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

atomic_four_lin_ode_set.hpp

View page source

atomic_lin_ode Set Routine: Example Implementation

Syntax

call_id = lin_ode . set ( r , step , pattern , transpose )

Prototype

   typedef CppAD::sparse_rc< CppAD::vector<size_t> > sparse_rc;

template <class Base>
size_t atomic_lin_ode<Base>::set(
   const Base& r, const Base& step, sparse_rc& pattern, const bool& transpose
)

Purpose

Stores the auxiliary information for a an atomic operation that computes the solution of a linear ODE.

r

This argument is the final value for the variable that the ODE is with respect to.

step

This is a positive maximum step size to use when solving the ODE.

pattern

This argument is a sparsity pattern. It would be const except for the fact that pattern.set_row_major () is called so that checking for equality is faster; see set_row_major .

transpose

If this argument is true (false) the sparsity pattern is for \(A(x)\R{T}\) (\(A(x)\)).

Source

# include <cppad/example/atomic_four/lin_ode/lin_ode.hpp>

namespace CppAD { // BEGIN_CPPAD_NAMESPACE
// BEGIN PROTOTYPE
template <class Base>
size_t atomic_lin_ode<Base>::set(
   const Base& r, const Base& step, sparse_rc& pattern, const bool& transpose
)
// END PROTOTYPE
{
   // pattern
   // set_row_major so that checking for pattern equality is faster
   pattern.set_row_major();
   //
   // thread
   size_t thread = thread_alloc::thread_num();
   //
   // work_[thread]
   if( work_[thread] == nullptr )
      work_[thread] = new thread_struct;
   //
   // pattern_vec
   CppAD::vector<sparse_rc>& pattern_vec( work_[thread]->pattern_vec );
   //
   // pattern_index
   size_t     n_pattern     = pattern_vec.size();
   size_t     pattern_index = n_pattern;
   for(size_t i = 0; i < n_pattern; ++i)
      if( pattern == pattern_vec[i] )
         pattern_index = i;
   if( pattern_index == n_pattern )
   {  pattern_vec.push_back( pattern );
      CPPAD_ASSERT_UNKNOWN( pattern_vec[pattern_index] == pattern );
   }
   //
   // call_vec
   CppAD::vector<call_struct>& call_vec( work_[thread]->call_vec );
   //
   // call_id
   size_t call_id = call_vec.size();
   //
   // call
   call_struct call;
   call.thread        = thread;
   call.r             = r;
   call.step          = step;
   call.pattern_index = pattern_index;
   call.transpose     = transpose;
   //
   // work_[thread]
   call_vec.push_back( call );
   //
   return call_id;
}
} // END_CPPAD_NAMESPACE