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

optimize_print_for.cpp

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Optimize Print Forward Operators: Example and Test

# include <cppad/cppad.hpp>

namespace {
   struct tape_size { size_t n_var; size_t n_op; };

   void PrintFor(
      double pos, const char* before, double var, const char* after
   )
   {  if( pos <= 0.0 )
         std::cout << before << var << after;
      return;
   }
   template <class Vector> void fun(
      const std::string& options ,
      const Vector& x, Vector& y, tape_size& before, tape_size& after
   )
   {  typedef typename Vector::value_type scalar;

      // phantom variable with index 0 and independent variables
      // begin operator, independent variable operators and end operator
      before.n_var = 1 + x.size(); before.n_op  = 2 + x.size();
      after.n_var  = 1 + x.size(); after.n_op   = 2 + x.size();

      // Argument to PrintFor is only needed
      // if we are keeping print forward operators
      scalar minus_one = x[0] - 1.0;
      before.n_var += 1; before.n_op += 1;
      if( options.find("no_print_for_op") == std::string::npos )
      {  after.n_var += 1;  after.n_op += 1;
      }

      // print argument to log function minus one, if it is <= 0
      PrintFor(minus_one, "minus_one == ", minus_one , " is <=  0\n");
      before.n_var += 0; before.n_op += 1;
      if( options.find("no_print_for_op") == std::string::npos )
      {  after.n_var += 0;  after.n_op += 1;
      }

      // now compute log
      y[0] = log( x[0] );
      before.n_var += 1; before.n_op += 1;
      after.n_var  += 1; after.n_op  += 1;
   }
}

bool print_for(void)
{  bool ok = true;
   using CppAD::AD;
   using CppAD::NearEqual;
   double eps10 = 10.0 * std::numeric_limits<double>::epsilon();

   // domain space vector
   size_t n  = 1;
   CPPAD_TESTVECTOR(AD<double>) ax(n);
   ax[0] = 1.5;

   // range space vector
   size_t m = 1;
   CPPAD_TESTVECTOR(AD<double>) ay(m);

   for(size_t k = 0; k < 2; k++)
   {  // optimization options
      std::string options = "";
      if( k == 0 )
         options = "no_print_for_op";

      // declare independent variables and start tape recording
      CppAD::Independent(ax);

      // compute function value
      tape_size before, after;
      fun(options, ax, ay, before, after);

      // create f: x -> y and stop tape recording
      CppAD::ADFun<double> f(ax, ay);
      ok &= f.size_order() == 1; // this constructor does 0 order forward
      ok &= f.size_var() == before.n_var;
      ok &= f.size_op() == before.n_op;

      // Optimize the operation sequence
      f.optimize(options);
      ok &= f.size_order() == 0; // 0 order forward not present
      ok &= f.size_var() == after.n_var;
      ok &= f.size_op() == after.n_op;

      // Check result for a zero order calculation for a different x
      CPPAD_TESTVECTOR(double) x(n), y(m), check(m);
      x[0] = 2.75;
      y    = f.Forward(0, x);
      fun(options, x, check, before, after);
      ok &= NearEqual(y[0], check[0], eps10, eps10);
   }
   return ok;
}