Prev

Next

Index-> contents reference index search external

Up-> cppad_swig library a_fun a_fun_optimize a_fun_optimize_xam.m

cppad_swig-> testing swig_xam.i library whats_new_2018

library-> module a_double vector a_fun sparse error xam.m4

a_fun-> independent abort_recording a_fun_ctor a_fun_jacobian a_fun_hessian a_fun_forward a_fun_reverse a_fun_optimize a_fun_property

a_fun_optimize-> a_fun_optimize_xam.cpp a_fun_optimize_xam.m a_fun_optimize_xam.pm a_fun_optimize_xam.py

a_fun_optimize_xam.m

Headings

function ok = a_fun_optimize_xam()
     %
     % load the Cppad Swig library
     m_cppad
     %
     % initialize return variable
     ok = true;
     % -----------------------------------------------------------------------
     n_ind = 1; % number of independent variables
     n_dep = 1; % number of dependent variables
     n_var = 1; % phantom variable at address 0
     n_op = 1;  % special operator at beginning
     %
     % dimension some vectors
     x = m_cppad.vec_double(n_ind);
     ay = m_cppad.vec_a_double(n_dep);
     %
     % independent variables
     x(0) = 1.0;
     ax = m_cppad.independent(x);
     n_var = n_var + n_ind; % one for each indpendent
     n_op = n_op + n_ind;
     %
     % accumulate summation
     ax0 = ax(0);
     csum = m_cppad.a_double(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;
     af = m_cppad.a_fun(ax, ay);
     n_op = n_op + 1; % speical operator at end
     %
     % check number of variables and operators
     ok = ok && af.size_var() == n_var;
     ok = ok && af.size_op() == n_op;
     %
     % optimize
     af.optimize();
     %
     % number of variables and operators has decreased by two
     ok = ok && af.size_var() == n_var-2;
     ok = ok && af.size_op() == n_op-2;
     %
     return;
end