namespace QuanTAlib; /// /// Represents a Mean Error calculator that measures the average difference /// between actual values and predicted values. /// /// /// The Me class calculates the Mean Error using a circular buffer /// to efficiently manage the data points within the specified period. /// public class Me : AbstractBase { private readonly CircularBuffer _actualBuffer; private readonly CircularBuffer _predictedBuffer; /// /// Initializes a new instance of the Me class with the specified period. /// /// The period over which to calculate the Mean Error. /// /// Thrown when period is less than 1. /// public Me(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 = $"Me(period={period})"; Init(); } /// /// Initializes a new instance of the Mape class with the specified source and period. /// /// The source object to subscribe to for value updates. /// The period over which to calculate the Mean Absolute Percentage Error. public Me(object source, int period) : this(period) { var pubEvent = source.GetType().GetEvent("Pub"); pubEvent?.AddEventHandler(source, new ValueSignal(Sub)); } /// /// Initializes the Me instance by clearing the buffers. /// public override void Init() { base.Init(); _actualBuffer.Clear(); _predictedBuffer.Clear(); } /// /// Manages the state of the Me instance based on whether new values are being processed. /// /// Indicates whether the current inputs are new values. protected override void ManageState(bool isNew) { if (isNew) { _lastValidValue = Input.Value; _index++; } } /// /// Performs the Mean Error calculation for the current period. /// /// /// The calculated Mean Error value for the current period. /// /// /// This method calculates the Mean Error using the formula: /// ME = sum(actual - predicted) / n /// where actual is each actual value, predicted is each predicted value, and n is the number of values. /// 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 me = 0; if (_actualBuffer.Count > 0) { var actualValues = _actualBuffer.GetSpan().ToArray(); var predictedValues = _predictedBuffer.GetSpan().ToArray(); double sumError = 0; for (int i = 0; i < _actualBuffer.Count; i++) { sumError += actualValues[i] - predictedValues[i]; } me = sumError / _actualBuffer.Count; } IsHot = _index >= WarmupPeriod; return me; } /// /// Calculates the Mean Error for the given actual and predicted values. /// /// The actual value. /// The predicted value. /// The calculated Mean Error. public double Calc(double actual, double predicted) { Input = new TValue(DateTime.Now, actual); Input2 = new TValue(DateTime.Now, predicted); return Calculation(); } }