File:  [local] / rpl / lapack / lapack / zspsvx.f
Revision 1.6: download - view: text, annotated - select for diffs - revision graph
Fri Aug 13 21:04:14 2010 UTC (13 years, 9 months ago) by bertrand
Branches: MAIN
CVS tags: rpl-4_0_19, rpl-4_0_18, HEAD
Patches pour OS/2

    1:       SUBROUTINE ZSPSVX( FACT, UPLO, N, NRHS, AP, AFP, IPIV, B, LDB, X,
    2:      $                   LDX, RCOND, FERR, BERR, WORK, RWORK, INFO )
    3: *
    4: *  -- LAPACK driver routine (version 3.2) --
    5: *  -- LAPACK is a software package provided by Univ. of Tennessee,    --
    6: *  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
    7: *     November 2006
    8: *
    9: *     .. Scalar Arguments ..
   10:       CHARACTER          FACT, UPLO
   11:       INTEGER            INFO, LDB, LDX, N, NRHS
   12:       DOUBLE PRECISION   RCOND
   13: *     ..
   14: *     .. Array Arguments ..
   15:       INTEGER            IPIV( * )
   16:       DOUBLE PRECISION   BERR( * ), FERR( * ), RWORK( * )
   17:       COMPLEX*16         AFP( * ), AP( * ), B( LDB, * ), WORK( * ),
   18:      $                   X( LDX, * )
   19: *     ..
   20: *
   21: *  Purpose
   22: *  =======
   23: *
   24: *  ZSPSVX uses the diagonal pivoting factorization A = U*D*U**T or
   25: *  A = L*D*L**T to compute the solution to a complex system of linear
   26: *  equations A * X = B, where A is an N-by-N symmetric matrix stored
   27: *  in packed format and X and B are N-by-NRHS matrices.
   28: *
   29: *  Error bounds on the solution and a condition estimate are also
   30: *  provided.
   31: *
   32: *  Description
   33: *  ===========
   34: *
   35: *  The following steps are performed:
   36: *
   37: *  1. If FACT = 'N', the diagonal pivoting method is used to factor A as
   38: *        A = U * D * U**T,  if UPLO = 'U', or
   39: *        A = L * D * L**T,  if UPLO = 'L',
   40: *     where U (or L) is a product of permutation and unit upper (lower)
   41: *     triangular matrices and D is symmetric and block diagonal with
   42: *     1-by-1 and 2-by-2 diagonal blocks.
   43: *
   44: *  2. If some D(i,i)=0, so that D is exactly singular, then the routine
   45: *     returns with INFO = i. Otherwise, the factored form of A is used
   46: *     to estimate the condition number of the matrix A.  If the
   47: *     reciprocal of the condition number is less than machine precision,
   48: *     INFO = N+1 is returned as a warning, but the routine still goes on
   49: *     to solve for X and compute error bounds as described below.
   50: *
   51: *  3. The system of equations is solved for X using the factored form
   52: *     of A.
   53: *
   54: *  4. Iterative refinement is applied to improve the computed solution
   55: *     matrix and calculate error bounds and backward error estimates
   56: *     for it.
   57: *
   58: *  Arguments
   59: *  =========
   60: *
   61: *  FACT    (input) CHARACTER*1
   62: *          Specifies whether or not the factored form of A has been
   63: *          supplied on entry.
   64: *          = 'F':  On entry, AFP and IPIV contain the factored form
   65: *                  of A.  AP, AFP and IPIV will not be modified.
   66: *          = 'N':  The matrix A will be copied to AFP and factored.
   67: *
   68: *  UPLO    (input) CHARACTER*1
   69: *          = 'U':  Upper triangle of A is stored;
   70: *          = 'L':  Lower triangle of A is stored.
   71: *
   72: *  N       (input) INTEGER
   73: *          The number of linear equations, i.e., the order of the
   74: *          matrix A.  N >= 0.
   75: *
   76: *  NRHS    (input) INTEGER
   77: *          The number of right hand sides, i.e., the number of columns
   78: *          of the matrices B and X.  NRHS >= 0.
   79: *
   80: *  AP      (input) COMPLEX*16 array, dimension (N*(N+1)/2)
   81: *          The upper or lower triangle of the symmetric matrix A, packed
   82: *          columnwise in a linear array.  The j-th column of A is stored
   83: *          in the array AP as follows:
   84: *          if UPLO = 'U', AP(i + (j-1)*j/2) = A(i,j) for 1<=i<=j;
   85: *          if UPLO = 'L', AP(i + (j-1)*(2*n-j)/2) = A(i,j) for j<=i<=n.
   86: *          See below for further details.
   87: *
   88: *  AFP     (input or output) COMPLEX*16 array, dimension (N*(N+1)/2)
   89: *          If FACT = 'F', then AFP is an input argument and on entry
   90: *          contains the block diagonal matrix D and the multipliers used
   91: *          to obtain the factor U or L from the factorization
   92: *          A = U*D*U**T or A = L*D*L**T as computed by ZSPTRF, stored as
   93: *          a packed triangular matrix in the same storage format as A.
   94: *
   95: *          If FACT = 'N', then AFP is an output argument and on exit
   96: *          contains the block diagonal matrix D and the multipliers used
   97: *          to obtain the factor U or L from the factorization
   98: *          A = U*D*U**T or A = L*D*L**T as computed by ZSPTRF, stored as
   99: *          a packed triangular matrix in the same storage format as A.
  100: *
  101: *  IPIV    (input or output) INTEGER array, dimension (N)
  102: *          If FACT = 'F', then IPIV is an input argument and on entry
  103: *          contains details of the interchanges and the block structure
  104: *          of D, as determined by ZSPTRF.
  105: *          If IPIV(k) > 0, then rows and columns k and IPIV(k) were
  106: *          interchanged and D(k,k) is a 1-by-1 diagonal block.
  107: *          If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and
  108: *          columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k)
  109: *          is a 2-by-2 diagonal block.  If UPLO = 'L' and IPIV(k) =
  110: *          IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were
  111: *          interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
  112: *
  113: *          If FACT = 'N', then IPIV is an output argument and on exit
  114: *          contains details of the interchanges and the block structure
  115: *          of D, as determined by ZSPTRF.
  116: *
  117: *  B       (input) COMPLEX*16 array, dimension (LDB,NRHS)
  118: *          The N-by-NRHS right hand side matrix B.
  119: *
  120: *  LDB     (input) INTEGER
  121: *          The leading dimension of the array B.  LDB >= max(1,N).
  122: *
  123: *  X       (output) COMPLEX*16 array, dimension (LDX,NRHS)
  124: *          If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X.
  125: *
  126: *  LDX     (input) INTEGER
  127: *          The leading dimension of the array X.  LDX >= max(1,N).
  128: *
  129: *  RCOND   (output) DOUBLE PRECISION
  130: *          The estimate of the reciprocal condition number of the matrix
  131: *          A.  If RCOND is less than the machine precision (in
  132: *          particular, if RCOND = 0), the matrix is singular to working
  133: *          precision.  This condition is indicated by a return code of
  134: *          INFO > 0.
  135: *
  136: *  FERR    (output) DOUBLE PRECISION array, dimension (NRHS)
  137: *          The estimated forward error bound for each solution vector
  138: *          X(j) (the j-th column of the solution matrix X).
  139: *          If XTRUE is the true solution corresponding to X(j), FERR(j)
  140: *          is an estimated upper bound for the magnitude of the largest
  141: *          element in (X(j) - XTRUE) divided by the magnitude of the
  142: *          largest element in X(j).  The estimate is as reliable as
  143: *          the estimate for RCOND, and is almost always a slight
  144: *          overestimate of the true error.
  145: *
  146: *  BERR    (output) DOUBLE PRECISION array, dimension (NRHS)
  147: *          The componentwise relative backward error of each solution
  148: *          vector X(j) (i.e., the smallest relative change in
  149: *          any element of A or B that makes X(j) an exact solution).
  150: *
  151: *  WORK    (workspace) COMPLEX*16 array, dimension (2*N)
  152: *
  153: *  RWORK   (workspace) DOUBLE PRECISION array, dimension (N)
  154: *
  155: *  INFO    (output) INTEGER
  156: *          = 0: successful exit
  157: *          < 0: if INFO = -i, the i-th argument had an illegal value
  158: *          > 0:  if INFO = i, and i is
  159: *                <= N:  D(i,i) is exactly zero.  The factorization
  160: *                       has been completed but the factor D is exactly
  161: *                       singular, so the solution and error bounds could
  162: *                       not be computed. RCOND = 0 is returned.
  163: *                = N+1: D is nonsingular, but RCOND is less than machine
  164: *                       precision, meaning that the matrix is singular
  165: *                       to working precision.  Nevertheless, the
  166: *                       solution and error bounds are computed because
  167: *                       there are a number of situations where the
  168: *                       computed solution can be more accurate than the
  169: *                       value of RCOND would suggest.
  170: *
  171: *  Further Details
  172: *  ===============
  173: *
  174: *  The packed storage scheme is illustrated by the following example
  175: *  when N = 4, UPLO = 'U':
  176: *
  177: *  Two-dimensional storage of the symmetric matrix A:
  178: *
  179: *     a11 a12 a13 a14
  180: *         a22 a23 a24
  181: *             a33 a34     (aij = aji)
  182: *                 a44
  183: *
  184: *  Packed storage of the upper triangle of A:
  185: *
  186: *  AP = [ a11, a12, a22, a13, a23, a33, a14, a24, a34, a44 ]
  187: *
  188: *  =====================================================================
  189: *
  190: *     .. Parameters ..
  191:       DOUBLE PRECISION   ZERO
  192:       PARAMETER          ( ZERO = 0.0D+0 )
  193: *     ..
  194: *     .. Local Scalars ..
  195:       LOGICAL            NOFACT
  196:       DOUBLE PRECISION   ANORM
  197: *     ..
  198: *     .. External Functions ..
  199:       LOGICAL            LSAME
  200:       DOUBLE PRECISION   DLAMCH, ZLANSP
  201:       EXTERNAL           LSAME, DLAMCH, ZLANSP
  202: *     ..
  203: *     .. External Subroutines ..
  204:       EXTERNAL           XERBLA, ZCOPY, ZLACPY, ZSPCON, ZSPRFS, ZSPTRF,
  205:      $                   ZSPTRS
  206: *     ..
  207: *     .. Intrinsic Functions ..
  208:       INTRINSIC          MAX
  209: *     ..
  210: *     .. Executable Statements ..
  211: *
  212: *     Test the input parameters.
  213: *
  214:       INFO = 0
  215:       NOFACT = LSAME( FACT, 'N' )
  216:       IF( .NOT.NOFACT .AND. .NOT.LSAME( FACT, 'F' ) ) THEN
  217:          INFO = -1
  218:       ELSE IF( .NOT.LSAME( UPLO, 'U' ) .AND. .NOT.LSAME( UPLO, 'L' ) )
  219:      $          THEN
  220:          INFO = -2
  221:       ELSE IF( N.LT.0 ) THEN
  222:          INFO = -3
  223:       ELSE IF( NRHS.LT.0 ) THEN
  224:          INFO = -4
  225:       ELSE IF( LDB.LT.MAX( 1, N ) ) THEN
  226:          INFO = -9
  227:       ELSE IF( LDX.LT.MAX( 1, N ) ) THEN
  228:          INFO = -11
  229:       END IF
  230:       IF( INFO.NE.0 ) THEN
  231:          CALL XERBLA( 'ZSPSVX', -INFO )
  232:          RETURN
  233:       END IF
  234: *
  235:       IF( NOFACT ) THEN
  236: *
  237: *        Compute the factorization A = U*D*U' or A = L*D*L'.
  238: *
  239:          CALL ZCOPY( N*( N+1 ) / 2, AP, 1, AFP, 1 )
  240:          CALL ZSPTRF( UPLO, N, AFP, IPIV, INFO )
  241: *
  242: *        Return if INFO is non-zero.
  243: *
  244:          IF( INFO.GT.0 )THEN
  245:             RCOND = ZERO
  246:             RETURN
  247:          END IF
  248:       END IF
  249: *
  250: *     Compute the norm of the matrix A.
  251: *
  252:       ANORM = ZLANSP( 'I', UPLO, N, AP, RWORK )
  253: *
  254: *     Compute the reciprocal of the condition number of A.
  255: *
  256:       CALL ZSPCON( UPLO, N, AFP, IPIV, ANORM, RCOND, WORK, INFO )
  257: *
  258: *     Compute the solution vectors X.
  259: *
  260:       CALL ZLACPY( 'Full', N, NRHS, B, LDB, X, LDX )
  261:       CALL ZSPTRS( UPLO, N, NRHS, AFP, IPIV, X, LDX, INFO )
  262: *
  263: *     Use iterative refinement to improve the computed solutions and
  264: *     compute error bounds and backward error estimates for them.
  265: *
  266:       CALL ZSPRFS( UPLO, N, NRHS, AP, AFP, IPIV, B, LDB, X, LDX, FERR,
  267:      $             BERR, WORK, RWORK, INFO )
  268: *
  269: *     Set INFO = N+1 if the matrix is singular to working precision.
  270: *
  271:       IF( RCOND.LT.DLAMCH( 'Epsilon' ) )
  272:      $   INFO = N + 1
  273: *
  274:       RETURN
  275: *
  276: *     End of ZSPSVX
  277: *
  278:       END

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