/* nag_lapackeig_zgesdd (f08krc) Example Program.
*
* Copyright 2022 Numerical Algorithms Group.
*
* Mark 28.3, 2022.
*/
#include <math.h>
#include <nag.h>
#include <stdio.h>
int main(void) {
/* Scalars */
Complex alpha, beta;
double eps, norm, serrbd;
Integer exit_status = 0, i, j, m, minmn, n, pda, pdd, pdu, pdvt;
/* Arrays */
Complex *a = 0, *d = 0, *u = 0, *vt = 0;
double *rcondu = 0, *rcondv = 0, *s = 0, *uerrbd = 0, *verrbd = 0;
/* Nag Types */
NagError fail;
Nag_OrderType order;
#ifdef NAG_COLUMN_MAJOR
#define A(I, J) a[(J - 1) * pda + I - 1]
#define U(I, J) u[(J - 1) * pdu + I - 1]
order = Nag_ColMajor;
#else
#define A(I, J) a[(I - 1) * pda + J - 1]
#define U(I, J) u[(I - 1) * pdu + J - 1]
order = Nag_RowMajor;
#endif
INIT_FAIL(fail);
printf("nag_lapackeig_zgesdd (f08krc) Example Program Results\n\n");
/* Skip heading in data file */
scanf("%*[^\n]");
scanf("%" NAG_IFMT "%" NAG_IFMT "%*[^\n]", &m, &n);
if (m < 0 || n < 0) {
printf("Invalid m or n\n");
exit_status = 1;
goto END;
}
minmn = MIN(m, n);
/* Allocate memory */
if (!(a = NAG_ALLOC(m * n, Complex)) || !(d = NAG_ALLOC(m * n, Complex)) ||
!(vt = NAG_ALLOC(n * n, Complex)) || !(u = NAG_ALLOC(m * m, Complex)) ||
!(rcondu = NAG_ALLOC(minmn, double)) ||
!(rcondv = NAG_ALLOC(minmn, double)) || !(s = NAG_ALLOC(minmn, double)) ||
!(uerrbd = NAG_ALLOC(minmn, double)) ||
!(verrbd = NAG_ALLOC(minmn, double))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
#ifdef NAG_COLUMN_MAJOR
pda = m;
#else
pda = n;
#endif
pdd = pda;
pdu = m;
pdvt = n;
/* Read the m by n matrix A from data file. */
for (i = 1; i <= m; ++i)
for (j = 1; j <= n; ++j)
scanf(" ( %lf , %lf )", &A(i, j).re, &A(i, j).im);
scanf("%*[^\n]");
/* Copy A to D: nag_blast_zge_copy (f16tfc),
* Complex valued general matrix copy.
*/
nag_blast_zge_copy(order, Nag_NoTrans, m, n, a, pda, d, pdd, &fail);
/* nag_file_print_matrix_complex_gen_comp (x04dbc): Print matrix A */
fflush(stdout);
nag_file_print_matrix_complex_gen_comp(
order, Nag_GeneralMatrix, Nag_NonUnitDiag, m, n, a, pda, Nag_BracketForm,
"%5.2f", "Matrix A", Nag_IntegerLabels, 0, Nag_IntegerLabels, 0, 80, 0, 0,
&fail);
printf("\n");
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_complex_gen_comp (x04dbc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}
/* Compute the singular values and left and right singular vectors */
/* of A (A = U*S*(V^H), m.le.n) */
nag_lapackeig_zgesdd(order, Nag_DoAll, m, n, a, pda, s, u, pdu, vt, pdvt,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_lapackeig_zgesdd (f08krc).\n%s\n", fail.message);
exit_status = 1;
goto END;
}
/* Reconstruct A from its decomposition and subtract from original A:
* first, U <- U*S, then D <- D - U*S*V^H using
* nag_blast_zgemm (f16zac).
*/
for (i = 1; i <= m; i++)
for (j = 1; j <= minmn; j++)
U(i, j).re *= s[j - 1], U(i, j).im *= s[j - 1];
alpha = nag_complex_create(-1.0, 0.0);
beta = nag_complex_create(1.0, 0.0);
nag_blast_zgemm(order, Nag_NoTrans, Nag_NoTrans, m, n, minmn, alpha, u, pdu,
vt, pdvt, beta, d, pdd, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_blast_zgemm (f16zac).\n%s\n", fail.message);
exit_status = 1;
goto END;
}
/* Find norm of difference matrix D and print warning if it is too large.
* nag_blast_zge_norm (f16uac) using one-norm.
*/
nag_blast_zge_norm(order, Nag_OneNorm, m, n, d, pdd, &norm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_blast_zge_norm (f16uac).\n%s\n", fail.message);
exit_status = 1;
goto END;
}
/* Get the machine precision, using nag_machine_precision (x02ajc) */
eps = nag_machine_precision;
if (norm > pow(eps, 0.8)) {
printf("Norm of A-(U*S*V^H) is much greater than 0.\n"
" Schur factorization has failed.\n");
exit_status = 1;
goto END;
}
/* Print singular values and error estimates on values and vectors. */
printf("\nSingular values\n");
for (i = 0; i < minmn; ++i)
printf("%10.4f%s", s[i], i % 8 == 7 ? "\n" : " ");
printf("\n");
/* Approximate error bound for the computed singular values.
* Note that for the 2-norm, s[0] = norm(A).
*/
serrbd = eps * s[0];
/* Call nag_lapackeig_ddisna (f08flc) to estimate reciprocal condition numbers
* for the singular vectors.
*/
nag_lapackeig_ddisna(Nag_LeftSingVecs, m, n, s, rcondu, &fail);
nag_lapackeig_ddisna(Nag_RightSingVecs, m, n, s, rcondv, &fail);
/* Compute the error estimates for the singular vectors */
for (i = 0; i < m; ++i) {
uerrbd[i] = serrbd / rcondu[i];
verrbd[i] = serrbd / rcondv[i];
}
printf("\nError estimate for the singular values\n%11.1e\n", serrbd);
printf("\nError estimates for the left singular vectors\n");
for (i = 0; i < m; ++i)
printf(" %10.1e%s", uerrbd[i], i % 6 == 5 ? "\n" : "");
printf("\n\nError estimates for the right singular vectors\n");
for (i = 0; i < m; ++i)
printf(" %10.1e%s", verrbd[i], i % 6 == 5 ? "\n" : "");
printf("\n");
END:
NAG_FREE(a);
NAG_FREE(d);
NAG_FREE(vt);
NAG_FREE(u);
NAG_FREE(rcondu);
NAG_FREE(rcondv);
NAG_FREE(s);
NAG_FREE(uerrbd);
NAG_FREE(verrbd);
return exit_status;
}
#undef A
#undef U