NAG Library Manual, Mark 27
Interfaces:  FL   CL   CPP   AD 
NAG AD Library Introduction
E02 (Fit) Chapter Contents
E02 (Fit) Chapter Introduction (FL)
e02de:  FL   CL   CPP   AD 

NAG AD Library
e02de_a1w_f (dim2_spline_evalv_a1w)

Note: _a1w_ denotes that first order adjoints are computed in working precision; this has the corresponding argument type nagad_a1w_w_rtype. Further implementations, for example for higher order differentiation or using the tangent linear approach, may become available at later marks of the NAG AD Library. The method of codifying AD implementations in the routine name and corresponding argument types is described in the NAG AD Library Introduction.
NAG Library Manual, Mark 27
Interfaces:  FL   CL   CPP   AD 
NAG AD Library Introduction
E02 (Fit) Chapter Contents
E02 (Fit) Chapter Introduction (FL)
e02de:  FL   CL   CPP   AD 

▸▿ Contents

© The Numerical Algorithms Group Ltd. 2019

1 Purpose

e02de_a1w_f is the adjoint version of the primal routine e02def.

2 Specification

Fortran Interface
Subroutine e02de_a1w_f ( ad_handle, m, px, py, x, y, lamda, mu, c, ff, wrk, iwrk, ifail)
Integer, Intent (In) :: m, px, py
Integer, Intent (Inout) :: ifail
Integer, Intent (Out) :: iwrk(py-4)
Type (nagad_a1w_w_rtype), Intent (In) :: x(m), y(m), lamda(px), mu(py), c((px-4)*(py-4))
Type (nagad_a1w_w_rtype), Intent (Out) :: ff(m), wrk(py-4)
Type (c_ptr), Intent (In) :: ad_handle
C++ Header Interface
#include <nagad.h>
void e02de_a1w_f_ ( void *&ad_handle, const Integer &m, const Integer &px, const Integer &py, nagad_a1w_w_rtype x[], nagad_a1w_w_rtype y[], nagad_a1w_w_rtype lamda[], nagad_a1w_w_rtype mu[], nagad_a1w_w_rtype c[], nagad_a1w_w_rtype ff[], nagad_a1w_w_rtype wrk[], Integer iwrk[], Integer &ifail)
The routine may be called by the names e02de_a1w_f or nagf_fit_dim2_spline_evalv_a1w.

3 Description

e02de_a1w_f is the adjoint version of the primal routine e02def.
e02def calculates values of a bicubic spline from its B-spline representation. For further information see Section 3 in the documentation for e02def.

4 References

None.

5 Arguments

In addition to the arguments present in the interface of the primal routine, e02de_a1w_f includes some arguments specific to AD.
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.
1: ad_handle – Type (c_ptr) Input
On entry: a handle to the AD configuration data object, as created by x10aa_a1w_f.
2: m – Integer Input
3: px – Integer Input
4: py – Integer Input
5: x(m) – Type (nagad_a1w_w_rtype) array Input
6: y(m) – Type (nagad_a1w_w_rtype) array Input
7: lamda(px) – Type (nagad_a1w_w_rtype) array Input
8: mu(py) – Type (nagad_a1w_w_rtype) array Input
9: c(px-4×py-4) – Type (nagad_a1w_w_rtype) array Input
10: ff(m) – Type (nagad_a1w_w_rtype) array Output
11: wrk(py-4) – Type (nagad_a1w_w_rtype) array Workspace
12: iwrk(py-4) – Integer array Workspace
13: ifail – Integer Input/Output

6 Error Indicators and Warnings

e02de_a1w_f preserves all error codes from e02def and in addition can return:
ifail=-89
An unexpected AD error has been triggered by this routine. Please contact NAG.
See Section 4.5.2 in the NAG AD Library Introduction for further information.
ifail=-899
Dynamic memory allocation failed for AD.
See Section 4.5.1 in the NAG AD Library Introduction for further information.

7 Accuracy

Not applicable.

8 Parallelism and Performance

e02de_a1w_f is not threaded in any implementation.

9 Further Comments

None.

10 Example

The following examples are variants of the example for e02def, modified to demonstrate calling the NAG AD Library.
LanguageSource FileDataResults
Fortrane02de_a1w_fe.f90e02de_a1w_fe.de02de_a1w_fe.r
C++e02de_a1w_hcppe.cppe02de_a1w_hcppe.de02de_a1w_hcppe.r
NAG Library Manual, Mark 27
Interfaces:  FL   CL   CPP   AD 
NAG AD Library Introduction
E02 (Fit) Chapter Contents
E02 (Fit) Chapter Introduction (FL)
e02de:  FL   CL   CPP   AD 
© The Numerical Algorithms Group Ltd. 2019