/* nag_opt_handle_set_linmatineq (e04rnc) Example Program.
*
* Copyright 2019 Numerical Algorithms Group.
*
* Mark 27.0, 2019.
*/
/* Compute E-optimal experiment design via semidefinite programming,
* this can be done as follows
* max {lambda_min(A) | A = sum x_i*v_i*v_i^T, x_i>=0, sum x_i = 1}
* where v_i are given vectors.
*/
#include <stdio.h>
#include <nag.h>
int main(void)
{
const double big = 1e+20;
const double tol = 0.00001;
Integer exit_status = 0;
Integer dima, i, idlc, idblk, idx, inform, j, k, m, nblk, nnzasum, nnzb,
nnzu, nnzua, nnzuc, nvar, p;
double blb[1], bub[1], c[1], rinfo[32], stats[32];
Integer idxc[1];
double *a = 0, *b = 0, *bl = 0, *bu = 0, *v = 0, *x = 0;
Integer *icola = 0, *icolb = 0, *irowa = 0, *irowb = 0, *nnza = 0;
void *handle = 0;
/* Nag Types */
NagError fail;
#define V(I,J) v[((I)-1)*p + (J)-1]
printf("nag_opt_handle_set_linmatineq (e04rnc) Example Program Results\n\n");
fflush(stdout);
/* Skip heading in data file. */
scanf("%*[^\n]");
/* Read in the number of vectors and their size. */
scanf("%" NAG_IFMT "%*[^\n]", &m);
scanf("%" NAG_IFMT "%*[^\n]", &p);
/* Allocate memory for the vectors and read them in. */
if (!(v = NAG_ALLOC(m * p, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
for (i = 1; i <= m; i++)
for (j = 1; j <= p; j++)
scanf("%lf", &V(i, j));
scanf("%*[^\n]");
/* Variables of the problem will be x_1, ..., x_m (weights of the vectors)
* and t (artificial variable for minimum eigenvalue). */
nvar = m + 1;
/* nag_opt_handle_init (e04rac).
* Initialize an empty problem handle with NVAR variables. */
nag_opt_handle_init(&handle, nvar, NAGERR_DEFAULT);
/* nag_opt_handle_set_quadobj (e04rfc).
* Add the objective function to the handle: max t. */
idxc[0] = m + 1;
c[0] = 1.0;
nag_opt_handle_set_quadobj(handle, 1, idxc, c, 0, NULL, NULL, NULL,
NAGERR_DEFAULT);
if (!(bl = NAG_ALLOC(nvar, double)) || !(bu = NAG_ALLOC(nvar, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* nag_opt_handle_set_simplebounds (e04rhc).
* Add simple bounds on variables to the problem formulation. */
for (i = 0; i < m; i++)
bl[i] = 0.0;
bl[m] = -big;
for (i = 0; i <= m; i++)
bu[i] = big;
nag_opt_handle_set_simplebounds(handle, nvar, bl, bu, NAGERR_DEFAULT);
/* Create linear constraint: sum x_i = 1. */
nnzb = m;
if (!(irowb = NAG_ALLOC(nnzb, Integer)) ||
!(icolb = NAG_ALLOC(nnzb, Integer)) || !(b = NAG_ALLOC(nnzb, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
for (i = 0; i < m; i++) {
/* irowb, icolb use 1-based indices */
irowb[i] = 1;
icolb[i] = i + 1;
b[i] = 1.0;
}
blb[0] = 1.0;
bub[0] = 1.0;
idlc = 0;
/* nag_opt_handle_set_linconstr (e04rjc).
* Add the linear constraint to the problem formulation. */
nag_opt_handle_set_linconstr(handle, 1, blb, bub, nnzb, irowb, icolb, b,
&idlc, NAGERR_DEFAULT);
/* Generate matrix constraint as:
* sum_{i=1}^m x_i*v_i*v_i^T - t*I >=0 */
nblk = 1;
idblk = 0;
dima = p;
/* Total number of nonzeros */
nnzasum = p + m * (p + 1) * p / 2;
if (!(nnza = NAG_ALLOC(nvar + 1, Integer)) ||
!(irowa = NAG_ALLOC(nnzasum, Integer)) ||
!(icola = NAG_ALLOC(nnzasum, Integer)) ||
!(a = NAG_ALLOC(nnzasum, double)) || !(x = NAG_ALLOC(nvar, double)))
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}
/* A_0 is empty */
nnza[0] = 0;
/* A_1, A_2, ..., A_m are v_i*v_i^T */
idx = 0;
for (k = 1; k <= m; k++) {
nnza[k] = (p + 1) * p / 2;
for (i = 1; i <= p; i++)
for (j = i; j <= p; j++) {
irowa[idx] = i;
icola[idx] = j;
a[idx] = V(k, i) * V(k, j);
idx++;
}
}
/* A_{m+1} is the -identity */
nnza[m + 1] = p;
for (i = 1; i <= p; i++) {
irowa[idx] = i;
icola[idx] = i;
a[idx] = -1.0;
idx++;
}
/* nag_opt_handle_set_linmatineq (e04rnc).
* Add the linear matrix constraint to the problem formulation. */
nag_opt_handle_set_linmatineq(handle, nvar, dima, nnza, nnzasum, irowa,
icola, a, nblk, NULL, &idblk, NAGERR_DEFAULT);
/* Set optional arguments of the solver by calling
* nag_opt_handle_opt_set (e04zmc). */
nag_opt_handle_opt_set(handle, "Task = Maximize", NAGERR_DEFAULT);
nag_opt_handle_opt_set(handle, "Initial X = Automatic", NAGERR_DEFAULT);
/* Pass the handle to the solver, we are not interested in
* Lagrangian multipliers.
* nag_opt_handle_solve_pennon (e04svc). */
nnzu = 0;
nnzuc = 0;
nnzua = 0;
INIT_FAIL(fail);
nag_opt_handle_solve_pennon(handle, nvar, x, nnzu, NULL, nnzuc, NULL,
nnzua, NULL, rinfo, stats, &inform, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_opt_handle_solve_pennon (e04svc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}
/* Print results */
printf("\n Weight Row of design matrix");
for (i = 1; i <= m; i++)
if (x[i - 1] > tol) {
printf("\n %7.2f ", x[i - 1]);
for (j = 1; j <= p; j++)
printf("%7.2f ", V(i, j));
}
printf("\n only those rows with a weight > %7.1e are shown\n", tol);
END:
/* nag_opt_handle_free (e04rzc).
* Destroy the problem handle and deallocate all the memory. */
if (handle)
nag_opt_handle_free(&handle, NAGERR_DEFAULT);
NAG_FREE(a);
NAG_FREE(b);
NAG_FREE(bl);
NAG_FREE(bu);
NAG_FREE(v);
NAG_FREE(x);
NAG_FREE(icola);
NAG_FREE(icolb);
NAG_FREE(irowa);
NAG_FREE(irowb);
NAG_FREE(nnza);
return exit_status;
}