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