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// SPDX-License-Identifier: EPL-2.0 OR GPL-2.0-or-later
// SPDX-FileCopyrightText: Bradley M. Bell <bradbell@seanet.com>
// SPDX-FileContributor: 2003-22 Bradley M. Bell
// ----------------------------------------------------------------------------
/*
{xrst_begin ad_fun.cpp}
Creating Your Own Interface to an ADFun Object
##############################################
{xrst_literal
// BEGIN C++
// END C++
}
{xrst_end ad_fun.cpp}
*/
// BEGIN C++
# include <cppad/cppad.hpp>
namespace {
// This class is an example of a different interface to an AD function object
template <class Base>
class my_ad_fun {
private:
CppAD::ADFun<Base> f;
public:
// default constructor
my_ad_fun(void)
{ }
// destructor
~ my_ad_fun(void)
{ }
// Construct an my_ad_fun object with an operation sequence.
// This is the same as for ADFun<Base> except that no zero
// order forward sweep is done. Note Hessian and Jacobian do
// their own zero order forward mode sweep.
template <class ADvector>
my_ad_fun(const ADvector& x, const ADvector& y)
{ f.Dependent(x, y); }
// same as ADFun<Base>::Jacobian
template <class BaseVector>
BaseVector jacobian(const BaseVector& x)
{ return f.Jacobian(x); }
// same as ADFun<Base>::Hessian
template <class BaseVector>
BaseVector hessian(const BaseVector &x, const BaseVector &w)
{ return f.Hessian(x, w); }
};
} // End empty namespace
bool ad_fun(void)
{ // This example is similar to example/jacobian.cpp, except that it
// uses my_ad_fun instead of ADFun.
bool ok = true;
using CppAD::AD;
using CppAD::NearEqual;
double eps99 = 99.0 * std::numeric_limits<double>::epsilon();
using CppAD::exp;
using CppAD::sin;
using CppAD::cos;
// domain space vector
size_t n = 2;
CPPAD_TESTVECTOR(AD<double>) X(n);
X[0] = 1.;
X[1] = 2.;
// declare independent variables and starting recording
CppAD::Independent(X);
// a calculation between the domain and range values
AD<double> Square = X[0] * X[0];
// range space vector
size_t m = 3;
CPPAD_TESTVECTOR(AD<double>) Y(m);
Y[0] = Square * exp( X[1] );
Y[1] = Square * sin( X[1] );
Y[2] = Square * cos( X[1] );
// create f: X -> Y and stop tape recording
my_ad_fun<double> f(X, Y);
// new value for the independent variable vector
CPPAD_TESTVECTOR(double) x(n);
x[0] = 2.;
x[1] = 1.;
// compute the derivative at this x
CPPAD_TESTVECTOR(double) jac( m * n );
jac = f.jacobian(x);
/*
F'(x) = [ 2 * x[0] * exp(x[1]) , x[0] * x[0] * exp(x[1]) ]
[ 2 * x[0] * sin(x[1]) , x[0] * x[0] * cos(x[1]) ]
[ 2 * x[0] * cos(x[1]) , -x[0] * x[0] * sin(x[i]) ]
*/
ok &= NearEqual( 2.*x[0]*exp(x[1]), jac[0*n+0], eps99, eps99);
ok &= NearEqual( 2.*x[0]*sin(x[1]), jac[1*n+0], eps99, eps99);
ok &= NearEqual( 2.*x[0]*cos(x[1]), jac[2*n+0], eps99, eps99);
ok &= NearEqual( x[0] * x[0] *exp(x[1]), jac[0*n+1], eps99, eps99);
ok &= NearEqual( x[0] * x[0] *cos(x[1]), jac[1*n+1], eps99, eps99);
ok &= NearEqual(-x[0] * x[0] *sin(x[1]), jac[2*n+1], eps99, eps99);
return ok;
}
// END C++
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