/// <summary>
/// Compute L2-norm. L2-norm computation doesn't subtract the mean from the source values.
/// However, we substract the mean here in case subMean is true (if subMean is false, mean is zero).
/// </summary>
private static Float L2Norm(Float[] values, int count, Float mean = 0)
{
if (count == 0)
{
return(0);
}
return(MathUtils.Sqrt(SseUtils.SumSq(mean, values, 0, count)));
}
/// <summary>
/// Compute Standard Deviation.
/// We have two overloads of StdDev instead of one with <see cref="Nullable{Float}"/> mean for perf reasons.
/// </summary>
private static Float StdDev(Float[] values, int count, int length, Float mean)
{
Contracts.Assert(0 <= count && count <= length);
if (count == 0)
{
return(0);
}
Float sumSq = 0;
if (count != length && mean != 0)
{
// Sparse representation.
Float meanSq = mean * mean;
sumSq = (length - count) * meanSq;
}
sumSq += SseUtils.SumSq(mean, values, 0, count);
return(MathUtils.Sqrt(sumSq / length));
}
/// <summary>
/// Compute Standard Deviation. In case of both subMean and useStd are true, we technically need to compute variance
/// based on centered values (i.e. after subtracting the mean). But since the centered
/// values mean is approximately zero, we can use variance of non-centered values.
/// </summary>
private static Float StdDev(Float[] values, int count, int length)
{
Contracts.Assert(0 <= count && count <= length);
if (count == 0)
{
return(0);
}
// We need a mean to compute variance.
Float tmpMean = SseUtils.Sum(values, 0, count) / length;
Float sumSq = 0;
if (count != length && tmpMean != 0)
{
// Sparse representation.
Float meanSq = tmpMean * tmpMean;
sumSq = (length - count) * meanSq;
}
sumSq += SseUtils.SumSq(tmpMean, values, 0, count);
return(MathUtils.Sqrt(sumSq / length));
}
private static Float L2DistSquaredHalfSparse(Float[] valuesA, int lengthA, Float[] valuesB, int[] indicesB, int countB)
{
Contracts.AssertValueOrNull(valuesA);
Contracts.AssertValueOrNull(valuesB);
Contracts.AssertValueOrNull(indicesB);
Contracts.Assert(0 <= lengthA && lengthA <= Utils.Size(valuesA));
Contracts.Assert(0 <= countB && countB <= Utils.Size(indicesB));
Contracts.Assert(countB <= Utils.Size(valuesB));
var normA = SseUtils.SumSq(valuesA, 0, lengthA);
if (countB == 0)
{
return(normA);
}
var normB = SseUtils.SumSq(valuesB, 0, countB);
var dotP = SseUtils.DotProductSparse(valuesA, valuesB, indicesB, countB);
var res = normA + normB - 2 * dotP;
return(res < 0 ? 0 : res);
}
public static float SumSq(float[] src, int offset, int count) => SseUtils.SumSq(src, offset, count);
/// <summary>
/// Returns the L2 norm of the vector (sum of squares of the components).
/// </summary>
public static Float Norm(Float[] a)
{
return(MathUtils.Sqrt(SseUtils.SumSq(a, a.Length)));
}