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Up-> cppad_py library py_lib py_fun py_independent

cppad_py-> setup.py library whats_new_2018

library-> py_lib cpp_lib

py_lib-> py_fun py_sparse py_utility more_py

py_fun-> py_independent py_abort_recording py_fun_ctor py_fun_property py_fun_new_dynamic py_fun_jacobian py_fun_hessian py_fun_forward py_fun_reverse py_fun_optimize

py_independent-> fun_dynamic_xam.py

Headings-> Syntax x dynamic ax adynamic Purpose Example

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

x
This argument is a numpy vector with float elements. It specifies the number of independent variables and their values during the recording. We use nx = x.size to denote the number of independent variables.

dynamic
This argument is a numpy vector with float elements. It specifies the number of independent dynamic parameters and their values during the recording. We use nd = dynamic.size to denote the number of independent dynamic parameters.

ax
This result is a numpy vector with a_double elements. This is the vector of independent variables. It has size nx and for i = 0 to n-1
     ax[i].value() == x[i]

adynamic
This result is a numpy vector with a_double elements. This is the vector of independent dynamic parameters. It has size nd and for i = 0 to n-1
     adynamic[i].value() == dynamic[i]

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

Example
Most of the python d_fun examples use this function. The fun_dynamic_xam.py uses the syntax that includes dynamic parameters.

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Input File: lib/python/independent.py