single_eig(3)

πŸ“¦
version 3.11.0 Β· 2 versions
, in debian bookworm

✨ single_eig(3) ✨

okay bestie, sit down, hydrate, we're doing this 🫢 this is single_eig(3), a page from the LAPACK manual, and it's the full guide to the real LAPACK TESTING EIG crew. it is long. it is detailed. it is giving "phone book but make it linear algebra". but we're getting through it together, no cap. πŸ’–


🌸 NAME 🌸

single_eig β€” real

that's the whole name. that's it. iconic. πŸ’…


🌸 SYNOPSIS 🌸

Functions

  • program schkee
    • SCHKEE

🌸 Detailed Description 🌸

okay so. this is the group of real LAPACK TESTING EIG routines. that's the whole vibe check. ✨


🌸 Function Documentation 🌸

πŸ’– program schkee πŸ’–

SCHKEE

Purpose:

SCHKEE tests the REAL LAPACK subroutines for the matrix eigenvalue problem. The test paths in this version are

  • NEP (Nonsymmetric Eigenvalue Problem): test SGEHRD, SORGHR, SHSEQR, STREVC, SHSEIN, and SORMHR
  • SEP (Symmetric Eigenvalue Problem): test SSYTRD, SORGTR, SSTEQR, SSTERF, SSTEIN, SSTEDC, and drivers SSYEV(X), SSBEV(X), SSPEV(X), SSTEV(X), SSYEVD, SSBEVD, SSPEVD, SSTEVD
  • SVD (Singular Value Decomposition): test SGEBRD, SORGBR, SBDSQR, SBDSDC and the drivers SGESVD, SGESDD
  • SEV (Nonsymmetric Eigenvalue/eigenvector Driver): test SGEEV
  • SES (Nonsymmetric Schur form Driver): test SGEES
  • SVX (Nonsymmetric Eigenvalue/eigenvector Expert Driver): test SGEEVX
  • SSX (Nonsymmetric Schur form Expert Driver): test SGEESX
  • SGG (Generalized Nonsymmetric Eigenvalue Problem): test SGGHD3, SGGBAL, SGGBAK, SHGEQZ, and STGEVC
  • SGS (Generalized Nonsymmetric Schur form Driver): test SGGES
  • SGV (Generalized Nonsymmetric Eigenvalue/eigenvector Driver): test SGGEV
  • SGX (Generalized Nonsymmetric Schur form Expert Driver): test SGGESX
  • SXV (Generalized Nonsymmetric Eigenvalue/eigenvector Expert Driver): test SGGEVX
  • SSG (Symmetric Generalized Eigenvalue Problem): test SSYGST, SSYGV, SSYGVD, SSYGVX, SSPGST, SSPGV, SSPGVD, SSPGVX, SSBGST, SSBGV, SSBGVD, and SSBGVX
  • SSB (Symmetric Band Eigenvalue Problem): test SSBTRD
  • SBB (Band Singular Value Decomposition): test SGBBRD
  • SEC (Eigencondition estimation): test SLALN2, SLASY2, SLAEQU, SLAEXC, STRSYL, STREXC, STRSNA, STRSEN, and SLAQTR
  • SBL (Balancing a general matrix) β€” test SGEBAL
  • SBK (Back transformation on a balanced matrix) β€” test SGEBAK
  • SGL (Balancing a matrix pair) β€” test SGGBAL
  • SGK (Back transformation on a matrix pair) β€” test SGGBAK
  • GLM (Generalized Linear Regression Model): tests SGGGLM
  • GQR (Generalized QR and RQ factorizations): tests SGGQRF and SGGRQF
  • GSV (Generalized Singular Value Decomposition): tests SGGSVD, SGGSVP, STGSJA, SLAGS2, SLAPLL, and SLAPMT
  • CSD (CS decomposition): tests SORCSD
  • LSE (Constrained Linear Least Squares): tests SGGLSE

each test path has a different set of inputs, but the data sets for the driver routines xEV, xES, xVX, and xSX can be concatenated in a single input file. the first line of input should contain one of the 3-character path names in columns 1-3. the number of remaining lines depends on what is found on the first line. πŸ‘‘

the number of matrix types used in testing is often controllable from the input file. the number of matrix types for each path, and the test routine that describes them, is as follows:

  • SHS or NEP β€” 21 types β€” SCHKHS
  • SST or SEP β€” 21 types β€” SCHKST (routines)
  • SST or SEP β€” 18 types β€” SDRVST (drivers)
  • SBD or SVD β€” 16 types β€” SCHKBD (routines)
  • SBD or SVD β€” 5 types β€” SDRVBD (drivers)
  • SEV β€” 21 types β€” SDRVEV
  • SES β€” 21 types β€” SDRVES
  • SVX β€” 21 types β€” SDRVVX
  • SSX β€” 21 types β€” SDRVSX
  • SGG β€” 26 types β€” SCHKGG (routines)
  • SGS β€” 26 types β€” SDRGES
  • SGX β€” 5 types β€” SDRGSX
  • SGV β€” 26 types β€” SDRGEV
  • SXV β€” 2 types β€” SDRGVX
  • SSG β€” 21 types β€” SDRVSG
  • SSB β€” 15 types β€” SCHKSB
  • SBB β€” 15 types β€” SCHKBB
  • SEC β€” - β€” SCHKEC
  • SBL β€” - β€” SCHKBL
  • SBK β€” - β€” SCHKBK
  • SGL β€” - β€” SCHKGL
  • SGK β€” - β€” SCHKGK
  • GLM β€” 8 types β€” SCKGLM
  • GQR β€” 8 types β€” SCKGQR
  • GSV β€” 8 types β€” SCKGSV
  • CSD β€” 3 types β€” SCKCSD
  • LSE β€” 8 types β€” SCKLSE

πŸ¦‹ NEP input file πŸ¦‹

  • line 2: NN, INTEGER
    • Number of values of N.
  • line 3: NVAL, INTEGER array, dimension (NN)
    • The values for the matrix dimension N.
  • line 4: NPARMS, INTEGER
    • Number of values of the parameters NB, NBMIN, NX, NS, and MAXB.
  • line 5: NBVAL, INTEGER array, dimension (NPARMS)
    • The values for the blocksize NB.
  • line 6: NBMIN, INTEGER array, dimension (NPARMS)
    • The values for the minimum blocksize NBMIN.
  • line 7: NXVAL, INTEGER array, dimension (NPARMS)
    • The values for the crossover point NX.
  • line 8: INMIN, INTEGER array, dimension (NPARMS)
    • LAHQR vs TTQRE crossover point, >= 11
  • line 9: INWIN, INTEGER array, dimension (NPARMS)
    • recommended deflation window size
  • line 10: INIBL, INTEGER array, dimension (NPARMS)
    • nibble crossover point
  • line 11: ISHFTS, INTEGER array, dimension (NPARMS)
    • number of simultaneous shifts)
  • line 12: IACC22, INTEGER array, dimension (NPARMS)
    • select structured matrix multiply: 0, 1 or 2)
  • line 13: THRESH
    • Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. To have all of the test ratios printed, use THRESH = 0.0 .
  • line 14: NEWSD, INTEGER
    • A code indicating how to set the random number seed.
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 14 was 2:

  • line 15: INTEGER array, dimension (4)
    • Four integer values for the random number seed.
  • lines 15-EOF: The remaining lines occur in sets of 1 or 2 and allow the user to specify the matrix types. Each line contains a 3-character path name in columns 1-3, and the number of matrix types must be the first nonblank item in columns 4-80. If the number of matrix types is at least 1 but is less than the maximum number of possible types, a second line will be read to get the numbers of the matrix types to be used. For example,
NEP 21

requests all of the matrix types for the nonsymmetric eigenvalue problem, while

NEP  4
9 10 11 12

requests only matrices of type 9, 10, 11, and 12.

ngl the valid 3-character path names here are 'NEP' or 'SHS' for the nonsymmetric eigenvalue routines. πŸ’œ

🌈 SEP or SSG input file 🌈

  • line 2: NN, INTEGER
    • Number of values of N.
  • line 3: NVAL, INTEGER array, dimension (NN)
    • The values for the matrix dimension N.
  • line 4: NPARMS, INTEGER
    • Number of values of the parameters NB, NBMIN, and NX.
  • line 5: NBVAL, INTEGER array, dimension (NPARMS)
    • The values for the blocksize NB.
  • line 6: NBMIN, INTEGER array, dimension (NPARMS)
    • The values for the minimum blocksize NBMIN.
  • line 7: NXVAL, INTEGER array, dimension (NPARMS)
    • The values for the crossover point NX.
  • line 8: THRESH
    • Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold.
  • line 9: TSTCHK, LOGICAL
    • Flag indicating whether or not to test the LAPACK routines.
  • line 10: TSTDRV, LOGICAL
    • Flag indicating whether or not to test the driver routines.
  • line 11: TSTERR, LOGICAL
    • Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines.
  • line 12: NEWSD, INTEGER
    • A code indicating how to set the random number seed.
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 12 was 2:

  • line 13: INTEGER array, dimension (4)
    • Four integer values for the random number seed.
  • lines 13-EOF: Lines specifying matrix types, as for NEP. The 3-character path names are 'SEP' or 'SST' for the symmetric eigenvalue routines and driver routines, and 'SSG' for the routines for the symmetric generalized eigenvalue problem.

πŸ“ SVD input file πŸ“

  • line 2: NN, INTEGER
    • Number of values of M and N.
  • line 3: MVAL, INTEGER array, dimension (NN)
    • The values for the matrix row dimension M.
  • line 4: NVAL, INTEGER array, dimension (NN)
    • The values for the matrix column dimension N.
  • line 5: NPARMS, INTEGER
    • Number of values of the parameter NB, NBMIN, NX, and NRHS.
  • line 6: NBVAL, INTEGER array, dimension (NPARMS)
    • The values for the blocksize NB.
  • line 7: NBMIN, INTEGER array, dimension (NPARMS)
    • The values for the minimum blocksize NBMIN.
  • line 8: NXVAL, INTEGER array, dimension (NPARMS)
    • The values for the crossover point NX.
  • line 9: NSVAL, INTEGER array, dimension (NPARMS)
    • The values for the number of right hand sides NRHS.
  • line 10: THRESH
    • Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold.
  • line 11: TSTCHK, LOGICAL β€” the flag that decides whether or not we're testing the LAPACK routines at all. 🫢
  • line 12: TSTDRV, LOGICAL β€” same energy, but for the driver routines. πŸš—
  • line 13: TSTERR, LOGICAL β€” and this one says whether or not we're testing the error exits for the LAPACK routines and the driver routines. Not me being thorough or anything. πŸ’…
  • line 14: NEWSD, INTEGER β€” a code telling you how to set the random number seed. It's giving choose-your-own-adventure:
    • = 0: set the seed to a default value before each run
    • = 1: initialize the seed to a default value only before the first run
    • = 2: like 1, but use the seed values on the next line

If line 14 was 2, you get a lil bonus line:

  • line 15: INTEGER array, dimension (4) β€” four integer values for the random number seed. Four. That's the whole vibe. 🎲
  • lines 15-EOF: β€” lines specifying matrix types, as for NEP. The 3-character path names are 'SVD' or 'SBD', for both the SVD routines and the SVD driver routines. ✨

🌸 SEV and SES data files 🌸

  • line 1: β€” 'SEV' or 'SES' in columns 1 to 3. That's how we know who we are bestie.
  • line 2: NSIZES, INTEGER β€” number of sizes of matrices to use. Should be at least 0 and at most 20. And heads up: if NSIZES = 0, no testing is done β€” but the remaining 3 lines are still read. The dedication. 😭
  • line 3: NN, INTEGER array, dimension(NSIZES) β€” dimensions of matrices to be tested. πŸ“
  • line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs β€” these integer parameters determine how blocking is done (see ILAENV for details):
    • NB : block size
    • NBMIN : minimum block size
    • NX : minimum dimension for blocking
    • NS : number of shifts in xHSEQR
    • NBCOL : minimum column dimension for blocking
  • line 5: THRESH, REAL β€” the test threshold that computed residuals get compared against. Should generally be in the range from 10. to 20. And if it's 0., all test case data will be printed. All of it. Buckle up. πŸ”₯
  • line 6: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits.
  • line 7: NEWSD, INTEGER β€” code indicating how to set the random number seed:
    • = 0: set the seed to a default value before each run
    • = 1: initialize the seed to a default value only before the first run
    • = 2: like 1, but use the seed values on the next line

If line 7 was 2:

  • line 8: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸŽ€
  • lines 9 and following: β€” lines specifying matrix types, as for NEP. The 3-character path name is 'SEV' to test SGEEV, or 'SES' to test SGEES. Pick your fighter. πŸ‘‘

πŸ¦‹ The SVX data πŸ¦‹

The SVX data has two parts. The first part is identical to SEV, and the second part consists of test matrices with precomputed solutions. Iconic two-act structure, no notes.

  • line 1: β€” 'SVX' in columns 1-3.
  • line 2: NSIZES, INTEGER β€” if NSIZES = 0, no testing of randomly generated examples is done, but any precomputed examples are tested. (The precomputed ones always show up. Main characters. πŸ’…)
  • line 3: NN, INTEGER array, dimension(NSIZES)
  • line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs
  • line 5: THRESH, REAL
  • line 6: TSTERR, LOGICAL
  • line 7: NEWSD, INTEGER

If line 7 was 2:

  • line 8: INTEGER array, dimension (4)
  • lines 9 and following: β€” the first line contains 'SVX' in columns 1-3, followed by the number of matrix types, possibly with a second line to specify certain matrix types. If the number of matrix types = 0, no testing of randomly generated examples is done, but any precomputed examples are tested.
  • remaining lines: β€” each matrix is stored on 1+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next N lines contain the matrix, one row per line. The last N lines correspond to each eigenvalue. Each of these last N lines contains 4 real values: the real part of the eigenvalue, the imaginary part of the eigenvalue, the reciprocal condition number of the eigenvalues, and the reciprocal condition number of the eigenvector.
The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. Non-negotiable, bestie. πŸ™ˆ

🌈 The SSX data 🌈

The SSX data is like SVX. The first part is identical to SEV, and the second part consists of test matrices with precomputed solutions.

  • line 1: β€” 'SSX' in columns 1-3.
  • line 2: NSIZES, INTEGER β€” if NSIZES = 0, no testing of randomly generated examples is done, but any precomputed examples are tested.
  • line 3: NN, INTEGER array, dimension(NSIZES)
  • line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs
  • line 5: THRESH, REAL
  • line 6: TSTERR, LOGICAL
  • line 7: NEWSD, INTEGER

If line 7 was 2:

  • line 8: INTEGER array, dimension (4)
  • lines 9 and following: β€” the first line contains 'SSX' in columns 1-3, followed by the number of matrix types, possibly with a second line to specify certain matrix types. If the number of matrix types = 0, no testing of randomly generated examples is done, but any precomputed examples are tested.
  • remaining lines: β€” each matrix is stored on 3+N lines, where N is its dimension. The first line contains the dimension N and the dimension M of an invariant subspace. The second line contains M integers, identifying the eigenvalues in the invariant subspace (by their position in a list of eigenvalues ordered by increasing real part). The next N lines contain the matrix. The last line contains the reciprocal condition number for the average of the selected eigenvalues, and the reciprocal condition number for the corresponding right invariant subspace.
The end of data is indicated by a line containing N=0 and M=0. Even if no data is to be tested, there must be at least one line containing N=0 and M=0. Both zeros. Don't skip one. 😀

πŸ’œ SGG input file πŸ’œ

  • line 2: NN, INTEGER β€” number of values of N.
  • line 3: NVAL, INTEGER array, dimension (NN) β€” the values for the matrix dimension N.
  • line 4: NPARMS, INTEGER β€” number of values of the parameters NB, NBMIN, NS, MAXB, and NBCOL.
  • line 5: NBVAL, INTEGER array, dimension (NPARMS) β€” the values for the blocksize NB.
  • line 6: NBMIN, INTEGER array, dimension (NPARMS) β€” the values for NBMIN, the minimum row dimension for blocks.
  • line 7: NSVAL, INTEGER array, dimension (NPARMS) β€” the values for the number of shifts.
  • line 8: MXBVAL, INTEGER array, dimension (NPARMS) β€” the values for MAXB, used in determining minimum blocksize.
  • line 9: IACC22, INTEGER array, dimension (NPARMS) β€” select structured matrix multiply: 1 or 2)
  • line 10: NBCOL, INTEGER array, dimension (NPARMS) β€” the values for NBCOL, the minimum column dimension for blocks.
  • line 11: THRESH β€” threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. πŸ‘€
  • line 12: TSTCHK, LOGICAL β€” flag indicating whether or not to test the LAPACK routines.
  • line 13: TSTDRV, LOGICAL β€” flag indicating whether or not to test the driver routines.
  • line 14: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines.
  • line 15: NEWSD, INTEGER β€” a code indicating how to set the random number seed:
    • = 0: set the seed to a default value before each run
    • = 1: initialize the seed to a default value only before the first run
    • = 2: like 1, but use the seed values on the next line

If line 15 was 2:

  • line 16: INTEGER array, dimension (4) β€” four integer values for the random number seed.
  • lines 17-EOF: β€” lines specifying matrix types, as for NEP. The 3-character path name is 'SGG' for the generalized eigenvalue problem routines and driver routines. 🎯

🧚 SGS and SGV input files 🧚

  • line 1: β€” 'SGS' or 'SGV' in columns 1 to 3.
  • line 2: NN, INTEGER β€” number of values of N.
  • line 3: NVAL, INTEGER array, dimension(NN) β€” dimensions of matrices to be tested.
  • line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs β€” these integer parameters determine how blocking is done (see ILAENV for details):
    • NB : block size
    • NBMIN : minimum block size
    • NX : minimum dimension for blocking
    • NS : number of shifts in xHGEQR
    • NBCOL : minimum column dimension for blocking
  • line 5: THRESH, REAL β€” the test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. If it is 0., all test case data will be printed.
  • line 6: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits.
  • line 7: NEWSD, INTEGER β€” a code indicating how to set the random number seed:
    • = 0: set the seed to a default value before each run
    • = 1: initialize the seed to a default value only before the first run
    • = 2: like 1, but use the seed values on the next line

If line 17 was 2:

  • line 7: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ“

lines 7-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'SGS' for the generalized eigenvalue problem routines and driver routines. πŸ’… periodt.


SXV input files πŸ¦‹

  • line 1: 'SXV' in columns 1 to 3. okay so first line is literally just the tag. ✨
  • line 2: N, INTEGER β€” bestie, this is the value of N. πŸ’–
  • line 3: NB, NBMIN, NX, NS, NBCOL, INTEGERs β€” these integer parameters determine how blocking is done (see ILAENV for details). the way that blocking gets configured, iconic. πŸ‘‘
    • NB : block size
    • NBMIN : minimum block size
    • NX : minimum dimension for blocking
    • NS : number of shifts in xHGEQR
    • NBCOL : minimum column dimension for blocking
  • line 4: THRESH, REAL β€” the test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. no cap, keep it in that range. πŸ”₯
  • line 5: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. vibe check on error handling. πŸŽ€
  • line 6: NEWSD, INTEGER β€” a code indicating how to set the random number seed. choose your seed destiny 🌈
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 6 was 2:

  • line 7: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ’œ

If line 2 was 0:

  • line 7-EOF: Precomputed examples are tested. 🧚
  • remaining lines : Each example is stored on 3+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next N lines contain the matrix A, one row per line. The next N lines contain the matrix B. The next line contains the reciprocals of the eigenvalue condition numbers. The last line contains the reciprocals of the eigenvector condition numbers. The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. 😭 the way that there's always a N=0 line, even if empty, is so real.

SGX input files πŸ’…

  • line 1: 'SGX' in columns 1 to 3. ✨
  • line 2: N, INTEGER β€” value of N. πŸ’–
  • line 3: NB, NBMIN, NX, NS, NBCOL, INTEGERs β€” these integer parameters determine how blocking is done (see ILAENV for details). slay πŸ‘‘
    • NB : block size
    • NBMIN : minimum block size
    • NX : minimum dimension for blocking
    • NS : number of shifts in xHGEQR
    • NBCOL : minimum column dimension for blocking
  • line 4: THRESH, REAL β€” the test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. πŸ”₯
  • line 5: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸŽ€
  • line 6: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌈
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 6 was 2:

  • line 7: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ’œ

If line 2 was 0:

  • line 7-EOF: Precomputed examples are tested. 🧚
  • remaining lines : Each example is stored on 3+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next line contains an integer k such that only the last k eigenvalues will be selected and appear in the leading diagonal blocks of $A$ and $B$. The next N lines contain the matrix A, one row per line. The next N lines contain the matrix B. The last line contains the reciprocal of the eigenvalue cluster condition number and the reciprocal of the deflating subspace (associated with the selected eigencluster) condition number. The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. 😭 it's giving extra credit for the eigencluster details.

SSB input file 🌸

  • line 2: NN, INTEGER β€” number of values of N. πŸ’–
  • line 3: NVAL, INTEGER array, dimension (NN) β€” the values for the matrix dimension N. ✨
  • line 4: NK, INTEGER β€” number of values of K. πŸ‘‘
  • line 5: KVAL, INTEGER array, dimension (NK) β€” the values for the matrix dimension K. πŸ’…
  • line 6: THRESH β€” threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. πŸ”₯
  • line 7: NEWSD, INTEGER β€” a code indicating how to set the random number seed. main character energy 🌈
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 7 was 2:

  • line 8: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ’œ
  • lines 8-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'SSB'. πŸ¦‹

SBB input file πŸŽ€

  • line 2: NN, INTEGER β€” number of values of M and N. πŸ’–
  • line 3: MVAL, INTEGER array, dimension (NN) β€” the values for the matrix row dimension M. ✨
  • line 4: NVAL, INTEGER array, dimension (NN) β€” the values for the matrix column dimension N. πŸ’…
  • line 4: NK, INTEGER β€” number of values of K. πŸ‘‘ not the line number glitching, that's literally what it says
  • line 5: KVAL, INTEGER array, dimension (NK) β€” the values for the matrix bandwidth K. πŸ”₯
  • line 6: NPARMS, INTEGER β€” number of values of the parameter NRHS. 🌸
  • line 7: NSVAL, INTEGER array, dimension (NPARMS) β€” the values for the number of right hand sides NRHS. πŸ¦‹
  • line 8: THRESH β€” threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. πŸ’œ
  • line 9: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌈
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 9 was 2:

  • line 10: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ’œ
  • lines 10-EOF: Lines specifying matrix types, as for SVD. The 3-character path name is 'SBB'. πŸ¦‹

SEC input file 😭

  • line 2: THRESH, REAL β€” threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. πŸ”₯
  • lines 3-EOF: Input for testing the eigencondition routines consists of a set of specially constructed test cases and their solutions. The data format is not intended to be modified by the user. periodt, don't touch it. 🧚

SBL and SBK input files πŸ’…

  • line 1: 'SBL' in columns 1-3 to test SGEBAL, or 'SBK' in columns 1-3 to test SGEBAK. πŸ‘‘
  • The remaining lines consist of specially constructed test cases. ✨

SGL and SGK input files 🌈

  • line 1: 'SGL' in columns 1-3 to test SGGBAL, or 'SGK' in columns 1-3 to test SGGBAK. πŸ’–
  • The remaining lines consist of specially constructed test cases. ✨

GLM data file πŸ“

  • line 1: 'GLM' in columns 1 to 3. ✨
  • line 2: NN, INTEGER β€” number of values of M, P, and N. πŸ’–
  • line 3: MVAL, INTEGER array, dimension(NN) β€” values of M (row dimension). πŸ‘‘
  • line 4: PVAL, INTEGER array, dimension(NN) β€” values of P (row dimension). πŸ’…
  • line 5: NVAL, INTEGER array, dimension(NN) β€” values of N (column dimension), note M <= N <= M+P. πŸ”₯
  • line 6: THRESH, REAL β€” threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. 🌸
  • line 7: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸŽ€
  • line 8: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌈
    • = 0: Set the seed to a default value before each run
    • = 1: Initialize the seed to a default value only before the first run
    • = 2: Like 1, but use the seed values on the next line

If line 8 was 2:

  • line 9: INTEGER array, dimension (4) β€” four integer values for the random number seed. πŸ’œ
  • lines 9-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'GLM' for the generalized linear regression model routines. πŸ¦‹

GQR data file πŸ’œ

  • line 1: 'GQR' in columns 1 to 3. ✨
  • line 2: NN, INTEGER β€” number of values of M, P, and N. πŸ’–

okay bestie, we're still in the data-file zone and you already know the vibe. no re-intro, just picking up at line 3 of the GQR file like nothing happened. πŸ’…

  • line 3: MVAL, INTEGER array, dimension(NN) β€” the values of M. πŸ‘‘
  • line 4: PVAL, INTEGER array, dimension(NN) β€” the values of P. ✨
  • line 5: NVAL, INTEGER array, dimension(NN) β€” the values of N. 🌸
  • line 6: THRESH, REAL β€” the threshold value for the test ratios. information will be printed about each test for which the test ratio is greater than or equal to the threshold. 🚨
  • line 7: TSTERR, LOGICAL β€” a flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸ•΅οΈβ€β™€οΈ
  • line 8: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌱
    • = 0: set the seed to a default value before each run.
    • = 1: initialize the seed to a default value only before the first run.
    • = 2: like 1, but use the seed values on the next line.

if line 8 was 2:

  • line 9: INTEGER array, dimension (4) β€” four integer values for the random number seed. 🎲
  • lines 9-EOF: lines specifying matrix types, as for NEP. the 3-character path name is 'GQR' for the generalized QR and RQ routines. πŸ”₯

GSV data file πŸ¦‹

  • line 1: 'GSV' in columns 1 to 3. πŸ“›
  • line 2: NN, INTEGER β€” number of values of M, P, and N. πŸ”’
  • line 3: MVAL, INTEGER array, dimension(NN) β€” values of M (row dimension). πŸ“
  • line 4: PVAL, INTEGER array, dimension(NN) β€” values of P (row dimension). πŸ“
  • line 5: NVAL, INTEGER array, dimension(NN) β€” values of N (column dimension). πŸ“Š
  • line 6: THRESH, REAL β€” threshold value for the test ratios. information will be printed about each test for which the test ratio is greater than or equal to the threshold. 🚨
  • line 7: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸ•΅οΈβ€β™€οΈ
  • line 8: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌱
    • = 0: set the seed to a default value before each run.
    • = 1: initialize the seed to a default value only before the first run.
    • = 2: like 1, but use the seed values on the next line.

if line 8 was 2:

  • line 9: INTEGER array, dimension (4) β€” four integer values for the random number seed. 🎲
  • lines 9-EOF: lines specifying matrix types, as for NEP. the 3-character path name is 'GSV' for the generalized SVD routines. πŸ”₯

CSD data file πŸŽ€

  • line 1: 'CSD' in columns 1 to 3. πŸ“›
  • line 2: NM, INTEGER β€” number of values of M, P, and N. πŸ”’
  • line 3: MVAL, INTEGER array, dimension(NM) β€” values of M (row and column dimension of orthogonal matrix). 🧊
  • line 4: PVAL, INTEGER array, dimension(NM) β€” values of P (row dimension of top-left block). 🧱
  • line 5: NVAL, INTEGER array, dimension(NM) β€” values of N (column dimension of top-left block). 🧱
  • line 6: THRESH, REAL β€” threshold value for the test ratios. information will be printed about each test for which the test ratio is greater than or equal to the threshold. 🚨
  • line 7: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸ•΅οΈβ€β™€οΈ
  • line 8: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌱
    • = 0: set the seed to a default value before each run.
    • = 1: initialize the seed to a default value only before the first run.
    • = 2: like 1, but use the seed values on the next line.

if line 8 was 2:

  • line 9: INTEGER array, dimension (4) β€” four integer values for the random number seed. 🎲
  • lines 9-EOF: lines specifying matrix types, as for NEP. the 3-character path name is 'CSD' for the CSD routine. πŸ”₯

LSE data file 🌈

  • line 1: 'LSE' in columns 1 to 3. πŸ“›
  • line 2: NN, INTEGER β€” number of values of M, P, and N. πŸ”’
  • line 3: MVAL, INTEGER array, dimension(NN) β€” values of M. πŸ“
  • line 4: PVAL, INTEGER array, dimension(NN) β€” values of P. πŸ“
  • line 5: NVAL, INTEGER array, dimension(NN) β€” values of N, note P <= N <= P+M. ⚠️
  • line 6: THRESH, REAL β€” threshold value for the test ratios. information will be printed about each test for which the test ratio is greater than or equal to the threshold. 🚨
  • line 7: TSTERR, LOGICAL β€” flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. πŸ•΅οΈβ€β™€οΈ
  • line 8: NEWSD, INTEGER β€” a code indicating how to set the random number seed. 🌱
    • = 0: set the seed to a default value before each run.
    • = 1: initialize the seed to a default value only before the first run.
    • = 2: like 1, but use the seed values on the next line.

if line 8 was 2:

  • line 9: INTEGER array, dimension (4) β€” four integer values for the random number seed. 🎲
  • lines 9-EOF: lines specifying matrix types, as for NEP. the 3-character path name is 'GSV' for the generalized SVD routines. πŸ”₯

🌟 big brain parameter tea: NMAX is currently set to 132 and must be at least 12 for some of the precomputed examples, and LWORK = NMAX*(5*NMAX+5)+1 in the parameter statements below. for SVD, we assume NRHS may be as big as N. the parameter NEED is set to 14 to allow for 14 N-by-N matrices for SGG. πŸ‘‘

Author πŸ‘‘

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

Author πŸ€–

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