      subroutine dgbfa(abd,lda,n,ml,mu,ipvt,info)
      integer lda,n,ml,mu,ipvt(*),info
      double precision abd(lda,*)
c!purpose
c
c     dgbfa factors a double precision band matrix by elimination.
c
c     dgbfa is usually called by dgbco, but it can be called
c     directly with a saving in time if  rcond  is not needed.
c
c!calling sequence
c
c      subroutine dgbfa(abd,lda,n,ml,mu,ipvt,info)
c     on entry
c
c        abd     double precision(lda, n)
c                contains the matrix in band storage.  the columns
c                of the matrix are stored in the columns of  abd  and
c                the diagonals of the matrix are stored in rows
c                ml+1 through 2*ml+mu+1 of  abd .
c                see the comments below for details.
c
c        lda     integer
c                the leading dimension of the array  abd .
c                lda must be .ge. 2*ml + mu + 1 .
c
c        n       integer
c                the order of the original matrix.
c
c        ml      integer
c                number of diagonals below the main diagonal.
c                0 .le. ml .lt. n .
c
c        mu      integer
c                number of diagonals above the main diagonal.
c                0 .le. mu .lt. n .
c                more efficient if  ml .le. mu .
c     on return
c
c        abd     an upper triangular matrix in band storage and
c                the multipliers which were used to obtain it.
c                the factorization can be written  a = l*u  where
c                l  is a product of permutation and unit lower
c                triangular matrices and  u  is upper triangular.
c
c        ipvt    integer(n)
c                an integer vector of pivot indices.
c
c        info    integer
c                = 0  normal value.
c                = k  if  u(k,k) .eq. 0.0 .  this is not an error
c                     condition for this subroutine, but it does
c                     indicate that dgbsl will divide by zero if
c                     called.  use  rcond  in dgbco for a reliable
c                     indication of singularity.
c
c     band storage
c
c           if  a  is a band matrix, the following program segment
c           will set up the input.
c
c                   ml = (band width below the diagonal)
c                   mu = (band width above the diagonal)
c                   m = ml + mu + 1
c                   do 20 j = 1, n
c                      i1 = max(1, j-mu)
c                      i2 = min(n, j+ml)
c                      do 10 i = i1, i2
c                         k = i - j + m
c                         abd(k,j) = a(i,j)
c                10    continue
c                20 continue
c
c           this uses rows  ml+1  through  2*ml+mu+1  of  abd .
c           in addition, the first  ml  rows in  abd  are used for
c           elements generated during the triangularization.
c           the total number of rows needed in  abd  is  2*ml+mu+1 .
c           the  ml+mu by ml+mu  upper left triangle and the
c           ml by ml  lower right triangle are not referenced.
c
c!originator
c     linpack. this version dated 08/14/78 .
c     cleve moler, university of new mexico, argonne national lab.
c
c!auxiliary routines
c
c     blas daxpy,dscal,idamax
c     fortran max,min
c
c!
c     internal variables
c
      double precision t
      integer i,idamax,i0,j,ju,jz,j0,j1,k,kp1,l,lm,m,mm,nm1
c
c
      m = ml + mu + 1
      info = 0
c
c     zero initial fill-in columns
c
      j0 = mu + 2
      j1 = min(n,m) - 1
      if (j1 .lt. j0) go to 30
      do 20 jz = j0, j1
         i0 = m + 1 - jz
         do 10 i = i0, ml
            abd(i,jz) = 0.0d+0
   10    continue
   20 continue
   30 continue
      jz = j1
      ju = 0
c
c     gaussian elimination with partial pivoting
c
      nm1 = n - 1
      if (nm1 .lt. 1) go to 130
      do 120 k = 1, nm1
         kp1 = k + 1
c
c        zero next fill-in column
c
         jz = jz + 1
         if (jz .gt. n) go to 50
         if (ml .lt. 1) go to 50
            do 40 i = 1, ml
               abd(i,jz) = 0.0d+0
   40       continue
   50    continue
c
c        find l = pivot index
c
         lm = min(ml,n-k)
         l = idamax(lm+1,abd(m,k),1) + m - 1
         ipvt(k) = l + k - m
c
c        zero pivot implies this column already triangularized
c
         if (abd(l,k) .eq. 0.0d+0) go to 100
c
c           interchange if necessary
c
            if (l .eq. m) go to 60
               t = abd(l,k)
               abd(l,k) = abd(m,k)
               abd(m,k) = t
   60       continue
c
c           compute multipliers
c
            t = -1.0d+0/abd(m,k)
            call dscal(lm,t,abd(m+1,k),1)
c
c           row elimination with column indexing
c
            ju = min(max(ju,mu+ipvt(k)),n)
            mm = m
            if (ju .lt. kp1) go to 90
            do 80 j = kp1, ju
               l = l - 1
               mm = mm - 1
               t = abd(l,j)
               if (l .eq. mm) go to 70
                  abd(l,j) = abd(mm,j)
                  abd(mm,j) = t
   70          continue
               call daxpy(lm,t,abd(m+1,k),1,abd(mm+1,j),1)
   80       continue
   90       continue
         go to 110
  100    continue
            info = k
  110    continue
  120 continue
  130 continue
      ipvt(n) = n
      if (abd(m,n) .eq. 0.0d+0) info = n
      return
      end
