ZGET22 does an eigenvector check.


 The basic test is:


    RESULT(1) = | A E  -  E W | / ( |A| |E| ulp )


 using the 1-norm.  It also tests the normalization of E:


    RESULT(2) = max | m-norm(E(j)) - 1 | / ( n ulp )


                 j


 where E(j) is the j-th eigenvector, and m-norm is the max-norm of a


 vector.  The max-norm of a complex n-vector x in this case is the


 maximum of |re(x(i)| + |im(x(i)| over i = 1, ..., n.

TRANSA

          TRANSA is CHARACTER*1


          Specifies whether or not A is transposed.


          = 'N':  No transpose


          = 'T':  Transpose


          = 'C':  Conjugate transpose

TRANSE

          TRANSE is CHARACTER*1


          Specifies whether or not E is transposed.


          = 'N':  No transpose, eigenvectors are in columns of E


          = 'T':  Transpose, eigenvectors are in rows of E


          = 'C':  Conjugate transpose, eigenvectors are in rows of E

TRANSW

          TRANSW is CHARACTER*1


          Specifies whether or not W is transposed.


          = 'N':  No transpose


          = 'T':  Transpose, same as TRANSW = 'N'


          = 'C':  Conjugate transpose, use -WI(j) instead of WI(j)

N

          N is INTEGER


          The order of the matrix A.  N >= 0.

A

          A is COMPLEX*16 array, dimension (LDA,N)


          The matrix whose eigenvectors are in E.

LDA

          LDA is INTEGER


          The leading dimension of the array A.  LDA >= max(1,N).

E

          E is COMPLEX*16 array, dimension (LDE,N)


          The matrix of eigenvectors. If TRANSE = 'N', the eigenvectors


          are stored in the columns of E, if TRANSE = 'T' or 'C', the


          eigenvectors are stored in the rows of E.

LDE

          LDE is INTEGER


          The leading dimension of the array E.  LDE >= max(1,N).

W

          W is COMPLEX*16 array, dimension (N)


          The eigenvalues of A.

WORK

          WORK is COMPLEX*16 array, dimension (N*N)

RWORK

          RWORK is DOUBLE PRECISION array, dimension (N)

RESULT

          RESULT is DOUBLE PRECISION array, dimension (2)


          RESULT(1) = | A E  -  E W | / ( |A| |E| ulp )


          RESULT(2) = max | m-norm(E(j)) - 1 | / ( n ulp )


                       j

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