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SUM, MIDPOINT, MIDPRICE

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Miha Kralj
2022-11-14 09:52:40 -08:00
parent ddfcb6bd99
commit ee11595ffa
7 changed files with 372 additions and 166 deletions
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Source/Basics/MIDPOINT_Series.cs
+44
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namespace QuanTAlib;
using System;
/* <summary>
MIDPOINT: Midpoint value (max+min)/2 in the given period in the series.
If period = 0 => period = full length of the series
Sources:
https://thefaqblog.com/what-is-the-midpoint-in-statistics/
</summary> */
public class MIDPOINT_Series : Single_TSeries_Indicator
{
public MIDPOINT_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
if (base._data.Count > 0)
{ base.Add(base._data); }
}
private readonly System.Collections.Generic.List<double> _buffer = new();
public override void Add((DateTime t, double v) TValue, bool update)
{
if (update)
{ this._buffer[this._buffer.Count - 1] = TValue.v; }
else
{ this._buffer.Add(TValue.v); }
if (this._buffer.Count > this._p && this._p != 0)
{ this._buffer.RemoveAt(0); }
double _max = TValue.v;
double _min = TValue.v;
for (int i = 0; i < this._buffer.Count; i++)
{
_max = Math.Max(this._buffer[i], _max);
_min = Math.Min(this._buffer[i], _min);
}
double _mid = (_max + _min) * 0.5;
var result = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _mid);
base.Add(result, update);
}
}
Source/Basics/MIDPRICE_Series.cs
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namespace QuanTAlib;
using System;
/* <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)
{
if (update)
{
this._bufferhi[this._bufferhi.Count - 1] = TBar.h;
this._bufferlo[this._bufferlo.Count - 1] = TBar.l;
}
else
{
this._bufferhi.Add(TBar.h);
this._bufferlo.Add(TBar.l);
}
if (this._bufferhi.Count > this._p && this._p != 0)
{ this._bufferhi.RemoveAt(0); }
if (this._bufferlo.Count > this._p && this._p != 0)
{ this._bufferlo.RemoveAt(0); }
double _max = TBar.h;
double _min = TBar.l;
for (int i = 0; i < this._bufferhi.Count; i++)
{
_max = Math.Max(this._bufferhi[i], _max);
_min = Math.Min(this._bufferlo[i], _min);
}
double _mid = (_max + _min) * 0.5;
var result = (TBar.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _mid);
base.Add(result, update);
}
}
Source/Basics/SUM_Series.cs
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namespace QuanTAlib;
using System;
/* <summary>
SUM: Cumulative Sum (aka Running Total)
SUM across a period provides a rolling sum of all values across the period.
If SUM values would be divided with period, the output would be SMA()
Sources:
https://en.wikipedia.org/wiki/CUSUM
</summary> */
public class SUM_Series : Single_TSeries_Indicator
{
public SUM_Series(TSeries source, int period, bool useNaN = false) : base(source, period, useNaN)
{
if (base._data.Count > 0) { base.Add(base._data); }
}
private readonly System.Collections.Generic.List<double> _buffer = new();
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { _buffer[_buffer.Count - 1] = TValue.v; }
else { _buffer.Add(TValue.v); }
if (_buffer.Count > this._p && this._p != 0) { _buffer.RemoveAt(0); }
double _sum = 0;
for (int i = 0; i < _buffer.Count; i++) { _sum += _buffer[i]; }
var result = (TValue.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _sum);
base.Add(result, update);
}
}
Source/Trends/ALMA_Series.cs
+47 -45
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@@ -14,52 +14,54 @@ Sources:
https://phemex.com/academy/what-is-arnaud-legoux-moving-averages
https://www.prorealcode.com/prorealtime-indicators/alma-arnaud-legoux-moving-average/
TODO: Discrepancy with Pandas-TA (but passes the validation with Skender.GetAlma)
</summary> */
public class ALMA_Series : Single_TSeries_Indicator
{
private readonly System.Collections.Generic.List<double> _buffer = new();
private readonly double[] _weight;
private double _norm;
private readonly double _offset, _sigma;
public ALMA_Series(TSeries source, int period, double offset = 0.85, double sigma = 6.0, bool useNaN = false)
: base(source, period, useNaN)
{
_offset = offset;
_sigma = sigma;
_weight = new double[period];
if (this._data.Count > 0) { base.Add(this._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
else { this._buffer.Add(TValue.v); }
if (this._buffer.Count > this._p) { this._buffer.RemoveAt(0); }
if (this._buffer.Count <= _p) { calc_weights(); }
double _weightedSum = 0;
for (int i = 0; i < this._buffer.Count; i++) { _weightedSum += _weight[i] * _buffer[i]; }
double _alma = _weightedSum / _norm;
var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _alma);
base.Add(ret, update);
}
private void calc_weights()
{
int _len = this._buffer.Count;
_norm = 0;
double _m = _offset * (_len - 1);
double _s = _len / _sigma;
for (int i = 0; i < _len; i++)
{
double _wt = Math.Exp(-((i - _m) * (i - _m)) / (2 * _s * _s));
_weight[i] = _wt;
_norm += _wt;
}
}
{
private readonly System.Collections.Generic.List<double> _buffer = new();
private readonly double[] _weight;
private double _norm;
private readonly double _offset, _sigma;
public ALMA_Series(TSeries source, int period, double offset = 0.85, double sigma = 6.0, bool useNaN = false)
: base(source, period, useNaN)
{
_offset = offset;
_sigma = sigma;
_weight = new double[period];
if (this._data.Count > 0) { base.Add(this._data); }
}
public override void Add((System.DateTime t, double v) TValue, bool update)
{
if (update) { this._buffer[this._buffer.Count - 1] = TValue.v; }
else { this._buffer.Add(TValue.v); }
if (this._buffer.Count > this._p) { this._buffer.RemoveAt(0); }
if (this._buffer.Count <= _p) { calc_weights(); }
double _weightedSum = 0;
for (int i = 0; i < this._buffer.Count; i++) { _weightedSum += _weight[i] * _buffer[i]; }
double _alma = _weightedSum / _norm;
var ret = (TValue.t, this.Count < this._p - 1 && this._NaN ? double.NaN : _alma);
base.Add(ret, update);
}
private void calc_weights()
{
int _len = this._buffer.Count;
_norm = 0;
double _m = _offset * (_len - 1);
double _s = _len / _sigma;
for (int i = 0; i < _len; i++)
{
double _wt = Math.Exp(-((i - _m) * (i - _m)) / (2 * _s * _s));
_weight[i] = _wt;
_norm += _wt;
}
}
}