/* D01FB_T1W_F C++ Header Example Program.
*
* Copyright 2019 Numerical Algorithms Group.
* Mark 27, 2019.
*/
#include <nag.h>
#include <dco.hpp>
#include <nagad.h>
#include <stdio.h>
#include <math.h>
#include <iostream>
using namespace std;
extern "C"
{
static void NAG_CALL fun(void* &ad_handle,
const Integer& ndim,
const nagad_t1w_w_rtype x[],
nagad_t1w_w_rtype& ret,
Integer iuser[],
nagad_t1w_w_rtype ruser[]);
}
int main(void)
{
// Scalars
int exit_status = 0;
Integer ndim = 4;
cout << "D01FB_T1W_F C++ Header Example Program Results\n\n";
// Allocate memory
Integer *nptvec = 0;
nagad_t1w_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_t1w_w_rtype [lwa];
weight = new nagad_t1w_w_rtype [lwa];
// Create AD configuration data object
Integer ifail = 0;
void *ad_handle = 0;
x10aa_t1w_f_(ad_handle,ifail);
// Evaluate primal weights and abscisae in each dimension
int j = 0;
for (int i=0;i<ndim;i++) {
Integer ifail = 0, quadtype = 0;
nagad_t1w_w_rtype a, b;
switch (i) {
case 0:
a = 1.0;
b = 2.0;
quadtype = 0;
break;
case 1:
a = 0.0;
b = 2.0;
quadtype = -3;
break;
case 2:
a = 0.0;
b = 0.5;
quadtype = -4;
break;
case 3:
a = 1.0;
b = 2.0;
quadtype = -5;
break;
}
d01tb_t1w_f_(ad_handle,quadtype,a,b,nptvec[i],&weight[j],&abscis[j],
ifail);
j = j + nptvec[i];
}
// Call the AD routine
ifail = 0;
nagad_t1w_w_rtype ans;
nagad_t1w_w_rtype ruser[1];
Integer iuser[1];
d01fb_t1w_f_(ad_handle,ndim,nptvec,lwa,weight,abscis,
fun,ans,iuser,ruser,ifail);
cout << "\n Derivatives calculated: First order tangents\n";
cout << " Computational mode : algorithmic\n";
// Get derivatives
cout.setf(ios::right);
cout.precision(4);
cout << "\n Solution, x = ";
double ans_value = nagad_t1w_get_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++) {
for (int k = 1; k <= nptvec[i]; k++) {
j = j + 1;
double inc = 1.0, zero = 0.0;
nagad_t1w_inc_derivative(&weight[j],inc);
d01fb_t1w_f_(ad_handle,ndim,nptvec,lwa,weight,abscis,fun,ans,iuser,ruser,
ifail);
double w = nagad_t1w_get_derivative(ans);
nagad_t1w_set_derivative(&weight[j],zero);
nagad_t1w_inc_derivative(&abscis[j],inc);
d01fb_t1w_f_(ad_handle,ndim,nptvec,lwa,weight,abscis,fun,ans,iuser,ruser,
ifail);
double a = nagad_t1w_get_derivative(ans);
nagad_t1w_set_derivative(&abscis[j],zero);
if (k==1) {
cout.width(4); cout << i;
} else {
cout << " ";
}
cout.width(8); cout << k;
cout.width(12); cout << w;
cout.width(12); cout << a << endl;
}
}
// Remove computational data object
x10ab_t1w_f_(ad_handle,ifail);
delete [] nptvec;
delete [] abscis;
delete [] weight;
return exit_status;
}
static void NAG_CALL fun(void* &ad_handle,
const Integer& ndim,
const nagad_t1w_w_rtype x[],
nagad_t1w_w_rtype& ret,
Integer iuser[],
nagad_t1w_w_rtype ruser[])
{
// dco/c++ overloading used here to perform AD
double p1 = 6.0, p2 = 8.0;
nagad_t1w_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;
}