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Livre :
Expressions régulières,
Syntaxe et mise en oeuvre :
GNU/Linux |
CentOS 4.8 |
i386 |
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dgesvx(l) |
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DGESVX - use the LU factorization to compute the solution to a real system of linear equations A * X = B,
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SUBROUTINE DGESVX( |
FACT, TRANS, N, NRHS, A, LDA, AF, LDAF, IPIV, EQUED, R, C, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, IWORK, INFO ) | ||
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CHARACTER |
EQUED, FACT, TRANS | ||
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INTEGER |
INFO, LDA, LDAF, LDB, LDX, N, NRHS | ||
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DOUBLE |
PRECISION RCOND | ||
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INTEGER |
IPIV( * ), IWORK( * ) | ||
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DOUBLE |
PRECISION A( LDA, * ), AF( LDAF, * ), B( LDB, * ), BERR( * ), C( * ), FERR( * ), R( * ), WORK( * ), X( LDX, * ) |
DGESVX uses the LU factorization to compute the solution to a real system of linear equations A * X = B, where A is an N-by-N matrix and X and B are N-by-NRHS matrices.
Error bounds on the solution and a condition estimate are also provided.
The following steps are performed:
1. If FACT =
’E’, real scaling factors are computed to
equilibrate
the system:
TRANS = ’N’: diag(R)*A*diag(C) *inv(diag(C))*X =
diag(R)*B
TRANS = ’T’: (diag(R)*A*diag(C))**T
*inv(diag(R))*X = diag(C)*B
TRANS = ’C’: (diag(R)*A*diag(C))**H
*inv(diag(R))*X = diag(C)*B
Whether or not the system will be equilibrated depends on
the
scaling of the matrix A, but if equilibration is used, A is
overwritten by diag(R)*A*diag(C) and B by diag(R)*B (if
TRANS=’N’)
or diag(C)*B (if TRANS = ’T’ or
’C’).
2. If FACT =
’N’ or ’E’, the LU decomposition is
used to factor the
matrix A (after equilibration if FACT = ’E’) as
A = P * L * U,
where P is a permutation matrix, L is a unit lower
triangular
matrix, and U is upper triangular.
3. If some
U(i,i)=0, so that U is exactly singular, then the routine
returns with INFO = i. Otherwise, the factored form of A is
used
to estimate the condition number of the matrix A. If the
reciprocal of the condition number is less than machine
precision,
INFO = N+1 is returned as a warning, but the routine still
goes on
to solve for X and compute error bounds as described
below.
4. The system
of equations is solved for X using the factored form
of A.
5. Iterative
refinement is applied to improve the computed solution
matrix and calculate error bounds and backward error
estimates
for it.
6. If
equilibration was used, the matrix X is premultiplied by
diag(C) (if TRANS = ’N’) or diag(R) (if TRANS =
’T’ or ’C’) so
that it solves the original system before equilibration.
FACT (input) CHARACTER*1
Specifies whether or not the
factored form of the matrix A is supplied on entry, and if
not, whether the matrix A should be equilibrated before it
is factored. = ’F’: On entry, AF and IPIV
contain the factored form of A. If EQUED is not
’N’, the matrix A has been equilibrated with
scaling factors given by R and C. A, AF, and IPIV are not
modified. = ’N’: The matrix A will be copied to
AF and factored.
= ’E’: The matrix A will be equilibrated if
necessary, then copied to AF and factored.
TRANS (input) CHARACTER*1
Specifies the form of the
system of equations:
= ’N’: A * X = B (No transpose)
= ’T’: A**T * X = B (Transpose)
= ’C’: A**H * X = B (Transpose)
N (input) INTEGER
The number of linear equations, i.e., the order of the matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the N-by-N matrix A. If FACT = ’F’ and EQUED is not ’N’, then A must have been equilibrated by the scaling factors in R and/or C. A is not modified if FACT = ’F’ or
On exit, if
EQUED .ne. ’N’, A is scaled as follows: EQUED =
’R’: A := diag(R) * A
EQUED = ’C’: A := A * diag(C)
EQUED = ’B’: A := diag(R) * A * diag(C).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
AF (input or output) DOUBLE PRECISION array, dimension (LDAF,N)
If FACT = ’F’, then AF is an input argument and on entry contains the factors L and U from the factorization A = P*L*U as computed by DGETRF. If EQUED .ne. ’N’, then AF is the factored form of the equilibrated matrix A.
If FACT = ’N’, then AF is an output argument and on exit returns the factors L and U from the factorization A = P*L*U of the original matrix A.
If FACT = ’E’, then AF is an output argument and on exit returns the factors L and U from the factorization A = P*L*U of the equilibrated matrix A (see the description of A for the form of the equilibrated matrix).
LDAF (input) INTEGER
The leading dimension of the array AF. LDAF >= max(1,N).
IPIV (input or output) INTEGER array, dimension (N)
If FACT = ’F’, then IPIV is an input argument and on entry contains the pivot indices from the factorization A = P*L*U as computed by DGETRF; row i of the matrix was interchanged with row IPIV(i).
If FACT = ’N’, then IPIV is an output argument and on exit contains the pivot indices from the factorization A = P*L*U of the original matrix A.
If FACT = ’E’, then IPIV is an output argument and on exit contains the pivot indices from the factorization A = P*L*U of the equilibrated matrix A.
EQUED (input or output) CHARACTER*1
Specifies the form of
equilibration that was done. = ’N’: No
equilibration (always true if FACT = ’N’).
= ’R’: Row equilibration, i.e., A has been
premultiplied by diag(R). = ’C’: Column
equilibration, i.e., A has been postmultiplied by diag(C). =
’B’: Both row and column equilibration, i.e., A
has been replaced by diag(R) * A * diag(C). EQUED is an
input argument if FACT = ’F’; otherwise, it is
an output argument.
R (input or output) DOUBLE PRECISION array, dimension (N)
The row scale factors for A. If EQUED = ’R’ or ’B’, A is multiplied on the left by diag(R); if EQUED = ’N’ or ’C’, R is not accessed. R is an input argument if FACT = ’F’; otherwise, R is an output argument. If FACT = ’F’ and EQUED = ’R’ or ’B’, each element of R must be positive.
C (input or output) DOUBLE PRECISION array, dimension (N)
The column scale factors for A. If EQUED = ’C’ or ’B’, A is multiplied on the right by diag(C); if EQUED = ’N’ or ’R’, C is not accessed. C is an input argument if FACT = ’F’; otherwise, C is an output argument. If FACT = ’F’ and EQUED = ’C’ or ’B’, each element of C must be positive.
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On entry, the N-by-NRHS right hand side matrix B. On exit, if EQUED = ’N’, B is not modified; if TRANS = ’N’ and EQUED = ’R’ or ’B’, B is overwritten by diag(R)*B; if TRANS = ’T’ or ’C’ and EQUED = ’C’ or ’B’, B is overwritten by diag(C)*B.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
X (output) DOUBLE PRECISION array, dimension (LDX,NRHS)
If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X to the original system of equations. Note that A and B are modified on exit if EQUED .ne. ’N’, and the solution to the equilibrated system is inv(diag(C))*X if TRANS = ’N’ and EQUED = ’C’ or ’B’, or inv(diag(R))*X if TRANS = ’T’ or ’C’ and EQUED = ’R’ or ’B’.
LDX (input) INTEGER
The leading dimension of the array X. LDX >= max(1,N).
RCOND (output) DOUBLE PRECISION
The estimate of the reciprocal condition number of the matrix A after equilibration (if done). If RCOND is less than the machine precision (in particular, if RCOND = 0), the matrix is singular to working precision. This condition is indicated by a return code of INFO > 0.
FERR (output) DOUBLE PRECISION array, dimension (NRHS)
The estimated forward error bound for each solution vector X(j) (the j-th column of the solution matrix X). If XTRUE is the true solution corresponding to X(j), FERR(j) is an estimated upper bound for the magnitude of the largest element in (X(j) - XTRUE) divided by the magnitude of the largest element in X(j). The estimate is as reliable as the estimate for RCOND, and is almost always a slight overestimate of the true error.
BERR (output) DOUBLE PRECISION array, dimension (NRHS)
The componentwise relative backward error of each solution vector X(j) (i.e., the smallest relative change in any element of A or B that makes X(j) an exact solution).
WORK (workspace/output) DOUBLE PRECISION array, dimension (4*N)
On exit, WORK(1) contains the reciprocal pivot growth factor norm(A)/norm(U). The "max absolute element" norm is used. If WORK(1) is much less than 1, then the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, condition estimator RCOND, and forward error bound FERR could be unreliable. If factorization fails with 0<INFO<=N, then WORK(1) contains the reciprocal pivot growth factor for the leading INFO columns of A.
IWORK (workspace) INTEGER
array, dimension (N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, and i is
<= N: U(i,i) is exactly zero. The factorization has been
completed, but the factor U is exactly singular, so the
solution and error bounds could not be computed. RCOND = 0
is returned. = N+1: U is nonsingular, but RCOND is less than
machine precision, meaning that the matrix is singular to
working precision. Nevertheless, the solution and error
bounds are computed because there are a number of situations
where the computed solution can be more accurate than the
value of RCOND would suggest.
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dgesvx(l) | |