gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-19 02:58:05 +00:00
Code Issues Packages Projects Releases Wiki Activity

clean code fixes

Browse Source
This commit is contained in:
Miha Kralj
2024-10-06 17:16:47 -07:00
parent bcac34bf09
commit b7b5a4a1bf
52 changed files with 787 additions and 643 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lib/averages/Afirma.cs
+145 -156
View File
@@ -1,162 +1,151 @@
using System;
namespace QuanTAlib;
namespace QuanTAlib
public class Afirma : AbstractBase
{
public class Afirma : AbstractBase
public enum WindowType
{
public enum WindowType
{
Rectangular,
Hanning1,
Hanning2,
Blackman,
BlackmanHarris
}
private readonly int Periods;
private readonly int Taps;
private readonly WindowType Window;
private readonly CircularBuffer _buffer;
private readonly double[] _weights;
private readonly double _wsum;
private readonly double[] _armaBuffer;
private readonly int _n;
private readonly double _sx2, _sx3, _sx4, _sx5, _sx6, _den;
public Afirma(int periods, int taps, WindowType window)
{
if (periods < 1)
{
throw new ArgumentOutOfRangeException(nameof(periods), "Periods must be greater than or equal to 1.");
}
if (taps < 1)
{
throw new ArgumentOutOfRangeException(nameof(taps), "Taps must be greater than or equal to 1.");
}
Periods = periods;
Taps = taps;
Window = window;
WarmupPeriod = taps;
_buffer = new CircularBuffer(taps);
_weights = new double[taps];
_wsum = CalculateWeights();
_armaBuffer = new double[taps];
_n = (Taps - 1) / 2;
// Calculate least squares coefficients in the constructor
_sx2 = (2 * _n + 1) / 3.0;
_sx3 = _n * (_n + 1) / 2.0;
_sx4 = _sx2 * (3 * _n * _n + 3 * _n - 1) / 5.0;
_sx5 = _sx3 * (2 * _n * _n + 2 * _n - 1) / 3.0;
_sx6 = _sx2 * (3 * Math.Pow(_n, 3) * (_n + 2) - 3 * _n + 1) / 7.0;
_den = _sx6 * _sx4 / _sx5 - _sx5;
Name = "Afirma";
Init();
}
public Afirma(object source, int periods, int taps, WindowType window) : this(periods, taps, window)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
}
protected override double Calculation()
{
ManageState(IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (_index >= Taps)
{
double a0 = _buffer[_n];
double a1 = _buffer[_n] - _buffer[_n + 1];
double sx2y = 0.0;
double sx3y = 0.0;
for (int i = 0; i <= _n; i++)
{
sx2y += i * i * _buffer[_n - i];
sx3y += i * i * i * _buffer[_n - i];
}
sx2y = 2.0 * sx2y / _n / (_n + 1);
sx3y = 2.0 * sx3y / _n / (_n + 1);
double p = sx2y - a0 * _sx2 - a1 * _sx3;
double q = sx3y - a0 * _sx3 - a1 * _sx4;
double a2 = (p * _sx6 / _sx5 - q) / _den;
double a3 = (q * _sx4 / _sx5 - p) / _den;
for (int k = 0; k <= _n; k++)
{
_armaBuffer[_n - k] = a0 + k * a1 + k * k * a2 + k * k * k * a3;
}
}
double result = 0.0;
for (int k = 0; k < Taps; k++)
{
result += _buffer[k] * _weights[k] / _wsum;
}
IsHot = _index >= WarmupPeriod;
return result;
}
private double CalculateWeights()
{
double wsum = 0.0;
double centerTap = (Taps - 1) / 2.0;
for (int k = 0; k < Taps; k++)
{
double windowWeight;
switch (Window)
{
case WindowType.Rectangular:
windowWeight = 1.0;
break;
case WindowType.Hanning1:
windowWeight = 0.50 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.Hanning2:
windowWeight = 0.54 - 0.46 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.Blackman:
windowWeight = 0.42 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.08 * Math.Cos(4.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.BlackmanHarris:
windowWeight = 0.35875 - 0.48829 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.14128 * Math.Cos(4.0 * Math.PI * k / (Taps - 1)) - 0.01168 * Math.Cos(6.0 * Math.PI * k / (Taps - 1));
break;
default:
windowWeight = 1.0;
break;
}
double sincWeight;
if (Math.Abs(k - centerTap) < 1e-10)
{
sincWeight = 1.0;
}
else
{
sincWeight = Math.Sin(Math.PI * (k - centerTap) / Periods) / (Math.PI * (k - centerTap) / Periods);
}
_weights[k] = windowWeight * sincWeight;
wsum += _weights[k];
}
return wsum;
}
Rectangular,
Hanning1,
Hanning2,
Blackman,
BlackmanHarris
}
private readonly int Periods;
private readonly int Taps;
private readonly WindowType Window;
private readonly CircularBuffer _buffer;
private readonly double[] _weights;
private readonly double _wsum;
private readonly double[] _armaBuffer;
private readonly int _n;
private readonly double _sx2, _sx3, _sx4, _sx5, _sx6, _den;
public Afirma(int periods, int taps, WindowType window)
{
if (periods < 1)
{
throw new ArgumentOutOfRangeException(nameof(periods), "Periods must be greater than or equal to 1.");
}
if (taps < 1)
{
throw new ArgumentOutOfRangeException(nameof(taps), "Taps must be greater than or equal to 1.");
}
Periods = periods;
Taps = taps;
Window = window;
WarmupPeriod = taps;
_buffer = new CircularBuffer(taps);
_weights = new double[taps];
_wsum = CalculateWeights();
_armaBuffer = new double[taps];
_n = (Taps - 1) / 2;
// Calculate least squares coefficients in the constructor
_sx2 = (2 * _n + 1) / 3.0;
_sx3 = _n * (_n + 1) / 2.0;
_sx4 = _sx2 * (3 * _n * _n + 3 * _n - 1) / 5.0;
_sx5 = _sx3 * (2 * _n * _n + 2 * _n - 1) / 3.0;
_sx6 = _sx2 * (3 * Math.Pow(_n, 3) * (_n + 2) - 3 * _n + 1) / 7.0;
_den = _sx6 * _sx4 / _sx5 - _sx5;
Name = "Afirma";
Init();
}
public Afirma(object source, int periods, int taps, WindowType window) : this(periods, taps, window)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
}
protected override double Calculation()
{
ManageState(IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (_index >= Taps)
{
double a0 = _buffer[_n];
double a1 = _buffer[_n] - _buffer[_n + 1];
double sx2y = 0.0;
double sx3y = 0.0;
for (int i = 0; i <= _n; i++)
{
sx2y += i * i * _buffer[_n - i];
sx3y += i * i * i * _buffer[_n - i];
}
sx2y = 2.0 * sx2y / _n / (_n + 1);
sx3y = 2.0 * sx3y / _n / (_n + 1);
double p = sx2y - a0 * _sx2 - a1 * _sx3;
double q = sx3y - a0 * _sx3 - a1 * _sx4;
double a2 = (p * _sx6 / _sx5 - q) / _den;
double a3 = (q * _sx4 / _sx5 - p) / _den;
for (int k = 0; k <= _n; k++)
{
_armaBuffer[_n - k] = a0 + k * a1 + k * k * a2 + k * k * k * a3;
}
}
double result = 0.0;
for (int k = 0; k < Taps; k++)
{
result += _buffer[k] * _weights[k] / _wsum;
}
IsHot = _index >= WarmupPeriod;
return result;
}
private double CalculateWeights()
{
double wsum = 0.0;
double centerTap = (Taps - 1) / 2.0;
for (int k = 0; k < Taps; k++)
{
double windowWeight;
switch (Window)
{
case WindowType.Rectangular:
windowWeight = 1.0;
break;
case WindowType.Hanning1:
windowWeight = 0.50 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.Hanning2:
windowWeight = 0.54 - 0.46 * Math.Cos(2.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.Blackman:
windowWeight = 0.42 - 0.50 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.08 * Math.Cos(4.0 * Math.PI * k / (Taps - 1));
break;
case WindowType.BlackmanHarris:
windowWeight = 0.35875 - 0.48829 * Math.Cos(2.0 * Math.PI * k / (Taps - 1)) + 0.14128 * Math.Cos(4.0 * Math.PI * k / (Taps - 1)) - 0.01168 * Math.Cos(6.0 * Math.PI * k / (Taps - 1));
break;
default:
windowWeight = 1.0;
break;
}
double sincWeight;
sincWeight = Math.Abs(k - centerTap) < 1e-10 ? 1.0 : Math.Sin(Math.PI * (k - centerTap) / Periods) / (Math.PI * (k - centerTap) / Periods);
_weights[k] = windowWeight * sincWeight;
wsum += _weights[k];
}
return wsum;
}
}
lib/averages/Alma.cs
+1 -1
View File
@@ -25,7 +25,7 @@ public class Alma : AbstractBase
/// <param name="offset">Controls the smoothness and high-frequency filtering. Default is 0.85.</param>
/// <param name="sigma">Controls the shape of the Gaussian distribution. Default is 6.</param>
/// <exception cref="ArgumentException">Thrown when period is less than 1.</exception>
public Alma(int period, double offset = 0.85, double sigma = 6) : base()
public Alma(int period, double offset = 0.85, double sigma = 6)
{
if (period < 1)
{
lib/averages/Convolution.cs
+2 -2
View File
@@ -4,8 +4,8 @@ public class Convolution : AbstractBase
{
private readonly double[] _kernel;
private readonly int _kernelSize;
private CircularBuffer _buffer;
private double[] _normalizedKernel;
private readonly CircularBuffer _buffer;
private readonly double[] _normalizedKernel;
public Convolution(double[] kernel)
{
lib/averages/Dema.cs
+1 -1
View File
@@ -28,7 +28,7 @@ public class Dema : AbstractBase
private double _lastEma2, _p_lastEma2;
private double _k, _e, _p_e;
public Dema(int period) : base()
public Dema(int period)
{
if (period < 1)
{
lib/averages/Ema.cs
+6 -4
View File
@@ -27,10 +27,12 @@ public class Ema : AbstractBase
private readonly int _period;
private CircularBuffer _sma;
private double _lastEma, _p_lastEma;
private double _k, _e, _p_e;
private bool _isInit, _p_isInit, _useSma;
private double _e, _p_e;
private readonly double _k;
private bool _isInit, _p_isInit;
private readonly bool _useSma;
public Ema(int period, bool useSma = true) : base()
public Ema(int period, bool useSma = true)
{
if (period < 1)
{
@@ -45,7 +47,7 @@ public class Ema : AbstractBase
Init();
}
public Ema(double alpha) : base()
public Ema(double alpha)
{
_k = alpha;
_useSma = false;
lib/averages/Frama.cs
+75 -76
View File
@@ -1,99 +1,98 @@
using System;
namespace QuanTAlib
namespace QuanTAlib;
public class Frama : AbstractBase
{
public class Frama : AbstractBase
private readonly int _period;
private readonly double _fc;
private readonly CircularBuffer _buffer;
private double _lastFrama;
private double _prevLastFrama;
public Frama(int period, double fc = 0.5)
{
private readonly int _period;
private readonly double _fc;
private CircularBuffer _buffer;
private double _lastFrama;
private double _prevLastFrama;
if (period < 2)
throw new ArgumentException("Period must be at least 2", nameof(period));
public Frama(int period, double fc = 0.5) : base()
_period = period;
_fc = fc;
_buffer = new CircularBuffer(period);
WarmupPeriod = period;
}
public override void Init()
{
base.Init();
_buffer.Clear();
_lastFrama = 0;
_prevLastFrama = 0;
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
if (period < 2)
throw new ArgumentException("Period must be at least 2", nameof(period));
_prevLastFrama = _lastFrama;
_index++;
}
else
{
_lastFrama = _prevLastFrama;
}
}
_period = period;
_fc = fc;
_buffer = new CircularBuffer(period);
WarmupPeriod = period;
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (_buffer.Count < _period)
{
_lastFrama = _buffer.Average();
return _lastFrama;
}
public override void Init()
{
base.Init();
_buffer.Clear();
_lastFrama = 0;
_prevLastFrama = 0;
}
int half = _period / 2;
double hh = double.MinValue, ll = double.MaxValue;
double hh1 = double.MinValue, ll1 = double.MaxValue;
double hh2 = double.MinValue, ll2 = double.MaxValue;
protected override void ManageState(bool isNew)
for (int i = 0; i < _period; i++)
{
if (isNew)
double price = _buffer[i];
hh = Math.Max(hh, price);
ll = Math.Min(ll, price);
if (i < half)
{
_prevLastFrama = _lastFrama;
_index++;
hh1 = Math.Max(hh1, price);
ll1 = Math.Min(ll1, price);
}
else
{
_lastFrama = _prevLastFrama;
hh2 = Math.Max(hh2, price);
ll2 = Math.Min(ll2, price);
}
}
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double n1 = (hh - ll) / _period;
double n2 = (hh1 - ll1 + hh2 - ll2) / (_period / 2);
if (_buffer.Count < _period)
{
_lastFrama = _buffer.Average();
return _lastFrama;
}
double d = (Math.Log(n2 + double.Epsilon) - Math.Log(n1 + double.Epsilon)) / Math.Log(2);
int half = _period / 2;
double hh = double.MinValue, ll = double.MaxValue;
double hh1 = double.MinValue, ll1 = double.MaxValue;
double hh2 = double.MinValue, ll2 = double.MaxValue;
double alpha = Math.Exp(-4.6 * (d - 1));
alpha = Math.Max(Math.Min(alpha, 1), 0.01); // Ensure alpha is between 0.01 and 1
for (int i = 0; i < _period; i++)
{
double price = _buffer[i];
hh = Math.Max(hh, price);
ll = Math.Min(ll, price);
_lastFrama = alpha * (Input.Value - _lastFrama) + _lastFrama;
if (i < half)
{
hh1 = Math.Max(hh1, price);
ll1 = Math.Min(ll1, price);
}
else
{
hh2 = Math.Max(hh2, price);
ll2 = Math.Min(ll2, price);
}
}
double n1 = (hh - ll) / _period;
double n2 = (hh1 - ll1 + hh2 - ll2) / (_period / 2);
double d = (Math.Log(n2 + double.Epsilon) - Math.Log(n1 + double.Epsilon)) / Math.Log(2);
double alpha = Math.Exp(-4.6 * (d - 1));
alpha = Math.Max(Math.Min(alpha, 1), 0.01); // Ensure alpha is between 0.01 and 1
_lastFrama = alpha * (Input.Value - _lastFrama) + _lastFrama;
IsHot = _index >= WarmupPeriod;
return _lastFrama;
}
protected override double GetLastValid()
{
return _lastFrama;
}
IsHot = _index >= WarmupPeriod;
return _lastFrama;
}
}
protected override double GetLastValid()
{
return _lastFrama;
}
}
lib/averages/Htit.cs
+4 -6
View File
@@ -1,7 +1,7 @@
//not working yet
//TODO consistency test
using QuanTAlib;
namespace QuanTAlib;
public class Htit : AbstractBase
{
@@ -21,7 +21,7 @@ public class Htit : AbstractBase
private double _lastPd = 0;
private double _p_lastPd = 0;
public Htit() : base()
public Htit()
{
Name = "Htit";
WarmupPeriod = 12;
@@ -138,9 +138,7 @@ public class Htit : AbstractBase
{
return ((4 * _itBuffer[0]) + (3 * _itBuffer[1]) + (2 * _itBuffer[2]) + _itBuffer[3]) / 10;
}
else
{
return pr;
}
return pr;
}
}
lib/averages/Hwma.cs
+1 -1
View File
@@ -15,7 +15,7 @@ public class Hwma : AbstractBase
{
}
public Hwma(int period, double nA, double nB, double nC) : base()
public Hwma(int period, double nA, double nB, double nC)
{
if (period < 1)
{
lib/averages/Jma.cs
+6 -6
View File
@@ -1,20 +1,20 @@
using QuanTAlib;
namespace QuanTAlib;
//TODO consistency test
public class Jma : AbstractBase
{
public readonly int Period;
private readonly double _phase;
private readonly int _vshort, _vlong;
private CircularBuffer _values;
private CircularBuffer _voltyShort;
private CircularBuffer _vsumBuff;
private CircularBuffer _avoltyBuff;
private readonly CircularBuffer _values;
private readonly CircularBuffer _voltyShort;
private readonly CircularBuffer _vsumBuff;
private readonly CircularBuffer _avoltyBuff;
private double _beta, _len1, _pow1;
private double _upperBand, _lowerBand, _prevMa1, _prevDet0, _prevDet1, _prevJma;
private double _p_UpperBand, _p_LowerBand, _p_prevMa1, _p_prevDet0, _p_prevDet1, _p_prevJma;
public Jma(int period, double phase = 0, int vshort = 10) : base()
public Jma(int period, double phase = 0, int vshort = 10)
{
if (period < 1)
{
lib/averages/Kama.cs
+1 -3
View File
@@ -1,5 +1,3 @@
using System;
namespace QuanTAlib;
public class Kama : AbstractBase
@@ -9,7 +7,7 @@ public class Kama : AbstractBase
private CircularBuffer? _buffer;
private double _lastKama, _p_lastKama;
public Kama(int period, int fast = 2, int slow = 30) : base()
public Kama(int period, int fast = 2, int slow = 30)
{
if (period < 1)
{
lib/averages/Ltma.cs
+1 -1
View File
@@ -10,7 +10,7 @@ public class Ltma : AbstractBase
public double Gamma => _gamma;
public Ltma(double gamma = 0.1) : base()
public Ltma(double gamma = 0.1)
{
if (gamma < 0 || gamma > 1)
throw new ArgumentOutOfRangeException(nameof(gamma), "Gamma must be between 0 and 1.");
lib/averages/Maaf.cs
+3 -2
View File
@@ -8,12 +8,13 @@ public class Maaf : AbstractBase
{
private readonly CircularBuffer _priceBuffer;
private readonly CircularBuffer _smoothBuffer;
private double _prevFilter, _prevValue2, _threshold;
private double _prevFilter, _prevValue2;
private readonly double _threshold;
private double _p_prevFilter, _p_prevValue2;
private readonly int _period;
public Maaf(int Period = 39, double Threshold = 0.002) : base()
public Maaf(int Period = 39, double Threshold = 0.002)
{
_period = Period;
_threshold = Threshold;
lib/averages/Mama.cs
+3 -4
View File
@@ -1,17 +1,16 @@
using QuanTAlib;
using System;
namespace QuanTAlib;
public class Mama : AbstractBase
{
private readonly double _fastLimit, _slowLimit;
private CircularBuffer _pr, _sm, _dt, _i1, _q1, _i2, _q2, _re, _im, _pd, _ph;
private readonly CircularBuffer _pr, _sm, _dt, _i1, _q1, _i2, _q2, _re, _im, _pd, _ph;
private double _mama, _fama;
private double _prevMama, _prevFama, _sumPr;
private double _p_prevMama, _p_prevFama, _p_sumPr;
public TValue Fama { get; private set; }
public Mama(double fastLimit = 0.5, double slowLimit = 0.05) : base()
public Mama(double fastLimit = 0.5, double slowLimit = 0.05)
{
Fama = new TValue();
Name = $"Mama({_fastLimit:F2}, {_slowLimit:F2})";
lib/averages/Mgdi.cs
+1 -1
View File
@@ -5,7 +5,7 @@ public class Mgdi : AbstractBase
private readonly int _period;
private readonly double _kFactor;
private double _prevMd, _p_prevMd;
public Mgdi(int period, double kFactor = 0.6) : base()
public Mgdi(int period, double kFactor = 0.6)
{
if (period <= 0)
{
lib/averages/Mma.cs
+65 -69
View File
@@ -1,78 +1,74 @@
using System;
using System.Linq;
namespace QuanTAlib;
namespace QuanTAlib
public class Mma : AbstractBase
{
public class Mma : AbstractBase
private readonly int _period;
private readonly CircularBuffer _buffer;
private double _lastMma;
public Mma(int period)
{
private readonly int _period;
private readonly CircularBuffer _buffer;
private double _lastMma;
public Mma(int period) : base()
if (period < 2)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
_period = period;
_buffer = new CircularBuffer(period);
Name = "Mma";
WarmupPeriod = period;
Init();
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
_period = period;
_buffer = new CircularBuffer(period);
Name = "Mma";
WarmupPeriod = period;
Init();
}
public Mma(object source, int period) : this(period)
public Mma(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
public override void Init()
{
base.Init();
_lastMma = 0;
_buffer.Clear();
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
public override void Init()
{
base.Init();
_lastMma = 0;
_buffer.Clear();
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
_index++;
}
}
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (_index >= _period)
{
double T = _buffer.Sum();
double S = CalculateWeightedSum();
_lastMma = (T / _period) + (6 * S) / ((_period + 1) * _period);
}
else
{
// Use simple average until we have enough data points
_lastMma = _buffer.Average();
}
IsHot = _index >= _period;
return _lastMma;
}
private double CalculateWeightedSum()
{
double sum = 0;
for (int i = 0; i < _period; i++)
{
double weight = (_period - (2 * i + 1)) / 2.0;
sum += weight * _buffer[^(i + 1)];
}
return sum;
_index++;
}
}
}
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (_index >= _period)
{
double T = _buffer.Sum();
double S = CalculateWeightedSum();
_lastMma = (T / _period) + (6 * S) / ((_period + 1) * _period);
}
else
{
// Use simple average until we have enough data points
_lastMma = _buffer.Average();
}
IsHot = _index >= _period;
return _lastMma;
}
private double CalculateWeightedSum()
{
double sum = 0;
for (int i = 0; i < _period; i++)
{
double weight = (_period - (2 * i + 1)) / 2.0;
sum += weight * _buffer[^(i + 1)];
}
return sum;
}
}
lib/averages/Qema.cs
+1 -1
View File
@@ -6,7 +6,7 @@ public class Qema : AbstractBase
private readonly Ema _ema1, _ema2, _ema3, _ema4;
private double _lastQema, _p_lastQema;
public Qema(double k1=0.2, double k2=0.2, double k3=0.2, double k4=0.2) : base()
public Qema(double k1=0.2, double k2=0.2, double k3=0.2, double k4=0.2)
{
if (k1 <= 0 || k2 <= 0 || k3 <= 0 || k4 <= 0 )
{
lib/averages/Rema.cs
+1 -1
View File
@@ -12,7 +12,7 @@ public class Rema : AbstractBase
public int Period => _period;
public double Lambda => _lambda;
public Rema(int period, double lambda = 0.5) : base()
public Rema(int period, double lambda = 0.5)
{
if (period < 1)
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
lib/averages/Rma.cs
+30 -15
View File
@@ -1,16 +1,20 @@
using System;
using System.Runtime.CompilerServices;
namespace QuanTAlib {
namespace QuanTAlib;
public class Rma : AbstractBase {
public class Rma : AbstractBase
{
private readonly int _period;
private double _alpha;
private readonly double _alpha;
private double _lastRMA;
private double _savedLastRMA;
public Rma(int period) : base() {
if (period < 1) {
public Rma(int period)
{
if (period < 1)
{
throw new ArgumentException("Period must be greater than or equal to 1.", nameof(period));
}
_period = period;
@@ -20,38 +24,50 @@ public class Rma : AbstractBase {
Init();
}
public Rma(object source, int period) : this(period) {
public Rma(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
public override void Init() {
public override void Init()
{
base.Init();
_lastRMA = 0;
_savedLastRMA = 0;
}
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_savedLastRMA = _lastRMA;
_lastValidValue = Input.Value;
_index++;
} else {
}
else
{
_lastRMA = _savedLastRMA;
}
}
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
double rma;
if (_index == 1) {
if (_index == 1)
{
rma = Input.Value;
} else if (_index <= _period) {
}
else if (_index <= _period)
{
// Simple average during initial period
rma = (_lastRMA * (_index - 1) + Input.Value) / _index;
} else {
}
else
{
// Wilder's smoothing method
rma = _alpha * (Input.Value - _lastRMA) + _lastRMA;
}
@@ -62,4 +78,3 @@ public class Rma : AbstractBase {
return rma;
}
}
}
lib/averages/Sma.cs
+1 -1
View File
@@ -6,7 +6,7 @@ public class Sma : AbstractBase
// inherited _value
private readonly CircularBuffer _buffer;
public Sma(int period) : base()
public Sma(int period)
{
if (period < 1)
{
lib/averages/Smma.cs
+1 -1
View File
@@ -8,7 +8,7 @@ public class Smma : AbstractBase
private CircularBuffer? _buffer;
private double _lastSmma, _p_lastSmma;
public Smma(int period) : base()
public Smma(int period)
{
if (period < 1)
{
lib/averages/Tema.cs
+2 -2
View File
@@ -8,7 +8,7 @@ public class Tema : AbstractBase
private double _lastEma3, _p_lastEma3;
private double _k, _e, _p_e;
public Tema(int period) : base()
public Tema(int period)
{
if (period < 1)
{
@@ -58,7 +58,7 @@ public class Tema : AbstractBase
{
double result, _ema1, _ema2, _ema3;
ManageState(Input.IsNew);
_e = (_e > 1e-10) ? (1 - _k) * _e : 0;
double _invE = (_e > 1e-10) ? 1 / (1 - _e) : 1;
lib/averages/Trima.cs
+1 -8
View File
@@ -30,14 +30,7 @@ public class Trima : AbstractBase
for (int i = 0; i < period; i++)
{
if (i < halfPeriod)
{
kernel[i] = i + 1;
}
else
{
kernel[i] = period - i;
}
kernel[i] = i < halfPeriod ? i + 1 : period - i;
weightSum += kernel[i];
}
lib/averages/Zlema.cs
+4 -4
View File
@@ -7,11 +7,11 @@ public class Zlema : AbstractBase
{
private readonly int _period;
private CircularBuffer? _buffer;
private double _alpha;
private int _lag;
private readonly double _alpha;
private readonly int _lag;
private double _lastZLEMA, _p_lastZLEMA;
public Zlema(int period) : base()
public Zlema(int period)
{
if (period < 1)
{
@@ -55,7 +55,7 @@ public class Zlema : AbstractBase
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer!.Add(Input.Value, Input.IsNew);
int lag = Math.Max(Math.Min((int)((_period - 1) * 0.5), _buffer.Count - 1), 0) + 1;
lib/core/AbstractBarBase.cs
+1 -1
View File
@@ -8,7 +8,7 @@ namespace QuanTAlib;
/// and methods used by inheriting indicator types. It handles the basic flow of
/// receiving bar data, performing calculations, and publishing results.
/// </remarks>
public abstract class AbstractBarBase : iTValue {
public abstract class AbstractBarBase : ITValue {
public DateTime Time { get; set; }
public double Value { get; set; }
public bool IsNew { get; set; }
lib/core/abstractBase.cs
+1 -1
View File
@@ -8,7 +8,7 @@ namespace QuanTAlib;
/// and methods used by inheriting indicator types. It handles the basic flow of
/// receiving data, performing calculations, and publishing results.
/// </remarks>
public abstract class AbstractBase : iTValue
public abstract class AbstractBase : ITValue
{
public DateTime Time { get; set; }
public double Value { get; set; }
lib/core/circularbuffer.cs
+95 -47
View File
@@ -12,7 +12,8 @@ namespace QuanTAlib;
/// a fixed-size buffer of double values. It uses SIMD operations for improved performance
/// on supported hardware.
/// </remarks>
public class CircularBuffer : IEnumerable<double> {
public class CircularBuffer : IEnumerable<double>
{
private readonly double[] _buffer;
private int _start = 0;
private int _size = 0;
@@ -31,7 +32,8 @@ public class CircularBuffer : IEnumerable<double> {
/// Initializes a new instance of the CircularBuffer class with the specified capacity.
/// </summary>
/// <param name="capacity">The maximum number of elements the buffer can hold.</param>
public CircularBuffer(int capacity) {
public CircularBuffer(int capacity)
{
Capacity = capacity;
_buffer = GC.AllocateArray<double>(capacity, pinned: true);
}
@@ -42,16 +44,23 @@ public class CircularBuffer : IEnumerable<double> {
/// <param name="item">The item to add to the buffer.</param>
/// <param name="isNew">Indicates whether the item is a new value or an update to the last added value.</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Add(double item, bool isNew = true) {
if (_size == 0 || isNew) {
if (_size < Capacity) {
public void Add(double item, bool isNew = true)
{
if (_size == 0 || isNew)
{
if (_size < Capacity)
{
_buffer[(_start + _size) % Capacity] = item;
_size++;
} else {
}
else
{
_buffer[_start] = item;
_start = (_start + 1) % Capacity;
}
} else {
}
else
{
_buffer[(_start + _size - 1) % Capacity] = item;
}
}
@@ -61,15 +70,18 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <param name="index">The zero-based index of the element to get or set.</param>
/// <returns>The element at the specified index.</returns>
public double this[Index index] {
public double this[Index index]
{
[MethodImpl(MethodImplOptions.AggressiveInlining)]
get {
get
{
int actualIndex = index.IsFromEnd ? _size - index.Value : index.Value;
actualIndex = Math.Clamp(actualIndex, 0, _size - 1);
return _buffer[(_start + actualIndex) % Capacity];
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
set {
set
{
int actualIndex = index.IsFromEnd ? _size - index.Value : index.Value;
actualIndex = Math.Clamp(actualIndex, 0, _size - 1);
_buffer[(_start + actualIndex) % Capacity] = value;
@@ -77,7 +89,8 @@ public class CircularBuffer : IEnumerable<double> {
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static void ThrowArgumentOutOfRangeException() {
private static void ThrowArgumentOutOfRangeException()
{
throw new ArgumentOutOfRangeException("index", "Index is out of range.");
}
@@ -86,7 +99,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The newest element in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Newest() {
public double Newest()
{
if (_size == 0)
return 0;
return _buffer[(_start + _size - 1) % Capacity];
@@ -97,14 +111,16 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The oldest element in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Oldest() {
public double Oldest()
{
if (_size == 0)
ThrowInvalidOperationException();
return _buffer[_start];
}
[MethodImpl(MethodImplOptions.NoInlining)]
private static void ThrowInvalidOperationException() {
private static void ThrowInvalidOperationException()
{
throw new InvalidOperationException("Buffer is empty.");
}
@@ -119,13 +135,15 @@ public class CircularBuffer : IEnumerable<double> {
/// <summary>
/// Represents an enumerator for the CircularBuffer.
/// </summary>
public struct Enumerator : IEnumerator<double> {
public struct Enumerator : IEnumerator<double>
{
private readonly CircularBuffer _buffer;
private int _index;
private double _current;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
internal Enumerator(CircularBuffer buffer) {
internal Enumerator(CircularBuffer buffer)
{
_buffer = buffer;
_index = -1;
_current = default;
@@ -136,7 +154,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>true if the enumerator was successfully advanced to the next element; false if the enumerator has passed the end of the collection.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public bool MoveNext() {
public bool MoveNext()
{
if (_index + 1 >= _buffer._size)
return false;
@@ -154,7 +173,8 @@ public class CircularBuffer : IEnumerable<double> {
/// <summary>
/// Sets the enumerator to its initial position, which is before the first element in the buffer.
/// </summary>
public void Reset() {
public void Reset()
{
_index = -1;
_current = default;
}
@@ -171,13 +191,17 @@ public class CircularBuffer : IEnumerable<double> {
/// <param name="destination">The one-dimensional array that is the destination of the elements copied from the buffer.</param>
/// <param name="destinationIndex">The zero-based index in array at which copying begins.</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void CopyTo(double[] destination, int destinationIndex) {
public void CopyTo(double[] destination, int destinationIndex)
{
if (_size == 0)
return;
if (_start + _size <= Capacity) {
if (_start + _size <= Capacity)
{
Array.Copy(_buffer, _start, destination, destinationIndex, _size);
} else {
}
else
{
int firstPartLength = Capacity - _start;
Array.Copy(_buffer, _start, destination, destinationIndex, firstPartLength);
Array.Copy(_buffer, 0, destination, destinationIndex + firstPartLength, _size - firstPartLength);
@@ -189,15 +213,17 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>A read-only span over the buffer contents.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ReadOnlySpan<double> GetSpan() {
public ReadOnlySpan<double> GetSpan()
{
if (_size == 0)
return ReadOnlySpan<double>.Empty;
if (_start + _size <= Capacity) {
if (_start + _size <= Capacity)
{
return new ReadOnlySpan<double>(_buffer, _start, _size);
} else {
return new ReadOnlySpan<double>(ToArray());
}
return new ReadOnlySpan<double>(ToArray());
}
/// <summary>
@@ -216,7 +242,8 @@ public class CircularBuffer : IEnumerable<double> {
/// Removes all elements from the buffer.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public void Clear() {
public void Clear()
{
Array.Clear(_buffer, 0, _buffer.Length);
_start = 0;
_size = 0;
@@ -227,7 +254,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The maximum value in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Max() {
public double Max()
{
if (_size == 0)
ThrowInvalidOperationException();
@@ -239,7 +267,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The minimum value in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Min() {
public double Min()
{
if (_size == 0)
ThrowInvalidOperationException();
@@ -251,7 +280,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The sum of all values in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Sum() {
public double Sum()
{
return SumSimd();
}
@@ -260,7 +290,8 @@ public class CircularBuffer : IEnumerable<double> {
/// </summary>
/// <returns>The average of all values in the buffer.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public double Average() {
public double Average()
{
if (_size == 0)
ThrowInvalidOperationException();
@@ -268,22 +299,26 @@ public class CircularBuffer : IEnumerable<double> {
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double MaxSimd() {
private double MaxSimd()
{
var span = GetSpan();
var vectorSize = Vector<double>.Count;
var maxVector = new Vector<double>(double.MinValue);
int i = 0;
for (; i <= span.Length - vectorSize; i += vectorSize) {
for (; i <= span.Length - vectorSize; i += vectorSize)
{
maxVector = Vector.Max(maxVector, new Vector<double>(span.Slice(i, vectorSize)));
}
double max = double.MinValue;
for (int j = 0; j < vectorSize; j++) {
for (int j = 0; j < vectorSize; j++)
{
max = Math.Max(max, maxVector[j]);
}
for (; i < span.Length; i++) {
for (; i < span.Length; i++)
{
max = Math.Max(max, span[i]);
}
@@ -291,22 +326,26 @@ public class CircularBuffer : IEnumerable<double> {
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double MinSimd() {
private double MinSimd()
{
var span = GetSpan();
var vectorSize = Vector<double>.Count;
var minVector = new Vector<double>(double.MaxValue);
int i = 0;
for (; i <= span.Length - vectorSize; i += vectorSize) {
for (; i <= span.Length - vectorSize; i += vectorSize)
{
minVector = Vector.Min(minVector, new Vector<double>(span.Slice(i, vectorSize)));
}
double min = double.MaxValue;
for (int j = 0; j < vectorSize; j++) {
for (int j = 0; j < vectorSize; j++)
{
min = Math.Min(min, minVector[j]);
}
for (; i < span.Length; i++) {
for (; i < span.Length; i++)
{
min = Math.Min(min, span[i]);
}
@@ -314,22 +353,26 @@ public class CircularBuffer : IEnumerable<double> {
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private double SumSimd() {
private double SumSimd()
{
var span = GetSpan();
var vectorSize = Vector<double>.Count;
var sumVector = Vector<double>.Zero;
int i = 0;
for (; i <= span.Length - vectorSize; i += vectorSize) {
for (; i <= span.Length - vectorSize; i += vectorSize)
{
sumVector += new Vector<double>(span.Slice(i, vectorSize));
}
double sum = 0;
for (int j = 0; j < vectorSize; j++) {
for (int j = 0; j < vectorSize; j++)
{
sum += sumVector[j];
}
for (; i < span.Length; i++) {
for (; i < span.Length; i++)
{
sum += span[i];
}
@@ -340,7 +383,8 @@ public class CircularBuffer : IEnumerable<double> {
/// Copies the buffer elements to a new array.
/// </summary>
/// <returns>An array containing copies of the buffer elements.</returns>
public double[] ToArray() {
public double[] ToArray()
{
double[] array = new double[_size];
CopyTo(array, 0);
return array;
@@ -350,10 +394,12 @@ public class CircularBuffer : IEnumerable<double> {
/// Performs a parallel operation on the buffer elements.
/// </summary>
/// <param name="operation">The operation to perform on each partition of the buffer.</param>
public void ParallelOperation(Func<double[], int, int, double> operation) {
public void ParallelOperation(Func<double[], int, int, double> operation)
{
const int MinimumPartitionSize = 1024;
if (_size < MinimumPartitionSize) {
if (_size < MinimumPartitionSize)
{
var span = GetSpan();
var array = span.ToArray();
operation(array, 0, array.Length);
@@ -363,7 +409,8 @@ public class CircularBuffer : IEnumerable<double> {
int partitionCount = Environment.ProcessorCount;
int partitionSize = _size / partitionCount;
if (partitionSize < MinimumPartitionSize) {
if (partitionSize < MinimumPartitionSize)
{
partitionCount = Math.Max(1, _size / MinimumPartitionSize);
partitionSize = _size / partitionCount;
}
@@ -371,7 +418,8 @@ public class CircularBuffer : IEnumerable<double> {
var buffer = ToArray();
var results = new double[partitionCount];
Parallel.For(0, partitionCount, i => {
Parallel.For(0, partitionCount, i =>
{
int start = i * partitionSize;
int length = (i == partitionCount - 1) ? _size - start : partitionSize;
results[i] = operation(buffer, start, length);
lib/core/formatters.cs
+1 -1
View File
@@ -9,7 +9,7 @@ public static class Formatters
const string pad = "18";
public static void Initialize()
{
Formatter.Register<iTValue>((tick, writer) =>
Formatter.Register<ITValue>((tick, writer) =>
{
var sb = new StringBuilder();
sb.Append("<table style='border-collapse: collapse; text-align: left;'><tr>");
lib/core/tbar.cs
+2 -2
View File
@@ -1,6 +1,6 @@
namespace QuanTAlib;
public interface iTBar
public interface ITBar
{
DateTime Time { get; }
double Open { get; }
@@ -11,7 +11,7 @@ public interface iTBar
bool IsNew { get; }
}
public readonly record struct TBar(DateTime Time, double Open, double High, double Low, double Close, double Volume, bool IsNew = true) : iTBar
public readonly record struct TBar(DateTime Time, double Open, double High, double Low, double Close, double Volume, bool IsNew = true) : ITBar
{
public DateTime Time { get; init; } = Time;
public double Open { get; init; } = Open;
lib/core/tvalue.cs
+2 -2
View File
@@ -1,6 +1,6 @@
namespace QuanTAlib;
public interface iTValue
public interface ITValue
{
DateTime Time { get; }
double Value { get; }
@@ -8,7 +8,7 @@ public interface iTValue
bool IsHot { get; }
}
public readonly record struct TValue(DateTime Time, double Value, bool IsNew = true, bool IsHot = true) : iTValue
public readonly record struct TValue(DateTime Time, double Value, bool IsNew = true, bool IsHot = true) : ITValue
{
public DateTime Time { get; init; } = Time;
public double Value { get; init; } = Value;
lib/feeds/GbmFeed.cs
+1 -1
View File
@@ -8,7 +8,7 @@ public class GbmFeed : TBarSeries
private readonly Random _random;
private double _lastClose, _lastHigh, _lastLow;
public GbmFeed(double initialPrice = 100.0, double mu = 0.05, double sigma = 0.2) : base()
public GbmFeed(double initialPrice = 100.0, double mu = 0.05, double sigma = 0.2)
{
_lastClose = _lastHigh = _lastLow = initialPrice;
_mu = mu;
lib/statistics/Entropy.cs
+1 -1
View File
@@ -16,7 +16,7 @@ public class Entropy : AbstractBase
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when the period is less than 2.
/// </exception>
public Entropy(int period) : base()
public Entropy(int period)
{
if (period < 2)
{
lib/statistics/Kurtosis.cs
+1 -1
View File
@@ -16,7 +16,7 @@ public class Kurtosis : AbstractBase
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when the period is less than 4.
/// </exception>
public Kurtosis(int period) : base()
public Kurtosis(int period)
{
if (period < 4)
{
lib/statistics/Max.cs
+2 -2
View File
@@ -20,7 +20,7 @@ public class Max : AbstractBase
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when the period is less than 1 or decay is negative.
/// </exception>
public Max(int period, double decay = 0) : base()
public Max(int period, double decay = 0)
{
if (period < 1)
{
@@ -105,7 +105,7 @@ public class Max : AbstractBase
}
double decayRate = 1 - Math.Exp(-_halfLife * _timeSinceNewMax / Period);
_currentMax = _currentMax - decayRate * (_currentMax - _buffer.Average());
_currentMax -= decayRate * (_currentMax - _buffer.Average());
_currentMax = Math.Min(_currentMax, _buffer.Max());
IsHot = true;
lib/statistics/Median.cs
+2 -11
View File
@@ -16,7 +16,7 @@ public class Median : AbstractBase
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when the period is less than 1.
/// </exception>
public Median(int period) : base()
public Median(int period)
{
if (period < 1)
{
@@ -76,16 +76,7 @@ public class Median : AbstractBase
Array.Sort(sortedValues);
int middleIndex = sortedValues.Length / 2;
if (sortedValues.Length % 2 == 0)
{
// Even number of values: average of two middle values
median = (sortedValues[middleIndex - 1] + sortedValues[middleIndex]) / 2.0;
}
else
{
// Odd number of values: middle value
median = sortedValues[middleIndex];
}
median = (sortedValues.Length % 2 == 0) ? (sortedValues[middleIndex - 1] + sortedValues[middleIndex]) / 2.0 : sortedValues[middleIndex];
}
else
{
lib/statistics/Min.cs
+24 -12
View File
@@ -10,7 +10,8 @@ namespace QuanTAlib;
/// efficiently. It also implements a decay mechanism to adjust the minimum value over
/// time, allowing for a more responsive indicator in changing market conditions.
/// </remarks>
public class Min : AbstractBase {
public class Min : AbstractBase
{
private readonly int Period;
private readonly CircularBuffer _buffer;
private readonly double _halfLife;
@@ -25,11 +26,14 @@ public class Min : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 1 or decay is negative.
/// </exception>
public Min(int period, double decay = 0) : base() {
if (period < 1) {
public Min(int period, double decay = 0)
{
if (period < 1)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
}
if (decay < 0) {
if (decay < 0)
{
throw new ArgumentOutOfRangeException(nameof(decay), "Half-life must be non-negative.");
}
Period = period;
@@ -46,7 +50,8 @@ public class Min : AbstractBase {
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the minimum value.</param>
/// <param name="decay">The decay factor to apply to older values (default is 0).</param>
public Min(object source, int period, double decay = 0) : this(period, decay) {
public Min(object source, int period, double decay = 0) : this(period, decay)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -54,7 +59,8 @@ public class Min : AbstractBase {
/// <summary>
/// Initializes the Min instance by setting initial values.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_currentMin = double.MaxValue;
_timeSinceNewMin = 0;
@@ -64,14 +70,18 @@ public class Min : AbstractBase {
/// Manages the state of the Min instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_p_currentMin = _currentMin;
_lastValidValue = Input.Value;
_index++;
_timeSinceNewMin++;
_p_timeSinceNewMin = _timeSinceNewMin;
} else {
}
else
{
_currentMin = _p_currentMin;
_timeSinceNewMin = _p_timeSinceNewMin;
}
@@ -87,17 +97,19 @@ public class Min : AbstractBase {
/// The decay rate is calculated using an exponential function based on the time since
/// the last new minimum and the specified half-life.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
if (Input.Value <= _currentMin) {
if (Input.Value <= _currentMin)
{
_currentMin = Input.Value;
_timeSinceNewMin = 0;
}
double decayRate = 1 - Math.Exp(-_halfLife * _timeSinceNewMin / Period);
_currentMin = _currentMin + decayRate * (_buffer.Average() - _currentMin);
_currentMin += decayRate * (_buffer.Average() - _currentMin);
_currentMin = Math.Max(_currentMin, _buffer.Min());
IsHot = true;
lib/statistics/Mode.cs
+19 -9
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// efficiently. Before the specified period is reached, it returns the average of
/// the available values as an approximation.
/// </remarks>
public class Mode : AbstractBase {
public class Mode : AbstractBase
{
private readonly int Period;
private readonly CircularBuffer _buffer;
@@ -20,8 +21,10 @@ public class Mode : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 1.
/// </exception>
public Mode(int period) : base() {
if (period < 1) {
public Mode(int period)
{
if (period < 1)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
}
Period = period;
@@ -36,7 +39,8 @@ public class Mode : AbstractBase {
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the mode.</param>
public Mode(object source, int period) : this(period) {
public Mode(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -45,8 +49,10 @@ public class Mode : AbstractBase {
/// Manages the state of the Mode instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -64,12 +70,14 @@ public class Mode : AbstractBase {
/// the available values as an approximation of the mode. Once the period is
/// reached, it calculates the true mode by grouping and counting the values.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double mode;
if (_index >= Period) {
if (_index >= Period)
{
var values = _buffer.GetSpan().ToArray();
var groupedValues = values.GroupBy(v => v)
.OrderByDescending(g => g.Count())
@@ -82,7 +90,9 @@ public class Mode : AbstractBase {
.ToList();
mode = modes.Average(); // If there are multiple modes, we return their average
} else {
}
else
{
mode = _buffer.Average(); // Use average until we have enough data points
}
lib/statistics/Percentile.cs
+28 -13
View File
@@ -10,7 +10,8 @@ namespace QuanTAlib;
/// between two data points. Before the specified period is reached, it returns the
/// average of the available values as an approximation.
/// </remarks>
public class Percentile : AbstractBase {
public class Percentile : AbstractBase
{
private readonly int Period;
private readonly double Percent;
private readonly CircularBuffer _buffer;
@@ -23,11 +24,14 @@ public class Percentile : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2 or percent is not between 0 and 100.
/// </exception>
public Percentile(int period, double percent) : base() {
if (period < 2) {
public Percentile(int period, double percent)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2 for percentile calculation.");
}
if (percent < 0 || percent > 100) {
if (percent < 0 || percent > 100)
{
throw new ArgumentOutOfRangeException(nameof(percent), "Percent must be between 0 and 100.");
}
Period = period;
@@ -44,7 +48,8 @@ public class Percentile : AbstractBase {
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the percentile.</param>
/// <param name="percent">The percentile to calculate (between 0 and 100).</param>
public Percentile(object source, int period, double percent) : this(period, percent) {
public Percentile(object source, int period, double percent) : this(period, percent)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -52,7 +57,8 @@ public class Percentile : AbstractBase {
/// <summary>
/// Initializes the Percentile instance by clearing the buffer.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
}
@@ -61,8 +67,10 @@ public class Percentile : AbstractBase {
/// Manages the state of the Percentile instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -80,12 +88,14 @@ public class Percentile : AbstractBase {
/// as an approximation. Once the period is reached, it calculates the true percentile by
/// sorting the values and interpolating as necessary.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double result;
if (_buffer.Count >= Period) {
if (_buffer.Count >= Period)
{
var values = _buffer.GetSpan().ToArray();
Array.Sort(values);
@@ -93,16 +103,21 @@ public class Percentile : AbstractBase {
int lowerIndex = (int)Math.Floor(position);
int upperIndex = (int)Math.Ceiling(position);
if (lowerIndex == upperIndex) {
if (lowerIndex == upperIndex)
{
result = values[lowerIndex];
} else {
}
else
{
// Interpolate between the two nearest values
double lowerValue = values[lowerIndex];
double upperValue = values[upperIndex];
double fraction = position - lowerIndex;
result = lowerValue + (upperValue - lowerValue) * fraction;
}
} else {
}
else
{
// Use average for insufficient data, like the Median class
result = _buffer.Average();
}
lib/statistics/Skew.cs
+22 -11
View File
@@ -10,7 +10,8 @@ namespace QuanTAlib;
/// for sample skewness calculation. A minimum of 3 data points is required for the
/// calculation.
/// </remarks>
public class Skew : AbstractBase {
public class Skew : AbstractBase
{
private readonly int Period;
private readonly CircularBuffer _buffer;
@@ -21,8 +22,10 @@ public class Skew : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 3.
/// </exception>
public Skew(int period) : base() {
if (period < 3) {
public Skew(int period)
{
if (period < 3)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 3 for skewness calculation.");
}
Period = period;
@@ -37,7 +40,8 @@ public class Skew : AbstractBase {
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the skewness.</param>
public Skew(object source, int period) : this(period) {
public Skew(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -45,7 +49,8 @@ public class Skew : AbstractBase {
/// <summary>
/// Initializes the Skew instance by clearing the buffer.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
}
@@ -54,8 +59,10 @@ public class Skew : AbstractBase {
/// Manages the state of the Skew instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -73,13 +80,15 @@ public class Skew : AbstractBase {
/// calculation. If there are fewer than 3 data points, or if the standard
/// deviation is zero, the method returns 0.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double skew = 0;
if (_buffer.Count >= 3) { // We need at least 3 data points for skewness
if (_buffer.Count >= 3)
{ // We need at least 3 data points for skewness
var values = _buffer.GetSpan().ToArray();
double mean = values.Average();
double n = values.Length;
@@ -87,7 +96,8 @@ public class Skew : AbstractBase {
double sumCubedDeviations = 0;
double sumSquaredDeviations = 0;
foreach (var value in values) {
foreach (var value in values)
{
double deviation = value - mean;
sumCubedDeviations += Math.Pow(deviation, 3);
sumSquaredDeviations += Math.Pow(deviation, 2);
@@ -98,7 +108,8 @@ public class Skew : AbstractBase {
double m2 = sumSquaredDeviations / n;
double s3 = Math.Pow(m2, 1.5);
if (s3 != 0) { // Avoid division by zero
if (s3 != 0)
{ // Avoid division by zero
skew = (Math.Sqrt(n * (n - 1)) / (n - 2)) * (m3 / s3);
}
}
lib/statistics/Stddev.cs
+18 -9
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// standard deviation based on the isPopulation parameter. It uses a circular buffer
/// to efficiently manage the data points within the specified period.
/// </remarks>
public class Stddev : AbstractBase {
public class Stddev : AbstractBase
{
private readonly int Period;
private readonly bool IsPopulation;
private readonly CircularBuffer _buffer;
@@ -25,8 +26,10 @@ public class Stddev : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Stddev(int period, bool isPopulation = false) : base() {
if (period < 2) {
public Stddev(int period, bool isPopulation = false)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
Period = period;
@@ -46,7 +49,8 @@ public class Stddev : AbstractBase {
/// <param name="isPopulation">
/// A flag indicating whether to calculate population (true) or sample (false) standard deviation.
/// </param>
public Stddev(object source, int period, bool isPopulation = false) : this(period, isPopulation) {
public Stddev(object source, int period, bool isPopulation = false) : this(period, isPopulation)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -54,7 +58,8 @@ public class Stddev : AbstractBase {
/// <summary>
/// Initializes the Stddev instance by clearing the buffer.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
}
@@ -63,8 +68,10 @@ public class Stddev : AbstractBase {
/// Manages the state of the Stddev instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -83,13 +90,15 @@ public class Stddev : AbstractBase {
/// where x is each value, mean is the average of all values, and n is the number of values.
/// If there's only one value in the buffer, the method returns 0.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double stddev = 0;
if (_buffer.Count > 1) {
if (_buffer.Count > 1)
{
var values = _buffer.GetSpan().ToArray();
double mean = values.Average();
double sumOfSquaredDifferences = values.Sum(x => Math.Pow(x - mean, 2));
lib/statistics/Variance.cs
+18 -9
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// variance based on the isPopulation parameter. It uses a circular buffer
/// to efficiently manage the data points within the specified period.
/// </remarks>
public class Variance : AbstractBase {
public class Variance : AbstractBase
{
private readonly int Period;
private readonly bool IsPopulation;
private readonly CircularBuffer _buffer;
@@ -25,8 +26,10 @@ public class Variance : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Variance(int period, bool isPopulation = false) : base() {
if (period < 2) {
public Variance(int period, bool isPopulation = false)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
Period = period;
@@ -46,7 +49,8 @@ public class Variance : AbstractBase {
/// <param name="isPopulation">
/// A flag indicating whether to calculate population (true) or sample (false) variance.
/// </param>
public Variance(object source, int period, bool isPopulation = false) : this(period, isPopulation) {
public Variance(object source, int period, bool isPopulation = false) : this(period, isPopulation)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -54,7 +58,8 @@ public class Variance : AbstractBase {
/// <summary>
/// Initializes the Variance instance by clearing the buffer.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
}
@@ -63,8 +68,10 @@ public class Variance : AbstractBase {
/// Manages the state of the Variance instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -83,13 +90,15 @@ public class Variance : AbstractBase {
/// where x is each value, mean is the average of all values, and n is the number of values.
/// If there's only one value in the buffer, the method returns 0.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double variance = 0;
if (_buffer.Count > 1) {
if (_buffer.Count > 1)
{
var values = _buffer.GetSpan().ToArray();
double mean = values.Average();
double sumOfSquaredDifferences = values.Sum(x => Math.Pow(x - mean, 2));
lib/statistics/Zscore.cs
+20 -10
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// the most recent value in a given period. It uses a circular buffer to
/// efficiently manage the data points within the specified period.
/// </remarks>
public class Zscore : AbstractBase {
public class Zscore : AbstractBase
{
private readonly int Period;
private readonly CircularBuffer _buffer;
@@ -20,8 +21,10 @@ public class Zscore : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Zscore(int period) : base() {
if (period < 2) {
public Zscore(int period)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2 for Z-score calculation.");
}
Period = period;
@@ -36,7 +39,8 @@ public class Zscore : AbstractBase {
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the Z-score.</param>
public Zscore(object source, int period) : this(period) {
public Zscore(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -44,7 +48,8 @@ public class Zscore : AbstractBase {
/// <summary>
/// Initializes the Zscore instance by clearing the buffer.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
}
@@ -53,8 +58,10 @@ public class Zscore : AbstractBase {
/// Manages the state of the Zscore instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -72,13 +79,15 @@ public class Zscore : AbstractBase {
/// where x is the input value, μ is the mean of the period, and σ is the sample standard deviation.
/// If there are fewer than 2 data points or if the standard deviation is 0, the method returns 0.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double zScore = 0;
if (_buffer.Count >= 2) { // We need at least 2 data points for Z-score
if (_buffer.Count >= 2)
{ // We need at least 2 data points for Z-score
var values = _buffer.GetSpan().ToArray();
double mean = values.Average();
double n = values.Length;
@@ -86,7 +95,8 @@ public class Zscore : AbstractBase {
double sumSquaredDeviations = values.Sum(x => Math.Pow(x - mean, 2));
double standardDeviation = Math.Sqrt(sumSquaredDeviations / (n - 1)); // Sample standard deviation
if (standardDeviation != 0) { // Avoid division by zero
if (standardDeviation != 0)
{ // Avoid division by zero
zScore = (Input.Value - mean) / standardDeviation;
}
}
lib/volatility/Historical.cs
+24 -12
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// both annualized and non-annualized volatility measures. The calculation uses a sample
/// standard deviation formula and assumes 252 trading days in a year for annualization.
/// </remarks>
public class Historical : AbstractBase {
public class Historical : AbstractBase
{
private readonly int Period;
private readonly bool IsAnnualized;
private readonly CircularBuffer _buffer;
@@ -24,8 +25,10 @@ public class Historical : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Historical(int period, bool isAnnualized = true) : base() {
if (period < 2) {
public Historical(int period, bool isAnnualized = true)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
Period = period;
@@ -43,7 +46,8 @@ public class Historical : AbstractBase {
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate historical volatility.</param>
/// <param name="isAnnualized">Whether to annualize the volatility (default is true).</param>
public Historical(object source, int period, bool isAnnualized = true) : this(period, isAnnualized) {
public Historical(object source, int period, bool isAnnualized = true) : this(period, isAnnualized)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -51,7 +55,8 @@ public class Historical : AbstractBase {
/// <summary>
/// Initializes the Historical instance by clearing buffers and resetting the previous close value.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_buffer.Clear();
_logReturns.Clear();
@@ -62,8 +67,10 @@ public class Historical : AbstractBase {
/// Manages the state of the Historical instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -82,19 +89,23 @@ public class Historical : AbstractBase {
/// 3. If annualized, multiply by the square root of 252 (assumed trading days in a year).
/// The method returns 0 until enough data points are available for the calculation.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double volatility = 0;
if (_buffer.Count > 1) {
if (_previousClose != 0) {
if (_buffer.Count > 1)
{
if (_previousClose != 0)
{
double logReturn = Math.Log(Input.Value / _previousClose);
_logReturns.Add(logReturn, Input.IsNew);
}
if (_logReturns.Count == Period) {
if (_logReturns.Count == Period)
{
var returns = _logReturns.GetSpan().ToArray();
double mean = returns.Average();
double sumOfSquaredDifferences = returns.Sum(x => Math.Pow(x - mean, 2));
@@ -102,7 +113,8 @@ public class Historical : AbstractBase {
double variance = sumOfSquaredDifferences / (Period - 1); // Using sample standard deviation
volatility = Math.Sqrt(variance);
if (IsAnnualized) {
if (IsAnnualized)
{
// Assuming 252 trading days in a year. Adjust as needed.
volatility *= Math.Sqrt(252);
}
lib/volatility/Realized.cs
+22 -11
View File
@@ -9,7 +9,8 @@ namespace QuanTAlib;
/// both annualized and non-annualized volatility measures. The calculation uses a rolling
/// sum of squared returns for efficiency and assumes 252 trading days in a year for annualization.
/// </remarks>
public class Realized : AbstractBase {
public class Realized : AbstractBase
{
private readonly int Period;
private readonly bool IsAnnualized;
private readonly CircularBuffer _returns;
@@ -24,8 +25,10 @@ public class Realized : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Realized(int period, bool isAnnualized = true) : base() {
if (period < 2) {
public Realized(int period, bool isAnnualized = true)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
Period = period;
@@ -39,7 +42,8 @@ public class Realized : AbstractBase {
/// <summary>
/// Initializes the Realized instance by clearing buffers and resetting calculation variables.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_returns.Clear();
_previousClose = 0;
@@ -50,8 +54,10 @@ public class Realized : AbstractBase {
/// Manages the state of the Realized instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
@@ -72,14 +78,17 @@ public class Realized : AbstractBase {
/// 5. If annualized, multiply by the square root of 252 (assumed trading days in a year).
/// The method returns 0 until enough data points are available for the calculation.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
double volatility = 0;
if (_previousClose != 0) {
if (_previousClose != 0)
{
double logReturn = Math.Log(Input.Value / _previousClose);
if (_returns.Count == Period) {
if (_returns.Count == Period)
{
// Remove the oldest squared return from the sum
_sumSquaredReturns -= Math.Pow(_returns[0], 2);
}
@@ -87,11 +96,13 @@ public class Realized : AbstractBase {
_returns.Add(logReturn, Input.IsNew);
_sumSquaredReturns += Math.Pow(logReturn, 2);
if (_returns.Count == Period) {
if (_returns.Count == Period)
{
double variance = _sumSquaredReturns / Period;
volatility = Math.Sqrt(variance);
if (IsAnnualized) {
if (IsAnnualized)
{
// Assuming 252 trading days in a year. Adjust as needed.
volatility *= Math.Sqrt(252);
}
lib/volatility/Rvi.cs
+19 -15
View File
@@ -13,10 +13,11 @@ namespace QuanTAlib;
/// This implementation uses a combination of Standard Deviation and Simple Moving Average
/// calculations to compute the RVI.
/// </remarks>
public class Rvi : AbstractBase {
public class Rvi : AbstractBase
{
private readonly int Period;
private Stddev _upStdDev, _downStdDev;
private Sma _upSma, _downSma;
private readonly Stddev _upStdDev, _downStdDev;
private readonly Sma _upSma, _downSma;
private double _previousClose;
/// <summary>
@@ -26,8 +27,10 @@ public class Rvi : AbstractBase {
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Rvi(int period) : base() {
if (period < 2) {
public Rvi(int period)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
Period = period;
@@ -45,7 +48,8 @@ public class Rvi : AbstractBase {
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the RVI.</param>
public Rvi(object source, int period) : this(period) {
public Rvi(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
@@ -53,7 +57,8 @@ public class Rvi : AbstractBase {
/// <summary>
/// Initializes the Rvi instance by setting up the initial state.
/// </summary>
public override void Init() {
public override void Init()
{
base.Init();
_previousClose = 0;
}
@@ -62,8 +67,10 @@ public class Rvi : AbstractBase {
/// Manages the state of the Rvi instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Value;
_index++;
}
@@ -84,7 +91,8 @@ public class Rvi : AbstractBase {
/// 5. Compute the RVI as a percentage of up volatility to total volatility.
/// The method returns 0 if the sum of up and down volatility is zero.
/// </remarks>
protected override double Calculation() {
protected override double Calculation()
{
ManageState(Input.IsNew);
double close = Input.Value;
@@ -97,11 +105,7 @@ public class Rvi : AbstractBase {
_downSma.Calc(_downStdDev.Calc(new TValue(Input.Time, downMove, Input.IsNew)));
double rvi;
if (_upSma.Value + _downSma.Value != 0) {
rvi = 100 * _upSma.Value / (_upSma.Value + _downSma.Value);
} else {
rvi = 0;
}
rvi = (_upSma.Value + _downSma.Value != 0) ? 100 * _upSma.Value / (_upSma.Value + _downSma.Value) : 0;
_previousClose = close;
IsHot = _index >= WarmupPeriod;