*DECK SNSQ SUBROUTINE SNSQ (FCN, JAC, IOPT, N, X, FVEC, FJAC, LDFJAC, XTOL, + MAXFEV, ML, MU, EPSFCN, DIAG, MODE, FACTOR, NPRINT, INFO, NFEV, + NJEV, R, LR, QTF, WA1, WA2, WA3, WA4) C***BEGIN PROLOGUE SNSQ C***PURPOSE Find a zero of a system of a N nonlinear functions in N C variables by a modification of the Powell hybrid method. C***LIBRARY SLATEC C***CATEGORY F2A C***TYPE SINGLE PRECISION (SNSQ-S, DNSQ-D) C***KEYWORDS NONLINEAR SQUARE SYSTEM, POWELL HYBRID METHOD, ZEROS C***AUTHOR Hiebert, K. L., (SNLA) C***DESCRIPTION C C 1. Purpose. C C The purpose of SNSQ is to find a zero of a system of N non- C linear functions in N variables by a modification of the Powell C hybrid method. The user must provide a subroutine which calcu- C lates the functions. The user has the option of either to C provide a subroutine which calculates the Jacobian or to let the C code calculate it by a forward-difference approximation. C This code is the combination of the MINPACK codes (Argonne) C HYBRD and HYBRDJ. C C C 2. Subroutine and Type Statements. C C SUBROUTINE SNSQ(FCN,JAC,IOPT,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV, C * ML,MU,EPSFCN,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV, C * NJEV,R,LR,QTF,WA1,WA2,WA3,WA4) C INTEGER IOPT,N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,NJEV,LR C REAL XTOL,EPSFCN,FACTOR C REAL X(N),FVEC(N),DIAG(N),FJAC(LDFJAC,N),R(LR),QTF(N), C * WA1(N),WA2(N),WA3(N),WA4(N) C EXTERNAL FCN,JAC C C C 3. Parameters. C C Parameters designated as input parameters must be specified on C entry to SNSQ and are not changed on exit, while parameters C designated as output parameters need not be specified on entry C and are set to appropriate values on exit from SNSQ. C C FCN is the name of the user-supplied subroutine which calculates C the functions. FCN must be declared in an EXTERNAL statement C in the user calling 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 the C user wants to terminate execution of SNSQ. In this case, set C IFLAG to a negative integer. C C JAC is the name of the user-supplied subroutine which calculates C the Jacobian. If IOPT=1, then JAC must be declared in an C EXTERNAL statement in the user calling program, and should be C written as follows. C C SUBROUTINE JAC(N,X,FVEC,FJAC,LDFJAC,IFLAG) C INTEGER N,LDFJAC,IFLAG C REAL X(N),FVEC(N),FJAC(LDFJAC,N) C ---------- C Calculate the Jacobian at X and return this C matrix in FJAC. FVEC contains the function C values at X and should not be altered. C ---------- C RETURN C END C C The value of IFLAG should not be changed by JAC unless the C user wants to terminate execution of SNSQ. In this case, set C IFLAG to a negative integer. C C If IOPT=2, JAC can be ignored (treat it as a dummy argument). C C IOPT is an input variable which specifies how the Jacobian will C be calculated. If IOPT=1, then the user must supply the C Jacobian through the subroutine JAC. If IOPT=2, then the C code will approximate the Jacobian by forward-differencing. C C N is a positive integer input variable set to the number of C functions and variables. C C X is an array of length N. On input, X must contain an initial C estimate of the solution vector. On output, X contains the C final estimate of the solution vector. C C FVEC is an output array of length N which contains the functions C evaluated at the output X. C C FJAC is an output N by N array which contains the orthogonal C matrix Q produced by the QR factorization of the final approx- C imate 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 non-negative input variable. Termination occurs when C the relative error between two consecutive iterates is at most C XTOL. Therefore, XTOL measures the relative error desired in C the approximate solution. Section 4 contains more details C about XTOL. C C MAXFEV is a positive integer input variable. Termination occurs C when the number of calls to FCN is at least MAXFEV by the end C of an iteration. C C ML is a non-negative integer input variable which specifies the C number of subdiagonals within the band of the Jacobian matrix. C If the Jacobian is not banded or IOPT=1, set ML to at C least N - 1. C C MU is a non-negative integer input variable which specifies the C number of superdiagonals within the band of the Jacobian C matrix. If the Jacobian is not banded or IOPT=1, set MU to at C least N - 1. C C EPSFCN is an input variable used in determining a suitable step C for the forward-difference approximation. This approximation C assumes that the relative errors in the functions are of the C order of EPSFCN. If EPSFCN is less than the machine preci- C sion, it is assumed that the relative errors in the functions C are of the order of the machine precision. If IOPT=1, then C EPSFCN can be ignored (treat it as a dummy argument). C C DIAG is an array of length N. If MODE = 1 (see below), DIAG is C internally set. If MODE = 2, DIAG must contain positive C entries that serve as implicit (multiplicative) scale factors C for the variables. C C MODE is an integer input variable. If MODE = 1, the variables C will be scaled internally. If MODE = 2, the scaling is speci- C fied by the input DIAG. Other values of MODE are equivalent C to MODE = 1. C C FACTOR is a positive input variable used in determining the ini- C tial step bound. This bound is set to the product of FACTOR C and the Euclidean norm of DIAG*X if nonzero, or else to FACTOR C itself. In most cases FACTOR should lie in the interval C (.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, FCN is C called with IFLAG = 0 at the beginning of the first iteration C and every NPRINT iteration thereafter and immediately prior C to return, with X and FVEC available for printing. Appropriate C print statements must be added to FCN(see example). If NPRINT C is not positive, no special calls of FCN with IFLAG = 0 are C made. C C INFO is an integer output variable. If the user has terminated C execution, INFO is set to the (negative) value of IFLAG. See C description of FCN and JAC. Otherwise, INFO is set as follows. C C INFO = 0 improper input parameters. C C INFO = 1 relative error between two consecutive iterates is C 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 the C approximate solution X is possible. C C INFO = 4 iteration is not making good progress, as measured C by the improvement from the last five Jacobian eval- C uations. C C INFO = 5 iteration is not making good progress, as measured C by the improvement from the last ten iterations. C C Sections 4 and 5 contain more details about INFO. C C NFEV is an integer output variable set to the number of calls to C FCN. C C NJEV is an integer output variable set to the number of calls to C JAC. (If IOPT=2, then NJEV is set to zero.) C C R is an output array of length LR which contains the upper C triangular matrix produced by the QR factorization of the C 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 the vector C (Q TRANSPOSE)*FVEC. C C WA1, WA2, WA3, and WA4 are work arrays of length N. C C C 4. Successful Completion. C C The accuracy of SNSQ is controlled by the convergence parameter C XTOL. This parameter is used in a test which makes a comparison C between the approximation X and a solution XSOL. SNSQ termi- C nates when the test is satisfied. If the convergence parameter C is less than the machine precision (as defined by the function C R1MACH(4)), then SNSQ only attempts to satisfy the test C defined by the machine precision. Further progress is not C usually possible. C C The test assumes that the functions are reasonably well behaved, C and, if the Jacobian is supplied by the user, that the functions C and the Jacobian are coded consistently. If these conditions C are not satisfied, then SNSQ may incorrectly indicate conver- C gence. The coding of the Jacobian can be checked by the C subroutine CHKDER. If the Jacobian is coded correctly or IOPT=2, C then the validity of the answer can be checked, for example, by C rerunning SNSQ with a tighter tolerance. C C Convergence Test. If ENORM(Z) denotes the Euclidean norm of a C vector Z and D is the diagonal matrix whose entries are C defined by the array DIAG, then this test attempts to guaran- C tee that C C ENORM(D*(X-XSOL)) .LE. XTOL*ENORM(D*XSOL). C C If this condition is satisfied with XTOL = 10**(-K), then the C larger components of D*X have K significant decimal digits and C INFO is set to 1. There is a danger that the smaller compo- C nents of D*X may have large relative errors, but the fast rate C of convergence of SNSQ usually avoids this possibility. C Unless high precision solutions are required, the recommended C value for XTOL is the square root of the machine precision. C C C 5. Unsuccessful Completion. C C Unsuccessful termination of SNSQ can be due to improper input C parameters, arithmetic interrupts, an excessive number of func- C tion evaluations, or lack of good progress. C C Improper Input Parameters. INFO is set to 0 if IOPT .LT. 1, C or IOPT .GT. 2, or N .LE. 0, or LDFJAC .LT. N, or C XTOL .LT. 0.E0, or MAXFEV .LE. 0, or ML .LT. 0, or MU .LT. 0, C or FACTOR .LE. 0.E0, or LR .LT. (N*(N+1))/2. C C Arithmetic Interrupts. If these interrupts occur in the FCN C subroutine during an early stage of the computation, they may C be caused by an unacceptable choice of X by SNSQ. In this C case, it may be possible to remedy the situation by rerunning C SNSQ with a smaller value of FACTOR. C C Excessive Number of Function Evaluations. A reasonable value C for MAXFEV is 100*(N+1) for IOPT=1 and 200*(N+1) for IOPT=2. C If the number of calls to FCN reaches MAXFEV, then this C indicates that the routine is converging very slowly as C measured by the progress of FVEC, and INFO is set to 2. This C situation should be unusual because, as indicated below, lack C of good progress is usually diagnosed earlier by SNSQ, C causing termination with INFO = 4 or INFO = 5. C C Lack of Good Progress. SNSQ searches for a zero of the system C by minimizing the sum of the squares of the functions. In so C doing, it can become trapped in a region where the minimum C does not correspond to a zero of the system and, in this situ- C ation, the iteration eventually fails to make good progress. C In particular, this will happen if the system does not have a C zero. If the system has a zero, rerunning SNSQ from a dif- C ferent starting point may be helpful. C C C 6. Characteristics of the Algorithm. C C SNSQ is a modification of the Powell hybrid method. Two of its C main characteristics involve the choice of the correction as a C convex combination of the Newton and scaled gradient directions, C and the updating of the Jacobian by the rank-1 method of Broy- C den. The choice of the correction guarantees (under reasonable C conditions) global convergence for starting points far from the C solution and a fast rate of convergence. The Jacobian is C calculated at the starting point by either the user-supplied C subroutine or a forward-difference approximation, but it is not C recalculated until the rank-1 method fails to produce satis- C factory progress. C C Timing. The time required by SNSQ to solve a given problem C depends on N, the behavior of the functions, the accuracy C requested, and the starting point. The number of arithmetic C operations needed by SNSQ is about 11.5*(N**2) to process C each evaluation of the functions (call to FCN) and 1.3*(N**3) C to process each evaluation of the Jacobian (call to JAC, C if IOPT = 1). Unless FCN and JAC can be evaluated quickly, C the timing of SNSQ will be strongly influenced by the time C spent in FCN and JAC. C C Storage. SNSQ requires (3*N**2 + 17*N)/2 single precision C storage locations, in addition to the storage required by the C program. There are no internally declared storage arrays. C C C 7. Example. C C The problem is to determine the values of X(1), X(2), ..., X(9), C which solve the system of tridiagonal equations C C (3-2*X(1))*X(1) -2*X(2) = -1 C -X(I-1) + (3-2*X(I))*X(I) -2*X(I+1) = -1, I=2-8 C -X(8) + (3-2*X(9))*X(9) = -1 C C ********** C C PROGRAM TEST C C C C Driver for SNSQ example. C C C INTEGER J,IOPT,N,MAXFEV,ML,MU,MODE,NPRINT,INFO,NFEV,LDFJAC,LR, C * NWRITE C REAL XTOL,EPSFCN,FACTOR,FNORM C REAL X(9),FVEC(9),DIAG(9),FJAC(9,9),R(45),QTF(9), C * WA1(9),WA2(9),WA3(9),WA4(9) C REAL ENORM,R1MACH C EXTERNAL FCN C DATA NWRITE /6/ C C C IOPT = 2 C N = 9 C C C C The following starting values provide a rough solution. C C C DO 10 J = 1, 9 C X(J) = -1.E0 C 10 CONTINUE C C C LDFJAC = 9 C LR = 45 C C C C Set XTOL to the square root of the machine precision. C C Unless high precision solutions are required, C C this is the recommended setting. C C C XTOL = SQRT(R1MACH(4)) C C C MAXFEV = 2000 C ML = 1 C MU = 1 C EPSFCN = 0.E0 C MODE = 2 C DO 20 J = 1, 9 C DIAG(J) = 1.E0 C 20 CONTINUE C FACTOR = 1.E2 C NPRINT = 0 C C C CALL SNSQ(FCN,JAC,IOPT,N,X,FVEC,FJAC,LDFJAC,XTOL,MAXFEV,ML,MU, C * EPSFCN,DIAG,MODE,FACTOR,NPRINT,INFO,NFEV,NJEV, C * R,LR,QTF,WA1,WA2,WA3,WA4) C FNORM = ENORM(N,FVEC) C WRITE (NWRITE,1000) FNORM,NFEV,INFO,(X(J),J=1,N) C STOP C 1000 FORMAT (5X,' FINAL L2 NORM OF THE RESIDUALS',E15.7 // C * 5X,' NUMBER OF FUNCTION EVALUATIONS',I10 // C * 5X,' EXIT PARAMETER',16X,I10 // C * 5X,' FINAL APPROXIMATE SOLUTION' // (5X,3E15.7)) C END C SUBROUTINE FCN(N,X,FVEC,IFLAG) C INTEGER N,IFLAG C REAL X(N),FVEC(N) C INTEGER K C REAL ONE,TEMP,TEMP1,TEMP2,THREE,TWO,ZERO C DATA ZERO,ONE,TWO,THREE /0.E0,1.E0,2.E0,3.E0/ C C C IF (IFLAG .NE. 0) GO TO 5 C C C C Insert print statements here when NPRINT is positive. C C C RETURN C 5 CONTINUE C DO 10 K = 1, N C TEMP = (THREE - TWO*X(K))*X(K) C TEMP1 = ZERO C IF (K .NE. 1) TEMP1 = X(K-1) C TEMP2 = ZERO C IF (K .NE. N) TEMP2 = X(K+1) C FVEC(K) = TEMP - TEMP1 - TWO*TEMP2 + ONE C 10 CONTINUE C RETURN C END C C Results obtained with different compilers or machines C may be slightly different. C C FINAL L2 NORM OF THE RESIDUALS 0.1192636E-07 C C NUMBER OF FUNCTION EVALUATIONS 14 C C EXIT PARAMETER 1 C C FINAL APPROXIMATE SOLUTION C C -0.5706545E+00 -0.6816283E+00 -0.7017325E+00 C -0.7042129E+00 -0.7013690E+00 -0.6918656E+00 C -0.6657920E+00 -0.5960342E+00 -0.4164121E+00 C C***REFERENCES M. J. D. Powell, A hybrid method for nonlinear equa- C tions. In Numerical Methods for Nonlinear Algebraic C Equations, P. Rabinowitz, Editor. Gordon and Breach, C 1988. C***ROUTINES CALLED DOGLEG, ENORM, FDJAC1, QFORM, QRFAC, R1MACH, C R1MPYQ, R1UPDT, XERMSG C***REVISION HISTORY (YYMMDD) C 800301 DATE WRITTEN C 890531 Changed all specific intrinsics to generic. (WRB) C 890831 Modified array declarations. (WRB) C 890831 REVISION DATE from Version 3.2 C 891214 Prologue converted to Version 4.0 format. (BAB) C 900315 CALLs to XERROR changed to CALLs to XERMSG. (THJ) C 920501 Reformatted the REFERENCES section. (WRB) C***END PROLOGUE SNSQ