NAG CL Interface
f01fmc (complex_​gen_​matrix_​fun_​usd)

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1 Purpose

f01fmc computes the matrix function, f(A), of a complex n×n matrix A, using analytical derivatives of f you have supplied.

2 Specification

#include <nag.h>
void  f01fmc (Nag_OrderType order, Integer n, Complex a[], Integer pda,
void (*f)(Integer m, Integer *iflag, Integer nz, const Complex z[], Complex fz[], Nag_Comm *comm),
Nag_Comm *comm, Integer *iflag, NagError *fail)
The function may be called by the names: f01fmc or nag_matop_complex_gen_matrix_fun_usd.

3 Description

f(A) is computed using the Schur–Parlett algorithm described in Higham (2008) and Davies and Higham (2003).
The scalar function f, and the derivatives of f, are returned by the function f which, given an integer m, should evaluate f(m)(zi) at a number of points zi, for i=1,2,,nz, on the complex plane. f01fmc is, therefore, appropriate for functions that can be evaluated on the complex plane and whose derivatives, of arbitrary order, can also be evaluated on the complex plane.

4 References

Davies P I and Higham N J (2003) A Schur–Parlett algorithm for computing matrix functions SIAM J. Matrix Anal. Appl. 25(2) 464–485
Higham N J (2008) Functions of Matrices: Theory and Computation SIAM, Philadelphia, PA, USA

5 Arguments

1: order Nag_OrderType Input
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by order=Nag_RowMajor. See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.
Constraint: order=Nag_RowMajor or Nag_ColMajor.
2: n Integer Input
On entry: n, the order of the matrix A.
Constraint: n0.
3: a[dim] Complex Input/Output
Note: the dimension, dim, of the array a must be at least pda×n.
The (i,j)th element of the matrix A is stored in
  • a[(j-1)×pda+i-1] when order=Nag_ColMajor;
  • a[(i-1)×pda+j-1] when order=Nag_RowMajor.
On entry: the n×n matrix A.
On exit: the n×n matrix, f(A).
4: pda Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraint: pdan.
5: f function, supplied by the user External Function
Given an integer m, the function f evaluates f(m)(zi) at a number of points zi.
The specification of f is:
void  f (Integer m, Integer *iflag, Integer nz, const Complex z[], Complex fz[], Nag_Comm *comm)
1: m Integer Input
On entry: the order, m, of the derivative required.
If m=0, f(zi) should be returned. For m>0, f(m)(zi) should be returned.
2: iflag Integer * Input/Output
On entry: iflag will be zero.
On exit: iflag should either be unchanged from its entry value of zero, or may be set nonzero to indicate that there is a problem in evaluating the function f(z); for instance f(zi) may not be defined for a particular zi. If iflag is returned as nonzero then f01fmc will terminate the computation, with fail.code= NE_INT, NE_INT_2 or NE_USER_STOP.
3: nz Integer Input
On entry: nz, the number of function or derivative values required.
4: z[dim] const Complex Input
On entry: the nz points z1,z2,,znz at which the function f is to be evaluated.
5: fz[dim] Complex Output
On exit: the nz function or derivative values. fz[i-1] should return the value f(m)(zi), for i=1,2,,nz.
6: comm Nag_Comm *
Pointer to structure of type Nag_Comm; the following members are relevant to f.
userdouble *
iuserInteger *
pPointer 
The type Pointer will be void *. Before calling f01fmc you may allocate memory and initialize these pointers with various quantities for use by f when called from f01fmc (see Section 3.1.1 in the Introduction to the NAG Library CL Interface).
Note: f should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by f01fmc. If your code inadvertently does return any NaNs or infinities, f01fmc is likely to produce unexpected results.
6: comm Nag_Comm *
The NAG communication argument (see Section 3.1.1 in the Introduction to the NAG Library CL Interface).
7: iflag Integer * Output
On exit: iflag=0, unless iflag has been set nonzero inside f, in which case iflag will be the value set and fail will be set to fail.code= NE_INT, NE_INT_2 or NE_USER_STOP.
8: fail NagError * Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
NE_CONVERGENCE
A Taylor series failed to converge.
NE_INT
On entry, n=value.
Constraint: n0.
NE_INT_2
On entry, pda=value and n=value.
Constraint: pdan.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
An unexpected internal error occurred when ordering the eigenvalues of A. Please contact NAG.
The function was unable to compute the Schur decomposition of A.
Note:  this failure should not occur and suggests that the function has been called incorrectly.
There was an error whilst reordering the Schur form of A.
Note:  this failure should not occur and suggests that the function has been called incorrectly.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NE_USER_STOP
Termination requested in f.

7 Accuracy

For a normal matrix A (for which AH A=AAH), the Schur decomposition is diagonal and the algorithm reduces to evaluating f at the eigenvalues of A and then constructing f(A) using the Schur vectors. This should give a very accurate result. In general, however, no error bounds are available for the algorithm. See Section 9.4 of Higham (2008) for further discussion of the Schur–Parlett algorithm.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.
f01fmc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library. In these implementations, this function may make calls to the user-supplied functions from within an OpenMP parallel region. Thus OpenMP pragmas within the user functions can only be used if you are compiling the user-supplied function and linking the executable in accordance with the instructions in the Users' Note for your implementation. You must also ensure that you use the NAG communication argument comm in a thread safe manner, which is best achieved by only using it to supply read-only data to the user functions.
f01fmc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9 Further Comments

Up to 6n2 of Complex allocatable memory is required.
The cost of the Schur–Parlett algorithm depends on the spectrum of A, but is roughly between 28n3 and n4/3 floating-point operations. There is an additional cost in evaluating f and its derivatives. If the derivatives of f are not known analytically, then f01flc can be used to evaluate f(A) using numerical differentiation. If A is complex Hermitian then it is recommended that f01ffc be used as it is more efficient and, in general, more accurate than f01fmc.
Note that f must be analytic in the region of the complex plane containing the spectrum of A.
For further information on matrix functions, see Higham (2008).
If estimates of the condition number of the matrix function are required then f01kcc should be used.
f01emc can be used to find the matrix function f(A) for a real matrix A.

10 Example

This example finds the e3A where
A= ( 1.0+0.0i 0.0+0.0i 1.0+0.0i 0.0+2.0i 0.0+1.0i 1.0+0.0i -1.0+0.0i 1.0+0.0i -1.0+0.0i 0.0+1.0i 0.0+1.0i 0.0+1.0i 1.0+1.0i 0.0+2.0i -1.0+0.0i 0.0+1.0i ) .  

10.1 Program Text

Program Text (f01fmce.c)

10.2 Program Data

Program Data (f01fmce.d)

10.3 Program Results

Program Results (f01fmce.r)