2025-12-16 21:16:50 -08:00
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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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/// EMA: Exponential Moving Average
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/// </summary>
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/// <remarks>
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/// EMA applies exponential weighting to data points, giving more weight to recent values.
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/// Uses a single state variable for O(1) complexity per update.
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///
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/// Calculation:
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/// alpha = 2 / (period + 1)
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/// EMA_new = EMA_old + alpha * (newest - EMA_old)
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///
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/// Initialization:
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/// Uses a compensator factor to correct early-stage bias (when n < period).
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/// Output = EMA_state / (1 - (1-alpha)^n)
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///
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/// O(1) update:
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/// No buffer required, only previous EMA value and compensator state.
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///
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/// IsHot:
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/// Becomes true when n = ln(0.05) / ln(1 - alpha)
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Ema : AbstractBase
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{
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[StructLayout(LayoutKind.Auto)]
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2025-12-16 21:16:50 -08:00
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private record struct State(double Ema, double E, bool IsHot, bool IsCompensated)
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{
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public static State New() => new() { Ema = 0, E = 1.0, IsHot = false, IsCompensated = false };
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}
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private readonly double _alpha;
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private readonly double _decay;
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private State _state = State.New();
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private State _p_state = State.New();
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private double _lastValidValue;
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private double _p_lastValidValue;
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/// <summary>
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/// Creates EMA with specified period.
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/// Alpha = 2 / (period + 1)
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/// </summary>
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/// <param name="period">Period for EMA calculation (must be > 0)</param>
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public Ema(int period)
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{
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if (period <= 0)
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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_alpha = 2.0 / (period + 1);
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_decay = 1.0 - _alpha;
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Name = $"Ema({period})";
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WarmupPeriod = period;
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}
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/// <summary>
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/// Creates EMA with specified source and period.
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/// Subscribes to source.Pub event.
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/// </summary>
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/// <param name="source">Source to subscribe to</param>
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/// <param name="period">Period for EMA calculation</param>
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public Ema(ITValuePublisher source, int period) : this(period)
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{
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source.Pub += Handle;
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}
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public Ema(TSeries source, int period) : this(period)
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{
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Prime(source.Values);
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if (source.Count > 0)
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{
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Last = new TValue(source.LastTime, Last.Value);
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}
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source.Pub += Handle;
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}
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/// <summary>
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/// Creates EMA with specified alpha smoothing factor.
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/// </summary>
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/// <param name="alpha">Smoothing factor (0 < alpha <= 1)</param>
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public Ema(double alpha)
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{
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if (alpha <= 0 || alpha > 1)
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throw new ArgumentException("Alpha must be greater than 0 and at most 1", nameof(alpha));
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_alpha = alpha;
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_decay = 1.0 - alpha;
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Name = $"Ema(α={alpha:F4})";
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// Approximate period from alpha: alpha = 2/(N+1) => N = 2/alpha - 1
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WarmupPeriod = (int)(2.0 / alpha - 1.0);
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}
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/// <summary>
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/// True if the EMA has warmed up and is providing valid results.
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/// </summary>
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public override bool IsHot => _state.IsHot;
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/// <summary>
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/// Initializes the indicator state using the provided history.
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/// </summary>
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/// <param name="source">Historical data</param>
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public override void Prime(ReadOnlySpan<double> source)
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{
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if (source.Length == 0) return;
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// Reset state
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_state = State.New();
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_p_state = State.New();
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_lastValidValue = 0;
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_p_lastValidValue = 0;
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// Run the calculation on the history to update state
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// We don't need the output, just the final state
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int len = source.Length;
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double decay = _decay;
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int i = 0;
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// Find first valid value to seed lastValid
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bool foundValid = false;
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(source[k]))
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{
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_lastValidValue = source[k];
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foundValid = true;
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break;
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}
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}
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2025-12-25 20:53:56 -08:00
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if (!foundValid)
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{
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Last = new TValue(DateTime.MinValue, double.NaN);
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_p_state = _state;
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_p_lastValidValue = _lastValidValue;
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return;
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}
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2025-12-16 21:16:50 -08:00
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if (!_state.IsCompensated)
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{
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for (; i < len && _state.E > COMPENSATOR_THRESHOLD; i++)
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{
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double val = source[i];
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if (double.IsFinite(val))
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_lastValidValue = val;
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else
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val = _lastValidValue;
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_state.Ema += _alpha * (val - _state.Ema);
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_state.E *= decay;
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if (!_state.IsHot && _state.E <= COVERAGE_THRESHOLD)
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_state.IsHot = true;
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}
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if (_state.E <= COMPENSATOR_THRESHOLD)
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_state.IsCompensated = true;
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}
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for (; i < len; i++)
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{
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double val = source[i];
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if (double.IsFinite(val))
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_lastValidValue = val;
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else
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val = _lastValidValue;
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_state.Ema += _alpha * (val - _state.Ema);
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}
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// Calculate the initial "Last" value
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double result = _state.IsCompensated ? _state.Ema : _state.Ema / (1.0 - _state.E);
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// Note: We can't infer accurate Time from a simple Span<double>,
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// so we leave 'Last' with default time or user updates it on next Tick.
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Last = new TValue(DateTime.MinValue, result);
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// Backup state for the next update cycle
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_p_state = _state;
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_p_lastValidValue = _lastValidValue;
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}
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2025-12-27 15:46:28 -08:00
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private void Handle(object? sender, TValueEventArgs e) => Update(e.Value, e.IsNew);
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private double GetValidValue(double input)
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{
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if (double.IsFinite(input))
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{
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_lastValidValue = input;
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return input;
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}
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return _lastValidValue;
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}
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private const double COVERAGE_THRESHOLD = 0.05;
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private const double COMPENSATOR_THRESHOLD = 1e-10;
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override TValue Update(TValue input, bool isNew = true)
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{
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if (isNew)
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{
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_p_state = _state;
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_p_lastValidValue = _lastValidValue;
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}
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else
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{
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_state = _p_state;
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_lastValidValue = _p_lastValidValue;
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}
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double val = GetValidValue(input.Value);
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val = Compute(val, _alpha, _decay, ref _state);
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Last = new TValue(input.Time, val);
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PubEvent(Last);
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return Last;
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}
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public override TSeries Update(TSeries source)
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{
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if (source.Count == 0) return [];
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int len = source.Count;
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var t = new List<long>(len);
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var v = new List<double>(len);
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CollectionsMarshal.SetCount(t, len);
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CollectionsMarshal.SetCount(v, len);
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var tSpan = CollectionsMarshal.AsSpan(t);
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var vSpan = CollectionsMarshal.AsSpan(v);
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var sourceValues = source.Values;
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var sourceTimes = source.Times;
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State state = _state;
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double lastValidValue = _lastValidValue;
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CalculateCore(sourceValues, vSpan, _alpha, ref state, ref lastValidValue);
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_state = state;
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_lastValidValue = lastValidValue;
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sourceTimes.CopyTo(tSpan);
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_p_state = _state;
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_p_lastValidValue = _lastValidValue;
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Last = new TValue(tSpan[len - 1], vSpan[len - 1]);
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return new TSeries(t, v);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static double Compute(double input, double alpha, double decay, ref State state)
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{
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// state.Ema += alpha * (input - state.Ema)
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// state.Ema = state.Ema + alpha * input - alpha * state.Ema
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// state.Ema = state.Ema * (1 - alpha) + alpha * input
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// state.Ema = state.Ema * decay + alpha * input
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state.Ema = Math.FusedMultiplyAdd(state.Ema, decay, alpha * input);
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double result;
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if (!state.IsCompensated)
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{
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state.E *= decay;
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if (!state.IsHot && state.E <= COVERAGE_THRESHOLD)
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state.IsHot = true;
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if (state.E <= COMPENSATOR_THRESHOLD)
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{
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state.IsCompensated = true;
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result = state.Ema;
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}
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else
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{
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result = state.Ema / (1.0 - state.E);
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}
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}
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else
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{
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result = state.Ema;
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}
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return result;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static void CalculateCore(ReadOnlySpan<double> source, Span<double> output, double alpha, ref State state, ref double lastValidValue)
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{
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int len = source.Length;
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double decay = 1.0 - alpha;
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int i = 0;
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|
|
|
|
|
|
|
|
if (!state.IsCompensated)
|
|
|
|
|
|
{
|
|
|
|
|
|
for (; i < len && state.E > COMPENSATOR_THRESHOLD; i++)
|
|
|
|
|
|
{
|
|
|
|
|
|
double val = source[i];
|
|
|
|
|
|
if (double.IsFinite(val))
|
|
|
|
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|
lastValidValue = val;
|
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|
else
|
|
|
|
|
|
val = lastValidValue;
|
|
|
|
|
|
|
2025-12-25 17:18:41 -08:00
|
|
|
|
|
|
|
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|
|
state.Ema = Math.FusedMultiplyAdd(state.Ema, decay, alpha * val);
|
2025-12-16 21:16:50 -08:00
|
|
|
|
state.E *= decay;
|
|
|
|
|
|
|
|
|
|
|
|
if (!state.IsHot && state.E <= COVERAGE_THRESHOLD)
|
|
|
|
|
|
state.IsHot = true;
|
|
|
|
|
|
|
|
|
|
|
|
output[i] = state.Ema / (1.0 - state.E);
|
|
|
|
|
|
}
|
|
|
|
|
|
if (state.E <= COMPENSATOR_THRESHOLD)
|
|
|
|
|
|
state.IsCompensated = true;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
for (; i < len; i++)
|
|
|
|
|
|
{
|
|
|
|
|
|
double val = source[i];
|
|
|
|
|
|
if (double.IsFinite(val))
|
|
|
|
|
|
lastValidValue = val;
|
|
|
|
|
|
else
|
|
|
|
|
|
val = lastValidValue;
|
|
|
|
|
|
|
2025-12-25 17:18:41 -08:00
|
|
|
|
// state.Ema += alpha * (val - state.Ema); // skipcq: S125
|
|
|
|
|
|
state.Ema = Math.FusedMultiplyAdd(state.Ema, decay, alpha * val);
|
2025-12-16 21:16:50 -08:00
|
|
|
|
output[i] = state.Ema;
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// <summary>
|
|
|
|
|
|
/// Runs a high-performance batch calculation on history and returns
|
|
|
|
|
|
/// a "Hot" Ema instance ready to process the next tick immediately.
|
|
|
|
|
|
/// </summary>
|
|
|
|
|
|
/// <param name="source">Historical time series</param>
|
|
|
|
|
|
/// <param name="period">EMA Period</param>
|
|
|
|
|
|
/// <returns>A tuple containing the full calculation results and the hot indicator instance</returns>
|
|
|
|
|
|
public static (TSeries Results, Ema Indicator) Calculate(TSeries source, int period)
|
|
|
|
|
|
{
|
|
|
|
|
|
var ema = new Ema(period);
|
|
|
|
|
|
TSeries results = ema.Update(source);
|
|
|
|
|
|
return (results, ema);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// <summary>
|
|
|
|
|
|
/// Calculates EMA for the entire series using a new instance.
|
|
|
|
|
|
/// </summary>
|
|
|
|
|
|
/// <param name="source">Input series</param>
|
|
|
|
|
|
/// <param name="period">EMA period</param>
|
|
|
|
|
|
/// <returns>EMA series</returns>
|
|
|
|
|
|
public static TSeries Batch(TSeries source, int period)
|
|
|
|
|
|
{
|
|
|
|
|
|
var ema = new Ema(period);
|
|
|
|
|
|
return ema.Update(source);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// <summary>
|
|
|
|
|
|
/// Calculates EMA in-place using period, writing results to pre-allocated output span.
|
|
|
|
|
|
/// Zero-allocation method for maximum performance.
|
|
|
|
|
|
/// Alpha = 2 / (period + 1)
|
|
|
|
|
|
/// </summary>
|
|
|
|
|
|
/// <param name="source">Input values</param>
|
|
|
|
|
|
/// <param name="output">Output span (must be same length as source)</param>
|
|
|
|
|
|
/// <param name="period">EMA period (must be > 0)</param>
|
|
|
|
|
|
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
|
|
|
|
|
public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period)
|
|
|
|
|
|
{
|
|
|
|
|
|
if (period <= 0)
|
|
|
|
|
|
throw new ArgumentException("Period must be greater than 0", nameof(period));
|
|
|
|
|
|
|
|
|
|
|
|
double alpha = 2.0 / (period + 1);
|
|
|
|
|
|
Batch(source, output, alpha);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
[MethodImpl(MethodImplOptions.AggressiveInlining)]
|
|
|
|
|
|
public static void Batch(ReadOnlySpan<double> source, Span<double> output, double alpha)
|
|
|
|
|
|
{
|
|
|
|
|
|
if (source.Length != output.Length)
|
2025-12-25 20:18:14 -08:00
|
|
|
|
throw new ArgumentException("Source and output must have the same length", nameof(source));
|
2025-12-16 21:16:50 -08:00
|
|
|
|
if (alpha <= 0 || alpha > 1)
|
2025-12-25 20:18:14 -08:00
|
|
|
|
throw new ArgumentOutOfRangeException(nameof(alpha), "Alpha must be > 0 and <= 1");
|
2025-12-16 21:16:50 -08:00
|
|
|
|
|
|
|
|
|
|
if (source.Length == 0) return;
|
|
|
|
|
|
|
|
|
|
|
|
var state = State.New();
|
|
|
|
|
|
double lastValid = 0;
|
feat(rsi, alma, bilateral, blma, butter, ema, htit, kama, lsma, pwma, rma, trima, vidya, wma): enhance calculations with NaN handling and edge case management; improve performance and stability across multiple classes
2025-12-25 22:16:07 -08:00
|
|
|
|
bool foundValid = false;
|
2025-12-16 21:16:50 -08:00
|
|
|
|
|
|
|
|
|
|
// Find first valid value to seed lastValid
|
|
|
|
|
|
for (int k = 0; k < source.Length; k++)
|
|
|
|
|
|
{
|
|
|
|
|
|
if (double.IsFinite(source[k]))
|
|
|
|
|
|
{
|
|
|
|
|
|
lastValid = source[k];
|
feat(rsi, alma, bilateral, blma, butter, ema, htit, kama, lsma, pwma, rma, trima, vidya, wma): enhance calculations with NaN handling and edge case management; improve performance and stability across multiple classes
2025-12-25 22:16:07 -08:00
|
|
|
|
foundValid = true;
|
2025-12-16 21:16:50 -08:00
|
|
|
|
break;
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|
|
|
|
|
|
|
feat(rsi, alma, bilateral, blma, butter, ema, htit, kama, lsma, pwma, rma, trima, vidya, wma): enhance calculations with NaN handling and edge case management; improve performance and stability across multiple classes
2025-12-25 22:16:07 -08:00
|
|
|
|
if (!foundValid)
|
|
|
|
|
|
{
|
|
|
|
|
|
output.Fill(double.NaN);
|
|
|
|
|
|
return;
|
|
|
|
|
|
}
|
|
|
|
|
|
|
2025-12-16 21:16:50 -08:00
|
|
|
|
CalculateCore(source, output, alpha, ref state, ref lastValid);
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
/// <summary>
|
|
|
|
|
|
/// Resets the EMA state.
|
|
|
|
|
|
/// </summary>
|
|
|
|
|
|
public override void Reset()
|
|
|
|
|
|
{
|
|
|
|
|
|
_state = State.New();
|
|
|
|
|
|
_p_state = _state;
|
|
|
|
|
|
_lastValidValue = 0;
|
|
|
|
|
|
_p_lastValidValue = 0;
|
|
|
|
|
|
Last = default;
|
|
|
|
|
|
}
|
|
|
|
|
|
}
|