SLATEC Routines --- SNLS1E ---
*DECK SNLS1E
SUBROUTINE SNLS1E (FCN, IOPT, M, N, X, FVEC, TOL, NPRINT, INFO,
+ IW, WA, LWA)
C***BEGIN PROLOGUE SNLS1E
C***PURPOSE An easy-to-use code which minimizes the sum of the squares
C of M nonlinear functions in N variables by a modification
C of the Levenberg-Marquardt algorithm.
C***LIBRARY SLATEC
C***CATEGORY K1B1A1, K1B1A2
C***TYPE SINGLE PRECISION (SNLS1E-S, DNLS1E-D)
C***KEYWORDS EASY-TO-USE, LEVENBERG-MARQUARDT, NONLINEAR DATA FITTING,
C NONLINEAR LEAST SQUARES
C***AUTHOR Hiebert, K. L., (SNLA)
C***DESCRIPTION
C
C 1. Purpose.
C
C The purpose of SNLS1E is to minimize the sum of the squares of M
C 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 SNLS1. The user must provide a
C subroutine which calculates the functions. The user has the
C option of how the Jacobian will be supplied. The user can
C supply the full Jacobian, or the rows of the Jacobian (to avoid
C storing the full Jacobian), or let the code approximate the
C Jacobian by forward-differencing. This code is the combination
C of the MINPACK codes (Argonne) LMDER1, LMDIF1, and LMSTR1.
C
C
C 2. Subroutine and Type Statements.
C
C SUBROUTINE SNLS1E(FCN,IOPT,M,N,X,FVEC,TOL,NPRINT,
C * INFO,IW,WA,LWA)
C INTEGER IOPT,M,N,NPRINT,INFO,LWA
C INTEGER IW(N)
C REAL TOL
C REAL X(N),FVEC(M),WA(LWA)
C EXTERNAL FCN
C
C
C 3. Parameters.
C
C Parameters designated as input parameters must be specified on
C entry to SNLS1E 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 SNLS1E.
C
C FCN is the name of the user-supplied subroutine which calculates
C the functions. If the user wants to supply the Jacobian
C (IOPT=2 or 3), then FCN must be written to calculate the
C Jacobian, as well as the functions. See the explanation
C of the IOPT argument below.
C If the user wants the iterates printed (NPRINT positive), then
C FCN must do the printing. See the explanation of NPRINT
C below. FCN must be declared in an EXTERNAL statement in the
C calling program and should be written as follows.
C
C
C SUBROUTINE FCN(IFLAG,M,N,X,FVEC,FJAC,LDFJAC)
C INTEGER IFLAG,LDFJAC,M,N
C REAL X(N),FVEC(M)
C ----------
C FJAC and LDFJAC may be ignored , if IOPT=1.
C REAL FJAC(LDFJAC,N) , if IOPT=2.
C REAL FJAC(N) , if IOPT=3.
C ----------
C If IFLAG=0, the values in X and FVEC are available
C for printing. See the explanation of NPRINT below.
C IFLAG will never be zero unless NPRINT is positive.
C The values of X and FVEC must not be changed.
C RETURN
C ----------
C If IFLAG=1, calculate the functions at X and return
C this vector in FVEC.
C RETURN
C ----------
C If IFLAG=2, calculate the full Jacobian at X and return
C this matrix in FJAC. Note that IFLAG will never be 2 unless
C IOPT=2. FVEC contains the function values at X and must
C not be altered. FJAC(I,J) must be set to the derivative
C of FVEC(I) with respect to X(J).
C RETURN
C ----------
C If IFLAG=3, calculate the LDFJAC-th row of the Jacobian
C and return this vector in FJAC. Note that IFLAG will
C never be 3 unless IOPT=3. FVEC contains the function
C values at X and must not be altered. FJAC(J) must be
C set to the derivative of FVEC(LDFJAC) with respect to X(J).
C RETURN
C ----------
C END
C
C
C The value of IFLAG should not be changed by FCN unless the
C user wants to terminate execution of SNLS1E. In this case,
C set IFLAG to a negative integer.
C
C
C IOPT is an input variable which specifies how the Jacobian will
C be calculated. If IOPT=2 or 3, then the user must supply the
C Jacobian, as well as the function values, through the
C subroutine FCN. If IOPT=2, the user supplies the full
C Jacobian with one call to FCN. If IOPT=3, the user supplies
C one row of the Jacobian with each call. (In this manner,
C storage can be saved because the full Jacobian is not stored.)
C If IOPT=1, the code will approximate the Jacobian by forward
C differencing.
C
C M is a positive integer input variable set to the number of
C functions.
C
C N is a positive integer input variable set to the number of
C variables. N must not exceed M.
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 M which contains the functions
C evaluated at the output X.
C
C TOL is a non-negative input variable. Termination occurs when
C the algorithm estimates either that the relative error in the
C sum of squares is at most TOL or that the relative error
C between X and the solution is at most TOL. Section 4 contains
C more details about TOL.
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 iterations 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) and
C FVEC should not be altered. If NPRINT is not positive, no
C special calls of FCN with IFLAG = 0 are 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 algorithm estimates that the relative error in the
C sum of squares is at most TOL.
C
C INFO = 2 algorithm estimates that the relative error between
C 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 Jacobian to
C machine precision.
C
C INFO = 5 number of calls to FCN has reached 100*(N+1)
C for IOPT=2 or 3 or 200*(N+1) for IOPT=1.
C
C INFO = 6 TOL is too small. No further reduction in the sum
C of squares is possible.
C
C INFO = 7 TOL is too small. No further improvement in the
C approximate solution X is possible.
C
C Sections 4 and 5 contain more details about INFO.
C
C IW 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 N*(M+5)+M for IOPT=1 and 2 or N*(N+5)+M for IOPT=3.
C
C
C 4. Successful Completion.
C
C The accuracy of SNLS1E is controlled by the convergence parame-
C ter TOL. This parameter is used in tests which make three types
C of comparisons between the approximation X and a solution XSOL.
C SNLS1E terminates when any of the tests is satisfied. If TOL is
C less than the machine precision (as defined by the function
C R1MACH(4)), then SNLS1E only attempts to satisfy the test
C defined by the machine precision. Further progress is not usu-
C ally possible. Unless high precision solutions are required,
C the recommended value for TOL is the square root of the machine
C precision.
C
C The tests assume 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 SNLS1E may incorrectly indicate conver-
C gence. If the Jacobian is coded correctly or IOPT=1,
C then the validity of the answer can be checked, for example, by
C rerunning SNLS1E with tighter tolerances.
C
C First Convergence Test. If ENORM(Z) denotes the Euclidean norm
C of a vector Z, then this test attempts to guarantee that
C
C ENORM(FVEC) .LE. (1+TOL)*ENORM(FVECS),
C
C where FVECS denotes the functions evaluated at XSOL. If this
C condition is satisfied with TOL = 10**(-K), then the final
C residual norm ENORM(FVEC) has K significant decimal digits and
C INFO is set to 1 (or to 3 if the second test is also satis-
C fied).
C
C Second Convergence Test. If D is a diagonal matrix (implicitly
C generated by SNLS1E) whose entries contain scale factors for
C the variables, then this test attempts to guarantee that
C
C ENORM(D*(X-XSOL)) .LE. TOL*ENORM(D*XSOL).
C
C If this condition is satisfied with TOL = 10**(-K), then the
C larger components of D*X have K significant decimal digits and
C INFO is set to 2 (or to 3 if the first test is also satis-
C fied). There is a danger that the smaller components of D*X
C may have large relative errors, but the choice of D is such
C that the accuracy of the components of X is usually related to
C their sensitivity.
C
C Third Convergence Test. This test is satisfied when FVEC is
C orthogonal to the columns of the Jacobian to machine preci-
C sion. There is no clear relationship between this test and
C the accuracy of SNLS1E, and furthermore, the test is equally
C well satisfied at other critical points, namely maximizers and
C saddle points. Therefore, termination caused by this test
C (INFO = 4) should be examined carefully.
C
C
C 5. Unsuccessful Completion.
C
C Unsuccessful termination of SNLS1E can be due to improper input
C parameters, arithmetic interrupts, or an excessive number of
C function evaluations.
C
C Improper Input Parameters. INFO is set to 0 if IOPT .LT. 1
C or IOPT .GT. 3, or N .LE. 0, or M .LT. N, or TOL .LT. 0.E0,
C or for IOPT=1 or 2 LWA .LT. N*(M+5)+M, or for IOPT=3
C LWA .LT. N*(N+5)+M.
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 SNLS1E. In this
C case, it may be possible to remedy the situation by not evalu-
C ating the functions here, but instead setting the components
C of FVEC to numbers that exceed those in the initial FVEC.
C
C Excessive Number of Function Evaluations. If the number of
C calls to FCN reaches 100*(N+1) for IOPT=2 or 3 or 200*(N+1)
C for IOPT=1, then this indicates that the routine is converging
C very slowly as measured by the progress of FVEC, and INFO is
C set to 5. In this case, it may be helpful to restart SNLS1E,
C thereby forcing it to disregard old (and possibly harmful)
C information.
C
C
C 6. Characteristics of the Algorithm.
C
C SNLS1E is a modification of the Levenberg-Marquardt algorithm.
C Two of its main characteristics involve the proper use of
C implicitly scaled variables and an optimal choice for the cor-
C rection. The use of implicitly scaled variables achieves scale
C invariance of SNLS1E and limits the size of the correction in
C any direction where the functions are changing rapidly. The
C optimal choice of the correction guarantees (under reasonable
C conditions) global convergence from starting points far from the
C solution and a fast rate of convergence for problems with small
C residuals.
C
C Timing. The time required by SNLS1E to solve a given problem
C depends on M and N, the behavior of the functions, the accu-
C racy requested, and the starting point. The number of arith-
C metic operations needed by SNLS1E is about N**3 to process
C each evaluation of the functions (call to FCN) and to process
C each evaluation of the Jacobian SNLS1E takes M*N**2 for IOPT=2
C (one call to JAC), M*N**2 for IOPT=1 (N calls to FCN) and
C 1.5*M*N**2 for IOPT=3 (M calls to FCN). Unless FCN
C can be evaluated quickly, the timing of SNLS1E will be
C strongly influenced by the time spent in FCN.
C
C Storage. SNLS1E requires (M*N + 2*M + 6*N) for IOPT=1 or 2 and
C (N**2 + 2*M + 6*N) for IOPT=3 single precision storage
C locations and N integer storage locations, in addition to
C the storage required by the program. There are no internally
C declared storage arrays.
C
C *Long Description:
C
C 7. Example.
C
C The problem is to determine the values of X(1), X(2), and X(3)
C which provide the best fit (in the least squares sense) of
C
C X(1) + U(I)/(V(I)*X(2) + W(I)*X(3)), I = 1, 15
C
C to the data
C
C Y = (0.14,0.18,0.22,0.25,0.29,0.32,0.35,0.39,
C 0.37,0.58,0.73,0.96,1.34,2.10,4.39),
C
C where U(I) = I, V(I) = 16 - I, and W(I) = MIN(U(I),V(I)). The
C I-th component of FVEC is thus defined by
C
C Y(I) - (X(1) + U(I)/(V(I)*X(2) + W(I)*X(3))).
C
C **********
C
C PROGRAM TEST
C C
C C Driver for SNLS1E example.
C C
C INTEGER I,IOPT,M,N,NPRINT,JNFO,LWA,NWRITE
C INTEGER IW(3)
C REAL TOL,FNORM
C REAL X(3),FVEC(15),WA(75)
C REAL ENORM,R1MACH
C EXTERNAL FCN
C DATA NWRITE /6/
C C
C IOPT = 1
C M = 15
C N = 3
C C
C C The following starting values provide a rough fit.
C C
C X(1) = 1.E0
C X(2) = 1.E0
C X(3) = 1.E0
C C
C LWA = 75
C NPRINT = 0
C C
C C Set TOL 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 TOL = SQRT(R1MACH(4))
C C
C CALL SNLS1E(FCN,IOPT,M,N,X,FVEC,TOL,NPRINT,
C * INFO,IW,WA,LWA)
C FNORM = ENORM(M,FVEC)
C WRITE (NWRITE,1000) FNORM,INFO,(X(J),J=1,N)
C STOP
C 1000 FORMAT (5X,' FINAL L2 NORM OF THE RESIDUALS',E15.7 //
C * 5X,' EXIT PARAMETER',16X,I10 //
C * 5X,' FINAL APPROXIMATE SOLUTION' // 5X,3E15.7)
C END
C SUBROUTINE FCN(IFLAG,M,N,X,FVEC,DUM,IDUM)
C C This is the form of the FCN routine if IOPT=1,
C C that is, if the user does not calculate the Jacobian.
C INTEGER M,N,IFLAG
C REAL X(N),FVEC(M)
C INTEGER I
C REAL TMP1,TMP2,TMP3,TMP4
C REAL Y(15)
C DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8),
C * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15)
C * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1,
C * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/
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 I = 1, M
C TMP1 = I
C TMP2 = 16 - I
C TMP3 = TMP1
C IF (I .GT. 8) TMP3 = TMP2
C FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3))
C 10 CONTINUE
C RETURN
C END
C
C
C Results obtained with different compilers or machines
C may be slightly different.
C
C FINAL L2 NORM OF THE RESIDUALS 0.9063596E-01
C
C EXIT PARAMETER 1
C
C FINAL APPROXIMATE SOLUTION
C
C 0.8241058E-01 0.1133037E+01 0.2343695E+01
C
C
C For IOPT=2, FCN would be modified as follows to also
C calculate the full Jacobian when IFLAG=2.
C
C SUBROUTINE FCN(IFLAG,M,N,X,FVEC,FJAC,LDFJAC)
C C
C C This is the form of the FCN routine if IOPT=2,
C C that is, if the user calculates the full Jacobian.
C C
C INTEGER LDFJAC,M,N,IFLAG
C REAL X(N),FVEC(M)
C REAL FJAC(LDFJAC,N)
C INTEGER I
C REAL TMP1,TMP2,TMP3,TMP4
C REAL Y(15)
C DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8),
C * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15)
C * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1,
C * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/
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 IF(IFLAG.NE.1) GO TO 20
C DO 10 I = 1, M
C TMP1 = I
C TMP2 = 16 - I
C TMP3 = TMP1
C IF (I .GT. 8) TMP3 = TMP2
C FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3))
C 10 CONTINUE
C RETURN
C C
C C Below, calculate the full Jacobian.
C C
C 20 CONTINUE
C C
C DO 30 I = 1, M
C TMP1 = I
C TMP2 = 16 - I
C TMP3 = TMP1
C IF (I .GT. 8) TMP3 = TMP2
C TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2
C FJAC(I,1) = -1.E0
C FJAC(I,2) = TMP1*TMP2/TMP4
C FJAC(I,3) = TMP1*TMP3/TMP4
C 30 CONTINUE
C RETURN
C END
C
C
C For IOPT = 3, FJAC would be dimensioned as FJAC(3,3),
C LDFJAC would be set to 3, and FCN would be written as
C follows to calculate a row of the Jacobian when IFLAG=3.
C
C SUBROUTINE FCN(IFLAG,M,N,X,FVEC,FJAC,LDFJAC)
C C This is the form of the FCN routine if IOPT=3,
C C that is, if the user calculates the Jacobian row by row.
C INTEGER M,N,IFLAG
C REAL X(N),FVEC(M)
C REAL FJAC(N)
C INTEGER I
C REAL TMP1,TMP2,TMP3,TMP4
C REAL Y(15)
C DATA Y(1),Y(2),Y(3),Y(4),Y(5),Y(6),Y(7),Y(8),
C * Y(9),Y(10),Y(11),Y(12),Y(13),Y(14),Y(15)
C * /1.4E-1,1.8E-1,2.2E-1,2.5E-1,2.9E-1,3.2E-1,3.5E-1,3.9E-1,
C * 3.7E-1,5.8E-1,7.3E-1,9.6E-1,1.34E0,2.1E0,4.39E0/
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 IF( IFLAG.NE.1) GO TO 20
C DO 10 I = 1, M
C TMP1 = I
C TMP2 = 16 - I
C TMP3 = TMP1
C IF (I .GT. 8) TMP3 = TMP2
C FVEC(I) = Y(I) - (X(1) + TMP1/(X(2)*TMP2 + X(3)*TMP3))
C 10 CONTINUE
C RETURN
C C
C C Below, calculate the LDFJAC-th row of the Jacobian.
C C
C 20 CONTINUE
C
C I = LDFJAC
C TMP1 = I
C TMP2 = 16 - I
C TMP3 = TMP1
C IF (I .GT. 8) TMP3 = TMP2
C TMP4 = (X(2)*TMP2 + X(3)*TMP3)**2
C FJAC(1) = -1.E0
C FJAC(2) = TMP1*TMP2/TMP4
C FJAC(3) = TMP1*TMP3/TMP4
C RETURN
C END
C
C***REFERENCES Jorge J. More, The Levenberg-Marquardt algorithm:
C implementation and theory. In Numerical Analysis
C Proceedings (Dundee, June 28 - July 1, 1977, G. A.
C Watson, Editor), Lecture Notes in Mathematics 630,
C Springer-Verlag, 1978.
C***ROUTINES CALLED SNLS1, XERMSG
C***REVISION HISTORY (YYMMDD)
C 800301 DATE WRITTEN
C 890206 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 SNLS1E