GURLS_EXPORT void svd(const gMat2D<float>& A, gMat2D<float>& U, gVec<float>& W, gMat2D<float>& Vt)
{
float* Ubuf;
float* Sbuf;
float* Vtbuf;
int Urows, Ucols;
int Slen;
int Vtrows, Vtcols;
gurls::svd(A.getData(), Ubuf, Sbuf, Vtbuf,
A.rows(), A.cols(),
Urows, Ucols, Slen, Vtrows, Vtcols);
U.resize(Urows, Ucols);
copy(U.getData(), Ubuf, U.getSize());
W.resize(Slen);
copy(W.getData(), Sbuf, Slen);
Vt.resize(Vtrows, Vtcols);
copy(Vt.getData(), Vtbuf, Vt.getSize());
delete [] Ubuf;
delete [] Sbuf;
delete [] Vtbuf;
}
GURLS_EXPORT void eig(const gMat2D<float>& A, gVec<float>& Wr, gVec<float>& Wi)
{
if (A.cols() != A.rows())
throw gException("The input matrix A must be squared");
float* Atmp = new float[A.getSize()];
copy(Atmp, A.getData(), A.getSize());
char jobvl = 'N', jobvr = 'N';
int n = A.cols(), lda = A.cols(), ldvl = 1, ldvr = 1;
int info, lwork = 4*n;
float* work = new float[lwork];
sgeev_(&jobvl, &jobvr, &n, Atmp, &lda, Wr.getData(), Wi.getData(), NULL, &ldvl, NULL, &ldvr, work, &lwork, &info);
delete[] Atmp;
delete[] work;
if(info != 0)
{
std::stringstream str;
str << "Eigenvalues/eigenVectors computation failed, error code " << info << ";" << std::endl;
throw gException(str.str());
}
}
GURLS_EXPORT void cholesky(const gMat2D<float>& A, gMat2D<float>& L, bool upper)
{
float* chol = cholesky<float>(A.getData(), A.rows(), A.cols(), upper);
copy(L.getData(), chol, A.getSize());
delete [] chol;
}
void RecursiveRLSCholUpdateWrapper<T>::update(const gMat2D<T> &X, const gMat2D<T> &y)
{
if(!this->trainedModel())
throw gException("Error, Train Model First");
RLSPrimalRecUpdateCholesky<T> optimizer;
const unsigned long d = X.getSize();
const unsigned long t = y.getSize();
gMat2D<T>X_mat(1, d);
copy(X_mat.getData(), X.getData(), d);
gMat2D<T>y_mat(1, t);
copy(y_mat.getData(), y.getData(), t);
GurlsOptionsList* ret = optimizer.execute(X_mat, y_mat, *(this->opt));
this->opt->removeOpt("optimizer");
this->opt->addOpt("optimizer", ret);
}
