minpack-19961126/0000755000175000017500000000000011616327335014311 5ustar sylvestresylvestreminpack-19961126/lmdif.f0000644000175000017500000003627003226632010015546 0ustar sylvestresylvestre subroutine lmdif(fcn,m,n,x,fvec,ftol,xtol,gtol,maxfev,epsfcn, * diag,mode,factor,nprint,info,nfev,fjac,ldfjac, * ipvt,qtf,wa1,wa2,wa3,wa4) integer m,n,maxfev,mode,nprint,info,nfev,ldfjac integer ipvt(n) double precision ftol,xtol,gtol,epsfcn,factor double precision x(n),fvec(m),diag(n),fjac(ldfjac,n),qtf(n), * wa1(n),wa2(n),wa3(n),wa4(m) external fcn c ********** c c subroutine lmdif c c the purpose of lmdif is to minimize the sum of the squares of c m nonlinear functions in n variables by a modification of c the levenberg-marquardt algorithm. 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 lmdif(fcn,m,n,x,fvec,ftol,xtol,gtol,maxfev,epsfcn, c diag,mode,factor,nprint,info,nfev,fjac, c ldfjac,ipvt,qtf,wa1,wa2,wa3,wa4) 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 double precision 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 lmdif. 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 ftol is a nonnegative input variable. termination c occurs when both the actual and predicted relative c reductions in the sum of squares are at most ftol. c therefore, ftol measures the relative error desired c in the sum of squares. c c xtol is a nonnegative input variable. termination c occurs when the relative error between two consecutive c iterates is at most xtol. therefore, xtol measures the c relative error desired in the approximate solution. c c gtol is a nonnegative input variable. termination c occurs when the cosine of the angle between fvec and c any column of the jacobian is at most gtol in absolute c value. therefore, gtol measures the orthogonality c desired between the function vector and the columns c of the jacobian. c c maxfev is a positive integer input variable. termination c occurs when the number of calls to fcn is at least c maxfev by the end of an iteration. c c epsfcn is an input variable used in determining a suitable c step length for the forward-difference approximation. this c approximation assumes that the relative errors in the c functions are of the order of epsfcn. if epsfcn is less c than the machine precision, it is assumed that the relative c errors in the functions are of the order of the machine c precision. c c diag is an array of length n. if mode = 1 (see c below), diag is internally set. if mode = 2, diag c must contain positive entries that serve as c multiplicative scale factors for the variables. c c mode is an integer input variable. if mode = 1, the c variables will be scaled internally. if mode = 2, c the scaling is specified by the input diag. other c values of mode are equivalent to mode = 1. c c factor is a positive input variable used in determining the c initial step bound. this bound is set to the product of c factor and the euclidean norm of diag*x if nonzero, or else c to factor itself. in most cases factor should lie in the c interval (.1,100.). 100. is a generally recommended value. c c nprint is an integer input variable that enables controlled c printing of iterates if it is positive. in this case, c fcn is called with iflag = 0 at the beginning of the first c iteration and every nprint iterations thereafter and c immediately prior to return, with x and fvec available c for printing. if nprint is not positive, no special calls c of fcn with iflag = 0 are made. 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 both actual and predicted relative reductions c in the sum of squares are at most ftol. c c info = 2 relative error between two consecutive iterates c is at most xtol. c c info = 3 conditions for info = 1 and info = 2 both hold. c c info = 4 the cosine of the angle between fvec and any c column of the jacobian is at most gtol in c absolute value. c c info = 5 number of calls to fcn has reached or c exceeded maxfev. c c info = 6 ftol is too small. no further reduction in c the sum of squares is possible. c c info = 7 xtol is too small. no further improvement in c the approximate solution x is possible. c c info = 8 gtol is too small. fvec is orthogonal to the c columns of the jacobian to machine precision. c c nfev is an integer output variable set to the number of c calls to fcn. c c fjac is an output m by n array. the upper n by n submatrix c of fjac contains an upper triangular matrix r with c diagonal elements of nonincreasing magnitude such that c c t t t c p *(jac *jac)*p = r *r, c c where p is a permutation matrix and jac is the final c calculated jacobian. column j of p is column ipvt(j) c (see below) of the identity matrix. the lower trapezoidal c part of fjac contains information generated during c the computation of r. c c ldfjac is a positive integer input variable not less than m c which specifies the leading dimension of the array fjac. c c ipvt is an integer output array of length n. ipvt c defines a permutation matrix p such that jac*p = q*r, c where jac is the final calculated jacobian, q is c orthogonal (not stored), and r is upper triangular c with diagonal elements of nonincreasing magnitude. c column j of p is column ipvt(j) of the identity matrix. c c qtf is an output array of length n which contains c the first n elements of the vector (q transpose)*fvec. c c wa1, wa2, and wa3 are work arrays of length n. c c wa4 is a work array of length m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dpmpar,enorm,fdjac2,lmpar,qrfac c c fortran-supplied ... dabs,dmax1,dmin1,dsqrt,mod c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,iflag,iter,j,l double precision actred,delta,dirder,epsmch,fnorm,fnorm1,gnorm, * one,par,pnorm,prered,p1,p5,p25,p75,p0001,ratio, * sum,temp,temp1,temp2,xnorm,zero double precision dpmpar,enorm data one,p1,p5,p25,p75,p0001,zero * /1.0d0,1.0d-1,5.0d-1,2.5d-1,7.5d-1,1.0d-4,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c info = 0 iflag = 0 nfev = 0 c c check the input parameters for errors. c if (n .le. 0 .or. m .lt. n .or. ldfjac .lt. m * .or. ftol .lt. zero .or. xtol .lt. zero .or. gtol .lt. zero * .or. maxfev .le. 0 .or. factor .le. zero) go to 300 if (mode .ne. 2) go to 20 do 10 j = 1, n if (diag(j) .le. zero) go to 300 10 continue 20 continue c c evaluate the function at the starting point c and calculate its norm. c iflag = 1 call fcn(m,n,x,fvec,iflag) nfev = 1 if (iflag .lt. 0) go to 300 fnorm = enorm(m,fvec) c c initialize levenberg-marquardt parameter and iteration counter. c par = zero iter = 1 c c beginning of the outer loop. c 30 continue c c calculate the jacobian matrix. c iflag = 2 call fdjac2(fcn,m,n,x,fvec,fjac,ldfjac,iflag,epsfcn,wa4) nfev = nfev + n if (iflag .lt. 0) go to 300 c c if requested, call fcn to enable printing of iterates. c if (nprint .le. 0) go to 40 iflag = 0 if (mod(iter-1,nprint) .eq. 0) call fcn(m,n,x,fvec,iflag) if (iflag .lt. 0) go to 300 40 continue c c compute the qr factorization of the jacobian. c call qrfac(m,n,fjac,ldfjac,.true.,ipvt,n,wa1,wa2,wa3) c c on the first iteration and if mode is 1, scale according c to the norms of the columns of the initial jacobian. c if (iter .ne. 1) go to 80 if (mode .eq. 2) go to 60 do 50 j = 1, n diag(j) = wa2(j) if (wa2(j) .eq. zero) diag(j) = one 50 continue 60 continue c c on the first iteration, calculate the norm of the scaled x c and initialize the step bound delta. c do 70 j = 1, n wa3(j) = diag(j)*x(j) 70 continue xnorm = enorm(n,wa3) delta = factor*xnorm if (delta .eq. zero) delta = factor 80 continue c c form (q transpose)*fvec and store the first n components in c qtf. c do 90 i = 1, m wa4(i) = fvec(i) 90 continue do 130 j = 1, n if (fjac(j,j) .eq. zero) go to 120 sum = zero do 100 i = j, m sum = sum + fjac(i,j)*wa4(i) 100 continue temp = -sum/fjac(j,j) do 110 i = j, m wa4(i) = wa4(i) + fjac(i,j)*temp 110 continue 120 continue fjac(j,j) = wa1(j) qtf(j) = wa4(j) 130 continue c c compute the norm of the scaled gradient. c gnorm = zero if (fnorm .eq. zero) go to 170 do 160 j = 1, n l = ipvt(j) if (wa2(l) .eq. zero) go to 150 sum = zero do 140 i = 1, j sum = sum + fjac(i,j)*(qtf(i)/fnorm) 140 continue gnorm = dmax1(gnorm,dabs(sum/wa2(l))) 150 continue 160 continue 170 continue c c test for convergence of the gradient norm. c if (gnorm .le. gtol) info = 4 if (info .ne. 0) go to 300 c c rescale if necessary. c if (mode .eq. 2) go to 190 do 180 j = 1, n diag(j) = dmax1(diag(j),wa2(j)) 180 continue 190 continue c c beginning of the inner loop. c 200 continue c c determine the levenberg-marquardt parameter. c call lmpar(n,fjac,ldfjac,ipvt,diag,qtf,delta,par,wa1,wa2, * wa3,wa4) c c store the direction p and x + p. calculate the norm of p. c do 210 j = 1, n wa1(j) = -wa1(j) wa2(j) = x(j) + wa1(j) wa3(j) = diag(j)*wa1(j) 210 continue pnorm = enorm(n,wa3) c c on the first iteration, adjust the initial step bound. c if (iter .eq. 1) delta = dmin1(delta,pnorm) c c evaluate the function at x + p and calculate its norm. c iflag = 1 call fcn(m,n,wa2,wa4,iflag) nfev = nfev + 1 if (iflag .lt. 0) go to 300 fnorm1 = enorm(m,wa4) c c compute the scaled actual reduction. c actred = -one if (p1*fnorm1 .lt. fnorm) actred = one - (fnorm1/fnorm)**2 c c compute the scaled predicted reduction and c the scaled directional derivative. c do 230 j = 1, n wa3(j) = zero l = ipvt(j) temp = wa1(l) do 220 i = 1, j wa3(i) = wa3(i) + fjac(i,j)*temp 220 continue 230 continue temp1 = enorm(n,wa3)/fnorm temp2 = (dsqrt(par)*pnorm)/fnorm prered = temp1**2 + temp2**2/p5 dirder = -(temp1**2 + temp2**2) c c compute the ratio of the actual to the predicted c reduction. c ratio = zero if (prered .ne. zero) ratio = actred/prered c c update the step bound. c if (ratio .gt. p25) go to 240 if (actred .ge. zero) temp = p5 if (actred .lt. zero) * temp = p5*dirder/(dirder + p5*actred) if (p1*fnorm1 .ge. fnorm .or. temp .lt. p1) temp = p1 delta = temp*dmin1(delta,pnorm/p1) par = par/temp go to 260 240 continue if (par .ne. zero .and. ratio .lt. p75) go to 250 delta = pnorm/p5 par = p5*par 250 continue 260 continue c c test for successful iteration. c if (ratio .lt. p0001) go to 290 c c successful iteration. update x, fvec, and their norms. c do 270 j = 1, n x(j) = wa2(j) wa2(j) = diag(j)*x(j) 270 continue do 280 i = 1, m fvec(i) = wa4(i) 280 continue xnorm = enorm(n,wa2) fnorm = fnorm1 iter = iter + 1 290 continue c c tests for convergence. c if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one) info = 1 if (delta .le. xtol*xnorm) info = 2 if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one .and. info .eq. 2) info = 3 if (info .ne. 0) go to 300 c c tests for termination and stringent tolerances. c if (nfev .ge. maxfev) info = 5 if (dabs(actred) .le. epsmch .and. prered .le. epsmch * .and. p5*ratio .le. one) info = 6 if (delta .le. epsmch*xnorm) info = 7 if (gnorm .le. epsmch) info = 8 if (info .ne. 0) go to 300 c c end of the inner loop. repeat if iteration unsuccessful. c if (ratio .lt. p0001) go to 200 c c end of the outer loop. c go to 30 300 continue c c termination, either normal or user imposed. c if (iflag .lt. 0) info = iflag iflag = 0 if (nprint .gt. 0) call fcn(m,n,x,fvec,iflag) return c c last card of subroutine lmdif. c end minpack-19961126/dpmpar.f0000644000175000017500000001323606246623144015750 0ustar sylvestresylvestre double precision function dpmpar(i) integer i c ********** c c Function dpmpar c c This function provides double precision machine parameters c when the appropriate set of data statements is activated (by c removing the c from column 1) and all other data statements are c rendered inactive. Most of the parameter values were obtained c from the corresponding Bell Laboratories Port Library function. c c The function statement is c c double precision function dpmpar(i) c c where c c i is an integer input variable set to 1, 2, or 3 which c selects the desired machine parameter. If the machine has c t base b digits and its smallest and largest exponents are c emin and emax, respectively, then these parameters are c c dpmpar(1) = b**(1 - t), the machine precision, c c dpmpar(2) = b**(emin - 1), the smallest magnitude, c c dpmpar(3) = b**emax*(1 - b**(-t)), the largest magnitude. c c Argonne National Laboratory. MINPACK Project. November 1996. c Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More' c c ********** integer mcheps(4) integer minmag(4) integer maxmag(4) double precision dmach(3) equivalence (dmach(1),mcheps(1)) equivalence (dmach(2),minmag(1)) equivalence (dmach(3),maxmag(1)) c c Machine constants for the IBM 360/370 series, c the Amdahl 470/V6, the ICL 2900, the Itel AS/6, c the Xerox Sigma 5/7/9 and the Sel systems 85/86. c c data mcheps(1),mcheps(2) / z34100000, z00000000 / c data minmag(1),minmag(2) / z00100000, z00000000 / c data maxmag(1),maxmag(2) / z7fffffff, zffffffff / c c Machine constants for the Honeywell 600/6000 series. c c data mcheps(1),mcheps(2) / o606400000000, o000000000000 / c data minmag(1),minmag(2) / o402400000000, o000000000000 / c data maxmag(1),maxmag(2) / o376777777777, o777777777777 / c c Machine constants for the CDC 6000/7000 series. c c data mcheps(1) / 15614000000000000000b / c data mcheps(2) / 15010000000000000000b / c c data minmag(1) / 00604000000000000000b / c data minmag(2) / 00000000000000000000b / c c data maxmag(1) / 37767777777777777777b / c data maxmag(2) / 37167777777777777777b / c c Machine constants for the PDP-10 (KA processor). c c data mcheps(1),mcheps(2) / "114400000000, "000000000000 / c data minmag(1),minmag(2) / "033400000000, "000000000000 / c data maxmag(1),maxmag(2) / "377777777777, "344777777777 / c c Machine constants for the PDP-10 (KI processor). c c data mcheps(1),mcheps(2) / "104400000000, "000000000000 / c data minmag(1),minmag(2) / "000400000000, "000000000000 / c data maxmag(1),maxmag(2) / "377777777777, "377777777777 / c c Machine constants for the PDP-11. c c data mcheps(1),mcheps(2) / 9472, 0 / c data mcheps(3),mcheps(4) / 0, 0 / c c data minmag(1),minmag(2) / 128, 0 / c data minmag(3),minmag(4) / 0, 0 / c c data maxmag(1),maxmag(2) / 32767, -1 / c data maxmag(3),maxmag(4) / -1, -1 / c c Machine constants for the Burroughs 6700/7700 systems. c c data mcheps(1) / o1451000000000000 / c data mcheps(2) / o0000000000000000 / c c data minmag(1) / o1771000000000000 / c data minmag(2) / o7770000000000000 / c c data maxmag(1) / o0777777777777777 / c data maxmag(2) / o7777777777777777 / c c Machine constants for the Burroughs 5700 system. c c data mcheps(1) / o1451000000000000 / c data mcheps(2) / o0000000000000000 / c c data minmag(1) / o1771000000000000 / c data minmag(2) / o0000000000000000 / c c data maxmag(1) / o0777777777777777 / c data maxmag(2) / o0007777777777777 / c c Machine constants for the Burroughs 1700 system. c c data mcheps(1) / zcc6800000 / c data mcheps(2) / z000000000 / c c data minmag(1) / zc00800000 / c data minmag(2) / z000000000 / c c data maxmag(1) / zdffffffff / c data maxmag(2) / zfffffffff / c c Machine constants for the Univac 1100 series. c c data mcheps(1),mcheps(2) / o170640000000, o000000000000 / c data minmag(1),minmag(2) / o000040000000, o000000000000 / c data maxmag(1),maxmag(2) / o377777777777, o777777777777 / c c Machine constants for the Data General Eclipse S/200. c c Note - it may be appropriate to include the following card - c static dmach(3) c c data minmag/20k,3*0/,maxmag/77777k,3*177777k/ c data mcheps/32020k,3*0/ c c Machine constants for the Harris 220. c c data mcheps(1),mcheps(2) / '20000000, '00000334 / c data minmag(1),minmag(2) / '20000000, '00000201 / c data maxmag(1),maxmag(2) / '37777777, '37777577 / c c Machine constants for the Cray-1. c c data mcheps(1) / 0376424000000000000000b / c data mcheps(2) / 0000000000000000000000b / c c data minmag(1) / 0200034000000000000000b / c data minmag(2) / 0000000000000000000000b / c c data maxmag(1) / 0577777777777777777777b / c data maxmag(2) / 0000007777777777777776b / c c Machine constants for the Prime 400. c c data mcheps(1),mcheps(2) / :10000000000, :00000000123 / c data minmag(1),minmag(2) / :10000000000, :00000100000 / c data maxmag(1),maxmag(2) / :17777777777, :37777677776 / c c Machine constants for the VAX-11. c c data mcheps(1),mcheps(2) / 9472, 0 / c data minmag(1),minmag(2) / 128, 0 / c data maxmag(1),maxmag(2) / -32769, -1 / c c Machine constants for IEEE machines. c data dmach(1) /2.22044604926d-16/ data dmach(2) /2.22507385852d-308/ data dmach(3) /1.79769313485d+308/ c dpmpar = dmach(i) return c c Last card of function dpmpar. c end minpack-19961126/qrfac.f0000644000175000017500000001245103226632013015545 0ustar sylvestresylvestre subroutine qrfac(m,n,a,lda,pivot,ipvt,lipvt,rdiag,acnorm,wa) integer m,n,lda,lipvt integer ipvt(lipvt) logical pivot double precision a(lda,n),rdiag(n),acnorm(n),wa(n) c ********** c c subroutine qrfac c c this subroutine uses householder transformations with column c pivoting (optional) to compute a qr factorization of the c m by n matrix a. that is, qrfac determines an orthogonal c matrix q, a permutation matrix p, and an upper trapezoidal c matrix r with diagonal elements of nonincreasing magnitude, c such that a*p = q*r. the householder transformation for c column k, k = 1,2,...,min(m,n), is of the form c c t c i - (1/u(k))*u*u c c where u has zeros in the first k-1 positions. the form of c this transformation and the method of pivoting first c appeared in the corresponding linpack subroutine. c c the subroutine statement is c c subroutine qrfac(m,n,a,lda,pivot,ipvt,lipvt,rdiag,acnorm,wa) c c where c c m is a positive integer input variable set to the number c of rows of a. c c n is a positive integer input variable set to the number c of columns of a. c c a is an m by n array. on input a contains the matrix for c which the qr factorization is to be computed. on output c the strict upper trapezoidal part of a contains the strict c upper trapezoidal part of r, and the lower trapezoidal c part of a contains a factored form of q (the non-trivial c elements of the u vectors described above). c c lda is a positive integer input variable not less than m c which specifies the leading dimension of the array a. c c pivot is a logical input variable. if pivot is set true, c then column pivoting is enforced. if pivot is set false, c then no column pivoting is done. c c ipvt is an integer output array of length lipvt. ipvt c defines the permutation matrix p such that a*p = q*r. c column j of p is column ipvt(j) of the identity matrix. c if pivot is false, ipvt is not referenced. c c lipvt is a positive integer input variable. if pivot is false, c then lipvt may be as small as 1. if pivot is true, then c lipvt must be at least n. c c rdiag is an output array of length n which contains the c diagonal elements of r. c c acnorm is an output array of length n which contains the c norms of the corresponding columns of the input matrix a. c if this information is not needed, then acnorm can coincide c with rdiag. c c wa is a work array of length n. if pivot is false, then wa c can coincide with rdiag. c c subprograms called c c minpack-supplied ... dpmpar,enorm c c fortran-supplied ... dmax1,dsqrt,min0 c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j,jp1,k,kmax,minmn double precision ajnorm,epsmch,one,p05,sum,temp,zero double precision dpmpar,enorm data one,p05,zero /1.0d0,5.0d-2,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c c compute the initial column norms and initialize several arrays. c do 10 j = 1, n acnorm(j) = enorm(m,a(1,j)) rdiag(j) = acnorm(j) wa(j) = rdiag(j) if (pivot) ipvt(j) = j 10 continue c c reduce a to r with householder transformations. c minmn = min0(m,n) do 110 j = 1, minmn if (.not.pivot) go to 40 c c bring the column of largest norm into the pivot position. c kmax = j do 20 k = j, n if (rdiag(k) .gt. rdiag(kmax)) kmax = k 20 continue if (kmax .eq. j) go to 40 do 30 i = 1, m temp = a(i,j) a(i,j) = a(i,kmax) a(i,kmax) = temp 30 continue rdiag(kmax) = rdiag(j) wa(kmax) = wa(j) k = ipvt(j) ipvt(j) = ipvt(kmax) ipvt(kmax) = k 40 continue c c compute the householder transformation to reduce the c j-th column of a to a multiple of the j-th unit vector. c ajnorm = enorm(m-j+1,a(j,j)) if (ajnorm .eq. zero) go to 100 if (a(j,j) .lt. zero) ajnorm = -ajnorm do 50 i = j, m a(i,j) = a(i,j)/ajnorm 50 continue a(j,j) = a(j,j) + one c c apply the transformation to the remaining columns c and update the norms. c jp1 = j + 1 if (n .lt. jp1) go to 100 do 90 k = jp1, n sum = zero do 60 i = j, m sum = sum + a(i,j)*a(i,k) 60 continue temp = sum/a(j,j) do 70 i = j, m a(i,k) = a(i,k) - temp*a(i,j) 70 continue if (.not.pivot .or. rdiag(k) .eq. zero) go to 80 temp = a(j,k)/rdiag(k) rdiag(k) = rdiag(k)*dsqrt(dmax1(zero,one-temp**2)) if (p05*(rdiag(k)/wa(k))**2 .gt. epsmch) go to 80 rdiag(k) = enorm(m-j,a(jp1,k)) wa(k) = rdiag(k) 80 continue 90 continue 100 continue rdiag(j) = -ajnorm 110 continue return c c last card of subroutine qrfac. c end minpack-19961126/config.sub0000644000175000017500000007746011616327304016303 0ustar sylvestresylvestre#! /bin/sh # Configuration validation subroutine script. # Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, # 2000, 2001, 2002, 2003, 2004, 2005, 2006 Free Software Foundation, # Inc. timestamp='2006-09-20' # This file is (in principle) common to ALL GNU software. # The presence of a machine in this file suggests that SOME GNU software # can handle that machine. 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See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street - Fifth Floor, Boston, MA # 02110-1301, USA. # # As a special exception to the GNU General Public License, if you # distribute this file as part of a program that contains a # configuration script generated by Autoconf, you may include it under # the same distribution terms that you use for the rest of that program. # Please send patches to . Submit a context # diff and a properly formatted ChangeLog entry. # # Configuration subroutine to validate and canonicalize a configuration type. # Supply the specified configuration type as an argument. # If it is invalid, we print an error message on stderr and exit with code 1. # Otherwise, we print the canonical config type on stdout and succeed. # This file is supposed to be the same for all GNU packages # and recognize all the CPU types, system types and aliases # that are meaningful with *any* GNU software. # Each package is responsible for reporting which valid configurations # it does not support. The user should be able to distinguish # a failure to support a valid configuration from a meaningless # configuration. # The goal of this file is to map all the various variations of a given # machine specification into a single specification in the form: # CPU_TYPE-MANUFACTURER-OPERATING_SYSTEM # or in some cases, the newer four-part form: # CPU_TYPE-MANUFACTURER-KERNEL-OPERATING_SYSTEM # It is wrong to echo any other type of specification. me=`echo "$0" | sed -e 's,.*/,,'` usage="\ Usage: $0 [OPTION] CPU-MFR-OPSYS $0 [OPTION] ALIAS Canonicalize a configuration name. Operation modes: -h, --help print this help, then exit -t, --time-stamp print date of last modification, then exit -v, --version print version number, then exit Report bugs and patches to ." version="\ GNU config.sub ($timestamp) Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE." help=" Try \`$me --help' for more information." # Parse command line while test $# -gt 0 ; do case $1 in --time-stamp | --time* | -t ) echo "$timestamp" ; exit ;; --version | -v ) echo "$version" ; exit ;; --help | --h* | -h ) echo "$usage"; exit ;; -- ) # Stop option processing shift; break ;; - ) # Use stdin as input. break ;; -* ) echo "$me: invalid option $1$help" exit 1 ;; *local*) # First pass through any local machine types. echo $1 exit ;; * ) break ;; esac done case $# in 0) echo "$me: missing argument$help" >&2 exit 1;; 1) ;; *) echo "$me: too many arguments$help" >&2 exit 1;; esac # Separate what the user gave into CPU-COMPANY and OS or KERNEL-OS (if any). # Here we must recognize all the valid KERNEL-OS combinations. maybe_os=`echo $1 | sed 's/^\(.*\)-\([^-]*-[^-]*\)$/\2/'` case $maybe_os in nto-qnx* | linux-gnu* | linux-dietlibc | linux-newlib* | linux-uclibc* | \ uclinux-uclibc* | uclinux-gnu* | kfreebsd*-gnu* | knetbsd*-gnu* | netbsd*-gnu* | \ storm-chaos* | os2-emx* | rtmk-nova*) os=-$maybe_os basic_machine=`echo $1 | sed 's/^\(.*\)-\([^-]*-[^-]*\)$/\1/'` ;; *) basic_machine=`echo $1 | sed 's/-[^-]*$//'` if [ $basic_machine != $1 ] then os=`echo $1 | sed 's/.*-/-/'` else os=; fi ;; esac ### Let's recognize common machines as not being operating systems so ### that things like config.sub decstation-3100 work. We also ### recognize some manufacturers as not being operating systems, so we ### can provide default operating systems below. case $os in -sun*os*) # Prevent following clause from handling this invalid input. ;; -dec* | -mips* | -sequent* | -encore* | -pc532* | -sgi* | -sony* | \ -att* | -7300* | -3300* | -delta* | -motorola* | -sun[234]* | \ -unicom* | -ibm* | -next | -hp | -isi* | -apollo | -altos* | \ -convergent* | -ncr* | -news | -32* | -3600* | -3100* | -hitachi* |\ -c[123]* | -convex* | -sun | -crds | -omron* | -dg | -ultra | -tti* | \ -harris | -dolphin | -highlevel | -gould | -cbm | -ns | -masscomp | \ -apple | -axis | -knuth | -cray) os= basic_machine=$1 ;; -sim | -cisco | -oki | -wec | -winbond) os= basic_machine=$1 ;; -scout) ;; -wrs) os=-vxworks basic_machine=$1 ;; -chorusos*) os=-chorusos basic_machine=$1 ;; -chorusrdb) os=-chorusrdb basic_machine=$1 ;; -hiux*) os=-hiuxwe2 ;; -sco6) os=-sco5v6 basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco5) os=-sco3.2v5 basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco4) os=-sco3.2v4 basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco3.2.[4-9]*) os=`echo $os | sed -e 's/sco3.2./sco3.2v/'` basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco3.2v[4-9]*) # Don't forget version if it is 3.2v4 or newer. basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco5v6*) # Don't forget version if it is 3.2v4 or newer. basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -sco*) os=-sco3.2v2 basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -udk*) basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -isc) os=-isc2.2 basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -clix*) basic_machine=clipper-intergraph ;; -isc*) basic_machine=`echo $1 | sed -e 's/86-.*/86-pc/'` ;; -lynx*) os=-lynxos ;; -ptx*) basic_machine=`echo $1 | sed -e 's/86-.*/86-sequent/'` ;; -windowsnt*) os=`echo $os | sed -e 's/windowsnt/winnt/'` ;; -psos*) os=-psos ;; -mint | -mint[0-9]*) basic_machine=m68k-atari os=-mint ;; esac # Decode aliases for certain CPU-COMPANY combinations. case $basic_machine in # Recognize the basic CPU types without company name. # Some are omitted here because they have special meanings below. 1750a | 580 \ | a29k \ | alpha | alphaev[4-8] | alphaev56 | alphaev6[78] | alphapca5[67] \ | alpha64 | alpha64ev[4-8] | alpha64ev56 | alpha64ev6[78] | alpha64pca5[67] \ | am33_2.0 \ | arc | arm | arm[bl]e | arme[lb] | armv[2345] | armv[345][lb] | avr | avr32 \ | bfin \ | c4x | clipper \ | d10v | d30v | dlx | dsp16xx \ | fr30 | frv \ | h8300 | h8500 | hppa | hppa1.[01] | hppa2.0 | hppa2.0[nw] | hppa64 \ | i370 | i860 | i960 | ia64 \ | ip2k | iq2000 \ | m32c | m32r | m32rle | m68000 | m68k | m88k \ | maxq | mb | microblaze | mcore \ | mips | mipsbe | mipseb | mipsel | mipsle \ | mips16 \ | mips64 | mips64el \ | mips64vr | mips64vrel \ | mips64orion | mips64orionel \ | mips64vr4100 | mips64vr4100el \ | mips64vr4300 | mips64vr4300el \ | mips64vr5000 | mips64vr5000el \ | mips64vr5900 | mips64vr5900el \ | mipsisa32 | mipsisa32el \ | mipsisa32r2 | mipsisa32r2el \ | mipsisa64 | mipsisa64el \ | mipsisa64r2 | mipsisa64r2el \ | mipsisa64sb1 | mipsisa64sb1el \ | mipsisa64sr71k | mipsisa64sr71kel \ | mipstx39 | mipstx39el \ | mn10200 | mn10300 \ | mt \ | msp430 \ | nios | nios2 \ | ns16k | ns32k \ | or32 \ | pdp10 | pdp11 | pj | pjl \ | powerpc | powerpc64 | powerpc64le | powerpcle | ppcbe \ | pyramid \ | score \ | sh | sh[1234] | sh[24]a | sh[23]e | sh[34]eb | sheb | shbe | shle | sh[1234]le | sh3ele \ | sh64 | sh64le \ | sparc | sparc64 | sparc64b | sparc64v | sparc86x | sparclet | sparclite \ | sparcv8 | sparcv9 | sparcv9b | sparcv9v \ | spu | strongarm \ | tahoe | thumb | tic4x | tic80 | tron \ | v850 | v850e \ | we32k \ | x86 | xc16x | xscale | xscalee[bl] | xstormy16 | xtensa \ | z8k) basic_machine=$basic_machine-unknown ;; m6811 | m68hc11 | m6812 | m68hc12) # Motorola 68HC11/12. basic_machine=$basic_machine-unknown os=-none ;; m88110 | m680[12346]0 | m683?2 | m68360 | m5200 | v70 | w65 | z8k) ;; ms1) basic_machine=mt-unknown ;; # We use `pc' rather than `unknown' # because (1) that's what they normally are, and # (2) the word "unknown" tends to confuse beginning users. i*86 | x86_64) basic_machine=$basic_machine-pc ;; # Object if more than one company name word. *-*-*) echo Invalid configuration \`$1\': machine \`$basic_machine\' not recognized 1>&2 exit 1 ;; # Recognize the basic CPU types with company name. 580-* \ | a29k-* \ | alpha-* | alphaev[4-8]-* | alphaev56-* | alphaev6[78]-* \ | alpha64-* | alpha64ev[4-8]-* | alpha64ev56-* | alpha64ev6[78]-* \ | alphapca5[67]-* | alpha64pca5[67]-* | arc-* \ | arm-* | armbe-* | armle-* | armeb-* | armv*-* \ | avr-* | avr32-* \ | bfin-* | bs2000-* \ | c[123]* | c30-* | [cjt]90-* | c4x-* | c54x-* | c55x-* | c6x-* \ | clipper-* | craynv-* | cydra-* \ | d10v-* | d30v-* | dlx-* \ | elxsi-* \ | f30[01]-* | f700-* | fr30-* | frv-* | fx80-* \ | h8300-* | h8500-* \ | hppa-* | hppa1.[01]-* | hppa2.0-* | hppa2.0[nw]-* | hppa64-* \ | i*86-* | i860-* | i960-* | ia64-* \ | ip2k-* | iq2000-* \ | m32c-* | m32r-* | m32rle-* \ | m68000-* | m680[012346]0-* | m68360-* | m683?2-* | m68k-* \ | m88110-* | m88k-* | maxq-* | mcore-* \ | mips-* | mipsbe-* | mipseb-* | mipsel-* | mipsle-* \ | mips16-* \ | mips64-* | mips64el-* \ | mips64vr-* | mips64vrel-* \ | mips64orion-* | mips64orionel-* \ | mips64vr4100-* | mips64vr4100el-* \ | mips64vr4300-* | mips64vr4300el-* \ | mips64vr5000-* | mips64vr5000el-* \ | mips64vr5900-* | mips64vr5900el-* \ | mipsisa32-* | mipsisa32el-* \ | mipsisa32r2-* | mipsisa32r2el-* \ | mipsisa64-* | mipsisa64el-* \ | mipsisa64r2-* | mipsisa64r2el-* \ | mipsisa64sb1-* | mipsisa64sb1el-* \ | mipsisa64sr71k-* | mipsisa64sr71kel-* \ | mipstx39-* | mipstx39el-* \ | mmix-* \ | mt-* \ | msp430-* \ | nios-* | nios2-* \ | none-* | np1-* | ns16k-* | ns32k-* \ | orion-* \ | pdp10-* | pdp11-* | pj-* | pjl-* | pn-* | power-* \ | powerpc-* | powerpc64-* | powerpc64le-* | powerpcle-* | ppcbe-* \ | pyramid-* \ | romp-* | rs6000-* \ | sh-* | sh[1234]-* | sh[24]a-* | sh[23]e-* | sh[34]eb-* | sheb-* | shbe-* \ | shle-* | sh[1234]le-* | sh3ele-* | sh64-* | sh64le-* \ | sparc-* | sparc64-* | sparc64b-* | sparc64v-* | sparc86x-* | sparclet-* \ | sparclite-* \ | sparcv8-* | sparcv9-* | sparcv9b-* | sparcv9v-* | strongarm-* | sv1-* | sx?-* \ | tahoe-* | thumb-* \ | tic30-* | tic4x-* | tic54x-* | tic55x-* | tic6x-* | tic80-* \ | tron-* \ | v850-* | v850e-* | vax-* \ | we32k-* \ | x86-* | x86_64-* | xc16x-* | xps100-* | xscale-* | xscalee[bl]-* \ | xstormy16-* | xtensa-* \ | ymp-* \ | z8k-*) ;; # Recognize the various machine names and aliases which stand # for a CPU type and a company and sometimes even an OS. 386bsd) basic_machine=i386-unknown os=-bsd ;; 3b1 | 7300 | 7300-att | att-7300 | pc7300 | safari | unixpc) basic_machine=m68000-att ;; 3b*) basic_machine=we32k-att ;; a29khif) basic_machine=a29k-amd os=-udi ;; abacus) basic_machine=abacus-unknown ;; adobe68k) basic_machine=m68010-adobe os=-scout ;; alliant | fx80) basic_machine=fx80-alliant ;; altos | altos3068) basic_machine=m68k-altos ;; am29k) basic_machine=a29k-none os=-bsd ;; amd64) basic_machine=x86_64-pc ;; amd64-*) basic_machine=x86_64-`echo $basic_machine | sed 's/^[^-]*-//'` ;; amdahl) basic_machine=580-amdahl os=-sysv ;; amiga | amiga-*) basic_machine=m68k-unknown ;; amigaos | amigados) basic_machine=m68k-unknown os=-amigaos ;; amigaunix | amix) basic_machine=m68k-unknown os=-sysv4 ;; apollo68) basic_machine=m68k-apollo os=-sysv ;; apollo68bsd) basic_machine=m68k-apollo os=-bsd ;; aux) basic_machine=m68k-apple os=-aux ;; balance) basic_machine=ns32k-sequent os=-dynix ;; c90) basic_machine=c90-cray os=-unicos ;; convex-c1) basic_machine=c1-convex os=-bsd ;; convex-c2) basic_machine=c2-convex os=-bsd ;; convex-c32) basic_machine=c32-convex os=-bsd ;; convex-c34) basic_machine=c34-convex os=-bsd ;; convex-c38) basic_machine=c38-convex os=-bsd ;; cray | j90) basic_machine=j90-cray os=-unicos ;; craynv) basic_machine=craynv-cray os=-unicosmp ;; cr16c) basic_machine=cr16c-unknown os=-elf ;; crds | unos) basic_machine=m68k-crds ;; crisv32 | crisv32-* | etraxfs*) basic_machine=crisv32-axis ;; cris | cris-* | etrax*) basic_machine=cris-axis ;; crx) basic_machine=crx-unknown os=-elf ;; da30 | da30-*) basic_machine=m68k-da30 ;; decstation | decstation-3100 | pmax | pmax-* | pmin | dec3100 | decstatn) basic_machine=mips-dec ;; decsystem10* | dec10*) basic_machine=pdp10-dec os=-tops10 ;; decsystem20* | dec20*) basic_machine=pdp10-dec os=-tops20 ;; delta | 3300 | motorola-3300 | motorola-delta \ | 3300-motorola | delta-motorola) basic_machine=m68k-motorola ;; delta88) basic_machine=m88k-motorola os=-sysv3 ;; djgpp) basic_machine=i586-pc os=-msdosdjgpp ;; dpx20 | dpx20-*) basic_machine=rs6000-bull os=-bosx ;; dpx2* | dpx2*-bull) basic_machine=m68k-bull os=-sysv3 ;; ebmon29k) basic_machine=a29k-amd os=-ebmon ;; elxsi) basic_machine=elxsi-elxsi os=-bsd ;; encore | umax | mmax) basic_machine=ns32k-encore ;; es1800 | OSE68k | ose68k | ose | OSE) basic_machine=m68k-ericsson os=-ose ;; fx2800) basic_machine=i860-alliant ;; genix) basic_machine=ns32k-ns ;; gmicro) basic_machine=tron-gmicro os=-sysv ;; go32) basic_machine=i386-pc os=-go32 ;; h3050r* | hiux*) basic_machine=hppa1.1-hitachi os=-hiuxwe2 ;; h8300hms) basic_machine=h8300-hitachi os=-hms ;; h8300xray) basic_machine=h8300-hitachi os=-xray ;; h8500hms) basic_machine=h8500-hitachi os=-hms ;; harris) basic_machine=m88k-harris os=-sysv3 ;; hp300-*) basic_machine=m68k-hp ;; hp300bsd) basic_machine=m68k-hp os=-bsd ;; hp300hpux) basic_machine=m68k-hp os=-hpux ;; hp3k9[0-9][0-9] | hp9[0-9][0-9]) basic_machine=hppa1.0-hp ;; hp9k2[0-9][0-9] | hp9k31[0-9]) basic_machine=m68000-hp ;; hp9k3[2-9][0-9]) basic_machine=m68k-hp ;; hp9k6[0-9][0-9] | hp6[0-9][0-9]) basic_machine=hppa1.0-hp ;; hp9k7[0-79][0-9] | hp7[0-79][0-9]) basic_machine=hppa1.1-hp ;; hp9k78[0-9] | hp78[0-9]) # FIXME: really hppa2.0-hp basic_machine=hppa1.1-hp ;; hp9k8[67]1 | hp8[67]1 | hp9k80[24] | hp80[24] | hp9k8[78]9 | hp8[78]9 | hp9k893 | hp893) # FIXME: really hppa2.0-hp basic_machine=hppa1.1-hp ;; hp9k8[0-9][13679] | hp8[0-9][13679]) basic_machine=hppa1.1-hp ;; hp9k8[0-9][0-9] | hp8[0-9][0-9]) basic_machine=hppa1.0-hp ;; hppa-next) os=-nextstep3 ;; hppaosf) basic_machine=hppa1.1-hp os=-osf ;; hppro) basic_machine=hppa1.1-hp os=-proelf ;; i370-ibm* | ibm*) basic_machine=i370-ibm ;; # I'm not sure what "Sysv32" means. Should this be sysv3.2? i*86v32) basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'` os=-sysv32 ;; i*86v4*) basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'` os=-sysv4 ;; i*86v) basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'` os=-sysv ;; i*86sol2) basic_machine=`echo $1 | sed -e 's/86.*/86-pc/'` os=-solaris2 ;; i386mach) basic_machine=i386-mach os=-mach ;; i386-vsta | vsta) basic_machine=i386-unknown os=-vsta ;; iris | iris4d) basic_machine=mips-sgi case $os in -irix*) ;; *) os=-irix4 ;; esac ;; isi68 | isi) basic_machine=m68k-isi os=-sysv ;; m88k-omron*) basic_machine=m88k-omron ;; magnum | m3230) basic_machine=mips-mips os=-sysv ;; merlin) basic_machine=ns32k-utek os=-sysv ;; mingw32) basic_machine=i386-pc os=-mingw32 ;; miniframe) basic_machine=m68000-convergent ;; *mint | -mint[0-9]* | *MiNT | *MiNT[0-9]*) basic_machine=m68k-atari os=-mint ;; mips3*-*) basic_machine=`echo $basic_machine | sed -e 's/mips3/mips64/'` ;; mips3*) basic_machine=`echo $basic_machine | sed -e 's/mips3/mips64/'`-unknown ;; monitor) basic_machine=m68k-rom68k os=-coff ;; morphos) basic_machine=powerpc-unknown os=-morphos ;; msdos) basic_machine=i386-pc os=-msdos ;; ms1-*) basic_machine=`echo $basic_machine | sed -e 's/ms1-/mt-/'` ;; mvs) basic_machine=i370-ibm os=-mvs ;; ncr3000) basic_machine=i486-ncr os=-sysv4 ;; netbsd386) basic_machine=i386-unknown os=-netbsd ;; netwinder) basic_machine=armv4l-rebel os=-linux ;; news | news700 | news800 | news900) basic_machine=m68k-sony os=-newsos ;; news1000) basic_machine=m68030-sony os=-newsos ;; news-3600 | risc-news) basic_machine=mips-sony os=-newsos ;; necv70) basic_machine=v70-nec os=-sysv ;; next | m*-next ) basic_machine=m68k-next case $os in -nextstep* ) ;; -ns2*) os=-nextstep2 ;; *) os=-nextstep3 ;; esac ;; nh3000) basic_machine=m68k-harris os=-cxux ;; nh[45]000) basic_machine=m88k-harris os=-cxux ;; nindy960) basic_machine=i960-intel os=-nindy ;; mon960) basic_machine=i960-intel os=-mon960 ;; nonstopux) basic_machine=mips-compaq os=-nonstopux ;; np1) basic_machine=np1-gould ;; nsr-tandem) basic_machine=nsr-tandem ;; op50n-* | op60c-*) basic_machine=hppa1.1-oki os=-proelf ;; openrisc | openrisc-*) basic_machine=or32-unknown ;; os400) basic_machine=powerpc-ibm os=-os400 ;; OSE68000 | ose68000) basic_machine=m68000-ericsson os=-ose ;; os68k) basic_machine=m68k-none os=-os68k ;; pa-hitachi) basic_machine=hppa1.1-hitachi os=-hiuxwe2 ;; paragon) basic_machine=i860-intel os=-osf ;; pbd) basic_machine=sparc-tti ;; pbb) basic_machine=m68k-tti ;; pc532 | pc532-*) basic_machine=ns32k-pc532 ;; pc98) basic_machine=i386-pc ;; pc98-*) basic_machine=i386-`echo $basic_machine | sed 's/^[^-]*-//'` ;; pentium | p5 | k5 | k6 | nexgen | viac3) basic_machine=i586-pc ;; pentiumpro | p6 | 6x86 | athlon | athlon_*) basic_machine=i686-pc ;; pentiumii | pentium2 | pentiumiii | pentium3) basic_machine=i686-pc ;; pentium4) basic_machine=i786-pc ;; pentium-* | p5-* | k5-* | k6-* | nexgen-* | viac3-*) basic_machine=i586-`echo $basic_machine | sed 's/^[^-]*-//'` ;; pentiumpro-* | p6-* | 6x86-* | athlon-*) basic_machine=i686-`echo $basic_machine | sed 's/^[^-]*-//'` ;; pentiumii-* | pentium2-* | pentiumiii-* | pentium3-*) basic_machine=i686-`echo $basic_machine | sed 's/^[^-]*-//'` ;; pentium4-*) basic_machine=i786-`echo $basic_machine | sed 's/^[^-]*-//'` ;; pn) basic_machine=pn-gould ;; power) basic_machine=power-ibm ;; ppc) basic_machine=powerpc-unknown ;; ppc-*) basic_machine=powerpc-`echo $basic_machine | sed 's/^[^-]*-//'` ;; ppcle | powerpclittle | ppc-le | powerpc-little) basic_machine=powerpcle-unknown ;; ppcle-* | powerpclittle-*) basic_machine=powerpcle-`echo $basic_machine | sed 's/^[^-]*-//'` ;; ppc64) basic_machine=powerpc64-unknown ;; ppc64-*) basic_machine=powerpc64-`echo $basic_machine | sed 's/^[^-]*-//'` ;; ppc64le | powerpc64little | ppc64-le | powerpc64-little) basic_machine=powerpc64le-unknown ;; ppc64le-* | powerpc64little-*) basic_machine=powerpc64le-`echo $basic_machine | sed 's/^[^-]*-//'` ;; ps2) basic_machine=i386-ibm ;; pw32) basic_machine=i586-unknown os=-pw32 ;; rdos) basic_machine=i386-pc os=-rdos ;; rom68k) basic_machine=m68k-rom68k os=-coff ;; rm[46]00) basic_machine=mips-siemens ;; rtpc | rtpc-*) basic_machine=romp-ibm ;; s390 | s390-*) basic_machine=s390-ibm ;; s390x | s390x-*) basic_machine=s390x-ibm ;; sa29200) basic_machine=a29k-amd os=-udi ;; sb1) basic_machine=mipsisa64sb1-unknown ;; sb1el) basic_machine=mipsisa64sb1el-unknown ;; sde) basic_machine=mipsisa32-sde os=-elf ;; sei) basic_machine=mips-sei os=-seiux ;; sequent) basic_machine=i386-sequent ;; sh) basic_machine=sh-hitachi os=-hms ;; sh64) basic_machine=sh64-unknown ;; sparclite-wrs | simso-wrs) basic_machine=sparclite-wrs os=-vxworks ;; sps7) basic_machine=m68k-bull os=-sysv2 ;; spur) basic_machine=spur-unknown ;; st2000) basic_machine=m68k-tandem ;; stratus) basic_machine=i860-stratus os=-sysv4 ;; sun2) basic_machine=m68000-sun ;; sun2os3) basic_machine=m68000-sun os=-sunos3 ;; sun2os4) basic_machine=m68000-sun os=-sunos4 ;; sun3os3) basic_machine=m68k-sun os=-sunos3 ;; sun3os4) basic_machine=m68k-sun os=-sunos4 ;; sun4os3) basic_machine=sparc-sun os=-sunos3 ;; sun4os4) basic_machine=sparc-sun os=-sunos4 ;; sun4sol2) basic_machine=sparc-sun os=-solaris2 ;; sun3 | sun3-*) basic_machine=m68k-sun ;; sun4) basic_machine=sparc-sun ;; sun386 | sun386i | roadrunner) basic_machine=i386-sun ;; sv1) basic_machine=sv1-cray os=-unicos ;; symmetry) basic_machine=i386-sequent os=-dynix ;; t3e) basic_machine=alphaev5-cray os=-unicos ;; t90) basic_machine=t90-cray os=-unicos ;; tic54x | c54x*) basic_machine=tic54x-unknown os=-coff ;; tic55x | c55x*) basic_machine=tic55x-unknown os=-coff ;; tic6x | c6x*) basic_machine=tic6x-unknown os=-coff ;; tx39) basic_machine=mipstx39-unknown ;; tx39el) basic_machine=mipstx39el-unknown ;; toad1) basic_machine=pdp10-xkl os=-tops20 ;; tower | tower-32) basic_machine=m68k-ncr ;; tpf) basic_machine=s390x-ibm os=-tpf ;; udi29k) basic_machine=a29k-amd os=-udi ;; ultra3) basic_machine=a29k-nyu os=-sym1 ;; v810 | necv810) basic_machine=v810-nec os=-none ;; vaxv) basic_machine=vax-dec os=-sysv ;; vms) basic_machine=vax-dec os=-vms ;; 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We pick the logical manufacturer. vendor=unknown case $basic_machine in *-unknown) case $os in -riscix*) vendor=acorn ;; -sunos*) vendor=sun ;; -aix*) vendor=ibm ;; -beos*) vendor=be ;; -hpux*) vendor=hp ;; -mpeix*) vendor=hp ;; -hiux*) vendor=hitachi ;; -unos*) vendor=crds ;; -dgux*) vendor=dg ;; -luna*) vendor=omron ;; -genix*) vendor=ns ;; -mvs* | -opened*) vendor=ibm ;; -os400*) vendor=ibm ;; -ptx*) vendor=sequent ;; -tpf*) vendor=ibm ;; -vxsim* | -vxworks* | -windiss*) vendor=wrs ;; -aux*) vendor=apple ;; -hms*) vendor=hitachi ;; -mpw* | -macos*) vendor=apple ;; -*mint | -mint[0-9]* | -*MiNT | -MiNT[0-9]*) vendor=atari ;; -vos*) vendor=stratus ;; esac basic_machine=`echo $basic_machine | sed "s/unknown/$vendor/"` ;; esac echo $basic_machine$os exit # Local variables: # eval: (add-hook 'write-file-hooks 'time-stamp) # time-stamp-start: "timestamp='" # time-stamp-format: "%:y-%02m-%02d" # time-stamp-end: "'" # End: minpack-19961126/hybrj1.f0000644000175000017500000001035003226632006015646 0ustar sylvestresylvestre subroutine hybrj1(fcn,n,x,fvec,fjac,ldfjac,tol,info,wa,lwa) integer n,ldfjac,info,lwa double precision tol double precision x(n),fvec(n),fjac(ldfjac,n),wa(lwa) external fcn c ********** c c subroutine hybrj1 c c the purpose of hybrj1 is to find a zero of a system of c n nonlinear functions in n variables by a modification c of the powell hybrid method. this is done by using the c more general nonlinear equation solver hybrj. the user c must provide a subroutine which calculates the functions c and the jacobian. c c the subroutine statement is c c subroutine hybrj1(fcn,n,x,fvec,fjac,ldfjac,tol,info,wa,lwa) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the jacobian. fcn must c be declared in an external statement in the user c calling program, and should be written as follows. c c subroutine fcn(n,x,fvec,fjac,ldfjac,iflag) c integer n,ldfjac,iflag c double precision x(n),fvec(n),fjac(ldfjac,n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. do not alter fjac. c if iflag = 2 calculate the jacobian at x and c return this matrix in fjac. do not alter 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 hybrj1. c in this case set iflag to a negative integer. c c n is a positive integer input variable set to the number c of functions and variables. 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 n which contains c the functions evaluated at the output x. c c fjac is an output n by n array which contains the c orthogonal matrix q produced by the qr factorization c of the final approximate jacobian. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. c c tol is a nonnegative input variable. termination occurs c when the algorithm estimates that the relative error c between x and the solution is at 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 between x and the solution is at most tol. c c info = 2 number of calls to fcn with iflag = 1 has c reached 100*(n+1). c c info = 3 tol is too small. no further improvement in c the approximate solution x is possible. c c info = 4 iteration is not making good progress. c c wa is a work array of length lwa. c c lwa is a positive integer input variable not less than c (n*(n+13))/2. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... hybrj c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer j,lr,maxfev,mode,nfev,njev,nprint double precision factor,one,xtol,zero data factor,one,zero /1.0d2,1.0d0,0.0d0/ info = 0 c c check the input parameters for errors. c if (n .le. 0 .or. ldfjac .lt. n .or. tol .lt. zero * .or. lwa .lt. (n*(n + 13))/2) go to 20 c c call hybrj. c maxfev = 100*(n + 1) xtol = tol mode = 2 do 10 j = 1, n wa(j) = one 10 continue nprint = 0 lr = (n*(n + 1))/2 call hybrj(fcn,n,x,fvec,fjac,ldfjac,xtol,maxfev,wa(1),mode, * factor,nprint,info,nfev,njev,wa(6*n+1),lr,wa(n+1), * wa(2*n+1),wa(3*n+1),wa(4*n+1),wa(5*n+1)) if (info .eq. 5) info = 4 20 continue return c c last card of subroutine hybrj1. c end minpack-19961126/dogleg.f0000644000175000017500000001226703226632002015715 0ustar sylvestresylvestre subroutine dogleg(n,r,lr,diag,qtb,delta,x,wa1,wa2) integer n,lr double precision delta double precision r(lr),diag(n),qtb(n),x(n),wa1(n),wa2(n) c ********** c c subroutine dogleg c c given an m by n matrix a, an n by n nonsingular diagonal c matrix d, an m-vector b, and a positive number delta, the c problem is to determine the convex combination x of the c gauss-newton and scaled gradient directions that minimizes c (a*x - b) in the least squares sense, subject to the c restriction that the euclidean norm of d*x be at most delta. c c this subroutine completes the solution of the problem c if it is provided with the necessary information from the c qr factorization of a. that is, if a = q*r, where q has c orthogonal columns and r is an upper triangular matrix, c then dogleg expects the full upper triangle of r and c the first n components of (q transpose)*b. c c the subroutine statement is c c subroutine dogleg(n,r,lr,diag,qtb,delta,x,wa1,wa2) c c where c c n is a positive integer input variable set to the order of r. c c r is an input array of length lr which must contain the upper c triangular matrix r stored by rows. c c lr is a positive integer input variable not less than c (n*(n+1))/2. c c diag is an input array of length n which must contain the c diagonal elements of the matrix d. c c qtb is an input array of length n which must contain the first c n elements of the vector (q transpose)*b. c c delta is a positive input variable which specifies an upper c bound on the euclidean norm of d*x. c c x is an output array of length n which contains the desired c convex combination of the gauss-newton direction and the c scaled gradient direction. c c wa1 and wa2 are work arrays of length n. c c subprograms called c c minpack-supplied ... dpmpar,enorm c c fortran-supplied ... dabs,dmax1,dmin1,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j,jj,jp1,k,l double precision alpha,bnorm,epsmch,gnorm,one,qnorm,sgnorm,sum, * temp,zero double precision dpmpar,enorm data one,zero /1.0d0,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c c first, calculate the gauss-newton direction. c jj = (n*(n + 1))/2 + 1 do 50 k = 1, n j = n - k + 1 jp1 = j + 1 jj = jj - k l = jj + 1 sum = zero if (n .lt. jp1) go to 20 do 10 i = jp1, n sum = sum + r(l)*x(i) l = l + 1 10 continue 20 continue temp = r(jj) if (temp .ne. zero) go to 40 l = j do 30 i = 1, j temp = dmax1(temp,dabs(r(l))) l = l + n - i 30 continue temp = epsmch*temp if (temp .eq. zero) temp = epsmch 40 continue x(j) = (qtb(j) - sum)/temp 50 continue c c test whether the gauss-newton direction is acceptable. c do 60 j = 1, n wa1(j) = zero wa2(j) = diag(j)*x(j) 60 continue qnorm = enorm(n,wa2) if (qnorm .le. delta) go to 140 c c the gauss-newton direction is not acceptable. c next, calculate the scaled gradient direction. c l = 1 do 80 j = 1, n temp = qtb(j) do 70 i = j, n wa1(i) = wa1(i) + r(l)*temp l = l + 1 70 continue wa1(j) = wa1(j)/diag(j) 80 continue c c calculate the norm of the scaled gradient and test for c the special case in which the scaled gradient is zero. c gnorm = enorm(n,wa1) sgnorm = zero alpha = delta/qnorm if (gnorm .eq. zero) go to 120 c c calculate the point along the scaled gradient c at which the quadratic is minimized. c do 90 j = 1, n wa1(j) = (wa1(j)/gnorm)/diag(j) 90 continue l = 1 do 110 j = 1, n sum = zero do 100 i = j, n sum = sum + r(l)*wa1(i) l = l + 1 100 continue wa2(j) = sum 110 continue temp = enorm(n,wa2) sgnorm = (gnorm/temp)/temp c c test whether the scaled gradient direction is acceptable. c alpha = zero if (sgnorm .ge. delta) go to 120 c c the scaled gradient direction is not acceptable. c finally, calculate the point along the dogleg c at which the quadratic is minimized. c bnorm = enorm(n,qtb) temp = (bnorm/gnorm)*(bnorm/qnorm)*(sgnorm/delta) temp = temp - (delta/qnorm)*(sgnorm/delta)**2 * + dsqrt((temp-(delta/qnorm))**2 * +(one-(delta/qnorm)**2)*(one-(sgnorm/delta)**2)) alpha = ((delta/qnorm)*(one - (sgnorm/delta)**2))/temp 120 continue c c form appropriate convex combination of the gauss-newton c direction and the scaled gradient direction. c temp = (one - alpha)*dmin1(sgnorm,delta) do 130 j = 1, n x(j) = temp*wa1(j) + alpha*x(j) 130 continue 140 continue return c c last card of subroutine dogleg. c end minpack-19961126/lmder.f0000644000175000017500000003612303226632010015553 0ustar sylvestresylvestre subroutine lmder(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol, * maxfev,diag,mode,factor,nprint,info,nfev,njev, * ipvt,qtf,wa1,wa2,wa3,wa4) integer m,n,ldfjac,maxfev,mode,nprint,info,nfev,njev integer ipvt(n) double precision ftol,xtol,gtol,factor double precision x(n),fvec(m),fjac(ldfjac,n),diag(n),qtf(n), * wa1(n),wa2(n),wa3(n),wa4(m) c ********** c c subroutine lmder c c the purpose of lmder is to minimize the sum of the squares of c m nonlinear functions in n variables by a modification of c the levenberg-marquardt algorithm. the user must provide a c subroutine which calculates the functions and the jacobian. c c the subroutine statement is c c subroutine lmder(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol, c maxfev,diag,mode,factor,nprint,info,nfev, c njev,ipvt,qtf,wa1,wa2,wa3,wa4) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the jacobian. fcn must c be declared in an external statement in the user c calling program, and should be written as follows. c c subroutine fcn(m,n,x,fvec,fjac,ldfjac,iflag) c integer m,n,ldfjac,iflag c double precision x(n),fvec(m),fjac(ldfjac,n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. do not alter fjac. c if iflag = 2 calculate the jacobian at x and c return this matrix in fjac. do not alter 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 lmder. 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 fjac is an output m by n array. the upper n by n submatrix c of fjac contains an upper triangular matrix r with c diagonal elements of nonincreasing magnitude such that c c t t t c p *(jac *jac)*p = r *r, c c where p is a permutation matrix and jac is the final c calculated jacobian. column j of p is column ipvt(j) c (see below) of the identity matrix. the lower trapezoidal c part of fjac contains information generated during c the computation of r. c c ldfjac is a positive integer input variable not less than m c which specifies the leading dimension of the array fjac. c c ftol is a nonnegative input variable. termination c occurs when both the actual and predicted relative c reductions in the sum of squares are at most ftol. c therefore, ftol measures the relative error desired c in the sum of squares. c c xtol is a nonnegative input variable. termination c occurs when the relative error between two consecutive c iterates is at most xtol. therefore, xtol measures the c relative error desired in the approximate solution. c c gtol is a nonnegative input variable. termination c occurs when the cosine of the angle between fvec and c any column of the jacobian is at most gtol in absolute c value. therefore, gtol measures the orthogonality c desired between the function vector and the columns c of the jacobian. c c maxfev is a positive integer input variable. termination c occurs when the number of calls to fcn with iflag = 1 c has reached maxfev. c c diag is an array of length n. if mode = 1 (see c below), diag is internally set. if mode = 2, diag c must contain positive entries that serve as c multiplicative scale factors for the variables. c c mode is an integer input variable. if mode = 1, the c variables will be scaled internally. if mode = 2, c the scaling is specified by the input diag. other c values of mode are equivalent to mode = 1. c c factor is a positive input variable used in determining the c initial step bound. this bound is set to the product of c factor and the euclidean norm of diag*x if nonzero, or else c to factor itself. in most cases factor should lie in the c interval (.1,100.).100. is a generally recommended value. c c nprint is an integer input variable that enables controlled c printing of iterates if it is positive. in this case, c fcn is called with iflag = 0 at the beginning of the first c iteration and every nprint iterations thereafter and c immediately prior to return, with x, fvec, and fjac c available for printing. fvec and fjac should not be c altered. if nprint is not positive, no special calls c of fcn with iflag = 0 are made. 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 both actual and predicted relative reductions c in the sum of squares are at most ftol. c c info = 2 relative error between two consecutive iterates c is at most xtol. c c info = 3 conditions for info = 1 and info = 2 both hold. c c info = 4 the cosine of the angle between fvec and any c column of the jacobian is at most gtol in c absolute value. c c info = 5 number of calls to fcn with iflag = 1 has c reached maxfev. c c info = 6 ftol is too small. no further reduction in c the sum of squares is possible. c c info = 7 xtol is too small. no further improvement in c the approximate solution x is possible. c c info = 8 gtol is too small. fvec is orthogonal to the c columns of the jacobian to machine precision. c c nfev is an integer output variable set to the number of c calls to fcn with iflag = 1. c c njev is an integer output variable set to the number of c calls to fcn with iflag = 2. c c ipvt is an integer output array of length n. ipvt c defines a permutation matrix p such that jac*p = q*r, c where jac is the final calculated jacobian, q is c orthogonal (not stored), and r is upper triangular c with diagonal elements of nonincreasing magnitude. c column j of p is column ipvt(j) of the identity matrix. c c qtf is an output array of length n which contains c the first n elements of the vector (q transpose)*fvec. c c wa1, wa2, and wa3 are work arrays of length n. c c wa4 is a work array of length m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dpmpar,enorm,lmpar,qrfac c c fortran-supplied ... dabs,dmax1,dmin1,dsqrt,mod c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,iflag,iter,j,l double precision actred,delta,dirder,epsmch,fnorm,fnorm1,gnorm, * one,par,pnorm,prered,p1,p5,p25,p75,p0001,ratio, * sum,temp,temp1,temp2,xnorm,zero double precision dpmpar,enorm data one,p1,p5,p25,p75,p0001,zero * /1.0d0,1.0d-1,5.0d-1,2.5d-1,7.5d-1,1.0d-4,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c info = 0 iflag = 0 nfev = 0 njev = 0 c c check the input parameters for errors. c if (n .le. 0 .or. m .lt. n .or. ldfjac .lt. m * .or. ftol .lt. zero .or. xtol .lt. zero .or. gtol .lt. zero * .or. maxfev .le. 0 .or. factor .le. zero) go to 300 if (mode .ne. 2) go to 20 do 10 j = 1, n if (diag(j) .le. zero) go to 300 10 continue 20 continue c c evaluate the function at the starting point c and calculate its norm. c iflag = 1 call fcn(m,n,x,fvec,fjac,ldfjac,iflag) nfev = 1 if (iflag .lt. 0) go to 300 fnorm = enorm(m,fvec) c c initialize levenberg-marquardt parameter and iteration counter. c par = zero iter = 1 c c beginning of the outer loop. c 30 continue c c calculate the jacobian matrix. c iflag = 2 call fcn(m,n,x,fvec,fjac,ldfjac,iflag) njev = njev + 1 if (iflag .lt. 0) go to 300 c c if requested, call fcn to enable printing of iterates. c if (nprint .le. 0) go to 40 iflag = 0 if (mod(iter-1,nprint) .eq. 0) * call fcn(m,n,x,fvec,fjac,ldfjac,iflag) if (iflag .lt. 0) go to 300 40 continue c c compute the qr factorization of the jacobian. c call qrfac(m,n,fjac,ldfjac,.true.,ipvt,n,wa1,wa2,wa3) c c on the first iteration and if mode is 1, scale according c to the norms of the columns of the initial jacobian. c if (iter .ne. 1) go to 80 if (mode .eq. 2) go to 60 do 50 j = 1, n diag(j) = wa2(j) if (wa2(j) .eq. zero) diag(j) = one 50 continue 60 continue c c on the first iteration, calculate the norm of the scaled x c and initialize the step bound delta. c do 70 j = 1, n wa3(j) = diag(j)*x(j) 70 continue xnorm = enorm(n,wa3) delta = factor*xnorm if (delta .eq. zero) delta = factor 80 continue c c form (q transpose)*fvec and store the first n components in c qtf. c do 90 i = 1, m wa4(i) = fvec(i) 90 continue do 130 j = 1, n if (fjac(j,j) .eq. zero) go to 120 sum = zero do 100 i = j, m sum = sum + fjac(i,j)*wa4(i) 100 continue temp = -sum/fjac(j,j) do 110 i = j, m wa4(i) = wa4(i) + fjac(i,j)*temp 110 continue 120 continue fjac(j,j) = wa1(j) qtf(j) = wa4(j) 130 continue c c compute the norm of the scaled gradient. c gnorm = zero if (fnorm .eq. zero) go to 170 do 160 j = 1, n l = ipvt(j) if (wa2(l) .eq. zero) go to 150 sum = zero do 140 i = 1, j sum = sum + fjac(i,j)*(qtf(i)/fnorm) 140 continue gnorm = dmax1(gnorm,dabs(sum/wa2(l))) 150 continue 160 continue 170 continue c c test for convergence of the gradient norm. c if (gnorm .le. gtol) info = 4 if (info .ne. 0) go to 300 c c rescale if necessary. c if (mode .eq. 2) go to 190 do 180 j = 1, n diag(j) = dmax1(diag(j),wa2(j)) 180 continue 190 continue c c beginning of the inner loop. c 200 continue c c determine the levenberg-marquardt parameter. c call lmpar(n,fjac,ldfjac,ipvt,diag,qtf,delta,par,wa1,wa2, * wa3,wa4) c c store the direction p and x + p. calculate the norm of p. c do 210 j = 1, n wa1(j) = -wa1(j) wa2(j) = x(j) + wa1(j) wa3(j) = diag(j)*wa1(j) 210 continue pnorm = enorm(n,wa3) c c on the first iteration, adjust the initial step bound. c if (iter .eq. 1) delta = dmin1(delta,pnorm) c c evaluate the function at x + p and calculate its norm. c iflag = 1 call fcn(m,n,wa2,wa4,fjac,ldfjac,iflag) nfev = nfev + 1 if (iflag .lt. 0) go to 300 fnorm1 = enorm(m,wa4) c c compute the scaled actual reduction. c actred = -one if (p1*fnorm1 .lt. fnorm) actred = one - (fnorm1/fnorm)**2 c c compute the scaled predicted reduction and c the scaled directional derivative. c do 230 j = 1, n wa3(j) = zero l = ipvt(j) temp = wa1(l) do 220 i = 1, j wa3(i) = wa3(i) + fjac(i,j)*temp 220 continue 230 continue temp1 = enorm(n,wa3)/fnorm temp2 = (dsqrt(par)*pnorm)/fnorm prered = temp1**2 + temp2**2/p5 dirder = -(temp1**2 + temp2**2) c c compute the ratio of the actual to the predicted c reduction. c ratio = zero if (prered .ne. zero) ratio = actred/prered c c update the step bound. c if (ratio .gt. p25) go to 240 if (actred .ge. zero) temp = p5 if (actred .lt. zero) * temp = p5*dirder/(dirder + p5*actred) if (p1*fnorm1 .ge. fnorm .or. temp .lt. p1) temp = p1 delta = temp*dmin1(delta,pnorm/p1) par = par/temp go to 260 240 continue if (par .ne. zero .and. ratio .lt. p75) go to 250 delta = pnorm/p5 par = p5*par 250 continue 260 continue c c test for successful iteration. c if (ratio .lt. p0001) go to 290 c c successful iteration. update x, fvec, and their norms. c do 270 j = 1, n x(j) = wa2(j) wa2(j) = diag(j)*x(j) 270 continue do 280 i = 1, m fvec(i) = wa4(i) 280 continue xnorm = enorm(n,wa2) fnorm = fnorm1 iter = iter + 1 290 continue c c tests for convergence. c if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one) info = 1 if (delta .le. xtol*xnorm) info = 2 if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one .and. info .eq. 2) info = 3 if (info .ne. 0) go to 300 c c tests for termination and stringent tolerances. c if (nfev .ge. maxfev) info = 5 if (dabs(actred) .le. epsmch .and. prered .le. epsmch * .and. p5*ratio .le. one) info = 6 if (delta .le. epsmch*xnorm) info = 7 if (gnorm .le. epsmch) info = 8 if (info .ne. 0) go to 300 c c end of the inner loop. repeat if iteration unsuccessful. c if (ratio .lt. p0001) go to 200 c c end of the outer loop. c go to 30 300 continue c c termination, either normal or user imposed. c if (iflag .lt. 0) info = iflag iflag = 0 if (nprint .gt. 0) call fcn(m,n,x,fvec,fjac,ldfjac,iflag) return c c last card of subroutine lmder. c end minpack-19961126/lmstr1.f0000644000175000017500000001273103226632012015673 0ustar sylvestresylvestre subroutine lmstr1(fcn,m,n,x,fvec,fjac,ldfjac,tol,info,ipvt,wa, * lwa) integer m,n,ldfjac,info,lwa integer ipvt(n) double precision tol double precision x(n),fvec(m),fjac(ldfjac,n),wa(lwa) external fcn c ********** c c subroutine lmstr1 c c the purpose of lmstr1 is to minimize the sum of the squares of c m nonlinear functions in n variables by a modification of c the levenberg-marquardt algorithm which uses minimal storage. c this is done by using the more general least-squares solver c lmstr. the user must provide a subroutine which calculates c the functions and the rows of the jacobian. c c the subroutine statement is c c subroutine lmstr1(fcn,m,n,x,fvec,fjac,ldfjac,tol,info, c ipvt,wa,lwa) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the rows of the jacobian. c fcn must be declared in an external statement in the c user calling program, and should be written as follows. c c subroutine fcn(m,n,x,fvec,fjrow,iflag) c integer m,n,iflag c double precision x(n),fvec(m),fjrow(n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. c if iflag = i calculate the (i-1)-st row of the c jacobian at x and return this vector in fjrow. 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 lmstr1. 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 fjac is an output n by n array. the upper triangle of fjac c contains an upper triangular matrix r such that c c t t t c p *(jac *jac)*p = r *r, c c where p is a permutation matrix and jac is the final c calculated jacobian. column j of p is column ipvt(j) c (see below) of the identity matrix. the lower triangular c part of fjac contains information generated during c the computation of r. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. 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 with iflag = 1 has c reached 100*(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 ipvt is an integer output array of length n. ipvt c defines a permutation matrix p such that jac*p = q*r, c where jac is the final calculated jacobian, q is c orthogonal (not stored), and r is upper triangular. c column j of p is column ipvt(j) of the identity matrix. c c wa is a work array of length lwa. c c lwa is a positive integer input variable not less than 5*n+m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... lmstr c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, dudley v. goetschel, kenneth e. hillstrom, c jorge j. more c c ********** integer maxfev,mode,nfev,njev,nprint double precision factor,ftol,gtol,xtol,zero data factor,zero /1.0d2,0.0d0/ info = 0 c c check the input parameters for errors. c if (n .le. 0 .or. m .lt. n .or. ldfjac .lt. n .or. tol .lt. zero * .or. lwa .lt. 5*n + m) go to 10 c c call lmstr. c maxfev = 100*(n + 1) ftol = tol xtol = tol gtol = zero mode = 1 nprint = 0 call lmstr(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol,maxfev, * wa(1),mode,factor,nprint,info,nfev,njev,ipvt,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 lmstr1. c end minpack-19961126/index.html0000644000175000017500000001003607260121571016300 0ustar sylvestresylvestre minpack

minpack

Click here to see the number of accesses to this library.


lib	ex
for	test programs

file	readme
for	overview of minpack

file	chkder.f  chkder.f plus dependencies
gams	F3,G4c,K6d
for	check gradients for consistency with functions

file	dogleg.f  dogleg.f plus dependencies
for	determine combination of gauss-newton and gradient directions

file	dpmpar.f
for	provide double precision machine parameters

file	enorm.f
for	calculate euclidean norm of vector

file	fdjac1.f  fdjac1.f plus dependencies
for	calculate difference approximation to jacobian (nonlinear equations)

file	fdjac2.f  fdjac2.f plus dependencies
for	calculate difference approximation to jacobian (least squares)

file	hybrd.f  hybrd.f plus dependencies
gams	F2
for	solve systems of nonlinear equations (approximate jacobian)

file	hybrd1.f  hybrd1.f plus dependencies
gams	F2
for	easy-to-use driver for (minpack/hybrd)

file	hybrj.f  hybrj.f plus dependencies
gams	F2
for	solve systems of nonlinear equations (analytic jacobian)

file	hybrj1.f  hybrj1.f plus dependencies
gams	F2
for	easy-to-use driver for (minpack/hybrj)

file	lmder.f  lmder.f plus dependencies
gams	K1b1a2
for	solve nonlinear least squares problem (analytic jacobian)

file	lmder1.f  lmder1.f plus dependencies
gams	K1b1a2
for	easy-to-use driver for (minpack/lmder)

file	lmdif.f  lmdif.f plus dependencies
gams	K1b1a1
for	solve nonlinear least squares problem (approximate jacobian)

file	lmdif1.f  lmdif1.f plus dependencies
gams	K1b1a1
for	easy-to-use driver for (minpack/lmdif)

file	lmpar.f  lmpar.f plus dependencies
for	determine levenberg-marquardt parameter

file	lmstr.f  lmstr.f plus dependencies
gams	K1b1a2
for	solve nonlinear least squares problem (storage conserving)

file	lmstr1.f  lmstr1.f plus dependencies
gams	K1b1a2
for	easy-to-use driver for (minpack/lmstr)

file	qform.f
for	accumulate orthogonal matrix from qr factorization

file	qrfac.f  qrfac.f plus dependencies
for	compute qr factorization of rectangular matrix

file	qrsolv.f
for	complete solution of least squares problem

file	rwupdt.f
for	update qr factorization after row addition

file	r1mpyq.f
for	apply orthogonal transformations from qr factorization

file	r1updt.f  r1updt.f plus dependencies
for	update qr factorization after rank-1 addition

minpack-19961126/qrsolv.f0000644000175000017500000001404203226632013015775 0ustar sylvestresylvestre subroutine qrsolv(n,r,ldr,ipvt,diag,qtb,x,sdiag,wa) integer n,ldr integer ipvt(n) double precision r(ldr,n),diag(n),qtb(n),x(n),sdiag(n),wa(n) c ********** c c subroutine qrsolv c c given an m by n matrix a, an n by n diagonal matrix d, c and an m-vector b, the problem is to determine an x which c solves the system c c a*x = b , d*x = 0 , c c in the least squares sense. c c this subroutine completes the solution of the problem c if it is provided with the necessary information from the c qr factorization, with column pivoting, of a. that is, if c a*p = q*r, where p is a permutation matrix, q has orthogonal c columns, and r is an upper triangular matrix with diagonal c elements of nonincreasing magnitude, then qrsolv expects c the full upper triangle of r, the permutation matrix p, c and the first n components of (q transpose)*b. the system c a*x = b, d*x = 0, is then equivalent to c c t t c r*z = q *b , p *d*p*z = 0 , c c where x = p*z. if this system does not have full rank, c then a least squares solution is obtained. on output qrsolv c also provides an upper triangular matrix s such that c c t t t c p *(a *a + d*d)*p = s *s . c c s is computed within qrsolv and may be of separate interest. c c the subroutine statement is c c subroutine qrsolv(n,r,ldr,ipvt,diag,qtb,x,sdiag,wa) c c where c c n is a positive integer input variable set to the order of r. c c r is an n by n array. on input the full upper triangle c must contain the full upper triangle of the matrix r. c on output the full upper triangle is unaltered, and the c strict lower triangle contains the strict upper triangle c (transposed) of the upper triangular matrix s. c c ldr is a positive integer input variable not less than n c which specifies the leading dimension of the array r. c c ipvt is an integer input array of length n which defines the c permutation matrix p such that a*p = q*r. column j of p c is column ipvt(j) of the identity matrix. c c diag is an input array of length n which must contain the c diagonal elements of the matrix d. c c qtb is an input array of length n which must contain the first c n elements of the vector (q transpose)*b. c c x is an output array of length n which contains the least c squares solution of the system a*x = b, d*x = 0. c c sdiag is an output array of length n which contains the c diagonal elements of the upper triangular matrix s. c c wa is a work array of length n. c c subprograms called c c fortran-supplied ... dabs,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j,jp1,k,kp1,l,nsing double precision cos,cotan,p5,p25,qtbpj,sin,sum,tan,temp,zero data p5,p25,zero /5.0d-1,2.5d-1,0.0d0/ c c copy r and (q transpose)*b to preserve input and initialize s. c in particular, save the diagonal elements of r in x. c do 20 j = 1, n do 10 i = j, n r(i,j) = r(j,i) 10 continue x(j) = r(j,j) wa(j) = qtb(j) 20 continue c c eliminate the diagonal matrix d using a givens rotation. c do 100 j = 1, n c c prepare the row of d to be eliminated, locating the c diagonal element using p from the qr factorization. c l = ipvt(j) if (diag(l) .eq. zero) go to 90 do 30 k = j, n sdiag(k) = zero 30 continue sdiag(j) = diag(l) c c the transformations to eliminate the row of d c modify only a single element of (q transpose)*b c beyond the first n, which is initially zero. c qtbpj = zero do 80 k = j, n c c determine a givens rotation which eliminates the c appropriate element in the current row of d. c if (sdiag(k) .eq. zero) go to 70 if (dabs(r(k,k)) .ge. dabs(sdiag(k))) go to 40 cotan = r(k,k)/sdiag(k) sin = p5/dsqrt(p25+p25*cotan**2) cos = sin*cotan go to 50 40 continue tan = sdiag(k)/r(k,k) cos = p5/dsqrt(p25+p25*tan**2) sin = cos*tan 50 continue c c compute the modified diagonal element of r and c the modified element of ((q transpose)*b,0). c r(k,k) = cos*r(k,k) + sin*sdiag(k) temp = cos*wa(k) + sin*qtbpj qtbpj = -sin*wa(k) + cos*qtbpj wa(k) = temp c c accumulate the tranformation in the row of s. c kp1 = k + 1 if (n .lt. kp1) go to 70 do 60 i = kp1, n temp = cos*r(i,k) + sin*sdiag(i) sdiag(i) = -sin*r(i,k) + cos*sdiag(i) r(i,k) = temp 60 continue 70 continue 80 continue 90 continue c c store the diagonal element of s and restore c the corresponding diagonal element of r. c sdiag(j) = r(j,j) r(j,j) = x(j) 100 continue c c solve the triangular system for z. if the system is c singular, then obtain a least squares solution. c nsing = n do 110 j = 1, n if (sdiag(j) .eq. zero .and. nsing .eq. n) nsing = j - 1 if (nsing .lt. n) wa(j) = zero 110 continue if (nsing .lt. 1) go to 150 do 140 k = 1, nsing j = nsing - k + 1 sum = zero jp1 = j + 1 if (nsing .lt. jp1) go to 130 do 120 i = jp1, nsing sum = sum + r(i,j)*wa(i) 120 continue 130 continue wa(j) = (wa(j) - sum)/sdiag(j) 140 continue 150 continue c c permute the components of z back to components of x. c do 160 j = 1, n l = ipvt(j) x(l) = wa(j) 160 continue return c c last card of subroutine qrsolv. c end minpack-19961126/lmder1.f0000644000175000017500000001305203226632010015630 0ustar sylvestresylvestre subroutine lmder1(fcn,m,n,x,fvec,fjac,ldfjac,tol,info,ipvt,wa, * lwa) integer m,n,ldfjac,info,lwa integer ipvt(n) double precision tol double precision x(n),fvec(m),fjac(ldfjac,n),wa(lwa) external fcn c ********** c c subroutine lmder1 c c the purpose of lmder1 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 lmder. the user must provide a c subroutine which calculates the functions and the jacobian. c c the subroutine statement is c c subroutine lmder1(fcn,m,n,x,fvec,fjac,ldfjac,tol,info, c ipvt,wa,lwa) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the jacobian. fcn must c be declared in an external statement in the user c calling program, and should be written as follows. c c subroutine fcn(m,n,x,fvec,fjac,ldfjac,iflag) c integer m,n,ldfjac,iflag c double precision x(n),fvec(m),fjac(ldfjac,n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. do not alter fjac. c if iflag = 2 calculate the jacobian at x and c return this matrix in fjac. do not alter 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 lmder1. 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 fjac is an output m by n array. the upper n by n submatrix c of fjac contains an upper triangular matrix r with c diagonal elements of nonincreasing magnitude such that c c t t t c p *(jac *jac)*p = r *r, c c where p is a permutation matrix and jac is the final c calculated jacobian. column j of p is column ipvt(j) c (see below) of the identity matrix. the lower trapezoidal c part of fjac contains information generated during c the computation of r. c c ldfjac is a positive integer input variable not less than m c which specifies the leading dimension of the array fjac. 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 with iflag = 1 has c reached 100*(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 ipvt is an integer output array of length n. ipvt c defines a permutation matrix p such that jac*p = q*r, c where jac is the final calculated jacobian, q is c orthogonal (not stored), and r is upper triangular c with diagonal elements of nonincreasing magnitude. c column j of p is column ipvt(j) of the identity matrix. c c wa is a work array of length lwa. c c lwa is a positive integer input variable not less than 5*n+m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... lmder c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer maxfev,mode,nfev,njev,nprint double precision factor,ftol,gtol,xtol,zero data factor,zero /1.0d2,0.0d0/ info = 0 c c check the input parameters for errors. c if (n .le. 0 .or. m .lt. n .or. ldfjac .lt. m .or. tol .lt. zero * .or. lwa .lt. 5*n + m) go to 10 c c call lmder. c maxfev = 100*(n + 1) ftol = tol xtol = tol gtol = zero mode = 1 nprint = 0 call lmder(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol,maxfev, * wa(1),mode,factor,nprint,info,nfev,njev,ipvt,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 lmder1. c end minpack-19961126/ltmain.sh0000644000175000017500000055523711616327304016146 0ustar sylvestresylvestre# ltmain.sh - Provide generalized library-building support services. # NOTE: Changing this file will not affect anything until you rerun configure. # # Copyright (C) 1996, 1997, 1998, 1999, 2000, 2001, 2003, 2004, 2005 # Free Software Foundation, Inc. # Originally by Gordon Matzigkeit , 1996 # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # As a special exception to the GNU General Public License, if you # distribute this file as part of a program that contains a # configuration script generated by Autoconf, you may include it under # the same distribution terms that you use for the rest of that program. basename="s,^.*/,,g" # Work around backward compatibility issue on IRIX 6.5. On IRIX 6.4+, sh # is ksh but when the shell is invoked as "sh" and the current value of # the _XPG environment variable is not equal to 1 (one), the special # positional parameter $0, within a function call, is the name of the # function. progpath="$0" # The name of this program: progname=`echo "$progpath" | $SED $basename` modename="$progname" # Global variables: EXIT_SUCCESS=0 EXIT_FAILURE=1 PROGRAM=ltmain.sh PACKAGE=libtool VERSION="1.5.20 Debian 1.5.20-2" TIMESTAMP=" (1.1220.2.287 2005/08/31 18:54:15)" # See if we are running on zsh, and set the options which allow our # commands through without removal of \ escapes. if test -n "${ZSH_VERSION+set}" ; then setopt NO_GLOB_SUBST fi # Check that we have a working $echo. if test "X$1" = X--no-reexec; then # Discard the --no-reexec flag, and continue. shift elif test "X$1" = X--fallback-echo; then # Avoid inline document here, it may be left over : elif test "X`($echo '\t') 2>/dev/null`" = 'X\t'; then # Yippee, $echo works! : else # Restart under the correct shell, and then maybe $echo will work. exec $SHELL "$progpath" --no-reexec ${1+"$@"} fi if test "X$1" = X--fallback-echo; then # used as fallback echo shift cat <&2 $echo "Fatal configuration error. See the $PACKAGE docs for more information." 1>&2 exit $EXIT_FAILURE fi # Global variables. mode=$default_mode nonopt= prev= prevopt= run= show="$echo" show_help= execute_dlfiles= lo2o="s/\\.lo\$/.${objext}/" o2lo="s/\\.${objext}\$/.lo/" ##################################### # Shell function definitions: # This seems to be the best place for them # func_win32_libid arg # return the library type of file 'arg' # # Need a lot of goo to handle *both* DLLs and import libs # Has to be a shell function in order to 'eat' the argument # that is supplied when $file_magic_command is called. func_win32_libid () { win32_libid_type="unknown" win32_fileres=`file -L $1 2>/dev/null` case $win32_fileres in *ar\ archive\ import\ library*) # definitely import win32_libid_type="x86 archive import" ;; *ar\ archive*) # could be an import, or static if eval $OBJDUMP -f $1 | $SED -e '10q' 2>/dev/null | \ $EGREP -e 'file format pe-i386(.*architecture: i386)?' >/dev/null ; then win32_nmres=`eval $NM -f posix -A $1 | \ sed -n -e '1,100{/ I /{x;/import/!{s/^/import/;h;p;};x;};}'` if test "X$win32_nmres" = "Ximport" ; then win32_libid_type="x86 archive import" else win32_libid_type="x86 archive static" fi fi ;; *DLL*) win32_libid_type="x86 DLL" ;; *executable*) # but shell scripts are "executable" too... case $win32_fileres in *MS\ Windows\ PE\ Intel*) win32_libid_type="x86 DLL" ;; esac ;; esac $echo $win32_libid_type } # func_infer_tag arg # Infer tagged configuration to use if any are available and # if one wasn't chosen via the "--tag" command line option. # Only attempt this if the compiler in the base compile # command doesn't match the default compiler. # arg is usually of the form 'gcc ...' func_infer_tag () { if test -n "$available_tags" && test -z "$tagname"; then CC_quoted= for arg in $CC; do case $arg in *[\[\~\#\^\&\*\(\)\{\}\|\;\<\>\?\'\ \ ]*|*]*|"") arg="\"$arg\"" ;; esac CC_quoted="$CC_quoted $arg" done case $@ in # Blanks in the command may have been stripped by the calling shell, # but not from the CC environment variable when configure was run. 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strcpy ((char *) xmalloc (strlen (string) + 1), string) : NULL ; } char * basename (const char *name) { const char *base; #if defined (HAVE_DOS_BASED_FILE_SYSTEM) /* Skip over the disk name in MSDOS pathnames. */ if (isalpha (name[0]) && name[1] == ':') name += 2; #endif for (base = name; *name; name++) if (IS_DIR_SEPARATOR (*name)) base = name + 1; return (char *) base; } char * fnqualify(const char *path) { size_t size; char *p; char tmp[LT_PATHMAX + 1]; assert(path != NULL); /* Is it qualified already? */ #if defined (HAVE_DOS_BASED_FILE_SYSTEM) if (isalpha (path[0]) && path[1] == ':') return xstrdup (path); #endif if (IS_DIR_SEPARATOR (path[0])) return xstrdup (path); /* prepend the current directory */ /* doesn't handle '~' */ if (getcwd (tmp, LT_PATHMAX) == NULL) lt_fatal ("getcwd failed"); size = strlen(tmp) + 1 + strlen(path) + 1; /* +2 for '/' and '\0' */ p = XMALLOC(char, size); sprintf(p, "%s%c%s", tmp, DIR_SEPARATOR, path); return p; } char * strendzap(char *str, const char *pat) { size_t len, patlen; assert(str != NULL); assert(pat != NULL); len = strlen(str); patlen = strlen(pat); if (patlen <= len) { str += len - patlen; if (strcmp(str, pat) == 0) *str = '\0'; } return str; } static void lt_error_core (int exit_status, const char * mode, const char * message, va_list ap) { fprintf (stderr, "%s: %s: ", program_name, mode); vfprintf (stderr, message, ap); fprintf (stderr, ".\n"); if (exit_status >= 0) exit (exit_status); } void lt_fatal (const char *message, ...) { va_list ap; va_start (ap, message); lt_error_core (EXIT_FAILURE, "FATAL", message, ap); va_end (ap); } EOF # we should really use a build-platform specific compiler # here, but OTOH, the wrappers (shell script and this C one) # are only useful if you want to execute the "real" binary. # Since the "real" binary is built for $host, then this # wrapper might as well be built for $host, too. $run $LTCC -s -o $cwrapper $cwrappersource ;; esac $rm $output trap "$rm $output; exit $EXIT_FAILURE" 1 2 15 $echo > $output "\ #! $SHELL # $output - temporary wrapper script for $objdir/$outputname # Generated by $PROGRAM - GNU $PACKAGE $VERSION$TIMESTAMP # # The $output program cannot be directly executed until all the libtool # libraries that it depends on are installed. # # This wrapper script should never be moved out of the build directory. # If it is, it will not operate correctly. # Sed substitution that helps us do robust quoting. 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1 if (nm1 .lt. 1) go to 50 do 20 nmj = 1, nm1 j = n - nmj if (dabs(v(j)) .gt. one) cos = one/v(j) if (dabs(v(j)) .gt. one) sin = dsqrt(one-cos**2) if (dabs(v(j)) .le. one) sin = v(j) if (dabs(v(j)) .le. one) cos = dsqrt(one-sin**2) do 10 i = 1, m temp = cos*a(i,j) - sin*a(i,n) a(i,n) = sin*a(i,j) + cos*a(i,n) a(i,j) = temp 10 continue 20 continue c c apply the second set of givens rotations to a. c do 40 j = 1, nm1 if (dabs(w(j)) .gt. one) cos = one/w(j) if (dabs(w(j)) .gt. one) sin = dsqrt(one-cos**2) if (dabs(w(j)) .le. one) sin = w(j) if (dabs(w(j)) .le. one) cos = dsqrt(one-sin**2) do 30 i = 1, m temp = cos*a(i,j) + sin*a(i,n) a(i,n) = -sin*a(i,j) + cos*a(i,n) a(i,j) = temp 30 continue 40 continue 50 continue return c c last card of subroutine r1mpyq. c end minpack-19961126/fdjac2.f0000644000175000017500000000641403226632004015604 0ustar sylvestresylvestre subroutine fdjac2(fcn,m,n,x,fvec,fjac,ldfjac,iflag,epsfcn,wa) integer m,n,ldfjac,iflag double precision epsfcn double precision x(n),fvec(m),fjac(ldfjac,n),wa(m) c ********** c c subroutine fdjac2 c c this subroutine computes a forward-difference approximation c to the m by n jacobian matrix associated with a specified c problem of m functions in n variables. c c the subroutine statement is c c subroutine fdjac2(fcn,m,n,x,fvec,fjac,ldfjac,iflag,epsfcn,wa) 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 double precision 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 fdjac2. 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 input array of length n. c c fvec is an input array of length m which must contain the c functions evaluated at x. c c fjac is an output m by n array which contains the c approximation to the jacobian matrix evaluated at x. c c ldfjac is a positive integer input variable not less than m c which specifies the leading dimension of the array fjac. c c iflag is an integer variable which can be used to terminate c the execution of fdjac2. see description of fcn. c c epsfcn is an input variable used in determining a suitable c step length for the forward-difference approximation. this c approximation assumes that the relative errors in the c functions are of the order of epsfcn. if epsfcn is less c than the machine precision, it is assumed that the relative c errors in the functions are of the order of the machine c precision. c c wa is a work array of length m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dpmpar c c fortran-supplied ... dabs,dmax1,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j double precision eps,epsmch,h,temp,zero double precision dpmpar data zero /0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c eps = dsqrt(dmax1(epsfcn,epsmch)) do 20 j = 1, n temp = x(j) h = eps*dabs(temp) if (h .eq. zero) h = eps x(j) = temp + h call fcn(m,n,x,wa,iflag) if (iflag .lt. 0) go to 30 x(j) = temp do 10 i = 1, m fjac(i,j) = (wa(i) - 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then cp $export_symbols $output_objdir/$soname.def; else echo EXPORTS > $output_objdir/$soname.def; cat $export_symbols >> $output_objdir/$soname.def; fi~ $CC -shared -nostdlib $output_objdir/$soname.def $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; darwin* | rhapsody*) _LT_AC_TAGVAR(archive_cmds_need_lc, $1)=no _LT_AC_TAGVAR(hardcode_direct, $1)=no _LT_AC_TAGVAR(hardcode_automatic, $1)=yes _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=unsupported _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='' _LT_AC_TAGVAR(link_all_deplibs, $1)=yes _LT_AC_TAGVAR(allow_undefined_flag, $1)="$_lt_dar_allow_undefined" if test "$GXX" = yes ; then output_verbose_link_cmd='echo' _LT_AC_TAGVAR(archive_cmds, $1)="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}" _LT_AC_TAGVAR(module_cmds, $1)="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}" _LT_AC_TAGVAR(archive_expsym_cmds, $1)="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}" _LT_AC_TAGVAR(module_expsym_cmds, $1)="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}" if test "$lt_cv_apple_cc_single_mod" != "yes"; then _LT_AC_TAGVAR(archive_cmds, $1)="\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dsymutil}" _LT_AC_TAGVAR(archive_expsym_cmds, $1)="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dar_export_syms}${_lt_dsymutil}" fi else case $cc_basename in xlc*) output_verbose_link_cmd='echo' _LT_AC_TAGVAR(archive_cmds, $1)='$CC -qmkshrobj ${wl}-single_module $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}`echo $rpath/$soname` $xlcverstring' _LT_AC_TAGVAR(module_cmds, $1)='$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags' # Don't fix this by using the ld -exported_symbols_list flag, it doesn't exist in older darwin lds _LT_AC_TAGVAR(archive_expsym_cmds, $1)='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC -qmkshrobj ${wl}-single_module $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}$rpath/$soname $xlcverstring~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' _LT_AC_TAGVAR(module_expsym_cmds, $1)='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' ;; *) _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; esac fi ;; dgux*) case $cc_basename in ec++*) # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; ghcx*) # Green Hills C++ Compiler # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; *) # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; esac ;; freebsd[[12]]*) # C++ shared libraries reported to be fairly broken before switch to ELF _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; freebsd-elf*) _LT_AC_TAGVAR(archive_cmds_need_lc, $1)=no ;; freebsd* | dragonfly*) # FreeBSD 3 and later use GNU C++ and GNU ld with standard ELF # conventions _LT_AC_TAGVAR(ld_shlibs, $1)=yes ;; gnu*) ;; hpux9*) _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir' _LT_AC_TAGVAR(hardcode_libdir_separator, $1)=: _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E' _LT_AC_TAGVAR(hardcode_direct, $1)=yes _LT_AC_TAGVAR(hardcode_minus_L, $1)=yes # Not in the search PATH, # but as the default # location of the library. case $cc_basename in CC*) # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; aCC*) _LT_AC_TAGVAR(archive_cmds, $1)='$rm $output_objdir/$soname~$CC -b ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' # Commands to make compiler produce verbose output that lists # what "hidden" libraries, object files and flags are used when # linking a shared library. # # There doesn't appear to be a way to prevent this compiler from # explicitly linking system object files so we need to strip them # from the output so that they don't get included in the library # dependencies. output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | grep "[[-]]L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; echo $list' ;; *) if test "$GXX" = yes; then _LT_AC_TAGVAR(archive_cmds, $1)='$rm $output_objdir/$soname~$CC -shared -nostdlib -fPIC ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' else # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; esac ;; hpux10*|hpux11*) if test $with_gnu_ld = no; then _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir' _LT_AC_TAGVAR(hardcode_libdir_separator, $1)=: case $host_cpu in hppa*64*|ia64*) ;; *) _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E' ;; esac fi case $host_cpu in hppa*64*|ia64*) _LT_AC_TAGVAR(hardcode_direct, $1)=no _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=no ;; *) _LT_AC_TAGVAR(hardcode_direct, $1)=yes _LT_AC_TAGVAR(hardcode_minus_L, $1)=yes # Not in the search PATH, # but as the default # location of the library. ;; esac case $cc_basename in CC*) # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; aCC*) case $host_cpu in hppa*64*) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; ia64*) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; *) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; esac # Commands to make compiler produce verbose output that lists # what "hidden" libraries, object files and flags are used when # linking a shared library. # # There doesn't appear to be a way to prevent this compiler from # explicitly linking system object files so we need to strip them # from the output so that they don't get included in the library # dependencies. output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | grep "\-L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; echo $list' ;; *) if test "$GXX" = yes; then if test $with_gnu_ld = no; then case $host_cpu in hppa*64*) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib -fPIC ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; ia64*) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib -fPIC ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; *) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags' ;; esac fi else # FIXME: insert proper C++ library support _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; esac ;; interix[[3-9]]*) _LT_AC_TAGVAR(hardcode_direct, $1)=no _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=no _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir' _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E' # Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc. # Instead, shared libraries are loaded at an image base (0x10000000 by # default) and relocated if they conflict, which is a slow very memory # consuming and fragmenting process. To avoid this, we pick a random, # 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link # time. 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(KAI) C++ Compiler # KCC will only create a shared library if the output file # ends with ".so" (or ".sl" for HP-UX), so rename the library # to its proper name (with version) after linking. _LT_AC_TAGVAR(archive_cmds, $1)='tempext=`echo $shared_ext | $SED -e '\''s/\([[^()0-9A-Za-z{}]]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib; mv \$templib $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='tempext=`echo $shared_ext | $SED -e '\''s/\([[^()0-9A-Za-z{}]]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib ${wl}-retain-symbols-file,$export_symbols; mv \$templib $lib' # Commands to make compiler produce verbose output that lists # what "hidden" libraries, object files and flags are used when # linking a shared library. # # There doesn't appear to be a way to prevent this compiler from # explicitly linking system object files so we need to strip them # from the output so that they don't get included in the library # dependencies. output_verbose_link_cmd='templist=`$CC $CFLAGS -v conftest.$objext -o libconftest$shared_ext 2>&1 | grep "ld"`; rm -f libconftest$shared_ext; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; echo $list' _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}--rpath,$libdir' _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic' # Archives containing C++ object files must be created using # "CC -Bstatic", where "CC" is the KAI C++ compiler. _LT_AC_TAGVAR(old_archive_cmds, $1)='$CC -Bstatic -o $oldlib $oldobjs' ;; icpc*) # Intel C++ with_gnu_ld=yes # version 8.0 and above of icpc choke on multiply defined symbols # if we add $predep_objects and $postdep_objects, however 7.1 and # earlier do not add the objects themselves. case `$CC -V 2>&1` in *"Version 7."*) _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib' ;; 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AC_MSG_CHECKING([command to parse $NM output from $compiler object]) AC_CACHE_VAL([lt_cv_sys_global_symbol_pipe], [ # These are sane defaults that work on at least a few old systems. # [They come from Ultrix. 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FIXME _LT_AC_TAGVAR(archive_cmds, $1)='$CC -nostart $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; cygwin* | mingw* | pw32*) # _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1) is actually meaningless, # as there is no search path for DLLs. _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir' _LT_AC_TAGVAR(allow_undefined_flag, $1)=unsupported _LT_AC_TAGVAR(always_export_symbols, $1)=no _LT_AC_TAGVAR(enable_shared_with_static_runtimes, $1)=yes _LT_AC_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[[BCDGRS]][[ ]]/s/.*[[ ]]\([[^ ]]*\)/\1 DATA/'\'' -e '\''/^[[AITW]][[ ]]/s/.*[[ ]]//'\'' | sort | uniq > $export_symbols' if $LD --help 2>&1 | grep 'auto-import' > /dev/null; then _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib' # If the export-symbols file already is a .def file (1st line # is EXPORTS), use it as is; otherwise, prepend... _LT_AC_TAGVAR(archive_expsym_cmds, $1)='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then cp $export_symbols $output_objdir/$soname.def; else echo EXPORTS > $output_objdir/$soname.def; cat $export_symbols >> $output_objdir/$soname.def; fi~ $CC -shared $output_objdir/$soname.def $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; interix[[3-9]]*) _LT_AC_TAGVAR(hardcode_direct, $1)=no _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=no _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir' _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E' # Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc. # Instead, shared libraries are loaded at an image base (0x10000000 by # default) and relocated if they conflict, which is a slow very memory # consuming and fragmenting process. To avoid this, we pick a random, # 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link # time. Moving up from 0x10000000 also allows more sbrk(2) space. _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='sed "s,^,_," $export_symbols >$output_objdir/$soname.expsym~$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--retain-symbols-file,$output_objdir/$soname.expsym ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib' ;; gnu* | linux* | k*bsd*-gnu) if $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then tmp_addflag= case $cc_basename,$host_cpu in pgcc*) # Portland Group C compiler _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; $echo \"$new_convenience\"` ${wl}--no-whole-archive' tmp_addflag=' $pic_flag' ;; pgf77* | pgf90* | pgf95*) # Portland Group f77 and f90 compilers _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; $echo \"$new_convenience\"` ${wl}--no-whole-archive' tmp_addflag=' $pic_flag -Mnomain' ;; ecc*,ia64* | icc*,ia64*) # Intel C compiler on ia64 tmp_addflag=' -i_dynamic' ;; efc*,ia64* | ifort*,ia64*) # Intel Fortran compiler on ia64 tmp_addflag=' -i_dynamic -nofor_main' ;; ifc* | ifort*) # Intel Fortran compiler tmp_addflag=' -nofor_main' ;; esac case `$CC -V 2>&1 | sed 5q` in *Sun\ C*) # Sun C 5.9 _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`new_convenience=; for conv in $convenience\"\"; do test -z \"$conv\" || new_convenience=\"$new_convenience,$conv\"; done; $echo \"$new_convenience\"` ${wl}--no-whole-archive' tmp_sharedflag='-G' ;; *Sun\ F*) # Sun Fortran 8.3 tmp_sharedflag='-G' ;; *) tmp_sharedflag='-shared' ;; esac _LT_AC_TAGVAR(archive_cmds, $1)='$CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' if test $supports_anon_versioning = yes; then _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$echo "{ global:" > $output_objdir/$libname.ver~ cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~ $echo "local: *; };" >> $output_objdir/$libname.ver~ $CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-version-script ${wl}$output_objdir/$libname.ver -o $lib' fi _LT_AC_TAGVAR(link_all_deplibs, $1)=no else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; netbsd* | netbsdelf*-gnu) if echo __ELF__ | $CC -E - | grep __ELF__ >/dev/null; then _LT_AC_TAGVAR(archive_cmds, $1)='$LD -Bshareable $libobjs $deplibs $linker_flags -o $lib' wlarc= else _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib' fi ;; solaris*) if $LD -v 2>&1 | grep 'BFD 2\.8' > /dev/null; then _LT_AC_TAGVAR(ld_shlibs, $1)=no cat <&2 *** Warning: The releases 2.8.* of the GNU linker cannot reliably *** create shared libraries on Solaris systems. Therefore, libtool *** is disabling shared libraries support. We urge you to upgrade GNU *** binutils to release 2.9.1 or newer. Another option is to modify *** your PATH or compiler configuration so that the native linker is *** used, and then restart. EOF elif $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX*) case `$LD -v 2>&1` in *\ [[01]].* | *\ 2.[[0-9]].* | *\ 2.1[[0-5]].*) _LT_AC_TAGVAR(ld_shlibs, $1)=no cat <<_LT_EOF 1>&2 *** Warning: Releases of the GNU linker prior to 2.16.91.0.3 can not *** reliably create shared libraries on SCO systems. Therefore, libtool *** is disabling shared libraries support. We urge you to upgrade GNU *** binutils to release 2.16.91.0.3 or newer. Another option is to modify *** your PATH or compiler configuration so that the native linker is *** used, and then restart. _LT_EOF ;; *) if $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='`test -z "$SCOABSPATH" && echo ${wl}-rpath,$libdir`' _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname,\${SCOABSPATH:+${install_libdir}/}$soname -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname,\${SCOABSPATH:+${install_libdir}/}$soname,-retain-symbols-file,$export_symbols -o $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; esac ;; sunos4*) _LT_AC_TAGVAR(archive_cmds, $1)='$LD -assert pure-text -Bshareable -o $lib $libobjs $deplibs $linker_flags' wlarc= _LT_AC_TAGVAR(hardcode_direct, $1)=yes _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=no ;; *) if $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then _LT_AC_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib' else _LT_AC_TAGVAR(ld_shlibs, $1)=no fi ;; esac if test "$_LT_AC_TAGVAR(ld_shlibs, $1)" = no; then runpath_var= _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)= _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)= _LT_AC_TAGVAR(whole_archive_flag_spec, $1)= fi else # PORTME fill in a description of your system's linker (not GNU ld) case $host_os in aix3*) _LT_AC_TAGVAR(allow_undefined_flag, $1)=unsupported _LT_AC_TAGVAR(always_export_symbols, $1)=yes _LT_AC_TAGVAR(archive_expsym_cmds, $1)='$LD -o $output_objdir/$soname $libobjs $deplibs $linker_flags -bE:$export_symbols -T512 -H512 -bM:SRE~$AR $AR_FLAGS $lib $output_objdir/$soname' # Note: this linker hardcodes the directories in LIBPATH if there # are no directories specified by -L. _LT_AC_TAGVAR(hardcode_minus_L, $1)=yes if test "$GCC" = yes && test -z "$lt_prog_compiler_static"; then # Neither direct hardcoding nor static linking is supported with a # broken collect2. _LT_AC_TAGVAR(hardcode_direct, $1)=unsupported fi ;; aix[[4-9]]*) if test "$host_cpu" = ia64; then # On IA64, the linker does run time linking by default, so we don't # have to do anything special. aix_use_runtimelinking=no exp_sym_flag='-Bexport' no_entry_flag="" else # If we're using GNU nm, then we don't want the "-C" option. # -C means demangle to AIX nm, but means don't demangle with GNU nm if $NM -V 2>&1 | grep 'GNU' > /dev/null; then _LT_AC_TAGVAR(export_symbols_cmds, $1)='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\[$]2 == "T") || (\[$]2 == "D") || (\[$]2 == "B")) && ([substr](\[$]3,1,1) != ".")) { print \[$]3 } }'\'' | sort -u > $export_symbols' else _LT_AC_TAGVAR(export_symbols_cmds, $1)='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\[$]2 == "T") || (\[$]2 == "D") || (\[$]2 == "B")) && ([substr](\[$]3,1,1) != ".")) { print \[$]3 } }'\'' | sort -u > $export_symbols' fi aix_use_runtimelinking=no # Test if we are trying to use run time linking or normal # AIX style linking. If -brtl is somewhere in LDFLAGS, we # need to do runtime linking. case $host_os in aix4.[[23]]|aix4.[[23]].*|aix[[5-9]]*) for ld_flag in $LDFLAGS; do if (test $ld_flag = "-brtl" || test $ld_flag = "-Wl,-brtl"); then aix_use_runtimelinking=yes break fi done ;; esac exp_sym_flag='-bexport' no_entry_flag='-bnoentry' fi # When large executables or shared objects are built, AIX ld can # have problems creating the table of contents. If linking a library # or program results in "error TOC overflow" add -mminimal-toc to # CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not # enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS. _LT_AC_TAGVAR(archive_cmds, $1)='' _LT_AC_TAGVAR(hardcode_direct, $1)=yes _LT_AC_TAGVAR(hardcode_libdir_separator, $1)=':' _LT_AC_TAGVAR(link_all_deplibs, $1)=yes if test "$GCC" = yes; then case $host_os in aix4.[[012]]|aix4.[[012]].*) # We only want to do this on AIX 4.2 and lower, the check # below for broken collect2 doesn't work under 4.3+ collect2name=`${CC} -print-prog-name=collect2` if test -f "$collect2name" && \ strings "$collect2name" | grep resolve_lib_name >/dev/null then # We have reworked collect2 : else # We have old collect2 _LT_AC_TAGVAR(hardcode_direct, $1)=unsupported # It fails to find uninstalled libraries when the uninstalled # path is not listed in the libpath. Setting hardcode_minus_L # to unsupported forces relinking _LT_AC_TAGVAR(hardcode_minus_L, $1)=yes _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir' _LT_AC_TAGVAR(hardcode_libdir_separator, $1)= fi ;; esac shared_flag='-shared' if test "$aix_use_runtimelinking" = yes; then shared_flag="$shared_flag "'${wl}-G' fi else # not using gcc if test "$host_cpu" = ia64; then # VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release # chokes on -Wl,-G. The following line is correct: shared_flag='-G' else if test "$aix_use_runtimelinking" = yes; then shared_flag='${wl}-G' else shared_flag='${wl}-bM:SRE' fi fi fi # It seems that -bexpall does not export symbols beginning with # underscore (_), so it is better to generate a list of symbols to export. _LT_AC_TAGVAR(always_export_symbols, $1)=yes if test "$aix_use_runtimelinking" = yes; then # Warning - without using the other runtime loading flags (-brtl), # -berok will link without error, but may produce a broken library. _LT_AC_TAGVAR(allow_undefined_flag, $1)='-berok' # Determine the default libpath from the value encoded in an empty executable. _LT_AC_SYS_LIBPATH_AIX _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath" _LT_AC_TAGVAR(archive_expsym_cmds, $1)="\$CC"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then echo "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag" else if test "$host_cpu" = ia64; then _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R $libdir:/usr/lib:/lib' _LT_AC_TAGVAR(allow_undefined_flag, $1)="-z nodefs" _LT_AC_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols" else # Determine the default libpath from the value encoded in an empty executable. _LT_AC_SYS_LIBPATH_AIX _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath" # Warning - without using the other run time loading flags, # -berok will link without error, but may produce a broken library. _LT_AC_TAGVAR(no_undefined_flag, $1)=' ${wl}-bernotok' _LT_AC_TAGVAR(allow_undefined_flag, $1)=' ${wl}-berok' # Exported symbols can be pulled into shared objects from archives _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='$convenience' _LT_AC_TAGVAR(archive_cmds_need_lc, $1)=yes # This is similar to how AIX traditionally builds its shared libraries. _LT_AC_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname' fi fi ;; amigaos*) _LT_AC_TAGVAR(archive_cmds, $1)='$rm $output_objdir/a2ixlibrary.data~$echo "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$echo "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$echo "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$echo "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)' _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir' _LT_AC_TAGVAR(hardcode_minus_L, $1)=yes # see comment about different semantics on the GNU ld section _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; bsdi[[45]]*) _LT_AC_TAGVAR(export_dynamic_flag_spec, $1)=-rdynamic ;; cygwin* | mingw* | pw32*) # When not using gcc, we currently assume that we are using # Microsoft Visual C++. # hardcode_libdir_flag_spec is actually meaningless, as there is # no search path for DLLs. _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)=' ' _LT_AC_TAGVAR(allow_undefined_flag, $1)=unsupported # Tell ltmain to make .lib files, not .a files. libext=lib # Tell ltmain to make .dll files, not .so files. shrext_cmds=".dll" # FIXME: Setting linknames here is a bad hack. _LT_AC_TAGVAR(archive_cmds, $1)='$CC -o $lib $libobjs $compiler_flags `echo "$deplibs" | $SED -e '\''s/ -lc$//'\''` -link -dll~linknames=' # The linker will automatically build a .lib file if we build a DLL. _LT_AC_TAGVAR(old_archive_From_new_cmds, $1)='true' # FIXME: Should let the user specify the lib program. _LT_AC_TAGVAR(old_archive_cmds, $1)='lib -OUT:$oldlib$oldobjs$old_deplibs' _LT_AC_TAGVAR(fix_srcfile_path, $1)='`cygpath -w "$srcfile"`' _LT_AC_TAGVAR(enable_shared_with_static_runtimes, $1)=yes ;; darwin* | rhapsody*) case $host_os in rhapsody* | darwin1.[[012]]) _LT_AC_TAGVAR(allow_undefined_flag, $1)='${wl}-undefined ${wl}suppress' ;; *) # Darwin 1.3 on if test -z ${MACOSX_DEPLOYMENT_TARGET} ; then _LT_AC_TAGVAR(allow_undefined_flag, $1)='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' else case ${MACOSX_DEPLOYMENT_TARGET} in 10.[[012]]) _LT_AC_TAGVAR(allow_undefined_flag, $1)='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; 10.*) _LT_AC_TAGVAR(allow_undefined_flag, $1)='${wl}-undefined ${wl}dynamic_lookup' ;; esac fi ;; esac _LT_AC_TAGVAR(archive_cmds_need_lc, $1)=no _LT_AC_TAGVAR(hardcode_direct, $1)=no _LT_AC_TAGVAR(hardcode_automatic, $1)=yes _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=unsupported _LT_AC_TAGVAR(whole_archive_flag_spec, $1)='' _LT_AC_TAGVAR(link_all_deplibs, $1)=yes if test "$GCC" = yes ; then output_verbose_link_cmd='echo' _LT_AC_TAGVAR(archive_cmds, $1)="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}" _LT_AC_TAGVAR(module_cmds, $1)="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}" _LT_AC_TAGVAR(archive_expsym_cmds, $1)="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}" _LT_AC_TAGVAR(module_expsym_cmds, $1)="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}" else case $cc_basename in xlc*) output_verbose_link_cmd='echo' _LT_AC_TAGVAR(archive_cmds, $1)='$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}`echo $rpath/$soname` $xlcverstring' _LT_AC_TAGVAR(module_cmds, $1)='$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags' # Don't fix this by using the ld -exported_symbols_list flag, it doesn't exist in older darwin lds _LT_AC_TAGVAR(archive_expsym_cmds, $1)='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}$rpath/$soname $xlcverstring~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' _LT_AC_TAGVAR(module_expsym_cmds, $1)='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' ;; *) _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; esac fi ;; dgux*) _LT_AC_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' _LT_AC_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir' _LT_AC_TAGVAR(hardcode_shlibpath_var, $1)=no ;; freebsd1*) _LT_AC_TAGVAR(ld_shlibs, $1)=no ;; # FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor # support. 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You may want to install GNU tar or Free paxutils, or check the command line arguments." exit 1 ;; *) echo 1>&2 "\ WARNING: \`$1' is needed, and is $msg. You might have modified some files without having the proper tools for further handling them. Check the \`README' file, it often tells you about the needed prerequisites for installing this package. You may also peek at any GNU archive site, in case some other package would contain this missing \`$1' program." exit 1 ;; esac exit 0 # Local variables: # eval: (add-hook 'write-file-hooks 'time-stamp) # time-stamp-start: "scriptversion=" # time-stamp-format: "%:y-%02m-%02d.%02H" # time-stamp-end: "$" # End: minpack-19961126/lmstr.f0000644000175000017500000003702203226632012015612 0ustar sylvestresylvestre subroutine lmstr(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol, * maxfev,diag,mode,factor,nprint,info,nfev,njev, * ipvt,qtf,wa1,wa2,wa3,wa4) integer m,n,ldfjac,maxfev,mode,nprint,info,nfev,njev integer ipvt(n) logical sing double precision ftol,xtol,gtol,factor double precision x(n),fvec(m),fjac(ldfjac,n),diag(n),qtf(n), * wa1(n),wa2(n),wa3(n),wa4(m) c ********** c c subroutine lmstr c c the purpose of lmstr is to minimize the sum of the squares of c m nonlinear functions in n variables by a modification of c the levenberg-marquardt algorithm which uses minimal storage. c the user must provide a subroutine which calculates the c functions and the rows of the jacobian. c c the subroutine statement is c c subroutine lmstr(fcn,m,n,x,fvec,fjac,ldfjac,ftol,xtol,gtol, c maxfev,diag,mode,factor,nprint,info,nfev, c njev,ipvt,qtf,wa1,wa2,wa3,wa4) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the rows of the jacobian. c fcn must be declared in an external statement in the c user calling program, and should be written as follows. c c subroutine fcn(m,n,x,fvec,fjrow,iflag) c integer m,n,iflag c double precision x(n),fvec(m),fjrow(n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. c if iflag = i calculate the (i-1)-st row of the c jacobian at x and return this vector in fjrow. 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 lmstr. 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 fjac is an output n by n array. the upper triangle of fjac c contains an upper triangular matrix r such that c c t t t c p *(jac *jac)*p = r *r, c c where p is a permutation matrix and jac is the final c calculated jacobian. column j of p is column ipvt(j) c (see below) of the identity matrix. the lower triangular c part of fjac contains information generated during c the computation of r. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. c c ftol is a nonnegative input variable. termination c occurs when both the actual and predicted relative c reductions in the sum of squares are at most ftol. c therefore, ftol measures the relative error desired c in the sum of squares. c c xtol is a nonnegative input variable. termination c occurs when the relative error between two consecutive c iterates is at most xtol. therefore, xtol measures the c relative error desired in the approximate solution. c c gtol is a nonnegative input variable. termination c occurs when the cosine of the angle between fvec and c any column of the jacobian is at most gtol in absolute c value. therefore, gtol measures the orthogonality c desired between the function vector and the columns c of the jacobian. c c maxfev is a positive integer input variable. termination c occurs when the number of calls to fcn with iflag = 1 c has reached maxfev. c c diag is an array of length n. if mode = 1 (see c below), diag is internally set. if mode = 2, diag c must contain positive entries that serve as c multiplicative scale factors for the variables. c c mode is an integer input variable. if mode = 1, the c variables will be scaled internally. if mode = 2, c the scaling is specified by the input diag. other c values of mode are equivalent to mode = 1. c c factor is a positive input variable used in determining the c initial step bound. this bound is set to the product of c factor and the euclidean norm of diag*x if nonzero, or else c to factor itself. in most cases factor should lie in the c interval (.1,100.). 100. is a generally recommended value. c c nprint is an integer input variable that enables controlled c printing of iterates if it is positive. in this case, c fcn is called with iflag = 0 at the beginning of the first c iteration and every nprint iterations thereafter and c immediately prior to return, with x and fvec available c for printing. if nprint is not positive, no special calls c of fcn with iflag = 0 are made. 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 both actual and predicted relative reductions c in the sum of squares are at most ftol. c c info = 2 relative error between two consecutive iterates c is at most xtol. c c info = 3 conditions for info = 1 and info = 2 both hold. c c info = 4 the cosine of the angle between fvec and any c column of the jacobian is at most gtol in c absolute value. c c info = 5 number of calls to fcn with iflag = 1 has c reached maxfev. c c info = 6 ftol is too small. no further reduction in c the sum of squares is possible. c c info = 7 xtol is too small. no further improvement in c the approximate solution x is possible. c c info = 8 gtol is too small. fvec is orthogonal to the c columns of the jacobian to machine precision. c c nfev is an integer output variable set to the number of c calls to fcn with iflag = 1. c c njev is an integer output variable set to the number of c calls to fcn with iflag = 2. c c ipvt is an integer output array of length n. ipvt c defines a permutation matrix p such that jac*p = q*r, c where jac is the final calculated jacobian, q is c orthogonal (not stored), and r is upper triangular. c column j of p is column ipvt(j) of the identity matrix. c c qtf is an output array of length n which contains c the first n elements of the vector (q transpose)*fvec. c c wa1, wa2, and wa3 are work arrays of length n. c c wa4 is a work array of length m. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dpmpar,enorm,lmpar,qrfac,rwupdt c c fortran-supplied ... dabs,dmax1,dmin1,dsqrt,mod c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, dudley v. goetschel, kenneth e. hillstrom, c jorge j. more c c ********** integer i,iflag,iter,j,l double precision actred,delta,dirder,epsmch,fnorm,fnorm1,gnorm, * one,par,pnorm,prered,p1,p5,p25,p75,p0001,ratio, * sum,temp,temp1,temp2,xnorm,zero double precision dpmpar,enorm data one,p1,p5,p25,p75,p0001,zero * /1.0d0,1.0d-1,5.0d-1,2.5d-1,7.5d-1,1.0d-4,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c info = 0 iflag = 0 nfev = 0 njev = 0 c c check the input parameters for errors. c if (n .le. 0 .or. m .lt. n .or. ldfjac .lt. n * .or. ftol .lt. zero .or. xtol .lt. zero .or. gtol .lt. zero * .or. maxfev .le. 0 .or. factor .le. zero) go to 340 if (mode .ne. 2) go to 20 do 10 j = 1, n if (diag(j) .le. zero) go to 340 10 continue 20 continue c c evaluate the function at the starting point c and calculate its norm. c iflag = 1 call fcn(m,n,x,fvec,wa3,iflag) nfev = 1 if (iflag .lt. 0) go to 340 fnorm = enorm(m,fvec) c c initialize levenberg-marquardt parameter and iteration counter. c par = zero iter = 1 c c beginning of the outer loop. c 30 continue c c if requested, call fcn to enable printing of iterates. c if (nprint .le. 0) go to 40 iflag = 0 if (mod(iter-1,nprint) .eq. 0) call fcn(m,n,x,fvec,wa3,iflag) if (iflag .lt. 0) go to 340 40 continue c c compute the qr factorization of the jacobian matrix c calculated one row at a time, while simultaneously c forming (q transpose)*fvec and storing the first c n components in qtf. c do 60 j = 1, n qtf(j) = zero do 50 i = 1, n fjac(i,j) = zero 50 continue 60 continue iflag = 2 do 70 i = 1, m call fcn(m,n,x,fvec,wa3,iflag) if (iflag .lt. 0) go to 340 temp = fvec(i) call rwupdt(n,fjac,ldfjac,wa3,qtf,temp,wa1,wa2) iflag = iflag + 1 70 continue njev = njev + 1 c c if the jacobian is rank deficient, call qrfac to c reorder its columns and update the components of qtf. c sing = .false. do 80 j = 1, n if (fjac(j,j) .eq. zero) sing = .true. ipvt(j) = j wa2(j) = enorm(j,fjac(1,j)) 80 continue if (.not.sing) go to 130 call qrfac(n,n,fjac,ldfjac,.true.,ipvt,n,wa1,wa2,wa3) do 120 j = 1, n if (fjac(j,j) .eq. zero) go to 110 sum = zero do 90 i = j, n sum = sum + fjac(i,j)*qtf(i) 90 continue temp = -sum/fjac(j,j) do 100 i = j, n qtf(i) = qtf(i) + fjac(i,j)*temp 100 continue 110 continue fjac(j,j) = wa1(j) 120 continue 130 continue c c on the first iteration and if mode is 1, scale according c to the norms of the columns of the initial jacobian. c if (iter .ne. 1) go to 170 if (mode .eq. 2) go to 150 do 140 j = 1, n diag(j) = wa2(j) if (wa2(j) .eq. zero) diag(j) = one 140 continue 150 continue c c on the first iteration, calculate the norm of the scaled x c and initialize the step bound delta. c do 160 j = 1, n wa3(j) = diag(j)*x(j) 160 continue xnorm = enorm(n,wa3) delta = factor*xnorm if (delta .eq. zero) delta = factor 170 continue c c compute the norm of the scaled gradient. c gnorm = zero if (fnorm .eq. zero) go to 210 do 200 j = 1, n l = ipvt(j) if (wa2(l) .eq. zero) go to 190 sum = zero do 180 i = 1, j sum = sum + fjac(i,j)*(qtf(i)/fnorm) 180 continue gnorm = dmax1(gnorm,dabs(sum/wa2(l))) 190 continue 200 continue 210 continue c c test for convergence of the gradient norm. c if (gnorm .le. gtol) info = 4 if (info .ne. 0) go to 340 c c rescale if necessary. c if (mode .eq. 2) go to 230 do 220 j = 1, n diag(j) = dmax1(diag(j),wa2(j)) 220 continue 230 continue c c beginning of the inner loop. c 240 continue c c determine the levenberg-marquardt parameter. c call lmpar(n,fjac,ldfjac,ipvt,diag,qtf,delta,par,wa1,wa2, * wa3,wa4) c c store the direction p and x + p. calculate the norm of p. c do 250 j = 1, n wa1(j) = -wa1(j) wa2(j) = x(j) + wa1(j) wa3(j) = diag(j)*wa1(j) 250 continue pnorm = enorm(n,wa3) c c on the first iteration, adjust the initial step bound. c if (iter .eq. 1) delta = dmin1(delta,pnorm) c c evaluate the function at x + p and calculate its norm. c iflag = 1 call fcn(m,n,wa2,wa4,wa3,iflag) nfev = nfev + 1 if (iflag .lt. 0) go to 340 fnorm1 = enorm(m,wa4) c c compute the scaled actual reduction. c actred = -one if (p1*fnorm1 .lt. fnorm) actred = one - (fnorm1/fnorm)**2 c c compute the scaled predicted reduction and c the scaled directional derivative. c do 270 j = 1, n wa3(j) = zero l = ipvt(j) temp = wa1(l) do 260 i = 1, j wa3(i) = wa3(i) + fjac(i,j)*temp 260 continue 270 continue temp1 = enorm(n,wa3)/fnorm temp2 = (dsqrt(par)*pnorm)/fnorm prered = temp1**2 + temp2**2/p5 dirder = -(temp1**2 + temp2**2) c c compute the ratio of the actual to the predicted c reduction. c ratio = zero if (prered .ne. zero) ratio = actred/prered c c update the step bound. c if (ratio .gt. p25) go to 280 if (actred .ge. zero) temp = p5 if (actred .lt. zero) * temp = p5*dirder/(dirder + p5*actred) if (p1*fnorm1 .ge. fnorm .or. temp .lt. p1) temp = p1 delta = temp*dmin1(delta,pnorm/p1) par = par/temp go to 300 280 continue if (par .ne. zero .and. ratio .lt. p75) go to 290 delta = pnorm/p5 par = p5*par 290 continue 300 continue c c test for successful iteration. c if (ratio .lt. p0001) go to 330 c c successful iteration. update x, fvec, and their norms. c do 310 j = 1, n x(j) = wa2(j) wa2(j) = diag(j)*x(j) 310 continue do 320 i = 1, m fvec(i) = wa4(i) 320 continue xnorm = enorm(n,wa2) fnorm = fnorm1 iter = iter + 1 330 continue c c tests for convergence. c if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one) info = 1 if (delta .le. xtol*xnorm) info = 2 if (dabs(actred) .le. ftol .and. prered .le. ftol * .and. p5*ratio .le. one .and. info .eq. 2) info = 3 if (info .ne. 0) go to 340 c c tests for termination and stringent tolerances. c if (nfev .ge. maxfev) info = 5 if (dabs(actred) .le. epsmch .and. prered .le. epsmch * .and. p5*ratio .le. one) info = 6 if (delta .le. epsmch*xnorm) info = 7 if (gnorm .le. epsmch) info = 8 if (info .ne. 0) go to 340 c c end of the inner loop. repeat if iteration unsuccessful. c if (ratio .lt. p0001) go to 240 c c end of the outer loop. c go to 30 340 continue c c termination, either normal or user imposed. c if (iflag .lt. 0) info = iflag iflag = 0 if (nprint .gt. 0) call fcn(m,n,x,fvec,wa3,iflag) return c c last card of subroutine lmstr. c end minpack-19961126/config.h.in0000644000175000017500000000036411616327304016333 0ustar sylvestresylvestre/* config.h.in. Generated automatically from configure.in by autoheader 2.13. */ /* Define if you have the header file. */ #undef HAVE_DLFCN_H /* Name of package */ #undef PACKAGE /* Version number of package */ #undef VERSION minpack-19961126/ex/0000755000175000017500000000000011616327304014721 5ustar sylvestresylvestreminpack-19961126/ex/tlmder1.f0000644000175000017500000000432411616327304016443 0ustar sylvestresylvestreC DRIVER FOR LMDER1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),WA(30) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDER1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file230000644000175000017500000000024504210375534015731 0ustar sylvestresylvestre 1 2 2 4 3 2 4 4 5 3 6 9 7 7 8 10 9 10 10 10 11 10 12 10 13 10 14 10 0 0 minpack-19961126/ex/file200000644000175000017500000005470504210375337015741 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS THE ABILITY OF CHKDER TO DETECT C INCONSISTENCIES BETWEEN FUNCTIONS AND THEIR FIRST DERIVATIVES. C FOURTEEN TEST FUNCTION VECTORS AND JACOBIANS ARE USED. ELEVEN OF C THE TESTS ARE FALSE(F), I.E. THERE ARE INCONSISTENCIES BETWEEN C THE FUNCTION VECTORS AND THE CORRESPONDING JACOBIANS. THREE OF C THE TESTS ARE TRUE(T), I.E. THERE ARE NO INCONSISTENCIES. THE C DRIVER READS IN DATA, CALLS CHKDER AND PRINTS OUT INFORMATION C REQUIRED BY AND RECEIVED FROM CHKDER. C C SUBPROGRAMS CALLED C C MINPACK SUPPLIED ... CHKDER,ERRJAC,INITPT,VECFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,LDFJAC,LNP,MODE,N,NPROB,NREAD,NWRITE INTEGER NA(14),NP(14) LOGICAL A(14) DOUBLE PRECISION CP,ONE DOUBLE PRECISION DIFF(10),ERR(10),ERRMAX(14),ERRMIN(14), * FJAC(10,10),FVEC1(10),FVEC2(10),X1(10),X2(10) C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA A(1),A(2),A(3),A(4),A(5),A(6),A(7),A(8),A(9),A(10),A(11), * A(12),A(13),A(14) * /.FALSE.,.FALSE.,.FALSE.,.TRUE.,.FALSE.,.FALSE.,.FALSE., * .TRUE.,.FALSE.,.FALSE.,.FALSE.,.FALSE.,.TRUE.,.FALSE./ DATA CP,ONE /1.23D-1,1.0D0/ LDFJAC = 10 10 CONTINUE READ (NREAD,60) NPROB,N IF (NPROB .LE. 0) GO TO 40 CALL INITPT(N,X1,NPROB,ONE) DO 20 I = 1, N X1(I) = X1(I) + CP CP = -CP 20 CONTINUE WRITE (NWRITE,70) NPROB,N,A(NPROB) MODE = 1 CALL CHKDER(N,N,X1,FVEC1,FJAC,LDFJAC,X2,FVEC2,MODE,ERR) MODE = 2 CALL VECFCN(N,X1,FVEC1,NPROB) CALL ERRJAC(N,X1,FJAC,LDFJAC,NPROB) CALL VECFCN(N,X2,FVEC2,NPROB) CALL CHKDER(N,N,X1,FVEC1,FJAC,LDFJAC,X2,FVEC2,MODE,ERR) ERRMIN(NPROB) = ERR(1) ERRMAX(NPROB) = ERR(1) DO 30 I = 1, N DIFF(I) = FVEC2(I) - FVEC1(I) IF (ERRMIN(NPROB) .GT. ERR(I)) ERRMIN(NPROB) = ERR(I) IF (ERRMAX(NPROB) .LT. ERR(I)) ERRMAX(NPROB) = ERR(I) 30 CONTINUE NP(NPROB) = NPROB LNP = NPROB NA(NPROB) = N WRITE (NWRITE,80) (FVEC1(I), I = 1, N) WRITE (NWRITE,90) (DIFF(I), I = 1, N) WRITE (NWRITE,100) (ERR(I), I = 1, N) GO TO 10 40 CONTINUE WRITE (NWRITE,110) LNP WRITE (NWRITE,120) DO 50 I = 1, LNP WRITE (NWRITE,130) NP(I),NA(I),A(I),ERRMIN(I),ERRMAX(I) 50 CONTINUE STOP 60 FORMAT (2I5) 70 FORMAT ( /// 5X, 8H PROBLEM, I5, 5X, 15H WITH DIMENSION, I5, 2X, * 5H IS , L1) 80 FORMAT ( // 5X, 25H FIRST FUNCTION VECTOR // (5X, 5D15.7)) 90 FORMAT ( // 5X, 27H FUNCTION DIFFERENCE VECTOR // (5X, 5D15.7)) 100 FORMAT ( // 5X, 13H ERROR VECTOR // (5X, 5D15.7)) 110 FORMAT (12H1SUMMARY OF , I3, 16H TESTS OF CHKDER /) 120 FORMAT (46H NPROB N STATUS ERRMIN ERRMAX /) 130 FORMAT (I4, I6, 6X, L1, 3X, 2D15.7) C C LAST CARD OF DERIVATIVE CHECK TEST DRIVER. C END SUBROUTINE ERRJAC(N,X,FJAC,LDFJAC,NPROB) INTEGER N,LDFJAC,NPROB DOUBLE PRECISION X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE ERRJAC C C THIS SUBROUTINE IS DERIVED FROM VECJAC WHICH DEFINES THE C JACOBIAN MATRICES OF FOURTEEN TEST FUNCTIONS. THE PROBLEM C DIMENSIONS ARE AS DESCRIBED IN THE PROLOGUE COMMENTS OF VECFCN. C VARIOUS ERRORS ARE DELIBERATELY INTRODUCED TO PROVIDE A TEST C FOR CHKDER. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE ERRJAC(N,X,FJAC,LDFJAC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER VARIABLE. C C X IS AN ARRAY OF LENGTH N. C C FJAC IS AN N BY N ARRAY. ON OUTPUT FJAC CONTAINS THE C JACOBIAN MATRIX, WITH VARIOUS ERRORS DELIBERATELY C INTRODUCED, OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DMIN1,DSIN,DSQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,K1,K2,ML,MU DOUBLE PRECISION C1,C3,C4,C5,C6,C9,EIGHT,FIFTN,FIVE,FOUR,H, * HUNDRD,ONE,PROD,SIX,SUM,SUM1,SUM2,TEMP,TEMP1, * TEMP2,TEMP3,TEMP4,TEN,THREE,TI,TJ,TK,TPI, * TWENTY,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,SIX,EIGHT,TEN,FIFTN,TWENTY, * HUNDRD * /0.0D0,1.0D0,2.0D0,3.0D0,4.0D0,5.0D0,6.0D0,8.0D0,1.0D1, * 1.5D1,2.0D1,1.0D2/ DATA C1,C3,C4,C5,C6,C9 /1.0D4,2.0D2,2.02D1,1.98D1,1.8D2,2.9D1/ DFLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,20,50,60,90,100,200,230,290,320,350,380,420,450), * NPROB C C ROSENBROCK FUNCTION WITH SIGN REVERSAL AFFECTING ELEMENT (1,1). C 10 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = ZERO FJAC(2,1) = -TWENTY*X(1) FJAC(2,2) = TEN GO TO 490 C C POWELL SINGULAR FUNCTION WITH SIGN REVERSAL AFFECTING ELEMENT C (3,3). C 20 CONTINUE DO 40 K = 1, 4 DO 30 J = 1, 4 FJAC(K,J) = ZERO 30 CONTINUE 40 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = DSQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = TWO*FJAC(3,2) FJAC(4,1) = TWO*DSQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 490 C C POWELL BADLY SCALED FUNCTION WITH THE SIGN OF THE JACOBIAN C REVERSED. C 50 CONTINUE FJAC(1,1) = -C1*X(2) FJAC(1,2) = -C1*X(1) FJAC(2,1) = DEXP(-X(1)) FJAC(2,2) = DEXP(-X(2)) GO TO 490 C C WOOD FUNCTION WITHOUT ERROR. C 60 CONTINUE DO 80 K = 1, 4 DO 70 J = 1, 4 FJAC(K,J) = ZERO 70 CONTINUE 80 CONTINUE TEMP1 = X(2) - THREE*X(1)**2 TEMP2 = X(4) - THREE*X(3)**2 FJAC(1,1) = -C3*TEMP1 + ONE FJAC(1,2) = -C3*X(1) FJAC(2,1) = -TWO*C3*X(1) FJAC(2,2) = C3 + C4 FJAC(2,4) = C5 FJAC(3,3) = -C6*TEMP2 + ONE FJAC(3,4) = -C6*X(3) FJAC(4,2) = C5 FJAC(4,3) = -TWO*C6*X(3) FJAC(4,4) = C6 + C4 GO TO 490 C C HELICAL VALLEY FUNCTION WITH MULTIPLICATIVE ERROR AFFECTING C ELEMENTS (2,1) AND (2,2). C 90 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP = X(1)**2 + X(2)**2 TEMP1 = TPI*TEMP TEMP2 = DSQRT(TEMP) FJAC(1,1) = HUNDRD*X(2)/TEMP1 FJAC(1,2) = -HUNDRD*X(1)/TEMP1 FJAC(1,3) = TEN FJAC(2,1) = FIVE*X(1)/TEMP2 FJAC(2,2) = FIVE*X(2)/TEMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 490 C C WATSON FUNCTION WITH SIGN REVERSALS AFFECTING THE COMPUTATION OF C TEMP1. C 100 CONTINUE DO 120 K = 1, N DO 110 J = K, N FJAC(K,J) = ZERO 110 CONTINUE 120 CONTINUE DO 170 I = 1, 29 TI = DFLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 130 J = 2, N SUM1 = SUM1 + DFLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 130 CONTINUE SUM2 = ZERO TEMP = ONE DO 140 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 140 CONTINUE TEMP1 = TWO*(SUM1 + SUM2**2 + ONE) TEMP2 = TWO*SUM2 TEMP = TI**2 TK = ONE DO 160 K = 1, N TJ = TK DO 150 J = K, N FJAC(K,J) = FJAC(K,J) * + TJ * *((DFLOAT(K-1)/TI - TEMP2) * *(DFLOAT(J-1)/TI - TEMP2) - TEMP1) TJ = TI*TJ 150 CONTINUE TK = TEMP*TK 160 CONTINUE 170 CONTINUE FJAC(1,1) = FJAC(1,1) + SIX*X(1)**2 - TWO*X(2) + THREE FJAC(1,2) = FJAC(1,2) - TWO*X(1) FJAC(2,2) = FJAC(2,2) + ONE DO 190 K = 1, N DO 180 J = K, N FJAC(J,K) = FJAC(K,J) 180 CONTINUE 190 CONTINUE GO TO 490 C C CHEBYQUAD FUNCTION WITH JACOBIAN TWICE CORRECT SIZE. C 200 CONTINUE TK = ONE/DFLOAT(N) DO 220 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 TEMP3 = ZERO TEMP4 = TWO DO 210 K = 1, N FJAC(K,J) = TWO*TK*TEMP4 TI = FOUR*TEMP2 + TEMP*TEMP4 - TEMP3 TEMP3 = TEMP4 TEMP4 = TI TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 210 CONTINUE 220 CONTINUE GO TO 490 C C BROWN ALMOST-LINEAR FUNCTION WITHOUT ERROR. C 230 CONTINUE PROD = ONE DO 250 J = 1, N PROD = X(J)*PROD DO 240 K = 1, N FJAC(K,J) = ONE 240 CONTINUE FJAC(J,J) = TWO 250 CONTINUE DO 280 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 270 TEMP = ONE PROD = ONE DO 260 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 260 CONTINUE 270 CONTINUE FJAC(N,J) = PROD/TEMP 280 CONTINUE GO TO 490 C C DISCRETE BOUNDARY VALUE FUNCTION WITH MULTIPLICATIVE ERROR C AFFECTING THE JACOBIAN DIAGONAL. C 290 CONTINUE H = ONE/DFLOAT(N+1) DO 310 K = 1, N TEMP = THREE*(X(K) + DFLOAT(K)*H + ONE)**2 DO 300 J = 1, N FJAC(K,J) = ZERO 300 CONTINUE FJAC(K,K) = FOUR + TEMP*H**2 IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -ONE 310 CONTINUE GO TO 490 C C DISCRETE INTEGRAL EQUATION FUNCTION WITH SIGN ERROR AFFECTING C THE JACOBIAN DIAGONAL. C 320 CONTINUE H = ONE/DFLOAT(N+1) DO 340 K = 1, N TK = DFLOAT(K)*H DO 330 J = 1, N TJ = DFLOAT(J)*H TEMP = THREE*(X(J) + TJ + ONE)**2 FJAC(K,J) = H*DMIN1(TJ*(ONE-TK),TK*(ONE-TJ))*TEMP/TWO 330 CONTINUE FJAC(K,K) = FJAC(K,K) - ONE 340 CONTINUE GO TO 490 C C TRIGONOMETRIC FUNCTION WITH SIGN ERRORS AFFECTING THE C OFFDIAGONAL ELEMENTS OF THE JACOBIAN. C 350 CONTINUE DO 370 J = 1, N TEMP = DSIN(X(J)) DO 360 K = 1, N FJAC(K,J) = -TEMP 360 CONTINUE FJAC(J,J) = DFLOAT(J+1)*TEMP - DCOS(X(J)) 370 CONTINUE GO TO 490 C C VARIABLY DIMENSIONED FUNCTION WITH OPERATION ERROR AFFECTING C THE UPPER TRIANGULAR ELEMENTS OF THE JACOBIAN. C 380 CONTINUE SUM = ZERO DO 390 J = 1, N SUM = SUM + DFLOAT(J)*(X(J) - ONE) 390 CONTINUE TEMP = ONE + SIX*SUM**2 DO 410 K = 1, N DO 400 J = K, N FJAC(K,J) = DFLOAT(K*J)/TEMP FJAC(J,K) = FJAC(K,J) 400 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 410 CONTINUE GO TO 490 C C BROYDEN TRIDIAGONAL FUNCTION WITHOUT ERROR. C 420 CONTINUE DO 440 K = 1, N DO 430 J = 1, N FJAC(K,J) = ZERO 430 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 440 CONTINUE GO TO 490 C C BROYDEN BANDED FUNCTION WITH SIGN ERROR AFFECTING THE JACOBIAN C DIAGONAL. C 450 CONTINUE ML = 5 MU = 1 DO 480 K = 1, N DO 460 J = 1, N FJAC(K,J) = ZERO 460 CONTINUE K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) DO 470 J = K1, K2 IF (J .NE. K) FJAC(K,J) = -(ONE + TWO*X(J)) 470 CONTINUE FJAC(K,K) = TWO - FIFTN*X(K)**2 480 CONTINUE 490 CONTINUE RETURN C C LAST CARD OF SUBROUTINE ERRJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,H,HALF,ONE,THREE,TJ,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0D0,5.0D-1,1.0D0,3.0D0,1.2D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/DFLOAT(N+1) DO 90 J = 1, N X(J) = DFLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/DFLOAT(N+1) DO 130 J = 1, N TJ = DFLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/DFLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/DFLOAT(N) DO 170 J = 1, N X(J) = ONE - DFLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB DOUBLE PRECISION X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIGN,DSIN,DSQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE, * PROD,SUM,SUM1,SUM2,TEMP,TEMP1,TEMP2,TEN,THREE, * TI,TJ,TK,TPI,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0D0,1.0D0,2.0D0,3.0D0,5.0D0,8.0D0,1.0D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0D4,1.0001D0,2.0D2,2.02D1,1.98D1,1.8D2,2.5D-1,5.0D-1, * 2.9D1/ DFLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = DEXP(-X(1)) + DEXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP1 = DSIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI + C8 TEMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = DFLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + DFLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(DFLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/DFLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(DFLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/DFLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + DFLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/DFLOAT(N+1) DO 260 K = 1, N TK = DFLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = DCOS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = DFLOAT(N+K) - DSIN(X(K)) - SUM - DFLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + DFLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + DFLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END minpack-19961126/ex/file010000644000175000017500000001051304210374273015723 0ustar sylvestresylvestre REAL FUNCTION SPMPAR(I) INTEGER I C ********** C C FUNCTION SPMPAR C C THIS FUNCTION PROVIDES SINGLE PRECISION MACHINE PARAMETERS C WHEN THE APPROPRIATE SET OF DATA STATEMENTS IS ACTIVATED (BY C REMOVING THE C FROM COLUMN 1) AND ALL OTHER DATA STATEMENTS ARE C RENDERED INACTIVE. MOST OF THE PARAMETER VALUES WERE OBTAINED C FROM THE CORRESPONDING BELL LABORATORIES PORT LIBRARY FUNCTION. C C THE FUNCTION STATEMENT IS C C REAL FUNCTION SPMPAR(I) C C WHERE C C I IS AN INTEGER INPUT VARIABLE SET TO 1, 2, OR 3 WHICH C SELECTS THE DESIRED MACHINE PARAMETER. IF THE MACHINE HAS C T BASE B DIGITS AND ITS SMALLEST AND LARGEST EXPONENTS ARE C EMIN AND EMAX, RESPECTIVELY, THEN THESE PARAMETERS ARE C C SPMPAR(1) = B**(1 - T), THE MACHINE PRECISION, C C SPMPAR(2) = B**(EMIN - 1), THE SMALLEST MAGNITUDE, C C SPMPAR(3) = B**EMAX*(1 - B**(-T)), THE LARGEST MAGNITUDE. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER MCHEPS(2) INTEGER MINMAG(2) INTEGER MAXMAG(2) REAL RMACH(3) EQUIVALENCE (RMACH(1),MCHEPS(1)) EQUIVALENCE (RMACH(2),MINMAG(1)) EQUIVALENCE (RMACH(3),MAXMAG(1)) C C MACHINE CONSTANTS FOR THE IBM 360/370 SERIES, C THE AMDAHL 470/V6, THE ICL 2900, THE ITEL AS/6, C THE XEROX SIGMA 5/7/9 AND THE SEL SYSTEMS 85/86. C DATA RMACH(1) / Z3C100000 / DATA RMACH(2) / Z00100000 / DATA RMACH(3) / Z7FFFFFFF / C C MACHINE CONSTANTS FOR THE HONEYWELL 600/6000 SERIES. C C DATA RMACH(1) / O716400000000 / C DATA RMACH(2) / O402400000000 / C DATA RMACH(3) / O376777777777 / C C MACHINE CONSTANTS FOR THE CDC 6000/7000 SERIES. C C DATA RMACH(1) / 16414000000000000000B / C DATA RMACH(2) / 00014000000000000000B / C DATA RMACH(3) / 37767777777777777777B / C C MACHINE CONSTANTS FOR THE PDP-10 (KA OR KI PROCESSOR). C C DATA RMACH(1) / "147400000000 / C DATA RMACH(2) / "000400000000 / C DATA RMACH(3) / "377777777777 / C C MACHINE CONSTANTS FOR THE PDP-11 FORTRAN SUPPORTING C 32-BIT INTEGERS (EXPRESSED IN INTEGER AND OCTAL). C C DATA MCHEPS(1) / 889192448 / C DATA MINMAG(1) / 8388608 / C DATA MAXMAG(1) / 2147483647 / C C DATA RMACH(1) / O06500000000 / C DATA RMACH(2) / O00040000000 / C DATA RMACH(3) / O17777777777 / C C MACHINE CONSTANTS FOR THE PDP-11 FORTRAN SUPPORTING C 16-BIT INTEGERS (EXPRESSED IN INTEGER AND OCTAL). C C DATA MCHEPS(1),MCHEPS(2) / 13568, 0 / C DATA MINMAG(1),MINMAG(2) / 128, 0 / C DATA MAXMAG(1),MAXMAG(2) / 32767, -1 / C C DATA MCHEPS(1),MCHEPS(2) / O032400, O000000 / C DATA MINMAG(1),MINMAG(2) / O000200, O000000 / C DATA MAXMAG(1),MAXMAG(2) / O077777, O177777 / C C MACHINE CONSTANTS FOR THE BURROUGHS 5700/6700/7700 SYSTEMS. C C DATA RMACH(1) / O1301000000000000 / C DATA RMACH(2) / O1771000000000000 / C DATA RMACH(3) / O0777777777777777 / C C MACHINE CONSTANTS FOR THE BURROUGHS 1700 SYSTEM. C C DATA RMACH(1) / Z4EA800000 / C DATA RMACH(2) / Z400800000 / C DATA RMACH(3) / Z5FFFFFFFF / C C MACHINE CONSTANTS FOR THE UNIVAC 1100 SERIES. C C DATA RMACH(1) / O147400000000 / C DATA RMACH(2) / O000400000000 / C DATA RMACH(3) / O377777777777 / C C MACHINE CONSTANTS FOR THE DATA GENERAL ECLIPSE S/200. C C NOTE - IT MAY BE APPROPRIATE TO INCLUDE THE FOLLOWING CARD - C STATIC RMACH(3) C C DATA MINMAG/20K,0/,MAXMAG/77777K,177777K/ C DATA MCHEPS/36020K,0/ C C MACHINE CONSTANTS FOR THE HARRIS 220. C C DATA MCHEPS(1) / '20000000, '00000353 / C DATA MINMAG(1) / '20000000, '00000201 / C DATA MAXMAG(1) / '37777777, '00000177 / C C MACHINE CONSTANTS FOR THE CRAY-1. C C DATA RMACH(1) / 0377224000000000000000B / C DATA RMACH(2) / 0200034000000000000000B / C DATA RMACH(3) / 0577777777777777777776B / C C MACHINE CONSTANTS FOR THE PRIME 400. C C DATA MCHEPS(1) / :10000000153 / C DATA MINMAG(1) / :10000000000 / C DATA MAXMAG(1) / :17777777777 / C C MACHINE CONSTANTS FOR THE VAX-11. C C DATA MCHEPS(1) / 13568 / C DATA MINMAG(1) / 128 / C DATA MAXMAG(1) / -32769 / C SPMPAR = RMACH(I) RETURN C C LAST CARD OF FUNCTION SPMPAR. C END minpack-19961126/ex/file210000644000175000017500000000056004210375425015726 0ustar sylvestresylvestre 1 2 3 2 4 3 3 2 2 4 4 3 5 3 3 6 6 2 6 9 2 7 5 3 7 6 3 7 7 3 7 8 1 7 9 1 8 10 3 8 30 1 8 40 1 9 10 3 10 1 3 10 10 3 11 10 3 12 10 3 13 10 3 14 10 3 0 0 0 minpack-19961126/ex/file030000644000175000017500000050426204210374456015741 0ustar sylvestresylvestre1 0 Page 0 Documentation for MINPACK subroutine HYBRD1 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of HYBRD1 is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. This is done by using the more general nonlinea equation solver HYBRD. The user must provide a subroutine whic calculates the functions. The Jacobian is then calculated by a forward-difference approximation. 0 2. Subroutine and type statements. 0 SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) INTEGER N,INFO,LWA REAL TOL REAL X(N),FVEC(N),WA(LWA) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to HYBRD1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRD1. 0 FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows 0 SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG REAL X(N),FVEC(N) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of HYBRD1. In this case se IFLAG to a negative integer. 1 0 Page 0 N is a positive integer input variable set to the number of functions and variables. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length N which contains the function evaluated at the output X. 0 TOL is a nonnegative input variable. Termination occurs when the algorithm estimates that the relative error between X and the solution is at most TOL. Section 4 contains more details about TOL. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Algorithm estimates that the relative error between X and the solution is at most TOL. 0 INFO = 2 Number of calls to FCN has reached or exceeded 200*(N+1). 0 INFO = 3 TOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 4 Iteration is not making good progress. 0 Sections 4 and 5 contain more details about INFO. 0 WA is a work array of length LWA. 0 LWA is a positive integer input variable not less than (N*(3*N+13))/2. 0 4. Successful completion. 0 The accuracy of HYBRD1 is controlled by the convergence parame- ter TOL. This parameter is used in a test which makes a compar ison between the approximation X and a solution XSOL. HYBRD1 terminates when the test is satisfied. If TOL is less than the machine precision (as defined by the MINPACK function SPMPAR(1)), then HYBRD1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. 0 The test assumes that the functions are reasonably well behaved 1 0 Page 0 If this condition is not satisfied, then HYBRD1 may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning HYBRD1 with a tighter toler- ance. 0 Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(X-XSOL) .LE. TOL*ENORM(XSOL). 0 If this condition is satisfied with TOL = 10**(-K), then the larger components of X have K significant decimal digits and INFO is set to 1. There is a danger that the smaller compo- nents of X may have large relative errors, but the fast rate of convergence of HYBRD1 usually avoids this possibility. 0 5. Unsuccessful completion. 0 Unsuccessful termination of HYBRD1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, errors in the functions, or lack of good prog ress. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or TOL .LT. 0.E0, or LWA .LT. (N*(3*N+13))/2. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRD1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead HYBRD, which includes in its calling sequence the step-length- governing parameter FACTOR. 0 Excessive number of function evaluations. If the number of calls to FCN reaches 200*(N+1), then this indicates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 2. This situation should be unu- sual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRD1, causing termination with INFO = 4. 0 Errors in the functions. The choice of step length in the for- ward-difference approximation to the Jacobian assumes that th relative errors in the functions are of the order of the machine precision. If this is not the case, HYBRD1 may fail (usually with INFO = 4). The user should then use HYBRD instead, or one of the programs which require the analytic Jacobian (HYBRJ1 and HYBRJ). 1 0 Page 0 Lack of good progress. HYBRD1 searches for a zero of the syste by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRD1 from a dif- ferent starting point may be helpful. 0 6. Characteristics of the algorithm. 0 HYBRD1 is a modification of the Powell hybrid method. Two of its main characteristics involve the choice of the correction a a convex combination of the Newton and scaled gradient direc- tions, and the updating of the Jacobian by the rank-1 method of Broyden. The choice of the correction guarantees (under reason able conditions) global convergence for starting points far fro the solution and a fast rate of convergence. The Jacobian is approximated by forward differences at the starting point, but forward differences are not used again until the rank-1 method fails to produce satisfactory progress. 0 Timing. The time required by HYBRD1 to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRD1 is about 11.5*(N**2) to process each call to FCN. Unless FCN can be evaluated quickly, the timing of HYBRD1 will be strongly influenced by the time spen in FCN. 0 Storage. HYBRD1 requires (3*N**2 + 17*N)/2 single precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... DOGLEG,SPMPAR,ENORM,FDJAC1,HYBRD, QFORM,QRFAC,R1MPYQ,R1UPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MIN0,MOD 0 8. References. 0 M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 0 9. Example. 1 0 Page 0 The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations 0 (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 0 C ********** C C DRIVER FOR HYBRD1 EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,N,INFO,LWA,NWRITE REAL TOL,FNORM REAL X(9),FVEC(9),WA(180) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.E0 10 CONTINUE C LWA = 180 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = SQRT(SPMPAR(1)) C CALL HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3E15.7)) C C LAST CARD OF DRIVER FOR HYBRD1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG REAL X(N),FVEC(N) C 1 0 Page 0 C SUBROUTINE FCN FOR HYBRD1 EXAMPLE. C INTEGER K REAL ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.E0,1.E0,2.E0,3.E0/ C DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.1192636E-07 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 -0.5706545E+00 -0.6816283E+00 -0.7017325E+00 -0.7042129E+00 -0.7013690E+00 -0.6918656E+00 -0.6657920E+00 -0.5960342E+00 -0.4164121E+00 1 0 1 0 Page 0 Documentation for MINPACK subroutine HYBRD 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of HYBRD is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. The user must provide a subroutine which calcu- lates the functions. The Jacobian is then calculated by a for- ward-difference approximation. 0 2. Subroutine and type statements. 0 SUBROUTINE HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * R,LR,QTF,WA1,WA2,WA3,WA4) INTEGER N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR REAL XTOL,EPSFCN,FACTOR REAL X(N),FVEC(N),DIAG(N),FJAC(LDFJAC,N),R(LR),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(N) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to HYBRD and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRD. 0 FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows 0 SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG REAL X(N),FVEC(N) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END 0 The value of IFLAG should not be changed by FCN unless the 1 0 Page 0 user wants to terminate execution of HYBRD. In this case set IFLAG to a negative integer. 0 N is a positive integer input variable set to the number of functions and variables. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length N which contains the function evaluated at the output X. 0 XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at mos XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. 0 MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN is at least MAXFEV by the end of an iteration. 0 ML is a nonnegative integer input variable which specifies the number of subdiagonals within the band of the Jacobian matrix If the Jacobian is not banded, set ML to at least N - 1. 0 MU is a nonnegative integer input variable which specifies the number of superdiagonals within the band of the Jacobian matrix. If the Jacobian is not banded, set MU to at least N - 1. 0 EPSFCN is an input variable used in determining a suitable step for the forward-difference approximation. This approximation assumes that the relative errors in the functions are of the order of EPSFCN. If EPSFCN is less than the machine preci- sion, it is assumed that the relative errors in the functions are of the order of the machine precision. 0 DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. 0 MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. 0 FACTOR is a positive input variable used in determining the ini tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. 1 0 Page 0 NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Relative error between two consecutive iterates is at most XTOL. 0 INFO = 2 Number of calls to FCN has reached or exceeded MAXFEV. 0 INFO = 3 XTOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 4 Iteration is not making good progress, as measured by the improvement from the last five Jacobian eval uations. 0 INFO = 5 Iteration is not making good progress, as measured by the improvement from the last ten iterations. 0 Sections 4 and 5 contain more details about INFO. 0 NFEV is an integer output variable set to the number of calls t FCN. 0 FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx imate Jacobian. 0 LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. 0 R is an output array of length LR which contains the upper triangular matrix produced by the QR factorization of the final approximate Jacobian, stored rowwise. 0 LR is a positive integer input variable not less than (N*(N+1))/2. 0 QTF is an output array of length N which contains the vector (Q transpose)*FVEC. 0 WA1, WA2, WA3, and WA4 are work arrays of length N. 1 0 Page 0 4. Successful completion. 0 The accuracy of HYBRD is controlled by the convergence paramete XTOL. This parameter is used in a test which makes a compariso between the approximation X and a solution XSOL. HYBRD termi- nates when the test is satisfied. If the convergence parameter is less than the machine precision (as defined by the MINPACK function SPMPAR(1)), then HYBRD only attempts to satisfy the test defined by the machine precision. Further progress is not usually possible. 0 The test assumes that the functions are reasonably well behaved If this condition is not satisfied, then HYBRD may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning HYBRD with a tighter toler- ance. 0 Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z and D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempts to guaran- tee that 0 ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). 0 If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 1. There is a danger that the smaller compo- nents of D*X may have large relative errors, but the fast rat of convergence of HYBRD usually avoids this possibility. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 0 5. Unsuccessful completion. 0 Unsuccessful termination of HYBRD can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or XTOL .LT. 0.E0, or MAXFEV .LE. 0, or ML .LT. 0, or MU .LT. 0, or FACTOR .LE. 0.E0, or LDFJAC .LT. N, or LR .LT. (N*(N+1))/2 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRD. In this case, it may be possible to remedy the situation by rerunning HYBRD with a smaller value of FACTOR. 0 Excessive number of function evaluations. A reasonable value for MAXFEV is 200*(N+1). If the number of calls to FCN reaches MAXFEV, then this indicates that the routine is con- verging very slowly as measured by the progress of FVEC, and 1 0 Page 0 INFO is set to 2. This situation should be unusual because, as indicated below, lack of good progress is usually diagnose earlier by HYBRD, causing termination with INFO = 4 or INFO = 5. 0 Lack of good progress. HYBRD searches for a zero of the system by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRD from a dif- ferent starting point may be helpful. 0 6. Characteristics of the algorithm. 0 HYBRD is a modification of the Powell hybrid method. Two of it main characteristics involve the choice of the correction as a convex combination of the Newton and scaled gradient directions and the updating of the Jacobian by the rank-1 method of Broy- den. The choice of the correction guarantees (under reasonable conditions) global convergence for starting points far from the solution and a fast rate of convergence. The Jacobian is approximated by forward differences at the starting point, but forward differences are not used again until the rank-1 method fails to produce satisfactory progress. 0 Timing. The time required by HYBRD to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRD is about 11.5*(N**2) to process each call to FCN. Unless FCN can be evaluated quickly, the timing of HYBRD will be strongly influenced by the time spent in FCN. 0 Storage. HYBRD requires (3*N**2 + 17*N)/2 single precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... DOGLEG,SPMPAR,ENORM,FDJAC1, QFORM,QRFAC,R1MPYQ,R1UPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MIN0,MOD 0 8. References. 0 M. J. D. Powell, A Hybrid Method for Nonlinear Equations. 1 0 Page 0 Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations 0 (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 0 C ********** C C DRIVER FOR HYBRD EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR,NWRITE REAL XTOL,EPSFCN,FACTOR,FNORM REAL X(9),FVEC(9),DIAG(9),FJAC(9,9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.E0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = SQRT(SPMPAR(1)) C MAXFEV = 2000 ML = 1 MU = 1 EPSFCN = 0.E0 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.E0 1 0 Page 0 20 CONTINUE FACTOR = 1.E2 NPRINT = 0 C CALL HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * R,LR,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3E15.7)) C C LAST CARD OF DRIVER FOR HYBRD EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG REAL X(N),FVEC(N) C C SUBROUTINE FCN FOR HYBRD EXAMPLE. C INTEGER K REAL ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.E0,1.E0,2.E0,3.E0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.1192636E-07 0 NUMBER OF FUNCTION EVALUATIONS 14 1 0 Page 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 -0.5706545E+00 -0.6816283E+00 -0.7017325E+00 -0.7042129E+00 -0.7013690E+00 -0.6918656E+00 -0.6657920E+00 -0.5960342E+00 -0.4164121E+00 1 0 1 0 Page 0 Documentation for MINPACK subroutine HYBRJ1 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of HYBRJ1 is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. This is done by using the more general nonlinea equation solver HYBRJ. The user must provide a subroutine whic calculates the functions and the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) INTEGER N,LDFJAC,INFO,LWA REAL TOL REAL X(N),FVEC(N),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to HYBRJ1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRJ1. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. 0 SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG REAL X(N),FVEC(N),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END 0 The value of IFLAG should not be changed by FCN unless the 1 0 Page 0 user wants to terminate execution of HYBRJ1. In this case se IFLAG to a negative integer. 0 N is a positive integer input variable set to the number of functions and variables. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length N which contains the function evaluated at the output X. 0 FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx imate Jacobian. Section 6 contains more details about the approximation to the Jacobian. 0 LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. 0 TOL is a nonnegative input variable. Termination occurs when the algorithm estimates that the relative error between X and the solution is at most TOL. Section 4 contains more details about TOL. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Algorithm estimates that the relative error between X and the solution is at most TOL. 0 INFO = 2 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). 0 INFO = 3 TOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 4 Iteration is not making good progress. 0 Sections 4 and 5 contain more details about INFO. 0 WA is a work array of length LWA. 0 LWA is a positive integer input variable not less than (N*(N+13))/2. 0 4. Successful completion. 0 The accuracy of HYBRJ1 is controlled by the convergence 1 0 Page 0 parameter TOL. This parameter is used in a test which makes a comparison between the approximation X and a solution XSOL. HYBRJ1 terminates when the test is satisfied. If TOL is less than the machine precision (as defined by the MINPACK function SPMPAR(1)), then HYBRJ1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. 0 The test assumes that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then HYBRJ1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning HYBRJ1 with a tighter toler- ance. 0 Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(X-XSOL) .LE. TOL*ENORM(XSOL). 0 If this condition is satisfied with TOL = 10**(-K), then the larger components of X have K significant decimal digits and INFO is set to 1. There is a danger that the smaller compo- nents of X may have large relative errors, but the fast rate of convergence of HYBRJ1 usually avoids this possibility. 0 5. Unsuccessful completion. 0 Unsuccessful termination of HYBRJ1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or LDFJAC .LT. N, or TOL .LT. 0.E0, or LWA .LT. (N*(N+13))/2. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRJ1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead HYBRJ, which includes in its calling sequence the step-length- governing parameter FACTOR. 0 Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi cates that the routine is converging very slowly as measured 1 0 Page 0 by the progress of FVEC, and INFO is set to 2. This situatio should be unusual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRJ1, causing ter- mination with INFO = 4. 0 Lack of good progress. HYBRJ1 searches for a zero of the syste by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRJ1 from a dif- ferent starting point may be helpful. 0 6. Characteristics of the algorithm. 0 HYBRJ1 is a modification of the Powell hybrid method. Two of its main characteristics involve the choice of the correction a a convex combination of the Newton and scaled gradient direc- tions, and the updating of the Jacobian by the rank-1 method of Broyden. The choice of the correction guarantees (under reason able conditions) global convergence for starting points far fro the solution and a fast rate of convergence. The Jacobian is calculated at the starting point, but it is not recalculated until the rank-1 method fails to produce satisfactory progress. 0 Timing. The time required by HYBRJ1 to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRJ1 is about 11.5*(N**2) to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.3*(N**3) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of HYBRJ1 will be strongly influenced by the time spent in FCN. 0 Storage. HYBRJ1 requires (3*N**2 + 17*N)/2 single precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... DOGLEG,SPMPAR,ENORM,HYBRJ, QFORM,QRFAC,R1MPYQ,R1UPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MIN0,MOD 0 8. References. 1 0 Page 0 M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations 0 (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 0 C ********** C C DRIVER FOR HYBRJ1 EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,INFO,LWA,NWRITE REAL TOL,FNORM REAL X(9),FVEC(9),FJAC(9,9),WA(99) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.E0 10 CONTINUE C LDFJAC = 9 LWA = 99 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = SQRT(SPMPAR(1)) C CALL HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3E15.7)) 1 0 Page 0 C C LAST CARD OF DRIVER FOR HYBRJ1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG REAL X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ1 EXAMPLE. C INTEGER J,K REAL ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.E0,1.E0,2.E0,3.E0,4.E0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.1192636E-07 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 -0.5706545E+00 -0.6816283E+00 -0.7017325E+00 -0.7042129E+00 -0.7013690E+00 -0.6918656E+00 -0.6657920E+00 -0.5960342E+00 -0.4164121E+00 1 0 1 0 Page 0 Documentation for MINPACK subroutine HYBRJ 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of HYBRJ is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. The user must provide a subroutine which calcu- lates the functions and the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, * WA1,WA2,WA3,WA4) INTEGER N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR REAL XTOL,FACTOR REAL X(N),FVEC(N),FJAC(LDFJAC,N),DIAG(N),R(LR),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(N) 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to HYBRJ and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRJ. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. 0 SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG REAL X(N),FVEC(N),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END 1 0 Page 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of HYBRJ. In this case set IFLAG to a negative integer. 0 N is a positive integer input variable set to the number of functions and variables. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length N which contains the function evaluated at the output X. 0 FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx imate Jacobian. Section 6 contains more details about the approximation to the Jacobian. 0 LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. 0 XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at mos XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. 0 MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached MAXFEV. 0 DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. 0 MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. 0 FACTOR is a positive input variable used in determining the ini tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. 0 NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. FVEC and FJAC should not be altered. If NPRINT is not positive, no 1 0 Page 0 special calls of FCN with IFLAG = 0 are made. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Relative error between two consecutive iterates is at most XTOL. 0 INFO = 2 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. 0 INFO = 3 XTOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 4 Iteration is not making good progress, as measured by the improvement from the last five Jacobian eval uations. 0 INFO = 5 Iteration is not making good progress, as measured by the improvement from the last ten iterations. 0 Sections 4 and 5 contain more details about INFO. 0 NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. 0 NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. 0 R is an output array of length LR which contains the upper triangular matrix produced by the QR factorization of the final approximate Jacobian, stored rowwise. 0 LR is a positive integer input variable not less than (N*(N+1))/2. 0 QTF is an output array of length N which contains the vector (Q transpose)*FVEC. 0 WA1, WA2, WA3, and WA4 are work arrays of length N. 0 4. Successful completion. 0 The accuracy of HYBRJ is controlled by the convergence paramete XTOL. This parameter is used in a test which makes a compariso between the approximation X and a solution XSOL. HYBRJ termi- nates when the test is satisfied. If the convergence parameter is less than the machine precision (as defined by the MINPACK function SPMPAR(1)), then HYBRJ only attempts to satisfy the test defined by the machine precision. Further progress is not 1 0 Page 0 usually possible. 0 The test assumes that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then HYBRJ may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning HYBRJ with a tighter toler- ance. 0 Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z and D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempts to guaran- tee that 0 ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). 0 If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 1. There is a danger that the smaller compo- nents of D*X may have large relative errors, but the fast rat of convergence of HYBRJ usually avoids this possibility. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 0 5. Unsuccessful completion. 0 Unsuccessful termination of HYBRJ can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or LDFJAC .LT. N, or XTOL .LT. 0.E0, or MAXFEV .LE. 0, or FACTOR .LE. 0.E0, or LR .LT. (N*(N+1))/2. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRJ. In this case, it may be possible to remedy the situation by rerunning HYBRJ with a smaller value of FACTOR. 0 Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routin is converging very slowly as measured by the progress of FVEC and INFO is set to 2. This situation should be unusual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRJ, causing termination with INFO = 4 or INFO = 5. 0 Lack of good progress. HYBRJ searches for a zero of the system by minimizing the sum of the squares of the functions. In so 1 0 Page 0 doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRJ from a dif- ferent starting point may be helpful. 0 6. Characteristics of the algorithm. 0 HYBRJ is a modification of the Powell hybrid method. Two of it main characteristics involve the choice of the correction as a convex combination of the Newton and scaled gradient directions and the updating of the Jacobian by the rank-1 method of Broy- den. The choice of the correction guarantees (under reasonable conditions) global convergence for starting points far from the solution and a fast rate of convergence. The Jacobian is calcu lated at the starting point, but it is not recalculated until the rank-1 method fails to produce satisfactory progress. 0 Timing. The time required by HYBRJ to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRJ is about 11.5*(N**2) to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.3*(N**3) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of HYBRJ will be strongly influenced by the time spent in FCN. 0 Storage. HYBRJ requires (3*N**2 + 17*N)/2 single precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... DOGLEG,SPMPAR,ENORM, QFORM,QRFAC,R1MPYQ,R1UPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MIN0,MOD 0 8. References. 0 M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 0 9. Example. 1 0 Page 0 The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations 0 (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 0 C ********** C C DRIVER FOR HYBRJ EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR,NWRITE REAL XTOL,FACTOR,FNORM REAL X(9),FVEC(9),FJAC(9,9),DIAG(9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.E0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = SQRT(SPMPAR(1)) C MAXFEV = 1000 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.E0 20 CONTINUE FACTOR = 1.E2 NPRINT = 0 C CALL HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, * WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) 1 0 Page 0 STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3E15.7)) C C LAST CARD OF DRIVER FOR HYBRJ EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG REAL X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ EXAMPLE. C INTEGER J,K REAL ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.E0,1.E0,2.E0,3.E0,4.E0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 1 0 Page 0 FINAL L2 NORM OF THE RESIDUALS 0.1192636E-07 0 NUMBER OF FUNCTION EVALUATIONS 11 0 NUMBER OF JACOBIAN EVALUATIONS 1 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 -0.5706545E+00 -0.6816283E+00 -0.7017325E+00 -0.7042129E+00 -0.7013690E+00 -0.6918656E+00 -0.6657920E+00 -0.5960342E+00 -0.4164121E+00 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMDER1 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMDER1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. This is done by using the more general least-squares solver LMDER. The user must provide a subroutine which calculates the functions and the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) REAL TOL REAL X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMDER1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDER1. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. 0 SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END 1 0 Page 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDER1. In this case se IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that 0 T T T P *(JAC *JAC)*P = R *R, 0 where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. 0 LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. 0 TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. 0 INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 FVEC is orthogonal to the columns of the Jacobian t machine precision. 1 0 Page 0 INFO = 5 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). 0 INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. 0 Sections 4 and 5 contain more details about INFO. 0 IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. 0 WA is a work array of length LWA. 0 LWA is a positive integer input variable not less than 5*N+M. 0 4. Successful completion. 0 The accuracy of LMDER1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMDER1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func tion SPMPAR(1)), then LMDER1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. 0 The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMDER1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMDER1 with a tighter toler- ance. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also 1 0 Page 0 satisfied). 0 Second convergence test. If D is a diagonal matrix (implicitly generated by LMDER1) whose entries contain scale factors for the variables, then this test attempts to guarantee that 0 ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). 0 If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. 0 Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMDER1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMDER1 can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or TOL .LT. 0.E0, or LWA .LT. 5*N+M. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDER1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMDER, which includes in its calling sequence the step-length- governing parameter FACTOR. 0 Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi cates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMDER1, thereby forcing it to disregard old (and possibly harmful) information. 0 1 0 Page 0 6. Characteristics of the algorithm. 0 LMDER1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMDER1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. 0 Timing. The time required by LMDER1 to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDER1 is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and M*(N**2) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of LMDER1 will be strongly influenced by the time spent in FCN. 0 Storage. LMDER1 requires M*N + 2*M + 6*N single precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,LMDER,LMPAR,QRFAC,QRSOLV 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 1 0 Page 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMDER1 EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) REAL TOL,FNORM REAL X(3),FVEC(15),FJAC(15,3),WA(30) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LDFJAC = 15 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = SQRT(SPMPAR(1)) C CALL LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C C LAST CARD OF DRIVER FOR LMDER1 EXAMPLE. C 1 0 Page 0 END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER1 EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3,TMP4 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.E0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 0.8241058E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMDER 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMDER is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. The user must provide a subrou- tine which calculates the functions and the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) REAL FTOL,XTOL,GTOL,FACTOR REAL X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMDER and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDER. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. 0 SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END 1 0 Page 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDER. In this case set IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that 0 T T T P *(JAC *JAC)*P = R *R, 0 where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. 0 LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. 0 FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. 0 XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at mos XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. 0 GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vecto and the columns of the Jacobian. Section 4 contains more details about GTOL. 0 MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached MAXFEV. 1 0 Page 0 DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. 0 MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. 0 FACTOR is a positive input variable used in determining the ini tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. 0 NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X, FVEC, and FJAC available for printing. FVEC and FJAC should not be altered. If NPRINT is not posi- tive, no special calls of FCN with IFLAG = 0 are made. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. 0 INFO = 2 Relative error between two consecutive iterates is at most XTOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. 0 INFO = 5 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. 0 INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. 0 Sections 4 and 5 contain more details about INFO. 1 0 Page 0 NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. 0 NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. 0 IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. 0 QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. 0 WA1, WA2, and WA3 are work arrays of length N. 0 WA4 is a work array of length M. 0 4. Successful completion. 0 The accuracy of LMDER is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMDER terminates when any of the tests is satisfied. If any of the convergence parameters is less tha the machine precision (as defined by the MINPACK function SPMPAR(1)), then LMDER only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. 0 The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMDER may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMDER with tighter toler- ances. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the recommended value for FTOL is the square root of the machine precision. 1 0 Page 0 Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that 0 ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). 0 If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 0 Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMDER, and furthermore, the test is equally well satisfied at other crit ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMDER can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or FTOL .LT. 0.E0, or XTOL .LT. 0.E0, or GTOL .LT. 0.E0, or MAXFEV .LE. 0, or FACTOR .LE. 0.E0. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDER. In this case, it may be possible to remedy the situation by rerunning LMDER with a smaller value of FACTOR. 0 Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routin is converging very slowly as measured by the progress of FVEC and INFO is set to 5. In this case, it may be helpful to restart LMDER with MODE set to 1. 0 6. Characteristics of the algorithm. 0 LMDER is a modification of the Levenberg-Marquardt algorithm. 1 0 Page 0 Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMDER and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (unde reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. 0 Timing. The time required by LMDER to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDER is about N**3 to process eac evaluation of the functions (call to FCN with IFLAG = 1) and M*(N**2) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, th timing of LMDER will be strongly influenced by the time spent in FCN. 0 Storage. LMDER requires M*N + 2*M + 6*N single precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,LMPAR,QRFAC,QRSOLV 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 1 0 Page 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMDER EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) REAL FTOL,XTOL,GTOL,FACTOR,FNORM REAL X(3),FVEC(15),FJAC(15,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = SQRT(SPMPAR(1)) XTOL = SQRT(SPMPAR(1)) GTOL = 0.E0 C MAXFEV = 400 MODE = 1 FACTOR = 1.E2 NPRINT = 0 C CALL LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // 1 0 Page 0 * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C C LAST CARD OF DRIVER FOR LMDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3,TMP4 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.E0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 1 0 Page 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 NUMBER OF FUNCTION EVALUATIONS 6 0 NUMBER OF JACOBIAN EVALUATIONS 5 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 0.8241058E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMSTR1 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMSTR1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm which uses minimal storage. This is done by using the more general least-squares solver LMSTR. The user must provide a subroutine which calculates the func- tions and the rows of the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) REAL TOL REAL X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMSTR1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMSTR1. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the rows of the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program and should be written as follows. 0 SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M),FJROW(N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. ---------- RETURN 1 0 Page 0 END 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMSTR1. In this case se IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 FJAC is an output N by N array. The upper triangle of FJAC con tains an upper triangular matrix R such that 0 T T T P *(JAC *JAC)*P = R *R, 0 where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower triangular part of FJAC contains information generated during the computation of R. 0 LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. 0 TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. 0 INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 FVEC is orthogonal to the columns of the Jacobian t 1 0 Page 0 machine precision. 0 INFO = 5 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). 0 INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. 0 Sections 4 and 5 contain more details about INFO. 0 IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular. Column j of P is column IPVT(j) of the identity matrix. 0 WA is a work array of length LWA. 0 LWA is a positive integer input variable not less than 5*N+M. 0 4. Successful completion. 0 The accuracy of LMSTR1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMSTR1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func tion SPMPAR(1)), then LMSTR1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. 0 The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMSTR1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMSTR1 with a tighter toler- ance. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an 1 0 Page 0 INFO is set to 1 (or to 3 if the second test is also satis- fied). 0 Second convergence test. If D is a diagonal matrix (implicitly generated by LMSTR1) whose entries contain scale factors for the variables, then this test attempts to guarantee that 0 ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). 0 If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. 0 Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMSTR1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMSTR1 can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. N, or TOL .LT. 0.E0, or LWA .LT. 5*N+M. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMSTR1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMSTR, which includes in its calling sequence the step-length- governing parameter FACTOR. 0 Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi cates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMSTR1, thereby forcing it to disregard old (and possibly harmful) information. 1 0 Page 0 6. Characteristics of the algorithm. 0 LMSTR1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMSTR1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. 0 Timing. The time required by LMSTR1 to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMSTR1 is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.5*(N**2) to process each row of the Jacobian (call to FCN with IFLAG .GE. 2). Unless FCN can be evaluated quickly, the timing of LMSTR1 will be strongly influenced by the time spent in FCN. 0 Storage. LMSTR1 requires N**2 + 2*M + 6*N single precision sto rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,LMSTR,LMPAR,QRFAC,QRSOLV, RWUPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 1 0 Page 0 to the data 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMSTR1 EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) REAL TOL,FNORM REAL X(3),FVEC(15),FJAC(3,3),WA(30) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LDFJAC = 3 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = SQRT(SPMPAR(1)) C CALL LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C 1 0 Page 0 C LAST CARD OF DRIVER FOR LMSTR1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR1 EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3,TMP4 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.E0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 0.8241058E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMSTR 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMSTR is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm which uses minimal storage. The user must provide a subroutine which calculates the functions and the rows of the Jacobian. 0 2. Subroutine and type statements. 0 SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) REAL FTOL,XTOL,GTOL,FACTOR REAL X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMSTR and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMSTR. 0 FCN is the name of the user-supplied subroutine which calculate the functions and the rows of the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program and should be written as follows. 0 SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M),FJROW(N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. ---------- RETURN 1 0 Page 0 END 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMSTR. In this case set IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 FJAC is an output N by N array. The upper triangle of FJAC con tains an upper triangular matrix R such that 0 T T T P *(JAC *JAC)*P = R *R, 0 where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower triangular part of FJAC contains information generated during the computation of R. 0 LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. 0 FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. 0 XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at mos XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. 0 GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vecto and the columns of the Jacobian. Section 4 contains more details about GTOL. 0 MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached 1 0 Page 0 MAXFEV. 0 DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. 0 MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. 0 FACTOR is a positive input variable used in determining the ini tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. 0 NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. 0 INFO = 2 Relative error between two consecutive iterates is at most XTOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. 0 INFO = 5 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. 0 INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. 1 0 Page 0 Sections 4 and 5 contain more details about INFO. 0 NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. 0 NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. 0 IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular. Column j of P is column IPVT(j) of the identity matrix. 0 QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. 0 WA1, WA2, and WA3 are work arrays of length N. 0 WA4 is a work array of length M. 0 4. Successful completion. 0 The accuracy of LMSTR is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMSTR terminates when any of the tests is satisfied. If any of the convergence parameters is less tha the machine precision (as defined by the MINPACK function SPMPAR(1)), then LMSTR only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. 0 The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMSTR may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMSTR with tighter toler- ances. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the recommended value for FTOL is the square root of the machine 1 0 Page 0 precision. 0 Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that 0 ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). 0 If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 0 Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMSTR, and furthermore, the test is equally well satisfied at other crit ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMSTR can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. N, or FTOL .LT. 0.E0, or XTOL .LT. 0.E0, or GTOL .LT. 0.E0, or MAXFEV .LE. 0, or FACTOR .LE. 0.E0. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMSTR. In this case, it may be possible to remedy the situation by rerunning LMSTR with a smaller value of FACTOR. 0 Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routin is converging very slowly as measured by the progress of FVEC and INFO is set to 5. In this case, it may be helpful to restart LMSTR with MODE set to 1. 0 6. Characteristics of the algorithm. 1 0 Page 0 LMSTR is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMSTR and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (unde reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. 0 Timing. The time required by LMSTR to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMSTR is about N**3 to process eac evaluation of the functions (call to FCN with IFLAG = 1) and 1.5*(N**2) to process each row of the Jacobian (call to FCN with IFLAG .GE. 2). Unless FCN can be evaluated quickly, the timing of LMSTR will be strongly influenced by the time spent in FCN. 0 Storage. LMSTR requires N**2 + 2*M + 6*N single precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,LMPAR,QRFAC,QRSOLV,RWUPDT 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 1 0 Page 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMSTR EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) REAL FTOL,XTOL,GTOL,FACTOR,FNORM REAL X(3),FVEC(15),FJAC(3,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LDFJAC = 3 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = SQRT(SPMPAR(1)) XTOL = SQRT(SPMPAR(1)) GTOL = 0.E0 C MAXFEV = 400 MODE = 1 FACTOR = 1.E2 NPRINT = 0 C CALL LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // 1 0 Page 0 * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C C LAST CARD OF DRIVER FOR LMSTR EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3,TMP4 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.E0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 1 0 Page 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 NUMBER OF FUNCTION EVALUATIONS 6 0 NUMBER OF JACOBIAN EVALUATIONS 5 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 0.8241058E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMDIF1 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMDIF1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. This is done by using the more general least-squares solver LMDIF. The user must provide a subroutine which calculates the functions. The Jacobian is the calculated by a forward-difference approximation. 0 2. Subroutine and type statements. 0 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 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMDIF1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDIF1. 0 FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows 0 SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDIF1. In this case se 1 0 Page 0 IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. 0 INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 FVEC is orthogonal to the columns of the Jacobian t machine precision. 0 INFO = 5 Number of calls to FCN has reached or exceeded 200*(N+1). 0 INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. 0 Sections 4 and 5 contain more details about INFO. 0 IWA is an integer work array of length N. 0 WA is a work array of length LWA. 0 LWA is a positive integer input variable not less than 1 0 Page 0 M*N+5*N+M. 0 4. Successful completion. 0 The accuracy of LMDIF1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMDIF1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func tion SPMPAR(1)), then LMDIF1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. 0 The tests assume that the functions are reasonably well behaved If this condition is not satisfied, then LMDIF1 may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning LMDIF1 with a tighter toler- ance. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). 0 Second convergence test. If D is a diagonal matrix (implicitly generated by LMDIF1) whose entries contain scale factors for the variables, then this test attempts to guarantee that 0 ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). 0 If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. 0 Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMDIF1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Also, errors in the functions (see below) may result in the test being satisfied at a point not close to th 1 0 Page 0 minimum. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMDIF1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or errors in the functions. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or TOL .LT. 0.E0, or LWA .LT. M*N+5*N+M. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDIF1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMDIF, which includes in its calling sequence the step-length-governing parameter FACTOR. 0 Excessive number of function evaluations. If the number of calls to FCN reaches 200*(N+1), then this indicates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be help- ful to restart LMDIF1, thereby forcing it to disregard old (and possibly harmful) information. 0 Errors in the functions. The choice of step length in the for- ward-difference approximation to the Jacobian assumes that th relative errors in the functions are of the order of the machine precision. If this is not the case, LMDIF1 may fail (usually with INFO = 4). The user should then use LMDIF instead, or one of the programs which require the analytic Jacobian (LMDER1 and LMDER). 0 6. Characteristics of the algorithm. 0 LMDIF1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMDIF1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. 0 Timing. The time required by LMDIF1 to solve a given problem 1 0 Page 0 depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDIF1 is about N**3 to process each evaluation of the functions (one call to FCN) and M*(N**2) to process each approximation to the Jacobian (N calls to FCN). Unless FCN can be evaluated quickly, the tim- ing of LMDIF1 will be strongly influenced by the time spent i FCN. 0 Storage. LMDIF1 requires M*N + 2*M + 6*N single precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,FDJAC2,LMDIF,LMPAR, QRFAC,QRSOLV 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMDIF1 EXAMPLE. C SINGLE PRECISION VERSION C 1 0 Page 0 C ********** INTEGER J,M,N,INFO,LWA,NWRITE INTEGER IWA(3) REAL TOL,FNORM REAL X(3),FVEC(15),WA(75) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LWA = 75 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = SQRT(SPMPAR(1)) C CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C C LAST CARD OF DRIVER FOR LMDIF1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF1 EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C 1 0 Page 0 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 0 0.8241057E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine LMDIF 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of LMDIF is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. The user must provide a subrou- tine which calculates the functions. The Jacobian is then cal- culated by a forward-difference approximation. 0 2. Subroutine and type statements. 0 SUBROUTINE LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC INTEGER IPVT(N) REAL FTOL,XTOL,GTOL,EPSFCN,FACTOR REAL X(N),FVEC(M),DIAG(N),FJAC(LDFJAC,N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) EXTERNAL FCN 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to LMDIF and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDIF. 0 FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows 0 SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END 1 0 Page 0 The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDIF. In this case set IFLAG to a negative integer. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. N must not exceed M. 0 X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. 0 FVEC is an output array of length M which contains the function evaluated at the output X. 0 FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. 0 XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at mos XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. 0 GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vecto and the columns of the Jacobian. Section 4 contains more details about GTOL. 0 MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN is at least MAXFEV by the end of an iteration. 0 EPSFCN is an input variable used in determining a suitable step for the forward-difference approximation. This approximation assumes that the relative errors in the functions are of the order of EPSFCN. If EPSFCN is less than the machine preci- sion, it is assumed that the relative errors in the functions are of the order of the machine precision. 0 DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. 0 MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is 1 0 Page 0 specified by the input DIAG. Other values of MODE are equiva lent to MODE = 1. 0 FACTOR is a positive input variable used in determining the ini tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. 0 NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. 0 INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. 0 INFO = 0 Improper input parameters. 0 INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. 0 INFO = 2 Relative error between two consecutive iterates is at most XTOL. 0 INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. 0 INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. 0 INFO = 5 Number of calls to FCN has reached or exceeded MAXFEV. 0 INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. 0 INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. 0 INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. 0 Sections 4 and 5 contain more details about INFO. 0 NFEV is an integer output variable set to the number of calls t FCN. 0 FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that 1 0 Page 0 T T T P *(JAC *JAC)*P = R *R, 0 where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. 0 LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. 0 IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. 0 QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. 0 WA1, WA2, and WA3 are work arrays of length N. 0 WA4 is a work array of length M. 0 4. Successful completion. 0 The accuracy of LMDIF is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMDIF terminates when any of the tests is satisfied. If any of the convergence parameters is less tha the machine precision (as defined by the MINPACK function SPMPAR(1)), then LMDIF only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. 0 The tests assume that the functions are reasonably well behaved If this condition is not satisfied, then LMDIF may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning LMDIF with tighter toler- ances. 0 First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that 0 ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), 0 where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the 1 0 Page 0 recommended value for FTOL is the square root of the machine precision. 0 Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that 0 ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). 0 If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 0 Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMDIF, and furthermore, the test is equally well satisfied at other crit ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 0 5. Unsuccessful completion. 0 Unsuccessful termination of LMDIF can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. 0 Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or FTOL .LT. 0.E0, or XTOL .LT. 0.E0, or GTOL .LT. 0.E0, or MAXFEV .LE. 0, or FACTOR .LE. 0.E0. 0 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDIF. In this case, it may be possible to remedy the situation by rerunning LMDIF with a smaller value of FACTOR. 0 Excessive number of function evaluations. A reasonable value for MAXFEV is 200*(N+1). If the number of calls to FCN reaches MAXFEV, then this indicates that the routine is con- verging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMDIF with MODE set to 1. 0 1 0 Page 0 6. Characteristics of the algorithm. 0 LMDIF is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMDIF and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (unde reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. 0 Timing. The time required by LMDIF to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDIF is about N**3 to process eac evaluation of the functions (one call to FCN) and M*(N**2) to process each approximation to the Jacobian (N calls to FCN). Unless FCN can be evaluated quickly, the timing of LMDIF will be strongly influenced by the time spent in FCN. 0 Storage. LMDIF requires M*N + 2*M + 6*N single precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 0 7. Subprograms required. 0 USER-supplied ...... FCN 0 MINPACK-supplied ... SPMPAR,ENORM,FDJAC2,LMPAR,QRFAC,QRSOLV 0 FORTRAN-supplied ... ABS,AMAX1,AMIN1,SQRT,MOD 0 8. References. 0 Jorge J. More, The Levenberg-Marquardt Algorithm, Implementatio and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 0 9. Example. 0 The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 1 0 Page 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 0 C ********** C C DRIVER FOR LMDIF EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER J,M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC,NWRITE INTEGER IPVT(3) REAL FTOL,XTOL,GTOL,EPSFCN,FACTOR,FNORM REAL X(3),FVEC(15),DIAG(3),FJAC(15,3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) REAL ENORM,SPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.E0 X(2) = 1.E0 X(3) = 1.E0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = SQRT(SPMPAR(1)) XTOL = SQRT(SPMPAR(1)) GTOL = 0.E0 C MAXFEV = 800 EPSFCN = 0.E0 MODE = 1 FACTOR = 1.E2 NPRINT = 0 C CALL LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) 1 0 Page 0 FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,E15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3E15.7) C C LAST CARD OF DRIVER FOR LMDIF EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF EXAMPLE. C INTEGER I REAL TMP1,TMP2,TMP3 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be slightly different. 0 FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01 0 NUMBER OF FUNCTION EVALUATIONS 21 0 EXIT PARAMETER 1 0 FINAL APPROXIMATE SOLUTION 1 0 Page 0 0.8241057E-01 0.1133037E+01 0.2343695E+01 1 0 1 0 Page 0 Documentation for MINPACK subroutine CHKDER 0 Single precision version 0 Argonne National Laboratory 0 Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More 0 March 1980 0 1. Purpose. 0 The purpose of CHKDER is to check the gradients of M nonlinear functions in N variables, evaluated at a point X, for consis- tency with the functions themselves. The user must call CHKDER twice, first with MODE = 1 and then with MODE = 2. 0 2. Subroutine and type statements. 0 SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) INTEGER M,N,LDFJAC,MODE REAL X(N),FVEC(M),FJAC(LDFJAC,N),XP(N),FVECP(M),ERR(M) 0 3. Parameters. 0 Parameters designated as input parameters must be specified on entry to CHKDER and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from CHKDER. 0 M is a positive integer input variable set to the number of functions. 0 N is a positive integer input variable set to the number of variables. 0 X is an input array of length N. 0 FVEC is an array of length M. On input when MODE = 2, FVEC mus contain the functions evaluated at X. 0 FJAC is an M by N array. On input when MODE = 2, the rows of FJAC must contain the gradients of the respective functions evaluated at X. 0 LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. 0 XP is an array of length N. On output when MODE = 1, XP is set to a neighboring point of X. 1 0 Page 0 FVECP is an array of length M. On input when MODE = 2, FVECP must contain the functions evaluated at XP. 0 MODE is an integer input variable set to 1 on the first call an 2 on the second. Other values of MODE are equivalent to MODE = 1. 0 ERR is an array of length M. On output when MODE = 2, ERR con- tains measures of correctness of the respective gradients. I there is no severe loss of significance, then if ERR(I) is 1. the I-th gradient is correct, while if ERR(I) is 0.0 the I-th gradient is incorrect. For values of ERR between 0.0 and 1.0 the categorization is less certain. In general, a value of ERR(I) greater than 0.5 indicates that the I-th gradient is probably correct, while a value of ERR(I) less than 0.5 indi- cates that the I-th gradient is probably incorrect. 0 4. Successful completion. 0 CHKDER usually guarantees that if ERR(I) is 1.0, then the I-th gradient at X is consistent with the I-th function. This sug- gests that the input X be such that consistency of the gradient at X implies consistency of the gradient at all points of inter est. If all the components of X are distinct and the fractiona part of each one has two nonzero digits, then X is likely to be a satisfactory choice. 0 If ERR(I) is not 1.0 but is greater than 0.5, then the I-th gra dient is probably consistent with the I-th function (the more s the larger ERR(I) is), but the conditions for ERR(I) to be 1.0 have not been completely satisfied. In this case, it is recom- mended that CHKDER be rerun with other input values of X. If ERR(I) is always greater than 0.5, then the I-th gradient is consistent with the I-th function. 0 5. Unsuccessful completion. 0 CHKDER does not perform reliably if cancellation or rounding errors cause a severe loss of significance in the evaluation of a function. Therefore, none of the components of X should be unusually small (in particular, zero) or any other value which may cause loss of significance. The relative differences between corresponding elements of FVECP and FVEC should be at least two orders of magnitude greater than the machine precisio (as defined by the MINPACK function SPMPAR(1)). If there is a severe loss of significance in the evaluation of the I-th func- tion, then ERR(I) may be 0.0 and yet the I-th gradient could be correct. 0 If ERR(I) is not 0.0 but is less than 0.5, then the I-th gra- dient is probably not consistent with the I-th function (the more so the smaller ERR(I) is), but the conditions for ERR(I) t 1 0 Page 0 be 0.0 have not been completely satisfied. In this case, it is recommended that CHKDER be rerun with other input values of X. If ERR(I) is always less than 0.5 and if there is no severe los of significance, then the I-th gradient is not consistent with the I-th function. 0 6. Characteristics of the algorithm. 0 CHKDER checks the I-th gradient for consistency with the I-th function by computing a forward-difference approximation along suitably chosen direction and comparing this approximation with the user-supplied gradient along the same direction. The prin- cipal characteristic of CHKDER is its invariance to changes in scale of the variables or functions. 0 Timing. The time required by CHKDER depends only on M and N. The number of arithmetic operations needed by CHKDER is about N when MODE = 1 and M*N when MODE = 2. 0 Storage. CHKDER requires M*N + 3*M + 2*N single precision stor age locations, in addition to the storage required by the pro gram. There are no internally declared storage arrays. 0 7. Subprograms required. 0 MINPACK-supplied ... SPMPAR 0 FORTRAN-supplied ... ABS,ALOG10,SQRT 0 8. References. 0 None. 0 9. Example. 0 This example checks the Jacobian matrix for the problem that determines the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of 0 x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 0 to the data 0 y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), 0 where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by 0 y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). 1 0 Page 0 C ********** C C DRIVER FOR CHKDER EXAMPLE. C SINGLE PRECISION VERSION C C ********** INTEGER I,M,N,LDFJAC,MODE,NWRITE REAL X(3),FVEC(15),FJAC(15,3),XP(3),FVECP(15),ERR(15) C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING VALUES SHOULD BE SUITABLE FOR C CHECKING THE JACOBIAN MATRIX. C X(1) = 9.2E-1 X(2) = 1.3E-1 X(3) = 5.4E-1 C LDFJAC = 15 C MODE = 1 CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) MODE = 2 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,1) CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,2) CALL FCN(M,N,XP,FVECP,FJAC,LDFJAC,1) CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) C DO 10 I = 1, M FVECP(I) = FVECP(I) - FVEC(I) 10 CONTINUE WRITE (NWRITE,1000) (FVEC(I),I=1,M) WRITE (NWRITE,2000) (FVECP(I),I=1,M) WRITE (NWRITE,3000) (ERR(I),I=1,M) STOP 1000 FORMAT (/5X,5H FVEC // (5X,3E15.7)) 2000 FORMAT (/5X,13H FVECP - FVEC // (5X,3E15.7)) 3000 FORMAT (/5X,4H ERR // (5X,3E15.7)) C C LAST CARD OF DRIVER FOR CHKDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR CHKDER EXAMPLE. C INTEGER I 1 0 Page 0 REAL TMP1,TMP2,TMP3,TMP4 REAL Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I C C ERROR INTRODUCED INTO NEXT STATEMENT FOR ILLUSTRATION. C CORRECTED STATEMENT SHOULD READ TMP3 = TMP1 . C TMP3 = TMP2 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.E0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END 0 Results obtained with different compilers or machines may be different. In particular, the differences FVECP - FVEC are machine dependent. 0 FVEC 0 -0.1181606E+01 -0.1429655E+01 -0.1606344E+01 -0.1745269E+01 -0.1840654E+01 -0.1921586E+01 -0.1984141E+01 -0.2022537E+01 -0.2468977E+01 -0.2827562E+01 -0.3473582E+01 -0.4437612E+01 -0.6047662E+01 -0.9267761E+01 -0.1891806E+02 0 FVECP - FVEC 0 -0.7724666E-08 -0.3432405E-08 -0.2034843E-09 0.2313685E-08 0.4331078E-08 0.5984096E-08 1 0 Page 0 0.7363281E-08 0.8531470E-08 0.1488591E-07 0.2335850E-07 0.3522012E-07 0.5301255E-07 0.8266660E-07 0.1419747E-06 0.3198990E-06 0 ERR 0 0.1141397E+00 0.9943516E-01 0.9674474E-01 0.9980447E-01 0.1073116E+00 0.1220445E+00 0.1526814E+00 0.1000000E+01 0.1000000E+01 0.1000000E+01 0.1000000E+01 0.1000000E+01 0.1000000E+01 0.1000000E+01 0.1000000E+01 minpack-19961126/ex/file150000644000175000017500000003414704210375143015736 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE SOLUTION OF N NONLINEAR C EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER AND AN C INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, CALLS THE C NONLINEAR EQUATION SOLVER, AND FINALLY PRINTS OUT INFORMATION C ON THE PERFORMANCE OF THE SOLVER. THIS IS ONLY A SAMPLE DRIVER, C MANY OTHER DRIVERS ARE POSSIBLE. THE INTERFACE SUBROUTINE FCN C IS NECESSARY TO TAKE INTO ACCOUNT THE FORMS OF CALLING C SEQUENCES USED BY THE FUNCTION SUBROUTINES IN THE VARIOUS C NONLINEAR EQUATION SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,HYBRD1,INITPT,VECFCN C C FORTRAN-SUPPLIED ... DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LWA,N,NFEV,NPROB,NREAD,NTRIES,NWRITE INTEGER NA(60),NF(60),NP(60),NX(60) DOUBLE PRECISION FACTOR,FNORM1,FNORM2,ONE,TEN,TOL DOUBLE PRECISION FNM(60),FVEC(40),WA(2660),X(40) DOUBLE PRECISION DPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0D0,1.0D1/ TOL = DSQRT(DPMPAR(1)) LWA = 2660 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL VECFCN(N,X,FVEC,NPROB) FNORM1 = ENORM(N,FVEC) WRITE (NWRITE,60) NPROB,N NFEV = 0 CALL HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) FNORM2 = ENORM(N,FVEC) NP(IC) = NPROB NA(IC) = N NF(IC) = NFEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) FNORM1,FNORM2,NFEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),NF(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (3I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 10H DIMENSION, I5, 5X //) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, D15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , D15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5D15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO HYBRD1 /) 90 FORMAT (39H NPROB N NFEV INFO FINAL L2 NORM /) 100 FORMAT (I4, I6, I7, I6, 1X, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C EQUATION SOLVER. FCN SHOULD ONLY CALL THE TESTING FUNCTION C SUBROUTINE VECFCN WITH THE APPROPRIATE VALUE OF PROBLEM C NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... VECFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV COMMON /REFNUM/ NPROB,NFEV CALL VECFCN(N,X,FVEC,NPROB) NFEV = NFEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB DOUBLE PRECISION X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIGN,DSIN,DSQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE, * PROD,SUM,SUM1,SUM2,TEMP,TEMP1,TEMP2,TEN,THREE, * TI,TJ,TK,TPI,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0D0,1.0D0,2.0D0,3.0D0,5.0D0,8.0D0,1.0D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0D4,1.0001D0,2.0D2,2.02D1,1.98D1,1.8D2,2.5D-1,5.0D-1, * 2.9D1/ DFLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = DEXP(-X(1)) + DEXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP1 = DSIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI + C8 TEMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = DFLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + DFLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(DFLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/DFLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(DFLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/DFLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + DFLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/DFLOAT(N+1) DO 260 K = 1, N TK = DFLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = DCOS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = DFLOAT(N+K) - DSIN(X(K)) - SUM - DFLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + DFLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + DFLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,H,HALF,ONE,THREE,TJ,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0D0,5.0D-1,1.0D0,3.0D0,1.2D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/DFLOAT(N+1) DO 90 J = 1, N X(J) = DFLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/DFLOAT(N+1) DO 130 J = 1, N TJ = DFLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/DFLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/DFLOAT(N) DO 170 J = 1, N X(J) = ONE - DFLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END minpack-19961126/ex/file090000644000175000017500000005426404210374714015746 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE SOLUTION OF N NONLINEAR C EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER AND AN C INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, CALLS THE C NONLINEAR EQUATION SOLVER, AND FINALLY PRINTS OUT INFORMATION C ON THE PERFORMANCE OF THE SOLVER. THIS IS ONLY A SAMPLE DRIVER, C MANY OTHER DRIVERS ARE POSSIBLE. THE INTERFACE SUBROUTINE FCN C IS NECESSARY TO TAKE INTO ACCOUNT THE FORMS OF CALLING C SEQUENCES USED BY THE FUNCTION AND JACOBIAN SUBROUTINES IN C THE VARIOUS NONLINEAR EQUATION SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,HYBRJ1,INITPT,VECFCN C C FORTRAN-SUPPLIED ... SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,N,NFEV,NJEV,NPROB,NREAD,NTRIES, * NWRITE INTEGER NA(60),NF(60),NJ(60),NP(60),NX(60) REAL FACTOR,FNORM1,FNORM2,ONE,TEN,TOL REAL FNM(60),FJAC(40,40),FVEC(40),WA(1060),X(40) REAL SPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0E0,1.0E1/ TOL = SQRT(SPMPAR(1)) LDFJAC = 40 LWA = 1060 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL VECFCN(N,X,FVEC,NPROB) FNORM1 = ENORM(N,FVEC) WRITE (NWRITE,60) NPROB,N NFEV = 0 NJEV = 0 CALL HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) FNORM2 = ENORM(N,FVEC) NP(IC) = NPROB NA(IC) = N NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (3I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 10H DIMENSION, I5, 5X //) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, E15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , E15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5E15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO HYBRJ1 /) 90 FORMAT (46H NPROB N NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (I4, I6, 2I7, I6, 1X, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG REAL X(N),FVEC(N),FJAC(LDFJAC,N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C EQUATION SOLVER. FCN SHOULD ONLY CALL THE TESTING FUNCTION C AND JACOBIAN SUBROUTINES VECFCN AND VECJAC WITH THE C APPROPRIATE VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... VECFCN,VECJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL VECFCN(N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL VECJAC(N,X,FJAC,LDFJAC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE VECJAC(N,X,FJAC,LDFJAC,NPROB) INTEGER N,LDFJAC,NPROB REAL X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE VECJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF FOURTEEN C TEST FUNCTIONS. THE PROBLEM DIMENSIONS ARE AS DESCRIBED C IN THE PROLOGUE COMMENTS OF VECFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECJAC(N,X,FJAC,LDFJAC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER VARIABLE. C C X IS AN ARRAY OF LENGTH N. C C FJAC IS AN N BY N ARRAY. ON OUTPUT FJAC CONTAINS THE C JACOBIAN MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,AMIN1,SIN,SQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,K1,K2,ML,MU REAL C1,C3,C4,C5,C6,C9,EIGHT,FIFTN,FIVE,FOUR,H,HUNDRD,ONE,PROD, * SIX,SUM,SUM1,SUM2,TEMP,TEMP1,TEMP2,TEMP3,TEMP4,TEN,THREE, * TI,TJ,TK,TPI,TWENTY,TWO,ZERO REAL FLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,SIX,EIGHT,TEN,FIFTN,TWENTY, * HUNDRD * /0.0E0,1.0E0,2.0E0,3.0E0,4.0E0,5.0E0,6.0E0,8.0E0,1.0E1, * 1.5E1,2.0E1,1.0E2/ DATA C1,C3,C4,C5,C6,C9 /1.0E4,2.0E2,2.02E1,1.98E1,1.8E2,2.9E1/ FLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,20,50,60,90,100,200,230,290,320,350,380,420,450), * NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FJAC(1,1) = -ONE FJAC(1,2) = ZERO FJAC(2,1) = -TWENTY*X(1) FJAC(2,2) = TEN GO TO 490 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE DO 40 K = 1, 4 DO 30 J = 1, 4 FJAC(K,J) = ZERO 30 CONTINUE 40 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = SQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*SQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 490 C C POWELL BADLY SCALED FUNCTION. C 50 CONTINUE FJAC(1,1) = C1*X(2) FJAC(1,2) = C1*X(1) FJAC(2,1) = -EXP(-X(1)) FJAC(2,2) = -EXP(-X(2)) GO TO 490 C C WOOD FUNCTION. C 60 CONTINUE DO 80 K = 1, 4 DO 70 J = 1, 4 FJAC(K,J) = ZERO 70 CONTINUE 80 CONTINUE TEMP1 = X(2) - THREE*X(1)**2 TEMP2 = X(4) - THREE*X(3)**2 FJAC(1,1) = -C3*TEMP1 + ONE FJAC(1,2) = -C3*X(1) FJAC(2,1) = -TWO*C3*X(1) FJAC(2,2) = C3 + C4 FJAC(2,4) = C5 FJAC(3,3) = -C6*TEMP2 + ONE FJAC(3,4) = -C6*X(3) FJAC(4,2) = C5 FJAC(4,3) = -TWO*C6*X(3) FJAC(4,4) = C6 + C4 GO TO 490 C C HELICAL VALLEY FUNCTION. C 90 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP = X(1)**2 + X(2)**2 TEMP1 = TPI*TEMP TEMP2 = SQRT(TEMP) FJAC(1,1) = HUNDRD*X(2)/TEMP1 FJAC(1,2) = -HUNDRD*X(1)/TEMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TEMP2 FJAC(2,2) = TEN*X(2)/TEMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 490 C C WATSON FUNCTION. C 100 CONTINUE DO 120 K = 1, N DO 110 J = K, N FJAC(K,J) = ZERO 110 CONTINUE 120 CONTINUE DO 170 I = 1, 29 TI = FLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 130 J = 2, N SUM1 = SUM1 + FLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 130 CONTINUE SUM2 = ZERO TEMP = ONE DO 140 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 140 CONTINUE TEMP1 = TWO*(SUM1 - SUM2**2 - ONE) TEMP2 = TWO*SUM2 TEMP = TI**2 TK = ONE DO 160 K = 1, N TJ = TK DO 150 J = K, N FJAC(K,J) = FJAC(K,J) * + TJ * *((FLOAT(K-1)/TI - TEMP2) * *(FLOAT(J-1)/TI - TEMP2) - TEMP1) TJ = TI*TJ 150 CONTINUE TK = TEMP*TK 160 CONTINUE 170 CONTINUE FJAC(1,1) = FJAC(1,1) + SIX*X(1)**2 - TWO*X(2) + THREE FJAC(1,2) = FJAC(1,2) - TWO*X(1) FJAC(2,2) = FJAC(2,2) + ONE DO 190 K = 1, N DO 180 J = K, N FJAC(J,K) = FJAC(K,J) 180 CONTINUE 190 CONTINUE GO TO 490 C C CHEBYQUAD FUNCTION. C 200 CONTINUE TK = ONE/FLOAT(N) DO 220 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 TEMP3 = ZERO TEMP4 = TWO DO 210 K = 1, N FJAC(K,J) = TK*TEMP4 TI = FOUR*TEMP2 + TEMP*TEMP4 - TEMP3 TEMP3 = TEMP4 TEMP4 = TI TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 210 CONTINUE 220 CONTINUE GO TO 490 C C BROWN ALMOST-LINEAR FUNCTION. C 230 CONTINUE PROD = ONE DO 250 J = 1, N PROD = X(J)*PROD DO 240 K = 1, N FJAC(K,J) = ONE 240 CONTINUE FJAC(J,J) = TWO 250 CONTINUE DO 280 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 270 TEMP = ONE PROD = ONE DO 260 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 260 CONTINUE 270 CONTINUE FJAC(N,J) = PROD/TEMP 280 CONTINUE GO TO 490 C C DISCRETE BOUNDARY VALUE FUNCTION. C 290 CONTINUE H = ONE/FLOAT(N+1) DO 310 K = 1, N TEMP = THREE*(X(K) + FLOAT(K)*H + ONE)**2 DO 300 J = 1, N FJAC(K,J) = ZERO 300 CONTINUE FJAC(K,K) = TWO + TEMP*H**2/TWO IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -ONE 310 CONTINUE GO TO 490 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 320 CONTINUE H = ONE/FLOAT(N+1) DO 340 K = 1, N TK = FLOAT(K)*H DO 330 J = 1, N TJ = FLOAT(J)*H TEMP = THREE*(X(J) + TJ + ONE)**2 FJAC(K,J) = H*AMIN1(TJ*(ONE-TK),TK*(ONE-TJ))*TEMP/TWO 330 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 340 CONTINUE GO TO 490 C C TRIGONOMETRIC FUNCTION. C 350 CONTINUE DO 370 J = 1, N TEMP = SIN(X(J)) DO 360 K = 1, N FJAC(K,J) = TEMP 360 CONTINUE FJAC(J,J) = FLOAT(J+1)*TEMP - COS(X(J)) 370 CONTINUE GO TO 490 C C VARIABLY DIMENSIONED FUNCTION. C 380 CONTINUE SUM = ZERO DO 390 J = 1, N SUM = SUM + FLOAT(J)*(X(J) - ONE) 390 CONTINUE TEMP = ONE + SIX*SUM**2 DO 410 K = 1, N DO 400 J = K, N FJAC(K,J) = FLOAT(K*J)*TEMP FJAC(J,K) = FJAC(K,J) 400 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 410 CONTINUE GO TO 490 C C BROYDEN TRIDIAGONAL FUNCTION. C 420 CONTINUE DO 440 K = 1, N DO 430 J = 1, N FJAC(K,J) = ZERO 430 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 440 CONTINUE GO TO 490 C C BROYDEN BANDED FUNCTION. C 450 CONTINUE ML = 5 MU = 1 DO 480 K = 1, N DO 460 J = 1, N FJAC(K,J) = ZERO 460 CONTINUE K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) DO 470 J = K1, K2 IF (J .NE. K) FJAC(K,J) = -(ONE + TWO*X(J)) 470 CONTINUE FJAC(K,K) = TWO + FIFTN*X(K)**2 480 CONTINUE 490 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,H,HALF,ONE,THREE,TJ,ZERO REAL FLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0E0,5.0E-1,1.0E0,3.0E0,1.2E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/FLOAT(N+1) DO 90 J = 1, N X(J) = FLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/FLOAT(N+1) DO 130 J = 1, N TJ = FLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/FLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/FLOAT(N) DO 170 J = 1, N X(J) = ONE - FLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB REAL X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIGN,SIN,SQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE,PROD,SUM,SUM1, * SUM2,TEMP,TEMP1,TEMP2,TEN,THREE,TI,TJ,TK,TPI,TWO,ZERO REAL FLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0E0,1.0E0,2.0E0,3.0E0,5.0E0,8.0E0,1.0E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0E4,1.0001E0,2.0E2,2.02E1,1.98E1,1.8E2,2.5E-1,5.0E-1, * 2.9E1/ FLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = EXP(-X(1)) + EXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP1 = SIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI + C8 TEMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = FLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + FLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(FLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/FLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(FLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/FLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + FLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/FLOAT(N+1) DO 260 K = 1, N TK = FLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = COS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = FLOAT(N+K) - SIN(X(K)) - SUM - FLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + FLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + FLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END minpack-19961126/ex/index.html0000644000175000017500000000333707260121571016722 0ustar sylvestresylvestre minpack/ex

minpack/ex

Click here to see the number of accesses to this library.


file	file01
for	Function SPMPAR

file	file02
for	MINPACK-1
prec	single

file	file03
for	MINPACK-1 documentation
,	unfortunately, column 73 was lost at Argonne long ago
prec	single

file	file04
for	Function DPMPAR

file	file05
for	MINPACK-1

file	file06
for	MINPACK-1 documentation
,	unfortunately, column 73 was lost at Argonne long ago
prec	double

file	file07
for	SMCHAR test

file	file08
for	HYBRD  test
prec	single

file	file09
for	HYBRJ  test
prec	single

file	file10
for	LMDER  test
prec	single

file	file11
for	LMSTR  test
prec	single

file	file12
for	LMDIF  test
prec	single

file	file13
for	CHKDER test
prec	single

file	file14
for	DMCHAR test

file	file15
for	HYBRD  test
prec	double

file	file16
for	HYBRJ  test
prec	double

file	file17
for	LMDER  test
prec	double

file	file18
for	LMSTR  test
prec	double

file	file19
for	LMDIF  test
prec	double

file	file20
for	CHKDER test
prec	double

file	file21
for	HYBRD and HYBRJ data

file	file22
for	LMDER, LMSTR, and LMDIf data

file	file23
for	CHKDER data

minpack-19961126/ex/thybrj.f0000644000175000017500000000506211616327304016375 0ustar sylvestresylvestreC DRIVER FOR HYBRJ EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR,NWRITE DOUBLE PRECISION XTOL,FACTOR,FNORM DOUBLE PRECISION X(9),FVEC(9),FJAC(9,9),DIAG(9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = DSQRT(DPMPAR(1)) C MAXFEV = 1000 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.D0 20 CONTINUE FACTOR = 1.D2 NPRINT = 0 C CALL HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, * WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRJ EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ EXAMPLE. C INTEGER J,K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.D0,1.D0,2.D0,3.D0,4.D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file070000644000175000017500000002557004210374622015740 0ustar sylvestresylvestreC ********** C C THIS PROGRAM CHECKS THE CONSTANTS OF MACHINE PRECISION AND C SMALLEST AND LARGEST MACHINE REPRESENTABLE NUMBERS SPECIFIED IN C FUNCTION SPMPAR, AGAINST THE CORRESPONDING HARDWARE-DETERMINED C MACHINE CONSTANTS OBTAINED BY SMCHAR, A SUBROUTINE DUE TO C W. J. CODY. C C DATA STATEMENTS IN SPMPAR CORRESPONDING TO THE MACHINE USED MUST C BE ACTIVATED BY REMOVING C IN COLUMN 1. C C THE PRINTED OUTPUT CONSISTS OF THE MACHINE CONSTANTS OBTAINED BY C SMCHAR AND COMPARISONS OF THE SPMPAR CONSTANTS WITH THEIR C SMCHAR COUNTERPARTS. DESCRIPTIONS OF THE MACHINE CONSTANTS ARE C GIVEN IN THE PROLOGUE COMMENTS OF SMCHAR. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SMCHAR,SPMPAR C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IBETA,IEXP,IRND,IT,MACHEP,MAXEXP,MINEXP,NEGEP,NGRD, * NWRITE REAL DWARF,EPS,EPSMCH,EPSNEG,GIANT,XMAX,XMIN REAL RERR(3) REAL SPMPAR C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C C DETERMINE THE MACHINE CONSTANTS DYNAMICALLY FROM SMCHAR. C CALL SMCHAR(IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP,MAXEXP, * EPS,EPSNEG,XMIN,XMAX) C C COMPARE THE SPMPAR CONSTANTS WITH THEIR SMCHAR COUNTERPARTS AND C STORE THE RELATIVE DIFFERENCES IN RERR. C EPSMCH = SPMPAR(1) DWARF = SPMPAR(2) GIANT = SPMPAR(3) RERR(1) = (EPSMCH - EPS)/EPSMCH RERR(2) = (DWARF - XMIN)/DWARF RERR(3) = (XMAX - GIANT)/GIANT C C WRITE THE SMCHAR CONSTANTS. C WRITE (NWRITE,10) * IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP,MAXEXP,EPS, * EPSNEG,XMIN,XMAX C C WRITE THE SPMPAR CONSTANTS AND THE RELATIVE DIFFERENCES. C WRITE (NWRITE,20) EPSMCH,RERR(1),DWARF,RERR(2),GIANT,RERR(3) STOP 10 FORMAT (17H1SMCHAR CONSTANTS /// 8H IBETA =, I6 // 8H IT =, * I6 // 8H IRND =, I6 // 8H NGRD =, I6 // 9H MACHEP =, * I6 // 8H NEGEP =, I6 // 7H IEXP =, I6 // 9H MINEXP =, * I6 // 9H MAXEXP =, I6 // 6H EPS =, E15.7 // 9H EPSNEG =, * E15.7 // 7H XMIN =, E15.7 // 7H XMAX =, E15.7) 20 FORMAT ( /// 42H SPMPAR CONSTANTS AND RELATIVE DIFFERENCES /// * 9H EPSMCH =, E15.7 / 10H RERR(1) =, E15.7 // * 8H DWARF =, E15.7 / 10H RERR(2) =, E15.7 // 8H GIANT =, * E15.7 / 10H RERR(3) =, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE SMCHAR(IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP, 1 MAXEXP,EPS,EPSNEG,XMIN,XMAX) C INTEGER I,IBETA,IEXP,IRND,IT,IZ,J,K,MACHEP,MAXEXP,MINEXP, 1 MX,NEGEP,NGRD REAL A,B,BETA,BETAIN,BETAM1,EPS,EPSNEG,ONE,XMAX,XMIN,Y,Z,ZERO C C THIS SUBROUTINE IS INTENDED TO DETERMINE THE CHARACTERISTICS C OF THE FLOATING-POINT ARITHMETIC SYSTEM THAT ARE SPECIFIED C BELOW. THE FIRST THREE ARE DETERMINED ACCORDING TO AN C ALGORITHM DUE TO M. MALCOLM, CACM 15 (1972), PP. 949-951, C INCORPORATING SOME, BUT NOT ALL, OF THE IMPROVEMENTS C SUGGESTED BY M. GENTLEMAN AND S. MAROVICH, CACM 17 (1974), C PP. 276-277. C C C IBETA - THE RADIX OF THE FLOATING-POINT REPRESENTATION C IT - THE NUMBER OF BASE IBETA DIGITS IN THE FLOATING-POINT C SIGNIFICAND C IRND - 0 IF FLOATING-POINT ADDITION CHOPS, C 1 IF FLOATING-POINT ADDITION ROUNDS C NGRD - THE NUMBER OF GUARD DIGITS FOR MULTIPLICATION. IT IS C 0 IF IRND=1, OR IF IRND=0 AND ONLY IT BASE IBET C DIGITS PARTICIPATE IN THE POST NORMALIZATION SHIFT C OF THE FLOATING-POINT SIGNIFICAND IN MULTIPLICATION C 1 IF IRND=0 AND MORE THAN IT BASE IBETA DIGITS C PARTICIPATE IN THE POST NORMALIZATION SHIFT OF THE C FLOATING-POINT SIGNIFICAND IN MULTIPLICATION C MACHEP - THE LARGEST NEGATIVE INTEGER SUCH THAT C 1.0+FLOAT(IBETA)**MACHEP .NE. 1.0, EXCEPT THAT C MACHEP IS BOUNDED BELOW BY -(IT+3) C NEGEPS - THE LARGEST NEGATIVE INTEGER SUCH THAT C 1.0-FLOAT(IBETA)**NEGEPS .NE. 1.0, EXCEPT THAT C NEGEPS IS BOUNDED BELOW BY -(IT+3) C IEXP - THE NUMBER OF BITS (DECIMAL PLACES IF IBETA = 10) C RESERVED FOR THE REPRESENTATION OF THE EXPONENT C (INCLUDING THE BIAS OR SIGN) OF A FLOATING-POINT C NUMBER C MINEXP - THE LARGEST IN MAGNITUDE NEGATIVE INTEGER SUCH THAT C FLOAT(IBETA)**MINEXP IS A POSITIVE FLOATING-POINT C NUMBER C MAXEXP - THE LARGEST POSITIVE INTEGER EXPONENT FOR A FINITE C FLOATING-POINT NUMBER C EPS - THE SMALLEST POSITIVE FLOATING-POINT NUMBER SUCH C THAT 1.0+EPS .NE. 1.0. IN PARTICULAR, IF EITHER C IBETA = 2 OR IRND = 0, EPS = FLOAT(IBETA)**MACHEP. C OTHERWISE, EPS = (FLOAT(IBETA)**MACHEP)/2 C EPSNEG - A SMALL POSITIVE FLOATING-POINT NUMBER SUCH THAT C 1.0-EPSNEG .NE. 1.0. IN PARTICULAR, IF IBETA = 2 C OR IRND = 0, EPSNEG = FLOAT(IBETA)**NEGEPS. C OTHERWISE, EPSNEG = (IBETA**NEGEPS)/2. BECAUSE C NEGEPS IS BOUNDED BELOW BY -(IT+3), EPSNEG MAY NOT C BE THE SMALLEST NUMBER WHICH CAN ALTER 1.0 BY C SUBTRACTION. C XMIN - THE SMALLEST NON-VANISHING FLOATING-POINT POWER OF TH C RADIX. IN PARTICULAR, XMIN = FLOAT(IBETA)**MINEXP C XMAX - THE LARGEST FINITE FLOATING-POINT NUMBER. IN C PARTICULAR XMAX = (1.0-EPSNEG)*FLOAT(IBETA)**MAXEXP C NOTE - ON SOME MACHINES XMAX WILL BE ONLY THE C SECOND, OR PERHAPS THIRD, LARGEST NUMBER, BEING C TOO SMALL BY 1 OR 2 UNITS IN THE LAST DIGIT OF C THE SIGNIFICAND. C C LATEST REVISION - OCTOBER 22, 1979 C C AUTHOR - W. J. CODY C ARGONNE NATIONAL LABORATORY C C----------------------------------------------------------------- ONE = FLOAT(1) ZERO = 0.0E0 C----------------------------------------------------------------- C DETERMINE IBETA,BETA ALA MALCOLM C----------------------------------------------------------------- A = ONE 10 A = A + A IF (((A+ONE)-A)-ONE .EQ. ZERO) GO TO 10 B = ONE 20 B = B + B IF ((A+B)-A .EQ. ZERO) GO TO 20 IBETA = INT((A+B)-A) BETA = FLOAT(IBETA) C----------------------------------------------------------------- C DETERMINE IT, IRND C----------------------------------------------------------------- IT = 0 B = ONE 100 IT = IT + 1 B = B * BETA IF (((B+ONE)-B)-ONE .EQ. ZERO) GO TO 100 IRND = 0 BETAM1 = BETA - ONE IF ((A+BETAM1)-A .NE. ZERO) IRND = 1 C----------------------------------------------------------------- C DETERMINE NEGEP, EPSNEG C----------------------------------------------------------------- NEGEP = IT + 3 BETAIN = ONE / BETA A = ONE C DO 200 I = 1, NEGEP A = A * BETAIN 200 CONTINUE C B = A 210 IF ((ONE-A)-ONE .NE. ZERO) GO TO 220 A = A * BETA NEGEP = NEGEP - 1 GO TO 210 220 NEGEP = -NEGEP EPSNEG = A IF ((IBETA .EQ. 2) .OR. (IRND .EQ. 0)) GO TO 300 A = (A*(ONE+A)) / (ONE+ONE) IF ((ONE-A)-ONE .NE. ZERO) EPSNEG = A C----------------------------------------------------------------- C DETERMINE MACHEP, EPS C----------------------------------------------------------------- 300 MACHEP = -IT - 3 A = B 310 IF((ONE+A)-ONE .NE. ZERO) GO TO 320 A = A * BETA MACHEP = MACHEP + 1 GO TO 310 320 EPS = A IF ((IBETA .EQ. 2) .OR. (IRND .EQ. 0)) GO TO 350 A = (A*(ONE+A)) / (ONE+ONE) IF ((ONE+A)-ONE .NE. ZERO) EPS = A C----------------------------------------------------------------- C DETERMINE NGRD C----------------------------------------------------------------- 350 NGRD = 0 IF ((IRND .EQ. 0) .AND. ((ONE+EPS)*ONE-ONE) .NE. ZERO) NGRD = 1 C----------------------------------------------------------------- C DETERMINE IEXP, MINEXP, XMIN C C LOOP TO DETERMINE LARGEST I AND K = 2**I SUCH THAT C (1/BETA) ** (2**(I)) C DOES NOT UNDERFLOW C EXIT FROM LOOP IS SIGNALED BY AN UNDERFLOW. C----------------------------------------------------------------- I = 0 K = 1 Z = BETAIN 400 Y = Z Z = Y * Y C----------------------------------------------------------------- C CHECK FOR UNDERFLOW HERE C----------------------------------------------------------------- A = Z * ONE IF ((A+A .EQ. ZERO) .OR. (ABS(Z) .GE. Y)) GO TO 410 I = I + 1 K = K + K GO TO 400 410 IF (IBETA .EQ. 10) GO TO 420 IEXP = I + 1 MX = K + K GO TO 450 C----------------------------------------------------------------- C FOR DECIMAL MACHINES ONLY C----------------------------------------------------------------- 420 IEXP = 2 IZ = IBETA 430 IF (K .LT. IZ) GO TO 440 IZ = IZ * IBETA IEXP = IEXP + 1 GO TO 430 440 MX = IZ + IZ - 1 C----------------------------------------------------------------- C LOOP TO DETERMINE MINEXP, XMIN C EXIT FROM LOOP IS SIGNALED BY AN UNDERFLOW. C----------------------------------------------------------------- 450 XMIN = Y Y = Y * BETAIN C----------------------------------------------------------------- C CHECK FOR UNDERFLOW HERE C----------------------------------------------------------------- A = Y * ONE IF (((A+A) .EQ. ZERO) .OR. (ABS(Y) .GE. XMIN)) GO TO 460 K = K + 1 GO TO 450 460 MINEXP = -K C----------------------------------------------------------------- C DETERMINE MAXEXP, XMAX C----------------------------------------------------------------- IF ((MX .GT. K+K-3) .OR. (IBETA .EQ. 10)) GO TO 500 MX = MX + MX IEXP = IEXP + 1 500 MAXEXP = MX + MINEXP C----------------------------------------------------------------- C ADJUST FOR MACHINES WITH IMPLICIT LEADING C BIT IN BINARY SIGNIFICAND AND MACHINES WITH C RADIX POINT AT EXTREME RIGHT OF SIGNIFICAND C----------------------------------------------------------------- I = MAXEXP + MINEXP IF ((IBETA .EQ. 2) .AND. (I .EQ. 0)) MAXEXP = MAXEXP - 1 IF (I .GT. 20) MAXEXP = MAXEXP - 1 IF (A .NE. Y) MAXEXP = MAXEXP - 2 XMAX = ONE - EPSNEG IF (XMAX*ONE .NE. XMAX) XMAX = ONE - BETA * EPSNEG XMAX = XMAX / (BETA * BETA * BETA * XMIN) I = MAXEXP + MINEXP + 3 IF (I .LE. 0) GO TO 520 C DO 510 J = 1, I IF (IBETA .EQ. 2) XMAX = XMAX + XMAX IF (IBETA .NE. 2) XMAX = XMAX * BETA 510 CONTINUE C 520 RETURN C ---------- LAST CARD OF SMCHAR ---------- END minpack-19961126/ex/tlmstr1.f0000644000175000017500000000427211616327304016503 0ustar sylvestresylvestreC DRIVER FOR LMSTR1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(3,3),WA(30) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 3 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMSTR1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.D0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/tchkder.f0000644000175000017500000000457711616327304016531 0ustar sylvestresylvestreC DRIVER FOR CHKDER EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER I,M,N,LDFJAC,MODE,NWRITE DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),XP(3),FVECP(15), * ERR(15) C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING VALUES SHOULD BE SUITABLE FOR C CHECKING THE JACOBIAN MATRIX. C X(1) = 9.2D-1 X(2) = 1.3D-1 X(3) = 5.4D-1 C LDFJAC = 15 C MODE = 1 CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) MODE = 2 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,1) CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,2) CALL FCN(M,N,XP,FVECP,FJAC,LDFJAC,1) CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) C DO 10 I = 1, M FVECP(I) = FVECP(I) - FVEC(I) 10 CONTINUE WRITE (NWRITE,1000) (FVEC(I),I=1,M) WRITE (NWRITE,2000) (FVECP(I),I=1,M) WRITE (NWRITE,3000) (ERR(I),I=1,M) STOP 1000 FORMAT (/5X,5H FVEC // (5X,3D15.7)) 2000 FORMAT (/5X,13H FVECP - FVEC // (5X,3D15.7)) 3000 FORMAT (/5X,4H ERR // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR CHKDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR CHKDER EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I C C ERROR INTRODUCED INTO NEXT STATEMENT FOR ILLUSTRATION. C CORRECTED STATEMENT SHOULD READ TMP3 = TMP1 . C TMP3 = TMP2 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file060000644000175000017500000050702211616327304015737 0ustar sylvestresylvestre Page Documentation for MINPACK subroutine HYBRD1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of HYBRD1 is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. This is done by using the more general nonlinear equation solver HYBRD. The user must provide a subroutine which calculates the functions. The Jacobian is then calculated by a forward-difference approximation. 2. Subroutine and type statements. SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) INTEGER N,INFO,LWA DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(N),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to HYBRD1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRD1. FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of HYBRD1. In this case set IFLAG to a negative integer. Page N is a positive integer input variable set to the number of functions and variables. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length N which contains the function evaluated at the output X. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates that the relative error between X and the solution is at most TOL. Section 4 contains more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 2 Number of calls to FCN has reached or exceeded 200*(N+1). INFO = 3 TOL is too small. No further improvement in the approximate solution X is possible. INFO = 4 Iteration is not making good progress. Sections 4 and 5 contain more details about INFO. WA is a work array of length LWA. LWA is a positive integer input variable not less than (N*(3*N+13))/2. 4. Successful completion. The accuracy of HYBRD1 is controlled by the convergence parame- ter TOL. This parameter is used in a test which makes a compar- ison between the approximation X and a solution XSOL. HYBRD1 terminates when the test is satisfied. If TOL is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then HYBRD1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The test assumes that the functions are reasonably well behaved Page If this condition is not satisfied, then HYBRD1 may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning HYBRD1 with a tighter toler- ance. Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(X-XSOL) .LE. TOL*ENORM(XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of X have K significant decimal digits and INFO is set to 1. There is a danger that the smaller compo- nents of X may have large relative errors, but the fast rate of convergence of HYBRD1 usually avoids this possibility. 5. Unsuccessful completion. Unsuccessful termination of HYBRD1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, errors in the functions, or lack of good prog ress. Improper input parameters. INFO is set to 0 if N .LE. 0, or TOL .LT. 0.D0, or LWA .LT. (N*(3*N+13))/2. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRD1. In this case, it may be possible to remedy the situation by not evalu- ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead HYBRD, which includes in its calling sequence the step-length- governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN reaches 200*(N+1), then this indicates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 2. This situation should be unu- sual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRD1, causing termination with INFO = 4. Errors in the functions. The choice of step length in the for- ward-difference approximation to the Jacobian assumes that th relative errors in the functions are of the order of the machine precision. If this is not the case, HYBRD1 may fail (usually with INFO = 4). The user should then use HYBRD instead, or one of the programs which require the analytic Jacobian (HYBRJ1 and HYBRJ). Page Lack of good progress. HYBRD1 searches for a zero of the system by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ- ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRD1 from a dif- ferent starting point may be helpful. 6. Characteristics of the algorithm. HYBRD1 is a modification of the Powell hybrid method. Two of its main characteristics involve the choice of the correction a a convex combination of the Newton and scaled gradient direc- tions, and the updating of the Jacobian by the rank-1 method of Broyden. The choice of the correction guarantees (under reason able conditions) global convergence for starting points far fro the solution and a fast rate of convergence. The Jacobian is approximated by forward differences at the starting point, but forward differences are not used again until the rank-1 method fails to produce satisfactory progress. Timing. The time required by HYBRD1 to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRD1 is about 11.5*(N**2) to process each call to FCN. Unless FCN can be evaluated quickly, the timing of HYBRD1 will be strongly influenced by the time spent in FCN. Storage. HYBRD1 requires (3*N**2 + 17*N)/2 double precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DOGLEG,DPMPAR,ENORM,FDJAC1,HYBRD, QFORM,QRFAC,R1MPYQ,R1UPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MIN0,MOD 8. References. M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 9. Example. Page The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 C ********** C C DRIVER FOR HYBRD1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,INFO,LWA,NWRITE DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(9),FVEC(9),WA(180) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LWA = 180 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRD1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) C Page C SUBROUTINE FCN FOR HYBRD1 EXAMPLE. C INTEGER K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.D0,1.D0,2.D0,3.D0/ C DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.1192636D-07 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION -0.5706545D+00 -0.6816283D+00 -0.7017325D+00 -0.7042129D+00 -0.7013690D+00 -0.6918656D+00 -0.6657920D+00 -0.5960342D+00 -0.4164121D+00 Page Documentation for MINPACK subroutine HYBRD Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of HYBRD is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. The user must provide a subroutine which calcu- lates the functions. The Jacobian is then calculated by a for- ward-difference approximation. 2. Subroutine and type statements. SUBROUTINE HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * R,LR,QTF,WA1,WA2,WA3,WA4) INTEGER N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR DOUBLE PRECISION XTOL,EPSFCN,FACTOR DOUBLE PRECISION X(N),FVEC(N),DIAG(N),FJAC(LDFJAC,N),R(LR),QTF( * WA1(N),WA2(N),WA3(N),WA4(N) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to HYBRD and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRD. FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END The value of IFLAG should not be changed by FCN unless the Page user wants to terminate execution of HYBRD. In this case set IFLAG to a negative integer. N is a positive integer input variable set to the number of functions and variables. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length N which contains the function evaluated at the output X. XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at most XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN is at least MAXFEV by the end of an iteration. ML is a nonnegative integer input variable which specifies the number of subdiagonals within the band of the Jacobian matrix If the Jacobian is not banded, set ML to at least N - 1. MU is a nonnegative integer input variable which specifies the number of superdiagonals within the band of the Jacobian matrix. If the Jacobian is not banded, set MU to at least N - 1. EPSFCN is an input variable used in determining a suitable step for the forward-difference approximation. This approximation assumes that the relative errors in the functions are of the order of EPSFCN. If EPSFCN is less than the machine preci- sion, it is assumed that the relative errors in the functions are of the order of the machine precision. DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci- fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. FACTOR is a positive input variable used in determining the ini- tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. Page NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Relative error between two consecutive iterates is at most XTOL. INFO = 2 Number of calls to FCN has reached or exceeded MAXFEV. INFO = 3 XTOL is too small. No further improvement in the approximate solution X is possible. INFO = 4 Iteration is not making good progress, as measured by the improvement from the last five Jacobian eval- uations. INFO = 5 Iteration is not making good progress, as measured by the improvement from the last ten iterations. Sections 4 and 5 contain more details about INFO. NFEV is an integer output variable set to the number of calls t FCN. FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx- imate Jacobian. LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. R is an output array of length LR which contains the upper triangular matrix produced by the QR factorization of the final approximate Jacobian, stored rowwise. LR is a positive integer input variable not less than (N*(N+1))/2. QTF is an output array of length N which contains the vector (Q transpose)*FVEC. WA1, WA2, WA3, and WA4 are work arrays of length N. Page 4. Successful completion. The accuracy of HYBRD is controlled by the convergence parameter XTOL. This parameter is used in a test which makes a comparison between the approximation X and a solution XSOL. HYBRD termi- nates when the test is satisfied. If the convergence parameter is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then HYBRD only attempts to satisfy the test defined by the machine precision. Further progress is not usually possible. The test assumes that the functions are reasonably well behaved If this condition is not satisfied, then HYBRD may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning HYBRD with a tighter toler- ance. Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z and D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempts to guaran- tee that ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 1. There is a danger that the smaller compo- nents of D*X may have large relative errors, but the fast rat of convergence of HYBRD usually avoids this possibility. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 5. Unsuccessful completion. Unsuccessful termination of HYBRD can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. Improper input parameters. INFO is set to 0 if N .LE. 0, or XTOL .LT. 0.D0, or MAXFEV .LE. 0, or ML .LT. 0, or MU .LT. 0, or FACTOR .LE. 0.D0, or LDFJAC .LT. N, or LR .LT. (N*(N+1))/2 Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRD. In this case, it may be possible to remedy the situation by rerunning HYBRD with a smaller value of FACTOR. Excessive number of function evaluations. A reasonable value for MAXFEV is 200*(N+1). If the number of calls to FCN reaches MAXFEV, then this indicates that the routine is con- verging very slowly as measured by the progress of FVEC, and Page INFO is set to 2. This situation should be unusual because, as indicated below, lack of good progress is usually diagnose earlier by HYBRD, causing termination with INFO = 4 or INFO = 5. Lack of good progress. HYBRD searches for a zero of the system by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ- ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRD from a dif- ferent starting point may be helpful. 6. Characteristics of the algorithm. HYBRD is a modification of the Powell hybrid method. Two of it main characteristics involve the choice of the correction as a convex combination of the Newton and scaled gradient directions and the updating of the Jacobian by the rank-1 method of Broy- den. The choice of the correction guarantees (under reasonable conditions) global convergence for starting points far from the solution and a fast rate of convergence. The Jacobian is approximated by forward differences at the starting point, but forward differences are not used again until the rank-1 method fails to produce satisfactory progress. Timing. The time required by HYBRD to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRD is about 11.5*(N**2) to process each call to FCN. Unless FCN can be evaluated quickly, the timing of HYBRD will be strongly influenced by the time spent in FCN. Storage. HYBRD requires (3*N**2 + 17*N)/2 double precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DOGLEG,DPMPAR,ENORM,FDJAC1, QFORM,QRFAC,R1MPYQ,R1UPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MIN0,MOD 8. References. M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Page Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 9. Example. The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 C ********** C C DRIVER FOR HYBRD EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR,NWRITE DOUBLE PRECISION XTOL,EPSFCN,FACTOR,FNORM DOUBLE PRECISION X(9),FVEC(9),DIAG(9),FJAC(9,9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = DSQRT(DPMPAR(1)) C MAXFEV = 2000 ML = 1 MU = 1 EPSFCN = 0.D0 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.D0 Page 20 CONTINUE FACTOR = 1.D2 NPRINT = 0 C CALL HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * R,LR,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRD EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) C C SUBROUTINE FCN FOR HYBRD EXAMPLE. C INTEGER K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.D0,1.D0,2.D0,3.D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.1192636D-07 NUMBER OF FUNCTION EVALUATIONS 14 Page EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION -0.5706545D+00 -0.6816283D+00 -0.7017325D+00 -0.7042129D+00 -0.7013690D+00 -0.6918656D+00 -0.6657920D+00 -0.5960342D+00 -0.4164121D+00 Page Documentation for MINPACK subroutine HYBRJ1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of HYBRJ1 is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. This is done by using the more general nonlinear equation solver HYBRJ. The user must provide a subroutine which calculates the functions and the Jacobian. 2. Subroutine and type statements. SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) INTEGER N,LDFJAC,INFO,LWA DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to HYBRJ1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRJ1. FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END The value of IFLAG should not be changed by FCN unless the Page user wants to terminate execution of HYBRJ1. In this case set IFLAG to a negative integer. N is a positive integer input variable set to the number of functions and variables. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length N which contains the function evaluated at the output X. FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx- imate Jacobian. Section 6 contains more details about the approximation to the Jacobian. LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates that the relative error between X and the solution is at most TOL. Section 4 contains more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 2 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). INFO = 3 TOL is too small. No further improvement in the approximate solution X is possible. INFO = 4 Iteration is not making good progress. Sections 4 and 5 contain more details about INFO. WA is a work array of length LWA. LWA is a positive integer input variable not less than (N*(N+13))/2. 4. Successful completion. The accuracy of HYBRJ1 is controlled by the convergence Page parameter TOL. This parameter is used in a test which makes a comparison between the approximation X and a solution XSOL. HYBRJ1 terminates when the test is satisfied. If TOL is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then HYBRJ1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The test assumes that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then HYBRJ1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning HYBRJ1 with a tighter toler- ance. Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(X-XSOL) .LE. TOL*ENORM(XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of X have K significant decimal digits and INFO is set to 1. There is a danger that the smaller compo- nents of X may have large relative errors, but the fast rate of convergence of HYBRJ1 usually avoids this possibility. 5. Unsuccessful completion. Unsuccessful termination of HYBRJ1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. Improper input parameters. INFO is set to 0 if N .LE. 0, or LDFJAC .LT. N, or TOL .LT. 0.D0, or LWA .LT. (N*(N+13))/2. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRJ1. In this case, it may be possible to remedy the situation by not evalu ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead HYBRJ, which includes in its calling sequence the step-length- governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi- cates that the routine is converging very slowly as measured Page by the progress of FVEC, and INFO is set to 2. This situation should be unusual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRJ1, causing ter- mination with INFO = 4. Lack of good progress. HYBRJ1 searches for a zero of the system by minimizing the sum of the squares of the functions. In so doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ- ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRJ1 from a dif- ferent starting point may be helpful. 6. Characteristics of the algorithm. HYBRJ1 is a modification of the Powell hybrid method. Two of its main characteristics involve the choice of the correction a a convex combination of the Newton and scaled gradient direc- tions, and the updating of the Jacobian by the rank-1 method of Broyden. The choice of the correction guarantees (under reason able conditions) global convergence for starting points far fro the solution and a fast rate of convergence. The Jacobian is calculated at the starting point, but it is not recalculated until the rank-1 method fails to produce satisfactory progress. Timing. The time required by HYBRJ1 to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRJ1 is about 11.5*(N**2) to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.3*(N**3) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of HYBRJ1 will be strongly influenced by the time spent in FCN. Storage. HYBRJ1 requires (3*N**2 + 17*N)/2 double precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DOGLEG,DPMPAR,ENORM,HYBRJ, QFORM,QRFAC,R1MPYQ,R1UPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MIN0,MOD 8. References. Page M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 9. Example. The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 C ********** C C DRIVER FOR HYBRJ1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,INFO,LWA,NWRITE DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(9),FVEC(9),FJAC(9,9),WA(99) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LWA = 99 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) Page C C LAST CARD OF DRIVER FOR HYBRJ1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ1 EXAMPLE. C INTEGER J,K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.D0,1.D0,2.D0,3.D0,4.D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.1192636D-07 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION -0.5706545D+00 -0.6816283D+00 -0.7017325D+00 -0.7042129D+00 -0.7013690D+00 -0.6918656D+00 -0.6657920D+00 -0.5960342D+00 -0.4164121D+00 Page Documentation for MINPACK subroutine HYBRJ Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of HYBRJ is to find a zero of a system of N non- linear functions in N variables by a modification of the Powell hybrid method. The user must provide a subroutine which calcu- lates the functions and the Jacobian. 2. Subroutine and type statements. SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, * WA1,WA2,WA3,WA4) INTEGER N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR DOUBLE PRECISION XTOL,FACTOR DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N),DIAG(N),R(LR),QTF( * WA1(N),WA2(N),WA3(N),WA4(N) 3. Parameters. Parameters designated as input parameters must be specified on entry to HYBRJ and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from HYBRJ. FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END Page The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of HYBRJ. In this case set IFLAG to a negative integer. N is a positive integer input variable set to the number of functions and variables. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length N which contains the function evaluated at the output X. FJAC is an output N by N array which contains the orthogonal matrix Q produced by the QR factorization of the final approx- imate Jacobian. Section 6 contains more details about the approximation to the Jacobian. LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at most XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached MAXFEV. DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci- fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. FACTOR is a positive input variable used in determining the ini- tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. FVEC and FJAC should not be altered. If NPRINT is not positive, no Page special calls of FCN with IFLAG = 0 are made. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Relative error between two consecutive iterates is at most XTOL. INFO = 2 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. INFO = 3 XTOL is too small. No further improvement in the approximate solution X is possible. INFO = 4 Iteration is not making good progress, as measured by the improvement from the last five Jacobian eval- uations. INFO = 5 Iteration is not making good progress, as measured by the improvement from the last ten iterations. Sections 4 and 5 contain more details about INFO. NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. R is an output array of length LR which contains the upper triangular matrix produced by the QR factorization of the final approximate Jacobian, stored rowwise. LR is a positive integer input variable not less than (N*(N+1))/2. QTF is an output array of length N which contains the vector (Q transpose)*FVEC. WA1, WA2, WA3, and WA4 are work arrays of length N. 4. Successful completion. The accuracy of HYBRJ is controlled by the convergence parameter XTOL. This parameter is used in a test which makes a comparison between the approximation X and a solution XSOL. HYBRJ termi- nates when the test is satisfied. If the convergence parameter is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then HYBRJ only attempts to satisfy the test defined by the machine precision. Further progress is not Page usually possible. The test assumes that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then HYBRJ may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning HYBRJ with a tighter toler- ance. Convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z and D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempts to guaran- tee that ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 1. There is a danger that the smaller compo- nents of D*X may have large relative errors, but the fast rat of convergence of HYBRJ usually avoids this possibility. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. 5. Unsuccessful completion. Unsuccessful termination of HYBRJ can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or lack of good progress. Improper input parameters. INFO is set to 0 if N .LE. 0, or LDFJAC .LT. N, or XTOL .LT. 0.D0, or MAXFEV .LE. 0, or FACTOR .LE. 0.D0, or LR .LT. (N*(N+1))/2. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by HYBRJ. In this case, it may be possible to remedy the situation by rerunning HYBRJ with a smaller value of FACTOR. Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routine is converging very slowly as measured by the progress of FVEC and INFO is set to 2. This situation should be unusual because, as indicated below, lack of good progress is usually diagnosed earlier by HYBRJ, causing termination with INFO = 4 or INFO = 5. Lack of good progress. HYBRJ searches for a zero of the system by minimizing the sum of the squares of the functions. In so Page doing, it can become trapped in a region where the minimum does not correspond to a zero of the system and, in this situ- ation, the iteration eventually fails to make good progress. In particular, this will happen if the system does not have a zero. If the system has a zero, rerunning HYBRJ from a dif- ferent starting point may be helpful. 6. Characteristics of the algorithm. HYBRJ is a modification of the Powell hybrid method. Two of it main characteristics involve the choice of the correction as a convex combination of the Newton and scaled gradient directions and the updating of the Jacobian by the rank-1 method of Broy- den. The choice of the correction guarantees (under reasonable conditions) global convergence for starting points far from the solution and a fast rate of convergence. The Jacobian is calcu lated at the starting point, but it is not recalculated until the rank-1 method fails to produce satisfactory progress. Timing. The time required by HYBRJ to solve a given problem depends on N, the behavior of the functions, the accuracy requested, and the starting point. The number of arithmetic operations needed by HYBRJ is about 11.5*(N**2) to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.3*(N**3) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of HYBRJ will be strongly influenced by the time spent in FCN. Storage. HYBRJ requires (3*N**2 + 17*N)/2 double precision storage locations, in addition to the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DOGLEG,DPMPAR,ENORM, QFORM,QRFAC,R1MPYQ,R1UPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MIN0,MOD 8. References. M. J. D. Powell, A Hybrid Method for Nonlinear Equations. Numerical Methods for Nonlinear Algebraic Equations, P. Rabinowitz, editor. Gordon and Breach, 1970. 9. Example. Page The problem is to determine the values of x(1), x(2), ..., x(9) which solve the system of tridiagonal equations (3-2*x(1))*x(1) -2*x(2) = -1 -x(i-1) + (3-2*x(i))*x(i) -2*x(i+1) = -1, i=2-8 -x(8) + (3-2*x(9))*x(9) = -1 C ********** C C DRIVER FOR HYBRJ EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR,NWRITE DOUBLE PRECISION XTOL,FACTOR,FNORM DOUBLE PRECISION X(9),FVEC(9),FJAC(9,9),DIAG(9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = DSQRT(DPMPAR(1)) C MAXFEV = 1000 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.D0 20 CONTINUE FACTOR = 1.D2 NPRINT = 0 C CALL HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, * WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) Page STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRJ EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ EXAMPLE. C INTEGER J,K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.D0,1.D0,2.D0,3.D0,4.D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. Page FINAL L2 NORM OF THE RESIDUALS 0.1192636D-07 NUMBER OF FUNCTION EVALUATIONS 11 NUMBER OF JACOBIAN EVALUATIONS 1 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION -0.5706545D+00 -0.6816283D+00 -0.7017325D+00 -0.7042129D+00 -0.7013690D+00 -0.6918656D+00 -0.6657920D+00 -0.5960342D+00 -0.4164121D+00 Page Documentation for MINPACK subroutine LMDER1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMDER1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. This is done by using the more general least-squares solver LMDER. The user must provide a subroutine which calculates the functions and the Jacobian. 2. Subroutine and type statements. SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to LMDER1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDER1. FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END Page The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDER1. In this case set IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that T T T P *(JAC *JAC)*P = R *R, where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 FVEC is orthogonal to the columns of the Jacobian t machine precision. Page INFO = 5 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. Sections 4 and 5 contain more details about INFO. IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. WA is a work array of length LWA. LWA is a positive integer input variable not less than 5*N+M. 4. Successful completion. The accuracy of LMDER1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMDER1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func- tion DPMPAR(1)), then LMDER1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMDER1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMDER1 with a tighter toler- ance. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also Page satisfied). Second convergence test. If D is a diagonal matrix (implicitly generated by LMDER1) whose entries contain scale factors for the variables, then this test attempts to guarantee that ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMDER1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 5. Unsuccessful completion. Unsuccessful termination of LMDER1 can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or TOL .LT. 0.D0, or LWA .LT. 5*N+M. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDER1. In this case, it may be possible to remedy the situation by not evalu- ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMDER, which includes in its calling sequence the step-length- governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi- cates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMDER1, thereby forcing it to disregard old (and possibly harmful) information. Page 6. Characteristics of the algorithm. LMDER1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMDER1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. Timing. The time required by LMDER1 to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDER1 is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and M*(N**2) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, the timing of LMDER1 will be strongly influenced by the time spent in FCN. Storage. LMDER1 requires M*N + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,LMDER,LMPAR,QRFAC,QRSOLV FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data Page y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMDER1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),WA(30) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDER1 EXAMPLE. C Page END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241058D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine LMDER Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMDER is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. The user must provide a subrou- tine which calculates the functions and the Jacobian. 2. Subroutine and type statements. SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) 3. Parameters. Parameters designated as input parameters must be specified on entry to LMDER and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDER. FCN is the name of the user-supplied subroutine which calculate the functions and the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows. SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND RETURN THIS MATRIX IN FJAC. DO NOT ALTER FVEC. ---------- RETURN END Page The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDER. In this case set IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that T T T P *(JAC *JAC)*P = R *R, where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at most XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vector and the columns of the Jacobian. Section 4 contains more details about GTOL. MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached MAXFEV. Page DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci- fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. FACTOR is a positive input variable used in determining the ini- tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X, FVEC, and FJAC available for printing. FVEC and FJAC should not be altered. If NPRINT is not posi- tive, no special calls of FCN with IFLAG = 0 are made. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. INFO = 2 Relative error between two consecutive iterates is at most XTOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. INFO = 5 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. Sections 4 and 5 contain more details about INFO. Page NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. WA1, WA2, and WA3 are work arrays of length N. WA4 is a work array of length M. 4. Successful completion. The accuracy of LMDER is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMDER terminates when any of the tests is satisfied. If any of the convergence parameters is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then LMDER only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMDER may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMDER with tighter toler- ances. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the recommended value for FTOL is the square root of the machine precision. Page Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMDER, and furthermore, the test is equally well satisfied at other crit- ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 5. Unsuccessful completion. Unsuccessful termination of LMDER can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or FTOL .LT. 0.D0, or XTOL .LT. 0.D0, or GTOL .LT. 0.D0, or MAXFEV .LE. 0, or FACTOR .LE. 0.D0. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDER. In this case, it may be possible to remedy the situation by rerunning LMDER with a smaller value of FACTOR. Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routine is converging very slowly as measured by the progress of FVEC and INFO is set to 5. In this case, it may be helpful to restart LMDER with MODE set to 1. 6. Characteristics of the algorithm. LMDER is a modification of the Levenberg-Marquardt algorithm. Page Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMDER and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. Timing. The time required by LMDER to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDER is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and M*(N**2) to process each evaluation of the Jacobian (call to FCN with IFLAG = 2). Unless FCN can be evaluated quickly, th timing of LMDER will be strongly influenced by the time spent in FCN. Storage. LMDER requires M*N + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,LMPAR,QRFAC,QRSOLV FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), Page where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMDER EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 400 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // Page * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Page Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 NUMBER OF FUNCTION EVALUATIONS 6 NUMBER OF JACOBIAN EVALUATIONS 5 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241058D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine LMSTR1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMSTR1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm which uses minimal storage. This is done by using the more general least-squares solver LMSTR. The user must provide a subroutine which calculates the func- tions and the rows of the Jacobian. 2. Subroutine and type statements. SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to LMSTR1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMSTR1. FCN is the name of the user-supplied subroutine which calculate the functions and the rows of the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program and should be written as follows. SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. ---------- RETURN Page END The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMSTR1. In this case set IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. FJAC is an output N by N array. The upper triangle of FJAC con tains an upper triangular matrix R such that T T T P *(JAC *JAC)*P = R *R, where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower triangular part of FJAC contains information generated during the computation of R. LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 FVEC is orthogonal to the columns of the Jacobian t Page machine precision. INFO = 5 Number of calls to FCN with IFLAG = 1 has reached 100*(N+1). INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. Sections 4 and 5 contain more details about INFO. IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular. Column j of P is column IPVT(j) of the identity matrix. WA is a work array of length LWA. LWA is a positive integer input variable not less than 5*N+M. 4. Successful completion. The accuracy of LMSTR1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMSTR1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func- tion DPMPAR(1)), then LMSTR1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMSTR1 ma incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMSTR1 with a tighter toler- ance. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an Page INFO is set to 1 (or to 3 if the second test is also satis- fied). Second convergence test. If D is a diagonal matrix (implicitly generated by LMSTR1) whose entries contain scale factors for the variables, then this test attempts to guarantee that ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMSTR1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 5. Unsuccessful completion. Unsuccessful termination of LMSTR1 can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. N, or TOL .LT. 0.D0, or LWA .LT. 5*N+M. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMSTR1. In this case, it may be possible to remedy the situation by not evalu- ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMSTR, which includes in its calling sequence the step-length- governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN with IFLAG = 1 reaches 100*(N+1), then this indi- cates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMSTR1, thereby forcing it to disregard old (and possibly harmful) information. Page 6. Characteristics of the algorithm. LMSTR1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMSTR1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. Timing. The time required by LMSTR1 to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMSTR1 is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.5*(N**2) to process each row of the Jacobian (call to FCN with IFLAG .GE. 2). Unless FCN can be evaluated quickly, the timing of LMSTR1 will be strongly influenced by the time spent in FCN. Storage. LMSTR1 requires N**2 + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,LMSTR,LMPAR,QRFAC,QRSOLV, RWUPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 Page to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMSTR1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,INFO,LWA,NWRITE INTEGER IPVT(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(3,3),WA(30) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 3 LWA = 30 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL, * INFO,IPVT,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C Page C LAST CARD OF DRIVER FOR LMSTR1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.D0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241058D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine LMSTR Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMSTR is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm which uses minimal storage. The user must provide a subroutine which calculates the functions and the rows of the Jacobian. 2. Subroutine and type statements. SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) 3. Parameters. Parameters designated as input parameters must be specified on entry to LMSTR and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMSTR. FCN is the name of the user-supplied subroutine which calculate the functions and the rows of the Jacobian. FCN must be declared in an EXTERNAL statement in the user calling program and should be written as follows. SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) ---------- IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. ---------- RETURN Page END The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMSTR. In this case set IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. FJAC is an output N by N array. The upper triangle of FJAC con tains an upper triangular matrix R such that T T T P *(JAC *JAC)*P = R *R, where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower triangular part of FJAC contains information generated during the computation of R. LDFJAC is a positive integer input variable not less than N which specifies the leading dimension of the array FJAC. FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at most XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vector and the columns of the Jacobian. Section 4 contains more details about GTOL. MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN with IFLAG = 1 has reached Page MAXFEV. DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is speci- fied by the input DIAG. Other values of MODE are equivalent to MODE = 1. FACTOR is a positive input variable used in determining the ini- tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. INFO = 2 Relative error between two consecutive iterates is at most XTOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. INFO = 5 Number of calls to FCN with IFLAG = 1 has reached MAXFEV. INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. Page Sections 4 and 5 contain more details about INFO. NFEV is an integer output variable set to the number of calls t FCN with IFLAG = 1. NJEV is an integer output variable set to the number of calls t FCN with IFLAG = 2. IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular. Column j of P is column IPVT(j) of the identity matrix. QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. WA1, WA2, and WA3 are work arrays of length N. WA4 is a work array of length M. 4. Successful completion. The accuracy of LMSTR is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMSTR terminates when any of the tests is satisfied. If any of the convergence parameters is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then LMSTR only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. The tests assume that the functions and the Jacobian are coded consistently, and that the functions are reasonably well behaved. If these conditions are not satisfied, then LMSTR may incorrectly indicate convergence. The coding of the Jacobian can be checked by the MINPACK subroutine CHKDER. If the Jaco- bian is coded correctly, then the validity of the answer can be checked, for example, by rerunning LMSTR with tighter toler- ances. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the recommended value for FTOL is the square root of the machine Page precision. Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMSTR, and furthermore, the test is equally well satisfied at other crit- ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 5. Unsuccessful completion. Unsuccessful termination of LMSTR can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. N, or FTOL .LT. 0.D0, or XTOL .LT. 0.D0, or GTOL .LT. 0.D0, or MAXFEV .LE. 0, or FACTOR .LE. 0.D0. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMSTR. In this case, it may be possible to remedy the situation by rerunning LMSTR with a smaller value of FACTOR. Excessive number of function evaluations. A reasonable value for MAXFEV is 100*(N+1). If the number of calls to FCN with IFLAG = 1 reaches MAXFEV, then this indicates that the routine is converging very slowly as measured by the progress of FVEC and INFO is set to 5. In this case, it may be helpful to restart LMSTR with MODE set to 1. 6. Characteristics of the algorithm. Page LMSTR is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMSTR and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. Timing. The time required by LMSTR to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMSTR is about N**3 to process each evaluation of the functions (call to FCN with IFLAG = 1) and 1.5*(N**2) to process each row of the Jacobian (call to FCN with IFLAG .GE. 2). Unless FCN can be evaluated quickly, the timing of LMSTR will be strongly influenced by the time spent in FCN. Storage. LMSTR requires N**2 + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,LMPAR,QRFAC,QRSOLV,RWUPDT FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), Page where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMSTR EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(3,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 3 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 400 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // Page * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMSTR EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.D0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Page Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 NUMBER OF FUNCTION EVALUATIONS 6 NUMBER OF JACOBIAN EVALUATIONS 5 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241058D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine LMDIF1 Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMDIF1 is to minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. This is done by using the more general least-squares solver LMDIF. The user must provide a subroutine which calculates the functions. The Jacobian is the calculated by a forward-difference approximation. 2. Subroutine and type statements. SUBROUTINE LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) INTEGER M,N,INFO,LWA INTEGER IWA(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),WA(LWA) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to LMDIF1 and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDIF1. FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDIF1. In this case set Page IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. TOL is a nonnegative input variable. Termination occurs when the algorithm estimates either that the relative error in the sum of squares is at most TOL or that the relative error between X and the solution is at most TOL. Section 4 contain more details about TOL. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Algorithm estimates that the relative error in the sum of squares is at most TOL. INFO = 2 Algorithm estimates that the relative error between X and the solution is at most TOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 FVEC is orthogonal to the columns of the Jacobian t machine precision. INFO = 5 Number of calls to FCN has reached or exceeded 200*(N+1). INFO = 6 TOL is too small. No further reduction in the sum of squares is possible. INFO = 7 TOL is too small. No further improvement in the approximate solution X is possible. Sections 4 and 5 contain more details about INFO. IWA is an integer work array of length N. WA is a work array of length LWA. LWA is a positive integer input variable not less than Page M*N+5*N+M. 4. Successful completion. The accuracy of LMDIF1 is controlled by the convergence parame- ter TOL. This parameter is used in tests which make three type of comparisons between the approximation X and a solution XSOL. LMDIF1 terminates when any of the tests is satisfied. If TOL i less than the machine precision (as defined by the MINPACK func- tion DPMPAR(1)), then LMDIF1 only attempts to satisfy the test defined by the machine precision. Further progress is not usu- ally possible. Unless high precision solutions are required, the recommended value for TOL is the square root of the machine precision. The tests assume that the functions are reasonably well behaved If this condition is not satisfied, then LMDIF1 may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning LMDIF1 with a tighter toler- ance. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with TOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Second convergence test. If D is a diagonal matrix (implicitly generated by LMDIF1) whose entries contain scale factors for the variables, then this test attempts to guarantee that ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL). If this condition is satisfied with TOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but the choice of D is such that the accuracy of the components of X is usually related t their sensitivity. Third convergence test. This test is satisfied when FVEC is orthogonal to the columns of the Jacobian to machine preci- sion. There is no clear relationship between this test and the accuracy of LMDIF1, and furthermore, the test is equally well satisfied at other critical points, namely maximizers an saddle points. Also, errors in the functions (see below) may result in the test being satisfied at a point not close to th Page minimum. Therefore, termination caused by this test (INFO = 4) should be examined carefully. 5. Unsuccessful completion. Unsuccessful termination of LMDIF1 can be due to improper input parameters, arithmetic interrupts, an excessive number of func- tion evaluations, or errors in the functions. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or TOL .LT. 0.D0, or LWA .LT. M*N+5*N+M. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDIF1. In this case, it may be possible to remedy the situation by not evalu- ating the functions here, but instead setting the components of FVEC to numbers that exceed those in the initial FVEC, thereby indirectly reducing the step length. The step length can be more directly controlled by using instead LMDIF, which includes in its calling sequence the step-length-governing parameter FACTOR. Excessive number of function evaluations. If the number of calls to FCN reaches 200*(N+1), then this indicates that the routine is converging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be help- ful to restart LMDIF1, thereby forcing it to disregard old (and possibly harmful) information. Errors in the functions. The choice of step length in the for- ward-difference approximation to the Jacobian assumes that th relative errors in the functions are of the order of the machine precision. If this is not the case, LMDIF1 may fail (usually with INFO = 4). The user should then use LMDIF instead, or one of the programs which require the analytic Jacobian (LMDER1 and LMDER). 6. Characteristics of the algorithm. LMDIF1 is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables and an optimal choice for the cor- rection. The use of implicitly scaled variables achieves scale invariance of LMDIF1 and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from th solution and a fast rate of convergence for problems with small residuals. Timing. The time required by LMDIF1 to solve a given problem Page depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDIF1 is about N**3 to process each evaluation of the functions (one call to FCN) and M*(N**2) to process each approximation to the Jacobian (N calls to FCN). Unless FCN can be evaluated quickly, the tim- ing of LMDIF1 will be strongly influenced by the time spent i FCN. Storage. LMDIF1 requires M*N + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,FDJAC2,LMDIF,LMPAR, QRFAC,QRSOLV FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMDIF1 EXAMPLE. C DOUBLE PRECISION VERSION C Page C ********** INTEGER J,M,N,INFO,LWA,NWRITE INTEGER IWA(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),WA(75) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LWA = 75 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDIF1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C Page DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION 0.8241057D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine LMDIF Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of LMDIF is to minimize the sum of the squares of M nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm. The user must provide a subrou- tine which calculates the functions. The Jacobian is then cal- culated by a forward-difference approximation. 2. Subroutine and type statements. SUBROUTINE LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC INTEGER IPVT(N) DOUBLE PRECISION FTOL,XTOL,GTOL,EPSFCN,FACTOR DOUBLE PRECISION X(N),FVEC(M),DIAG(N),FJAC(LDFJAC,N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) EXTERNAL FCN 3. Parameters. Parameters designated as input parameters must be specified on entry to LMDIF and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from LMDIF. FCN is the name of the user-supplied subroutine which calculate the functions. FCN must be declared in an EXTERNAL statement in the user calling program, and should be written as follows SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) ---------- CALCULATE THE FUNCTIONS AT X AND RETURN THIS VECTOR IN FVEC. ---------- RETURN END Page The value of IFLAG should not be changed by FCN unless the user wants to terminate execution of LMDIF. In this case set IFLAG to a negative integer. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. N must not exceed M. X is an array of length N. On input X must contain an initial estimate of the solution vector. On output X contains the final estimate of the solution vector. FVEC is an output array of length M which contains the function evaluated at the output X. FTOL is a nonnegative input variable. Termination occurs when both the actual and predicted relative reductions in the sum of squares are at most FTOL. Therefore, FTOL measures the relative error desired in the sum of squares. Section 4 con- tains more details about FTOL. XTOL is a nonnegative input variable. Termination occurs when the relative error between two consecutive iterates is at most XTOL. Therefore, XTOL measures the relative error desired in the approximate solution. Section 4 contains more details about XTOL. GTOL is a nonnegative input variable. Termination occurs when the cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. Therefore, GTOL measures the orthogonality desired between the function vector and the columns of the Jacobian. Section 4 contains more details about GTOL. MAXFEV is a positive integer input variable. Termination occur when the number of calls to FCN is at least MAXFEV by the end of an iteration. EPSFCN is an input variable used in determining a suitable step for the forward-difference approximation. This approximation assumes that the relative errors in the functions are of the order of EPSFCN. If EPSFCN is less than the machine preci- sion, it is assumed that the relative errors in the functions are of the order of the machine precision. DIAG is an array of length N. If MODE = 1 (see below), DIAG is internally set. If MODE = 2, DIAG must contain positive entries that serve as multiplicative scale factors for the variables. MODE is an integer input variable. If MODE = 1, the variables will be scaled internally. If MODE = 2, the scaling is Page specified by the input DIAG. Other values of MODE are equiva- lent to MODE = 1. FACTOR is a positive input variable used in determining the ini- tial step bound. This bound is set to the product of FACTOR and the Euclidean norm of DIAG*X if nonzero, or else to FACTO itself. In most cases FACTOR should lie in the interval (.1,100.). 100. is a generally recommended value. NPRINT is an integer input variable that enables controlled printing of iterates if it is positive. In this case, FCN is called with IFLAG = 0 at the beginning of the first iteration and every NPRINT iterations thereafter and immediately prior to return, with X and FVEC available for printing. If NPRINT is not positive, no special calls of FCN with IFLAG = 0 are made. INFO is an integer output variable. If the user has terminated execution, INFO is set to the (negative) value of IFLAG. See description of FCN. Otherwise, INFO is set as follows. INFO = 0 Improper input parameters. INFO = 1 Both actual and predicted relative reductions in th sum of squares are at most FTOL. INFO = 2 Relative error between two consecutive iterates is at most XTOL. INFO = 3 Conditions for INFO = 1 and INFO = 2 both hold. INFO = 4 The cosine of the angle between FVEC and any column of the Jacobian is at most GTOL in absolute value. INFO = 5 Number of calls to FCN has reached or exceeded MAXFEV. INFO = 6 FTOL is too small. No further reduction in the sum of squares is possible. INFO = 7 XTOL is too small. No further improvement in the approximate solution X is possible. INFO = 8 GTOL is too small. FVEC is orthogonal to the columns of the Jacobian to machine precision. Sections 4 and 5 contain more details about INFO. NFEV is an integer output variable set to the number of calls t FCN. FJAC is an output M by N array. The upper N by N submatrix of FJAC contains an upper triangular matrix R with diagonal ele- ments of nonincreasing magnitude such that Page T T T P *(JAC *JAC)*P = R *R, where P is a permutation matrix and JAC is the final calcu- lated Jacobian. Column j of P is column IPVT(j) (see below) of the identity matrix. The lower trapezoidal part of FJAC contains information generated during the computation of R. LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. IPVT is an integer output array of length N. IPVT defines a permutation matrix P such that JAC*P = Q*R, where JAC is the final calculated Jacobian, Q is orthogonal (not stored), and is upper triangular with diagonal elements of nonincreasing magnitude. Column j of P is column IPVT(j) of the identity matrix. QTF is an output array of length N which contains the first N elements of the vector (Q transpose)*FVEC. WA1, WA2, and WA3 are work arrays of length N. WA4 is a work array of length M. 4. Successful completion. The accuracy of LMDIF is controlled by the convergence parame- ters FTOL, XTOL, and GTOL. These parameters are used in tests which make three types of comparisons between the approximation X and a solution XSOL. LMDIF terminates when any of the tests is satisfied. If any of the convergence parameters is less than the machine precision (as defined by the MINPACK function DPMPAR(1)), then LMDIF only attempts to satisfy the test define by the machine precision. Further progress is not usually pos- sible. The tests assume that the functions are reasonably well behaved If this condition is not satisfied, then LMDIF may incorrectly indicate convergence. The validity of the answer can be checked, for example, by rerunning LMDIF with tighter toler- ances. First convergence test. If ENORM(Z) denotes the Euclidean norm of a vector Z, then this test attempts to guarantee that ENORM(FVEC) .LE. (1+FTOL)*ENORM(FVECS), where FVECS denotes the functions evaluated at XSOL. If this condition is satisfied with FTOL = 10**(-K), then the final residual norm ENORM(FVEC) has K significant decimal digits an INFO is set to 1 (or to 3 if the second test is also satis- fied). Unless high precision solutions are required, the Page recommended value for FTOL is the square root of the machine precision. Second convergence test. If D is the diagonal matrix whose entries are defined by the array DIAG, then this test attempt to guarantee that ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). If this condition is satisfied with XTOL = 10**(-K), then the larger components of D*X have K significant decimal digits an INFO is set to 2 (or to 3 if the first test is also satis- fied). There is a danger that the smaller components of D*X may have large relative errors, but if MODE = 1, then the accuracy of the components of X is usually related to their sensitivity. Unless high precision solutions are required, the recommended value for XTOL is the square root of the machine precision. Third convergence test. This test is satisfied when the cosine of the angle between FVEC and any column of the Jacobian at X is at most GTOL in absolute value. There is no clear rela- tionship between this test and the accuracy of LMDIF, and furthermore, the test is equally well satisfied at other crit- ical points, namely maximizers and saddle points. Therefore, termination caused by this test (INFO = 4) should be examined carefully. The recommended value for GTOL is zero. 5. Unsuccessful completion. Unsuccessful termination of LMDIF can be due to improper input parameters, arithmetic interrupts, or an excessive number of function evaluations. Improper input parameters. INFO is set to 0 if N .LE. 0, or M .LT. N, or LDFJAC .LT. M, or FTOL .LT. 0.D0, or XTOL .LT. 0.D0, or GTOL .LT. 0.D0, or MAXFEV .LE. 0, or FACTOR .LE. 0.D0. Arithmetic interrupts. If these interrupts occur in the FCN subroutine during an early stage of the computation, they may be caused by an unacceptable choice of X by LMDIF. In this case, it may be possible to remedy the situation by rerunning LMDIF with a smaller value of FACTOR. Excessive number of function evaluations. A reasonable value for MAXFEV is 200*(N+1). If the number of calls to FCN reaches MAXFEV, then this indicates that the routine is con- verging very slowly as measured by the progress of FVEC, and INFO is set to 5. In this case, it may be helpful to restart LMDIF with MODE set to 1. Page 6. Characteristics of the algorithm. LMDIF is a modification of the Levenberg-Marquardt algorithm. Two of its main characteristics involve the proper use of implicitly scaled variables (if MODE = 1) and an optimal choice for the correction. The use of implicitly scaled variables achieves scale invariance of LMDIF and limits the size of the correction in any direction where the functions are changing rapidly. The optimal choice of the correction guarantees (under reasonable conditions) global convergence from starting points far from the solution and a fast rate of convergence for prob- lems with small residuals. Timing. The time required by LMDIF to solve a given problem depends on M and N, the behavior of the functions, the accu- racy requested, and the starting point. The number of arith- metic operations needed by LMDIF is about N**3 to process each evaluation of the functions (one call to FCN) and M*(N**2) to process each approximation to the Jacobian (N calls to FCN). Unless FCN can be evaluated quickly, the timing of LMDIF will be strongly influenced by the time spent in FCN. Storage. LMDIF requires M*N + 2*M + 6*N double precision sto- rage locations and N integer storage locations, in addition t the storage required by the program. There are no internally declared storage arrays. 7. Subprograms required. USER-supplied ...... FCN MINPACK-supplied ... DPMPAR,ENORM,FDJAC2,LMPAR,QRFAC,QRSOLV FORTRAN-supplied ... DABS,DMAX1,DMIN1,DSQRT,MOD 8. References. Jorge J. More, The Levenberg-Marquardt Algorithm, Implementation and Theory. Numerical Analysis, G. A. Watson, editor. Lecture Notes in Mathematics 630, Springer-Verlag, 1977. 9. Example. The problem is to determine the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data Page y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). C ********** C C DRIVER FOR LMDIF EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,EPSFCN,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),DIAG(3),FJAC(15,3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 800 EPSFCN = 0.D0 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) Page FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDIF EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be slightly different. FINAL L2 NORM OF THE RESIDUALS 0.9063596D-01 NUMBER OF FUNCTION EVALUATIONS 21 EXIT PARAMETER 1 FINAL APPROXIMATE SOLUTION Page 0.8241057D-01 0.1133037D+01 0.2343695D+01 Page Documentation for MINPACK subroutine CHKDER Double precision version Argonne National Laboratory Burton S. Garbow, Kenneth E. Hillstrom, Jorge J. More March 1980 1. Purpose. The purpose of CHKDER is to check the gradients of M nonlinear functions in N variables, evaluated at a point X, for consis- tency with the functions themselves. The user must call CHKDER twice, first with MODE = 1 and then with MODE = 2. 2. Subroutine and type statements. SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) INTEGER M,N,LDFJAC,MODE DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),XP(N),FVECP(M), * ERR(M) 3. Parameters. Parameters designated as input parameters must be specified on entry to CHKDER and are not changed on exit, while parameters designated as output parameters need not be specified on entry and are set to appropriate values on exit from CHKDER. M is a positive integer input variable set to the number of functions. N is a positive integer input variable set to the number of variables. X is an input array of length N. FVEC is an array of length M. On input when MODE = 2, FVEC must contain the functions evaluated at X. FJAC is an M by N array. On input when MODE = 2, the rows of FJAC must contain the gradients of the respective functions evaluated at X. LDFJAC is a positive integer input variable not less than M which specifies the leading dimension of the array FJAC. XP is an array of length N. On output when MODE = 1, XP is set to a neighboring point of X. Page FVECP is an array of length M. On input when MODE = 2, FVECP must contain the functions evaluated at XP. MODE is an integer input variable set to 1 on the first call an 2 on the second. Other values of MODE are equivalent to MODE = 1. ERR is an array of length M. On output when MODE = 2, ERR con- tains measures of correctness of the respective gradients. I there is no severe loss of significance, then if ERR(I) is 1. the I-th gradient is correct, while if ERR(I) is 0.0 the I-th gradient is incorrect. For values of ERR between 0.0 and 1.0 the categorization is less certain. In general, a value of ERR(I) greater than 0.5 indicates that the I-th gradient is probably correct, while a value of ERR(I) less than 0.5 indi- cates that the I-th gradient is probably incorrect. 4. Successful completion. CHKDER usually guarantees that if ERR(I) is 1.0, then the I-th gradient at X is consistent with the I-th function. This sug- gests that the input X be such that consistency of the gradient at X implies consistency of the gradient at all points of inter est. If all the components of X are distinct and the fractional part of each one has two nonzero digits, then X is likely to be a satisfactory choice. If ERR(I) is not 1.0 but is greater than 0.5, then the I-th gra- dient is probably consistent with the I-th function (the more s the larger ERR(I) is), but the conditions for ERR(I) to be 1.0 have not been completely satisfied. In this case, it is recom- mended that CHKDER be rerun with other input values of X. If ERR(I) is always greater than 0.5, then the I-th gradient is consistent with the I-th function. 5. Unsuccessful completion. CHKDER does not perform reliably if cancellation or rounding errors cause a severe loss of significance in the evaluation of a function. Therefore, none of the components of X should be unusually small (in particular, zero) or any other value which may cause loss of significance. The relative differences between corresponding elements of FVECP and FVEC should be at least two orders of magnitude greater than the machine precision (as defined by the MINPACK function DPMPAR(1)). If there is a severe loss of significance in the evaluation of the I-th func- tion, then ERR(I) may be 0.0 and yet the I-th gradient could be correct. If ERR(I) is not 0.0 but is less than 0.5, then the I-th gra- dient is probably not consistent with the I-th function (the more so the smaller ERR(I) is), but the conditions for ERR(I) t Page be 0.0 have not been completely satisfied. In this case, it is recommended that CHKDER be rerun with other input values of X. If ERR(I) is always less than 0.5 and if there is no severe loss of significance, then the I-th gradient is not consistent with the I-th function. 6. Characteristics of the algorithm. CHKDER checks the I-th gradient for consistency with the I-th function by computing a forward-difference approximation along suitably chosen direction and comparing this approximation with the user-supplied gradient along the same direction. The prin- cipal characteristic of CHKDER is its invariance to changes in scale of the variables or functions. Timing. The time required by CHKDER depends only on M and N. The number of arithmetic operations needed by CHKDER is about N when MODE = 1 and M*N when MODE = 2. Storage. CHKDER requires M*N + 3*M + 2*N double precision stor- age locations, in addition to the storage required by the pro gram. There are no internally declared storage arrays. 7. Subprograms required. MINPACK-supplied ... DPMPAR FORTRAN-supplied ... DABS,DLOG10,DSQRT 8. References. None. 9. Example. This example checks the Jacobian matrix for the problem that determines the values of x(1), x(2), and x(3) which provide the best fit (in the least squares sense) of x(1) + u(i)/(v(i)*x(2) + w(i)*x(3)), i = 1, 15 to the data y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39, 0.37,0.58,0.73,0.96,1.34,2.10,4.39), where u(i) = i, v(i) = 16 - i, and w(i) = min(u(i),v(i)). The i-th component of FVEC is thus defined by y(i) - (x(1) + u(i)/(v(i)*x(2) + w(i)*x(3))). Page C ********** C C DRIVER FOR CHKDER EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER I,M,N,LDFJAC,MODE,NWRITE DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),XP(3),FVECP(15), * ERR(15) C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING VALUES SHOULD BE SUITABLE FOR C CHECKING THE JACOBIAN MATRIX. C X(1) = 9.2D-1 X(2) = 1.3D-1 X(3) = 5.4D-1 C LDFJAC = 15 C MODE = 1 CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) MODE = 2 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,1) CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,2) CALL FCN(M,N,XP,FVECP,FJAC,LDFJAC,1) CALL CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) C DO 10 I = 1, M FVECP(I) = FVECP(I) - FVEC(I) 10 CONTINUE WRITE (NWRITE,1000) (FVEC(I),I=1,M) WRITE (NWRITE,2000) (FVECP(I),I=1,M) WRITE (NWRITE,3000) (ERR(I),I=1,M) STOP 1000 FORMAT (/5X,5H FVEC // (5X,3D15.7)) 2000 FORMAT (/5X,13H FVECP - FVEC // (5X,3D15.7)) 3000 FORMAT (/5X,4H ERR // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR CHKDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR CHKDER EXAMPLE. C Page INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I C C ERROR INTRODUCED INTO NEXT STATEMENT FOR ILLUSTRATION. C CORRECTED STATEMENT SHOULD READ TMP3 = TMP1 . C TMP3 = TMP2 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END Results obtained with different compilers or machines may be different. In particular, the differences FVECP - FVEC are machine dependent. FVEC -0.1181606D+01 -0.1429655D+01 -0.1606344D+01 -0.1745269D+01 -0.1840654D+01 -0.1921586D+01 -0.1984141D+01 -0.2022537D+01 -0.2468977D+01 -0.2827562D+01 -0.3473582D+01 -0.4437612D+01 -0.6047662D+01 -0.9267761D+01 -0.1891806D+02 FVECP - FVEC -0.7724666D-08 -0.3432405D-08 -0.2034843D-09 Page 0.2313685D-08 0.4331078D-08 0.5984096D-08 0.7363281D-08 0.8531470D-08 0.1488591D-07 0.2335850D-07 0.3522012D-07 0.5301255D-07 0.8266660D-07 0.1419747D-06 0.3198990D-06 ERR 0.1141397D+00 0.9943516D-01 0.9674474D-01 0.9980447D-01 0.1073116D+00 0.1220445D+00 0.1526814D+00 0.1000000D+01 0.1000000D+01 0.1000000D+01 0.1000000D+01 0.1000000D+01 0.1000000D+01 0.1000000D+01 0.1000000D+01 minpack-19961126/ex/tlmder.f0000644000175000017500000000541711616327304016366 0ustar sylvestresylvestreC DRIVER FOR LMDER EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 400 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDER EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR LMDER EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .EQ. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE DO 30 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -1.D0 FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file120000644000175000017500000004455304210375053015735 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,INITPT,LMDIF1,SSQFCN C C FORTRAN-SUPPLIED ... SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES,NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) REAL FACTOR,FNORM1,FNORM2,ONE,TEN,TOL REAL FNM(60),FVEC(65),WA(2865),X(40) REAL SPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0E0,1.0E1/ TOL = SQRT(SPMPAR(1)) LWA = 2865 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJEV = NJEV/N NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, E15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , E15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5E15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMDIF1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 2X, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST-SQUARES SOLVER. FCN SHOULD ONLY CALL THE TESTING C FUNCTION SUBROUTINE SSQFCN WITH THE APPROPRIATE VALUE OF C PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB REAL X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIN,SQRT,SIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 REAL C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM,S1,S2,TEMP, * TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO,ZERO,ZP25,ZP5 REAL V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) REAL FLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0E0,2.5E-1,5.0E-1,1.0E0,2.0E0,5.0E0,8.0E0,1.0E1,1.3E1, * 1.4E1,2.9E1,4.5E1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0E0,2.0E0,1.0E0,5.0E-1,2.5E-1,1.67E-1,1.25E-1,1.0E-1, * 8.33E-2,7.14E-2,6.25E-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957E-1,1.947E-1,1.735E-1,1.6E-1,8.44E-2,6.27E-2,4.56E-2, * 3.42E-2,3.23E-2,2.35E-2,2.46E-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478E4,2.861E4,2.365E4,1.963E4,1.637E4,1.372E4,1.154E4, * 9.744E3,8.261E3,7.03E3,6.005E3,5.147E3,4.427E3,3.82E3, * 3.307E3,2.872E3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44E-1,9.08E-1,9.32E-1,9.36E-1,9.25E-1,9.08E-1,8.81E-1, * 8.5E-1,8.18E-1,7.84E-1,7.51E-1,7.18E-1,6.85E-1,6.58E-1, * 6.28E-1,6.03E-1,5.8E-1,5.58E-1,5.38E-1,5.22E-1,5.06E-1, * 4.9E-1,4.78E-1,4.67E-1,4.57E-1,4.48E-1,4.38E-1,4.31E-1, * 4.24E-1,4.2E-1,4.14E-1,4.11E-1,4.06E-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366E0,1.191E0,1.112E0,1.013E0,9.91E-1,8.85E-1,8.31E-1, * 8.47E-1,7.86E-1,7.25E-1,7.46E-1,6.79E-1,6.08E-1,6.55E-1, * 6.16E-1,6.06E-1,6.02E-1,6.26E-1,6.51E-1,7.24E-1,6.49E-1, * 6.49E-1,6.94E-1,6.44E-1,6.24E-1,6.61E-1,6.12E-1,5.58E-1, * 5.33E-1,4.95E-1,5.0E-1,4.23E-1,3.95E-1,3.75E-1,3.72E-1, * 3.91E-1,3.96E-1,4.05E-1,4.28E-1,4.29E-1,5.23E-1,5.62E-1, * 6.07E-1,6.53E-1,6.72E-1,7.08E-1,6.33E-1,6.68E-1,6.45E-1, * 6.32E-1,5.91E-1,5.59E-1,5.97E-1,6.25E-1,7.39E-1,7.1E-1, * 7.29E-1,7.2E-1,6.36E-1,5.81E-1,4.28E-1,2.92E-1,1.62E-1, * 9.8E-2,5.4E-2/ FLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/FLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + FLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = FLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + FLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = FLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*ATAN(ONE) TMP1 = SIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI + ZP5 TMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = FLOAT(I) TMP2 = FLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*FLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = EXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = FLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + FLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = FLOAT(I) TMP1 = TEMP/TEN FVEC(I) = EXP(-TMP1*X(1)) - EXP(-TMP1*X(2)) * + (EXP(-TEMP) - EXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = FLOAT(I) FVEC(I) = TWO + TWO*TEMP - EXP(TEMP*X(1)) - EXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = FLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - EXP(TEMP) TMP2 = X(3) + SIN(TEMP)*X(4) - COS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/FLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(FLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*FLOAT(I-1) TMP1 = EXP(-X(4)*TEMP) TMP2 = EXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = FLOAT(I-1)/TEN TMP1 = EXP(-X(5)*TEMP) TMP2 = EXP(-X(6)*(TEMP-X(9))**2) TMP3 = EXP(-X(7)*(TEMP-X(10))**2) TMP4 = EXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17, * FIVE,H,HALF,ONE,SEVEN,TEN,THREE,TWENTY,TWNTF,TWO,ZERO REAL FLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0E0,5.0E-1,1.0E0,2.0E0,3.0E0,5.0E0,7.0E0,1.0E1,2.0E1, * 2.5E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2E0,2.5E-1,3.9E-1,4.15E-1,2.0E-2,4.0E3,2.5E2,3.0E-1, * 4.0E-1,1.5E0,1.0E-2,1.3E0,6.5E-1,7.0E-1,6.0E-1,4.5E0, * 5.5E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/FLOAT(N+1) DO 160 J = 1, N X(J) = FLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END minpack-19961126/ex/file050000644000175000017500000046076704210374547015757 0ustar sylvestresylvestre SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) INTEGER M,N,LDFJAC,MODE DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),XP(N),FVECP(M), * ERR(M) C ********** C C SUBROUTINE CHKDER C C THIS SUBROUTINE CHECKS THE GRADIENTS OF M NONLINEAR FUNCTIONS C IN N VARIABLES, EVALUATED AT A POINT X, FOR CONSISTENCY WITH C THE FUNCTIONS THEMSELVES. THE USER MUST CALL CHKDER TWICE, C FIRST WITH MODE = 1 AND THEN WITH MODE = 2. C C MODE = 1. ON INPUT, X MUST CONTAIN THE POINT OF EVALUATION. C ON OUTPUT, XP IS SET TO A NEIGHBORING POINT. C C MODE = 2. ON INPUT, FVEC MUST CONTAIN THE FUNCTIONS AND THE C ROWS OF FJAC MUST CONTAIN THE GRADIENTS C OF THE RESPECTIVE FUNCTIONS EACH EVALUATED C AT X, AND FVECP MUST CONTAIN THE FUNCTIONS C EVALUATED AT XP. C ON OUTPUT, ERR CONTAINS MEASURES OF CORRECTNESS OF C THE RESPECTIVE GRADIENTS. C C THE SUBROUTINE DOES NOT PERFORM RELIABLY IF CANCELLATION OR C ROUNDING ERRORS CAUSE A SEVERE LOSS OF SIGNIFICANCE IN THE C EVALUATION OF A FUNCTION. THEREFORE, NONE OF THE COMPONENTS C OF X SHOULD BE UNUSUALLY SMALL (IN PARTICULAR, ZERO) OR ANY C OTHER VALUE WHICH MAY CAUSE LOSS OF SIGNIFICANCE. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) C C WHERE 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. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN ARRAY OF LENGTH M. ON INPUT WHEN MODE = 2, C FVEC MUST CONTAIN THE FUNCTIONS EVALUATED AT X. C C FJAC IS AN M BY N ARRAY. ON INPUT WHEN MODE = 2, C THE ROWS OF FJAC MUST CONTAIN THE GRADIENTS OF C THE RESPECTIVE FUNCTIONS EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT PARAMETER NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C XP IS AN ARRAY OF LENGTH N. ON OUTPUT WHEN MODE = 1, C XP IS SET TO A NEIGHBORING POINT OF X. C C FVECP IS AN ARRAY OF LENGTH M. ON INPUT WHEN MODE = 2, C FVECP MUST CONTAIN THE FUNCTIONS EVALUATED AT XP. C C MODE IS AN INTEGER INPUT VARIABLE SET TO 1 ON THE FIRST CALL C AND 2 ON THE SECOND. OTHER VALUES OF MODE ARE EQUIVALENT C TO MODE = 1. C C ERR IS AN ARRAY OF LENGTH M. ON OUTPUT WHEN MODE = 2, C ERR CONTAINS MEASURES OF CORRECTNESS OF THE RESPECTIVE C GRADIENTS. IF THERE IS NO SEVERE LOSS OF SIGNIFICANCE, C THEN IF ERR(I) IS 1.0 THE I-TH GRADIENT IS CORRECT, C WHILE IF ERR(I) IS 0.0 THE I-TH GRADIENT IS INCORRECT. C FOR VALUES OF ERR BETWEEN 0.0 AND 1.0, THE CATEGORIZATION C IS LESS CERTAIN. IN GENERAL, A VALUE OF ERR(I) GREATER C THAN 0.5 INDICATES THAT THE I-TH GRADIENT IS PROBABLY C CORRECT, WHILE A VALUE OF ERR(I) LESS THAN 0.5 INDICATES C THAT THE I-TH GRADIENT IS PROBABLY INCORRECT. C C SUBPROGRAMS CALLED C C MINPACK SUPPLIED ... DPMPAR C C FORTRAN SUPPLIED ... DABS,DLOG10,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J DOUBLE PRECISION EPS,EPSF,EPSLOG,EPSMCH,FACTOR,ONE,TEMP,ZERO DOUBLE PRECISION DPMPAR DATA FACTOR,ONE,ZERO /1.0D2,1.0D0,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C EPS = DSQRT(EPSMCH) C IF (MODE .EQ. 2) GO TO 20 C C MODE = 1. C DO 10 J = 1, N TEMP = EPS*DABS(X(J)) IF (TEMP .EQ. ZERO) TEMP = EPS XP(J) = X(J) + TEMP 10 CONTINUE GO TO 70 20 CONTINUE C C MODE = 2. C EPSF = FACTOR*EPSMCH EPSLOG = DLOG10(EPS) DO 30 I = 1, M ERR(I) = ZERO 30 CONTINUE DO 50 J = 1, N TEMP = DABS(X(J)) IF (TEMP .EQ. ZERO) TEMP = ONE DO 40 I = 1, M ERR(I) = ERR(I) + TEMP*FJAC(I,J) 40 CONTINUE 50 CONTINUE DO 60 I = 1, M TEMP = ONE IF (FVEC(I) .NE. ZERO .AND. FVECP(I) .NE. ZERO * .AND. DABS(FVECP(I)-FVEC(I)) .GE. EPSF*DABS(FVEC(I))) * TEMP = EPS*DABS((FVECP(I)-FVEC(I))/EPS-ERR(I)) * /(DABS(FVEC(I)) + DABS(FVECP(I))) ERR(I) = ONE IF (TEMP .GT. EPSMCH .AND. TEMP .LT. EPS) * ERR(I) = (DLOG10(TEMP) - EPSLOG)/EPSLOG IF (TEMP .GE. EPS) ERR(I) = ZERO 60 CONTINUE 70 CONTINUE C RETURN C C LAST CARD OF SUBROUTINE CHKDER. C END SUBROUTINE DOGLEG(N,R,LR,DIAG,QTB,DELTA,X,WA1,WA2) INTEGER N,LR DOUBLE PRECISION DELTA DOUBLE PRECISION R(LR),DIAG(N),QTB(N),X(N),WA1(N),WA2(N) C ********** C C SUBROUTINE DOGLEG C C GIVEN AN M BY N MATRIX A, AN N BY N NONSINGULAR DIAGONAL C MATRIX D, AN M-VECTOR B, AND A POSITIVE NUMBER DELTA, THE C PROBLEM IS TO DETERMINE THE CONVEX COMBINATION X OF THE C GAUSS-NEWTON AND SCALED GRADIENT DIRECTIONS THAT MINIMIZES C (A*X - B) IN THE LEAST SQUARES SENSE, SUBJECT TO THE C RESTRICTION THAT THE EUCLIDEAN NORM OF D*X BE AT MOST DELTA. C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION OF A. THAT IS, IF A = Q*R, WHERE Q HAS C ORTHOGONAL COLUMNS AND R IS AN UPPER TRIANGULAR MATRIX, C THEN DOGLEG EXPECTS THE FULL UPPER TRIANGLE OF R AND C THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE DOGLEG(N,R,LR,DIAG,QTB,DELTA,X,WA1,WA2) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN INPUT ARRAY OF LENGTH LR WHICH MUST CONTAIN THE UPPER C TRIANGULAR MATRIX R STORED BY ROWS. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C DELTA IS A POSITIVE INPUT VARIABLE WHICH SPECIFIES AN UPPER C BOUND ON THE EUCLIDEAN NORM OF D*X. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE DESIRED C CONVEX COMBINATION OF THE GAUSS-NEWTON DIRECTION AND THE C SCALED GRADIENT DIRECTION. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DPMPAR,ENORM C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JJ,JP1,K,L DOUBLE PRECISION ALPHA,BNORM,EPSMCH,GNORM,ONE,QNORM,SGNORM,SUM, * TEMP,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,ZERO /1.0D0,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C C FIRST, CALCULATE THE GAUSS-NEWTON DIRECTION. C JJ = (N*(N + 1))/2 + 1 DO 50 K = 1, N J = N - K + 1 JP1 = J + 1 JJ = JJ - K L = JJ + 1 SUM = ZERO IF (N .LT. JP1) GO TO 20 DO 10 I = JP1, N SUM = SUM + R(L)*X(I) L = L + 1 10 CONTINUE 20 CONTINUE TEMP = R(JJ) IF (TEMP .NE. ZERO) GO TO 40 L = J DO 30 I = 1, J TEMP = DMAX1(TEMP,DABS(R(L))) L = L + N - I 30 CONTINUE TEMP = EPSMCH*TEMP IF (TEMP .EQ. ZERO) TEMP = EPSMCH 40 CONTINUE X(J) = (QTB(J) - SUM)/TEMP 50 CONTINUE C C TEST WHETHER THE GAUSS-NEWTON DIRECTION IS ACCEPTABLE. C DO 60 J = 1, N WA1(J) = ZERO WA2(J) = DIAG(J)*X(J) 60 CONTINUE QNORM = ENORM(N,WA2) IF (QNORM .LE. DELTA) GO TO 140 C C THE GAUSS-NEWTON DIRECTION IS NOT ACCEPTABLE. C NEXT, CALCULATE THE SCALED GRADIENT DIRECTION. C L = 1 DO 80 J = 1, N TEMP = QTB(J) DO 70 I = J, N WA1(I) = WA1(I) + R(L)*TEMP L = L + 1 70 CONTINUE WA1(J) = WA1(J)/DIAG(J) 80 CONTINUE C C CALCULATE THE NORM OF THE SCALED GRADIENT AND TEST FOR C THE SPECIAL CASE IN WHICH THE SCALED GRADIENT IS ZERO. C GNORM = ENORM(N,WA1) SGNORM = ZERO ALPHA = DELTA/QNORM IF (GNORM .EQ. ZERO) GO TO 120 C C CALCULATE THE POINT ALONG THE SCALED GRADIENT C AT WHICH THE QUADRATIC IS MINIMIZED. C DO 90 J = 1, N WA1(J) = (WA1(J)/GNORM)/DIAG(J) 90 CONTINUE L = 1 DO 110 J = 1, N SUM = ZERO DO 100 I = J, N SUM = SUM + R(L)*WA1(I) L = L + 1 100 CONTINUE WA2(J) = SUM 110 CONTINUE TEMP = ENORM(N,WA2) SGNORM = (GNORM/TEMP)/TEMP C C TEST WHETHER THE SCALED GRADIENT DIRECTION IS ACCEPTABLE. C ALPHA = ZERO IF (SGNORM .GE. DELTA) GO TO 120 C C THE SCALED GRADIENT DIRECTION IS NOT ACCEPTABLE. C FINALLY, CALCULATE THE POINT ALONG THE DOGLEG C AT WHICH THE QUADRATIC IS MINIMIZED. C BNORM = ENORM(N,QTB) TEMP = (BNORM/GNORM)*(BNORM/QNORM)*(SGNORM/DELTA) TEMP = TEMP - (DELTA/QNORM)*(SGNORM/DELTA)**2 * + DSQRT((TEMP-(DELTA/QNORM))**2 * +(ONE-(DELTA/QNORM)**2)*(ONE-(SGNORM/DELTA)**2)) ALPHA = ((DELTA/QNORM)*(ONE - (SGNORM/DELTA)**2))/TEMP 120 CONTINUE C C FORM APPROPRIATE CONVEX COMBINATION OF THE GAUSS-NEWTON C DIRECTION AND THE SCALED GRADIENT DIRECTION. C TEMP = (ONE - ALPHA)*DMIN1(SGNORM,DELTA) DO 130 J = 1, N X(J) = TEMP*WA1(J) + ALPHA*X(J) 130 CONTINUE 140 CONTINUE RETURN C C LAST CARD OF SUBROUTINE DOGLEG. C END DOUBLE PRECISION FUNCTION ENORM(N,X) INTEGER N DOUBLE PRECISION X(N) C ********** C C FUNCTION ENORM C C GIVEN AN N-VECTOR X, THIS FUNCTION CALCULATES THE C EUCLIDEAN NORM OF X. C C THE EUCLIDEAN NORM IS COMPUTED BY ACCUMULATING THE SUM OF C SQUARES IN THREE DIFFERENT SUMS. THE SUMS OF SQUARES FOR THE C SMALL AND LARGE COMPONENTS ARE SCALED SO THAT NO OVERFLOWS C OCCUR. NON-DESTRUCTIVE UNDERFLOWS ARE PERMITTED. UNDERFLOWS C AND OVERFLOWS DO NOT OCCUR IN THE COMPUTATION OF THE UNSCALED C SUM OF SQUARES FOR THE INTERMEDIATE COMPONENTS. C THE DEFINITIONS OF SMALL, INTERMEDIATE AND LARGE COMPONENTS C DEPEND ON TWO CONSTANTS, RDWARF AND RGIANT. THE MAIN C RESTRICTIONS ON THESE CONSTANTS ARE THAT RDWARF**2 NOT C UNDERFLOW AND RGIANT**2 NOT OVERFLOW. THE CONSTANTS C GIVEN HERE ARE SUITABLE FOR EVERY KNOWN COMPUTER. C C THE FUNCTION STATEMENT IS C C DOUBLE PRECISION FUNCTION ENORM(N,X) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DABS,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I DOUBLE PRECISION AGIANT,FLOATN,ONE,RDWARF,RGIANT,S1,S2,S3,XABS, * X1MAX,X3MAX,ZERO DATA ONE,ZERO,RDWARF,RGIANT /1.0D0,0.0D0,3.834D-20,1.304D19/ S1 = ZERO S2 = ZERO S3 = ZERO X1MAX = ZERO X3MAX = ZERO FLOATN = N AGIANT = RGIANT/FLOATN DO 90 I = 1, N XABS = DABS(X(I)) IF (XABS .GT. RDWARF .AND. XABS .LT. AGIANT) GO TO 70 IF (XABS .LE. RDWARF) GO TO 30 C C SUM FOR LARGE COMPONENTS. C IF (XABS .LE. X1MAX) GO TO 10 S1 = ONE + S1*(X1MAX/XABS)**2 X1MAX = XABS GO TO 20 10 CONTINUE S1 = S1 + (XABS/X1MAX)**2 20 CONTINUE GO TO 60 30 CONTINUE C C SUM FOR SMALL COMPONENTS. C IF (XABS .LE. X3MAX) GO TO 40 S3 = ONE + S3*(X3MAX/XABS)**2 X3MAX = XABS GO TO 50 40 CONTINUE IF (XABS .NE. ZERO) S3 = S3 + (XABS/X3MAX)**2 50 CONTINUE 60 CONTINUE GO TO 80 70 CONTINUE C C SUM FOR INTERMEDIATE COMPONENTS. C S2 = S2 + XABS**2 80 CONTINUE 90 CONTINUE C C CALCULATION OF NORM. C IF (S1 .EQ. ZERO) GO TO 100 ENORM = X1MAX*DSQRT(S1+(S2/X1MAX)/X1MAX) GO TO 130 100 CONTINUE IF (S2 .EQ. ZERO) GO TO 110 IF (S2 .GE. X3MAX) * ENORM = DSQRT(S2*(ONE+(X3MAX/S2)*(X3MAX*S3))) IF (S2 .LT. X3MAX) * ENORM = DSQRT(X3MAX*((S2/X3MAX)+(X3MAX*S3))) GO TO 120 110 CONTINUE ENORM = X3MAX*DSQRT(S3) 120 CONTINUE 130 CONTINUE RETURN C C LAST CARD OF FUNCTION ENORM. C END SUBROUTINE FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN, * WA1,WA2) INTEGER N,LDFJAC,IFLAG,ML,MU DOUBLE PRECISION EPSFCN DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N),WA1(N),WA2(N) C ********** C C SUBROUTINE FDJAC1 C C THIS SUBROUTINE COMPUTES A FORWARD-DIFFERENCE APPROXIMATION C TO THE N BY N JACOBIAN MATRIX ASSOCIATED WITH A SPECIFIED C PROBLEM OF N FUNCTIONS IN N VARIABLES. IF THE JACOBIAN HAS C A BANDED FORM, THEN FUNCTION EVALUATIONS ARE SAVED BY ONLY C APPROXIMATING THE NONZERO TERMS. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN, C WA1,WA2) 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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C DOUBLE PRECISION X(N),FVEC(N) 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 FDJAC1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C FUNCTIONS EVALUATED AT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C APPROXIMATION TO THE JACOBIAN MATRIX EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IFLAG IS AN INTEGER VARIABLE WHICH CAN BE USED TO TERMINATE C THE EXECUTION OF FDJAC1. SEE DESCRIPTION OF FCN. C C ML IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUBDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C ML TO AT LEAST N - 1. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C MU IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUPERDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C MU TO AT LEAST N - 1. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. IF ML + MU + 1 IS AT C LEAST N, THEN THE JACOBIAN IS CONSIDERED DENSE, AND WA2 IS C NOT REFERENCED. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DPMPAR C C FORTRAN-SUPPLIED ... DABS,DMAX1,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,K,MSUM DOUBLE PRECISION EPS,EPSMCH,H,TEMP,ZERO DOUBLE PRECISION DPMPAR DATA ZERO /0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C EPS = DSQRT(DMAX1(EPSFCN,EPSMCH)) MSUM = ML + MU + 1 IF (MSUM .LT. N) GO TO 40 C C COMPUTATION OF DENSE APPROXIMATE JACOBIAN. C DO 20 J = 1, N TEMP = X(J) H = EPS*DABS(TEMP) IF (H .EQ. ZERO) H = EPS X(J) = TEMP + H CALL FCN(N,X,WA1,IFLAG) IF (IFLAG .LT. 0) GO TO 30 X(J) = TEMP DO 10 I = 1, N FJAC(I,J) = (WA1(I) - FVEC(I))/H 10 CONTINUE 20 CONTINUE 30 CONTINUE GO TO 110 40 CONTINUE C C COMPUTATION OF BANDED APPROXIMATE JACOBIAN. C DO 90 K = 1, MSUM DO 60 J = K, N, MSUM WA2(J) = X(J) H = EPS*DABS(WA2(J)) IF (H .EQ. ZERO) H = EPS X(J) = WA2(J) + H 60 CONTINUE CALL FCN(N,X,WA1,IFLAG) IF (IFLAG .LT. 0) GO TO 100 DO 80 J = K, N, MSUM X(J) = WA2(J) H = EPS*DABS(WA2(J)) IF (H .EQ. ZERO) H = EPS DO 70 I = 1, N FJAC(I,J) = ZERO IF (I .GE. J - MU .AND. I .LE. J + ML) * FJAC(I,J) = (WA1(I) - FVEC(I))/H 70 CONTINUE 80 CONTINUE 90 CONTINUE 100 CONTINUE 110 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FDJAC1. C END SUBROUTINE FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION EPSFCN DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),WA(M) C ********** C C SUBROUTINE FDJAC2 C C THIS SUBROUTINE COMPUTES A FORWARD-DIFFERENCE APPROXIMATION C TO THE M BY N JACOBIAN MATRIX ASSOCIATED WITH A SPECIFIED C PROBLEM OF M FUNCTIONS IN N VARIABLES. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA) 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 DOUBLE PRECISION 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 FDJAC2. 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 INPUT ARRAY OF LENGTH N. C C FVEC IS AN INPUT ARRAY OF LENGTH M WHICH MUST CONTAIN THE C FUNCTIONS EVALUATED AT X. C C FJAC IS AN OUTPUT M BY N ARRAY WHICH CONTAINS THE C APPROXIMATION TO THE JACOBIAN MATRIX EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IFLAG IS AN INTEGER VARIABLE WHICH CAN BE USED TO TERMINATE C THE EXECUTION OF FDJAC2. SEE DESCRIPTION OF FCN. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C WA IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR C C FORTRAN-SUPPLIED ... DABS,DMAX1,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J DOUBLE PRECISION EPS,EPSMCH,H,TEMP,ZERO DOUBLE PRECISION DPMPAR DATA ZERO /0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C EPS = DSQRT(DMAX1(EPSFCN,EPSMCH)) DO 20 J = 1, N TEMP = X(J) H = EPS*DABS(TEMP) IF (H .EQ. ZERO) H = EPS X(J) = TEMP + H CALL FCN(M,N,X,WA,IFLAG) IF (IFLAG .LT. 0) GO TO 30 X(J) = TEMP DO 10 I = 1, M FJAC(I,J) = (WA(I) - FVEC(I))/H 10 CONTINUE 20 CONTINUE 30 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FDJAC2. C END SUBROUTINE HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC,R,LR, * QTF,WA1,WA2,WA3,WA4) INTEGER N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR DOUBLE PRECISION XTOL,EPSFCN,FACTOR DOUBLE PRECISION X(N),FVEC(N),DIAG(N),FJAC(LDFJAC,N),R(LR), * QTF(N),WA1(N),WA2(N),WA3(N),WA4(N) EXTERNAL FCN C ********** C C SUBROUTINE HYBRD C C THE PURPOSE OF HYBRD IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. 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 HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN, C DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC, C LDFJAC,R,LR,QTF,WA1,WA2,WA3,WA4) 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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C DOUBLE PRECISION X(N),FVEC(N) 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 HYBRD. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN IS AT LEAST MAXFEV C BY THE END OF AN ITERATION. C C ML IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUBDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C ML TO AT LEAST N - 1. C C MU IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUPERDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C MU TO AT LEAST N - 1. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 2 NUMBER OF CALLS TO FCN HAS REACHED OR EXCEEDED C MAXFEV. C C INFO = 3 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C FIVE JACOBIAN EVALUATIONS. C C INFO = 5 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C TEN ITERATIONS. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C R IS AN OUTPUT ARRAY OF LENGTH LR WHICH CONTAINS THE C UPPER TRIANGULAR MATRIX PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN, STORED ROWWISE. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, WA3, AND WA4 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DOGLEG,DPMPAR,ENORM,FDJAC1, C QFORM,QRFAC,R1MPYQ,R1UPDT C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,MIN0,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,JM1,L,MSUM,NCFAIL,NCSUC,NSLOW1,NSLOW2 INTEGER IWA(1) LOGICAL JEVAL,SING DOUBLE PRECISION ACTRED,DELTA,EPSMCH,FNORM,FNORM1,ONE,PNORM, * PRERED,P1,P5,P001,P0001,RATIO,SUM,TEMP,XNORM, * ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P1,P5,P001,P0001,ZERO * /1.0D0,1.0D-1,5.0D-1,1.0D-3,1.0D-4,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. XTOL .LT. ZERO .OR. MAXFEV .LE. 0 * .OR. ML .LT. 0 .OR. MU .LT. 0 .OR. FACTOR .LE. ZERO * .OR. LDFJAC .LT. N .OR. LR .LT. (N*(N + 1))/2) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,X,FVEC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(N,FVEC) C C DETERMINE THE NUMBER OF CALLS TO FCN NEEDED TO COMPUTE C THE JACOBIAN MATRIX. C MSUM = MIN0(ML+MU+1,N) C C INITIALIZE ITERATION COUNTER AND MONITORS. C ITER = 1 NCSUC = 0 NCFAIL = 0 NSLOW1 = 0 NSLOW2 = 0 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE JEVAL = .TRUE. C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN,WA1, * WA2) NFEV = NFEV + MSUM IF (IFLAG .LT. 0) GO TO 300 C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(N,N,FJAC,LDFJAC,.FALSE.,IWA,1,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 70 IF (MODE .EQ. 2) GO TO 50 DO 40 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 40 CONTINUE 50 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 60 J = 1, N WA3(J) = DIAG(J)*X(J) 60 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 70 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE IN QTF. C DO 80 I = 1, N QTF(I) = FVEC(I) 80 CONTINUE DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE 120 CONTINUE C C COPY THE TRIANGULAR FACTOR OF THE QR FACTORIZATION INTO R. C SING = .FALSE. DO 150 J = 1, N L = J JM1 = J - 1 IF (JM1 .LT. 1) GO TO 140 DO 130 I = 1, JM1 R(L) = FJAC(I,J) L = L + N - I 130 CONTINUE 140 CONTINUE R(L) = WA1(J) IF (WA1(J) .EQ. ZERO) SING = .TRUE. 150 CONTINUE C C ACCUMULATE THE ORTHOGONAL FACTOR IN FJAC. C CALL QFORM(N,N,FJAC,LDFJAC,WA1) C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 170 DO 160 J = 1, N DIAG(J) = DMAX1(DIAG(J),WA2(J)) 160 CONTINUE 170 CONTINUE C C BEGINNING OF THE INNER LOOP. C 180 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 190 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(N,X,FVEC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 190 CONTINUE C C DETERMINE THE DIRECTION P. C CALL DOGLEG(N,R,LR,DIAG,QTF,DELTA,WA1,WA2,WA3) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 200 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 200 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = DMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,WA2,WA4,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(N,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION. C L = 1 DO 220 I = 1, N SUM = ZERO DO 210 J = I, N SUM = SUM + R(L)*WA1(J) L = L + 1 210 CONTINUE WA3(I) = QTF(I) + SUM 220 CONTINUE TEMP = ENORM(N,WA3) PRERED = ZERO IF (TEMP .LT. FNORM) PRERED = ONE - (TEMP/FNORM)**2 C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .GT. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GE. P1) GO TO 230 NCSUC = 0 NCFAIL = NCFAIL + 1 DELTA = P5*DELTA GO TO 240 230 CONTINUE NCFAIL = 0 NCSUC = NCSUC + 1 IF (RATIO .GE. P5 .OR. NCSUC .GT. 1) * DELTA = DMAX1(DELTA,PNORM/P5) IF (DABS(RATIO-ONE) .LE. P1) DELTA = PNORM/P5 240 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 260 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 250 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) FVEC(J) = WA4(J) 250 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 260 CONTINUE C C DETERMINE THE PROGRESS OF THE ITERATION. C NSLOW1 = NSLOW1 + 1 IF (ACTRED .GE. P001) NSLOW1 = 0 IF (JEVAL) NSLOW2 = NSLOW2 + 1 IF (ACTRED .GE. P1) NSLOW2 = 0 C C TEST FOR CONVERGENCE. C IF (DELTA .LE. XTOL*XNORM .OR. FNORM .EQ. ZERO) INFO = 1 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 2 IF (P1*DMAX1(P1*DELTA,PNORM) .LE. EPSMCH*XNORM) INFO = 3 IF (NSLOW2 .EQ. 5) INFO = 4 IF (NSLOW1 .EQ. 10) INFO = 5 IF (INFO .NE. 0) GO TO 300 C C CRITERION FOR RECALCULATING JACOBIAN APPROXIMATION C BY FORWARD DIFFERENCES. C IF (NCFAIL .EQ. 2) GO TO 290 C C CALCULATE THE RANK ONE MODIFICATION TO THE JACOBIAN C AND UPDATE QTF IF NECESSARY. C DO 280 J = 1, N SUM = ZERO DO 270 I = 1, N SUM = SUM + FJAC(I,J)*WA4(I) 270 CONTINUE WA2(J) = (SUM - WA3(J))/PNORM WA1(J) = DIAG(J)*((DIAG(J)*WA1(J))/PNORM) IF (RATIO .GE. P0001) QTF(J) = SUM 280 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE UPDATED JACOBIAN. C CALL R1UPDT(N,N,R,LR,WA1,WA2,WA3,SING) CALL R1MPYQ(N,N,FJAC,LDFJAC,WA2,WA3) CALL R1MPYQ(1,N,QTF,1,WA2,WA3) C C END OF THE INNER LOOP. C JEVAL = .FALSE. GO TO 180 290 CONTINUE C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(N,X,FVEC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE HYBRD. C END SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) INTEGER N,INFO,LWA DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE HYBRD1 C C THE PURPOSE OF HYBRD1 IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THIS IS DONE BY USING THE C MORE GENERAL NONLINEAR EQUATION SOLVER HYBRD. THE USER C MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE FUNCTIONS. C THE JACOBIAN IS THEN CALCULATED BY A FORWARD-DIFFERENCE C APPROXIMATION. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C DOUBLE PRECISION X(N),FVEC(N) 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 HYBRD1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N 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 THAT THE RELATIVE ERROR C BETWEEN X AND THE SOLUTION IS AT 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 BETWEEN X AND THE SOLUTION IS AT MOST TOL. C C INFO = 2 NUMBER OF CALLS TO FCN HAS REACHED OR EXCEEDED C 200*(N+1). C C INFO = 3 TOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(3*N+13))/2. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... HYBRD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER INDEX,J,LR,MAXFEV,ML,MODE,MU,NFEV,NPRINT DOUBLE PRECISION EPSFCN,FACTOR,ONE,XTOL,ZERO DATA FACTOR,ONE,ZERO /1.0D2,1.0D0,0.0D0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. TOL .LT. ZERO .OR. LWA .LT. (N*(3*N + 13))/2) * GO TO 20 C C CALL HYBRD. C MAXFEV = 200*(N + 1) XTOL = TOL ML = N - 1 MU = N - 1 EPSFCN = ZERO MODE = 2 DO 10 J = 1, N WA(J) = ONE 10 CONTINUE NPRINT = 0 LR = (N*(N + 1))/2 INDEX = 6*N + LR CALL HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,WA(1),MODE, * FACTOR,NPRINT,INFO,NFEV,WA(INDEX+1),N,WA(6*N+1),LR, * WA(N+1),WA(2*N+1),WA(3*N+1),WA(4*N+1),WA(5*N+1)) IF (INFO .EQ. 5) INFO = 4 20 CONTINUE RETURN C C LAST CARD OF SUBROUTINE HYBRD1. C END SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG,MODE, * FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF,WA1,WA2, * WA3,WA4) INTEGER N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR DOUBLE PRECISION XTOL,FACTOR DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N),DIAG(N),R(LR), * QTF(N),WA1(N),WA2(N),WA3(N),WA4(N) C ********** C C SUBROUTINE HYBRJ C C THE PURPOSE OF HYBRJ IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, C MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, C WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER N,LDFJAC,IFLAG C DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 HYBRJ. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. FVEC AND FJAC SHOULD NOT BE ALTERED. C IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS OF FCN C WITH IFLAG = 0 ARE MADE. 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 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 2 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 3 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C FIVE JACOBIAN EVALUATIONS. C C INFO = 5 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C TEN ITERATIONS. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C R IS AN OUTPUT ARRAY OF LENGTH LR WHICH CONTAINS THE C UPPER TRIANGULAR MATRIX PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN, STORED ROWWISE. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, WA3, AND WA4 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DOGLEG,DPMPAR,ENORM, C QFORM,QRFAC,R1MPYQ,R1UPDT C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,JM1,L,NCFAIL,NCSUC,NSLOW1,NSLOW2 INTEGER IWA(1) LOGICAL JEVAL,SING DOUBLE PRECISION ACTRED,DELTA,EPSMCH,FNORM,FNORM1,ONE,PNORM, * PRERED,P1,P5,P001,P0001,RATIO,SUM,TEMP,XNORM, * ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P1,P5,P001,P0001,ZERO * /1.0D0,1.0D-1,5.0D-1,1.0D-3,1.0D-4,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. LDFJAC .LT. N .OR. XTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO * .OR. LR .LT. (N*(N + 1))/2) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(N,FVEC) C C INITIALIZE ITERATION COUNTER AND MONITORS. C ITER = 1 NCSUC = 0 NCFAIL = 0 NSLOW1 = 0 NSLOW2 = 0 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE JEVAL = .TRUE. C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) NJEV = NJEV + 1 IF (IFLAG .LT. 0) GO TO 300 C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(N,N,FJAC,LDFJAC,.FALSE.,IWA,1,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 70 IF (MODE .EQ. 2) GO TO 50 DO 40 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 40 CONTINUE 50 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 60 J = 1, N WA3(J) = DIAG(J)*X(J) 60 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 70 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE IN QTF. C DO 80 I = 1, N QTF(I) = FVEC(I) 80 CONTINUE DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE 120 CONTINUE C C COPY THE TRIANGULAR FACTOR OF THE QR FACTORIZATION INTO R. C SING = .FALSE. DO 150 J = 1, N L = J JM1 = J - 1 IF (JM1 .LT. 1) GO TO 140 DO 130 I = 1, JM1 R(L) = FJAC(I,J) L = L + N - I 130 CONTINUE 140 CONTINUE R(L) = WA1(J) IF (WA1(J) .EQ. ZERO) SING = .TRUE. 150 CONTINUE C C ACCUMULATE THE ORTHOGONAL FACTOR IN FJAC. C CALL QFORM(N,N,FJAC,LDFJAC,WA1) C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 170 DO 160 J = 1, N DIAG(J) = DMAX1(DIAG(J),WA2(J)) 160 CONTINUE 170 CONTINUE C C BEGINNING OF THE INNER LOOP. C 180 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 190 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) * CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 190 CONTINUE C C DETERMINE THE DIRECTION P. C CALL DOGLEG(N,R,LR,DIAG,QTF,DELTA,WA1,WA2,WA3) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 200 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 200 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = DMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,WA2,WA4,FJAC,LDFJAC,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(N,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION. C L = 1 DO 220 I = 1, N SUM = ZERO DO 210 J = I, N SUM = SUM + R(L)*WA1(J) L = L + 1 210 CONTINUE WA3(I) = QTF(I) + SUM 220 CONTINUE TEMP = ENORM(N,WA3) PRERED = ZERO IF (TEMP .LT. FNORM) PRERED = ONE - (TEMP/FNORM)**2 C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .GT. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GE. P1) GO TO 230 NCSUC = 0 NCFAIL = NCFAIL + 1 DELTA = P5*DELTA GO TO 240 230 CONTINUE NCFAIL = 0 NCSUC = NCSUC + 1 IF (RATIO .GE. P5 .OR. NCSUC .GT. 1) * DELTA = DMAX1(DELTA,PNORM/P5) IF (DABS(RATIO-ONE) .LE. P1) DELTA = PNORM/P5 240 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 260 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 250 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) FVEC(J) = WA4(J) 250 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 260 CONTINUE C C DETERMINE THE PROGRESS OF THE ITERATION. C NSLOW1 = NSLOW1 + 1 IF (ACTRED .GE. P001) NSLOW1 = 0 IF (JEVAL) NSLOW2 = NSLOW2 + 1 IF (ACTRED .GE. P1) NSLOW2 = 0 C C TEST FOR CONVERGENCE. C IF (DELTA .LE. XTOL*XNORM .OR. FNORM .EQ. ZERO) INFO = 1 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 2 IF (P1*DMAX1(P1*DELTA,PNORM) .LE. EPSMCH*XNORM) INFO = 3 IF (NSLOW2 .EQ. 5) INFO = 4 IF (NSLOW1 .EQ. 10) INFO = 5 IF (INFO .NE. 0) GO TO 300 C C CRITERION FOR RECALCULATING JACOBIAN. C IF (NCFAIL .EQ. 2) GO TO 290 C C CALCULATE THE RANK ONE MODIFICATION TO THE JACOBIAN C AND UPDATE QTF IF NECESSARY. C DO 280 J = 1, N SUM = ZERO DO 270 I = 1, N SUM = SUM + FJAC(I,J)*WA4(I) 270 CONTINUE WA2(J) = (SUM - WA3(J))/PNORM WA1(J) = DIAG(J)*((DIAG(J)*WA1(J))/PNORM) IF (RATIO .GE. P0001) QTF(J) = SUM 280 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE UPDATED JACOBIAN. C CALL R1UPDT(N,N,R,LR,WA1,WA2,WA3,SING) CALL R1MPYQ(N,N,FJAC,LDFJAC,WA2,WA3) CALL R1MPYQ(1,N,QTF,1,WA2,WA3) C C END OF THE INNER LOOP. C JEVAL = .FALSE. GO TO 180 290 CONTINUE C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE HYBRJ. C END SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) INTEGER N,LDFJAC,INFO,LWA DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE HYBRJ1 C C THE PURPOSE OF HYBRJ1 IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THIS IS DONE BY USING THE C MORE GENERAL NONLINEAR EQUATION SOLVER HYBRJ. THE USER C MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE FUNCTIONS C AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER N,LDFJAC,IFLAG C DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 HYBRJ1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C TOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION OCCURS C WHEN THE ALGORITHM ESTIMATES THAT THE RELATIVE ERROR C BETWEEN X AND THE SOLUTION IS AT 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 BETWEEN X AND THE SOLUTION IS AT MOST TOL. C C INFO = 2 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED 100*(N+1). C C INFO = 3 TOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+13))/2. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... HYBRJ C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER J,LR,MAXFEV,MODE,NFEV,NJEV,NPRINT DOUBLE PRECISION FACTOR,ONE,XTOL,ZERO DATA FACTOR,ONE,ZERO /1.0D2,1.0D0,0.0D0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. LDFJAC .LT. N .OR. TOL .LT. ZERO * .OR. LWA .LT. (N*(N + 13))/2) GO TO 20 C C CALL HYBRJ. C MAXFEV = 100*(N + 1) XTOL = TOL MODE = 2 DO 10 J = 1, N WA(J) = ONE 10 CONTINUE NPRINT = 0 LR = (N*(N + 1))/2 CALL HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,WA(1),MODE, * FACTOR,NPRINT,INFO,NFEV,NJEV,WA(6*N+1),LR,WA(N+1), * WA(2*N+1),WA(3*N+1),WA(4*N+1),WA(5*N+1)) IF (INFO .EQ. 5) INFO = 4 20 CONTINUE RETURN C C LAST CARD OF SUBROUTINE HYBRJ1. C END SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) C ********** C C SUBROUTINE LMDER C C THE PURPOSE OF LMDER IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, C MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV, C NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER M,N,LDFJAC,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 LMDER. 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 FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.).100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X, FVEC, AND FJAC C AVAILABLE FOR PRINTING. FVEC AND FJAC SHOULD NOT BE C ALTERED. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,LMPAR,QRFAC C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,DSQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L DOUBLE PRECISION ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM, * ONE,PAR,PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO, * SUM,TEMP,TEMP1,TEMP2,XNORM,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0D0,1.0D-1,5.0D-1,2.5D-1,7.5D-1,1.0D-4,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. M * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) NJEV = NJEV + 1 IF (IFLAG .LT. 0) GO TO 300 C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) * CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(M,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 80 IF (MODE .EQ. 2) GO TO 60 DO 50 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 50 CONTINUE 60 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 70 J = 1, N WA3(J) = DIAG(J)*X(J) 70 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 80 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE THE FIRST N COMPONENTS IN C QTF. C DO 90 I = 1, M WA4(I) = FVEC(I) 90 CONTINUE DO 130 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 120 SUM = ZERO DO 100 I = J, M SUM = SUM + FJAC(I,J)*WA4(I) 100 CONTINUE TEMP = -SUM/FJAC(J,J) DO 110 I = J, M WA4(I) = WA4(I) + FJAC(I,J)*TEMP 110 CONTINUE 120 CONTINUE FJAC(J,J) = WA1(J) QTF(J) = WA4(J) 130 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 170 DO 160 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 150 SUM = ZERO DO 140 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 140 CONTINUE GNORM = DMAX1(GNORM,DABS(SUM/WA2(L))) 150 CONTINUE 160 CONTINUE 170 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 300 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 190 DO 180 J = 1, N DIAG(J) = DMAX1(DIAG(J),WA2(J)) 180 CONTINUE 190 CONTINUE C C BEGINNING OF THE INNER LOOP. C 200 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 210 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 210 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = DMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,FJAC,LDFJAC,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 230 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 220 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 220 CONTINUE 230 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (DSQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 240 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*DMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 260 240 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 250 DELTA = PNORM/P5 PAR = P5*PAR 250 CONTINUE 260 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 290 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 270 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 270 CONTINUE DO 280 I = 1, M FVEC(I) = WA4(I) 280 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 290 CONTINUE C C TESTS FOR CONVERGENCE. C IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (DABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 300 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 200 C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMDER. C END SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IPVT,WA, * LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE LMDER1 C C THE PURPOSE OF LMDER1 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 LMDER. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO, C IPVT,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER M,N,LDFJAC,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 LMDER1. 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 FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. 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 WITH IFLAG = 1 HAS C REACHED 100*(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 IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN 5*N+M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... LMDER C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER MAXFEV,MODE,NFEV,NJEV,NPRINT DOUBLE PRECISION FACTOR,FTOL,GTOL,XTOL,ZERO DATA FACTOR,ZERO /1.0D2,0.0D0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. M .OR. TOL .LT. ZERO * .OR. LWA .LT. 5*N + M) GO TO 10 C C CALL LMDER. C MAXFEV = 100*(N + 1) FTOL = TOL XTOL = TOL GTOL = ZERO MODE = 1 NPRINT = 0 CALL LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL,MAXFEV, * WA(1),MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,IPVT,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 LMDER1. C END SUBROUTINE LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC INTEGER IPVT(N) DOUBLE PRECISION FTOL,XTOL,GTOL,EPSFCN,FACTOR DOUBLE PRECISION X(N),FVEC(M),DIAG(N),FJAC(LDFJAC,N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) EXTERNAL FCN C ********** C C SUBROUTINE LMDIF C C THE PURPOSE OF LMDIF IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM. 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 LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, C DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC, C LDFJAC,IPVT,QTF,WA1,WA2,WA3,WA4) 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 DOUBLE PRECISION 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 LMDIF. 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 FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN IS AT LEAST C MAXFEV BY THE END OF AN ITERATION. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN HAS REACHED OR C EXCEEDED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN. C C FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,FDJAC2,LMPAR,QRFAC C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,DSQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L DOUBLE PRECISION ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM, * ONE,PAR,PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO, * SUM,TEMP,TEMP1,TEMP2,XNORM,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0D0,1.0D-1,5.0D-1,2.5D-1,7.5D-1,1.0D-4,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. M * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA4) NFEV = NFEV + N IF (IFLAG .LT. 0) GO TO 300 C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(M,N,X,FVEC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(M,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 80 IF (MODE .EQ. 2) GO TO 60 DO 50 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 50 CONTINUE 60 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 70 J = 1, N WA3(J) = DIAG(J)*X(J) 70 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 80 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE THE FIRST N COMPONENTS IN C QTF. C DO 90 I = 1, M WA4(I) = FVEC(I) 90 CONTINUE DO 130 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 120 SUM = ZERO DO 100 I = J, M SUM = SUM + FJAC(I,J)*WA4(I) 100 CONTINUE TEMP = -SUM/FJAC(J,J) DO 110 I = J, M WA4(I) = WA4(I) + FJAC(I,J)*TEMP 110 CONTINUE 120 CONTINUE FJAC(J,J) = WA1(J) QTF(J) = WA4(J) 130 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 170 DO 160 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 150 SUM = ZERO DO 140 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 140 CONTINUE GNORM = DMAX1(GNORM,DABS(SUM/WA2(L))) 150 CONTINUE 160 CONTINUE 170 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 300 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 190 DO 180 J = 1, N DIAG(J) = DMAX1(DIAG(J),WA2(J)) 180 CONTINUE 190 CONTINUE C C BEGINNING OF THE INNER LOOP. C 200 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 210 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 210 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = DMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 230 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 220 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 220 CONTINUE 230 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (DSQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 240 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*DMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 260 240 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 250 DELTA = PNORM/P5 PAR = P5*PAR 250 CONTINUE 260 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 290 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 270 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 270 CONTINUE DO 280 I = 1, M FVEC(I) = WA4(I) 280 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 290 CONTINUE C C TESTS FOR CONVERGENCE. C IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (DABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 300 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 200 C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMDIF. C END SUBROUTINE LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) INTEGER M,N,INFO,LWA INTEGER IWA(N) DOUBLE PRECISION TOL DOUBLE PRECISION 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 DOUBLE PRECISION 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 DOUBLE PRECISION EPSFCN,FACTOR,FTOL,GTOL,XTOL,ZERO DATA FACTOR,ZERO /1.0D2,0.0D0/ 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 SUBROUTINE LMPAR(N,R,LDR,IPVT,DIAG,QTB,DELTA,PAR,X,SDIAG,WA1, * WA2) INTEGER N,LDR INTEGER IPVT(N) DOUBLE PRECISION DELTA,PAR DOUBLE PRECISION R(LDR,N),DIAG(N),QTB(N),X(N),SDIAG(N),WA1(N), * WA2(N) C ********** C C SUBROUTINE LMPAR C C GIVEN AN M BY N MATRIX A, AN N BY N NONSINGULAR DIAGONAL C MATRIX D, AN M-VECTOR B, AND A POSITIVE NUMBER DELTA, C THE PROBLEM IS TO DETERMINE A VALUE FOR THE PARAMETER C PAR SUCH THAT IF X SOLVES THE SYSTEM C C A*X = B , SQRT(PAR)*D*X = 0 , C C IN THE LEAST SQUARES SENSE, AND DXNORM IS THE EUCLIDEAN C NORM OF D*X, THEN EITHER PAR IS ZERO AND C C (DXNORM-DELTA) .LE. 0.1*DELTA , C C OR PAR IS POSITIVE AND C C ABS(DXNORM-DELTA) .LE. 0.1*DELTA . C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION, WITH COLUMN PIVOTING, OF A. THAT IS, IF C A*P = Q*R, WHERE P IS A PERMUTATION MATRIX, Q HAS ORTHOGONAL C COLUMNS, AND R IS AN UPPER TRIANGULAR MATRIX WITH DIAGONAL C ELEMENTS OF NONINCREASING MAGNITUDE, THEN LMPAR EXPECTS C THE FULL UPPER TRIANGLE OF R, THE PERMUTATION MATRIX P, C AND THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. ON OUTPUT C LMPAR ALSO PROVIDES AN UPPER TRIANGULAR MATRIX S SUCH THAT C C T T T C P *(A *A + PAR*D*D)*P = S *S . C C S IS EMPLOYED WITHIN LMPAR AND MAY BE OF SEPARATE INTEREST. C C ONLY A FEW ITERATIONS ARE GENERALLY NEEDED FOR CONVERGENCE C OF THE ALGORITHM. IF, HOWEVER, THE LIMIT OF 10 ITERATIONS C IS REACHED, THEN THE OUTPUT PAR WILL CONTAIN THE BEST C VALUE OBTAINED SO FAR. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMPAR(N,R,LDR,IPVT,DIAG,QTB,DELTA,PAR,X,SDIAG, C WA1,WA2) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE FULL UPPER TRIANGLE C MUST CONTAIN THE FULL UPPER TRIANGLE OF THE MATRIX R. C ON OUTPUT THE FULL UPPER TRIANGLE IS UNALTERED, AND THE C STRICT LOWER TRIANGLE CONTAINS THE STRICT UPPER TRIANGLE C (TRANSPOSED) OF THE UPPER TRIANGULAR MATRIX S. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C IPVT IS AN INTEGER INPUT ARRAY OF LENGTH N WHICH DEFINES THE C PERMUTATION MATRIX P SUCH THAT A*P = Q*R. COLUMN J OF P C IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C DELTA IS A POSITIVE INPUT VARIABLE WHICH SPECIFIES AN UPPER C BOUND ON THE EUCLIDEAN NORM OF D*X. C C PAR IS A NONNEGATIVE VARIABLE. ON INPUT PAR CONTAINS AN C INITIAL ESTIMATE OF THE LEVENBERG-MARQUARDT PARAMETER. C ON OUTPUT PAR CONTAINS THE FINAL ESTIMATE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE LEAST C SQUARES SOLUTION OF THE SYSTEM A*X = B, SQRT(PAR)*D*X = 0, C FOR THE OUTPUT PAR. C C SDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF THE UPPER TRIANGULAR MATRIX S. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DPMPAR,ENORM,QRSOLV C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,ITER,J,JM1,JP1,K,L,NSING DOUBLE PRECISION DXNORM,DWARF,FP,GNORM,PARC,PARL,PARU,P1,P001, * SUM,TEMP,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA P1,P001,ZERO /1.0D-1,1.0D-3,0.0D0/ C C DWARF IS THE SMALLEST POSITIVE MAGNITUDE. C DWARF = DPMPAR(2) C C COMPUTE AND STORE IN X THE GAUSS-NEWTON DIRECTION. IF THE C JACOBIAN IS RANK-DEFICIENT, OBTAIN A LEAST SQUARES SOLUTION. C NSING = N DO 10 J = 1, N WA1(J) = QTB(J) IF (R(J,J) .EQ. ZERO .AND. NSING .EQ. N) NSING = J - 1 IF (NSING .LT. N) WA1(J) = ZERO 10 CONTINUE IF (NSING .LT. 1) GO TO 50 DO 40 K = 1, NSING J = NSING - K + 1 WA1(J) = WA1(J)/R(J,J) TEMP = WA1(J) JM1 = J - 1 IF (JM1 .LT. 1) GO TO 30 DO 20 I = 1, JM1 WA1(I) = WA1(I) - R(I,J)*TEMP 20 CONTINUE 30 CONTINUE 40 CONTINUE 50 CONTINUE DO 60 J = 1, N L = IPVT(J) X(L) = WA1(J) 60 CONTINUE C C INITIALIZE THE ITERATION COUNTER. C EVALUATE THE FUNCTION AT THE ORIGIN, AND TEST C FOR ACCEPTANCE OF THE GAUSS-NEWTON DIRECTION. C ITER = 0 DO 70 J = 1, N WA2(J) = DIAG(J)*X(J) 70 CONTINUE DXNORM = ENORM(N,WA2) FP = DXNORM - DELTA IF (FP .LE. P1*DELTA) GO TO 220 C C IF THE JACOBIAN IS NOT RANK DEFICIENT, THE NEWTON C STEP PROVIDES A LOWER BOUND, PARL, FOR THE ZERO OF C THE FUNCTION. OTHERWISE SET THIS BOUND TO ZERO. C PARL = ZERO IF (NSING .LT. N) GO TO 120 DO 80 J = 1, N L = IPVT(J) WA1(J) = DIAG(L)*(WA2(L)/DXNORM) 80 CONTINUE DO 110 J = 1, N SUM = ZERO JM1 = J - 1 IF (JM1 .LT. 1) GO TO 100 DO 90 I = 1, JM1 SUM = SUM + R(I,J)*WA1(I) 90 CONTINUE 100 CONTINUE WA1(J) = (WA1(J) - SUM)/R(J,J) 110 CONTINUE TEMP = ENORM(N,WA1) PARL = ((FP/DELTA)/TEMP)/TEMP 120 CONTINUE C C CALCULATE AN UPPER BOUND, PARU, FOR THE ZERO OF THE FUNCTION. C DO 140 J = 1, N SUM = ZERO DO 130 I = 1, J SUM = SUM + R(I,J)*QTB(I) 130 CONTINUE L = IPVT(J) WA1(J) = SUM/DIAG(L) 140 CONTINUE GNORM = ENORM(N,WA1) PARU = GNORM/DELTA IF (PARU .EQ. ZERO) PARU = DWARF/DMIN1(DELTA,P1) C C IF THE INPUT PAR LIES OUTSIDE OF THE INTERVAL (PARL,PARU), C SET PAR TO THE CLOSER ENDPOINT. C PAR = DMAX1(PAR,PARL) PAR = DMIN1(PAR,PARU) IF (PAR .EQ. ZERO) PAR = GNORM/DXNORM C C BEGINNING OF AN ITERATION. C 150 CONTINUE ITER = ITER + 1 C C EVALUATE THE FUNCTION AT THE CURRENT VALUE OF PAR. C IF (PAR .EQ. ZERO) PAR = DMAX1(DWARF,P001*PARU) TEMP = DSQRT(PAR) DO 160 J = 1, N WA1(J) = TEMP*DIAG(J) 160 CONTINUE CALL QRSOLV(N,R,LDR,IPVT,WA1,QTB,X,SDIAG,WA2) DO 170 J = 1, N WA2(J) = DIAG(J)*X(J) 170 CONTINUE DXNORM = ENORM(N,WA2) TEMP = FP FP = DXNORM - DELTA C C IF THE FUNCTION IS SMALL ENOUGH, ACCEPT THE CURRENT VALUE C OF PAR. ALSO TEST FOR THE EXCEPTIONAL CASES WHERE PARL C IS ZERO OR THE NUMBER OF ITERATIONS HAS REACHED 10. C IF (DABS(FP) .LE. P1*DELTA * .OR. PARL .EQ. ZERO .AND. FP .LE. TEMP * .AND. TEMP .LT. ZERO .OR. ITER .EQ. 10) GO TO 220 C C COMPUTE THE NEWTON CORRECTION. C DO 180 J = 1, N L = IPVT(J) WA1(J) = DIAG(L)*(WA2(L)/DXNORM) 180 CONTINUE DO 210 J = 1, N WA1(J) = WA1(J)/SDIAG(J) TEMP = WA1(J) JP1 = J + 1 IF (N .LT. JP1) GO TO 200 DO 190 I = JP1, N WA1(I) = WA1(I) - R(I,J)*TEMP 190 CONTINUE 200 CONTINUE 210 CONTINUE TEMP = ENORM(N,WA1) PARC = ((FP/DELTA)/TEMP)/TEMP C C DEPENDING ON THE SIGN OF THE FUNCTION, UPDATE PARL OR PARU. C IF (FP .GT. ZERO) PARL = DMAX1(PARL,PAR) IF (FP .LT. ZERO) PARU = DMIN1(PARU,PAR) C C COMPUTE AN IMPROVED ESTIMATE FOR PAR. C PAR = DMAX1(PARL,PAR+PARC) C C END OF AN ITERATION. C GO TO 150 220 CONTINUE C C TERMINATION. C IF (ITER .EQ. 0) PAR = ZERO RETURN C C LAST CARD OF SUBROUTINE LMPAR. C END SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) LOGICAL SING DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), * WA1(N),WA2(N),WA3(N),WA4(M) C ********** C C SUBROUTINE LMSTR C C THE PURPOSE OF LMSTR IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM WHICH USES MINIMAL STORAGE. C THE USER MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE C FUNCTIONS AND THE ROWS OF THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, C MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV, C NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C FCN MUST BE DECLARED IN AN EXTERNAL STATEMENT IN THE C USER CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) C INTEGER M,N,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. C IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE C JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. 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 LMSTR. 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 FJAC IS AN OUTPUT N BY N ARRAY. THE UPPER TRIANGLE OF FJAC C CONTAINS AN UPPER TRIANGULAR MATRIX R SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRIANGULAR C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,LMPAR,QRFAC,RWUPDT C C FORTRAN-SUPPLIED ... DABS,DMAX1,DMIN1,DSQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L DOUBLE PRECISION ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM, * ONE,PAR,PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO, * SUM,TEMP,TEMP1,TEMP2,XNORM,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0D0,1.0D-1,5.0D-1,2.5D-1,7.5D-1,1.0D-4,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. N * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 340 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 340 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,WA3,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 340 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(M,N,X,FVEC,WA3,IFLAG) IF (IFLAG .LT. 0) GO TO 340 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN MATRIX C CALCULATED ONE ROW AT A TIME, WHILE SIMULTANEOUSLY C FORMING (Q TRANSPOSE)*FVEC AND STORING THE FIRST C N COMPONENTS IN QTF. C DO 60 J = 1, N QTF(J) = ZERO DO 50 I = 1, N FJAC(I,J) = ZERO 50 CONTINUE 60 CONTINUE IFLAG = 2 DO 70 I = 1, M CALL FCN(M,N,X,FVEC,WA3,IFLAG) IF (IFLAG .LT. 0) GO TO 340 TEMP = FVEC(I) CALL RWUPDT(N,FJAC,LDFJAC,WA3,QTF,TEMP,WA1,WA2) IFLAG = IFLAG + 1 70 CONTINUE NJEV = NJEV + 1 C C IF THE JACOBIAN IS RANK DEFICIENT, CALL QRFAC TO C REORDER ITS COLUMNS AND UPDATE THE COMPONENTS OF QTF. C SING = .FALSE. DO 80 J = 1, N IF (FJAC(J,J) .EQ. ZERO) SING = .TRUE. IPVT(J) = J WA2(J) = ENORM(J,FJAC(1,J)) 80 CONTINUE IF (.NOT.SING) GO TO 130 CALL QRFAC(N,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE FJAC(J,J) = WA1(J) 120 CONTINUE 130 CONTINUE C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 170 IF (MODE .EQ. 2) GO TO 150 DO 140 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 140 CONTINUE 150 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 160 J = 1, N WA3(J) = DIAG(J)*X(J) 160 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 170 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 210 DO 200 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 190 SUM = ZERO DO 180 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 180 CONTINUE GNORM = DMAX1(GNORM,DABS(SUM/WA2(L))) 190 CONTINUE 200 CONTINUE 210 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 340 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 230 DO 220 J = 1, N DIAG(J) = DMAX1(DIAG(J),WA2(J)) 220 CONTINUE 230 CONTINUE C C BEGINNING OF THE INNER LOOP. C 240 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 250 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 250 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = DMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,WA3,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 340 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 270 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 260 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 260 CONTINUE 270 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (DSQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 280 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*DMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 300 280 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 290 DELTA = PNORM/P5 PAR = P5*PAR 290 CONTINUE 300 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 330 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 310 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 310 CONTINUE DO 320 I = 1, M FVEC(I) = WA4(I) 320 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 330 CONTINUE C C TESTS FOR CONVERGENCE. C IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (DABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 340 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (DABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 340 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 240 C C END OF THE OUTER LOOP. C GO TO 30 340 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,WA3,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMSTR. C END SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IPVT,WA, * LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) DOUBLE PRECISION TOL DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE LMSTR1 C C THE PURPOSE OF LMSTR1 IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM WHICH USES MINIMAL STORAGE. C THIS IS DONE BY USING THE MORE GENERAL LEAST-SQUARES SOLVER C LMSTR. THE USER MUST PROVIDE A SUBROUTINE WHICH CALCULATES C THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO, C IPVT,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C FCN MUST BE DECLARED IN AN EXTERNAL STATEMENT IN THE C USER CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) C INTEGER M,N,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. C IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE C JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. 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 LMSTR1. 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 FJAC IS AN OUTPUT N BY N ARRAY. THE UPPER TRIANGLE OF FJAC C CONTAINS AN UPPER TRIANGULAR MATRIX R SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRIANGULAR C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. 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 WITH IFLAG = 1 HAS C REACHED 100*(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 IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN 5*N+M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... LMSTR C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER MAXFEV,MODE,NFEV,NJEV,NPRINT DOUBLE PRECISION FACTOR,FTOL,GTOL,XTOL,ZERO DATA FACTOR,ZERO /1.0D2,0.0D0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. N .OR. TOL .LT. ZERO * .OR. LWA .LT. 5*N + M) GO TO 10 C C CALL LMSTR. C MAXFEV = 100*(N + 1) FTOL = TOL XTOL = TOL GTOL = ZERO MODE = 1 NPRINT = 0 CALL LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL,MAXFEV, * WA(1),MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,IPVT,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 LMSTR1. C END SUBROUTINE QFORM(M,N,Q,LDQ,WA) INTEGER M,N,LDQ DOUBLE PRECISION Q(LDQ,M),WA(M) C ********** C C SUBROUTINE QFORM C C THIS SUBROUTINE PROCEEDS FROM THE COMPUTED QR FACTORIZATION OF C AN M BY N MATRIX A TO ACCUMULATE THE M BY M ORTHOGONAL MATRIX C Q FROM ITS FACTORED FORM. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QFORM(M,N,Q,LDQ,WA) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A AND THE ORDER OF Q. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C Q IS AN M BY M ARRAY. ON INPUT THE FULL LOWER TRAPEZOID IN C THE FIRST MIN(M,N) COLUMNS OF Q CONTAINS THE FACTORED FORM. C ON OUTPUT Q HAS BEEN ACCUMULATED INTO A SQUARE MATRIX. C C LDQ IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY Q. C C WA IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JM1,K,L,MINMN,NP1 DOUBLE PRECISION ONE,SUM,TEMP,ZERO DATA ONE,ZERO /1.0D0,0.0D0/ C C ZERO OUT UPPER TRIANGLE OF Q IN THE FIRST MIN(M,N) COLUMNS. C MINMN = MIN0(M,N) IF (MINMN .LT. 2) GO TO 30 DO 20 J = 2, MINMN JM1 = J - 1 DO 10 I = 1, JM1 Q(I,J) = ZERO 10 CONTINUE 20 CONTINUE 30 CONTINUE C C INITIALIZE REMAINING COLUMNS TO THOSE OF THE IDENTITY MATRIX. C NP1 = N + 1 IF (M .LT. NP1) GO TO 60 DO 50 J = NP1, M DO 40 I = 1, M Q(I,J) = ZERO 40 CONTINUE Q(J,J) = ONE 50 CONTINUE 60 CONTINUE C C ACCUMULATE Q FROM ITS FACTORED FORM. C DO 120 L = 1, MINMN K = MINMN - L + 1 DO 70 I = K, M WA(I) = Q(I,K) Q(I,K) = ZERO 70 CONTINUE Q(K,K) = ONE IF (WA(K) .EQ. ZERO) GO TO 110 DO 100 J = K, M SUM = ZERO DO 80 I = K, M SUM = SUM + Q(I,J)*WA(I) 80 CONTINUE TEMP = SUM/WA(K) DO 90 I = K, M Q(I,J) = Q(I,J) - TEMP*WA(I) 90 CONTINUE 100 CONTINUE 110 CONTINUE 120 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QFORM. C END SUBROUTINE QRFAC(M,N,A,LDA,PIVOT,IPVT,LIPVT,RDIAG,ACNORM,WA) INTEGER M,N,LDA,LIPVT INTEGER IPVT(LIPVT) LOGICAL PIVOT DOUBLE PRECISION A(LDA,N),RDIAG(N),ACNORM(N),WA(N) C ********** C C SUBROUTINE QRFAC C C THIS SUBROUTINE USES HOUSEHOLDER TRANSFORMATIONS WITH COLUMN C PIVOTING (OPTIONAL) TO COMPUTE A QR FACTORIZATION OF THE C M BY N MATRIX A. THAT IS, QRFAC DETERMINES AN ORTHOGONAL C MATRIX Q, A PERMUTATION MATRIX P, AND AN UPPER TRAPEZOIDAL C MATRIX R WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE, C SUCH THAT A*P = Q*R. THE HOUSEHOLDER TRANSFORMATION FOR C COLUMN K, K = 1,2,...,MIN(M,N), IS OF THE FORM C C T C I - (1/U(K))*U*U C C WHERE U HAS ZEROS IN THE FIRST K-1 POSITIONS. THE FORM OF C THIS TRANSFORMATION AND THE METHOD OF PIVOTING FIRST C APPEARED IN THE CORRESPONDING LINPACK SUBROUTINE. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QRFAC(M,N,A,LDA,PIVOT,IPVT,LIPVT,RDIAG,ACNORM,WA) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C A IS AN M BY N ARRAY. ON INPUT A CONTAINS THE MATRIX FOR C WHICH THE QR FACTORIZATION IS TO BE COMPUTED. ON OUTPUT C THE STRICT UPPER TRAPEZOIDAL PART OF A CONTAINS THE STRICT C UPPER TRAPEZOIDAL PART OF R, AND THE LOWER TRAPEZOIDAL C PART OF A CONTAINS A FACTORED FORM OF Q (THE NON-TRIVIAL C ELEMENTS OF THE U VECTORS DESCRIBED ABOVE). C C LDA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY A. C C PIVOT IS A LOGICAL INPUT VARIABLE. IF PIVOT IS SET TRUE, C THEN COLUMN PIVOTING IS ENFORCED. IF PIVOT IS SET FALSE, C THEN NO COLUMN PIVOTING IS DONE. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH LIPVT. IPVT C DEFINES THE PERMUTATION MATRIX P SUCH THAT A*P = Q*R. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C IF PIVOT IS FALSE, IPVT IS NOT REFERENCED. C C LIPVT IS A POSITIVE INTEGER INPUT VARIABLE. IF PIVOT IS FALSE, C THEN LIPVT MAY BE AS SMALL AS 1. IF PIVOT IS TRUE, THEN C LIPVT MUST BE AT LEAST N. C C RDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF R. C C ACNORM IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C NORMS OF THE CORRESPONDING COLUMNS OF THE INPUT MATRIX A. C IF THIS INFORMATION IS NOT NEEDED, THEN ACNORM CAN COINCIDE C WITH RDIAG. C C WA IS A WORK ARRAY OF LENGTH N. IF PIVOT IS FALSE, THEN WA C CAN COINCIDE WITH RDIAG. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DPMPAR,ENORM C C FORTRAN-SUPPLIED ... DMAX1,DSQRT,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JP1,K,KMAX,MINMN DOUBLE PRECISION AJNORM,EPSMCH,ONE,P05,SUM,TEMP,ZERO DOUBLE PRECISION DPMPAR,ENORM DATA ONE,P05,ZERO /1.0D0,5.0D-2,0.0D0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = DPMPAR(1) C C COMPUTE THE INITIAL COLUMN NORMS AND INITIALIZE SEVERAL ARRAYS. C DO 10 J = 1, N ACNORM(J) = ENORM(M,A(1,J)) RDIAG(J) = ACNORM(J) WA(J) = RDIAG(J) IF (PIVOT) IPVT(J) = J 10 CONTINUE C C REDUCE A TO R WITH HOUSEHOLDER TRANSFORMATIONS. C MINMN = MIN0(M,N) DO 110 J = 1, MINMN IF (.NOT.PIVOT) GO TO 40 C C BRING THE COLUMN OF LARGEST NORM INTO THE PIVOT POSITION. C KMAX = J DO 20 K = J, N IF (RDIAG(K) .GT. RDIAG(KMAX)) KMAX = K 20 CONTINUE IF (KMAX .EQ. J) GO TO 40 DO 30 I = 1, M TEMP = A(I,J) A(I,J) = A(I,KMAX) A(I,KMAX) = TEMP 30 CONTINUE RDIAG(KMAX) = RDIAG(J) WA(KMAX) = WA(J) K = IPVT(J) IPVT(J) = IPVT(KMAX) IPVT(KMAX) = K 40 CONTINUE C C COMPUTE THE HOUSEHOLDER TRANSFORMATION TO REDUCE THE C J-TH COLUMN OF A TO A MULTIPLE OF THE J-TH UNIT VECTOR. C AJNORM = ENORM(M-J+1,A(J,J)) IF (AJNORM .EQ. ZERO) GO TO 100 IF (A(J,J) .LT. ZERO) AJNORM = -AJNORM DO 50 I = J, M A(I,J) = A(I,J)/AJNORM 50 CONTINUE A(J,J) = A(J,J) + ONE C C APPLY THE TRANSFORMATION TO THE REMAINING COLUMNS C AND UPDATE THE NORMS. C JP1 = J + 1 IF (N .LT. JP1) GO TO 100 DO 90 K = JP1, N SUM = ZERO DO 60 I = J, M SUM = SUM + A(I,J)*A(I,K) 60 CONTINUE TEMP = SUM/A(J,J) DO 70 I = J, M A(I,K) = A(I,K) - TEMP*A(I,J) 70 CONTINUE IF (.NOT.PIVOT .OR. RDIAG(K) .EQ. ZERO) GO TO 80 TEMP = A(J,K)/RDIAG(K) RDIAG(K) = RDIAG(K)*DSQRT(DMAX1(ZERO,ONE-TEMP**2)) IF (P05*(RDIAG(K)/WA(K))**2 .GT. EPSMCH) GO TO 80 RDIAG(K) = ENORM(M-J,A(JP1,K)) WA(K) = RDIAG(K) 80 CONTINUE 90 CONTINUE 100 CONTINUE RDIAG(J) = -AJNORM 110 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QRFAC. C END SUBROUTINE QRSOLV(N,R,LDR,IPVT,DIAG,QTB,X,SDIAG,WA) INTEGER N,LDR INTEGER IPVT(N) DOUBLE PRECISION R(LDR,N),DIAG(N),QTB(N),X(N),SDIAG(N),WA(N) C ********** C C SUBROUTINE QRSOLV C C GIVEN AN M BY N MATRIX A, AN N BY N DIAGONAL MATRIX D, C AND AN M-VECTOR B, THE PROBLEM IS TO DETERMINE AN X WHICH C SOLVES THE SYSTEM C C A*X = B , D*X = 0 , C C IN THE LEAST SQUARES SENSE. C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION, WITH COLUMN PIVOTING, OF A. THAT IS, IF C A*P = Q*R, WHERE P IS A PERMUTATION MATRIX, Q HAS ORTHOGONAL C COLUMNS, AND R IS AN UPPER TRIANGULAR MATRIX WITH DIAGONAL C ELEMENTS OF NONINCREASING MAGNITUDE, THEN QRSOLV EXPECTS C THE FULL UPPER TRIANGLE OF R, THE PERMUTATION MATRIX P, C AND THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. THE SYSTEM C A*X = B, D*X = 0, IS THEN EQUIVALENT TO C C T T C R*Z = Q *B , P *D*P*Z = 0 , C C WHERE X = P*Z. IF THIS SYSTEM DOES NOT HAVE FULL RANK, C THEN A LEAST SQUARES SOLUTION IS OBTAINED. ON OUTPUT QRSOLV C ALSO PROVIDES AN UPPER TRIANGULAR MATRIX S SUCH THAT C C T T T C P *(A *A + D*D)*P = S *S . C C S IS COMPUTED WITHIN QRSOLV AND MAY BE OF SEPARATE INTEREST. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QRSOLV(N,R,LDR,IPVT,DIAG,QTB,X,SDIAG,WA) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE FULL UPPER TRIANGLE C MUST CONTAIN THE FULL UPPER TRIANGLE OF THE MATRIX R. C ON OUTPUT THE FULL UPPER TRIANGLE IS UNALTERED, AND THE C STRICT LOWER TRIANGLE CONTAINS THE STRICT UPPER TRIANGLE C (TRANSPOSED) OF THE UPPER TRIANGULAR MATRIX S. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C IPVT IS AN INTEGER INPUT ARRAY OF LENGTH N WHICH DEFINES THE C PERMUTATION MATRIX P SUCH THAT A*P = Q*R. COLUMN J OF P C IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE LEAST C SQUARES SOLUTION OF THE SYSTEM A*X = B, D*X = 0. C C SDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF THE UPPER TRIANGULAR MATRIX S. C C WA IS A WORK ARRAY OF LENGTH N. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DABS,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JP1,K,KP1,L,NSING DOUBLE PRECISION COS,COTAN,P5,P25,QTBPJ,SIN,SUM,TAN,TEMP,ZERO DATA P5,P25,ZERO /5.0D-1,2.5D-1,0.0D0/ C C COPY R AND (Q TRANSPOSE)*B TO PRESERVE INPUT AND INITIALIZE S. C IN PARTICULAR, SAVE THE DIAGONAL ELEMENTS OF R IN X. C DO 20 J = 1, N DO 10 I = J, N R(I,J) = R(J,I) 10 CONTINUE X(J) = R(J,J) WA(J) = QTB(J) 20 CONTINUE C C ELIMINATE THE DIAGONAL MATRIX D USING A GIVENS ROTATION. C DO 100 J = 1, N C C PREPARE THE ROW OF D TO BE ELIMINATED, LOCATING THE C DIAGONAL ELEMENT USING P FROM THE QR FACTORIZATION. C L = IPVT(J) IF (DIAG(L) .EQ. ZERO) GO TO 90 DO 30 K = J, N SDIAG(K) = ZERO 30 CONTINUE SDIAG(J) = DIAG(L) C C THE TRANSFORMATIONS TO ELIMINATE THE ROW OF D C MODIFY ONLY A SINGLE ELEMENT OF (Q TRANSPOSE)*B C BEYOND THE FIRST N, WHICH IS INITIALLY ZERO. C QTBPJ = ZERO DO 80 K = J, N C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C APPROPRIATE ELEMENT IN THE CURRENT ROW OF D. C IF (SDIAG(K) .EQ. ZERO) GO TO 70 IF (DABS(R(K,K)) .GE. DABS(SDIAG(K))) GO TO 40 COTAN = R(K,K)/SDIAG(K) SIN = P5/DSQRT(P25+P25*COTAN**2) COS = SIN*COTAN GO TO 50 40 CONTINUE TAN = SDIAG(K)/R(K,K) COS = P5/DSQRT(P25+P25*TAN**2) SIN = COS*TAN 50 CONTINUE C C COMPUTE THE MODIFIED DIAGONAL ELEMENT OF R AND C THE MODIFIED ELEMENT OF ((Q TRANSPOSE)*B,0). C R(K,K) = COS*R(K,K) + SIN*SDIAG(K) TEMP = COS*WA(K) + SIN*QTBPJ QTBPJ = -SIN*WA(K) + COS*QTBPJ WA(K) = TEMP C C ACCUMULATE THE TRANFORMATION IN THE ROW OF S. C KP1 = K + 1 IF (N .LT. KP1) GO TO 70 DO 60 I = KP1, N TEMP = COS*R(I,K) + SIN*SDIAG(I) SDIAG(I) = -SIN*R(I,K) + COS*SDIAG(I) R(I,K) = TEMP 60 CONTINUE 70 CONTINUE 80 CONTINUE 90 CONTINUE C C STORE THE DIAGONAL ELEMENT OF S AND RESTORE C THE CORRESPONDING DIAGONAL ELEMENT OF R. C SDIAG(J) = R(J,J) R(J,J) = X(J) 100 CONTINUE C C SOLVE THE TRIANGULAR SYSTEM FOR Z. IF THE SYSTEM IS C SINGULAR, THEN OBTAIN A LEAST SQUARES SOLUTION. C NSING = N DO 110 J = 1, N IF (SDIAG(J) .EQ. ZERO .AND. NSING .EQ. N) NSING = J - 1 IF (NSING .LT. N) WA(J) = ZERO 110 CONTINUE IF (NSING .LT. 1) GO TO 150 DO 140 K = 1, NSING J = NSING - K + 1 SUM = ZERO JP1 = J + 1 IF (NSING .LT. JP1) GO TO 130 DO 120 I = JP1, NSING SUM = SUM + R(I,J)*WA(I) 120 CONTINUE 130 CONTINUE WA(J) = (WA(J) - SUM)/SDIAG(J) 140 CONTINUE 150 CONTINUE C C PERMUTE THE COMPONENTS OF Z BACK TO COMPONENTS OF X. C DO 160 J = 1, N L = IPVT(J) X(L) = WA(J) 160 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QRSOLV. C END SUBROUTINE RWUPDT(N,R,LDR,W,B,ALPHA,COS,SIN) INTEGER N,LDR DOUBLE PRECISION ALPHA DOUBLE PRECISION R(LDR,N),W(N),B(N),COS(N),SIN(N) C ********** C C SUBROUTINE RWUPDT C C GIVEN AN N BY N UPPER TRIANGULAR MATRIX R, THIS SUBROUTINE C COMPUTES THE QR DECOMPOSITION OF THE MATRIX FORMED WHEN A ROW C IS ADDED TO R. IF THE ROW IS SPECIFIED BY THE VECTOR W, THEN C RWUPDT DETERMINES AN ORTHOGONAL MATRIX Q SUCH THAT WHEN THE C N+1 BY N MATRIX COMPOSED OF R AUGMENTED BY W IS PREMULTIPLIED C BY (Q TRANSPOSE), THE RESULTING MATRIX IS UPPER TRAPEZOIDAL. C THE MATRIX (Q TRANSPOSE) IS THE PRODUCT OF N TRANSFORMATIONS C C G(N)*G(N-1)* ... *G(1) C C WHERE G(I) IS A GIVENS ROTATION IN THE (I,N+1) PLANE WHICH C ELIMINATES ELEMENTS IN THE (N+1)-ST PLANE. RWUPDT ALSO C COMPUTES THE PRODUCT (Q TRANSPOSE)*C WHERE C IS THE C (N+1)-VECTOR (B,ALPHA). Q ITSELF IS NOT ACCUMULATED, RATHER C THE INFORMATION TO RECOVER THE G ROTATIONS IS SUPPLIED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE RWUPDT(N,R,LDR,W,B,ALPHA,COS,SIN) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE UPPER TRIANGULAR PART OF C R MUST CONTAIN THE MATRIX TO BE UPDATED. ON OUTPUT R C CONTAINS THE UPDATED TRIANGULAR MATRIX. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C W IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE ROW C VECTOR TO BE ADDED TO R. C C B IS AN ARRAY OF LENGTH N. ON INPUT B MUST CONTAIN THE C FIRST N ELEMENTS OF THE VECTOR C. ON OUTPUT B CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*C. C C ALPHA IS A VARIABLE. ON INPUT ALPHA MUST CONTAIN THE C (N+1)-ST ELEMENT OF THE VECTOR C. ON OUTPUT ALPHA CONTAINS C THE (N+1)-ST ELEMENT OF THE VECTOR (Q TRANSPOSE)*C. C C COS IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C COSINES OF THE TRANSFORMING GIVENS ROTATIONS. C C SIN IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C SINES OF THE TRANSFORMING GIVENS ROTATIONS. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DABS,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER I,J,JM1 DOUBLE PRECISION COTAN,ONE,P5,P25,ROWJ,TAN,TEMP,ZERO DATA ONE,P5,P25,ZERO /1.0D0,5.0D-1,2.5D-1,0.0D0/ C DO 60 J = 1, N ROWJ = W(J) JM1 = J - 1 C C APPLY THE PREVIOUS TRANSFORMATIONS TO C R(I,J), I=1,2,...,J-1, AND TO W(J). C IF (JM1 .LT. 1) GO TO 20 DO 10 I = 1, JM1 TEMP = COS(I)*R(I,J) + SIN(I)*ROWJ ROWJ = -SIN(I)*R(I,J) + COS(I)*ROWJ R(I,J) = TEMP 10 CONTINUE 20 CONTINUE C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES W(J). C COS(J) = ONE SIN(J) = ZERO IF (ROWJ .EQ. ZERO) GO TO 50 IF (DABS(R(J,J)) .GE. DABS(ROWJ)) GO TO 30 COTAN = R(J,J)/ROWJ SIN(J) = P5/DSQRT(P25+P25*COTAN**2) COS(J) = SIN(J)*COTAN GO TO 40 30 CONTINUE TAN = ROWJ/R(J,J) COS(J) = P5/DSQRT(P25+P25*TAN**2) SIN(J) = COS(J)*TAN 40 CONTINUE C C APPLY THE CURRENT TRANSFORMATION TO R(J,J), B(J), AND ALPHA. C R(J,J) = COS(J)*R(J,J) + SIN(J)*ROWJ TEMP = COS(J)*B(J) + SIN(J)*ALPHA ALPHA = -SIN(J)*B(J) + COS(J)*ALPHA B(J) = TEMP 50 CONTINUE 60 CONTINUE RETURN C C LAST CARD OF SUBROUTINE RWUPDT. C END SUBROUTINE R1MPYQ(M,N,A,LDA,V,W) INTEGER M,N,LDA DOUBLE PRECISION A(LDA,N),V(N),W(N) C ********** C C SUBROUTINE R1MPYQ C C GIVEN AN M BY N MATRIX A, THIS SUBROUTINE COMPUTES A*Q WHERE C Q IS THE PRODUCT OF 2*(N - 1) TRANSFORMATIONS C C GV(N-1)*...*GV(1)*GW(1)*...*GW(N-1) C C AND GV(I), GW(I) ARE GIVENS ROTATIONS IN THE (I,N) PLANE WHICH C ELIMINATE ELEMENTS IN THE I-TH AND N-TH PLANES, RESPECTIVELY. C Q ITSELF IS NOT GIVEN, RATHER THE INFORMATION TO RECOVER THE C GV, GW ROTATIONS IS SUPPLIED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE R1MPYQ(M,N,A,LDA,V,W) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C A IS AN M BY N ARRAY. ON INPUT A MUST CONTAIN THE MATRIX C TO BE POSTMULTIPLIED BY THE ORTHOGONAL MATRIX Q C DESCRIBED ABOVE. ON OUTPUT A*Q HAS REPLACED A. C C LDA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY A. C C V IS AN INPUT ARRAY OF LENGTH N. V(I) MUST CONTAIN THE C INFORMATION NECESSARY TO RECOVER THE GIVENS ROTATION GV(I) C DESCRIBED ABOVE. C C W IS AN INPUT ARRAY OF LENGTH N. W(I) MUST CONTAIN THE C INFORMATION NECESSARY TO RECOVER THE GIVENS ROTATION GW(I) C DESCRIBED ABOVE. C C SUBROUTINES CALLED C C FORTRAN-SUPPLIED ... DABS,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,NMJ,NM1 DOUBLE PRECISION COS,ONE,SIN,TEMP DATA ONE /1.0D0/ C C APPLY THE FIRST SET OF GIVENS ROTATIONS TO A. C NM1 = N - 1 IF (NM1 .LT. 1) GO TO 50 DO 20 NMJ = 1, NM1 J = N - NMJ IF (DABS(V(J)) .GT. ONE) COS = ONE/V(J) IF (DABS(V(J)) .GT. ONE) SIN = DSQRT(ONE-COS**2) IF (DABS(V(J)) .LE. ONE) SIN = V(J) IF (DABS(V(J)) .LE. ONE) COS = DSQRT(ONE-SIN**2) DO 10 I = 1, M TEMP = COS*A(I,J) - SIN*A(I,N) A(I,N) = SIN*A(I,J) + COS*A(I,N) A(I,J) = TEMP 10 CONTINUE 20 CONTINUE C C APPLY THE SECOND SET OF GIVENS ROTATIONS TO A. C DO 40 J = 1, NM1 IF (DABS(W(J)) .GT. ONE) COS = ONE/W(J) IF (DABS(W(J)) .GT. ONE) SIN = DSQRT(ONE-COS**2) IF (DABS(W(J)) .LE. ONE) SIN = W(J) IF (DABS(W(J)) .LE. ONE) COS = DSQRT(ONE-SIN**2) DO 30 I = 1, M TEMP = COS*A(I,J) + SIN*A(I,N) A(I,N) = -SIN*A(I,J) + COS*A(I,N) A(I,J) = TEMP 30 CONTINUE 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE R1MPYQ. C END SUBROUTINE R1UPDT(M,N,S,LS,U,V,W,SING) INTEGER M,N,LS LOGICAL SING DOUBLE PRECISION S(LS),U(M),V(N),W(M) C ********** C C SUBROUTINE R1UPDT C C GIVEN AN M BY N LOWER TRAPEZOIDAL MATRIX S, AN M-VECTOR U, C AND AN N-VECTOR V, THE PROBLEM IS TO DETERMINE AN C ORTHOGONAL MATRIX Q SUCH THAT C C T C (S + U*V )*Q C C IS AGAIN LOWER TRAPEZOIDAL. C C THIS SUBROUTINE DETERMINES Q AS THE PRODUCT OF 2*(N - 1) C TRANSFORMATIONS C C GV(N-1)*...*GV(1)*GW(1)*...*GW(N-1) C C WHERE GV(I), GW(I) ARE GIVENS ROTATIONS IN THE (I,N) PLANE C WHICH ELIMINATE ELEMENTS IN THE I-TH AND N-TH PLANES, C RESPECTIVELY. Q ITSELF IS NOT ACCUMULATED, RATHER THE C INFORMATION TO RECOVER THE GV, GW ROTATIONS IS RETURNED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE R1UPDT(M,N,S,LS,U,V,W,SING) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF S. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF S. N MUST NOT EXCEED M. C C S IS AN ARRAY OF LENGTH LS. ON INPUT S MUST CONTAIN THE LOWER C TRAPEZOIDAL MATRIX S STORED BY COLUMNS. ON OUTPUT S CONTAINS C THE LOWER TRAPEZOIDAL MATRIX PRODUCED AS DESCRIBED ABOVE. C C LS IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(2*M-N+1))/2. C C U IS AN INPUT ARRAY OF LENGTH M WHICH MUST CONTAIN THE C VECTOR U. C C V IS AN ARRAY OF LENGTH N. ON INPUT V MUST CONTAIN THE VECTOR C V. ON OUTPUT V(I) CONTAINS THE INFORMATION NECESSARY TO C RECOVER THE GIVENS ROTATION GV(I) DESCRIBED ABOVE. C C W IS AN OUTPUT ARRAY OF LENGTH M. W(I) CONTAINS INFORMATION C NECESSARY TO RECOVER THE GIVENS ROTATION GW(I) DESCRIBED C ABOVE. C C SING IS A LOGICAL OUTPUT VARIABLE. SING IS SET TRUE IF ANY C OF THE DIAGONAL ELEMENTS OF THE OUTPUT S ARE ZERO. OTHERWISE C SING IS SET FALSE. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DPMPAR C C FORTRAN-SUPPLIED ... DABS,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE, C JOHN L. NAZARETH C C ********** INTEGER I,J,JJ,L,NMJ,NM1 DOUBLE PRECISION COS,COTAN,GIANT,ONE,P5,P25,SIN,TAN,TAU,TEMP, * ZERO DOUBLE PRECISION DPMPAR DATA ONE,P5,P25,ZERO /1.0D0,5.0D-1,2.5D-1,0.0D0/ C C GIANT IS THE LARGEST MAGNITUDE. C GIANT = DPMPAR(3) C C INITIALIZE THE DIAGONAL ELEMENT POINTER. C JJ = (N*(2*M - N + 1))/2 - (M - N) C C MOVE THE NONTRIVIAL PART OF THE LAST COLUMN OF S INTO W. C L = JJ DO 10 I = N, M W(I) = S(L) L = L + 1 10 CONTINUE C C ROTATE THE VECTOR V INTO A MULTIPLE OF THE N-TH UNIT VECTOR C IN SUCH A WAY THAT A SPIKE IS INTRODUCED INTO W. C NM1 = N - 1 IF (NM1 .LT. 1) GO TO 70 DO 60 NMJ = 1, NM1 J = N - NMJ JJ = JJ - (M - J + 1) W(J) = ZERO IF (V(J) .EQ. ZERO) GO TO 50 C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C J-TH ELEMENT OF V. C IF (DABS(V(N)) .GE. DABS(V(J))) GO TO 20 COTAN = V(N)/V(J) SIN = P5/DSQRT(P25+P25*COTAN**2) COS = SIN*COTAN TAU = ONE IF (DABS(COS)*GIANT .GT. ONE) TAU = ONE/COS GO TO 30 20 CONTINUE TAN = V(J)/V(N) COS = P5/DSQRT(P25+P25*TAN**2) SIN = COS*TAN TAU = SIN 30 CONTINUE C C APPLY THE TRANSFORMATION TO V AND STORE THE INFORMATION C NECESSARY TO RECOVER THE GIVENS ROTATION. C V(N) = SIN*V(J) + COS*V(N) V(J) = TAU C C APPLY THE TRANSFORMATION TO S AND EXTEND THE SPIKE IN W. C L = JJ DO 40 I = J, M TEMP = COS*S(L) - SIN*W(I) W(I) = SIN*S(L) + COS*W(I) S(L) = TEMP L = L + 1 40 CONTINUE 50 CONTINUE 60 CONTINUE 70 CONTINUE C C ADD THE SPIKE FROM THE RANK 1 UPDATE TO W. C DO 80 I = 1, M W(I) = W(I) + V(N)*U(I) 80 CONTINUE C C ELIMINATE THE SPIKE. C SING = .FALSE. IF (NM1 .LT. 1) GO TO 140 DO 130 J = 1, NM1 IF (W(J) .EQ. ZERO) GO TO 120 C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C J-TH ELEMENT OF THE SPIKE. C IF (DABS(S(JJ)) .GE. DABS(W(J))) GO TO 90 COTAN = S(JJ)/W(J) SIN = P5/DSQRT(P25+P25*COTAN**2) COS = SIN*COTAN TAU = ONE IF (DABS(COS)*GIANT .GT. ONE) TAU = ONE/COS GO TO 100 90 CONTINUE TAN = W(J)/S(JJ) COS = P5/DSQRT(P25+P25*TAN**2) SIN = COS*TAN TAU = SIN 100 CONTINUE C C APPLY THE TRANSFORMATION TO S AND REDUCE THE SPIKE IN W. C L = JJ DO 110 I = J, M TEMP = COS*S(L) + SIN*W(I) W(I) = -SIN*S(L) + COS*W(I) S(L) = TEMP L = L + 1 110 CONTINUE C C STORE THE INFORMATION NECESSARY TO RECOVER THE C GIVENS ROTATION. C W(J) = TAU 120 CONTINUE C C TEST FOR ZERO DIAGONAL ELEMENTS IN THE OUTPUT S. C IF (S(JJ) .EQ. ZERO) SING = .TRUE. JJ = JJ + (M - J + 1) 130 CONTINUE 140 CONTINUE C C MOVE W BACK INTO THE LAST COLUMN OF THE OUTPUT S. C L = JJ DO 150 I = N, M S(L) = W(I) L = L + 1 150 CONTINUE IF (S(JJ) .EQ. ZERO) SING = .TRUE. RETURN C C LAST CARD OF SUBROUTINE R1UPDT. C END minpack-19961126/ex/file110000644000175000017500000006667404210375024015742 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,INITPT,LMSTR1,SSQFCN C C FORTRAN-SUPPLIED ... SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES, * NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) REAL FACTOR,FNORM1,FNORM2,ONE,TEN,TOL REAL FJAC(40,40),FNM(60),FVEC(65),WA(265),X(40) REAL SPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0E0,1.0E1/ TOL = SQRT(SPMPAR(1)) LDFJAC = 40 LWA = 265 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IWA,WA, * LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, E15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , E15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5E15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMSTR1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 2X, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG REAL X(N),FVEC(M),FJROW(N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST SQUARES SOLVER. IF IFLAG = 1, FCN SHOULD ONLY CALL THE C TESTING FUNCTION SUBROUTINE SSQFCN. IF IFLAG = I, I .GE. 2, C FCN SHOULD ONLY CALL SUBROUTINE SSQJAC TO CALCULATE THE C (I-1)-ST ROW OF THE JACOBIAN. (THE SSQJAC SUBROUTINE PROVIDED C HERE FOR TESTING PURPOSES CALCULATES THE ENTIRE JACOBIAN C MATRIX AND IS THEREFORE CALLED ONLY WHEN IFLAG = 2.) EACH C CALL TO SSQFCN OR SSQJAC SHOULD SPECIFY THE APPROPRIATE C VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN,SSQJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV,J REAL TEMP(65,40) COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL SSQJAC(M,N,X,TEMP,65,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 IF (IFLAG .EQ. 1) GO TO 120 DO 110 J = 1, N FJROW(J) = TEMP(IFLAG-1,J) 110 CONTINUE 120 CONTINUE RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) INTEGER M,N,LDFJAC,NPROB REAL X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE SSQJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF EIGHTEEN C NONLINEAR LEAST SQUARES PROBLEMS. THE PROBLEM DIMENSIONS ARE C AS DESCRIBED IN THE PROLOGUE COMMENTS OF SSQFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FJAC IS AN M BY N OUTPUT ARRAY WHICH CONTAINS THE JACOBIAN C MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIN,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,MM1,NM1 REAL C14,C20,C29,C45,C100,DIV,DX,EIGHT,FIVE,FOUR,ONE,PROD,S2, * TEMP,TEN,THREE,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO,ZERO REAL V(11) REAL FLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,EIGHT,TEN,C14,C20,C29,C45,C100 * /0.0E0,1.0E0,2.0E0,3.0E0,4.0E0,5.0E0,8.0E0,1.0E1,1.4E1, * 2.0E1,2.9E1,4.5E1,1.0E2/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0E0,2.0E0,1.0E0,5.0E-1,2.5E-1,1.67E-1,1.25E-1,1.0E-1, * 8.33E-2,7.14E-2,6.25E-2/ FLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,40,70,130,140,150,180,190,210,230,250,310,330,350,370, * 400,460,480), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE TEMP = TWO/FLOAT(M) DO 30 J = 1, N DO 20 I = 1, M FJAC(I,J) = -TEMP 20 CONTINUE FJAC(J,J) = FJAC(J,J) + ONE 30 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE DO 60 J = 1, N DO 50 I = 1, M FJAC(I,J) = FLOAT(I)*FLOAT(J) 50 CONTINUE 60 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE DO 90 J = 1, N DO 80 I = 1, M FJAC(I,J) = ZERO 80 CONTINUE 90 CONTINUE NM1 = N - 1 MM1 = M - 1 IF (NM1 .LT. 2) GO TO 120 DO 110 J = 2, NM1 DO 100 I = 2, MM1 FJAC(I,J) = FLOAT(I-1)*FLOAT(J) 100 CONTINUE 110 CONTINUE 120 CONTINUE GO TO 500 C C ROSENBROCK FUNCTION. C 130 CONTINUE FJAC(1,1) = -C20*X(1) FJAC(1,2) = TEN FJAC(2,1) = -ONE FJAC(2,2) = ZERO GO TO 500 C C HELICAL VALLEY FUNCTION. C 140 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP = X(1)**2 + X(2)**2 TMP1 = TPI*TEMP TMP2 = SQRT(TEMP) FJAC(1,1) = C100*X(2)/TMP1 FJAC(1,2) = -C100*X(1)/TMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TMP2 FJAC(2,2) = TEN*X(2)/TMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 500 C C POWELL SINGULAR FUNCTION. C 150 CONTINUE DO 170 J = 1, 4 DO 160 I = 1, 4 FJAC(I,J) = ZERO 160 CONTINUE 170 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = SQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*SQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 500 C C FREUDENSTEIN AND ROTH FUNCTION. C 180 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = X(2)*(TEN - THREE*X(2)) - TWO FJAC(2,1) = ONE FJAC(2,2) = X(2)*(TWO + THREE*X(2)) - C14 GO TO 500 C C BARD FUNCTION. C 190 CONTINUE DO 200 I = 1, 15 TMP1 = FLOAT(I) TMP2 = FLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -ONE FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 200 CONTINUE GO TO 500 C C KOWALIK AND OSBORNE FUNCTION. C 210 CONTINUE DO 220 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FJAC(I,1) = -TMP1/TMP2 FJAC(I,2) = -V(I)*X(1)/TMP2 FJAC(I,3) = FJAC(I,1)*FJAC(I,2) FJAC(I,4) = FJAC(I,3)/V(I) 220 CONTINUE GO TO 500 C C MEYER FUNCTION. C 230 CONTINUE DO 240 I = 1, 16 TEMP = FIVE*FLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = EXP(TMP1) FJAC(I,1) = TMP2 FJAC(I,2) = X(1)*TMP2/TEMP FJAC(I,3) = -TMP1*FJAC(I,2) 240 CONTINUE GO TO 500 C C WATSON FUNCTION. C 250 CONTINUE DO 280 I = 1, 29 DIV = FLOAT(I)/C29 S2 = ZERO DX = ONE DO 260 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 260 CONTINUE TEMP = TWO*DIV*S2 DX = ONE/DIV DO 270 J = 1, N FJAC(I,J) = DX*(FLOAT(J-1) - TEMP) DX = DIV*DX 270 CONTINUE 280 CONTINUE DO 300 J = 1, N DO 290 I = 30, 31 FJAC(I,J) = ZERO 290 CONTINUE 300 CONTINUE FJAC(30,1) = ONE FJAC(31,1) = -TWO*X(1) FJAC(31,2) = ONE GO TO 500 C C BOX 3-DIMENSIONAL FUNCTION. C 310 CONTINUE DO 320 I = 1, M TEMP = FLOAT(I) TMP1 = TEMP/TEN FJAC(I,1) = -TMP1*EXP(-TMP1*X(1)) FJAC(I,2) = TMP1*EXP(-TMP1*X(2)) FJAC(I,3) = EXP(-TEMP) - EXP(-TMP1) 320 CONTINUE GO TO 500 C C JENNRICH AND SAMPSON FUNCTION. C 330 CONTINUE DO 340 I = 1, M TEMP = FLOAT(I) FJAC(I,1) = -TEMP*EXP(TEMP*X(1)) FJAC(I,2) = -TEMP*EXP(TEMP*X(2)) 340 CONTINUE GO TO 500 C C BROWN AND DENNIS FUNCTION. C 350 CONTINUE DO 360 I = 1, M TEMP = FLOAT(I)/FIVE TI = SIN(TEMP) TMP1 = X(1) + TEMP*X(2) - EXP(TEMP) TMP2 = X(3) + TI*X(4) - COS(TEMP) FJAC(I,1) = TWO*TMP1 FJAC(I,2) = TEMP*FJAC(I,1) FJAC(I,3) = TWO*TMP2 FJAC(I,4) = TI*FJAC(I,3) 360 CONTINUE GO TO 500 C C CHEBYQUAD FUNCTION. C 370 CONTINUE DX = ONE/FLOAT(N) DO 390 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 TMP3 = ZERO TMP4 = TWO DO 380 I = 1, M FJAC(I,J) = DX*TMP4 TI = FOUR*TMP2 + TEMP*TMP4 - TMP3 TMP3 = TMP4 TMP4 = TI TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 380 CONTINUE 390 CONTINUE GO TO 500 C C BROWN ALMOST-LINEAR FUNCTION. C 400 CONTINUE PROD = ONE DO 420 J = 1, N PROD = X(J)*PROD DO 410 I = 1, N FJAC(I,J) = ONE 410 CONTINUE FJAC(J,J) = TWO 420 CONTINUE DO 450 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 440 TEMP = ONE PROD = ONE DO 430 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 430 CONTINUE 440 CONTINUE FJAC(N,J) = PROD/TEMP 450 CONTINUE GO TO 500 C C OSBORNE 1 FUNCTION. C 460 CONTINUE DO 470 I = 1, 33 TEMP = TEN*FLOAT(I-1) TMP1 = EXP(-X(4)*TEMP) TMP2 = EXP(-X(5)*TEMP) FJAC(I,1) = -ONE FJAC(I,2) = -TMP1 FJAC(I,3) = -TMP2 FJAC(I,4) = TEMP*X(2)*TMP1 FJAC(I,5) = TEMP*X(3)*TMP2 470 CONTINUE GO TO 500 C C OSBORNE 2 FUNCTION. C 480 CONTINUE DO 490 I = 1, 65 TEMP = FLOAT(I-1)/TEN TMP1 = EXP(-X(5)*TEMP) TMP2 = EXP(-X(6)*(TEMP-X(9))**2) TMP3 = EXP(-X(7)*(TEMP-X(10))**2) TMP4 = EXP(-X(8)*(TEMP-X(11))**2) FJAC(I,1) = -TMP1 FJAC(I,2) = -TMP2 FJAC(I,3) = -TMP3 FJAC(I,4) = -TMP4 FJAC(I,5) = TEMP*X(1)*TMP1 FJAC(I,6) = X(2)*(TEMP - X(9))**2*TMP2 FJAC(I,7) = X(3)*(TEMP - X(10))**2*TMP3 FJAC(I,8) = X(4)*(TEMP - X(11))**2*TMP4 FJAC(I,9) = -TWO*X(2)*X(6)*(TEMP - X(9))*TMP2 FJAC(I,10) = -TWO*X(3)*X(7)*(TEMP - X(10))*TMP3 FJAC(I,11) = -TWO*X(4)*X(8)*(TEMP - X(11))*TMP4 490 CONTINUE 500 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17, * FIVE,H,HALF,ONE,SEVEN,TEN,THREE,TWENTY,TWNTF,TWO,ZERO REAL FLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0E0,5.0E-1,1.0E0,2.0E0,3.0E0,5.0E0,7.0E0,1.0E1,2.0E1, * 2.5E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2E0,2.5E-1,3.9E-1,4.15E-1,2.0E-2,4.0E3,2.5E2,3.0E-1, * 4.0E-1,1.5E0,1.0E-2,1.3E0,6.5E-1,7.0E-1,6.0E-1,4.5E0, * 5.5E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/FLOAT(N+1) DO 160 J = 1, N X(J) = FLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB REAL X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIN,SQRT,SIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 REAL C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM,S1,S2,TEMP, * TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO,ZERO,ZP25,ZP5 REAL V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) REAL FLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0E0,2.5E-1,5.0E-1,1.0E0,2.0E0,5.0E0,8.0E0,1.0E1,1.3E1, * 1.4E1,2.9E1,4.5E1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0E0,2.0E0,1.0E0,5.0E-1,2.5E-1,1.67E-1,1.25E-1,1.0E-1, * 8.33E-2,7.14E-2,6.25E-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957E-1,1.947E-1,1.735E-1,1.6E-1,8.44E-2,6.27E-2,4.56E-2, * 3.42E-2,3.23E-2,2.35E-2,2.46E-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478E4,2.861E4,2.365E4,1.963E4,1.637E4,1.372E4,1.154E4, * 9.744E3,8.261E3,7.03E3,6.005E3,5.147E3,4.427E3,3.82E3, * 3.307E3,2.872E3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44E-1,9.08E-1,9.32E-1,9.36E-1,9.25E-1,9.08E-1,8.81E-1, * 8.5E-1,8.18E-1,7.84E-1,7.51E-1,7.18E-1,6.85E-1,6.58E-1, * 6.28E-1,6.03E-1,5.8E-1,5.58E-1,5.38E-1,5.22E-1,5.06E-1, * 4.9E-1,4.78E-1,4.67E-1,4.57E-1,4.48E-1,4.38E-1,4.31E-1, * 4.24E-1,4.2E-1,4.14E-1,4.11E-1,4.06E-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366E0,1.191E0,1.112E0,1.013E0,9.91E-1,8.85E-1,8.31E-1, * 8.47E-1,7.86E-1,7.25E-1,7.46E-1,6.79E-1,6.08E-1,6.55E-1, * 6.16E-1,6.06E-1,6.02E-1,6.26E-1,6.51E-1,7.24E-1,6.49E-1, * 6.49E-1,6.94E-1,6.44E-1,6.24E-1,6.61E-1,6.12E-1,5.58E-1, * 5.33E-1,4.95E-1,5.0E-1,4.23E-1,3.95E-1,3.75E-1,3.72E-1, * 3.91E-1,3.96E-1,4.05E-1,4.28E-1,4.29E-1,5.23E-1,5.62E-1, * 6.07E-1,6.53E-1,6.72E-1,7.08E-1,6.33E-1,6.68E-1,6.45E-1, * 6.32E-1,5.91E-1,5.59E-1,5.97E-1,6.25E-1,7.39E-1,7.1E-1, * 7.29E-1,7.2E-1,6.36E-1,5.81E-1,4.28E-1,2.92E-1,1.62E-1, * 9.8E-2,5.4E-2/ FLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/FLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + FLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = FLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + FLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = FLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*ATAN(ONE) TMP1 = SIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI + ZP5 TMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = FLOAT(I) TMP2 = FLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*FLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = EXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = FLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + FLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = FLOAT(I) TMP1 = TEMP/TEN FVEC(I) = EXP(-TMP1*X(1)) - EXP(-TMP1*X(2)) * + (EXP(-TEMP) - EXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = FLOAT(I) FVEC(I) = TWO + TWO*TEMP - EXP(TEMP*X(1)) - EXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = FLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - EXP(TEMP) TMP2 = X(3) + SIN(TEMP)*X(4) - COS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/FLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(FLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*FLOAT(I-1) TMP1 = EXP(-X(4)*TEMP) TMP2 = EXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = FLOAT(I-1)/TEN TMP1 = EXP(-X(5)*TEMP) TMP2 = EXP(-X(6)*(TEMP-X(9))**2) TMP3 = EXP(-X(7)*(TEMP-X(10))**2) TMP4 = EXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END minpack-19961126/ex/tlmstr.f0000644000175000017500000000536511616327304016426 0ustar sylvestresylvestreC DRIVER FOR LMSTR EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),FJAC(3,3),DIAG(3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 3 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 400 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,NJEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,31H NUMBER OF JACOBIAN EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMSTR EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C C SUBROUTINE FCN FOR LMSTR EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE IF (IFLAG .GE. 2) GO TO 20 DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE GO TO 40 20 CONTINUE I = IFLAG - 1 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJROW(1) = -1.D0 FJROW(2) = TMP1*TMP2/TMP4 FJROW(3) = TMP1*TMP3/TMP4 30 CONTINUE 40 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file140000644000175000017500000002573004210375123015731 0ustar sylvestresylvestreC ********** C C THIS PROGRAM CHECKS THE CONSTANTS OF MACHINE PRECISION AND C SMALLEST AND LARGEST MACHINE REPRESENTABLE NUMBERS SPECIFIED IN C FUNCTION DPMPAR, AGAINST THE CORRESPONDING HARDWARE-DETERMINED C MACHINE CONSTANTS OBTAINED BY DMCHAR, A SUBROUTINE DUE TO C W. J. CODY. C C DATA STATEMENTS IN DPMPAR CORRESPONDING TO THE MACHINE USED MUST C BE ACTIVATED BY REMOVING C IN COLUMN 1. C C THE PRINTED OUTPUT CONSISTS OF THE MACHINE CONSTANTS OBTAINED BY C DMCHAR AND COMPARISONS OF THE DPMPAR CONSTANTS WITH THEIR C DMCHAR COUNTERPARTS. DESCRIPTIONS OF THE MACHINE CONSTANTS ARE C GIVEN IN THE PROLOGUE COMMENTS OF DMCHAR. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... DMCHAR,DPMPAR C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IBETA,IEXP,IRND,IT,MACHEP,MAXEXP,MINEXP,NEGEP,NGRD, * NWRITE DOUBLE PRECISION DWARF,EPS,EPSMCH,EPSNEG,GIANT,XMAX,XMIN DOUBLE PRECISION RERR(3) DOUBLE PRECISION DPMPAR C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C C DETERMINE THE MACHINE CONSTANTS DYNAMICALLY FROM DMCHAR. C CALL DMCHAR(IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP,MAXEXP, * EPS,EPSNEG,XMIN,XMAX) C C COMPARE THE DPMPAR CONSTANTS WITH THEIR DMCHAR COUNTERPARTS AND C STORE THE RELATIVE DIFFERENCES IN RERR. C EPSMCH = DPMPAR(1) DWARF = DPMPAR(2) GIANT = DPMPAR(3) RERR(1) = (EPSMCH - EPS)/EPSMCH RERR(2) = (DWARF - XMIN)/DWARF RERR(3) = (XMAX - GIANT)/GIANT C C WRITE THE DMCHAR CONSTANTS. C WRITE (NWRITE,10) * IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP,MAXEXP,EPS, * EPSNEG,XMIN,XMAX C C WRITE THE DPMPAR CONSTANTS AND THE RELATIVE DIFFERENCES. C WRITE (NWRITE,20) EPSMCH,RERR(1),DWARF,RERR(2),GIANT,RERR(3) STOP 10 FORMAT (17H1DMCHAR CONSTANTS /// 8H IBETA =, I6 // 8H IT =, * I6 // 8H IRND =, I6 // 8H NGRD =, I6 // 9H MACHEP =, * I6 // 8H NEGEP =, I6 // 7H IEXP =, I6 // 9H MINEXP =, * I6 // 9H MAXEXP =, I6 // 6H EPS =, D15.7 // 9H EPSNEG =, * D15.7 // 7H XMIN =, D15.7 // 7H XMAX =, D15.7) 20 FORMAT ( /// 42H DPMPAR CONSTANTS AND RELATIVE DIFFERENCES /// * 9H EPSMCH =, D15.7 / 10H RERR(1) =, D15.7 // * 8H DWARF =, D15.7 / 10H RERR(2) =, D15.7 // 8H GIANT =, * D15.7 / 10H RERR(3) =, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE DMCHAR(IBETA,IT,IRND,NGRD,MACHEP,NEGEP,IEXP,MINEXP, 1 MAXEXP,EPS,EPSNEG,XMIN,XMAX) C INTEGER I,IBETA,IEXP,IRND,IT,IZ,J,K,MACHEP,MAXEXP,MINEXP, 1 MX,NEGEP,NGRD DOUBLE PRECISION A,B,BETA,BETAIN,BETAM1,EPS,EPSNEG,ONE,XMAX, 1 XMIN,Y,Z,ZERO C C THIS SUBROUTINE IS INTENDED TO DETERMINE THE CHARACTERISTICS C OF THE FLOATING-POINT ARITHMETIC SYSTEM THAT ARE SPECIFIED C BELOW. THE FIRST THREE ARE DETERMINED ACCORDING TO AN C ALGORITHM DUE TO M. MALCOLM, CACM 15 (1972), PP. 949-951, C INCORPORATING SOME, BUT NOT ALL, OF THE IMPROVEMENTS C SUGGESTED BY M. GENTLEMAN AND S. MAROVICH, CACM 17 (1974), C PP. 276-277. C C C IBETA - THE RADIX OF THE FLOATING-POINT REPRESENTATION C IT - THE NUMBER OF BASE IBETA DIGITS IN THE FLOATING-POINT C SIGNIFICAND C IRND - 0 IF FLOATING-POINT ADDITION CHOPS, C 1 IF FLOATING-POINT ADDITION ROUNDS C NGRD - THE NUMBER OF GUARD DIGITS FOR MULTIPLICATION. IT IS C 0 IF IRND=1, OR IF IRND=0 AND ONLY IT BASE IBET C DIGITS PARTICIPATE IN THE POST NORMALIZATION SHIFT C OF THE FLOATING-POINT SIGNIFICAND IN MULTIPLICATION C 1 IF IRND=0 AND MORE THAN IT BASE IBETA DIGITS C PARTICIPATE IN THE POST NORMALIZATION SHIFT OF THE C FLOATING-POINT SIGNIFICAND IN MULTIPLICATION C MACHEP - THE LARGEST NEGATIVE INTEGER SUCH THAT C 1.0+FLOAT(IBETA)**MACHEP .NE. 1.0, EXCEPT THAT C MACHEP IS BOUNDED BELOW BY -(IT+3) C NEGEPS - THE LARGEST NEGATIVE INTEGER SUCH THAT C 1.0-FLOAT(IBETA)**NEGEPS .NE. 1.0, EXCEPT THAT C NEGEPS IS BOUNDED BELOW BY -(IT+3) C IEXP - THE NUMBER OF BITS (DECIMAL PLACES IF IBETA = 10) C RESERVED FOR THE REPRESENTATION OF THE EXPONENT C (INCLUDING THE BIAS OR SIGN) OF A FLOATING-POINT C NUMBER C MINEXP - THE LARGEST IN MAGNITUDE NEGATIVE INTEGER SUCH THAT C FLOAT(IBETA)**MINEXP IS A POSITIVE FLOATING-POINT C NUMBER C MAXEXP - THE LARGEST POSITIVE INTEGER EXPONENT FOR A FINITE C FLOATING-POINT NUMBER C EPS - THE SMALLEST POSITIVE FLOATING-POINT NUMBER SUCH C THAT 1.0+EPS .NE. 1.0. IN PARTICULAR, IF EITHER C IBETA = 2 OR IRND = 0, EPS = FLOAT(IBETA)**MACHEP. C OTHERWISE, EPS = (FLOAT(IBETA)**MACHEP)/2 C EPSNEG - A SMALL POSITIVE FLOATING-POINT NUMBER SUCH THAT C 1.0-EPSNEG .NE. 1.0. IN PARTICULAR, IF IBETA = 2 C OR IRND = 0, EPSNEG = FLOAT(IBETA)**NEGEPS. C OTHERWISE, EPSNEG = (IBETA**NEGEPS)/2. BECAUSE C NEGEPS IS BOUNDED BELOW BY -(IT+3), EPSNEG MAY NOT C BE THE SMALLEST NUMBER WHICH CAN ALTER 1.0 BY C SUBTRACTION. C XMIN - THE SMALLEST NON-VANISHING FLOATING-POINT POWER OF TH C RADIX. IN PARTICULAR, XMIN = FLOAT(IBETA)**MINEXP C XMAX - THE LARGEST FINITE FLOATING-POINT NUMBER. IN C PARTICULAR XMAX = (1.0-EPSNEG)*FLOAT(IBETA)**MAXEXP C NOTE - ON SOME MACHINES XMAX WILL BE ONLY THE C SECOND, OR PERHAPS THIRD, LARGEST NUMBER, BEING C TOO SMALL BY 1 OR 2 UNITS IN THE LAST DIGIT OF C THE SIGNIFICAND. C C LATEST REVISION - OCTOBER 22, 1979 C C AUTHOR - W. J. CODY C ARGONNE NATIONAL LABORATORY C C----------------------------------------------------------------- ONE = DBLE(FLOAT(1)) ZERO = 0.0D0 C----------------------------------------------------------------- C DETERMINE IBETA,BETA ALA MALCOLM C----------------------------------------------------------------- A = ONE 10 A = A + A IF (((A+ONE)-A)-ONE .EQ. ZERO) GO TO 10 B = ONE 20 B = B + B IF ((A+B)-A .EQ. ZERO) GO TO 20 IBETA = INT(SNGL((A + B) - A)) BETA = DBLE(FLOAT(IBETA)) C----------------------------------------------------------------- C DETERMINE IT, IRND C----------------------------------------------------------------- IT = 0 B = ONE 100 IT = IT + 1 B = B * BETA IF (((B+ONE)-B)-ONE .EQ. ZERO) GO TO 100 IRND = 0 BETAM1 = BETA - ONE IF ((A+BETAM1)-A .NE. ZERO) IRND = 1 C----------------------------------------------------------------- C DETERMINE NEGEP, EPSNEG C----------------------------------------------------------------- NEGEP = IT + 3 BETAIN = ONE / BETA A = ONE C DO 200 I = 1, NEGEP A = A * BETAIN 200 CONTINUE C B = A 210 IF ((ONE-A)-ONE .NE. ZERO) GO TO 220 A = A * BETA NEGEP = NEGEP - 1 GO TO 210 220 NEGEP = -NEGEP EPSNEG = A IF ((IBETA .EQ. 2) .OR. (IRND .EQ. 0)) GO TO 300 A = (A*(ONE+A)) / (ONE+ONE) IF ((ONE-A)-ONE .NE. ZERO) EPSNEG = A C----------------------------------------------------------------- C DETERMINE MACHEP, EPS C----------------------------------------------------------------- 300 MACHEP = -IT - 3 A = B 310 IF((ONE+A)-ONE .NE. ZERO) GO TO 320 A = A * BETA MACHEP = MACHEP + 1 GO TO 310 320 EPS = A IF ((IBETA .EQ. 2) .OR. (IRND .EQ. 0)) GO TO 350 A = (A*(ONE+A)) / (ONE+ONE) IF ((ONE+A)-ONE .NE. ZERO) EPS = A C----------------------------------------------------------------- C DETERMINE NGRD C----------------------------------------------------------------- 350 NGRD = 0 IF ((IRND .EQ. 0) .AND. ((ONE+EPS)*ONE-ONE) .NE. ZERO) NGRD = 1 C----------------------------------------------------------------- C DETERMINE IEXP, MINEXP, XMIN C C LOOP TO DETERMINE LARGEST I AND K = 2**I SUCH THAT C (1/BETA) ** (2**(I)) C DOES NOT UNDERFLOW C EXIT FROM LOOP IS SIGNALED BY AN UNDERFLOW. C----------------------------------------------------------------- I = 0 K = 1 Z = BETAIN 400 Y = Z Z = Y * Y C----------------------------------------------------------------- C CHECK FOR UNDERFLOW HERE C----------------------------------------------------------------- A = Z * ONE IF ((A+A .EQ. ZERO) .OR. (DABS(Z) .GE. Y)) GO TO 410 I = I + 1 K = K + K GO TO 400 410 IF (IBETA .EQ. 10) GO TO 420 IEXP = I + 1 MX = K + K GO TO 450 C----------------------------------------------------------------- C FOR DECIMAL MACHINES ONLY C----------------------------------------------------------------- 420 IEXP = 2 IZ = IBETA 430 IF (K .LT. IZ) GO TO 440 IZ = IZ * IBETA IEXP = IEXP + 1 GO TO 430 440 MX = IZ + IZ - 1 C----------------------------------------------------------------- C LOOP TO DETERMINE MINEXP, XMIN C EXIT FROM LOOP IS SIGNALED BY AN UNDERFLOW. C----------------------------------------------------------------- 450 XMIN = Y Y = Y * BETAIN C----------------------------------------------------------------- C CHECK FOR UNDERFLOW HERE C----------------------------------------------------------------- A = Y * ONE IF (((A+A) .EQ. ZERO) .OR. (DABS(Y) .GE. XMIN)) GO TO 460 K = K + 1 GO TO 450 460 MINEXP = -K C----------------------------------------------------------------- C DETERMINE MAXEXP, XMAX C----------------------------------------------------------------- IF ((MX .GT. K+K-3) .OR. (IBETA .EQ. 10)) GO TO 500 MX = MX + MX IEXP = IEXP + 1 500 MAXEXP = MX + MINEXP C----------------------------------------------------------------- C ADJUST FOR MACHINES WITH IMPLICIT LEADING C BIT IN BINARY SIGNIFICAND AND MACHINES WITH C RADIX POINT AT EXTREME RIGHT OF SIGNIFICAND C----------------------------------------------------------------- I = MAXEXP + MINEXP IF ((IBETA .EQ. 2) .AND. (I .EQ. 0)) MAXEXP = MAXEXP - 1 IF (I .GT. 20) MAXEXP = MAXEXP - 1 IF (A .NE. Y) MAXEXP = MAXEXP - 2 XMAX = ONE - EPSNEG IF (XMAX*ONE .NE. XMAX) XMAX = ONE - BETA * EPSNEG XMAX = XMAX / (BETA * BETA * BETA * XMIN) I = MAXEXP + MINEXP + 3 IF (I .LE. 0) GO TO 520 C DO 510 J = 1, I IF (IBETA .EQ. 2) XMAX = XMAX + XMAX IF (IBETA .NE. 2) XMAX = XMAX * BETA 510 CONTINUE C 520 RETURN C ---------- LAST CARD OF DMCHAR ---------- END minpack-19961126/ex/file080000644000175000017500000003362104210374651015737 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE SOLUTION OF N NONLINEAR C EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER AND AN C INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, CALLS THE C NONLINEAR EQUATION SOLVER, AND FINALLY PRINTS OUT INFORMATION C ON THE PERFORMANCE OF THE SOLVER. THIS IS ONLY A SAMPLE DRIVER, C MANY OTHER DRIVERS ARE POSSIBLE. THE INTERFACE SUBROUTINE FCN C IS NECESSARY TO TAKE INTO ACCOUNT THE FORMS OF CALLING C SEQUENCES USED BY THE FUNCTION SUBROUTINES IN THE VARIOUS C NONLINEAR EQUATION SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,HYBRD1,INITPT,VECFCN C C FORTRAN-SUPPLIED ... SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LWA,N,NFEV,NPROB,NREAD,NTRIES,NWRITE INTEGER NA(60),NF(60),NP(60),NX(60) REAL FACTOR,FNORM1,FNORM2,ONE,TEN,TOL REAL FNM(60),FVEC(40),WA(2660),X(40) REAL SPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0E0,1.0E1/ TOL = SQRT(SPMPAR(1)) LWA = 2660 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL VECFCN(N,X,FVEC,NPROB) FNORM1 = ENORM(N,FVEC) WRITE (NWRITE,60) NPROB,N NFEV = 0 CALL HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) FNORM2 = ENORM(N,FVEC) NP(IC) = NPROB NA(IC) = N NF(IC) = NFEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) FNORM1,FNORM2,NFEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),NF(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (3I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 10H DIMENSION, I5, 5X //) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, E15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , E15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5E15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO HYBRD1 /) 90 FORMAT (39H NPROB N NFEV INFO FINAL L2 NORM /) 100 FORMAT (I4, I6, I7, I6, 1X, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG REAL X(N),FVEC(N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C EQUATION SOLVER. FCN SHOULD ONLY CALL THE TESTING FUNCTION C SUBROUTINE VECFCN WITH THE APPROPRIATE VALUE OF PROBLEM C NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... VECFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV COMMON /REFNUM/ NPROB,NFEV CALL VECFCN(N,X,FVEC,NPROB) NFEV = NFEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB REAL X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIGN,SIN,SQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE,PROD,SUM,SUM1, * SUM2,TEMP,TEMP1,TEMP2,TEN,THREE,TI,TJ,TK,TPI,TWO,ZERO REAL FLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0E0,1.0E0,2.0E0,3.0E0,5.0E0,8.0E0,1.0E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0E4,1.0001E0,2.0E2,2.02E1,1.98E1,1.8E2,2.5E-1,5.0E-1, * 2.9E1/ FLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = EXP(-X(1)) + EXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP1 = SIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI + C8 TEMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = FLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + FLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(FLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/FLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(FLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/FLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + FLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/FLOAT(N+1) DO 260 K = 1, N TK = FLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = COS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = FLOAT(N+K) - SIN(X(K)) - SUM - FLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + FLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + FLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,H,HALF,ONE,THREE,TJ,ZERO REAL FLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0E0,5.0E-1,1.0E0,3.0E0,1.2E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/FLOAT(N+1) DO 90 J = 1, N X(J) = FLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/FLOAT(N+1) DO 130 J = 1, N TJ = FLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/FLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/FLOAT(N) DO 170 J = 1, N X(J) = ONE - FLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END minpack-19961126/ex/tlmdif1.f0000644000175000017500000000340411616327304016431 0ustar sylvestresylvestreC DRIVER FOR LMDIF1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,INFO,LWA,NWRITE INTEGER IWA(3) DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(3),FVEC(15),WA(75) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LWA = 75 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDIF1 EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF1 EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file130000644000175000017500000005421504210375101015724 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS THE ABILITY OF CHKDER TO DETECT C INCONSISTENCIES BETWEEN FUNCTIONS AND THEIR FIRST DERIVATIVES. C FOURTEEN TEST FUNCTION VECTORS AND JACOBIANS ARE USED. ELEVEN OF C THE TESTS ARE FALSE(F), I.E. THERE ARE INCONSISTENCIES BETWEEN C THE FUNCTION VECTORS AND THE CORRESPONDING JACOBIANS. THREE OF C THE TESTS ARE TRUE(T), I.E. THERE ARE NO INCONSISTENCIES. THE C DRIVER READS IN DATA, CALLS CHKDER AND PRINTS OUT INFORMATION C REQUIRED BY AND RECEIVED FROM CHKDER. C C SUBPROGRAMS CALLED C C MINPACK SUPPLIED ... CHKDER,ERRJAC,INITPT,VECFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,LDFJAC,LNP,MODE,N,NPROB,NREAD,NWRITE INTEGER NA(14),NP(14) LOGICAL A(14) REAL CP,ONE REAL DIFF(10),ERR(10),ERRMAX(14),ERRMIN(14),FJAC(10,10), * FVEC1(10),FVEC2(10),X1(10),X2(10) C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA A(1),A(2),A(3),A(4),A(5),A(6),A(7),A(8),A(9),A(10),A(11), * A(12),A(13),A(14) * /.FALSE.,.FALSE.,.FALSE.,.TRUE.,.FALSE.,.FALSE.,.FALSE., * .TRUE.,.FALSE.,.FALSE.,.FALSE.,.FALSE.,.TRUE.,.FALSE./ DATA CP,ONE /1.23E-1,1.0E0/ LDFJAC = 10 10 CONTINUE READ (NREAD,60) NPROB,N IF (NPROB .LE. 0) GO TO 40 CALL INITPT(N,X1,NPROB,ONE) DO 20 I = 1, N X1(I) = X1(I) + CP CP = -CP 20 CONTINUE WRITE (NWRITE,70) NPROB,N,A(NPROB) MODE = 1 CALL CHKDER(N,N,X1,FVEC1,FJAC,LDFJAC,X2,FVEC2,MODE,ERR) MODE = 2 CALL VECFCN(N,X1,FVEC1,NPROB) CALL ERRJAC(N,X1,FJAC,LDFJAC,NPROB) CALL VECFCN(N,X2,FVEC2,NPROB) CALL CHKDER(N,N,X1,FVEC1,FJAC,LDFJAC,X2,FVEC2,MODE,ERR) ERRMIN(NPROB) = ERR(1) ERRMAX(NPROB) = ERR(1) DO 30 I = 1, N DIFF(I) = FVEC2(I) - FVEC1(I) IF (ERRMIN(NPROB) .GT. ERR(I)) ERRMIN(NPROB) = ERR(I) IF (ERRMAX(NPROB) .LT. ERR(I)) ERRMAX(NPROB) = ERR(I) 30 CONTINUE NP(NPROB) = NPROB LNP = NPROB NA(NPROB) = N WRITE (NWRITE,80) (FVEC1(I), I = 1, N) WRITE (NWRITE,90) (DIFF(I), I = 1, N) WRITE (NWRITE,100) (ERR(I), I = 1, N) GO TO 10 40 CONTINUE WRITE (NWRITE,110) LNP WRITE (NWRITE,120) DO 50 I = 1, LNP WRITE (NWRITE,130) NP(I),NA(I),A(I),ERRMIN(I),ERRMAX(I) 50 CONTINUE STOP 60 FORMAT (2I5) 70 FORMAT ( /// 5X, 8H PROBLEM, I5, 5X, 15H WITH DIMENSION, I5, 2X, * 5H IS , L1) 80 FORMAT ( // 5X, 25H FIRST FUNCTION VECTOR // (5X, 5E15.7)) 90 FORMAT ( // 5X, 27H FUNCTION DIFFERENCE VECTOR // (5X, 5E15.7)) 100 FORMAT ( // 5X, 13H ERROR VECTOR // (5X, 5E15.7)) 110 FORMAT (12H1SUMMARY OF , I3, 16H TESTS OF CHKDER /) 120 FORMAT (46H NPROB N STATUS ERRMIN ERRMAX /) 130 FORMAT (I4, I6, 6X, L1, 3X, 2E15.7) C C LAST CARD OF DERIVATIVE CHECK TEST DRIVER. C END SUBROUTINE ERRJAC(N,X,FJAC,LDFJAC,NPROB) INTEGER N,LDFJAC,NPROB REAL X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE ERRJAC C C THIS SUBROUTINE IS DERIVED FROM VECJAC WHICH DEFINES THE C JACOBIAN MATRICES OF FOURTEEN TEST FUNCTIONS. THE PROBLEM C DIMENSIONS ARE AS DESCRIBED IN THE PROLOGUE COMMENTS OF VECFCN. C VARIOUS ERRORS ARE DELIBERATELY INTRODUCED TO PROVIDE A TEST C FOR CHKDER. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE ERRJAC(N,X,FJAC,LDFJAC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER VARIABLE. C C X IS AN ARRAY OF LENGTH N. C C FJAC IS AN N BY N ARRAY. ON OUTPUT FJAC CONTAINS THE C JACOBIAN MATRIX, WITH VARIOUS ERRORS DELIBERATELY C INTRODUCED, OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,AMIN1,SIN,SQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,K1,K2,ML,MU REAL C1,C3,C4,C5,C6,C9,EIGHT,FIFTN,FIVE,FOUR,H,HUNDRD,ONE,PROD, * SIX,SUM,SUM1,SUM2,TEMP,TEMP1,TEMP2,TEMP3,TEMP4,TEN,THREE, * TI,TJ,TK,TPI,TWENTY,TWO,ZERO REAL FLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,SIX,EIGHT,TEN,FIFTN,TWENTY, * HUNDRD * /0.0E0,1.0E0,2.0E0,3.0E0,4.0E0,5.0E0,6.0E0,8.0E0,1.0E1, * 1.5E1,2.0E1,1.0E2/ DATA C1,C3,C4,C5,C6,C9 /1.0E4,2.0E2,2.02E1,1.98E1,1.8E2,2.9E1/ FLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,20,50,60,90,100,200,230,290,320,350,380,420,450), * NPROB C C ROSENBROCK FUNCTION WITH SIGN REVERSAL AFFECTING ELEMENT (1,1). C 10 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = ZERO FJAC(2,1) = -TWENTY*X(1) FJAC(2,2) = TEN GO TO 490 C C POWELL SINGULAR FUNCTION WITH SIGN REVERSAL AFFECTING ELEMENT C (3,3). C 20 CONTINUE DO 40 K = 1, 4 DO 30 J = 1, 4 FJAC(K,J) = ZERO 30 CONTINUE 40 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = SQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = TWO*FJAC(3,2) FJAC(4,1) = TWO*SQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 490 C C POWELL BADLY SCALED FUNCTION WITH THE SIGN OF THE JACOBIAN C REVERSED. C 50 CONTINUE FJAC(1,1) = -C1*X(2) FJAC(1,2) = -C1*X(1) FJAC(2,1) = EXP(-X(1)) FJAC(2,2) = EXP(-X(2)) GO TO 490 C C WOOD FUNCTION WITHOUT ERROR. C 60 CONTINUE DO 80 K = 1, 4 DO 70 J = 1, 4 FJAC(K,J) = ZERO 70 CONTINUE 80 CONTINUE TEMP1 = X(2) - THREE*X(1)**2 TEMP2 = X(4) - THREE*X(3)**2 FJAC(1,1) = -C3*TEMP1 + ONE FJAC(1,2) = -C3*X(1) FJAC(2,1) = -TWO*C3*X(1) FJAC(2,2) = C3 + C4 FJAC(2,4) = C5 FJAC(3,3) = -C6*TEMP2 + ONE FJAC(3,4) = -C6*X(3) FJAC(4,2) = C5 FJAC(4,3) = -TWO*C6*X(3) FJAC(4,4) = C6 + C4 GO TO 490 C C HELICAL VALLEY FUNCTION WITH MULTIPLICATIVE ERROR AFFECTING C ELEMENTS (2,1) AND (2,2). C 90 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP = X(1)**2 + X(2)**2 TEMP1 = TPI*TEMP TEMP2 = SQRT(TEMP) FJAC(1,1) = HUNDRD*X(2)/TEMP1 FJAC(1,2) = -HUNDRD*X(1)/TEMP1 FJAC(1,3) = TEN FJAC(2,1) = FIVE*X(1)/TEMP2 FJAC(2,2) = FIVE*X(2)/TEMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 490 C C WATSON FUNCTION WITH SIGN REVERSALS AFFECTING THE COMPUTATION OF C TEMP1. C 100 CONTINUE DO 120 K = 1, N DO 110 J = K, N FJAC(K,J) = ZERO 110 CONTINUE 120 CONTINUE DO 170 I = 1, 29 TI = FLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 130 J = 2, N SUM1 = SUM1 + FLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 130 CONTINUE SUM2 = ZERO TEMP = ONE DO 140 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 140 CONTINUE TEMP1 = TWO*(SUM1 + SUM2**2 + ONE) TEMP2 = TWO*SUM2 TEMP = TI**2 TK = ONE DO 160 K = 1, N TJ = TK DO 150 J = K, N FJAC(K,J) = FJAC(K,J) * + TJ * *((FLOAT(K-1)/TI - TEMP2) * *(FLOAT(J-1)/TI - TEMP2) - TEMP1) TJ = TI*TJ 150 CONTINUE TK = TEMP*TK 160 CONTINUE 170 CONTINUE FJAC(1,1) = FJAC(1,1) + SIX*X(1)**2 - TWO*X(2) + THREE FJAC(1,2) = FJAC(1,2) - TWO*X(1) FJAC(2,2) = FJAC(2,2) + ONE DO 190 K = 1, N DO 180 J = K, N FJAC(J,K) = FJAC(K,J) 180 CONTINUE 190 CONTINUE GO TO 490 C C CHEBYQUAD FUNCTION WITH JACOBIAN TWICE CORRECT SIZE. C 200 CONTINUE TK = ONE/FLOAT(N) DO 220 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 TEMP3 = ZERO TEMP4 = TWO DO 210 K = 1, N FJAC(K,J) = TWO*TK*TEMP4 TI = FOUR*TEMP2 + TEMP*TEMP4 - TEMP3 TEMP3 = TEMP4 TEMP4 = TI TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 210 CONTINUE 220 CONTINUE GO TO 490 C C BROWN ALMOST-LINEAR FUNCTION WITHOUT ERROR. C 230 CONTINUE PROD = ONE DO 250 J = 1, N PROD = X(J)*PROD DO 240 K = 1, N FJAC(K,J) = ONE 240 CONTINUE FJAC(J,J) = TWO 250 CONTINUE DO 280 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 270 TEMP = ONE PROD = ONE DO 260 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 260 CONTINUE 270 CONTINUE FJAC(N,J) = PROD/TEMP 280 CONTINUE GO TO 490 C C DISCRETE BOUNDARY VALUE FUNCTION WITH MULTIPLICATIVE ERROR C AFFECTING THE JACOBIAN DIAGONAL. C 290 CONTINUE H = ONE/FLOAT(N+1) DO 310 K = 1, N TEMP = THREE*(X(K) + FLOAT(K)*H + ONE)**2 DO 300 J = 1, N FJAC(K,J) = ZERO 300 CONTINUE FJAC(K,K) = FOUR + TEMP*H**2 IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -ONE 310 CONTINUE GO TO 490 C C DISCRETE INTEGRAL EQUATION FUNCTION WITH SIGN ERROR AFFECTING C THE JACOBIAN DIAGONAL. C 320 CONTINUE H = ONE/FLOAT(N+1) DO 340 K = 1, N TK = FLOAT(K)*H DO 330 J = 1, N TJ = FLOAT(J)*H TEMP = THREE*(X(J) + TJ + ONE)**2 FJAC(K,J) = H*AMIN1(TJ*(ONE-TK),TK*(ONE-TJ))*TEMP/TWO 330 CONTINUE FJAC(K,K) = FJAC(K,K) - ONE 340 CONTINUE GO TO 490 C C TRIGONOMETRIC FUNCTION WITH SIGN ERRORS AFFECTING THE C OFFDIAGONAL ELEMENTS OF THE JACOBIAN. C 350 CONTINUE DO 370 J = 1, N TEMP = SIN(X(J)) DO 360 K = 1, N FJAC(K,J) = -TEMP 360 CONTINUE FJAC(J,J) = FLOAT(J+1)*TEMP - COS(X(J)) 370 CONTINUE GO TO 490 C C VARIABLY DIMENSIONED FUNCTION WITH OPERATION ERROR AFFECTING C THE UPPER TRIANGULAR ELEMENTS OF THE JACOBIAN. C 380 CONTINUE SUM = ZERO DO 390 J = 1, N SUM = SUM + FLOAT(J)*(X(J) - ONE) 390 CONTINUE TEMP = ONE + SIX*SUM**2 DO 410 K = 1, N DO 400 J = K, N FJAC(K,J) = FLOAT(K*J)/TEMP FJAC(J,K) = FJAC(K,J) 400 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 410 CONTINUE GO TO 490 C C BROYDEN TRIDIAGONAL FUNCTION WITHOUT ERROR. C 420 CONTINUE DO 440 K = 1, N DO 430 J = 1, N FJAC(K,J) = ZERO 430 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 440 CONTINUE GO TO 490 C C BROYDEN BANDED FUNCTION WITH SIGN ERROR AFFECTING THE JACOBIAN C DIAGONAL. C 450 CONTINUE ML = 5 MU = 1 DO 480 K = 1, N DO 460 J = 1, N FJAC(K,J) = ZERO 460 CONTINUE K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) DO 470 J = K1, K2 IF (J .NE. K) FJAC(K,J) = -(ONE + TWO*X(J)) 470 CONTINUE FJAC(K,K) = TWO - FIFTN*X(K)**2 480 CONTINUE 490 CONTINUE RETURN C C LAST CARD OF SUBROUTINE ERRJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,H,HALF,ONE,THREE,TJ,ZERO REAL FLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0E0,5.0E-1,1.0E0,3.0E0,1.2E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/FLOAT(N+1) DO 90 J = 1, N X(J) = FLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/FLOAT(N+1) DO 130 J = 1, N TJ = FLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/FLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/FLOAT(N) DO 170 J = 1, N X(J) = ONE - FLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB REAL X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIGN,SIN,SQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE,PROD,SUM,SUM1, * SUM2,TEMP,TEMP1,TEMP2,TEN,THREE,TI,TJ,TK,TPI,TWO,ZERO REAL FLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0E0,1.0E0,2.0E0,3.0E0,5.0E0,8.0E0,1.0E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0E4,1.0001E0,2.0E2,2.02E1,1.98E1,1.8E2,2.5E-1,5.0E-1, * 2.9E1/ FLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = EXP(-X(1)) + EXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP1 = SIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = ATAN(X(2)/X(1))/TPI + C8 TEMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = FLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + FLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(FLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/FLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(FLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/FLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + FLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/FLOAT(N+1) DO 260 K = 1, N TK = FLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = FLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = COS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = FLOAT(N+K) - SIN(X(K)) - SUM - FLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + FLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + FLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END minpack-19961126/ex/file020000644000175000017500000045610704210374371015740 0ustar sylvestresylvestre SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) INTEGER M,N,LDFJAC,MODE REAL X(N),FVEC(M),FJAC(LDFJAC,N),XP(N),FVECP(M),ERR(M) C ********** C C SUBROUTINE CHKDER C C THIS SUBROUTINE CHECKS THE GRADIENTS OF M NONLINEAR FUNCTIONS C IN N VARIABLES, EVALUATED AT A POINT X, FOR CONSISTENCY WITH C THE FUNCTIONS THEMSELVES. THE USER MUST CALL CHKDER TWICE, C FIRST WITH MODE = 1 AND THEN WITH MODE = 2. C C MODE = 1. ON INPUT, X MUST CONTAIN THE POINT OF EVALUATION. C ON OUTPUT, XP IS SET TO A NEIGHBORING POINT. C C MODE = 2. ON INPUT, FVEC MUST CONTAIN THE FUNCTIONS AND THE C ROWS OF FJAC MUST CONTAIN THE GRADIENTS C OF THE RESPECTIVE FUNCTIONS EACH EVALUATED C AT X, AND FVECP MUST CONTAIN THE FUNCTIONS C EVALUATED AT XP. C ON OUTPUT, ERR CONTAINS MEASURES OF CORRECTNESS OF C THE RESPECTIVE GRADIENTS. C C THE SUBROUTINE DOES NOT PERFORM RELIABLY IF CANCELLATION OR C ROUNDING ERRORS CAUSE A SEVERE LOSS OF SIGNIFICANCE IN THE C EVALUATION OF A FUNCTION. THEREFORE, NONE OF THE COMPONENTS C OF X SHOULD BE UNUSUALLY SMALL (IN PARTICULAR, ZERO) OR ANY C OTHER VALUE WHICH MAY CAUSE LOSS OF SIGNIFICANCE. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE CHKDER(M,N,X,FVEC,FJAC,LDFJAC,XP,FVECP,MODE,ERR) C C WHERE 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. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN ARRAY OF LENGTH M. ON INPUT WHEN MODE = 2, C FVEC MUST CONTAIN THE FUNCTIONS EVALUATED AT X. C C FJAC IS AN M BY N ARRAY. ON INPUT WHEN MODE = 2, C THE ROWS OF FJAC MUST CONTAIN THE GRADIENTS OF C THE RESPECTIVE FUNCTIONS EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT PARAMETER NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C XP IS AN ARRAY OF LENGTH N. ON OUTPUT WHEN MODE = 1, C XP IS SET TO A NEIGHBORING POINT OF X. C C FVECP IS AN ARRAY OF LENGTH M. ON INPUT WHEN MODE = 2, C FVECP MUST CONTAIN THE FUNCTIONS EVALUATED AT XP. C C MODE IS AN INTEGER INPUT VARIABLE SET TO 1 ON THE FIRST CALL C AND 2 ON THE SECOND. OTHER VALUES OF MODE ARE EQUIVALENT C TO MODE = 1. C C ERR IS AN ARRAY OF LENGTH M. ON OUTPUT WHEN MODE = 2, C ERR CONTAINS MEASURES OF CORRECTNESS OF THE RESPECTIVE C GRADIENTS. IF THERE IS NO SEVERE LOSS OF SIGNIFICANCE, C THEN IF ERR(I) IS 1.0 THE I-TH GRADIENT IS CORRECT, C WHILE IF ERR(I) IS 0.0 THE I-TH GRADIENT IS INCORRECT. C FOR VALUES OF ERR BETWEEN 0.0 AND 1.0, THE CATEGORIZATION C IS LESS CERTAIN. IN GENERAL, A VALUE OF ERR(I) GREATER C THAN 0.5 INDICATES THAT THE I-TH GRADIENT IS PROBABLY C CORRECT, WHILE A VALUE OF ERR(I) LESS THAN 0.5 INDICATES C THAT THE I-TH GRADIENT IS PROBABLY INCORRECT. C C SUBPROGRAMS CALLED C C MINPACK SUPPLIED ... SPMPAR C C FORTRAN SUPPLIED ... ABS,ALOG10,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J REAL EPS,EPSF,EPSLOG,EPSMCH,FACTOR,ONE,TEMP,ZERO REAL SPMPAR DATA FACTOR,ONE,ZERO /1.0E2,1.0E0,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C EPS = SQRT(EPSMCH) C IF (MODE .EQ. 2) GO TO 20 C C MODE = 1. C DO 10 J = 1, N TEMP = EPS*ABS(X(J)) IF (TEMP .EQ. ZERO) TEMP = EPS XP(J) = X(J) + TEMP 10 CONTINUE GO TO 70 20 CONTINUE C C MODE = 2. C EPSF = FACTOR*EPSMCH EPSLOG = ALOG10(EPS) DO 30 I = 1, M ERR(I) = ZERO 30 CONTINUE DO 50 J = 1, N TEMP = ABS(X(J)) IF (TEMP .EQ. ZERO) TEMP = ONE DO 40 I = 1, M ERR(I) = ERR(I) + TEMP*FJAC(I,J) 40 CONTINUE 50 CONTINUE DO 60 I = 1, M TEMP = ONE IF (FVEC(I) .NE. ZERO .AND. FVECP(I) .NE. ZERO * .AND. ABS(FVECP(I)-FVEC(I)) .GE. EPSF*ABS(FVEC(I))) * TEMP = EPS*ABS((FVECP(I)-FVEC(I))/EPS-ERR(I)) * /(ABS(FVEC(I)) + ABS(FVECP(I))) ERR(I) = ONE IF (TEMP .GT. EPSMCH .AND. TEMP .LT. EPS) * ERR(I) = (ALOG10(TEMP) - EPSLOG)/EPSLOG IF (TEMP .GE. EPS) ERR(I) = ZERO 60 CONTINUE 70 CONTINUE C RETURN C C LAST CARD OF SUBROUTINE CHKDER. C END SUBROUTINE DOGLEG(N,R,LR,DIAG,QTB,DELTA,X,WA1,WA2) INTEGER N,LR REAL DELTA REAL R(LR),DIAG(N),QTB(N),X(N),WA1(N),WA2(N) C ********** C C SUBROUTINE DOGLEG C C GIVEN AN M BY N MATRIX A, AN N BY N NONSINGULAR DIAGONAL C MATRIX D, AN M-VECTOR B, AND A POSITIVE NUMBER DELTA, THE C PROBLEM IS TO DETERMINE THE CONVEX COMBINATION X OF THE C GAUSS-NEWTON AND SCALED GRADIENT DIRECTIONS THAT MINIMIZES C (A*X - B) IN THE LEAST SQUARES SENSE, SUBJECT TO THE C RESTRICTION THAT THE EUCLIDEAN NORM OF D*X BE AT MOST DELTA. C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION OF A. THAT IS, IF A = Q*R, WHERE Q HAS C ORTHOGONAL COLUMNS AND R IS AN UPPER TRIANGULAR MATRIX, C THEN DOGLEG EXPECTS THE FULL UPPER TRIANGLE OF R AND C THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE DOGLEG(N,R,LR,DIAG,QTB,DELTA,X,WA1,WA2) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN INPUT ARRAY OF LENGTH LR WHICH MUST CONTAIN THE UPPER C TRIANGULAR MATRIX R STORED BY ROWS. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C DELTA IS A POSITIVE INPUT VARIABLE WHICH SPECIFIES AN UPPER C BOUND ON THE EUCLIDEAN NORM OF D*X. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE DESIRED C CONVEX COMBINATION OF THE GAUSS-NEWTON DIRECTION AND THE C SCALED GRADIENT DIRECTION. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SPMPAR,ENORM C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JJ,JP1,K,L REAL ALPHA,BNORM,EPSMCH,GNORM,ONE,QNORM,SGNORM,SUM,TEMP,ZERO REAL SPMPAR,ENORM DATA ONE,ZERO /1.0E0,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C C FIRST, CALCULATE THE GAUSS-NEWTON DIRECTION. C JJ = (N*(N + 1))/2 + 1 DO 50 K = 1, N J = N - K + 1 JP1 = J + 1 JJ = JJ - K L = JJ + 1 SUM = ZERO IF (N .LT. JP1) GO TO 20 DO 10 I = JP1, N SUM = SUM + R(L)*X(I) L = L + 1 10 CONTINUE 20 CONTINUE TEMP = R(JJ) IF (TEMP .NE. ZERO) GO TO 40 L = J DO 30 I = 1, J TEMP = AMAX1(TEMP,ABS(R(L))) L = L + N - I 30 CONTINUE TEMP = EPSMCH*TEMP IF (TEMP .EQ. ZERO) TEMP = EPSMCH 40 CONTINUE X(J) = (QTB(J) - SUM)/TEMP 50 CONTINUE C C TEST WHETHER THE GAUSS-NEWTON DIRECTION IS ACCEPTABLE. C DO 60 J = 1, N WA1(J) = ZERO WA2(J) = DIAG(J)*X(J) 60 CONTINUE QNORM = ENORM(N,WA2) IF (QNORM .LE. DELTA) GO TO 140 C C THE GAUSS-NEWTON DIRECTION IS NOT ACCEPTABLE. C NEXT, CALCULATE THE SCALED GRADIENT DIRECTION. C L = 1 DO 80 J = 1, N TEMP = QTB(J) DO 70 I = J, N WA1(I) = WA1(I) + R(L)*TEMP L = L + 1 70 CONTINUE WA1(J) = WA1(J)/DIAG(J) 80 CONTINUE C C CALCULATE THE NORM OF THE SCALED GRADIENT AND TEST FOR C THE SPECIAL CASE IN WHICH THE SCALED GRADIENT IS ZERO. C GNORM = ENORM(N,WA1) SGNORM = ZERO ALPHA = DELTA/QNORM IF (GNORM .EQ. ZERO) GO TO 120 C C CALCULATE THE POINT ALONG THE SCALED GRADIENT C AT WHICH THE QUADRATIC IS MINIMIZED. C DO 90 J = 1, N WA1(J) = (WA1(J)/GNORM)/DIAG(J) 90 CONTINUE L = 1 DO 110 J = 1, N SUM = ZERO DO 100 I = J, N SUM = SUM + R(L)*WA1(I) L = L + 1 100 CONTINUE WA2(J) = SUM 110 CONTINUE TEMP = ENORM(N,WA2) SGNORM = (GNORM/TEMP)/TEMP C C TEST WHETHER THE SCALED GRADIENT DIRECTION IS ACCEPTABLE. C ALPHA = ZERO IF (SGNORM .GE. DELTA) GO TO 120 C C THE SCALED GRADIENT DIRECTION IS NOT ACCEPTABLE. C FINALLY, CALCULATE THE POINT ALONG THE DOGLEG C AT WHICH THE QUADRATIC IS MINIMIZED. C BNORM = ENORM(N,QTB) TEMP = (BNORM/GNORM)*(BNORM/QNORM)*(SGNORM/DELTA) TEMP = TEMP - (DELTA/QNORM)*(SGNORM/DELTA)**2 * + SQRT((TEMP-(DELTA/QNORM))**2 * +(ONE-(DELTA/QNORM)**2)*(ONE-(SGNORM/DELTA)**2)) ALPHA = ((DELTA/QNORM)*(ONE - (SGNORM/DELTA)**2))/TEMP 120 CONTINUE C C FORM APPROPRIATE CONVEX COMBINATION OF THE GAUSS-NEWTON C DIRECTION AND THE SCALED GRADIENT DIRECTION. C TEMP = (ONE - ALPHA)*AMIN1(SGNORM,DELTA) DO 130 J = 1, N X(J) = TEMP*WA1(J) + ALPHA*X(J) 130 CONTINUE 140 CONTINUE RETURN C C LAST CARD OF SUBROUTINE DOGLEG. C END REAL FUNCTION ENORM(N,X) INTEGER N REAL X(N) C ********** C C FUNCTION ENORM C C GIVEN AN N-VECTOR X, THIS FUNCTION CALCULATES THE C EUCLIDEAN NORM OF X. C C THE EUCLIDEAN NORM IS COMPUTED BY ACCUMULATING THE SUM OF C SQUARES IN THREE DIFFERENT SUMS. THE SUMS OF SQUARES FOR THE C SMALL AND LARGE COMPONENTS ARE SCALED SO THAT NO OVERFLOWS C OCCUR. NON-DESTRUCTIVE UNDERFLOWS ARE PERMITTED. UNDERFLOWS C AND OVERFLOWS DO NOT OCCUR IN THE COMPUTATION OF THE UNSCALED C SUM OF SQUARES FOR THE INTERMEDIATE COMPONENTS. C THE DEFINITIONS OF SMALL, INTERMEDIATE AND LARGE COMPONENTS C DEPEND ON TWO CONSTANTS, RDWARF AND RGIANT. THE MAIN C RESTRICTIONS ON THESE CONSTANTS ARE THAT RDWARF**2 NOT C UNDERFLOW AND RGIANT**2 NOT OVERFLOW. THE CONSTANTS C GIVEN HERE ARE SUITABLE FOR EVERY KNOWN COMPUTER. C C THE FUNCTION STATEMENT IS C C REAL FUNCTION ENORM(N,X) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ABS,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I REAL AGIANT,FLOATN,ONE,RDWARF,RGIANT,S1,S2,S3,XABS,X1MAX,X3MAX, * ZERO DATA ONE,ZERO,RDWARF,RGIANT /1.0E0,0.0E0,3.834E-20,1.304E19/ S1 = ZERO S2 = ZERO S3 = ZERO X1MAX = ZERO X3MAX = ZERO FLOATN = N AGIANT = RGIANT/FLOATN DO 90 I = 1, N XABS = ABS(X(I)) IF (XABS .GT. RDWARF .AND. XABS .LT. AGIANT) GO TO 70 IF (XABS .LE. RDWARF) GO TO 30 C C SUM FOR LARGE COMPONENTS. C IF (XABS .LE. X1MAX) GO TO 10 S1 = ONE + S1*(X1MAX/XABS)**2 X1MAX = XABS GO TO 20 10 CONTINUE S1 = S1 + (XABS/X1MAX)**2 20 CONTINUE GO TO 60 30 CONTINUE C C SUM FOR SMALL COMPONENTS. C IF (XABS .LE. X3MAX) GO TO 40 S3 = ONE + S3*(X3MAX/XABS)**2 X3MAX = XABS GO TO 50 40 CONTINUE IF (XABS .NE. ZERO) S3 = S3 + (XABS/X3MAX)**2 50 CONTINUE 60 CONTINUE GO TO 80 70 CONTINUE C C SUM FOR INTERMEDIATE COMPONENTS. C S2 = S2 + XABS**2 80 CONTINUE 90 CONTINUE C C CALCULATION OF NORM. C IF (S1 .EQ. ZERO) GO TO 100 ENORM = X1MAX*SQRT(S1+(S2/X1MAX)/X1MAX) GO TO 130 100 CONTINUE IF (S2 .EQ. ZERO) GO TO 110 IF (S2 .GE. X3MAX) * ENORM = SQRT(S2*(ONE+(X3MAX/S2)*(X3MAX*S3))) IF (S2 .LT. X3MAX) * ENORM = SQRT(X3MAX*((S2/X3MAX)+(X3MAX*S3))) GO TO 120 110 CONTINUE ENORM = X3MAX*SQRT(S3) 120 CONTINUE 130 CONTINUE RETURN C C LAST CARD OF FUNCTION ENORM. C END SUBROUTINE FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN, * WA1,WA2) INTEGER N,LDFJAC,IFLAG,ML,MU REAL EPSFCN REAL X(N),FVEC(N),FJAC(LDFJAC,N),WA1(N),WA2(N) C ********** C C SUBROUTINE FDJAC1 C C THIS SUBROUTINE COMPUTES A FORWARD-DIFFERENCE APPROXIMATION C TO THE N BY N JACOBIAN MATRIX ASSOCIATED WITH A SPECIFIED C PROBLEM OF N FUNCTIONS IN N VARIABLES. IF THE JACOBIAN HAS C A BANDED FORM, THEN FUNCTION EVALUATIONS ARE SAVED BY ONLY C APPROXIMATING THE NONZERO TERMS. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN, C WA1,WA2) 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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C REAL X(N),FVEC(N) 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 FDJAC1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C FUNCTIONS EVALUATED AT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C APPROXIMATION TO THE JACOBIAN MATRIX EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IFLAG IS AN INTEGER VARIABLE WHICH CAN BE USED TO TERMINATE C THE EXECUTION OF FDJAC1. SEE DESCRIPTION OF FCN. C C ML IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUBDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C ML TO AT LEAST N - 1. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C MU IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUPERDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C MU TO AT LEAST N - 1. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. IF ML + MU + 1 IS AT C LEAST N, THEN THE JACOBIAN IS CONSIDERED DENSE, AND WA2 IS C NOT REFERENCED. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SPMPAR C C FORTRAN-SUPPLIED ... ABS,AMAX1,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,K,MSUM REAL EPS,EPSMCH,H,TEMP,ZERO REAL SPMPAR DATA ZERO /0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C EPS = SQRT(AMAX1(EPSFCN,EPSMCH)) MSUM = ML + MU + 1 IF (MSUM .LT. N) GO TO 40 C C COMPUTATION OF DENSE APPROXIMATE JACOBIAN. C DO 20 J = 1, N TEMP = X(J) H = EPS*ABS(TEMP) IF (H .EQ. ZERO) H = EPS X(J) = TEMP + H CALL FCN(N,X,WA1,IFLAG) IF (IFLAG .LT. 0) GO TO 30 X(J) = TEMP DO 10 I = 1, N FJAC(I,J) = (WA1(I) - FVEC(I))/H 10 CONTINUE 20 CONTINUE 30 CONTINUE GO TO 110 40 CONTINUE C C COMPUTATION OF BANDED APPROXIMATE JACOBIAN. C DO 90 K = 1, MSUM DO 60 J = K, N, MSUM WA2(J) = X(J) H = EPS*ABS(WA2(J)) IF (H .EQ. ZERO) H = EPS X(J) = WA2(J) + H 60 CONTINUE CALL FCN(N,X,WA1,IFLAG) IF (IFLAG .LT. 0) GO TO 100 DO 80 J = K, N, MSUM X(J) = WA2(J) H = EPS*ABS(WA2(J)) IF (H .EQ. ZERO) H = EPS DO 70 I = 1, N FJAC(I,J) = ZERO IF (I .GE. J - MU .AND. I .LE. J + ML) * FJAC(I,J) = (WA1(I) - FVEC(I))/H 70 CONTINUE 80 CONTINUE 90 CONTINUE 100 CONTINUE 110 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FDJAC1. C END SUBROUTINE FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA) INTEGER M,N,LDFJAC,IFLAG REAL EPSFCN REAL X(N),FVEC(M),FJAC(LDFJAC,N),WA(M) C ********** C C SUBROUTINE FDJAC2 C C THIS SUBROUTINE COMPUTES A FORWARD-DIFFERENCE APPROXIMATION C TO THE M BY N JACOBIAN MATRIX ASSOCIATED WITH A SPECIFIED C PROBLEM OF M FUNCTIONS IN N VARIABLES. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA) 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 FDJAC2. 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 INPUT ARRAY OF LENGTH N. C C FVEC IS AN INPUT ARRAY OF LENGTH M WHICH MUST CONTAIN THE C FUNCTIONS EVALUATED AT X. C C FJAC IS AN OUTPUT M BY N ARRAY WHICH CONTAINS THE C APPROXIMATION TO THE JACOBIAN MATRIX EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IFLAG IS AN INTEGER VARIABLE WHICH CAN BE USED TO TERMINATE C THE EXECUTION OF FDJAC2. SEE DESCRIPTION OF FCN. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C WA IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR C C FORTRAN-SUPPLIED ... ABS,AMAX1,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J REAL EPS,EPSMCH,H,TEMP,ZERO REAL SPMPAR DATA ZERO /0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C EPS = SQRT(AMAX1(EPSFCN,EPSMCH)) DO 20 J = 1, N TEMP = X(J) H = EPS*ABS(TEMP) IF (H .EQ. ZERO) H = EPS X(J) = TEMP + H CALL FCN(M,N,X,WA,IFLAG) IF (IFLAG .LT. 0) GO TO 30 X(J) = TEMP DO 10 I = 1, M FJAC(I,J) = (WA(I) - FVEC(I))/H 10 CONTINUE 20 CONTINUE 30 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FDJAC2. C END SUBROUTINE HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC,R,LR, * QTF,WA1,WA2,WA3,WA4) INTEGER N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR REAL XTOL,EPSFCN,FACTOR REAL X(N),FVEC(N),DIAG(N),FJAC(LDFJAC,N),R(LR),QTF(N),WA1(N), * WA2(N),WA3(N),WA4(N) EXTERNAL FCN C ********** C C SUBROUTINE HYBRD C C THE PURPOSE OF HYBRD IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. 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 HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN, C DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC, C LDFJAC,R,LR,QTF,WA1,WA2,WA3,WA4) 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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C REAL X(N),FVEC(N) 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 HYBRD. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN IS AT LEAST MAXFEV C BY THE END OF AN ITERATION. C C ML IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUBDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C ML TO AT LEAST N - 1. C C MU IS A NONNEGATIVE INTEGER INPUT VARIABLE WHICH SPECIFIES C THE NUMBER OF SUPERDIAGONALS WITHIN THE BAND OF THE C JACOBIAN MATRIX. IF THE JACOBIAN IS NOT BANDED, SET C MU TO AT LEAST N - 1. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 2 NUMBER OF CALLS TO FCN HAS REACHED OR EXCEEDED C MAXFEV. C C INFO = 3 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C FIVE JACOBIAN EVALUATIONS. C C INFO = 5 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C TEN ITERATIONS. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C R IS AN OUTPUT ARRAY OF LENGTH LR WHICH CONTAINS THE C UPPER TRIANGULAR MATRIX PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN, STORED ROWWISE. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, WA3, AND WA4 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DOGLEG,SPMPAR,ENORM,FDJAC1, C QFORM,QRFAC,R1MPYQ,R1UPDT C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,MIN0,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,JM1,L,MSUM,NCFAIL,NCSUC,NSLOW1,NSLOW2 INTEGER IWA(1) LOGICAL JEVAL,SING REAL ACTRED,DELTA,EPSMCH,FNORM,FNORM1,ONE,PNORM,PRERED,P1,P5, * P001,P0001,RATIO,SUM,TEMP,XNORM,ZERO REAL SPMPAR,ENORM DATA ONE,P1,P5,P001,P0001,ZERO * /1.0E0,1.0E-1,5.0E-1,1.0E-3,1.0E-4,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. XTOL .LT. ZERO .OR. MAXFEV .LE. 0 * .OR. ML .LT. 0 .OR. MU .LT. 0 .OR. FACTOR .LE. ZERO * .OR. LDFJAC .LT. N .OR. LR .LT. (N*(N + 1))/2) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,X,FVEC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(N,FVEC) C C DETERMINE THE NUMBER OF CALLS TO FCN NEEDED TO COMPUTE C THE JACOBIAN MATRIX. C MSUM = MIN0(ML+MU+1,N) C C INITIALIZE ITERATION COUNTER AND MONITORS. C ITER = 1 NCSUC = 0 NCFAIL = 0 NSLOW1 = 0 NSLOW2 = 0 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE JEVAL = .TRUE. C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FDJAC1(FCN,N,X,FVEC,FJAC,LDFJAC,IFLAG,ML,MU,EPSFCN,WA1, * WA2) NFEV = NFEV + MSUM IF (IFLAG .LT. 0) GO TO 300 C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(N,N,FJAC,LDFJAC,.FALSE.,IWA,1,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 70 IF (MODE .EQ. 2) GO TO 50 DO 40 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 40 CONTINUE 50 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 60 J = 1, N WA3(J) = DIAG(J)*X(J) 60 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 70 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE IN QTF. C DO 80 I = 1, N QTF(I) = FVEC(I) 80 CONTINUE DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE 120 CONTINUE C C COPY THE TRIANGULAR FACTOR OF THE QR FACTORIZATION INTO R. C SING = .FALSE. DO 150 J = 1, N L = J JM1 = J - 1 IF (JM1 .LT. 1) GO TO 140 DO 130 I = 1, JM1 R(L) = FJAC(I,J) L = L + N - I 130 CONTINUE 140 CONTINUE R(L) = WA1(J) IF (WA1(J) .EQ. ZERO) SING = .TRUE. 150 CONTINUE C C ACCUMULATE THE ORTHOGONAL FACTOR IN FJAC. C CALL QFORM(N,N,FJAC,LDFJAC,WA1) C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 170 DO 160 J = 1, N DIAG(J) = AMAX1(DIAG(J),WA2(J)) 160 CONTINUE 170 CONTINUE C C BEGINNING OF THE INNER LOOP. C 180 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 190 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(N,X,FVEC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 190 CONTINUE C C DETERMINE THE DIRECTION P. C CALL DOGLEG(N,R,LR,DIAG,QTF,DELTA,WA1,WA2,WA3) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 200 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 200 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = AMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,WA2,WA4,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(N,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION. C L = 1 DO 220 I = 1, N SUM = ZERO DO 210 J = I, N SUM = SUM + R(L)*WA1(J) L = L + 1 210 CONTINUE WA3(I) = QTF(I) + SUM 220 CONTINUE TEMP = ENORM(N,WA3) PRERED = ZERO IF (TEMP .LT. FNORM) PRERED = ONE - (TEMP/FNORM)**2 C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .GT. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GE. P1) GO TO 230 NCSUC = 0 NCFAIL = NCFAIL + 1 DELTA = P5*DELTA GO TO 240 230 CONTINUE NCFAIL = 0 NCSUC = NCSUC + 1 IF (RATIO .GE. P5 .OR. NCSUC .GT. 1) * DELTA = AMAX1(DELTA,PNORM/P5) IF (ABS(RATIO-ONE) .LE. P1) DELTA = PNORM/P5 240 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 260 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 250 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) FVEC(J) = WA4(J) 250 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 260 CONTINUE C C DETERMINE THE PROGRESS OF THE ITERATION. C NSLOW1 = NSLOW1 + 1 IF (ACTRED .GE. P001) NSLOW1 = 0 IF (JEVAL) NSLOW2 = NSLOW2 + 1 IF (ACTRED .GE. P1) NSLOW2 = 0 C C TEST FOR CONVERGENCE. C IF (DELTA .LE. XTOL*XNORM .OR. FNORM .EQ. ZERO) INFO = 1 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 2 IF (P1*AMAX1(P1*DELTA,PNORM) .LE. EPSMCH*XNORM) INFO = 3 IF (NSLOW2 .EQ. 5) INFO = 4 IF (NSLOW1 .EQ. 10) INFO = 5 IF (INFO .NE. 0) GO TO 300 C C CRITERION FOR RECALCULATING JACOBIAN APPROXIMATION C BY FORWARD DIFFERENCES. C IF (NCFAIL .EQ. 2) GO TO 290 C C CALCULATE THE RANK ONE MODIFICATION TO THE JACOBIAN C AND UPDATE QTF IF NECESSARY. C DO 280 J = 1, N SUM = ZERO DO 270 I = 1, N SUM = SUM + FJAC(I,J)*WA4(I) 270 CONTINUE WA2(J) = (SUM - WA3(J))/PNORM WA1(J) = DIAG(J)*((DIAG(J)*WA1(J))/PNORM) IF (RATIO .GE. P0001) QTF(J) = SUM 280 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE UPDATED JACOBIAN. C CALL R1UPDT(N,N,R,LR,WA1,WA2,WA3,SING) CALL R1MPYQ(N,N,FJAC,LDFJAC,WA2,WA3) CALL R1MPYQ(1,N,QTF,1,WA2,WA3) C C END OF THE INNER LOOP. C JEVAL = .FALSE. GO TO 180 290 CONTINUE C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(N,X,FVEC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE HYBRD. C END SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) INTEGER N,INFO,LWA REAL TOL REAL X(N),FVEC(N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE HYBRD1 C C THE PURPOSE OF HYBRD1 IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THIS IS DONE BY USING THE C MORE GENERAL NONLINEAR EQUATION SOLVER HYBRD. THE USER C MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE FUNCTIONS. C THE JACOBIAN IS THEN CALCULATED BY A FORWARD-DIFFERENCE C APPROXIMATION. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRD1(FCN,N,X,FVEC,TOL,INFO,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(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C REAL X(N),FVEC(N) 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 HYBRD1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N 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 THAT THE RELATIVE ERROR C BETWEEN X AND THE SOLUTION IS AT 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 BETWEEN X AND THE SOLUTION IS AT MOST TOL. C C INFO = 2 NUMBER OF CALLS TO FCN HAS REACHED OR EXCEEDED C 200*(N+1). C C INFO = 3 TOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(3*N+13))/2. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... HYBRD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER INDEX,J,LR,MAXFEV,ML,MODE,MU,NFEV,NPRINT REAL EPSFCN,FACTOR,ONE,XTOL,ZERO DATA FACTOR,ONE,ZERO /1.0E2,1.0E0,0.0E0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. TOL .LT. ZERO .OR. LWA .LT. (N*(3*N + 13))/2) * GO TO 20 C C CALL HYBRD. C MAXFEV = 200*(N + 1) XTOL = TOL ML = N - 1 MU = N - 1 EPSFCN = ZERO MODE = 2 DO 10 J = 1, N WA(J) = ONE 10 CONTINUE NPRINT = 0 LR = (N*(N + 1))/2 INDEX = 6*N + LR CALL HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,WA(1),MODE, * FACTOR,NPRINT,INFO,NFEV,WA(INDEX+1),N,WA(6*N+1),LR, * WA(N+1),WA(2*N+1),WA(3*N+1),WA(4*N+1),WA(5*N+1)) IF (INFO .EQ. 5) INFO = 4 20 CONTINUE RETURN C C LAST CARD OF SUBROUTINE HYBRD1. C END SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG,MODE, * FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF,WA1,WA2, * WA3,WA4) INTEGER N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV,LR REAL XTOL,FACTOR REAL X(N),FVEC(N),FJAC(LDFJAC,N),DIAG(N),R(LR),QTF(N),WA1(N), * WA2(N),WA3(N),WA4(N) C ********** C C SUBROUTINE HYBRJ C C THE PURPOSE OF HYBRJ IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,DIAG, C MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,R,LR,QTF, C WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER N,LDFJAC,IFLAG C REAL X(N),FVEC(N),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 HYBRJ. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. FVEC AND FJAC SHOULD NOT BE ALTERED. C IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS OF FCN C WITH IFLAG = 0 ARE MADE. 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 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 2 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 3 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C FIVE JACOBIAN EVALUATIONS. C C INFO = 5 ITERATION IS NOT MAKING GOOD PROGRESS, AS C MEASURED BY THE IMPROVEMENT FROM THE LAST C TEN ITERATIONS. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C R IS AN OUTPUT ARRAY OF LENGTH LR WHICH CONTAINS THE C UPPER TRIANGULAR MATRIX PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN, STORED ROWWISE. C C LR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+1))/2. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, WA3, AND WA4 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DOGLEG,SPMPAR,ENORM, C QFORM,QRFAC,R1MPYQ,R1UPDT C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,JM1,L,NCFAIL,NCSUC,NSLOW1,NSLOW2 INTEGER IWA(1) LOGICAL JEVAL,SING REAL ACTRED,DELTA,EPSMCH,FNORM,FNORM1,ONE,PNORM,PRERED,P1,P5, * P001,P0001,RATIO,SUM,TEMP,XNORM,ZERO REAL SPMPAR,ENORM DATA ONE,P1,P5,P001,P0001,ZERO * /1.0E0,1.0E-1,5.0E-1,1.0E-3,1.0E-4,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. LDFJAC .LT. N .OR. XTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO * .OR. LR .LT. (N*(N + 1))/2) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(N,FVEC) C C INITIALIZE ITERATION COUNTER AND MONITORS. C ITER = 1 NCSUC = 0 NCFAIL = 0 NSLOW1 = 0 NSLOW2 = 0 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE JEVAL = .TRUE. C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) NJEV = NJEV + 1 IF (IFLAG .LT. 0) GO TO 300 C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(N,N,FJAC,LDFJAC,.FALSE.,IWA,1,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 70 IF (MODE .EQ. 2) GO TO 50 DO 40 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 40 CONTINUE 50 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 60 J = 1, N WA3(J) = DIAG(J)*X(J) 60 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 70 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE IN QTF. C DO 80 I = 1, N QTF(I) = FVEC(I) 80 CONTINUE DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE 120 CONTINUE C C COPY THE TRIANGULAR FACTOR OF THE QR FACTORIZATION INTO R. C SING = .FALSE. DO 150 J = 1, N L = J JM1 = J - 1 IF (JM1 .LT. 1) GO TO 140 DO 130 I = 1, JM1 R(L) = FJAC(I,J) L = L + N - I 130 CONTINUE 140 CONTINUE R(L) = WA1(J) IF (WA1(J) .EQ. ZERO) SING = .TRUE. 150 CONTINUE C C ACCUMULATE THE ORTHOGONAL FACTOR IN FJAC. C CALL QFORM(N,N,FJAC,LDFJAC,WA1) C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 170 DO 160 J = 1, N DIAG(J) = AMAX1(DIAG(J),WA2(J)) 160 CONTINUE 170 CONTINUE C C BEGINNING OF THE INNER LOOP. C 180 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 190 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) * CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 190 CONTINUE C C DETERMINE THE DIRECTION P. C CALL DOGLEG(N,R,LR,DIAG,QTF,DELTA,WA1,WA2,WA3) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 200 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 200 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = AMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(N,WA2,WA4,FJAC,LDFJAC,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(N,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION. C L = 1 DO 220 I = 1, N SUM = ZERO DO 210 J = I, N SUM = SUM + R(L)*WA1(J) L = L + 1 210 CONTINUE WA3(I) = QTF(I) + SUM 220 CONTINUE TEMP = ENORM(N,WA3) PRERED = ZERO IF (TEMP .LT. FNORM) PRERED = ONE - (TEMP/FNORM)**2 C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .GT. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GE. P1) GO TO 230 NCSUC = 0 NCFAIL = NCFAIL + 1 DELTA = P5*DELTA GO TO 240 230 CONTINUE NCFAIL = 0 NCSUC = NCSUC + 1 IF (RATIO .GE. P5 .OR. NCSUC .GT. 1) * DELTA = AMAX1(DELTA,PNORM/P5) IF (ABS(RATIO-ONE) .LE. P1) DELTA = PNORM/P5 240 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 260 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 250 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) FVEC(J) = WA4(J) 250 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 260 CONTINUE C C DETERMINE THE PROGRESS OF THE ITERATION. C NSLOW1 = NSLOW1 + 1 IF (ACTRED .GE. P001) NSLOW1 = 0 IF (JEVAL) NSLOW2 = NSLOW2 + 1 IF (ACTRED .GE. P1) NSLOW2 = 0 C C TEST FOR CONVERGENCE. C IF (DELTA .LE. XTOL*XNORM .OR. FNORM .EQ. ZERO) INFO = 1 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 2 IF (P1*AMAX1(P1*DELTA,PNORM) .LE. EPSMCH*XNORM) INFO = 3 IF (NSLOW2 .EQ. 5) INFO = 4 IF (NSLOW1 .EQ. 10) INFO = 5 IF (INFO .NE. 0) GO TO 300 C C CRITERION FOR RECALCULATING JACOBIAN. C IF (NCFAIL .EQ. 2) GO TO 290 C C CALCULATE THE RANK ONE MODIFICATION TO THE JACOBIAN C AND UPDATE QTF IF NECESSARY. C DO 280 J = 1, N SUM = ZERO DO 270 I = 1, N SUM = SUM + FJAC(I,J)*WA4(I) 270 CONTINUE WA2(J) = (SUM - WA3(J))/PNORM WA1(J) = DIAG(J)*((DIAG(J)*WA1(J))/PNORM) IF (RATIO .GE. P0001) QTF(J) = SUM 280 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE UPDATED JACOBIAN. C CALL R1UPDT(N,N,R,LR,WA1,WA2,WA3,SING) CALL R1MPYQ(N,N,FJAC,LDFJAC,WA2,WA3) CALL R1MPYQ(1,N,QTF,1,WA2,WA3) C C END OF THE INNER LOOP. C JEVAL = .FALSE. GO TO 180 290 CONTINUE C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE HYBRJ. C END SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) INTEGER N,LDFJAC,INFO,LWA REAL TOL REAL X(N),FVEC(N),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE HYBRJ1 C C THE PURPOSE OF HYBRJ1 IS TO FIND A ZERO OF A SYSTEM OF C N NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION C OF THE POWELL HYBRID METHOD. THIS IS DONE BY USING THE C MORE GENERAL NONLINEAR EQUATION SOLVER HYBRJ. THE USER C MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE FUNCTIONS C AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER N,LDFJAC,IFLAG C REAL X(N),FVEC(N),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 HYBRJ1. C IN THIS CASE SET IFLAG TO A NEGATIVE INTEGER. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF FUNCTIONS AND VARIABLES. 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 N WHICH CONTAINS C THE FUNCTIONS EVALUATED AT THE OUTPUT X. C C FJAC IS AN OUTPUT N BY N ARRAY WHICH CONTAINS THE C ORTHOGONAL MATRIX Q PRODUCED BY THE QR FACTORIZATION C OF THE FINAL APPROXIMATE JACOBIAN. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C TOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION OCCURS C WHEN THE ALGORITHM ESTIMATES THAT THE RELATIVE ERROR C BETWEEN X AND THE SOLUTION IS AT 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 BETWEEN X AND THE SOLUTION IS AT MOST TOL. C C INFO = 2 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED 100*(N+1). C C INFO = 3 TOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 4 ITERATION IS NOT MAKING GOOD PROGRESS. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(N+13))/2. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... HYBRJ C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER J,LR,MAXFEV,MODE,NFEV,NJEV,NPRINT REAL FACTOR,ONE,XTOL,ZERO DATA FACTOR,ONE,ZERO /1.0E2,1.0E0,0.0E0/ INFO = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. LDFJAC .LT. N .OR. TOL .LT. ZERO * .OR. LWA .LT. (N*(N + 13))/2) GO TO 20 C C CALL HYBRJ. C MAXFEV = 100*(N + 1) XTOL = TOL MODE = 2 DO 10 J = 1, N WA(J) = ONE 10 CONTINUE NPRINT = 0 LR = (N*(N + 1))/2 CALL HYBRJ(FCN,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,WA(1),MODE, * FACTOR,NPRINT,INFO,NFEV,NJEV,WA(6*N+1),LR,WA(N+1), * WA(2*N+1),WA(3*N+1),WA(4*N+1),WA(5*N+1)) IF (INFO .EQ. 5) INFO = 4 20 CONTINUE RETURN C C LAST CARD OF SUBROUTINE HYBRJ1. C END SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) REAL FTOL,XTOL,GTOL,FACTOR REAL X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N),WA1(N),WA2(N), * WA3(N),WA4(M) C ********** C C SUBROUTINE LMDER C C THE PURPOSE OF LMDER IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, C MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV, C NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER M,N,LDFJAC,IFLAG C REAL X(N),FVEC(M),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 LMDER. 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 FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X, FVEC, AND FJAC C AVAILABLE FOR PRINTING. FVEC AND FJAC SHOULD NOT BE C ALTERED. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,LMPAR,QRFAC C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,SQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L REAL ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM,ONE,PAR, * PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO,SUM,TEMP,TEMP1, * TEMP2,XNORM,ZERO REAL SPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0E0,1.0E-1,5.0E-1,2.5E-1,7.5E-1,1.0E-4,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. M * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) NJEV = NJEV + 1 IF (IFLAG .LT. 0) GO TO 300 C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) * CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(M,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 80 IF (MODE .EQ. 2) GO TO 60 DO 50 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 50 CONTINUE 60 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 70 J = 1, N WA3(J) = DIAG(J)*X(J) 70 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 80 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE THE FIRST N COMPONENTS IN C QTF. C DO 90 I = 1, M WA4(I) = FVEC(I) 90 CONTINUE DO 130 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 120 SUM = ZERO DO 100 I = J, M SUM = SUM + FJAC(I,J)*WA4(I) 100 CONTINUE TEMP = -SUM/FJAC(J,J) DO 110 I = J, M WA4(I) = WA4(I) + FJAC(I,J)*TEMP 110 CONTINUE 120 CONTINUE FJAC(J,J) = WA1(J) QTF(J) = WA4(J) 130 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 170 DO 160 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 150 SUM = ZERO DO 140 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 140 CONTINUE GNORM = AMAX1(GNORM,ABS(SUM/WA2(L))) 150 CONTINUE 160 CONTINUE 170 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 300 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 190 DO 180 J = 1, N DIAG(J) = AMAX1(DIAG(J),WA2(J)) 180 CONTINUE 190 CONTINUE C C BEGINNING OF THE INNER LOOP. C 200 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 210 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 210 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = AMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,FJAC,LDFJAC,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 230 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 220 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 220 CONTINUE 230 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (SQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 240 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*AMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 260 240 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 250 DELTA = PNORM/P5 PAR = P5*PAR 250 CONTINUE 260 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 290 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 270 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 270 CONTINUE DO 280 I = 1, M FVEC(I) = WA4(I) 280 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 290 CONTINUE C C TESTS FOR CONVERGENCE. C IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (ABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 300 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 200 C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMDER. C END SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IPVT,WA, * LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) REAL TOL REAL X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE LMDER1 C C THE PURPOSE OF LMDER1 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 LMDER. THE USER MUST PROVIDE A C SUBROUTINE WHICH CALCULATES THE FUNCTIONS AND THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO, C IPVT,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE JACOBIAN. FCN MUST C BE DECLARED IN AN EXTERNAL STATEMENT IN THE USER C CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER M,N,LDFJAC,IFLAG C REAL X(N),FVEC(M),FJAC(LDFJAC,N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. DO NOT ALTER FJAC. C IF IFLAG = 2 CALCULATE THE JACOBIAN AT X AND C RETURN THIS MATRIX IN FJAC. DO NOT ALTER 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 LMDER1. 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 FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. 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 WITH IFLAG = 1 HAS C REACHED 100*(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 IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN 5*N+M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... LMDER C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER MAXFEV,MODE,NFEV,NJEV,NPRINT REAL 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. LDFJAC .LT. M .OR. TOL .LT. ZERO * .OR. LWA .LT. 5*N + M) GO TO 10 C C CALL LMDER. C MAXFEV = 100*(N + 1) FTOL = TOL XTOL = TOL GTOL = ZERO MODE = 1 NPRINT = 0 CALL LMDER(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL,MAXFEV, * WA(1),MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,IPVT,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 LMDER1. C END SUBROUTINE LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC INTEGER IPVT(N) REAL FTOL,XTOL,GTOL,EPSFCN,FACTOR REAL X(N),FVEC(M),DIAG(N),FJAC(LDFJAC,N),QTF(N),WA1(N),WA2(N), * WA3(N),WA4(M) EXTERNAL FCN C ********** C C SUBROUTINE LMDIF C C THE PURPOSE OF LMDIF IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM. 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 LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, C DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC, C LDFJAC,IPVT,QTF,WA1,WA2,WA3,WA4) 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 LMDIF. 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 FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN IS AT LEAST C MAXFEV BY THE END OF AN ITERATION. C C EPSFCN IS AN INPUT VARIABLE USED IN DETERMINING A SUITABLE C STEP LENGTH FOR THE FORWARD-DIFFERENCE APPROXIMATION. THIS C APPROXIMATION ASSUMES THAT THE RELATIVE ERRORS IN THE C FUNCTIONS ARE OF THE ORDER OF EPSFCN. IF EPSFCN IS LESS C THAN THE MACHINE PRECISION, IT IS ASSUMED THAT THE RELATIVE C ERRORS IN THE FUNCTIONS ARE OF THE ORDER OF THE MACHINE C PRECISION. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN HAS REACHED OR C EXCEEDED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN. C C FJAC IS AN OUTPUT M BY N ARRAY. THE UPPER N BY N SUBMATRIX C OF FJAC CONTAINS AN UPPER TRIANGULAR MATRIX R WITH C DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRAPEZOIDAL C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR C WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,FDJAC2,LMPAR,QRFAC C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,SQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L REAL ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM,ONE,PAR, * PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO,SUM,TEMP,TEMP1, * TEMP2,XNORM,ZERO REAL SPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0E0,1.0E-1,5.0E-1,2.5E-1,7.5E-1,1.0E-4,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. M * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 300 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 300 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 300 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C CALCULATE THE JACOBIAN MATRIX. C IFLAG = 2 CALL FDJAC2(FCN,M,N,X,FVEC,FJAC,LDFJAC,IFLAG,EPSFCN,WA4) NFEV = NFEV + N IF (IFLAG .LT. 0) GO TO 300 C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(M,N,X,FVEC,IFLAG) IF (IFLAG .LT. 0) GO TO 300 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN. C CALL QRFAC(M,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 80 IF (MODE .EQ. 2) GO TO 60 DO 50 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 50 CONTINUE 60 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 70 J = 1, N WA3(J) = DIAG(J)*X(J) 70 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 80 CONTINUE C C FORM (Q TRANSPOSE)*FVEC AND STORE THE FIRST N COMPONENTS IN C QTF. C DO 90 I = 1, M WA4(I) = FVEC(I) 90 CONTINUE DO 130 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 120 SUM = ZERO DO 100 I = J, M SUM = SUM + FJAC(I,J)*WA4(I) 100 CONTINUE TEMP = -SUM/FJAC(J,J) DO 110 I = J, M WA4(I) = WA4(I) + FJAC(I,J)*TEMP 110 CONTINUE 120 CONTINUE FJAC(J,J) = WA1(J) QTF(J) = WA4(J) 130 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 170 DO 160 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 150 SUM = ZERO DO 140 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 140 CONTINUE GNORM = AMAX1(GNORM,ABS(SUM/WA2(L))) 150 CONTINUE 160 CONTINUE 170 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 300 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 190 DO 180 J = 1, N DIAG(J) = AMAX1(DIAG(J),WA2(J)) 180 CONTINUE 190 CONTINUE C C BEGINNING OF THE INNER LOOP. C 200 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 210 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 210 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = AMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 300 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 230 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 220 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 220 CONTINUE 230 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (SQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 240 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*AMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 260 240 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 250 DELTA = PNORM/P5 PAR = P5*PAR 250 CONTINUE 260 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 290 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 270 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 270 CONTINUE DO 280 I = 1, M FVEC(I) = WA4(I) 280 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 290 CONTINUE C C TESTS FOR CONVERGENCE. C IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 300 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (ABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 300 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 200 C C END OF THE OUTER LOOP. C GO TO 30 300 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMDIF. C END 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 SUBROUTINE LMPAR(N,R,LDR,IPVT,DIAG,QTB,DELTA,PAR,X,SDIAG,WA1, * WA2) INTEGER N,LDR INTEGER IPVT(N) REAL DELTA,PAR REAL R(LDR,N),DIAG(N),QTB(N),X(N),SDIAG(N),WA1(N),WA2(N) C ********** C C SUBROUTINE LMPAR C C GIVEN AN M BY N MATRIX A, AN N BY N NONSINGULAR DIAGONAL C MATRIX D, AN M-VECTOR B, AND A POSITIVE NUMBER DELTA, C THE PROBLEM IS TO DETERMINE A VALUE FOR THE PARAMETER C PAR SUCH THAT IF X SOLVES THE SYSTEM C C A*X = B , SQRT(PAR)*D*X = 0 , C C IN THE LEAST SQUARES SENSE, AND DXNORM IS THE EUCLIDEAN C NORM OF D*X, THEN EITHER PAR IS ZERO AND C C (DXNORM-DELTA) .LE. 0.1*DELTA , C C OR PAR IS POSITIVE AND C C ABS(DXNORM-DELTA) .LE. 0.1*DELTA . C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION, WITH COLUMN PIVOTING, OF A. THAT IS, IF C A*P = Q*R, WHERE P IS A PERMUTATION MATRIX, Q HAS ORTHOGONAL C COLUMNS, AND R IS AN UPPER TRIANGULAR MATRIX WITH DIAGONAL C ELEMENTS OF NONINCREASING MAGNITUDE, THEN LMPAR EXPECTS C THE FULL UPPER TRIANGLE OF R, THE PERMUTATION MATRIX P, C AND THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. ON OUTPUT C LMPAR ALSO PROVIDES AN UPPER TRIANGULAR MATRIX S SUCH THAT C C T T T C P *(A *A + PAR*D*D)*P = S *S . C C S IS EMPLOYED WITHIN LMPAR AND MAY BE OF SEPARATE INTEREST. C C ONLY A FEW ITERATIONS ARE GENERALLY NEEDED FOR CONVERGENCE C OF THE ALGORITHM. IF, HOWEVER, THE LIMIT OF 10 ITERATIONS C IS REACHED, THEN THE OUTPUT PAR WILL CONTAIN THE BEST C VALUE OBTAINED SO FAR. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMPAR(N,R,LDR,IPVT,DIAG,QTB,DELTA,PAR,X,SDIAG, C WA1,WA2) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE FULL UPPER TRIANGLE C MUST CONTAIN THE FULL UPPER TRIANGLE OF THE MATRIX R. C ON OUTPUT THE FULL UPPER TRIANGLE IS UNALTERED, AND THE C STRICT LOWER TRIANGLE CONTAINS THE STRICT UPPER TRIANGLE C (TRANSPOSED) OF THE UPPER TRIANGULAR MATRIX S. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C IPVT IS AN INTEGER INPUT ARRAY OF LENGTH N WHICH DEFINES THE C PERMUTATION MATRIX P SUCH THAT A*P = Q*R. COLUMN J OF P C IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C DELTA IS A POSITIVE INPUT VARIABLE WHICH SPECIFIES AN UPPER C BOUND ON THE EUCLIDEAN NORM OF D*X. C C PAR IS A NONNEGATIVE VARIABLE. ON INPUT PAR CONTAINS AN C INITIAL ESTIMATE OF THE LEVENBERG-MARQUARDT PARAMETER. C ON OUTPUT PAR CONTAINS THE FINAL ESTIMATE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE LEAST C SQUARES SOLUTION OF THE SYSTEM A*X = B, SQRT(PAR)*D*X = 0, C FOR THE OUTPUT PAR. C C SDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF THE UPPER TRIANGULAR MATRIX S. C C WA1 AND WA2 ARE WORK ARRAYS OF LENGTH N. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SPMPAR,ENORM,QRSOLV C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,ITER,J,JM1,JP1,K,L,NSING REAL DXNORM,DWARF,FP,GNORM,PARC,PARL,PARU,P1,P001,SUM,TEMP,ZERO REAL SPMPAR,ENORM DATA P1,P001,ZERO /1.0E-1,1.0E-3,0.0E0/ C C DWARF IS THE SMALLEST POSITIVE MAGNITUDE. C DWARF = SPMPAR(2) C C COMPUTE AND STORE IN X THE GAUSS-NEWTON DIRECTION. IF THE C JACOBIAN IS RANK-DEFICIENT, OBTAIN A LEAST SQUARES SOLUTION. C NSING = N DO 10 J = 1, N WA1(J) = QTB(J) IF (R(J,J) .EQ. ZERO .AND. NSING .EQ. N) NSING = J - 1 IF (NSING .LT. N) WA1(J) = ZERO 10 CONTINUE IF (NSING .LT. 1) GO TO 50 DO 40 K = 1, NSING J = NSING - K + 1 WA1(J) = WA1(J)/R(J,J) TEMP = WA1(J) JM1 = J - 1 IF (JM1 .LT. 1) GO TO 30 DO 20 I = 1, JM1 WA1(I) = WA1(I) - R(I,J)*TEMP 20 CONTINUE 30 CONTINUE 40 CONTINUE 50 CONTINUE DO 60 J = 1, N L = IPVT(J) X(L) = WA1(J) 60 CONTINUE C C INITIALIZE THE ITERATION COUNTER. C EVALUATE THE FUNCTION AT THE ORIGIN, AND TEST C FOR ACCEPTANCE OF THE GAUSS-NEWTON DIRECTION. C ITER = 0 DO 70 J = 1, N WA2(J) = DIAG(J)*X(J) 70 CONTINUE DXNORM = ENORM(N,WA2) FP = DXNORM - DELTA IF (FP .LE. P1*DELTA) GO TO 220 C C IF THE JACOBIAN IS NOT RANK DEFICIENT, THE NEWTON C STEP PROVIDES A LOWER BOUND, PARL, FOR THE ZERO OF C THE FUNCTION. OTHERWISE SET THIS BOUND TO ZERO. C PARL = ZERO IF (NSING .LT. N) GO TO 120 DO 80 J = 1, N L = IPVT(J) WA1(J) = DIAG(L)*(WA2(L)/DXNORM) 80 CONTINUE DO 110 J = 1, N SUM = ZERO JM1 = J - 1 IF (JM1 .LT. 1) GO TO 100 DO 90 I = 1, JM1 SUM = SUM + R(I,J)*WA1(I) 90 CONTINUE 100 CONTINUE WA1(J) = (WA1(J) - SUM)/R(J,J) 110 CONTINUE TEMP = ENORM(N,WA1) PARL = ((FP/DELTA)/TEMP)/TEMP 120 CONTINUE C C CALCULATE AN UPPER BOUND, PARU, FOR THE ZERO OF THE FUNCTION. C DO 140 J = 1, N SUM = ZERO DO 130 I = 1, J SUM = SUM + R(I,J)*QTB(I) 130 CONTINUE L = IPVT(J) WA1(J) = SUM/DIAG(L) 140 CONTINUE GNORM = ENORM(N,WA1) PARU = GNORM/DELTA IF (PARU .EQ. ZERO) PARU = DWARF/AMIN1(DELTA,P1) C C IF THE INPUT PAR LIES OUTSIDE OF THE INTERVAL (PARL,PARU), C SET PAR TO THE CLOSER ENDPOINT. C PAR = AMAX1(PAR,PARL) PAR = AMIN1(PAR,PARU) IF (PAR .EQ. ZERO) PAR = GNORM/DXNORM C C BEGINNING OF AN ITERATION. C 150 CONTINUE ITER = ITER + 1 C C EVALUATE THE FUNCTION AT THE CURRENT VALUE OF PAR. C IF (PAR .EQ. ZERO) PAR = AMAX1(DWARF,P001*PARU) TEMP = SQRT(PAR) DO 160 J = 1, N WA1(J) = TEMP*DIAG(J) 160 CONTINUE CALL QRSOLV(N,R,LDR,IPVT,WA1,QTB,X,SDIAG,WA2) DO 170 J = 1, N WA2(J) = DIAG(J)*X(J) 170 CONTINUE DXNORM = ENORM(N,WA2) TEMP = FP FP = DXNORM - DELTA C C IF THE FUNCTION IS SMALL ENOUGH, ACCEPT THE CURRENT VALUE C OF PAR. ALSO TEST FOR THE EXCEPTIONAL CASES WHERE PARL C IS ZERO OR THE NUMBER OF ITERATIONS HAS REACHED 10. C IF (ABS(FP) .LE. P1*DELTA * .OR. PARL .EQ. ZERO .AND. FP .LE. TEMP * .AND. TEMP .LT. ZERO .OR. ITER .EQ. 10) GO TO 220 C C COMPUTE THE NEWTON CORRECTION. C DO 180 J = 1, N L = IPVT(J) WA1(J) = DIAG(L)*(WA2(L)/DXNORM) 180 CONTINUE DO 210 J = 1, N WA1(J) = WA1(J)/SDIAG(J) TEMP = WA1(J) JP1 = J + 1 IF (N .LT. JP1) GO TO 200 DO 190 I = JP1, N WA1(I) = WA1(I) - R(I,J)*TEMP 190 CONTINUE 200 CONTINUE 210 CONTINUE TEMP = ENORM(N,WA1) PARC = ((FP/DELTA)/TEMP)/TEMP C C DEPENDING ON THE SIGN OF THE FUNCTION, UPDATE PARL OR PARU. C IF (FP .GT. ZERO) PARL = AMAX1(PARL,PAR) IF (FP .LT. ZERO) PARU = AMIN1(PARU,PAR) C C COMPUTE AN IMPROVED ESTIMATE FOR PAR. C PAR = AMAX1(PARL,PAR+PARC) C C END OF AN ITERATION. C GO TO 150 220 CONTINUE C C TERMINATION. C IF (ITER .EQ. 0) PAR = ZERO RETURN C C LAST CARD OF SUBROUTINE LMPAR. C END SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, * MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, * IPVT,QTF,WA1,WA2,WA3,WA4) INTEGER M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV INTEGER IPVT(N) LOGICAL SING REAL FTOL,XTOL,GTOL,FACTOR REAL X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N),WA1(N),WA2(N), * WA3(N),WA4(M) C ********** C C SUBROUTINE LMSTR C C THE PURPOSE OF LMSTR IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM WHICH USES MINIMAL STORAGE. C THE USER MUST PROVIDE A SUBROUTINE WHICH CALCULATES THE C FUNCTIONS AND THE ROWS OF THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL, C MAXFEV,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV, C NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C FCN MUST BE DECLARED IN AN EXTERNAL STATEMENT IN THE C USER CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) C INTEGER M,N,IFLAG C REAL X(N),FVEC(M),FJROW(N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. C IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE C JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. 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 LMSTR. 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 FJAC IS AN OUTPUT N BY N ARRAY. THE UPPER TRIANGLE OF FJAC C CONTAINS AN UPPER TRIANGULAR MATRIX R SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRIANGULAR C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C FTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN BOTH THE ACTUAL AND PREDICTED RELATIVE C REDUCTIONS IN THE SUM OF SQUARES ARE AT MOST FTOL. C THEREFORE, FTOL MEASURES THE RELATIVE ERROR DESIRED C IN THE SUM OF SQUARES. C C XTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE RELATIVE ERROR BETWEEN TWO CONSECUTIVE C ITERATES IS AT MOST XTOL. THEREFORE, XTOL MEASURES THE C RELATIVE ERROR DESIRED IN THE APPROXIMATE SOLUTION. C C GTOL IS A NONNEGATIVE INPUT VARIABLE. TERMINATION C OCCURS WHEN THE COSINE OF THE ANGLE BETWEEN FVEC AND C ANY COLUMN OF THE JACOBIAN IS AT MOST GTOL IN ABSOLUTE C VALUE. THEREFORE, GTOL MEASURES THE ORTHOGONALITY C DESIRED BETWEEN THE FUNCTION VECTOR AND THE COLUMNS C OF THE JACOBIAN. C C MAXFEV IS A POSITIVE INTEGER INPUT VARIABLE. TERMINATION C OCCURS WHEN THE NUMBER OF CALLS TO FCN WITH IFLAG = 1 C HAS REACHED MAXFEV. C C DIAG IS AN ARRAY OF LENGTH N. IF MODE = 1 (SEE C BELOW), DIAG IS INTERNALLY SET. IF MODE = 2, DIAG C MUST CONTAIN POSITIVE ENTRIES THAT SERVE AS C MULTIPLICATIVE SCALE FACTORS FOR THE VARIABLES. C C MODE IS AN INTEGER INPUT VARIABLE. IF MODE = 1, THE C VARIABLES WILL BE SCALED INTERNALLY. IF MODE = 2, C THE SCALING IS SPECIFIED BY THE INPUT DIAG. OTHER C VALUES OF MODE ARE EQUIVALENT TO MODE = 1. C C FACTOR IS A POSITIVE INPUT VARIABLE USED IN DETERMINING THE C INITIAL STEP BOUND. THIS BOUND IS SET TO THE PRODUCT OF C FACTOR AND THE EUCLIDEAN NORM OF DIAG*X IF NONZERO, OR ELSE C TO FACTOR ITSELF. IN MOST CASES FACTOR SHOULD LIE IN THE C INTERVAL (.1,100.). 100. IS A GENERALLY RECOMMENDED VALUE. C C NPRINT IS AN INTEGER INPUT VARIABLE THAT ENABLES CONTROLLED C PRINTING OF ITERATES IF IT IS POSITIVE. IN THIS CASE, C FCN IS CALLED WITH IFLAG = 0 AT THE BEGINNING OF THE FIRST C ITERATION AND EVERY NPRINT ITERATIONS THEREAFTER AND C IMMEDIATELY PRIOR TO RETURN, WITH X AND FVEC AVAILABLE C FOR PRINTING. IF NPRINT IS NOT POSITIVE, NO SPECIAL CALLS C OF FCN WITH IFLAG = 0 ARE MADE. 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 BOTH ACTUAL AND PREDICTED RELATIVE REDUCTIONS C IN THE SUM OF SQUARES ARE AT MOST FTOL. C C INFO = 2 RELATIVE ERROR BETWEEN TWO CONSECUTIVE ITERATES C IS AT MOST XTOL. C C INFO = 3 CONDITIONS FOR INFO = 1 AND INFO = 2 BOTH HOLD. C C INFO = 4 THE COSINE OF THE ANGLE BETWEEN FVEC AND ANY C COLUMN OF THE JACOBIAN IS AT MOST GTOL IN C ABSOLUTE VALUE. C C INFO = 5 NUMBER OF CALLS TO FCN WITH IFLAG = 1 HAS C REACHED MAXFEV. C C INFO = 6 FTOL IS TOO SMALL. NO FURTHER REDUCTION IN C THE SUM OF SQUARES IS POSSIBLE. C C INFO = 7 XTOL IS TOO SMALL. NO FURTHER IMPROVEMENT IN C THE APPROXIMATE SOLUTION X IS POSSIBLE. C C INFO = 8 GTOL IS TOO SMALL. FVEC IS ORTHOGONAL TO THE C COLUMNS OF THE JACOBIAN TO MACHINE PRECISION. C C NFEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 1. C C NJEV IS AN INTEGER OUTPUT VARIABLE SET TO THE NUMBER OF C CALLS TO FCN WITH IFLAG = 2. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C QTF IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*FVEC. C C WA1, WA2, AND WA3 ARE WORK ARRAYS OF LENGTH N. C C WA4 IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,LMPAR,QRFAC,RWUPDT C C FORTRAN-SUPPLIED ... ABS,AMAX1,AMIN1,SQRT,MOD C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER I,IFLAG,ITER,J,L REAL ACTRED,DELTA,DIRDER,EPSMCH,FNORM,FNORM1,GNORM,ONE,PAR, * PNORM,PRERED,P1,P5,P25,P75,P0001,RATIO,SUM,TEMP,TEMP1, * TEMP2,XNORM,ZERO REAL SPMPAR,ENORM DATA ONE,P1,P5,P25,P75,P0001,ZERO * /1.0E0,1.0E-1,5.0E-1,2.5E-1,7.5E-1,1.0E-4,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C INFO = 0 IFLAG = 0 NFEV = 0 NJEV = 0 C C CHECK THE INPUT PARAMETERS FOR ERRORS. C IF (N .LE. 0 .OR. M .LT. N .OR. LDFJAC .LT. N * .OR. FTOL .LT. ZERO .OR. XTOL .LT. ZERO .OR. GTOL .LT. ZERO * .OR. MAXFEV .LE. 0 .OR. FACTOR .LE. ZERO) GO TO 340 IF (MODE .NE. 2) GO TO 20 DO 10 J = 1, N IF (DIAG(J) .LE. ZERO) GO TO 340 10 CONTINUE 20 CONTINUE C C EVALUATE THE FUNCTION AT THE STARTING POINT C AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,X,FVEC,WA3,IFLAG) NFEV = 1 IF (IFLAG .LT. 0) GO TO 340 FNORM = ENORM(M,FVEC) C C INITIALIZE LEVENBERG-MARQUARDT PARAMETER AND ITERATION COUNTER. C PAR = ZERO ITER = 1 C C BEGINNING OF THE OUTER LOOP. C 30 CONTINUE C C IF REQUESTED, CALL FCN TO ENABLE PRINTING OF ITERATES. C IF (NPRINT .LE. 0) GO TO 40 IFLAG = 0 IF (MOD(ITER-1,NPRINT) .EQ. 0) CALL FCN(M,N,X,FVEC,WA3,IFLAG) IF (IFLAG .LT. 0) GO TO 340 40 CONTINUE C C COMPUTE THE QR FACTORIZATION OF THE JACOBIAN MATRIX C CALCULATED ONE ROW AT A TIME, WHILE SIMULTANEOUSLY C FORMING (Q TRANSPOSE)*FVEC AND STORING THE FIRST C N COMPONENTS IN QTF. C DO 60 J = 1, N QTF(J) = ZERO DO 50 I = 1, N FJAC(I,J) = ZERO 50 CONTINUE 60 CONTINUE IFLAG = 2 DO 70 I = 1, M CALL FCN(M,N,X,FVEC,WA3,IFLAG) IF (IFLAG .LT. 0) GO TO 340 TEMP = FVEC(I) CALL RWUPDT(N,FJAC,LDFJAC,WA3,QTF,TEMP,WA1,WA2) IFLAG = IFLAG + 1 70 CONTINUE NJEV = NJEV + 1 C C IF THE JACOBIAN IS RANK DEFICIENT, CALL QRFAC TO C REORDER ITS COLUMNS AND UPDATE THE COMPONENTS OF QTF. C SING = .FALSE. DO 80 J = 1, N IF (FJAC(J,J) .EQ. ZERO) SING = .TRUE. IPVT(J) = J WA2(J) = ENORM(J,FJAC(1,J)) 80 CONTINUE IF (.NOT.SING) GO TO 130 CALL QRFAC(N,N,FJAC,LDFJAC,.TRUE.,IPVT,N,WA1,WA2,WA3) DO 120 J = 1, N IF (FJAC(J,J) .EQ. ZERO) GO TO 110 SUM = ZERO DO 90 I = J, N SUM = SUM + FJAC(I,J)*QTF(I) 90 CONTINUE TEMP = -SUM/FJAC(J,J) DO 100 I = J, N QTF(I) = QTF(I) + FJAC(I,J)*TEMP 100 CONTINUE 110 CONTINUE FJAC(J,J) = WA1(J) 120 CONTINUE 130 CONTINUE C C ON THE FIRST ITERATION AND IF MODE IS 1, SCALE ACCORDING C TO THE NORMS OF THE COLUMNS OF THE INITIAL JACOBIAN. C IF (ITER .NE. 1) GO TO 170 IF (MODE .EQ. 2) GO TO 150 DO 140 J = 1, N DIAG(J) = WA2(J) IF (WA2(J) .EQ. ZERO) DIAG(J) = ONE 140 CONTINUE 150 CONTINUE C C ON THE FIRST ITERATION, CALCULATE THE NORM OF THE SCALED X C AND INITIALIZE THE STEP BOUND DELTA. C DO 160 J = 1, N WA3(J) = DIAG(J)*X(J) 160 CONTINUE XNORM = ENORM(N,WA3) DELTA = FACTOR*XNORM IF (DELTA .EQ. ZERO) DELTA = FACTOR 170 CONTINUE C C COMPUTE THE NORM OF THE SCALED GRADIENT. C GNORM = ZERO IF (FNORM .EQ. ZERO) GO TO 210 DO 200 J = 1, N L = IPVT(J) IF (WA2(L) .EQ. ZERO) GO TO 190 SUM = ZERO DO 180 I = 1, J SUM = SUM + FJAC(I,J)*(QTF(I)/FNORM) 180 CONTINUE GNORM = AMAX1(GNORM,ABS(SUM/WA2(L))) 190 CONTINUE 200 CONTINUE 210 CONTINUE C C TEST FOR CONVERGENCE OF THE GRADIENT NORM. C IF (GNORM .LE. GTOL) INFO = 4 IF (INFO .NE. 0) GO TO 340 C C RESCALE IF NECESSARY. C IF (MODE .EQ. 2) GO TO 230 DO 220 J = 1, N DIAG(J) = AMAX1(DIAG(J),WA2(J)) 220 CONTINUE 230 CONTINUE C C BEGINNING OF THE INNER LOOP. C 240 CONTINUE C C DETERMINE THE LEVENBERG-MARQUARDT PARAMETER. C CALL LMPAR(N,FJAC,LDFJAC,IPVT,DIAG,QTF,DELTA,PAR,WA1,WA2, * WA3,WA4) C C STORE THE DIRECTION P AND X + P. CALCULATE THE NORM OF P. C DO 250 J = 1, N WA1(J) = -WA1(J) WA2(J) = X(J) + WA1(J) WA3(J) = DIAG(J)*WA1(J) 250 CONTINUE PNORM = ENORM(N,WA3) C C ON THE FIRST ITERATION, ADJUST THE INITIAL STEP BOUND. C IF (ITER .EQ. 1) DELTA = AMIN1(DELTA,PNORM) C C EVALUATE THE FUNCTION AT X + P AND CALCULATE ITS NORM. C IFLAG = 1 CALL FCN(M,N,WA2,WA4,WA3,IFLAG) NFEV = NFEV + 1 IF (IFLAG .LT. 0) GO TO 340 FNORM1 = ENORM(M,WA4) C C COMPUTE THE SCALED ACTUAL REDUCTION. C ACTRED = -ONE IF (P1*FNORM1 .LT. FNORM) ACTRED = ONE - (FNORM1/FNORM)**2 C C COMPUTE THE SCALED PREDICTED REDUCTION AND C THE SCALED DIRECTIONAL DERIVATIVE. C DO 270 J = 1, N WA3(J) = ZERO L = IPVT(J) TEMP = WA1(L) DO 260 I = 1, J WA3(I) = WA3(I) + FJAC(I,J)*TEMP 260 CONTINUE 270 CONTINUE TEMP1 = ENORM(N,WA3)/FNORM TEMP2 = (SQRT(PAR)*PNORM)/FNORM PRERED = TEMP1**2 + TEMP2**2/P5 DIRDER = -(TEMP1**2 + TEMP2**2) C C COMPUTE THE RATIO OF THE ACTUAL TO THE PREDICTED C REDUCTION. C RATIO = ZERO IF (PRERED .NE. ZERO) RATIO = ACTRED/PRERED C C UPDATE THE STEP BOUND. C IF (RATIO .GT. P25) GO TO 280 IF (ACTRED .GE. ZERO) TEMP = P5 IF (ACTRED .LT. ZERO) * TEMP = P5*DIRDER/(DIRDER + P5*ACTRED) IF (P1*FNORM1 .GE. FNORM .OR. TEMP .LT. P1) TEMP = P1 DELTA = TEMP*AMIN1(DELTA,PNORM/P1) PAR = PAR/TEMP GO TO 300 280 CONTINUE IF (PAR .NE. ZERO .AND. RATIO .LT. P75) GO TO 290 DELTA = PNORM/P5 PAR = P5*PAR 290 CONTINUE 300 CONTINUE C C TEST FOR SUCCESSFUL ITERATION. C IF (RATIO .LT. P0001) GO TO 330 C C SUCCESSFUL ITERATION. UPDATE X, FVEC, AND THEIR NORMS. C DO 310 J = 1, N X(J) = WA2(J) WA2(J) = DIAG(J)*X(J) 310 CONTINUE DO 320 I = 1, M FVEC(I) = WA4(I) 320 CONTINUE XNORM = ENORM(N,WA2) FNORM = FNORM1 ITER = ITER + 1 330 CONTINUE C C TESTS FOR CONVERGENCE. C IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE) INFO = 1 IF (DELTA .LE. XTOL*XNORM) INFO = 2 IF (ABS(ACTRED) .LE. FTOL .AND. PRERED .LE. FTOL * .AND. P5*RATIO .LE. ONE .AND. INFO .EQ. 2) INFO = 3 IF (INFO .NE. 0) GO TO 340 C C TESTS FOR TERMINATION AND STRINGENT TOLERANCES. C IF (NFEV .GE. MAXFEV) INFO = 5 IF (ABS(ACTRED) .LE. EPSMCH .AND. PRERED .LE. EPSMCH * .AND. P5*RATIO .LE. ONE) INFO = 6 IF (DELTA .LE. EPSMCH*XNORM) INFO = 7 IF (GNORM .LE. EPSMCH) INFO = 8 IF (INFO .NE. 0) GO TO 340 C C END OF THE INNER LOOP. REPEAT IF ITERATION UNSUCCESSFUL. C IF (RATIO .LT. P0001) GO TO 240 C C END OF THE OUTER LOOP. C GO TO 30 340 CONTINUE C C TERMINATION, EITHER NORMAL OR USER IMPOSED. C IF (IFLAG .LT. 0) INFO = IFLAG IFLAG = 0 IF (NPRINT .GT. 0) CALL FCN(M,N,X,FVEC,WA3,IFLAG) RETURN C C LAST CARD OF SUBROUTINE LMSTR. C END SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IPVT,WA, * LWA) INTEGER M,N,LDFJAC,INFO,LWA INTEGER IPVT(N) REAL TOL REAL X(N),FVEC(M),FJAC(LDFJAC,N),WA(LWA) EXTERNAL FCN C ********** C C SUBROUTINE LMSTR1 C C THE PURPOSE OF LMSTR1 IS TO MINIMIZE THE SUM OF THE SQUARES OF C M NONLINEAR FUNCTIONS IN N VARIABLES BY A MODIFICATION OF C THE LEVENBERG-MARQUARDT ALGORITHM WHICH USES MINIMAL STORAGE. C THIS IS DONE BY USING THE MORE GENERAL LEAST-SQUARES SOLVER C LMSTR. THE USER MUST PROVIDE A SUBROUTINE WHICH CALCULATES C THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO, C IPVT,WA,LWA) C C WHERE C C FCN IS THE NAME OF THE USER-SUPPLIED SUBROUTINE WHICH C CALCULATES THE FUNCTIONS AND THE ROWS OF THE JACOBIAN. C FCN MUST BE DECLARED IN AN EXTERNAL STATEMENT IN THE C USER CALLING PROGRAM, AND SHOULD BE WRITTEN AS FOLLOWS. C C SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) C INTEGER M,N,IFLAG C REAL X(N),FVEC(M),FJROW(N) C ---------- C IF IFLAG = 1 CALCULATE THE FUNCTIONS AT X AND C RETURN THIS VECTOR IN FVEC. C IF IFLAG = I CALCULATE THE (I-1)-ST ROW OF THE C JACOBIAN AT X AND RETURN THIS VECTOR IN FJROW. 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 LMSTR1. 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 FJAC IS AN OUTPUT N BY N ARRAY. THE UPPER TRIANGLE OF FJAC C CONTAINS AN UPPER TRIANGULAR MATRIX R SUCH THAT C C T T T C P *(JAC *JAC)*P = R *R, C C WHERE P IS A PERMUTATION MATRIX AND JAC IS THE FINAL C CALCULATED JACOBIAN. COLUMN J OF P IS COLUMN IPVT(J) C (SEE BELOW) OF THE IDENTITY MATRIX. THE LOWER TRIANGULAR C PART OF FJAC CONTAINS INFORMATION GENERATED DURING C THE COMPUTATION OF R. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. 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 WITH IFLAG = 1 HAS C REACHED 100*(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 IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH N. IPVT C DEFINES A PERMUTATION MATRIX P SUCH THAT JAC*P = Q*R, C WHERE JAC IS THE FINAL CALCULATED JACOBIAN, Q IS C ORTHOGONAL (NOT STORED), AND R IS UPPER TRIANGULAR. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C WA IS A WORK ARRAY OF LENGTH LWA. C C LWA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN 5*N+M. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... LMSTR C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER MAXFEV,MODE,NFEV,NJEV,NPRINT REAL 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. LDFJAC .LT. N .OR. TOL .LT. ZERO * .OR. LWA .LT. 5*N + M) GO TO 10 C C CALL LMSTR. C MAXFEV = 100*(N + 1) FTOL = TOL XTOL = TOL GTOL = ZERO MODE = 1 NPRINT = 0 CALL LMSTR(FCN,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL,GTOL,MAXFEV, * WA(1),MODE,FACTOR,NPRINT,INFO,NFEV,NJEV,IPVT,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 LMSTR1. C END SUBROUTINE QFORM(M,N,Q,LDQ,WA) INTEGER M,N,LDQ REAL Q(LDQ,M),WA(M) C ********** C C SUBROUTINE QFORM C C THIS SUBROUTINE PROCEEDS FROM THE COMPUTED QR FACTORIZATION OF C AN M BY N MATRIX A TO ACCUMULATE THE M BY M ORTHOGONAL MATRIX C Q FROM ITS FACTORED FORM. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QFORM(M,N,Q,LDQ,WA) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A AND THE ORDER OF Q. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C Q IS AN M BY M ARRAY. ON INPUT THE FULL LOWER TRAPEZOID IN C THE FIRST MIN(M,N) COLUMNS OF Q CONTAINS THE FACTORED FORM. C ON OUTPUT Q HAS BEEN ACCUMULATED INTO A SQUARE MATRIX. C C LDQ IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY Q. C C WA IS A WORK ARRAY OF LENGTH M. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JM1,K,L,MINMN,NP1 REAL ONE,SUM,TEMP,ZERO DATA ONE,ZERO /1.0E0,0.0E0/ C C ZERO OUT UPPER TRIANGLE OF Q IN THE FIRST MIN(M,N) COLUMNS. C MINMN = MIN0(M,N) IF (MINMN .LT. 2) GO TO 30 DO 20 J = 2, MINMN JM1 = J - 1 DO 10 I = 1, JM1 Q(I,J) = ZERO 10 CONTINUE 20 CONTINUE 30 CONTINUE C C INITIALIZE REMAINING COLUMNS TO THOSE OF THE IDENTITY MATRIX. C NP1 = N + 1 IF (M .LT. NP1) GO TO 60 DO 50 J = NP1, M DO 40 I = 1, M Q(I,J) = ZERO 40 CONTINUE Q(J,J) = ONE 50 CONTINUE 60 CONTINUE C C ACCUMULATE Q FROM ITS FACTORED FORM. C DO 120 L = 1, MINMN K = MINMN - L + 1 DO 70 I = K, M WA(I) = Q(I,K) Q(I,K) = ZERO 70 CONTINUE Q(K,K) = ONE IF (WA(K) .EQ. ZERO) GO TO 110 DO 100 J = K, M SUM = ZERO DO 80 I = K, M SUM = SUM + Q(I,J)*WA(I) 80 CONTINUE TEMP = SUM/WA(K) DO 90 I = K, M Q(I,J) = Q(I,J) - TEMP*WA(I) 90 CONTINUE 100 CONTINUE 110 CONTINUE 120 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QFORM. C END SUBROUTINE QRFAC(M,N,A,LDA,PIVOT,IPVT,LIPVT,RDIAG,ACNORM,WA) INTEGER M,N,LDA,LIPVT INTEGER IPVT(LIPVT) LOGICAL PIVOT REAL A(LDA,N),RDIAG(N),ACNORM(N),WA(N) C ********** C C SUBROUTINE QRFAC C C THIS SUBROUTINE USES HOUSEHOLDER TRANSFORMATIONS WITH COLUMN C PIVOTING (OPTIONAL) TO COMPUTE A QR FACTORIZATION OF THE C M BY N MATRIX A. THAT IS, QRFAC DETERMINES AN ORTHOGONAL C MATRIX Q, A PERMUTATION MATRIX P, AND AN UPPER TRAPEZOIDAL C MATRIX R WITH DIAGONAL ELEMENTS OF NONINCREASING MAGNITUDE, C SUCH THAT A*P = Q*R. THE HOUSEHOLDER TRANSFORMATION FOR C COLUMN K, K = 1,2,...,MIN(M,N), IS OF THE FORM C C T C I - (1/U(K))*U*U C C WHERE U HAS ZEROS IN THE FIRST K-1 POSITIONS. THE FORM OF C THIS TRANSFORMATION AND THE METHOD OF PIVOTING FIRST C APPEARED IN THE CORRESPONDING LINPACK SUBROUTINE. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QRFAC(M,N,A,LDA,PIVOT,IPVT,LIPVT,RDIAG,ACNORM,WA) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C A IS AN M BY N ARRAY. ON INPUT A CONTAINS THE MATRIX FOR C WHICH THE QR FACTORIZATION IS TO BE COMPUTED. ON OUTPUT C THE STRICT UPPER TRAPEZOIDAL PART OF A CONTAINS THE STRICT C UPPER TRAPEZOIDAL PART OF R, AND THE LOWER TRAPEZOIDAL C PART OF A CONTAINS A FACTORED FORM OF Q (THE NON-TRIVIAL C ELEMENTS OF THE U VECTORS DESCRIBED ABOVE). C C LDA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY A. C C PIVOT IS A LOGICAL INPUT VARIABLE. IF PIVOT IS SET TRUE, C THEN COLUMN PIVOTING IS ENFORCED. IF PIVOT IS SET FALSE, C THEN NO COLUMN PIVOTING IS DONE. C C IPVT IS AN INTEGER OUTPUT ARRAY OF LENGTH LIPVT. IPVT C DEFINES THE PERMUTATION MATRIX P SUCH THAT A*P = Q*R. C COLUMN J OF P IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C IF PIVOT IS FALSE, IPVT IS NOT REFERENCED. C C LIPVT IS A POSITIVE INTEGER INPUT VARIABLE. IF PIVOT IS FALSE, C THEN LIPVT MAY BE AS SMALL AS 1. IF PIVOT IS TRUE, THEN C LIPVT MUST BE AT LEAST N. C C RDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF R. C C ACNORM IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C NORMS OF THE CORRESPONDING COLUMNS OF THE INPUT MATRIX A. C IF THIS INFORMATION IS NOT NEEDED, THEN ACNORM CAN COINCIDE C WITH RDIAG. C C WA IS A WORK ARRAY OF LENGTH N. IF PIVOT IS FALSE, THEN WA C CAN COINCIDE WITH RDIAG. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SPMPAR,ENORM C C FORTRAN-SUPPLIED ... AMAX1,SQRT,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JP1,K,KMAX,MINMN REAL AJNORM,EPSMCH,ONE,P05,SUM,TEMP,ZERO REAL SPMPAR,ENORM DATA ONE,P05,ZERO /1.0E0,5.0E-2,0.0E0/ C C EPSMCH IS THE MACHINE PRECISION. C EPSMCH = SPMPAR(1) C C COMPUTE THE INITIAL COLUMN NORMS AND INITIALIZE SEVERAL ARRAYS. C DO 10 J = 1, N ACNORM(J) = ENORM(M,A(1,J)) RDIAG(J) = ACNORM(J) WA(J) = RDIAG(J) IF (PIVOT) IPVT(J) = J 10 CONTINUE C C REDUCE A TO R WITH HOUSEHOLDER TRANSFORMATIONS. C MINMN = MIN0(M,N) DO 110 J = 1, MINMN IF (.NOT.PIVOT) GO TO 40 C C BRING THE COLUMN OF LARGEST NORM INTO THE PIVOT POSITION. C KMAX = J DO 20 K = J, N IF (RDIAG(K) .GT. RDIAG(KMAX)) KMAX = K 20 CONTINUE IF (KMAX .EQ. J) GO TO 40 DO 30 I = 1, M TEMP = A(I,J) A(I,J) = A(I,KMAX) A(I,KMAX) = TEMP 30 CONTINUE RDIAG(KMAX) = RDIAG(J) WA(KMAX) = WA(J) K = IPVT(J) IPVT(J) = IPVT(KMAX) IPVT(KMAX) = K 40 CONTINUE C C COMPUTE THE HOUSEHOLDER TRANSFORMATION TO REDUCE THE C J-TH COLUMN OF A TO A MULTIPLE OF THE J-TH UNIT VECTOR. C AJNORM = ENORM(M-J+1,A(J,J)) IF (AJNORM .EQ. ZERO) GO TO 100 IF (A(J,J) .LT. ZERO) AJNORM = -AJNORM DO 50 I = J, M A(I,J) = A(I,J)/AJNORM 50 CONTINUE A(J,J) = A(J,J) + ONE C C APPLY THE TRANSFORMATION TO THE REMAINING COLUMNS C AND UPDATE THE NORMS. C JP1 = J + 1 IF (N .LT. JP1) GO TO 100 DO 90 K = JP1, N SUM = ZERO DO 60 I = J, M SUM = SUM + A(I,J)*A(I,K) 60 CONTINUE TEMP = SUM/A(J,J) DO 70 I = J, M A(I,K) = A(I,K) - TEMP*A(I,J) 70 CONTINUE IF (.NOT.PIVOT .OR. RDIAG(K) .EQ. ZERO) GO TO 80 TEMP = A(J,K)/RDIAG(K) RDIAG(K) = RDIAG(K)*SQRT(AMAX1(ZERO,ONE-TEMP**2)) IF (P05*(RDIAG(K)/WA(K))**2 .GT. EPSMCH) GO TO 80 RDIAG(K) = ENORM(M-J,A(JP1,K)) WA(K) = RDIAG(K) 80 CONTINUE 90 CONTINUE 100 CONTINUE RDIAG(J) = -AJNORM 110 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QRFAC. C END SUBROUTINE QRSOLV(N,R,LDR,IPVT,DIAG,QTB,X,SDIAG,WA) INTEGER N,LDR INTEGER IPVT(N) REAL R(LDR,N),DIAG(N),QTB(N),X(N),SDIAG(N),WA(N) C ********** C C SUBROUTINE QRSOLV C C GIVEN AN M BY N MATRIX A, AN N BY N DIAGONAL MATRIX D, C AND AN M-VECTOR B, THE PROBLEM IS TO DETERMINE AN X WHICH C SOLVES THE SYSTEM C C A*X = B , D*X = 0 , C C IN THE LEAST SQUARES SENSE. C C THIS SUBROUTINE COMPLETES THE SOLUTION OF THE PROBLEM C IF IT IS PROVIDED WITH THE NECESSARY INFORMATION FROM THE C QR FACTORIZATION, WITH COLUMN PIVOTING, OF A. THAT IS, IF C A*P = Q*R, WHERE P IS A PERMUTATION MATRIX, Q HAS ORTHOGONAL C COLUMNS, AND R IS AN UPPER TRIANGULAR MATRIX WITH DIAGONAL C ELEMENTS OF NONINCREASING MAGNITUDE, THEN QRSOLV EXPECTS C THE FULL UPPER TRIANGLE OF R, THE PERMUTATION MATRIX P, C AND THE FIRST N COMPONENTS OF (Q TRANSPOSE)*B. THE SYSTEM C A*X = B, D*X = 0, IS THEN EQUIVALENT TO C C T T C R*Z = Q *B , P *D*P*Z = 0 , C C WHERE X = P*Z. IF THIS SYSTEM DOES NOT HAVE FULL RANK, C THEN A LEAST SQUARES SOLUTION IS OBTAINED. ON OUTPUT QRSOLV C ALSO PROVIDES AN UPPER TRIANGULAR MATRIX S SUCH THAT C C T T T C P *(A *A + D*D)*P = S *S . C C S IS COMPUTED WITHIN QRSOLV AND MAY BE OF SEPARATE INTEREST. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE QRSOLV(N,R,LDR,IPVT,DIAG,QTB,X,SDIAG,WA) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE FULL UPPER TRIANGLE C MUST CONTAIN THE FULL UPPER TRIANGLE OF THE MATRIX R. C ON OUTPUT THE FULL UPPER TRIANGLE IS UNALTERED, AND THE C STRICT LOWER TRIANGLE CONTAINS THE STRICT UPPER TRIANGLE C (TRANSPOSED) OF THE UPPER TRIANGULAR MATRIX S. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C IPVT IS AN INTEGER INPUT ARRAY OF LENGTH N WHICH DEFINES THE C PERMUTATION MATRIX P SUCH THAT A*P = Q*R. COLUMN J OF P C IS COLUMN IPVT(J) OF THE IDENTITY MATRIX. C C DIAG IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE C DIAGONAL ELEMENTS OF THE MATRIX D. C C QTB IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE FIRST C N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*B. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE LEAST C SQUARES SOLUTION OF THE SYSTEM A*X = B, D*X = 0. C C SDIAG IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C DIAGONAL ELEMENTS OF THE UPPER TRIANGULAR MATRIX S. C C WA IS A WORK ARRAY OF LENGTH N. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ABS,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,JP1,K,KP1,L,NSING REAL COS,COTAN,P5,P25,QTBPJ,SIN,SUM,TAN,TEMP,ZERO DATA P5,P25,ZERO /5.0E-1,2.5E-1,0.0E0/ C C COPY R AND (Q TRANSPOSE)*B TO PRESERVE INPUT AND INITIALIZE S. C IN PARTICULAR, SAVE THE DIAGONAL ELEMENTS OF R IN X. C DO 20 J = 1, N DO 10 I = J, N R(I,J) = R(J,I) 10 CONTINUE X(J) = R(J,J) WA(J) = QTB(J) 20 CONTINUE C C ELIMINATE THE DIAGONAL MATRIX D USING A GIVENS ROTATION. C DO 100 J = 1, N C C PREPARE THE ROW OF D TO BE ELIMINATED, LOCATING THE C DIAGONAL ELEMENT USING P FROM THE QR FACTORIZATION. C L = IPVT(J) IF (DIAG(L) .EQ. ZERO) GO TO 90 DO 30 K = J, N SDIAG(K) = ZERO 30 CONTINUE SDIAG(J) = DIAG(L) C C THE TRANSFORMATIONS TO ELIMINATE THE ROW OF D C MODIFY ONLY A SINGLE ELEMENT OF (Q TRANSPOSE)*B C BEYOND THE FIRST N, WHICH IS INITIALLY ZERO. C QTBPJ = ZERO DO 80 K = J, N C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C APPROPRIATE ELEMENT IN THE CURRENT ROW OF D. C IF (SDIAG(K) .EQ. ZERO) GO TO 70 IF (ABS(R(K,K)) .GE. ABS(SDIAG(K))) GO TO 40 COTAN = R(K,K)/SDIAG(K) SIN = P5/SQRT(P25+P25*COTAN**2) COS = SIN*COTAN GO TO 50 40 CONTINUE TAN = SDIAG(K)/R(K,K) COS = P5/SQRT(P25+P25*TAN**2) SIN = COS*TAN 50 CONTINUE C C COMPUTE THE MODIFIED DIAGONAL ELEMENT OF R AND C THE MODIFIED ELEMENT OF ((Q TRANSPOSE)*B,0). C R(K,K) = COS*R(K,K) + SIN*SDIAG(K) TEMP = COS*WA(K) + SIN*QTBPJ QTBPJ = -SIN*WA(K) + COS*QTBPJ WA(K) = TEMP C C ACCUMULATE THE TRANFORMATION IN THE ROW OF S. C KP1 = K + 1 IF (N .LT. KP1) GO TO 70 DO 60 I = KP1, N TEMP = COS*R(I,K) + SIN*SDIAG(I) SDIAG(I) = -SIN*R(I,K) + COS*SDIAG(I) R(I,K) = TEMP 60 CONTINUE 70 CONTINUE 80 CONTINUE 90 CONTINUE C C STORE THE DIAGONAL ELEMENT OF S AND RESTORE C THE CORRESPONDING DIAGONAL ELEMENT OF R. C SDIAG(J) = R(J,J) R(J,J) = X(J) 100 CONTINUE C C SOLVE THE TRIANGULAR SYSTEM FOR Z. IF THE SYSTEM IS C SINGULAR, THEN OBTAIN A LEAST SQUARES SOLUTION. C NSING = N DO 110 J = 1, N IF (SDIAG(J) .EQ. ZERO .AND. NSING .EQ. N) NSING = J - 1 IF (NSING .LT. N) WA(J) = ZERO 110 CONTINUE IF (NSING .LT. 1) GO TO 150 DO 140 K = 1, NSING J = NSING - K + 1 SUM = ZERO JP1 = J + 1 IF (NSING .LT. JP1) GO TO 130 DO 120 I = JP1, NSING SUM = SUM + R(I,J)*WA(I) 120 CONTINUE 130 CONTINUE WA(J) = (WA(J) - SUM)/SDIAG(J) 140 CONTINUE 150 CONTINUE C C PERMUTE THE COMPONENTS OF Z BACK TO COMPONENTS OF X. C DO 160 J = 1, N L = IPVT(J) X(L) = WA(J) 160 CONTINUE RETURN C C LAST CARD OF SUBROUTINE QRSOLV. C END SUBROUTINE RWUPDT(N,R,LDR,W,B,ALPHA,COS,SIN) INTEGER N,LDR REAL ALPHA REAL R(LDR,N),W(N),B(N),COS(N),SIN(N) C ********** C C SUBROUTINE RWUPDT C C GIVEN AN N BY N UPPER TRIANGULAR MATRIX R, THIS SUBROUTINE C COMPUTES THE QR DECOMPOSITION OF THE MATRIX FORMED WHEN A ROW C IS ADDED TO R. IF THE ROW IS SPECIFIED BY THE VECTOR W, THEN C RWUPDT DETERMINES AN ORTHOGONAL MATRIX Q SUCH THAT WHEN THE C N+1 BY N MATRIX COMPOSED OF R AUGMENTED BY W IS PREMULTIPLIED C BY (Q TRANSPOSE), THE RESULTING MATRIX IS UPPER TRAPEZOIDAL. C THE MATRIX (Q TRANSPOSE) IS THE PRODUCT OF N TRANSFORMATIONS C C G(N)*G(N-1)* ... *G(1) C C WHERE G(I) IS A GIVENS ROTATION IN THE (I,N+1) PLANE WHICH C ELIMINATES ELEMENTS IN THE (N+1)-ST PLANE. RWUPDT ALSO C COMPUTES THE PRODUCT (Q TRANSPOSE)*C WHERE C IS THE C (N+1)-VECTOR (B,ALPHA). Q ITSELF IS NOT ACCUMULATED, RATHER C THE INFORMATION TO RECOVER THE G ROTATIONS IS SUPPLIED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE RWUPDT(N,R,LDR,W,B,ALPHA,COS,SIN) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE ORDER OF R. C C R IS AN N BY N ARRAY. ON INPUT THE UPPER TRIANGULAR PART OF C R MUST CONTAIN THE MATRIX TO BE UPDATED. ON OUTPUT R C CONTAINS THE UPDATED TRIANGULAR MATRIX. C C LDR IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY R. C C W IS AN INPUT ARRAY OF LENGTH N WHICH MUST CONTAIN THE ROW C VECTOR TO BE ADDED TO R. C C B IS AN ARRAY OF LENGTH N. ON INPUT B MUST CONTAIN THE C FIRST N ELEMENTS OF THE VECTOR C. ON OUTPUT B CONTAINS C THE FIRST N ELEMENTS OF THE VECTOR (Q TRANSPOSE)*C. C C ALPHA IS A VARIABLE. ON INPUT ALPHA MUST CONTAIN THE C (N+1)-ST ELEMENT OF THE VECTOR C. ON OUTPUT ALPHA CONTAINS C THE (N+1)-ST ELEMENT OF THE VECTOR (Q TRANSPOSE)*C. C C COS IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C COSINES OF THE TRANSFORMING GIVENS ROTATIONS. C C SIN IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE C SINES OF THE TRANSFORMING GIVENS ROTATIONS. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ABS,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, DUDLEY V. GOETSCHEL, KENNETH E. HILLSTROM, C JORGE J. MORE C C ********** INTEGER I,J,JM1 REAL COTAN,ONE,P5,P25,ROWJ,TAN,TEMP,ZERO DATA ONE,P5,P25,ZERO /1.0E0,5.0E-1,2.5E-1,0.0E0/ C DO 60 J = 1, N ROWJ = W(J) JM1 = J - 1 C C APPLY THE PREVIOUS TRANSFORMATIONS TO C R(I,J), I=1,2,...,J-1, AND TO W(J). C IF (JM1 .LT. 1) GO TO 20 DO 10 I = 1, JM1 TEMP = COS(I)*R(I,J) + SIN(I)*ROWJ ROWJ = -SIN(I)*R(I,J) + COS(I)*ROWJ R(I,J) = TEMP 10 CONTINUE 20 CONTINUE C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES W(J). C COS(J) = ONE SIN(J) = ZERO IF (ROWJ .EQ. ZERO) GO TO 50 IF (ABS(R(J,J)) .GE. ABS(ROWJ)) GO TO 30 COTAN = R(J,J)/ROWJ SIN(J) = P5/SQRT(P25+P25*COTAN**2) COS(J) = SIN(J)*COTAN GO TO 40 30 CONTINUE TAN = ROWJ/R(J,J) COS(J) = P5/SQRT(P25+P25*TAN**2) SIN(J) = COS(J)*TAN 40 CONTINUE C C APPLY THE CURRENT TRANSFORMATION TO R(J,J), B(J), AND ALPHA. C R(J,J) = COS(J)*R(J,J) + SIN(J)*ROWJ TEMP = COS(J)*B(J) + SIN(J)*ALPHA ALPHA = -SIN(J)*B(J) + COS(J)*ALPHA B(J) = TEMP 50 CONTINUE 60 CONTINUE RETURN C C LAST CARD OF SUBROUTINE RWUPDT. C END SUBROUTINE R1MPYQ(M,N,A,LDA,V,W) INTEGER M,N,LDA REAL A(LDA,N),V(N),W(N) C ********** C C SUBROUTINE R1MPYQ C C GIVEN AN M BY N MATRIX A, THIS SUBROUTINE COMPUTES A*Q WHERE C Q IS THE PRODUCT OF 2*(N - 1) TRANSFORMATIONS C C GV(N-1)*...*GV(1)*GW(1)*...*GW(N-1) C C AND GV(I), GW(I) ARE GIVENS ROTATIONS IN THE (I,N) PLANE WHICH C ELIMINATE ELEMENTS IN THE I-TH AND N-TH PLANES, RESPECTIVELY. C Q ITSELF IS NOT GIVEN, RATHER THE INFORMATION TO RECOVER THE C GV, GW ROTATIONS IS SUPPLIED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE R1MPYQ(M,N,A,LDA,V,W) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF A. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF A. C C A IS AN M BY N ARRAY. ON INPUT A MUST CONTAIN THE MATRIX C TO BE POSTMULTIPLIED BY THE ORTHOGONAL MATRIX Q C DESCRIBED ABOVE. ON OUTPUT A*Q HAS REPLACED A. C C LDA IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY A. C C V IS AN INPUT ARRAY OF LENGTH N. V(I) MUST CONTAIN THE C INFORMATION NECESSARY TO RECOVER THE GIVENS ROTATION GV(I) C DESCRIBED ABOVE. C C W IS AN INPUT ARRAY OF LENGTH N. W(I) MUST CONTAIN THE C INFORMATION NECESSARY TO RECOVER THE GIVENS ROTATION GW(I) C DESCRIBED ABOVE. C C SUBROUTINES CALLED C C FORTRAN-SUPPLIED ... ABS,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,J,NMJ,NM1 REAL COS,ONE,SIN,TEMP DATA ONE /1.0E0/ C C APPLY THE FIRST SET OF GIVENS ROTATIONS TO A. C NM1 = N - 1 IF (NM1 .LT. 1) GO TO 50 DO 20 NMJ = 1, NM1 J = N - NMJ IF (ABS(V(J)) .GT. ONE) COS = ONE/V(J) IF (ABS(V(J)) .GT. ONE) SIN = SQRT(ONE-COS**2) IF (ABS(V(J)) .LE. ONE) SIN = V(J) IF (ABS(V(J)) .LE. ONE) COS = SQRT(ONE-SIN**2) DO 10 I = 1, M TEMP = COS*A(I,J) - SIN*A(I,N) A(I,N) = SIN*A(I,J) + COS*A(I,N) A(I,J) = TEMP 10 CONTINUE 20 CONTINUE C C APPLY THE SECOND SET OF GIVENS ROTATIONS TO A. C DO 40 J = 1, NM1 IF (ABS(W(J)) .GT. ONE) COS = ONE/W(J) IF (ABS(W(J)) .GT. ONE) SIN = SQRT(ONE-COS**2) IF (ABS(W(J)) .LE. ONE) SIN = W(J) IF (ABS(W(J)) .LE. ONE) COS = SQRT(ONE-SIN**2) DO 30 I = 1, M TEMP = COS*A(I,J) + SIN*A(I,N) A(I,N) = -SIN*A(I,J) + COS*A(I,N) A(I,J) = TEMP 30 CONTINUE 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE R1MPYQ. C END SUBROUTINE R1UPDT(M,N,S,LS,U,V,W,SING) INTEGER M,N,LS LOGICAL SING REAL S(LS),U(M),V(N),W(M) C ********** C C SUBROUTINE R1UPDT C C GIVEN AN M BY N LOWER TRAPEZOIDAL MATRIX S, AN M-VECTOR U, C AND AN N-VECTOR V, THE PROBLEM IS TO DETERMINE AN C ORTHOGONAL MATRIX Q SUCH THAT C C T C (S + U*V )*Q C C IS AGAIN LOWER TRAPEZOIDAL. C C THIS SUBROUTINE DETERMINES Q AS THE PRODUCT OF 2*(N - 1) C TRANSFORMATIONS C C GV(N-1)*...*GV(1)*GW(1)*...*GW(N-1) C C WHERE GV(I), GW(I) ARE GIVENS ROTATIONS IN THE (I,N) PLANE C WHICH ELIMINATE ELEMENTS IN THE I-TH AND N-TH PLANES, C RESPECTIVELY. Q ITSELF IS NOT ACCUMULATED, RATHER THE C INFORMATION TO RECOVER THE GV, GW ROTATIONS IS RETURNED. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE R1UPDT(M,N,S,LS,U,V,W,SING) C C WHERE C C M IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF ROWS OF S. C C N IS A POSITIVE INTEGER INPUT VARIABLE SET TO THE NUMBER C OF COLUMNS OF S. N MUST NOT EXCEED M. C C S IS AN ARRAY OF LENGTH LS. ON INPUT S MUST CONTAIN THE LOWER C TRAPEZOIDAL MATRIX S STORED BY COLUMNS. ON OUTPUT S CONTAINS C THE LOWER TRAPEZOIDAL MATRIX PRODUCED AS DESCRIBED ABOVE. C C LS IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN C (N*(2*M-N+1))/2. C C U IS AN INPUT ARRAY OF LENGTH M WHICH MUST CONTAIN THE C VECTOR U. C C V IS AN ARRAY OF LENGTH N. ON INPUT V MUST CONTAIN THE VECTOR C V. ON OUTPUT V(I) CONTAINS THE INFORMATION NECESSARY TO C RECOVER THE GIVENS ROTATION GV(I) DESCRIBED ABOVE. C C W IS AN OUTPUT ARRAY OF LENGTH M. W(I) CONTAINS INFORMATION C NECESSARY TO RECOVER THE GIVENS ROTATION GW(I) DESCRIBED C ABOVE. C C SING IS A LOGICAL OUTPUT VARIABLE. SING IS SET TRUE IF ANY C OF THE DIAGONAL ELEMENTS OF THE OUTPUT S ARE ZERO. OTHERWISE C SING IS SET FALSE. C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SPMPAR C C FORTRAN-SUPPLIED ... ABS,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE, C JOHN L. NAZARETH C C ********** INTEGER I,J,JJ,L,NMJ,NM1 REAL COS,COTAN,GIANT,ONE,P5,P25,SIN,TAN,TAU,TEMP,ZERO REAL SPMPAR DATA ONE,P5,P25,ZERO /1.0E0,5.0E-1,2.5E-1,0.0E0/ C C GIANT IS THE LARGEST MAGNITUDE. C GIANT = SPMPAR(3) C C INITIALIZE THE DIAGONAL ELEMENT POINTER. C JJ = (N*(2*M - N + 1))/2 - (M - N) C C MOVE THE NONTRIVIAL PART OF THE LAST COLUMN OF S INTO W. C L = JJ DO 10 I = N, M W(I) = S(L) L = L + 1 10 CONTINUE C C ROTATE THE VECTOR V INTO A MULTIPLE OF THE N-TH UNIT VECTOR C IN SUCH A WAY THAT A SPIKE IS INTRODUCED INTO W. C NM1 = N - 1 IF (NM1 .LT. 1) GO TO 70 DO 60 NMJ = 1, NM1 J = N - NMJ JJ = JJ - (M - J + 1) W(J) = ZERO IF (V(J) .EQ. ZERO) GO TO 50 C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C J-TH ELEMENT OF V. C IF (ABS(V(N)) .GE. ABS(V(J))) GO TO 20 COTAN = V(N)/V(J) SIN = P5/SQRT(P25+P25*COTAN**2) COS = SIN*COTAN TAU = ONE IF (ABS(COS)*GIANT .GT. ONE) TAU = ONE/COS GO TO 30 20 CONTINUE TAN = V(J)/V(N) COS = P5/SQRT(P25+P25*TAN**2) SIN = COS*TAN TAU = SIN 30 CONTINUE C C APPLY THE TRANSFORMATION TO V AND STORE THE INFORMATION C NECESSARY TO RECOVER THE GIVENS ROTATION. C V(N) = SIN*V(J) + COS*V(N) V(J) = TAU C C APPLY THE TRANSFORMATION TO S AND EXTEND THE SPIKE IN W. C L = JJ DO 40 I = J, M TEMP = COS*S(L) - SIN*W(I) W(I) = SIN*S(L) + COS*W(I) S(L) = TEMP L = L + 1 40 CONTINUE 50 CONTINUE 60 CONTINUE 70 CONTINUE C C ADD THE SPIKE FROM THE RANK 1 UPDATE TO W. C DO 80 I = 1, M W(I) = W(I) + V(N)*U(I) 80 CONTINUE C C ELIMINATE THE SPIKE. C SING = .FALSE. IF (NM1 .LT. 1) GO TO 140 DO 130 J = 1, NM1 IF (W(J) .EQ. ZERO) GO TO 120 C C DETERMINE A GIVENS ROTATION WHICH ELIMINATES THE C J-TH ELEMENT OF THE SPIKE. C IF (ABS(S(JJ)) .GE. ABS(W(J))) GO TO 90 COTAN = S(JJ)/W(J) SIN = P5/SQRT(P25+P25*COTAN**2) COS = SIN*COTAN TAU = ONE IF (ABS(COS)*GIANT .GT. ONE) TAU = ONE/COS GO TO 100 90 CONTINUE TAN = W(J)/S(JJ) COS = P5/SQRT(P25+P25*TAN**2) SIN = COS*TAN TAU = SIN 100 CONTINUE C C APPLY THE TRANSFORMATION TO S AND REDUCE THE SPIKE IN W. C L = JJ DO 110 I = J, M TEMP = COS*S(L) + SIN*W(I) W(I) = -SIN*S(L) + COS*W(I) S(L) = TEMP L = L + 1 110 CONTINUE C C STORE THE INFORMATION NECESSARY TO RECOVER THE C GIVENS ROTATION. C W(J) = TAU 120 CONTINUE C C TEST FOR ZERO DIAGONAL ELEMENTS IN THE OUTPUT S. C IF (S(JJ) .EQ. ZERO) SING = .TRUE. JJ = JJ + (M - J + 1) 130 CONTINUE 140 CONTINUE C C MOVE W BACK INTO THE LAST COLUMN OF THE OUTPUT S. C L = JJ DO 150 I = N, M S(L) = W(I) L = L + 1 150 CONTINUE IF (S(JJ) .EQ. ZERO) SING = .TRUE. RETURN C C LAST CARD OF SUBROUTINE R1UPDT. C END minpack-19961126/ex/thybrd1.f0000644000175000017500000000312611616327304016447 0ustar sylvestresylvestreC DRIVER FOR HYBRD1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,INFO,LWA,NWRITE DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(9),FVEC(9),WA(180) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LWA = 180 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL HYBRD1(FCN,N,X,FVEC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRD1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) C C SUBROUTINE FCN FOR HYBRD1 EXAMPLE. C INTEGER K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.D0,1.D0,2.D0,3.D0/ C DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file160000644000175000017500000005477204210375171015746 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE SOLUTION OF N NONLINEAR C EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER AND AN C INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, CALLS THE C NONLINEAR EQUATION SOLVER, AND FINALLY PRINTS OUT INFORMATION C ON THE PERFORMANCE OF THE SOLVER. THIS IS ONLY A SAMPLE DRIVER, C MANY OTHER DRIVERS ARE POSSIBLE. THE INTERFACE SUBROUTINE FCN C IS NECESSARY TO TAKE INTO ACCOUNT THE FORMS OF CALLING C SEQUENCES USED BY THE FUNCTION AND JACOBIAN SUBROUTINES IN C THE VARIOUS NONLINEAR EQUATION SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,HYBRJ1,INITPT,VECFCN C C FORTRAN-SUPPLIED ... DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,N,NFEV,NJEV,NPROB,NREAD,NTRIES, 1 NWRITE INTEGER NA(60),NF(60),NJ(60),NP(60),NX(60) DOUBLE PRECISION FACTOR,FNORM1,FNORM2,ONE,TEN,TOL DOUBLE PRECISION FNM(60),FJAC(40,40),FVEC(40),WA(1060),X(40) DOUBLE PRECISION DPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0D0,1.0D1/ TOL = DSQRT(DPMPAR(1)) LDFJAC = 40 LWA = 1060 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL VECFCN(N,X,FVEC,NPROB) FNORM1 = ENORM(N,FVEC) WRITE (NWRITE,60) NPROB,N NFEV = 0 NJEV = 0 CALL HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) FNORM2 = ENORM(N,FVEC) NP(IC) = NPROB NA(IC) = N NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) 1 FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (3I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 10H DIMENSION, I5, 5X //) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, D15.7 // 5X, 1 33H FINAL L2 NORM OF THE RESIDUALS , D15.7 // 5X, 2 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, 3 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, 4 15H EXIT PARAMETER, 18X, I10 // 5X, 5 27H FINAL APPROXIMATE SOLUTION // (5X, 5D15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO HYBRJ1 /) 90 FORMAT (46H NPROB N NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (I4, I6, 2I7, I6, 1X, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C EQUATION SOLVER. FCN SHOULD ONLY CALL THE TESTING FUNCTION C AND JACOBIAN SUBROUTINES VECFCN AND VECJAC WITH THE C APPROPRIATE VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... VECFCN,VECJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL VECFCN(N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL VECJAC(N,X,FJAC,LDFJAC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE VECJAC(N,X,FJAC,LDFJAC,NPROB) INTEGER N,LDFJAC,NPROB DOUBLE PRECISION X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE VECJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF FOURTEEN C TEST FUNCTIONS. THE PROBLEM DIMENSIONS ARE AS DESCRIBED C IN THE PROLOGUE COMMENTS OF VECFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECJAC(N,X,FJAC,LDFJAC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER VARIABLE. C C X IS AN ARRAY OF LENGTH N. C C FJAC IS AN N BY N ARRAY. ON OUTPUT FJAC CONTAINS THE C JACOBIAN MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER VARIABLE NOT LESS THAN N C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DMIN1,DSIN,DSQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,K1,K2,ML,MU DOUBLE PRECISION C1,C3,C4,C5,C6,C9,EIGHT,FIFTN,FIVE,FOUR,H, * HUNDRD,ONE,PROD,SIX,SUM,SUM1,SUM2,TEMP,TEMP1, * TEMP2,TEMP3,TEMP4,TEN,THREE,TI,TJ,TK,TPI, * TWENTY,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,SIX,EIGHT,TEN,FIFTN,TWENTY, * HUNDRD * /0.0D0,1.0D0,2.0D0,3.0D0,4.0D0,5.0D0,6.0D0,8.0D0,1.0D1, * 1.5D1,2.0D1,1.0D2/ DATA C1,C3,C4,C5,C6,C9 /1.0D4,2.0D2,2.02D1,1.98D1,1.8D2,2.9D1/ DFLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,20,50,60,90,100,200,230,290,320,350,380,420,450), * NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FJAC(1,1) = -ONE FJAC(1,2) = ZERO FJAC(2,1) = -TWENTY*X(1) FJAC(2,2) = TEN GO TO 490 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE DO 40 K = 1, 4 DO 30 J = 1, 4 FJAC(K,J) = ZERO 30 CONTINUE 40 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = DSQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*DSQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 490 C C POWELL BADLY SCALED FUNCTION. C 50 CONTINUE FJAC(1,1) = C1*X(2) FJAC(1,2) = C1*X(1) FJAC(2,1) = -DEXP(-X(1)) FJAC(2,2) = -DEXP(-X(2)) GO TO 490 C C WOOD FUNCTION. C 60 CONTINUE DO 80 K = 1, 4 DO 70 J = 1, 4 FJAC(K,J) = ZERO 70 CONTINUE 80 CONTINUE TEMP1 = X(2) - THREE*X(1)**2 TEMP2 = X(4) - THREE*X(3)**2 FJAC(1,1) = -C3*TEMP1 + ONE FJAC(1,2) = -C3*X(1) FJAC(2,1) = -TWO*C3*X(1) FJAC(2,2) = C3 + C4 FJAC(2,4) = C5 FJAC(3,3) = -C6*TEMP2 + ONE FJAC(3,4) = -C6*X(3) FJAC(4,2) = C5 FJAC(4,3) = -TWO*C6*X(3) FJAC(4,4) = C6 + C4 GO TO 490 C C HELICAL VALLEY FUNCTION. C 90 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP = X(1)**2 + X(2)**2 TEMP1 = TPI*TEMP TEMP2 = DSQRT(TEMP) FJAC(1,1) = HUNDRD*X(2)/TEMP1 FJAC(1,2) = -HUNDRD*X(1)/TEMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TEMP2 FJAC(2,2) = TEN*X(2)/TEMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 490 C C WATSON FUNCTION. C 100 CONTINUE DO 120 K = 1, N DO 110 J = K, N FJAC(K,J) = ZERO 110 CONTINUE 120 CONTINUE DO 170 I = 1, 29 TI = DFLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 130 J = 2, N SUM1 = SUM1 + DFLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 130 CONTINUE SUM2 = ZERO TEMP = ONE DO 140 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 140 CONTINUE TEMP1 = TWO*(SUM1 - SUM2**2 - ONE) TEMP2 = TWO*SUM2 TEMP = TI**2 TK = ONE DO 160 K = 1, N TJ = TK DO 150 J = K, N FJAC(K,J) = FJAC(K,J) * + TJ * *((DFLOAT(K-1)/TI - TEMP2) * *(DFLOAT(J-1)/TI - TEMP2) - TEMP1) TJ = TI*TJ 150 CONTINUE TK = TEMP*TK 160 CONTINUE 170 CONTINUE FJAC(1,1) = FJAC(1,1) + SIX*X(1)**2 - TWO*X(2) + THREE FJAC(1,2) = FJAC(1,2) - TWO*X(1) FJAC(2,2) = FJAC(2,2) + ONE DO 190 K = 1, N DO 180 J = K, N FJAC(J,K) = FJAC(K,J) 180 CONTINUE 190 CONTINUE GO TO 490 C C CHEBYQUAD FUNCTION. C 200 CONTINUE TK = ONE/DFLOAT(N) DO 220 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 TEMP3 = ZERO TEMP4 = TWO DO 210 K = 1, N FJAC(K,J) = TK*TEMP4 TI = FOUR*TEMP2 + TEMP*TEMP4 - TEMP3 TEMP3 = TEMP4 TEMP4 = TI TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 210 CONTINUE 220 CONTINUE GO TO 490 C C BROWN ALMOST-LINEAR FUNCTION. C 230 CONTINUE PROD = ONE DO 250 J = 1, N PROD = X(J)*PROD DO 240 K = 1, N FJAC(K,J) = ONE 240 CONTINUE FJAC(J,J) = TWO 250 CONTINUE DO 280 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 270 TEMP = ONE PROD = ONE DO 260 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 260 CONTINUE 270 CONTINUE FJAC(N,J) = PROD/TEMP 280 CONTINUE GO TO 490 C C DISCRETE BOUNDARY VALUE FUNCTION. C 290 CONTINUE H = ONE/DFLOAT(N+1) DO 310 K = 1, N TEMP = THREE*(X(K) + DFLOAT(K)*H + ONE)**2 DO 300 J = 1, N FJAC(K,J) = ZERO 300 CONTINUE FJAC(K,K) = TWO + TEMP*H**2/TWO IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -ONE 310 CONTINUE GO TO 490 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 320 CONTINUE H = ONE/DFLOAT(N+1) DO 340 K = 1, N TK = DFLOAT(K)*H DO 330 J = 1, N TJ = DFLOAT(J)*H TEMP = THREE*(X(J) + TJ + ONE)**2 FJAC(K,J) = H*DMIN1(TJ*(ONE-TK),TK*(ONE-TJ))*TEMP/TWO 330 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 340 CONTINUE GO TO 490 C C TRIGONOMETRIC FUNCTION. C 350 CONTINUE DO 370 J = 1, N TEMP = DSIN(X(J)) DO 360 K = 1, N FJAC(K,J) = TEMP 360 CONTINUE FJAC(J,J) = DFLOAT(J+1)*TEMP - DCOS(X(J)) 370 CONTINUE GO TO 490 C C VARIABLY DIMENSIONED FUNCTION. C 380 CONTINUE SUM = ZERO DO 390 J = 1, N SUM = SUM + DFLOAT(J)*(X(J) - ONE) 390 CONTINUE TEMP = ONE + SIX*SUM**2 DO 410 K = 1, N DO 400 J = K, N FJAC(K,J) = DFLOAT(K*J)*TEMP FJAC(J,K) = FJAC(K,J) 400 CONTINUE FJAC(K,K) = FJAC(K,K) + ONE 410 CONTINUE GO TO 490 C C BROYDEN TRIDIAGONAL FUNCTION. C 420 CONTINUE DO 440 K = 1, N DO 430 J = 1, N FJAC(K,J) = ZERO 430 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 440 CONTINUE GO TO 490 C C BROYDEN BANDED FUNCTION. C 450 CONTINUE ML = 5 MU = 1 DO 480 K = 1, N DO 460 J = 1, N FJAC(K,J) = ZERO 460 CONTINUE K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) DO 470 J = K1, K2 IF (J .NE. K) FJAC(K,J) = -(ONE + TWO*X(J)) 470 CONTINUE FJAC(K,K) = TWO + FIFTN*X(K)**2 480 CONTINUE 490 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR C THE FUNCTIONS DEFINED BY SUBROUTINE VECFCN. THE SUBROUTINE C RETURNS IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING C POINT. FOR THE SIXTH FUNCTION THE STANDARD STARTING POINT IS C ZERO, SO IN THIS CASE, IF FACTOR IS NOT UNITY, THEN THE C SUBROUTINE RETURNS THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,H,HALF,ONE,THREE,TJ,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,THREE,C1 /0.0D0,5.0D-1,1.0D0,3.0D0,1.2D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,20,30,40,50,60,80,100,120,120,140,160,180,180), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE X(1) = -C1 X(2) = ONE GO TO 200 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 200 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE X(1) = ZERO X(2) = ONE GO TO 200 C C WOOD FUNCTION. C 40 CONTINUE X(1) = -THREE X(2) = -ONE X(3) = -THREE X(4) = -ONE GO TO 200 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 200 C C WATSON FUNCTION. C 60 CONTINUE DO 70 J = 1, N X(J) = ZERO 70 CONTINUE GO TO 200 C C CHEBYQUAD FUNCTION. C 80 CONTINUE H = ONE/DFLOAT(N+1) DO 90 J = 1, N X(J) = DFLOAT(J)*H 90 CONTINUE GO TO 200 C C BROWN ALMOST-LINEAR FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = HALF 110 CONTINUE GO TO 200 C C DISCRETE BOUNDARY VALUE AND INTEGRAL EQUATION FUNCTIONS. C 120 CONTINUE H = ONE/DFLOAT(N+1) DO 130 J = 1, N TJ = DFLOAT(J)*H X(J) = TJ*(TJ - ONE) 130 CONTINUE GO TO 200 C C TRIGONOMETRIC FUNCTION. C 140 CONTINUE H = ONE/DFLOAT(N) DO 150 J = 1, N X(J) = H 150 CONTINUE GO TO 200 C C VARIABLY DIMENSIONED FUNCTION. C 160 CONTINUE H = ONE/DFLOAT(N) DO 170 J = 1, N X(J) = ONE - DFLOAT(J)*H 170 CONTINUE GO TO 200 C C BROYDEN TRIDIAGONAL AND BANDED FUNCTIONS. C 180 CONTINUE DO 190 J = 1, N X(J) = -ONE 190 CONTINUE 200 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 250 IF (NPROB .EQ. 6) GO TO 220 DO 210 J = 1, N X(J) = FACTOR*X(J) 210 CONTINUE GO TO 240 220 CONTINUE DO 230 J = 1, N X(J) = FACTOR 230 CONTINUE 240 CONTINUE 250 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE VECFCN(N,X,FVEC,NPROB) INTEGER N,NPROB DOUBLE PRECISION X(N),FVEC(N) C ********** C C SUBROUTINE VECFCN C C THIS SUBROUTINE DEFINES FOURTEEN TEST FUNCTIONS. THE FIRST C FIVE TEST FUNCTIONS ARE OF DIMENSIONS 2,4,2,4,3, RESPECTIVELY, C WHILE THE REMAINING TEST FUNCTIONS ARE OF VARIABLE DIMENSION C N FOR ANY N GREATER THAN OR EQUAL TO 1 (PROBLEM 6 IS AN C EXCEPTION TO THIS, SINCE IT DOES NOT ALLOW N = 1). C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE VECFCN(N,X,FVEC,NPROB) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE NPROB C FUNCTION VECTOR EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 14. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIGN,DSIN,DSQRT, C MAX0,MIN0 C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,K,K1,K2,KP1,ML,MU DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,EIGHT,FIVE,H,ONE, * PROD,SUM,SUM1,SUM2,TEMP,TEMP1,TEMP2,TEN,THREE, * TI,TJ,TK,TPI,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FIVE,EIGHT,TEN * /0.0D0,1.0D0,2.0D0,3.0D0,5.0D0,8.0D0,1.0D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9 * /1.0D4,1.0001D0,2.0D2,2.02D1,1.98D1,1.8D2,2.5D-1,5.0D-1, * 2.9D1/ DFLOAT(IVAR) = IVAR C C PROBLEM SELECTOR. C GO TO (10,20,30,40,50,60,120,170,200,220,270,300,330,350), NPROB C C ROSENBROCK FUNCTION. C 10 CONTINUE FVEC(1) = ONE - X(1) FVEC(2) = TEN*(X(2) - X(1)**2) GO TO 380 C C POWELL SINGULAR FUNCTION. C 20 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 380 C C POWELL BADLY SCALED FUNCTION. C 30 CONTINUE FVEC(1) = C1*X(1)*X(2) - ONE FVEC(2) = DEXP(-X(1)) + DEXP(-X(2)) - C2 GO TO 380 C C WOOD FUNCTION. C 40 CONTINUE TEMP1 = X(2) - X(1)**2 TEMP2 = X(4) - X(3)**2 FVEC(1) = -C3*X(1)*TEMP1 - (ONE - X(1)) FVEC(2) = C3*TEMP1 + C4*(X(2) - ONE) + C5*(X(4) - ONE) FVEC(3) = -C6*X(3)*TEMP2 - (ONE - X(3)) FVEC(4) = C6*TEMP2 + C4*(X(4) - ONE) + C5*(X(2) - ONE) GO TO 380 C C HELICAL VALLEY FUNCTION. C 50 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP1 = DSIGN(C7,X(2)) IF (X(1) .GT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TEMP1 = DATAN(X(2)/X(1))/TPI + C8 TEMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TEMP1) FVEC(2) = TEN*(TEMP2 - ONE) FVEC(3) = X(3) GO TO 380 C C WATSON FUNCTION. C 60 CONTINUE DO 70 K = 1, N FVEC(K) = ZERO 70 CONTINUE DO 110 I = 1, 29 TI = DFLOAT(I)/C9 SUM1 = ZERO TEMP = ONE DO 80 J = 2, N SUM1 = SUM1 + DFLOAT(J-1)*TEMP*X(J) TEMP = TI*TEMP 80 CONTINUE SUM2 = ZERO TEMP = ONE DO 90 J = 1, N SUM2 = SUM2 + TEMP*X(J) TEMP = TI*TEMP 90 CONTINUE TEMP1 = SUM1 - SUM2**2 - ONE TEMP2 = TWO*TI*SUM2 TEMP = ONE/TI DO 100 K = 1, N FVEC(K) = FVEC(K) + TEMP*(DFLOAT(K-1) - TEMP2)*TEMP1 TEMP = TI*TEMP 100 CONTINUE 110 CONTINUE TEMP = X(2) - X(1)**2 - ONE FVEC(1) = FVEC(1) + X(1)*(ONE - TWO*TEMP) FVEC(2) = FVEC(2) + TEMP GO TO 380 C C CHEBYQUAD FUNCTION. C 120 CONTINUE DO 130 K = 1, N FVEC(K) = ZERO 130 CONTINUE DO 150 J = 1, N TEMP1 = ONE TEMP2 = TWO*X(J) - ONE TEMP = TWO*TEMP2 DO 140 I = 1, N FVEC(I) = FVEC(I) + TEMP2 TI = TEMP*TEMP2 - TEMP1 TEMP1 = TEMP2 TEMP2 = TI 140 CONTINUE 150 CONTINUE TK = ONE/DFLOAT(N) IEV = -1 DO 160 K = 1, N FVEC(K) = TK*FVEC(K) IF (IEV .GT. 0) FVEC(K) = FVEC(K) + ONE/(DFLOAT(K)**2 - ONE) IEV = -IEV 160 CONTINUE GO TO 380 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 180 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 180 CONTINUE DO 190 K = 1, N FVEC(K) = X(K) + SUM 190 CONTINUE FVEC(N) = PROD - ONE GO TO 380 C C DISCRETE BOUNDARY VALUE FUNCTION. C 200 CONTINUE H = ONE/DFLOAT(N+1) DO 210 K = 1, N TEMP = (X(K) + DFLOAT(K)*H + ONE)**3 TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TWO*X(K) - TEMP1 - TEMP2 + TEMP*H**2/TWO 210 CONTINUE GO TO 380 C C DISCRETE INTEGRAL EQUATION FUNCTION. C 220 CONTINUE H = ONE/DFLOAT(N+1) DO 260 K = 1, N TK = DFLOAT(K)*H SUM1 = ZERO DO 230 J = 1, K TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM1 = SUM1 + TJ*TEMP 230 CONTINUE SUM2 = ZERO KP1 = K + 1 IF (N .LT. KP1) GO TO 250 DO 240 J = KP1, N TJ = DFLOAT(J)*H TEMP = (X(J) + TJ + ONE)**3 SUM2 = SUM2 + (ONE - TJ)*TEMP 240 CONTINUE 250 CONTINUE FVEC(K) = X(K) + H*((ONE - TK)*SUM1 + TK*SUM2)/TWO 260 CONTINUE GO TO 380 C C TRIGONOMETRIC FUNCTION. C 270 CONTINUE SUM = ZERO DO 280 J = 1, N FVEC(J) = DCOS(X(J)) SUM = SUM + FVEC(J) 280 CONTINUE DO 290 K = 1, N FVEC(K) = DFLOAT(N+K) - DSIN(X(K)) - SUM - DFLOAT(K)*FVEC(K) 290 CONTINUE GO TO 380 C C VARIABLY DIMENSIONED FUNCTION. C 300 CONTINUE SUM = ZERO DO 310 J = 1, N SUM = SUM + DFLOAT(J)*(X(J) - ONE) 310 CONTINUE TEMP = SUM*(ONE + TWO*SUM**2) DO 320 K = 1, N FVEC(K) = X(K) - ONE + DFLOAT(K)*TEMP 320 CONTINUE GO TO 380 C C BROYDEN TRIDIAGONAL FUNCTION. C 330 CONTINUE DO 340 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 340 CONTINUE GO TO 380 C C BROYDEN BANDED FUNCTION. C 350 CONTINUE ML = 5 MU = 1 DO 370 K = 1, N K1 = MAX0(1,K-ML) K2 = MIN0(K+MU,N) TEMP = ZERO DO 360 J = K1, K2 IF (J .NE. K) TEMP = TEMP + X(J)*(ONE + X(J)) 360 CONTINUE FVEC(K) = X(K)*(TWO + FIVE*X(K)**2) + ONE - TEMP 370 CONTINUE 380 CONTINUE RETURN C C LAST CARD OF SUBROUTINE VECFCN. C END minpack-19961126/ex/file170000644000175000017500000006662304210375215015744 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,INITPT,LMDER1,SSQFCN C C FORTRAN-SUPPLIED ... DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES, * NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) DOUBLE PRECISION FACTOR,FNORM1,FNORM2,ONE,TEN,TOL DOUBLE PRECISION FJAC(65,40),FNM(60),FVEC(65),WA(265),X(40) DOUBLE PRECISION DPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0D0,1.0D1/ TOL = DSQRT(DPMPAR(1)) LDFJAC = 65 LWA = 265 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IWA,WA, * LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, D15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , D15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5D15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMDER1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 1X, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST-SQUARES SOLVER. FCN SHOULD ONLY CALL THE TESTING C FUNCTION AND JACOBIAN SUBROUTINES SSQFCN AND SSQJAC WITH C THE APPROPRIATE VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN,SSQJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) INTEGER M,N,LDFJAC,NPROB DOUBLE PRECISION X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE SSQJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF EIGHTEEN C NONLINEAR LEAST SQUARES PROBLEMS. THE PROBLEM DIMENSIONS ARE C AS DESCRIBED IN THE PROLOGUE COMMENTS OF SSQFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FJAC IS AN M BY N OUTPUT ARRAY WHICH CONTAINS THE JACOBIAN C MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIN,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,MM1,NM1 DOUBLE PRECISION C14,C20,C29,C45,C100,DIV,DX,EIGHT,FIVE,FOUR, * ONE,PROD,S2,TEMP,TEN,THREE,TI,TMP1,TMP2,TMP3, * TMP4,TPI,TWO,ZERO DOUBLE PRECISION V(11) DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,EIGHT,TEN,C14,C20,C29,C45,C100 * /0.0D0,1.0D0,2.0D0,3.0D0,4.0D0,5.0D0,8.0D0,1.0D1,1.4D1, * 2.0D1,2.9D1,4.5D1,1.0D2/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0D0,2.0D0,1.0D0,5.0D-1,2.5D-1,1.67D-1,1.25D-1,1.0D-1, * 8.33D-2,7.14D-2,6.25D-2/ DFLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,40,70,130,140,150,180,190,210,230,250,310,330,350,370, * 400,460,480), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE TEMP = TWO/DFLOAT(M) DO 30 J = 1, N DO 20 I = 1, M FJAC(I,J) = -TEMP 20 CONTINUE FJAC(J,J) = FJAC(J,J) + ONE 30 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE DO 60 J = 1, N DO 50 I = 1, M FJAC(I,J) = DFLOAT(I)*DFLOAT(J) 50 CONTINUE 60 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE DO 90 J = 1, N DO 80 I = 1, M FJAC(I,J) = ZERO 80 CONTINUE 90 CONTINUE NM1 = N - 1 MM1 = M - 1 IF (NM1 .LT. 2) GO TO 120 DO 110 J = 2, NM1 DO 100 I = 2, MM1 FJAC(I,J) = DFLOAT(I-1)*DFLOAT(J) 100 CONTINUE 110 CONTINUE 120 CONTINUE GO TO 500 C C ROSENBROCK FUNCTION. C 130 CONTINUE FJAC(1,1) = -C20*X(1) FJAC(1,2) = TEN FJAC(2,1) = -ONE FJAC(2,2) = ZERO GO TO 500 C C HELICAL VALLEY FUNCTION. C 140 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP = X(1)**2 + X(2)**2 TMP1 = TPI*TEMP TMP2 = DSQRT(TEMP) FJAC(1,1) = C100*X(2)/TMP1 FJAC(1,2) = -C100*X(1)/TMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TMP2 FJAC(2,2) = TEN*X(2)/TMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 500 C C POWELL SINGULAR FUNCTION. C 150 CONTINUE DO 170 J = 1, 4 DO 160 I = 1, 4 FJAC(I,J) = ZERO 160 CONTINUE 170 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = DSQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*DSQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 500 C C FREUDENSTEIN AND ROTH FUNCTION. C 180 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = X(2)*(TEN - THREE*X(2)) - TWO FJAC(2,1) = ONE FJAC(2,2) = X(2)*(TWO + THREE*X(2)) - C14 GO TO 500 C C BARD FUNCTION. C 190 CONTINUE DO 200 I = 1, 15 TMP1 = DFLOAT(I) TMP2 = DFLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -ONE FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 200 CONTINUE GO TO 500 C C KOWALIK AND OSBORNE FUNCTION. C 210 CONTINUE DO 220 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FJAC(I,1) = -TMP1/TMP2 FJAC(I,2) = -V(I)*X(1)/TMP2 FJAC(I,3) = FJAC(I,1)*FJAC(I,2) FJAC(I,4) = FJAC(I,3)/V(I) 220 CONTINUE GO TO 500 C C MEYER FUNCTION. C 230 CONTINUE DO 240 I = 1, 16 TEMP = FIVE*DFLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = DEXP(TMP1) FJAC(I,1) = TMP2 FJAC(I,2) = X(1)*TMP2/TEMP FJAC(I,3) = -TMP1*FJAC(I,2) 240 CONTINUE GO TO 500 C C WATSON FUNCTION. C 250 CONTINUE DO 280 I = 1, 29 DIV = DFLOAT(I)/C29 S2 = ZERO DX = ONE DO 260 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 260 CONTINUE TEMP = TWO*DIV*S2 DX = ONE/DIV DO 270 J = 1, N FJAC(I,J) = DX*(DFLOAT(J-1) - TEMP) DX = DIV*DX 270 CONTINUE 280 CONTINUE DO 300 J = 1, N DO 290 I = 30, 31 FJAC(I,J) = ZERO 290 CONTINUE 300 CONTINUE FJAC(30,1) = ONE FJAC(31,1) = -TWO*X(1) FJAC(31,2) = ONE GO TO 500 C C BOX 3-DIMENSIONAL FUNCTION. C 310 CONTINUE DO 320 I = 1, M TEMP = DFLOAT(I) TMP1 = TEMP/TEN FJAC(I,1) = -TMP1*DEXP(-TMP1*X(1)) FJAC(I,2) = TMP1*DEXP(-TMP1*X(2)) FJAC(I,3) = DEXP(-TEMP) - DEXP(-TMP1) 320 CONTINUE GO TO 500 C C JENNRICH AND SAMPSON FUNCTION. C 330 CONTINUE DO 340 I = 1, M TEMP = DFLOAT(I) FJAC(I,1) = -TEMP*DEXP(TEMP*X(1)) FJAC(I,2) = -TEMP*DEXP(TEMP*X(2)) 340 CONTINUE GO TO 500 C C BROWN AND DENNIS FUNCTION. C 350 CONTINUE DO 360 I = 1, M TEMP = DFLOAT(I)/FIVE TI = DSIN(TEMP) TMP1 = X(1) + TEMP*X(2) - DEXP(TEMP) TMP2 = X(3) + TI*X(4) - DCOS(TEMP) FJAC(I,1) = TWO*TMP1 FJAC(I,2) = TEMP*FJAC(I,1) FJAC(I,3) = TWO*TMP2 FJAC(I,4) = TI*FJAC(I,3) 360 CONTINUE GO TO 500 C C CHEBYQUAD FUNCTION. C 370 CONTINUE DX = ONE/DFLOAT(N) DO 390 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 TMP3 = ZERO TMP4 = TWO DO 380 I = 1, M FJAC(I,J) = DX*TMP4 TI = FOUR*TMP2 + TEMP*TMP4 - TMP3 TMP3 = TMP4 TMP4 = TI TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 380 CONTINUE 390 CONTINUE GO TO 500 C C BROWN ALMOST-LINEAR FUNCTION. C 400 CONTINUE PROD = ONE DO 420 J = 1, N PROD = X(J)*PROD DO 410 I = 1, N FJAC(I,J) = ONE 410 CONTINUE FJAC(J,J) = TWO 420 CONTINUE DO 450 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 440 TEMP = ONE PROD = ONE DO 430 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 430 CONTINUE 440 CONTINUE FJAC(N,J) = PROD/TEMP 450 CONTINUE GO TO 500 C C OSBORNE 1 FUNCTION. C 460 CONTINUE DO 470 I = 1, 33 TEMP = TEN*DFLOAT(I-1) TMP1 = DEXP(-X(4)*TEMP) TMP2 = DEXP(-X(5)*TEMP) FJAC(I,1) = -ONE FJAC(I,2) = -TMP1 FJAC(I,3) = -TMP2 FJAC(I,4) = TEMP*X(2)*TMP1 FJAC(I,5) = TEMP*X(3)*TMP2 470 CONTINUE GO TO 500 C C OSBORNE 2 FUNCTION. C 480 CONTINUE DO 490 I = 1, 65 TEMP = DFLOAT(I-1)/TEN TMP1 = DEXP(-X(5)*TEMP) TMP2 = DEXP(-X(6)*(TEMP-X(9))**2) TMP3 = DEXP(-X(7)*(TEMP-X(10))**2) TMP4 = DEXP(-X(8)*(TEMP-X(11))**2) FJAC(I,1) = -TMP1 FJAC(I,2) = -TMP2 FJAC(I,3) = -TMP3 FJAC(I,4) = -TMP4 FJAC(I,5) = TEMP*X(1)*TMP1 FJAC(I,6) = X(2)*(TEMP - X(9))**2*TMP2 FJAC(I,7) = X(3)*(TEMP - X(10))**2*TMP3 FJAC(I,8) = X(4)*(TEMP - X(11))**2*TMP4 FJAC(I,9) = -TWO*X(2)*X(6)*(TEMP - X(9))*TMP2 FJAC(I,10) = -TWO*X(3)*X(7)*(TEMP - X(10))*TMP3 FJAC(I,11) = -TWO*X(4)*X(8)*(TEMP - X(11))*TMP4 490 CONTINUE 500 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14, * C15,C16,C17,FIVE,H,HALF,ONE,SEVEN,TEN,THREE, * TWENTY,TWNTF,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0D0,5.0D-1,1.0D0,2.0D0,3.0D0,5.0D0,7.0D0,1.0D1,2.0D1, * 2.5D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2D0,2.5D-1,3.9D-1,4.15D-1,2.0D-2,4.0D3,2.5D2,3.0D-1, * 4.0D-1,1.5D0,1.0D-2,1.3D0,6.5D-1,7.0D-1,6.0D-1,4.5D0, * 5.5D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/DFLOAT(N+1) DO 160 J = 1, N X(J) = DFLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB DOUBLE PRECISION X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIN,DSQRT,DSIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 DOUBLE PRECISION C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM, * S1,S2,TEMP,TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO, * ZERO,ZP25,ZP5 DOUBLE PRECISION V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) DOUBLE PRECISION DFLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0D0,2.5D-1,5.0D-1,1.0D0,2.0D0,5.0D0,8.0D0,1.0D1,1.3D1, * 1.4D1,2.9D1,4.5D1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0D0,2.0D0,1.0D0,5.0D-1,2.5D-1,1.67D-1,1.25D-1,1.0D-1, * 8.33D-2,7.14D-2,6.25D-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957D-1,1.947D-1,1.735D-1,1.6D-1,8.44D-2,6.27D-2,4.56D-2, * 3.42D-2,3.23D-2,2.35D-2,2.46D-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478D4,2.861D4,2.365D4,1.963D4,1.637D4,1.372D4,1.154D4, * 9.744D3,8.261D3,7.03D3,6.005D3,5.147D3,4.427D3,3.82D3, * 3.307D3,2.872D3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44D-1,9.08D-1,9.32D-1,9.36D-1,9.25D-1,9.08D-1,8.81D-1, * 8.5D-1,8.18D-1,7.84D-1,7.51D-1,7.18D-1,6.85D-1,6.58D-1, * 6.28D-1,6.03D-1,5.8D-1,5.58D-1,5.38D-1,5.22D-1,5.06D-1, * 4.9D-1,4.78D-1,4.67D-1,4.57D-1,4.48D-1,4.38D-1,4.31D-1, * 4.24D-1,4.2D-1,4.14D-1,4.11D-1,4.06D-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366D0,1.191D0,1.112D0,1.013D0,9.91D-1,8.85D-1,8.31D-1, * 8.47D-1,7.86D-1,7.25D-1,7.46D-1,6.79D-1,6.08D-1,6.55D-1, * 6.16D-1,6.06D-1,6.02D-1,6.26D-1,6.51D-1,7.24D-1,6.49D-1, * 6.49D-1,6.94D-1,6.44D-1,6.24D-1,6.61D-1,6.12D-1,5.58D-1, * 5.33D-1,4.95D-1,5.0D-1,4.23D-1,3.95D-1,3.75D-1,3.72D-1, * 3.91D-1,3.96D-1,4.05D-1,4.28D-1,4.29D-1,5.23D-1,5.62D-1, * 6.07D-1,6.53D-1,6.72D-1,7.08D-1,6.33D-1,6.68D-1,6.45D-1, * 6.32D-1,5.91D-1,5.59D-1,5.97D-1,6.25D-1,7.39D-1,7.1D-1, * 7.29D-1,7.2D-1,6.36D-1,5.81D-1,4.28D-1,2.92D-1,1.62D-1, * 9.8D-2,5.4D-2/ DFLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/DFLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + DFLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = DFLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + DFLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = DFLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*DATAN(ONE) TMP1 = DSIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI + ZP5 TMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = DFLOAT(I) TMP2 = DFLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*DFLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = DEXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = DFLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + DFLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = DFLOAT(I) TMP1 = TEMP/TEN FVEC(I) = DEXP(-TMP1*X(1)) - DEXP(-TMP1*X(2)) * + (DEXP(-TEMP) - DEXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = DFLOAT(I) FVEC(I) = TWO + TWO*TEMP - DEXP(TEMP*X(1)) - DEXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = DFLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - DEXP(TEMP) TMP2 = X(3) + DSIN(TEMP)*X(4) - DCOS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/DFLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(DFLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*DFLOAT(I-1) TMP1 = DEXP(-X(4)*TEMP) TMP2 = DEXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = DFLOAT(I-1)/TEN TMP1 = DEXP(-X(5)*TEMP) TMP2 = DEXP(-X(6)*(TEMP-X(9))**2) TMP3 = DEXP(-X(7)*(TEMP-X(10))**2) TMP4 = DEXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END minpack-19961126/ex/file220000644000175000017500000000114104210375465015727 0ustar sylvestresylvestre 1 5 10 1 1 5 50 1 2 5 10 1 2 5 50 1 3 5 10 1 3 5 50 1 4 2 2 3 5 3 3 3 6 4 4 3 7 2 2 3 8 3 15 3 9 4 11 3 10 3 16 2 11 6 31 3 11 9 31 3 11 12 31 3 12 3 10 1 13 2 10 1 14 4 20 3 15 1 8 3 15 8 8 1 15 9 9 1 15 10 10 1 16 10 10 3 16 30 30 1 16 40 40 1 17 5 33 1 18 11 65 1 0 0 0 0 minpack-19961126/ex/thybrd.f0000644000175000017500000000431011616327304016362 0ustar sylvestresylvestreC DRIVER FOR HYBRD EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR,NWRITE DOUBLE PRECISION XTOL,EPSFCN,FACTOR,FNORM DOUBLE PRECISION X(9),FVEC(9),DIAG(9),FJAC(9,9),R(45),QTF(9), * WA1(9),WA2(9),WA3(9),WA4(9) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LR = 45 C C SET XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C XTOL = DSQRT(DPMPAR(1)) C MAXFEV = 2000 ML = 1 MU = 1 EPSFCN = 0.D0 MODE = 2 DO 20 J = 1, 9 DIAG(J) = 1.D0 20 CONTINUE FACTOR = 1.D2 NPRINT = 0 C CALL HYBRD(FCN,N,X,FVEC,XTOL,MAXFEV,ML,MU,EPSFCN,DIAG, * MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * R,LR,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRD EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,IFLAG) INTEGER N,IFLAG DOUBLE PRECISION X(N),FVEC(N) C C SUBROUTINE FCN FOR HYBRD EXAMPLE. C INTEGER K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE /0.D0,1.D0,2.D0,3.D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file190000644000175000017500000004517204210375301015736 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,INITPT,LMDIF1,SSQFCN C C FORTRAN-SUPPLIED ... DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES,NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) DOUBLE PRECISION FACTOR,FNORM1,FNORM2,ONE,TEN,TOL DOUBLE PRECISION FNM(60),FVEC(65),WA(2865),X(40) DOUBLE PRECISION DPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0D0,1.0D1/ TOL = DSQRT(DPMPAR(1)) LWA = 2865 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMDIF1(FCN,M,N,X,FVEC,TOL,INFO,IWA,WA,LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJEV = NJEV/N NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, D15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , D15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5D15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMDIF1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 1X, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST-SQUARES SOLVER. FCN SHOULD ONLY CALL THE TESTING C FUNCTION SUBROUTINE SSQFCN WITH THE APPROPRIATE VALUE OF C PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB DOUBLE PRECISION X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIN,DSQRT,DSIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 DOUBLE PRECISION C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM, * S1,S2,TEMP,TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO, * ZERO,ZP25,ZP5 DOUBLE PRECISION V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) DOUBLE PRECISION DFLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0D0,2.5D-1,5.0D-1,1.0D0,2.0D0,5.0D0,8.0D0,1.0D1,1.3D1, * 1.4D1,2.9D1,4.5D1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0D0,2.0D0,1.0D0,5.0D-1,2.5D-1,1.67D-1,1.25D-1,1.0D-1, * 8.33D-2,7.14D-2,6.25D-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957D-1,1.947D-1,1.735D-1,1.6D-1,8.44D-2,6.27D-2,4.56D-2, * 3.42D-2,3.23D-2,2.35D-2,2.46D-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478D4,2.861D4,2.365D4,1.963D4,1.637D4,1.372D4,1.154D4, * 9.744D3,8.261D3,7.03D3,6.005D3,5.147D3,4.427D3,3.82D3, * 3.307D3,2.872D3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44D-1,9.08D-1,9.32D-1,9.36D-1,9.25D-1,9.08D-1,8.81D-1, * 8.5D-1,8.18D-1,7.84D-1,7.51D-1,7.18D-1,6.85D-1,6.58D-1, * 6.28D-1,6.03D-1,5.8D-1,5.58D-1,5.38D-1,5.22D-1,5.06D-1, * 4.9D-1,4.78D-1,4.67D-1,4.57D-1,4.48D-1,4.38D-1,4.31D-1, * 4.24D-1,4.2D-1,4.14D-1,4.11D-1,4.06D-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366D0,1.191D0,1.112D0,1.013D0,9.91D-1,8.85D-1,8.31D-1, * 8.47D-1,7.86D-1,7.25D-1,7.46D-1,6.79D-1,6.08D-1,6.55D-1, * 6.16D-1,6.06D-1,6.02D-1,6.26D-1,6.51D-1,7.24D-1,6.49D-1, * 6.49D-1,6.94D-1,6.44D-1,6.24D-1,6.61D-1,6.12D-1,5.58D-1, * 5.33D-1,4.95D-1,5.0D-1,4.23D-1,3.95D-1,3.75D-1,3.72D-1, * 3.91D-1,3.96D-1,4.05D-1,4.28D-1,4.29D-1,5.23D-1,5.62D-1, * 6.07D-1,6.53D-1,6.72D-1,7.08D-1,6.33D-1,6.68D-1,6.45D-1, * 6.32D-1,5.91D-1,5.59D-1,5.97D-1,6.25D-1,7.39D-1,7.1D-1, * 7.29D-1,7.2D-1,6.36D-1,5.81D-1,4.28D-1,2.92D-1,1.62D-1, * 9.8D-2,5.4D-2/ DFLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/DFLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + DFLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = DFLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + DFLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = DFLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*DATAN(ONE) TMP1 = DSIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI + ZP5 TMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = DFLOAT(I) TMP2 = DFLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*DFLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = DEXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = DFLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + DFLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = DFLOAT(I) TMP1 = TEMP/TEN FVEC(I) = DEXP(-TMP1*X(1)) - DEXP(-TMP1*X(2)) * + (DEXP(-TEMP) - DEXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = DFLOAT(I) FVEC(I) = TWO + TWO*TEMP - DEXP(TEMP*X(1)) - DEXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = DFLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - DEXP(TEMP) TMP2 = X(3) + DSIN(TEMP)*X(4) - DCOS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/DFLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(DFLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*DFLOAT(I-1) TMP1 = DEXP(-X(4)*TEMP) TMP2 = DEXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = DFLOAT(I-1)/TEN TMP1 = DEXP(-X(5)*TEMP) TMP2 = DEXP(-X(6)*(TEMP-X(9))**2) TMP3 = DEXP(-X(7)*(TEMP-X(10))**2) TMP4 = DEXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14, * C15,C16,C17,FIVE,H,HALF,ONE,SEVEN,TEN,THREE, * TWENTY,TWNTF,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0D0,5.0D-1,1.0D0,2.0D0,3.0D0,5.0D0,7.0D0,1.0D1,2.0D1, * 2.5D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2D0,2.5D-1,3.9D-1,4.15D-1,2.0D-2,4.0D3,2.5D2,3.0D-1, * 4.0D-1,1.5D0,1.0D-2,1.3D0,6.5D-1,7.0D-1,6.0D-1,4.5D0, * 5.5D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/DFLOAT(N+1) DO 160 J = 1, N X(J) = DFLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END minpack-19961126/ex/thybrj1.f0000644000175000017500000000375211616327304016462 0ustar sylvestresylvestreC DRIVER FOR HYBRJ1 EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,N,LDFJAC,INFO,LWA,NWRITE DOUBLE PRECISION TOL,FNORM DOUBLE PRECISION X(9),FVEC(9),FJAC(9,9),WA(99) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C N = 9 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH SOLUTION. C DO 10 J = 1, 9 X(J) = -1.D0 10 CONTINUE C LDFJAC = 9 LWA = 99 C C SET TOL TO THE SQUARE ROOT OF THE MACHINE PRECISION. C UNLESS HIGH PRECISION SOLUTIONS ARE REQUIRED, C THIS IS THE RECOMMENDED SETTING. C TOL = DSQRT(DPMPAR(1)) C CALL HYBRJ1(FCN,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,WA,LWA) FNORM = ENORM(N,FVEC) WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // (5X,3D15.7)) C C LAST CARD OF DRIVER FOR HYBRJ1 EXAMPLE. C END SUBROUTINE FCN(N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER N,LDFJAC,IFLAG DOUBLE PRECISION X(N),FVEC(N),FJAC(LDFJAC,N) C C SUBROUTINE FCN FOR HYBRJ1 EXAMPLE. C INTEGER J,K DOUBLE PRECISION ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO DATA ZERO,ONE,TWO,THREE,FOUR /0.D0,1.D0,2.D0,3.D0,4.D0/ C IF (IFLAG .EQ. 2) GO TO 20 DO 10 K = 1, N TEMP = (THREE - TWO*X(K))*X(K) TEMP1 = ZERO IF (K .NE. 1) TEMP1 = X(K-1) TEMP2 = ZERO IF (K .NE. N) TEMP2 = X(K+1) FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE 10 CONTINUE GO TO 50 20 CONTINUE DO 40 K = 1, N DO 30 J = 1, N FJAC(K,J) = ZERO 30 CONTINUE FJAC(K,K) = THREE - FOUR*X(K) IF (K .NE. 1) FJAC(K,K-1) = -ONE IF (K .NE. N) FJAC(K,K+1) = -TWO 40 CONTINUE 50 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. C END minpack-19961126/ex/file100000644000175000017500000006600504210374757015741 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... SPMPAR,ENORM,INITPT,LMDER1,SSQFCN C C FORTRAN-SUPPLIED ... SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES, * NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) REAL FACTOR,FNORM1,FNORM2,ONE,TEN,TOL REAL FJAC(65,40),FNM(60),FVEC(65),WA(265),X(40) REAL SPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0E0,1.0E1/ TOL = SQRT(SPMPAR(1)) LDFJAC = 65 LWA = 265 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMDER1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IWA,WA, * LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, E15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , E15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5E15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMDER1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 2X, E15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,FJAC,LDFJAC,IFLAG) INTEGER M,N,LDFJAC,IFLAG REAL X(N),FVEC(M),FJAC(LDFJAC,N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST-SQUARES SOLVER. FCN SHOULD ONLY CALL THE TESTING C FUNCTION AND JACOBIAN SUBROUTINES SSQFCN AND SSQJAC WITH C THE APPROPRIATE VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN,SSQJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) INTEGER M,N,LDFJAC,NPROB REAL X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE SSQJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF EIGHTEEN C NONLINEAR LEAST SQUARES PROBLEMS. THE PROBLEM DIMENSIONS ARE C AS DESCRIBED IN THE PROLOGUE COMMENTS OF SSQFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FJAC IS AN M BY N OUTPUT ARRAY WHICH CONTAINS THE JACOBIAN C MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIN,SQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,MM1,NM1 REAL C14,C20,C29,C45,C100,DIV,DX,EIGHT,FIVE,FOUR,ONE,PROD,S2, * TEMP,TEN,THREE,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO,ZERO REAL V(11) REAL FLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,EIGHT,TEN,C14,C20,C29,C45,C100 * /0.0E0,1.0E0,2.0E0,3.0E0,4.0E0,5.0E0,8.0E0,1.0E1,1.4E1, * 2.0E1,2.9E1,4.5E1,1.0E2/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0E0,2.0E0,1.0E0,5.0E-1,2.5E-1,1.67E-1,1.25E-1,1.0E-1, * 8.33E-2,7.14E-2,6.25E-2/ FLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,40,70,130,140,150,180,190,210,230,250,310,330,350,370, * 400,460,480), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE TEMP = TWO/FLOAT(M) DO 30 J = 1, N DO 20 I = 1, M FJAC(I,J) = -TEMP 20 CONTINUE FJAC(J,J) = FJAC(J,J) + ONE 30 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE DO 60 J = 1, N DO 50 I = 1, M FJAC(I,J) = FLOAT(I)*FLOAT(J) 50 CONTINUE 60 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE DO 90 J = 1, N DO 80 I = 1, M FJAC(I,J) = ZERO 80 CONTINUE 90 CONTINUE NM1 = N - 1 MM1 = M - 1 IF (NM1 .LT. 2) GO TO 120 DO 110 J = 2, NM1 DO 100 I = 2, MM1 FJAC(I,J) = FLOAT(I-1)*FLOAT(J) 100 CONTINUE 110 CONTINUE 120 CONTINUE GO TO 500 C C ROSENBROCK FUNCTION. C 130 CONTINUE FJAC(1,1) = -C20*X(1) FJAC(1,2) = TEN FJAC(2,1) = -ONE FJAC(2,2) = ZERO GO TO 500 C C HELICAL VALLEY FUNCTION. C 140 CONTINUE TPI = EIGHT*ATAN(ONE) TEMP = X(1)**2 + X(2)**2 TMP1 = TPI*TEMP TMP2 = SQRT(TEMP) FJAC(1,1) = C100*X(2)/TMP1 FJAC(1,2) = -C100*X(1)/TMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TMP2 FJAC(2,2) = TEN*X(2)/TMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 500 C C POWELL SINGULAR FUNCTION. C 150 CONTINUE DO 170 J = 1, 4 DO 160 I = 1, 4 FJAC(I,J) = ZERO 160 CONTINUE 170 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = SQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*SQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 500 C C FREUDENSTEIN AND ROTH FUNCTION. C 180 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = X(2)*(TEN - THREE*X(2)) - TWO FJAC(2,1) = ONE FJAC(2,2) = X(2)*(TWO + THREE*X(2)) - C14 GO TO 500 C C BARD FUNCTION. C 190 CONTINUE DO 200 I = 1, 15 TMP1 = FLOAT(I) TMP2 = FLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -ONE FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 200 CONTINUE GO TO 500 C C KOWALIK AND OSBORNE FUNCTION. C 210 CONTINUE DO 220 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FJAC(I,1) = -TMP1/TMP2 FJAC(I,2) = -V(I)*X(1)/TMP2 FJAC(I,3) = FJAC(I,1)*FJAC(I,2) FJAC(I,4) = FJAC(I,3)/V(I) 220 CONTINUE GO TO 500 C C MEYER FUNCTION. C 230 CONTINUE DO 240 I = 1, 16 TEMP = FIVE*FLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = EXP(TMP1) FJAC(I,1) = TMP2 FJAC(I,2) = X(1)*TMP2/TEMP FJAC(I,3) = -TMP1*FJAC(I,2) 240 CONTINUE GO TO 500 C C WATSON FUNCTION. C 250 CONTINUE DO 280 I = 1, 29 DIV = FLOAT(I)/C29 S2 = ZERO DX = ONE DO 260 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 260 CONTINUE TEMP = TWO*DIV*S2 DX = ONE/DIV DO 270 J = 1, N FJAC(I,J) = DX*(FLOAT(J-1) - TEMP) DX = DIV*DX 270 CONTINUE 280 CONTINUE DO 300 J = 1, N DO 290 I = 30, 31 FJAC(I,J) = ZERO 290 CONTINUE 300 CONTINUE FJAC(30,1) = ONE FJAC(31,1) = -TWO*X(1) FJAC(31,2) = ONE GO TO 500 C C BOX 3-DIMENSIONAL FUNCTION. C 310 CONTINUE DO 320 I = 1, M TEMP = FLOAT(I) TMP1 = TEMP/TEN FJAC(I,1) = -TMP1*EXP(-TMP1*X(1)) FJAC(I,2) = TMP1*EXP(-TMP1*X(2)) FJAC(I,3) = EXP(-TEMP) - EXP(-TMP1) 320 CONTINUE GO TO 500 C C JENNRICH AND SAMPSON FUNCTION. C 330 CONTINUE DO 340 I = 1, M TEMP = FLOAT(I) FJAC(I,1) = -TEMP*EXP(TEMP*X(1)) FJAC(I,2) = -TEMP*EXP(TEMP*X(2)) 340 CONTINUE GO TO 500 C C BROWN AND DENNIS FUNCTION. C 350 CONTINUE DO 360 I = 1, M TEMP = FLOAT(I)/FIVE TI = SIN(TEMP) TMP1 = X(1) + TEMP*X(2) - EXP(TEMP) TMP2 = X(3) + TI*X(4) - COS(TEMP) FJAC(I,1) = TWO*TMP1 FJAC(I,2) = TEMP*FJAC(I,1) FJAC(I,3) = TWO*TMP2 FJAC(I,4) = TI*FJAC(I,3) 360 CONTINUE GO TO 500 C C CHEBYQUAD FUNCTION. C 370 CONTINUE DX = ONE/FLOAT(N) DO 390 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 TMP3 = ZERO TMP4 = TWO DO 380 I = 1, M FJAC(I,J) = DX*TMP4 TI = FOUR*TMP2 + TEMP*TMP4 - TMP3 TMP3 = TMP4 TMP4 = TI TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 380 CONTINUE 390 CONTINUE GO TO 500 C C BROWN ALMOST-LINEAR FUNCTION. C 400 CONTINUE PROD = ONE DO 420 J = 1, N PROD = X(J)*PROD DO 410 I = 1, N FJAC(I,J) = ONE 410 CONTINUE FJAC(J,J) = TWO 420 CONTINUE DO 450 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 440 TEMP = ONE PROD = ONE DO 430 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 430 CONTINUE 440 CONTINUE FJAC(N,J) = PROD/TEMP 450 CONTINUE GO TO 500 C C OSBORNE 1 FUNCTION. C 460 CONTINUE DO 470 I = 1, 33 TEMP = TEN*FLOAT(I-1) TMP1 = EXP(-X(4)*TEMP) TMP2 = EXP(-X(5)*TEMP) FJAC(I,1) = -ONE FJAC(I,2) = -TMP1 FJAC(I,3) = -TMP2 FJAC(I,4) = TEMP*X(2)*TMP1 FJAC(I,5) = TEMP*X(3)*TMP2 470 CONTINUE GO TO 500 C C OSBORNE 2 FUNCTION. C 480 CONTINUE DO 490 I = 1, 65 TEMP = FLOAT(I-1)/TEN TMP1 = EXP(-X(5)*TEMP) TMP2 = EXP(-X(6)*(TEMP-X(9))**2) TMP3 = EXP(-X(7)*(TEMP-X(10))**2) TMP4 = EXP(-X(8)*(TEMP-X(11))**2) FJAC(I,1) = -TMP1 FJAC(I,2) = -TMP2 FJAC(I,3) = -TMP3 FJAC(I,4) = -TMP4 FJAC(I,5) = TEMP*X(1)*TMP1 FJAC(I,6) = X(2)*(TEMP - X(9))**2*TMP2 FJAC(I,7) = X(3)*(TEMP - X(10))**2*TMP3 FJAC(I,8) = X(4)*(TEMP - X(11))**2*TMP4 FJAC(I,9) = -TWO*X(2)*X(6)*(TEMP - X(9))*TMP2 FJAC(I,10) = -TWO*X(3)*X(7)*(TEMP - X(10))*TMP3 FJAC(I,11) = -TWO*X(4)*X(8)*(TEMP - X(11))*TMP4 490 CONTINUE 500 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB REAL FACTOR REAL X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J REAL C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17, * FIVE,H,HALF,ONE,SEVEN,TEN,THREE,TWENTY,TWNTF,TWO,ZERO REAL FLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0E0,5.0E-1,1.0E0,2.0E0,3.0E0,5.0E0,7.0E0,1.0E1,2.0E1, * 2.5E1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2E0,2.5E-1,3.9E-1,4.15E-1,2.0E-2,4.0E3,2.5E2,3.0E-1, * 4.0E-1,1.5E0,1.0E-2,1.3E0,6.5E-1,7.0E-1,6.0E-1,4.5E0, * 5.5E0/ FLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/FLOAT(N+1) DO 160 J = 1, N X(J) = FLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB REAL X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... ATAN,COS,EXP,SIN,SQRT,SIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 REAL C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM,S1,S2,TEMP, * TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO,ZERO,ZP25,ZP5 REAL V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) REAL FLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0E0,2.5E-1,5.0E-1,1.0E0,2.0E0,5.0E0,8.0E0,1.0E1,1.3E1, * 1.4E1,2.9E1,4.5E1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0E0,2.0E0,1.0E0,5.0E-1,2.5E-1,1.67E-1,1.25E-1,1.0E-1, * 8.33E-2,7.14E-2,6.25E-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1, * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957E-1,1.947E-1,1.735E-1,1.6E-1,8.44E-2,6.27E-2,4.56E-2, * 3.42E-2,3.23E-2,2.35E-2,2.46E-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478E4,2.861E4,2.365E4,1.963E4,1.637E4,1.372E4,1.154E4, * 9.744E3,8.261E3,7.03E3,6.005E3,5.147E3,4.427E3,3.82E3, * 3.307E3,2.872E3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44E-1,9.08E-1,9.32E-1,9.36E-1,9.25E-1,9.08E-1,8.81E-1, * 8.5E-1,8.18E-1,7.84E-1,7.51E-1,7.18E-1,6.85E-1,6.58E-1, * 6.28E-1,6.03E-1,5.8E-1,5.58E-1,5.38E-1,5.22E-1,5.06E-1, * 4.9E-1,4.78E-1,4.67E-1,4.57E-1,4.48E-1,4.38E-1,4.31E-1, * 4.24E-1,4.2E-1,4.14E-1,4.11E-1,4.06E-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366E0,1.191E0,1.112E0,1.013E0,9.91E-1,8.85E-1,8.31E-1, * 8.47E-1,7.86E-1,7.25E-1,7.46E-1,6.79E-1,6.08E-1,6.55E-1, * 6.16E-1,6.06E-1,6.02E-1,6.26E-1,6.51E-1,7.24E-1,6.49E-1, * 6.49E-1,6.94E-1,6.44E-1,6.24E-1,6.61E-1,6.12E-1,5.58E-1, * 5.33E-1,4.95E-1,5.0E-1,4.23E-1,3.95E-1,3.75E-1,3.72E-1, * 3.91E-1,3.96E-1,4.05E-1,4.28E-1,4.29E-1,5.23E-1,5.62E-1, * 6.07E-1,6.53E-1,6.72E-1,7.08E-1,6.33E-1,6.68E-1,6.45E-1, * 6.32E-1,5.91E-1,5.59E-1,5.97E-1,6.25E-1,7.39E-1,7.1E-1, * 7.29E-1,7.2E-1,6.36E-1,5.81E-1,4.28E-1,2.92E-1,1.62E-1, * 9.8E-2,5.4E-2/ FLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/FLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + FLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = FLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + FLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = FLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*ATAN(ONE) TMP1 = SIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = ATAN(X(2)/X(1))/TPI + ZP5 TMP2 = SQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = SQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = SQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = FLOAT(I) TMP2 = FLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*FLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = EXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = FLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + FLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = FLOAT(I) TMP1 = TEMP/TEN FVEC(I) = EXP(-TMP1*X(1)) - EXP(-TMP1*X(2)) * + (EXP(-TEMP) - EXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = FLOAT(I) FVEC(I) = TWO + TWO*TEMP - EXP(TEMP*X(1)) - EXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = FLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - EXP(TEMP) TMP2 = X(3) + SIN(TEMP)*X(4) - COS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/FLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(FLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -FLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*FLOAT(I-1) TMP1 = EXP(-X(4)*TEMP) TMP2 = EXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = FLOAT(I-1)/TEN TMP1 = EXP(-X(5)*TEMP) TMP2 = EXP(-X(6)*(TEMP-X(9))**2) TMP3 = EXP(-X(7)*(TEMP-X(10))**2) TMP4 = EXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END minpack-19961126/ex/file180000644000175000017500000006752604210375253015752 0ustar sylvestresylvestreC ********** C C THIS PROGRAM TESTS CODES FOR THE LEAST-SQUARES SOLUTION OF C M NONLINEAR EQUATIONS IN N VARIABLES. IT CONSISTS OF A DRIVER C AND AN INTERFACE SUBROUTINE FCN. THE DRIVER READS IN DATA, C CALLS THE NONLINEAR LEAST-SQUARES SOLVER, AND FINALLY PRINTS C OUT INFORMATION ON THE PERFORMANCE OF THE SOLVER. THIS IS C ONLY A SAMPLE DRIVER, MANY OTHER DRIVERS ARE POSSIBLE. THE C INTERFACE SUBROUTINE FCN IS NECESSARY TO TAKE INTO ACCOUNT THE C FORMS OF CALLING SEQUENCES USED BY THE FUNCTION AND JACOBIAN C SUBROUTINES IN THE VARIOUS NONLINEAR LEAST-SQUARES SOLVERS. C C SUBPROGRAMS CALLED C C USER-SUPPLIED ...... FCN C C MINPACK-SUPPLIED ... DPMPAR,ENORM,INITPT,LMSTR1,SSQFCN C C FORTRAN-SUPPLIED ... DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IC,INFO,K,LDFJAC,LWA,M,N,NFEV,NJEV,NPROB,NREAD,NTRIES, * NWRITE INTEGER IWA(40),MA(60),NA(60),NF(60),NJ(60),NP(60),NX(60) DOUBLE PRECISION FACTOR,FNORM1,FNORM2,ONE,TEN,TOL DOUBLE PRECISION FJAC(40,40),FNM(60),FVEC(65),WA(265),X(40) DOUBLE PRECISION DPMPAR,ENORM EXTERNAL FCN COMMON /REFNUM/ NPROB,NFEV,NJEV C C LOGICAL INPUT UNIT IS ASSUMED TO BE NUMBER 5. C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NREAD,NWRITE /5,6/ C DATA ONE,TEN /1.0D0,1.0D1/ TOL = DSQRT(DPMPAR(1)) LDFJAC = 40 LWA = 265 IC = 0 10 CONTINUE READ (NREAD,50) NPROB,N,M,NTRIES IF (NPROB .LE. 0) GO TO 30 FACTOR = ONE DO 20 K = 1, NTRIES IC = IC + 1 CALL INITPT(N,X,NPROB,FACTOR) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM1 = ENORM(M,FVEC) WRITE (NWRITE,60) NPROB,N,M NFEV = 0 NJEV = 0 CALL LMSTR1(FCN,M,N,X,FVEC,FJAC,LDFJAC,TOL,INFO,IWA,WA, * LWA) CALL SSQFCN(M,N,X,FVEC,NPROB) FNORM2 = ENORM(M,FVEC) NP(IC) = NPROB NA(IC) = N MA(IC) = M NF(IC) = NFEV NJ(IC) = NJEV NX(IC) = INFO FNM(IC) = FNORM2 WRITE (NWRITE,70) * FNORM1,FNORM2,NFEV,NJEV,INFO,(X(I), I = 1, N) FACTOR = TEN*FACTOR 20 CONTINUE GO TO 10 30 CONTINUE WRITE (NWRITE,80) IC WRITE (NWRITE,90) DO 40 I = 1, IC WRITE (NWRITE,100) NP(I),NA(I),MA(I),NF(I),NJ(I),NX(I),FNM(I) 40 CONTINUE STOP 50 FORMAT (4I5) 60 FORMAT ( //// 5X, 8H PROBLEM, I5, 5X, 11H DIMENSIONS, 2I5, 5X // * ) 70 FORMAT (5X, 33H INITIAL L2 NORM OF THE RESIDUALS, D15.7 // 5X, * 33H FINAL L2 NORM OF THE RESIDUALS , D15.7 // 5X, * 33H NUMBER OF FUNCTION EVALUATIONS , I10 // 5X, * 33H NUMBER OF JACOBIAN EVALUATIONS , I10 // 5X, * 15H EXIT PARAMETER, 18X, I10 // 5X, * 27H FINAL APPROXIMATE SOLUTION // (5X, 5D15.7)) 80 FORMAT (12H1SUMMARY OF , I3, 16H CALLS TO LMSTR1 /) 90 FORMAT (49H NPROB N M NFEV NJEV INFO FINAL L2 NORM /) 100 FORMAT (3I5, 3I6, 1X, D15.7) C C LAST CARD OF DRIVER. C END SUBROUTINE FCN(M,N,X,FVEC,FJROW,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M),FJROW(N) C ********** C C THE CALLING SEQUENCE OF FCN SHOULD BE IDENTICAL TO THE C CALLING SEQUENCE OF THE FUNCTION SUBROUTINE IN THE NONLINEAR C LEAST SQUARES SOLVER. IF IFLAG = 1, FCN SHOULD ONLY CALL THE C TESTING FUNCTION SUBROUTINE SSQFCN. IF IFLAG = I, I .GE. 2, C FCN SHOULD ONLY CALL SUBROUTINE SSQJAC TO CALCULATE THE C (I-1)-ST ROW OF THE JACOBIAN. (THE SSQJAC SUBROUTINE PROVIDED C HERE FOR TESTING PURPOSES CALCULATES THE ENTIRE JACOBIAN C MATRIX AND IS THEREFORE CALLED ONLY WHEN IFLAG = 2.) EACH C CALL TO SSQFCN OR SSQJAC SHOULD SPECIFY THE APPROPRIATE C VALUE OF PROBLEM NUMBER (NPROB). C C SUBPROGRAMS CALLED C C MINPACK-SUPPLIED ... SSQFCN,SSQJAC C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER NPROB,NFEV,NJEV,J DOUBLE PRECISION TEMP(65,40) COMMON /REFNUM/ NPROB,NFEV,NJEV IF (IFLAG .EQ. 1) CALL SSQFCN(M,N,X,FVEC,NPROB) IF (IFLAG .EQ. 2) CALL SSQJAC(M,N,X,TEMP,65,NPROB) IF (IFLAG .EQ. 1) NFEV = NFEV + 1 IF (IFLAG .EQ. 2) NJEV = NJEV + 1 IF (IFLAG .EQ. 1) GO TO 120 DO 110 J = 1, N FJROW(J) = TEMP(IFLAG-1,J) 110 CONTINUE 120 CONTINUE RETURN C C LAST CARD OF INTERFACE SUBROUTINE FCN. C END SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) INTEGER M,N,LDFJAC,NPROB DOUBLE PRECISION X(N),FJAC(LDFJAC,N) C ********** C C SUBROUTINE SSQJAC C C THIS SUBROUTINE DEFINES THE JACOBIAN MATRICES OF EIGHTEEN C NONLINEAR LEAST SQUARES PROBLEMS. THE PROBLEM DIMENSIONS ARE C AS DESCRIBED IN THE PROLOGUE COMMENTS OF SSQFCN. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQJAC(M,N,X,FJAC,LDFJAC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FJAC IS AN M BY N OUTPUT ARRAY WHICH CONTAINS THE JACOBIAN C MATRIX OF THE NPROB FUNCTION EVALUATED AT X. C C LDFJAC IS A POSITIVE INTEGER INPUT VARIABLE NOT LESS THAN M C WHICH SPECIFIES THE LEADING DIMENSION OF THE ARRAY FJAC. C C NPROB IS A POSITIVE INTEGER VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIN,DSQRT C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IVAR,J,K,MM1,NM1 DOUBLE PRECISION C14,C20,C29,C45,C100,DIV,DX,EIGHT,FIVE,FOUR, * ONE,PROD,S2,TEMP,TEN,THREE,TI,TMP1,TMP2,TMP3, * TMP4,TPI,TWO,ZERO DOUBLE PRECISION V(11) DOUBLE PRECISION DFLOAT DATA ZERO,ONE,TWO,THREE,FOUR,FIVE,EIGHT,TEN,C14,C20,C29,C45,C100 * /0.0D0,1.0D0,2.0D0,3.0D0,4.0D0,5.0D0,8.0D0,1.0D1,1.4D1, * 2.0D1,2.9D1,4.5D1,1.0D2/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0D0,2.0D0,1.0D0,5.0D-1,2.5D-1,1.67D-1,1.25D-1,1.0D-1, * 8.33D-2,7.14D-2,6.25D-2/ DFLOAT(IVAR) = IVAR C C JACOBIAN ROUTINE SELECTOR. C GO TO (10,40,70,130,140,150,180,190,210,230,250,310,330,350,370, * 400,460,480), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE TEMP = TWO/DFLOAT(M) DO 30 J = 1, N DO 20 I = 1, M FJAC(I,J) = -TEMP 20 CONTINUE FJAC(J,J) = FJAC(J,J) + ONE 30 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE DO 60 J = 1, N DO 50 I = 1, M FJAC(I,J) = DFLOAT(I)*DFLOAT(J) 50 CONTINUE 60 CONTINUE GO TO 500 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE DO 90 J = 1, N DO 80 I = 1, M FJAC(I,J) = ZERO 80 CONTINUE 90 CONTINUE NM1 = N - 1 MM1 = M - 1 IF (NM1 .LT. 2) GO TO 120 DO 110 J = 2, NM1 DO 100 I = 2, MM1 FJAC(I,J) = DFLOAT(I-1)*DFLOAT(J) 100 CONTINUE 110 CONTINUE 120 CONTINUE GO TO 500 C C ROSENBROCK FUNCTION. C 130 CONTINUE FJAC(1,1) = -C20*X(1) FJAC(1,2) = TEN FJAC(2,1) = -ONE FJAC(2,2) = ZERO GO TO 500 C C HELICAL VALLEY FUNCTION. C 140 CONTINUE TPI = EIGHT*DATAN(ONE) TEMP = X(1)**2 + X(2)**2 TMP1 = TPI*TEMP TMP2 = DSQRT(TEMP) FJAC(1,1) = C100*X(2)/TMP1 FJAC(1,2) = -C100*X(1)/TMP1 FJAC(1,3) = TEN FJAC(2,1) = TEN*X(1)/TMP2 FJAC(2,2) = TEN*X(2)/TMP2 FJAC(2,3) = ZERO FJAC(3,1) = ZERO FJAC(3,2) = ZERO FJAC(3,3) = ONE GO TO 500 C C POWELL SINGULAR FUNCTION. C 150 CONTINUE DO 170 J = 1, 4 DO 160 I = 1, 4 FJAC(I,J) = ZERO 160 CONTINUE 170 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = TEN FJAC(2,3) = DSQRT(FIVE) FJAC(2,4) = -FJAC(2,3) FJAC(3,2) = TWO*(X(2) - TWO*X(3)) FJAC(3,3) = -TWO*FJAC(3,2) FJAC(4,1) = TWO*DSQRT(TEN)*(X(1) - X(4)) FJAC(4,4) = -FJAC(4,1) GO TO 500 C C FREUDENSTEIN AND ROTH FUNCTION. C 180 CONTINUE FJAC(1,1) = ONE FJAC(1,2) = X(2)*(TEN - THREE*X(2)) - TWO FJAC(2,1) = ONE FJAC(2,2) = X(2)*(TWO + THREE*X(2)) - C14 GO TO 500 C C BARD FUNCTION. C 190 CONTINUE DO 200 I = 1, 15 TMP1 = DFLOAT(I) TMP2 = DFLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2 FJAC(I,1) = -ONE FJAC(I,2) = TMP1*TMP2/TMP4 FJAC(I,3) = TMP1*TMP3/TMP4 200 CONTINUE GO TO 500 C C KOWALIK AND OSBORNE FUNCTION. C 210 CONTINUE DO 220 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FJAC(I,1) = -TMP1/TMP2 FJAC(I,2) = -V(I)*X(1)/TMP2 FJAC(I,3) = FJAC(I,1)*FJAC(I,2) FJAC(I,4) = FJAC(I,3)/V(I) 220 CONTINUE GO TO 500 C C MEYER FUNCTION. C 230 CONTINUE DO 240 I = 1, 16 TEMP = FIVE*DFLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = DEXP(TMP1) FJAC(I,1) = TMP2 FJAC(I,2) = X(1)*TMP2/TEMP FJAC(I,3) = -TMP1*FJAC(I,2) 240 CONTINUE GO TO 500 C C WATSON FUNCTION. C 250 CONTINUE DO 280 I = 1, 29 DIV = DFLOAT(I)/C29 S2 = ZERO DX = ONE DO 260 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 260 CONTINUE TEMP = TWO*DIV*S2 DX = ONE/DIV DO 270 J = 1, N FJAC(I,J) = DX*(DFLOAT(J-1) - TEMP) DX = DIV*DX 270 CONTINUE 280 CONTINUE DO 300 J = 1, N DO 290 I = 30, 31 FJAC(I,J) = ZERO 290 CONTINUE 300 CONTINUE FJAC(30,1) = ONE FJAC(31,1) = -TWO*X(1) FJAC(31,2) = ONE GO TO 500 C C BOX 3-DIMENSIONAL FUNCTION. C 310 CONTINUE DO 320 I = 1, M TEMP = DFLOAT(I) TMP1 = TEMP/TEN FJAC(I,1) = -TMP1*DEXP(-TMP1*X(1)) FJAC(I,2) = TMP1*DEXP(-TMP1*X(2)) FJAC(I,3) = DEXP(-TEMP) - DEXP(-TMP1) 320 CONTINUE GO TO 500 C C JENNRICH AND SAMPSON FUNCTION. C 330 CONTINUE DO 340 I = 1, M TEMP = DFLOAT(I) FJAC(I,1) = -TEMP*DEXP(TEMP*X(1)) FJAC(I,2) = -TEMP*DEXP(TEMP*X(2)) 340 CONTINUE GO TO 500 C C BROWN AND DENNIS FUNCTION. C 350 CONTINUE DO 360 I = 1, M TEMP = DFLOAT(I)/FIVE TI = DSIN(TEMP) TMP1 = X(1) + TEMP*X(2) - DEXP(TEMP) TMP2 = X(3) + TI*X(4) - DCOS(TEMP) FJAC(I,1) = TWO*TMP1 FJAC(I,2) = TEMP*FJAC(I,1) FJAC(I,3) = TWO*TMP2 FJAC(I,4) = TI*FJAC(I,3) 360 CONTINUE GO TO 500 C C CHEBYQUAD FUNCTION. C 370 CONTINUE DX = ONE/DFLOAT(N) DO 390 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 TMP3 = ZERO TMP4 = TWO DO 380 I = 1, M FJAC(I,J) = DX*TMP4 TI = FOUR*TMP2 + TEMP*TMP4 - TMP3 TMP3 = TMP4 TMP4 = TI TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 380 CONTINUE 390 CONTINUE GO TO 500 C C BROWN ALMOST-LINEAR FUNCTION. C 400 CONTINUE PROD = ONE DO 420 J = 1, N PROD = X(J)*PROD DO 410 I = 1, N FJAC(I,J) = ONE 410 CONTINUE FJAC(J,J) = TWO 420 CONTINUE DO 450 J = 1, N TEMP = X(J) IF (TEMP .NE. ZERO) GO TO 440 TEMP = ONE PROD = ONE DO 430 K = 1, N IF (K .NE. J) PROD = X(K)*PROD 430 CONTINUE 440 CONTINUE FJAC(N,J) = PROD/TEMP 450 CONTINUE GO TO 500 C C OSBORNE 1 FUNCTION. C 460 CONTINUE DO 470 I = 1, 33 TEMP = TEN*DFLOAT(I-1) TMP1 = DEXP(-X(4)*TEMP) TMP2 = DEXP(-X(5)*TEMP) FJAC(I,1) = -ONE FJAC(I,2) = -TMP1 FJAC(I,3) = -TMP2 FJAC(I,4) = TEMP*X(2)*TMP1 FJAC(I,5) = TEMP*X(3)*TMP2 470 CONTINUE GO TO 500 C C OSBORNE 2 FUNCTION. C 480 CONTINUE DO 490 I = 1, 65 TEMP = DFLOAT(I-1)/TEN TMP1 = DEXP(-X(5)*TEMP) TMP2 = DEXP(-X(6)*(TEMP-X(9))**2) TMP3 = DEXP(-X(7)*(TEMP-X(10))**2) TMP4 = DEXP(-X(8)*(TEMP-X(11))**2) FJAC(I,1) = -TMP1 FJAC(I,2) = -TMP2 FJAC(I,3) = -TMP3 FJAC(I,4) = -TMP4 FJAC(I,5) = TEMP*X(1)*TMP1 FJAC(I,6) = X(2)*(TEMP - X(9))**2*TMP2 FJAC(I,7) = X(3)*(TEMP - X(10))**2*TMP3 FJAC(I,8) = X(4)*(TEMP - X(11))**2*TMP4 FJAC(I,9) = -TWO*X(2)*X(6)*(TEMP - X(9))*TMP2 FJAC(I,10) = -TWO*X(3)*X(7)*(TEMP - X(10))*TMP3 FJAC(I,11) = -TWO*X(4)*X(8)*(TEMP - X(11))*TMP4 490 CONTINUE 500 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQJAC. C END SUBROUTINE INITPT(N,X,NPROB,FACTOR) INTEGER N,NPROB DOUBLE PRECISION FACTOR DOUBLE PRECISION X(N) C ********** C C SUBROUTINE INITPT C C THIS SUBROUTINE SPECIFIES THE STANDARD STARTING POINTS FOR THE C FUNCTIONS DEFINED BY SUBROUTINE SSQFCN. THE SUBROUTINE RETURNS C IN X A MULTIPLE (FACTOR) OF THE STANDARD STARTING POINT. FOR C THE 11TH FUNCTION THE STANDARD STARTING POINT IS ZERO, SO IN C THIS CASE, IF FACTOR IS NOT UNITY, THEN THE SUBROUTINE RETURNS C THE VECTOR X(J) = FACTOR, J=1,...,N. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE INITPT(N,X,NPROB,FACTOR) C C WHERE C C N IS A POSITIVE INTEGER INPUT VARIABLE. C C X IS AN OUTPUT ARRAY OF LENGTH N WHICH CONTAINS THE STANDARD C STARTING POINT FOR PROBLEM NPROB MULTIPLIED BY FACTOR. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C FACTOR IS AN INPUT VARIABLE WHICH SPECIFIES THE MULTIPLE OF C THE STANDARD STARTING POINT. IF FACTOR IS UNITY, NO C MULTIPLICATION IS PERFORMED. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER IVAR,J DOUBLE PRECISION C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14, * C15,C16,C17,FIVE,H,HALF,ONE,SEVEN,TEN,THREE, * TWENTY,TWNTF,TWO,ZERO DOUBLE PRECISION DFLOAT DATA ZERO,HALF,ONE,TWO,THREE,FIVE,SEVEN,TEN,TWENTY,TWNTF * /0.0D0,5.0D-1,1.0D0,2.0D0,3.0D0,5.0D0,7.0D0,1.0D1,2.0D1, * 2.5D1/ DATA C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15,C16,C17 * /1.2D0,2.5D-1,3.9D-1,4.15D-1,2.0D-2,4.0D3,2.5D2,3.0D-1, * 4.0D-1,1.5D0,1.0D-2,1.3D0,6.5D-1,7.0D-1,6.0D-1,4.5D0, * 5.5D0/ DFLOAT(IVAR) = IVAR C C SELECTION OF INITIAL POINT. C GO TO (10,10,10,30,40,50,60,70,80,90,100,120,130,140,150,170, * 190,200), NPROB C C LINEAR FUNCTION - FULL RANK OR RANK 1. C 10 CONTINUE DO 20 J = 1, N X(J) = ONE 20 CONTINUE GO TO 210 C C ROSENBROCK FUNCTION. C 30 CONTINUE X(1) = -C1 X(2) = ONE GO TO 210 C C HELICAL VALLEY FUNCTION. C 40 CONTINUE X(1) = -ONE X(2) = ZERO X(3) = ZERO GO TO 210 C C POWELL SINGULAR FUNCTION. C 50 CONTINUE X(1) = THREE X(2) = -ONE X(3) = ZERO X(4) = ONE GO TO 210 C C FREUDENSTEIN AND ROTH FUNCTION. C 60 CONTINUE X(1) = HALF X(2) = -TWO GO TO 210 C C BARD FUNCTION. C 70 CONTINUE X(1) = ONE X(2) = ONE X(3) = ONE GO TO 210 C C KOWALIK AND OSBORNE FUNCTION. C 80 CONTINUE X(1) = C2 X(2) = C3 X(3) = C4 X(4) = C3 GO TO 210 C C MEYER FUNCTION. C 90 CONTINUE X(1) = C5 X(2) = C6 X(3) = C7 GO TO 210 C C WATSON FUNCTION. C 100 CONTINUE DO 110 J = 1, N X(J) = ZERO 110 CONTINUE GO TO 210 C C BOX 3-DIMENSIONAL FUNCTION. C 120 CONTINUE X(1) = ZERO X(2) = TEN X(3) = TWENTY GO TO 210 C C JENNRICH AND SAMPSON FUNCTION. C 130 CONTINUE X(1) = C8 X(2) = C9 GO TO 210 C C BROWN AND DENNIS FUNCTION. C 140 CONTINUE X(1) = TWNTF X(2) = FIVE X(3) = -FIVE X(4) = -ONE GO TO 210 C C CHEBYQUAD FUNCTION. C 150 CONTINUE H = ONE/DFLOAT(N+1) DO 160 J = 1, N X(J) = DFLOAT(J)*H 160 CONTINUE GO TO 210 C C BROWN ALMOST-LINEAR FUNCTION. C 170 CONTINUE DO 180 J = 1, N X(J) = HALF 180 CONTINUE GO TO 210 C C OSBORNE 1 FUNCTION. C 190 CONTINUE X(1) = HALF X(2) = C10 X(3) = -ONE X(4) = C11 X(5) = C5 GO TO 210 C C OSBORNE 2 FUNCTION. C 200 CONTINUE X(1) = C12 X(2) = C13 X(3) = C13 X(4) = C14 X(5) = C15 X(6) = THREE X(7) = FIVE X(8) = SEVEN X(9) = TWO X(10) = C16 X(11) = C17 210 CONTINUE C C COMPUTE MULTIPLE OF INITIAL POINT. C IF (FACTOR .EQ. ONE) GO TO 260 IF (NPROB .EQ. 11) GO TO 230 DO 220 J = 1, N X(J) = FACTOR*X(J) 220 CONTINUE GO TO 250 230 CONTINUE DO 240 J = 1, N X(J) = FACTOR 240 CONTINUE 250 CONTINUE 260 CONTINUE RETURN C C LAST CARD OF SUBROUTINE INITPT. C END SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) INTEGER M,N,NPROB DOUBLE PRECISION X(N),FVEC(M) C ********** C C SUBROUTINE SSQFCN C C THIS SUBROUTINE DEFINES THE FUNCTIONS OF EIGHTEEN NONLINEAR C LEAST SQUARES PROBLEMS. THE ALLOWABLE VALUES OF (M,N) FOR C FUNCTIONS 1,2 AND 3 ARE VARIABLE BUT WITH M .GE. N. C FOR FUNCTIONS 4,5,6,7,8,9 AND 10 THE VALUES OF (M,N) ARE C (2,2),(3,3),(4,4),(2,2),(15,3),(11,4) AND (16,3), RESPECTIVELY. C FUNCTION 11 (WATSON) HAS M = 31 WITH N USUALLY 6 OR 9. C HOWEVER, ANY N, N = 2,...,31, IS PERMITTED. C FUNCTIONS 12,13 AND 14 HAVE N = 3,2 AND 4, RESPECTIVELY, BUT C ALLOW ANY M .GE. N, WITH THE USUAL CHOICES BEING 10,10 AND 20. C FUNCTION 15 (CHEBYQUAD) ALLOWS M AND N VARIABLE WITH M .GE. N. C FUNCTION 16 (BROWN) ALLOWS N VARIABLE WITH M = N. C FOR FUNCTIONS 17 AND 18, THE VALUES OF (M,N) ARE C (33,5) AND (65,11), RESPECTIVELY. C C THE SUBROUTINE STATEMENT IS C C SUBROUTINE SSQFCN(M,N,X,FVEC,NPROB) C C WHERE C C M AND N ARE POSITIVE INTEGER INPUT VARIABLES. N MUST NOT C EXCEED M. C C X IS AN INPUT ARRAY OF LENGTH N. C C FVEC IS AN OUTPUT ARRAY OF LENGTH M WHICH CONTAINS THE NPROB C FUNCTION EVALUATED AT X. C C NPROB IS A POSITIVE INTEGER INPUT VARIABLE WHICH DEFINES THE C NUMBER OF THE PROBLEM. NPROB MUST NOT EXCEED 18. C C SUBPROGRAMS CALLED C C FORTRAN-SUPPLIED ... DATAN,DCOS,DEXP,DSIN,DSQRT,DSIGN C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER I,IEV,IVAR,J,NM1 DOUBLE PRECISION C13,C14,C29,C45,DIV,DX,EIGHT,FIVE,ONE,PROD,SUM, * S1,S2,TEMP,TEN,TI,TMP1,TMP2,TMP3,TMP4,TPI,TWO, * ZERO,ZP25,ZP5 DOUBLE PRECISION V(11),Y1(15),Y2(11),Y3(16),Y4(33),Y5(65) DOUBLE PRECISION DFLOAT DATA ZERO,ZP25,ZP5,ONE,TWO,FIVE,EIGHT,TEN,C13,C14,C29,C45 * /0.0D0,2.5D-1,5.0D-1,1.0D0,2.0D0,5.0D0,8.0D0,1.0D1,1.3D1, * 1.4D1,2.9D1,4.5D1/ DATA V(1),V(2),V(3),V(4),V(5),V(6),V(7),V(8),V(9),V(10),V(11) * /4.0D0,2.0D0,1.0D0,5.0D-1,2.5D-1,1.67D-1,1.25D-1,1.0D-1, * 8.33D-2,7.14D-2,6.25D-2/ DATA Y1(1),Y1(2),Y1(3),Y1(4),Y1(5),Y1(6),Y1(7),Y1(8),Y1(9), * Y1(10),Y1(11),Y1(12),Y1(13),Y1(14),Y1(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ DATA Y2(1),Y2(2),Y2(3),Y2(4),Y2(5),Y2(6),Y2(7),Y2(8),Y2(9), * Y2(10),Y2(11) * /1.957D-1,1.947D-1,1.735D-1,1.6D-1,8.44D-2,6.27D-2,4.56D-2, * 3.42D-2,3.23D-2,2.35D-2,2.46D-2/ DATA Y3(1),Y3(2),Y3(3),Y3(4),Y3(5),Y3(6),Y3(7),Y3(8),Y3(9), * Y3(10),Y3(11),Y3(12),Y3(13),Y3(14),Y3(15),Y3(16) * /3.478D4,2.861D4,2.365D4,1.963D4,1.637D4,1.372D4,1.154D4, * 9.744D3,8.261D3,7.03D3,6.005D3,5.147D3,4.427D3,3.82D3, * 3.307D3,2.872D3/ DATA Y4(1),Y4(2),Y4(3),Y4(4),Y4(5),Y4(6),Y4(7),Y4(8),Y4(9), * Y4(10),Y4(11),Y4(12),Y4(13),Y4(14),Y4(15),Y4(16),Y4(17), * Y4(18),Y4(19),Y4(20),Y4(21),Y4(22),Y4(23),Y4(24),Y4(25), * Y4(26),Y4(27),Y4(28),Y4(29),Y4(30),Y4(31),Y4(32),Y4(33) * /8.44D-1,9.08D-1,9.32D-1,9.36D-1,9.25D-1,9.08D-1,8.81D-1, * 8.5D-1,8.18D-1,7.84D-1,7.51D-1,7.18D-1,6.85D-1,6.58D-1, * 6.28D-1,6.03D-1,5.8D-1,5.58D-1,5.38D-1,5.22D-1,5.06D-1, * 4.9D-1,4.78D-1,4.67D-1,4.57D-1,4.48D-1,4.38D-1,4.31D-1, * 4.24D-1,4.2D-1,4.14D-1,4.11D-1,4.06D-1/ DATA Y5(1),Y5(2),Y5(3),Y5(4),Y5(5),Y5(6),Y5(7),Y5(8),Y5(9), * Y5(10),Y5(11),Y5(12),Y5(13),Y5(14),Y5(15),Y5(16),Y5(17), * Y5(18),Y5(19),Y5(20),Y5(21),Y5(22),Y5(23),Y5(24),Y5(25), * Y5(26),Y5(27),Y5(28),Y5(29),Y5(30),Y5(31),Y5(32),Y5(33), * Y5(34),Y5(35),Y5(36),Y5(37),Y5(38),Y5(39),Y5(40),Y5(41), * Y5(42),Y5(43),Y5(44),Y5(45),Y5(46),Y5(47),Y5(48),Y5(49), * Y5(50),Y5(51),Y5(52),Y5(53),Y5(54),Y5(55),Y5(56),Y5(57), * Y5(58),Y5(59),Y5(60),Y5(61),Y5(62),Y5(63),Y5(64),Y5(65) * /1.366D0,1.191D0,1.112D0,1.013D0,9.91D-1,8.85D-1,8.31D-1, * 8.47D-1,7.86D-1,7.25D-1,7.46D-1,6.79D-1,6.08D-1,6.55D-1, * 6.16D-1,6.06D-1,6.02D-1,6.26D-1,6.51D-1,7.24D-1,6.49D-1, * 6.49D-1,6.94D-1,6.44D-1,6.24D-1,6.61D-1,6.12D-1,5.58D-1, * 5.33D-1,4.95D-1,5.0D-1,4.23D-1,3.95D-1,3.75D-1,3.72D-1, * 3.91D-1,3.96D-1,4.05D-1,4.28D-1,4.29D-1,5.23D-1,5.62D-1, * 6.07D-1,6.53D-1,6.72D-1,7.08D-1,6.33D-1,6.68D-1,6.45D-1, * 6.32D-1,5.91D-1,5.59D-1,5.97D-1,6.25D-1,7.39D-1,7.1D-1, * 7.29D-1,7.2D-1,6.36D-1,5.81D-1,4.28D-1,2.92D-1,1.62D-1, * 9.8D-2,5.4D-2/ DFLOAT(IVAR) = IVAR C C FUNCTION ROUTINE SELECTOR. C GO TO (10,40,70,110,120,130,140,150,170,190,210,250,270,290,310, * 360,390,410), NPROB C C LINEAR FUNCTION - FULL RANK. C 10 CONTINUE SUM = ZERO DO 20 J = 1, N SUM = SUM + X(J) 20 CONTINUE TEMP = TWO*SUM/DFLOAT(M) + ONE DO 30 I = 1, M FVEC(I) = -TEMP IF (I .LE. N) FVEC(I) = FVEC(I) + X(I) 30 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1. C 40 CONTINUE SUM = ZERO DO 50 J = 1, N SUM = SUM + DFLOAT(J)*X(J) 50 CONTINUE DO 60 I = 1, M FVEC(I) = DFLOAT(I)*SUM - ONE 60 CONTINUE GO TO 430 C C LINEAR FUNCTION - RANK 1 WITH ZERO COLUMNS AND ROWS. C 70 CONTINUE SUM = ZERO NM1 = N - 1 IF (NM1 .LT. 2) GO TO 90 DO 80 J = 2, NM1 SUM = SUM + DFLOAT(J)*X(J) 80 CONTINUE 90 CONTINUE DO 100 I = 1, M FVEC(I) = DFLOAT(I-1)*SUM - ONE 100 CONTINUE FVEC(M) = -ONE GO TO 430 C C ROSENBROCK FUNCTION. C 110 CONTINUE FVEC(1) = TEN*(X(2) - X(1)**2) FVEC(2) = ONE - X(1) GO TO 430 C C HELICAL VALLEY FUNCTION. C 120 CONTINUE TPI = EIGHT*DATAN(ONE) TMP1 = DSIGN(ZP25,X(2)) IF (X(1) .GT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI IF (X(1) .LT. ZERO) TMP1 = DATAN(X(2)/X(1))/TPI + ZP5 TMP2 = DSQRT(X(1)**2+X(2)**2) FVEC(1) = TEN*(X(3) - TEN*TMP1) FVEC(2) = TEN*(TMP2 - ONE) FVEC(3) = X(3) GO TO 430 C C POWELL SINGULAR FUNCTION. C 130 CONTINUE FVEC(1) = X(1) + TEN*X(2) FVEC(2) = DSQRT(FIVE)*(X(3) - X(4)) FVEC(3) = (X(2) - TWO*X(3))**2 FVEC(4) = DSQRT(TEN)*(X(1) - X(4))**2 GO TO 430 C C FREUDENSTEIN AND ROTH FUNCTION. C 140 CONTINUE FVEC(1) = -C13 + X(1) + ((FIVE - X(2))*X(2) - TWO)*X(2) FVEC(2) = -C29 + X(1) + ((ONE + X(2))*X(2) - C14)*X(2) GO TO 430 C C BARD FUNCTION. C 150 CONTINUE DO 160 I = 1, 15 TMP1 = DFLOAT(I) TMP2 = DFLOAT(16-I) TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y1(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 160 CONTINUE GO TO 430 C C KOWALIK AND OSBORNE FUNCTION. C 170 CONTINUE DO 180 I = 1, 11 TMP1 = V(I)*(V(I) + X(2)) TMP2 = V(I)*(V(I) + X(3)) + X(4) FVEC(I) = Y2(I) - X(1)*TMP1/TMP2 180 CONTINUE GO TO 430 C C MEYER FUNCTION. C 190 CONTINUE DO 200 I = 1, 16 TEMP = FIVE*DFLOAT(I) + C45 + X(3) TMP1 = X(2)/TEMP TMP2 = DEXP(TMP1) FVEC(I) = X(1)*TMP2 - Y3(I) 200 CONTINUE GO TO 430 C C WATSON FUNCTION. C 210 CONTINUE DO 240 I = 1, 29 DIV = DFLOAT(I)/C29 S1 = ZERO DX = ONE DO 220 J = 2, N S1 = S1 + DFLOAT(J-1)*DX*X(J) DX = DIV*DX 220 CONTINUE S2 = ZERO DX = ONE DO 230 J = 1, N S2 = S2 + DX*X(J) DX = DIV*DX 230 CONTINUE FVEC(I) = S1 - S2**2 - ONE 240 CONTINUE FVEC(30) = X(1) FVEC(31) = X(2) - X(1)**2 - ONE GO TO 430 C C BOX 3-DIMENSIONAL FUNCTION. C 250 CONTINUE DO 260 I = 1, M TEMP = DFLOAT(I) TMP1 = TEMP/TEN FVEC(I) = DEXP(-TMP1*X(1)) - DEXP(-TMP1*X(2)) * + (DEXP(-TEMP) - DEXP(-TMP1))*X(3) 260 CONTINUE GO TO 430 C C JENNRICH AND SAMPSON FUNCTION. C 270 CONTINUE DO 280 I = 1, M TEMP = DFLOAT(I) FVEC(I) = TWO + TWO*TEMP - DEXP(TEMP*X(1)) - DEXP(TEMP*X(2)) 280 CONTINUE GO TO 430 C C BROWN AND DENNIS FUNCTION. C 290 CONTINUE DO 300 I = 1, M TEMP = DFLOAT(I)/FIVE TMP1 = X(1) + TEMP*X(2) - DEXP(TEMP) TMP2 = X(3) + DSIN(TEMP)*X(4) - DCOS(TEMP) FVEC(I) = TMP1**2 + TMP2**2 300 CONTINUE GO TO 430 C C CHEBYQUAD FUNCTION. C 310 CONTINUE DO 320 I = 1, M FVEC(I) = ZERO 320 CONTINUE DO 340 J = 1, N TMP1 = ONE TMP2 = TWO*X(J) - ONE TEMP = TWO*TMP2 DO 330 I = 1, M FVEC(I) = FVEC(I) + TMP2 TI = TEMP*TMP2 - TMP1 TMP1 = TMP2 TMP2 = TI 330 CONTINUE 340 CONTINUE DX = ONE/DFLOAT(N) IEV = -1 DO 350 I = 1, M FVEC(I) = DX*FVEC(I) IF (IEV .GT. 0) FVEC(I) = FVEC(I) + ONE/(DFLOAT(I)**2 - ONE) IEV = -IEV 350 CONTINUE GO TO 430 C C BROWN ALMOST-LINEAR FUNCTION. C 360 CONTINUE SUM = -DFLOAT(N+1) PROD = ONE DO 370 J = 1, N SUM = SUM + X(J) PROD = X(J)*PROD 370 CONTINUE DO 380 I = 1, N FVEC(I) = X(I) + SUM 380 CONTINUE FVEC(N) = PROD - ONE GO TO 430 C C OSBORNE 1 FUNCTION. C 390 CONTINUE DO 400 I = 1, 33 TEMP = TEN*DFLOAT(I-1) TMP1 = DEXP(-X(4)*TEMP) TMP2 = DEXP(-X(5)*TEMP) FVEC(I) = Y4(I) - (X(1) + X(2)*TMP1 + X(3)*TMP2) 400 CONTINUE GO TO 430 C C OSBORNE 2 FUNCTION. C 410 CONTINUE DO 420 I = 1, 65 TEMP = DFLOAT(I-1)/TEN TMP1 = DEXP(-X(5)*TEMP) TMP2 = DEXP(-X(6)*(TEMP-X(9))**2) TMP3 = DEXP(-X(7)*(TEMP-X(10))**2) TMP4 = DEXP(-X(8)*(TEMP-X(11))**2) FVEC(I) = Y5(I) * - (X(1)*TMP1 + X(2)*TMP2 + X(3)*TMP3 + X(4)*TMP4) 420 CONTINUE 430 CONTINUE RETURN C C LAST CARD OF SUBROUTINE SSQFCN. C END minpack-19961126/ex/file040000644000175000017500000001453304210374513015731 0ustar sylvestresylvestre DOUBLE PRECISION FUNCTION DPMPAR(I) INTEGER I C ********** C C FUNCTION DPMPAR C C THIS FUNCTION PROVIDES DOUBLE PRECISION MACHINE PARAMETERS C WHEN THE APPROPRIATE SET OF DATA STATEMENTS IS ACTIVATED (BY C REMOVING THE C FROM COLUMN 1) AND ALL OTHER DATA STATEMENTS ARE C RENDERED INACTIVE. MOST OF THE PARAMETER VALUES WERE OBTAINED C FROM THE CORRESPONDING BELL LABORATORIES PORT LIBRARY FUNCTION. C C THE FUNCTION STATEMENT IS C C DOUBLE PRECISION FUNCTION DPMPAR(I) C C WHERE C C I IS AN INTEGER INPUT VARIABLE SET TO 1, 2, OR 3 WHICH C SELECTS THE DESIRED MACHINE PARAMETER. IF THE MACHINE HAS C T BASE B DIGITS AND ITS SMALLEST AND LARGEST EXPONENTS ARE C EMIN AND EMAX, RESPECTIVELY, THEN THESE PARAMETERS ARE C C DPMPAR(1) = B**(1 - T), THE MACHINE PRECISION, C C DPMPAR(2) = B**(EMIN - 1), THE SMALLEST MAGNITUDE, C C DPMPAR(3) = B**EMAX*(1 - B**(-T)), THE LARGEST MAGNITUDE. C C ARGONNE NATIONAL LABORATORY. MINPACK PROJECT. MARCH 1980. C BURTON S. GARBOW, KENNETH E. HILLSTROM, JORGE J. MORE C C ********** INTEGER MCHEPS(4) INTEGER MINMAG(4) INTEGER MAXMAG(4) DOUBLE PRECISION DMACH(3) EQUIVALENCE (DMACH(1),MCHEPS(1)) EQUIVALENCE (DMACH(2),MINMAG(1)) EQUIVALENCE (DMACH(3),MAXMAG(1)) C C MACHINE CONSTANTS FOR THE IBM 360/370 SERIES, C THE AMDAHL 470/V6, THE ICL 2900, THE ITEL AS/6, C THE XEROX SIGMA 5/7/9 AND THE SEL SYSTEMS 85/86. C DATA MCHEPS(1),MCHEPS(2) / Z34100000, Z00000000 / DATA MINMAG(1),MINMAG(2) / Z00100000, Z00000000 / DATA MAXMAG(1),MAXMAG(2) / Z7FFFFFFF, ZFFFFFFFF / C C MACHINE CONSTANTS FOR THE HONEYWELL 600/6000 SERIES. C C DATA MCHEPS(1),MCHEPS(2) / O606400000000, O000000000000 / C DATA MINMAG(1),MINMAG(2) / O402400000000, O000000000000 / C DATA MAXMAG(1),MAXMAG(2) / O376777777777, O777777777777 / C C MACHINE CONSTANTS FOR THE CDC 6000/7000 SERIES. C C DATA MCHEPS(1) / 15614000000000000000B / C DATA MCHEPS(2) / 15010000000000000000B / C C DATA MINMAG(1) / 00604000000000000000B / C DATA MINMAG(2) / 00000000000000000000B / C C DATA MAXMAG(1) / 37767777777777777777B / C DATA MAXMAG(2) / 37167777777777777777B / C C MACHINE CONSTANTS FOR THE PDP-10 (KA PROCESSOR). C C DATA MCHEPS(1),MCHEPS(2) / "114400000000, "000000000000 / C DATA MINMAG(1),MINMAG(2) / "033400000000, "000000000000 / C DATA MAXMAG(1),MAXMAG(2) / "377777777777, "344777777777 / C C MACHINE CONSTANTS FOR THE PDP-10 (KI PROCESSOR). C C DATA MCHEPS(1),MCHEPS(2) / "104400000000, "000000000000 / C DATA MINMAG(1),MINMAG(2) / "000400000000, "000000000000 / C DATA MAXMAG(1),MAXMAG(2) / "377777777777, "377777777777 / C C MACHINE CONSTANTS FOR THE PDP-11 FORTRAN SUPPORTING C 32-BIT INTEGERS (EXPRESSED IN INTEGER AND OCTAL). C C DATA MCHEPS(1),MCHEPS(2) / 620756992, 0 / C DATA MINMAG(1),MINMAG(2) / 8388608, 0 / C DATA MAXMAG(1),MAXMAG(2) / 2147483647, -1 / C C DATA MCHEPS(1),MCHEPS(2) / O04500000000, O00000000000 / C DATA MINMAG(1),MINMAG(2) / O00040000000, O00000000000 / C DATA MAXMAG(1),MAXMAG(2) / O17777777777, O37777777777 / C C MACHINE CONSTANTS FOR THE PDP-11 FORTRAN SUPPORTING C 16-BIT INTEGERS (EXPRESSED IN INTEGER AND OCTAL). C C DATA MCHEPS(1),MCHEPS(2) / 9472, 0 / C DATA MCHEPS(3),MCHEPS(4) / 0, 0 / C C DATA MINMAG(1),MINMAG(2) / 128, 0 / C DATA MINMAG(3),MINMAG(4) / 0, 0 / C C DATA MAXMAG(1),MAXMAG(2) / 32767, -1 / C DATA MAXMAG(3),MAXMAG(4) / -1, -1 / C C DATA MCHEPS(1),MCHEPS(2) / O022400, O000000 / C DATA MCHEPS(3),MCHEPS(4) / O000000, O000000 / C C DATA MINMAG(1),MINMAG(2) / O000200, O000000 / C DATA MINMAG(3),MINMAG(4) / O000000, O000000 / C C DATA MAXMAG(1),MAXMAG(2) / O077777, O177777 / C DATA MAXMAG(3),MAXMAG(4) / O177777, O177777 / C C MACHINE CONSTANTS FOR THE BURROUGHS 6700/7700 SYSTEMS. C C DATA MCHEPS(1) / O1451000000000000 / C DATA MCHEPS(2) / O0000000000000000 / C C DATA MINMAG(1) / O1771000000000000 / C DATA MINMAG(2) / O7770000000000000 / C C DATA MAXMAG(1) / O0777777777777777 / C DATA MAXMAG(2) / O7777777777777777 / C C MACHINE CONSTANTS FOR THE BURROUGHS 5700 SYSTEM. C C DATA MCHEPS(1) / O1451000000000000 / C DATA MCHEPS(2) / O0000000000000000 / C C DATA MINMAG(1) / O1771000000000000 / C DATA MINMAG(2) / O0000000000000000 / C C DATA MAXMAG(1) / O0777777777777777 / C DATA MAXMAG(2) / O0007777777777777 / C C MACHINE CONSTANTS FOR THE BURROUGHS 1700 SYSTEM. C C DATA MCHEPS(1) / ZCC6800000 / C DATA MCHEPS(2) / Z000000000 / C C DATA MINMAG(1) / ZC00800000 / C DATA MINMAG(2) / Z000000000 / C C DATA MAXMAG(1) / ZDFFFFFFFF / C DATA MAXMAG(2) / ZFFFFFFFFF / C C MACHINE CONSTANTS FOR THE UNIVAC 1100 SERIES. C C DATA MCHEPS(1),MCHEPS(2) / O170640000000, O000000000000 / C DATA MINMAG(1),MINMAG(2) / O000040000000, O000000000000 / C DATA MAXMAG(1),MAXMAG(2) / O377777777777, O777777777777 / C C MACHINE CONSTANTS FOR THE DATA GENERAL ECLIPSE S/200. C C NOTE - IT MAY BE APPROPRIATE TO INCLUDE THE FOLLOWING CARD - C STATIC DMACH(3) C C DATA MINMAG/20K,3*0/,MAXMAG/77777K,3*177777K/ C DATA MCHEPS/32020K,3*0/ C C MACHINE CONSTANTS FOR THE HARRIS 220. C C DATA MCHEPS(1),MCHEPS(2) / '20000000, '00000334 / C DATA MINMAG(1),MINMAG(2) / '20000000, '00000201 / C DATA MAXMAG(1),MAXMAG(2) / '37777777, '37777577 / C C MACHINE CONSTANTS FOR THE CRAY-1. C C DATA MCHEPS(1) / 0376424000000000000000B / C DATA MCHEPS(2) / 0000000000000000000000B / C C DATA MINMAG(1) / 0200034000000000000000B / C DATA MINMAG(2) / 0000000000000000000000B / C C DATA MAXMAG(1) / 0577777777777777777777B / C DATA MAXMAG(2) / 0000007777777777777776B / C C MACHINE CONSTANTS FOR THE PRIME 400. C C DATA MCHEPS(1),MCHEPS(2) / :10000000000, :00000000123 / C DATA MINMAG(1),MINMAG(2) / :10000000000, :00000100000 / C DATA MAXMAG(1),MAXMAG(2) / :17777777777, :37777677776 / C C MACHINE CONSTANTS FOR THE VAX-11. C C DATA MCHEPS(1),MCHEPS(2) / 9472, 0 / C DATA MINMAG(1),MINMAG(2) / 128, 0 / C DATA MAXMAG(1),MAXMAG(2) / -32769, -1 / C DPMPAR = DMACH(I) RETURN C C LAST CARD OF FUNCTION DPMPAR. C END minpack-19961126/ex/tlmdif.f0000644000175000017500000000453311616327304016354 0ustar sylvestresylvestreC DRIVER FOR LMDIF EXAMPLE. C DOUBLE PRECISION VERSION C C ********** INTEGER J,M,N,MAXFEV,MODE,NPRINT,INFO,NFEV,LDFJAC,NWRITE INTEGER IPVT(3) DOUBLE PRECISION FTOL,XTOL,GTOL,EPSFCN,FACTOR,FNORM DOUBLE PRECISION X(3),FVEC(15),DIAG(3),FJAC(15,3),QTF(3), * WA1(3),WA2(3),WA3(3),WA4(15) DOUBLE PRECISION ENORM,DPMPAR EXTERNAL FCN C C LOGICAL OUTPUT UNIT IS ASSUMED TO BE NUMBER 6. C DATA NWRITE /6/ C M = 15 N = 3 C C THE FOLLOWING STARTING VALUES PROVIDE A ROUGH FIT. C X(1) = 1.D0 X(2) = 1.D0 X(3) = 1.D0 C LDFJAC = 15 C C SET FTOL AND XTOL TO THE SQUARE ROOT OF THE MACHINE PRECISION C AND GTOL TO ZERO. UNLESS HIGH PRECISION SOLUTIONS ARE C REQUIRED, THESE ARE THE RECOMMENDED SETTINGS. C FTOL = DSQRT(DPMPAR(1)) XTOL = DSQRT(DPMPAR(1)) GTOL = 0.D0 C MAXFEV = 800 EPSFCN = 0.D0 MODE = 1 FACTOR = 1.D2 NPRINT = 0 C CALL LMDIF(FCN,M,N,X,FVEC,FTOL,XTOL,GTOL,MAXFEV,EPSFCN, * DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,FJAC,LDFJAC, * IPVT,QTF,WA1,WA2,WA3,WA4) FNORM = ENORM(M,FVEC) WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) STOP 1000 FORMAT (5X,31H FINAL L2 NORM OF THE RESIDUALS,D15.7 // * 5X,31H NUMBER OF FUNCTION EVALUATIONS,I10 // * 5X,15H EXIT PARAMETER,16X,I10 // * 5X,27H FINAL APPROXIMATE SOLUTION // 5X,3D15.7) C C LAST CARD OF DRIVER FOR LMDIF EXAMPLE. C END SUBROUTINE FCN(M,N,X,FVEC,IFLAG) INTEGER M,N,IFLAG DOUBLE PRECISION X(N),FVEC(M) C C SUBROUTINE FCN FOR LMDIF EXAMPLE. C INTEGER I DOUBLE PRECISION TMP1,TMP2,TMP3 DOUBLE PRECISION Y(15) DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8), * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15) * /1.4D-1,1.8D-1,2.2D-1,2.5D-1,2.9D-1,3.2D-1,3.5D-1,3.9D-1, * 3.7D-1,5.8D-1,7.3D-1,9.6D-1,1.34D0,2.1D0,4.39D0/ C IF (IFLAG .NE. 0) GO TO 5 C C INSERT PRINT STATEMENTS HERE WHEN NPRINT IS POSITIVE. C RETURN 5 CONTINUE DO 10 I = 1, 15 TMP1 = I TMP2 = 16 - I TMP3 = TMP1 IF (I .GT. 8) TMP3 = TMP2 FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3)) 10 CONTINUE RETURN C C LAST CARD OF SUBROUTINE FCN. 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IFS=$PATH_SEPARATOR for as_dir in $PATH$PATH_SEPARATOR/usr/xpg4/bin do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_prog in egrep; do for ac_exec_ext in '' $ac_executable_extensions; do ac_path_EGREP="$as_dir/$ac_prog$ac_exec_ext" { test -f "$ac_path_EGREP" && $as_test_x "$ac_path_EGREP"; } || continue # Check for GNU ac_path_EGREP and select it if it is found. # Check for GNU $ac_path_EGREP case `"$ac_path_EGREP" --version 2>&1` in *GNU*) ac_cv_path_EGREP="$ac_path_EGREP" ac_path_EGREP_found=:;; *) ac_count=0 echo $ECHO_N "0123456789$ECHO_C" >"conftest.in" while : do cat "conftest.in" "conftest.in" >"conftest.tmp" mv "conftest.tmp" "conftest.in" cp "conftest.in" "conftest.nl" echo 'EGREP' >> "conftest.nl" "$ac_path_EGREP" 'EGREP$' < "conftest.nl" >"conftest.out" 2>/dev/null || break diff "conftest.out" "conftest.nl" >/dev/null 2>&1 || break ac_count=`expr $ac_count + 1` if test $ac_count -gt ${ac_path_EGREP_max-0}; then # Best one so far, save it but keep looking for a better one ac_cv_path_EGREP="$ac_path_EGREP" ac_path_EGREP_max=$ac_count fi # 10*(2^10) chars as input seems more than enough test $ac_count -gt 10 && break done rm -f conftest.in conftest.tmp conftest.nl conftest.out;; esac $ac_path_EGREP_found && break 3 done done done IFS=$as_save_IFS fi EGREP="$ac_cv_path_EGREP" if test -z "$EGREP"; then { { echo "$as_me:$LINENO: error: no acceptable $ac_prog_name could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" >&5 echo "$as_me: error: no acceptable $ac_prog_name could be found in $PATH$PATH_SEPARATOR/usr/xpg4/bin" >&2;} { (exit 1); exit 1; }; } fi else ac_cv_path_EGREP=$EGREP fi fi fi { echo "$as_me:$LINENO: result: $ac_cv_path_EGREP" >&5 echo "${ECHO_T}$ac_cv_path_EGREP" >&6; } EGREP="$ac_cv_path_EGREP" # Check whether --with-gnu-ld was given. if test "${with_gnu_ld+set}" = set; then withval=$with_gnu_ld; test "$withval" = no || with_gnu_ld=yes else with_gnu_ld=no fi ac_prog=ld if test "$GCC" = yes; then # Check if gcc -print-prog-name=ld gives a path. { echo "$as_me:$LINENO: checking for ld used by $CC" >&5 echo $ECHO_N "checking for ld used by $CC... $ECHO_C" >&6; } case $host in *-*-mingw*) # gcc leaves a trailing carriage return which upsets mingw ac_prog=`($CC -print-prog-name=ld) 2>&5 | tr -d '\015'` ;; *) ac_prog=`($CC -print-prog-name=ld) 2>&5` ;; esac case $ac_prog in # Accept absolute paths. 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} if test "${lt_cv_ld_reload_flag+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else lt_cv_ld_reload_flag='-r' fi { echo "$as_me:$LINENO: result: $lt_cv_ld_reload_flag" >&5 echo "${ECHO_T}$lt_cv_ld_reload_flag" >&6; } reload_flag=$lt_cv_ld_reload_flag case $reload_flag in "" | " "*) ;; *) reload_flag=" $reload_flag" ;; esac reload_cmds='$LD$reload_flag -o $output$reload_objs' case $host_os in darwin*) if test "$GCC" = yes; then reload_cmds='$LTCC $LTCFLAGS -nostdlib ${wl}-r -o $output$reload_objs' else reload_cmds='$LD$reload_flag -o $output$reload_objs' fi ;; esac { echo "$as_me:$LINENO: checking for BSD-compatible nm" >&5 echo $ECHO_N "checking for BSD-compatible nm... $ECHO_C" >&6; } if test "${lt_cv_path_NM+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$NM"; then # Let the user override the test. lt_cv_path_NM="$NM" else lt_nm_to_check="${ac_tool_prefix}nm" if test -n "$ac_tool_prefix" && test "$build" = "$host"; then lt_nm_to_check="$lt_nm_to_check nm" fi for lt_tmp_nm in $lt_nm_to_check; do lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR for ac_dir in $PATH /usr/ccs/bin/elf /usr/ccs/bin /usr/ucb /bin; do IFS="$lt_save_ifs" test -z "$ac_dir" && ac_dir=. tmp_nm="$ac_dir/$lt_tmp_nm" if test -f "$tmp_nm" || test -f "$tmp_nm$ac_exeext" ; then # Check to see if the nm accepts a BSD-compat flag. # Adding the `sed 1q' prevents false positives on HP-UX, which says: # nm: unknown option "B" ignored # Tru64's nm complains that /dev/null is an invalid object file case `"$tmp_nm" -B /dev/null 2>&1 | sed '1q'` in */dev/null* | *'Invalid file or object type'*) lt_cv_path_NM="$tmp_nm -B" break ;; *) case `"$tmp_nm" -p /dev/null 2>&1 | sed '1q'` in */dev/null*) lt_cv_path_NM="$tmp_nm -p" break ;; *) lt_cv_path_NM=${lt_cv_path_NM="$tmp_nm"} # keep the first match, but continue # so that we can try to find one that supports BSD flags ;; esac ;; esac fi done IFS="$lt_save_ifs" done test -z "$lt_cv_path_NM" && lt_cv_path_NM=nm fi fi { echo "$as_me:$LINENO: result: $lt_cv_path_NM" >&5 echo "${ECHO_T}$lt_cv_path_NM" >&6; } NM="$lt_cv_path_NM" { echo "$as_me:$LINENO: checking whether ln -s works" >&5 echo $ECHO_N "checking whether ln -s works... $ECHO_C" >&6; } LN_S=$as_ln_s if test "$LN_S" = "ln -s"; then { echo "$as_me:$LINENO: result: yes" >&5 echo "${ECHO_T}yes" >&6; } else { echo "$as_me:$LINENO: result: no, using $LN_S" >&5 echo "${ECHO_T}no, using $LN_S" >&6; } fi { echo "$as_me:$LINENO: checking how to recognize dependent libraries" >&5 echo $ECHO_N "checking how to recognize dependent libraries... $ECHO_C" >&6; } if test "${lt_cv_deplibs_check_method+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else lt_cv_file_magic_cmd='$MAGIC_CMD' lt_cv_file_magic_test_file= lt_cv_deplibs_check_method='unknown' # Need to set the preceding variable on all platforms that support # interlibrary dependencies. # 'none' -- dependencies not supported. # `unknown' -- same as none, but documents that we really don't know. # 'pass_all' -- all dependencies passed with no checks. # 'test_compile' -- check by making test program. # 'file_magic [[regex]]' -- check by looking for files in library path # which responds to the $file_magic_cmd with a given extended regex. # If you have `file' or equivalent on your system and you're not sure # whether `pass_all' will *always* work, you probably want this one. case $host_os in aix[4-9]*) lt_cv_deplibs_check_method=pass_all ;; beos*) lt_cv_deplibs_check_method=pass_all ;; bsdi[45]*) lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (shared object|dynamic lib)' lt_cv_file_magic_cmd='/usr/bin/file -L' lt_cv_file_magic_test_file=/shlib/libc.so ;; cygwin*) # func_win32_libid is a shell function defined in ltmain.sh lt_cv_deplibs_check_method='file_magic ^x86 archive import|^x86 DLL' lt_cv_file_magic_cmd='func_win32_libid' ;; mingw* | pw32*) # Base MSYS/MinGW do not provide the 'file' command needed by # func_win32_libid shell function, so use a weaker test based on 'objdump', # unless we find 'file', for example because we are cross-compiling. if ( file / ) >/dev/null 2>&1; then lt_cv_deplibs_check_method='file_magic ^x86 archive import|^x86 DLL' lt_cv_file_magic_cmd='func_win32_libid' else lt_cv_deplibs_check_method='file_magic file format pei*-i386(.*architecture: i386)?' lt_cv_file_magic_cmd='$OBJDUMP -f' fi ;; darwin* | rhapsody*) lt_cv_deplibs_check_method=pass_all ;; freebsd* | dragonfly*) if echo __ELF__ | $CC -E - | grep __ELF__ > /dev/null; then case $host_cpu in i*86 ) # Not sure whether the presence of OpenBSD here was a mistake. # Let's accept both of them until this is cleared up. lt_cv_deplibs_check_method='file_magic (FreeBSD|OpenBSD|DragonFly)/i[3-9]86 (compact )?demand paged shared library' lt_cv_file_magic_cmd=/usr/bin/file lt_cv_file_magic_test_file=`echo /usr/lib/libc.so.*` ;; esac else lt_cv_deplibs_check_method=pass_all fi ;; gnu*) lt_cv_deplibs_check_method=pass_all ;; hpux10.20* | hpux11*) lt_cv_file_magic_cmd=/usr/bin/file case $host_cpu in ia64*) lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|ELF-[0-9][0-9]) shared object file - IA64' lt_cv_file_magic_test_file=/usr/lib/hpux32/libc.so ;; hppa*64*) lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|ELF-[0-9][0-9]) shared object file - PA-RISC [0-9].[0-9]' lt_cv_file_magic_test_file=/usr/lib/pa20_64/libc.sl ;; *) lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|PA-RISC[0-9].[0-9]) shared library' lt_cv_file_magic_test_file=/usr/lib/libc.sl ;; esac ;; interix[3-9]*) # PIC code is broken on Interix 3.x, that's why |\.a not |_pic\.a here lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so|\.a)$' ;; irix5* | irix6* | nonstopux*) case $LD in *-32|*"-32 ") libmagic=32-bit;; *-n32|*"-n32 ") libmagic=N32;; *-64|*"-64 ") libmagic=64-bit;; *) libmagic=never-match;; esac lt_cv_deplibs_check_method=pass_all ;; # This must be Linux ELF. linux* | k*bsd*-gnu) lt_cv_deplibs_check_method=pass_all ;; netbsd* | netbsdelf*-gnu) if echo __ELF__ | $CC -E - | grep __ELF__ > /dev/null; then lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|_pic\.a)$' else lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so|_pic\.a)$' fi ;; newos6*) lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (executable|dynamic lib)' lt_cv_file_magic_cmd=/usr/bin/file lt_cv_file_magic_test_file=/usr/lib/libnls.so ;; nto-qnx*) lt_cv_deplibs_check_method=unknown ;; openbsd*) if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|\.so|_pic\.a)$' else lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|_pic\.a)$' fi ;; osf3* | osf4* | osf5*) lt_cv_deplibs_check_method=pass_all ;; rdos*) lt_cv_deplibs_check_method=pass_all ;; solaris*) lt_cv_deplibs_check_method=pass_all ;; sysv4 | sysv4.3*) case $host_vendor in motorola) lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (shared object|dynamic lib) M[0-9][0-9]* Version [0-9]' lt_cv_file_magic_test_file=`echo /usr/lib/libc.so*` ;; ncr) lt_cv_deplibs_check_method=pass_all ;; sequent) lt_cv_file_magic_cmd='/bin/file' lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [LM]SB (shared object|dynamic lib )' ;; sni) lt_cv_file_magic_cmd='/bin/file' lt_cv_deplibs_check_method="file_magic ELF [0-9][0-9]*-bit [LM]SB dynamic lib" lt_cv_file_magic_test_file=/lib/libc.so ;; siemens) lt_cv_deplibs_check_method=pass_all ;; pc) lt_cv_deplibs_check_method=pass_all ;; esac ;; sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*) lt_cv_deplibs_check_method=pass_all ;; esac fi { echo "$as_me:$LINENO: result: $lt_cv_deplibs_check_method" >&5 echo "${ECHO_T}$lt_cv_deplibs_check_method" >&6; } file_magic_cmd=$lt_cv_file_magic_cmd deplibs_check_method=$lt_cv_deplibs_check_method test -z "$deplibs_check_method" && deplibs_check_method=unknown # If no C compiler was specified, use CC. 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SAVE_CFLAGS="$CFLAGS" CFLAGS="$CFLAGS -belf" { echo "$as_me:$LINENO: checking whether the C compiler needs -belf" >&5 echo $ECHO_N "checking whether the C compiler needs -belf... $ECHO_C" >&6; } if test "${lt_cv_cc_needs_belf+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else ac_ext=c ac_cpp='$CPP $CPPFLAGS' ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' ac_compiler_gnu=$ac_cv_c_compiler_gnu cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_cv_cc_needs_belf=yes else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 lt_cv_cc_needs_belf=no fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext ac_ext=c ac_cpp='$CPP $CPPFLAGS' ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' ac_compiler_gnu=$ac_cv_c_compiler_gnu fi { echo "$as_me:$LINENO: result: $lt_cv_cc_needs_belf" >&5 echo "${ECHO_T}$lt_cv_cc_needs_belf" >&6; } if test x"$lt_cv_cc_needs_belf" != x"yes"; then # this is probably gcc 2.8.0, egcs 1.0 or newer; no need for -belf CFLAGS="$SAVE_CFLAGS" fi ;; sparc*-*solaris*) # Find out which ABI we are using. echo 'int i;' > conftest.$ac_ext if { (eval echo "$as_me:$LINENO: \"$ac_compile\"") >&5 (eval $ac_compile) 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; then case `/usr/bin/file conftest.o` in *64-bit*) case $lt_cv_prog_gnu_ld in yes*) LD="${LD-ld} -m elf64_sparc" ;; *) if ${LD-ld} -64 -r -o conftest2.o conftest.o >/dev/null 2>&1; then LD="${LD-ld} -64" fi ;; esac ;; esac fi rm -rf conftest* ;; esac need_locks="$enable_libtool_lock" ac_ext=c ac_cpp='$CPP $CPPFLAGS' ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' ac_compiler_gnu=$ac_cv_c_compiler_gnu { echo "$as_me:$LINENO: checking how to run the C preprocessor" >&5 echo $ECHO_N "checking how to run the C preprocessor... $ECHO_C" >&6; } # On Suns, sometimes $CPP names a directory. if test -n "$CPP" && test -d "$CPP"; then CPP= fi if test -z "$CPP"; then if test "${ac_cv_prog_CPP+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else # Double quotes because CPP needs to be expanded for CPP in "$CC -E" "$CC -E -traditional-cpp" "/lib/cpp" do ac_preproc_ok=false for ac_c_preproc_warn_flag in '' yes do # Use a header file that comes with gcc, so configuring glibc # with a fresh cross-compiler works. # Prefer to if __STDC__ is defined, since # exists even on freestanding compilers. # On the NeXT, cc -E runs the code through the compiler's parser, # not just through cpp. "Syntax error" is here to catch this case. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #ifdef __STDC__ # include #else # include #endif Syntax error _ACEOF if { (ac_try="$ac_cpp conftest.$ac_ext" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_cpp conftest.$ac_ext") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } >/dev/null && { test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" || test ! -s conftest.err }; then : else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 # Broken: fails on valid input. continue fi rm -f conftest.err conftest.$ac_ext # OK, works on sane cases. Now check whether nonexistent headers # can be detected and how. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include _ACEOF if { (ac_try="$ac_cpp conftest.$ac_ext" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_cpp conftest.$ac_ext") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } >/dev/null && { test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" || test ! -s conftest.err }; then # Broken: success on invalid input. continue else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 # Passes both tests. ac_preproc_ok=: break fi rm -f conftest.err conftest.$ac_ext done # Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped. rm -f conftest.err conftest.$ac_ext if $ac_preproc_ok; then break fi done ac_cv_prog_CPP=$CPP fi CPP=$ac_cv_prog_CPP else ac_cv_prog_CPP=$CPP fi { echo "$as_me:$LINENO: result: $CPP" >&5 echo "${ECHO_T}$CPP" >&6; } ac_preproc_ok=false for ac_c_preproc_warn_flag in '' yes do # Use a header file that comes with gcc, so configuring glibc # with a fresh cross-compiler works. # Prefer to if __STDC__ is defined, since # exists even on freestanding compilers. # On the NeXT, cc -E runs the code through the compiler's parser, # not just through cpp. "Syntax error" is here to catch this case. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #ifdef __STDC__ # include #else # include #endif Syntax error _ACEOF if { (ac_try="$ac_cpp conftest.$ac_ext" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_cpp conftest.$ac_ext") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } >/dev/null && { test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" || test ! -s conftest.err }; then : else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 # Broken: fails on valid input. continue fi rm -f conftest.err conftest.$ac_ext # OK, works on sane cases. Now check whether nonexistent headers # can be detected and how. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include _ACEOF if { (ac_try="$ac_cpp conftest.$ac_ext" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_cpp conftest.$ac_ext") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } >/dev/null && { test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" || test ! -s conftest.err }; then # Broken: success on invalid input. continue else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 # Passes both tests. ac_preproc_ok=: break fi rm -f conftest.err conftest.$ac_ext done # Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped. rm -f conftest.err conftest.$ac_ext if $ac_preproc_ok; then : else { { echo "$as_me:$LINENO: error: C preprocessor \"$CPP\" fails sanity check See \`config.log' for more details." >&5 echo "$as_me: error: C preprocessor \"$CPP\" fails sanity check See \`config.log' for more details." >&2;} { (exit 1); exit 1; }; } fi ac_ext=c ac_cpp='$CPP $CPPFLAGS' ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' ac_compiler_gnu=$ac_cv_c_compiler_gnu { echo "$as_me:$LINENO: checking for ANSI C header files" >&5 echo $ECHO_N "checking for ANSI C header files... $ECHO_C" >&6; } if test "${ac_cv_header_stdc+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include #include #include #include int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext if { (ac_try="$ac_compile" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_compile") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest.$ac_objext; then ac_cv_header_stdc=yes else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 ac_cv_header_stdc=no fi rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext if test $ac_cv_header_stdc = yes; then # SunOS 4.x string.h does not declare mem*, contrary to ANSI. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include _ACEOF if (eval "$ac_cpp conftest.$ac_ext") 2>&5 | $EGREP "memchr" >/dev/null 2>&1; then : else ac_cv_header_stdc=no fi rm -f conftest* fi if test $ac_cv_header_stdc = yes; then # ISC 2.0.2 stdlib.h does not declare free, contrary to ANSI. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include _ACEOF if (eval "$ac_cpp conftest.$ac_ext") 2>&5 | $EGREP "free" >/dev/null 2>&1; then : else ac_cv_header_stdc=no fi rm -f conftest* fi if test $ac_cv_header_stdc = yes; then # /bin/cc in Irix-4.0.5 gets non-ANSI ctype macros unless using -ansi. if test "$cross_compiling" = yes; then : else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ #include #include #if ((' ' & 0x0FF) == 0x020) # define ISLOWER(c) ('a' <= (c) && (c) <= 'z') # define TOUPPER(c) (ISLOWER(c) ? 'A' + ((c) - 'a') : (c)) #else # define ISLOWER(c) \ (('a' <= (c) && (c) <= 'i') \ || ('j' <= (c) && (c) <= 'r') \ || ('s' <= (c) && (c) <= 'z')) # define TOUPPER(c) (ISLOWER(c) ? ((c) | 0x40) : (c)) #endif #define XOR(e, f) (((e) && !(f)) || (!(e) && (f))) int main () { int i; for (i = 0; i < 256; i++) if (XOR (islower (i), ISLOWER (i)) || toupper (i) != TOUPPER (i)) return 2; return 0; } _ACEOF rm -f conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { ac_try='./conftest$ac_exeext' { (case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_try") 2>&5 ac_status=$? echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); }; }; then : else echo "$as_me: program exited with status $ac_status" >&5 echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 ( exit $ac_status ) ac_cv_header_stdc=no fi rm -f core *.core core.conftest.* gmon.out bb.out conftest$ac_exeext conftest.$ac_objext conftest.$ac_ext fi fi fi { echo "$as_me:$LINENO: result: $ac_cv_header_stdc" >&5 echo "${ECHO_T}$ac_cv_header_stdc" >&6; } if test $ac_cv_header_stdc = yes; then cat >>confdefs.h <<\_ACEOF #define STDC_HEADERS 1 _ACEOF fi # On IRIX 5.3, sys/types and inttypes.h are conflicting. for ac_header in sys/types.h sys/stat.h stdlib.h string.h memory.h strings.h \ inttypes.h stdint.h unistd.h do as_ac_Header=`echo "ac_cv_header_$ac_header" | $as_tr_sh` { echo "$as_me:$LINENO: checking for $ac_header" >&5 echo $ECHO_N "checking for $ac_header... $ECHO_C" >&6; } if { as_var=$as_ac_Header; eval "test \"\${$as_var+set}\" = set"; }; then echo $ECHO_N "(cached) $ECHO_C" >&6 else cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ $ac_includes_default #include <$ac_header> _ACEOF rm -f conftest.$ac_objext if { (ac_try="$ac_compile" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_compile") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest.$ac_objext; then eval "$as_ac_Header=yes" else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 eval "$as_ac_Header=no" fi rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext fi ac_res=`eval echo '${'$as_ac_Header'}'` { echo "$as_me:$LINENO: result: $ac_res" >&5 echo "${ECHO_T}$ac_res" >&6; } if test `eval echo '${'$as_ac_Header'}'` = yes; then cat >>confdefs.h <<_ACEOF #define `echo "HAVE_$ac_header" | $as_tr_cpp` 1 _ACEOF fi done for ac_header in dlfcn.h do as_ac_Header=`echo "ac_cv_header_$ac_header" | $as_tr_sh` if { as_var=$as_ac_Header; eval "test \"\${$as_var+set}\" = set"; }; then { echo "$as_me:$LINENO: checking for $ac_header" >&5 echo $ECHO_N "checking for $ac_header... $ECHO_C" >&6; } if { as_var=$as_ac_Header; eval "test \"\${$as_var+set}\" = set"; }; then echo $ECHO_N "(cached) $ECHO_C" >&6 fi ac_res=`eval echo '${'$as_ac_Header'}'` { echo "$as_me:$LINENO: result: $ac_res" >&5 echo "${ECHO_T}$ac_res" >&6; } else # Is the header compilable? 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Xsed='sed -e 1s/^X//' sed_quote_subst='s/\([\\"\\`$\\\\]\)/\\\1/g' # Same as above, but do not quote variable references. double_quote_subst='s/\([\\"\\`\\\\]\)/\\\1/g' # Sed substitution to delay expansion of an escaped shell variable in a # double_quote_subst'ed string. delay_variable_subst='s/\\\\\\\\\\\$/\\\\\\$/g' # Sed substitution to avoid accidental globbing in evaled expressions no_glob_subst='s/\*/\\\*/g' # Constants: rm="rm -f" # Global variables: default_ofile=libtool can_build_shared=yes # All known linkers require a `.a' archive for static linking (except MSVC, # which needs '.lib'). libext=a ltmain="$ac_aux_dir/ltmain.sh" ofile="$default_ofile" with_gnu_ld="$lt_cv_prog_gnu_ld" if test -n "$ac_tool_prefix"; then # Extract the first word of "${ac_tool_prefix}ar", so it can be a program name with args. set dummy ${ac_tool_prefix}ar; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_AR+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$AR"; then ac_cv_prog_AR="$AR" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_AR="${ac_tool_prefix}ar" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi AR=$ac_cv_prog_AR if test -n "$AR"; then { echo "$as_me:$LINENO: result: $AR" >&5 echo "${ECHO_T}$AR" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi fi if test -z "$ac_cv_prog_AR"; then ac_ct_AR=$AR # Extract the first word of "ar", so it can be a program name with args. set dummy ar; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_ac_ct_AR+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_AR"; then ac_cv_prog_ac_ct_AR="$ac_ct_AR" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_ac_ct_AR="ar" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi ac_ct_AR=$ac_cv_prog_ac_ct_AR if test -n "$ac_ct_AR"; then { echo "$as_me:$LINENO: result: $ac_ct_AR" >&5 echo "${ECHO_T}$ac_ct_AR" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test "x$ac_ct_AR" = x; then AR="false" else case $cross_compiling:$ac_tool_warned in yes:) { echo "$as_me:$LINENO: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&5 echo "$as_me: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&2;} ac_tool_warned=yes ;; esac AR=$ac_ct_AR fi else AR="$ac_cv_prog_AR" fi if test -n "$ac_tool_prefix"; then # Extract the first word of "${ac_tool_prefix}ranlib", so it can be a program name with args. set dummy ${ac_tool_prefix}ranlib; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_RANLIB+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$RANLIB"; then ac_cv_prog_RANLIB="$RANLIB" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_RANLIB="${ac_tool_prefix}ranlib" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi RANLIB=$ac_cv_prog_RANLIB if test -n "$RANLIB"; then { echo "$as_me:$LINENO: result: $RANLIB" >&5 echo "${ECHO_T}$RANLIB" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi fi if test -z "$ac_cv_prog_RANLIB"; then ac_ct_RANLIB=$RANLIB # Extract the first word of "ranlib", so it can be a program name with args. set dummy ranlib; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_ac_ct_RANLIB+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_RANLIB"; then ac_cv_prog_ac_ct_RANLIB="$ac_ct_RANLIB" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_ac_ct_RANLIB="ranlib" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi ac_ct_RANLIB=$ac_cv_prog_ac_ct_RANLIB if test -n "$ac_ct_RANLIB"; then { echo "$as_me:$LINENO: result: $ac_ct_RANLIB" >&5 echo "${ECHO_T}$ac_ct_RANLIB" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test "x$ac_ct_RANLIB" = x; then RANLIB=":" else case $cross_compiling:$ac_tool_warned in yes:) { echo "$as_me:$LINENO: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&5 echo "$as_me: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&2;} ac_tool_warned=yes ;; esac RANLIB=$ac_ct_RANLIB fi else RANLIB="$ac_cv_prog_RANLIB" fi if test -n "$ac_tool_prefix"; then # Extract the first word of "${ac_tool_prefix}strip", so it can be a program name with args. set dummy ${ac_tool_prefix}strip; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_STRIP+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$STRIP"; then ac_cv_prog_STRIP="$STRIP" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_STRIP="${ac_tool_prefix}strip" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi STRIP=$ac_cv_prog_STRIP if test -n "$STRIP"; then { echo "$as_me:$LINENO: result: $STRIP" >&5 echo "${ECHO_T}$STRIP" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi fi if test -z "$ac_cv_prog_STRIP"; then ac_ct_STRIP=$STRIP # Extract the first word of "strip", so it can be a program name with args. set dummy strip; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_ac_ct_STRIP+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_STRIP"; then ac_cv_prog_ac_ct_STRIP="$ac_ct_STRIP" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_ac_ct_STRIP="strip" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi ac_ct_STRIP=$ac_cv_prog_ac_ct_STRIP if test -n "$ac_ct_STRIP"; then { echo "$as_me:$LINENO: result: $ac_ct_STRIP" >&5 echo "${ECHO_T}$ac_ct_STRIP" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test "x$ac_ct_STRIP" = x; then STRIP=":" else case $cross_compiling:$ac_tool_warned in yes:) { echo "$as_me:$LINENO: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&5 echo "$as_me: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&2;} ac_tool_warned=yes ;; esac STRIP=$ac_ct_STRIP fi else STRIP="$ac_cv_prog_STRIP" fi old_CC="$CC" old_CFLAGS="$CFLAGS" # Set sane defaults for various variables test -z "$AR" && AR=ar test -z "$AR_FLAGS" && AR_FLAGS=cru test -z "$AS" && AS=as test -z "$CC" && CC=cc test -z "$LTCC" && LTCC=$CC test -z "$LTCFLAGS" && LTCFLAGS=$CFLAGS test -z "$DLLTOOL" && DLLTOOL=dlltool test -z "$LD" && LD=ld test -z "$LN_S" && LN_S="ln -s" test -z "$MAGIC_CMD" && MAGIC_CMD=file test -z "$NM" && NM=nm test -z "$SED" && SED=sed test -z "$OBJDUMP" && OBJDUMP=objdump test -z "$RANLIB" && RANLIB=: test -z "$STRIP" && STRIP=: test -z "$ac_objext" && ac_objext=o # Determine commands to create old-style static archives. old_archive_cmds='$AR $AR_FLAGS $oldlib$oldobjs' old_postinstall_cmds='chmod 644 $oldlib' old_postuninstall_cmds= if test -n "$RANLIB"; then case $host_os in openbsd*) old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB -t \$oldlib" ;; *) old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB \$oldlib" ;; esac old_archive_cmds="$old_archive_cmds~\$RANLIB \$oldlib" fi for cc_temp in $compiler""; do case $cc_temp in compile | *[\\/]compile | ccache | *[\\/]ccache ) ;; distcc | *[\\/]distcc | purify | *[\\/]purify ) ;; \-*) ;; *) break;; esac done cc_basename=`$echo "X$cc_temp" | $Xsed -e 's%.*/%%' -e "s%^$host_alias-%%"` # Only perform the check for file, if the check method requires it case $deplibs_check_method in file_magic*) if test "$file_magic_cmd" = '$MAGIC_CMD'; then { echo "$as_me:$LINENO: checking for ${ac_tool_prefix}file" >&5 echo $ECHO_N "checking for ${ac_tool_prefix}file... $ECHO_C" >&6; } if test "${lt_cv_path_MAGIC_CMD+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else case $MAGIC_CMD in [\\/*] | ?:[\\/]*) lt_cv_path_MAGIC_CMD="$MAGIC_CMD" # Let the user override the test with a path. ;; *) lt_save_MAGIC_CMD="$MAGIC_CMD" lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR ac_dummy="/usr/bin$PATH_SEPARATOR$PATH" for ac_dir in $ac_dummy; do IFS="$lt_save_ifs" test -z "$ac_dir" && ac_dir=. if test -f $ac_dir/${ac_tool_prefix}file; then lt_cv_path_MAGIC_CMD="$ac_dir/${ac_tool_prefix}file" if test -n "$file_magic_test_file"; then case $deplibs_check_method in "file_magic "*) file_magic_regex=`expr "$deplibs_check_method" : "file_magic \(.*\)"` MAGIC_CMD="$lt_cv_path_MAGIC_CMD" if eval $file_magic_cmd \$file_magic_test_file 2> /dev/null | $EGREP "$file_magic_regex" > /dev/null; then : else cat <&2 *** Warning: the command libtool uses to detect shared libraries, *** $file_magic_cmd, produces output that libtool cannot recognize. *** The result is that libtool may fail to recognize shared libraries *** as such. This will affect the creation of libtool libraries that *** depend on shared libraries, but programs linked with such libtool *** libraries will work regardless of this problem. Nevertheless, you *** may want to report the problem to your system manager and/or to *** bug-libtool@gnu.org EOF fi ;; esac fi break fi done IFS="$lt_save_ifs" MAGIC_CMD="$lt_save_MAGIC_CMD" ;; esac fi MAGIC_CMD="$lt_cv_path_MAGIC_CMD" if test -n "$MAGIC_CMD"; then { echo "$as_me:$LINENO: result: $MAGIC_CMD" >&5 echo "${ECHO_T}$MAGIC_CMD" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test -z "$lt_cv_path_MAGIC_CMD"; then if test -n "$ac_tool_prefix"; then { echo "$as_me:$LINENO: checking for file" >&5 echo $ECHO_N "checking for file... $ECHO_C" >&6; } if test "${lt_cv_path_MAGIC_CMD+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else case $MAGIC_CMD in [\\/*] | ?:[\\/]*) lt_cv_path_MAGIC_CMD="$MAGIC_CMD" # Let the user override the test with a path. ;; *) lt_save_MAGIC_CMD="$MAGIC_CMD" lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR ac_dummy="/usr/bin$PATH_SEPARATOR$PATH" for ac_dir in $ac_dummy; do IFS="$lt_save_ifs" test -z "$ac_dir" && ac_dir=. if test -f $ac_dir/file; then lt_cv_path_MAGIC_CMD="$ac_dir/file" if test -n "$file_magic_test_file"; then case $deplibs_check_method in "file_magic "*) file_magic_regex=`expr "$deplibs_check_method" : "file_magic \(.*\)"` MAGIC_CMD="$lt_cv_path_MAGIC_CMD" if eval $file_magic_cmd \$file_magic_test_file 2> /dev/null | $EGREP "$file_magic_regex" > /dev/null; then : else cat <&2 *** Warning: the command libtool uses to detect shared libraries, *** $file_magic_cmd, produces output that libtool cannot recognize. *** The result is that libtool may fail to recognize shared libraries *** as such. This will affect the creation of libtool libraries that *** depend on shared libraries, but programs linked with such libtool *** libraries will work regardless of this problem. Nevertheless, you *** may want to report the problem to your system manager and/or to *** bug-libtool@gnu.org EOF fi ;; esac fi break fi done IFS="$lt_save_ifs" MAGIC_CMD="$lt_save_MAGIC_CMD" ;; esac fi MAGIC_CMD="$lt_cv_path_MAGIC_CMD" if test -n "$MAGIC_CMD"; then { echo "$as_me:$LINENO: result: $MAGIC_CMD" >&5 echo "${ECHO_T}$MAGIC_CMD" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi else MAGIC_CMD=: fi fi fi ;; esac case $host_os in rhapsody* | darwin*) if test -n "$ac_tool_prefix"; then # Extract the first word of "${ac_tool_prefix}dsymutil", so it can be a program name with args. set dummy ${ac_tool_prefix}dsymutil; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_DSYMUTIL+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$DSYMUTIL"; then ac_cv_prog_DSYMUTIL="$DSYMUTIL" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_DSYMUTIL="${ac_tool_prefix}dsymutil" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi DSYMUTIL=$ac_cv_prog_DSYMUTIL if test -n "$DSYMUTIL"; then { echo "$as_me:$LINENO: result: $DSYMUTIL" >&5 echo "${ECHO_T}$DSYMUTIL" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi fi if test -z "$ac_cv_prog_DSYMUTIL"; then ac_ct_DSYMUTIL=$DSYMUTIL # Extract the first word of "dsymutil", so it can be a program name with args. set dummy dsymutil; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_ac_ct_DSYMUTIL+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_DSYMUTIL"; then ac_cv_prog_ac_ct_DSYMUTIL="$ac_ct_DSYMUTIL" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_ac_ct_DSYMUTIL="dsymutil" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi ac_ct_DSYMUTIL=$ac_cv_prog_ac_ct_DSYMUTIL if test -n "$ac_ct_DSYMUTIL"; then { echo "$as_me:$LINENO: result: $ac_ct_DSYMUTIL" >&5 echo "${ECHO_T}$ac_ct_DSYMUTIL" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test "x$ac_ct_DSYMUTIL" = x; then DSYMUTIL=":" else case $cross_compiling:$ac_tool_warned in yes:) { echo "$as_me:$LINENO: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&5 echo "$as_me: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&2;} ac_tool_warned=yes ;; esac DSYMUTIL=$ac_ct_DSYMUTIL fi else DSYMUTIL="$ac_cv_prog_DSYMUTIL" fi if test -n "$ac_tool_prefix"; then # Extract the first word of "${ac_tool_prefix}nmedit", so it can be a program name with args. set dummy ${ac_tool_prefix}nmedit; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_NMEDIT+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$NMEDIT"; then ac_cv_prog_NMEDIT="$NMEDIT" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_NMEDIT="${ac_tool_prefix}nmedit" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi NMEDIT=$ac_cv_prog_NMEDIT if test -n "$NMEDIT"; then { echo "$as_me:$LINENO: result: $NMEDIT" >&5 echo "${ECHO_T}$NMEDIT" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi fi if test -z "$ac_cv_prog_NMEDIT"; then ac_ct_NMEDIT=$NMEDIT # Extract the first word of "nmedit", so it can be a program name with args. set dummy nmedit; ac_word=$2 { echo "$as_me:$LINENO: checking for $ac_word" >&5 echo $ECHO_N "checking for $ac_word... $ECHO_C" >&6; } if test "${ac_cv_prog_ac_ct_NMEDIT+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else if test -n "$ac_ct_NMEDIT"; then ac_cv_prog_ac_ct_NMEDIT="$ac_ct_NMEDIT" # Let the user override the test. else as_save_IFS=$IFS; IFS=$PATH_SEPARATOR for as_dir in $PATH do IFS=$as_save_IFS test -z "$as_dir" && as_dir=. for ac_exec_ext in '' $ac_executable_extensions; do if { test -f "$as_dir/$ac_word$ac_exec_ext" && $as_test_x "$as_dir/$ac_word$ac_exec_ext"; }; then ac_cv_prog_ac_ct_NMEDIT="nmedit" echo "$as_me:$LINENO: found $as_dir/$ac_word$ac_exec_ext" >&5 break 2 fi done done IFS=$as_save_IFS fi fi ac_ct_NMEDIT=$ac_cv_prog_ac_ct_NMEDIT if test -n "$ac_ct_NMEDIT"; then { echo "$as_me:$LINENO: result: $ac_ct_NMEDIT" >&5 echo "${ECHO_T}$ac_ct_NMEDIT" >&6; } else { echo "$as_me:$LINENO: result: no" >&5 echo "${ECHO_T}no" >&6; } fi if test "x$ac_ct_NMEDIT" = x; then NMEDIT=":" else case $cross_compiling:$ac_tool_warned in yes:) { echo "$as_me:$LINENO: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&5 echo "$as_me: WARNING: In the future, Autoconf will not detect cross-tools whose name does not start with the host triplet. If you think this configuration is useful to you, please write to autoconf@gnu.org." >&2;} ac_tool_warned=yes ;; esac NMEDIT=$ac_ct_NMEDIT fi else NMEDIT="$ac_cv_prog_NMEDIT" fi { echo "$as_me:$LINENO: checking for -single_module linker flag" >&5 echo $ECHO_N "checking for -single_module linker flag... $ECHO_C" >&6; } if test "${lt_cv_apple_cc_single_mod+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else lt_cv_apple_cc_single_mod=no if test -z "${LT_MULTI_MODULE}"; then # By default we will add the -single_module flag. You can override # by either setting the environment variable LT_MULTI_MODULE # non-empty at configure time, or by adding -multi_module to the # link flags. echo "int foo(void){return 1;}" > conftest.c $LTCC $LTCFLAGS $LDFLAGS -o libconftest.dylib \ -dynamiclib ${wl}-single_module conftest.c if test -f libconftest.dylib; then lt_cv_apple_cc_single_mod=yes rm -rf libconftest.dylib* fi rm conftest.c fi fi { echo "$as_me:$LINENO: result: $lt_cv_apple_cc_single_mod" >&5 echo "${ECHO_T}$lt_cv_apple_cc_single_mod" >&6; } { echo "$as_me:$LINENO: checking for -exported_symbols_list linker flag" >&5 echo $ECHO_N "checking for -exported_symbols_list linker flag... $ECHO_C" >&6; } if test "${lt_cv_ld_exported_symbols_list+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else lt_cv_ld_exported_symbols_list=no save_LDFLAGS=$LDFLAGS echo "_main" > conftest.sym LDFLAGS="$LDFLAGS -Wl,-exported_symbols_list,conftest.sym" cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_cv_ld_exported_symbols_list=yes else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 lt_cv_ld_exported_symbols_list=no fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext LDFLAGS="$save_LDFLAGS" fi { echo "$as_me:$LINENO: result: $lt_cv_ld_exported_symbols_list" >&5 echo "${ECHO_T}$lt_cv_ld_exported_symbols_list" >&6; } case $host_os in rhapsody* | darwin1.[0123]) _lt_dar_allow_undefined='${wl}-undefined ${wl}suppress' ;; darwin1.*) _lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; darwin*) # if running on 10.5 or later, the deployment target defaults # to the OS version, if on x86, and 10.4, the deployment # target defaults to 10.4. Don't you love it? case ${MACOSX_DEPLOYMENT_TARGET-10.0},$host in 10.0,*86*-darwin8*|10.0,*-darwin[91]*) _lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;; 10.[012]*) _lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; 10.*) _lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;; esac ;; esac if test "$lt_cv_apple_cc_single_mod" = "yes"; then _lt_dar_single_mod='$single_module' fi if test "$lt_cv_ld_exported_symbols_list" = "yes"; then _lt_dar_export_syms=' ${wl}-exported_symbols_list,$output_objdir/${libname}-symbols.expsym' else _lt_dar_export_syms="~$NMEDIT -s \$output_objdir/\${libname}-symbols.expsym \${lib}" fi if test "$DSYMUTIL" != ":"; then _lt_dsymutil="~$DSYMUTIL \$lib || :" else _lt_dsymutil= fi ;; esac enable_dlopen=no enable_win32_dll=no # Check whether --enable-libtool-lock was given. if test "${enable_libtool_lock+set}" = set; then enableval=$enable_libtool_lock; fi test "x$enable_libtool_lock" != xno && enable_libtool_lock=yes # Check whether --with-pic was given. if test "${with_pic+set}" = set; then withval=$with_pic; pic_mode="$withval" else pic_mode=default fi test -z "$pic_mode" && pic_mode=default # Use C for the default configuration in the libtool script tagname= lt_save_CC="$CC" ac_ext=c ac_cpp='$CPP $CPPFLAGS' ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' ac_compiler_gnu=$ac_cv_c_compiler_gnu # Source file extension for C test sources. ac_ext=c # Object file extension for compiled C test sources. objext=o objext=$objext # Code to be used in simple compile tests lt_simple_compile_test_code="int some_variable = 0;" # Code to be used in simple link tests lt_simple_link_test_code='int main(){return(0);}' # If no C compiler was specified, use CC. LTCC=${LTCC-"$CC"} # If no C compiler flags were specified, use CFLAGS. LTCFLAGS=${LTCFLAGS-"$CFLAGS"} # Allow CC to be a program name with arguments. compiler=$CC # save warnings/boilerplate of simple test code ac_outfile=conftest.$ac_objext echo "$lt_simple_compile_test_code" >conftest.$ac_ext eval "$ac_compile" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err _lt_compiler_boilerplate=`cat conftest.err` $rm conftest* ac_outfile=conftest.$ac_objext echo "$lt_simple_link_test_code" >conftest.$ac_ext eval "$ac_link" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err _lt_linker_boilerplate=`cat conftest.err` $rm -r conftest* lt_prog_compiler_no_builtin_flag= if test "$GCC" = yes; then lt_prog_compiler_no_builtin_flag=' -fno-builtin' { echo "$as_me:$LINENO: checking if $compiler supports -fno-rtti -fno-exceptions" >&5 echo $ECHO_N "checking if $compiler supports -fno-rtti -fno-exceptions... $ECHO_C" >&6; } if test "${lt_cv_prog_compiler_rtti_exceptions+set}" = set; then echo $ECHO_N "(cached) $ECHO_C" >&6 else lt_cv_prog_compiler_rtti_exceptions=no ac_outfile=conftest.$ac_objext echo "$lt_simple_compile_test_code" > conftest.$ac_ext lt_compiler_flag="-fno-rtti -fno-exceptions" # Insert the option either (1) after the last *FLAGS variable, or # (2) before a word containing "conftest.", or (3) at the end. # Note that $ac_compile itself does not contain backslashes and begins # with a dollar sign (not a hyphen), so the echo should work correctly. # The option is referenced via a variable to avoid confusing sed. lt_compile=`echo "$ac_compile" | $SED \ -e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \ -e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \ -e 's:$: $lt_compiler_flag:'` (eval echo "\"\$as_me:7415: $lt_compile\"" >&5) (eval "$lt_compile" 2>conftest.err) ac_status=$? cat conftest.err >&5 echo "$as_me:7419: \$? = $ac_status" >&5 if (exit $ac_status) && test -s "$ac_outfile"; then # The compiler can only warn and ignore the option if not recognized # So say no if there are warnings other than the usual output. $echo "X$_lt_compiler_boilerplate" | $Xsed -e '/^$/d' >conftest.exp $SED '/^$/d; /^ *+/d' conftest.err >conftest.er2 if test ! -s conftest.er2 || diff conftest.exp conftest.er2 >/dev/null; then lt_cv_prog_compiler_rtti_exceptions=yes fi fi $rm conftest* fi { echo "$as_me:$LINENO: result: $lt_cv_prog_compiler_rtti_exceptions" >&5 echo "${ECHO_T}$lt_cv_prog_compiler_rtti_exceptions" >&6; } if test x"$lt_cv_prog_compiler_rtti_exceptions" = xyes; then lt_prog_compiler_no_builtin_flag="$lt_prog_compiler_no_builtin_flag -fno-rtti -fno-exceptions" else : fi fi lt_prog_compiler_wl= lt_prog_compiler_pic= lt_prog_compiler_static= { echo "$as_me:$LINENO: checking for $compiler option to produce PIC" >&5 echo $ECHO_N "checking for $compiler option to produce PIC... $ECHO_C" >&6; } if test "$GCC" = yes; then lt_prog_compiler_wl='-Wl,' lt_prog_compiler_static='-static' case $host_os in aix*) # All AIX code is PIC. if test "$host_cpu" = ia64; then # AIX 5 now supports IA64 processor lt_prog_compiler_static='-Bstatic' fi ;; amigaos*) # FIXME: we need at least 68020 code to build shared libraries, but # adding the `-m68020' flag to GCC prevents building anything better, # like `-m68040'. lt_prog_compiler_pic='-m68020 -resident32 -malways-restore-a4' ;; beos* | irix5* | irix6* | nonstopux* | osf3* | osf4* | osf5*) # PIC is the default for these OSes. ;; mingw* | cygwin* | pw32* | os2*) # This hack is so that the source file can tell whether it is being # built for inclusion in a dll (and should export symbols for example). # Although the cygwin gcc ignores -fPIC, still need this for old-style # (--disable-auto-import) libraries lt_prog_compiler_pic='-DDLL_EXPORT' ;; darwin* | rhapsody*) # PIC is the default on this platform # Common symbols not allowed in MH_DYLIB files lt_prog_compiler_pic='-fno-common' ;; interix[3-9]*) # Interix 3.x gcc -fpic/-fPIC options generate broken code. # Instead, we relocate shared libraries at runtime. ;; msdosdjgpp*) # Just because we use GCC doesn't mean we suddenly get shared libraries # on systems that don't support them. lt_prog_compiler_can_build_shared=no enable_shared=no ;; sysv4*MP*) if test -d /usr/nec; then lt_prog_compiler_pic=-Kconform_pic fi ;; hpux*) # PIC is the default for IA64 HP-UX and 64-bit HP-UX, but # not for PA HP-UX. case $host_cpu in hppa*64*|ia64*) # +Z the default ;; *) lt_prog_compiler_pic='-fPIC' ;; esac ;; *) lt_prog_compiler_pic='-fPIC' ;; esac else # PORTME Check for flag to pass linker flags through the system compiler. case $host_os in aix*) lt_prog_compiler_wl='-Wl,' if test "$host_cpu" = ia64; then # AIX 5 now supports IA64 processor lt_prog_compiler_static='-Bstatic' else lt_prog_compiler_static='-bnso -bI:/lib/syscalls.exp' fi ;; darwin*) # PIC is the default on this platform # Common symbols not allowed in MH_DYLIB files case $cc_basename in xlc*) lt_prog_compiler_pic='-qnocommon' lt_prog_compiler_wl='-Wl,' ;; esac ;; mingw* | cygwin* | pw32* | os2*) # This hack is so that the source file can tell whether it is being # built for inclusion in a dll (and should export symbols for example). lt_prog_compiler_pic='-DDLL_EXPORT' ;; hpux9* | hpux10* | hpux11*) lt_prog_compiler_wl='-Wl,' # PIC is the default for IA64 HP-UX and 64-bit HP-UX, but # not for PA HP-UX. case $host_cpu in hppa*64*|ia64*) # +Z the default ;; *) lt_prog_compiler_pic='+Z' ;; esac # Is there a better lt_prog_compiler_static that works with the bundled CC? 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} && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_aix_libpath_sed=' /Import File Strings/,/^$/ { /^0/ { s/^0 *\(.*\)$/\1/ p } }' aix_libpath=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` # Check for a 64-bit object if we didn't find anything. if test -z "$aix_libpath"; then aix_libpath=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` fi else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext if test -z "$aix_libpath"; then aix_libpath="/usr/lib:/lib"; fi hardcode_libdir_flag_spec='${wl}-blibpath:$libdir:'"$aix_libpath" archive_expsym_cmds="\$CC"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then echo "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag" else if test "$host_cpu" = ia64; then hardcode_libdir_flag_spec='${wl}-R $libdir:/usr/lib:/lib' allow_undefined_flag="-z nodefs" archive_expsym_cmds="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols" else # Determine the default libpath from the value encoded in an empty executable. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_aix_libpath_sed=' /Import File Strings/,/^$/ { /^0/ { s/^0 *\(.*\)$/\1/ p } }' aix_libpath=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` # Check for a 64-bit object if we didn't find anything. if test -z "$aix_libpath"; then aix_libpath=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` fi else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext if test -z "$aix_libpath"; then aix_libpath="/usr/lib:/lib"; fi hardcode_libdir_flag_spec='${wl}-blibpath:$libdir:'"$aix_libpath" # Warning - without using the other run time loading flags, # -berok will link without error, but may produce a broken library. no_undefined_flag=' ${wl}-bernotok' allow_undefined_flag=' ${wl}-berok' # Exported symbols can be pulled into shared objects from archives whole_archive_flag_spec='$convenience' archive_cmds_need_lc=yes # This is similar to how AIX traditionally builds its shared libraries. archive_expsym_cmds="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname' fi fi ;; amigaos*) archive_cmds='$rm $output_objdir/a2ixlibrary.data~$echo "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$echo "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$echo "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$echo "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)' hardcode_libdir_flag_spec='-L$libdir' hardcode_minus_L=yes # see comment about different semantics on the GNU ld section ld_shlibs=no ;; bsdi[45]*) export_dynamic_flag_spec=-rdynamic ;; cygwin* | mingw* | pw32*) # When not using gcc, we currently assume that we are using # Microsoft Visual C++. # hardcode_libdir_flag_spec is actually meaningless, as there is # no search path for DLLs. hardcode_libdir_flag_spec=' ' allow_undefined_flag=unsupported # Tell ltmain to make .lib files, not .a files. libext=lib # Tell ltmain to make .dll files, not .so files. shrext_cmds=".dll" # FIXME: Setting linknames here is a bad hack. archive_cmds='$CC -o $lib $libobjs $compiler_flags `echo "$deplibs" | $SED -e '\''s/ -lc$//'\''` -link -dll~linknames=' # The linker will automatically build a .lib file if we build a DLL. old_archive_From_new_cmds='true' # FIXME: Should let the user specify the lib program. old_archive_cmds='lib -OUT:$oldlib$oldobjs$old_deplibs' fix_srcfile_path='`cygpath -w "$srcfile"`' enable_shared_with_static_runtimes=yes ;; darwin* | rhapsody*) case $host_os in rhapsody* | darwin1.[012]) allow_undefined_flag='${wl}-undefined ${wl}suppress' ;; *) # Darwin 1.3 on if test -z ${MACOSX_DEPLOYMENT_TARGET} ; then allow_undefined_flag='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' else case ${MACOSX_DEPLOYMENT_TARGET} in 10.[012]) allow_undefined_flag='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; 10.*) allow_undefined_flag='${wl}-undefined ${wl}dynamic_lookup' ;; esac fi ;; esac archive_cmds_need_lc=no hardcode_direct=no hardcode_automatic=yes hardcode_shlibpath_var=unsupported whole_archive_flag_spec='' link_all_deplibs=yes if test "$GCC" = yes ; then output_verbose_link_cmd='echo' archive_cmds="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}" module_cmds="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}" archive_expsym_cmds="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}" module_expsym_cmds="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}" else case $cc_basename in xlc*) output_verbose_link_cmd='echo' archive_cmds='$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}`echo $rpath/$soname` $xlcverstring' module_cmds='$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags' # Don't fix this by using the ld -exported_symbols_list flag, it doesn't exist in older darwin lds archive_expsym_cmds='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}$rpath/$soname $xlcverstring~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' module_expsym_cmds='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' ;; *) ld_shlibs=no ;; esac fi ;; dgux*) archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec='-L$libdir' hardcode_shlibpath_var=no ;; freebsd1*) ld_shlibs=no ;; # FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor # support. 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hpux10*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then archive_cmds='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags' fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec='${wl}+b ${wl}$libdir' hardcode_libdir_separator=: hardcode_direct=yes export_dynamic_flag_spec='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L=yes fi ;; hpux11*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then case $host_cpu in hppa*64*) archive_cmds='$CC -shared ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds='$CC -shared ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac else case $host_cpu in hppa*64*) archive_cmds='$CC -b ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec='${wl}+b ${wl}$libdir' hardcode_libdir_separator=: case $host_cpu in hppa*64*|ia64*) hardcode_libdir_flag_spec_ld='+b $libdir' hardcode_direct=no hardcode_shlibpath_var=no ;; *) hardcode_direct=yes export_dynamic_flag_spec='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L=yes ;; esac fi ;; irix5* | irix6* | nonstopux*) if test "$GCC" = yes; then archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else archive_cmds='$LD -shared $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec_ld='-rpath $libdir' fi hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator=: link_all_deplibs=yes ;; netbsd* | netbsdelf*-gnu) if echo __ELF__ | $CC -E - | grep __ELF__ >/dev/null; then archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' # a.out else archive_cmds='$LD -shared -o $lib $libobjs $deplibs $linker_flags' # ELF fi hardcode_libdir_flag_spec='-R$libdir' hardcode_direct=yes hardcode_shlibpath_var=no ;; newsos6) archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct=yes hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator=: hardcode_shlibpath_var=no ;; openbsd*) if test -f /usr/libexec/ld.so; then hardcode_direct=yes hardcode_shlibpath_var=no if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then archive_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-retain-symbols-file,$export_symbols' hardcode_libdir_flag_spec='${wl}-rpath,$libdir' export_dynamic_flag_spec='${wl}-E' else case $host_os in openbsd[01].* | openbsd2.[0-7] | openbsd2.[0-7].*) archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec='-R$libdir' ;; *) archive_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' hardcode_libdir_flag_spec='${wl}-rpath,$libdir' ;; esac fi else ld_shlibs=no fi ;; os2*) hardcode_libdir_flag_spec='-L$libdir' hardcode_minus_L=yes allow_undefined_flag=unsupported archive_cmds='$echo "LIBRARY $libname INITINSTANCE" > $output_objdir/$libname.def~$echo "DESCRIPTION \"$libname\"" >> $output_objdir/$libname.def~$echo DATA >> $output_objdir/$libname.def~$echo " SINGLE NONSHARED" >> $output_objdir/$libname.def~$echo EXPORTS >> $output_objdir/$libname.def~emxexp $libobjs >> $output_objdir/$libname.def~$CC -Zdll -Zcrtdll -o $lib $libobjs $deplibs $compiler_flags $output_objdir/$libname.def' old_archive_From_new_cmds='emximp -o $output_objdir/$libname.a $output_objdir/$libname.def' ;; osf3*) if test "$GCC" = yes; then allow_undefined_flag=' ${wl}-expect_unresolved ${wl}\*' archive_cmds='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else allow_undefined_flag=' -expect_unresolved \*' archive_cmds='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' fi hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator=: ;; osf4* | osf5*) # as osf3* with the addition of -msym flag if test "$GCC" = yes; then allow_undefined_flag=' ${wl}-expect_unresolved ${wl}\*' archive_cmds='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir' else allow_undefined_flag=' -expect_unresolved \*' archive_cmds='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -msym -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' archive_expsym_cmds='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done; echo "-hidden">> $lib.exp~ $LD -shared${allow_undefined_flag} -input $lib.exp $linker_flags $libobjs $deplibs -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib~$rm $lib.exp' # Both c and cxx compiler support -rpath directly hardcode_libdir_flag_spec='-rpath $libdir' fi hardcode_libdir_separator=: ;; 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esac ;; gnu*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' shlibpath_var=LD_LIBRARY_PATH hardcode_into_libs=yes ;; hpux9* | hpux10* | hpux11*) # Give a soname corresponding to the major version so that dld.sl refuses to # link against other versions. version_type=sunos need_lib_prefix=no need_version=no case $host_cpu in ia64*) shrext_cmds='.so' hardcode_into_libs=yes dynamic_linker="$host_os dld.so" shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' if test "X$HPUX_IA64_MODE" = X32; then sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib" else sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64" fi sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; hppa*64*) shrext_cmds='.sl' hardcode_into_libs=yes dynamic_linker="$host_os dld.sl" shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64" sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; *) shrext_cmds='.sl' dynamic_linker="$host_os dld.sl" shlibpath_var=SHLIB_PATH shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' ;; esac # HP-UX runs *really* slowly unless shared libraries are mode 555. postinstall_cmds='chmod 555 $lib' ;; interix[3-9]*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)' shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=no hardcode_into_libs=yes ;; irix5* | irix6* | nonstopux*) case $host_os in nonstopux*) version_type=nonstopux ;; *) if test "$lt_cv_prog_gnu_ld" = yes; then version_type=linux else version_type=irix fi ;; esac need_lib_prefix=no need_version=no soname_spec='${libname}${release}${shared_ext}$major' library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}' case $host_os in irix5* | nonstopux*) libsuff= shlibsuff= ;; *) case $LD in # libtool.m4 will add one of these switches to LD *-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ") libsuff= shlibsuff= libmagic=32-bit;; *-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ") libsuff=32 shlibsuff=N32 libmagic=N32;; *-64|*"-64 "|*-melf64bmip|*"-melf64bmip ") libsuff=64 shlibsuff=64 libmagic=64-bit;; *) libsuff= shlibsuff= libmagic=never-match;; esac ;; esac shlibpath_var=LD_LIBRARY${shlibsuff}_PATH shlibpath_overrides_runpath=no sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}" sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}" hardcode_into_libs=yes ;; 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Another option is to modify *** your PATH or compiler configuration so that the native linker is *** used, and then restart. _LT_EOF ;; *) if $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then hardcode_libdir_flag_spec_F77='`test -z "$SCOABSPATH" && echo ${wl}-rpath,$libdir`' archive_cmds_F77='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname,\${SCOABSPATH:+${install_libdir}/}$soname -o $lib' archive_expsym_cmds_F77='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname,\${SCOABSPATH:+${install_libdir}/}$soname,-retain-symbols-file,$export_symbols -o $lib' else ld_shlibs_F77=no fi ;; esac ;; sunos4*) archive_cmds_F77='$LD -assert pure-text -Bshareable -o $lib $libobjs $deplibs $linker_flags' wlarc= hardcode_direct_F77=yes hardcode_shlibpath_var_F77=no ;; *) if $LD --help 2>&1 | grep ': supported targets:.* elf' > /dev/null; then archive_cmds_F77='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib' archive_expsym_cmds_F77='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib' else ld_shlibs_F77=no fi ;; esac if test "$ld_shlibs_F77" = no; then runpath_var= hardcode_libdir_flag_spec_F77= export_dynamic_flag_spec_F77= whole_archive_flag_spec_F77= fi else # PORTME fill in a description of your system's linker (not GNU ld) case $host_os in aix3*) allow_undefined_flag_F77=unsupported always_export_symbols_F77=yes archive_expsym_cmds_F77='$LD -o $output_objdir/$soname $libobjs $deplibs $linker_flags -bE:$export_symbols -T512 -H512 -bM:SRE~$AR $AR_FLAGS $lib $output_objdir/$soname' # Note: this linker hardcodes the directories in LIBPATH if there # are no directories specified by -L. hardcode_minus_L_F77=yes if test "$GCC" = yes && test -z "$lt_prog_compiler_static"; then # Neither direct hardcoding nor static linking is supported with a # broken collect2. hardcode_direct_F77=unsupported fi ;; aix[4-9]*) if test "$host_cpu" = ia64; then # On IA64, the linker does run time linking by default, so we don't # have to do anything special. aix_use_runtimelinking=no exp_sym_flag='-Bexport' no_entry_flag="" else # If we're using GNU nm, then we don't want the "-C" option. # -C means demangle to AIX nm, but means don't demangle with GNU nm if $NM -V 2>&1 | grep 'GNU' > /dev/null; then export_symbols_cmds_F77='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\$2 == "T") || (\$2 == "D") || (\$2 == "B")) && (substr(\$3,1,1) != ".")) { print \$3 } }'\'' | sort -u > $export_symbols' else export_symbols_cmds_F77='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\$2 == "T") || (\$2 == "D") || (\$2 == "B")) && (substr(\$3,1,1) != ".")) { print \$3 } }'\'' | sort -u > $export_symbols' fi aix_use_runtimelinking=no # Test if we are trying to use run time linking or normal # AIX style linking. If -brtl is somewhere in LDFLAGS, we # need to do runtime linking. case $host_os in aix4.[23]|aix4.[23].*|aix[5-9]*) for ld_flag in $LDFLAGS; do if (test $ld_flag = "-brtl" || test $ld_flag = "-Wl,-brtl"); then aix_use_runtimelinking=yes break fi done ;; esac exp_sym_flag='-bexport' no_entry_flag='-bnoentry' fi # When large executables or shared objects are built, AIX ld can # have problems creating the table of contents. If linking a library # or program results in "error TOC overflow" add -mminimal-toc to # CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not # enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS. archive_cmds_F77='' hardcode_direct_F77=yes hardcode_libdir_separator_F77=':' link_all_deplibs_F77=yes if test "$GCC" = yes; then case $host_os in aix4.[012]|aix4.[012].*) # We only want to do this on AIX 4.2 and lower, the check # below for broken collect2 doesn't work under 4.3+ collect2name=`${CC} -print-prog-name=collect2` if test -f "$collect2name" && \ strings "$collect2name" | grep resolve_lib_name >/dev/null then # We have reworked collect2 : else # We have old collect2 hardcode_direct_F77=unsupported # It fails to find uninstalled libraries when the uninstalled # path is not listed in the libpath. Setting hardcode_minus_L # to unsupported forces relinking hardcode_minus_L_F77=yes hardcode_libdir_flag_spec_F77='-L$libdir' hardcode_libdir_separator_F77= fi ;; esac shared_flag='-shared' if test "$aix_use_runtimelinking" = yes; then shared_flag="$shared_flag "'${wl}-G' fi else # not using gcc if test "$host_cpu" = ia64; then # VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release # chokes on -Wl,-G. The following line is correct: shared_flag='-G' else if test "$aix_use_runtimelinking" = yes; then shared_flag='${wl}-G' else shared_flag='${wl}-bM:SRE' fi fi fi # It seems that -bexpall does not export symbols beginning with # underscore (_), so it is better to generate a list of symbols to export. always_export_symbols_F77=yes if test "$aix_use_runtimelinking" = yes; then # Warning - without using the other runtime loading flags (-brtl), # -berok will link without error, but may produce a broken library. allow_undefined_flag_F77='-berok' # Determine the default libpath from the value encoded in an empty executable. cat >conftest.$ac_ext <<_ACEOF program main end _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_f77_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_aix_libpath_sed=' /Import File Strings/,/^$/ { /^0/ { s/^0 *\(.*\)$/\1/ p } }' aix_libpath=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` # Check for a 64-bit object if we didn't find anything. if test -z "$aix_libpath"; then aix_libpath=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` fi else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext if test -z "$aix_libpath"; then aix_libpath="/usr/lib:/lib"; fi hardcode_libdir_flag_spec_F77='${wl}-blibpath:$libdir:'"$aix_libpath" archive_expsym_cmds_F77="\$CC"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then echo "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag" else if test "$host_cpu" = ia64; then hardcode_libdir_flag_spec_F77='${wl}-R $libdir:/usr/lib:/lib' allow_undefined_flag_F77="-z nodefs" archive_expsym_cmds_F77="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols" else # Determine the default libpath from the value encoded in an empty executable. cat >conftest.$ac_ext <<_ACEOF program main end _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_f77_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_aix_libpath_sed=' /Import File Strings/,/^$/ { /^0/ { s/^0 *\(.*\)$/\1/ p } }' aix_libpath=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` # Check for a 64-bit object if we didn't find anything. if test -z "$aix_libpath"; then aix_libpath=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` fi else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext if test -z "$aix_libpath"; then aix_libpath="/usr/lib:/lib"; fi hardcode_libdir_flag_spec_F77='${wl}-blibpath:$libdir:'"$aix_libpath" # Warning - without using the other run time loading flags, # -berok will link without error, but may produce a broken library. no_undefined_flag_F77=' ${wl}-bernotok' allow_undefined_flag_F77=' ${wl}-berok' # Exported symbols can be pulled into shared objects from archives whole_archive_flag_spec_F77='$convenience' archive_cmds_need_lc_F77=yes # This is similar to how AIX traditionally builds its shared libraries. archive_expsym_cmds_F77="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname' fi fi ;; amigaos*) archive_cmds_F77='$rm $output_objdir/a2ixlibrary.data~$echo "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$echo "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$echo "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$echo "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)' hardcode_libdir_flag_spec_F77='-L$libdir' hardcode_minus_L_F77=yes # see comment about different semantics on the GNU ld section ld_shlibs_F77=no ;; bsdi[45]*) export_dynamic_flag_spec_F77=-rdynamic ;; cygwin* | mingw* | pw32*) # When not using gcc, we currently assume that we are using # Microsoft Visual C++. # hardcode_libdir_flag_spec is actually meaningless, as there is # no search path for DLLs. hardcode_libdir_flag_spec_F77=' ' allow_undefined_flag_F77=unsupported # Tell ltmain to make .lib files, not .a files. libext=lib # Tell ltmain to make .dll files, not .so files. shrext_cmds=".dll" # FIXME: Setting linknames here is a bad hack. archive_cmds_F77='$CC -o $lib $libobjs $compiler_flags `echo "$deplibs" | $SED -e '\''s/ -lc$//'\''` -link -dll~linknames=' # The linker will automatically build a .lib file if we build a DLL. old_archive_From_new_cmds_F77='true' # FIXME: Should let the user specify the lib program. old_archive_cmds_F77='lib -OUT:$oldlib$oldobjs$old_deplibs' fix_srcfile_path_F77='`cygpath -w "$srcfile"`' enable_shared_with_static_runtimes_F77=yes ;; darwin* | rhapsody*) case $host_os in rhapsody* | darwin1.[012]) allow_undefined_flag_F77='${wl}-undefined ${wl}suppress' ;; *) # Darwin 1.3 on if test -z ${MACOSX_DEPLOYMENT_TARGET} ; then allow_undefined_flag_F77='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' else case ${MACOSX_DEPLOYMENT_TARGET} in 10.[012]) allow_undefined_flag_F77='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; 10.*) allow_undefined_flag_F77='${wl}-undefined ${wl}dynamic_lookup' ;; esac fi ;; esac archive_cmds_need_lc_F77=no hardcode_direct_F77=no hardcode_automatic_F77=yes hardcode_shlibpath_var_F77=unsupported whole_archive_flag_spec_F77='' link_all_deplibs_F77=yes if test "$GCC" = yes ; then output_verbose_link_cmd='echo' archive_cmds_F77="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}" module_cmds_F77="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}" archive_expsym_cmds_F77="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}" module_expsym_cmds_F77="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}" else case $cc_basename in xlc*) output_verbose_link_cmd='echo' archive_cmds_F77='$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}`echo $rpath/$soname` $xlcverstring' module_cmds_F77='$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags' # Don't fix this by using the ld -exported_symbols_list flag, it doesn't exist in older darwin lds archive_expsym_cmds_F77='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}$rpath/$soname $xlcverstring~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' module_expsym_cmds_F77='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' ;; *) ld_shlibs_F77=no ;; esac fi ;; dgux*) archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec_F77='-L$libdir' hardcode_shlibpath_var_F77=no ;; freebsd1*) ld_shlibs_F77=no ;; # FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor # support. Future versions do this automatically, but an explicit c++rt0.o # does not break anything, and helps significantly (at the cost of a little # extra space). freebsd2.2*) archive_cmds_F77='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags /usr/lib/c++rt0.o' hardcode_libdir_flag_spec_F77='-R$libdir' hardcode_direct_F77=yes hardcode_shlibpath_var_F77=no ;; # Unfortunately, older versions of FreeBSD 2 do not have this feature. freebsd2*) archive_cmds_F77='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_F77=yes hardcode_minus_L_F77=yes hardcode_shlibpath_var_F77=no ;; # FreeBSD 3 and greater uses gcc -shared to do shared libraries. freebsd* | dragonfly*) archive_cmds_F77='$CC -shared -o $lib $libobjs $deplibs $compiler_flags' hardcode_libdir_flag_spec_F77='-R$libdir' hardcode_direct_F77=yes hardcode_shlibpath_var_F77=no ;; hpux9*) if test "$GCC" = yes; then archive_cmds_F77='$rm $output_objdir/$soname~$CC -shared -fPIC ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $libobjs $deplibs $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' else archive_cmds_F77='$rm $output_objdir/$soname~$LD -b +b $install_libdir -o $output_objdir/$soname $libobjs $deplibs $linker_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' fi hardcode_libdir_flag_spec_F77='${wl}+b ${wl}$libdir' hardcode_libdir_separator_F77=: hardcode_direct_F77=yes # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_F77=yes export_dynamic_flag_spec_F77='${wl}-E' ;; hpux10*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then archive_cmds_F77='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_F77='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags' fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec_F77='${wl}+b ${wl}$libdir' hardcode_libdir_separator_F77=: hardcode_direct_F77=yes export_dynamic_flag_spec_F77='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_F77=yes fi ;; hpux11*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then case $host_cpu in hppa*64*) archive_cmds_F77='$CC -shared ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds_F77='$CC -shared ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds_F77='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac else case $host_cpu in hppa*64*) archive_cmds_F77='$CC -b ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds_F77='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds_F77='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec_F77='${wl}+b ${wl}$libdir' hardcode_libdir_separator_F77=: case $host_cpu in hppa*64*|ia64*) hardcode_libdir_flag_spec_ld_F77='+b $libdir' hardcode_direct_F77=no hardcode_shlibpath_var_F77=no ;; *) hardcode_direct_F77=yes export_dynamic_flag_spec_F77='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_F77=yes ;; esac fi ;; irix5* | irix6* | nonstopux*) if test "$GCC" = yes; then archive_cmds_F77='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else archive_cmds_F77='$LD -shared $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec_ld_F77='-rpath $libdir' fi hardcode_libdir_flag_spec_F77='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_F77=: link_all_deplibs_F77=yes ;; netbsd* | netbsdelf*-gnu) if echo __ELF__ | $CC -E - | grep __ELF__ >/dev/null; then archive_cmds_F77='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' # a.out else archive_cmds_F77='$LD -shared -o $lib $libobjs $deplibs $linker_flags' # ELF fi hardcode_libdir_flag_spec_F77='-R$libdir' hardcode_direct_F77=yes hardcode_shlibpath_var_F77=no ;; newsos6) archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_F77=yes hardcode_libdir_flag_spec_F77='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_F77=: hardcode_shlibpath_var_F77=no ;; openbsd*) if test -f /usr/libexec/ld.so; then hardcode_direct_F77=yes hardcode_shlibpath_var_F77=no if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then archive_cmds_F77='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_F77='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-retain-symbols-file,$export_symbols' hardcode_libdir_flag_spec_F77='${wl}-rpath,$libdir' export_dynamic_flag_spec_F77='${wl}-E' else case $host_os in openbsd[01].* | openbsd2.[0-7] | openbsd2.[0-7].*) archive_cmds_F77='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec_F77='-R$libdir' ;; *) archive_cmds_F77='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' hardcode_libdir_flag_spec_F77='${wl}-rpath,$libdir' ;; esac fi else ld_shlibs_F77=no fi ;; os2*) hardcode_libdir_flag_spec_F77='-L$libdir' hardcode_minus_L_F77=yes allow_undefined_flag_F77=unsupported archive_cmds_F77='$echo "LIBRARY $libname INITINSTANCE" > $output_objdir/$libname.def~$echo "DESCRIPTION \"$libname\"" >> $output_objdir/$libname.def~$echo DATA >> $output_objdir/$libname.def~$echo " SINGLE NONSHARED" >> $output_objdir/$libname.def~$echo EXPORTS >> $output_objdir/$libname.def~emxexp $libobjs >> $output_objdir/$libname.def~$CC -Zdll -Zcrtdll -o $lib $libobjs $deplibs $compiler_flags $output_objdir/$libname.def' old_archive_From_new_cmds_F77='emximp -o $output_objdir/$libname.a $output_objdir/$libname.def' ;; osf3*) if test "$GCC" = yes; then allow_undefined_flag_F77=' ${wl}-expect_unresolved ${wl}\*' archive_cmds_F77='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else allow_undefined_flag_F77=' -expect_unresolved \*' archive_cmds_F77='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' fi hardcode_libdir_flag_spec_F77='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_F77=: ;; osf4* | osf5*) # as osf3* with the addition of -msym flag if test "$GCC" = yes; then allow_undefined_flag_F77=' ${wl}-expect_unresolved ${wl}\*' archive_cmds_F77='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec_F77='${wl}-rpath ${wl}$libdir' else allow_undefined_flag_F77=' -expect_unresolved \*' archive_cmds_F77='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -msym -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' archive_expsym_cmds_F77='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done; echo "-hidden">> $lib.exp~ $LD -shared${allow_undefined_flag} -input $lib.exp $linker_flags $libobjs $deplibs -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib~$rm $lib.exp' # Both c and cxx compiler support -rpath directly hardcode_libdir_flag_spec_F77='-rpath $libdir' fi hardcode_libdir_separator_F77=: ;; solaris*) no_undefined_flag_F77=' -z text' if test "$GCC" = yes; then wlarc='${wl}' archive_cmds_F77='$CC -shared ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_F77='$echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~$echo "local: *; };" >> $lib.exp~ $CC -shared ${wl}-M ${wl}$lib.exp ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags~$rm $lib.exp' else wlarc='' archive_cmds_F77='$LD -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $linker_flags' archive_expsym_cmds_F77='$echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~$echo "local: *; };" >> $lib.exp~ $LD -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $linker_flags~$rm $lib.exp' fi hardcode_libdir_flag_spec_F77='-R$libdir' hardcode_shlibpath_var_F77=no case $host_os in solaris2.[0-5] | solaris2.[0-5].*) ;; *) # The compiler driver will combine and reorder linker options, # but understands `-z linker_flag'. GCC discards it without `$wl', # but is careful enough not to reorder. # Supported since Solaris 2.6 (maybe 2.5.1?) if test "$GCC" = yes; then whole_archive_flag_spec_F77='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract' else whole_archive_flag_spec_F77='-z allextract$convenience -z defaultextract' fi ;; esac link_all_deplibs_F77=yes ;; sunos4*) if test "x$host_vendor" = xsequent; then # Use $CC to link under sequent, because it throws in some extra .o # files that make .init and .fini sections work. archive_cmds_F77='$CC -G ${wl}-h $soname -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_F77='$LD -assert pure-text -Bstatic -o $lib $libobjs $deplibs $linker_flags' fi hardcode_libdir_flag_spec_F77='-L$libdir' hardcode_direct_F77=yes hardcode_minus_L_F77=yes hardcode_shlibpath_var_F77=no ;; sysv4) case $host_vendor in sni) archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_F77=yes # is this really true??? ;; siemens) ## LD is ld it makes a PLAMLIB ## CC just makes a GrossModule. archive_cmds_F77='$LD -G -o $lib $libobjs $deplibs $linker_flags' reload_cmds_F77='$CC -r -o $output$reload_objs' hardcode_direct_F77=no ;; motorola) archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_F77=no #Motorola manual says yes, but my tests say they lie ;; esac runpath_var='LD_RUN_PATH' hardcode_shlibpath_var_F77=no ;; sysv4.3*) archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_shlibpath_var_F77=no export_dynamic_flag_spec_F77='-Bexport' ;; sysv4*MP*) if test -d /usr/nec; then archive_cmds_F77='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_shlibpath_var_F77=no runpath_var=LD_RUN_PATH hardcode_runpath_var=yes ld_shlibs_F77=yes fi ;; sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[01].[10]* | unixware7* | sco3.2v5.0.[024]*) no_undefined_flag_F77='${wl}-z,text' archive_cmds_need_lc_F77=no hardcode_shlibpath_var_F77=no runpath_var='LD_RUN_PATH' if test "$GCC" = yes; then archive_cmds_F77='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_F77='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_F77='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_F77='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' fi ;; sysv5* | sco3.2v5* | sco5v6*) # Note: We can NOT use -z defs as we might desire, because we do not # link with -lc, and that would cause any symbols used from libc to # always be unresolved, which means just about no library would # ever link correctly. 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The import file would start with # the line `#! .'. This would cause the generated library to # depend on `.', always an invalid library. This was fixed in # development snapshots of GCC prior to 3.0. case $host_os in aix4 | aix4.[01] | aix4.[01].*) if { echo '#if __GNUC__ > 2 || (__GNUC__ == 2 && __GNUC_MINOR__ >= 97)' echo ' yes ' echo '#endif'; } | ${CC} -E - | grep yes > /dev/null; then : else can_build_shared=no fi ;; esac # AIX (on Power*) has no versioning support, so currently we can not hardcode correct # soname into executable. Probably we can add versioning support to # collect2, so additional links can be useful in future. if test "$aix_use_runtimelinking" = yes; then # If using run time linking (on AIX 4.2 or later) use lib.so # instead of lib.a to let people know that these are not # typical AIX shared libraries. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' else # We preserve .a as extension for shared libraries through AIX4.2 # and later when we are not doing run time linking. library_names_spec='${libname}${release}.a $libname.a' soname_spec='${libname}${release}${shared_ext}$major' fi shlibpath_var=LIBPATH fi ;; amigaos*) library_names_spec='$libname.ixlibrary $libname.a' # Create ${libname}_ixlibrary.a entries in /sys/libs. finish_eval='for lib in `ls $libdir/*.ixlibrary 2>/dev/null`; do libname=`$echo "X$lib" | $Xsed -e '\''s%^.*/\([^/]*\)\.ixlibrary$%\1%'\''`; test $rm /sys/libs/${libname}_ixlibrary.a; $show "cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a"; cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a || exit 1; done' ;; beos*) library_names_spec='${libname}${shared_ext}' dynamic_linker="$host_os ld.so" shlibpath_var=LIBRARY_PATH ;; bsdi[45]*) version_type=linux need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' finish_cmds='PATH="\$PATH:/sbin" ldconfig $libdir' shlibpath_var=LD_LIBRARY_PATH sys_lib_search_path_spec="/shlib /usr/lib /usr/X11/lib /usr/contrib/lib /lib /usr/local/lib" sys_lib_dlsearch_path_spec="/shlib /usr/lib /usr/local/lib" # the default ld.so.conf also contains /usr/contrib/lib and # /usr/X11R6/lib (/usr/X11 is a link to /usr/X11R6), but let us allow # libtool to hard-code these into programs ;; cygwin* | mingw* | pw32*) version_type=windows shrext_cmds=".dll" need_version=no need_lib_prefix=no case $GCC,$host_os in yes,cygwin* | yes,mingw* | yes,pw32*) library_names_spec='$libname.dll.a' # DLL is installed to $(libdir)/../bin by postinstall_cmds postinstall_cmds='base_file=`basename \${file}`~ dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i;echo \$dlname'\''`~ dldir=$destdir/`dirname \$dlpath`~ test -d \$dldir || mkdir -p \$dldir~ $install_prog $dir/$dlname \$dldir/$dlname~ chmod a+x \$dldir/$dlname' postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~ dlpath=$dir/\$dldll~ $rm \$dlpath' shlibpath_overrides_runpath=yes case $host_os in cygwin*) # Cygwin DLLs use 'cyg' prefix rather than 'lib' soname_spec='`echo ${libname} | sed -e 's/^lib/cyg/'``echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}' sys_lib_search_path_spec="/usr/lib /lib/w32api /lib /usr/local/lib" ;; mingw*) # MinGW DLLs use traditional 'lib' prefix soname_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}' sys_lib_search_path_spec=`$CC -print-search-dirs | grep "^libraries:" | $SED -e "s/^libraries://" -e "s,=/,/,g"` if echo "$sys_lib_search_path_spec" | grep ';[c-zC-Z]:/' >/dev/null; then # It is most probably a Windows format PATH printed by # mingw gcc, but we are running on Cygwin. 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When/if they implement a new # versioning mechanism, adjust this. if test -x /usr/bin/objformat; then objformat=`/usr/bin/objformat` else case $host_os in freebsd[123]*) objformat=aout ;; *) objformat=elf ;; esac fi version_type=freebsd-$objformat case $version_type in freebsd-elf*) library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}' need_version=no need_lib_prefix=no ;; freebsd-*) library_names_spec='${libname}${release}${shared_ext}$versuffix $libname${shared_ext}$versuffix' need_version=yes ;; esac shlibpath_var=LD_LIBRARY_PATH case $host_os in freebsd2*) shlibpath_overrides_runpath=yes ;; freebsd3.[01]* | freebsdelf3.[01]*) shlibpath_overrides_runpath=yes hardcode_into_libs=yes ;; freebsd3.[2-9]* | freebsdelf3.[2-9]* | \ freebsd4.[0-5] | freebsdelf4.[0-5] | freebsd4.1.1 | freebsdelf4.1.1) shlibpath_overrides_runpath=no hardcode_into_libs=yes ;; *) # from 4.6 on, and DragonFly shlibpath_overrides_runpath=yes hardcode_into_libs=yes ;; esac ;; gnu*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' shlibpath_var=LD_LIBRARY_PATH hardcode_into_libs=yes ;; hpux9* | hpux10* | hpux11*) # Give a soname corresponding to the major version so that dld.sl refuses to # link against other versions. version_type=sunos need_lib_prefix=no need_version=no case $host_cpu in ia64*) shrext_cmds='.so' hardcode_into_libs=yes dynamic_linker="$host_os dld.so" shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' if test "X$HPUX_IA64_MODE" = X32; then sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib" else sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64" fi sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; hppa*64*) shrext_cmds='.sl' hardcode_into_libs=yes dynamic_linker="$host_os dld.sl" shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64" sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; *) shrext_cmds='.sl' dynamic_linker="$host_os dld.sl" shlibpath_var=SHLIB_PATH shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' ;; esac # HP-UX runs *really* slowly unless shared libraries are mode 555. postinstall_cmds='chmod 555 $lib' ;; interix[3-9]*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)' shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=no hardcode_into_libs=yes ;; irix5* | irix6* | nonstopux*) case $host_os in nonstopux*) version_type=nonstopux ;; *) if test "$lt_cv_prog_gnu_ld" = yes; then version_type=linux else version_type=irix fi ;; esac need_lib_prefix=no need_version=no soname_spec='${libname}${release}${shared_ext}$major' library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}' case $host_os in irix5* | nonstopux*) libsuff= shlibsuff= ;; *) case $LD in # libtool.m4 will add one of these switches to LD *-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ") libsuff= shlibsuff= libmagic=32-bit;; *-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ") libsuff=32 shlibsuff=N32 libmagic=N32;; *-64|*"-64 "|*-melf64bmip|*"-melf64bmip ") libsuff=64 shlibsuff=64 libmagic=64-bit;; *) libsuff= shlibsuff= libmagic=never-match;; esac ;; esac shlibpath_var=LD_LIBRARY${shlibsuff}_PATH shlibpath_overrides_runpath=no sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}" sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}" hardcode_into_libs=yes ;; 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else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag" else if test "$host_cpu" = ia64; then hardcode_libdir_flag_spec_GCJ='${wl}-R $libdir:/usr/lib:/lib' allow_undefined_flag_GCJ="-z nodefs" archive_expsym_cmds_GCJ="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols" else # Determine the default libpath from the value encoded in an empty executable. cat >conftest.$ac_ext <<_ACEOF /* confdefs.h. */ _ACEOF cat confdefs.h >>conftest.$ac_ext cat >>conftest.$ac_ext <<_ACEOF /* end confdefs.h. */ int main () { ; return 0; } _ACEOF rm -f conftest.$ac_objext conftest$ac_exeext if { (ac_try="$ac_link" case "(($ac_try" in *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; *) ac_try_echo=$ac_try;; esac eval "echo \"\$as_me:$LINENO: $ac_try_echo\"") >&5 (eval "$ac_link") 2>conftest.er1 ac_status=$? grep -v '^ *+' conftest.er1 >conftest.err rm -f conftest.er1 cat conftest.err >&5 echo "$as_me:$LINENO: \$? = $ac_status" >&5 (exit $ac_status); } && { test -z "$ac_c_werror_flag" || test ! -s conftest.err } && test -s conftest$ac_exeext && $as_test_x conftest$ac_exeext; then lt_aix_libpath_sed=' /Import File Strings/,/^$/ { /^0/ { s/^0 *\(.*\)$/\1/ p } }' aix_libpath=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` # Check for a 64-bit object if we didn't find anything. if test -z "$aix_libpath"; then aix_libpath=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"` fi else echo "$as_me: failed program was:" >&5 sed 's/^/| /' conftest.$ac_ext >&5 fi rm -f core conftest.err conftest.$ac_objext conftest_ipa8_conftest.oo \ conftest$ac_exeext conftest.$ac_ext if test -z "$aix_libpath"; then aix_libpath="/usr/lib:/lib"; fi hardcode_libdir_flag_spec_GCJ='${wl}-blibpath:$libdir:'"$aix_libpath" # Warning - without using the other run time loading flags, # -berok will link without error, but may produce a broken library. no_undefined_flag_GCJ=' ${wl}-bernotok' allow_undefined_flag_GCJ=' ${wl}-berok' # Exported symbols can be pulled into shared objects from archives whole_archive_flag_spec_GCJ='$convenience' archive_cmds_need_lc_GCJ=yes # This is similar to how AIX traditionally builds its shared libraries. archive_expsym_cmds_GCJ="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname' fi fi ;; amigaos*) archive_cmds_GCJ='$rm $output_objdir/a2ixlibrary.data~$echo "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$echo "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$echo "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$echo "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)' hardcode_libdir_flag_spec_GCJ='-L$libdir' hardcode_minus_L_GCJ=yes # see comment about different semantics on the GNU ld section ld_shlibs_GCJ=no ;; bsdi[45]*) export_dynamic_flag_spec_GCJ=-rdynamic ;; cygwin* | mingw* | pw32*) # When not using gcc, we currently assume that we are using # Microsoft Visual C++. # hardcode_libdir_flag_spec is actually meaningless, as there is # no search path for DLLs. hardcode_libdir_flag_spec_GCJ=' ' allow_undefined_flag_GCJ=unsupported # Tell ltmain to make .lib files, not .a files. libext=lib # Tell ltmain to make .dll files, not .so files. shrext_cmds=".dll" # FIXME: Setting linknames here is a bad hack. archive_cmds_GCJ='$CC -o $lib $libobjs $compiler_flags `echo "$deplibs" | $SED -e '\''s/ -lc$//'\''` -link -dll~linknames=' # The linker will automatically build a .lib file if we build a DLL. old_archive_From_new_cmds_GCJ='true' # FIXME: Should let the user specify the lib program. old_archive_cmds_GCJ='lib -OUT:$oldlib$oldobjs$old_deplibs' fix_srcfile_path_GCJ='`cygpath -w "$srcfile"`' enable_shared_with_static_runtimes_GCJ=yes ;; darwin* | rhapsody*) case $host_os in rhapsody* | darwin1.[012]) allow_undefined_flag_GCJ='${wl}-undefined ${wl}suppress' ;; *) # Darwin 1.3 on if test -z ${MACOSX_DEPLOYMENT_TARGET} ; then allow_undefined_flag_GCJ='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' else case ${MACOSX_DEPLOYMENT_TARGET} in 10.[012]) allow_undefined_flag_GCJ='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;; 10.*) allow_undefined_flag_GCJ='${wl}-undefined ${wl}dynamic_lookup' ;; esac fi ;; esac archive_cmds_need_lc_GCJ=no hardcode_direct_GCJ=no hardcode_automatic_GCJ=yes hardcode_shlibpath_var_GCJ=unsupported whole_archive_flag_spec_GCJ='' link_all_deplibs_GCJ=yes if test "$GCC" = yes ; then output_verbose_link_cmd='echo' archive_cmds_GCJ="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}" module_cmds_GCJ="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}" archive_expsym_cmds_GCJ="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}" module_expsym_cmds_GCJ="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}" else case $cc_basename in xlc*) output_verbose_link_cmd='echo' archive_cmds_GCJ='$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}`echo $rpath/$soname` $xlcverstring' module_cmds_GCJ='$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags' # Don't fix this by using the ld -exported_symbols_list flag, it doesn't exist in older darwin lds archive_expsym_cmds_GCJ='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC -qmkshrobj $allow_undefined_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-install_name ${wl}$rpath/$soname $xlcverstring~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' module_expsym_cmds_GCJ='sed -e "s,#.*,," -e "s,^[ ]*,," -e "s,^\(..*\),_&," < $export_symbols > $output_objdir/${libname}-symbols.expsym~$CC $allow_undefined_flag -o $lib -bundle $libobjs $deplibs$compiler_flags~nmedit -s $output_objdir/${libname}-symbols.expsym ${lib}' ;; *) ld_shlibs_GCJ=no ;; esac fi ;; dgux*) archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec_GCJ='-L$libdir' hardcode_shlibpath_var_GCJ=no ;; freebsd1*) ld_shlibs_GCJ=no ;; # FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor # support. Future versions do this automatically, but an explicit c++rt0.o # does not break anything, and helps significantly (at the cost of a little # extra space). freebsd2.2*) archive_cmds_GCJ='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags /usr/lib/c++rt0.o' hardcode_libdir_flag_spec_GCJ='-R$libdir' hardcode_direct_GCJ=yes hardcode_shlibpath_var_GCJ=no ;; # Unfortunately, older versions of FreeBSD 2 do not have this feature. freebsd2*) archive_cmds_GCJ='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_GCJ=yes hardcode_minus_L_GCJ=yes hardcode_shlibpath_var_GCJ=no ;; # FreeBSD 3 and greater uses gcc -shared to do shared libraries. freebsd* | dragonfly*) archive_cmds_GCJ='$CC -shared -o $lib $libobjs $deplibs $compiler_flags' hardcode_libdir_flag_spec_GCJ='-R$libdir' hardcode_direct_GCJ=yes hardcode_shlibpath_var_GCJ=no ;; hpux9*) if test "$GCC" = yes; then archive_cmds_GCJ='$rm $output_objdir/$soname~$CC -shared -fPIC ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $libobjs $deplibs $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' else archive_cmds_GCJ='$rm $output_objdir/$soname~$LD -b +b $install_libdir -o $output_objdir/$soname $libobjs $deplibs $linker_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib' fi hardcode_libdir_flag_spec_GCJ='${wl}+b ${wl}$libdir' hardcode_libdir_separator_GCJ=: hardcode_direct_GCJ=yes # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_GCJ=yes export_dynamic_flag_spec_GCJ='${wl}-E' ;; hpux10*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then archive_cmds_GCJ='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_GCJ='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags' fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec_GCJ='${wl}+b ${wl}$libdir' hardcode_libdir_separator_GCJ=: hardcode_direct_GCJ=yes export_dynamic_flag_spec_GCJ='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_GCJ=yes fi ;; hpux11*) if test "$GCC" = yes -a "$with_gnu_ld" = no; then case $host_cpu in hppa*64*) archive_cmds_GCJ='$CC -shared ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds_GCJ='$CC -shared ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds_GCJ='$CC -shared -fPIC ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac else case $host_cpu in hppa*64*) archive_cmds_GCJ='$CC -b ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' ;; ia64*) archive_cmds_GCJ='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags' ;; *) archive_cmds_GCJ='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags' ;; esac fi if test "$with_gnu_ld" = no; then hardcode_libdir_flag_spec_GCJ='${wl}+b ${wl}$libdir' hardcode_libdir_separator_GCJ=: case $host_cpu in hppa*64*|ia64*) hardcode_libdir_flag_spec_ld_GCJ='+b $libdir' hardcode_direct_GCJ=no hardcode_shlibpath_var_GCJ=no ;; *) hardcode_direct_GCJ=yes export_dynamic_flag_spec_GCJ='${wl}-E' # hardcode_minus_L: Not really in the search PATH, # but as the default location of the library. hardcode_minus_L_GCJ=yes ;; esac fi ;; irix5* | irix6* | nonstopux*) if test "$GCC" = yes; then archive_cmds_GCJ='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else archive_cmds_GCJ='$LD -shared $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec_ld_GCJ='-rpath $libdir' fi hardcode_libdir_flag_spec_GCJ='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_GCJ=: link_all_deplibs_GCJ=yes ;; netbsd* | netbsdelf*-gnu) if echo __ELF__ | $CC -E - | grep __ELF__ >/dev/null; then archive_cmds_GCJ='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' # a.out else archive_cmds_GCJ='$LD -shared -o $lib $libobjs $deplibs $linker_flags' # ELF fi hardcode_libdir_flag_spec_GCJ='-R$libdir' hardcode_direct_GCJ=yes hardcode_shlibpath_var_GCJ=no ;; newsos6) archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_GCJ=yes hardcode_libdir_flag_spec_GCJ='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_GCJ=: hardcode_shlibpath_var_GCJ=no ;; openbsd*) if test -f /usr/libexec/ld.so; then hardcode_direct_GCJ=yes hardcode_shlibpath_var_GCJ=no if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then archive_cmds_GCJ='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_GCJ='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-retain-symbols-file,$export_symbols' hardcode_libdir_flag_spec_GCJ='${wl}-rpath,$libdir' export_dynamic_flag_spec_GCJ='${wl}-E' else case $host_os in openbsd[01].* | openbsd2.[0-7] | openbsd2.[0-7].*) archive_cmds_GCJ='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' hardcode_libdir_flag_spec_GCJ='-R$libdir' ;; *) archive_cmds_GCJ='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags' hardcode_libdir_flag_spec_GCJ='${wl}-rpath,$libdir' ;; esac fi else ld_shlibs_GCJ=no fi ;; os2*) hardcode_libdir_flag_spec_GCJ='-L$libdir' hardcode_minus_L_GCJ=yes allow_undefined_flag_GCJ=unsupported archive_cmds_GCJ='$echo "LIBRARY $libname INITINSTANCE" > $output_objdir/$libname.def~$echo "DESCRIPTION \"$libname\"" >> $output_objdir/$libname.def~$echo DATA >> $output_objdir/$libname.def~$echo " SINGLE NONSHARED" >> $output_objdir/$libname.def~$echo EXPORTS >> $output_objdir/$libname.def~emxexp $libobjs >> $output_objdir/$libname.def~$CC -Zdll -Zcrtdll -o $lib $libobjs $deplibs $compiler_flags $output_objdir/$libname.def' old_archive_From_new_cmds_GCJ='emximp -o $output_objdir/$libname.a $output_objdir/$libname.def' ;; osf3*) if test "$GCC" = yes; then allow_undefined_flag_GCJ=' ${wl}-expect_unresolved ${wl}\*' archive_cmds_GCJ='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' else allow_undefined_flag_GCJ=' -expect_unresolved \*' archive_cmds_GCJ='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' fi hardcode_libdir_flag_spec_GCJ='${wl}-rpath ${wl}$libdir' hardcode_libdir_separator_GCJ=: ;; osf4* | osf5*) # as osf3* with the addition of -msym flag if test "$GCC" = yes; then allow_undefined_flag_GCJ=' ${wl}-expect_unresolved ${wl}\*' archive_cmds_GCJ='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && echo ${wl}-set_version ${wl}$verstring` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib' hardcode_libdir_flag_spec_GCJ='${wl}-rpath ${wl}$libdir' else allow_undefined_flag_GCJ=' -expect_unresolved \*' archive_cmds_GCJ='$LD -shared${allow_undefined_flag} $libobjs $deplibs $linker_flags -msym -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib' archive_expsym_cmds_GCJ='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done; echo "-hidden">> $lib.exp~ $LD -shared${allow_undefined_flag} -input $lib.exp $linker_flags $libobjs $deplibs -soname $soname `test -n "$verstring" && echo -set_version $verstring` -update_registry ${output_objdir}/so_locations -o $lib~$rm $lib.exp' # Both c and cxx compiler support -rpath directly hardcode_libdir_flag_spec_GCJ='-rpath $libdir' fi hardcode_libdir_separator_GCJ=: ;; solaris*) no_undefined_flag_GCJ=' -z text' if test "$GCC" = yes; then wlarc='${wl}' archive_cmds_GCJ='$CC -shared ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_GCJ='$echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~$echo "local: *; };" >> $lib.exp~ $CC -shared ${wl}-M ${wl}$lib.exp ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags~$rm $lib.exp' else wlarc='' archive_cmds_GCJ='$LD -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $linker_flags' archive_expsym_cmds_GCJ='$echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~$echo "local: *; };" >> $lib.exp~ $LD -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $linker_flags~$rm $lib.exp' fi hardcode_libdir_flag_spec_GCJ='-R$libdir' hardcode_shlibpath_var_GCJ=no case $host_os in solaris2.[0-5] | solaris2.[0-5].*) ;; *) # The compiler driver will combine and reorder linker options, # but understands `-z linker_flag'. GCC discards it without `$wl', # but is careful enough not to reorder. # Supported since Solaris 2.6 (maybe 2.5.1?) if test "$GCC" = yes; then whole_archive_flag_spec_GCJ='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract' else whole_archive_flag_spec_GCJ='-z allextract$convenience -z defaultextract' fi ;; esac link_all_deplibs_GCJ=yes ;; sunos4*) if test "x$host_vendor" = xsequent; then # Use $CC to link under sequent, because it throws in some extra .o # files that make .init and .fini sections work. archive_cmds_GCJ='$CC -G ${wl}-h $soname -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_GCJ='$LD -assert pure-text -Bstatic -o $lib $libobjs $deplibs $linker_flags' fi hardcode_libdir_flag_spec_GCJ='-L$libdir' hardcode_direct_GCJ=yes hardcode_minus_L_GCJ=yes hardcode_shlibpath_var_GCJ=no ;; sysv4) case $host_vendor in sni) archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_GCJ=yes # is this really true??? ;; siemens) ## LD is ld it makes a PLAMLIB ## CC just makes a GrossModule. archive_cmds_GCJ='$LD -G -o $lib $libobjs $deplibs $linker_flags' reload_cmds_GCJ='$CC -r -o $output$reload_objs' hardcode_direct_GCJ=no ;; motorola) archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_direct_GCJ=no #Motorola manual says yes, but my tests say they lie ;; esac runpath_var='LD_RUN_PATH' hardcode_shlibpath_var_GCJ=no ;; sysv4.3*) archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_shlibpath_var_GCJ=no export_dynamic_flag_spec_GCJ='-Bexport' ;; sysv4*MP*) if test -d /usr/nec; then archive_cmds_GCJ='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags' hardcode_shlibpath_var_GCJ=no runpath_var=LD_RUN_PATH hardcode_runpath_var=yes ld_shlibs_GCJ=yes fi ;; sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[01].[10]* | unixware7* | sco3.2v5.0.[024]*) no_undefined_flag_GCJ='${wl}-z,text' archive_cmds_need_lc_GCJ=no hardcode_shlibpath_var_GCJ=no runpath_var='LD_RUN_PATH' if test "$GCC" = yes; then archive_cmds_GCJ='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_GCJ='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' else archive_cmds_GCJ='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' archive_expsym_cmds_GCJ='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags' fi ;; sysv5* | sco3.2v5* | sco5v6*) # Note: We can NOT use -z defs as we might desire, because we do not # link with -lc, and that would cause any symbols used from libc to # always be unresolved, which means just about no library would # ever link correctly. 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When/if they implement a new # versioning mechanism, adjust this. if test -x /usr/bin/objformat; then objformat=`/usr/bin/objformat` else case $host_os in freebsd[123]*) objformat=aout ;; *) objformat=elf ;; esac fi version_type=freebsd-$objformat case $version_type in freebsd-elf*) library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}' need_version=no need_lib_prefix=no ;; freebsd-*) library_names_spec='${libname}${release}${shared_ext}$versuffix $libname${shared_ext}$versuffix' need_version=yes ;; esac shlibpath_var=LD_LIBRARY_PATH case $host_os in freebsd2*) shlibpath_overrides_runpath=yes ;; freebsd3.[01]* | freebsdelf3.[01]*) shlibpath_overrides_runpath=yes hardcode_into_libs=yes ;; freebsd3.[2-9]* | freebsdelf3.[2-9]* | \ freebsd4.[0-5] | freebsdelf4.[0-5] | freebsd4.1.1 | freebsdelf4.1.1) shlibpath_overrides_runpath=no hardcode_into_libs=yes ;; *) # from 4.6 on, and DragonFly shlibpath_overrides_runpath=yes hardcode_into_libs=yes ;; esac ;; gnu*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' shlibpath_var=LD_LIBRARY_PATH hardcode_into_libs=yes ;; hpux9* | hpux10* | hpux11*) # Give a soname corresponding to the major version so that dld.sl refuses to # link against other versions. version_type=sunos need_lib_prefix=no need_version=no case $host_cpu in ia64*) shrext_cmds='.so' hardcode_into_libs=yes dynamic_linker="$host_os dld.so" shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' if test "X$HPUX_IA64_MODE" = X32; then sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib" else sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64" fi sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; hppa*64*) shrext_cmds='.sl' hardcode_into_libs=yes dynamic_linker="$host_os dld.sl" shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH shlibpath_overrides_runpath=yes # Unless +noenvvar is specified. library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64" sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec ;; *) shrext_cmds='.sl' dynamic_linker="$host_os dld.sl" shlibpath_var=SHLIB_PATH shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' ;; esac # HP-UX runs *really* slowly unless shared libraries are mode 555. postinstall_cmds='chmod 555 $lib' ;; interix[3-9]*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)' shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=no hardcode_into_libs=yes ;; irix5* | irix6* | nonstopux*) case $host_os in nonstopux*) version_type=nonstopux ;; *) if test "$lt_cv_prog_gnu_ld" = yes; then version_type=linux else version_type=irix fi ;; esac need_lib_prefix=no need_version=no soname_spec='${libname}${release}${shared_ext}$major' library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}' case $host_os in irix5* | nonstopux*) libsuff= shlibsuff= ;; *) case $LD in # libtool.m4 will add one of these switches to LD *-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ") libsuff= shlibsuff= libmagic=32-bit;; *-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ") libsuff=32 shlibsuff=N32 libmagic=N32;; *-64|*"-64 "|*-melf64bmip|*"-melf64bmip ") libsuff=64 shlibsuff=64 libmagic=64-bit;; *) libsuff= shlibsuff= libmagic=never-match;; esac ;; esac shlibpath_var=LD_LIBRARY${shlibsuff}_PATH shlibpath_overrides_runpath=no sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}" sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}" hardcode_into_libs=yes ;; # No shared lib support for Linux oldld, aout, or coff. linux*oldld* | linux*aout* | linux*coff*) dynamic_linker=no ;; # This must be Linux ELF. linux* | k*bsd*-gnu) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' finish_cmds='PATH="\$PATH:/sbin" ldconfig -n $libdir' shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=no # This implies no fast_install, which is unacceptable. # Some rework will be needed to allow for fast_install # before this can be enabled. hardcode_into_libs=yes # Append ld.so.conf contents to the search path if test -f /etc/ld.so.conf; then lt_ld_extra=`awk '/^include / { system(sprintf("cd /etc; cat %s 2>/dev/null", \$2)); skip = 1; } { if (!skip) print \$0; skip = 0; }' < /etc/ld.so.conf | $SED -e 's/#.*//;/^[ ]*hwcap[ ]/d;s/[:, ]/ /g;s/=[^=]*$//;s/=[^= ]* / /g;/^$/d' | tr '\n' ' '` sys_lib_dlsearch_path_spec="/lib /usr/lib $lt_ld_extra" fi # We used to test for /lib/ld.so.1 and disable shared libraries on # powerpc, because MkLinux only supported shared libraries with the # GNU dynamic linker. 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then case $host_os in openbsd2.[89] | openbsd2.[89].*) shlibpath_overrides_runpath=no ;; *) shlibpath_overrides_runpath=yes ;; esac else shlibpath_overrides_runpath=yes fi ;; os2*) libname_spec='$name' shrext_cmds=".dll" need_lib_prefix=no library_names_spec='$libname${shared_ext} $libname.a' dynamic_linker='OS/2 ld.exe' shlibpath_var=LIBPATH ;; osf3* | osf4* | osf5*) version_type=osf need_lib_prefix=no need_version=no soname_spec='${libname}${release}${shared_ext}$major' library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' shlibpath_var=LD_LIBRARY_PATH sys_lib_search_path_spec="/usr/shlib /usr/ccs/lib /usr/lib/cmplrs/cc /usr/lib /usr/local/lib /var/shlib" sys_lib_dlsearch_path_spec="$sys_lib_search_path_spec" ;; rdos*) dynamic_linker=no ;; solaris*) version_type=linux need_lib_prefix=no need_version=no library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}' soname_spec='${libname}${release}${shared_ext}$major' shlibpath_var=LD_LIBRARY_PATH shlibpath_overrides_runpath=yes hardcode_into_libs=yes # ldd complains unless libraries are executable postinstall_cmds='chmod +x $lib' ;; 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So we exec the FD to /dev/null, # effectively closing config.log, so it can be properly (re)opened and # appended to by config.status. When coming back to configure, we # need to make the FD available again. if test "$no_create" != yes; then ac_cs_success=: ac_config_status_args= test "$silent" = yes && ac_config_status_args="$ac_config_status_args --quiet" exec 5>/dev/null $SHELL $CONFIG_STATUS $ac_config_status_args || ac_cs_success=false exec 5>>config.log # Use ||, not &&, to avoid exiting from the if with $? = 1, which # would make configure fail if this is the last instruction. $ac_cs_success || { (exit 1); exit 1; } fi minpack-19961126/readme0000644000175000017500000000126105573651073015475 0ustar sylvestresylvestre====== readme for minpack ====== Minpack includes software for solving nonlinear equations and nonlinear least squares problems. Five algorithmic paths each include a core subroutine and an easy-to-use driver. The algorithms proceed either from an analytic specification of the Jacobian matrix or directly from the problem functions. The paths include facilities for systems of equations with a banded Jacobian matrix, for least squares problems with a large amount of data, and for checking the consistency of the Jacobian matrix with the functions. This directory contains the double-precision versions. Jorge More', Burt Garbow, and Ken Hillstrom at Argonne National Laboratory. minpack-19961126/minpack.h0000644000175000017500000001235111616327304016102 0ustar sylvestresylvestre/* Declarations for minpack */ #ifdef __cplusplus extern "C" { #endif /* find a zero of a system of N nonlinear functions in N variables by a modification of the Powell hybrid method (Jacobian calculated by a forward-difference approximation) */ void hybrd1_ ( void (*fcn)(int *n, double *x, double *fvec, int *iflag ), int *n, double *x, double *fvec, double *tol, int *info, double *wa, int *lwa ); /* find a zero of a system of N nonlinear functions in N variables by a modification of the Powell hybrid method (Jacobian calculated by a forward-difference approximation, more general). */ void hybrd_ ( void (*fcn)(int *n, double *x, double *fvec, int *iflag ), int *n, double *x, double *fvec, double *xtol, int *maxfev, int *ml, int *mu, double *epsfcn, double *diag, int *mode, double *factor, int *nprint, int *info, int *nfev, double *fjac, int *ldfjac, double *r, int *lr, double *qtf, double *wa1, double *wa2, double *wa3, double *wa4); /* find a zero of a system of N nonlinear functions in N variables by a modification of the Powell hybrid method (user-supplied Jacobian) */ void hybrj1_ ( void (*fcn)(int *n, double *x, double *fvec, double *fjec, int *ldfjac, int *iflag ), int *n, double *x, double *fvec, double *fjec, int *ldfjac, double *tol, int *info, double *wa, int *lwa ); /* find a zero of a system of N nonlinear functions in N variables by a modification of the Powell hybrid method (user-supplied Jacobian, more general) */ void hybrj_ ( void (*fcn)(int *n, double *x, double *fvec, double *fjec, int *ldfjac, int *iflag ), int *n, double *x, double *fvec, double *fjec, int *ldfjac, double *xtol, int *maxfev, double *diag, int *mode, double *factor, int *nprint, int *info, int *nfev, int *njev, double *r, int *lr, double *qtf, double *wa1, double *wa2, double *wa3, double *wa4 ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (Jacobian calculated by a forward-difference approximation) */ void lmdif1_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, int *iflag ), int *m, int *n, double *x, double *fvec, double *tol, int *info, int *iwa, double *wa, int *lwa ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (Jacobian calculated by a forward-difference approximation, more general) */ void lmdif_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, int *iflag ), int *m, int *n, double *x, double *fvec, double *ftol, double *xtol, double *gtol, int *maxfev, double *epsfcn, double *diag, int *mode, double *factor, int *nprint, int *info, int *nfev, double *fjac, int *ldfjac, int *ipvt, double *qtf, double *wa1, double *wa2, double *wa3, double *wa4 ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (user-supplied Jacobian) */ void lmder1_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, double *fjec, int *ldfjac, int *iflag ), int *m, int *n, double *x, double *fvec, double *fjec, int *ldfjac, double *tol, int *info, int *ipvt, double *wa, int *lwa ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (user-supplied Jacobian, more general) */ void lmder_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, double *fjec, int *ldfjac, int *iflag ), int *m, int *n, double *x, double *fvec, double *fjec, int *ldfjac, double *ftol, double *xtol, double *gtol, int *maxfev, double *diag, int *mode, double *factor, int *nprint, int *info, int *nfev, int *njev, int *ipvt, double *qtf, double *wa1, double *wa2, double *wa3, double *wa4 ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (user-supplied Jacobian, minimal storage) */ void lmstr1_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, double *fjrow, int *iflag ), int *m, int *n, double *x, double *fvec, double *fjac, int *ldfjac, double *tol, int *info, int *ipvt, double *wa, int *lwa ); /* minimize the sum of the squares of nonlinear functions in N variables by a modification of the Levenberg-Marquardt algorithm (user-supplied Jacobian, minimal storage, more general) */ void lmstr_ ( void (*fcn)(int *m, int *n, double *x, double *fvec, double *fjrow, int *iflag ), int *m, int *n, double *x, double *fvec, double *fjac, int *ldfjac, double *ftol, double *xtol, double *gtol, int *maxfev, double *diag, int *mode, double *factor, int *nprint, int *info, int *nfev, int *njev, int *ipvt, double *qtf, double *wa1, double *wa2, double *wa3, double *wa4 ); void chkder_ ( int *m, int *n, double *x, double *fvec, double *fjec, int *ldfjac, double *xp, double *fvecp, int *mode, double *err ); double dpmpar_ ( int *i ); double enorm_ ( int *n, double *x ); #ifdef __cplusplus } #endif minpack-19961126/r1updt.f0000644000175000017500000001310603226632013015666 0ustar sylvestresylvestre subroutine r1updt(m,n,s,ls,u,v,w,sing) integer m,n,ls logical sing double precision s(ls),u(m),v(n),w(m) c ********** c c subroutine r1updt c c given an m by n lower trapezoidal matrix s, an m-vector u, c and an n-vector v, the problem is to determine an c orthogonal matrix q such that c c t c (s + u*v )*q c c is again lower trapezoidal. c c this subroutine determines q as the product of 2*(n - 1) c transformations c c gv(n-1)*...*gv(1)*gw(1)*...*gw(n-1) c c where gv(i), gw(i) are givens rotations in the (i,n) plane c which eliminate elements in the i-th and n-th planes, c respectively. q itself is not accumulated, rather the c information to recover the gv, gw rotations is returned. c c the subroutine statement is c c subroutine r1updt(m,n,s,ls,u,v,w,sing) c c where c c m is a positive integer input variable set to the number c of rows of s. c c n is a positive integer input variable set to the number c of columns of s. n must not exceed m. c c s is an array of length ls. on input s must contain the lower c trapezoidal matrix s stored by columns. on output s contains c the lower trapezoidal matrix produced as described above. c c ls is a positive integer input variable not less than c (n*(2*m-n+1))/2. c c u is an input array of length m which must contain the c vector u. c c v is an array of length n. on input v must contain the vector c v. on output v(i) contains the information necessary to c recover the givens rotation gv(i) described above. c c w is an output array of length m. w(i) contains information c necessary to recover the givens rotation gw(i) described c above. c c sing is a logical output variable. sing is set true if any c of the diagonal elements of the output s are zero. otherwise c sing is set false. c c subprograms called c c minpack-supplied ... dpmpar c c fortran-supplied ... dabs,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more, c john l. nazareth c c ********** integer i,j,jj,l,nmj,nm1 double precision cos,cotan,giant,one,p5,p25,sin,tan,tau,temp, * zero double precision dpmpar data one,p5,p25,zero /1.0d0,5.0d-1,2.5d-1,0.0d0/ c c giant is the largest magnitude. c giant = dpmpar(3) c c initialize the diagonal element pointer. c jj = (n*(2*m - n + 1))/2 - (m - n) c c move the nontrivial part of the last column of s into w. c l = jj do 10 i = n, m w(i) = s(l) l = l + 1 10 continue c c rotate the vector v into a multiple of the n-th unit vector c in such a way that a spike is introduced into w. c nm1 = n - 1 if (nm1 .lt. 1) go to 70 do 60 nmj = 1, nm1 j = n - nmj jj = jj - (m - j + 1) w(j) = zero if (v(j) .eq. zero) go to 50 c c determine a givens rotation which eliminates the c j-th element of v. c if (dabs(v(n)) .ge. dabs(v(j))) go to 20 cotan = v(n)/v(j) sin = p5/dsqrt(p25+p25*cotan**2) cos = sin*cotan tau = one if (dabs(cos)*giant .gt. one) tau = one/cos go to 30 20 continue tan = v(j)/v(n) cos = p5/dsqrt(p25+p25*tan**2) sin = cos*tan tau = sin 30 continue c c apply the transformation to v and store the information c necessary to recover the givens rotation. c v(n) = sin*v(j) + cos*v(n) v(j) = tau c c apply the transformation to s and extend the spike in w. c l = jj do 40 i = j, m temp = cos*s(l) - sin*w(i) w(i) = sin*s(l) + cos*w(i) s(l) = temp l = l + 1 40 continue 50 continue 60 continue 70 continue c c add the spike from the rank 1 update to w. c do 80 i = 1, m w(i) = w(i) + v(n)*u(i) 80 continue c c eliminate the spike. c sing = .false. if (nm1 .lt. 1) go to 140 do 130 j = 1, nm1 if (w(j) .eq. zero) go to 120 c c determine a givens rotation which eliminates the c j-th element of the spike. c if (dabs(s(jj)) .ge. dabs(w(j))) go to 90 cotan = s(jj)/w(j) sin = p5/dsqrt(p25+p25*cotan**2) cos = sin*cotan tau = one if (dabs(cos)*giant .gt. one) tau = one/cos go to 100 90 continue tan = w(j)/s(jj) cos = p5/dsqrt(p25+p25*tan**2) sin = cos*tan tau = sin 100 continue c c apply the transformation to s and reduce the spike in w. c l = jj do 110 i = j, m temp = cos*s(l) + sin*w(i) w(i) = -sin*s(l) + cos*w(i) s(l) = temp l = l + 1 110 continue c c store the information necessary to recover the c givens rotation. c w(j) = tau 120 continue c c test for zero diagonal elements in the output s. c if (s(jj) .eq. zero) sing = .true. jj = jj + (m - j + 1) 130 continue 140 continue c c move w back into the last column of the output s. c l = jj do 150 i = n, m s(l) = w(i) l = l + 1 150 continue if (s(jj) .eq. zero) sing = .true. return c c last card of subroutine r1updt. c end minpack-19961126/hybrd.f0000644000175000017500000003505403226632006015567 0ustar sylvestresylvestre subroutine hybrd(fcn,n,x,fvec,xtol,maxfev,ml,mu,epsfcn,diag, * mode,factor,nprint,info,nfev,fjac,ldfjac,r,lr, * qtf,wa1,wa2,wa3,wa4) integer n,maxfev,ml,mu,mode,nprint,info,nfev,ldfjac,lr double precision xtol,epsfcn,factor double precision x(n),fvec(n),diag(n),fjac(ldfjac,n),r(lr), * qtf(n),wa1(n),wa2(n),wa3(n),wa4(n) external fcn c ********** c c subroutine hybrd c c the purpose of hybrd is to find a zero of a system of c n nonlinear functions in n variables by a modification c of the powell hybrid method. 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 hybrd(fcn,n,x,fvec,xtol,maxfev,ml,mu,epsfcn, c diag,mode,factor,nprint,info,nfev,fjac, c ldfjac,r,lr,qtf,wa1,wa2,wa3,wa4) 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(n,x,fvec,iflag) c integer n,iflag c double precision x(n),fvec(n) 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 hybrd. c in this case set iflag to a negative integer. c c n is a positive integer input variable set to the number c of functions and variables. 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 n which contains c the functions evaluated at the output x. c c xtol is a nonnegative input variable. termination c occurs when the relative error between two consecutive c iterates is at most xtol. c c maxfev is a positive integer input variable. termination c occurs when the number of calls to fcn is at least maxfev c by the end of an iteration. c c ml is a nonnegative integer input variable which specifies c the number of subdiagonals within the band of the c jacobian matrix. if the jacobian is not banded, set c ml to at least n - 1. c c mu is a nonnegative integer input variable which specifies c the number of superdiagonals within the band of the c jacobian matrix. if the jacobian is not banded, set c mu to at least n - 1. c c epsfcn is an input variable used in determining a suitable c step length for the forward-difference approximation. this c approximation assumes that the relative errors in the c functions are of the order of epsfcn. if epsfcn is less c than the machine precision, it is assumed that the relative c errors in the functions are of the order of the machine c precision. c c diag is an array of length n. if mode = 1 (see c below), diag is internally set. if mode = 2, diag c must contain positive entries that serve as c multiplicative scale factors for the variables. c c mode is an integer input variable. if mode = 1, the c variables will be scaled internally. if mode = 2, c the scaling is specified by the input diag. other c values of mode are equivalent to mode = 1. c c factor is a positive input variable used in determining the c initial step bound. this bound is set to the product of c factor and the euclidean norm of diag*x if nonzero, or else c to factor itself. in most cases factor should lie in the c interval (.1,100.). 100. is a generally recommended value. c c nprint is an integer input variable that enables controlled c printing of iterates if it is positive. in this case, c fcn is called with iflag = 0 at the beginning of the first c iteration and every nprint iterations thereafter and c immediately prior to return, with x and fvec available c for printing. if nprint is not positive, no special calls c of fcn with iflag = 0 are made. 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 relative error between two consecutive iterates c is at most xtol. c c info = 2 number of calls to fcn has reached or exceeded c maxfev. c c info = 3 xtol is too small. no further improvement in c the approximate solution x is possible. c c info = 4 iteration is not making good progress, as c measured by the improvement from the last c five jacobian evaluations. c c info = 5 iteration is not making good progress, as c measured by the improvement from the last c ten iterations. c c nfev is an integer output variable set to the number of c calls to fcn. c c fjac is an output n by n array which contains the c orthogonal matrix q produced by the qr factorization c of the final approximate jacobian. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. c c r is an output array of length lr which contains the c upper triangular matrix produced by the qr factorization c of the final approximate jacobian, stored rowwise. c c lr is a positive integer input variable not less than c (n*(n+1))/2. c c qtf is an output array of length n which contains c the vector (q transpose)*fvec. c c wa1, wa2, wa3, and wa4 are work arrays of length n. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dogleg,dpmpar,enorm,fdjac1, c qform,qrfac,r1mpyq,r1updt c c fortran-supplied ... dabs,dmax1,dmin1,min0,mod c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,iflag,iter,j,jm1,l,msum,ncfail,ncsuc,nslow1,nslow2 integer iwa(1) logical jeval,sing double precision actred,delta,epsmch,fnorm,fnorm1,one,pnorm, * prered,p1,p5,p001,p0001,ratio,sum,temp,xnorm, * zero double precision dpmpar,enorm data one,p1,p5,p001,p0001,zero * /1.0d0,1.0d-1,5.0d-1,1.0d-3,1.0d-4,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c info = 0 iflag = 0 nfev = 0 c c check the input parameters for errors. c if (n .le. 0 .or. xtol .lt. zero .or. maxfev .le. 0 * .or. ml .lt. 0 .or. mu .lt. 0 .or. factor .le. zero * .or. ldfjac .lt. n .or. lr .lt. (n*(n + 1))/2) go to 300 if (mode .ne. 2) go to 20 do 10 j = 1, n if (diag(j) .le. zero) go to 300 10 continue 20 continue c c evaluate the function at the starting point c and calculate its norm. c iflag = 1 call fcn(n,x,fvec,iflag) nfev = 1 if (iflag .lt. 0) go to 300 fnorm = enorm(n,fvec) c c determine the number of calls to fcn needed to compute c the jacobian matrix. c msum = min0(ml+mu+1,n) c c initialize iteration counter and monitors. c iter = 1 ncsuc = 0 ncfail = 0 nslow1 = 0 nslow2 = 0 c c beginning of the outer loop. c 30 continue jeval = .true. c c calculate the jacobian matrix. c iflag = 2 call fdjac1(fcn,n,x,fvec,fjac,ldfjac,iflag,ml,mu,epsfcn,wa1, * wa2) nfev = nfev + msum if (iflag .lt. 0) go to 300 c c compute the qr factorization of the jacobian. c call qrfac(n,n,fjac,ldfjac,.false.,iwa,1,wa1,wa2,wa3) c c on the first iteration and if mode is 1, scale according c to the norms of the columns of the initial jacobian. c if (iter .ne. 1) go to 70 if (mode .eq. 2) go to 50 do 40 j = 1, n diag(j) = wa2(j) if (wa2(j) .eq. zero) diag(j) = one 40 continue 50 continue c c on the first iteration, calculate the norm of the scaled x c and initialize the step bound delta. c do 60 j = 1, n wa3(j) = diag(j)*x(j) 60 continue xnorm = enorm(n,wa3) delta = factor*xnorm if (delta .eq. zero) delta = factor 70 continue c c form (q transpose)*fvec and store in qtf. c do 80 i = 1, n qtf(i) = fvec(i) 80 continue do 120 j = 1, n if (fjac(j,j) .eq. zero) go to 110 sum = zero do 90 i = j, n sum = sum + fjac(i,j)*qtf(i) 90 continue temp = -sum/fjac(j,j) do 100 i = j, n qtf(i) = qtf(i) + fjac(i,j)*temp 100 continue 110 continue 120 continue c c copy the triangular factor of the qr factorization into r. c sing = .false. do 150 j = 1, n l = j jm1 = j - 1 if (jm1 .lt. 1) go to 140 do 130 i = 1, jm1 r(l) = fjac(i,j) l = l + n - i 130 continue 140 continue r(l) = wa1(j) if (wa1(j) .eq. zero) sing = .true. 150 continue c c accumulate the orthogonal factor in fjac. c call qform(n,n,fjac,ldfjac,wa1) c c rescale if necessary. c if (mode .eq. 2) go to 170 do 160 j = 1, n diag(j) = dmax1(diag(j),wa2(j)) 160 continue 170 continue c c beginning of the inner loop. c 180 continue c c if requested, call fcn to enable printing of iterates. c if (nprint .le. 0) go to 190 iflag = 0 if (mod(iter-1,nprint) .eq. 0) call fcn(n,x,fvec,iflag) if (iflag .lt. 0) go to 300 190 continue c c determine the direction p. c call dogleg(n,r,lr,diag,qtf,delta,wa1,wa2,wa3) c c store the direction p and x + p. calculate the norm of p. c do 200 j = 1, n wa1(j) = -wa1(j) wa2(j) = x(j) + wa1(j) wa3(j) = diag(j)*wa1(j) 200 continue pnorm = enorm(n,wa3) c c on the first iteration, adjust the initial step bound. c if (iter .eq. 1) delta = dmin1(delta,pnorm) c c evaluate the function at x + p and calculate its norm. c iflag = 1 call fcn(n,wa2,wa4,iflag) nfev = nfev + 1 if (iflag .lt. 0) go to 300 fnorm1 = enorm(n,wa4) c c compute the scaled actual reduction. c actred = -one if (fnorm1 .lt. fnorm) actred = one - (fnorm1/fnorm)**2 c c compute the scaled predicted reduction. c l = 1 do 220 i = 1, n sum = zero do 210 j = i, n sum = sum + r(l)*wa1(j) l = l + 1 210 continue wa3(i) = qtf(i) + sum 220 continue temp = enorm(n,wa3) prered = zero if (temp .lt. fnorm) prered = one - (temp/fnorm)**2 c c compute the ratio of the actual to the predicted c reduction. c ratio = zero if (prered .gt. zero) ratio = actred/prered c c update the step bound. c if (ratio .ge. p1) go to 230 ncsuc = 0 ncfail = ncfail + 1 delta = p5*delta go to 240 230 continue ncfail = 0 ncsuc = ncsuc + 1 if (ratio .ge. p5 .or. ncsuc .gt. 1) * delta = dmax1(delta,pnorm/p5) if (dabs(ratio-one) .le. p1) delta = pnorm/p5 240 continue c c test for successful iteration. c if (ratio .lt. p0001) go to 260 c c successful iteration. update x, fvec, and their norms. c do 250 j = 1, n x(j) = wa2(j) wa2(j) = diag(j)*x(j) fvec(j) = wa4(j) 250 continue xnorm = enorm(n,wa2) fnorm = fnorm1 iter = iter + 1 260 continue c c determine the progress of the iteration. c nslow1 = nslow1 + 1 if (actred .ge. p001) nslow1 = 0 if (jeval) nslow2 = nslow2 + 1 if (actred .ge. p1) nslow2 = 0 c c test for convergence. c if (delta .le. xtol*xnorm .or. fnorm .eq. zero) info = 1 if (info .ne. 0) go to 300 c c tests for termination and stringent tolerances. c if (nfev .ge. maxfev) info = 2 if (p1*dmax1(p1*delta,pnorm) .le. epsmch*xnorm) info = 3 if (nslow2 .eq. 5) info = 4 if (nslow1 .eq. 10) info = 5 if (info .ne. 0) go to 300 c c criterion for recalculating jacobian approximation c by forward differences. c if (ncfail .eq. 2) go to 290 c c calculate the rank one modification to the jacobian c and update qtf if necessary. c do 280 j = 1, n sum = zero do 270 i = 1, n sum = sum + fjac(i,j)*wa4(i) 270 continue wa2(j) = (sum - wa3(j))/pnorm wa1(j) = diag(j)*((diag(j)*wa1(j))/pnorm) if (ratio .ge. p0001) qtf(j) = sum 280 continue c c compute the qr factorization of the updated jacobian. c call r1updt(n,n,r,lr,wa1,wa2,wa3,sing) call r1mpyq(n,n,fjac,ldfjac,wa2,wa3) call r1mpyq(1,n,qtf,1,wa2,wa3) c c end of the inner loop. c jeval = .false. go to 180 290 continue c c end of the outer loop. c go to 30 300 continue c c termination, either normal or user imposed. c if (iflag .lt. 0) info = iflag iflag = 0 if (nprint .gt. 0) call fcn(n,x,fvec,iflag) return c c last card of subroutine hybrd. c end minpack-19961126/lmpar.f0000644000175000017500000002006303226632011015560 0ustar sylvestresylvestre subroutine lmpar(n,r,ldr,ipvt,diag,qtb,delta,par,x,sdiag,wa1, * wa2) integer n,ldr integer ipvt(n) double precision delta,par double precision r(ldr,n),diag(n),qtb(n),x(n),sdiag(n),wa1(n), * wa2(n) c ********** c c subroutine lmpar c c given an m by n matrix a, an n by n nonsingular diagonal c matrix d, an m-vector b, and a positive number delta, c the problem is to determine a value for the parameter c par such that if x solves the system c c a*x = b , sqrt(par)*d*x = 0 , c c in the least squares sense, and dxnorm is the euclidean c norm of d*x, then either par is zero and c c (dxnorm-delta) .le. 0.1*delta , c c or par is positive and c c abs(dxnorm-delta) .le. 0.1*delta . c c this subroutine completes the solution of the problem c if it is provided with the necessary information from the c qr factorization, with column pivoting, of a. that is, if c a*p = q*r, where p is a permutation matrix, q has orthogonal c columns, and r is an upper triangular matrix with diagonal c elements of nonincreasing magnitude, then lmpar expects c the full upper triangle of r, the permutation matrix p, c and the first n components of (q transpose)*b. on output c lmpar also provides an upper triangular matrix s such that c c t t t c p *(a *a + par*d*d)*p = s *s . c c s is employed within lmpar and may be of separate interest. c c only a few iterations are generally needed for convergence c of the algorithm. if, however, the limit of 10 iterations c is reached, then the output par will contain the best c value obtained so far. c c the subroutine statement is c c subroutine lmpar(n,r,ldr,ipvt,diag,qtb,delta,par,x,sdiag, c wa1,wa2) c c where c c n is a positive integer input variable set to the order of r. c c r is an n by n array. on input the full upper triangle c must contain the full upper triangle of the matrix r. c on output the full upper triangle is unaltered, and the c strict lower triangle contains the strict upper triangle c (transposed) of the upper triangular matrix s. c c ldr is a positive integer input variable not less than n c which specifies the leading dimension of the array r. c c ipvt is an integer input array of length n which defines the c permutation matrix p such that a*p = q*r. column j of p c is column ipvt(j) of the identity matrix. c c diag is an input array of length n which must contain the c diagonal elements of the matrix d. c c qtb is an input array of length n which must contain the first c n elements of the vector (q transpose)*b. c c delta is a positive input variable which specifies an upper c bound on the euclidean norm of d*x. c c par is a nonnegative variable. on input par contains an c initial estimate of the levenberg-marquardt parameter. c on output par contains the final estimate. c c x is an output array of length n which contains the least c squares solution of the system a*x = b, sqrt(par)*d*x = 0, c for the output par. c c sdiag is an output array of length n which contains the c diagonal elements of the upper triangular matrix s. c c wa1 and wa2 are work arrays of length n. c c subprograms called c c minpack-supplied ... dpmpar,enorm,qrsolv c c fortran-supplied ... dabs,dmax1,dmin1,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,iter,j,jm1,jp1,k,l,nsing double precision dxnorm,dwarf,fp,gnorm,parc,parl,paru,p1,p001, * sum,temp,zero double precision dpmpar,enorm data p1,p001,zero /1.0d-1,1.0d-3,0.0d0/ c c dwarf is the smallest positive magnitude. c dwarf = dpmpar(2) c c compute and store in x the gauss-newton direction. if the c jacobian is rank-deficient, obtain a least squares solution. c nsing = n do 10 j = 1, n wa1(j) = qtb(j) if (r(j,j) .eq. zero .and. nsing .eq. n) nsing = j - 1 if (nsing .lt. n) wa1(j) = zero 10 continue if (nsing .lt. 1) go to 50 do 40 k = 1, nsing j = nsing - k + 1 wa1(j) = wa1(j)/r(j,j) temp = wa1(j) jm1 = j - 1 if (jm1 .lt. 1) go to 30 do 20 i = 1, jm1 wa1(i) = wa1(i) - r(i,j)*temp 20 continue 30 continue 40 continue 50 continue do 60 j = 1, n l = ipvt(j) x(l) = wa1(j) 60 continue c c initialize the iteration counter. c evaluate the function at the origin, and test c for acceptance of the gauss-newton direction. c iter = 0 do 70 j = 1, n wa2(j) = diag(j)*x(j) 70 continue dxnorm = enorm(n,wa2) fp = dxnorm - delta if (fp .le. p1*delta) go to 220 c c if the jacobian is not rank deficient, the newton c step provides a lower bound, parl, for the zero of c the function. otherwise set this bound to zero. c parl = zero if (nsing .lt. n) go to 120 do 80 j = 1, n l = ipvt(j) wa1(j) = diag(l)*(wa2(l)/dxnorm) 80 continue do 110 j = 1, n sum = zero jm1 = j - 1 if (jm1 .lt. 1) go to 100 do 90 i = 1, jm1 sum = sum + r(i,j)*wa1(i) 90 continue 100 continue wa1(j) = (wa1(j) - sum)/r(j,j) 110 continue temp = enorm(n,wa1) parl = ((fp/delta)/temp)/temp 120 continue c c calculate an upper bound, paru, for the zero of the function. c do 140 j = 1, n sum = zero do 130 i = 1, j sum = sum + r(i,j)*qtb(i) 130 continue l = ipvt(j) wa1(j) = sum/diag(l) 140 continue gnorm = enorm(n,wa1) paru = gnorm/delta if (paru .eq. zero) paru = dwarf/dmin1(delta,p1) c c if the input par lies outside of the interval (parl,paru), c set par to the closer endpoint. c par = dmax1(par,parl) par = dmin1(par,paru) if (par .eq. zero) par = gnorm/dxnorm c c beginning of an iteration. c 150 continue iter = iter + 1 c c evaluate the function at the current value of par. c if (par .eq. zero) par = dmax1(dwarf,p001*paru) temp = dsqrt(par) do 160 j = 1, n wa1(j) = temp*diag(j) 160 continue call qrsolv(n,r,ldr,ipvt,wa1,qtb,x,sdiag,wa2) do 170 j = 1, n wa2(j) = diag(j)*x(j) 170 continue dxnorm = enorm(n,wa2) temp = fp fp = dxnorm - delta c c if the function is small enough, accept the current value c of par. also test for the exceptional cases where parl c is zero or the number of iterations has reached 10. c if (dabs(fp) .le. p1*delta * .or. parl .eq. zero .and. fp .le. temp * .and. temp .lt. zero .or. iter .eq. 10) go to 220 c c compute the newton correction. c do 180 j = 1, n l = ipvt(j) wa1(j) = diag(l)*(wa2(l)/dxnorm) 180 continue do 210 j = 1, n wa1(j) = wa1(j)/sdiag(j) temp = wa1(j) jp1 = j + 1 if (n .lt. jp1) go to 200 do 190 i = jp1, n wa1(i) = wa1(i) - r(i,j)*temp 190 continue 200 continue 210 continue temp = enorm(n,wa1) parc = ((fp/delta)/temp)/temp c c depending on the sign of the function, update parl or paru. c if (fp .gt. zero) parl = dmax1(parl,par) if (fp .lt. zero) paru = dmin1(paru,par) c c compute an improved estimate for par. c par = dmax1(parl,par+parc) c c end of an iteration. c go to 150 220 continue c c termination. c if (iter .eq. 0) par = zero return c c last card of subroutine lmpar. c end minpack-19961126/Makefile.in0000644000175000017500000004620411616327304016360 0ustar sylvestresylvestre# Makefile.in generated by automake 1.9.6 from Makefile.am. # @configure_input@ # Copyright (C) 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, # 2003, 2004, 2005 Free Software Foundation, Inc. # This Makefile.in is free software; the Free Software Foundation # gives unlimited permission to copy and/or distribute it, # with or without modifications, as long as this notice is preserved. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY, to the extent permitted by law; without # even the implied warranty of MERCHANTABILITY or FITNESS FOR A # PARTICULAR PURPOSE. @SET_MAKE@ srcdir = @srcdir@ top_srcdir = @top_srcdir@ VPATH = @srcdir@ pkgdatadir = $(datadir)/@PACKAGE@ pkglibdir = $(libdir)/@PACKAGE@ pkgincludedir = $(includedir)/@PACKAGE@ top_builddir = . am__cd = CDPATH="$${ZSH_VERSION+.}$(PATH_SEPARATOR)" && cd INSTALL = @INSTALL@ install_sh_DATA = $(install_sh) -c -m 644 install_sh_PROGRAM = $(install_sh) -c install_sh_SCRIPT = $(install_sh) -c INSTALL_HEADER = $(INSTALL_DATA) transform = $(program_transform_name) NORMAL_INSTALL = : PRE_INSTALL = : POST_INSTALL = : NORMAL_UNINSTALL = : PRE_UNINSTALL = : POST_UNINSTALL = : build_triplet = @build@ host_triplet = @host@ DIST_COMMON = $(am__configure_deps) $(include_HEADERS) \ $(srcdir)/Makefile.am $(srcdir)/Makefile.in \ $(top_srcdir)/configure config.guess config.sub install-sh \ ltmain.sh missing mkinstalldirs subdir = . 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M.I.T. makes no representations about the # suitability of this software for any purpose. It is provided "as is" # without express or implied warranty. # # Calling this script install-sh is preferred over install.sh, to prevent # `make' implicit rules from creating a file called install from it # when there is no Makefile. # # This script is compatible with the BSD install script, but was written # from scratch. It can only install one file at a time, a restriction # shared with many OS's install programs. # set DOITPROG to echo to test this script # Don't use :- since 4.3BSD and earlier shells don't like it. doit="${DOITPROG-}" # put in absolute paths if you don't have them in your path; or use env. vars. mvprog="${MVPROG-mv}" cpprog="${CPPROG-cp}" chmodprog="${CHMODPROG-chmod}" chownprog="${CHOWNPROG-chown}" chgrpprog="${CHGRPPROG-chgrp}" stripprog="${STRIPPROG-strip}" rmprog="${RMPROG-rm}" mkdirprog="${MKDIRPROG-mkdir}" transformbasename="" transform_arg="" instcmd="$mvprog" chmodcmd="$chmodprog 0755" chowncmd="" chgrpcmd="" stripcmd="" rmcmd="$rmprog -f" mvcmd="$mvprog" src="" dst="" dir_arg="" while [ x"$1" != x ]; do case $1 in -c) instcmd="$cpprog" shift continue;; -d) dir_arg=true shift continue;; -m) chmodcmd="$chmodprog $2" shift shift continue;; -o) chowncmd="$chownprog $2" shift shift continue;; -g) chgrpcmd="$chgrpprog $2" shift shift continue;; -s) stripcmd="$stripprog" shift continue;; -t=*) transformarg=`echo $1 | sed 's/-t=//'` shift continue;; -b=*) transformbasename=`echo $1 | sed 's/-b=//'` shift continue;; *) if [ x"$src" = x ] then src=$1 else # this colon is to work around a 386BSD /bin/sh bug : dst=$1 fi shift continue;; esac done if [ x"$src" = x ] then echo "install: no input file specified" exit 1 else true fi if [ x"$dir_arg" != x ]; then dst=$src src="" if [ -d $dst ]; then instcmd=: chmodcmd="" else instcmd=mkdir fi else # Waiting for this to be detected by the "$instcmd $src $dsttmp" command # might cause directories to be created, which would be especially bad # if $src (and thus $dsttmp) contains '*'. if [ -f $src -o -d $src ] then true else echo "install: $src does not exist" exit 1 fi if [ x"$dst" = x ] then echo "install: no destination specified" exit 1 else true fi # If destination is a directory, append the input filename; if your system # does not like double slashes in filenames, you may need to add some logic if [ -d $dst ] then dst="$dst"/`basename $src` else true fi fi ## this sed command emulates the dirname command dstdir=`echo $dst | sed -e 's,[^/]*$,,;s,/$,,;s,^$,.,'` # Make sure that the destination directory exists. # this part is taken from Noah Friedman's mkinstalldirs script # Skip lots of stat calls in the usual case. if [ ! -d "$dstdir" ]; then defaultIFS=' ' IFS="${IFS-${defaultIFS}}" oIFS="${IFS}" # Some sh's can't handle IFS=/ for some reason. IFS='%' set - `echo ${dstdir} | sed -e 's@/@%@g' -e 's@^%@/@'` IFS="${oIFS}" pathcomp='' while [ $# -ne 0 ] ; do pathcomp="${pathcomp}${1}" shift if [ ! -d "${pathcomp}" ] ; then $mkdirprog "${pathcomp}" else true fi pathcomp="${pathcomp}/" done fi if [ x"$dir_arg" != x ] then $doit $instcmd $dst && if [ x"$chowncmd" != x ]; then $doit $chowncmd $dst; else true ; fi && if [ x"$chgrpcmd" != x ]; then $doit $chgrpcmd $dst; else true ; fi && if [ x"$stripcmd" != x ]; then $doit $stripcmd $dst; else true ; fi && if [ x"$chmodcmd" != x ]; then $doit $chmodcmd $dst; else true ; fi else # If we're going to rename the final executable, determine the name now. if [ x"$transformarg" = x ] then dstfile=`basename $dst` else dstfile=`basename $dst $transformbasename | sed $transformarg`$transformbasename fi # don't allow the sed command to completely eliminate the filename if [ x"$dstfile" = x ] then dstfile=`basename $dst` else true fi # Make a temp file name in the proper directory. dsttmp=$dstdir/#inst.$$# # Move or copy the file name to the temp name $doit $instcmd $src $dsttmp && trap "rm -f ${dsttmp}" 0 && # and set any options; do chmod last to preserve setuid bits # If any of these fail, we abort the whole thing. If we want to # ignore errors from any of these, just make sure not to ignore # errors from the above "$doit $instcmd $src $dsttmp" command. if [ x"$chowncmd" != x ]; then $doit $chowncmd $dsttmp; else true;fi && if [ x"$chgrpcmd" != x ]; then $doit $chgrpcmd $dsttmp; else true;fi && if [ x"$stripcmd" != x ]; then $doit $stripcmd $dsttmp; else true;fi && if [ x"$chmodcmd" != x ]; then $doit $chmodcmd $dsttmp; else true;fi && # Now rename the file to the real destination. $doit $rmcmd -f $dstdir/$dstfile && $doit $mvcmd $dsttmp $dstdir/$dstfile fi && exit 0 minpack-19961126/mkinstalldirs0000644000175000017500000000132211616327304017106 0ustar sylvestresylvestre#! /bin/sh # mkinstalldirs --- make directory hierarchy # Author: Noah Friedman # Created: 1993-05-16 # Public domain # $Id: mkinstalldirs,v 1.13 1999/01/05 03:18:55 bje Exp $ errstatus=0 for file do set fnord `echo ":$file" | sed -ne 's/^:\//#/;s/^://;s/\// /g;s/^#/\//;p'` shift pathcomp= for d do pathcomp="$pathcomp$d" case "$pathcomp" in -* ) pathcomp=./$pathcomp ;; esac if test ! -d "$pathcomp"; then echo "mkdir $pathcomp" mkdir "$pathcomp" || lasterr=$? if test ! -d "$pathcomp"; then errstatus=$lasterr fi fi pathcomp="$pathcomp/" done done exit $errstatus # mkinstalldirs ends here minpack-19961126/fdjac1.f0000644000175000017500000001152603226632004015603 0ustar sylvestresylvestre subroutine fdjac1(fcn,n,x,fvec,fjac,ldfjac,iflag,ml,mu,epsfcn, * wa1,wa2) integer n,ldfjac,iflag,ml,mu double precision epsfcn double precision x(n),fvec(n),fjac(ldfjac,n),wa1(n),wa2(n) c ********** c c subroutine fdjac1 c c this subroutine computes a forward-difference approximation c to the n by n jacobian matrix associated with a specified c problem of n functions in n variables. if the jacobian has c a banded form, then function evaluations are saved by only c approximating the nonzero terms. c c the subroutine statement is c c subroutine fdjac1(fcn,n,x,fvec,fjac,ldfjac,iflag,ml,mu,epsfcn, c wa1,wa2) 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(n,x,fvec,iflag) c integer n,iflag c double precision x(n),fvec(n) 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 fdjac1. c in this case set iflag to a negative integer. c c n is a positive integer input variable set to the number c of functions and variables. c c x is an input array of length n. c c fvec is an input array of length n which must contain the c functions evaluated at x. c c fjac is an output n by n array which contains the c approximation to the jacobian matrix evaluated at x. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. c c iflag is an integer variable which can be used to terminate c the execution of fdjac1. see description of fcn. c c ml is a nonnegative integer input variable which specifies c the number of subdiagonals within the band of the c jacobian matrix. if the jacobian is not banded, set c ml to at least n - 1. c c epsfcn is an input variable used in determining a suitable c step length for the forward-difference approximation. this c approximation assumes that the relative errors in the c functions are of the order of epsfcn. if epsfcn is less c than the machine precision, it is assumed that the relative c errors in the functions are of the order of the machine c precision. c c mu is a nonnegative integer input variable which specifies c the number of superdiagonals within the band of the c jacobian matrix. if the jacobian is not banded, set c mu to at least n - 1. c c wa1 and wa2 are work arrays of length n. if ml + mu + 1 is at c least n, then the jacobian is considered dense, and wa2 is c not referenced. c c subprograms called c c minpack-supplied ... dpmpar c c fortran-supplied ... dabs,dmax1,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j,k,msum double precision eps,epsmch,h,temp,zero double precision dpmpar data zero /0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c eps = dsqrt(dmax1(epsfcn,epsmch)) msum = ml + mu + 1 if (msum .lt. n) go to 40 c c computation of dense approximate jacobian. c do 20 j = 1, n temp = x(j) h = eps*dabs(temp) if (h .eq. zero) h = eps x(j) = temp + h call fcn(n,x,wa1,iflag) if (iflag .lt. 0) go to 30 x(j) = temp do 10 i = 1, n fjac(i,j) = (wa1(i) - fvec(i))/h 10 continue 20 continue 30 continue go to 110 40 continue c c computation of banded approximate jacobian. c do 90 k = 1, msum do 60 j = k, n, msum wa2(j) = x(j) h = eps*dabs(wa2(j)) if (h .eq. zero) h = eps x(j) = wa2(j) + h 60 continue call fcn(n,x,wa1,iflag) if (iflag .lt. 0) go to 100 do 80 j = k, n, msum x(j) = wa2(j) h = eps*dabs(wa2(j)) if (h .eq. zero) h = eps do 70 i = 1, n fjac(i,j) = zero if (i .ge. j - mu .and. i .le. j + ml) * fjac(i,j) = (wa1(i) - fvec(i))/h 70 continue 80 continue 90 continue 100 continue 110 continue return c c last card of subroutine fdjac1. c end minpack-19961126/chkder.f0000644000175000017500000001143403226632001015706 0ustar sylvestresylvestre subroutine chkder(m,n,x,fvec,fjac,ldfjac,xp,fvecp,mode,err) integer m,n,ldfjac,mode double precision x(n),fvec(m),fjac(ldfjac,n),xp(n),fvecp(m), * err(m) c ********** c c subroutine chkder c c this subroutine checks the gradients of m nonlinear functions c in n variables, evaluated at a point x, for consistency with c the functions themselves. the user must call chkder twice, c first with mode = 1 and then with mode = 2. c c mode = 1. on input, x must contain the point of evaluation. c on output, xp is set to a neighboring point. c c mode = 2. on input, fvec must contain the functions and the c rows of fjac must contain the gradients c of the respective functions each evaluated c at x, and fvecp must contain the functions c evaluated at xp. c on output, err contains measures of correctness of c the respective gradients. c c the subroutine does not perform reliably if cancellation or c rounding errors cause a severe loss of significance in the c evaluation of a function. therefore, none of the components c of x should be unusually small (in particular, zero) or any c other value which may cause loss of significance. c c the subroutine statement is c c subroutine chkder(m,n,x,fvec,fjac,ldfjac,xp,fvecp,mode,err) c c where 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. c c x is an input array of length n. c c fvec is an array of length m. on input when mode = 2, c fvec must contain the functions evaluated at x. c c fjac is an m by n array. on input when mode = 2, c the rows of fjac must contain the gradients of c the respective functions evaluated at x. c c ldfjac is a positive integer input parameter not less than m c which specifies the leading dimension of the array fjac. c c xp is an array of length n. on output when mode = 1, c xp is set to a neighboring point of x. c c fvecp is an array of length m. on input when mode = 2, c fvecp must contain the functions evaluated at xp. c c mode is an integer input variable set to 1 on the first call c and 2 on the second. other values of mode are equivalent c to mode = 1. c c err is an array of length m. on output when mode = 2, c err contains measures of correctness of the respective c gradients. if there is no severe loss of significance, c then if err(i) is 1.0 the i-th gradient is correct, c while if err(i) is 0.0 the i-th gradient is incorrect. c for values of err between 0.0 and 1.0, the categorization c is less certain. in general, a value of err(i) greater c than 0.5 indicates that the i-th gradient is probably c correct, while a value of err(i) less than 0.5 indicates c that the i-th gradient is probably incorrect. c c subprograms called c c minpack supplied ... dpmpar c c fortran supplied ... dabs,dlog10,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j double precision eps,epsf,epslog,epsmch,factor,one,temp,zero double precision dpmpar data factor,one,zero /1.0d2,1.0d0,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c eps = dsqrt(epsmch) c if (mode .eq. 2) go to 20 c c mode = 1. c do 10 j = 1, n temp = eps*dabs(x(j)) if (temp .eq. zero) temp = eps xp(j) = x(j) + temp 10 continue go to 70 20 continue c c mode = 2. c epsf = factor*epsmch epslog = dlog10(eps) do 30 i = 1, m err(i) = zero 30 continue do 50 j = 1, n temp = dabs(x(j)) if (temp .eq. zero) temp = one do 40 i = 1, m err(i) = err(i) + temp*fjac(i,j) 40 continue 50 continue do 60 i = 1, m temp = one if (fvec(i) .ne. zero .and. fvecp(i) .ne. zero * .and. dabs(fvecp(i)-fvec(i)) .ge. epsf*dabs(fvec(i))) * temp = eps*dabs((fvecp(i)-fvec(i))/eps-err(i)) * /(dabs(fvec(i)) + dabs(fvecp(i))) err(i) = one if (temp .gt. epsmch .and. temp .lt. eps) * err(i) = (dlog10(temp) - epslog)/epslog if (temp .ge. eps) err(i) = zero 60 continue 70 continue c return c c last card of subroutine chkder. c end minpack-19961126/hybrd1.f0000644000175000017500000000752403226632006015651 0ustar sylvestresylvestre subroutine hybrd1(fcn,n,x,fvec,tol,info,wa,lwa) integer n,info,lwa double precision tol double precision x(n),fvec(n),wa(lwa) external fcn c ********** c c subroutine hybrd1 c c the purpose of hybrd1 is to find a zero of a system of c n nonlinear functions in n variables by a modification c of the powell hybrid method. this is done by using the c more general nonlinear equation solver hybrd. the user c must provide a subroutine which calculates the functions. c the jacobian is then calculated by a forward-difference c approximation. c c the subroutine statement is c c subroutine hybrd1(fcn,n,x,fvec,tol,info,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(n,x,fvec,iflag) c integer n,iflag c double precision x(n),fvec(n) 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 hybrd1. c in this case set iflag to a negative integer. c c n is a positive integer input variable set to the number c of functions and variables. 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 n 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 that the relative error c between x and the solution is at 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 between x and the solution is at most tol. c c info = 2 number of calls to fcn has reached or exceeded c 200*(n+1). c c info = 3 tol is too small. no further improvement in c the approximate solution x is possible. c c info = 4 iteration is not making good progress. c c wa is a work array of length lwa. c c lwa is a positive integer input variable not less than c (n*(3*n+13))/2. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... hybrd c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer index,j,lr,maxfev,ml,mode,mu,nfev,nprint double precision epsfcn,factor,one,xtol,zero data factor,one,zero /1.0d2,1.0d0,0.0d0/ info = 0 c c check the input parameters for errors. c if (n .le. 0 .or. tol .lt. zero .or. lwa .lt. (n*(3*n + 13))/2) * go to 20 c c call hybrd. c maxfev = 200*(n + 1) xtol = tol ml = n - 1 mu = n - 1 epsfcn = zero mode = 2 do 10 j = 1, n wa(j) = one 10 continue nprint = 0 lr = (n*(n + 1))/2 index = 6*n + lr call hybrd(fcn,n,x,fvec,xtol,maxfev,ml,mu,epsfcn,wa(1),mode, * factor,nprint,info,nfev,wa(index+1),n,wa(6*n+1),lr, * wa(n+1),wa(2*n+1),wa(3*n+1),wa(4*n+1),wa(5*n+1)) if (info .eq. 5) info = 4 20 continue return c c last card of subroutine hybrd1. c end minpack-19961126/rwupdt.f0000644000175000017500000000733503226632014016004 0ustar sylvestresylvestre subroutine rwupdt(n,r,ldr,w,b,alpha,cos,sin) integer n,ldr double precision alpha double precision r(ldr,n),w(n),b(n),cos(n),sin(n) c ********** c c subroutine rwupdt c c given an n by n upper triangular matrix r, this subroutine c computes the qr decomposition of the matrix formed when a row c is added to r. if the row is specified by the vector w, then c rwupdt determines an orthogonal matrix q such that when the c n+1 by n matrix composed of r augmented by w is premultiplied c by (q transpose), the resulting matrix is upper trapezoidal. c the matrix (q transpose) is the product of n transformations c c g(n)*g(n-1)* ... *g(1) c c where g(i) is a givens rotation in the (i,n+1) plane which c eliminates elements in the (n+1)-st plane. rwupdt also c computes the product (q transpose)*c where c is the c (n+1)-vector (b,alpha). q itself is not accumulated, rather c the information to recover the g rotations is supplied. c c the subroutine statement is c c subroutine rwupdt(n,r,ldr,w,b,alpha,cos,sin) c c where c c n is a positive integer input variable set to the order of r. c c r is an n by n array. on input the upper triangular part of c r must contain the matrix to be updated. on output r c contains the updated triangular matrix. c c ldr is a positive integer input variable not less than n c which specifies the leading dimension of the array r. c c w is an input array of length n which must contain the row c vector to be added to r. c c b is an array of length n. on input b must contain the c first n elements of the vector c. on output b contains c the first n elements of the vector (q transpose)*c. c c alpha is a variable. on input alpha must contain the c (n+1)-st element of the vector c. on output alpha contains c the (n+1)-st element of the vector (q transpose)*c. c c cos is an output array of length n which contains the c cosines of the transforming givens rotations. c c sin is an output array of length n which contains the c sines of the transforming givens rotations. c c subprograms called c c fortran-supplied ... dabs,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, dudley v. goetschel, kenneth e. hillstrom, c jorge j. more c c ********** integer i,j,jm1 double precision cotan,one,p5,p25,rowj,tan,temp,zero data one,p5,p25,zero /1.0d0,5.0d-1,2.5d-1,0.0d0/ c do 60 j = 1, n rowj = w(j) jm1 = j - 1 c c apply the previous transformations to c r(i,j), i=1,2,...,j-1, and to w(j). c if (jm1 .lt. 1) go to 20 do 10 i = 1, jm1 temp = cos(i)*r(i,j) + sin(i)*rowj rowj = -sin(i)*r(i,j) + cos(i)*rowj r(i,j) = temp 10 continue 20 continue c c determine a givens rotation which eliminates w(j). c cos(j) = one sin(j) = zero if (rowj .eq. zero) go to 50 if (dabs(r(j,j)) .ge. dabs(rowj)) go to 30 cotan = r(j,j)/rowj sin(j) = p5/dsqrt(p25+p25*cotan**2) cos(j) = sin(j)*cotan go to 40 30 continue tan = rowj/r(j,j) cos(j) = p5/dsqrt(p25+p25*tan**2) sin(j) = cos(j)*tan 40 continue c c apply the current transformation to r(j,j), b(j), and alpha. c r(j,j) = cos(j)*r(j,j) + sin(j)*rowj temp = cos(j)*b(j) + sin(j)*alpha alpha = -sin(j)*b(j) + cos(j)*alpha b(j) = temp 50 continue 60 continue return c c last card of subroutine rwupdt. c end minpack-19961126/configure.in0000644000175000017500000000144111616327304016616 0ustar sylvestresylvestrednl Process this file with autoconf to produce a configure script. AC_INIT(lmdif.f) dnl Every other copy of the package version number gets its value from here AM_INIT_AUTOMAKE(minpack, 19961126) # shared library version control VERSION_CURRENT=1 VERSION_REVISION=0 VERSION_AGE=0 AC_SUBST(VERSION) AC_SUBST(VERSION_CURRENT) AC_SUBST(VERSION_REVISION) AC_SUBST(VERSION_AGE) dnl Checks for programs. AC_PROG_INSTALL AC_PROG_F77 AC_PROG_CC AM_PROG_LIBTOOL dnl maybe bash is not in /bin on this system AC_PATH_PROG(bash, bash, FAIL) if test "$bash" = "FAIL"; then AC_MSG_ERROR(Cannot continue: bash not found) fi dnl Checks for libraries. dnl Checks for header files. dnl Checks for typedefs, structures, and compiler characteristics. dnl Checks for library functions. AC_OUTPUT(Makefile) minpack-19961126/hybrj.f0000644000175000017500000003337503226632006015601 0ustar sylvestresylvestre subroutine hybrj(fcn,n,x,fvec,fjac,ldfjac,xtol,maxfev,diag,mode, * factor,nprint,info,nfev,njev,r,lr,qtf,wa1,wa2, * wa3,wa4) integer n,ldfjac,maxfev,mode,nprint,info,nfev,njev,lr double precision xtol,factor double precision x(n),fvec(n),fjac(ldfjac,n),diag(n),r(lr), * qtf(n),wa1(n),wa2(n),wa3(n),wa4(n) c ********** c c subroutine hybrj c c the purpose of hybrj is to find a zero of a system of c n nonlinear functions in n variables by a modification c of the powell hybrid method. the user must provide a c subroutine which calculates the functions and the jacobian. c c the subroutine statement is c c subroutine hybrj(fcn,n,x,fvec,fjac,ldfjac,xtol,maxfev,diag, c mode,factor,nprint,info,nfev,njev,r,lr,qtf, c wa1,wa2,wa3,wa4) c c where c c fcn is the name of the user-supplied subroutine which c calculates the functions and the jacobian. fcn must c be declared in an external statement in the user c calling program, and should be written as follows. c c subroutine fcn(n,x,fvec,fjac,ldfjac,iflag) c integer n,ldfjac,iflag c double precision x(n),fvec(n),fjac(ldfjac,n) c ---------- c if iflag = 1 calculate the functions at x and c return this vector in fvec. do not alter fjac. c if iflag = 2 calculate the jacobian at x and c return this matrix in fjac. do not alter 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 hybrj. c in this case set iflag to a negative integer. c c n is a positive integer input variable set to the number c of functions and variables. 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 n which contains c the functions evaluated at the output x. c c fjac is an output n by n array which contains the c orthogonal matrix q produced by the qr factorization c of the final approximate jacobian. c c ldfjac is a positive integer input variable not less than n c which specifies the leading dimension of the array fjac. c c xtol is a nonnegative input variable. termination c occurs when the relative error between two consecutive c iterates is at most xtol. c c maxfev is a positive integer input variable. termination c occurs when the number of calls to fcn with iflag = 1 c has reached maxfev. c c diag is an array of length n. if mode = 1 (see c below), diag is internally set. if mode = 2, diag c must contain positive entries that serve as c multiplicative scale factors for the variables. c c mode is an integer input variable. if mode = 1, the c variables will be scaled internally. if mode = 2, c the scaling is specified by the input diag. other c values of mode are equivalent to mode = 1. c c factor is a positive input variable used in determining the c initial step bound. this bound is set to the product of c factor and the euclidean norm of diag*x if nonzero, or else c to factor itself. in most cases factor should lie in the c interval (.1,100.). 100. is a generally recommended value. c c nprint is an integer input variable that enables controlled c printing of iterates if it is positive. in this case, c fcn is called with iflag = 0 at the beginning of the first c iteration and every nprint iterations thereafter and c immediately prior to return, with x and fvec available c for printing. fvec and fjac should not be altered. c if nprint is not positive, no special calls of fcn c with iflag = 0 are made. 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 relative error between two consecutive iterates c is at most xtol. c c info = 2 number of calls to fcn with iflag = 1 has c reached maxfev. c c info = 3 xtol is too small. no further improvement in c the approximate solution x is possible. c c info = 4 iteration is not making good progress, as c measured by the improvement from the last c five jacobian evaluations. c c info = 5 iteration is not making good progress, as c measured by the improvement from the last c ten iterations. c c nfev is an integer output variable set to the number of c calls to fcn with iflag = 1. c c njev is an integer output variable set to the number of c calls to fcn with iflag = 2. c c r is an output array of length lr which contains the c upper triangular matrix produced by the qr factorization c of the final approximate jacobian, stored rowwise. c c lr is a positive integer input variable not less than c (n*(n+1))/2. c c qtf is an output array of length n which contains c the vector (q transpose)*fvec. c c wa1, wa2, wa3, and wa4 are work arrays of length n. c c subprograms called c c user-supplied ...... fcn c c minpack-supplied ... dogleg,dpmpar,enorm, c qform,qrfac,r1mpyq,r1updt c c fortran-supplied ... dabs,dmax1,dmin1,mod c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,iflag,iter,j,jm1,l,ncfail,ncsuc,nslow1,nslow2 integer iwa(1) logical jeval,sing double precision actred,delta,epsmch,fnorm,fnorm1,one,pnorm, * prered,p1,p5,p001,p0001,ratio,sum,temp,xnorm, * zero double precision dpmpar,enorm data one,p1,p5,p001,p0001,zero * /1.0d0,1.0d-1,5.0d-1,1.0d-3,1.0d-4,0.0d0/ c c epsmch is the machine precision. c epsmch = dpmpar(1) c info = 0 iflag = 0 nfev = 0 njev = 0 c c check the input parameters for errors. c if (n .le. 0 .or. ldfjac .lt. n .or. xtol .lt. zero * .or. maxfev .le. 0 .or. factor .le. zero * .or. lr .lt. (n*(n + 1))/2) go to 300 if (mode .ne. 2) go to 20 do 10 j = 1, n if (diag(j) .le. zero) go to 300 10 continue 20 continue c c evaluate the function at the starting point c and calculate its norm. c iflag = 1 call fcn(n,x,fvec,fjac,ldfjac,iflag) nfev = 1 if (iflag .lt. 0) go to 300 fnorm = enorm(n,fvec) c c initialize iteration counter and monitors. c iter = 1 ncsuc = 0 ncfail = 0 nslow1 = 0 nslow2 = 0 c c beginning of the outer loop. c 30 continue jeval = .true. c c calculate the jacobian matrix. c iflag = 2 call fcn(n,x,fvec,fjac,ldfjac,iflag) njev = njev + 1 if (iflag .lt. 0) go to 300 c c compute the qr factorization of the jacobian. c call qrfac(n,n,fjac,ldfjac,.false.,iwa,1,wa1,wa2,wa3) c c on the first iteration and if mode is 1, scale according c to the norms of the columns of the initial jacobian. c if (iter .ne. 1) go to 70 if (mode .eq. 2) go to 50 do 40 j = 1, n diag(j) = wa2(j) if (wa2(j) .eq. zero) diag(j) = one 40 continue 50 continue c c on the first iteration, calculate the norm of the scaled x c and initialize the step bound delta. c do 60 j = 1, n wa3(j) = diag(j)*x(j) 60 continue xnorm = enorm(n,wa3) delta = factor*xnorm if (delta .eq. zero) delta = factor 70 continue c c form (q transpose)*fvec and store in qtf. c do 80 i = 1, n qtf(i) = fvec(i) 80 continue do 120 j = 1, n if (fjac(j,j) .eq. zero) go to 110 sum = zero do 90 i = j, n sum = sum + fjac(i,j)*qtf(i) 90 continue temp = -sum/fjac(j,j) do 100 i = j, n qtf(i) = qtf(i) + fjac(i,j)*temp 100 continue 110 continue 120 continue c c copy the triangular factor of the qr factorization into r. c sing = .false. do 150 j = 1, n l = j jm1 = j - 1 if (jm1 .lt. 1) go to 140 do 130 i = 1, jm1 r(l) = fjac(i,j) l = l + n - i 130 continue 140 continue r(l) = wa1(j) if (wa1(j) .eq. zero) sing = .true. 150 continue c c accumulate the orthogonal factor in fjac. c call qform(n,n,fjac,ldfjac,wa1) c c rescale if necessary. c if (mode .eq. 2) go to 170 do 160 j = 1, n diag(j) = dmax1(diag(j),wa2(j)) 160 continue 170 continue c c beginning of the inner loop. c 180 continue c c if requested, call fcn to enable printing of iterates. c if (nprint .le. 0) go to 190 iflag = 0 if (mod(iter-1,nprint) .eq. 0) * call fcn(n,x,fvec,fjac,ldfjac,iflag) if (iflag .lt. 0) go to 300 190 continue c c determine the direction p. c call dogleg(n,r,lr,diag,qtf,delta,wa1,wa2,wa3) c c store the direction p and x + p. calculate the norm of p. c do 200 j = 1, n wa1(j) = -wa1(j) wa2(j) = x(j) + wa1(j) wa3(j) = diag(j)*wa1(j) 200 continue pnorm = enorm(n,wa3) c c on the first iteration, adjust the initial step bound. c if (iter .eq. 1) delta = dmin1(delta,pnorm) c c evaluate the function at x + p and calculate its norm. c iflag = 1 call fcn(n,wa2,wa4,fjac,ldfjac,iflag) nfev = nfev + 1 if (iflag .lt. 0) go to 300 fnorm1 = enorm(n,wa4) c c compute the scaled actual reduction. c actred = -one if (fnorm1 .lt. fnorm) actred = one - (fnorm1/fnorm)**2 c c compute the scaled predicted reduction. c l = 1 do 220 i = 1, n sum = zero do 210 j = i, n sum = sum + r(l)*wa1(j) l = l + 1 210 continue wa3(i) = qtf(i) + sum 220 continue temp = enorm(n,wa3) prered = zero if (temp .lt. fnorm) prered = one - (temp/fnorm)**2 c c compute the ratio of the actual to the predicted c reduction. c ratio = zero if (prered .gt. zero) ratio = actred/prered c c update the step bound. c if (ratio .ge. p1) go to 230 ncsuc = 0 ncfail = ncfail + 1 delta = p5*delta go to 240 230 continue ncfail = 0 ncsuc = ncsuc + 1 if (ratio .ge. p5 .or. ncsuc .gt. 1) * delta = dmax1(delta,pnorm/p5) if (dabs(ratio-one) .le. p1) delta = pnorm/p5 240 continue c c test for successful iteration. c if (ratio .lt. p0001) go to 260 c c successful iteration. update x, fvec, and their norms. c do 250 j = 1, n x(j) = wa2(j) wa2(j) = diag(j)*x(j) fvec(j) = wa4(j) 250 continue xnorm = enorm(n,wa2) fnorm = fnorm1 iter = iter + 1 260 continue c c determine the progress of the iteration. c nslow1 = nslow1 + 1 if (actred .ge. p001) nslow1 = 0 if (jeval) nslow2 = nslow2 + 1 if (actred .ge. p1) nslow2 = 0 c c test for convergence. c if (delta .le. xtol*xnorm .or. fnorm .eq. zero) info = 1 if (info .ne. 0) go to 300 c c tests for termination and stringent tolerances. c if (nfev .ge. maxfev) info = 2 if (p1*dmax1(p1*delta,pnorm) .le. epsmch*xnorm) info = 3 if (nslow2 .eq. 5) info = 4 if (nslow1 .eq. 10) info = 5 if (info .ne. 0) go to 300 c c criterion for recalculating jacobian. c if (ncfail .eq. 2) go to 290 c c calculate the rank one modification to the jacobian c and update qtf if necessary. c do 280 j = 1, n sum = zero do 270 i = 1, n sum = sum + fjac(i,j)*wa4(i) 270 continue wa2(j) = (sum - wa3(j))/pnorm wa1(j) = diag(j)*((diag(j)*wa1(j))/pnorm) if (ratio .ge. p0001) qtf(j) = sum 280 continue c c compute the qr factorization of the updated jacobian. c call r1updt(n,n,r,lr,wa1,wa2,wa3,sing) call r1mpyq(n,n,fjac,ldfjac,wa2,wa3) call r1mpyq(1,n,qtf,1,wa2,wa3) c c end of the inner loop. c jeval = .false. go to 180 290 continue c c end of the outer loop. c go to 30 300 continue c c termination, either normal or user imposed. c if (iflag .lt. 0) info = iflag iflag = 0 if (nprint .gt. 0) call fcn(n,x,fvec,fjac,ldfjac,iflag) return c c last card of subroutine hybrj. c end minpack-19961126/enorm.f0000644000175000017500000000607703226632003015577 0ustar sylvestresylvestre double precision function enorm(n,x) integer n double precision x(n) c ********** c c function enorm c c given an n-vector x, this function calculates the c euclidean norm of x. c c the euclidean norm is computed by accumulating the sum of c squares in three different sums. the sums of squares for the c small and large components are scaled so that no overflows c occur. non-destructive underflows are permitted. underflows c and overflows do not occur in the computation of the unscaled c sum of squares for the intermediate components. c the definitions of small, intermediate and large components c depend on two constants, rdwarf and rgiant. the main c restrictions on these constants are that rdwarf**2 not c underflow and rgiant**2 not overflow. the constants c given here are suitable for every known computer. c c the function statement is c c double precision function enorm(n,x) c c where c c n is a positive integer input variable. c c x is an input array of length n. c c subprograms called c c fortran-supplied ... dabs,dsqrt c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i double precision agiant,floatn,one,rdwarf,rgiant,s1,s2,s3,xabs, * x1max,x3max,zero data one,zero,rdwarf,rgiant /1.0d0,0.0d0,3.834d-20,1.304d19/ s1 = zero s2 = zero s3 = zero x1max = zero x3max = zero floatn = n agiant = rgiant/floatn do 90 i = 1, n xabs = dabs(x(i)) if (xabs .gt. rdwarf .and. xabs .lt. agiant) go to 70 if (xabs .le. rdwarf) go to 30 c c sum for large components. c if (xabs .le. x1max) go to 10 s1 = one + s1*(x1max/xabs)**2 x1max = xabs go to 20 10 continue s1 = s1 + (xabs/x1max)**2 20 continue go to 60 30 continue c c sum for small components. c if (xabs .le. x3max) go to 40 s3 = one + s3*(x3max/xabs)**2 x3max = xabs go to 50 40 continue if (xabs .ne. zero) s3 = s3 + (xabs/x3max)**2 50 continue 60 continue go to 80 70 continue c c sum for intermediate components. c s2 = s2 + xabs**2 80 continue 90 continue c c calculation of norm. c if (s1 .eq. zero) go to 100 enorm = x1max*dsqrt(s1+(s2/x1max)/x1max) go to 130 100 continue if (s2 .eq. zero) go to 110 if (s2 .ge. x3max) * enorm = dsqrt(s2*(one+(x3max/s2)*(x3max*s3))) if (s2 .lt. x3max) * enorm = dsqrt(x3max*((s2/x3max)+(x3max*s3))) go to 120 110 continue enorm = x3max*dsqrt(s3) 120 continue 130 continue return c c last card of function enorm. c end minpack-19961126/config.guess0000644000175000017500000012626011616327304016631 0ustar sylvestresylvestre#! /bin/sh # Attempt to guess a canonical system name. # Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, # 2000, 2001, 2002, 2003, 2004, 2005, 2006 Free Software Foundation, # Inc. timestamp='2006-07-02' # This file is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, but # WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. 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I hope that # covers most systems running today. This code pipes the CPU # types through head -n 1, so we only detect the type of CPU 0. ALPHA_CPU_TYPE=`/usr/sbin/psrinfo -v | sed -n -e 's/^ The alpha \(.*\) processor.*$/\1/p' | head -n 1` case "$ALPHA_CPU_TYPE" in "EV4 (21064)") UNAME_MACHINE="alpha" ;; "EV4.5 (21064)") UNAME_MACHINE="alpha" ;; "LCA4 (21066/21068)") UNAME_MACHINE="alpha" ;; "EV5 (21164)") UNAME_MACHINE="alphaev5" ;; "EV5.6 (21164A)") UNAME_MACHINE="alphaev56" ;; "EV5.6 (21164PC)") UNAME_MACHINE="alphapca56" ;; "EV5.7 (21164PC)") UNAME_MACHINE="alphapca57" ;; "EV6 (21264)") UNAME_MACHINE="alphaev6" ;; "EV6.7 (21264A)") UNAME_MACHINE="alphaev67" ;; "EV6.8CB (21264C)") UNAME_MACHINE="alphaev68" ;; "EV6.8AL (21264B)") UNAME_MACHINE="alphaev68" ;; "EV6.8CX (21264D)") UNAME_MACHINE="alphaev68" ;; "EV6.9A (21264/EV69A)") UNAME_MACHINE="alphaev69" ;; "EV7 (21364)") UNAME_MACHINE="alphaev7" ;; "EV7.9 (21364A)") UNAME_MACHINE="alphaev79" ;; esac # A Pn.n version is a patched version. # A Vn.n version is a released version. # A Tn.n version is a released field test version. # A Xn.n version is an unreleased experimental baselevel. # 1.2 uses "1.2" for uname -r. echo ${UNAME_MACHINE}-dec-osf`echo ${UNAME_RELEASE} | sed -e 's/^[PVTX]//' | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'` exit ;; Alpha\ *:Windows_NT*:*) # How do we know it's Interix rather than the generic POSIX subsystem? # Should we change UNAME_MACHINE based on the output of uname instead # of the specific Alpha model? echo alpha-pc-interix exit ;; 21064:Windows_NT:50:3) echo alpha-dec-winnt3.5 exit ;; Amiga*:UNIX_System_V:4.0:*) echo m68k-unknown-sysv4 exit ;; *:[Aa]miga[Oo][Ss]:*:*) echo ${UNAME_MACHINE}-unknown-amigaos exit ;; *:[Mm]orph[Oo][Ss]:*:*) echo ${UNAME_MACHINE}-unknown-morphos exit ;; *:OS/390:*:*) echo i370-ibm-openedition exit ;; *:z/VM:*:*) echo s390-ibm-zvmoe exit ;; *:OS400:*:*) echo powerpc-ibm-os400 exit ;; arm:RISC*:1.[012]*:*|arm:riscix:1.[012]*:*) echo arm-acorn-riscix${UNAME_RELEASE} exit ;; arm:riscos:*:*|arm:RISCOS:*:*) echo arm-unknown-riscos exit ;; SR2?01:HI-UX/MPP:*:* | SR8000:HI-UX/MPP:*:*) echo hppa1.1-hitachi-hiuxmpp exit ;; Pyramid*:OSx*:*:* | MIS*:OSx*:*:* | MIS*:SMP_DC-OSx*:*:*) # akee@wpdis03.wpafb.af.mil (Earle F. Ake) contributed MIS and NILE. if test "`(/bin/universe) 2>/dev/null`" = att ; then echo pyramid-pyramid-sysv3 else echo pyramid-pyramid-bsd fi exit ;; NILE*:*:*:dcosx) echo pyramid-pyramid-svr4 exit ;; DRS?6000:unix:4.0:6*) echo sparc-icl-nx6 exit ;; DRS?6000:UNIX_SV:4.2*:7* | DRS?6000:isis:4.2*:7*) case `/usr/bin/uname -p` in sparc) echo sparc-icl-nx7; exit ;; esac ;; sun4H:SunOS:5.*:*) echo sparc-hal-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'` exit ;; sun4*:SunOS:5.*:* | tadpole*:SunOS:5.*:*) echo sparc-sun-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'` exit ;; i86pc:SunOS:5.*:*) echo i386-pc-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'` exit ;; sun4*:SunOS:6*:*) # According to config.sub, this is the proper way to canonicalize # SunOS6. Hard to guess exactly what SunOS6 will be like, but # it's likely to be more like Solaris than SunOS4. echo sparc-sun-solaris3`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'` exit ;; sun4*:SunOS:*:*) case "`/usr/bin/arch -k`" in Series*|S4*) UNAME_RELEASE=`uname -v` ;; esac # Japanese Language versions have a version number like `4.1.3-JL'. echo sparc-sun-sunos`echo ${UNAME_RELEASE}|sed -e 's/-/_/'` exit ;; sun3*:SunOS:*:*) echo m68k-sun-sunos${UNAME_RELEASE} exit ;; sun*:*:4.2BSD:*) UNAME_RELEASE=`(sed 1q /etc/motd | awk '{print substr($5,1,3)}') 2>/dev/null` test "x${UNAME_RELEASE}" = "x" && UNAME_RELEASE=3 case "`/bin/arch`" in sun3) echo m68k-sun-sunos${UNAME_RELEASE} ;; sun4) echo sparc-sun-sunos${UNAME_RELEASE} ;; esac exit ;; aushp:SunOS:*:*) echo sparc-auspex-sunos${UNAME_RELEASE} exit ;; # The situation for MiNT is a little confusing. The machine name # can be virtually everything (everything which is not # "atarist" or "atariste" at least should have a processor # > m68000). The system name ranges from "MiNT" over "FreeMiNT" # to the lowercase version "mint" (or "freemint"). Finally # the system name "TOS" denotes a system which is actually not # MiNT. But MiNT is downward compatible to TOS, so this should # be no problem. atarist[e]:*MiNT:*:* | atarist[e]:*mint:*:* | atarist[e]:*TOS:*:*) echo m68k-atari-mint${UNAME_RELEASE} exit ;; atari*:*MiNT:*:* | atari*:*mint:*:* | atarist[e]:*TOS:*:*) echo m68k-atari-mint${UNAME_RELEASE} exit ;; *falcon*:*MiNT:*:* | *falcon*:*mint:*:* | *falcon*:*TOS:*:*) echo m68k-atari-mint${UNAME_RELEASE} exit ;; milan*:*MiNT:*:* | milan*:*mint:*:* | *milan*:*TOS:*:*) echo m68k-milan-mint${UNAME_RELEASE} exit ;; hades*:*MiNT:*:* | hades*:*mint:*:* | *hades*:*TOS:*:*) echo m68k-hades-mint${UNAME_RELEASE} exit ;; *:*MiNT:*:* | *:*mint:*:* | *:*TOS:*:*) echo m68k-unknown-mint${UNAME_RELEASE} exit ;; m68k:machten:*:*) echo m68k-apple-machten${UNAME_RELEASE} exit ;; powerpc:machten:*:*) echo powerpc-apple-machten${UNAME_RELEASE} exit ;; RISC*:Mach:*:*) echo mips-dec-mach_bsd4.3 exit ;; RISC*:ULTRIX:*:*) echo mips-dec-ultrix${UNAME_RELEASE} exit ;; VAX*:ULTRIX*:*:*) echo vax-dec-ultrix${UNAME_RELEASE} exit ;; 2020:CLIX:*:* | 2430:CLIX:*:*) echo clipper-intergraph-clix${UNAME_RELEASE} exit ;; mips:*:*:UMIPS | mips:*:*:RISCos) eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #ifdef __cplusplus #include /* for printf() prototype */ int main (int argc, char *argv[]) { #else int main (argc, argv) int argc; char *argv[]; { #endif #if defined (host_mips) && defined (MIPSEB) #if defined (SYSTYPE_SYSV) printf ("mips-mips-riscos%ssysv\n", argv[1]); exit (0); #endif #if defined (SYSTYPE_SVR4) printf ("mips-mips-riscos%ssvr4\n", argv[1]); exit (0); #endif #if defined (SYSTYPE_BSD43) || defined(SYSTYPE_BSD) printf ("mips-mips-riscos%sbsd\n", argv[1]); exit (0); #endif #endif exit (-1); } EOF $CC_FOR_BUILD -o $dummy $dummy.c && dummyarg=`echo "${UNAME_RELEASE}" | sed -n 's/\([0-9]*\).*/\1/p'` && SYSTEM_NAME=`$dummy $dummyarg` && { echo "$SYSTEM_NAME"; exit; } echo mips-mips-riscos${UNAME_RELEASE} exit ;; Motorola:PowerMAX_OS:*:*) echo powerpc-motorola-powermax exit ;; Motorola:*:4.3:PL8-*) echo powerpc-harris-powermax exit ;; Night_Hawk:*:*:PowerMAX_OS | Synergy:PowerMAX_OS:*:*) echo powerpc-harris-powermax exit ;; Night_Hawk:Power_UNIX:*:*) echo powerpc-harris-powerunix exit ;; m88k:CX/UX:7*:*) echo m88k-harris-cxux7 exit ;; m88k:*:4*:R4*) echo m88k-motorola-sysv4 exit ;; m88k:*:3*:R3*) echo m88k-motorola-sysv3 exit ;; AViiON:dgux:*:*) # DG/UX returns AViiON for all architectures UNAME_PROCESSOR=`/usr/bin/uname -p` if [ $UNAME_PROCESSOR = mc88100 ] || [ $UNAME_PROCESSOR = mc88110 ] then if [ ${TARGET_BINARY_INTERFACE}x = m88kdguxelfx ] || \ [ ${TARGET_BINARY_INTERFACE}x = x ] then echo m88k-dg-dgux${UNAME_RELEASE} else echo m88k-dg-dguxbcs${UNAME_RELEASE} fi else echo i586-dg-dgux${UNAME_RELEASE} fi exit ;; M88*:DolphinOS:*:*) # DolphinOS (SVR3) echo m88k-dolphin-sysv3 exit ;; M88*:*:R3*:*) # Delta 88k system running SVR3 echo m88k-motorola-sysv3 exit ;; XD88*:*:*:*) # Tektronix XD88 system running UTekV (SVR3) echo m88k-tektronix-sysv3 exit ;; Tek43[0-9][0-9]:UTek:*:*) # Tektronix 4300 system running UTek (BSD) echo m68k-tektronix-bsd exit ;; *:IRIX*:*:*) echo mips-sgi-irix`echo ${UNAME_RELEASE}|sed -e 's/-/_/g'` exit ;; ????????:AIX?:[12].1:2) # AIX 2.2.1 or AIX 2.1.1 is RT/PC AIX. echo romp-ibm-aix # uname -m gives an 8 hex-code CPU id exit ;; # Note that: echo "'`uname -s`'" gives 'AIX ' i*86:AIX:*:*) echo i386-ibm-aix exit ;; ia64:AIX:*:*) if [ -x /usr/bin/oslevel ] ; then IBM_REV=`/usr/bin/oslevel` else IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE} fi echo ${UNAME_MACHINE}-ibm-aix${IBM_REV} exit ;; *:AIX:2:3) if grep bos325 /usr/include/stdio.h >/dev/null 2>&1; then eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #include main() { if (!__power_pc()) exit(1); puts("powerpc-ibm-aix3.2.5"); exit(0); } EOF if $CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy` then echo "$SYSTEM_NAME" else echo rs6000-ibm-aix3.2.5 fi elif grep bos324 /usr/include/stdio.h >/dev/null 2>&1; then echo rs6000-ibm-aix3.2.4 else echo rs6000-ibm-aix3.2 fi exit ;; *:AIX:*:[45]) IBM_CPU_ID=`/usr/sbin/lsdev -C -c processor -S available | sed 1q | awk '{ print $1 }'` if /usr/sbin/lsattr -El ${IBM_CPU_ID} | grep ' POWER' >/dev/null 2>&1; then IBM_ARCH=rs6000 else IBM_ARCH=powerpc fi if [ -x /usr/bin/oslevel ] ; then IBM_REV=`/usr/bin/oslevel` else IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE} fi echo ${IBM_ARCH}-ibm-aix${IBM_REV} exit ;; *:AIX:*:*) echo rs6000-ibm-aix exit ;; ibmrt:4.4BSD:*|romp-ibm:BSD:*) echo romp-ibm-bsd4.4 exit ;; ibmrt:*BSD:*|romp-ibm:BSD:*) # covers RT/PC BSD and echo romp-ibm-bsd${UNAME_RELEASE} # 4.3 with uname added to exit ;; # report: romp-ibm BSD 4.3 *:BOSX:*:*) echo rs6000-bull-bosx exit ;; DPX/2?00:B.O.S.:*:*) echo m68k-bull-sysv3 exit ;; 9000/[34]??:4.3bsd:1.*:*) echo m68k-hp-bsd exit ;; hp300:4.4BSD:*:* | 9000/[34]??:4.3bsd:2.*:*) echo m68k-hp-bsd4.4 exit ;; 9000/[34678]??:HP-UX:*:*) HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'` case "${UNAME_MACHINE}" in 9000/31? ) HP_ARCH=m68000 ;; 9000/[34]?? ) HP_ARCH=m68k ;; 9000/[678][0-9][0-9]) if [ -x /usr/bin/getconf ]; then sc_cpu_version=`/usr/bin/getconf SC_CPU_VERSION 2>/dev/null` sc_kernel_bits=`/usr/bin/getconf SC_KERNEL_BITS 2>/dev/null` case "${sc_cpu_version}" in 523) HP_ARCH="hppa1.0" ;; # CPU_PA_RISC1_0 528) HP_ARCH="hppa1.1" ;; # CPU_PA_RISC1_1 532) # CPU_PA_RISC2_0 case "${sc_kernel_bits}" in 32) HP_ARCH="hppa2.0n" ;; 64) HP_ARCH="hppa2.0w" ;; '') HP_ARCH="hppa2.0" ;; # HP-UX 10.20 esac ;; esac fi if [ "${HP_ARCH}" = "" ]; then eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #define _HPUX_SOURCE #include #include int main () { #if defined(_SC_KERNEL_BITS) long bits = sysconf(_SC_KERNEL_BITS); #endif long cpu = sysconf (_SC_CPU_VERSION); switch (cpu) { case CPU_PA_RISC1_0: puts ("hppa1.0"); break; case CPU_PA_RISC1_1: puts ("hppa1.1"); break; case CPU_PA_RISC2_0: #if defined(_SC_KERNEL_BITS) switch (bits) { case 64: puts ("hppa2.0w"); break; case 32: puts ("hppa2.0n"); break; default: puts ("hppa2.0"); break; } break; #else /* !defined(_SC_KERNEL_BITS) */ puts ("hppa2.0"); break; #endif default: puts ("hppa1.0"); break; } exit (0); } EOF (CCOPTS= $CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null) && HP_ARCH=`$dummy` test -z "$HP_ARCH" && HP_ARCH=hppa fi ;; esac if [ ${HP_ARCH} = "hppa2.0w" ] then eval $set_cc_for_build # hppa2.0w-hp-hpux* has a 64-bit kernel and a compiler generating # 32-bit code. hppa64-hp-hpux* has the same kernel and a compiler # generating 64-bit code. GNU and HP use different nomenclature: # # $ CC_FOR_BUILD=cc ./config.guess # => hppa2.0w-hp-hpux11.23 # $ CC_FOR_BUILD="cc +DA2.0w" ./config.guess # => hppa64-hp-hpux11.23 if echo __LP64__ | (CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) | grep __LP64__ >/dev/null then HP_ARCH="hppa2.0w" else HP_ARCH="hppa64" fi fi echo ${HP_ARCH}-hp-hpux${HPUX_REV} exit ;; ia64:HP-UX:*:*) HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'` echo ia64-hp-hpux${HPUX_REV} exit ;; 3050*:HI-UX:*:*) eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #include int main () { long cpu = sysconf (_SC_CPU_VERSION); /* The order matters, because CPU_IS_HP_MC68K erroneously returns true for CPU_PA_RISC1_0. CPU_IS_PA_RISC returns correct results, however. */ if (CPU_IS_PA_RISC (cpu)) { switch (cpu) { case CPU_PA_RISC1_0: puts ("hppa1.0-hitachi-hiuxwe2"); break; case CPU_PA_RISC1_1: puts ("hppa1.1-hitachi-hiuxwe2"); break; case CPU_PA_RISC2_0: puts ("hppa2.0-hitachi-hiuxwe2"); break; default: puts ("hppa-hitachi-hiuxwe2"); break; } } else if (CPU_IS_HP_MC68K (cpu)) puts ("m68k-hitachi-hiuxwe2"); else puts ("unknown-hitachi-hiuxwe2"); exit (0); } EOF $CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy` && { echo "$SYSTEM_NAME"; exit; } echo unknown-hitachi-hiuxwe2 exit ;; 9000/7??:4.3bsd:*:* | 9000/8?[79]:4.3bsd:*:* ) echo hppa1.1-hp-bsd exit ;; 9000/8??:4.3bsd:*:*) echo hppa1.0-hp-bsd exit ;; *9??*:MPE/iX:*:* | *3000*:MPE/iX:*:*) echo hppa1.0-hp-mpeix exit ;; hp7??:OSF1:*:* | hp8?[79]:OSF1:*:* ) echo hppa1.1-hp-osf exit ;; hp8??:OSF1:*:*) echo hppa1.0-hp-osf exit ;; i*86:OSF1:*:*) if [ -x /usr/sbin/sysversion ] ; then echo ${UNAME_MACHINE}-unknown-osf1mk else echo ${UNAME_MACHINE}-unknown-osf1 fi exit ;; parisc*:Lites*:*:*) echo hppa1.1-hp-lites exit ;; C1*:ConvexOS:*:* | convex:ConvexOS:C1*:*) echo c1-convex-bsd exit ;; C2*:ConvexOS:*:* | convex:ConvexOS:C2*:*) if getsysinfo -f scalar_acc then echo c32-convex-bsd else echo c2-convex-bsd fi exit ;; C34*:ConvexOS:*:* | convex:ConvexOS:C34*:*) echo c34-convex-bsd exit ;; C38*:ConvexOS:*:* | convex:ConvexOS:C38*:*) echo c38-convex-bsd exit ;; C4*:ConvexOS:*:* | convex:ConvexOS:C4*:*) echo c4-convex-bsd exit ;; CRAY*Y-MP:*:*:*) echo ymp-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/' exit ;; CRAY*[A-Z]90:*:*:*) echo ${UNAME_MACHINE}-cray-unicos${UNAME_RELEASE} \ | sed -e 's/CRAY.*\([A-Z]90\)/\1/' \ -e y/ABCDEFGHIJKLMNOPQRSTUVWXYZ/abcdefghijklmnopqrstuvwxyz/ \ -e 's/\.[^.]*$/.X/' exit ;; CRAY*TS:*:*:*) echo t90-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/' exit ;; CRAY*T3E:*:*:*) echo alphaev5-cray-unicosmk${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/' exit ;; CRAY*SV1:*:*:*) echo sv1-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/' exit ;; *:UNICOS/mp:*:*) echo craynv-cray-unicosmp${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/' exit ;; F30[01]:UNIX_System_V:*:* | F700:UNIX_System_V:*:*) FUJITSU_PROC=`uname -m | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'` FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'` FUJITSU_REL=`echo ${UNAME_RELEASE} | sed -e 's/ /_/'` echo "${FUJITSU_PROC}-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}" exit ;; 5000:UNIX_System_V:4.*:*) FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'` FUJITSU_REL=`echo ${UNAME_RELEASE} | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/ /_/'` echo "sparc-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}" exit ;; i*86:BSD/386:*:* | i*86:BSD/OS:*:* | *:Ascend\ Embedded/OS:*:*) echo ${UNAME_MACHINE}-pc-bsdi${UNAME_RELEASE} exit ;; sparc*:BSD/OS:*:*) echo sparc-unknown-bsdi${UNAME_RELEASE} exit ;; *:BSD/OS:*:*) echo ${UNAME_MACHINE}-unknown-bsdi${UNAME_RELEASE} exit ;; *:FreeBSD:*:*) case ${UNAME_MACHINE} in pc98) echo i386-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;; amd64) echo x86_64-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;; *) echo ${UNAME_MACHINE}-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;; esac exit ;; i*:CYGWIN*:*) echo ${UNAME_MACHINE}-pc-cygwin exit ;; i*:MINGW*:*) echo ${UNAME_MACHINE}-pc-mingw32 exit ;; i*:windows32*:*) # uname -m includes "-pc" on this system. echo ${UNAME_MACHINE}-mingw32 exit ;; i*:PW*:*) echo ${UNAME_MACHINE}-pc-pw32 exit ;; x86:Interix*:[3456]*) echo i586-pc-interix${UNAME_RELEASE} exit ;; EM64T:Interix*:[3456]*) echo x86_64-unknown-interix${UNAME_RELEASE} exit ;; [345]86:Windows_95:* | [345]86:Windows_98:* | [345]86:Windows_NT:*) echo i${UNAME_MACHINE}-pc-mks exit ;; i*:Windows_NT*:* | Pentium*:Windows_NT*:*) # How do we know it's Interix rather than the generic POSIX subsystem? # It also conflicts with pre-2.0 versions of AT&T UWIN. Should we # UNAME_MACHINE based on the output of uname instead of i386? echo i586-pc-interix exit ;; i*:UWIN*:*) echo ${UNAME_MACHINE}-pc-uwin exit ;; amd64:CYGWIN*:*:* | x86_64:CYGWIN*:*:*) echo x86_64-unknown-cygwin exit ;; p*:CYGWIN*:*) echo powerpcle-unknown-cygwin exit ;; prep*:SunOS:5.*:*) echo powerpcle-unknown-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'` exit ;; *:GNU:*:*) # the GNU system echo `echo ${UNAME_MACHINE}|sed -e 's,[-/].*$,,'`-unknown-gnu`echo ${UNAME_RELEASE}|sed -e 's,/.*$,,'` exit ;; *:GNU/*:*:*) # other systems with GNU libc and userland echo ${UNAME_MACHINE}-unknown-`echo ${UNAME_SYSTEM} | sed 's,^[^/]*/,,' | tr '[A-Z]' '[a-z]'``echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'`-gnu exit ;; i*86:Minix:*:*) echo ${UNAME_MACHINE}-pc-minix exit ;; arm*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; avr32*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; cris:Linux:*:*) echo cris-axis-linux-gnu exit ;; crisv32:Linux:*:*) echo crisv32-axis-linux-gnu exit ;; frv:Linux:*:*) echo frv-unknown-linux-gnu exit ;; ia64:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; m32r*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; m68*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; mips:Linux:*:*) eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #undef CPU #undef mips #undef mipsel #if defined(__MIPSEL__) || defined(__MIPSEL) || defined(_MIPSEL) || defined(MIPSEL) CPU=mipsel #else #if defined(__MIPSEB__) || defined(__MIPSEB) || defined(_MIPSEB) || defined(MIPSEB) CPU=mips #else CPU= #endif #endif EOF eval "`$CC_FOR_BUILD -E $dummy.c 2>/dev/null | sed -n ' /^CPU/{ s: ::g p }'`" test x"${CPU}" != x && { echo "${CPU}-unknown-linux-gnu"; exit; } ;; mips64:Linux:*:*) eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #undef CPU #undef mips64 #undef mips64el #if defined(__MIPSEL__) || defined(__MIPSEL) || defined(_MIPSEL) || defined(MIPSEL) CPU=mips64el #else #if defined(__MIPSEB__) || defined(__MIPSEB) || defined(_MIPSEB) || defined(MIPSEB) CPU=mips64 #else CPU= #endif #endif EOF eval "`$CC_FOR_BUILD -E $dummy.c 2>/dev/null | sed -n ' /^CPU/{ s: ::g p }'`" test x"${CPU}" != x && { echo "${CPU}-unknown-linux-gnu"; exit; } ;; or32:Linux:*:*) echo or32-unknown-linux-gnu exit ;; ppc:Linux:*:*) echo powerpc-unknown-linux-gnu exit ;; ppc64:Linux:*:*) echo powerpc64-unknown-linux-gnu exit ;; alpha:Linux:*:*) case `sed -n '/^cpu model/s/^.*: \(.*\)/\1/p' < /proc/cpuinfo` in EV5) UNAME_MACHINE=alphaev5 ;; EV56) UNAME_MACHINE=alphaev56 ;; PCA56) UNAME_MACHINE=alphapca56 ;; PCA57) UNAME_MACHINE=alphapca56 ;; EV6) UNAME_MACHINE=alphaev6 ;; EV67) UNAME_MACHINE=alphaev67 ;; EV68*) UNAME_MACHINE=alphaev68 ;; esac objdump --private-headers /bin/sh | grep ld.so.1 >/dev/null if test "$?" = 0 ; then LIBC="libc1" ; else LIBC="" ; fi echo ${UNAME_MACHINE}-unknown-linux-gnu${LIBC} exit ;; parisc:Linux:*:* | hppa:Linux:*:*) # Look for CPU level case `grep '^cpu[^a-z]*:' /proc/cpuinfo 2>/dev/null | cut -d' ' -f2` in PA7*) echo hppa1.1-unknown-linux-gnu ;; PA8*) echo hppa2.0-unknown-linux-gnu ;; *) echo hppa-unknown-linux-gnu ;; esac exit ;; parisc64:Linux:*:* | hppa64:Linux:*:*) echo hppa64-unknown-linux-gnu exit ;; s390:Linux:*:* | s390x:Linux:*:*) echo ${UNAME_MACHINE}-ibm-linux exit ;; sh64*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; sh*:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; sparc:Linux:*:* | sparc64:Linux:*:*) echo ${UNAME_MACHINE}-unknown-linux-gnu exit ;; vax:Linux:*:*) echo ${UNAME_MACHINE}-dec-linux-gnu exit ;; x86_64:Linux:*:*) echo x86_64-unknown-linux-gnu exit ;; i*86:Linux:*:*) # The BFD linker knows what the default object file format is, so # first see if it will tell us. cd to the root directory to prevent # problems with other programs or directories called `ld' in the path. # Set LC_ALL=C to ensure ld outputs messages in English. ld_supported_targets=`cd /; LC_ALL=C ld --help 2>&1 \ | sed -ne '/supported targets:/!d s/[ ][ ]*/ /g s/.*supported targets: *// s/ .*// p'` case "$ld_supported_targets" in elf32-i386) TENTATIVE="${UNAME_MACHINE}-pc-linux-gnu" ;; a.out-i386-linux) echo "${UNAME_MACHINE}-pc-linux-gnuaout" exit ;; coff-i386) echo "${UNAME_MACHINE}-pc-linux-gnucoff" exit ;; "") # Either a pre-BFD a.out linker (linux-gnuoldld) or # one that does not give us useful --help. echo "${UNAME_MACHINE}-pc-linux-gnuoldld" exit ;; esac # Determine whether the default compiler is a.out or elf eval $set_cc_for_build sed 's/^ //' << EOF >$dummy.c #include #ifdef __ELF__ # ifdef __GLIBC__ # if __GLIBC__ >= 2 LIBC=gnu # else LIBC=gnulibc1 # endif # else LIBC=gnulibc1 # endif #else #if defined(__INTEL_COMPILER) || defined(__PGI) || defined(__SUNPRO_C) || defined(__SUNPRO_CC) LIBC=gnu #else LIBC=gnuaout #endif #endif #ifdef __dietlibc__ LIBC=dietlibc #endif EOF eval "`$CC_FOR_BUILD -E $dummy.c 2>/dev/null | sed -n ' /^LIBC/{ s: ::g p }'`" test x"${LIBC}" != x && { echo "${UNAME_MACHINE}-pc-linux-${LIBC}" exit } test x"${TENTATIVE}" != x && { echo "${TENTATIVE}"; exit; } ;; i*86:DYNIX/ptx:4*:*) # ptx 4.0 does uname -s correctly, with DYNIX/ptx in there. # earlier versions are messed up and put the nodename in both # sysname and nodename. echo i386-sequent-sysv4 exit ;; i*86:UNIX_SV:4.2MP:2.*) # Unixware is an offshoot of SVR4, but it has its own version # number series starting with 2... # I am not positive that other SVR4 systems won't match this, # I just have to hope. -- rms. # Use sysv4.2uw... so that sysv4* matches it. echo ${UNAME_MACHINE}-pc-sysv4.2uw${UNAME_VERSION} exit ;; i*86:OS/2:*:*) # If we were able to find `uname', then EMX Unix compatibility # is probably installed. echo ${UNAME_MACHINE}-pc-os2-emx exit ;; i*86:XTS-300:*:STOP) echo ${UNAME_MACHINE}-unknown-stop exit ;; i*86:atheos:*:*) echo ${UNAME_MACHINE}-unknown-atheos exit ;; i*86:syllable:*:*) echo ${UNAME_MACHINE}-pc-syllable exit ;; i*86:LynxOS:2.*:* | i*86:LynxOS:3.[01]*:* | i*86:LynxOS:4.0*:*) echo i386-unknown-lynxos${UNAME_RELEASE} exit ;; i*86:*DOS:*:*) echo ${UNAME_MACHINE}-pc-msdosdjgpp exit ;; i*86:*:4.*:* | i*86:SYSTEM_V:4.*:*) UNAME_REL=`echo ${UNAME_RELEASE} | sed 's/\/MP$//'` if grep Novell /usr/include/link.h >/dev/null 2>/dev/null; then echo ${UNAME_MACHINE}-univel-sysv${UNAME_REL} else echo ${UNAME_MACHINE}-pc-sysv${UNAME_REL} fi exit ;; i*86:*:5:[678]*) # UnixWare 7.x, OpenUNIX and OpenServer 6. case `/bin/uname -X | grep "^Machine"` in *486*) UNAME_MACHINE=i486 ;; *Pentium) UNAME_MACHINE=i586 ;; *Pent*|*Celeron) UNAME_MACHINE=i686 ;; esac echo ${UNAME_MACHINE}-unknown-sysv${UNAME_RELEASE}${UNAME_SYSTEM}${UNAME_VERSION} exit ;; i*86:*:3.2:*) if test -f /usr/options/cb.name; then UNAME_REL=`sed -n 's/.*Version //p' /dev/null >/dev/null ; then UNAME_REL=`(/bin/uname -X|grep Release|sed -e 's/.*= //')` (/bin/uname -X|grep i80486 >/dev/null) && UNAME_MACHINE=i486 (/bin/uname -X|grep '^Machine.*Pentium' >/dev/null) \ && UNAME_MACHINE=i586 (/bin/uname -X|grep '^Machine.*Pent *II' >/dev/null) \ && UNAME_MACHINE=i686 (/bin/uname -X|grep '^Machine.*Pentium Pro' >/dev/null) \ && UNAME_MACHINE=i686 echo ${UNAME_MACHINE}-pc-sco$UNAME_REL else echo ${UNAME_MACHINE}-pc-sysv32 fi exit ;; pc:*:*:*) # Left here for compatibility: # uname -m prints for DJGPP always 'pc', but it prints nothing about # the processor, so we play safe by assuming i386. echo i386-pc-msdosdjgpp exit ;; Intel:Mach:3*:*) echo i386-pc-mach3 exit ;; paragon:*:*:*) echo i860-intel-osf1 exit ;; i860:*:4.*:*) # i860-SVR4 if grep Stardent /usr/include/sys/uadmin.h >/dev/null 2>&1 ; then echo i860-stardent-sysv${UNAME_RELEASE} # Stardent Vistra i860-SVR4 else # Add other i860-SVR4 vendors below as they are discovered. echo i860-unknown-sysv${UNAME_RELEASE} # Unknown i860-SVR4 fi exit ;; mini*:CTIX:SYS*5:*) # "miniframe" echo m68010-convergent-sysv exit ;; mc68k:UNIX:SYSTEM5:3.51m) echo m68k-convergent-sysv exit ;; M680?0:D-NIX:5.3:*) echo m68k-diab-dnix exit ;; M68*:*:R3V[5678]*:*) test -r /sysV68 && { echo 'm68k-motorola-sysv'; exit; } ;; 3[345]??:*:4.0:3.0 | 3[34]??A:*:4.0:3.0 | 3[34]??,*:*:4.0:3.0 | 3[34]??/*:*:4.0:3.0 | 4400:*:4.0:3.0 | 4850:*:4.0:3.0 | SKA40:*:4.0:3.0 | SDS2:*:4.0:3.0 | SHG2:*:4.0:3.0 | S7501*:*:4.0:3.0) OS_REL='' test -r /etc/.relid \ && OS_REL=.`sed -n 's/[^ ]* [^ ]* \([0-9][0-9]\).*/\1/p' < /etc/.relid` /bin/uname -p 2>/dev/null | grep 86 >/dev/null \ && { echo i486-ncr-sysv4.3${OS_REL}; exit; } /bin/uname -p 2>/dev/null | /bin/grep entium >/dev/null \ && { echo i586-ncr-sysv4.3${OS_REL}; exit; } ;; 3[34]??:*:4.0:* | 3[34]??,*:*:4.0:*) /bin/uname -p 2>/dev/null | grep 86 >/dev/null \ && { echo i486-ncr-sysv4; exit; } ;; m68*:LynxOS:2.*:* | m68*:LynxOS:3.0*:*) echo m68k-unknown-lynxos${UNAME_RELEASE} exit ;; mc68030:UNIX_System_V:4.*:*) echo m68k-atari-sysv4 exit ;; TSUNAMI:LynxOS:2.*:*) echo sparc-unknown-lynxos${UNAME_RELEASE} exit ;; rs6000:LynxOS:2.*:*) echo rs6000-unknown-lynxos${UNAME_RELEASE} exit ;; PowerPC:LynxOS:2.*:* | PowerPC:LynxOS:3.[01]*:* | PowerPC:LynxOS:4.0*:*) echo powerpc-unknown-lynxos${UNAME_RELEASE} exit ;; SM[BE]S:UNIX_SV:*:*) echo mips-dde-sysv${UNAME_RELEASE} exit ;; RM*:ReliantUNIX-*:*:*) echo mips-sni-sysv4 exit ;; RM*:SINIX-*:*:*) echo mips-sni-sysv4 exit ;; *:SINIX-*:*:*) if uname -p 2>/dev/null >/dev/null ; then UNAME_MACHINE=`(uname -p) 2>/dev/null` echo ${UNAME_MACHINE}-sni-sysv4 else echo ns32k-sni-sysv fi exit ;; PENTIUM:*:4.0*:*) # Unisys `ClearPath HMP IX 4000' SVR4/MP effort # says echo i586-unisys-sysv4 exit ;; *:UNIX_System_V:4*:FTX*) # From Gerald Hewes . # How about differentiating between stratus architectures? -djm echo hppa1.1-stratus-sysv4 exit ;; *:*:*:FTX*) # From seanf@swdc.stratus.com. echo i860-stratus-sysv4 exit ;; i*86:VOS:*:*) # From Paul.Green@stratus.com. echo ${UNAME_MACHINE}-stratus-vos exit ;; *:VOS:*:*) # From Paul.Green@stratus.com. echo hppa1.1-stratus-vos exit ;; mc68*:A/UX:*:*) echo m68k-apple-aux${UNAME_RELEASE} exit ;; news*:NEWS-OS:6*:*) echo mips-sony-newsos6 exit ;; R[34]000:*System_V*:*:* | R4000:UNIX_SYSV:*:* | R*000:UNIX_SV:*:*) if [ -d /usr/nec ]; then echo mips-nec-sysv${UNAME_RELEASE} else echo mips-unknown-sysv${UNAME_RELEASE} fi exit ;; BeBox:BeOS:*:*) # BeOS running on hardware made by Be, PPC only. echo powerpc-be-beos exit ;; BeMac:BeOS:*:*) # BeOS running on Mac or Mac clone, PPC only. echo powerpc-apple-beos exit ;; BePC:BeOS:*:*) # BeOS running on Intel PC compatible. echo i586-pc-beos exit ;; SX-4:SUPER-UX:*:*) echo sx4-nec-superux${UNAME_RELEASE} exit ;; SX-5:SUPER-UX:*:*) echo sx5-nec-superux${UNAME_RELEASE} exit ;; SX-6:SUPER-UX:*:*) echo sx6-nec-superux${UNAME_RELEASE} exit ;; Power*:Rhapsody:*:*) echo powerpc-apple-rhapsody${UNAME_RELEASE} exit ;; *:Rhapsody:*:*) echo ${UNAME_MACHINE}-apple-rhapsody${UNAME_RELEASE} exit ;; *:Darwin:*:*) UNAME_PROCESSOR=`uname -p` || UNAME_PROCESSOR=unknown case $UNAME_PROCESSOR in unknown) UNAME_PROCESSOR=powerpc ;; esac echo ${UNAME_PROCESSOR}-apple-darwin${UNAME_RELEASE} exit ;; *:procnto*:*:* | *:QNX:[0123456789]*:*) UNAME_PROCESSOR=`uname -p` if test "$UNAME_PROCESSOR" = "x86"; then UNAME_PROCESSOR=i386 UNAME_MACHINE=pc fi echo ${UNAME_PROCESSOR}-${UNAME_MACHINE}-nto-qnx${UNAME_RELEASE} exit ;; *:QNX:*:4*) echo i386-pc-qnx exit ;; NSE-?:NONSTOP_KERNEL:*:*) echo nse-tandem-nsk${UNAME_RELEASE} exit ;; NSR-?:NONSTOP_KERNEL:*:*) echo nsr-tandem-nsk${UNAME_RELEASE} exit ;; *:NonStop-UX:*:*) echo mips-compaq-nonstopux exit ;; BS2000:POSIX*:*:*) echo bs2000-siemens-sysv exit ;; DS/*:UNIX_System_V:*:*) echo ${UNAME_MACHINE}-${UNAME_SYSTEM}-${UNAME_RELEASE} exit ;; *:Plan9:*:*) # "uname -m" is not consistent, so use $cputype instead. 386 # is converted to i386 for consistency with other x86 # operating systems. if test "$cputype" = "386"; then UNAME_MACHINE=i386 else UNAME_MACHINE="$cputype" fi echo ${UNAME_MACHINE}-unknown-plan9 exit ;; *:TOPS-10:*:*) echo pdp10-unknown-tops10 exit ;; *:TENEX:*:*) echo pdp10-unknown-tenex exit ;; KS10:TOPS-20:*:* | KL10:TOPS-20:*:* | TYPE4:TOPS-20:*:*) echo pdp10-dec-tops20 exit ;; XKL-1:TOPS-20:*:* | TYPE5:TOPS-20:*:*) echo pdp10-xkl-tops20 exit ;; *:TOPS-20:*:*) echo pdp10-unknown-tops20 exit ;; *:ITS:*:*) echo pdp10-unknown-its exit ;; SEI:*:*:SEIUX) echo mips-sei-seiux${UNAME_RELEASE} exit ;; *:DragonFly:*:*) echo ${UNAME_MACHINE}-unknown-dragonfly`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` exit ;; *:*VMS:*:*) UNAME_MACHINE=`(uname -p) 2>/dev/null` case "${UNAME_MACHINE}" in A*) echo alpha-dec-vms ; exit ;; I*) echo ia64-dec-vms ; exit ;; V*) echo vax-dec-vms ; exit ;; esac ;; *:XENIX:*:SysV) echo i386-pc-xenix exit ;; i*86:skyos:*:*) echo ${UNAME_MACHINE}-pc-skyos`echo ${UNAME_RELEASE}` | sed -e 's/ .*$//' exit ;; i*86:rdos:*:*) echo ${UNAME_MACHINE}-pc-rdos exit ;; esac #echo '(No uname command or uname output not recognized.)' 1>&2 #echo "${UNAME_MACHINE}:${UNAME_SYSTEM}:${UNAME_RELEASE}:${UNAME_VERSION}" 1>&2 eval $set_cc_for_build cat >$dummy.c < # include #endif main () { #if defined (sony) #if defined (MIPSEB) /* BFD wants "bsd" instead of "newsos". Perhaps BFD should be changed, I don't know.... */ printf ("mips-sony-bsd\n"); exit (0); #else #include printf ("m68k-sony-newsos%s\n", #ifdef NEWSOS4 "4" #else "" #endif ); exit (0); #endif #endif #if defined (__arm) && defined (__acorn) && defined (__unix) printf ("arm-acorn-riscix\n"); exit (0); #endif #if defined (hp300) && !defined (hpux) printf ("m68k-hp-bsd\n"); exit (0); #endif #if defined (NeXT) #if !defined (__ARCHITECTURE__) #define __ARCHITECTURE__ "m68k" #endif int version; version=`(hostinfo | sed -n 's/.*NeXT Mach \([0-9]*\).*/\1/p') 2>/dev/null`; if (version < 4) printf ("%s-next-nextstep%d\n", __ARCHITECTURE__, version); else printf ("%s-next-openstep%d\n", __ARCHITECTURE__, version); exit (0); #endif #if defined (MULTIMAX) || defined (n16) #if defined (UMAXV) printf ("ns32k-encore-sysv\n"); exit (0); #else #if defined (CMU) printf ("ns32k-encore-mach\n"); exit (0); #else printf ("ns32k-encore-bsd\n"); exit (0); #endif #endif #endif #if defined (__386BSD__) printf ("i386-pc-bsd\n"); exit (0); #endif #if defined (sequent) #if defined (i386) printf ("i386-sequent-dynix\n"); exit (0); #endif #if defined (ns32000) printf ("ns32k-sequent-dynix\n"); exit (0); #endif #endif #if defined (_SEQUENT_) struct utsname un; uname(&un); if (strncmp(un.version, "V2", 2) == 0) { printf ("i386-sequent-ptx2\n"); exit (0); } if (strncmp(un.version, "V1", 2) == 0) { /* XXX is V1 correct? */ printf ("i386-sequent-ptx1\n"); exit (0); } printf ("i386-sequent-ptx\n"); exit (0); #endif #if defined (vax) # if !defined (ultrix) # include # if defined (BSD) # if BSD == 43 printf ("vax-dec-bsd4.3\n"); exit (0); # else # if BSD == 199006 printf ("vax-dec-bsd4.3reno\n"); exit (0); # else printf ("vax-dec-bsd\n"); exit (0); # endif # endif # else printf ("vax-dec-bsd\n"); exit (0); # endif # else printf ("vax-dec-ultrix\n"); exit (0); # endif #endif #if defined (alliant) && defined (i860) printf ("i860-alliant-bsd\n"); exit (0); #endif exit (1); } EOF $CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null && SYSTEM_NAME=`$dummy` && { echo "$SYSTEM_NAME"; exit; } # Apollos put the system type in the environment. test -d /usr/apollo && { echo ${ISP}-apollo-${SYSTYPE}; exit; } # Convex versions that predate uname can use getsysinfo(1) if [ -x /usr/convex/getsysinfo ] then case `getsysinfo -f cpu_type` in c1*) echo c1-convex-bsd exit ;; c2*) if getsysinfo -f scalar_acc then echo c32-convex-bsd else echo c2-convex-bsd fi exit ;; c34*) echo c34-convex-bsd exit ;; c38*) echo c38-convex-bsd exit ;; c4*) echo c4-convex-bsd exit ;; esac fi cat >&2 < in order to provide the needed information to handle your system. config.guess timestamp = $timestamp uname -m = `(uname -m) 2>/dev/null || echo unknown` uname -r = `(uname -r) 2>/dev/null || echo unknown` uname -s = `(uname -s) 2>/dev/null || echo unknown` uname -v = `(uname -v) 2>/dev/null || echo unknown` /usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null` /bin/uname -X = `(/bin/uname -X) 2>/dev/null` hostinfo = `(hostinfo) 2>/dev/null` /bin/universe = `(/bin/universe) 2>/dev/null` /usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null` /bin/arch = `(/bin/arch) 2>/dev/null` /usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null` /usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null` UNAME_MACHINE = ${UNAME_MACHINE} UNAME_RELEASE = ${UNAME_RELEASE} UNAME_SYSTEM = ${UNAME_SYSTEM} UNAME_VERSION = ${UNAME_VERSION} EOF exit 1 # Local variables: # eval: (add-hook 'write-file-hooks 'time-stamp) # time-stamp-start: "timestamp='" # time-stamp-format: "%:y-%02m-%02d" # time-stamp-end: "'" # End: minpack-19961126/Makefile.am0000644000175000017500000000237511616327304016350 0ustar sylvestresylvestre# Don't require all the GNU mandated files # Remove comment from no-dependencies for distributions compatable with # traditional 'make' AUTOMAKE_OPTIONS = 1.2 foreign # no-dependencies lib_LTLIBRARIES = libminpack.la VERSION_CURRENT=@VERSION_CURRENT@ VERSION_REVISION=@VERSION_REVISION@ VERSION_AGE=@VERSION_AGE@ libminpack_la_LDFLAGS = -version-info $(VERSION_CURRENT):$(VERSION_REVISION):$(VERSION_AGE) -D_REENTRANT,Wl,-z,defs # Library sources libminpack_la_SOURCES = chkder.f dogleg.f dpmpar.f enorm.f fdjac1.f \ fdjac2.f hybrd.f hybrd1.f hybrj.f hybrj1.f lmder.f lmder1.f lmdif.f \ lmdif1.f lmpar.f lmstr.f lmstr1.f qform.f qrfac.f qrsolv.f r1mpyq.f \ r1updt.f rwupdt.f # Source files not used for Unix library but which are distributed #EXTRA_libminpack_la_SOURCES = mac.c nt.c vms.c # Headers which are installed include_HEADERS = minpack.h # Headers which are not installed but which are distributed #noinst_HEADERS = Colorlist.h animate.h display.h formats.h logo.h mac.h \ # nt.h pict.h version.h vms.h # Additional files to distribute #EXTRA_DIST = Imakefile Make.com # Ensure that configuration header is not distributed #dist-hook: # $(RM) $(distdir)/config.h INCLUDES = #$(X_CFLAGS) # Since we are building a library, no need for LIBS #LIBS = minpack-19961126/qform.f0000644000175000017500000000467603226632013015607 0ustar sylvestresylvestre subroutine qform(m,n,q,ldq,wa) integer m,n,ldq double precision q(ldq,m),wa(m) c ********** c c subroutine qform c c this subroutine proceeds from the computed qr factorization of c an m by n matrix a to accumulate the m by m orthogonal matrix c q from its factored form. c c the subroutine statement is c c subroutine qform(m,n,q,ldq,wa) c c where c c m is a positive integer input variable set to the number c of rows of a and the order of q. c c n is a positive integer input variable set to the number c of columns of a. c c q is an m by m array. on input the full lower trapezoid in c the first min(m,n) columns of q contains the factored form. c on output q has been accumulated into a square matrix. c c ldq is a positive integer input variable not less than m c which specifies the leading dimension of the array q. c c wa is a work array of length m. c c subprograms called c c fortran-supplied ... min0 c c argonne national laboratory. minpack project. march 1980. c burton s. garbow, kenneth e. hillstrom, jorge j. more c c ********** integer i,j,jm1,k,l,minmn,np1 double precision one,sum,temp,zero data one,zero /1.0d0,0.0d0/ c c zero out upper triangle of q in the first min(m,n) columns. c minmn = min0(m,n) if (minmn .lt. 2) go to 30 do 20 j = 2, minmn jm1 = j - 1 do 10 i = 1, jm1 q(i,j) = zero 10 continue 20 continue 30 continue c c initialize remaining columns to those of the identity matrix. c np1 = n + 1 if (m .lt. np1) go to 60 do 50 j = np1, m do 40 i = 1, m q(i,j) = zero 40 continue q(j,j) = one 50 continue 60 continue c c accumulate q from its factored form. c do 120 l = 1, minmn k = minmn - l + 1 do 70 i = k, m wa(i) = q(i,k) q(i,k) = zero 70 continue q(k,k) = one if (wa(k) .eq. zero) go to 110 do 100 j = k, m sum = zero do 80 i = k, m sum = sum + q(i,j)*wa(i) 80 continue temp = sum/wa(k) do 90 i = k, m q(i,j) = q(i,j) - temp*wa(i) 90 continue 100 continue 110 continue 120 continue return c c last card of subroutine qform. c end