DDRVSX(3)

📦 version 3.12.0, in opensuse-leap 16.0

💅 NAME

/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/TESTING/EIG/ddrvsx.f — okay so this is the ddrvsx.f(3) page from the Library Functions Manual. Iconic. 💖

✨ SYNOPSIS

💖 Functions/Subroutines

subroutine DDRVSX (nsizes, nn, ntypes, dotype, iseed, thresh, niunit,
    nounit, a, lda, h, ht, wr, wi, wrt, wit, wrtmp, witmp, vs, ldvs,
    vs1, result, work, lwork, iwork, bwork, info)

DDRVSX — that's the subroutine, no notes. 💅

🌸 Function/Subroutine Documentation

🌟 subroutine DDRVSX

subroutine DDRVSX (integer nsizes, integer, dimension( * ) nn, integer
       ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
       double precision thresh, integer niunit, integer nounit, double
       precision, dimension( lda, * ) a, integer lda, double precision,
       dimension( lda, * ) h, double precision, dimension( lda, * ) ht, double
       precision, dimension( * ) wr, double precision, dimension( * ) wi,
       double precision, dimension( * ) wrt, double precision, dimension( * )
       wit, double precision, dimension( * ) wrtmp, double precision,
       dimension( * ) witmp, double precision, dimension( ldvs, * ) vs, integer
       ldvs, double precision, dimension( ldvs, * ) vs1, double precision,
       dimension( 17 ) result, double precision, dimension( * ) work, integer
       lwork, integer, dimension( * ) iwork, logical, dimension( * ) bwork,
       integer info)

DDRVSX — yes bestie, she's the whole main character here. 👑

🎀 Purpose

DDRVSX checks the nonsymmetric eigenvalue (Schur form) problem expert driver DGEESX. No cap, that's the assignment. 🔥

DDRVSX uses both test matrices generated randomly depending on data supplied in the calling sequence, as well as on data read from an input file and including precomputed condition numbers to which it compares the ones it computes. 🦋

When DDRVSX is called, a number of matrix () and a number of matrix are specified. For each size () 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 ) — 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 WR+sqrt(-1)*WI 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 ) — 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 WR+sqrt(-1)*WI are eigenvalues of T, 1/ulp otherwise. If workspace sufficient, also compare WR, WI 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 are specified by an array NN(1:NSIZES); the value of each element NN(j) specifies one size. The are specified by a logical array DOTYPE( 1:NTYPES ); if DOTYPE(j) is .TRUE., then matrix type 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 signs. (ULP = (first number larger than 1) - 1 )
  5. A diagonal matrix with geometrically spaced entries 1, ..., ULP and random signs.
  6. A diagonal matrix with entries 1, ULP, ..., ULP and random signs.
  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 orthogonal and T has evenly spaced entries 1, ..., ULP with random signs on the diagonal and random O(1) entries in the upper triangle.
  10. A matrix of the form U' T U, where U is orthogonal and T has geometrically spaced entries 1, ..., ULP with random signs 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 signs on the diagonal and random O(1) entries in the upper triangle.
  12. A matrix of the form U' T U, where U is orthogonal and T has real or complex conjugate paired eigenvalues randomly chosen from ( ULP, 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 signs 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 signs 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 signs 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 real or complex conjugate paired eigenvalues randomly chosen from ( ULP, 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: 🫶

  • (16) |RCONDE - RCDEIN| / cond(RCONDE) — RCONDE is the reciprocal average eigenvalue condition number computed by DGEESX 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. 💖
  • (17) |RCONDV - RCDVIN| / cond(RCONDV) — RCONDV is the reciprocal right invariant subspace condition number computed by DGEESX 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 — INTEGER. The number of elements in DOTYPE. NTYPES must be at least zero. If it’s zero, no randomly generated test matrices are tested, but test matrices read from NIUNIT will still 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 — 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 — 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 DDRVSX to continue the same random number sequence. 🎀
  • THRESH — DOUBLE PRECISION. A test will count as an error if the error, 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 — INTEGER. The FORTRAN unit number for reading in the data file of problems to solve. 🌸
  • NOUNIT — INTEGER. The FORTRAN unit number for printing out error messages (e.g., if a routine returns INFO not equal to 0). 😭
  • A — DOUBLE PRECISION 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 — INTEGER. The leading dimension of A, and H. LDA must be at least 1 and at least max( NN ). ⭐
  • H — DOUBLE PRECISION array, dimension (LDA, max(NN)). Another copy of the test matrix A, modified by DGEESX. 🦋
  • HT — DOUBLE PRECISION array, dimension (LDA, max(NN)). Yet another copy of the test matrix A, modified by DGEESX. 🧚
  • WR — DOUBLE PRECISION array, dimension (max(NN)). 🌈
  • WI — DOUBLE PRECISION array, dimension (max(NN)). The real and imaginary parts of the eigenvalues of A. On exit, WR + WI*i are the eigenvalues of the matrix in A. 👑
  • WRT — DOUBLE PRECISION array, dimension (max(NN)). 🌟
  • WIT — DOUBLE PRECISION array, dimension (max(NN)). Like WR, WI, these arrays contain the eigenvalues of A, but those computed when DGEESX only computes a partial eigendecomposition, i.e. not Schur vectors. 💜
  • WRTMP — DOUBLE PRECISION array, dimension (max(NN)). 🍓
  • WITMP — DOUBLE PRECISION array, dimension (max(NN)). More temporary storage for eigenvalues. 💀
  • VS — DOUBLE PRECISION array, dimension (LDVS, max(NN)). VS holds the computed Schur vectors. ✨
  • LDVS — INTEGER. Leading dimension of VS. Must be at least max(1,max(NN)). 🎀
  • VS1 — DOUBLE PRECISION array, dimension (LDVS, max(NN)). VS1 holds another copy of the computed Schur vectors. 🫶
  • RESULT — DOUBLE PRECISION array, dimension (17). The values computed by the 17 tests described above. The values are currently limited to 1/ulp, to avoid overflow. 🔥
  • WORK — DOUBLE PRECISION array, dimension (LWORK). 🌸
  • LWORK — INTEGER. The number of entries in WORK. This must be at least max(3*NN(j),2*NN(j)**2) for all j. 😭
  • IWORK — INTEGER array, dimension (max(NN)*max(NN)). 🦋
  • BWORK — LOGICAL array, dimension (max(NN)). 🧚
  • INFO — INTEGER. If 0, successful exit. If <0, input parameter -INFO is incorrect. If >0, DLATMR, SLATMS, SLATME or DGET24 returned an error code and INFO is its absolute value. 💅

✨ Some Local Variables and Parameters

  • ZERO, ONE — real 0 and 1.
  • MAXTYP — the number of types defined.
  • NMAX — largest value in NN.
  • NERRS — the number of tests which have exceeded THRESH.
  • COND, CONDS, IMODE — values to be passed to the matrix generators.
  • ANORM — norm of A; passed to matrix generators.
  • OVFL, UNFL — overflow and underflow thresholds.
  • ULP, ULPINV — finest relative precision and its inverse.
  • RTULP, RTULPI — square roots of the previous 4 values.

The following four arrays decode JTYPE:

  • KTYPE(j) — the general type (1-10) for type j.
  • KMODE(j) — the MODE value to be passed to the matrix generator for type j.
  • KMAGN(j) — the order of magnitude (O(1), O(overflow^(1/2) ), O(underflow^(1/2) )).
  • KCONDS(j) — selects whether CONDS is to be 1 or 1/sqrt(ulp). (0 means irrelevant.) 💀

✨ Author

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

Definition at line 450 of file ddrvsx.f.

✨ Author (yes, again, bestie)

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💖 source/version vibes: /home/abui...IG/ddrvsx.f(3) and LAPACK Version 3.12.0. The footer didn’t give us a separate date, so no invented one — just slay. 🎀

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