/* D01RG_T1W_F C++ Header Example Program.
 *
 * Copyright 2023 Numerical Algorithms Group.
 * Mark 29.1, 2023.
 */

#include <dco.hpp>
#include <iostream>
#include <math.h>
#include <nag.h>
#include <nagad.h>
#include <nagx07.h>
#include <stdio.h>
using namespace std;

int main()
{
  // Scalars
  int exit_status = 0;

  cout << "D01RG_T1W_F C++ Header Example Program Results\n\n";

  // The example function can raise various exceptions - it contains
  // a division by zero and a log singularity - although its integral
  // is well behaved.

  Integer exmode[3], exmode_old[3];
  nag_get_ieee_exception_mode(exmode_old);
  // Save the original halting mode.

  // Turn exception halting mode off for the three common exceptions.
  for (int i = 0; i < 3; i++)
  {
    exmode[i] = 0;
  }
  nag_set_ieee_exception_mode(exmode);

  // Skip first line of data file
  string mystr;
  getline(cin, mystr);

  // Read problem parameters
  double ar, br, epsabsr, epsrelr;
  cin >> ar;
  cin >> br;
  cin >> epsabsr;
  cin >> epsrelr;

  nagad_t1w_w_rtype a, b, epsabs, epsrel;
  a      = ar;
  b      = br;
  epsabs = epsabsr;
  epsrel = epsrelr;

  // Create AD configuration data object
  Integer           ifail = 0;
  nag::ad::handle_t ad_handle;

  auto f = [&](nag::ad::handle_t &     ad_handle,
            const nagad_t1w_w_rtype *x,
            const Integer &         nx,
            nagad_t1w_w_rtype *fv,
            Integer &               iflag)
          {
            // dco/c++ used here to perform AD of the following
            nagad_t1w_w_rtype tmp1, tmp2;
            for (int i = 0; i < nx; i++)
            {
              tmp1  = 10.0 * (1.0 - x[i]);
              tmp2  = sin(x[i]) / x[i];
              fv[i] = tmp2 * log(tmp1);
            }
          };
  // Increment variable to differentiate w.r.t.
  double inc         = 1.0;
  dco::derivative(a) = inc;

  // Call the AD routine
  nagad_t1w_w_rtype dinest, errest;
  Integer           nevals;
  ifail = -1;
  nag::ad::d01rg(ad_handle, a, b, f, epsabs, epsrel, dinest, errest, nevals, ifail);
  if (ifail < 0)
  {
    cout << "\n ** nag::ad::d01rg failed error exit ifail = " << ifail << endl;
    goto END;
  }
  // Print inputs and primal outputs.
  cout << "\n lower limit of integration (a) = " << ar << endl;
  cout << " upper limit of integration (b) = " << br << endl;
  cout << " absolute accuracy requested    = " << epsabsr << endl;
  cout << " relative accuracy requested    = " << epsrelr << endl;
  cout.setf(ios::scientific, ios::floatfield);
  cout.precision(4);
  if (ifail >= 0)
  {
    cout << "\n approximation to the integral  : " << dco::value(dinest)
         << endl;
    cout << " estimate of the absolute error : " << dco::value(errest) << endl;
    cout << " number of function evaluations : " << nevals << endl;
  }

  // evaluation of derivatives via tangents.
  double da;
  da = dco::derivative(dinest);

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

  cout << "\n Derivative of solution w.r.t to lower limit:\n";
  cout << " d/da(x) = " << da << endl;

END:

  // Restore the original halting mode
  nag_set_ieee_exception_mode(exmode_old);

  return exit_status;
}

static void NAG_CALL f(nag::ad::handle_t &     ad_handle,
                       const nagad_t1w_w_rtype x[],
                       const Integer &         nx,
                       nagad_t1w_w_rtype       fv[],
                       Integer &               iflag,
                       Integer                 iuser[],
                       nagad_t1w_w_rtype       ruser[])
{
  // dco/c++ used here to perform AD of the following
  nagad_t1w_w_rtype tmp1, tmp2;
  for (int i = 0; i < nx; i++)
  {
    tmp1  = 10.0 * (1.0 - x[i]);
    tmp2  = sin(x[i]) / x[i];
    fv[i] = tmp2 * log(tmp1);
  }
  return;
}