NAG Library Manual, Mark 27.2
Interfaces:  FL   CL   CPP   AD 

NAG AD Library Introduction
Example description
/* E04DG_A1W_F C++ Header Example Program.
 *
 * Copyright 2021 Numerical Algorithms Group.
 * Mark 27.2, 2021.
 */

#include <dco.hpp>
#include <iostream>
#include <math.h>
#include <nag.h>
#include <nagad.h>
#include <nagx02.h>
#include <stdio.h>
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
  dco::ga1s<double>::global_tape = dco::ga1s<double>::tape_t::create();

  // Create AD configuration data object
  Integer ifail     = 0;
  void *  ad_handle = 0;
  nag::ad::x10aa(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;
      dco::ga1s<double>::global_tape->register_variable(x_in[i]);
      x[i] = x_in[i];
    }

  // Initialize sav arrays
  ifail = 0;
  nag::ad::e04wb("E04DGA", cwsav, 1, lwsav, 120, iwsav, 610, rwsav, 475, ifail);

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

  // Solve the problem
  Integer iter;
  ifail = 0;
  nag::ad::e04dg(ad_handle, n, objfun, iter, objf, objgrd, x, iwork, work, -1,
                 iuser, -1, ruser, lwsav, iwsav, rwsav, ifail);

  // Primal results
  cout.setf(ios::scientific, ios::floatfield);
  cout.precision(3);
  cout << "\n Objective value = ";
  cout.width(12);
  cout << dco::value(objf);
  cout << "\n Solution point  = ";
  for (int i = 0; i < n; i++)
    {
      cout.width(12);
      cout << dco::value(x[i]);
    }

  cout << "\n Estim gradient  = ";
  for (int i = 0; i < n; i++)
    {
      cout.width(12);
      cout << dco::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;
    dco::derivative(objf) += inc;
  }
  ifail                                              = 0;
  dco::ga1s<double>::global_tape->sparse_interpret() = true;
  dco::ga1s<double>::global_tape->interpret_adjoint();

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

  //  Setup evaluation of derivatives via adjoints
  for (int j = 0; j < n; j++)
    {
      dco::ga1s<double>::global_tape->zero_adjoints();
      double inc = 1.0;
      dco::derivative(objgrd[j]) += inc;
      ifail                                              = 0;
      dco::ga1s<double>::global_tape->sparse_interpret() = true;
      dco::ga1s<double>::global_tape->interpret_adjoint();
      cout << " dobjgrd(";
      cout.width(1);
      cout << j + 1;
      cout << ")/dx : ";
      for (int i = 0; i < n; i++)
        {
          double d = dco::derivative(x[i]);
          cout.width(12);
          cout << d;
        }
      cout << endl;
    }

END:

  // Remove computational data object and tape
  nag::ad::x10ab(ad_handle, ifail);
  dco::ga1s<double>::tape_t::remove(dco::ga1s<double>::global_tape);

  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;
}