/* E04DG_A1W_F C++ Header Example Program.
*
* Copyright 2019 Numerical Algorithms Group.
* Mark 27, 2019.
*/
#include <nag.h>
#include <dco.hpp>
#include <nagad.h>
#include <stdio.h>
#include <math.h>
#include <nag_stdlib.h>
#include <nagx02.h>
#include <iostream>
using namespace std;
extern "C"
{
static void NAG_CALL objfun(void* &ad_handle,
Integer &mode,
const Integer &n,
const nagad_a1w_w_rtype x[],
nagad_a1w_w_rtype &objf,
nagad_a1w_w_rtype objgrd[],
const Integer &nstate,
Integer iuser[],
nagad_a1w_w_rtype ruser[]
);
}
int main(void)
{
int exit_status = 0;
nagad_a1w_w_rtype objf;
cout << "E04DG_A1W_F C++ Header Example Program Results\n\n";
// Create AD tape
nagad_a1w_ir_create();
// Create AD configuration data object
Integer ifail = 0;
void *ad_handle = 0;
x10aa_a1w_f_(ad_handle,ifail);
// 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];
nagad_a1w_w_rtype ruser[1], rwsav[475];
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)) ||
!(x = NAG_ALLOC(n, nagad_a1w_w_rtype)) ||
!(x_in = NAG_ALLOC(n, nagad_a1w_w_rtype)) ||
!(objgrd = NAG_ALLOC(n, nagad_a1w_w_rtype)) ||
!(work = NAG_ALLOC(13*n, nagad_a1w_w_rtype))) {
cout << "Allocation failure\n";
exit_status = -1;
goto END;
}
double xr;
for (int i=0; i<n; i++) {
cin >> xr;
x_in[i] = xr;
nagad_a1w_ir_register_variable(&x_in[i]);
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;
e04dg_a1w_f_(ad_handle,n,objfun,iter,objf,objgrd,x,iwork,work,iuser,
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.width(12); cout << nagad_a1w_get_value(objf);
cout << "\n Solution point = ";
for (int i=0; i<n; i++) {
cout.width(12); cout << nagad_a1w_get_value(x[i]);
}
cout << "\n Estim gradient = ";
for (int i=0; i<n; i++) {
cout.width(12); cout << nagad_a1w_get_value(objgrd[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;
nagad_a1w_inc_derivative(&objf,inc);
}
ifail = 0;
nagad_a1w_ir_interpret_adjoint(ifail);
// Get derivatives of solution points
cout << " dobjf/dx : ";
for (int i=0; i<n; i++) {
double d = nagad_a1w_get_derivative(x[i]);
cout.width(12); cout << d;
}
cout << endl;
// Setup evaluation of derivatives via adjoints
for (int j=0; j<n; j++) {
nagad_a1w_ir_zero_adjoints();
double inc = 1.0;
nagad_a1w_inc_derivative(&objgrd[j],inc);
ifail = 0;
nagad_a1w_ir_interpret_adjoint(ifail);
cout << " dobjgrd(";
cout.width(1); cout << j+1;
cout << ")/dx : ";
for (int i=0; i<n; i++) {
double d = nagad_a1w_get_derivative(x[i]);
cout.width(12); cout << d;
}
cout << endl;
}
END:
// Remove computational data object and tape
x10ab_a1w_f_(ad_handle,ifail);
nagad_a1w_ir_remove();
NAG_FREE(iwork);
NAG_FREE(x);
NAG_FREE(x_in);
NAG_FREE(objgrd);
NAG_FREE(work);
return exit_status;
}
static void NAG_CALL objfun(void* &ad_handle,
Integer &mode,
const Integer &n,
const nagad_a1w_w_rtype x[],
nagad_a1w_w_rtype &objf,
nagad_a1w_w_rtype objgrd[],
const Integer &nstate,
Integer iuser[],
nagad_a1w_w_rtype ruser[]
)
{
// 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;
}