Files
QuanTAlib/lib/errors/Rsquared.cs
T
2024-10-11 18:02:09 -07:00

133 lines
4.6 KiB
C#

namespace QuanTAlib;
/// <summary>
/// Represents a Coefficient of Determination (R-squared) calculator that measures the proportion of
/// the variance in the dependent variable that is predictable from the independent variable(s).
/// </summary>
/// <remarks>
/// The Rsquared class calculates the Coefficient of Determination using circular buffers
/// to efficiently manage the actual and predicted data points within the specified period.
/// </remarks>
public class Rsquared : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
/// <summary>
/// Initializes a new instance of the Rsquared class with the specified period.
/// </summary>
/// <param name="period">The period over which to calculate the Coefficient of Determination.</param>
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Rsquared(int period)
{
if (period < 2)
{
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
}
WarmupPeriod = period;
_actualBuffer = new CircularBuffer(period);
_predictedBuffer = new CircularBuffer(period);
Name = $"Rsquared(period={period})";
Init();
}
/// <summary>
/// Initializes a new instance of the Mape class with the specified source and period.
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the Mean Absolute Percentage Error.</param>
public Rsquared(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
/// <summary>
/// Initializes the Rsquared instance by clearing the buffers.
/// </summary>
public override void Init()
{
base.Init();
_actualBuffer.Clear();
_predictedBuffer.Clear();
}
/// <summary>
/// Manages the state of the Rsquared instance based on whether new values are being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current inputs are new values.</param>
protected override void ManageState(bool isNew)
{
if (isNew)
{
_lastValidValue = Input.Value;
_index++;
}
}
/// <summary>
/// Performs the Coefficient of Determination calculation for the current period.
/// </summary>
/// <returns>
/// The calculated Coefficient of Determination value for the current period.
/// </returns>
/// <remarks>
/// This method calculates the Coefficient of Determination using the formula:
/// R^2 = 1 - (SSres / SStot)
/// where SSres is the sum of squared residuals and SStot is the total sum of squares.
/// </remarks>
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 >= 2)
{
var actualValues = _actualBuffer.GetSpan().ToArray();
var predictedValues = _predictedBuffer.GetSpan().ToArray();
double actualMean = actualValues.Average();
double ssRes = 0;
double ssTot = 0;
for (int i = 0; i < _actualBuffer.Count; i++)
{
double residual = actualValues[i] - predictedValues[i];
ssRes += residual * residual;
double deviation = actualValues[i] - actualMean;
ssTot += deviation * deviation;
}
if (ssTot != 0)
{
rsquared = 1 - (ssRes / ssTot);
}
}
IsHot = _index >= WarmupPeriod;
return rsquared;
}
/// <summary>
/// Calculates the Coefficient of Determination for the given actual and predicted values.
/// </summary>
/// <param name="actual">The actual value.</param>
/// <param name="predicted">The predicted value.</param>
/// <returns>The calculated Coefficient of Determination.</returns>
public double Calc(double actual, double predicted)
{
Input = new TValue(DateTime.Now, actual);
Input2 = new TValue(DateTime.Now, predicted);
return Calculation();
}
}