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fun_optimize_xam.cpp

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C++: Optimize an d_fun: Example and Test

# include <cstdio>
# include <cppad/py/cppad_py.hpp>

bool fun_optimize_xam(void) {
   using cppad_py::a_double;
   using cppad_py::vec_double;
   using cppad_py::vec_a_double;
   using cppad_py::d_fun;
   //
   // initialize return variable
   bool ok = true;
   //------------------------------------------------------------------------
   int n_ind = 1; // number of independent variables
   int n_dep = 1; // number of dependent variables
   int n_var = 1; // phantom variable at address 0
   int n_op = 1;  // special operator at beginning
   //
   // dimension some vectors
   vec_double x(n_ind);
   vec_a_double ay(n_dep);
   //
   // independent variables
   x[0] = 1.0;
   vec_a_double ax = cppad_py::independent(x);
   n_var = n_var + n_ind; // one for each indpendent
   n_op = n_op + n_ind;
   //
   // accumulate summation
   a_double ax0 = ax[0];
   a_double csum(0.0);
   csum = ax0 + ax0 + ax0 + ax0;
   n_var = n_var + 3; // one per + operator
   n_op = n_op + 3;
   //
   // define f(x) = y_0 = csum
   ay[0] = csum;
   d_fun f(ax, ay);
   n_op = n_op + 1; // speical operator at end
   //
   // check number of variables and operators
   ok = ok && f.size_var() == n_var;
   ok = ok && f.size_op() == n_op;
   //
   // optimize
   f.optimize();
   //
   // number of variables and operators has decreased by two
   ok = ok && f.size_var() == n_var-2;
   ok = ok && f.size_op() == n_op-2;
   //
   return( ok  );
}