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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>
This commit is contained in:
Miha Kralj
co-authored by
Claude Opus 4.5
aider
Warp
Claude Opus 4.5
aider
Warp
parent
5bcdf8d614
commit
86fe32a682
@@ -0,0 +1,307 @@
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using System.Runtime.CompilerServices;
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using System.Runtime.InteropServices;
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namespace QuanTAlib;
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/// <summary>
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/// MdAE: Median Absolute Error
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/// </summary>
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/// <remarks>
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/// MdAE is the median of absolute errors between actual and predicted values.
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/// Unlike MAE which uses the mean, MdAE is robust to outliers.
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///
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/// Formula:
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/// MdAE = Median(|actual - predicted|)
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///
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/// Key properties:
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/// - Robust to outliers (50% breakdown point)
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/// - Same units as the original data
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/// - Less sensitive to extreme errors than MAE
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/// - MdAE = 0 indicates at least half the predictions are perfect
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Mdae : AbstractBase
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{
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private const int StackAllocThreshold = 256;
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private readonly RingBuffer _buffer;
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private readonly double[] _sortBuffer;
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[StructLayout(LayoutKind.Auto)]
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private record struct State(double LastValidActual, double LastValidPredicted, int TickCount);
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private State _state;
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private State _p_state;
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public Mdae(int period)
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{
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if (period <= 0)
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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_buffer = new RingBuffer(period);
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_sortBuffer = new double[period];
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Name = $"Mdae({period})";
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WarmupPeriod = period;
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}
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public override bool IsHot => _buffer.IsFull;
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public TValue Update(TValue actual, TValue predicted, bool isNew = true)
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{
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double actualVal = actual.Value;
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double predictedVal = predicted.Value;
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// Snapshot BEFORE any mutations for correct rollback
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if (isNew)
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{
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_p_state = _state;
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}
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else
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{
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_state = _p_state;
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}
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if (!double.IsFinite(actualVal))
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actualVal = double.IsFinite(_state.LastValidActual) ? _state.LastValidActual : 0.0;
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else
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_state.LastValidActual = actualVal;
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if (!double.IsFinite(predictedVal))
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predictedVal = double.IsFinite(_state.LastValidPredicted) ? _state.LastValidPredicted : 0.0;
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else
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_state.LastValidPredicted = predictedVal;
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double absError = Math.Abs(actualVal - predictedVal);
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if (isNew)
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{
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_buffer.Add(absError);
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_state.TickCount++;
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}
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else
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{
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_buffer.UpdateNewest(absError);
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}
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// Calculate median
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double result = CalculateMedian();
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Last = new TValue(actual.Time, result);
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PubEvent(Last, isNew);
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return Last;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public TValue Update(double actual, double predicted, bool isNew = true)
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{
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return Update(new TValue(DateTime.UtcNow, actual), new TValue(DateTime.UtcNow, predicted), isNew);
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}
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public override TValue Update(TValue input, bool isNew = true)
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{
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throw new NotSupportedException("MdAE requires two inputs. Use Update(actual, predicted).");
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}
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public override TSeries Update(TSeries source)
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{
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throw new NotSupportedException("MdAE requires two inputs. Use Calculate(actualSeries, predictedSeries, period).");
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}
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public override void Prime(ReadOnlySpan<double> source, TimeSpan? step = null)
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{
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throw new NotSupportedException("MdAE requires two inputs.");
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}
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public override void Reset()
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{
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_buffer.Clear();
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_state = default;
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_p_state = default;
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Last = default;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private double CalculateMedian()
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{
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int count = _buffer.Count;
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if (count == 0) return 0.0;
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// Copy buffer contents to sort buffer using GetSequencedSpans to handle wraparound
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_buffer.GetSequencedSpans(out var first, out var second);
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first.CopyTo(_sortBuffer.AsSpan(0, first.Length));
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if (second.Length > 0)
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{
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second.CopyTo(_sortBuffer.AsSpan(first.Length, second.Length));
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}
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// Sort the portion we copied
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Array.Sort(_sortBuffer, 0, count);
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// Calculate median
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if ((count & 1) != 0)
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{
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return _sortBuffer[count / 2];
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}
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// For even count, average the two middle elements
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int mid = count / 2;
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return (_sortBuffer[mid - 1] + _sortBuffer[mid]) * 0.5;
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}
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public static TSeries Calculate(TSeries actual, TSeries predicted, int period)
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{
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if (actual.Count != predicted.Count)
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throw new ArgumentException("Actual and predicted series must have the same length", nameof(predicted));
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int len = actual.Count;
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var t = new List<long>(len);
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var v = new List<double>(len);
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CollectionsMarshal.SetCount(t, len);
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CollectionsMarshal.SetCount(v, len);
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var tSpan = CollectionsMarshal.AsSpan(t);
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var vSpan = CollectionsMarshal.AsSpan(v);
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Batch(actual.Values, predicted.Values, vSpan, period);
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actual.Times.CopyTo(tSpan);
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return new TSeries(t, v);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static void Batch(ReadOnlySpan<double> actual, ReadOnlySpan<double> predicted, Span<double> output, int period)
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{
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if (actual.Length != predicted.Length || actual.Length != output.Length)
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throw new ArgumentException("All spans must have the same length", nameof(output));
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if (period <= 0)
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throw new ArgumentException("Period must be greater than 0", nameof(period));
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int len = actual.Length;
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if (len == 0) return;
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// Use stackalloc for small periods, heap for larger
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scoped Span<double> buffer;
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scoped Span<double> sortBuffer;
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if (period <= StackAllocThreshold)
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{
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buffer = stackalloc double[period];
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sortBuffer = stackalloc double[period];
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}
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else
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{
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buffer = new double[period];
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sortBuffer = new double[period];
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}
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double lastValidActual = 0;
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double lastValidPredicted = 0;
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(actual[k])) { lastValidActual = actual[k]; break; }
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}
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for (int k = 0; k < len; k++)
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{
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if (double.IsFinite(predicted[k])) { lastValidPredicted = predicted[k]; break; }
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}
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int bufferIndex = 0;
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int bufferCount = 0;
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for (int i = 0; i < len; i++)
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{
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double act = actual[i];
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double pred = predicted[i];
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if (double.IsFinite(act)) lastValidActual = act; else act = lastValidActual;
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if (double.IsFinite(pred)) lastValidPredicted = pred; else pred = lastValidPredicted;
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double absError = Math.Abs(act - pred);
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// Add to circular buffer
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buffer[bufferIndex] = absError;
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bufferIndex++;
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if (bufferIndex >= period) bufferIndex = 0;
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if (bufferCount < period) bufferCount++;
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// Copy and use QuickSelect for median
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buffer.Slice(0, bufferCount).CopyTo(sortBuffer);
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// Calculate median using QuickSelect
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if ((bufferCount & 1) != 0)
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{
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output[i] = QuickSelectSpan(sortBuffer.Slice(0, bufferCount), bufferCount / 2);
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continue;
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}
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int mid = bufferCount / 2;
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double upper = QuickSelectSpan(sortBuffer.Slice(0, bufferCount), mid);
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// Copy again for second selection
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buffer.Slice(0, bufferCount).CopyTo(sortBuffer);
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double lower = QuickSelectSpan(sortBuffer.Slice(0, bufferCount), mid - 1);
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output[i] = (lower + upper) * 0.5;
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}
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}
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/// <summary>
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/// QuickSelect for Span - finds the k-th smallest element in O(n) average time.
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/// Uses insertion sort for small arrays and Lomuto partition for larger arrays.
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/// </summary>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static double QuickSelectSpan(Span<double> span, int k)
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{
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int left = 0;
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int right = span.Length - 1;
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while (left < right)
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{
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// For small subarrays (<=16 elements), use insertion sort - simple and cache-friendly
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if (right - left < 16)
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{
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for (int i = left + 1; i <= right; i++)
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{
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double key = span[i];
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int j = i - 1;
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while (j >= left && span[j] > key)
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{
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span[j + 1] = span[j];
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j--;
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}
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span[j + 1] = key;
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}
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return span[k];
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}
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// Median-of-three pivot selection for better pivot choice
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int mid = left + (right - left) / 2;
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if (span[mid] < span[left]) (span[left], span[mid]) = (span[mid], span[left]);
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if (span[right] < span[left]) (span[left], span[right]) = (span[right], span[left]);
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if (span[right] < span[mid]) (span[mid], span[right]) = (span[right], span[mid]);
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// Use median as pivot, move to right-1 position
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double pivot = span[mid];
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(span[mid], span[right - 1]) = (span[right - 1], span[mid]);
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// Lomuto partition scheme (safer, no overflow risk)
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int storeIndex = left;
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for (int i = left; i < right - 1; i++)
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{
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if (span[i] < pivot)
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{
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(span[storeIndex], span[i]) = (span[i], span[storeIndex]);
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storeIndex++;
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}
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}
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(span[storeIndex], span[right - 1]) = (span[right - 1], span[storeIndex]);
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if (k == storeIndex) return span[storeIndex];
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if (k < storeIndex) right = storeIndex - 1;
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else left = storeIndex + 1;
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}
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return span[left];
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}
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}
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