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

fadbad_ode.cpp

View page source

Fadbad Speed: Ode

Specifications

See link_ode .

Implementation

// suppress conversion warnings before other includes
# include <cppad/wno_conversion.hpp>
//
# include <FADBAD++/fadiff.h>
# include <algorithm>
# include <cassert>
# include <cppad/utility/vector.hpp>
# include <cppad/speed/uniform_01.hpp>
# include <cppad/speed/ode_evaluate.hpp>

// list of possible options
# include <map>
extern std::map<std::string, bool> global_option;

namespace fadbad {
    // define fabs for use by ode_evaluate
    fadbad::F<double> fabs(const fadbad::F<double>& x)
    {  return std::max(-x, x); }
}

bool link_ode(
    size_t                     size       ,
    size_t                     repeat     ,
    CppAD::vector<double>      &x         ,
    CppAD::vector<double>      &jacobian
)
{
    // speed test global option values
    if( global_option["atomic"] )
        return false;
    if( global_option["memory"] || global_option["onetape"] || global_option["optimize"] )
        return false;
    // -------------------------------------------------------------
    // setup
    assert( x.size() == size );
    assert( jacobian.size() == size * size );

    typedef fadbad::F<double>       ADScalar;
    typedef CppAD::vector<ADScalar> ADVector;

    size_t i, j;
    size_t p = 0;          // use ode to calculate function values
    size_t n = size;       // number of independent variables
    size_t m = n;          // number of dependent variables
    ADVector X(n), Y(m);   // independent and dependent variables

    // -------------------------------------------------------------
    while(repeat--)
    {  // choose next x value
        CppAD::uniform_01(n, x);
        for(j = 0; j < n; j++)
        {  // set value of x[j]
            X[j] = x[j];
            // set up for X as the independent variable vector
            X[j].diff((unsigned int) j, (unsigned int) n);
        }

        // evaluate function
        CppAD::ode_evaluate(X, p, Y);

        // return values with Y as the dependent variable vector
        for(i = 0; i < m; i++)
        {  for(j = 0; j < n; j++)
                jacobian[ i * n + j ] = Y[i].d((unsigned int) j);
        }
    }
    return true;
}