// DO NOT EDIT INSIDE THIS REGION !! CHANGES WILL BE LOST !!
/// <summary>
/// singular value decomposition
/// </summary>
/// <param name="X">matrix X. The elements of X will not be altered.</param>
/// <param name="U">(return value) left singular vectors of X as columns of matrix U.
/// If this parameter is set, it must be not null. It might be an empty array. On return
/// it will be set to a physical array accordingly.</param>
/// <param name="V">right singular vectors of X as rows of matrix V.
/// If this parameter is set, it must be not null. It might be an empty array. On return
/// it will be set to a physical array accordingly.</param>
/// <param name="small">if true: return only first min(M,N) columns of U and S will be
/// of size [min(M,N),min(M,N)]</param>
/// <param name="discardFiniteTest">if true: the matrix given will not be checked for infinte or NaN values. If such elements
/// are contained nevertheless, this may result in failing convergence or error. In worst case
/// the function may hang inside the Lapack lib. Use with care! </param>
/// <returns>singluar values as diagonal matrix of same size as X</returns>
/// <remarks>the right singular vectors V will be returned as reference array.</remarks>
public static ILArray <float> svd(ILArray <float> X, ref ILArray <float> U, ref ILArray <float> V, bool small, bool discardFiniteTest)
{
if (!X.IsMatrix)
{
throw new ILArgumentSizeException("svd is defined for matrices only!");
}
// early exit for small matrices
if (X.Dimensions[1] < 4 && X.Dimensions[0] == X.Dimensions[1])
{
switch (X.Dimensions[0])
{
case 1:
if (!Object.Equals(U, null))
{
U = ( float )1.0;
}
if (!Object.Equals(V, null))
{
V = ( float )1.0;
}
return(new ILArray <float> (ILMath.abs(X)));
//case 2:
// return -1;
//case 3:
// return -1;
}
}
if (!discardFiniteTest && !all(all(isfinite(X))))
{
throw new ILArgumentException("svd: input must have only finite elements!");
}
if (Lapack == null)
{
throw new ILMathException("No Lapack package available.");
}
// parameter evaluation
int M = X.Dimensions[0]; int N = X.Dimensions[1];
int minMN = (M < N) ? M : N;
int LDU = M; int LDVT = N;
int LDA = M;
float [] dS = new float [minMN];
char jobz = (small) ? 'S' : 'A';
float [] dU = null;
float [] dVT = null;
int info = 0;
if (!Object.Equals(U, null) || !Object.Equals(V, null))
{
// need to return U and VT
if (small)
{
dU = new float [M * minMN];
dVT = new float [N * minMN];
}
else
{
dU = new float [M * M];
dVT = new float [N * N];
}
}
else
{
jobz = 'N';
}
if (X.IsReference)
{
X.Detach();
}
// must create copy of input !
float [] dInput = new float [X.m_data.Length];
System.Array.Copy(X.m_data, dInput, X.m_data.Length);
Lapack.sgesdd(jobz, M, N, dInput, LDA, dS, dU, LDU, dVT, LDVT, ref info);
if (info < 0)
{
throw new ILArgumentException("ILMath.svd: the " + (-info).ToString() + "th argument was invalid.");
}
if (info > 0)
{
throw new ILArgumentException("svd was not converging!");
}
ILArray <float> ret = null;
if (info == 0)
{
// success
if (!Object.Equals(U, null) || !Object.Equals(V, null))
{
if (small)
{
ret = ILArray <float> .zeros(minMN, minMN);
}
else
{
ret = ILArray <float> .zeros(M, N);
}
for (int i = 0; i < minMN; i++)
{
ret.SetValue(dS[i], i, i);
}
if (!Object.Equals(U, null))
{
U = new ILArray <float> (dU, M, dU.Length / M);
}
if (!Object.Equals(V, null))
{
V = new ILArray <float> (dVT, N, dVT.Length / N).T;
}
}
else
{
ret = new ILArray <float> (dS, minMN, 1);
}
}
return(ret);
}
