mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-05 12:37:43 +00:00
7253f61299
- Implemented the TRAMA (Trend Regularity Adaptive Moving Average) class with adaptive EMA logic. - Added unit tests for TRAMA functionality, including constructor validation, basic calculations, state management, and robustness checks. - Created validation tests to ensure consistency across different modes of operation (streaming, batch, and static calculations). - Enhanced documentation for TRAMA, including performance profiles and quality metrics. - Updated workspace configuration by removing unnecessary folder references.
409 lines
12 KiB
C#
409 lines
12 KiB
C#
using System.Buffers;
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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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/// PARZEN: Parzen (de la Vallée-Poussin) Window Moving Average
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/// </summary>
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/// <remarks>
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/// Symmetric FIR filter using the Parzen piecewise cubic window function.
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/// The Parzen window is the self-convolution of two Bartlett (triangular) windows
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/// at half-length, yielding continuous first and second derivatives and -24 dB/octave
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/// sidelobe rolloff. All weights are non-negative.
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///
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/// Calculation: Precomputed piecewise cubic weights, applied as FIR convolution
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/// over sliding window. O(period) per bar.
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/// </remarks>
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/// <seealso href="Parzen.md">Detailed documentation</seealso>
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[SkipLocalsInit]
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public sealed class Parzen : AbstractBase
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{
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private readonly int _period;
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private readonly double[] _weights;
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private readonly RingBuffer _buffer;
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private readonly ITValuePublisher? _source;
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private readonly TValuePublishedHandler? _pubHandler;
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private bool _isNew = true;
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private bool _disposed;
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private double _lastValidValue = double.NaN;
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private double _p_lastValidValue = double.NaN;
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public bool IsNew => _isNew;
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public override bool IsHot => _buffer.IsFull;
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/// <summary>
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/// Creates PARZEN with specified period.
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/// </summary>
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/// <param name="period">Lookback period (>= 2)</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Parzen(int period = 14)
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{
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if (period < 2)
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{
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throw new ArgumentException("Period must be at least 2", nameof(period));
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}
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_period = period;
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Name = $"Parzen({_period.ToString(System.Globalization.CultureInfo.InvariantCulture)})";
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WarmupPeriod = _period;
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_buffer = new RingBuffer(_period);
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_weights = new double[_period];
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ComputeParzenWeights(_weights, _period);
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}
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/// <summary>
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/// Creates PARZEN connected to a data source for event-based updates.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Parzen(ITValuePublisher source, int period = 14) : this(period)
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{
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_source = source;
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_pubHandler = Handle;
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_source.Pub += _pubHandler;
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}
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/// <summary>
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/// Computes Parzen (de la Vallée-Poussin) window weights and normalizes to sum=1.
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/// Inner region (|u| <= 0.5): w = 1 - 6u² + 6|u|³
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/// Outer region (0.5 < |u| <= 1.0): w = 2(1 - |u|)³
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/// All weights are non-negative.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static void ComputeParzenWeights(Span<double> weights, int period)
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{
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double halfN = (period - 1) * 0.5;
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double wsum = 0.0;
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for (int k = 0; k < period; k++)
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{
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double u = halfN > 0 ? (k - halfN) / halfN : 0.0;
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double absU = Math.Abs(u);
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double w;
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if (absU <= 0.5)
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{
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// Inner region: cubic spline
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w = Math.FusedMultiplyAdd(6.0, absU * absU * absU, 1.0 - 6.0 * absU * absU);
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}
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else if (absU <= 1.0)
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{
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// Outer region: cubic taper to zero
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double t = 1.0 - absU;
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w = 2.0 * t * t * t;
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}
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else
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{
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w = 0.0;
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}
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weights[k] = w;
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wsum += w;
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}
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if (Math.Abs(wsum) > double.Epsilon)
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{
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double inv = 1.0 / wsum;
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for (int k = 0; k < period; k++)
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{
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weights[k] *= inv;
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}
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}
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}
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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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_isNew = isNew;
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return Update(input, isNew, publish: true);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private TValue Update(TValue input, bool isNew, bool publish)
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{
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if (isNew)
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{
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_p_lastValidValue = _lastValidValue;
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}
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else
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{
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_lastValidValue = _p_lastValidValue;
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}
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double val = GetValidValue(input.Value);
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if (!double.IsFinite(val))
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{
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Last = new TValue(input.Time, double.NaN);
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if (publish) { PubEvent(Last, isNew); }
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return Last;
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}
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if (isNew)
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{
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_lastValidValue = val;
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_buffer.Add(val);
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int count = _buffer.Count;
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double result;
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if (count < _period)
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{
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result = val;
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}
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else
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{
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result = ConvolveFull(_buffer, _weights);
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}
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Last = new TValue(input.Time, result);
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if (publish) { PubEvent(Last, isNew); }
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return Last;
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}
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else
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{
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_buffer.Snapshot();
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double prevLast = _lastValidValue;
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double prevPLast = _p_lastValidValue;
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_lastValidValue = val;
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_buffer.UpdateNewest(val);
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int count = _buffer.Count;
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double result;
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if (count < _period)
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{
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result = val;
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}
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else
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{
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result = ConvolveFull(_buffer, _weights);
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}
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Last = new TValue(input.Time, result);
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_buffer.Restore();
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_lastValidValue = prevLast;
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_p_lastValidValue = prevPLast;
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if (publish) { PubEvent(Last, isNew); }
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return Last;
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}
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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)
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{
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return new TSeries([], []);
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}
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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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Batch(source.Values, vSpan, _period);
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source.Times.CopyTo(tSpan);
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Reset();
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int startIndex = Math.Max(0, len - _period);
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for (int i = startIndex; i < len; i++)
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{
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Update(source[i], isNew: true, publish: false);
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}
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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 void Handle(object? sender, in 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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return input;
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}
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return double.IsFinite(_lastValidValue) ? _lastValidValue : double.NaN;
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}
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/// <summary>
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/// FIR convolution using SIMD DotProduct over circular buffer.
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/// Weight[0] corresponds to oldest bar, Weight[period-1] to newest.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static double ConvolveFull(RingBuffer buffer, double[] weights)
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{
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ReadOnlySpan<double> internalBuf = buffer.InternalBuffer;
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int head = buffer.StartIndex;
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int period = buffer.Capacity;
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int part1Len = period - head;
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double sum1 = internalBuf.Slice(head, part1Len).DotProduct(weights.AsSpan(0, part1Len));
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double sum2 = internalBuf[..head].DotProduct(weights.AsSpan(part1Len));
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return sum1 + sum2;
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}
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public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
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{
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foreach (var value in source)
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{
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Update(new TValue(DateTime.MinValue, value));
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}
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}
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public static TSeries Batch(TSeries source, int period = 14)
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{
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var parzen = new Parzen(period);
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return parzen.Update(source);
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}
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/// <summary>
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/// Calculates Parzen Window MA over a span of values.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static void Batch(ReadOnlySpan<double> source, Span<double> output, int period = 14, double nanValue = double.NaN)
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{
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if (period < 2)
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{
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throw new ArgumentException("Period must be at least 2", nameof(period));
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}
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if (source.Length != output.Length)
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{
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throw new ArgumentException("Source and output must have the same length", nameof(output));
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}
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if (source.Length == 0)
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{
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return;
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}
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int len = source.Length;
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const int StackallocThreshold = 256;
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double[]? weightsRented = period > StackallocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
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Span<double> weights = period <= StackallocThreshold
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? stackalloc double[period]
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: weightsRented!.AsSpan(0, period);
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double[]? ringRented = period > StackallocThreshold ? ArrayPool<double>.Shared.Rent(period) : null;
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Span<double> ring = period <= StackallocThreshold
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? stackalloc double[period]
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: ringRented!.AsSpan(0, period);
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double[]? cleanRented = len > StackallocThreshold ? ArrayPool<double>.Shared.Rent(len) : null;
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Span<double> clean = len <= StackallocThreshold
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? stackalloc double[len]
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: cleanRented!.AsSpan(0, len);
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ComputeParzenWeights(weights, period);
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try
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{
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double lastValid = nanValue;
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for (int i = 0; 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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{
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lastValid = val;
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clean[i] = val;
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}
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else if (double.IsFinite(lastValid))
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{
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clean[i] = lastValid;
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}
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else
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{
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clean[i] = double.NaN;
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}
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}
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int ringIdx = 0;
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int count = 0;
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for (int i = 0; i < len; i++)
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{
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double val = clean[i];
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ring[ringIdx] = val;
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ringIdx++;
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if (ringIdx >= period)
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{
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ringIdx = 0;
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}
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if (count < period)
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{
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count++;
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}
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if (count < period)
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{
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output[i] = val;
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continue;
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}
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int part1Len = period - ringIdx;
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ReadOnlySpan<double> ringRo = ring;
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double sum = ringRo.Slice(ringIdx, part1Len).DotProduct(weights.Slice(0, part1Len))
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+ ringRo[..ringIdx].DotProduct(weights.Slice(part1Len));
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output[i] = sum;
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}
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}
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finally
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{
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if (weightsRented != null)
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{
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ArrayPool<double>.Shared.Return(weightsRented);
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}
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if (ringRented != null)
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{
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ArrayPool<double>.Shared.Return(ringRented);
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}
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if (cleanRented != null)
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{
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ArrayPool<double>.Shared.Return(cleanRented);
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}
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}
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}
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public static (TSeries Results, Parzen Indicator) Calculate(TSeries source, int period = 14)
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{
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var indicator = new Parzen(period);
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TSeries results = indicator.Update(source);
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return (results, indicator);
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}
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public override void Reset()
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{
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_buffer.Clear();
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_lastValidValue = double.NaN;
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_p_lastValidValue = double.NaN;
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Last = default;
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}
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protected override void Dispose(bool disposing)
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{
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if (!_disposed)
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{
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if (disposing && _source != null && _pubHandler != null)
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{
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_source.Pub -= _pubHandler;
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}
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_disposed = true;
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}
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base.Dispose(disposing);
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}
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}
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