1DGESDD(1)             LAPACK driver routine (version 3.1)            DGESDD(1)
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NAME

6       DGESDD - the singular value decomposition (SVD) of a real M-by-N matrix
7       A, optionally computing the left and right singular vectors
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SYNOPSIS

10       SUBROUTINE DGESDD( JOBZ, M, N, A, LDA,  S,  U,  LDU,  VT,  LDVT,  WORK,
11                          LWORK, IWORK, INFO )
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13           CHARACTER      JOBZ
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15           INTEGER        INFO, LDA, LDU, LDVT, LWORK, M, N
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17           INTEGER        IWORK( * )
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19           DOUBLE         PRECISION  A(  LDA,  *  ),  S( * ), U( LDU, * ), VT(
20                          LDVT, * ), WORK( * )
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PURPOSE

23       DGESDD computes the singular value decomposition (SVD) of a real M-by-N
24       matrix A, optionally computing the left and right singular vectors.  If
25       singular vectors are desired, it uses a divide-and-conquer algorithm.
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27       The SVD is written
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29            A = U * SIGMA * transpose(V)
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31       where SIGMA is an M-by-N matrix which is zero except for  its  min(m,n)
32       diagonal elements, U is an M-by-M orthogonal matrix, and V is an N-by-N
33       orthogonal matrix.  The diagonal elements of  SIGMA  are  the  singular
34       values  of  A;  they  are  real  and  non-negative, and are returned in
35       descending order.  The first min(m,n) columns of U and V are  the  left
36       and right singular vectors of A.
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38       Note that the routine returns VT = V**T, not V.
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40       The  divide  and  conquer  algorithm  makes very mild assumptions about
41       floating point arithmetic. It will work on machines with a guard  digit
42       in add/subtract, or on those binary machines without guard digits which
43       subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. It  could
44       conceivably  fail on hexadecimal or decimal machines without guard dig‐
45       its, but we know of none.
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ARGUMENTS

49       JOBZ    (input) CHARACTER*1
50               Specifies options for computing all or part of the matrix U:
51               = 'A':  all M columns of U and all N rows of V**T are  returned
52               in the arrays U and VT; = 'S':  the first min(M,N) columns of U
53               and the first min(M,N) rows of V**T are returned in the  arrays
54               U and VT; = 'O':  If M >= N, the first N columns of U are over‐
55               written on the array A and all rows of V**T are returned in the
56               array VT; otherwise, all columns of U are returned in the array
57               U and the first M rows of V**T are overwritten in the array  A;
58               = 'N':  no columns of U or rows of V**T are computed.
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60       M       (input) INTEGER
61               The number of rows of the input matrix A.  M >= 0.
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63       N       (input) INTEGER
64               The number of columns of the input matrix A.  N >= 0.
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66       A       (input/output) DOUBLE PRECISION array, dimension (LDA,N)
67               On  entry,  the M-by-N matrix A.  On exit, if JOBZ = 'O',  A is
68               overwritten with the first N columns of U  (the  left  singular
69               vectors,  stored  columnwise)  if M >= N; A is overwritten with
70               the first M rows of V**T (the right  singular  vectors,  stored
71               rowwise)  otherwise.   if  JOBZ .ne. 'O', the contents of A are
72               destroyed.
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74       LDA     (input) INTEGER
75               The leading dimension of the array A.  LDA >= max(1,M).
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77       S       (output) DOUBLE PRECISION array, dimension (min(M,N))
78               The singular values of A, sorted so that S(i) >= S(i+1).
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80       U       (output) DOUBLE PRECISION array, dimension (LDU,UCOL)
81               UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N; UCOL = min(M,N)
82               if  JOBZ  = 'S'.  If JOBZ = 'A' or JOBZ = 'O' and M < N, U con‐
83               tains the M-by-M orthogonal matrix U; if JOBZ = 'S', U contains
84               the  first  min(M,N)  columns  of U (the left singular vectors,
85               stored columnwise); if JOBZ = 'O' and M >= N, or JOBZ = 'N',  U
86               is not referenced.
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88       LDU     (input) INTEGER
89               The  leading dimension of the array U.  LDU >= 1; if JOBZ = 'S'
90               or 'A' or JOBZ = 'O' and M < N, LDU >= M.
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92       VT      (output) DOUBLE PRECISION array, dimension (LDVT,N)
93               If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the  N-by-N
94               orthogonal  matrix  V**T;  if JOBZ = 'S', VT contains the first
95               min(M,N) rows of V**T (the right singular vectors, stored  row‐
96               wise); if JOBZ = 'O' and M < N, or JOBZ = 'N', VT is not refer‐
97               enced.
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99       LDVT    (input) INTEGER
100               The leading dimension of the array VT.  LDVT >= 1;  if  JOBZ  =
101               'A' or JOBZ = 'O' and M >= N, LDVT >= N; if JOBZ = 'S', LDVT >=
102               min(M,N).
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104       WORK      (workspace/output)   DOUBLE   PRECISION   array,    dimension
105       (MAX(1,LWORK))
106               On exit, if INFO = 0, WORK(1) returns the optimal LWORK;
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108       LWORK   (input) INTEGER
109               The  dimension  of  the array WORK. LWORK >= 1.  If JOBZ = 'N',
110               LWORK >= 3*min(M,N) + max(max(M,N),7*min(M,N)).  If JOBZ = 'O',
111               LWORK            >=            3*min(M,N)*min(M,N)            +
112               max(max(M,N),5*min(M,N)*min(M,N)+4*min(M,N)).  If JOBZ = 'S' or
113               'A'         LWORK        >=        3*min(M,N)*min(M,N)        +
114               max(max(M,N),4*min(M,N)*min(M,N)+4*min(M,N)).  For good perfor‐
115               mance,  LWORK  should  generally  be larger.  If LWORK = -1 but
116               other input arguments are legal, WORK(1)  returns  the  optimal
117               LWORK.
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119       IWORK   (workspace) INTEGER array, dimension (8*min(M,N))
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121       INFO    (output) INTEGER
122               = 0:  successful exit.
123               < 0:  if INFO = -i, the i-th argument had an illegal value.
124               > 0:  DBDSDC did not converge, updating process failed.
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FURTHER DETAILS

127       Based on contributions by
128          Ming Gu and Huan Ren, Computer Science Division, University of
129          California at Berkeley, USA
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134 LAPACK driver routine (version 3.N1o)vember 2006                       DGESDD(1)
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