!************************************************************************* !* * !* Initialization of parameters for DC optimization based * !* clustering software (last modified 24.02.2016) * !* * !************************************************************************* !* !* Modules included: !* !* initclust ! Initialization of parameters for clustering. !* initdcclust ! Initialization of DC-Clust -solver. !* initdcdb ! Initialization of DCDB -solver. !* MODULE initclust ! Initialization of parameters for clustering codes. USE r_precision, ONLY : prec ! Precision for reals. IMPLICIT NONE ! Parameters INTEGER, PARAMETER :: & maxdim = 50000, & ! Maximum number of variables in optimization, ! maxdim >= maxclust * maxnft. maxsize = 1000000, & ! Maximum number of candidate points of data set, ! maxsize >> maxdim. maxrec = 500000, & ! Maximum number of recorts in dataset. maxnft = 250, & ! Maximum number of features in dataset. maxclust = 100, & ! Maximum number of clusters. maxclass = 100 ! Maximum number of classes (not used). ! Names of input and output files: ! Give names here or uncommend subroutine read_data from dcclustering.f95 CHARACTER(LEN=80), SAVE :: & infile = 'iris.txt', & ! Name of dataset file. outfile0 = 'cluster_centers_dcdb.txt', & ! Result file with cluster centers. outfile1 = 'cluster_indices_dcdb.txt' ! Result file with function values, ! Davies-Bouldin (DB) validity index, ! and cpu-time. ! infile, & ! Name of dataset file. ! outfile0, & ! Result file with cluster centers. ! outfile1 ! Result file with function values, Davies-Bouldin (DB) ! validity index, and cpu-time. ! Input real parameters. ! Give values here or uncommend subroutine read_data from dcclustering.f95 REAL, SAVE :: & tlimit = 72000.0 ! Maximum CPU-time in seconds, from user. REAL(KIND=prec), SAVE :: & ! a(maxrec,maxnft), & ! Data matrix, from input file, give the name of the file above or ! uncommend subroutine read_data from dcclustering.f95. gamma1 = 0.1_prec, & ! Parameter affecting the size of the set of starting point, ! from user, 0 < gamma1 < 1. Defaults: gamma1=0.1 for small problems ! and gamma1 = 0.9_prec for large problems. gamma2 = 0.9_prec ! Parameter affecting the size of the set of starting point, ! from user, 0 < gamma2 < 1. Defaults: gamma2=0.9 for small problems ! and gamma2 = 0.99 for large problems. ! gamma1, & ! Parameter affecting the size of the set of starting point, ! ! from user, 0 < gamma1 < 1. ! gamma2 ! Parameter affecting the size of the set of starting point, ! ! from user, 0 < gamma2 < 1. ! Other Real parameters. REAL(KIND=prec), SAVE :: & ! tnorm, & ! The total number of norms computed. dminim(maxrec), & ! plabel(maxclass) ! Index for class output (not used). ! Input integer parameters. ! Give values here or uncommend subroutine read_data from dcclustering.f95 INTEGER, SAVE :: & ! optmet = 2, & ! Optimization method: ! 1 = DC-Clust, ! 2 = DCDB. nclust = 40, & ! Maximum number of clusters, from user. nft = 4, & ! Number of features in data. nrecord = 150, & ! Number of recorts in data. nclass = 0, & ! Number of classes, from user (not used). npurity = 2 ! Switch for classes, from user, (not used): ! npurity = 1 if class outputs, ! npurity = 2 if no class outputs. ! optmet, & ! Optimization method: ! ! 1 = DC-Clust, ! ! 2 = DCDB. ! nclust, & ! Maximum number of clusters, from user. ! nft, & ! Number of features in data, from user. ! nrecord, & ! Number of reports in data, from user. ! nclass, & ! Number of classes, from user (not used). ! npurity ! Switch for classes, from user, (not used): ! ! npurity = 1 if class outputs, ! ! npurity = 2 if no class outputs. ! Other integer parameters. INTEGER, SAVE :: & ! mf, & ! Number of used features: ! mf = nft, when no classes, ! mf = nft - 1, when classes. nc, & ! Current number of clusters, loops from 1 to nclust ns, & ! Switch for auxiliary and real clustering problem. m, & ! Number of variables in optimization: ! m = mf if ns = 1, ! m = mf*nc if ns = 2. nob(maxclass), & ! Classes, (not used) nk(maxclust,maxrec), & ! nel(maxclust), & ! ncand, & ! Number of canditate points. lcand(maxrec) ! CONTAINS SUBROUTINE init_clustpar() ! User supplied subroutine for further initialization of parameters (when needed). ! May be left empty. IMPLICIT NONE IF (nrecord < 5000) THEN gamma1 = 0.1_prec gamma2 = 0.9_prec ELSE IF (nrecord < 50000) THEN gamma1 = 0.9_prec gamma2 = 0.95_prec ELSE IF (nrecord < 100000) THEN gamma1 = 0.95_prec gamma2 = 0.99_prec ELSE gamma1 = 0.975_prec gamma2 = 0.995_prec END IF END SUBROUTINE init_clustpar END MODULE initclust MODULE initdcclust ! Initialization of parameters for DC-Clust method. USE r_precision, ONLY : prec ! Precision for reals. USE initclust, ONLY : maxdim ! Maximum dimension of x. IMPLICIT NONE ! Parameters INTEGER, PARAMETER :: & maxdg=1000 ! optimization ! Real parameters. REAL(KIND=prec), SAVE :: & ! Previous common variables eps, & dg3(maxdim), & ! optimization z_opt(maxdg), & aa(maxdg,maxdg) ! Integer parameters. INTEGER, SAVE :: & ! Previous common variables nf, & multiple, & nscale, & niter, & maxiter, & ij(maxdg), & jvertex, & kmin CONTAINS SUBROUTINE init_dcclustpar() ! User supplied subroutine for further initialization of parameters (when needed). ! May be left empty. IMPLICIT NONE END SUBROUTINE init_dcclustpar END MODULE initdcclust MODULE initdcdb ! Initialization of parameters for DCDB method. USE r_precision, ONLY : prec ! Precision for reals. USE param, ONLY : zero, one ! Parameters. USE initclust, ONLY : maxdim ! Maximum dimension of x. IMPLICIT NONE ! Parameters INTEGER, PARAMETER :: & mcu = 7, & ! Maximum number of stored corrections, mcu >=1. mnma = 10, & ! Maximum number of function values used in nonmonotone line search. inma = 1, & ! Selection of line search method: ! inma = 0, Armijo line search, ! inma = 1, nonmonotone Armijo line search. maxnin = 20 ! Maximum number of interpolations in Armijo line search, maxnin >= 0. ! The value maxint = 2 is recommented with inma=0 and maxint=20 with inma=1. ! Real parameters (if parameter value <= 0.0 the default value of the parameter will be used). REAL(KIND=prec), SAVE :: & tolb = zero, & ! Tolerance for the function value (default = -large). tolf = 1.0E-8_prec, & ! Tolerance for change of function values (default = 1.0E-8). tolf2 = -10.0_prec, & ! Second tolerance for change of function values. ! - If tolf2 < 0 the the parameter and the corresponding termination ! criterion will be ignored (recommended with inma=1). ! - If tolf2 = 0 the default value 1.0E+4 will be used. tolg = 1.0E-5_prec, & ! Tolerance for the termination criterion (default = 1.0E-6). eta = 1.0E-4_prec, & ! Distance measure parameter, eta > 0. ! - If eta < 0 the default value 0.0001 will be used. epsl = 0.24E+00, & ! Line search parameter, 0 < epsl < 0.25 (default = 1.0E-4). told = 1.0E+6, & ! Upper bound for the diagonal elements (default = 1.0E+6). mintold = 1.0E-10_prec, & ! Lower bound for the diagonal elements (default = 1.0E-10). mintold2 = one, & ! Lower bound for the "concave" update (default = 1.0). sigma = 1.0E-10_prec ! -sigma is the smallest value that is considered as positive ! linearization error (default = 0). ! Integer parameters (if value <= 0 the default value of the parameter will be used). INTEGER, SAVE :: & n = maxdim, & ! Number of variables. mit = 5000, & ! Maximun number of iterations. mfe = 5000, & ! Maximun number of function evaluations. mtesf = 0, & ! Maximum number of iterations with changes of ! function values smaller than tolf (default = 10). iprint = 1 ! Printout specification: ! -1 - No printout. ! 0 - Only the error messages. ! 1 - The final values of the objective function ! (default used if iprint < -1). ! 2 - The final values of the objective function and the ! most serious warning messages. ! 3 - The whole final solution. ! 4 - At each iteration values of the objective function. ! 5 - At each iteration the whole solution REAL(KIND=prec), DIMENSION(maxdim), SAVE :: x ! Vector of variables CONTAINS SUBROUTINE defaults() ! Default values for parameters. USE param, ONLY: small, large, zero, one IMPLICIT NONE IF (iprint < -1) iprint = 1 ! Printout specification. IF (mit <= 0) mit = 5000 ! Maximum number of iterations. IF (mfe <= 0) mfe = n*mit ! Maximum number of function evaluations. IF (tolf <= zero) tolf = 1.0E-08_prec ! Tolerance for change of function values. IF (tolf2 == zero) tolf2 = 1.0E+04_prec ! Second tolerance for change of function values. IF (tolb == zero) tolb = -large + small ! Tolerance for the function value. IF (tolg <= zero) tolg = 1.0E-06_prec ! Tolerance for the termination criterion. IF (told <= zero) told = 1.0E+06_prec ! Upper bound for the diagonal elements. IF (mintold <= zero) told = 1.0E-10_prec ! Lower bound for the diagonal elements. IF (mintold2 <= zero) told = one ! Lower bound for "concave" update. IF (eta < zero) eta = 1.0E-04_prec ! Distance measure parameter IF (epsl <= zero) epsl = 1.0E-04_prec ! Line search parameter, IF (mtesf <= 0) mtesf = 10 ! Maximum number of iterations with changes ! of function values smaller than tolf. END SUBROUTINE defaults SUBROUTINE init_par() ! User supplied subroutine for further initialization of parameters (when needed). ! May be left empty. USE initclust, ONLY : ns,nc IMPLICIT NONE ! For big data sets use larger values ! tolg =1.0E+00 ! IF (ns == 2) THEN ! tolg = 1.0E+3 ! IF(nc == 5) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 10) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 15) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 20) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 25) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 30) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 35) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 40) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 45) THEN ! tolg = 1.0E-3 ! ELSE IF(nc == 50) THEN ! tolg = 1.0E-3 ! END IF ! END IF ! For small data sets IF(ns == 1) tolg = 1.0E-5 IF(ns == 2) tolg = 1.0E-4 END SUBROUTINE init_par END MODULE initdcdb