subroutine lmdif1(fcn,m,n,x,fvec,tol,info,iwa,wa,lwa)
integer m,n,info,lwa
integer iwa(n)
real tol
real x(n),fvec(m),wa(lwa)
external fcn
c **********
c
c subroutine lmdif1
c
c the purpose of lmdif1 is to minimize the sum of the squares of
c m nonlinear functions in n variables by a modification of the
c levenberg-marquardt algorithm. this is done by using the more
c general least-squares solver lmdif. the user must provide a
c subroutine which calculates the functions. the jacobian is
c then calculated by a forward-difference approximation.
c
c the subroutine statement is
c
c subroutine lmdif1(fcn,m,n,x,fvec,tol,info,iwa,wa,lwa)
c
c where
c
c fcn is the name of the user-supplied subroutine which
c calculates the functions. fcn must be declared
c in an external statement in the user calling
c program, and should be written as follows.
c
c subroutine fcn(m,n,x,fvec,iflag)
c integer m,n,iflag
c real x(n),fvec(m)
c ----------
c calculate the functions at x and
c return this vector in fvec.
c ----------
c return
c end
c
c the value of iflag should not be changed by fcn unless
c the user wants to terminate execution of lmdif1.
c in this case set iflag to a negative integer.
c
c m is a positive integer input variable set to the number
c of functions.
c
c n is a positive integer input variable set to the number
c of variables. n must not exceed m.
c
c x is an array of length n. on input x must contain
c an initial estimate of the solution vector. on output x
c contains the final estimate of the solution vector.
c
c fvec is an output array of length m which contains
c the functions evaluated at the output x.
c
c tol is a nonnegative input variable. termination occurs
c when the algorithm estimates either that the relative
c error in the sum of squares is at most tol or that
c the relative error between x and the solution is at
c most tol.
c
c info is an integer output variable. if the user has
c terminated execution, info is set to the (negative)
c value of iflag. see description of fcn. otherwise,
c info is set as follows.
c
c info = 0 improper input parameters.
c
c info = 1 algorithm estimates that the relative error
c in the sum of squares is at most tol.
c
c info = 2 algorithm estimates that the relative error
c between x and the solution is at most tol.
c
c info = 3 conditions for info = 1 and info = 2 both hold.
c
c info = 4 fvec is orthogonal to the columns of the
c jacobian to machine precision.
c
c info = 5 number of calls to fcn has reached or
c exceeded 200*(n+1).
c
c info = 6 tol is too small. no further reduction in
c the sum of squares is possible.
c
c info = 7 tol is too small. no further improvement in
c the approximate solution x is possible.
c
c iwa is an integer work array of length n.
c
c wa is a work array of length lwa.
c
c lwa is a positive integer input variable not less than
c m*n+5*n+m.
c
c subprograms called
c
c user-supplied ...... fcn
c
c minpack-supplied ... lmdif
c
c argonne national laboratory. minpack project. march 1980.
c burton s. garbow, kenneth e. hillstrom, jorge j. more
c
c **********
integer maxfev,mode,mp5n,nfev,nprint
real epsfcn,factor,ftol,gtol,xtol,zero
data factor,zero /1.0e2,0.0e0/
info = 0
c
c check the input parameters for errors.
c
if (n .le. 0 .or. m .lt. n .or. tol .lt. zero
* .or. lwa .lt. m*n + 5*n + m) go to 10
c
c call lmdif.
c
maxfev = 200*(n + 1)
ftol = tol
xtol = tol
gtol = zero
epsfcn = zero
mode = 1
nprint = 0
mp5n = m + 5*n
call lmdif(fcn,m,n,x,fvec,ftol,xtol,gtol,maxfev,epsfcn,wa(1),
* mode,factor,nprint,info,nfev,wa(mp5n+1),m,iwa,
* wa(n+1),wa(2*n+1),wa(3*n+1),wa(4*n+1),wa(5*n+1))
if (info .eq. 8) info = 4
10 continue
return
c
c last card of subroutine lmdif1.
c
end