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Class optimization
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Miha
+99
-90
@@ -1,104 +1,113 @@
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using System;
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using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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namespace QuanTAlib
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/// <summary>
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/// ZLEMA: Zero Lag Exponential Moving Average
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/// A modified exponential moving average designed to reduce lag by incorporating
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/// error correction based on predicted values. It estimates and removes lag by
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/// extrapolating the trend using the difference between current and lagged prices.
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/// </summary>
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/// <remarks>
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/// The ZLEMA calculation process:
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/// 1. Calculates lag period as (period - 1) / 2
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/// 2. Gets error correction term: 2 * price - lag_price
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/// 3. Applies EMA to error-corrected price
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/// 4. Results in reduced lag compared to standard EMA
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///
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/// Key characteristics:
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/// - Significantly reduced lag compared to EMA
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/// - More responsive to price changes
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/// - Uses error correction mechanism
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/// - Maintains smoothness despite reduced lag
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/// - Better trend following capabilities
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///
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/// Sources:
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/// John Ehlers and Ric Way - "Zero Lag (Well, Almost)"
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/// Technical Analysis of Stocks and Commodities, 2010
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/// </remarks>
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public class Zlema : AbstractBase
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{
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/// <summary>
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/// ZLEMA: Zero Lag Exponential Moving Average
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/// A modified exponential moving average designed to reduce lag by incorporating
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/// error correction based on predicted values. It estimates and removes lag by
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/// extrapolating the trend using the difference between current and lagged prices.
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/// </summary>
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/// <remarks>
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/// The ZLEMA calculation process:
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/// 1. Calculates lag period as (period - 1) / 2
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/// 2. Gets error correction term: 2 * price - lag_price
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/// 3. Applies EMA to error-corrected price
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/// 4. Results in reduced lag compared to standard EMA
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///
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/// Key characteristics:
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/// - Significantly reduced lag compared to EMA
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/// - More responsive to price changes
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/// - Uses error correction mechanism
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/// - Maintains smoothness despite reduced lag
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/// - Better trend following capabilities
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///
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/// Sources:
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/// John Ehlers and Ric Way - "Zero Lag (Well, Almost)"
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/// Technical Analysis of Stocks and Commodities, 2010
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/// </remarks>
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private readonly CircularBuffer _buffer;
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private readonly int _lag;
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private readonly Ema _ema;
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private double _lastZLEMA, _p_lastZLEMA;
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public class Zlema : AbstractBase
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/// <param name="period">The number of periods used in the ZLEMA calculation.</param>
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/// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
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public Zlema(int period)
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{
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private readonly CircularBuffer _buffer;
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private readonly int _lag;
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private readonly Ema _ema;
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private double _lastZLEMA, _p_lastZLEMA;
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/// <param name="period">The number of periods used in the ZLEMA calculation.</param>
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/// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
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public Zlema(int period)
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if (period < 1)
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{
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if (period < 1)
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{
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throw new ArgumentException("Period must be greater than or equal to 1.", nameof(period));
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}
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WarmupPeriod = period;
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_lag = (int)(0.5 * (period - 1));
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_buffer = new CircularBuffer(_lag + 1);
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_ema = new Ema(period, useSma: false);
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Name = $"Zlema({period})";
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Init();
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throw new System.ArgumentException("Period must be greater than or equal to 1.", nameof(period));
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}
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WarmupPeriod = period;
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_lag = (int)(0.5 * (period - 1));
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_buffer = new CircularBuffer(_lag + 1);
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_ema = new Ema(period, useSma: false);
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Name = $"Zlema({period})";
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Init();
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}
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The number of periods used in the ZLEMA calculation.</param>
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public Zlema(object source, int period) : this(period)
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The number of periods used in the ZLEMA calculation.</param>
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public Zlema(object source, int period) : this(period)
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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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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public override void Init()
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{
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base.Init();
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_buffer.Clear();
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_ema.Init();
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_lastZLEMA = 0;
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_p_lastZLEMA = 0;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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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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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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_lastValidValue = Input.Value;
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_index++;
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_p_lastZLEMA = _lastZLEMA;
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}
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public override void Init()
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else
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{
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base.Init();
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_buffer.Clear();
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_ema.Init();
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_lastZLEMA = 0;
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_p_lastZLEMA = 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_lastZLEMA = _lastZLEMA;
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}
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else
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{
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_lastZLEMA = _p_lastZLEMA;
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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(Input.IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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// Get lagged value and calculate error correction
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double lagValue = _buffer[Math.Max(0, _buffer.Count - 1 - _lag)];
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double errorCorrection = 2 * Input.Value - lagValue;
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// Apply EMA to error-corrected value
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double zlema = _ema.Calc(new TValue(errorCorrection, Input.IsNew)).Value;
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_lastZLEMA = zlema;
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IsHot = _index >= WarmupPeriod;
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return zlema;
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_lastZLEMA = _p_lastZLEMA;
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}
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private double CalculateErrorCorrection()
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{
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double lagValue = _buffer[System.Math.Max(0, _buffer.Count - 1 - _lag)];
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return 2.0 * Input.Value - lagValue;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private double CalculateZlema(double errorCorrection)
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{
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var tempValue = new TValue(Input.Time, errorCorrection, Input.IsNew);
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return _ema.Calc(tempValue).Value;
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}
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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// Calculate error correction and apply EMA
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double errorCorrection = CalculateErrorCorrection();
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double zlema = CalculateZlema(errorCorrection);
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_lastZLEMA = zlema;
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IsHot = _index >= WarmupPeriod;
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return zlema;
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}
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}
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