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

double_ode.cpp

View page source

Double Speed: Ode Solution

Specifications

See link_ode .

Implementation

# include <cstring>
# include <cppad/utility/vector.hpp>
# include <cppad/speed/ode_evaluate.hpp>
# include <cppad/speed/uniform_01.hpp>

// Note that CppAD uses global_option["memory"] at the main program level
# include <map>
extern std::map<std::string, bool> global_option;

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

   size_t n = size;

   size_t m = 0;
   CppAD::vector<double> f(n);

   while(repeat--)
   {  // choose next x value
      uniform_01(n, x);

      // evaluate function
      CppAD::ode_evaluate(x, m, f);

   }
   size_t i;
   for(i = 0; i < n; i++)
      jacobian[i] = f[i];
   return true;
}