mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-25 22:08:05 +00:00
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
@@ -1,87 +1,87 @@
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
|
||||
/* <summary>
|
||||
ENTROPY:
|
||||
Introduced by Claude Shannon in 1948, entropy measures the unpredictability
|
||||
of the data, or equivalently, of its average information.
|
||||
|
||||
Calculation:
|
||||
P = close / Σ(close)
|
||||
ENTROPY = Σ(-P * Log(P) / Log(base))
|
||||
|
||||
Sources:
|
||||
https://en.wikipedia.org/wiki/Entropy_(information_theory)
|
||||
https://math.stackexchange.com/questions/3428693/how-to-calculate-entropy-from-a-set-of-correlated-samples
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ENTROPY_Series : TSeries {
|
||||
protected readonly int _period;
|
||||
protected readonly bool _NaN;
|
||||
protected readonly TSeries _data;
|
||||
private readonly double _logbase;
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly System.Collections.Generic.List<double> _buff2 = new();
|
||||
|
||||
//core constructors
|
||||
public ENTROPY_Series(int period, double logbase, bool useNaN) {
|
||||
_period = period;
|
||||
_NaN = useNaN;
|
||||
_logbase = logbase;
|
||||
Name = $"ENTROPY({period})";
|
||||
}
|
||||
public ENTROPY_Series(TSeries source, int period, double logbase, bool useNaN) : this(period, logbase, useNaN) {
|
||||
_data = source;
|
||||
Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
|
||||
_data.Pub += Sub;
|
||||
Add(_data);
|
||||
}
|
||||
public ENTROPY_Series() : this(period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(int period) : this(period: period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source) : this(source.Close, period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source, int period) : this(source.Close, period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source, int period, bool useNaN) : this(source.Close, period: period, logbase: 2.0, useNaN: useNaN) { }
|
||||
public ENTROPY_Series(TSeries source) : this(source, period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TSeries source, int period) : this(source: source, period: period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TSeries source, int period, bool useNaN) : this(source: source, period: period, logbase: 2.0, useNaN: useNaN) { }
|
||||
|
||||
//////////////////
|
||||
// core Add() algo
|
||||
public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
|
||||
if (double.IsNaN(TValue.v)) {
|
||||
return base.Add((TValue.t, Double.NaN), update);
|
||||
}
|
||||
BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
|
||||
double _sum = _buffer.Sum();
|
||||
double _pp = this._buffer[^1] / _sum;
|
||||
double _ppp = -_pp * Math.Log(_pp) / Math.Log(this._logbase);
|
||||
BufferTrim(_buff2, _ppp, _period, update);
|
||||
double _entp = _buff2.Sum();
|
||||
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _entp);
|
||||
return base.Add(res, update);
|
||||
}
|
||||
|
||||
public override (DateTime t, double v) Add(TSeries data) {
|
||||
if (data == null) { return (DateTime.Today, Double.NaN); }
|
||||
foreach (var item in data) { Add(item, false); }
|
||||
return _data.Last;
|
||||
}
|
||||
public (DateTime t, double v) Add(bool update) {
|
||||
return this.Add(TValue: _data.Last, update: update);
|
||||
}
|
||||
public (DateTime t, double v) Add() {
|
||||
return Add(TValue: _data.Last, update: false);
|
||||
}
|
||||
private new void Sub(object source, TSeriesEventArgs e) {
|
||||
Add(TValue: _data.Last, update: e.update);
|
||||
}
|
||||
|
||||
//reset calculation
|
||||
public override void Reset() {
|
||||
_buffer.Clear();
|
||||
_buff2.Clear();
|
||||
}
|
||||
namespace QuanTAlib;
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
|
||||
/* <summary>
|
||||
ENTROPY:
|
||||
Introduced by Claude Shannon in 1948, entropy measures the unpredictability
|
||||
of the data, or equivalently, of its average information.
|
||||
|
||||
Calculation:
|
||||
P = close / Σ(close)
|
||||
ENTROPY = Σ(-P * Log(P) / Log(base))
|
||||
|
||||
Sources:
|
||||
https://en.wikipedia.org/wiki/Entropy_(information_theory)
|
||||
https://math.stackexchange.com/questions/3428693/how-to-calculate-entropy-from-a-set-of-correlated-samples
|
||||
|
||||
</summary> */
|
||||
|
||||
public class ENTROPY_Series : TSeries {
|
||||
protected readonly int _period;
|
||||
protected readonly bool _NaN;
|
||||
protected readonly TSeries _data;
|
||||
private readonly double _logbase;
|
||||
private readonly System.Collections.Generic.List<double> _buffer = new();
|
||||
private readonly System.Collections.Generic.List<double> _buff2 = new();
|
||||
|
||||
//core constructors
|
||||
public ENTROPY_Series(int period, double logbase, bool useNaN) {
|
||||
_period = period;
|
||||
_NaN = useNaN;
|
||||
_logbase = logbase;
|
||||
Name = $"ENTROPY({period})";
|
||||
}
|
||||
public ENTROPY_Series(TSeries source, int period, double logbase, bool useNaN) : this(period, logbase, useNaN) {
|
||||
_data = source;
|
||||
Name = Name.Substring(0, Name.IndexOf(")")) + $", {(string.IsNullOrEmpty(_data.Name) ? "data" : _data.Name)})";
|
||||
_data.Pub += Sub;
|
||||
Add(_data);
|
||||
}
|
||||
public ENTROPY_Series() : this(period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(int period) : this(period: period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source) : this(source.Close, period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source, int period) : this(source.Close, period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TBars source, int period, bool useNaN) : this(source.Close, period: period, logbase: 2.0, useNaN: useNaN) { }
|
||||
public ENTROPY_Series(TSeries source) : this(source, period: 0, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TSeries source, int period) : this(source: source, period: period, logbase: 2.0, useNaN: false) { }
|
||||
public ENTROPY_Series(TSeries source, int period, bool useNaN) : this(source: source, period: period, logbase: 2.0, useNaN: useNaN) { }
|
||||
|
||||
//////////////////
|
||||
// core Add() algo
|
||||
public override (DateTime t, double v) Add((DateTime t, double v) TValue, bool update = false) {
|
||||
if (double.IsNaN(TValue.v)) {
|
||||
return base.Add((TValue.t, Double.NaN), update);
|
||||
}
|
||||
BufferTrim(buffer: _buffer, value: TValue.v, period: _period, update: update);
|
||||
double _sum = _buffer.Sum();
|
||||
double _pp = this._buffer[^1] / _sum;
|
||||
double _ppp = -_pp * Math.Log(_pp) / Math.Log(this._logbase);
|
||||
BufferTrim(_buff2, _ppp, _period, update);
|
||||
double _entp = _buff2.Sum();
|
||||
var res = (TValue.t, Count < _period - 1 && _NaN ? double.NaN : _entp);
|
||||
return base.Add(res, update);
|
||||
}
|
||||
|
||||
public override (DateTime t, double v) Add(TSeries data) {
|
||||
if (data == null) { return (DateTime.Today, Double.NaN); }
|
||||
foreach (var item in data) { Add(item, false); }
|
||||
return _data.Last;
|
||||
}
|
||||
public (DateTime t, double v) Add(bool update) {
|
||||
return this.Add(TValue: _data.Last, update: update);
|
||||
}
|
||||
public (DateTime t, double v) Add() {
|
||||
return Add(TValue: _data.Last, update: false);
|
||||
}
|
||||
private new void Sub(object source, TSeriesEventArgs e) {
|
||||
Add(TValue: _data.Last, update: e.update);
|
||||
}
|
||||
|
||||
//reset calculation
|
||||
public override void Reset() {
|
||||
_buffer.Clear();
|
||||
_buff2.Clear();
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user