```/* nag_nearest_correlation_target (g02apc) Example Program.
*
* Copyright 2017 Numerical Algorithms Group.
*
* Mark 26.1, 2017.
*/

#include <stdio.h>
#include <nag.h>
#include <nag_stdlib.h>
#include <nagf08.h>
#include <nagg02.h>
#include <nagx04.h>

int main(void)
{

#define G(I,J) g[(J-1)*pdg + I-1]
#define H(I,J) h[(J-1)*pdh + I-1]

/*  Scalars */
Integer exit_status = 0;
Integer one = 1;
double alpha, eigmin, eigtol, errtol, norm, theta;
Integer i, j, iter, n, pdg, pdh, pdx;

/*  Arrays */
double *eig = 0, *g = 0, *h = 0, *x = 0;

/* Nag Types */
Nag_OrderType order;
NagError fail;

INIT_FAIL(fail);

/* Output preamble */
printf("nag_nearest_correlation_target (g02apc)");
printf(" Example Program Results\n\n");
fflush(stdout);

/* Skip heading in data file */
scanf("%*[^\n] ");

/* Read in the problem size and theta */
scanf("%" NAG_IFMT "%lf%*[^\n] ", &n, &theta);

pdg = n;
pdh = n;
pdx = n;
if (!(eig = NAG_ALLOC(n, double)) ||
!(g = NAG_ALLOC(pdg * n, double)) ||
!(h = NAG_ALLOC(pdh * n, double)) || !(x = NAG_ALLOC(pdx * n, double))
)
{
printf("Allocation failure\n");
exit_status = -1;
goto END;
}

/* Read in the matrix g */
for (i = 1; i <= n; i++)
for (j = 1; j <= n; j++)
scanf("%lf", &G(i, j));
scanf("%*[^\n] ");

/* Read in the matrix h */
for (i = 1; i <= n; i++)
for (j = 1; j <= n; j++)
scanf("%lf", &H(i, j));
scanf("%*[^\n] ");

/* Use the defaults for ERRTOL and EIGTOL */
errtol = -1.0;
eigtol = -1.0;

/*
* nag_nearest_correlation_target (g02apc).
* Calculate nearest correlation matrix using target matrix
*/
nag_nearest_correlation_target(g, pdg, n, theta, h, pdh, errtol,
eigtol, x, pdx, &alpha, &iter, &eigmin,
&norm, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_nearest_correlation_target (g02apc).\n%s\n",
fail.message);
exit_status = 1;
goto END;
}

/* Display results */

order = Nag_ColMajor;
/*
* nag_gen_real_mat_print (x04cac).
* Prints real general matrix
*/
nag_gen_real_mat_print(order, Nag_GeneralMatrix, Nag_NonUnitDiag, n, n, g,
pdg, "Symmetrised Input Matrix G", NULL, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_gen_real_mat_print (x04cac).\n%s\n", fail.message);
exit_status = 2;
goto END;
}

printf("\n");
fflush(stdout);
nag_gen_real_mat_print(order, Nag_GeneralMatrix, Nag_NonUnitDiag, n, n, x,
pdx, "Nearest Correlation Matrix X", NULL,
&fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_gen_real_mat_print (x04cac).\n%s\n", fail.message);
exit_status = 3;
goto END;
}

printf("\n%s %9" NAG_IFMT " \n\n", "Number of iterations taken:", iter);
printf("%s %34.4f \n\n", "alpha: ", alpha);
printf("%s %29.4f \n\n", "norm value: ", norm);
printf("%s %34.4f \n\n", "theta: ", theta);
printf("%s %15.4f \n", "Smallest eigenvalue of A: ", eigmin);

/*
* nag_dsyev (f08fac).
* Computes all eigenvalues and, optionally, eigenvectors of a real
* symmetric matrix
*/
nag_dsyev(order, Nag_EigVals, Nag_Upper, n, x, pdx, eig, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_dsyev (f08fac).\n%s\n", fail.message);
exit_status = 4;
goto END;
}

printf("\n");
fflush(stdout);
/*
* nag_gen_real_mat_print (x04cac).
* Print real general matrix (easy-to-use)
*/
nag_gen_real_mat_print(order, Nag_GeneralMatrix, Nag_NonUnitDiag, one, n,
eig, one, "Eigenvalues of x", NULL, &fail);
if (fail.code != NE_NOERROR) {
printf("Error from nag_gen_real_mat_print (x04cac).\n%s\n", fail.message);
exit_status = 5;
goto END;
}

END:
NAG_FREE(eig);
NAG_FREE(g);
NAG_FREE(h);
NAG_FREE(x);
return exit_status;

}
```