!>
!> DLAEV2 computes the eigendecomposition of a 2-by-2 symmetric matrix
!>    [  A   B  ]
!>    [  B   C  ].
!> On return, RT1 is the eigenvalue of larger absolute value, RT2 is the
!> eigenvalue of smaller absolute value, and (CS1,SN1) is the unit right
!> eigenvector for RT1, giving the decomposition
!>
!>    [ CS1  SN1 ] [  A   B  ] [ CS1 -SN1 ]  =  [ RT1  0  ]
!>    [-SN1  CS1 ] [  B   C  ] [ SN1  CS1 ]     [  0  RT2 ].
!> 

A

!>          A is DOUBLE PRECISION
!>          The (1,1) element of the 2-by-2 matrix.
!> 

B

!>          B is DOUBLE PRECISION
!>          The (1,2) element and the conjugate of the (2,1) element of
!>          the 2-by-2 matrix.
!> 

C

!>          C is DOUBLE PRECISION
!>          The (2,2) element of the 2-by-2 matrix.
!> 

RT1

!>          RT1 is DOUBLE PRECISION
!>          The eigenvalue of larger absolute value.
!> 

RT2

!>          RT2 is DOUBLE PRECISION
!>          The eigenvalue of smaller absolute value.
!> 

CS1

!>          CS1 is DOUBLE PRECISION
!> 

SN1

!>          SN1 is DOUBLE PRECISION
!>          The vector (CS1, SN1) is a unit right eigenvector for RT1.
!> 

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!>
!>  RT1 is accurate to a few ulps barring over/underflow.
!>
!>  RT2 may be inaccurate if there is massive cancellation in the
!>  determinant A*C-B*B; higher precision or correctly rounded or
!>  correctly truncated arithmetic would be needed to compute RT2
!>  accurately in all cases.
!>
!>  CS1 and SN1 are accurate to a few ulps barring over/underflow.
!>
!>  Overflow is possible only if RT1 is within a factor of 5 of overflow.
!>  Underflow is harmless if the input data is 0 or exceeds
!>     underflow_threshold / macheps.
!>