f08kp
is the AD Library version of the primal routine
f08kpf (zgesvd).
Based (in the C++ interface) on overload resolution,
f08kp 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.
f08kp
is the AD Library version of the primal routine
f08kpf (zgesvd).
f08kpf (zgesvd) computes the singular value decomposition (SVD) of a complex
matrix
, optionally computing the left and/or right singular vectors.
For further information see
Section 3 in the documentation for
f08kpf (zgesvd).
Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999)
LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia
https://www.netlib.org/lapack/lug
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.
f08kp uses the standard NAG
ifail mechanism. Any errors indicated via
info values returned by
f08kpf may be indicated with the same value returned by
ifail. In addition, this routine may 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
f08kpf (zgesvd),
modified to demonstrate calling the NAG AD Library.
This example finds the singular values and left and right singular vectors of the
matrix
together with approximate error bounds for the computed singular values and vectors.
The example program for
f08kr illustrates finding a singular value decomposition for the case
.