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Up-> cppad_py library cpp_lib cpp_fun cpp_independent

cppad_py-> setup.py library whats_new_2018

library-> py_lib cpp_lib

cpp_lib-> a_double vector cpp_fun sparse cpp_utility more_cpp

cpp_fun-> cpp_independent cpp_abort_recording cpp_fun_ctor cpp_fun_property cpp_fun_new_dynamic cpp_fun_jacobian cpp_fun_hessian cpp_fun_forward cpp_fun_reverse cpp_fun_optimize

cpp_independent-> fun_dynamic_xam.cpp

Headings-> Syntax Purpose x dynamic ax a_both Example

@(@\newcommand{\B}[1]{ {\bf #1} } \newcommand{\R}[1]{ {\rm #1} }@)@Declare Independent Variables and Start Recording
Syntax
ax = cppad_py::independent(x)
a_both = cppad_py::independent(x, dynamic)

Purpose
This starts recording a_double operations. This recording is terminated, and the information is stored, by calling the d_fun constructor . It can be terminated, and the information is lost, by calling abort_recording .

x
This argument has prototype
     const vec_double& x
Its specifies the number of independent variables and their values during the recording. We use the notation nx = x.size() to denote the number of independent variables.

dynamic
This argument has prototype
     const vec_double& dynamic
Its specifies the number of independent dynamic parameters and their values during the recording. We use the notation nd = dynamic.size() to denote the number of independent variables.

ax
This result has prototype
     vec_a_double& ax
and is the vector of independent variables. It has size nx and for i = 0 to n-1
     ax[i] == x[i]

a_both
this result has prototype
     vec_a_double& a_both
and is the vector of both the independent variables and independent dynamic parameters. It has size nx + nd . For i = 0 to nx-1
     a_both[i] == x[i]
is the i-th independent variable. For i = 0 to nd-1
     a_both[nx + i] == dynamic[i]
is the i-th independent dynamic parameter.

Example
Most of the c++ d_fun examples use the ax return syntax. The fun_dynamic_xam.cpp example uses the a_both return syntax.

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Input File: lib/cplusplus/fun.cpp