NAME

       larrr - larrr: step in stemr, test to do expensive tridiag eig algorithm

SYNOPSIS

   Functions
       subroutine dlarrr (n, d, e, info)
           DLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants
           expensive computations which guarantee high relative accuracy in the eigenvalues.
       subroutine slarrr (n, d, e, info)
           SLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants
           expensive computations which guarantee high relative accuracy in the eigenvalues.

Detailed Description

Function Documentation

   subroutine dlarrr (integer n, double precision, dimension( * ) d, double precision, dimension(
       * ) e, integer info)
       DLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants
       expensive computations which guarantee high relative accuracy in the eigenvalues.

       Purpose:

            Perform tests to decide whether the symmetric tridiagonal matrix T
            warrants expensive computations which guarantee high relative accuracy
            in the eigenvalues.

       Parameters
           N

                     N is INTEGER
                     The order of the matrix. N > 0.

           D

                     D is DOUBLE PRECISION array, dimension (N)
                     The N diagonal elements of the tridiagonal matrix T.

           E

                     E is DOUBLE PRECISION array, dimension (N)
                     On entry, the first (N-1) entries contain the subdiagonal
                     elements of the tridiagonal matrix T; E(N) is set to ZERO.

           INFO

                     INFO is INTEGER
                     INFO = 0(default) : the matrix warrants computations preserving
                                         relative accuracy.
                     INFO = 1          : the matrix warrants computations guaranteeing
                                         only absolute accuracy.

       Author
           Univ. of Tennessee

           Univ. of California Berkeley

           Univ. of Colorado Denver

           NAG Ltd.

       Contributors:
           Beresford Parlett, University of California, Berkeley, USA
            Jim Demmel, University of California, Berkeley, USA
            Inderjit Dhillon, University of Texas, Austin, USA
            Osni Marques, LBNL/NERSC, USA
            Christof Voemel, University of California, Berkeley, USA

   subroutine slarrr (integer n, real, dimension( * ) d, real, dimension( * ) e, integer info)
       SLARRR performs tests to decide whether the symmetric tridiagonal matrix T warrants
       expensive computations which guarantee high relative accuracy in the eigenvalues.

       Purpose:

            Perform tests to decide whether the symmetric tridiagonal matrix T
            warrants expensive computations which guarantee high relative accuracy
            in the eigenvalues.

       Parameters
           N

                     N is INTEGER
                     The order of the matrix. N > 0.

           D

                     D is REAL array, dimension (N)
                     The N diagonal elements of the tridiagonal matrix T.

           E

                     E is REAL array, dimension (N)
                     On entry, the first (N-1) entries contain the subdiagonal
                     elements of the tridiagonal matrix T; E(N) is set to ZERO.

           INFO

                     INFO is INTEGER
                     INFO = 0(default) : the matrix warrants computations preserving
                                         relative accuracy.
                     INFO = 1          : the matrix warrants computations guaranteeing
                                         only absolute accuracy.

       Author
           Univ. of Tennessee

           Univ. of California Berkeley

           Univ. of Colorado Denver

           NAG Ltd.

       Contributors:
           Beresford Parlett, University of California, Berkeley, USA
            Jim Demmel, University of California, Berkeley, USA
            Inderjit Dhillon, University of Texas, Austin, USA
            Osni Marques, LBNL/NERSC, USA
            Christof Voemel, University of California, Berkeley, USA

Author

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