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

130 lines
4.6 KiB
C#

namespace QuanTAlib;
/// <summary>
/// Represents a Relative Absolute Error calculator that measures the ratio of the sum of absolute errors
/// to the sum of absolute differences between actual values and the mean of actual values.
/// </summary>
/// <remarks>
/// The Rae class calculates the Relative Absolute Error using circular buffers
/// to efficiently manage the data points within the specified period.
/// </remarks>
public class Rae : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
/// <summary>
/// Initializes a new instance of the Rae class with the specified period.
/// </summary>
/// <param name="period">The period over which to calculate the Relative Absolute Error.</param>
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 2.
/// </exception>
public Rae(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 = $"Rae(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 Rae(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
/// <summary>
/// Initializes the Rae instance by clearing the buffers.
/// </summary>
public override void Init()
{
base.Init();
_actualBuffer.Clear();
_predictedBuffer.Clear();
}
/// <summary>
/// Manages the state of the Rae 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 Relative Absolute Error calculation for the current period.
/// </summary>
/// <returns>
/// The calculated Relative Absolute Error value for the current period.
/// </returns>
/// <remarks>
/// This method calculates the Relative Absolute Error using the formula:
/// RAE = sum(|actual - predicted|) / sum(|actual - mean(actual)|)
/// where actual is each actual value, predicted is each predicted value, and mean(actual) is the average of actual values.
/// </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 rae = 0;
if (_actualBuffer.Count >= 2)
{
var actualValues = _actualBuffer.GetSpan().ToArray();
var predictedValues = _predictedBuffer.GetSpan().ToArray();
double actualMean = actualValues.Average();
double sumAbsoluteError = 0;
double sumAbsoluteDifferenceFromMean = 0;
for (int i = 0; i < _actualBuffer.Count; i++)
{
sumAbsoluteError += Math.Abs(actualValues[i] - predictedValues[i]);
sumAbsoluteDifferenceFromMean += Math.Abs(actualValues[i] - actualMean);
}
if (sumAbsoluteDifferenceFromMean != 0)
{
rae = sumAbsoluteError / sumAbsoluteDifferenceFromMean;
}
}
IsHot = _index >= WarmupPeriod;
return rae;
}
/// <summary>
/// Calculates the Relative Absolute Error 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 Relative Absolute Error.</returns>
public double Calc(double actual, double predicted)
{
Input = new TValue(DateTime.Now, actual);
Input2 = new TValue(DateTime.Now, predicted);
return Calculation();
}
}