SUBROUTINE DNLS1 (FCN, IOPT, M, N, X, FVEC, FJAC, LDFJAC, FTOL, + XTOL, GTOL, MAXFEV, EPSFCN, DIAG, MODE, FACTOR, NPRINT, INFO, + NFEV, NJEV, IPVT, QTF, WA1, WA2, WA3, WA4) C***BEGIN PROLOGUE DNLS1 C***PURPOSE Minimize the sum of the squares of M nonlinear functions C in N variables by a modification of the Levenberg-Marquardt C algorithm. C***LIBRARY SLATEC C***CATEGORY K1B1A1, K1B1A2 C***TYPE DOUBLE PRECISION (SNLS1-S, DNLS1-D) C***KEYWORDS 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 DNLS1 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. The user must provide a subrou- C tine which calculates the functions. The user has the option C of how the Jacobian will be supplied. The user can supply the C full Jacobian, or the rows of the Jacobian (to avoid storing C the full Jacobian), or let the code approximate the Jacobian by C forward-differencing. This code is the combination of the C MINPACK codes (Argonne) LMDER, LMDIF, and LMSTR. C C C 2. Subroutine and Type Statements. C C SUBROUTINE DNLS1(FCN,IOPT,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL, C * GTOL,MAXFEV,EPSFCN,DIAG,MODE,FACTOR,NPRINT,INFO C * ,NFEV,NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C INTEGER IOPT,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV C INTEGER IPVT(N) C DOUBLE PRECISION FTOL,XTOL,GTOL,EPSFCN,FACTOR C DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),DIAG(N),QTF(N), C * WA1(N),WA2(N),WA3(N),WA4(M) C C C 3. Parameters. C C Parameters designated as input parameters must be specified on C entry to DNLS1 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 DNLS1. C C FCN is the name of the user-supplied subroutine which calculate 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 DOUBLE PRECISION X(N),FVEC(M) C ---------- C FJAC and LDFJAC may be ignored , if IOPT=1. C DOUBLE PRECISION FJAC(LDFJAC,N) , if IOPT=2. C DOUBLE PRECISION 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 DNLS1. In this case, set C 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 FJAC is an output array. For IOPT=1 and 2, FJAC is an M by N C array. For IOPT=3, FJAC is an N by N array. The upper N by N C submatrix 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 calcu- C lated Jacobian. Column J of P is column IPVT(J) (see below) C of the identity matrix. The lower part of FJAC contains C information generated during the computation of R. C C LDFJAC is a positive integer input variable which specifies C the leading dimension of the array FJAC. For IOPT=1 and 2, C LDFJAC must not be less than M. For IOPT=3, LDFJAC must not C be less than N. C C FTOL is a non-negative input variable. Termination occurs when C both the actual and predicted relative reductions in the sum C of squares are at most FTOL. Therefore, FTOL measures the C relative error desired in the sum of squares. Section 4 con- C tains more details about FTOL. 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 GTOL is a non-negative input variable. Termination occurs when C the cosine of the angle between FVEC and any column of the C Jacobian is at most GTOL in absolute value. Therefore, GTOL C measures the orthogonality desired between the function vector C and the columns of the Jacobian. Section 4 contains more C details about GTOL. C C MAXFEV is a positive integer input variable. Termination occurs C when the number of calls to FCN to evaluate the functions C has reached MAXFEV. 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=2 or 3, C then 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 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 to 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 both actual and predicted relative reductions in the C sum of squares are at most FTOL. C C INFO = 2 relative error between two consecutive iterates is C 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 column C of the Jacobian is at most GTOL in absolute value. C C INFO = 5 number of calls to FCN for function evaluation C has reached MAXFEV. C C INFO = 6 FTOL is too small. No further reduction in the sum C of squares is possible. C C INFO = 7 XTOL is too small. No further improvement in the C 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 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 for function evaluation. C C NJEV is an integer output variable set to the number of C evaluations of the full Jacobian. If IOPT=2, only one call to C FCN is required for each evaluation of the full Jacobian. C If IOPT=3, the M calls to FCN are required. C If IOPT=1, then NJEV is set to zero. C C IPVT is an integer output array of length N. IPVT defines a C permutation matrix P such that JAC*P = Q*R, where JAC is the C final calculated Jacobian, Q is orthogonal (not stored), and R C is upper triangular with diagonal elements of nonincreasing C magnitude. Column J of P is column IPVT(J) of the identity C matrix. C C QTF is an output array of length N which contains the first N C 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 C 4. Successful Completion. C C The accuracy of DNLS1 is controlled by the convergence parame- C ters FTOL, XTOL, and GTOL. These parameters are used in tests C which make three types of comparisons between the approximation C X and a solution XSOL. DNLS1 terminates when any of the tests C is satisfied. If any of the convergence parameters is less than C the machine precision (as defined by the function R1MACH(4)), C then DNLS1 only attempts to satisfy the test defined by the C machine precision. Further progress is not usually possible. 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 DNLS1 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 DNLS1 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+FTOL)*ENORM(FVECS), C C where FVECS denotes the functions evaluated at XSOL. If this C condition is satisfied with FTOL = 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). Unless high precision solutions are required, the C recommended value for FTOL is the square root of the machine C precision. C C Second Convergence Test. If D is the diagonal matrix whose C entries are defined by the array DIAG, then this test attempts C to guarantee 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 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 if MODE = 1, then the C accuracy of the components of X is usually related to their C sensitivity. Unless high precision solutions are required, C the recommended value for XTOL is the square root of the C machine precision. C C Third Convergence Test. This test is satisfied when the cosine C of the angle between FVEC and any column of the Jacobian at X C is at most GTOL in absolute value. There is no clear rela- C tionship between this test and the accuracy of DNLS1, and C furthermore, the test is equally well satisfied at other crit- C ical points, namely maximizers and saddle points. Therefore, C termination caused by this test (INFO = 4) should be examined C carefully. The recommended value for GTOL is zero. C C C 5. Unsuccessful Completion. C C Unsuccessful termination of DNLS1 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 for IOPT=1 or 2 C LDFJAC .LT. M, or for IOPT=3 LDFJAC .LT. N, or FTOL .LT. 0.E0, C or XTOL .LT. 0.E0, or GTOL .LT. 0.E0, or MAXFEV .LE. 0, or C FACTOR .LE. 0.E0. 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 DNLS1. In this C case, it may be possible to remedy the situation by rerunning C DNLS1 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=2 or 3 and 200*(N+1) for C IOPT=1. If the number of calls to FCN reaches MAXFEV, then C this indicates that the routine is converging very slowly C as measured by the progress of FVEC, and INFO is set to 5. C In this case, it may be helpful to restart DNLS1 with MODE C set to 1. C C C 6. Characteristics of the Algorithm. C C DNLS1 is a modification of the Levenberg-Marquardt algorithm. C Two of its main characteristics involve the proper use of C implicitly scaled variables (if MODE = 1) and an optimal choice C for the correction. The use of implicitly scaled variables C achieves scale invariance of DNLS1 and limits the size of the C correction in any direction where the functions are changing C rapidly. The optimal choice of the correction guarantees (under C reasonable conditions) global convergence from starting points C far from the solution and a fast rate of convergence for C problems with small residuals. C C Timing. The time required by DNLS1 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 DNLS1 is about N**3 to process each C evaluation of the functions (call to FCN) and to process each C evaluation of the Jacobian it takes M*N**2 for IOPT=2 (one C call to FCN), 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 DNLS1 will be C strongly influenced by the time spent in FCN. C C Storage. DNLS1 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 DNLS1 example. C C C INTEGER J,IOPT,M,N,LDFJAC,MAXFEV,MODE,NPRINT,INFO,NFEV,NJEV, C * NWRITE C INTEGER IPVT(3) C DOUBLE PRECISION FTOL,XTOL,GTOL,FACTOR,FNORM,EPSFCN C DOUBLE PRECISION X(3),FVEC(15),FJAC(15,3),DIAG(3),QTF(3), C * WA1(3),WA2(3),WA3(3),WA4(15) C DOUBLE PRECISION DENORM,D1MACH 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 LDFJAC = 15 C C C C Set FTOL and XTOL to the square root of the machine precision C C and GTOL to zero. Unless high precision solutions are C C required, these are the recommended settings. C C C FTOL = SQRT(R1MACH(4)) C XTOL = SQRT(R1MACH(4)) C GTOL = 0.E0 C C C MAXFEV = 400 C EPSFCN = 0.0 C MODE = 1 C FACTOR = 1.E2 C NPRINT = 0 C C C CALL DNLS1(FCN,IOPT,M,N,X,FVEC,FJAC,LDFJAC,FTOL,XTOL, C * GTOL,MAXFEV,EPSFCN,DIAG,MODE,FACTOR,NPRINT, C * INFO,NFEV,NJEV,IPVT,QTF,WA1,WA2,WA3,WA4) C FNORM = ENORM(M,FVEC) C WRITE (NWRITE,1000) FNORM,NFEV,NJEV,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,' NUMBER OF JACOBIAN EVALUATIONS',I10 // 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 I,M,N,IFLAG C DOUBLE PRECISION X(N),FVEC(M),Y(15) C DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 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 NUMBER OF FUNCTION EVALUATIONS 25 C C NUMBER OF JACOBIAN EVALUATIONS 0 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 I,LDFJAC,M,N,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJAC(LDFJAC,N),Y(15) C DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 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 I,M,N,IFLAG C DOUBLE PRECISION X(N),FVEC(M),FJAC(N),Y(15) C DOUBLE PRECISION TMP1,TMP2,TMP3,TMP4 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 D1MACH, DCKDER, DENORM, DFDJC3, DMPAR, DQRFAC, C DWUPDT, 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 891006 Cosmetic changes to prologue. (WRB) C 891006 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 900510 Convert XERRWV calls to XERMSG calls. (RWC) C 920205 Corrected XERN1 declaration. (WRB) C 920501 Reformatted the REFERENCES section. (WRB) C***END PROLOGUE DNLS1