SRC/zsysvxx.f(3)
Library Functions Manual π SRC/zsysvxx.f(3)
okay bestie, this is the page for SRC/zsysvxx.f, and we are keeping every single receipt. No cap, nothing skipped. β¨
π¦ NAME π¦
SRC/zsysvxx.f
π SYNOPSIS π
π Functions/Subroutines
subroutine zsysvxx (fact, uplo, n, nrhs, a, lda, af, ldaf, ipiv, equed,
s, b, ldb, x, ldx, rcond, rpvgrw, berr, n_err_bnds, err_bnds_norm,
err_bnds_comp, nparams, params, work, rwork, info)
ZSYSVXX computes the solution to system of linear equations A * X = B for SY matrices. Thatβs the whole errand, and itβs iconic. π
πΈ Function/Subroutine Documentation πΈ
subroutine zsysvxx (character fact, character uplo, integer n, integer nrhs,
complex*16, dimension( lda, * ) a, integer lda, complex*16, dimension(
ldaf, * ) af, integer ldaf, integer, dimension( * ) ipiv, character
equed, double precision, dimension( * ) s, complex*16, dimension( ldb, *
) b, integer ldb, complex*16, dimension( ldx, * ) x, integer ldx, double
precision rcond, double precision rpvgrw, double precision, dimension( *
) berr, integer n_err_bnds, double precision, dimension( nrhs, * )
err_bnds_norm, double precision, dimension( nrhs, * ) err_bnds_comp,
integer nparams, double precision, dimension( * ) params, complex*16,
dimension( * ) work, double precision, dimension( * ) rwork, integer
info)
ZSYSVXX computes the solution to system of linear equations A * X = B for SY matrices.
π Purpose π
okay so ZSYSVXX uses the diagonal pivoting factorization to compute the solution to a complex*16 system of linear equations A * X = B, where A is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices.
If requested, both normwise and maximum componentwise error bounds are returned. ZSYSVXX will return a solution with a tiny guaranteed error (O(eps) where eps is the working machine precision) unless the matrix is very ill-conditioned, in which case a warning is returned. Relevant condition numbers also are calculated and returned.
ZSYSVXX accepts user-provided factorizations and equilibration factors; see the definitions of the FACT and EQUED options. Solving with refinement and using a factorization from a previous ZSYSVXX call will also produce a solution with either O(eps) errors or warnings, but we cannot make that claim for general user-provided factorizations and equilibration factors if they differ from what ZSYSVXX would itself produce.
π Description π
The following steps are performed:
- If
FACT = 'E', double precision scaling factors are computed to equilibrate the system:
diag(S)*A*diag(S) *inv(diag(S))*X = diag(S)*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(S)*A*diag(S) and B by diag(S)*B.
- If
FACT = 'N'or'E', the LU decomposition is used to factor the matrixA(after equilibration ifFACT = 'E') as
A = U * D * U**T, if UPLO = 'U', or
A = L * D * L**T, if UPLO = 'L',
where U (or L) is a product of permutation and unit upper (lower) triangular matrices, and D is symmetric and block diagonal with 1-by-1 and 2-by-2 diagonal blocks.
- If some
D(i,i)=0, so thatDis exactly singular, then the routine returns withINFO = i. Otherwise, the factored form ofAis used to estimate the condition number of the matrixA(see argumentRCOND). If the reciprocal of the condition number is less than machine precision, the routine still goes on to solve forXand compute error bounds as described below. - The system of equations is solved for
Xusing the factored form ofA. - By default (unless
PARAMS(LA_LINRX_ITREF_I)is set to zero), the routine will use iterative refinement to try to get a small error and error bounds. Refinement calculates the residual to at least twice the working precision. - If equilibration was used, the matrix
Xis premultiplied bydiag(R)so that it solves the original system before equilibration.
Some optional parameters are bundled in the PARAMS array. These settings determine how refinement is performed, but often the defaults are acceptable. If the defaults are acceptable, users can pass NPARAMS = 0 which prevents the source code from accessing the PARAMS argument.
β¨ Parameters β¨
FACT
FACT is CHARACTER*1.
It 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,AFandIPIVcontain the factored form ofA. IfEQUEDis not'N', the matrixAhas been equilibrated with scaling factors given byS.A,AF, andIPIVare not modified.= 'N': The matrixAwill be copied toAFand factored.= 'E': The matrixAwill be equilibrated if necessary, then copied toAFand factored.
UPLO
UPLO is CHARACTER*1.
= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
N
N is INTEGER.
The number of linear equations, i.e., the order of the matrix A. N >= 0.
NRHS
NRHS is INTEGER.
The number of right hand sides, i.e., the number of columns of the matrices B and X. NRHS >= 0.
A
A is COMPLEX*16 array, dimension (LDA,N).
The symmetric matrix A. If UPLO = 'U', the leading N-by-N upper triangular part of A contains the upper triangular part of the matrix A, and the strictly lower triangular part of A is not referenced. If UPLO = 'L', the leading N-by-N lower triangular part of A contains the lower triangular part of the matrix A, and the strictly upper triangular part of A is not referenced.
On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by diag(S)*A*diag(S).
LDA
LDA is INTEGER.
The leading dimension of the array A. LDA >= max(1,N).
AF
AF is COMPLEX*16 array, dimension (LDAF,N).
If FACT = 'F', then AF is an input argument and on entry contains the block diagonal matrix D and the multipliers used to obtain the factor U or L from the factorization A = U*D*U**T or A = L*D*L**T as computed by ZSYTRF.
If FACT = 'N', then AF is an output argument and on exit returns the block diagonal matrix D and the multipliers used to obtain the factor U or L from the factorization A = U*D*U**T or A = L*D*L**T.
LDAF
LDAF is INTEGER.
The leading dimension of the array AF. LDAF >= max(1,N).
IPIV
IPIV is INTEGER array, dimension (N).
If FACT = 'F', then IPIV is an input argument and on entry contains details of the interchanges and the block structure of D, as determined by ZSYTRF. If IPIV(k) > 0, then rows and columns k and IPIV(k) were interchanged and D(k,k) is a 1-by-1 diagonal block. If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k) is a 2-by-2 diagonal block. If UPLO = 'L' and IPIV(k) = IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
If FACT = 'N', then IPIV is an output argument and on exit contains details of the interchanges and the block structure of D, as determined by ZSYTRF.
EQUED
EQUED is CHARACTER*1.
Specifies the form of equilibration that was done.
= 'N': No equilibration (always true ifFACT = 'N').= 'Y': Both row and column equilibration, i.e.,Ahas been replaced bydiag(S) * A * diag(S).
EQUED is an input argument if FACT = 'F'; otherwise, it is an output argument.
S
S is DOUBLE PRECISION array, dimension (N).
The scale factors for A. If EQUED = 'Y', A is multiplied on the left and right by diag(S). S is an input argument if FACT = 'F'; otherwise, S is an output argument. If FACT = 'F' and EQUED = 'Y', each element of S must be positive. If S is output, each element of S is a power of the radix. If S is input, each element of S should be a power of the radix to ensure a reliable solution and error estimates. Scaling by powers of the radix does not cause rounding errors unless the result underflows or overflows. Rounding errors during scaling lead to refining with a matrix that is not equivalent to the input matrix, producing error estimates that may not be reliable.
B
B is COMPLEX*16 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 EQUED = 'Y', B is overwritten by diag(S)*B.
LDB
LDB is INTEGER.
The leading dimension of the array B. LDB >= max(1,N).
X
X is COMPLEX*16 array, dimension (LDX,NRHS).
If INFO = 0, 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(S))*X.
LDX
LDX is INTEGER.
The leading dimension of the array X. LDX >= max(1,N).
RCOND
RCONDβDOUBLE PRECISION. This is the reciprocal scaled condition number, bestie. It estimates the reciprocal Skeel condition number of the matrixAafter equilibration (if equilibration was done). If itβs less than machine precision β and especially if itβs zero β thenAis singular to working precision. Tiny caveat with huge energy: the error can still be small even if this number is very small and the matrix looks ill-conditioned. πRPVGRWβDOUBLE PRECISION. Reciprocal pivot growth. On exit, this contains the reciprocal pivot growth factornorm(A)/norm(U). The source literally saysThe norm is used.If this is much less than 1, then the stability of the LU factorization of the (equilibrated) matrixAcould be poor. That also means the solutionX, the estimated condition numbers, and the error bounds could be unreliable. If factorization fails with0<INFO<=N, then this contains the reciprocal pivot growth factor for the leadingINFOcolumns ofA.BERRβDOUBLE PRECISIONarray, dimension(NRHS). Componentwise relative backward error. For each solution vectorX(j), this is the smallest relative change in any element ofAorBthat makesX(j)an exact solution.N_ERR_BNDSβINTEGER. Number of error bounds to return for each right-hand side and each type (normwise or componentwise). SeeERR_BNDS_NORMandERR_BNDS_COMPbelow. πERR_BNDS_NORMβDOUBLE PRECISIONarray, dimension(NRHS, N_ERR_BNDS). For each right-hand side, this array contains info about various error bounds and condition numbers corresponding to the normwise relative error, which is defined as follows:
max_j (abs(XTRUE(j,i) - X(j,i)))
------------------------------
max_j abs(X(j,i))
The array is indexed by the type of error information as described below. There currently are up to three pieces of information returned.
The first index in ERR_BNDS_NORM(i,:) corresponds to the ith right-hand side.
The second index in ERR_BNDS_NORM(:,err) contains these three fields:
err = 1β boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * dlamch('Epsilon').err = 2β error bound: the estimated forward error, almost certainly within a factor of 10 of the true error so long as the next entry is greater than the thresholdsqrt(n) * dlamch('Epsilon'). This error bound should only be trusted if the previous boolean is true.err = 3β reciprocal condition number: estimated normwise reciprocal condition number. Compared with the thresholdsqrt(n) * dlamch('Epsilon')to determine if the error estimate is β¦ (the original sentence trails off there, bestie, no cap). These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrixZ. LetZ = S*A, whereSscales each row by a power of the radix so all absolute row sums ofZare approximately 1.
See Lapack Working Note 165 for further details and extra cautions.
ERR_BNDS_COMPβDOUBLE PRECISIONarray, dimension(NRHS, N_ERR_BNDS). For each right-hand side, this array contains info about various error bounds and condition numbers corresponding to the componentwise relative error, which is defined as follows:
abs(XTRUE(j,i) - X(j,i))
max_j ----------------------
abs(X(j,i))
The array is indexed by the right-hand side i (the componentwise relative error depends on it), and the type of error information as described below. There currently are up to three pieces of information returned for each right-hand side. If componentwise accuracy is not requested (PARAMS(3) = 0.0), then ERR_BNDS_COMP is not accessed. If N_ERR_BNDS < 3, then at most the first (:,N_ERR_BNDS) entries are returned.
The first index in ERR_BNDS_COMP(i,:) corresponds to the ith right-hand side.
The second index in ERR_BNDS_COMP(:,err) contains these three fields:
err = 1β boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * dlamch('Epsilon').err = 2β error bound: the estimated forward error, almost certainly within a factor of 10 of the true error so long as the next entry is greater than the thresholdsqrt(n) * dlamch('Epsilon'). This error bound should only be trusted if the previous boolean is true.err = 3β reciprocal condition number: estimated componentwise reciprocal condition number. Compared with the thresholdsqrt(n) * dlamch('Epsilon')to determine if the error estimate is β¦ (same source blank, same vibe). These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrixZ. LetZ = S*(A*diag(x)), wherexis the solution for the current right-hand side andSscales each row ofA*diag(x)by a power of the radix so all absolute row sums ofZare approximately 1.
See Lapack Working Note 165 for further details and extra cautions.
NPARAMSβINTEGER. Specifies the number of parameters set inPARAMS. If<= 0, thePARAMSarray is never referenced and default values are used.PARAMSβDOUBLE PRECISIONarray, dimensionNPARAMS. Specifies algorithm parameters. If an entry is< 0.0, then that entry will be filled with the default value used for that parameter. Only positions up toNPARAMSare accessed; defaults are used for higher-numbered parameters.PARAMS(LA_LINRX_ITREF_I = 1)β whether to perform iterative refinement or not.- Default:
1.0D+0 = 0.0: no refinement is performed, and no error bounds are computed.= 1.0: use the extra-precise refinement algorithm. (Other values are reserved for future use.)
- Default:
PARAMS(LA_LINRX_ITHRESH_I = 2)β maximum number of residual computations allowed for refinement.- Default:
10 - Aggressive: set to
100to permit convergence using approximate factorizations or factorizations other than LU. If the factorization uses a technique other than Gaussian elimination, the guarantees inerr_bnds_normanderr_bnds_compmay no longer be trustworthy.
- Default:
PARAMS(LA_LINRX_CWISE_I = 3)β flag determining if the code will attempt to find a solution with small componentwise relative error in the double-precision algorithm. Positive is true,0.0is false.- Default:
1.0(attempt componentwise convergence)
- Default:
WORKβCOMPLEX*16array, dimension(2*N).RWORKβDOUBLE PRECISIONarray, dimension(2*N).INFOβINTEGER.= 0: successful exit. The solution to every right-hand side is guaranteed.< 0: ifINFO = -i, theith argument had an illegal value.> 0 and <= N:U(INFO,INFO)is exactly zero. The factorization has been completed, but the factorUis exactly singular, so the solution and error bounds could not be computed.RCOND = 0is returned.= N+J: the solution corresponding to theJth right-hand side is not guaranteed. The solutions corresponding to other right-hand sidesKwithK > Jmay not be guaranteed as well, but only the first such right-hand side is reported. If a small componentwise error is not requested (PARAMS(3) = 0.0) then theJth right-hand side is the first with a normwise error bound that is not guaranteed (the smallestJsuch thatERR_BNDS_NORM(J,1) = 0.0). By default (PARAMS(3) = 1.0) theJth right-hand side is the first with either a normwise or componentwise error bound that is not guaranteed (the smallestJsuch that eitherERR_BNDS_NORM(J,1) = 0.0orERR_BNDS_COMP(J,1) = 0.0). See the definition ofERR_BNDS_NORM(:,1)andERR_BNDS_COMP(:,1). To get information about all of the right-hand sides checkERR_BNDS_NORMorERR_BNDS_COMP.
π Author & Definition π
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition at line 502 of file zsysvxx.f.
Okay bestie, thatβs the whole continued argument saga. The footer energy: this page was generated automatically by Doxygen for LAPACK from the source code, and itβs LAPACK Version 3.12.0, SRC/zsysvxx.f(3). Stay accurate, stay slay, and may your condition numbers be trustworthy. πβ¨π
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