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dlasv2 examples
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Man Page Details
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NAME
       DLASV2 - the singular value decomposition of a 2-by-2 triangular matrix
       [ F G ]  [ 0 H ]

SYNOPSIS
       SUBROUTINE DLASV2( F, G, H, SSMIN, SSMAX, SNR, CSR, SNL, CSL )

           DOUBLE         PRECISION CSL, CSR, F, G, H, SNL, SNR, SSMAX, SSMIN

PURPOSE
       DLASV2 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) DOUBLE PRECISION
               The (1,1) element of the 2-by-2 matrix.

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

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

       SSMIN   (output) DOUBLE PRECISION
               abs(SSMIN) is the smaller singular value.

       SSMAX   (output) DOUBLE PRECISION
               abs(SSMAX) is the larger singular value.

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

       SNR     (output) DOUBLE PRECISION
               CSR      (output)  DOUBLE  PRECISION 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 parameter.

       Barring over/underflow and assuming a guard digit in  subtraction,  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 over-
       flows 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.

