/* E02BB_A1W_F C++ Header Example Program.
 *
 * Copyright 2017 Numerical Algorithms Group.
 * Mark 26.2, 2017.
 */

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

int main(void)
{
  // Scalars
  int               exit_status = 0;
  const Integer     m = 7;
  
  cout << "E02BB_A1W_F C++ Header Example Program Results\n\n";

  // Data points and values.
  double            xr[m], yr[m];
  nagad_a1w_w_rtype x[m], y[m];

  xr[0] = 0.0;  xr[1] = 0.2; xr[2] = 0.4; xr[3] = 0.6;
  xr[4] = 0.75; xr[5] = 0.9; xr[6] = 1.0;

  for (int i= 0; i < m; i++) {
    yr[i] = exp(xr[i]);

    x[i].value = xr[i];
    x[i].id = 0;
    y[i].value = yr[i];
    y[i].id = 0;
  }
  
  // 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);

  // Register variables to differentiate w.r.t.
  for (int i=0; i<m; i++) {
    nagad_a1w_ir_register_variable(&x[i]);
    nagad_a1w_ir_register_variable(&y[i]);
  }
  
  // Call the AD routine
  const Integer     lck = m + 4, lwrk = 6*m+16;
  nagad_a1w_w_rtype c[lck], lamda[lck], wrk[lwrk];
  ifail = 0;
  e01ba_a1w_f_(ad_handle,m,x,y,lamda,c,lck,wrk,lwrk,ifail);

  // Evaluate computed spline using e02bb
  double            xint_r = 0.5;
  nagad_a1w_w_rtype xint, fit;
  xint.value = xint_r;
  xint.id = 0;
  ifail = 0;
  e02bb_a1w_f_(ad_handle,lck,lamda,c,xint,fit,ifail);

  cout << "\n Value of fitted spline at x = " << xint_r;
  cout.precision(5);
  cout << " is: " << fit.value << endl;

  // Setup evaluation of derivatives via adjoints.
  double inc = 1.0;
  nagad_a1w_inc_derivative(&fit,inc);

  ifail = 0;
  nagad_a1w_ir_interpret_adjoint(ifail);

  cout << "\n Derivatives calculated: First order adjoints\n";
  cout << " Computational mode    : algorithmic\n";
  
  // Get derivatives
  cout << "\n Derivatives of fitted value w.r.t. data points:\n";
  cout << "  j    d/dx(j)      d/y(j)\n";
  cout.setf(ios::scientific,ios::floatfield);
  cout.precision(4);
  for (int j=0; j < m; j++) {
    double dx = nagad_a1w_get_derivative(x[j]);
    double dy = nagad_a1w_get_derivative(y[j]);
    cout.width(3); cout << j+1;
    cout.width(12); cout << dx;
    cout.width(12); cout << dy << endl;
  }

  // Remove computational data object and tape
  x10ab_a1w_f_(ad_handle,ifail);
  nagad_a1w_ir_remove();

  return exit_status;
}