TESTING/EIG/zdrvsx.f(3)
π§ TESTING/EIG/zdrvsx.f(3) π§
A page from the Library Functions Manual, part 1, and we are so ready for it, bestie.
πΈ NAME πΈ
TESTING/EIG/zdrvsx.f
β¨ SYNOPSIS β¨
π Functions/Subroutines π
subroutine zdrvsx (nsizes, nn, ntypes, dotype, iseed, thresh, niunit,
nounit, a, lda, h, ht, w, wt, wtmp, vs, ldvs, vs1, result, work,
lwork, rwork, bwork, info)
ZDRVSX
π¦ Function/Subroutine Documentation π¦
subroutine zdrvsx (integer nsizes, integer, dimension( * ) nn, integer
ntypes, logical, dimension( * ) dotype, integer, dimension( 4 ) iseed,
double precision thresh, integer niunit, integer nounit, complex*16,
dimension( lda, * ) a, integer lda, complex*16, dimension( lda, * ) h,
complex*16, dimension( lda, * ) ht, complex*16, dimension( * ) w,
complex*16, dimension( * ) wt, complex*16, dimension( * ) wtmp,
complex*16, dimension( ldvs, * ) vs, integer ldvs, complex*16,
dimension( ldvs, * ) vs1, double precision, dimension( 17 ) result,
complex*16, dimension( * ) work, integer lwork, double precision,
dimension( * ) rwork, logical, dimension( * ) bwork, integer info)
ZDRVSX
π₯ Purpose π₯
Okay so ZDRVSX is out here checking the nonsymmetric eigenvalue (Schur form) problem expert driver ZGEESX. Iconic behavior, honestly.
ZDRVSX uses both test matrices generated randomly depending on data supplied in the calling sequence, and data read from an input file, including precomputed condition numbers to which it compares the ones it computes. Double sourcing, very thorough, we love that.
When ZDRVSX is called, a number of matrix sizes (NSIZES) and a number of matrix types (NTYPES) are specified. For each size (NN(j)) 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 otherwiseβ no sorting of eigenvalues. - (2)
| A - VS T VS' | / ( n |A| ulp )β hereVSis the matrix of Schur eigenvectors, andTis in Schur form. No sorting of eigenvalues. - (3)
| I - VS VS' | / ( n ulp )β no sorting of eigenvalues. - (4)
0ifWare eigenvalues ofT,1/ulpotherwise β no sorting of eigenvalues. - (5)
0ifT(with VS) = T(without VS),1/ulpotherwise β no sorting of eigenvalues. - (6)
0ifeigenvalues(with VS) = eigenvalues(without VS),1/ulpotherwise β no sorting of eigenvalues. - (7)
0 if T is in Schur form, 1/ulp otherwiseβ with sorting of eigenvalues. - (8)
| A - VS T VS' | / ( n |A| ulp )β hereVSis the matrix of Schur eigenvectors, andTis in Schur form. With sorting of eigenvalues. - (9)
| I - VS VS' | / ( n ulp )β with sorting of eigenvalues. - (10)
0ifWare eigenvalues ofT,1/ulpotherwise. If workspace sufficient, also compareWwith and without reciprocal condition numbers. With sorting of eigenvalues. - (11)
0ifT(with VS) = T(without VS),1/ulpotherwise. If workspace sufficient, also compareTwith and without reciprocal condition numbers. With sorting of eigenvalues. - (12)
0ifeigenvalues(with VS) = eigenvalues(without VS),1/ulpotherwise. If workspace sufficient, also compareVSwith and without reciprocal condition numbers. With sorting of eigenvalues. - (13) if sorting worked and
SDIMis the number of eigenvalues which wereSELECTed. If workspace sufficient, also compareSDIMwith and without reciprocal condition numbers. - (14) if
RCONDEthe same no matter ifVSand/orRCONDVcomputed. - (15) if
RCONDVthe same no matter ifVSand/orRCONDEcomputed.
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, ..., ULPand random complex angles. (ULP = (first number larger than 1) - 1) - (5) A diagonal matrix with geometrically spaced entries
1, ..., ULPand random complex angles. - (6) A diagonal matrix with entries
1, ULP, ..., ULPand random complex angles. - (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, whereUis unitary andThas evenly spaced entries1, ..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (10) A matrix of the form
U' T U, whereUis unitary andThas geometrically spaced entries1, ..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (11) A matrix of the form
U' T U, whereUis orthogonal andThas entries1, ULP,..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (12) A matrix of the form
U' T U, whereUis unitary andThas complex eigenvalues randomly chosen fromULP < |z| < 1and randomO(1)entries in the upper triangle. - (13) A matrix of the form
X' T X, whereXhas conditionSQRT( ULP )andThas evenly spaced entries1, ..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (14) A matrix of the form
X' T X, whereXhas conditionSQRT( ULP )andThas geometrically spaced entries1, ..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (15) A matrix of the form
X' T X, whereXhas conditionSQRT( ULP )andThas entries1, ULP,..., ULPwith random complex angles on the diagonal and randomO(1)entries in the upper triangle. - (16) A matrix of the form
X' T X, whereXhas conditionSQRT( ULP )andThas complex eigenvalues randomly chosen fromULP < |z| < 1and randomO(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). IfNis at least4, 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 ZGEESX, 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 ZGEESX, 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.
π Parameters π
π NSIZES π
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.
π¦ NN π¦
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.
π NTYPES π
NTYPES is INTEGER. The number of elements in DOTYPE. NTYPES must be at least zero. If it is zero, no randomly generated test matrices are tested, but and 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. .
π DOTYPE π
DOTYPEβLOGICAL array, 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. periodt, thatβs the whole rule πISEEDβINTEGER array, dimension (4). On entry,ISEEDspecifies the seed of the random number generator. The 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 toZDRVSXto continue the same random number sequence. bestie, oddISEED(4)is not a suggestion, itβs the vibe check π²THRESHβDOUBLE PRECISION. A test will count as a fail 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. zero is the floor, not the ceiling π¨NIUNITβINTEGER. The FORTRAN unit number for reading in the data file of problems to solve.NOUNITβINTEGER. The FORTRAN unit number for printing out error messages (e.g., if a routine returnsINFOnot equal to0.)AβCOMPLEX*16 array, dimension (LDA, max(NN)). Used to hold the matrix whose eigenvalues are to be computed. On exit,Acontains the last matrix actually used. sheβs the main character matrix β¨LDAβINTEGER. The leading dimension ofA, andH.LDAmust be at least1and at leastmax( NN ).HβCOMPLEX*16 array, dimension (LDA, max(NN)). Another copy of the test matrixA, modified byZGEESX.HTβCOMPLEX*16 array, dimension (LDA, max(NN)). Yet another copy of the test matrixA, modified byZGEESX.WβCOMPLEX*16 array, dimension (max(NN)). The computed eigenvalues ofA.WTβCOMPLEX*16 array, dimension (max(NN)). LikeW, this array contains the eigenvalues ofA, but those computed whenZGEESXonly computes a partial eigendecomposition, i.e. not Schur vectors.WTMPβCOMPLEX*16 array, dimension (max(NN)). More temporary storage for eigenvalues.VSβCOMPLEX*16 array, dimension (LDVS, max(NN)).VSholds the computed Schur vectors. Schur vectors are lowkey iconic π¦LDVSβINTEGER. Leading dimension ofVS. Must be at leastmax(1,max(NN)).VS1βCOMPLEX*16 array, dimension (LDVS, max(NN)).VS1holds another copy of the computed Schur vectors.RESULTβDOUBLE PRECISION array, dimension (17). The values computed by the17tests described above. The values are currently limited to1/ulp, to avoid overflow. seventeen little test girlies, all reporting for duty πWORKβCOMPLEX*16 array, dimension (LWORK).LWORKβINTEGER. The number of entries inWORK. This must be at leastmax(1,2*NN(j)**2)for allj. do not skimp onLWORK, bestie πRWORKβDOUBLE PRECISION array, dimension (max(NN)).BWORKβLOGICAL array, dimension (max(NN)).INFOβINTEGER. If0, successful exit. If<0, input parameter-INFOis incorrect. If>0,ZLATMR,CLATMS,CLATMEorZGET24returned an error code andINFOis its absolute value. exit codes: the group chat receipts of linear algebra π
Some Local Variables and Parameters π§
ZERO,ONEβ real0and1.MAXTYPβ the number of types defined.NMAXβ largest value inNN.NERRSβ the number of tests which have exceededTHRESH.COND,CONDS,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.RTULP,RTULPIβ square roots of the previous 4 values.
The following four arrays decode JTYPE:
KTYPE(j)β the general type (1-10) for typej.KMODE(j)β theMODEvalue to be passed to the matrix generator for typej.KMAGN(j)β the order of magnitude (O(1),O(overflow^(1/2) ),O(underflow^(1/2) ))KCONDS(j)β decides whetherCONDSis1or1/sqrt(ulp). (0means irrelevant.)
okay but fr fr, every one of those constraints is load-bearing. this is not a drill, itβs a driver routine π
Author π
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Definition at line 431 of file zdrvsx.f.
Author (auto-generated bestie note) π«Ά
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