e05jc
is the AD Library version of the primal routine
e05jcf.
Based (in the C++ interface) on overload resolution,
e05jc can be used for primal, tangent and adjoint
evaluation. It supports tangents and adjoints of first order.
Note: this function can be used with AD tools other than dco/c++. For details, please contact
NAG.
e05jc
is the AD Library version of the primal routine
e05jcf.
e05jcf may be used to supply optional parameters to
e05jbf from an external file. The initialization routine
e05jaf must have been called before calling
e05jcf.
For further information see
Section 3 in the documentation for
e05jcf.
A brief summary of the AD specific arguments is given below. For the remainder, links are provided to the corresponding argument from the primal routine.
A tooltip popup for all arguments can be found by hovering over the argument name in
Section 2 and in this section.
e05jc preserves all error codes from
e05jcf and in addition can return:
An unexpected AD error has been triggered by this routine. Please
contact
NAG.
See
Error Handling in the NAG AD Library Introduction for further information.
The routine was called using a strategy that has not yet been implemented.
See
AD Strategies in the NAG AD Library Introduction for further information.
A C++ exception was thrown.
The error message will show the details of the C++ exception text.
Dynamic memory allocation failed for AD.
See
Error Handling in the NAG AD Library Introduction for further information.
Not applicable.
None.
The following examples are variants of the example for
e05jcf,
modified to demonstrate calling the NAG AD Library.
This example finds the global minimum of the ‘peaks’ function in two dimensions
on the box
.
By specifying an initialization list via
list,
numpts and
initpt we can start
e05jb looking close to one of the local minima and check that it really does move away from that point to one of the global minima.
More precisely, we choose
as our initial point (see
Section 10.3), and let the initialization list be
This example solves the optimization problem using some of the optional parameters described in
Section 12 in
e05jb.
None.