tests and cleanup

2026-08-20 11:38:05 +00:00 · 2024-10-11 18:02:09 -07:00
parent 839313c9f2
commit cc45cebeb4
96 changed files with 3640 additions and 327 deletions
@@ -0,0 +1,132 @@
+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();
+    }
+}