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NAME
     slasv2 - compute the singular value decomposition  of  a  2-
     by-2 triangular matrix  [ F G ]  [ 0 H ]

SYNOPSIS
     SUBROUTINE SLASV2( F, G, H, SSMIN, SSMAX, SNR, CSR, SNL, CSL
               )

     REAL CSL, CSR, F, G, H, SNL, SNR, SSMAX, SSMIN



     #include <sunperf.h>

     void slasv2(float f, float g, float h, float  *ssmin,  float
               *ssmax,  float *snr, float *csr, float *snl, float
               *csl) ;

PURPOSE
     SLASV2 computes the singular value decomposition of a 2-by-2
     triangular matrix
        [  F   G  ]
        [  0   H  ].
     On  return,  abs(SSMAX)  is  the  larger   singular   value,
     abs(SSMIN)  is the smaller singular value, and (CSL,SNL) and
     (CSR,SNR) are  the  left  and  right  singular  vectors  for
     abs(SSMAX), giving the decomposition

        [ CSL  SNL ] [  F   G  ] [ CSR -SNR ]  =  [ SSMAX   0   ]
        [-SNL  CSL ] [  0   H  ] [ SNR  CSR ]     [   0     SSMIN
     ].


ARGUMENTS
     F         (input) REAL
               The (1,1) element of the 2-by-2 matrix.

     G         (input) REAL
               The (1,2) element of the 2-by-2 matrix.

     H         (input) REAL
               The (2,2) element of the 2-by-2 matrix.

     SSMIN     (output) REAL
               abs(SSMIN) is the smaller singular value.

     SSMAX     (output) REAL
               abs(SSMAX) is the larger singular value.

     SNL       (output) REAL
               CSL     (output) REAL The vector (CSL, SNL)  is  a
               unit  left  singular vector for the singular value
               abs(SSMAX).

     SNR       (output) REAL
               CSR     (output) REAL The vector (CSR, SNR)  is  a
               unit  right singular vector for the singular value
               abs(SSMAX).

FURTHER DETAILS
     Any input parameter may be aliased with any  output  parame-
     ter.

     Barring over/underflow and assuming a guard  digit  in  sub-
     traction,  all output quantities are correct to within a few
     units in the last place (ulps).

     In IEEE arithmetic, the code works correctly if  one  matrix
     element is infinite.

     Overflow will not occur unless the  largest  singular  value
     itself  overflows  or  is within a few ulps of overflow. (On
     machines with partial overflow, like the Cray, overflow  may
     occur  if the largest singular value is within a factor of 2
     of overflow.)

     Underflow is harmless if underflow  is  gradual.  Otherwise,
     results may correspond to a matrix modified by perturbations
     of size near the underflow threshold.

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