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, _lastema_o;
	private int _llag;

	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._lastema_o = double.NaN;
		_llag = (int)((_p-1) * 0.5);
		if (_data.Count > 0) { base.Add(_data); }
	}

	public override void Add((System.DateTime t, double v) TValue, bool update)
	{
		int _lag = Math.Max(this.Count-_llag, 0);
		if (update) {
			_lastema = _lastema_o; _lag--;
		} else {
			_lastema_o = _lastema;
		}
        double _zl = TValue.v + (TValue.v - _data[_lag].v);
		double _ema = 0;

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

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