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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
@@ -1,96 +1,96 @@
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namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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/* <summary>
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SMA: Simple Moving Average
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The weights are equally distributed across the period, resulting in a mean() of
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the data within the period
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Sources:
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https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/simple-moving-average-sma/
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https://stats.stackexchange.com/a/24739
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Remark:
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This calc doesn't use LINQ or SUM() or any of (slow) iterative methods. It is not as fast as TA-LIB
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implementation, but it does allow incremental additions of inputs and real-time calculations of SMA()
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</summary> */
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public class SMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private double _sum, _oldsum;
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private readonly int _period;
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private readonly TSeries _data;
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protected readonly bool _NaN;
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//core constructor
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public SMA_Series(int period, bool useNaN) {
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_period = Math.Max(0, period);
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_NaN = useNaN;
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Name = $"SMA({period})";
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_sum = _oldsum = 0;
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}
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public SMA_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 SMA_Series() : this(0, false) {}
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public SMA_Series(int period) : this(period, false) {}
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public SMA_Series(TBars source) : this(source.Close, 0, false) {}
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public SMA_Series(TBars source, int period) : this(source.Close, period, false) {}
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public SMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) {}
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public SMA_Series(TSeries source) : this(source, 0, false) {}
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public SMA_Series(TSeries source, int period) : this(source, period, 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)) { return (TValue.t, double.NaN);
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} else {
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if (update && _buffer.Count > 0) {
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_sum -= _buffer[^1];
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_buffer[^1] = TValue.v;
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_oldsum = _sum;
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}
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else {
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_buffer.Add(TValue.v);
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_oldsum = _sum;
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}
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_sum += TValue.v;
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if (_period != 0 && _buffer.Count > _period) {
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_sum -= _buffer[0];
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_buffer.RemoveAt(0);
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}
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}
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double _div = _period == 0 ? _buffer.Count : Math.Min(_buffer.Count, _period);
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var _sma = _sum / _div;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _sma);
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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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_sum = _oldsum = 0;
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_buffer.Clear();
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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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/* <summary>
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SMA: Simple Moving Average
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The weights are equally distributed across the period, resulting in a mean() of
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the data within the period
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Sources:
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https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/simple-moving-average-sma/
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https://stats.stackexchange.com/a/24739
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Remark:
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This calc doesn't use LINQ or SUM() or any of (slow) iterative methods. It is not as fast as TA-LIB
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implementation, but it does allow incremental additions of inputs and real-time calculations of SMA()
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</summary> */
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public class SMA_Series : TSeries {
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private double _sum, _oldsum;
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private readonly int _period;
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private readonly TSeries _data;
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protected readonly bool _NaN;
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//core constructor
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public SMA_Series(int period, bool useNaN) {
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_period = Math.Max(0, period);
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_NaN = useNaN;
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Name = $"SMA({period})";
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_sum = _oldsum = 0;
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}
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public SMA_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 SMA_Series() : this(0, false) {}
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public SMA_Series(int period) : this(period, false) {}
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public SMA_Series(TBars source) : this(source.Close, 0, false) {}
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public SMA_Series(TBars source, int period) : this(source.Close, period, false) {}
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public SMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) {}
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public SMA_Series(TSeries source) : this(source, 0, false) {}
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public SMA_Series(TSeries source, int period) : this(source, period, 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)) { return (TValue.t, double.NaN);
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} else {
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if (update && _buffer.Count > 0) {
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_sum -= _buffer[^1];
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_buffer[^1] = TValue.v;
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_oldsum = _sum;
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}
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else {
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_buffer.Add(TValue.v);
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_oldsum = _sum;
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}
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_sum += TValue.v;
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if (_period != 0 && _buffer.Count > _period) {
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_sum -= _buffer[0];
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_buffer.RemoveAt(0);
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}
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}
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double _div = _period == 0 ? _buffer.Count : Math.Min(_buffer.Count, _period);
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var _sma = _sum / _div;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _sma);
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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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_sum = _oldsum = 0;
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_buffer.Clear();
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}
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}
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