QuanTAlib/Source/Trends/ZLEMA_Series.cs

namespace QuanTAlib;
using System;
using System.Linq;

/* <summary>
ZLEMA: Zero Lag Exponential Moving Average
    The Zero lag exponential moving average (ZLEMA) indicator was created by John
    Ehlers and Ric Way.

The formula for a given N-Day period and for a given Data series is:
    Lag = (Period-1)/2
    Ema Data = {Data+(Data-Data(Lag days ago))
    ZLEMA = EMA (EmaData,Period)

Remark:
    The idea is do a regular exponential moving average (EMA) calculation but on a
    de-lagged data instead of doing it on the regular data. Data is de-lagged by
    removing the data from "lag" days ago thus removing (or attempting to remove)
    the cumulative lag effect of the moving average.

</summary> */

public class ZLEMA_Series : Single_TSeries_Indicator
{
	private readonly System.Collections.Generic.List<double> _buffer = new();
	private readonly double _k, _k1m;
	private double _lastema, _lastlastema;

	public ZLEMA_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
	{
		this._k = 2.0 / (this._p + 1);
		this._k1m = 1.0 - this._k;
		this._lastema = this._lastlastema = double.NaN;
		if (base._data.Count > 0)
		{ base.Add(base._data); }
	}

	public override void Add((System.DateTime t, double v) TValue, bool update)
	{
		int _lag = (int)((_p-1) * 0.5);
        _lag = (this.Count-_lag < 0) ? 0 : this.Count-_lag;
        double _zl = TValue.v + (TValue.v - _data[_lag].v);

		double _ema = 0;
		if (update)
		{ this._lastema = this._lastlastema; }
		if (this.Count < this._p)
		{
            Add_Replace_Trim(_buffer, _zl, _p, update);
			_ema = _buffer.Average();
		}
		else
		{
			_ema = (_zl * this._k) + (this._lastema * this._k1m);
		}

		this._lastlastema = this._lastema;
		this._lastema = _ema;

        base.Add((TValue.t, _ema), update, _NaN);
        }
}