/* nag_lapacklin_dgesvx (f07abc) Example Program.
*
* Copyright 2022 Numerical Algorithms Group.
*
* Mark 28.4, 2022.
*/
#include <nag.h>
#include <stdio.h>
int main(void) {
/* Scalars */
double growth_factor, rcond;
Integer exit_status = 0, i, j, n, nrhs, pda, pdaf, pdb, pdx;
/* Arrays */
double *a = 0, *af = 0, *b = 0, *berr = 0, *c = 0, *ferr = 0;
double *r = 0, *x = 0;
Integer *ipiv = 0;
/* Nag Types */
NagError fail;
Nag_OrderType order;
Nag_EquilibrationType equed;
#ifdef NAG_COLUMN_MAJOR
#define A(I, J) a[(J - 1) * pda + I - 1]
#define B(I, J) b[(J - 1) * pdb + I - 1]
order = Nag_ColMajor;
#else
#define A(I, J) a[(I - 1) * pda + J - 1]
#define B(I, J) b[(I - 1) * pdb + J - 1]
order = Nag_RowMajor;
#endif
INIT_FAIL(fail);
printf("nag_lapacklin_dgesvx (f07abc) Example Program Results\n\n");
/* Skip heading in data file */
scanf("%*[^\n]");
scanf("%" NAG_IFMT "%" NAG_IFMT "%*[^\n]", &n, &nrhs);
if (n < 0 || nrhs < 0) {
printf("Invalid n or nrhs\n");
exit_status = 1;
return exit_status;
}
pda = n;
pdaf = n;
#ifdef NAG_COLUMN_MAJOR
pdb = n;
pdx = n;
#else
pdb = nrhs;
pdx = nrhs;
#endif
/* Allocate memory */
if (!(a = NAG_ALLOC(n * n, double)) || !(af = NAG_ALLOC(n * n, double)) ||
!(b = NAG_ALLOC(n * n, double)) || !(berr = NAG_ALLOC(n, double)) ||
!(c = NAG_ALLOC(n, double)) || !(ferr = NAG_ALLOC(n, double)) ||
!(r = NAG_ALLOC(n, double)) || !(x = NAG_ALLOC(n * n, double)) ||
!(ipiv = NAG_ALLOC(n, Integer))) {
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* Read A and B from data file */
for (i = 1; i <= n; ++i)
for (j = 1; j <= n; ++j)
scanf("%lf", &A(i, j));
scanf("%*[^\n] ");
for (i = 1; i <= n; ++i)
for (j = 1; j <= nrhs; ++j)
scanf("%lf", &B(i, j));
scanf("%*[^\n] ");
/* Solve the equations AX = B for X using
* nag_lapacklin_dgesvx (f07abc)
*/
nag_lapacklin_dgesvx(order, Nag_EquilibrateAndFactor, Nag_NoTrans, n, nrhs, a,
pda, af, pdaf, ipiv, &equed, r, c, b, pdb, x, pdx,
&rcond, ferr, berr, &growth_factor, &fail);
if (fail.code != NE_NOERROR && fail.code != NE_SINGULAR) {
printf("Error from nag_lapacklin_dgesvx (f07abc).\n%s\n", fail.message);
exit_status = 1;
goto END;
}
/* Print solution using
* nag_file_print_matrix_real_gen (x04cac)
*/
fflush(stdout);
nag_file_print_matrix_real_gen(order, Nag_GeneralMatrix, Nag_NonUnitDiag, n,
nrhs, x, pdx, "Solution(s)", 0, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_file_print_matrix_real_gen (x04cac).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}
/* Print error bounds, condition number, the form of equilibration
* and the pivot growth factor
*/
printf("\nBackward errors (machine-dependent)\n");
for (j = 1; j <= nrhs; ++j)
printf("%11.1e%s", berr[j - 1], j % 7 == 0 || j == nrhs ? "\n" : " ");
printf("\n\nEstimated forward error bounds (machine-dependent)\n");
for (j = 1; j <= nrhs; ++j)
printf("%11.1e%s", ferr[j - 1], j % 7 == 0 || j == nrhs ? "\n" : " ");
printf("\n");
if (equed == Nag_NoEquilibration)
printf("A has not been equilibrated\n");
else if (equed == Nag_RowEquilibration)
printf("A has been row scaled as diag(R)*A\n");
else if (equed == Nag_ColumnEquilibration)
printf("A has been column scaled as A*diag(C)\n");
else if (equed == Nag_RowAndColumnEquilibration)
printf("A has been row and column scaled as diag(R)*A*diag(C)\n");
printf("\nReciprocal condition number estimate of scaled matrix\n");
printf("%11.1e\n\n", rcond);
printf("Estimate of reciprocal pivot growth factor\n");
printf("%11.1e\n", growth_factor);
if (fail.code == NE_SINGULAR) {
printf("Error from nag_lapacklin_dgesvx (f07abc).\n%s\n", fail.message);
exit_status = 1;
}
END:
NAG_FREE(a);
NAG_FREE(af);
NAG_FREE(b);
NAG_FREE(berr);
NAG_FREE(c);
NAG_FREE(ferr);
NAG_FREE(r);
NAG_FREE(x);
NAG_FREE(ipiv);
return exit_status;
}
#undef B
#undef A