DLAQGE equilibrates a general M by N matrix A using the row and


 column scaling factors in the vectors R and C.

M

          M is INTEGER


          The number of rows of the matrix A.  M >= 0.

N

          N is INTEGER


          The number of columns of the matrix A.  N >= 0.

A

          A is DOUBLE PRECISION array, dimension (LDA,N)


          On entry, the M by N matrix A.


          On exit, the equilibrated matrix.  See EQUED for the form of


          the equilibrated matrix.

LDA

          LDA is INTEGER


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

R

          R is DOUBLE PRECISION array, dimension (M)


          The row scale factors for A.

C

          C is DOUBLE PRECISION array, dimension (N)


          The column scale factors for A.

ROWCND

          ROWCND is DOUBLE PRECISION


          Ratio of the smallest R(i) to the largest R(i).

COLCND

          COLCND is DOUBLE PRECISION


          Ratio of the smallest C(i) to the largest C(i).

AMAX

          AMAX is DOUBLE PRECISION


          Absolute value of largest matrix entry.

EQUED

          EQUED is CHARACTER*1


          Specifies the form of equilibration that was done.


          = 'N':  No equilibration


          = 'R':  Row equilibration, i.e., A has been premultiplied by


                  diag(R).


          = 'C':  Column equilibration, i.e., A has been postmultiplied


                  by diag(C).


          = 'B':  Both row and column equilibration, i.e., A has been


                  replaced by diag(R) * A * diag(C).

  THRESH is a threshold value used to decide if row or column scaling


  should be done based on the ratio of the row or column scaling


  factors.  If ROWCND < THRESH, row scaling is done, and if


  COLCND < THRESH, column scaling is done.


  LARGE and SMALL are threshold values used to decide if row scaling


  should be done based on the absolute size of the largest matrix


  element.  If AMAX > LARGE or AMAX < SMALL, row scaling is done.

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NAG Ltd.

December 2016