Mercurial > hg > octave-lyh
view libinterp/dldfcn/__glpk__.cc @ 17411:db8b90a56298
doc: Reword docstrings for cummax, cummin.
* libinterp/corefcn/max.cc: Reword docstrings for cummax, cummin.
Add %!tests for both functions.
author | Rik <rik@octave.org> |
---|---|
date | Tue, 10 Sep 2013 10:57:52 -0700 |
parents | 2899d110c178 |
children |
line wrap: on
line source
/* Copyright (C) 2005-2012 Nicolo' Giorgetti Copyright (C) 2013 Sébastien Villemot <sebastien@debian.org> This file is part of Octave. Octave 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 3 of the License, or (at your option) any later version. Octave 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 Octave; see the file COPYING. If not, see <http://www.gnu.org/licenses/>. */ #ifdef HAVE_CONFIG_H #include <config.h> #endif #include <cfloat> #include <csetjmp> #include <ctime> #include "lo-ieee.h" #include "defun-dld.h" #include "error.h" #include "gripes.h" #include "oct-map.h" #include "oct-obj.h" #include "pager.h" #if defined (HAVE_GLPK) extern "C" { #if defined (HAVE_GLPK_GLPK_H) #include <glpk/glpk.h> #else #include <glpk.h> #endif } struct control_params { int msglev; int dual; int price; int itlim; int outfrq; int branch; int btrack; int presol; int rtest; int tmlim; int outdly; double tolbnd; double toldj; double tolpiv; double objll; double objul; double tolint; double tolobj; }; static jmp_buf mark; //-- Address for long jump to jump to int glpk (int sense, int n, int m, double *c, int nz, int *rn, int *cn, double *a, double *b, char *ctype, int *freeLB, double *lb, int *freeUB, double *ub, int *vartype, int isMIP, int lpsolver, int save_pb, int scale, const control_params *par, double *xmin, double *fmin, int *status, double *lambda, double *redcosts, double *time) { int typx = 0; int errnum = 0; clock_t t_start = clock (); glp_prob *lp = glp_create_prob (); //-- Set the sense of optimization if (sense == 1) glp_set_obj_dir (lp, GLP_MIN); else glp_set_obj_dir (lp, GLP_MAX); glp_add_cols (lp, n); for (int i = 0; i < n; i++) { //-- Define type of the structural variables if (! freeLB[i] && ! freeUB[i]) { if (lb[i] != ub[i]) glp_set_col_bnds (lp, i+1, GLP_DB, lb[i], ub[i]); else glp_set_col_bnds (lp, i+1, GLP_FX, lb[i], ub[i]); } else { if (! freeLB[i] && freeUB[i]) glp_set_col_bnds (lp, i+1, GLP_LO, lb[i], ub[i]); else { if (freeLB[i] && ! freeUB[i]) glp_set_col_bnds (lp, i+1, GLP_UP, lb[i], ub[i]); else glp_set_col_bnds (lp, i+1, GLP_FR, lb[i], ub[i]); } } // -- Set the objective coefficient of the corresponding // -- structural variable. No constant term is assumed. glp_set_obj_coef(lp,i+1,c[i]); if (isMIP) glp_set_col_kind (lp, i+1, vartype[i]); } glp_add_rows (lp, m); for (int i = 0; i < m; i++) { /* If the i-th row has no lower bound (types F,U), the corrispondent parameter will be ignored. If the i-th row has no upper bound (types F,L), the corrispondent parameter will be ignored. If the i-th row is of S type, the i-th LB is used, but the i-th UB is ignored. */ switch (ctype[i]) { case 'F': typx = GLP_FR; break; case 'U': typx = GLP_UP; break; case 'L': typx = GLP_LO; break; case 'S': typx = GLP_FX; break; case 'D': typx = GLP_DB; break; } glp_set_row_bnds (lp, i+1, typx, b[i], b[i]); } glp_load_matrix (lp, nz, rn, cn, a); if (save_pb) { static char tmp[] = "outpb.lp"; if (glp_write_lp (lp, NULL, tmp) != 0) { error ("__glpk__: unable to write problem"); longjmp (mark, -1); } } //-- scale the problem data if (!par->presol || lpsolver != 1) glp_scale_prob (lp, scale); //-- build advanced initial basis (if required) if (lpsolver == 1 && !par->presol) glp_adv_basis (lp, 0); /* For MIP problems without a presolver, a first pass with glp_simplex is required */ if ((!isMIP && lpsolver == 1) || (isMIP && !par->presol)) { glp_smcp smcp; glp_init_smcp (&smcp); smcp.msg_lev = par->msglev; smcp.meth = par->dual; smcp.pricing = par->price; smcp.r_test = par->rtest; smcp.tol_bnd = par->tolbnd; smcp.tol_dj = par->toldj; smcp.tol_piv = par->tolpiv; smcp.obj_ll = par->objll; smcp.obj_ul = par->objul; smcp.it_lim = par->itlim; smcp.tm_lim = par->tmlim; smcp.out_frq = par->outfrq; smcp.out_dly = par->outdly; smcp.presolve = par->presol; errnum = glp_simplex (lp, &smcp); } if (isMIP) { glp_iocp iocp; glp_init_iocp (&iocp); iocp.msg_lev = par->msglev; iocp.br_tech = par->branch; iocp.bt_tech = par->btrack; iocp.tol_int = par->tolint; iocp.tol_obj = par->tolobj; iocp.tm_lim = par->tmlim; iocp.out_frq = par->outfrq; iocp.out_dly = par->outdly; iocp.presolve = par->presol; errnum = glp_intopt (lp, &iocp); } if (!isMIP && lpsolver == 2) { glp_iptcp iptcp; glp_init_iptcp (&iptcp); iptcp.msg_lev = par->msglev; errnum = glp_interior (lp, &iptcp); } if (errnum == 0) { if (isMIP) { *status = glp_mip_status (lp); *fmin = glp_mip_obj_val (lp); } else { if (lpsolver == 1) { *status = glp_get_status (lp); *fmin = glp_get_obj_val (lp); } else { *status = glp_ipt_status (lp); *fmin = glp_ipt_obj_val (lp); } } if (isMIP) { for (int i = 0; i < n; i++) xmin[i] = glp_mip_col_val (lp, i+1); } else { /* Primal values */ for (int i = 0; i < n; i++) { if (lpsolver == 1) xmin[i] = glp_get_col_prim (lp, i+1); else xmin[i] = glp_ipt_col_prim (lp, i+1); } /* Dual values */ for (int i = 0; i < m; i++) { if (lpsolver == 1) lambda[i] = glp_get_row_dual (lp, i+1); else lambda[i] = glp_ipt_row_dual (lp, i+1); } /* Reduced costs */ for (int i = 0; i < glp_get_num_cols (lp); i++) { if (lpsolver == 1) redcosts[i] = glp_get_col_dual (lp, i+1); else redcosts[i] = glp_ipt_col_dual (lp, i+1); } } *time = (clock () - t_start) / CLOCKS_PER_SEC; } glp_delete_prob (lp); return errnum; } #endif #define OCTAVE_GLPK_GET_REAL_PARAM(NAME, VAL) \ do \ { \ octave_value tmp = PARAM.getfield (NAME); \ \ if (tmp.is_defined ()) \ { \ if (! tmp.is_empty ()) \ { \ VAL = tmp.scalar_value (); \ \ if (error_state) \ { \ error ("glpk: invalid value in PARAM." NAME); \ return retval; \ } \ } \ else \ { \ error ("glpk: invalid value in PARAM." NAME); \ return retval; \ } \ } \ } \ while (0) #define OCTAVE_GLPK_GET_INT_PARAM(NAME, VAL) \ do \ { \ octave_value tmp = PARAM.getfield (NAME); \ \ if (tmp.is_defined ()) \ { \ if (! tmp.is_empty ()) \ { \ VAL = tmp.int_value (); \ \ if (error_state) \ { \ error ("glpk: invalid value in PARAM." NAME); \ return retval; \ } \ } \ else \ { \ error ("glpk: invalid value in PARAM." NAME); \ return retval; \ } \ } \ } \ while (0) DEFUN_DLD (__glpk__, args, , "-*- texinfo -*-\n\ @deftypefn {Loadable Function} {[@var{values}] =} __glpk__ (@var{args})\n\ Undocumented internal function.\n\ @end deftypefn") { // The list of values to return. See the declaration in oct-obj.h octave_value_list retval; #if defined (HAVE_GLPK) int nrhs = args.length (); if (nrhs != 9) { print_usage (); return retval; } //-- 1nd Input. A column array containing the objective function //-- coefficients. volatile int mrowsc = args(0).rows (); Matrix C (args(0).matrix_value ()); if (error_state) { error ("__glpk__: invalid value of C"); return retval; } double *c = C.fortran_vec (); Array<int> rn; Array<int> cn; ColumnVector a; volatile int mrowsA; volatile int nz = 0; //-- 2nd Input. A matrix containing the constraints coefficients. // If matrix A is NOT a sparse matrix if (args(1).is_sparse_type ()) { SparseMatrix A = args(1).sparse_matrix_value (); // get the sparse matrix if (error_state) { error ("__glpk__: invalid value of A"); return retval; } mrowsA = A.rows (); octave_idx_type Anc = A.cols (); octave_idx_type Anz = A.nnz (); rn.resize (dim_vector (Anz+1, 1)); cn.resize (dim_vector (Anz+1, 1)); a.resize (Anz+1, 0.0); if (Anc != mrowsc) { error ("__glpk__: invalid value of A"); return retval; } for (octave_idx_type j = 0; j < Anc; j++) for (octave_idx_type i = A.cidx (j); i < A.cidx (j+1); i++) { nz++; rn(nz) = A.ridx (i) + 1; cn(nz) = j + 1; a(nz) = A.data(i); } } else { Matrix A (args(1).matrix_value ()); // get the matrix if (error_state) { error ("__glpk__: invalid value of A"); return retval; } mrowsA = A.rows (); rn.resize (dim_vector (mrowsA*mrowsc+1, 1)); cn.resize (dim_vector (mrowsA*mrowsc+1, 1)); a.resize (mrowsA*mrowsc+1, 0.0); for (int i = 0; i < mrowsA; i++) { for (int j = 0; j < mrowsc; j++) { if (A(i,j) != 0) { nz++; rn(nz) = i + 1; cn(nz) = j + 1; a(nz) = A(i,j); } } } } //-- 3rd Input. A column array containing the right-hand side value // for each constraint in the constraint matrix. Matrix B (args(2).matrix_value ()); if (error_state) { error ("__glpk__: invalid value of B"); return retval; } double *b = B.fortran_vec (); //-- 4th Input. An array of length mrowsc containing the lower //-- bound on each of the variables. Matrix LB (args(3).matrix_value ()); if (error_state || LB.length () < mrowsc) { error ("__glpk__: invalid value of LB"); return retval; } double *lb = LB.fortran_vec (); //-- LB argument, default: Free Array<int> freeLB (dim_vector (mrowsc, 1)); for (int i = 0; i < mrowsc; i++) { if (xisinf (lb[i])) { freeLB(i) = 1; lb[i] = -octave_Inf; } else freeLB(i) = 0; } //-- 5th Input. An array of at least length numcols containing the upper //-- bound on each of the variables. Matrix UB (args(4).matrix_value ()); if (error_state || UB.length () < mrowsc) { error ("__glpk__: invalid value of UB"); return retval; } double *ub = UB.fortran_vec (); Array<int> freeUB (dim_vector (mrowsc, 1)); for (int i = 0; i < mrowsc; i++) { if (xisinf (ub[i])) { freeUB(i) = 1; ub[i] = octave_Inf; } else freeUB(i) = 0; } //-- 6th Input. A column array containing the sense of each constraint //-- in the constraint matrix. charMatrix CTYPE (args(5).char_matrix_value ()); if (error_state) { error ("__glpk__: invalid value of CTYPE"); return retval; } char *ctype = CTYPE.fortran_vec (); //-- 7th Input. A column array containing the types of the variables. charMatrix VTYPE (args(6).char_matrix_value ()); if (error_state) { error ("__glpk__: invalid value of VARTYPE"); return retval; } Array<int> vartype (dim_vector (mrowsc, 1)); volatile int isMIP = 0; for (int i = 0; i < mrowsc ; i++) { if (VTYPE(i,0) == 'I') { isMIP = 1; vartype(i) = GLP_IV; } else vartype(i) = GLP_CV; } //-- 8th Input. Sense of optimization. volatile int sense; double SENSE = args(7).scalar_value (); if (error_state) { error ("__glpk__: invalid value of SENSE"); return retval; } if (SENSE >= 0) sense = 1; else sense = -1; //-- 9th Input. A structure containing the control parameters. octave_scalar_map PARAM = args(8).scalar_map_value (); if (error_state) { error ("__glpk__: invalid value of PARAM"); return retval; } control_params par; //-- ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //-- Integer parameters //-- ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //-- Level of messages output by the solver par.msglev = 1; OCTAVE_GLPK_GET_INT_PARAM ("msglev", par.msglev); if (par.msglev < 0 || par.msglev > 3) { error ("__glpk__: PARAM.msglev must be 0 (no output) or 1 (error and warning messages only [default]) or 2 (normal output) or 3 (full output)"); return retval; } //-- scaling option volatile int scale = 16; OCTAVE_GLPK_GET_INT_PARAM ("scale", scale); if (scale < 0 || scale > 128) { error ("__glpk__: PARAM.scale must either be 128 (automatic selection of scaling options), or a bitwise or of: 1 (geometric mean scaling), 16 (equilibration scaling), 32 (round scale factors to power of two), 64 (skip if problem is well scaled"); return retval; } //-- Dual simplex option par.dual = 1; OCTAVE_GLPK_GET_INT_PARAM ("dual", par.dual); if (par.dual < 1 || par.dual > 3) { error ("__glpk__: PARAM.dual must be 1 (use two-phase primal simplex [default]) or 2 (use two-phase dual simplex) or 3 (use two-phase dual simplex, and if it fails, switch to the primal simplex)"); return retval; } //-- Pricing option par.price = 34; OCTAVE_GLPK_GET_INT_PARAM ("price", par.price); if (par.price != 17 && par.price != 34) { error ("__glpk__: PARAM.price must be 17 (textbook pricing) or 34 (steepest edge pricing [default])"); return retval; } //-- Simplex iterations limit par.itlim = std::numeric_limits<int>::max (); OCTAVE_GLPK_GET_INT_PARAM ("itlim", par.itlim); //-- Output frequency, in iterations par.outfrq = 200; OCTAVE_GLPK_GET_INT_PARAM ("outfrq", par.outfrq); //-- Branching heuristic option par.branch = 4; OCTAVE_GLPK_GET_INT_PARAM ("branch", par.branch); if (par.branch < 1 || par.branch > 5) { error ("__glpk__: PARAM.branch must be 1 (first fractional variable) or 2 (last fractional variable) or 3 (most fractional variable) or 4 (heuristic by Driebeck and Tomlin [default]) or 5 (hybrid pseudocost heuristic)"); return retval; } //-- Backtracking heuristic option par.btrack = 4; OCTAVE_GLPK_GET_INT_PARAM ("btrack", par.btrack); if (par.btrack < 1 || par.btrack > 4) { error ("__glpk__: PARAM.btrack must be 1 (depth first search) or 2 (breadth first search) or 3 (best local bound) or 4 (best projection heuristic [default]"); return retval; } //-- Presolver option par.presol = 1; OCTAVE_GLPK_GET_INT_PARAM ("presol", par.presol); if (par.presol < 0 || par.presol > 1) { error ("__glpk__: PARAM.presol must be 0 (do NOT use LP presolver) or 1 (use LP presolver [default])"); return retval; } //-- LPsolver option volatile int lpsolver = 1; OCTAVE_GLPK_GET_INT_PARAM ("lpsolver", lpsolver); if (lpsolver < 1 || lpsolver > 2) { error ("__glpk__: PARAM.lpsolver must be 1 (simplex method) or 2 (interior point method)"); return retval; } //-- Ratio test option par.rtest = 34; OCTAVE_GLPK_GET_INT_PARAM ("rtest", par.rtest); if (par.rtest != 17 && par.rtest != 34) { error ("__glpk__: PARAM.rtest must be 17 (standard ratio test) or 34 (Harris' two-pass ratio test [default])"); return retval; } par.tmlim = std::numeric_limits<int>::max (); OCTAVE_GLPK_GET_INT_PARAM ("tmlim", par.tmlim); par.outdly = 0; OCTAVE_GLPK_GET_INT_PARAM ("outdly", par.outdly); //-- Save option volatile int save_pb = 0; OCTAVE_GLPK_GET_INT_PARAM ("save", save_pb); save_pb = save_pb != 0; //-- ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //-- Real parameters //-- ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ //-- Relative tolerance used to check if the current basic solution //-- is primal feasible par.tolbnd = 1e-7; OCTAVE_GLPK_GET_REAL_PARAM ("tolbnd", par.tolbnd); //-- Absolute tolerance used to check if the current basic solution //-- is dual feasible par.toldj = 1e-7; OCTAVE_GLPK_GET_REAL_PARAM ("toldj", par.toldj); //-- Relative tolerance used to choose eligible pivotal elements of //-- the simplex table in the ratio test par.tolpiv = 1e-10; OCTAVE_GLPK_GET_REAL_PARAM ("tolpiv", par.tolpiv); par.objll = -std::numeric_limits<double>::max (); OCTAVE_GLPK_GET_REAL_PARAM ("objll", par.objll); par.objul = std::numeric_limits<double>::max (); OCTAVE_GLPK_GET_REAL_PARAM ("objul", par.objul); par.tolint = 1e-5; OCTAVE_GLPK_GET_REAL_PARAM ("tolint", par.tolint); par.tolobj = 1e-7; OCTAVE_GLPK_GET_REAL_PARAM ("tolobj", par.tolobj); //-- Assign pointers to the output parameters ColumnVector xmin (mrowsc, octave_NA); double fmin = octave_NA; ColumnVector lambda (mrowsA, octave_NA); ColumnVector redcosts (mrowsc, octave_NA); double time; int status, errnum = 0; int jmpret = setjmp (mark); if (jmpret == 0) errnum = glpk (sense, mrowsc, mrowsA, c, nz, rn.fortran_vec (), cn.fortran_vec (), a.fortran_vec (), b, ctype, freeLB.fortran_vec (), lb, freeUB.fortran_vec (), ub, vartype.fortran_vec (), isMIP, lpsolver, save_pb, scale, &par, xmin.fortran_vec (), &fmin, &status, lambda.fortran_vec (), redcosts.fortran_vec (), &time); octave_scalar_map extra; if (! isMIP) { extra.assign ("lambda", lambda); extra.assign ("redcosts", redcosts); } extra.assign ("time", time); extra.assign ("status", status); retval(3) = extra; retval(2) = errnum; retval(1) = fmin; retval(0) = xmin; #else gripe_not_supported ("glpk"); #endif return retval; } /* ## No test needed for internal helper function. %!assert (1) */