```/* E04DG_A1W_F C++ Header Example Program.
*
* Copyright 2019 Numerical Algorithms Group.
* Mark 27, 2019.
*/

#include <nag.h>
#include <dco.hpp>
#include <stdio.h>
#include <math.h>
#include <nag_stdlib.h>
#include <nagx02.h>
#include <iostream>
using namespace std;

extern "C"
{
Integer &mode,
const Integer &n,
const Integer &nstate,
Integer iuser[],
);
}

int main(void)
{
int               exit_status = 0;
cout << "E04DG_A1W_F C++ Header Example Program Results\n\n";

// Create AD configuration data object
Integer ifail = 0;

// Read problem parameters and register for differentiation
// Skip first line of data file
string mystr;
getline (cin, mystr);

Integer n;
cin >> n;

// AD routine fixed length array arguments
Integer           iuser[1], iwsav[610];
char              cwsav[1];
logical           lwsav[120];
const Charlen     name_l = 6, cwsav_l = 1;

// AD routine variable length arrays
Integer           *iwork = 0;
nagad_a1w_w_rtype *x = 0, *x_in = 0, *objgrd = 0, *work = 0;

if (!(iwork = NAG_ALLOC(n+1, Integer)) ||
cout << "Allocation failure\n";
exit_status = -1;
goto END;
}

double            xr;
for (int i=0; i<n; i++) {
cin >> xr;
x_in[i] = xr;
x[i] =  x_in[i];
}

// Initialize sav arrays
ifail = 0;
e04wb_a1w_f_("E04DGA",cwsav,1,lwsav,120,iwsav,610,rwsav,475,ifail,name_l,
cwsav_l);

// Options can be set here via E04DJA and/or E04DKA

// Solve the problem
Integer           iter;
ifail = -1;
ruser,lwsav,iwsav,rwsav,ifail);

// Primal results
cout.setf(ios::scientific,ios::floatfield);
cout.precision(3);
if (ifail>=0 && ifail<=9) {
cout << "\n Objective value = ";
cout << "\n Solution point  = ";
for (int i=0; i<n; i++) {
}

cout << "\n Estim gradient  = ";
for (int i=0; i<n; i++) {
}
}

cout << "\n\n Derivatives calculated: First order adjoints\n";
cout << " Computational mode    : algorithmic\n\n";
cout << " Derivatives:\n\n";

// Setup evaluation of derivatives of objf via adjoints.
{
double inc = 1.0;
}
ifail = 0;

// Get derivatives of solution points
cout << "      dobjf/dx : ";
for (int i=0; i<n; i++) {
cout.width(12); cout << d;
}
cout << endl;

//  Setup evaluation of derivatives via adjoints
for (int j=0; j<n; j++) {
double inc = 1.0;
ifail = 0;
cout << " dobjgrd(";
cout.width(1); cout << j+1;
cout << ")/dx : ";
for (int i=0; i<n; i++) {
cout.width(12); cout << d;
}
cout << endl;
}

END:

// Remove computational data object and tape

NAG_FREE(iwork);
NAG_FREE(x);
NAG_FREE(x_in);
NAG_FREE(objgrd);
NAG_FREE(work);

return exit_status;
}

Integer &mode,
const Integer &n,
const Integer &nstate,
Integer iuser[],
)
{
// dco/c++ used here to perform AD of objfun

nagad_a1w_w_rtype  x1, x2, y1, y2, expx1;

x1 = x[0];
x2 = x[1];
expx1 = exp(x1);
y1 = 2.0*x1;
y1 = y1 + x2;
y2 = x2 + 1.0;
x1 = y1*y1;
x2 = y2*y2;
x1 = x1 + x2;
objf = expx1*x1;

if (mode==2) {
y2 = y1 + y2;
y2 = 2.0*y2;
y1 = 4.0*y1;
y1 = expx1*y1;
objgrd[0] = y1 + objf;
objgrd[1] = expx1*y2;
}

return;
}
```