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Class optimization

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Miha
2024-10-27 16:11:08 -07:00
parent b2fcdda785
commit 6c67a0cf31
77 changed files with 2634 additions and 1455 deletions
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lib/errors/Mase.cs
+13 -4
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@@ -1,4 +1,4 @@
using System;
using System.Runtime.CompilerServices;
namespace QuanTAlib;
/// <summary>
@@ -29,7 +29,8 @@ namespace QuanTAlib;
/// https://robjhyndman.com/papers/another-look-at-measures-of-forecast-accuracy/
/// </remarks>
public class Mase : AbstractBase
[SkipLocalsInit]
public sealed class Mase : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
@@ -37,6 +38,7 @@ public class Mase : AbstractBase
/// <param name="period">The number of points over which to calculate the MASE.</param>
/// <exception cref="ArgumentOutOfRangeException">Thrown when period is less than 1.</exception>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public Mase(int period)
{
if (period < 1)
@@ -53,12 +55,14 @@ public class Mase : AbstractBase
/// <param name="source">The data source object that publishes updates.</param>
/// <param name="period">The number of points over which to calculate the MASE.</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public Mase(object source, int period) : this(period)
{
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override void Init()
{
base.Init();
@@ -67,6 +71,7 @@ public class Mase : AbstractBase
_naiveBuffer.Clear();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override void ManageState(bool isNew)
{
if (isNew)
@@ -76,6 +81,7 @@ public class Mase : AbstractBase
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
protected override double Calculation()
{
ManageState(Input.IsNew);
@@ -103,6 +109,7 @@ public class Mase : AbstractBase
/// Calculates the MASE value by comparing forecast error to naive forecast error.
/// </summary>
/// <returns>The calculated MASE value, or positive infinity if naive error is zero.</returns>
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private double CalculateMase()
{
if (_actualBuffer.Count <= 1) return 0;
@@ -112,14 +119,15 @@ public class Mase : AbstractBase
ReadOnlySpan<double> naiveValues = _naiveBuffer.GetSpan();
double sumAbsoluteError = CalculateSumAbsoluteError(actualValues, predictedValues);
double _naiveForecastError = CalculateNaiveForecastError(actualValues, naiveValues);
double naiveForecastError = CalculateNaiveForecastError(actualValues, naiveValues);
return _naiveForecastError != 0 ? (sumAbsoluteError / _actualBuffer.Count) / _naiveForecastError : double.PositiveInfinity;
return naiveForecastError != 0 ? (sumAbsoluteError / _actualBuffer.Count) / naiveForecastError : double.PositiveInfinity;
}
/// <summary>
/// Calculates the sum of absolute errors between actual and predicted values.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private static double CalculateSumAbsoluteError(ReadOnlySpan<double> actualValues, ReadOnlySpan<double> predictedValues)
{
double sum = 0;
@@ -133,6 +141,7 @@ public class Mase : AbstractBase
/// <summary>
/// Calculates the naive forecast error using the previous value as prediction.
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private static double CalculateNaiveForecastError(ReadOnlySpan<double> actualValues, ReadOnlySpan<double> naiveValues)
{
double sum = 0;