/* D01TC_A1W_F C++ Header Example Program.
 *
 * Copyright 2022 Numerical Algorithms Group.
 * Mark 28.4, 2022.
 */

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

int main()
{
  // Scalars
  int     exit_status = 0;
  Integer ndim        = 4;

  cout << "D01TC_A1W_F C++ Header Example Program Results\n\n";

  // Allocate memory
  Integer *          nptvec = 0;
  nagad_a1w_w_rtype *abscis = 0, *weight = 0;
  Integer            lwa = 0;

  nptvec = new Integer[ndim];
  for (int i = 0; i < ndim; i++)
  {
    nptvec[i] = 4;
    lwa       = lwa + nptvec[i];
  }
  abscis = new nagad_a1w_w_rtype[lwa];
  weight = new nagad_a1w_w_rtype[lwa];

  // Create AD tape
  dco::ga1s<double>::global_tape = dco::ga1s<double>::tape_t::create();

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

  // Evaluate primal weights and abscisae in each Dimension
  int j = 0;
  for (int i = 0; i < ndim; i++)
  {

    Integer           ifail = 0, quadtype = 0;
    nagad_a1w_w_rtype a, b, c, d;
    switch (i)
    {
    case 0:
      a        = 1.0;
      b        = 2.0;
      c        = 0.0;
      d        = 0.0;
      quadtype = 0;
      break;
    case 1:
      a        = 0.0;
      b        = 2.0;
      c        = 0.0;
      d        = 0.0;
      quadtype = -3;
      break;
    case 2:
      a        = 0.0;
      b        = 0.5;
      c        = 0.0;
      d        = 0.0;
      quadtype = -4;
      break;
    case 3:
      a        = 1.0;
      b        = 2.0;
      c        = 0.0;
      d        = 2.0;
      quadtype = -5;
      break;
    }
    nag::ad::d01tc(ad_handle, quadtype, a, b, c, d, nptvec[i], &weight[j],
                   &abscis[j], ifail);
    j = j + nptvec[i];
  }

  /* Register variables to differentiate w.r.t. */
  for (int i = 0; i < lwa; i++)
  {
    dco::ga1s<double>::global_tape->register_variable(weight[i]);
    dco::ga1s<double>::global_tape->register_variable(abscis[i]);
  }

  auto fun = [&](nag::ad::handle_t &     ad_handle,
              const Integer &         ndim,
              const nagad_a1w_w_rtype *x,
              nagad_a1w_w_rtype &     ret)
              {
                // dco/c++ overloading used here to perform AD
                double            p1 = 6.0, p2 = 8.0;
                nagad_a1w_w_rtype r1, r2;
                // Split the following function into manageable chunks
                // ret = (pow(x[0]*x[1]*x[2],p1)/pow(x[3]+2.0,p2))*
                //       exp(-2.0*x[1]-0.5*x[2]*x[2]);
                r1  = x[2] * x[2];
                r1  = 0.5 * r1;
                r2  = -2.0 * x[1];
                r1  = r2 - r1;
                ret = exp(r1);
                r1  = x[0] * x[1] * x[2];
                r1  = pow(r1, p1);
                r2  = x[3] + 2.0;
                r2  = pow(r2, p2);
                r2  = r1 / r2;
                ret = ret * r2;
                return;
              };
              
  // Call the AD routine
  ifail = 0;
  nagad_a1w_w_rtype ans;
  nag::ad::d01fb(ad_handle, ndim, nptvec, lwa, weight, abscis, fun, ans, ifail);

  double inc = 1.0;
  dco::derivative(ans) += inc;
  dco::ga1s<double>::global_tape->sparse_interpret() = true;
  dco::ga1s<double>::global_tape->interpret_adjoint();

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

  // Get derivatives
  cout.setf(ios::right);
  cout.precision(4);
  cout << "\n Solution, x = ";
  double ans_value = dco::value(ans);
  cout.width(12);
  cout << ans_value << endl;
  cout << " Derivatives:\n";
  cout << " dim   j  d/dweight    d/dabscis\n";

  cout.setf(ios::scientific, ios::floatfield);

  j = -1;
  for (int i = 0; i < ndim; i++)
  {
    j        = j + 1;
    double w = dco::derivative(weight[j]);
    double a = dco::derivative(abscis[j]);

    int k = 1;
    cout.width(4);
    cout << i;
    cout.width(4);
    cout << k;
    cout.width(12);
    cout << w;
    cout.width(12);
    cout << a << endl;
    for (k = 2; k <= nptvec[i]; k++)
    {
      j        = j + 1;
      double w = dco::derivative(weight[j]);
      double a = dco::derivative(abscis[j]);
      cout.width(8);
      cout << k;
      cout.width(12);
      cout << w;
      cout.width(12);
      cout << a << endl;
    }
  }

  dco::ga1s<double>::tape_t::remove(dco::ga1s<double>::global_tape);

  delete[] nptvec;
  delete[] abscis;
  delete[] weight;
  return exit_status;
}