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Creating Your Own Interface to an ADFun Object
`

    # 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 VectorBase>
              VectorBase jacobian(const VectorBase& x)
              {     return f.Jacobian(x); }

              // same as ADFun<Base>::Hessian
                 template <typename VectorBase>
              VectorBase hessian(const VectorBase &x, const VectorBase &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;
    }

`

Input File: example/general/ad_fun.cpp