SRC/dsygvx.f(3)
okay bestie, this is SRC/dsygvx.f(3) from the Library Functions Manual β yes, the manual-page energy is immaculate π
. letβs get into it.
πΈ NAME πΈ
SRC/dsygvx.f β thatβs the function page, periodt π
β¨ SYNOPSIS β¨
π§ Functions/Subroutines π§
subroutine dsygvx (itype, jobz, range, uplo, n, a, lda, b, ldb, vl, vu,
il, iu, abstol, m, w, z, ldz, work, lwork, iwork, ifail, info)
DSYGVX
π Function/Subroutine Documentation π
subroutine dsygvx (integer itype, character jobz, character range, character
uplo, integer n, double precision, dimension( lda, * ) a, integer lda,
double precision, dimension( ldb, * ) b, integer ldb, double precision
vl, double precision vu, integer il, integer iu, double precision
abstol, integer m, double precision, dimension( * ) w, double precision,
dimension( ldz, * ) z, integer ldz, double precision, dimension( * )
work, integer lwork, integer, dimension( * ) iwork, integer, dimension(
* ) ifail, integer info)
DSYGVX
π¦ Purpose π¦
okay so DSYGVX computes selected eigenvalues, and optionally eigenvectors, of a real generalized symmetric-definite eigenproblem, of the form A*x=(lambda)*B*x, A*Bx=(lambda)*x, or B*A*x=(lambda)*x. Here A and B are assumed to be symmetric and B is also positive definite. Eigenvalues and eigenvectors can be selected by specifying either a range of values or a range of indices for the desired eigenvalues. iconic behavior, no cap π
π Parameters π
ITYPEβITYPEisINTEGER. Specifies the problem type to be solved:= 1: A*x = (lambda)*B*x= 2: A*B*x = (lambda)*x= 3: B*A*x = (lambda)*xJOBZβJOBZisCHARACTER*1.= 'N': Compute eigenvalues only;= 'V': Compute eigenvalues and eigenvectors.RANGEβRANGEisCHARACTER*1.= 'A': all eigenvalues will be found.= 'V': all eigenvalues in the half-open interval(VL,VU]will be found.= 'I': theIL-th throughIU-th eigenvalues will be found.UPLOβUPLOisCHARACTER*1.= 'U': Upper triangle of A and B are stored;= 'L': Lower triangle of A and B are stored.NβNisINTEGER. The order of the matrix pencil(A,B).N >= 0.AβAisDOUBLE PRECISIONarray, dimension(LDA, N). On entry, the symmetric matrixA. IfUPLO = 'U', the leadingN-by-Nupper triangular part ofAcontains the upper triangular part of the matrixA. IfUPLO = 'L', the leadingN-by-Nlower triangular part ofAcontains the lower triangular part of the matrixA. On exit, the lower triangle (ifUPLO='L') or the upper triangle (ifUPLO='U') ofA, including the diagonal, is destroyed. yes bestie, destroyed πLDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).BβBisDOUBLE PRECISIONarray, dimension(LDB, N). On entry, the symmetric matrixB. IfUPLO = 'U', the leadingN-by-Nupper triangular part ofBcontains the upper triangular part of the matrixB. IfUPLO = 'L', the leadingN-by-Nlower triangular part ofBcontains the lower triangular part of the matrixB. On exit, ifINFO <= N, the part ofBcontaining the matrix is overwritten by the triangular factorUorLfrom the Cholesky factorizationB = U**T*UorB = L*L**T.LDBβLDBisINTEGER. The leading dimension of the arrayB.LDB >= max(1,N).VLβVLisDOUBLE PRECISION. IfRANGE='V', the lower bound of the interval to be searched for eigenvalues.VL < VU. Not referenced ifRANGE = 'A'or'I'.VUβVUisDOUBLE PRECISION. IfRANGE='V', the upper bound of the interval to be searched for eigenvalues.VL < VU. Not referenced ifRANGE = 'A'or'I'.ILβILisINTEGER. IfRANGE='I', the index of the smallest eigenvalue to be returned.1 <= IL <= IU <= N, ifN > 0;IL = 1andIU = 0ifN = 0. Not referenced ifRANGE = 'A'or'V'.IUβIUisINTEGER. IfRANGE='I', the index of the largest eigenvalue to be returned.1 <= IL <= IU <= N, ifN > 0;IL = 1andIU = 0ifN = 0. Not referenced ifRANGE = 'A'or'V'.ABSTOLβABSTOLisDOUBLE PRECISION. The absolute error tolerance for the eigenvalues. An approximate eigenvalue is accepted as converged when it is determined to lie in an interval[a,b]of width less than or equal to
ABSTOL + EPS * max( |a|,|b| ) ,
where EPS is the machine precision. If ABSTOL is less than or equal to zero, then EPS*|T| will be used in its place, where |T| is the 1-norm of the tridiagonal matrix obtained by reducing C to tridiagonal form, where C is the symmetric matrix of the standard symmetric problem to which the generalized problem is transformed. Eigenvalues will be computed most accurately when ABSTOL is set to twice the underflow threshold 2*DLAMCH('S'), not zero. If this routine returns with INFO>0, indicating that some eigenvectors did not converge, try setting ABSTOL to 2*DLAMCH('S').
MβMisINTEGER. The total number of eigenvalues found.0 <= M <= N. IfRANGE = 'A',M = N, and ifRANGE = 'I',M = IU-IL+1.WβWisDOUBLE PRECISIONarray, dimension(N). On normal exit, the firstMelements contain the selected eigenvalues in ascending order.ZβZisDOUBLE PRECISIONarray, dimension(LDZ, max(1,M)). IfJOBZ = 'N', thenZis not referenced. IfJOBZ = 'V', then ifINFO = 0, the firstMcolumns ofZcontain the orthonormal eigenvectors of the matrixAcorresponding to the selected eigenvalues, with thei-th column ofZholding the eigenvector associated withW(i). The eigenvectors are normalized as follows: ifITYPE = 1or2,Z**T*B*Z = I; ifITYPE = 3,Z**T*inv(B)*Z = I. If an eigenvector fails to converge, then that column ofZcontains the latest approximation to the eigenvector, and the index of the eigenvector is returned inIFAIL. Note: the user must ensure that at leastmax(1,M)columns are supplied in the arrayZ; ifRANGE = 'V', the exact value ofMis not known in advance and an upper bound must be used. bestie, read that note twice fr fr π«ΆLDZβLDZisINTEGER. The leading dimension of the arrayZ.LDZ >= 1, and ifJOBZ = 'V',LDZ >= max(1,N).WORKβWORKisDOUBLE PRECISIONarray, dimension(MAX(1,LWORK)). On exit, ifINFO = 0,WORK(1)returns the optimalLWORK.LWORKβLWORKisINTEGER. The length of the arrayWORK.LWORK >= max(1,8*N). For optimal efficiency,LWORK >= (NB+3)*N, whereNBis the blocksize forDSYTRDreturned byILAENV. IfLWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of theWORKarray, returns this value as the first entry of theWORKarray, and no error message related toLWORKis issued byXERBLA.IWORKβIWORKisINTEGERarray, dimension(5*N).IFAILβIFAILisINTEGERarray, dimension(N). IfJOBZ = 'V', then ifINFO = 0, the firstMelements ofIFAILare zero. IfINFO > 0, thenIFAILcontains the indices of the eigenvectors that failed to converge. IfJOBZ = 'N', thenIFAILis not referenced.INFOβINFOisINTEGER.= 0: successful exit< 0: if INFO = -i, the i-th argument had an illegal value> 0: DPOTRF or DSYEVX returned an error code:<= N: if INFO = i, DSYEVX failed to converge; i eigenvectors failed to converge. Their indices are stored in array IFAIL.> N: if INFO = N + i, for 1 <= i <= N, then the leading principal minor of order i of B is not positive. The factorization of B could not be completed and no eigenvalues or eigenvectors were computed.no cap, that last one is a whole mood π
π Author π
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π Contributors π
- Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA
Definition at line 294 of file dsygvx.f.
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