gavindiaz/QuanTAlib
1
0
Fork 0
mirror of https://github.com/mihakralj/QuanTAlib.git synced 2026-08-15 00:58:04 +00:00
Code Issues Packages Projects Releases Wiki Activity

Class optimization

Browse Source
This commit is contained in:
Miha
2024-10-27 16:11:08 -07:00
parent b2fcdda785
commit 6c67a0cf31
77 changed files with 2634 additions and 1455 deletions
Download Patch File Download Diff File Expand all files Collapse all files
lib/errors/Rsquared.cs
+24 -15
View File
@@ -1,5 +1,4 @@
using System;
using System.Linq;
using System.Runtime.CompilerServices;
namespace QuanTAlib;
/// <summary>
@@ -31,13 +30,15 @@ namespace QuanTAlib;
/// Note: Can be negative if predictions are worse than using the mean
/// </remarks>
public class Rsquared : AbstractBase
[SkipLocalsInit]
public sealed class Rsquared : AbstractBase
{
private readonly CircularBuffer _actualBuffer;
private readonly CircularBuffer _predictedBuffer;
/// <param name="period">The number of points over which to calculate the R-squared value.</param>
/// <exception cref="ArgumentOutOfRangeException">Thrown when period is less than 1.</exception>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public Rsquared(int period)
{
if (period < 1)
@@ -53,12 +54,14 @@ public class Rsquared : AbstractBase
/// <param name="source">The data source object that publishes updates.</param>
/// <param name="period">The number of points over which to calculate the R-squared value.</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public Rsquared(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();
@@ -66,6 +69,7 @@ public class Rsquared : AbstractBase
_predictedBuffer.Clear();
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override void ManageState(bool isNew)
{
if (isNew)
@@ -75,6 +79,15 @@ public class Rsquared : AbstractBase
}
}
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
private static (double squaredResidual, double squaredTotal) CalculateSquaredErrors(double actual, double predicted, double meanActual)
{
double deviation = actual - meanActual;
double error = actual - predicted;
return (error * error, deviation * deviation);
}
[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
protected override double Calculation()
{
ManageState(Input.IsNew);
@@ -89,25 +102,21 @@ public class Rsquared : AbstractBase
double rsquared = 0;
if (_actualBuffer.Count > 0)
{
var actualValues = _actualBuffer.GetSpan().ToArray();
var predictedValues = _predictedBuffer.GetSpan().ToArray();
ReadOnlySpan<double> actualValues = _actualBuffer.GetSpan();
ReadOnlySpan<double> predictedValues = _predictedBuffer.GetSpan();
double meanActual = actualValues.Average();
double meanActual = _actualBuffer.Average();
double sumSquaredTotal = 0;
double sumSquaredResidual = 0;
for (int i = 0; i < _actualBuffer.Count; i++)
for (int i = 0; i < actualValues.Length; i++)
{
double deviation = actualValues[i] - meanActual;
sumSquaredTotal += deviation * deviation;
double error = actualValues[i] - predictedValues[i];
sumSquaredResidual += error * error;
var (squaredResidual, squaredTotal) = CalculateSquaredErrors(actualValues[i], predictedValues[i], meanActual);
sumSquaredResidual += squaredResidual;
sumSquaredTotal += squaredTotal;
}
if (sumSquaredTotal != 0)
{
rsquared = 1 - (sumSquaredResidual / sumSquaredTotal);
}
rsquared = sumSquaredTotal != 0 ? 1 - (sumSquaredResidual / sumSquaredTotal) : 0;
}
IsHot = _index >= WarmupPeriod;