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https://github.com/mihakralj/QuanTAlib.git
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Add new data structures and event handling classes for trading platform. Include base classes, value and bar structs, event arguments, emitters, listeners. Update ruleset for SonarLint.
This commit is contained in:
Miha Kralj
@@ -1,95 +1,95 @@
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namespace QuanTAlib;
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using System;
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using System.Linq;
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/* <summary>
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ZLEMA: Zero Lag Exponential Moving Average
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The Zero lag exponential moving average (ZLEMA) indicator was created by John
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Ehlers and Ric Way.
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The formula for a given N-Day period and for a given Data series is:
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Lag = (Period-1)/2
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Ema Data = {Data+(Data-Data(Lag days ago))
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ZLEMA = EMA (EmaData,Period)
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Remark:
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The idea is do a regular exponential moving average (EMA) calculation but on a
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de-lagged data instead of doing it on the regular data. Data is de-lagged by
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removing the data from "lag" days ago thus removing (or attempting to remove)
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the cumulative lag effect of the moving average.
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</summary> */
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public class ZLEMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private int _len;
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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private readonly EMA_Series _ema;
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//core constructor
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public ZLEMA_Series(int period, bool useNaN, bool useSMA) {
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_period = period;
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_NaN = useNaN;
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Name = $"ZLEMA({period})";
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_len = 1;
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_ema = new(period);
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}
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//generic constructors (source)
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public ZLEMA_Series() : this(0, false, true) { }
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public ZLEMA_Series(int period) : this(period, false, true) { }
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public ZLEMA_Series(TBars source) : this(source.Close, 0, false) { }
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public ZLEMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public ZLEMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public ZLEMA_Series(TSeries source, int period) : this(source, period, false, true) { }
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public ZLEMA_Series(TSeries source, int period, bool useNaN) : this(source, period, useNaN, true) { }
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public ZLEMA_Series(TSeries source, int period, bool useNaN, bool useSMA) : this(period, useNaN, useSMA) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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int _lag;
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if (_period == 0) {
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_lag = (int)((_len - 1) * 0.5);
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_len++;
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}
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else { _lag = (int)((_period - 1) * 0.5); }
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_lag = Math.Min(_lag, _buffer.Count - 1);
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_lag = Math.Max(_lag, 0) + 1;
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double _zlValue = 2 * TValue.v - _buffer[^_lag];
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double _zlema = _ema.Add((TValue.t, _zlValue), update).v;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _zlema);
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return base.Add(res, update);
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}
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//variation of Add()
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buffer.Clear();
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_ema.Reset();
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}
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namespace QuanTAlib;
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using System;
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using System.Linq;
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/* <summary>
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ZLEMA: Zero Lag Exponential Moving Average
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The Zero lag exponential moving average (ZLEMA) indicator was created by John
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Ehlers and Ric Way.
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The formula for a given N-Day period and for a given Data series is:
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Lag = (Period-1)/2
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Ema Data = {Data+(Data-Data(Lag days ago))
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ZLEMA = EMA (EmaData,Period)
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Remark:
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The idea is do a regular exponential moving average (EMA) calculation but on a
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de-lagged data instead of doing it on the regular data. Data is de-lagged by
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removing the data from "lag" days ago thus removing (or attempting to remove)
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the cumulative lag effect of the moving average.
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</summary> */
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public class ZLEMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private int _len;
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protected readonly int _period;
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protected readonly bool _NaN;
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protected readonly TSeries _data;
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private readonly EMA_Series _ema;
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//core constructor
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public ZLEMA_Series(int period, bool useNaN, bool useSMA) {
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_period = period;
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_NaN = useNaN;
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Name = $"ZLEMA({period})";
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_len = 1;
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_ema = new(period);
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}
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//generic constructors (source)
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public ZLEMA_Series() : this(0, false, true) { }
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public ZLEMA_Series(int period) : this(period, false, true) { }
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public ZLEMA_Series(TBars source) : this(source.Close, 0, false) { }
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public ZLEMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public ZLEMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public ZLEMA_Series(TSeries source, int period) : this(source, period, false, true) { }
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public ZLEMA_Series(TSeries source, int period, bool useNaN) : this(source, period, useNaN, true) { }
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public ZLEMA_Series(TSeries source, int period, bool useNaN, bool useSMA) : this(period, useNaN, useSMA) {
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_data = source;
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Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
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_data.Pub += Sub;
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Add(_data);
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}
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// core Add() algo
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public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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int _lag;
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if (_period == 0) {
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_lag = (int)((_len - 1) * 0.5);
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_len++;
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}
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else { _lag = (int)((_period - 1) * 0.5); }
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_lag = Math.Min(_lag, _buffer.Count - 1);
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_lag = Math.Max(_lag, 0) + 1;
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double _zlValue = 2 * TValue.v - _buffer[^_lag];
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double _zlema = _ema.Add((TValue.t, _zlValue), update).v;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _zlema);
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return base.Add(res, update);
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}
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//variation of Add()
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public override (DateTime t, double v) Add(TSeries data) {
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if (data == null) { return (DateTime.Today, Double.NaN); }
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foreach (var item in data) { Add(item, false); }
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return _data.Last;
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}
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public (DateTime t, double v) Add(bool update) {
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return this.Add(TValue: _data.Last, update: update);
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}
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public (DateTime t, double v) Add() {
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return Add(TValue: _data.Last, update: false);
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}
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private new void Sub(object source, TSeriesEventArgs e) {
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Add(TValue: _data.Last, update: e.update);
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}
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//reset calculation
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public override void Reset() {
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_buffer.Clear();
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_ema.Reset();
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}
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}
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