Files
QuanTAlib/lib/errors/mae/Mae.cs
T
Miha Kralj 86fe32a682 SIMD Refactor: Merge simd-dev into dev (#55)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>
2026-01-18 19:02:03 -08:00

89 lines
3.2 KiB
C#

using System.Buffers;
using System.Runtime.CompilerServices;
namespace QuanTAlib;
/// <summary>
/// MAE: Mean Absolute Error
/// </summary>
/// <remarks>
/// MAE measures the average magnitude of errors between paired observations,
/// without considering their direction. It is the mean of the absolute differences
/// between actual and predicted values.
///
/// Formula:
/// MAE = (1/n) * Σ|actual - predicted|
///
/// Uses a RingBuffer for O(1) streaming updates with running sum.
///
/// Key properties:
/// - Always non-negative (MAE ≥ 0)
/// - Same units as the original data
/// - Less sensitive to outliers than MSE/RMSE
/// - MAE = 0 indicates perfect prediction
/// </remarks>
[SkipLocalsInit]
public sealed class Mae : BiInputIndicatorBase
{
/// <summary>
/// Creates MAE with specified period.
/// </summary>
/// <param name="period">Number of values to average (must be > 0)</param>
public Mae(int period) : base(period, $"Mae({period})") { }
/// <summary>
/// Computes absolute error: |actual - predicted|
/// </summary>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
protected override double ComputeError(double actual, double predicted)
=> Math.Abs(actual - predicted);
/// <summary>
/// Calculates MAE for the entire series pair.
/// </summary>
/// <param name="actual">Actual values series</param>
/// <param name="predicted">Predicted values series</param>
/// <param name="period">MAE period</param>
/// <returns>MAE series</returns>
public static TSeries Calculate(TSeries actual, TSeries predicted, int period)
=> CalculateImpl(actual, predicted, period, Batch);
/// <summary>
/// Calculates MAE in-place using pre-allocated spans.
/// Uses SIMD acceleration when available.
/// </summary>
/// <param name="actual">Actual values</param>
/// <param name="predicted">Predicted values</param>
/// <param name="output">Output span (must be same length as inputs)</param>
/// <param name="period">MAE period (must be > 0)</param>
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Batch(ReadOnlySpan<double> actual, ReadOnlySpan<double> predicted, Span<double> output, int period)
{
ValidateBatchInputs(actual, predicted, output, period);
if (actual.Length == 0) return;
// Allocate temporary buffer for absolute errors
const int StackAllocThreshold = 256;
int len = actual.Length;
if (len <= StackAllocThreshold)
{
Span<double> absErrors = stackalloc double[len];
ErrorHelpers.ComputeAbsoluteErrors(actual, predicted, absErrors);
ErrorHelpers.ApplyRollingMean(absErrors, output, period);
}
else
{
double[] rented = ArrayPool<double>.Shared.Rent(len);
try
{
Span<double> absErrors = rented.AsSpan(0, len);
ErrorHelpers.ComputeAbsoluteErrors(actual, predicted, absErrors);
ErrorHelpers.ApplyRollingMean(absErrors, output, period);
}
finally
{
ArrayPool<double>.Shared.Return(rented);
}
}
}
}