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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
@@ -1,94 +1,94 @@
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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.Threading.Tasks;
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using System.Numerics;
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using System.Linq;
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/* <summary>
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FWMA: Fibonacci's Weighted Moving Average is similar to a Weighted Moving Average
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(WMA) where the weights are based on the Fibonacci Sequence.
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</summary> */
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public class FWMA_Series : TSeries {
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private readonly List<double> _buffer = new();
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private List<double> _weights;
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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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protected int _len;
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public FWMA_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"FWMA({period})";
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_len = 0;
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_weights = CalculateWeights(_period);
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}
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public FWMA_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 FWMA_Series() : this(period: 0, useNaN: false) { }
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public FWMA_Series(int period) : this(period: period, useNaN: false) { }
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public FWMA_Series(TBars source) : this(source.Close, 0, false) { }
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public FWMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public FWMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public FWMA_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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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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if (_period == 0) {
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_len++;
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_weights = CalculateWeights(_len);
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}
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double _fwma = 0;
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double totalWeights = _weights.Sum();
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object lockObj = new object();
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Parallel.For(0, _buffer.Count, i =>
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{
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double temp = _buffer[i] * _weights[i];
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lock (lockObj) { _fwma += temp; }
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});
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_fwma /= totalWeights;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _fwma);
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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() {
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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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private static List<double> CalculateWeights(int period) {
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//to prevent overflow, max period can be no more than 1476
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period = (period > 1476) ? 1476 : period;
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List<double> weights = new List<double>(period);
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BigInteger a = 0;
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BigInteger b = 1;
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for (int i = 0; i < period; i++) {
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BigInteger temp = a;
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a = b;
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b = temp + b;
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weights.Add((double)Decimal.Parse(a.ToString()));
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}
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return weights;
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}
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public override void Reset() {
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_weights = CalculateWeights(_period);
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_buffer.Clear();
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}
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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.Threading.Tasks;
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using System.Numerics;
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using System.Linq;
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/* <summary>
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FWMA: Fibonacci's Weighted Moving Average is similar to a Weighted Moving Average
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(WMA) where the weights are based on the Fibonacci Sequence.
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</summary> */
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public class FWMA_Series : TSeries {
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private readonly List<double> _buffer = new();
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private List<double> _weights;
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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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protected int _len;
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public FWMA_Series(int period, bool useNaN) {
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_period = period;
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_NaN = useNaN;
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Name = $"FWMA({period})";
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_len = 0;
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_weights = CalculateWeights(_period);
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}
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public FWMA_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 FWMA_Series() : this(period: 0, useNaN: false) { }
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public FWMA_Series(int period) : this(period: period, useNaN: false) { }
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public FWMA_Series(TBars source) : this(source.Close, 0, false) { }
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public FWMA_Series(TBars source, int period) : this(source.Close, period, false) { }
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public FWMA_Series(TBars source, int period, bool useNaN) : this(source.Close, period, useNaN) { }
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public FWMA_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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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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if (_period == 0) {
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_len++;
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_weights = CalculateWeights(_len);
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}
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double _fwma = 0;
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double totalWeights = _weights.Sum();
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object lockObj = new object();
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Parallel.For(0, _buffer.Count, i =>
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{
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double temp = _buffer[i] * _weights[i];
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lock (lockObj) { _fwma += temp; }
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});
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_fwma /= totalWeights;
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _fwma);
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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() {
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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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private static List<double> CalculateWeights(int period) {
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//to prevent overflow, max period can be no more than 1476
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period = (period > 1476) ? 1476 : period;
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List<double> weights = new List<double>(period);
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BigInteger a = 0;
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BigInteger b = 1;
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for (int i = 0; i < period; i++) {
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BigInteger temp = a;
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a = b;
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b = temp + b;
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weights.Add((double)Decimal.Parse(a.ToString()));
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}
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return weights;
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}
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public override void Reset() {
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_weights = CalculateWeights(_period);
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_buffer.Clear();
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}
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}
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