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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
@@ -1,93 +1,93 @@
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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/* <summary>
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SMMA: Smoothed Moving Average
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The Smoothed Moving Average (SMMA) is a combination of a SMA and an EMA. It gives the recent prices
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an equal weighting as the historic prices as it takes all available price data into account.
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The main advantage of a smoothed moving average is that it removes short-term fluctuations.
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SMMA(i) = (SMMA-1*(N-1) + CLOSE (i)) / N
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Sources:
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https://blog.earn2trade.com/smoothed-moving-average
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https://guide.traderevolution.com/traderevolution/mobile-applications/phone/android/technical-indicators/moving-averages/smma-smoothed-moving-average
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https://www.chartmill.com/documentation/technical-analysis-indicators/217-MOVING-AVERAGES-%7C-The-Smoothed-Moving-Average-%28SMMA%29
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</summary> */
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public class SMMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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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 double _lastsmma, _lastlastsmma;
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//core constructors
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public SMMA_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"SMMA({period})";
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}
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public SMMA_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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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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public SMMA_Series() : this(period: 0, useNaN: false) { }
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public SMMA_Series(int period) : this(period: period, useNaN: false) { }
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public SMMA_Series(TBars source) : this(source.Close, 0, false) { }
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public SMMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public SMMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public SMMA_Series(TSeries source) : this(source, 0, false) { }
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public SMMA_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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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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if (double.IsNaN(TValue.v)) {
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return base.Add((TValue.t, double.NaN),update);
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}
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double _smma = 0;
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if (update) { this._lastsmma = this._lastlastsmma; }
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if (this.Count < this._period) {
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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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_smma = _buffer.Average();
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}
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else {
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_smma = ((_lastsmma * (_period - 1)) + TValue.v) / _period;
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}
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this._lastlastsmma = this._lastsmma;
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this._lastsmma = _smma;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _smma);
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return base.Add(res, update);
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}
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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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this._lastsmma = this._lastlastsmma = 0;
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}
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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/* <summary>
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SMMA: Smoothed Moving Average
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The Smoothed Moving Average (SMMA) is a combination of a SMA and an EMA. It gives the recent prices
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an equal weighting as the historic prices as it takes all available price data into account.
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The main advantage of a smoothed moving average is that it removes short-term fluctuations.
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SMMA(i) = (SMMA-1*(N-1) + CLOSE (i)) / N
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Sources:
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https://blog.earn2trade.com/smoothed-moving-average
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https://guide.traderevolution.com/traderevolution/mobile-applications/phone/android/technical-indicators/moving-averages/smma-smoothed-moving-average
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https://www.chartmill.com/documentation/technical-analysis-indicators/217-MOVING-AVERAGES-%7C-The-Smoothed-Moving-Average-%28SMMA%29
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</summary> */
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public class SMMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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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 double _lastsmma, _lastlastsmma;
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//core constructors
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public SMMA_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"SMMA({period})";
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}
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public SMMA_Series(TSeries source, int period, bool useNaN) : this(period, useNaN) {
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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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public SMMA_Series() : this(period: 0, useNaN: false) { }
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public SMMA_Series(int period) : this(period: period, useNaN: false) { }
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public SMMA_Series(TBars source) : this(source.Close, 0, false) { }
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public SMMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public SMMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public SMMA_Series(TSeries source) : this(source, 0, false) { }
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public SMMA_Series(TSeries source, int period) : this(source: source, period: period, useNaN: false) { }
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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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if (double.IsNaN(TValue.v)) {
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return base.Add((TValue.t, double.NaN),update);
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}
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double _smma = 0;
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if (update) { this._lastsmma = this._lastlastsmma; }
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if (this.Count < this._period) {
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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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_smma = _buffer.Average();
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}
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else {
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_smma = ((_lastsmma * (_period - 1)) + TValue.v) / _period;
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}
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this._lastlastsmma = this._lastsmma;
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this._lastsmma = _smma;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _smma);
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return base.Add(res, update);
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}
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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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this._lastsmma = this._lastlastsmma = 0;
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}
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}
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