cppad_ode.cpp

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Cppad Speed: Gradient of Ode Solution

Specifications

See link_ode .

Implementation

# include <cppad/cppad.hpp>
# include <cppad/speed/ode_evaluate.hpp>
# include <cppad/speed/uniform_01.hpp>
# include <cassert>

// Note that CppAD uses global_option["memory"] at the main program level
# include <map>
extern std::map<std::string, bool> global_option;
// see comments in main program for this external
extern size_t global_cppad_thread_alloc_inuse;

bool link_ode(
    size_t                     size       ,
    size_t                     repeat     ,
    CppAD::vector<double>      &x         ,
    CppAD::vector<double>      &jacobian
)
{  global_cppad_thread_alloc_inuse = 0;

    // --------------------------------------------------------------------
    // check global options
    const char* valid[] = { "memory", "onetape", "optimize", "val_graph"};
    size_t n_valid = sizeof(valid) / sizeof(valid[0]);
    typedef std::map<std::string, bool>::iterator iterator;
    //
    for(iterator itr=global_option.begin(); itr!=global_option.end(); ++itr)
    {  if( itr->second )
        {  bool ok = false;
            for(size_t i = 0; i < n_valid; i++)
                ok |= itr->first == valid[i];
            if( ! ok )
                return false;
        }
    }
    // --------------------------------------------------------------------
    // optimization options: no conditional skips or compare operators
    std::string optimize_options =
        "no_conditional_skip no_compare_op no_print_for_op";
    if( global_option["val_graph"] )
        optimize_options += " val_graph";
    // --------------------------------------------------------------------
    // setup
    assert( x.size() == size );
    assert( jacobian.size() == size * size );

    typedef CppAD::AD<double>       ADScalar;
    typedef CppAD::vector<ADScalar> ADVector;

    size_t 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
    CppAD::ADFun<double>  f;   // AD function

    // do not even record comparison operators
    size_t abort_op_index = 0;
    bool record_compare   = false;

    // -------------------------------------------------------------
    if( ! global_option["onetape"] ) while(repeat--)
    {  // choose next x value
        uniform_01(n, x);
        for(j = 0; j < n; j++)
            X[j] = x[j];

        // declare independent variables
        Independent(X, abort_op_index, record_compare);

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

        // create function object f : X -> Y
        f.Dependent(X, Y);

        if( global_option["optimize"] )
            f.optimize(optimize_options);

        // skip comparison operators
        f.compare_change_count(0);

        jacobian = f.Jacobian(x);
    }
    else
    {  // an x value
        uniform_01(n, x);
        for(j = 0; j < n; j++)
            X[j] = x[j];

        // declare the independent variable vector
        Independent(X, abort_op_index, record_compare);

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

        // create function object f : X -> Y
        f.Dependent(X, Y);

        if( global_option["optimize"] )
            f.optimize(optimize_options);

        // skip comparison operators
        f.compare_change_count(0);

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

            // evaluate jacobian
            jacobian = f.Jacobian(x);
        }
    }
    size_t thread                   = CppAD::thread_alloc::thread_num();
    global_cppad_thread_alloc_inuse = CppAD::thread_alloc::inuse(thread);
    return true;
}