switch_var_dyn.cpp

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Switching Between Variables and Dynamic Parameters: Example and Test

Function

For each ADFun object there is a corresponding function \(f(x, p)\) where x is the vector of independent variables and p is the vector of independent dynamic parameters.

Convert a Function to a Graph

The to_graph routine can be used to convert a ADFun to a graph representation; see cpp_ad_graph .

Convert a Graph to a Function

The from_graph routine can be used to convert a graph back to a function. During this conversion, it is possible to change dynamic parameters to variables and variables to dynamic parameters; see dyn2var and var2dyn in the from_graph documentation. Note that many such conversions can be done using the same cpp_ad_graph object.

Source Code

# include <cppad/cppad.hpp>

bool switch_var_dyn(void)
{  bool ok = true;
   using std::string;
   //
   // f(x_0, x_1, x_2) = y_0 = x_2 * ( x_0 + x_1 );
   CPPAD_TESTVECTOR( CppAD::AD<double> ) ax(3), ay(1);
   for(size_t j = 0; j < 3; ++j)
      ax[j] = CppAD::AD<double>(j);
   Independent(ax);
   ay[0] = ax[2] * ( ax[0] + ax[1] );
   CppAD::ADFun<double> f(ax, ay);
   ok &= f.Domain() == 3;
   ok &= f.Range() == 1;
   ok &= f.size_dyn_ind() == 0;
   //
   // set independent variables and parameters
   CPPAD_TESTVECTOR(double) p(0), x(3);
   x[0] = 2.0;
   x[1] = 3.0;
   x[2] = 4.0;
   //
   // compute y = f(x)
   f.new_dynamic(p);
   CPPAD_TESTVECTOR(double) y = f.Forward(0, x);
   //
   // check result
   ok &= y[0] == x[2] * ( x[0] + x[1] );
   // -----------------------------------------------------------------------
   //
   // C++ graph object
   CppAD::cpp_graph graph_obj;
   f.to_graph(graph_obj);
   //
   // change x[0]->p[0], x[1]->p[1], x[2]->x[0]
   CppAD::vector<bool> dyn2var(0), var2dyn(3);
   var2dyn[0] = true;
   var2dyn[1] = true;
   var2dyn[2] = false;
   f.from_graph(graph_obj, dyn2var, var2dyn);
   p.resize(2);
   x.resize(1);
   //
   ok &= f.Domain() == 1;
   ok &= f.Range() == 1;
   ok &= f.size_dyn_ind() == 2;
   //
   // set independent variables and parameters
   p[0] = 1.0;
   p[1] = 2.0;
   x[0] = 3.0;
   //
   // compute y = f(x, p)
   f.new_dynamic(p);
   y = f.Forward(0, x);
   //
   // check result
   ok &= y[0] == x[0] * ( p[0] + p[1] );
   //
   return ok;
}