fvar__op8_8cpp_source.html

 #include "fvar.hpp"


 prevariable& cube(const prevariable& v1)

 {

   dvariable* RETURN_PTR = gradient_structure::next_RETURN_PTR();


   double x=value(v1);

   double x2=x*x;


   RETURN_PTR->v->x=x2*x;

   gradient_structure::GRAD_STACK1->set_gradient_stack(default_evaluation2,

     &(RETURN_PTR->v->x), &(v1.v->x), 3.0*x2);


   return *RETURN_PTR;

 }

 prevariable& fourth(const prevariable& v1)

 {

   dvariable* RETURN_PTR = gradient_structure::next_RETURN_PTR();


   double x=value(v1);

   double x2=x*x;


   RETURN_PTR->v->x=x2*x2;

   gradient_structure::GRAD_STACK1->set_gradient_stack(default_evaluation2,

     &(RETURN_PTR->v->x), &(v1.v->x), 4.0*x2*x);


   return *RETURN_PTR;

 }

default_evaluation2
void default_evaluation2(void)
Description not yet available.
Definition: def_eval.cpp:136

prevariable
Base class for dvariable.
Definition: fvar.hpp:1315

x
#define x

cube
d3_array cube(const d3_array &m)
Description not yet available.
Definition: d3arr5.cpp:17

grad_stack::set_gradient_stack
void set_gradient_stack(void(*func)(void), double *dep_addr, double *ind_addr1=NULL, double mult1=0, double *ind_addr2=NULL, double mult2=0)
Description not yet available.
Definition: fvar.hpp:1045

gradient_structure::next_RETURN_PTR
static dvariable * next_RETURN_PTR()
Definition: gradstrc.cpp:457

fvar.hpp
Author: David Fournier Copyright (c) 2008-2012 Regents of the University of California.

prevariable::v
double_and_int * v
pointer to the data
Definition: fvar.hpp:1333

value
dvector value(const df1_one_vector &v)
Definition: df11fun.cpp:69

gradient_structure::GRAD_STACK1
static _THREAD grad_stack * GRAD_STACK1
Definition: gradient_structure.h:115

dvariable
Fundamental data type for reverse mode automatic differentiation.
Definition: fvar.hpp:1518

fourth
double fourth(const double m)
Fourth power of a number; constant objects.
Definition: dvector.cpp:704

double_and_int::x
double x
&lt; value of the variable
Definition: fvar.hpp:195