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https://github.com/mihakralj/QuanTAlib.git
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130 lines
4.6 KiB
C#
130 lines
4.6 KiB
C#
namespace QuanTAlib;
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/// <summary>
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/// Represents a Relative Absolute Error calculator that measures the ratio of the sum of absolute errors
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/// to the sum of absolute differences between actual values and the mean of actual values.
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/// </summary>
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/// <remarks>
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/// The Rae class calculates the Relative Absolute Error using circular buffers
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/// to efficiently manage the data points within the specified period.
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/// </remarks>
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public class Rae : AbstractBase
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{
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private readonly CircularBuffer _actualBuffer;
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private readonly CircularBuffer _predictedBuffer;
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/// <summary>
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/// Initializes a new instance of the Rae class with the specified period.
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/// </summary>
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/// <param name="period">The period over which to calculate the Relative Absolute Error.</param>
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/// <exception cref="ArgumentOutOfRangeException">
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/// Thrown when period is less than 2.
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/// </exception>
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public Rae(int period)
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{
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if (period < 2)
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{
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throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 2.");
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}
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WarmupPeriod = period;
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_actualBuffer = new CircularBuffer(period);
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_predictedBuffer = new CircularBuffer(period);
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Name = $"Rae(period={period})";
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Init();
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}
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/// <summary>
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/// Initializes a new instance of the Mape class with the specified source and period.
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/// </summary>
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/// <param name="source">The source object to subscribe to for value updates.</param>
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/// <param name="period">The period over which to calculate the Mean Absolute Percentage Error.</param>
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public Rae(object source, int period) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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/// <summary>
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/// Initializes the Rae instance by clearing the buffers.
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/// </summary>
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public override void Init()
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{
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base.Init();
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_actualBuffer.Clear();
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_predictedBuffer.Clear();
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}
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/// <summary>
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/// Manages the state of the Rae instance based on whether new values are being processed.
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/// </summary>
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/// <param name="isNew">Indicates whether the current inputs are new values.</param>
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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}
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}
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/// <summary>
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/// Performs the Relative Absolute Error calculation for the current period.
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/// </summary>
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/// <returns>
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/// The calculated Relative Absolute Error value for the current period.
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/// </returns>
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/// <remarks>
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/// This method calculates the Relative Absolute Error using the formula:
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/// RAE = sum(|actual - predicted|) / sum(|actual - mean(actual)|)
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/// where actual is each actual value, predicted is each predicted value, and mean(actual) is the average of actual values.
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/// </remarks>
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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double actual = Input.Value;
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_actualBuffer.Add(actual, Input.IsNew);
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double predicted = double.IsNaN(Input2.Value) ? _actualBuffer.Average() : Input2.Value;
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_predictedBuffer.Add(predicted, Input.IsNew);
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double rae = 0;
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if (_actualBuffer.Count >= 2)
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{
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var actualValues = _actualBuffer.GetSpan().ToArray();
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var predictedValues = _predictedBuffer.GetSpan().ToArray();
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double actualMean = actualValues.Average();
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double sumAbsoluteError = 0;
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double sumAbsoluteDifferenceFromMean = 0;
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for (int i = 0; i < _actualBuffer.Count; i++)
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{
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sumAbsoluteError += Math.Abs(actualValues[i] - predictedValues[i]);
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sumAbsoluteDifferenceFromMean += Math.Abs(actualValues[i] - actualMean);
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}
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if (sumAbsoluteDifferenceFromMean != 0)
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{
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rae = sumAbsoluteError / sumAbsoluteDifferenceFromMean;
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}
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}
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IsHot = _index >= WarmupPeriod;
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return rae;
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}
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/// <summary>
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/// Calculates the Relative Absolute Error for the given actual and predicted values.
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/// </summary>
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/// <param name="actual">The actual value.</param>
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/// <param name="predicted">The predicted value.</param>
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/// <returns>The calculated Relative Absolute Error.</returns>
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public double Calc(double actual, double predicted)
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{
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Input = new TValue(DateTime.Now, actual);
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Input2 = new TValue(DateTime.Now, predicted);
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return Calculation();
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}
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}
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