Files
QuanTAlib/lib/errors/Rsquared.cs
T
Miha Kralj ffed6491d4 corrections
2024-10-13 17:31:35 -07:00

81 lines
2.2 KiB
C#

namespace QuanTAlib;
public class Rsquared : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
public Rsquared(int period)
{
if (period < 1)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 1.");
}
WarmupPeriod = period;
_actualBuffer = new CircularBuffer(period);
_predictedBuffer = new CircularBuffer(period);
Name = $"Rsquared(period={period})";
Init();
}
public Rsquared(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
public override void Init()
{
base.Init();
_actualBuffer.Clear();
_predictedBuffer.Clear();
}
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
}
protected override double Calculation()
{
ManageState(Input.IsNew);
double actual = Input.Value;
_actualBuffer.Add(actual, Input.IsNew);
double predicted = double.IsNaN(Input2.Value) ? _actualBuffer.Average() : Input2.Value;
_predictedBuffer.Add(predicted, Input.IsNew);
double rsquared = 0;
if (_actualBuffer.Count > 0)
{
var actualValues = _actualBuffer.GetSpan().ToArray();
var predictedValues = _predictedBuffer.GetSpan().ToArray();
double meanActual = actualValues.Average();
double sumSquaredTotal = 0;
double sumSquaredResidual = 0;
for (int i = 0; i < _actualBuffer.Count; i++)
{
double deviation = actualValues[i] - meanActual;
sumSquaredTotal += deviation * deviation;
double error = actualValues[i] - predictedValues[i];
sumSquaredResidual += error * error;
}
if (sumSquaredTotal != 0)
{
rsquared = 1 - (sumSquaredResidual / sumSquaredTotal);
}
}
IsHot = _index >= WarmupPeriod;
return rsquared;
}
}