F11DPF solves a system of complex linear equations involving the incomplete
preconditioning matrix generated by
F11DNF.
SUBROUTINE F11DPF ( |
TRANS, N, A, LA, IROW, ICOL, IPIVP, IPIVQ, ISTR, IDIAG, CHECK, Y, X, IFAIL) |
INTEGER |
N, LA, IROW(LA), ICOL(LA), IPIVP(N), IPIVQ(N), ISTR(N+1), IDIAG(N), IFAIL |
COMPLEX (KIND=nag_wp) |
A(LA), Y(N), X(N) |
CHARACTER(1) |
TRANS, CHECK |
|
F11DPF solves a system of complex linear equations
according to the value of the parameter
TRANS, where the matrix
corresponds to an incomplete
decomposition of a complex sparse matrix stored in coordinate storage (CS) format (see
Section 2.1.1 in the F11 Chapter Introduction), as generated by
F11DNF.
In the above decomposition
is a lower triangular sparse matrix with unit diagonal elements,
is a diagonal matrix,
is an upper triangular sparse matrix with unit diagonal elements and,
and
are permutation matrices.
,
and
are supplied to F11DPF through the matrix
which is an
N by
N sparse matrix, stored in CS format, as returned by
F11DNF. The permutation matrices
and
are returned from
F11DNF via the arrays
IPIVP and
IPIVQ.
It is envisaged that a common use of F11DPF will be to carry out the preconditioning step required in the application of
F11BSF to sparse complex linear systems. F11DPF is used for this purpose by the Black Box routine
F11DQF.
F11DPF may also be used in combination with
F11DNF to solve a sparse system of complex linear equations directly (see
Section 9.5 in F11DNF). This use of F11DPF is illustrated in
Section 10.
None.
If on entry
or
, explanatory error messages are output on the current error message unit (as defined by
X04AAF).
If
the computed solution
is the exact solution of a perturbed system of equations
, where
is a modest linear function of
, and
is the
machine precision. An equivalent result holds when
.
Not applicable.
The time taken for a call to F11DPF is proportional to the value of
NNZC returned from
F11DNF.
It is expected that a common use of F11DPF will be to carry out the preconditioning step required in the application of
F11BSF to sparse complex linear systems. In this situation F11DPF is likely to be called many times with the same matrix
. In the interests of both reliability and efficiency, you are recommended to set
for the first of such calls, and to set
for all subsequent calls.
This example reads in a complex sparse non-Hermitian matrix
and a vector
. It then calls
F11DNF, with
and
, to compute the
complete
decomposition
Finally it calls F11DPF to solve the system