/* nag::ad::c05ay Vector Tangent over Tangent Example Program.
*/
#include <dco.hpp>
#include <iostream>
#include <array>
#include <nagad.h>
// Function which calls NAG AD Library routines.
template <typename T> void func(T r, T &x);
// Driver with the tangent calls.
// Finds the zero point f(xv) = 0 for the function
// f(x) = exp(-x) - r*x.
// Also, computes the Hessian d2x_dr2 = d2xv/dr2.
template <std::size_t N>
void driver(const double &rv, double &xv, std::array<double,N> &d2xdr2);
int main()
{
std::cout << " nag::ad::c05ay Vector Tangent over Tangent Example Program Results\n";
// Set problem parameters
double rv = 2.0;
// Solution x
double xv;
// Number of vector elements in vector mode
constexpr std::size_t N=3;
// Derivative of x
std::array<double,N> d2xdr2;
// Call driver
driver(rv, xv, d2xdr2);
// Print outputs
std::cout << "\n Derivatives calculated: Second order tangents\n";
// Print derivatives
std::cout.setf(std::ios::scientific, std::ios::floatfield);
std::cout.precision(12);
std::cout << "\n Solution:\n";
std::cout << " x = " << xv << std::endl;
std::cout << "\n Second derivative of solution x w.r.t. parameter r:\n";
for (std::size_t i=0; i<N; ++i) {
std::cout << " d2x/dr2(x)[" << i << "] = " << d2xdr2[i] << std::endl;
}
return 0;
}
// Driver with the tangent calls.
// Finds the zero point f(xv) = 0 for the function
// f(x) = exp(-x) - r*x.
// Also, computes the Hessian d2x_dr2 = d2xv/dr2.
template <std::size_t N>
void driver(const double &rv, double &xv, std::array<double,N> &d2xdr2)
{
using T = typename dco::gt1s<typename dco::gt1v<double,N>::type>::type;
// Function parameter r
T r = rv;
// Variable to differentiate w.r.t.
dco::derivative(dco::value(r))[0] = 1.0;
for (std::size_t i=1; i<N; ++i) {
dco::derivative(dco::value(r))[i] = 2.0;
}
dco::value(dco::derivative(r)) = 1.0;
// Variable to differentiate
T x;
// Call the NAG AD Lib functions
func(r, x);
// Extract the computed solution
xv = dco::passive_value(x);
// Extract the 2nd order tangent of x
for (std::size_t i=0; i<N; ++i) {
d2xdr2[i] = dco::derivative(dco::derivative(x))[i];
}
}
// Function which calls NAG AD Library routines.
template <typename T> void func(T r, T &x)
{
// Active variables
T a = 0.0, b = 1.0;
T eps = 1.0e-5, eta = 0.0;
// Create AD configuration data object
Integer ifail = 0;
nag::ad::handle_t ad_handle;
// Routine for computing an approximation to a simple zero of the function f
ifail = 0;
nag::ad::c05ay(ad_handle, a, b, eps, eta,
[&](nag::ad::handle_t const& handle, T const& x, T & z) {
z = exp(-x) - x * r;
},
x, ifail);
}