|
- *> \brief \b SCHKBD
- *
- * =========== DOCUMENTATION ===========
- *
- * Online html documentation available at
- * http://www.netlib.org/lapack/explore-html/
- *
- * Definition:
- * ===========
- *
- * SUBROUTINE SCHKBD( NSIZES, MVAL, NVAL, NTYPES, DOTYPE, NRHS,
- * ISEED, THRESH, A, LDA, BD, BE, S1, S2, X, LDX,
- * Y, Z, Q, LDQ, PT, LDPT, U, VT, WORK, LWORK,
- * IWORK, NOUT, INFO )
- *
- * .. Scalar Arguments ..
- * INTEGER INFO, LDA, LDPT, LDQ, LDX, LWORK, NOUT, NRHS,
- * $ NSIZES, NTYPES
- * REAL THRESH
- * ..
- * .. Array Arguments ..
- * LOGICAL DOTYPE( * )
- * INTEGER ISEED( 4 ), IWORK( * ), MVAL( * ), NVAL( * )
- * REAL A( LDA, * ), BD( * ), BE( * ), PT( LDPT, * ),
- * $ Q( LDQ, * ), S1( * ), S2( * ), U( LDPT, * ),
- * $ VT( LDPT, * ), WORK( * ), X( LDX, * ),
- * $ Y( LDX, * ), Z( LDX, * )
- * ..
- *
- *
- *> \par Purpose:
- * =============
- *>
- *> \verbatim
- *>
- *> SCHKBD checks the singular value decomposition (SVD) routines.
- *>
- *> SGEBRD reduces a real general m by n matrix A to upper or lower
- *> bidiagonal form B by an orthogonal transformation: Q' * A * P = B
- *> (or A = Q * B * P'). The matrix B is upper bidiagonal if m >= n
- *> and lower bidiagonal if m < n.
- *>
- *> SORGBR generates the orthogonal matrices Q and P' from SGEBRD.
- *> Note that Q and P are not necessarily square.
- *>
- *> SBDSQR computes the singular value decomposition of the bidiagonal
- *> matrix B as B = U S V'. It is called three times to compute
- *> 1) B = U S1 V', where S1 is the diagonal matrix of singular
- *> values and the columns of the matrices U and V are the left
- *> and right singular vectors, respectively, of B.
- *> 2) Same as 1), but the singular values are stored in S2 and the
- *> singular vectors are not computed.
- *> 3) A = (UQ) S (P'V'), the SVD of the original matrix A.
- *> In addition, SBDSQR has an option to apply the left orthogonal matrix
- *> U to a matrix X, useful in least squares applications.
- *>
- *> SBDSDC computes the singular value decomposition of the bidiagonal
- *> matrix B as B = U S V' using divide-and-conquer. It is called twice
- *> to compute
- *> 1) B = U S1 V', where S1 is the diagonal matrix of singular
- *> values and the columns of the matrices U and V are the left
- *> and right singular vectors, respectively, of B.
- *> 2) Same as 1), but the singular values are stored in S2 and the
- *> singular vectors are not computed.
- *>
- *> For each pair of matrix dimensions (M,N) and each selected matrix
- *> type, an M by N matrix A and an M by NRHS matrix X are generated.
- *> The problem dimensions are as follows
- *> A: M x N
- *> Q: M x min(M,N) (but M x M if NRHS > 0)
- *> P: min(M,N) x N
- *> B: min(M,N) x min(M,N)
- *> U, V: min(M,N) x min(M,N)
- *> S1, S2 diagonal, order min(M,N)
- *> X: M x NRHS
- *>
- *> For each generated matrix, 14 tests are performed:
- *>
- *> Test SGEBRD and SORGBR
- *>
- *> (1) | A - Q B PT | / ( |A| max(M,N) ulp ), PT = P'
- *>
- *> (2) | I - Q' Q | / ( M ulp )
- *>
- *> (3) | I - PT PT' | / ( N ulp )
- *>
- *> Test SBDSQR on bidiagonal matrix B
- *>
- *> (4) | B - U S1 VT | / ( |B| min(M,N) ulp ), VT = V'
- *>
- *> (5) | Y - U Z | / ( |Y| max(min(M,N),k) ulp ), where Y = Q' X
- *> and Z = U' Y.
- *> (6) | I - U' U | / ( min(M,N) ulp )
- *>
- *> (7) | I - VT VT' | / ( min(M,N) ulp )
- *>
- *> (8) S1 contains min(M,N) nonnegative values in decreasing order.
- *> (Return 0 if true, 1/ULP if false.)
- *>
- *> (9) | S1 - S2 | / ( |S1| ulp ), where S2 is computed without
- *> computing U and V.
- *>
- *> (10) 0 if the true singular values of B are within THRESH of
- *> those in S1. 2*THRESH if they are not. (Tested using
- *> SSVDCH)
- *>
- *> Test SBDSQR on matrix A
- *>
- *> (11) | A - (QU) S (VT PT) | / ( |A| max(M,N) ulp )
- *>
- *> (12) | X - (QU) Z | / ( |X| max(M,k) ulp )
- *>
- *> (13) | I - (QU)'(QU) | / ( M ulp )
- *>
- *> (14) | I - (VT PT) (PT'VT') | / ( N ulp )
- *>
- *> Test SBDSDC on bidiagonal matrix B
- *>
- *> (15) | B - U S1 VT | / ( |B| min(M,N) ulp ), VT = V'
- *>
- *> (16) | I - U' U | / ( min(M,N) ulp )
- *>
- *> (17) | I - VT VT' | / ( min(M,N) ulp )
- *>
- *> (18) S1 contains min(M,N) nonnegative values in decreasing order.
- *> (Return 0 if true, 1/ULP if false.)
- *>
- *> (19) | S1 - S2 | / ( |S1| ulp ), where S2 is computed without
- *> computing U and V.
- *> The possible matrix types are
- *>
- *> (1) The zero matrix.
- *> (2) The identity matrix.
- *>
- *> (3) A diagonal matrix with evenly spaced entries
- *> 1, ..., ULP and random signs.
- *> (ULP = (first number larger than 1) - 1 )
- *> (4) A diagonal matrix with geometrically spaced entries
- *> 1, ..., ULP and random signs.
- *> (5) A diagonal matrix with "clustered" entries 1, ULP, ..., ULP
- *> and random signs.
- *>
- *> (6) Same as (3), but multiplied by SQRT( overflow threshold )
- *> (7) Same as (3), but multiplied by SQRT( underflow threshold )
- *>
- *> (8) A matrix of the form U D V, where U and V are orthogonal and
- *> D has evenly spaced entries 1, ..., ULP with random signs
- *> on the diagonal.
- *>
- *> (9) A matrix of the form U D V, where U and V are orthogonal and
- *> D has geometrically spaced entries 1, ..., ULP with random
- *> signs on the diagonal.
- *>
- *> (10) A matrix of the form U D V, where U and V are orthogonal and
- *> D has "clustered" entries 1, ULP,..., ULP with random
- *> signs on the diagonal.
- *>
- *> (11) Same as (8), but multiplied by SQRT( overflow threshold )
- *> (12) Same as (8), but multiplied by SQRT( underflow threshold )
- *>
- *> (13) Rectangular matrix with random entries chosen from (-1,1).
- *> (14) Same as (13), but multiplied by SQRT( overflow threshold )
- *> (15) Same as (13), but multiplied by SQRT( underflow threshold )
- *>
- *> Special case:
- *> (16) A bidiagonal matrix with random entries chosen from a
- *> logarithmic distribution on [ulp^2,ulp^(-2)] (I.e., each
- *> entry is e^x, where x is chosen uniformly on
- *> [ 2 log(ulp), -2 log(ulp) ] .) For *this* type:
- *> (a) SGEBRD is not called to reduce it to bidiagonal form.
- *> (b) the bidiagonal is min(M,N) x min(M,N); if M<N, the
- *> matrix will be lower bidiagonal, otherwise upper.
- *> (c) only tests 5--8 and 14 are performed.
- *>
- *> A subset of the full set of matrix types may be selected through
- *> the logical array DOTYPE.
- *> \endverbatim
- *
- * Arguments:
- * ==========
- *
- *> \param[in] NSIZES
- *> \verbatim
- *> NSIZES is INTEGER
- *> The number of values of M and N contained in the vectors
- *> MVAL and NVAL. The matrix sizes are used in pairs (M,N).
- *> \endverbatim
- *>
- *> \param[in] MVAL
- *> \verbatim
- *> MVAL is INTEGER array, dimension (NM)
- *> The values of the matrix row dimension M.
- *> \endverbatim
- *>
- *> \param[in] NVAL
- *> \verbatim
- *> NVAL is INTEGER array, dimension (NM)
- *> The values of the matrix column dimension N.
- *> \endverbatim
- *>
- *> \param[in] NTYPES
- *> \verbatim
- *> NTYPES is INTEGER
- *> The number of elements in DOTYPE. If it is zero, SCHKBD
- *> does nothing. It must be at least zero. If it is MAXTYP+1
- *> and NSIZES is 1, then an additional type, MAXTYP+1 is
- *> defined, which is to use whatever matrices are in A and B.
- *> This is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
- *> DOTYPE(MAXTYP+1) is .TRUE. .
- *> \endverbatim
- *>
- *> \param[in] DOTYPE
- *> \verbatim
- *> DOTYPE is LOGICAL array, dimension (NTYPES)
- *> If DOTYPE(j) is .TRUE., then for each size (m,n), a matrix
- *> 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.
- *> \endverbatim
- *>
- *> \param[in] NRHS
- *> \verbatim
- *> NRHS is INTEGER
- *> The number of columns in the "right-hand side" matrices X, Y,
- *> and Z, used in testing SBDSQR. If NRHS = 0, then the
- *> operations on the right-hand side will not be tested.
- *> NRHS must be at least 0.
- *> \endverbatim
- *>
- *> \param[in,out] ISEED
- *> \verbatim
- *> 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 values of ISEED are changed on exit, and can be
- *> used in the next call to SCHKBD to continue the same random
- *> number sequence.
- *> \endverbatim
- *>
- *> \param[in] THRESH
- *> \verbatim
- *> THRESH is REAL
- *> The threshold value for the test ratios. A result is
- *> included in the output file if RESULT >= THRESH. To have
- *> every test ratio printed, use THRESH = 0. Note that the
- *> expected value of the test ratios is O(1), so THRESH should
- *> be a reasonably small multiple of 1, e.g., 10 or 100.
- *> \endverbatim
- *>
- *> \param[out] A
- *> \verbatim
- *> A is REAL array, dimension (LDA,NMAX)
- *> where NMAX is the maximum value of N in NVAL.
- *> \endverbatim
- *>
- *> \param[in] LDA
- *> \verbatim
- *> LDA is INTEGER
- *> The leading dimension of the array A. LDA >= max(1,MMAX),
- *> where MMAX is the maximum value of M in MVAL.
- *> \endverbatim
- *>
- *> \param[out] BD
- *> \verbatim
- *> BD is REAL array, dimension
- *> (max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] BE
- *> \verbatim
- *> BE is REAL array, dimension
- *> (max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] S1
- *> \verbatim
- *> S1 is REAL array, dimension
- *> (max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] S2
- *> \verbatim
- *> S2 is REAL array, dimension
- *> (max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] X
- *> \verbatim
- *> X is REAL array, dimension (LDX,NRHS)
- *> \endverbatim
- *>
- *> \param[in] LDX
- *> \verbatim
- *> LDX is INTEGER
- *> The leading dimension of the arrays X, Y, and Z.
- *> LDX >= max(1,MMAX)
- *> \endverbatim
- *>
- *> \param[out] Y
- *> \verbatim
- *> Y is REAL array, dimension (LDX,NRHS)
- *> \endverbatim
- *>
- *> \param[out] Z
- *> \verbatim
- *> Z is REAL array, dimension (LDX,NRHS)
- *> \endverbatim
- *>
- *> \param[out] Q
- *> \verbatim
- *> Q is REAL array, dimension (LDQ,MMAX)
- *> \endverbatim
- *>
- *> \param[in] LDQ
- *> \verbatim
- *> LDQ is INTEGER
- *> The leading dimension of the array Q. LDQ >= max(1,MMAX).
- *> \endverbatim
- *>
- *> \param[out] PT
- *> \verbatim
- *> PT is REAL array, dimension (LDPT,NMAX)
- *> \endverbatim
- *>
- *> \param[in] LDPT
- *> \verbatim
- *> LDPT is INTEGER
- *> The leading dimension of the arrays PT, U, and V.
- *> LDPT >= max(1, max(min(MVAL(j),NVAL(j)))).
- *> \endverbatim
- *>
- *> \param[out] U
- *> \verbatim
- *> U is REAL array, dimension
- *> (LDPT,max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] VT
- *> \verbatim
- *> VT is REAL array, dimension
- *> (LDPT,max(min(MVAL(j),NVAL(j))))
- *> \endverbatim
- *>
- *> \param[out] WORK
- *> \verbatim
- *> WORK is REAL array, dimension (LWORK)
- *> \endverbatim
- *>
- *> \param[in] LWORK
- *> \verbatim
- *> LWORK is INTEGER
- *> The number of entries in WORK. This must be at least
- *> 3(M+N) and M(M + max(M,N,k) + 1) + N*min(M,N) for all
- *> pairs (M,N)=(MM(j),NN(j))
- *> \endverbatim
- *>
- *> \param[out] IWORK
- *> \verbatim
- *> IWORK is INTEGER array, dimension at least 8*min(M,N)
- *> \endverbatim
- *>
- *> \param[in] NOUT
- *> \verbatim
- *> NOUT is INTEGER
- *> The FORTRAN unit number for printing out error messages
- *> (e.g., if a routine returns IINFO not equal to 0.)
- *> \endverbatim
- *>
- *> \param[out] INFO
- *> \verbatim
- *> INFO is INTEGER
- *> If 0, then everything ran OK.
- *> -1: NSIZES < 0
- *> -2: Some MM(j) < 0
- *> -3: Some NN(j) < 0
- *> -4: NTYPES < 0
- *> -6: NRHS < 0
- *> -8: THRESH < 0
- *> -11: LDA < 1 or LDA < MMAX, where MMAX is max( MM(j) ).
- *> -17: LDB < 1 or LDB < MMAX.
- *> -21: LDQ < 1 or LDQ < MMAX.
- *> -23: LDPT< 1 or LDPT< MNMAX.
- *> -27: LWORK too small.
- *> If SLATMR, SLATMS, SGEBRD, SORGBR, or SBDSQR,
- *> returns an error code, the
- *> absolute value of it is returned.
- *>
- *>-----------------------------------------------------------------------
- *>
- *> Some Local Variables and Parameters:
- *> ---- ----- --------- --- ----------
- *>
- *> ZERO, ONE Real 0 and 1.
- *> MAXTYP The number of types defined.
- *> NTEST The number of tests performed, or which can
- *> be performed so far, for the current matrix.
- *> MMAX Largest value in NN.
- *> NMAX Largest value in NN.
- *> MNMIN min(MM(j), NN(j)) (the dimension of the bidiagonal
- *> matrix.)
- *> MNMAX The maximum value of MNMIN for j=1,...,NSIZES.
- *> NFAIL The number of tests which have exceeded THRESH
- *> COND, IMODE Values to be passed to the matrix generators.
- *> ANORM Norm of A; passed to matrix generators.
- *>
- *> OVFL, UNFL Overflow and underflow thresholds.
- *> RTOVFL, RTUNFL Square roots of the previous 2 values.
- *> ULP, ULPINV Finest relative precision and its inverse.
- *>
- *> 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) )
- *> \endverbatim
- *
- * Authors:
- * ========
- *
- *> \author Univ. of Tennessee
- *> \author Univ. of California Berkeley
- *> \author Univ. of Colorado Denver
- *> \author NAG Ltd.
- *
- *> \date November 2011
- *
- *> \ingroup single_eig
- *
- * =====================================================================
- SUBROUTINE SCHKBD( NSIZES, MVAL, NVAL, NTYPES, DOTYPE, NRHS,
- $ ISEED, THRESH, A, LDA, BD, BE, S1, S2, X, LDX,
- $ Y, Z, Q, LDQ, PT, LDPT, U, VT, WORK, LWORK,
- $ IWORK, NOUT, INFO )
- *
- * -- LAPACK test routine (version 3.4.0) --
- * -- LAPACK is a software package provided by Univ. of Tennessee, --
- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
- * November 2011
- *
- * .. Scalar Arguments ..
- INTEGER INFO, LDA, LDPT, LDQ, LDX, LWORK, NOUT, NRHS,
- $ NSIZES, NTYPES
- REAL THRESH
- * ..
- * .. Array Arguments ..
- LOGICAL DOTYPE( * )
- INTEGER ISEED( 4 ), IWORK( * ), MVAL( * ), NVAL( * )
- REAL A( LDA, * ), BD( * ), BE( * ), PT( LDPT, * ),
- $ Q( LDQ, * ), S1( * ), S2( * ), U( LDPT, * ),
- $ VT( LDPT, * ), WORK( * ), X( LDX, * ),
- $ Y( LDX, * ), Z( LDX, * )
- * ..
- *
- * ======================================================================
- *
- * .. Parameters ..
- REAL ZERO, ONE, TWO, HALF
- PARAMETER ( ZERO = 0.0E0, ONE = 1.0E0, TWO = 2.0E0,
- $ HALF = 0.5E0 )
- INTEGER MAXTYP
- PARAMETER ( MAXTYP = 16 )
- * ..
- * .. Local Scalars ..
- LOGICAL BADMM, BADNN, BIDIAG
- CHARACTER UPLO
- CHARACTER*3 PATH
- INTEGER I, IINFO, IMODE, ITYPE, J, JCOL, JSIZE, JTYPE,
- $ LOG2UI, M, MINWRK, MMAX, MNMAX, MNMIN, MQ,
- $ MTYPES, N, NFAIL, NMAX, NTEST
- REAL AMNINV, ANORM, COND, OVFL, RTOVFL, RTUNFL,
- $ TEMP1, TEMP2, ULP, ULPINV, UNFL
- * ..
- * .. Local Arrays ..
- INTEGER IDUM( 1 ), IOLDSD( 4 ), KMAGN( MAXTYP ),
- $ KMODE( MAXTYP ), KTYPE( MAXTYP )
- REAL DUM( 1 ), DUMMA( 1 ), RESULT( 19 )
- * ..
- * .. External Functions ..
- REAL SLAMCH, SLARND
- EXTERNAL SLAMCH, SLARND
- * ..
- * .. External Subroutines ..
- EXTERNAL ALASUM, SBDSDC, SBDSQR, SBDT01, SBDT02, SBDT03,
- $ SCOPY, SGEBRD, SGEMM, SLABAD, SLACPY, SLAHD2,
- $ SLASET, SLATMR, SLATMS, SORGBR, SORT01, XERBLA
- * ..
- * .. Intrinsic Functions ..
- INTRINSIC ABS, EXP, INT, LOG, MAX, MIN, SQRT
- * ..
- * .. Scalars in Common ..
- LOGICAL LERR, OK
- CHARACTER*32 SRNAMT
- INTEGER INFOT, NUNIT
- * ..
- * .. Common blocks ..
- COMMON / INFOC / INFOT, NUNIT, OK, LERR
- COMMON / SRNAMC / SRNAMT
- * ..
- * .. Data statements ..
- DATA KTYPE / 1, 2, 5*4, 5*6, 3*9, 10 /
- DATA KMAGN / 2*1, 3*1, 2, 3, 3*1, 2, 3, 1, 2, 3, 0 /
- DATA KMODE / 2*0, 4, 3, 1, 4, 4, 4, 3, 1, 4, 4, 0,
- $ 0, 0, 0 /
- * ..
- * .. Executable Statements ..
- *
- * Check for errors
- *
- INFO = 0
- *
- BADMM = .FALSE.
- BADNN = .FALSE.
- MMAX = 1
- NMAX = 1
- MNMAX = 1
- MINWRK = 1
- DO 10 J = 1, NSIZES
- MMAX = MAX( MMAX, MVAL( J ) )
- IF( MVAL( J ).LT.0 )
- $ BADMM = .TRUE.
- NMAX = MAX( NMAX, NVAL( J ) )
- IF( NVAL( J ).LT.0 )
- $ BADNN = .TRUE.
- MNMAX = MAX( MNMAX, MIN( MVAL( J ), NVAL( J ) ) )
- MINWRK = MAX( MINWRK, 3*( MVAL( J )+NVAL( J ) ),
- $ MVAL( J )*( MVAL( J )+MAX( MVAL( J ), NVAL( J ),
- $ NRHS )+1 )+NVAL( J )*MIN( NVAL( J ), MVAL( J ) ) )
- 10 CONTINUE
- *
- * Check for errors
- *
- IF( NSIZES.LT.0 ) THEN
- INFO = -1
- ELSE IF( BADMM ) THEN
- INFO = -2
- ELSE IF( BADNN ) THEN
- INFO = -3
- ELSE IF( NTYPES.LT.0 ) THEN
- INFO = -4
- ELSE IF( NRHS.LT.0 ) THEN
- INFO = -6
- ELSE IF( LDA.LT.MMAX ) THEN
- INFO = -11
- ELSE IF( LDX.LT.MMAX ) THEN
- INFO = -17
- ELSE IF( LDQ.LT.MMAX ) THEN
- INFO = -21
- ELSE IF( LDPT.LT.MNMAX ) THEN
- INFO = -23
- ELSE IF( MINWRK.GT.LWORK ) THEN
- INFO = -27
- END IF
- *
- IF( INFO.NE.0 ) THEN
- CALL XERBLA( 'SCHKBD', -INFO )
- RETURN
- END IF
- *
- * Initialize constants
- *
- PATH( 1: 1 ) = 'Single precision'
- PATH( 2: 3 ) = 'BD'
- NFAIL = 0
- NTEST = 0
- UNFL = SLAMCH( 'Safe minimum' )
- OVFL = SLAMCH( 'Overflow' )
- CALL SLABAD( UNFL, OVFL )
- ULP = SLAMCH( 'Precision' )
- ULPINV = ONE / ULP
- LOG2UI = INT( LOG( ULPINV ) / LOG( TWO ) )
- RTUNFL = SQRT( UNFL )
- RTOVFL = SQRT( OVFL )
- INFOT = 0
- *
- * Loop over sizes, types
- *
- DO 200 JSIZE = 1, NSIZES
- M = MVAL( JSIZE )
- N = NVAL( JSIZE )
- MNMIN = MIN( M, N )
- AMNINV = ONE / MAX( M, N, 1 )
- *
- IF( NSIZES.NE.1 ) THEN
- MTYPES = MIN( MAXTYP, NTYPES )
- ELSE
- MTYPES = MIN( MAXTYP+1, NTYPES )
- END IF
- *
- DO 190 JTYPE = 1, MTYPES
- IF( .NOT.DOTYPE( JTYPE ) )
- $ GO TO 190
- *
- DO 20 J = 1, 4
- IOLDSD( J ) = ISEED( J )
- 20 CONTINUE
- *
- DO 30 J = 1, 14
- RESULT( J ) = -ONE
- 30 CONTINUE
- *
- UPLO = ' '
- *
- * Compute "A"
- *
- * Control parameters:
- *
- * KMAGN KMODE KTYPE
- * =1 O(1) clustered 1 zero
- * =2 large clustered 2 identity
- * =3 small exponential (none)
- * =4 arithmetic diagonal, (w/ eigenvalues)
- * =5 random symmetric, w/ eigenvalues
- * =6 nonsymmetric, w/ singular values
- * =7 random diagonal
- * =8 random symmetric
- * =9 random nonsymmetric
- * =10 random bidiagonal (log. distrib.)
- *
- IF( MTYPES.GT.MAXTYP )
- $ GO TO 100
- *
- ITYPE = KTYPE( JTYPE )
- IMODE = KMODE( JTYPE )
- *
- * Compute norm
- *
- GO TO ( 40, 50, 60 )KMAGN( JTYPE )
- *
- 40 CONTINUE
- ANORM = ONE
- GO TO 70
- *
- 50 CONTINUE
- ANORM = ( RTOVFL*ULP )*AMNINV
- GO TO 70
- *
- 60 CONTINUE
- ANORM = RTUNFL*MAX( M, N )*ULPINV
- GO TO 70
- *
- 70 CONTINUE
- *
- CALL SLASET( 'Full', LDA, N, ZERO, ZERO, A, LDA )
- IINFO = 0
- COND = ULPINV
- *
- BIDIAG = .FALSE.
- IF( ITYPE.EQ.1 ) THEN
- *
- * Zero matrix
- *
- IINFO = 0
- *
- ELSE IF( ITYPE.EQ.2 ) THEN
- *
- * Identity
- *
- DO 80 JCOL = 1, MNMIN
- A( JCOL, JCOL ) = ANORM
- 80 CONTINUE
- *
- ELSE IF( ITYPE.EQ.4 ) THEN
- *
- * Diagonal Matrix, [Eigen]values Specified
- *
- CALL SLATMS( MNMIN, MNMIN, 'S', ISEED, 'N', WORK, IMODE,
- $ COND, ANORM, 0, 0, 'N', A, LDA,
- $ WORK( MNMIN+1 ), IINFO )
- *
- ELSE IF( ITYPE.EQ.5 ) THEN
- *
- * Symmetric, eigenvalues specified
- *
- CALL SLATMS( MNMIN, MNMIN, 'S', ISEED, 'S', WORK, IMODE,
- $ COND, ANORM, M, N, 'N', A, LDA,
- $ WORK( MNMIN+1 ), IINFO )
- *
- ELSE IF( ITYPE.EQ.6 ) THEN
- *
- * Nonsymmetric, singular values specified
- *
- CALL SLATMS( M, N, 'S', ISEED, 'N', WORK, IMODE, COND,
- $ ANORM, M, N, 'N', A, LDA, WORK( MNMIN+1 ),
- $ IINFO )
- *
- ELSE IF( ITYPE.EQ.7 ) THEN
- *
- * Diagonal, random entries
- *
- CALL SLATMR( MNMIN, MNMIN, 'S', ISEED, 'N', WORK, 6, ONE,
- $ ONE, 'T', 'N', WORK( MNMIN+1 ), 1, ONE,
- $ WORK( 2*MNMIN+1 ), 1, ONE, 'N', IWORK, 0, 0,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- *
- ELSE IF( ITYPE.EQ.8 ) THEN
- *
- * Symmetric, random entries
- *
- CALL SLATMR( MNMIN, MNMIN, 'S', ISEED, 'S', WORK, 6, ONE,
- $ ONE, 'T', 'N', WORK( MNMIN+1 ), 1, ONE,
- $ WORK( M+MNMIN+1 ), 1, ONE, 'N', IWORK, M, N,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- *
- ELSE IF( ITYPE.EQ.9 ) THEN
- *
- * Nonsymmetric, random entries
- *
- CALL SLATMR( M, N, 'S', ISEED, 'N', WORK, 6, ONE, ONE,
- $ 'T', 'N', WORK( MNMIN+1 ), 1, ONE,
- $ WORK( M+MNMIN+1 ), 1, ONE, 'N', IWORK, M, N,
- $ ZERO, ANORM, 'NO', A, LDA, IWORK, IINFO )
- *
- ELSE IF( ITYPE.EQ.10 ) THEN
- *
- * Bidiagonal, random entries
- *
- TEMP1 = -TWO*LOG( ULP )
- DO 90 J = 1, MNMIN
- BD( J ) = EXP( TEMP1*SLARND( 2, ISEED ) )
- IF( J.LT.MNMIN )
- $ BE( J ) = EXP( TEMP1*SLARND( 2, ISEED ) )
- 90 CONTINUE
- *
- IINFO = 0
- BIDIAG = .TRUE.
- IF( M.GE.N ) THEN
- UPLO = 'U'
- ELSE
- UPLO = 'L'
- END IF
- ELSE
- IINFO = 1
- END IF
- *
- IF( IINFO.EQ.0 ) THEN
- *
- * Generate Right-Hand Side
- *
- IF( BIDIAG ) THEN
- CALL SLATMR( MNMIN, NRHS, 'S', ISEED, 'N', WORK, 6,
- $ ONE, ONE, 'T', 'N', WORK( MNMIN+1 ), 1,
- $ ONE, WORK( 2*MNMIN+1 ), 1, ONE, 'N',
- $ IWORK, MNMIN, NRHS, ZERO, ONE, 'NO', Y,
- $ LDX, IWORK, IINFO )
- ELSE
- CALL SLATMR( M, NRHS, 'S', ISEED, 'N', WORK, 6, ONE,
- $ ONE, 'T', 'N', WORK( M+1 ), 1, ONE,
- $ WORK( 2*M+1 ), 1, ONE, 'N', IWORK, M,
- $ NRHS, ZERO, ONE, 'NO', X, LDX, IWORK,
- $ IINFO )
- END IF
- END IF
- *
- * Error Exit
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'Generator', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- RETURN
- END IF
- *
- 100 CONTINUE
- *
- * Call SGEBRD and SORGBR to compute B, Q, and P, do tests.
- *
- IF( .NOT.BIDIAG ) THEN
- *
- * Compute transformations to reduce A to bidiagonal form:
- * B := Q' * A * P.
- *
- CALL SLACPY( ' ', M, N, A, LDA, Q, LDQ )
- CALL SGEBRD( M, N, Q, LDQ, BD, BE, WORK, WORK( MNMIN+1 ),
- $ WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
- *
- * Check error code from SGEBRD.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SGEBRD', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- RETURN
- END IF
- *
- CALL SLACPY( ' ', M, N, Q, LDQ, PT, LDPT )
- IF( M.GE.N ) THEN
- UPLO = 'U'
- ELSE
- UPLO = 'L'
- END IF
- *
- * Generate Q
- *
- MQ = M
- IF( NRHS.LE.0 )
- $ MQ = MNMIN
- CALL SORGBR( 'Q', M, MQ, N, Q, LDQ, WORK,
- $ WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
- *
- * Check error code from SORGBR.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SORGBR(Q)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- RETURN
- END IF
- *
- * Generate P'
- *
- CALL SORGBR( 'P', MNMIN, N, M, PT, LDPT, WORK( MNMIN+1 ),
- $ WORK( 2*MNMIN+1 ), LWORK-2*MNMIN, IINFO )
- *
- * Check error code from SORGBR.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SORGBR(P)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- RETURN
- END IF
- *
- * Apply Q' to an M by NRHS matrix X: Y := Q' * X.
- *
- CALL SGEMM( 'Transpose', 'No transpose', M, NRHS, M, ONE,
- $ Q, LDQ, X, LDX, ZERO, Y, LDX )
- *
- * Test 1: Check the decomposition A := Q * B * PT
- * 2: Check the orthogonality of Q
- * 3: Check the orthogonality of PT
- *
- CALL SBDT01( M, N, 1, A, LDA, Q, LDQ, BD, BE, PT, LDPT,
- $ WORK, RESULT( 1 ) )
- CALL SORT01( 'Columns', M, MQ, Q, LDQ, WORK, LWORK,
- $ RESULT( 2 ) )
- CALL SORT01( 'Rows', MNMIN, N, PT, LDPT, WORK, LWORK,
- $ RESULT( 3 ) )
- END IF
- *
- * Use SBDSQR to form the SVD of the bidiagonal matrix B:
- * B := U * S1 * VT, and compute Z = U' * Y.
- *
- CALL SCOPY( MNMIN, BD, 1, S1, 1 )
- IF( MNMIN.GT.0 )
- $ CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
- CALL SLACPY( ' ', M, NRHS, Y, LDX, Z, LDX )
- CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, U, LDPT )
- CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, VT, LDPT )
- *
- CALL SBDSQR( UPLO, MNMIN, MNMIN, MNMIN, NRHS, S1, WORK, VT,
- $ LDPT, U, LDPT, Z, LDX, WORK( MNMIN+1 ), IINFO )
- *
- * Check error code from SBDSQR.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SBDSQR(vects)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- IF( IINFO.LT.0 ) THEN
- RETURN
- ELSE
- RESULT( 4 ) = ULPINV
- GO TO 170
- END IF
- END IF
- *
- * Use SBDSQR to compute only the singular values of the
- * bidiagonal matrix B; U, VT, and Z should not be modified.
- *
- CALL SCOPY( MNMIN, BD, 1, S2, 1 )
- IF( MNMIN.GT.0 )
- $ CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
- *
- CALL SBDSQR( UPLO, MNMIN, 0, 0, 0, S2, WORK, VT, LDPT, U,
- $ LDPT, Z, LDX, WORK( MNMIN+1 ), IINFO )
- *
- * Check error code from SBDSQR.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SBDSQR(values)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- IF( IINFO.LT.0 ) THEN
- RETURN
- ELSE
- RESULT( 9 ) = ULPINV
- GO TO 170
- END IF
- END IF
- *
- * Test 4: Check the decomposition B := U * S1 * VT
- * 5: Check the computation Z := U' * Y
- * 6: Check the orthogonality of U
- * 7: Check the orthogonality of VT
- *
- CALL SBDT03( UPLO, MNMIN, 1, BD, BE, U, LDPT, S1, VT, LDPT,
- $ WORK, RESULT( 4 ) )
- CALL SBDT02( MNMIN, NRHS, Y, LDX, Z, LDX, U, LDPT, WORK,
- $ RESULT( 5 ) )
- CALL SORT01( 'Columns', MNMIN, MNMIN, U, LDPT, WORK, LWORK,
- $ RESULT( 6 ) )
- CALL SORT01( 'Rows', MNMIN, MNMIN, VT, LDPT, WORK, LWORK,
- $ RESULT( 7 ) )
- *
- * Test 8: Check that the singular values are sorted in
- * non-increasing order and are non-negative
- *
- RESULT( 8 ) = ZERO
- DO 110 I = 1, MNMIN - 1
- IF( S1( I ).LT.S1( I+1 ) )
- $ RESULT( 8 ) = ULPINV
- IF( S1( I ).LT.ZERO )
- $ RESULT( 8 ) = ULPINV
- 110 CONTINUE
- IF( MNMIN.GE.1 ) THEN
- IF( S1( MNMIN ).LT.ZERO )
- $ RESULT( 8 ) = ULPINV
- END IF
- *
- * Test 9: Compare SBDSQR with and without singular vectors
- *
- TEMP2 = ZERO
- *
- DO 120 J = 1, MNMIN
- TEMP1 = ABS( S1( J )-S2( J ) ) /
- $ MAX( SQRT( UNFL )*MAX( S1( 1 ), ONE ),
- $ ULP*MAX( ABS( S1( J ) ), ABS( S2( J ) ) ) )
- TEMP2 = MAX( TEMP1, TEMP2 )
- 120 CONTINUE
- *
- RESULT( 9 ) = TEMP2
- *
- * Test 10: Sturm sequence test of singular values
- * Go up by factors of two until it succeeds
- *
- TEMP1 = THRESH*( HALF-ULP )
- *
- DO 130 J = 0, LOG2UI
- * CALL SSVDCH( MNMIN, BD, BE, S1, TEMP1, IINFO )
- IF( IINFO.EQ.0 )
- $ GO TO 140
- TEMP1 = TEMP1*TWO
- 130 CONTINUE
- *
- 140 CONTINUE
- RESULT( 10 ) = TEMP1
- *
- * Use SBDSQR to form the decomposition A := (QU) S (VT PT)
- * from the bidiagonal form A := Q B PT.
- *
- IF( .NOT.BIDIAG ) THEN
- CALL SCOPY( MNMIN, BD, 1, S2, 1 )
- IF( MNMIN.GT.0 )
- $ CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
- *
- CALL SBDSQR( UPLO, MNMIN, N, M, NRHS, S2, WORK, PT, LDPT,
- $ Q, LDQ, Y, LDX, WORK( MNMIN+1 ), IINFO )
- *
- * Test 11: Check the decomposition A := Q*U * S2 * VT*PT
- * 12: Check the computation Z := U' * Q' * X
- * 13: Check the orthogonality of Q*U
- * 14: Check the orthogonality of VT*PT
- *
- CALL SBDT01( M, N, 0, A, LDA, Q, LDQ, S2, DUMMA, PT,
- $ LDPT, WORK, RESULT( 11 ) )
- CALL SBDT02( M, NRHS, X, LDX, Y, LDX, Q, LDQ, WORK,
- $ RESULT( 12 ) )
- CALL SORT01( 'Columns', M, MQ, Q, LDQ, WORK, LWORK,
- $ RESULT( 13 ) )
- CALL SORT01( 'Rows', MNMIN, N, PT, LDPT, WORK, LWORK,
- $ RESULT( 14 ) )
- END IF
- *
- * Use SBDSDC to form the SVD of the bidiagonal matrix B:
- * B := U * S1 * VT
- *
- CALL SCOPY( MNMIN, BD, 1, S1, 1 )
- IF( MNMIN.GT.0 )
- $ CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
- CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, U, LDPT )
- CALL SLASET( 'Full', MNMIN, MNMIN, ZERO, ONE, VT, LDPT )
- *
- CALL SBDSDC( UPLO, 'I', MNMIN, S1, WORK, U, LDPT, VT, LDPT,
- $ DUM, IDUM, WORK( MNMIN+1 ), IWORK, IINFO )
- *
- * Check error code from SBDSDC.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SBDSDC(vects)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- IF( IINFO.LT.0 ) THEN
- RETURN
- ELSE
- RESULT( 15 ) = ULPINV
- GO TO 170
- END IF
- END IF
- *
- * Use SBDSDC to compute only the singular values of the
- * bidiagonal matrix B; U and VT should not be modified.
- *
- CALL SCOPY( MNMIN, BD, 1, S2, 1 )
- IF( MNMIN.GT.0 )
- $ CALL SCOPY( MNMIN-1, BE, 1, WORK, 1 )
- *
- CALL SBDSDC( UPLO, 'N', MNMIN, S2, WORK, DUM, 1, DUM, 1,
- $ DUM, IDUM, WORK( MNMIN+1 ), IWORK, IINFO )
- *
- * Check error code from SBDSDC.
- *
- IF( IINFO.NE.0 ) THEN
- WRITE( NOUT, FMT = 9998 )'SBDSDC(values)', IINFO, M, N,
- $ JTYPE, IOLDSD
- INFO = ABS( IINFO )
- IF( IINFO.LT.0 ) THEN
- RETURN
- ELSE
- RESULT( 18 ) = ULPINV
- GO TO 170
- END IF
- END IF
- *
- * Test 15: Check the decomposition B := U * S1 * VT
- * 16: Check the orthogonality of U
- * 17: Check the orthogonality of VT
- *
- CALL SBDT03( UPLO, MNMIN, 1, BD, BE, U, LDPT, S1, VT, LDPT,
- $ WORK, RESULT( 15 ) )
- CALL SORT01( 'Columns', MNMIN, MNMIN, U, LDPT, WORK, LWORK,
- $ RESULT( 16 ) )
- CALL SORT01( 'Rows', MNMIN, MNMIN, VT, LDPT, WORK, LWORK,
- $ RESULT( 17 ) )
- *
- * Test 18: Check that the singular values are sorted in
- * non-increasing order and are non-negative
- *
- RESULT( 18 ) = ZERO
- DO 150 I = 1, MNMIN - 1
- IF( S1( I ).LT.S1( I+1 ) )
- $ RESULT( 18 ) = ULPINV
- IF( S1( I ).LT.ZERO )
- $ RESULT( 18 ) = ULPINV
- 150 CONTINUE
- IF( MNMIN.GE.1 ) THEN
- IF( S1( MNMIN ).LT.ZERO )
- $ RESULT( 18 ) = ULPINV
- END IF
- *
- * Test 19: Compare SBDSQR with and without singular vectors
- *
- TEMP2 = ZERO
- *
- DO 160 J = 1, MNMIN
- TEMP1 = ABS( S1( J )-S2( J ) ) /
- $ MAX( SQRT( UNFL )*MAX( S1( 1 ), ONE ),
- $ ULP*MAX( ABS( S1( 1 ) ), ABS( S2( 1 ) ) ) )
- TEMP2 = MAX( TEMP1, TEMP2 )
- 160 CONTINUE
- *
- RESULT( 19 ) = TEMP2
- *
- * End of Loop -- Check for RESULT(j) > THRESH
- *
- 170 CONTINUE
- DO 180 J = 1, 19
- IF( RESULT( J ).GE.THRESH ) THEN
- IF( NFAIL.EQ.0 )
- $ CALL SLAHD2( NOUT, PATH )
- WRITE( NOUT, FMT = 9999 )M, N, JTYPE, IOLDSD, J,
- $ RESULT( J )
- NFAIL = NFAIL + 1
- END IF
- 180 CONTINUE
- IF( .NOT.BIDIAG ) THEN
- NTEST = NTEST + 19
- ELSE
- NTEST = NTEST + 5
- END IF
- *
- 190 CONTINUE
- 200 CONTINUE
- *
- * Summary
- *
- CALL ALASUM( PATH, NOUT, NFAIL, NTEST, 0 )
- *
- RETURN
- *
- * End of SCHKBD
- *
- 9999 FORMAT( ' M=', I5, ', N=', I5, ', type ', I2, ', seed=',
- $ 4( I4, ',' ), ' test(', I2, ')=', G11.4 )
- 9998 FORMAT( ' SCHKBD: ', A, ' returned INFO=', I6, '.', / 9X, 'M=',
- $ I6, ', N=', I6, ', JTYPE=', I6, ', ISEED=(', 3( I5, ',' ),
- $ I5, ')' )
- *
- END
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