusedMultiplyAdd(data[idx], weight, weightedSum); idx--; if (idx < 0) { idx += capacity; } } return weightedSum; } [MethodImpl(MethodImplOptions.AggressiveInlining)] private static double ComputeWeightedSum(ReadOnlySpan buffer, int head, int count) { int idx = head - 1; if (idx < 0) { idx = count - 1; } double weightedSum = 0.0; for (int i = 0; i < count; i++) { double weight = (count - ((2 * i) + 1)) * 0.5; weightedSum = Math.FusedMultiplyAdd(buffer[idx], weight, weightedSum); idx--; if (idx < 0) { idx = count - 1; } } return weightedSum; } }