1DBDSDC(1)                LAPACK routine (version 3.1)                DBDSDC(1)
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NAME

6       DBDSDC - the singular value decomposition (SVD) of a real N-by-N (upper
7       or lower) bidiagonal matrix B
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SYNOPSIS

10       SUBROUTINE DBDSDC( UPLO, COMPQ, N, D, E, U, LDU, VT, LDVT, Q, IQ, WORK,
11                          IWORK, INFO )
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13           CHARACTER      COMPQ, UPLO
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15           INTEGER        INFO, LDU, LDVT, N
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17           INTEGER        IQ( * ), IWORK( * )
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19           DOUBLE         PRECISION  D(  * ), E( * ), Q( * ), U( LDU, * ), VT(
20                          LDVT, * ), WORK( * )
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PURPOSE

23       DBDSDC computes the singular value decomposition (SVD) of a real N-by-N
24       (upper  or  lower) bidiagonal matrix B:  B = U * S * VT, using a divide
25       and conquer method, where S is  a  diagonal  matrix  with  non-negative
26       diagonal elements (the singular values of B), and U and VT are orthogo‐
27       nal matrices of left and right singular vectors,  respectively.  DBDSDC
28       can  be  used  to compute all singular values, and optionally, singular
29       vectors or singular vectors in compact form.
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31       This code makes very mild assumptions about floating point  arithmetic.
32       It  will  work  on  machines  with a guard digit in add/subtract, or on
33       those binary machines without guard digits which subtract like the Cray
34       X-MP,  Cray  Y-MP,  Cray C-90, or Cray-2.  It could conceivably fail on
35       hexadecimal or decimal machines without guard digits, but  we  know  of
36       none.  See DLASD3 for details.
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38       The  code  currently  calls DLASDQ if singular values only are desired.
39       However, it can be slightly modified to compute singular  values  using
40       the divide and conquer method.
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ARGUMENTS

44       UPLO    (input) CHARACTER*1
45               = 'U':  B is upper bidiagonal.
46               = 'L':  B is lower bidiagonal.
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48       COMPQ   (input) CHARACTER*1
49               Specifies  whether  singular vectors are to be computed as fol‐
50               lows:
51               = 'N':  Compute singular values only;
52               = 'P':  Compute singular values and compute singular vectors in
53               compact form; = 'I':  Compute singular values and singular vec‐
54               tors.
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56       N       (input) INTEGER
57               The order of the matrix B.  N >= 0.
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59       D       (input/output) DOUBLE PRECISION array, dimension (N)
60               On entry, the n diagonal elements of the bidiagonal  matrix  B.
61               On exit, if INFO=0, the singular values of B.
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63       E       (input/output) DOUBLE PRECISION array, dimension (N-1)
64               On entry, the elements of E contain the offdiagonal elements of
65               the bidiagonal matrix whose SVD is desired.   On  exit,  E  has
66               been destroyed.
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68       U       (output) DOUBLE PRECISION array, dimension (LDU,N)
69               If   COMPQ  =  'I',  then: On exit, if INFO = 0, U contains the
70               left singular vectors of the bidiagonal matrix.  For other val‐
71               ues of COMPQ, U is not referenced.
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73       LDU     (input) INTEGER
74               The  leading  dimension of the array U.  LDU >= 1.  If singular
75               vectors are desired, then LDU >= max( 1, N ).
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77       VT      (output) DOUBLE PRECISION array, dimension (LDVT,N)
78               If  COMPQ = 'I', then: On exit, if INFO = 0, VT'  contains  the
79               right  singular  vectors  of  the bidiagonal matrix.  For other
80               values of COMPQ, VT is not referenced.
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82       LDVT    (input) INTEGER
83               The leading dimension of the array VT.  LDVT >= 1.  If singular
84               vectors are desired, then LDVT >= max( 1, N ).
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86       Q       (output) DOUBLE PRECISION array, dimension (LDQ)
87               If   COMPQ  = 'P', then: On exit, if INFO = 0, Q and IQ contain
88               the left and right singular vectors in a compact form,  requir‐
89               ing  O(N log N) space instead of 2*N**2.  In particular, Q con‐
90               tains all the DOUBLE PRECISION data in LDQ >= N*(11 +  2*SMLSIZ
91               +  8*INT(LOG_2(N/(SMLSIZ+1)))) words of memory, where SMLSIZ is
92               returned by ILAENV and is equal to the maximum size of the sub‐
93               problems  at  the bottom of the computation tree (usually about
94               25).  For other values of COMPQ, Q is not referenced.
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96       IQ      (output) INTEGER array, dimension (LDIQ)
97               If  COMPQ = 'P', then: On exit, if INFO = 0, Q and  IQ  contain
98               the  left and right singular vectors in a compact form, requir‐
99               ing O(N log N) space instead of 2*N**2.  In particular, IQ con‐
100               tains  all  INTEGER  data in LDIQ >= N*(3 + 3*INT(LOG_2(N/(SML‐
101               SIZ+1)))) words of memory, where SMLSIZ is returned  by  ILAENV
102               and is equal to the maximum size of the subproblems at the bot‐
103               tom of the computation tree (usually about 25).  For other val‐
104               ues of COMPQ, IQ is not referenced.
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106       WORK    (workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
107               If  COMPQ  =  'N'  then  LWORK >= (4 * N).  If COMPQ = 'P' then
108               LWORK >= (6 * N).  If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 *
109               N).
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111       IWORK   (workspace) INTEGER array, dimension (8*N)
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113       INFO    (output) INTEGER
114               = 0:  successful exit.
115               < 0:  if INFO = -i, the i-th argument had an illegal value.
116               >  0:   The algorithm failed to compute an singular value.  The
117               update process of divide and conquer failed.
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FURTHER DETAILS

120       Based on contributions by
121          Ming Gu and Huan Ren, Computer Science Division, University of
122          California at Berkeley, USA
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127 LAPACK routine (version 3.1)    November 2006                       DBDSDC(1)
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