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Chapter Introduction
NAG Toolbox

NAG Toolbox: nag_matop_complex_gen_matrix_fun_usd (f01fm)


    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example


nag_matop_complex_gen_matrix_fun_usd (f01fm) computes the matrix function, fA, of a complex n by n matrix A, using analytical derivatives of f you have supplied.


[a, user, iflag, ifail] = f01fm(a, f, 'n', n, 'user', user)
[a, user, iflag, ifail] = nag_matop_complex_gen_matrix_fun_usd(a, f, 'n', n, 'user', user)


fA 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 fmzi at a number of points zi, for i=1,2,,nz, on the complex plane. nag_matop_complex_gen_matrix_fun_usd (f01fm) 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.


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


Compulsory Input Parameters

1:     alda: – complex array
The first dimension of the array a must be at least n.
The second dimension of the array a must be at least n.
The n by n matrix A.
2:     f – function handle or string containing name of m-file
Given an integer m, the function f evaluates fmzi at a number of points zi.
[iflag, fz, user] = f(m, iflag, nz, z, user)

Input Parameters

1:     m int64int32nag_int scalar
The order, m, of the derivative required.
If m=0, fzi should be returned. For m>0, fmzi should be returned.
2:     iflag int64int32nag_int scalar
iflag will be zero.
3:     nz int64int32nag_int scalar
nz, the number of function or derivative values required.
4:     znz – complex array
The nz points z1,z2,,znz at which the function f is to be evaluated.
5:     user – Any MATLAB object
f is called from nag_matop_complex_gen_matrix_fun_usd (f01fm) with the object supplied to nag_matop_complex_gen_matrix_fun_usd (f01fm).

Output Parameters

1:     iflag int64int32nag_int scalar
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 fz; for instance fzi may not be defined for a particular zi. If iflag is returned as nonzero then nag_matop_complex_gen_matrix_fun_usd (f01fm) will terminate the computation, with ifail=2.
2:     fznz – complex array
The nz function or derivative values. fzi should return the value fmzi, for i=1,2,,nz.
3:     user – Any MATLAB object

Optional Input Parameters

1:     n int64int32nag_int scalar
Default: the first dimension of the array a.
n, the order of the matrix A.
Constraint: n0.
2:     user – Any MATLAB object
user is not used by nag_matop_complex_gen_matrix_fun_usd (f01fm), but is passed to f. Note that for large objects it may be more efficient to use a global variable which is accessible from the m-files than to use user.

Output Parameters

1:     alda: – complex array
The first dimension of the array a will be n.
The second dimension of the array a will be n.
The n by n matrix, fA.
2:     user – Any MATLAB object
3:     iflag int64int32nag_int scalar
iflag=0, unless iflag has been set nonzero inside f, in which case iflag will be the value set and ifail will be set to ifail=2.
4:     ifail int64int32nag_int scalar
ifail=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

Errors or warnings detected by the function:
A Taylor series failed to converge.
iflag has been set nonzero by the user.
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.
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.
An unexpected internal error occurred. Please contact NAG.
Input argument number _ is invalid.
On entry, argument lda is invalid.
Constraint: ldan.
An unexpected error has been triggered by this routine. Please contact NAG.
Your licence key may have expired or may not have been installed correctly.
Dynamic memory allocation failed.


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 fA 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.

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 nag_matop_complex_gen_matrix_fun_num (f01fl) can be used to evaluate fA using numerical differentiation. If A is complex Hermitian then it is recommended that nag_matop_complex_herm_matrix_fun (f01ff) be used as it is more efficient and, in general, more accurate than nag_matop_complex_gen_matrix_fun_usd (f01fm).
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 nag_matop_complex_gen_matrix_cond_usd (f01kc) should be used.
nag_matop_real_gen_matrix_fun_usd (f01em) can be used to find the matrix function fA for a real matrix A.


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 .  
function f01fm_example

fprintf('f01fm example results\n\n');

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];

% Compute exp(3*a)
[exp3a, user, iflag, ifail] = f01fm(a, @f);

disp('f(A) = exp(3A)');

function [iflag, fz, user] = f(m, iflag, nz, z, user)
  fz = double(3^m)*exp(3*z);
f01fm example results

f(A) = exp(3A)
 -10.3264 +14.8082i  -1.4883 +74.3369i -12.1206 -47.0956i  41.5622 +32.2927i
  63.3909 -40.5336i -21.0117 -62.7073i  16.5106 +35.2787i  -5.1725 +17.9413i
  -6.3954 +56.4708i  25.4246 +13.8034i -14.4937 - 9.2397i -20.3167 + 2.8647i
  31.4957 +23.2757i  28.6003 +21.4573i -23.8034 -11.6547i  23.9841 +18.7737i

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Chapter Contents
Chapter Introduction
NAG Toolbox

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