32 double value_x =
value(x);
33 for (
int i = min; i <=
max; ++i)
36 ptmp->
x = pt1->
x / value_x;
71 double* pdftmp = dftmp.
get_v() +
max;
73 double* pdft1 = dft1.get_v() +
max;
74 for (
int i = max; i >=
min; --i)
77 dfx -= *pdftmp * (*ptmp) * xinv;
78 *pdft1 = *pdftmp * xinv;
84 dft1.save_dvector_derivatives(t1_pos);
void DF_dv_dble_div(void)
Description not yet available.
Base class for dvariable.
Description not yet available.
void save_prevariable_value(const prevariable &v)
Vector of double precision numbers.
Description not yet available.
void verify_identifier_string(const char *)
Verifies gradient stack string.
Holds the data for the prevariable class.
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.
prevariable_position restore_prevariable_position()
void save_prevariable_position(const prevariable &v)
void save_dvar_vector_value(const dvar_vector &v)
dvar_vector_position restore_dvar_vector_position()
void RETURN_ARRAYS_INCREMENT()
Author: David Fournier Copyright (c) 2008-2012 Regents of the University of California.
static _THREAD gradient_structure * _instance
int save_identifier_string(const char *)
Writes a gradient stack verification string.
dvector restore_dvar_vector_value(const dvar_vector_position &tmp)
Restores the size, address, and value information for a dvar_vector.
void save_dvar_vector_position(const dvar_vector &v)
static _THREAD DF_FILE * fp
Stores the adjoint gradient data that will be processed by gradcalc.
dvector restore_dvar_vector_derivatives(const dvar_vector_position &tmp)
Description not yet available.
double restore_prevariable_value()
void RETURN_ARRAYS_DECREMENT()
d3_array operator/(const d3_array &m, const double d)
Author: David Fournier.
dvector value(const df1_one_vector &v)
void save_double_derivative(const double x, const prevariable_position &_pos)
Description not yet available.
static _THREAD grad_stack * GRAD_STACK1
class for things related to the gradient structures, including dimension of arrays, size of buffers, etc.
double x
< value of the variable