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Miha Kralj
2024-10-13 17:18:31 -07:00
parent 2236f5f483
commit bbefc72d73
65 changed files with 669 additions and 1087 deletions
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lib/errors/Msle.cs
+2 -54
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@@ -1,25 +1,10 @@
namespace QuanTAlib;
/// <summary>
/// Represents a Mean Squared Logarithmic Error calculator that measures the average of the squares
/// of the differences between the logarithms of actual values and predicted values.
/// </summary>
/// <remarks>
/// The Msle class calculates the Mean Squared Logarithmic Error using a circular buffer
/// to efficiently manage the data points within the specified period.
/// </remarks>
public class Msle : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
/// <summary>
/// Initializes a new instance of the Msle class with the specified period.
/// </summary>
/// <param name="period">The period over which to calculate the Mean Squared Logarithmic Error.</param>
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 1.
/// </exception>
public Msle(int period)
{
if (period < 1)
@@ -33,20 +18,12 @@ public class Msle : AbstractBase
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 Msle(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
/// <summary>
/// Initializes the Msle instance by clearing the buffers.
/// </summary>
public override void Init()
{
base.Init();
@@ -54,10 +31,6 @@ public class Msle : AbstractBase
_predictedBuffer.Clear();
}
/// <summary>
/// Manages the state of the Msle 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)
@@ -67,18 +40,6 @@ public class Msle : AbstractBase
}
}
/// <summary>
/// Performs the Mean Squared Logarithmic Error calculation for the current period.
/// </summary>
/// <returns>
/// The calculated Mean Squared Logarithmic Error value for the current period.
/// </returns>
/// <remarks>
/// This method calculates the Mean Squared Logarithmic Error using the formula:
/// MSLE = sum((log(actual + 1) - log(predicted + 1))^2) / n
/// where actual is each actual value, predicted is each predicted value, and n is the number of values.
/// We add 1 to both actual and predicted values to avoid taking the log of zero.
/// </remarks>
protected override double Calculation()
{
ManageState(Input.IsNew);
@@ -100,8 +61,8 @@ public class Msle : AbstractBase
{
double logActual = Math.Log(actualValues[i] + 1);
double logPredicted = Math.Log(predictedValues[i] + 1);
double logError = logActual - logPredicted;
sumSquaredLogError += logError * logError;
double error = logActual - logPredicted;
sumSquaredLogError += error * error;
}
msle = sumSquaredLogError / _actualBuffer.Count;
@@ -110,17 +71,4 @@ public class Msle : AbstractBase
IsHot = _index >= WarmupPeriod;
return msle;
}
/// <summary>
/// Calculates the Mean Squared Logarithmic 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 Mean Squared Logarithmic Error.</returns>
public double Calc(double actual, double predicted)
{
Input = new TValue(DateTime.Now, actual);
Input2 = new TValue(DateTime.Now, predicted);
return Calculation();
}
}