CDRVSX(3)

πŸ“¦ version 3.12.0, in opensuse-leap 16.0

πŸ’… CDRVSX(3) β€” Library Functions Manual, but make it bestie πŸ’…

Okay so this is the manual page for CDRVSX(3) β€” and yes, the actual file is /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/TESTING/EIG/cdrvsx.f. We are in the Library Functions Manual, bestie. Slay. 🫢

πŸ“› NAME πŸ“›

/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/TESTING/EIG/cdrvsx.f β€” that's the path this page is serving, no cap. πŸ’…

πŸ¦‹ SYNOPSIS πŸ¦‹

✨ Functions/Subroutines ✨

subroutine CDRVSX (nsizes, nn, ntypes, dotype, iseed, thresh, niunit,
    nounit, a, lda, h, ht, w, wt, wtmp, vs, ldvs, vs1, result, work,
    lwork, rwork, bwork, info)

CDRVSX β€” that's the subroutine, bestie. Periodt. ✨

πŸ’– Function/Subroutine Documentation πŸ’–

🌸 subroutine CDRVSX 🌸

subroutine CDRVSX (integer nsizes, integer, dimension( * ) nn, integer
    ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
    real thresh, integer niunit, integer nounit, complex, dimension( lda, *
    ) a, integer lda, complex, dimension( lda, * ) h, complex, dimension(
    lda, * ) ht, complex, dimension( * ) w, complex, dimension( * ) wt,
    complex, dimension( * ) wtmp, complex, dimension( ldvs, * ) vs, integer
    ldvs, complex, dimension( ldvs, * ) vs1, real, dimension( 17 ) result,
    complex, dimension( * ) work, integer lwork, real, dimension( * ) rwork,
    logical, dimension( * ) bwork, integer info)

CDRVSX πŸ’…

πŸŽ€ Purpose πŸŽ€

Okay bestie, so CDRVSX checks the nonsymmetric eigenvalue (Schur form) problem expert driver CGEESX. It checks it checks it. It uses both test matrices generated randomly depending on data supplied in the calling sequence, and data read from an input file, including precomputed condition numbers to which it compares the ones it computes. Iconic behavior. 🌈

When CDRVSX is called, a number of matrix sizes (NSIZES) and a number of matrix types (NTYPES) are specified. For each size (NN(j)) and each type of matrix, one matrix will be generated and used to test the nonsymmetric eigenroutines. For each matrix, 15 tests will be performed:

  1. 0 if T is in Schur form, 1/ulp otherwise (no sorting of eigenvalues)
  2. | A - VS T VS' | / ( n |A| ulp ) β€” here VS is the matrix of Schur eigenvectors, and T is in Schur form (no sorting of eigenvalues).
  3. | I - VS VS' | / ( n ulp ) (no sorting of eigenvalues).
  4. 0 if W are eigenvalues of T, 1/ulp otherwise (no sorting of eigenvalues)
  5. 0 if T(with VS) = T(without VS), 1/ulp otherwise (no sorting of eigenvalues)
  6. 0 if eigenvalues(with VS) = eigenvalues(without VS), 1/ulp otherwise (no sorting of eigenvalues)
  7. 0 if T is in Schur form, 1/ulp otherwise (with sorting of eigenvalues)
  8. | A - VS T VS' | / ( n |A| ulp ) β€” here VS is the matrix of Schur eigenvectors, and T is in Schur form (with sorting of eigenvalues).
  9. | I - VS VS' | / ( n ulp ) (with sorting of eigenvalues).
  10. 0 if W are eigenvalues of T, 1/ulp otherwise. If workspace sufficient, also compare W with and without reciprocal condition numbers (with sorting of eigenvalues)
  11. 0 if T(with VS) = T(without VS), 1/ulp otherwise. If workspace sufficient, also compare T with and without reciprocal condition numbers (with sorting of eigenvalues)
  12. 0 if eigenvalues(with VS) = eigenvalues(without VS), 1/ulp otherwise. If workspace sufficient, also compare VS with and without reciprocal condition numbers (with sorting of eigenvalues)
  13. if sorting worked and SDIM is the number of eigenvalues which were SELECTed. If workspace sufficient, also compare SDIM with and without reciprocal condition numbers
  14. if RCONDE the same no matter if VS and/or RCONDV computed
  15. if RCONDV the same no matter if VS and/or RCONDE computed

The sizes are specified by an array NN(1:NSIZES); the value of each element NN(j) specifies one size. The types are specified by a logical array DOTYPE( 1:NTYPES ); if DOTYPE(j) is .TRUE., then matrix type j will be generated. Currently, the list of possible types is:

  1. The zero matrix.
  2. The identity matrix.
  3. A (transposed) Jordan block, with 1's on the diagonal.
  4. A diagonal matrix with evenly spaced entries 1, ..., ULP and random complex angles. (ULP = (first number larger than 1) - 1 )
  5. A diagonal matrix with geometrically spaced entries 1, ..., ULP and random complex angles.
  6. A diagonal matrix with entries 1, ULP, ..., ULP and random complex angles.
  7. Same as (4), but multiplied by a constant near the overflow threshold
  8. Same as (4), but multiplied by a constant near the underflow threshold
  9. A matrix of the form U' T U, where U is unitary and T has evenly spaced entries 1, ..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  10. A matrix of the form U' T U, where U is unitary and T has geometrically spaced entries 1, ..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  11. A matrix of the form U' T U, where U is orthogonal and T has entries 1, ULP,..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  12. A matrix of the form U' T U, where U is unitary and T has complex eigenvalues randomly chosen from ULP < |z| < 1 and random O(1) entries in the upper triangle.
  13. A matrix of the form X' T X, where X has condition SQRT( ULP ) and T has evenly spaced entries 1, ..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  14. A matrix of the form X' T X, where X has condition SQRT( ULP ) and T has geometrically spaced entries 1, ..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  15. A matrix of the form X' T X, where X has condition SQRT( ULP ) and T has entries 1, ULP,..., ULP with random complex angles on the diagonal and random O(1) entries in the upper triangle.
  16. A matrix of the form X' T X, where X has condition SQRT( ULP ) and T has complex eigenvalues randomly chosen from ULP < |z| < 1 and random O(1) entries in the upper triangle.
  17. Same as (16), but multiplied by a constant near the overflow threshold
  18. Same as (16), but multiplied by a constant near the underflow threshold
  19. Nonsymmetric matrix with random entries chosen from (-1,1). If N is at least 4, all entries in first two rows and last row, and first column and last two columns are zero.
  20. Same as (19), but multiplied by a constant near the overflow threshold
  21. Same as (19), but multiplied by a constant near the underflow threshold

In addition, an input file will be read from logical unit number NIUNIT. The file contains matrices along with precomputed eigenvalues and reciprocal condition numbers for the eigenvalue average and right invariant subspace. For these matrices, in addition to tests (1) to (15) we will compute the following two tests:

  1. |RCONDE - RCDEIN| / cond(RCONDE) β€” RCONDE is the reciprocal average eigenvalue condition number computed by CGEESX and RCDEIN (the precomputed true value) is supplied as input. cond(RCONDE) is the condition number of RCONDE, and takes errors in computing RCONDE into account, so that the resulting quantity should be O(ULP). cond(RCONDE) is essentially given by norm(A)/RCONDV.
  2. |RCONDV - RCDVIN| / cond(RCONDV) β€” RCONDV is the reciprocal right invariant subspace condition number computed by CGEESX and RCDVIN (the precomputed true value) is supplied as input. cond(RCONDV) is the condition number of RCONDV, and takes errors in computing RCONDV into account, so that the resulting quantity should be O(ULP). cond(RCONDV) is essentially given by norm(A)/RCONDE.

🌈 Parameters 🌈

🌸 NSIZES 🌸

NSIZES is INTEGER. The number of sizes of matrices to use. NSIZES must be at least zero. If it is zero, no randomly generated matrices are tested, but any test matrices read from NIUNIT will be tested.

🌸 NN 🌸

NN is INTEGER array, dimension (NSIZES). An array containing the sizes to be used for the matrices. Zero values will be skipped. The values must be at least zero.

🌸 NTYPES 🌸

NTYPES is INTEGER. The number of elements in DOTYPE. NTYPES must be at least zero. If it is zero, no randomly generated test matrices are tested, but any test matrices read from NIUNIT will be tested. If it is MAXTYP+1 and NSIZES is 1, then an additional type, MAXTYP+1 is defined, which is to use whatever matrix is in A. This is only useful if DOTYPE(1:MAXTYP) is .FALSE. and DOTYPE(MAXTYP+1) is .TRUE. .

🌸 DOTYPE 🌸

Okay bestie, we're picking up mid-argument-list because the plot only thickens from here 🍿✨

  • DOTYPE β€” LOGICAL array, dimension (NTYPES). If DOTYPE(j) is .TRUE., then for each size in NN a matrix of that size and of type j will be generated. If NTYPES is smaller than the maximum number of types defined (PARAMETER MAXTYP), then types NTYPES+1 through MAXTYP will not be generated. If NTYPES is larger than MAXTYP, DOTYPE(MAXTYP+1) through DOTYPE(NTYPES) will be ignored.
  • ISEED β€” INTEGER array, dimension (4). On entry ISEED specifies the seed of the random number generator. The array elements should be between 0 and 4095; if not they will be reduced mod 4096. Also, ISEED(4) must be odd. The random number generator uses a linear congruential sequence limited to small integers, and so should produce machine independent random numbers. The values of ISEED are changed on exit, and can be used in the next call to CDRVSX to continue the same random number sequence. πŸ”
  • THRESH β€” REAL. A test will count as if the , computed as described above, exceeds THRESH. Note that the error is scaled to be O(1), so THRESH should be a reasonably small multiple of 1, e.g., 10 or 100. In particular, it should not depend on the precision (single vs. double) or the size of the matrix. It must be at least zero. 🚨
  • NIUNIT β€” INTEGER. The FORTRAN unit number for reading in the data file of problems to solve.
  • NOUNIT β€” INTEGER. The FORTRAN unit number for printing out error messages (e.g., if a routine returns INFO not equal to 0.)
  • A β€” COMPLEX array, dimension (LDA, max(NN)). Used to hold the matrix whose eigenvalues are to be computed. On exit, A contains the last matrix actually used.
  • LDA β€” INTEGER. The leading dimension of A, and H. LDA must be at least 1 and at least max( NN ).
  • H β€” COMPLEX array, dimension (LDA, max(NN)). Another copy of the test matrix A, modified by CGEESX.
  • HT β€” COMPLEX array, dimension (LDA, max(NN)). Yet another copy of the test matrix A, modified by CGEESX.
  • W β€” COMPLEX array, dimension (max(NN)). The computed eigenvalues of A.
  • WT β€” COMPLEX array, dimension (max(NN)). Like W, this array contains the eigenvalues of A, but those computed when CGEESX only computes a partial eigendecomposition, i.e. not Schur vectors.
  • WTMP β€” COMPLEX array, dimension (max(NN)). More temporary storage for eigenvalues.
  • VS β€” COMPLEX array, dimension (LDVS, max(NN)). VS holds the computed Schur vectors.
  • LDVS β€” INTEGER. Leading dimension of VS. Must be at least max(1,max(NN)).
  • VS1 β€” COMPLEX array, dimension (LDVS, max(NN)). VS1 holds another copy of the computed Schur vectors.
  • RESULT β€” REAL array, dimension (17). The values computed by the 17 tests described above. The values are currently limited to 1/ulp, to avoid overflow.
  • WORK β€” COMPLEX array, dimension (LWORK).
  • LWORK β€” INTEGER. The number of entries in WORK. This must be at least max(1,2*NN(j)**2) for all j.
  • RWORK β€” REAL array, dimension (max(NN)).
  • BWORK β€” LOGICAL array, dimension (max(NN)).
  • INFO β€” INTEGER. Here's the tea β˜•:
    • 0 β€” successful exit.
    • <0 β€” input parameter -INFO is incorrect.
    • >0 β€” CLATMR, CLATMS, CLATME or CGET24 returned an error code and INFO is its absolute value.

πŸ” Some Local Variables and Parameters

Bestie, these are the backstage crew β€” no cap, they matter:

  • ZERO, ONE β€” Real 0 and 1.
  • MAXTYP β€” The number of types defined.
  • NMAX β€” Largest value in NN.
  • NERRS β€” The number of tests which have exceeded THRESH
  • COND, CONDS, IMODE β€” Values to be passed to the matrix generators.
  • ANORM β€” Norm of A; passed to matrix generators.
  • OVFL, UNFL β€” Overflow and underflow thresholds.
  • ULP, ULPINV β€” Finest relative precision and its inverse.
  • RTULP, RTULPI β€” Square roots of the previous 4 values.
  • The following four arrays decode JTYPE:
    • KTYPE(j) β€” The general type (1-10) for type .
    • KMODE(j) β€” The MODE value to be passed to the matrix generator for type .
    • KMAGN(j) β€” The order of magnitude ( O(1), O(overflow^(1/2) ), O(underflow^(1/2) )
    • KCONDS(j) β€” Selectw whether CONDS is to be 1 or 1/sqrt(ulp). (0 means irrelevant.)

πŸ‘‘ Author

  • Univ. of Tennessee
  • Univ. of California Berkeley
  • Univ. of Colorado Denver
  • NAG Ltd.

Definition at line 431 of file cdrvsx.f.

πŸ€– Author

Generated automatically by Doxygen for LAPACK from the source code.


That's the whole vibe, bestie! This iconic page is from LAPACK Version 3.12.0, path /home/abui...IG/cdrvsx.f(3) β€” now go slay those eigenvalues and remember: you're the main character of linear algebra πŸ’…βœ¨πŸ¦‹

πŸ“¦ where this page comes from