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

number_skip.cpp

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Number of Variables That Can be Skipped: Example and Test

# include <cppad/cppad.hpp>
bool number_skip(void)
{   bool ok = true;
    using CppAD::AD;

    // independent variable vector
    CppAD::vector< AD<double> > ax(2);
    ax[0] = 0.;
    ax[1] = 1.;
    Independent(ax);

    // Use a conditional expression
    CppAD::vector< AD<double> > ay(1);

    // variable that gets optimized out
    AD<double> az = ax[0] * ax[0];


    // conditional expression
    ay[0] = CondExpLt(ax[0], ax[1], ax[0] + ax[1], ax[0] - ax[1]);

    // create function object F : x -> ay
    CppAD::ADFun<double> f;
    f.Dependent(ax, ay);

    // use zero order to evaluate F[ (3, 4) ]
    CppAD::vector<double>  x( f.Domain() );
    CppAD::vector<double>  y( f.Range() );
    x[0]    = 3.;
    x[1]    = 4.;
    y   = f.Forward(0, x);
    ok &= (y[0] == x[0] + x[1]);

    // before call to optimize
    ok &= f.number_skip() == 0;
    size_t n_var = f.size_var();

    // now optimize the operation sequence
    f.optimize();

    // after optimize, check forward mode result
    x[0]    = 4.;
    x[1]    = 3.;
    y   = f.Forward(0, x);
    ok &= (y[0] == x[0] - x[1]);

    // after optimize, check amount of optimization
    ok &= f.size_var() == n_var - 1;
    ok &= f.number_skip() == 1;

    return ok;
}