void mexFunction(
int nlhs, mxArray *plhs[],
int nrhs, const mxArray *prhs[] )
{ double *A, *U, *V, *VT, *S, *flag, *work, *AA;
mwIndex subs[2];
mwSize nsubs=2;
mwIndex *irS, *jcS, *iwork;
mwSize M, N, lwork, info, options, minMN, maxMN, k, j;
mwSize LDA, LDU, LDVT, nU, mVT, mS, nS;
char *jobz;
/* CHECK FOR PROPER NUMBER OF ARGUMENTS */
if (nrhs > 2){
mexErrMsgTxt("mexsvd: requires at most 2 input arguments."); }
if (nlhs > 4){
mexErrMsgTxt("mexsvd: requires at most 4 output argument."); }
/* CHECK THE DIMENSIONS */
M = mxGetM(prhs[0]);
N = mxGetN(prhs[0]);
if (mxIsSparse(prhs[0])) {
mexErrMsgTxt("mexeig: sparse matrix not allowed."); }
A = mxGetPr(prhs[0]);
LDA = M;
minMN = MIN(M,N);
maxMN = MAX(M,N);
options = 0;
if (nrhs==2) { options = (int)*mxGetPr(prhs[1]); }
if (options==0) {
/***** economical SVD ******/
jobz="S"; nU = minMN; mVT = minMN; mS = minMN; nS = minMN;
} else {
/***** full SVD ******/
jobz="A"; nU = M; mVT = N; mS = M; nS = N;
}
LDU = M;
LDVT = mVT;
/***** create return argument *****/
if (nlhs >=3) {
/***** compute singular values and vectors ******/
plhs[0] = mxCreateDoubleMatrix(M,nU,mxREAL);
U = mxGetPr(plhs[0]);
plhs[1] = mxCreateSparse(mS,nS,minMN,mxREAL);
S = mxGetPr(plhs[1]);
irS = mxGetIr(plhs[1]);
jcS = mxGetJc(plhs[1]);
plhs[2] = mxCreateDoubleMatrix(N,mVT,mxREAL);
V = mxGetPr(plhs[2]);
plhs[3] = mxCreateDoubleMatrix(1,1,mxREAL);
flag = mxGetPr(plhs[3]);
} else {
/***** compute only singular values ******/
plhs[0]= mxCreateDoubleMatrix(minMN,1,mxREAL);
S = mxGetPr(plhs[0]);
plhs[1] = mxCreateDoubleMatrix(1,1,mxREAL);
flag = mxGetPr(plhs[1]);
U = mxCalloc(M*nU,sizeof(double));
V = mxCalloc(N*mVT,sizeof(double));
jobz="N";
}
/***** Do the computations in a subroutine *****/
lwork = 4*minMN*minMN + MAX(maxMN,5*minMN*minMN+4*minMN);
work = mxCalloc(lwork,sizeof(double));
iwork = mxCalloc(8*minMN,sizeof(int));
VT = mxCalloc(mVT*N,sizeof(double));
AA = mxCalloc(M*N,sizeof(double));
memcpy(AA,mxGetPr(prhs[0]),(M*N)*sizeof(double));
dgesdd(jobz,&M,&N, AA,&LDA,S,U,&LDU,VT,&LDVT,work,&lwork,iwork, &info);
flag[0] = (double)info;
if (nlhs >= 3) {
for (k=0; k<minMN; k++) { irS[k] = k; }
jcS[0] = 0;
for (k=1; k<=nS; k++) {
if (k<minMN) { jcS[k] = k; } else { jcS[k] = minMN; }
}
for (k=0; k<mVT; k++) {
for (j=0; j<N; j++) { V[j+k*N] = VT[k+j*mVT]; }
}
}
return;
}
int main(void)
{
#define MMAX 8
#define NMAX 8
const long lda=MMAX;
long i, info, j, m, n, minmn;
double a[MMAX*NMAX], s[MMAX+NMAX], u[1], vt[1];
/* This macro allows access to a 1-d array as though
it is a 2-d array stored in column-major order,
as required by ACML C routines. */
#define A(I,J) a[((J)-1)*lda+(I)-1]
printf("ACML example: SVD of a matrix A using dgesdd\n");
printf("--------------------------------------------\n");
printf("\n");
/* Initialize matrix A */
m = 4;
n = 4;
A(1,1) = -0.57;
A(1,2) = -1.28;
A(1,3) = -0.39;
A(1,4) = 0.25;
A(2,1) = -1.93;
A(2,2) = 1.08;
A(2,3) = -0.31;
A(2,4) = -2.14;
A(3,1) = 2.30;
A(3,2) = 0.24;
A(3,3) = 0.40;
A(3,4) = -0.35;
A(4,1) = -1.93;
A(4,2) = 0.64;
A(4,3) = -0.66;
A(4,4) = 0.08;
printf("Matrix A:\n");
for (i = 1; i <= m; i++)
{
for (j = 1; j <= n; j++)
printf("%8.4f ", A(i,j));
printf("\n");
}
/* Compute singular value decomposition of A */
dgesdd('n',m,n,a,lda,s,u,1,vt,1,&info);
/* Print solution */
if (m < n)
minmn = m;
else
minmn = n;
printf("\n");
printf("Singular values of matrix A:\n");
for (i = 0; i < minmn; i++)
printf("%8.4f ", s[i]);
printf("\n");
return 0;
}