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Update main automation workflow to use wildcard for dotcover report path

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Miha Kralj
2023-05-04 08:40:37 -07:00
parent 5e7ba2427e
commit 56f8db2949
89 changed files with 1721 additions and 1356 deletions
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Calculations/Basics/CORR_Series.cs
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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); }
}
}
Calculations/Basics/COVAR_Series.cs
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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); }
}
}
Calculations/Basics/MIDPRICE_Series.cs
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namespace QuanTAlib;
using System;
using System.Linq;
/* <summary>
MIDPRICE: Midpoint price (highhest high + lowest low)/2 in the given period in the series.
If period = 0 => period = full length of the series
</summary> */
public class MIDPRICE_Series : Single_TBars_Indicator
{
public MIDPRICE_Series(TBars source, int period, bool useNaN = false) : base(source, period, useNaN)
{
if (base._bars.Count > 0)
{ base.Add(base._bars); }
}
private readonly System.Collections.Generic.List<double> _bufferhi = new();
private readonly System.Collections.Generic.List<double> _bufferlo = new();
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
{
Add_Replace_Trim(_bufferhi, TBar.h, _p, update);
Add_Replace_Trim(_bufferlo, TBar.l, _p, update);
double _max = _bufferhi.Max();
double _min = _bufferlo.Min();
double _mid = (_max + _min) * 0.5;
base.Add((TBar.t, _mid), update, _NaN);
}
}
Calculations/Basics/TR_Series.cs
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namespace QuanTAlib;
using System;
/* <summary>
TR: True Range
True Range was introduced by J. Welles Wilder in his book New Concepts in Technical Trading Systems.
It measures the daily range plus any gap from the closing price of the preceding day.
Calculation:
d1 = ABS(High - Low)
d2 = ABS(High - Previous close)
d3 = ABS(Previous close - Low)
TR = MAX(d1,d2,d3)
Sources:
https://www.macroption.com/true-range/
</summary> */
public class TR_Series : Single_TBars_Indicator
{
private double _cm1, _cm1_o;
public TR_Series(TBars source, bool useNaN = false) : base(source, period:0, useNaN:useNaN) {
_cm1 =_cm1_o = double.NaN;
if (this._bars.Count > 0) { base.Add(this._bars); }
}
public override void Add((DateTime t, double o, double h, double l, double c, double v) TBar, bool update)
{
if (update) {_cm1 = _cm1_o; } else { _cm1_o = _cm1; }
if (_cm1 is double.NaN) { _cm1 = TBar.c; } //first bar
double d1 = Math.Abs(TBar.h - TBar.l);
double d2 = Math.Abs(_cm1 - TBar.h);
double d3 = Math.Abs(_cm1 - TBar.l);
var ret = (TBar.t, (base.Count==0 && base._NaN) ? double.NaN : Math.Max(d1,Math.Max(d2,d3)) );
base.Add(ret, update);
_cm1 = TBar.c;
}
}