SDRVST2STG(3)
π TESTING/EIG/sdrvst2stg.f(3) π
From the Library Functions Manual, bestie β this is the page for TESTING/EIG/sdrvst2stg.f, and it's a whole mood. π
πΈ NAME πΈ
TESTING/EIG/sdrvst2stg.f
β¨ SYNOPSIS β¨
π§ Functions/Subroutines π§
subroutine sdrvst2stgβ the main character, with the full signature below. π«Ά
subroutine sdrvst2stg (nsizes, nn, ntypes, dotype, iseed, thresh,
nounit, a, lda, d1, d2, d3, d4, eveigs, wa1, wa2, wa3, u, ldu, v,
tau, z, work, lwork, iwork, liwork, result, info)
SDRVST2STG β that's the name, periodt. β¨
π Function/Subroutine Documentation π
π«Ά subroutine sdrvst2stg π«Ά
subroutine sdrvst2stg (integer nsizes, integer, dimension( * ) nn, integer
ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
real thresh, integer nounit, real, dimension( lda, * ) a, integer lda,
real, dimension( * ) d1, real, dimension( * ) d2, real, dimension( * )
d3, real, dimension( * ) d4, real, dimension( * ) eveigs, real,
dimension( * ) wa1, real, dimension( * ) wa2, real, dimension( * ) wa3,
real, dimension( ldu, * ) u, integer ldu, real, dimension( ldu, * ) v,
real, dimension( * ) tau, real, dimension( ldu, * ) z, real, dimension(
* ) work, integer lwork, integer, dimension( * ) iwork, integer liwork,
real, dimension( * ) result, integer info)
SDRVST2STG
π― Purpose π―
Okay so SDRVST2STG checks the symmetric eigenvalue problem drivers. π Like, it's the vibe-check friend for all these routines:
SSTEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix.SSTEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix.SSTEVRβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix using the Relatively Robust Representation where it can.SSYEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix.SSYEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix.SSYEVRβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix using the Relatively Robust Representation where it can.SSPEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage.SSPEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage.SSBEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric band matrix.SSBEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric band matrix.SSYEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix using a divide and conquer algorithm.SSPEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage, using a divide and conquer algorithm.SSBEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric band matrix, using a divide and conquer algorithm.
When SDRVST2STG 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 appropriate drivers. For each matrix and each driver routine called, the following tests will be performed:
| A - Z D Z' | / ( |A| n ulp )| I - Z Z' | / ( n ulp )| D1 - D2 | / ( |D1| ulp )
where Z is the matrix of eigenvectors returned when the eigenvector option is given, and D1 and D2 are the eigenvalues returned with and without the eigenvector option. π
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)β The zero matrix.(2)β The identity matrix.(3)β A diagonal matrix with evenly spaced eigenvalues1, ..., ULPand random signs.(ULP = (first number larger than 1) - 1 )(4)β A diagonal matrix with geometrically spaced eigenvalues1, ..., ULPand random signs.(5)β A diagonal matrix with eigenvalues1, ULP, ..., ULPand random signs.(6)β Same as(4), but multiplied bySQRT( overflow threshold ).(7)β Same as(4), but multiplied bySQRT( underflow threshold ).(8)β A matrix of the formU' D U, whereUis orthogonal andDhas evenly spaced entries1, ..., ULPwith random signs on the diagonal.(9)β A matrix of the formU' D U, whereUis orthogonal andDhas geometrically spaced entries1, ..., ULPwith random signs on the diagonal.(10)β A matrix of the formU' D U, whereUis orthogonal andDhas entries1, ULP,..., ULPwith random signs on the diagonal.(11)β Same as(8), but multiplied bySQRT( overflow threshold ).(12)β Same as(8), but multiplied bySQRT( underflow threshold ).(13)β Symmetric matrix with random entries chosen from(-1,1).(14)β Same as(13), but multiplied bySQRT( overflow threshold ).(15)β Same as(13), but multiplied bySQRT( underflow threshold ).(16)β A band matrix with half bandwidth randomly chosen between0andN-1, with evenly spaced eigenvalues1, ..., ULPwith random signs.(17)β Same as(16), but multiplied bySQRT( overflow threshold ).(18)β Same as(16), but multiplied bySQRT( underflow threshold ).NSIZESβINTEGER. The number of sizes of matrices to use. If itβs zero,SDRVST2STGdoes nothing. It must be at least zero. Status: not modified. πNNβINTEGERarray, dimension(NSIZES). Contains the sizes used for the matrices. Zero values get skipped. The values must be at least zero. Status: not modified. β¨NTYPESβINTEGER. The number of elements inDOTYPE. If itβs zero,SDRVST2STGdoes nothing. It must be at least zero. If it isMAXTYP+1andNSIZESis1, then an additional type,MAXTYP+1, is defined, which is to use whatever matrix is inA. This is only useful ifDOTYPE(1:MAXTYP)is.FALSE.andDOTYPE(MAXTYP+1)is.TRUE.. Status: not modified. π«ΆDOTYPEβLOGICALarray, dimension(NTYPES). IfDOTYPE(j)is.TRUE., then for each size inNNa matrix of that size and of typejwill be generated. IfNTYPESis smaller than the maximum number of types defined (PARAMETER MAXTYP), then typesNTYPES+1throughMAXTYPwill not be generated. IfNTYPESis larger thanMAXTYP,DOTYPE(MAXTYP+1)throughDOTYPE(NTYPES)will be ignored. Status: not modified. π¦ISEEDβINTEGERarray, dimension(4). On entry,ISEEDspecifies the seed of the random number generator. Array elements should be between0and4095; if not, they will be reduced mod4096. 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 ofISEEDare changed on exit, and can be used in the next call toSDRVST2STGto continue the same random number sequence. Status: modified. πTHRESHβREAL. A test will count as <something> if the <thing>, computed as described above, exceedsTHRESH. Note that the error is scaled to beO(1), soTHRESHshould be a reasonably small multiple of1, e.g.,10or100. In particular, it should not depend on the precision (single vs. double) or the size of the matrix. It must be at least zero. Status: not modified. πΈNOUNITβINTEGER. TheFORTRANunit number for printing out error messages (e.g., if a routine returnsIINFOnot equal to0). Status: not modified. πAβREALarray, dimension(LDA , max(NN)). Used to hold the matrix whose eigenvalues are to be computed. On exit,Acontains the last matrix actually used. Status: modified. π₯LDAβINTEGER. The leading dimension ofA. It must be at least1and at leastmax( NN ). Status: not modified. πD1βREALarray, dimension(max(NN)). The eigenvalues ofA, as computed bySSTEQRsimultaneously withZ. On exit, the eigenvalues inD1correspond with the matrix inA. Status: modified. βD2βREALarray, dimension(max(NN)). The eigenvalues ofA, as computed bySSTEQRifZis not computed. On exit, the eigenvalues inD2correspond with the matrix inA. Status: modified. πD3βREALarray, dimension(max(NN)). The eigenvalues ofA, as computed bySSTERF. On exit, the eigenvalues inD3correspond with the matrix inA. Status: modified. πD4βREALarray, dimension. πEVEIGSβREALarray, dimension(max(NN)). The eigenvalues as computed bySSTEV('N', ... ). And yes, thereβs a note that the author reserves the right to change this to the output of whichever algorithm computes the most accurate eigenvalues. π§WA1βREALarray, dimension.WA2βREALarray, dimension.WA3βREALarray, dimension.UβREALarray, dimension(LDU, max(NN)). The orthogonal matrix computed bySSYTRD + SORGTR. Status: modified. πLDUβINTEGER. The leading dimension ofU,Z, andV. It must be at least1and at leastmax( NN ). Status: not modified. π¦VβREALarray, dimension(LDU, max(NN)). The Householder vectors computed bySSYTRDin reducingAto tridiagonal form. Status: modified. β¨TAUβREALarray, dimension(max(NN)). The Householder factors computed bySSYTRDin reducingAto tridiagonal form. Status: modified. πZβREALarray, dimension(LDU, max(NN)). The orthogonal matrix of eigenvectors computed bySSTEQR,SPTEQR, andSSTEIN. Status: modified. πWORKβREALarray, dimension(LWORK). Workspace. Status: modified. πΈLWORKβINTEGER. The number of entries inWORK. This must be at least1 + 4 * Nmax + 2 * Nmax * lg Nmax + 4 * Nmax**2, whereNmax = max( NN(j), 2 )andlg = log base 2. Status: not modified. π₯IWORKβINTEGERarray, dimension(6 + 6*Nmax + 5 * Nmax * lg Nmax ), whereNmax = max( NN(j), 2 )andlg = log base 2. Workspace. Status: modified. πRESULTβREALarray, dimension(105). The values computed by the tests described above. The values are currently limited to1/ulp, to avoid overflow. Status: modified. βINFOβINTEGER. If0, then everything ran OK. π-1:NSIZES < 0-2: SomeNN(j) < 0-3:NTYPES < 0-5:THRESH < 0-9:LDA < 1orLDA < NMAX, whereNMAXismax( NN(j) ).-16:LDU < 1orLDU < NMAX.-21:LWORKtoo small.
If SLATMR, SLATMS, SSYTRD, SORGTR, SSTEQR, SSTERF, or SORMTR returns an error code, the absolute value of it is returned. Status: modified. π«Ά
π«Ά Some Local Variables and Parameters
ZERO,ONEβ real0and1. β¨MAXTYPβ the number of types defined. πNTESTβ the number of tests performed, or which can be performed so far, for the current matrix. πNTESTTβ the total number of tests performed so far. πΈNMAXβ largest value inNN. π¦NMATSβ the number of matrices generated so far. π₯NERRSβ the number of tests which have exceededTHRESHso far (computed bySLAFTS). πCOND,IMODEβ values to be passed to the matrix generators. πANORMβ norm ofA; passed to matrix generators. βOVFL,UNFLβ overflow and underflow thresholds. πULP,ULPINVβ finest relative precision and its inverse. πRTOVFL,RTUNFLβ square roots of the previous2values. π§
The following four arrays decode JTYPE:
KTYPE(j)β the general type (1-10) for type.KMODE(j)β theMODEvalue 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) )).
π§ͺ The tests performed areβ¦ (Routine tested)
- Test 1 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEV('V', ... ) - Test 2 β
| I - U U' | / ( n ulp )β routine tested:SSTEV('V', ... ) - Test 3 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSTEV('N', ... ) - Test 4 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVX('V','A', ... ) - Test 5 β
| I - U U' | / ( n ulp )β routine tested:SSTEVX('V','A', ... ) - Test 6 β
|D(with Z) - EVEIGS| / (|D| ulp)β routine tested:SSTEVX('N','A', ... ) - Test 7 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVR('V','A', ... ) - Test 8 β
| I - U U' | / ( n ulp )β routine tested:SSTEVR('V','A', ... ) - Test 9 β
|D(with Z) - EVEIGS| / (|D| ulp)β routine tested:SSTEVR('N','A', ... ) - Test 10 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVX('V','I', ... ) - Test 11 β
| I - U U' | / ( n ulp )β routine tested:SSTEVX('V','I', ... ) - Test 12 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSTEVX('N','I', ... ) - Test 13 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVX('V','V', ... ) - Test 14 β
| I - U U' | / ( n ulp )β routine tested:SSTEVX('V','V', ... ) - Test 15 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSTEVX('N','V', ... ) - Test 16 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVD('V', ... ) - Test 17 β
| I - U U' | / ( n ulp )β routine tested:SSTEVD('V', ... ) - Test 18 β
|D(with Z) - EVEIGS| / (|D| ulp)β routine tested:SSTEVD('N', ... ) - Test 19 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVR('V','I', ... ) - Test 20 β
| I - U U' | / ( n ulp )β routine tested:SSTEVR('V','I', ... ) - Test 21 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSTEVR('N','I', ... ) - Test 22 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSTEVR('V','V', ... ) - Test 23 β
| I - U U' | / ( n ulp )β routine tested:SSTEVR('V','V', ... ) - Test 24 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSTEVR('N','V', ... )
- Test 25 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSYEV('L','V', ... ) - Test 26 β
| I - U U' | / ( n ulp )β routine tested:SSYEV('L','V', ... ) - Test 27 β
|D(with Z) - D(w/o Z)| / (|D| ulp)β routine tested:SSYEV_2STAGE('L','N', ... ) - Test 28 β
| A - U S U' | / ( |A| n ulp )β routine tested:SSYEVX('L','V','A', ... )
okay bestie, weβre deep in the test list now and it is long, but I promised no skipping, so hereβs every single row exactly as the source gives it β line by line, no cap π
!> 29= | I - U U' | / ( n ulp ) SSYEVX('L','V','A', ... )
!> 30= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVX_2STAGE('L','N','A', ... )
!> 31= | A - U S U' | / ( |A| n ulp ) SSYEVX('L','V','I', ... )
!> 32= | I - U U' | / ( n ulp ) SSYEVX('L','V','I', ... )
!> 33= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVX_2STAGE('L','N','I', ... )
!> 34= | A - U S U' | / ( |A| n ulp ) SSYEVX('L','V','V', ... )
!> 35= | I - U U' | / ( n ulp ) SSYEVX('L','V','V', ... )
!> 36= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVX_2STAGE('L','N','V', ... )
!> 37= | A - U S U' | / ( |A| n ulp ) SSPEV('L','V', ... )
!> 38= | I - U U' | / ( n ulp ) SSPEV('L','V', ... )
!> 39= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEV('L','N', ... )
!> 40= | A - U S U' | / ( |A| n ulp ) SSPEVX('L','V','A', ... )
!> 41= | I - U U' | / ( n ulp ) SSPEVX('L','V','A', ... )
!> 42= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVX('L','N','A', ... )
!> 43= | A - U S U' | / ( |A| n ulp ) SSPEVX('L','V','I', ... )
!> 44= | I - U U' | / ( n ulp ) SSPEVX('L','V','I', ... )
!> 45= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVX('L','N','I', ... )
!> 46= | A - U S U' | / ( |A| n ulp ) SSPEVX('L','V','V', ... )
!> 47= | I - U U' | / ( n ulp ) SSPEVX('L','V','V', ... )
!> 48= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVX('L','N','V', ... )
!> 49= | A - U S U' | / ( |A| n ulp ) SSBEV('L','V', ... )
!> 50= | I - U U' | / ( n ulp ) SSBEV('L','V', ... )
!> 51= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEV_2STAGE('L','N', ... )
!> 52= | A - U S U' | / ( |A| n ulp ) SSBEVX('L','V','A', ... )
!> 53= | I - U U' | / ( n ulp ) SSBEVX('L','V','A', ... )
!> 54= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVX_2STAGE('L','N','A', ... )
!> 55= | A - U S U' | / ( |A| n ulp ) SSBEVX('L','V','I', ... )
!> 56= | I - U U' | / ( n ulp ) SSBEVX('L','V','I', ... )
!> 57= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVX_2STAGE('L','N','I', ... )
!> 58= | A - U S U' | / ( |A| n ulp ) SSBEVX('L','V','V', ... )
!> 59= | I - U U' | / ( n ulp ) SSBEVX('L','V','V', ... )
!> 60= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVX_2STAGE('L','N','V', ... )
!> 61= | A - U S U' | / ( |A| n ulp ) SSYEVD('L','V', ... )
!> 62= | I - U U' | / ( n ulp ) SSYEVD('L','V', ... )
!> 63= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVD_2STAGE('L','N', ... )
!> 64= | A - U S U' | / ( |A| n ulp ) SSPEVD('L','V', ... )
!> 65= | I - U U' | / ( n ulp ) SSPEVD('L','V', ... )
!> 66= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVD('L','N', ... )
!> 67= | A - U S U' | / ( |A| n ulp ) SSBEVD('L','V', ... )
!> 68= | I - U U' | / ( n ulp ) SSBEVD('L','V', ... )
!> 69= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVD_2STAGE('L','N', ... )
!> 70= | A - U S U' | / ( |A| n ulp ) SSYEVR('L','V','A', ... )
!> 71= | I - U U' | / ( n ulp ) SSYEVR('L','V','A', ... )
!> 72= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVR_2STAGE('L','N','A', ... )
!> 73= | A - U S U' | / ( |A| n ulp ) SSYEVR('L','V','I', ... )
!> 74= | I - U U' | / ( n ulp ) SSYEVR('L','V','I', ... )
!> 75= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVR_2STAGE('L','N','I', ... )
!> 76= | A - U S U' | / ( |A| n ulp ) SSYEVR('L','V','V', ... )
!> 77= | I - U U' | / ( n ulp ) SSYEVR('L','V','V', ... )
!> 78= |D(with Z) - D(w/o Z)| / (|D| ulp) SSYEVR_2STAGE('L','N','V', ... )
!>
!> Tests 25 through 78 are repeated (as tests 79 through 132)
!> with UPLO='U'
!>
!> To be added in 1999
!>
!> 79= | A - U S U' | / ( |A| n ulp ) SSPEVR('L','V','A', ... )
!> 80= | I - U U' | / ( n ulp ) SSPEVR('L','V','A', ... )
!> 81= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVR('L','N','A', ... )
!> 82= | A - U S U' | / ( |A| n ulp ) SSPEVR('L','V','I', ... )
!> 83= | I - U U' | / ( n ulp ) SSPEVR('L','V','I', ... )
!> 84= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVR('L','N','I', ... )
!> 85= | A - U S U' | / ( |A| n ulp ) SSPEVR('L','V','V', ... )
!> 86= | I - U U' | / ( n ulp ) SSPEVR('L','V','V', ... )
!> 87= |D(with Z) - D(w/o Z)| / (|D| ulp) SSPEVR('L','N','V', ... )
!> 88= | A - U S U' | / ( |A| n ulp ) SSBEVR('L','V','A', ... )
!> 89= | I - U U' | / ( n ulp ) SSBEVR('L','V','A', ... )
!> 90= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVR('L','N','A', ... )
!> 91= | A - U S U' | / ( |A| n ulp ) SSBEVR('L','V','I', ... )
!> 92= | I - U U' | / ( n ulp ) SSBEVR('L','V','I', ... )
!> 93= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVR('L','N','I', ... )
!> 94= | A - U S U' | / ( |A| n ulp ) SSBEVR('L','V','V', ... )
!> 95= | I - U U' | / ( n ulp ) SSBEVR('L','V','V', ... )
!> 96= |D(with Z) - D(w/o Z)| / (|D| ulp) SSBEVR('L','N','V', ... )
!>
π Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition at line 449 of file sdrvst2stg.f.
π Author (the Doxygen one π€)
Generated automatically by Doxygen for LAPACK from the source code.
and thatβs the whole page, bestie π β LAPACK Version 3.12.0, from TESTING/EIG/sdrvst2stg.f(3), mwah π
π¦ where this page comes from
- arch rolling: lapack-doc 3.12.1-2 Β· custom
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash-1017 on : a language model's rewrite of the original, under its terms