Files
QuanTAlib/lib/trends/mama/Mama.cs
T

288 lines
8.6 KiB
C#

using System;
using System.Runtime.CompilerServices;
namespace QuanTAlib;
/// <summary>
/// MESA Adaptive Moving Average (MAMA)
/// A trend-following indicator that adapts to the market's phase rate of change.
/// </summary>
[SkipLocalsInit]
public sealed class Mama : ITValuePublisher
{
public TValue Last { get; private set; }
public TValue Fama { get; private set; }
public bool IsHot => _index > 6;
public event Action<TValue>? Pub;
private readonly double _fastLimit;
private readonly double _slowLimit;
private double _period, _p_period;
private double _phase, _p_phase;
private double _mama, _p_mama;
private double _fama, _p_fama;
private double _sumPr, _p_sumPr;
private int _index;
// State variables for IIR filters need to be preserved
private double _i2, _p_i2;
private double _q2, _p_q2;
private double _re, _p_re;
private double _im, _p_im;
private double _lastValidPrice;
private readonly RingBuffer _priceBuffer;
private readonly RingBuffer _smoothBuffer;
private readonly RingBuffer _detrender;
private readonly RingBuffer _I1_buffer;
private readonly RingBuffer _Q1_buffer;
private const double c1 = 0.0962;
private const double c2 = 0.5769;
private const double TWOPI = 2.0 * Math.PI;
private const double RadToDeg = 180.0 / Math.PI;
public Mama(double fastLimit = 0.5, double slowLimit = 0.05)
{
if (fastLimit <= slowLimit || fastLimit <= 0 || slowLimit <= 0)
{
throw new ArgumentException("FastLimit must be > SlowLimit and > 0");
}
_fastLimit = fastLimit;
_slowLimit = slowLimit;
_priceBuffer = new RingBuffer(7);
_smoothBuffer = new RingBuffer(7);
_detrender = new RingBuffer(7);
_I1_buffer = new RingBuffer(7);
_Q1_buffer = new RingBuffer(7);
Name = $"Mama({fastLimit:F2},{slowLimit:F2})";
Init();
}
public Mama(ITValuePublisher source, double fastLimit = 0.5, double slowLimit = 0.05) : this(fastLimit, slowLimit)
{
source.Pub += (item) => Update(item);
}
public void Init()
{
_period = _p_period = 0.0;
_phase = _p_phase = 0.0;
_mama = _p_mama = double.NaN;
_fama = _p_fama = double.NaN;
_sumPr = _p_sumPr = 0.0;
_index = 0;
_i2 = _p_i2 = 0.0;
_q2 = _p_q2 = 0.0;
_re = _p_re = 0.0;
_im = _p_im = 0.0;
_lastValidPrice = 0.0;
_priceBuffer.Clear();
_smoothBuffer.Clear();
_detrender.Clear();
_I1_buffer.Clear();
_Q1_buffer.Clear();
Last = new TValue(DateTime.MinValue, double.NaN);
Fama = new TValue(DateTime.MinValue, double.NaN);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public TValue Update(TValue input, bool isNew = true)
{
if (isNew)
{
_p_period = _period;
_p_phase = _phase;
_p_mama = _mama;
_p_fama = _fama;
_p_sumPr = _sumPr;
_p_i2 = _i2;
_p_q2 = _q2;
_p_re = _re;
_p_im = _im;
_index++;
}
else
{
_period = _p_period;
_phase = _p_phase;
_mama = _p_mama;
_fama = _p_fama;
_sumPr = _p_sumPr;
_i2 = _p_i2;
_q2 = _p_q2;
_re = _p_re;
_im = _p_im;
}
double price = input.Value;
if (!double.IsFinite(price))
{
price = _lastValidPrice;
}
else
{
_lastValidPrice = price;
}
_priceBuffer.Add(price, isNew);
if (_index > 6)
{
double adj = (0.075 * _period) + 0.54;
// Smooth
double smooth = (4.0 * _priceBuffer[0] + 3.0 * _priceBuffer[1] + 2.0 * _priceBuffer[2] + _priceBuffer[3]) * 0.1;
_smoothBuffer.Add(smooth, isNew);
// Detrender
double dt = (c1 * _smoothBuffer[0] + c2 * _smoothBuffer[2] - c2 * _smoothBuffer[4] - c1 * _smoothBuffer[6]) * adj;
_detrender.Add(dt, isNew);
// Q1
double q1 = (c1 * dt + c2 * _detrender[2] - c2 * _detrender[4] - c1 * _detrender[6]) * adj;
_Q1_buffer.Add(q1, isNew);
// I1 = dt[3]
double i1 = _detrender[3];
_I1_buffer.Add(i1, isNew);
// Advance phases
// jI = CalculateHilbertTransform(_i1, adj)
double jI = (c1 * i1 + c2 * _I1_buffer[2] - c2 * _I1_buffer[4] - c1 * _I1_buffer[6]) * adj;
// jQ = CalculateHilbertTransform(_q1, adj)
double jQ = (c1 * q1 + c2 * _Q1_buffer[2] - c2 * _Q1_buffer[4] - c1 * _Q1_buffer[6]) * adj;
// Phasor addition
double i2_val = i1 - jQ;
double q2_val = q1 + jI;
// Smooth i2, q2
_i2 = 0.2 * i2_val + 0.8 * _p_i2;
_q2 = 0.2 * q2_val + 0.8 * _p_q2;
// Homodyne discriminator
double re_val = (_i2 * _p_i2) + (_q2 * _p_q2);
double im_val = (_i2 * _p_q2) - (_q2 * _p_i2);
// Smooth re, im
_re = 0.2 * re_val + 0.8 * _p_re;
_im = 0.2 * im_val + 0.8 * _p_im;
// Calculate Period
double period = (Math.Abs(_im) > double.Epsilon && Math.Abs(_re) > double.Epsilon)
? TWOPI / Math.Atan(_im / _re)
: 0.0;
// Adjust Period
period = period > 1.5 * _p_period ? 1.5 * _p_period : period;
period = period < 0.67 * _p_period ? 0.67 * _p_period : period;
period = period < 6.0 ? 6.0 : period;
period = period > 50.0 ? 50.0 : period;
// Smooth Period
_period = 0.2 * period + 0.8 * _p_period;
// Phase calculation
_phase = Math.Abs(i1) >= double.Epsilon ? Math.Atan(q1 / i1) * RadToDeg : 0.0;
// Adaptive alpha
double delta = Math.Max(_p_phase - _phase, 1.0);
double alpha = _fastLimit / delta;
alpha = Math.Clamp(alpha, _slowLimit, _fastLimit);
// Final indicators
_mama = alpha * _priceBuffer[0] + (1.0 - alpha) * _p_mama;
_fama = 0.5 * alpha * _mama + (1.0 - 0.5 * alpha) * _p_fama;
}
else
{
// Initialization phase
_sumPr += input.Value;
double avg = _index > 0 ? _sumPr / _index : input.Value;
_mama = avg;
_fama = avg;
// Initialize buffers with 0
_smoothBuffer.Add(0, isNew);
_detrender.Add(0, isNew);
_I1_buffer.Add(0, isNew);
_Q1_buffer.Add(0, isNew);
}
Last = new TValue(input.Time, _mama);
Fama = new TValue(input.Time, _fama);
Pub?.Invoke(Last);
return Last;
}
public TSeries Update(TSeries source)
{
if (source.Count == 0) return new TSeries();
int len = source.Count;
var v = new List<double>(len);
var t = new List<long>(len);
var temp = new Mama(_fastLimit, _slowLimit);
for (int i = 0; i < len; i++)
{
var item = source[i];
var result = temp.Update(item);
v.Add(result.Value);
t.Add(item.Time);
}
// Copy state from temp to this
_period = temp._period;
_p_period = temp._p_period;
_phase = temp._phase;
_p_phase = temp._p_phase;
_mama = temp._mama;
_p_mama = temp._p_mama;
_fama = temp._fama;
_p_fama = temp._p_fama;
_sumPr = temp._sumPr;
_p_sumPr = temp._p_sumPr;
_index = temp._index;
_i2 = temp._i2;
_p_i2 = temp._p_i2;
_q2 = temp._q2;
_p_q2 = temp._p_q2;
_re = temp._re;
_p_re = temp._p_re;
_im = temp._im;
_p_im = temp._p_im;
_lastValidPrice = temp._lastValidPrice;
_priceBuffer.CopyFrom(temp._priceBuffer);
_smoothBuffer.CopyFrom(temp._smoothBuffer);
_detrender.CopyFrom(temp._detrender);
_I1_buffer.CopyFrom(temp._I1_buffer);
_Q1_buffer.CopyFrom(temp._Q1_buffer);
Last = temp.Last;
Fama = temp.Fama;
return new TSeries(t, v);
}
public static void Calculate(ReadOnlySpan<double> source, Span<double> output, double fastLimit = 0.5, double slowLimit = 0.05)
{
var mama = new Mama(fastLimit, slowLimit);
for (int i = 0; i < source.Length; i++)
{
output[i] = mama.Update(new TValue(DateTime.MinValue, source[i])).Value;
}
}
public string Name { get; set; }
}