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This commit is contained in:
Miha Kralj
2024-09-23 22:08:40 -07:00
parent 846429eccf
commit 58d72c06ca
244 changed files with 621 additions and 14397 deletions
Download Patch File Download Diff File Expand all files Collapse all files
archive/Calculations/Basics/ADD_Series.cs
-32
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@@ -1,32 +0,0 @@
namespace QuanTAlib;
using System;
/* <summary>
ADD - adding TSeries+TSeries together, or TSeries+double, or double+TSeries
Remarks:
Most of scaffolding is packaged in abstracty class Pair_TSeries_Indicator.
</summary> */
public class ADD_Series : Pair_TSeries_Indicator
{
public ADD_Series(TSeries d1, TSeries d2) : base(d1, d2)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
public ADD_Series(TSeries d1, double dd2) : base(d1, dd2)
{
if (base._d1.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], (base._d1[i].t, dd2), false); } }
}
public ADD_Series(double dd1, TSeries d2) : base(dd1, d2)
{
if (base._d2.Count > 0) { for (int i = 0; i < base._d2.Count; i++) { this.Add((base._d2[i].t, dd1), base._d2[i], false); } }
}
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
(System.DateTime t, double v) result = ((TValue1.t > TValue2.t) ? TValue1.t : TValue2.t, TValue1.v + TValue2.v);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
archive/Calculations/Basics/CORR_Series.cs
-52
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namespace QuanTAlib;
using System;
using System.Collections.Generic;
using System.Linq;
/* <summary>
CORR: Pearson's Correlation Coefficient
PCC is a measure of linear correlation between two sets of data.
It is the ratio between the covariance of two variables and the product of
their standard deviations; it is essentially a normalized measurement of
the covariance, such that the result always has a value between −1 and 1.
Sources:
https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
</summary> */
public class CORR_Series : Pair_TSeries_Indicator
{
public CORR_Series(TSeries d1, TSeries d2, int period, bool useNaN = false) : base(d1, d2, period, useNaN)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
private readonly System.Collections.Generic.List<double> _x = new();
private readonly System.Collections.Generic.List<double> _xx = new();
private readonly System.Collections.Generic.List<double> _y = new();
private readonly System.Collections.Generic.List<double> _yy = new();
private readonly System.Collections.Generic.List<double> _xy = new();
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
Add_Replace_Trim(_x, TValue1.v, _p, update);
Add_Replace_Trim(_xx, TValue1.v * TValue1.v, _p, update);
Add_Replace_Trim(_y, TValue2.v, _p, update);
Add_Replace_Trim(_yy, TValue2.v * TValue2.v, _p, update);
Add_Replace_Trim(_xy, TValue1.v * TValue2.v, _p, update);
double _sumx = _x.Sum();
double _sumxx = _xx.Sum();
double _sumy = _y.Sum();
double _sumyy = _yy.Sum();
double _sumxy = _xy.Sum();
double _covar = (_sumxx - _sumx * _sumx / _p) * (_sumyy - _sumy * _sumy / _p);
double _cor = (_covar != 0) ? (_sumxy - _sumx * _sumy / _p) / Math.Sqrt(_covar) : 0.0;
var result = (TValue1.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _cor);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
archive/Calculations/Basics/COVAR_Series.cs
-48
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@@ -1,48 +0,0 @@
namespace QuanTAlib;
using System;
using System.Collections.Generic;
using System.Linq;
/* <summary>
COVAR: Covariance
Covariance is defined as the expected value (or mean) of the product
of their deviations from their individual expected values.
Sources:
https://en.wikipedia.org/wiki/Covariance
</summary> */
public class COVAR_Series : Pair_TSeries_Indicator
{
public COVAR_Series(TSeries d1, TSeries d2, int period, bool useNaN = false) : base(d1, d2, period, useNaN)
{
if (base._d1.Count > 0 && base._d2.Count > 0)
{
for (int i = 0; i < base._d1.Count; i++)
{
this.Add(base._d1[i], base._d2[i], false);
}
}
}
private readonly System.Collections.Generic.List<double> _x = new();
private readonly System.Collections.Generic.List<double> _y = new();
private readonly System.Collections.Generic.List<double> _xy = new();
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
BufferTrim(_x, TValue1.v, _p, update);
BufferTrim(_y, TValue2.v, _p, update);
BufferTrim(_xy, TValue1.v * TValue2.v, _p, update);
double _avgx = _x.Average();
double _avgy = _y.Average();
double _avgxy = _xy.Average();
double _covar = _avgxy - (_avgx * _avgy);
var result = (TValue1.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _covar);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
archive/Calculations/Basics/DIV_Series.cs
-32
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@@ -1,32 +0,0 @@
namespace QuanTAlib;
using System;
/* <summary>
DIV - divide TSeries/TSeries , or TSeries/double, or double/TSeries
Remarks:
Most of scaffolding is packaged in abstracty class Pair_TSeries_Indicator.
</summary> */
public class DIV_Series : Pair_TSeries_Indicator
{
public DIV_Series(TSeries d1, TSeries d2) : base(d1, d2)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
public DIV_Series(TSeries d1, double dd2) : base(d1, dd2)
{
if (base._d1.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], (base._d1[i].t, dd2), false); } }
}
public DIV_Series(double dd1, TSeries d2) : base(dd1, d2)
{
if (base._d2.Count > 0) { for (int i = 0; i < base._d2.Count; i++) { this.Add((base._d2[i].t, dd1), base._d2[i], false); } }
}
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
(System.DateTime t, double v) result = ((TValue1.t > TValue2.t) ? TValue1.t : TValue2.t,
(TValue2.v is not 0) ? TValue1.v / TValue2.v : Double.PositiveInfinity);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
archive/Calculations/Basics/MUL_Series.cs
-30
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namespace QuanTAlib;
using System;
/* <summary>
MUL - multiply TSeries*TSeries together, or TSeries*double, or double*TSeries
</summary> */
public class MUL_Series : Pair_TSeries_Indicator
{
public MUL_Series(TSeries d1, TSeries d2) : base(d1, d2)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
public MUL_Series(TSeries d1, double dd2) : base(d1, dd2)
{
if (base._d1.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], (base._d1[i].t, dd2), false); } }
}
public MUL_Series(double dd1, TSeries d2) : base(dd1, d2)
{
if (base._d2.Count > 0) { for (int i = 0; i < base._d2.Count; i++) { this.Add((base._d2[i].t, dd1), base._d2[i], false); } }
}
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
(System.DateTime t, double v) result = ((TValue1.t > TValue2.t) ? TValue1.t : TValue2.t,
TValue1.v * TValue2.v);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}
archive/Calculations/Basics/SUB_Series.cs
-31
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namespace QuanTAlib;
using System;
/* <summary>
SUB - subtracting TSeries-TSeries, or TSeries-double, or double-TSeries
</summary> */
public class SUB_Series : Pair_TSeries_Indicator
{
public SUB_Series(TSeries d1, TSeries d2) : base(d1, d2)
{
if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
}
public SUB_Series(TSeries d1, double dd2) : base(d1, dd2)
{
if (base._d1.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], (base._d1[i].t, dd2), false); } }
}
public SUB_Series(double dd1, TSeries d2) : base(dd1, d2)
{
if (base._d2.Count > 0) { for (int i = 0; i < base._d2.Count; i++) { this.Add((base._d2[i].t, dd1), base._d2[i], false); } }
}
public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
{
(System.DateTime t, double v) result = ((TValue1.t > TValue2.t) ? TValue1.t : TValue2.t,
TValue1.v - TValue2.v);
if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
}
}