/* C05QD_A1W_F C++ Header Example Program.
 *
 * Copyright 2022 Numerical Algorithms Group.
 * Mark 28.3, 2022.
 */

#include <dco.hpp>
#include <iostream>
#include <math.h>
#include <nag.h>
#include <nagad.h>
#include <nagx02.h>
#include <nagx04.h>
#include <stdio.h>
#include <string>
using namespace std;

int main()
{
  // Scalars
  int           exit_status = 0;
  const Integer mode = 2, n = 7;

  cout << "C05QD_A1W_F C++ Header Example Program Results\n\n";

  // problem parameters and starting value
  nagad_a1w_w_rtype ruser[5], x[7];

  ruser[0] = -1.0;
  ruser[1] = 3.0;
  ruser[2] = -2.0;
  ruser[3] = -2.0;
  ruser[4] = -1.0;

  for (int i = 0; i < n; ++i)
  {
    x[i] = -1.0;
  }

  // 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;

  // Register variables to differentiate w.r.t.
  for (int i = 0; i < 5; ++i)
  {
    dco::ga1s<double>::global_tape->register_variable(ruser[i]);
  }

  // Call AD routine
  nagad_a1w_w_rtype diag[n], epsfcn, fjac[n * n], factor, fvec[n], qtf[n],
      r[n * (n + 1) / 2], rwsav[4 * n + 10], xtol;
  Integer irevcm, iwsav[17], ml, mu;

  xtol   = sqrt(X02AJC);
  factor = 100.;
  for (int i = 0; i < n; ++i)
  {
    diag[i] = 1.;
  }
  ml     = 1;
  mu     = 1;
  epsfcn = 0.;

  irevcm = 0;

  do
  {
    ifail = 0;
    nag::ad::c05qd(ad_handle, irevcm, n, x, fvec, xtol, ml, mu, epsfcn, mode,
                   diag, factor, fjac, r, qtf, iwsav, rwsav, ifail);

    switch (irevcm)
    {
    case 1:
      // Monitoring exit
      continue;
    case 2:
      for (int i = 0; i < n; ++i)
      {
        fvec[i] = (ruser[1] + ruser[2] * x[i]) * x[i] - ruser[4];
      }
      for (int i = 1; i < n; ++i)
      {
        fvec[i] = fvec[i] + ruser[0] * x[i - 1];
      }
      for (int i = 0; i < n - 1; ++i)
      {
        fvec[i] = fvec[i] + ruser[3] * x[i + 1];
      }
      break;
    }
  } while (irevcm != 0);

  cout.setf(ios::scientific, ios::floatfield);
  cout.precision(4);
  cout << "           Solution:\n";
  for (int i = 0; i < n; ++i)
  {
    cout.width(10);
    cout << i + 1;
    cout.width(20);
    cout << dco::value(x[i]) << endl;
  }

  cout << "\n Derivatives calculated: First order adjoints\n";
  cout << " Computational mode    : algorithmic\n";
  cout << "\n Derivatives are of solution w.r.t function params\n\n";

  // Setup evaluation of derivatives via adjoints
  double dr[5 * n];
  for (int i = 0; i < n; ++i)
  {

    dco::ga1s<double>::global_tape->zero_adjoints();
    double inc            = 1.0;
    dco::derivative(x[i]) = inc;

    ifail                                              = 0;
    dco::ga1s<double>::global_tape->sparse_interpret() = true;
    dco::ga1s<double>::global_tape->interpret_adjoint();

    for (int j = 0; j < 5; ++j)
    {
      int k = j * n + i;
      dr[k] = dco::derivative(ruser[j]);
    }
  }

  NagError fail;
  INIT_FAIL(fail);
  x04cac(Nag_ColMajor, Nag_GeneralMatrix, Nag_NonUnitDiag, n, 5, dr, n,
         "    dx/druser", 0, &fail);

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

  return exit_status;
}