DDRVST(3)
π
DDRVST(3) β ddrvst.f(3) era π
ddrvst.f(3) Β· Library Functions Manual Β· header path: /home/abui...IG/ddrvst.f(3)
πΈ NAME πΈ
/home/abui...IG/ddrvst.f(3) β this is the DDRVST tester page, and yes, the whole NAME section is a path. It's giving "build directory main character energy", and we're keeping it exactly. π«Ά
π¦ SYNOPSIS π¦
π Functions/Subroutines π
subroutine DDRVST (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)
DDRVST
π Function/Subroutine Documentation π
okay so here's the full signature, bestie β all the types and dimensions are staying exactly as they are, no cap:
subroutine DDRVST (integer nsizes, integer, dimension( * ) nn, integer
ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
double precision thresh, integer nounit, double precision, dimension(
lda, * ) a, integer lda, double precision, dimension( * ) d1, double
precision, dimension( * ) d2, double precision, dimension( * ) d3,
double precision, dimension( * ) d4, double precision, dimension( * )
eveigs, double precision, dimension( * ) wa1, double precision,
dimension( * ) wa2, double precision, dimension( * ) wa3, double
precision, dimension( ldu, * ) u, integer ldu, double precision,
dimension( ldu, * ) v, double precision, dimension( * ) tau, double
precision, dimension( ldu, * ) z, double precision, dimension( * ) work,
integer lwork, integer, dimension( * ) iwork, integer liwork, double
precision, dimension( * ) result, integer info)
DDRVST
DDRVST
π― Purpose: π―
DDRVST checks the symmetric eigenvalue problem drivers. Slay. π
Here's the driver lineup, and every single name is exact β iykyk:
DSTEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix.DSTEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix.DSTEVRβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric tridiagonal matrix using the Relatively Robust Representation where it can.DSYEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix.DSYEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix.DSYEVRβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix using the Relatively Robust Representation where it can.DSPEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage.DSPEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage.DSBEVβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric band matrix.DSBEVXβ computes selected eigenvalues and, optionally, eigenvectors of a real symmetric band matrix.DSYEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix using a divide and conquer algorithm.DSPEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix in packed storage, using a divide and conquer algorithm.DSBEVDβ computes all eigenvalues and, optionally, eigenvectors of a real symmetric band matrix, using a divide and conquer algorithm.
When DDRVST is called, you specify a number of matrix sizes and a number of matrix types. 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:
(1) | A - Z D Z' | / ( |A| n ulp )
(2) | I - Z Z' | / ( n ulp )
(3) | 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.
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 withNeigenvalues1, 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 andDhasNentries1, 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 ).
Every argument gets its moment, periodt π:
NSIZESINTEGERβ the number of sizes of matrices to use. If it is zero,DDRVSTdoes nothing. It must be at least zero. Not modified.NNINTEGER array, dimension (NSIZES)β an array containing the sizes to be used for the matrices. Zero values will be skipped. The values must be at least zero. Not modified.NTYPESINTEGERβ the number of elements inDOTYPE. If it is zero,DDRVSTdoes nothing. It must be at least zero. If it isMAXTYP+1andNSIZESis1, then an additional type,MAXTYP+1is defined, which is to use whatever matrix is inA. This is only useful ifDOTYPE(1:MAXTYP)is.FALSE.andDOTYPE(MAXTYP+1)is.TRUE.. Not modified.DOTYPELOGICAL array, dimension (NTYPES)β 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. Not modified.ISEEDINTEGER array, dimension (4)β on entryISEEDspecifies the seed of the random number generator. The array elements should be between0and4095; if not they will be reducedmod 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 ofISEEDare changed on exit, and can be used in the next call toDDRVSTto continue the same random number sequence. Modified.THRESHDOUBLE PRECISIONβ A test will count as if the , computed as described above, exceedsTHRESH(yes, those blanks are literally in the source, I'm not inventing words π). 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. Not modified.NOUNITINTEGERβ the FORTRAN unit number for printing out error messages (e.g., if a routine returnsIINFOnot equal to0.) Not modified.ADOUBLE PRECISION array, dimension (LDA , max(NN))β used to hold the matrix whose eigenvalues are to be computed. On exit,Acontains the last matrix actually used. Modified.LDAINTEGERβ the leading dimension ofA. It must be at least1and at leastmax( NN ). Not modified.D1DOUBLE PRECISION array, dimension (max(NN))β the eigenvalues ofA, as computed byDSTEQRsimultaneously withZ. On exit, the eigenvalues inD1correspond with the matrix inA. Modified.D2DOUBLE PRECISION array, dimension (max(NN))β the eigenvalues ofA, as computed byDSTEQRifZis not computed. On exit, the eigenvalues inD2correspond with the matrix inA. Modified.D3DOUBLE PRECISION array, dimension (max(NN))β the eigenvalues ofA, as computed byDSTERF. On exit, the eigenvalues inD3correspond with the matrix inA. Modified.D4DOUBLE PRECISION array, dimensionβ the dimension slot is literally blank here π«EVEIGSDOUBLE PRECISION array, dimension (max(NN))β the eigenvalues as computed byDSTEV('N', ... )(I reserve the right to change this to the output of whichever algorithm computes the most accurate eigenvalues).WA1DOUBLE PRECISION array, dimensionβ blank dimension slot again π«WA2DOUBLE PRECISION array, dimensionβ blank dimension slot again π«WA3DOUBLE PRECISION array, dimensionβ blank dimension slot again π«UDOUBLE PRECISION array, dimension (LDU, max(NN))β the orthogonal matrix computed byDSYTRD+DORGTR. Modified.LDUINTEGERβ the leading dimension ofU,Z, andV. It must be at least1and at leastmax( NN ). Not modified.VDOUBLE PRECISION array, dimension (LDU, max(NN))β theHousholdervectors computed byDSYTRDin reducingAto tridiagonal form. Modified.TAUDOUBLE PRECISION array, dimension (max(NN))β the Householder factors computed byDSYTRDin reducingAto tridiagonal form. Modified.ZDOUBLE PRECISION array, dimension (LDU, max(NN))β the orthogonal matrix of eigenvectors computed byDSTEQR,DPTEQR, andDSTEIN. Modified.WORKDOUBLE PRECISION array, dimension (LWORK)β workspace. Modified.LWORKINTEGERβ the number of entries inWORK. This must be at least1 + 4 * Nmax + 2 * Nmax * lg Nmax + 4 * Nmax**2whereNmax = max( NN(j), 2 )andlg = log base 2. Not modified.IWORKINTEGER array,dimension (6 + 6*Nmax + 5 * Nmax * lg Nmax )β whereNmax = max( NN(j), 2 )andlg = log base 2. Workspace. Modified.RESULTDOUBLE PRECISION array, dimension (105)β the values computed by the tests described above. The values are currently limited to1/ulp, to avoid overflow. Modified.INFOINTEGERβ If0, then everything ran OK.-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 DLATMR, DLATMS, DSYTRD, DORGTR, DSTEQR, DSTERF, or DORMTR returns an error code, the absolute value of it is returned. Modified.
Some Local Variables and Parameters: ---- ----- --------- --- ----------
ZERO, ONEβ Real0and1.MAXTYPβ The number of types defined.NTESTβ The number of tests performed, or which can be performed so far, for the current matrix.NTESTTβ The total number of tests performed so far.NMAXβ Largest value inNN.NMATSβ The number of matrices generated so far.NERRSβ The number of tests which have exceededTHRESHso far (computed byDLAFTS).COND, IMODEβ Values to be passed to the matrix generators.ANORMβ Norm ofA; passed to matrix generators.OVFL, UNFLβ Overflow and underflow thresholds.ULP, ULPINVβ Finest relative precision and its inverse.RTOVFL, RTUNFLβ Square roots of the previous 2 values.
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) )
And here's the test lineup, bestie β formulas stay exactly as written π₯:
The tests performed are: Routine tested
1= | A - U S U' | / ( |A| n ulp ) DSTEV('V', ... )
2= | I - U U' | / ( n ulp ) DSTEV('V', ... )
3= |D(with Z) - D(w/o Z)| / (|D| ulp) DSTEV('N', ... )
4= | A - U S U' | / ( |A| n ulp ) DSTEVX('V','A', ... )
5= | I - U U' | / ( n ulp ) DSTEVX('V','A', ... )
6= |D(with Z) - EVEIGS| / (|D| ulp) DSTEVX('N','A', ... )
7= | A - U S U' | / ( |A| n ulp ) DSTEVR('V','A', ... )
8= | I - U U' | / ( n ulp ) DSTEVR('V','A', ... )
9= |D(with Z) - EVEIGS| / (|D| ulp) DSTEVR('N','A', ... )
10= | A - U S U' | / ( |A| n ulp ) DSTEVX('V','I', ... )
11= | I - U U' | / ( n ulp ) DSTEVX('V','I', ... )
12= |D(with Z) - D(w/o Z)| / (|D| ulp) DSTEVX('N','I', ... )
13= | A - U S U' | / ( |A| n ulp ) DSTEVX('V','V', ... )
14= | I - U U' | / ( n ulp ) DSTEVX('V','V', ... )
15= |D(with Z) - D(w/o Z)| / (|D| ulp) DSTEVX('N','V', ... )
16= | A - U S U' | / ( |A| n ulp ) DSTEVD('V', ... )
17= | I - U U' | / ( n ulp ) DSTEVD('V', ... )
18= |D(with Z) - EVEIGS| / (|D| ulp) DSTEVD('N', ... )
19= | A - U S U' | / ( |A| n ulp ) DSTEVR('V','I', ... )
20= | I - U U' | / ( n ulp ) DSTEVR('V','I', ... )
21= |D(with Z) - D(w/o Z)| / (|D| ulp) DSTEVR('N','I', ... )
22= | A - U S U' | / ( |A| n ulp ) DSTEVR('V','V', ... )
23= | I - U U' | / ( n ulp ) DSTEVR('V','V', ... )
24= |D(with Z) - D(w/o Z)| / (|D| ulp) DSTEVR('N','V', ... )
25= | A - U S U' | / ( |A| n ulp ) DSYEV('L','V', ... )
26= | I - U U' | / ( n ulp ) DSYEV('L','V', ... )
27= |D(with Z) - D(w/o Z)| / (|D| ulp) DSYEV('L','N', ... )
- 28 β
| A - U S U' | / ( |A| n ulp )βDSYEVX('L','V','A', ... ) - 29 β
| I - U U' | / ( n ulp )βDSYEVX('L','V','A', ... ) - 30 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVX('L','N','A', ... ) - 31 β
| A - U S U' | / ( |A| n ulp )βDSYEVX('L','V','I', ... ) - 32 β
| I - U U' | / ( n ulp )βDSYEVX('L','V','I', ... ) - 33 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVX('L','N','I', ... ) - 34 β
| A - U S U' | / ( |A| n ulp )βDSYEVX('L','V','V', ... ) - 35 β
| I - U U' | / ( n ulp )βDSYEVX('L','V','V', ... ) - 36 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVX('L','N','V', ... ) - 37 β
| A - U S U' | / ( |A| n ulp )βDSPEV('L','V', ... ) - 38 β
| I - U U' | / ( n ulp )βDSPEV('L','V', ... ) - 39 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEV('L','N', ... ) - 40 β
| A - U S U' | / ( |A| n ulp )βDSPEVX('L','V','A', ... ) - 41 β
| I - U U' | / ( n ulp )βDSPEVX('L','V','A', ... ) - 42 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVX('L','N','A', ... ) - 43 β
| A - U S U' | / ( |A| n ulp )βDSPEVX('L','V','I', ... ) - 44 β
| I - U U' | / ( n ulp )βDSPEVX('L','V','I', ... ) - 45 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVX('L','N','I', ... ) - 46 β
| A - U S U' | / ( |A| n ulp )βDSPEVX('L','V','V', ... ) - 47 β
| I - U U' | / ( n ulp )βDSPEVX('L','V','V', ... ) - 48 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVX('L','N','V', ... ) - 49 β
| A - U S U' | / ( |A| n ulp )βDSBEV('L','V', ... ) - 50 β
| I - U U' | / ( n ulp )βDSBEV('L','V', ... ) - 51 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEV('L','N', ... ) - 52 β
| A - U S U' | / ( |A| n ulp )βDSBEVX('L','V','A', ... ) - 53 β
| I - U U' | / ( n ulp )βDSBEVX('L','V','A', ... ) - 54 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVX('L','N','A', ... ) - 55 β
| A - U S U' | / ( |A| n ulp )βDSBEVX('L','V','I', ... ) - 56 β
| I - U U' | / ( n ulp )βDSBEVX('L','V','I', ... ) - 57 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVX('L','N','I', ... ) - 58 β
| A - U S U' | / ( |A| n ulp )βDSBEVX('L','V','V', ... ) - 59 β
| I - U U' | / ( n ulp )βDSBEVX('L','V','V', ... ) - 60 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVX('L','N','V', ... ) - 61 β
| A - U S U' | / ( |A| n ulp )βDSYEVD('L','V', ... ) - 62 β
| I - U U' | / ( n ulp )βDSYEVD('L','V', ... ) - 63 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVD('L','N', ... ) - 64 β
| A - U S U' | / ( |A| n ulp )βDSPEVD('L','V', ... ) - 65 β
| I - U U' | / ( n ulp )βDSPEVD('L','V', ... ) - 66 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVD('L','N', ... ) - 67 β
| A - U S U' | / ( |A| n ulp )βDSBEVD('L','V', ... ) - 68 β
| I - U U' | / ( n ulp )βDSBEVD('L','V', ... ) - 69 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVD('L','N', ... ) - 70 β
| A - U S U' | / ( |A| n ulp )βDSYEVR('L','V','A', ... ) - 71 β
| I - U U' | / ( n ulp )βDSYEVR('L','V','A', ... ) - 72 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVR('L','N','A', ... ) - 73 β
| A - U S U' | / ( |A| n ulp )βDSYEVR('L','V','I', ... ) - 74 β
| I - U U' | / ( n ulp )βDSYEVR('L','V','I', ... ) - 75 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVR('L','N','I', ... ) - 76 β
| A - U S U' | / ( |A| n ulp )βDSYEVR('L','V','V', ... ) - 77 β
| I - U U' | / ( n ulp )βDSYEVR('L','V','V', ... ) - 78 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSYEVR('L','N','V', ... )
okay bestie, take a breath π«Ά that's the whole 'L' run done. And here's the plot twist:
β¨ Tests 25 through 78 are repeated (as tests 79 through 132) with UPLO='U' β¨
like, the entire block, again, just flipped. the source comments literally say "To be added in 1999" for the ones below, so these are the wishlist entries β still numbered in the same scheme, no cap π
- 79 β
| A - U S U' | / ( |A| n ulp )βDSPEVR('L','V','A', ... ) - 80 β
| I - U U' | / ( n ulp )βDSPEVR('L','V','A', ... ) - 81 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVR('L','N','A', ... ) - 82 β
| A - U S U' | / ( |A| n ulp )βDSPEVR('L','V','I', ... ) - 83 β
| I - U U' | / ( n ulp )βDSPEVR('L','V','I', ... ) - 84 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVR('L','N','I', ... ) - 85 β
| A - U S U' | / ( |A| n ulp )βDSPEVR('L','V','V', ... ) - 86 β
| I - U U' | / ( n ulp )βDSPEVR('L','V','V', ... ) - 87 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSPEVR('L','N','V', ... ) - 88 β
| A - U S U' | / ( |A| n ulp )βDSBEVR('L','V','A', ... ) - 89 β
| I - U U' | / ( n ulp )βDSBEVR('L','V','A', ... ) - 90 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVR('L','N','A', ... ) - 91 β
| A - U S U' | / ( |A| n ulp )βDSBEVR('L','V','I', ... ) - 92 β
| I - U U' | / ( n ulp )βDSBEVR('L','V','I', ... ) - 93 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVR('L','N','I', ... ) - 94 β
| A - U S U' | / ( |A| n ulp )βDSBEVR('L','V','V', ... ) - 95 β
| I - U U' | / ( n ulp )βDSBEVR('L','V','V', ... ) - 96 β
|D(with Z) - D(w/o Z)| / (|D| ulp)βDSBEVR('L','N','V', ... )
and that's where the list justβ¦ stops at 96 π iconic cliffhanger behaviour, honestly.
π Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition at line 449 of file ddrvst.f.
π Author
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β¨
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