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https://github.com/mihakralj/QuanTAlib.git
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dependabot
This commit is contained in:
Miha Kralj
+153
-80
@@ -1,89 +1,162 @@
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namespace QuanTAlib;
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using System;
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public class Afirma : AbstractBase
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namespace QuanTAlib
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{
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private readonly int Period;
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private readonly CircularBuffer _buffer;
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private readonly double _alpha; // Adaptive factor
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private double _lastAfirma, _p_lastAfirma;
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private double _lastError, _p_lastError;
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public Afirma(int period, double alpha = 0.1)
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public class Afirma : AbstractBase
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{
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if (period < 1)
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public enum WindowType
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{
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throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
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Rectangular,
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Hanning1,
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Hanning2,
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Blackman,
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BlackmanHarris
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}
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if (alpha <= 0 || alpha >= 1)
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private readonly int Periods;
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private readonly int Taps;
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private readonly WindowType Window;
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private readonly CircularBuffer _buffer;
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private readonly double[] _weights;
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private readonly double _wsum;
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private readonly double[] _armaBuffer;
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private readonly int _n;
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private readonly double _sx2, _sx3, _sx4, _sx5, _sx6, _den;
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public Afirma(int periods, int taps, WindowType window)
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{
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throw new ArgumentOutOfRangeException(nameof(alpha), "Alpha must be between 0 and 1 (exclusive).");
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if (periods < 1)
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{
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throw new ArgumentOutOfRangeException(nameof(periods), "Periods must be greater than or equal to 1.");
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}
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if (taps < 1)
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{
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throw new ArgumentOutOfRangeException(nameof(taps), "Taps must be greater than or equal to 1.");
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}
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Periods = periods;
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Taps = taps;
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Window = window;
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WarmupPeriod = taps;
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_buffer = new CircularBuffer(taps);
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_weights = new double[taps];
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_wsum = CalculateWeights();
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_armaBuffer = new double[taps];
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_n = (Taps - 1) / 2;
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// Calculate least squares coefficients in the constructor
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_sx2 = (2 * _n + 1) / 3.0;
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_sx3 = _n * (_n + 1) / 2.0;
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_sx4 = _sx2 * (3 * _n * _n + 3 * _n - 1) / 5.0;
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_sx5 = _sx3 * (2 * _n * _n + 2 * _n - 1) / 3.0;
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_sx6 = _sx2 * (3 * Math.Pow(_n, 3) * (_n + 2) - 3 * _n + 1) / 7.0;
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_den = _sx6 * _sx4 / _sx5 - _sx5;
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Name = "Afirma";
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Init();
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}
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Period = period;
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WarmupPeriod = period;
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_buffer = new CircularBuffer(period);
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_alpha = alpha;
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Name = "Afirma";
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WarmupPeriod = period;
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Init();
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public Afirma(object source, int periods, int taps, WindowType window) : this(periods, taps, window)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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}
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}
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protected override double Calculation()
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{
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ManageState(IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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if (_index >= Taps)
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{
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double a0 = _buffer[_n];
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double a1 = _buffer[_n] - _buffer[_n + 1];
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double sx2y = 0.0;
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double sx3y = 0.0;
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for (int i = 0; i <= _n; i++)
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{
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sx2y += i * i * _buffer[_n - i];
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sx3y += i * i * i * _buffer[_n - i];
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}
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sx2y = 2.0 * sx2y / _n / (_n + 1);
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sx3y = 2.0 * sx3y / _n / (_n + 1);
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double p = sx2y - a0 * _sx2 - a1 * _sx3;
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double q = sx3y - a0 * _sx3 - a1 * _sx4;
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double a2 = (p * _sx6 / _sx5 - q) / _den;
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double a3 = (q * _sx4 / _sx5 - p) / _den;
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for (int k = 0; k <= _n; k++)
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{
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_armaBuffer[_n - k] = a0 + k * a1 + k * k * a2 + k * k * k * a3;
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}
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}
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double result = 0.0;
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for (int k = 0; k < Taps; k++)
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{
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result += _buffer[k] * _weights[k] / _wsum;
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}
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IsHot = _index >= WarmupPeriod;
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return result;
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}
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private double CalculateWeights()
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{
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double wsum = 0.0;
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double centerTap = (Taps - 1) / 2.0;
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for (int k = 0; k < Taps; k++)
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{
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double windowWeight;
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switch (Window)
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{
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case WindowType.Rectangular:
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windowWeight = 1.0;
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break;
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case WindowType.Hanning1:
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windowWeight = 0.50 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
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break;
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case WindowType.Hanning2:
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windowWeight = 0.54 - 0.46 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
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break;
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case WindowType.Blackman:
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windowWeight = 0.42 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.08 * Math.Cos(4.0 * Math.PI * k / (Taps - 1));
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break;
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case WindowType.BlackmanHarris:
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windowWeight = 0.35875 - 0.48829 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.14128 * Math.Cos(4.0 * Math.PI * k / (Taps - 1)) - 0.01168 * Math.Cos(6.0 * Math.PI * k / (Taps - 1));
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break;
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default:
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windowWeight = 1.0;
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break;
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}
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double sincWeight;
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if (Math.Abs(k - centerTap) < 1e-10)
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{
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sincWeight = 1.0;
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}
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else
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{
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sincWeight = Math.Sin(Math.PI * (k - centerTap) / Periods) / (Math.PI * (k - centerTap) / Periods);
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}
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_weights[k] = windowWeight * sincWeight;
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wsum += _weights[k];
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}
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return wsum;
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}
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}
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public Afirma(object source, int period, double alpha = 0.1) : this(period: period, alpha: alpha)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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public override void Init()
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{
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base.Init();
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_lastAfirma = 0;
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_lastError = 0;
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}
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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_p_lastAfirma = _lastAfirma;
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_p_lastError = _lastError;
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}
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else
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{
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_lastAfirma = _p_lastAfirma;
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_lastError = _p_lastError;
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}
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}
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/// <summary>
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/// Core AFIRMA calculation
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/// </summary>
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protected override double Calculation()
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{
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double result;
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ManageState(IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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if (_index < Period)
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{
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// Use simple average during warmup period
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result = _buffer.Average();
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}
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else
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{
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// AFIRMA calculation
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double sma = _buffer.Average();
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double error = Input.Value - _lastAfirma;
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double denominator = Math.Abs(error) + Math.Abs(_lastError);
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double adaptiveFactor = denominator != 0 ? _alpha * Math.Abs(error) / denominator : _alpha;
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result = sma + adaptiveFactor * (Input.Value - sma);
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_lastError = error;
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}
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_lastAfirma = result;
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IsHot = _index >= WarmupPeriod;
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return result;
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}
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}
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}
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@@ -0,0 +1,89 @@
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namespace QuanTAlib;
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public class Ama : AbstractBase
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{
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private readonly int Period;
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private readonly CircularBuffer _buffer;
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private readonly double _alpha; // Adaptive factor
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private double _lastAfirma, _p_lastAfirma;
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private double _lastError, _p_lastError;
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public Ama(int period, double alpha = 0.1)
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{
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if (period < 1)
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{
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throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
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}
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if (alpha <= 0 || alpha >= 1)
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{
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throw new ArgumentOutOfRangeException(nameof(alpha), "Alpha must be between 0 and 1 (exclusive).");
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}
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Period = period;
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WarmupPeriod = period;
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_buffer = new CircularBuffer(period);
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_alpha = alpha;
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Name = "Afirma";
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WarmupPeriod = period;
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Init();
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}
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public Ama(object source, int period, double alpha = 0.1) : this(period: period, alpha: alpha)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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public override void Init()
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{
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base.Init();
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_lastAfirma = 0;
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_lastError = 0;
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}
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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_p_lastAfirma = _lastAfirma;
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_p_lastError = _lastError;
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}
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else
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{
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_lastAfirma = _p_lastAfirma;
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_lastError = _p_lastError;
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}
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}
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/// <summary>
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/// Core AFIRMA calculation
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/// </summary>
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protected override double Calculation()
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{
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double result;
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ManageState(IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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if (_index < Period)
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{
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// Use simple average during warmup period
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result = _buffer.Average();
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}
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else
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{
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// AFIRMA calculation
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double sma = _buffer.Average();
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double error = Input.Value - _lastAfirma;
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double denominator = Math.Abs(error) + Math.Abs(_lastError);
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double adaptiveFactor = denominator != 0 ? _alpha * Math.Abs(error) / denominator : _alpha;
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result = sma + adaptiveFactor * (Input.Value - sma);
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_lastError = error;
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}
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_lastAfirma = result;
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IsHot = _index >= WarmupPeriod;
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return result;
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}
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}
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