TESTING/EIG/sdrvvx.f(3)

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version 3.12.1 · 2 versions
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💅 TESTING/EIG/sdrvvx.f 💅

ok so quick vibe check first: this page is from the Library Functions Manual, and it's the whole tea on sdrvvx — the expert-driver test routine for the nonsymmetric eigenvalue problem. grab a snack bestie, it's a long one 🍓

✨ NAME ✨

TESTING/EIG/sdrvvx.f — no cap, that's the whole name 🫶

🦋 SYNOPSIS 🦋

🌈 Functions/Subroutines 🌈

subroutine sdrvvx (nsizes, nn, ntypes, dotype, iseed, thresh, niunit,
    nounit, a, lda, h, wr, wi, wr1, wi1, vl, ldvl, vr, ldvr, lre, ldlre,
    rcondv, rcndv1, rcdvin, rconde, rcnde1, rcdein, scale, scale1,
    result, work, nwork, iwork, info)

SDRVVX 💫 (yes that's just the name again, slay)

🎀 Function/Subroutine Documentation 🎀

💖 subroutine sdrvvx

here's the full lil' signature, every single argument, typed and everything — do NOT lose track of these, there are like a million 😭

subroutine sdrvvx (integer nsizes, integer, dimension( * ) nn, integer
    ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
    real thresh, integer niunit, integer nounit, real, dimension( lda, * )
    a, integer lda, real, dimension( lda, * ) h, real, dimension( * ) wr,
    real, dimension( * ) wi, real, dimension( * ) wr1, real, dimension( * )
    wi1, real, dimension( ldvl, * ) vl, integer ldvl, real, dimension( ldvr,
    * ) vr, integer ldvr, real, dimension( ldlre, * ) lre, integer ldlre,
    real, dimension( * ) rcondv, real, dimension( * ) rcndv1, real,
    dimension( * ) rcdvin, real, dimension( * ) rconde, real, dimension( * )
    rcnde1, real, dimension( * ) rcdein, real, dimension( * ) scale, real,
    dimension( * ) scale1, real, dimension( 11 ) result, real, dimension( *
    ) work, integer nwork, integer, dimension( * ) iwork, integer info)

SDRVVX 👑

🌸 Purpose 🌸

ok so picture this: SDRVVX checks the nonsymmetric eigenvalue problem expert driver SGEEVX. that's literally its whole job 💅

SDRVVX 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 that file includes precomputed condition numbers, which it compares against the ones it computes itself. messy but iconic.

When SDRVVX is called, a number of matrix () and a number of matrix are specified in the calling sequence. For each size () and each type of matrix, one matrix will be generated and used to test the nonsymmetric eigenroutines. And for each matrix, 9 tests get performed 🔥

  1. | A * VR - VR * W | / ( n |A| ulp )

Here VR is the matrix of unit right eigenvectors. W is a block diagonal matrix, with a 1x1 block for each real eigenvalue and a 2x2 block for each complex conjugate pair. If eigenvalues j and j+1 are a complex conjugate pair, so WR(j) = WR(j+1) = wr and WI(j) = - WI(j+1) = wi, then the 2 x 2 block corresponding to the pair will be:

(  wr  wi  )
( -wi  wr  )

Such a block multiplying an n x 2 matrix ( ur ui ) on the right will be the same as multiplying ur + i*ui by wr + i*wi.

  1. | A**H * VL - VL * W**H | / ( n |A| ulp )

Here VL is the matrix of unit left eigenvectors, A**H is the conjugate transpose of A, and W is as above.

  1. | |VR(i)| - 1 | / ulp and largest component real

VR(i) denotes the i-th column of VR.

  1. | |VL(i)| - 1 | / ulp and largest component real

VL(i) denotes the i-th column of VL.

  1. W(full) = W(partial)

W(full) denotes the eigenvalues computed when VR, VL, RCONDV and RCONDE are also computed, and W(partial) denotes the eigenvalues computed when only some of VR, VL, RCONDV, and RCONDE are computed.

  1. VR(full) = VR(partial)

VR(full) denotes the right eigenvectors computed when VL, RCONDV and RCONDE are computed, and VR(partial) denotes the result when only some of VL and RCONDV are computed.

  1. VL(full) = VL(partial)

VL(full) denotes the left eigenvectors computed when VR, RCONDV and RCONDE are computed, and VL(partial) denotes the result when only some of VR and RCONDV are computed.

  1. this one's giving conditional energy:
0 if SCALE, ILO, IHI, ABNRM (full) =
     SCALE, ILO, IHI, ABNRM (partial)
1/ulp otherwise

SCALE, ILO, IHI and ABNRM describe how the matrix is balanced. (full) is when VR, VL, RCONDE and RCONDV are also computed, and (partial) is when some are not computed.

  1. RCONDV(full) = RCONDV(partial)

RCONDV(full) denotes the reciprocal condition numbers of the right eigenvectors computed when VR, VL and RCONDE are also computed. RCONDV(partial) denotes the reciprocal condition numbers when only some of VR, VL and RCONDE are 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 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

and there's more bestie 🫶 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 eigenvalues and right eigenvectors. For these matrices, in addition to tests (1) to (9) we will compute the following two tests:

  1. |RCONDV - RCDVIN| / cond(RCONDV)

RCONDV is the reciprocal right eigenvector condition number computed by SGEEVX 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.

  1. |RCONDE - RCDEIN| / cond(RCONDE)

RCONDE is the reciprocal eigenvalue condition number computed by SGEEVX 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.

🌟 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. (zero sizes get skipped, we respect the boundaries 💅)

🦋 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 get 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 — DOTYPE is 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 — ISEED is 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 SDRVVX to continue the same random number sequence. 🎀
  • THRESH — THRESH is REAL. A test will count as failed 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. no cap, keep it non-negative 🔥
  • NIUNIT — NIUNIT is INTEGER. The FORTRAN unit number for reading in the data file of problems to solve. 📖
  • NOUNIT — NOUNIT is INTEGER. The FORTRAN unit number for printing out error messages (e.g., if a routine returns INFO not equal to 0.) 🚨
  • A — A is REAL array, dimension (LDA, max(NN,12)). Used to hold the matrix whose eigenvalues are to be computed. On exit, A contains the last matrix actually used. 💖
  • LDA — LDA is INTEGER. The leading dimension of the arrays A and H. LDA >= max(NN,12), since 12 is the dimension of the largest matrix in the precomputed input file. 👑
  • H — H is REAL array, dimension (LDA, max(NN,12)). Another copy of the test matrix A, modified by SGEEVX. 🦋
  • WR — WR is REAL array, dimension (max(NN)). 🌸
  • WI — WI is REAL 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. 💜
  • WR1 — WR1 is REAL array, dimension (max(NN,12)). ⭐
  • WI1 — WI1 is REAL array, dimension (max(NN,12)). Like WR, WI, these arrays contain the eigenvalues of A, but those computed when SGEEVX only computes a partial eigendecomposition, i.e. not the eigenvalues and left and right eigenvectors. 🧚
  • VL — VL is REAL array, dimension (LDVL, max(NN,12)). VL holds the computed left eigenvectors. 💫
  • LDVL — LDVL is INTEGER. Leading dimension of VL. Must be at least max(1,max(NN,12)). 🫶
  • VR — VR is REAL array, dimension (LDVR, max(NN,12)). VR holds the computed right eigenvectors. 🌈
  • LDVR — LDVR is INTEGER. Leading dimension of VR. Must be at least max(1,max(NN,12)). ✨
  • LRE — LRE is REAL array, dimension (LDLRE, max(NN,12)). LRE holds the computed right or left eigenvectors. 🍓
  • LDLRE — LDLRE is INTEGER. Leading dimension of LRE. Must be at least max(1,max(NN,12)). 💅
  • RCONDV — RCONDV is REAL array, dimension (N). RCONDV holds the computed reciprocal condition numbers for eigenvectors. 🔥
  • RCNDV1 — RCNDV1 is REAL array, dimension (N). RCNDV1 holds more computed reciprocal condition numbers for eigenvectors. 💖
  • RCDVIN — RCDVIN is REAL array, dimension (N). When COMP = .TRUE. RCDVIN holds the precomputed reciprocal condition numbers for eigenvectors to be compared with RCONDV. 👑
  • RCONDE — RCONDE is REAL array, dimension (N). RCONDE holds the computed reciprocal condition numbers for eigenvalues. 🌸
  • RCNDE1 — RCNDE1 is REAL array, dimension (N). RCNDE1 holds more computed reciprocal condition numbers for eigenvalues. 🦋
  • RCDEIN — RCDEIN is REAL array, dimension (N). When COMP = .TRUE. RCDEIN holds the precomputed reciprocal condition numbers for eigenvalues to be compared with RCONDE. 💜
  • SCALE — SCALE is REAL array, dimension (N). Holds information describing balancing of matrix. ⭐
  • SCALE1 — SCALE1 is REAL array, dimension (N). Holds information describing balancing of matrix. 🧚
  • RESULT — RESULT is REAL array, dimension (11). The values computed by the seven tests described above. The values are currently limited to 1/ulp, to avoid overflow. 🫶
  • WORK — WORK is REAL array, dimension (NWORK). 🌈
  • NWORK — NWORK is INTEGER. The number of entries in WORK. This must be at least max(6*12+2*12**2,6*NN(j)+2*NN(j)**2) = max( 360 ,6*NN(j)+2*NN(j)**2) for all j. 🍓
  • IWORK — IWORK is INTEGER array, dimension (2*max(NN,12)). 💅
  • INFO — INFO is INTEGER. If 0, then successful exit. If <0, then input parameter -INFO is incorrect. If >0, SLATMR, SLATMS, SLATME or SGET23 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 or 12. 👑
  • 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 515 of file sdrvvx.f. ✨

🎀 Author

Generated automatically by Doxygen for LAPACK from the source code. 💖

💖 and that’s the footer handled cute, bestie: source/version LAPACK Version 3.12.0, page TESTING/EIG/sdrvvx.f(3) — the date/version footer spot is right here in the sign-off instead of a copy-paste line. periodt. 🫶

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