\(\newcommand{\W}[1]{ \; #1 \; }\) \(\newcommand{\R}[1]{ {\rm #1} }\) \(\newcommand{\B}[1]{ {\bf #1} }\) \(\newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} }\) \(\newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} }\) \(\newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} }\) \(\newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }\)

code_gen_fun_jacobian.cpp

View page source

Evaluate Jacobian of a Code Gen Function: Example and Test

# include <cppad/example/code_gen_fun.hpp>

bool jacobian(void)
{   bool ok = true;
    //
    typedef CppAD::cg::CG<double>     c_double;
    typedef CppAD::AD<c_double>      ac_double;
    //
    typedef CppAD::vector<double>     d_vector;
    typedef CppAD::vector<ac_double> ac_vector;
    //
    double eps99 = 99.0 * std::numeric_limits<double>::epsilon();

    // domain space vector
    size_t n  = 2;
    ac_vector ac_x(n);
    for(size_t j = 0; j < n; ++j)
        ac_x[j] = 1.0 / double(j + 1);

    // declare independent variables and start tape recording
    CppAD::Independent(ac_x);

    // range space vector
    size_t m = 3;
    ac_vector ac_y(m);
    for(size_t i = 0; i < m; ++i)
        ac_y[i] = double(i + 1) * sin( ac_x[i % n] );

    // create c_f: x -> y and stop tape recording
    CppAD::ADFun<c_double> c_f(ac_x, ac_y);

    // create compiled version of c_f
    std::string file_name = "example_lib";
    code_gen_fun::evaluation_enum eval_jac = code_gen_fun::dense_enum;
    code_gen_fun f(file_name, c_f, eval_jac);

    // evaluate the compiled jacobian
    d_vector x(n), J;
    for(size_t j = 0; j < n; ++j)
        x[j] = 1.0 / double(j + 2);
    J = f.jacobian(x);

    // check Jaociban values
    for(size_t i = 0; i < m; ++i)
    {   for(size_t j = 0; j < n; ++j)
        {   double check = 0.0;
            if( j == i % n )
                check = double(i + 1) * cos( x[i % n] );
            ok &= CppAD::NearEqual(J[i * n + j] , check, eps99, eps99);
        }
    }
    return ok;
}