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Miha Kralj
2026-01-25 16:01:45 -08:00
parent 2836f253c4
commit e59665c8f0
399 changed files with 6892 additions and 1323 deletions
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lib/statistics/covariance/Covariance.Simd.Tests.cs
+9 -2
View File
@@ -82,8 +82,15 @@ public class CovarianceSimdTests
{
double x = dataX[i];
double y = dataY[i];
if (!double.IsFinite(x)) x = 0;
if (!double.IsFinite(y)) y = 0;
if (!double.IsFinite(x))
{
x = 0;
}
if (!double.IsFinite(y))
{
y = 0;
}
var res = scalarCov.Update(x, y);
Assert.Equal(res.Value, result.Values[i], precision: 9);
lib/statistics/covariance/Covariance.cs
+56 -12
View File
@@ -182,7 +182,9 @@ public sealed class Covariance : AbstractBase
public static TSeries Calculate(TSeries sourceX, TSeries sourceY, int period, bool isPopulation = false)
{
if (sourceX.Count != sourceY.Count)
{
throw new ArgumentException("Source series must have the same length", nameof(sourceY));
}
int len = sourceX.Count;
var t = new List<long>(len);
@@ -203,12 +205,20 @@ public sealed class Covariance : AbstractBase
public static void Batch(ReadOnlySpan<double> sourceX, ReadOnlySpan<double> sourceY, Span<double> output, int period, bool isPopulation = false)
{
if (sourceX.Length != sourceY.Length || sourceX.Length != output.Length)
{
throw new ArgumentException("All spans must have the same length", nameof(output));
}
if (period < 2)
{
throw new ArgumentException("Period must be greater than or equal to 2", nameof(period));
}
int len = sourceX.Length;
if (len == 0) return;
if (len == 0)
{
return;
}
// SIMD overhead amortizes well for datasets >= 256 elements
const int SimdThreshold = 256;
@@ -242,8 +252,15 @@ public sealed class Covariance : AbstractBase
{
double x = sourceX[i];
double y = sourceY[i];
if (!double.IsFinite(x)) x = 0;
if (!double.IsFinite(y)) y = 0;
if (!double.IsFinite(x))
{
x = 0;
}
if (!double.IsFinite(y))
{
y = 0;
}
sumX += x;
sumY += y;
@@ -270,8 +287,15 @@ public sealed class Covariance : AbstractBase
{
double x = sourceX[i];
double y = sourceY[i];
if (!double.IsFinite(x)) x = 0;
if (!double.IsFinite(y)) y = 0;
if (!double.IsFinite(x))
{
x = 0;
}
if (!double.IsFinite(y))
{
y = 0;
}
double oldX = bufferX[bufferIndex];
double oldY = bufferY[bufferIndex];
@@ -283,7 +307,10 @@ public sealed class Covariance : AbstractBase
bufferX[bufferIndex] = x;
bufferY[bufferIndex] = y;
bufferIndex++;
if (bufferIndex >= period) bufferIndex = 0;
if (bufferIndex >= period)
{
bufferIndex = 0;
}
double n = period;
double numerator = sumXY - (sumX * sumY) / n;
@@ -357,7 +384,10 @@ public sealed class Covariance : AbstractBase
(double sumX, double sumY, double sumXY) = WarmupCovariance(period, len, isPopulation, ref srcXRef, ref srcYRef, ref outRef);
if (len <= period) return;
if (len <= period)
{
return;
}
var vInvN = Vector256.Create(invN);
var vInvDenom = Vector256.Create(invDenom);
@@ -452,13 +482,27 @@ public sealed class Covariance : AbstractBase
{
double x = Unsafe.Add(ref srcXRef, i);
double y = Unsafe.Add(ref srcYRef, i);
if (!double.IsFinite(x)) x = 0;
if (!double.IsFinite(y)) y = 0;
if (!double.IsFinite(x))
{
x = 0;
}
if (!double.IsFinite(y))
{
y = 0;
}
double oldX = Unsafe.Add(ref srcXRef, i - period);
double oldY = Unsafe.Add(ref srcYRef, i - period);
if (!double.IsFinite(oldX)) oldX = 0;
if (!double.IsFinite(oldY)) oldY = 0;
if (!double.IsFinite(oldX))
{
oldX = 0;
}
if (!double.IsFinite(oldY))
{
oldY = 0;
}
sumX = sumX - oldX + x;
sumY = sumY - oldY + y;
@@ -468,4 +512,4 @@ public sealed class Covariance : AbstractBase
Unsafe.Add(ref outRef, i) = numerator * invDenom;
}
}
}
}