namespace QuanTAlib;
using System;

/* <summary>
MAMA: MESA Adaptive Moving Average
    Created by John Ehlers, the MAMA indicator is a 5-period adaptive moving average of
    high/low price that uses classic electrical radio-frequency signal processing algorithms
    to reduce noise.

    KAMAi = KAMAi - 1 + SC * ( price - KAMAi-1 )

Sources:
    https://mesasoftware.com/papers/MAMA.pdf
    https://www.tradingview.com/script/foQxLbU3-Ehlers-MESA-Adaptive-Moving-Average-LazyBear/

</summary> */



public class MAMA_Series : Single_TSeries_Indicator {
	public MAMA_Series(TSeries source, double fastlimit = 0.5, double slowlimit = 0.05, bool useNaN = false) : base(source, 5, useNaN) {
		fastl = fastlimit;
		slowl = slowlimit;
		Fama = new TSeries();
		if (_data.Count > 0) {
			base.Add(_data);
		}
	}

	private double sumPr, jI, jQ;
	private readonly double fastl, slowl;
	private (double i, double i1, double i2, double i3, double i4, double i5, double i6, double io) pr, i1, q1, sm, dt;
	private (double i, double i1, double io) i2, q2, re, im, pd, ph, mama, fama;
	public TSeries Fama { get; }

	public override void Add((DateTime t, double v) TValue, bool update) {
		if (!update) {
			// roll forward (oldx = x)
			pr.io = pr.i6;
			pr.i6 = pr.i5;
			pr.i5 = pr.i4;
			pr.i4 = pr.i3;
			pr.i3 = pr.i2;
			pr.i2 = pr.i1;
			pr.i1 = pr.i;
			i1.io = i1.i6;
			i1.i6 = i1.i5;
			i1.i5 = i1.i4;
			i1.i4 = i1.i3;
			i1.i3 = i1.i2;
			i1.i2 = i1.i1;
			i1.i1 = i1.i;
			q1.io = q1.i6;
			q1.i6 = q1.i5;
			q1.i5 = q1.i4;
			q1.i4 = q1.i3;
			q1.i3 = q1.i2;
			q1.i2 = q1.i1;
			q1.i1 = q1.i;
			dt.io = dt.i6;
			dt.i6 = dt.i5;
			dt.i5 = dt.i4;
			dt.i4 = dt.i3;
			dt.i3 = dt.i2;
			dt.i2 = dt.i1;
			dt.i1 = dt.i;
			sm.io = sm.i6;
			sm.i6 = sm.i5;
			sm.i5 = sm.i4;
			sm.i4 = sm.i3;
			sm.i3 = sm.i2;
			sm.i2 = sm.i1;
			sm.i1 = sm.i;
			i2.io = i2.i1;
			i2.i1 = i2.i;
			q2.io = q2.i1;
			q2.i1 = q2.i;
			re.io = re.i1;
			re.i1 = re.i;
			im.io = im.i1;
			im.i1 = im.i;
			pd.io = pd.i1;
			pd.i1 = pd.i;
			ph.io = ph.i1;
			ph.i1 = ph.i;
			mama.io = mama.i1;
			mama.i1 = mama.i;
			fama.io = fama.i1;
			fama.i1 = fama.i;
		}

		var i = Count;
		pr.i = TValue.v;
		if (i > 5) {
			var adj = 0.075 * pd.i1 + 0.54;

			// smooth and detrender
			sm.i = (4 * pr.i + 3 * pr.i1 + 2 * pr.i2 + pr.i3) / 10;
			dt.i = (0.0962 * sm.i + 0.5769 * sm.i2 - 0.5769 * sm.i4 - 0.0962 * sm.i6) * adj;

			// in-phase and quadrature
			q1.i = (0.0962 * dt.i + 0.5769 * dt.i2 - 0.5769 * dt.i4 - 0.0962 * dt.i6) * adj;
			i1.i = dt.i3;

			// advance the phases by 90 degrees
			jI = (0.0962 * i1.i + 0.5769 * i1.i2 - 0.5769 * i1.i4 - 0.0962 * i1.i6) * adj;
			jQ = (0.0962 * q1.i + 0.5769 * q1.i2 - 0.5769 * q1.i4 - 0.0962 * q1.i6) * adj;

			// phasor addition for 3-bar averaging
			i2.i = i1.i - jQ;
			q2.i = q1.i + jI;

			i2.i = 0.2 * i2.i + 0.8 * i2.i1; // smoothing it
			q2.i = 0.2 * q2.i + 0.8 * q2.i1;

			// homodyne discriminator
			re.i = i2.i * i2.i1 + q2.i * q2.i1;
			im.i = i2.i * q2.i1 - q2.i * i2.i1;

			re.i = 0.2 * re.i + 0.8 * re.i1; // smoothing it
			im.i = 0.2 * im.i + 0.8 * im.i1;

			// calculate period
			pd.i = im.i != 0 && re.i != 0 ? 6.283185307179586 / Math.Atan(im.i / re.i) : 0d;

			// adjust period to thresholds
			pd.i = pd.i > 1.5 * pd.i1 ? 1.5 * pd.i1 : pd.i;
			pd.i = pd.i < 0.67 * pd.i1 ? 0.67 * pd.i1 : pd.i;
			pd.i = pd.i < 6d ? 6d : pd.i;
			pd.i = pd.i > 50d ? 50d : pd.i;

			// smooth the period
			pd.i = 0.2 * pd.i + 0.8 * pd.i1;

			// determine phase position
			ph.i = i1.i != 0 ? Math.Atan(q1.i / i1.i) * 57.29577951308232 : 0;

			// change in phase
			var delta = Math.Max(ph.i1 - ph.i, 1d);

			// adaptive alpha value
			var alpha = Math.Max(fastl / delta, slowl);

			// final indicators
			mama.i = alpha * pr.i + (1d - alpha) * mama.i1;
			fama.i = 0.5d * alpha * mama.i + (1d - 0.5d * alpha) * fama.i1;
		}
		else {
			sumPr += pr.i;
			pd.i = sm.i = dt.i = i1.i = q1.i = i2.i = q2.i = re.i = im.i = ph.i = 0;
			mama.i = fama.i = sumPr / (i + 1);
		}

		base.Add((TValue.t, mama.i), update, _NaN);
		var result = (TValue.t, Count < _p - 1 && _NaN ? double.NaN : fama.i);
		Fama.Add(result, update);
	}
}