mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-06 21:17:44 +00:00
Miha Kralj
90 lines
3.5 KiB
C#
90 lines
3.5 KiB
C#
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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ENTROPY:
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Introduced by Claude Shannon in 1948, entropy measures the unpredictability
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of the data, or equivalently, of its average information.
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Calculation:
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P = close / Σ(close)
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ENTROPY = Σ(-P * Log(P) / Log(base))
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Sources:
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https://en.wikipedia.org/wiki/Entropy_(information_theory)
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https://math.stackexchange.com/questions/3428693/how-to-calculate-entropy-from-a-set-of-correlated-samples
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</summary> */
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public class ENTROPY_Series : TSeries {
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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 double _logbase;
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private readonly System.Collections.Generic.List<double> _buffer = new();
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private readonly System.Collections.Generic.List<double> _buff2 = new();
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//core constructors
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public ENTROPY_Series(int period, double logbase, bool useNaN) : base() {
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_period = period;
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_NaN = useNaN;
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_logbase = logbase;
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Name = $"ENTROPY({period})";
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}
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public ENTROPY_Series(TSeries source, int period, double logbase, bool useNaN) : this(period, logbase, 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 ENTROPY_Series() : this(period: 0, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(int period) : this(period: period, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(TBars source) : this(source.Close, period: 0, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(TBars source, int period) : this(source.Close, period, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(TBars source, int period, bool useNaN) : this(source.Close, period: period, logbase: 2.0, useNaN: useNaN) { }
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public ENTROPY_Series(TSeries source) : this(source, period: 0, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(TSeries source, int period) : this(source: source, period: period, logbase: 2.0, useNaN: false) { }
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public ENTROPY_Series(TSeries source, int period, bool useNaN) : this(source: source, period: period, logbase: 2.0, useNaN: useNaN) { }
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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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BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
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double _sum = _buffer.Sum();
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double _pp = this._buffer[^1] / _sum;
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double _ppp = -_pp * Math.Log(_pp) / Math.Log(this._logbase);
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BufferTrim(_buff2, _ppp, _period, update);
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double _entp = _buff2.Sum();
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var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _entp);
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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 new (DateTime t, double v) Add((DateTime t, double v) TValue) {
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return Add(TValue, false);
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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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_buff2.Clear();
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}
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} |