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b4c3bb1387
Estimated hours taken: 3 Branches: main Clean up in unused module imports in the Mercury system detected by --warn-unused-imports. analysis/*.m: browser/*.m: deep_profiler/*.m: compiler/*.m: library/*.m: mdbcomp/*.m: profiler/*.m: slice/*.m: Remove unused module imports. Fix some minor departures from our coding standards. analysis/Mercury.options: browser/Mercury.options: deep_profiler/Mercury.options: compiler/Mercury.options: library/Mercury.options: mdbcomp/Mercury.options: profiler/Mercury.options: slice/Mercury.options: Set --no-warn-unused-imports for those modules that are used as packages or otherwise break --warn-unused-imports, e.g. because they contain predicates with both foreign and Mercury clauses and some of the imports only depend on the latter.
945 lines
29 KiB
Mathematica
945 lines
29 KiB
Mathematica
%-----------------------------------------------------------------------------%
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% vim: ft=mercury ts=4 sw=4 et
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%-----------------------------------------------------------------------------%
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% Copyright (C) 1997,2002-2006 The University of Melbourne.
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% This file may only be copied under the terms of the GNU General
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% Public License - see the file COPYING in the Mercury distribution.
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%-----------------------------------------------------------------------------%
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%
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% File: lp.m.
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% Main author: conway.
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%
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% This module implements a linear constraint solver that finds an
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% optimal solution to a set of linear [in]equalities with respect
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% to some objective function. It does this using the simplex method.
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%
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% The form of an [in]equation is
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% a1.x1 + a2.x2 + ... + an.xn {=<,=,>=} b
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% where all the numbers are floats, a variable xn may occur multiple
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% times in an equation (or the objective function) - the solver simplifies
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% all the inequations.
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% By default, there is an additional constraint on each of the `xn's:
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% xn >= 0
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% If you want xn to take on any value, you can include it in the list
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% of URS (UnRestricted in Sign) variables.
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%
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% The objective function is simply a weighted sum of the variables.
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%
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% The `x's are represented by `term.var's. The varset from which
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% they are allocated is passed to the solver because it needs to
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% introduce new variables as part of the solving algorithm.
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%
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%-----------------------------------------------------------------------------%
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:- module libs.lp.
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:- interface.
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:- import_module io.
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:- import_module list.
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:- import_module map.
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:- import_module pair.
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:- import_module term.
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:- import_module varset.
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%-----------------------------------------------------------------------------%
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:- type coeff == pair(var, float).
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:- type equation ---> eqn(list(coeff), operator, float).
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:- type operator ---> (=<) ; (=) ; (>=).
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:- type equations == list(equation).
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:- type objective == list(coeff).
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:- type direction ---> max ; min.
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:- type lp.result
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---> unsatisfiable
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; satisfiable(float, map(var, float)).
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%-----------------------------------------------------------------------------%
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% lp_solve(Inequations, MaxOrMin, Objective, Varset, URSVars,
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% Result, IO0, IO)
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% maximize (or minimize - depending on `MaxOrMin') `Objective'
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% subject to the constraints `Inequations'. The variables in
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% the objective and inequations are from `Varset' which is passed
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% so that the solver can allocate fresh variables as required.
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% URSVars is the list of variable that are unrestricted in sign.
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% lp_solve binds Result either to `unsatisfiable' if the there
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% was no optimum value of the objective function (ie the
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% constraints were inconsistent, or the objective function
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% is unbounded by the constraints), or `satisfiable(ObjVal,
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% MapFromObjVarsToVals)'.
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%
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:- pred lp_solve(equations::in, direction::in, objective::in, varset::in,
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list(var)::in, lp.result::out, io::di, io::uo) is det.
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%-----------------------------------------------------------------------------%
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%-----------------------------------------------------------------------------%
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:- implementation.
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:- import_module libs.compiler_util.
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:- import_module bool.
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:- import_module float.
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:- import_module int.
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:- import_module maybe.
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:- import_module set.
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:- import_module solutions.
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:- import_module string.
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:- import_module svmap.
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:- import_module svset.
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:- import_module svvarset.
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%-----------------------------------------------------------------------------%
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:- type lp_info
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---> lp(
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varset :: varset,
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urs_map :: map(var, pair(var)),
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% Map from variables with URS to the
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% corresponding pair of variables that
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% represent that variable in the standard
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% form (x = x' - x'', x', x'' >= 0).
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slack_vars :: list(var), % slack variables
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artificial_vars :: list(var) % artificial variables
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).
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%-----------------------------------------------------------------------------%
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lp_solve(Eqns, Dir, Obj, Varset0, URSVars, Result, !IO) :-
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lp_info_init(Varset0, URSVars, Info0),
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lp_solve_2(Eqns, Dir, Obj, Result, Info0, _, !IO).
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% lp_solve2(Eqns, Dir, Obj, Res, IO0, IO, LPInfo0, LPInfo) takes
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% a list of inequations `Eqns', a direction for optimization
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% `Dir', an objective function `Obj', an I/O state `IO0' and an
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% lp_info structure `LPInfo0'. See inline comments for details
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% on the algorithm.
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%
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:- pred lp_solve_2(equations::in, direction::in, objective::in,
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lp.result::out, lp_info::in, lp_info::out, io::di, io::uo)
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is det.
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lp_solve_2(Eqns0, Dir, Obj0, Result, !Info, !IO) :-
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%
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% Simplify the inequations and convert them to standard form by
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% introducing slack/excess/artificial variables. We also expand
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% URS variables by replacing them with the difference of two
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% fresh variables.
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%
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standardize_equations(Eqns0, Eqns, !Info),
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%
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% If we're maximizing the objective function then we need
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% to negate all the coefficients in the objective.
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%
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(
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Dir = max,
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negate_equation(eqn(Obj0, (=), 0.0), eqn(Obj1, _, _))
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;
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Dir = min,
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Obj1 = Obj0
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),
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simplify_coeffs(Obj1, Obj2),
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get_urs_vars(URS, !.Info, _),
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expand_urs_vars(Obj2, URS, Obj),
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list.length(Eqns, Rows),
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collect_vars(Eqns, Obj, Vars),
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set.to_sorted_list(Vars, VarList),
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list.length(VarList, Cols),
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map.init(VarNums0),
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number_vars(VarList, 0, VarNums0, VarNums),
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get_art_vars(ArtVars, !Info),
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some [!Tableau] (
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init_tableau(Rows, Cols, VarNums, URS, !:Tableau),
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insert_equations(Eqns, 1, Cols, VarNums, !Tableau),
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(
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ArtVars = [_|_],
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% There are one or more artificial variables, so we use
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% the two-phase method for solving the system.
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two_phase(Obj0, Obj, ArtVars, VarNums, !.Tableau, Result0)
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;
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ArtVars = [],
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one_phase(Obj0, Obj, VarNums, !.Tableau, Result0)
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)
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),
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(
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Dir = max,
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Result = Result0
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;
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Dir = min,
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(
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Result0 = unsatisfiable,
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Result = Result0
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;
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Result0 = satisfiable(NOptVal, OptCoffs),
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OptVal = -NOptVal,
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Result = satisfiable(OptVal, OptCoffs)
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)
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).
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%-----------------------------------------------------------------------------%
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:- pred one_phase(list(coeff)::in, list(coeff)::in, map(var, int)::in,
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tableau::in, lp.result::out) is det.
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one_phase(Obj0, Obj, VarNums, Tableau0, Result) :-
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insert_coeffs(Obj, 0, VarNums, Tableau0, Tableau1),
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ObjVars = get_vars_from_coeffs(Obj0),
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optimize(ObjVars, Tableau1, _, Result).
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:- func get_vars_from_coeffs(list(coeff)) = list(var).
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get_vars_from_coeffs(Coeffs) = Vars :-
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get_vars_from_coeffs_2(Coeffs, set.init, SetVars),
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Vars = set.to_sorted_list(SetVars).
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:- pred get_vars_from_coeffs_2(list(coeff)::in, set(var)::in, set(var)::out)
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is det.
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get_vars_from_coeffs_2([], !SetVar).
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get_vars_from_coeffs_2([Var - _ | Coeffs], !SetVar) :-
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svset.insert(Var, !SetVar),
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get_vars_from_coeffs_2(Coeffs, !SetVar).
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%-----------------------------------------------------------------------------%
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:- pred two_phase(list(coeff)::in, list(coeff)::in, list(var)::in,
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map(var, int)::in, tableau::in, lp.result::out) is det.
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two_phase(Obj0, Obj, ArtVars, VarNums, Tableau0, Result) :-
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%
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% Do phase 1: minimize the sum of the artificial variables.
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%
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some [!Tableau] (
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!:Tableau = Tableau0,
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construct_art_objective(ArtVars, ArtObj),
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insert_coeffs(ArtObj, 0, VarNums, !Tableau),
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ensure_zero_obj_coeffs(ArtVars, !Tableau),
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optimize(ArtVars, !Tableau, Res0),
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(
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Res0 = unsatisfiable,
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Result = unsatisfiable
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;
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Res0 = satisfiable(Val, _ArtRes),
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( Val \= 0.0 ->
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Result = unsatisfiable
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;
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fix_basis_and_rem_cols(ArtVars, !Tableau),
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% Do phase 2:
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% insert the real objective,
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% zero the objective coefficients of the
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% basis variables,
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% optimize the objective.
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insert_coeffs(Obj, 0, VarNums, !Tableau),
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get_basis_vars(!.Tableau, BasisVars),
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ensure_zero_obj_coeffs(BasisVars, !Tableau),
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ObjVars = get_vars_from_coeffs(Obj0),
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optimize(ObjVars, !.Tableau, _, Result)
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)
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)
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).
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%-----------------------------------------------------------------------------%
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:- pred construct_art_objective(list(var)::in, list(coeff)::out) is det.
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construct_art_objective([], []).
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construct_art_objective([V | Vs], [V - (1.0) | Rest]) :-
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construct_art_objective(Vs, Rest).
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%-----------------------------------------------------------------------------%
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:- pred standardize_equations(equations::in, equations::out,
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lp_info::in, lp_info::out) is det.
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standardize_equations(!Eqns, !Info) :-
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list.map_foldl(standardize_equation, !Eqns, !Info).
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% standardize_equation peforms the following operations on an
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% equation:
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% - ensures the constant is >= 0 (multiplying by -1 if
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% necessary)
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% - introduces slack, excess and artificial variables
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% - replace the URS variables with their corresponding
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% difference pair
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%
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:- pred standardize_equation(equation::in, equation::out,
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lp_info::in, lp_info::out) is det.
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standardize_equation(Eqn0, Eqn, !Info) :-
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Eqn0 = eqn(Coeffs0, (=<), Const0),
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( Const0 < 0.0 ->
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negate_equation(Eqn0, Eqn1),
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standardize_equation(Eqn1, Eqn, !Info)
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;
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new_slack_var(Var, !Info),
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Coeffs = [Var - 1.0 | Coeffs0],
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simplify_eq(eqn(Coeffs, (=<), Const0), Eqn1),
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get_urs_vars(URS, !Info),
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expand_urs_vars_e(Eqn1, URS, Eqn)
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).
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standardize_equation(Eqn0, Eqn, !Info) :-
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Eqn0 = eqn(Coeffs0, (=), Const0),
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( Const0 < 0.0 ->
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negate_equation(Eqn0, Eqn1),
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standardize_equation(Eqn1, Eqn, !Info)
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;
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new_art_var(Var, !Info),
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Coeffs = [Var - 1.0 | Coeffs0],
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simplify_eq(eqn(Coeffs, (=<), Const0), Eqn1),
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get_urs_vars(URS, !Info),
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expand_urs_vars_e(Eqn1, URS, Eqn)
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).
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standardize_equation(Eqn0, Eqn, !Info) :-
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Eqn0 = eqn(Coeffs0, (>=), Const0),
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( Const0 < 0.0 ->
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negate_equation(Eqn0, Eqn1),
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standardize_equation(Eqn1, Eqn, !Info)
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;
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new_slack_var(SVar, !Info),
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new_art_var(AVar, !Info),
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Coeffs = [SVar - (-1.0), AVar - (1.0) | Coeffs0],
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simplify_eq(eqn(Coeffs, (>=), Const0), Eqn1),
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get_urs_vars(URS, !Info),
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expand_urs_vars_e(Eqn1, URS, Eqn)
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).
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:- pred negate_equation(equation::in, equation::out) is det.
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negate_equation(eqn(Coeffs0, Op0, Const0), eqn(Coeffs, Op, Const)) :-
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(
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Op0 = (=<), Op = (>=)
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;
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Op0 = (=), Op = (=)
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;
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Op0 = (>=), Op = (=<)
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),
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Coeffs = list.map((func(V - X) = V - (-X)), Coeffs0),
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Const = -Const0.
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:- pred simplify_eq(equation::in, equation::out) is det.
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simplify_eq(eqn(Coeffs0, Op, Const), eqn(Coeffs, Op, Const)) :-
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simplify_coeffs(Coeffs0, Coeffs).
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:- pred simplify_coeffs(list(coeff)::in, list(coeff)::out) is det.
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simplify_coeffs(Coeffs0, Coeffs) :-
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map.init(CoeffMap0),
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AddCoeff = (pred(Pair::in, Map0::in, Map::out) is det :-
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Pair = Var - Coeff,
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add_var(Var, Coeff, Map0, Map)
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),
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list.foldl(AddCoeff, Coeffs0, CoeffMap0, CoeffMap),
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map.to_assoc_list(CoeffMap, Coeffs).
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:- pred add_var(var::in, float::in,
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map(var, float)::in, map(var, float)::out) is det.
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add_var(Var, Coeff, !Map) :-
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( map.search(!.Map, Var, Acc0) ->
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Acc1 = Acc0
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;
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Acc1 = 0.0
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),
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Acc = Acc1 + Coeff,
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svmap.set(Var, Acc, !Map).
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:- pred expand_urs_vars_e(equation::in, map(var, pair(var))::in,
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equation::out) is det.
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expand_urs_vars_e(eqn(Coeffs0, Op, Const), Vars, eqn(Coeffs, Op, Const)) :-
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expand_urs_vars(Coeffs0, Vars, Coeffs).
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:- pred expand_urs_vars(list(coeff)::in, map(var, pair(var))::in,
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list(coeff)::out) is det.
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expand_urs_vars(Coeffs0, Vars, Coeffs) :-
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expand_urs_vars(Coeffs0, Vars, [], Coeffs1),
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list.reverse(Coeffs1, Coeffs).
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:- pred expand_urs_vars(list(coeff)::in, map(var, pair(var))::in,
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list(coeff)::in, list(coeff)::out) is det.
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expand_urs_vars([], _Vars, !Coeffs).
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expand_urs_vars([Var - Coeff | Rest], Vars, !Coeffs) :-
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( map.search(Vars, Var, PVar - NVar) ->
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NCoeff = -Coeff,
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!:Coeffs = [NVar - NCoeff, PVar - Coeff | !.Coeffs]
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;
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!:Coeffs = [Var - Coeff | !.Coeffs]
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),
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expand_urs_vars(Rest, Vars, !Coeffs).
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%-----------------------------------------------------------------------------%
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:- pred collect_vars(equations::in, objective::in, set(var)::out) is det.
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collect_vars(Eqns, Obj, Vars) :-
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GetVar = (pred(Var::out) is nondet :-
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(
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list.member(Eqn, Eqns),
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Eqn = eqn(Coeffs, _, _),
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list.member(Pair, Coeffs),
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Pair = Var - _
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;
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list.member(Pair, Obj),
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Pair = Var - _
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)
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),
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solutions.solutions(GetVar, VarList),
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set.list_to_set(VarList, Vars).
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|
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:- pred number_vars(list(var)::in, int::in,
|
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map(var, int)::in, map(var, int)::out) is det.
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|
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number_vars([], _, !VarNums).
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number_vars([Var | Vars], N, !VarNums) :-
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svmap.det_insert(Var, N, !VarNums),
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number_vars(Vars, N + 1, !VarNums).
|
|
|
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:- pred insert_equations(equations::in, int::in, int::in, map(var, int)::in,
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tableau::in, tableau::out) is det.
|
|
|
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insert_equations([], _, _, _, !Tableau).
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insert_equations([Eqn | Eqns], Row, ConstCol, VarNums, !Tableau) :-
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Eqn = eqn(Coeffs, _Op, Const),
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insert_coeffs(Coeffs, Row, VarNums, !Tableau),
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set_index(Row, ConstCol, Const, !Tableau),
|
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insert_equations(Eqns, Row + 1, ConstCol, VarNums, !Tableau).
|
|
|
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:- pred insert_coeffs(list(coeff)::in, int::in, map(var, int)::in,
|
|
tableau::in, tableau::out) is det.
|
|
|
|
insert_coeffs([], _Row, _VarNums, !Tableau).
|
|
insert_coeffs([Coeff|Coeffs], Row, VarNums, !Tableau) :-
|
|
Coeff = Var - Const,
|
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map.lookup(VarNums, Var, Col),
|
|
set_index(Row, Col, Const, !Tableau),
|
|
insert_coeffs(Coeffs, Row, VarNums, !Tableau).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
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:- pred optimize(list(var)::in, tableau::in, tableau::out, lp.result::out)
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|
is det.
|
|
|
|
optimize(ObjVars, A0, A, Result) :-
|
|
simplex(A0, A, Res0),
|
|
(
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Res0 = no,
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Result = unsatisfiable
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|
;
|
|
Res0 = yes,
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rhs_col(A, M),
|
|
index(A, 0, M, ObjVal),
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extract_objective(ObjVars, A, ObjMap),
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|
Result = satisfiable(ObjVal, ObjMap)
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|
).
|
|
|
|
:- pred extract_objective(list(var)::in, tableau::in,
|
|
map(var, float)::out) is det.
|
|
|
|
extract_objective(ObjVars, Tab, Res) :-
|
|
list.foldl(extract_obj_var(Tab), ObjVars, map.init, Res).
|
|
|
|
:- pred extract_obj_var(tableau::in, var::in,
|
|
map(var, float)::in, map(var, float)::out) is det.
|
|
|
|
extract_obj_var(Tab, Var, !Map) :-
|
|
urs_vars(Tab, Vars),
|
|
( map.search(Vars, Var, Pos - Neg) ->
|
|
extract_obj_var2(Tab, Pos, PosVal),
|
|
extract_obj_var2(Tab, Neg, NegVal),
|
|
Val = PosVal - NegVal
|
|
;
|
|
extract_obj_var2(Tab, Var, Val)
|
|
),
|
|
svmap.set(Var, Val, !Map).
|
|
|
|
:- pred extract_obj_var2(tableau::in, var::in, float::out) is det.
|
|
|
|
extract_obj_var2(Tab, Var, Val) :-
|
|
var_col(Tab, Var, Col),
|
|
GetCell = (pred(Val0::out) is nondet :-
|
|
all_rows(Tab, Row),
|
|
index(Tab, Row, Col, 1.0),
|
|
rhs_col(Tab, RHS),
|
|
index(Tab, Row, RHS, Val0)
|
|
),
|
|
solutions.solutions(GetCell, Solns),
|
|
( Solns = [Val1] ->
|
|
Val = Val1
|
|
;
|
|
Val = 0.0
|
|
).
|
|
|
|
:- pred simplex(tableau::in, tableau::out, bool::out) is det.
|
|
|
|
simplex(A0, A, Result) :-
|
|
AllColumns = all_cols(A0),
|
|
MinAgg = (pred(Col::in, Min0::in, Min::out) is det :-
|
|
(
|
|
Min0 = no,
|
|
index(A0, 0, Col, MinVal),
|
|
( MinVal < 0.0 ->
|
|
Min = yes(Col - MinVal)
|
|
;
|
|
Min = no
|
|
)
|
|
;
|
|
Min0 = yes(_ - MinVal0),
|
|
index(A0, 0, Col, CellVal),
|
|
( CellVal < MinVal0 ->
|
|
Min = yes(Col - CellVal)
|
|
;
|
|
Min = Min0
|
|
)
|
|
)
|
|
),
|
|
solutions.aggregate(AllColumns, MinAgg, no, MinResult),
|
|
(
|
|
MinResult = no,
|
|
A = A0,
|
|
Result = yes
|
|
;
|
|
MinResult = yes(Q - _Val),
|
|
AllRows = all_rows(A0),
|
|
MaxAgg = (pred(Row::in, Max0::in, Max::out) is det :-
|
|
(
|
|
Max0 = no,
|
|
index(A0, Row, Q, MaxVal),
|
|
( MaxVal > 0.0 ->
|
|
rhs_col(A0, RHSC),
|
|
index(A0, Row, RHSC, MVal),
|
|
CVal = MVal/MaxVal,
|
|
Max = yes(Row - CVal)
|
|
;
|
|
Max = no
|
|
)
|
|
;
|
|
Max0 = yes(_ - MaxVal0),
|
|
index(A0, Row, Q, CellVal),
|
|
rhs_col(A0, RHSC),
|
|
index(A0, Row, RHSC, MVal),
|
|
(
|
|
CellVal > 0.0,
|
|
MaxVal1 = MVal/CellVal,
|
|
MaxVal1 =< MaxVal0
|
|
->
|
|
Max = yes(Row - MaxVal1)
|
|
;
|
|
Max = Max0
|
|
)
|
|
)
|
|
),
|
|
solutions.aggregate(AllRows, MaxAgg, no, MaxResult),
|
|
(
|
|
MaxResult = no,
|
|
A = A0,
|
|
Result = no
|
|
;
|
|
MaxResult = yes(P - _),
|
|
pivot(P, Q, A0, A1),
|
|
simplex(A1, A, Result)
|
|
)
|
|
).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
|
:- pred ensure_zero_obj_coeffs(list(var)::in, tableau::in, tableau::out)
|
|
is det.
|
|
|
|
ensure_zero_obj_coeffs([], !Tableau).
|
|
ensure_zero_obj_coeffs([V | Vs], !Tableau) :-
|
|
var_col(!.Tableau, V, Col),
|
|
index(!.Tableau, 0, Col, Val),
|
|
( Val = 0.0 ->
|
|
ensure_zero_obj_coeffs(Vs, !Tableau)
|
|
;
|
|
FindOne = (pred(P::out) is nondet :-
|
|
all_rows(!.Tableau, R),
|
|
index(!.Tableau, R, Col, ValF0),
|
|
ValF0 \= 0.0,
|
|
P = R - ValF0
|
|
),
|
|
solutions.solutions(FindOne, Ones),
|
|
(
|
|
Ones = [Row - Fac0|_],
|
|
Fac = -Val/Fac0,
|
|
row_op(Fac, Row, 0, !Tableau),
|
|
ensure_zero_obj_coeffs(Vs, !Tableau)
|
|
;
|
|
Ones = [],
|
|
unexpected(this_file, "problem with artificial variable")
|
|
)
|
|
).
|
|
|
|
:- pred fix_basis_and_rem_cols(list(var)::in, tableau::in, tableau::out)
|
|
is det.
|
|
|
|
fix_basis_and_rem_cols([], !Tableau).
|
|
fix_basis_and_rem_cols([V | Vs], !Tableau) :-
|
|
var_col(!.Tableau, V, Col),
|
|
BasisAgg = (pred(R::in, Ones0::in, Ones::out) is det :-
|
|
index(!.Tableau, R, Col, Val),
|
|
( Val = 0.0 ->
|
|
Ones = Ones0
|
|
;
|
|
Ones = [Val - R|Ones0]
|
|
)
|
|
),
|
|
solutions.aggregate(all_rows(!.Tableau), BasisAgg, [], Res),
|
|
(
|
|
Res = [1.0 - Row]
|
|
->
|
|
PivGoal = (pred(Col1::out) is nondet :-
|
|
all_cols(!.Tableau, Col1),
|
|
Col \= Col1,
|
|
index(!.Tableau, Row, Col1, Zz),
|
|
Zz \= 0.0
|
|
),
|
|
solutions.solutions(PivGoal, PivSolns),
|
|
(
|
|
PivSolns = [],
|
|
remove_col(Col, !Tableau),
|
|
remove_row(Row, !Tableau)
|
|
;
|
|
PivSolns = [Col2|_],
|
|
pivot(Row, Col2, !Tableau),
|
|
remove_col(Col, !Tableau)
|
|
)
|
|
;
|
|
true
|
|
),
|
|
remove_col(Col, !Tableau),
|
|
fix_basis_and_rem_cols(Vs, !Tableau).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
|
:- type cell ---> cell(int, int).
|
|
|
|
:- pred pivot(int::in, int::in, tableau::in, tableau::out) is det.
|
|
|
|
pivot(P, Q, !Tableau) :-
|
|
index(!.Tableau, P, Q, Apq),
|
|
MostCells = (pred(Cell::out) is nondet :-
|
|
all_rows0(!.Tableau, J),
|
|
J \= P,
|
|
all_cols0(!.Tableau, K),
|
|
K \= Q,
|
|
Cell = cell(J, K)
|
|
),
|
|
ScaleCell = (pred(Cell::in, !.T::in, !:T::out) is det :-
|
|
Cell = cell(J, K),
|
|
index(!.T, J, K, Ajk),
|
|
index(!.T, J, Q, Ajq),
|
|
index(!.T, P, K, Apk),
|
|
NewAjk = Ajk - Apk * Ajq / Apq,
|
|
set_index(J, K, NewAjk, !T)
|
|
),
|
|
solutions.aggregate(MostCells, ScaleCell, !Tableau),
|
|
QColumn = (pred(Cell::out) is nondet :-
|
|
all_rows0(!.Tableau, J),
|
|
Cell = cell(J, Q)
|
|
),
|
|
Zero = (pred(Cell::in, T0::in, T::out) is det :-
|
|
Cell = cell(J, K),
|
|
set_index(J, K, 0.0, T0, T)
|
|
),
|
|
solutions.aggregate(QColumn, Zero, !Tableau),
|
|
PRow = all_cols0(!.Tableau),
|
|
ScaleRow = (pred(K::in, T0::in, T::out) is det :-
|
|
index(T0, P, K, Apk),
|
|
NewApk = Apk / Apq,
|
|
set_index(P, K, NewApk, T0, T)
|
|
),
|
|
solutions.aggregate(PRow, ScaleRow, !Tableau),
|
|
set_index(P, Q, 1.0, !Tableau).
|
|
|
|
:- pred row_op(float::in, int::in, int::in,
|
|
tableau::in, tableau::out) is det.
|
|
|
|
row_op(Scale, From, To, !Tableau) :-
|
|
AllCols = all_cols0(!.Tableau),
|
|
AddRow = (pred(Col::in, !.Tableau::in, !:Tableau::out) is det :-
|
|
index(!.Tableau, From, Col, X),
|
|
index(!.Tableau, To, Col, Y),
|
|
Z = Y + (Scale * X),
|
|
set_index(To, Col, Z, !Tableau)
|
|
),
|
|
solutions.aggregate(AllCols, AddRow, !Tableau).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
|
:- type tableau
|
|
---> tableau(
|
|
rows :: int,
|
|
cols :: int,
|
|
var_nums :: map(var, int),
|
|
urs_vars :: map(var, pair(var)),
|
|
shunned_rows :: list(int),
|
|
shunned_cols :: list(int),
|
|
cells :: map(pair(int), float)
|
|
).
|
|
|
|
:- pred init_tableau(int::in, int::in, map(var, int)::in,
|
|
map(var, pair(var))::in, tableau::out) is det.
|
|
|
|
init_tableau(Rows, Cols, VarNums, URSVars, Tableau) :-
|
|
map.init(Cells),
|
|
Tableau = tableau(Rows, Cols, VarNums, URSVars, [], [], Cells).
|
|
|
|
:- pred index(tableau::in, int::in, int::in, float::out) is det.
|
|
|
|
index(Tableau, J, K, R) :-
|
|
Tableau = tableau(_, _, _, _, SR, SC, Cells),
|
|
(
|
|
(list.member(J, SR) ; list.member(K, SC))
|
|
->
|
|
unexpected(this_file, "index: attempt to address shunned row/col")
|
|
;
|
|
true
|
|
),
|
|
(
|
|
map.search(Cells, J - K, R0)
|
|
->
|
|
R = R0
|
|
;
|
|
R = 0.0
|
|
).
|
|
|
|
:- pred set_index(int::in, int::in, float::in,
|
|
tableau::in, tableau::out) is det.
|
|
|
|
set_index(J, K, R, !Tableau) :-
|
|
!.Tableau = tableau(Rows, Cols, VarNums, URS, SR, SC, Cells0),
|
|
(
|
|
(list.member(J, SR) ; list.member(K, SC))
|
|
->
|
|
unexpected(this_file, "set_index: attempt to write shunned row/col")
|
|
;
|
|
true
|
|
),
|
|
( R = 0.0 ->
|
|
map.delete(Cells0, J - K, Cells)
|
|
;
|
|
map.set(Cells0, J - K, R, Cells)
|
|
),
|
|
!:Tableau = tableau(Rows, Cols, VarNums, URS, SR, SC, Cells).
|
|
|
|
:- pred rhs_col(tableau::in, int::out) is det.
|
|
|
|
rhs_col(tableau(_, RHS, _, _, _, _, _), RHS).
|
|
|
|
:- pred all_rows0(tableau::in, int::out) is nondet.
|
|
|
|
all_rows0(Tableau, Row) :-
|
|
Tableau = tableau(Rows, _Cols, _, _, SR, _, _),
|
|
between(0, Rows, Row),
|
|
\+ list.member(Row, SR).
|
|
|
|
:- pred all_rows(tableau::in, int::out) is nondet.
|
|
|
|
all_rows(Tableau, Row) :-
|
|
Tableau = tableau(Rows, _Cols, _, _, SR, _, _),
|
|
between(1, Rows, Row),
|
|
\+ list.member(Row, SR).
|
|
|
|
:- pred all_cols0(tableau::in, int::out) is nondet.
|
|
|
|
all_cols0(Tableau, Col) :-
|
|
Tableau = tableau(_Rows, Cols, _, _, _, SC, _),
|
|
between(0, Cols, Col),
|
|
\+ list.member(Col, SC).
|
|
|
|
:- pred all_cols(tableau::in, int::out) is nondet.
|
|
|
|
all_cols(Tableau, Col) :-
|
|
Tableau = tableau(_Rows, Cols, _, _, _, SC, _),
|
|
Cols1 = Cols - 1,
|
|
between(0, Cols1, Col),
|
|
\+ list.member(Col, SC).
|
|
|
|
:- pred var_col(tableau::in, var::in, int::out) is det.
|
|
|
|
var_col(Tableau, Var, Col) :-
|
|
Tableau = tableau(_, _, VarCols, _, _, _, _),
|
|
map.lookup(VarCols, Var, Col).
|
|
|
|
:- pred urs_vars(tableau::in, map(var, pair(var))::out) is det.
|
|
|
|
urs_vars(Tableau, Tableau ^ urs_vars).
|
|
|
|
:- pred remove_row(int::in, tableau::in, tableau::out) is det.
|
|
|
|
remove_row(R, Tableau0, Tableau) :-
|
|
Tableau0 = tableau(Rows, Cols, VarNums, URS, SR, SC, Cells),
|
|
Tableau = tableau(Rows, Cols, VarNums, URS, [R|SR], SC, Cells).
|
|
|
|
:- pred remove_col(int::in, tableau::in, tableau::out) is det.
|
|
|
|
remove_col(C, Tableau0, Tableau) :-
|
|
Tableau0 = tableau(Rows, Cols, VarNums, URS, SR, SC, Cells),
|
|
Tableau = tableau(Rows, Cols, VarNums, URS, SR, [C|SC], Cells).
|
|
|
|
:- pred get_basis_vars(tableau::in, list(var)::out) is det.
|
|
|
|
get_basis_vars(Tab, Vars) :-
|
|
BasisCol = (pred(C::out) is nondet :-
|
|
all_cols(Tab, C),
|
|
NonZeroGoal = (pred(P::out) is nondet :-
|
|
all_rows(Tab, R),
|
|
index(Tab, R, C, Z),
|
|
Z \= 0.0,
|
|
P = R - Z
|
|
),
|
|
solutions.solutions(NonZeroGoal, Solns),
|
|
Solns = [_ - 1.0]
|
|
),
|
|
solutions.solutions(BasisCol, Cols),
|
|
BasisVars = (pred(V::out) is nondet :-
|
|
list.member(Col, Cols),
|
|
Tab = tableau(_, _, VarCols, _, _, _, _),
|
|
map.member(VarCols, V, Col)
|
|
),
|
|
solutions.solutions(BasisVars, Vars).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
|
:- pred lp_info_init(varset::in, list(var)::in, lp_info::out) is det.
|
|
|
|
lp_info_init(Varset0, URSVars, LPInfo) :-
|
|
Introduce = (pred(Orig::in, VP0::in, VP::out) is det :-
|
|
VP0 = VS0 - VM0,
|
|
varset.new_var(VS0, V1, VS1),
|
|
varset.new_var(VS1, V2, VS),
|
|
map.set(VM0, Orig, V1 - V2, VM),
|
|
VP = VS - VM
|
|
),
|
|
map.init(URSMap0),
|
|
list.foldl(Introduce, URSVars, Varset0 - URSMap0, Varset - URSMap),
|
|
LPInfo = lp(Varset, URSMap, [], []).
|
|
|
|
:- pred new_slack_var(var::out, lp_info::in, lp_info::out) is det.
|
|
|
|
new_slack_var(Var, !Info) :-
|
|
some [!Varset] (
|
|
get_varset(!:Varset, !Info),
|
|
svvarset.new_var(Var, !Varset),
|
|
set_varset(!.Varset, !Info)
|
|
),
|
|
get_slack_vars(Vars, !Info),
|
|
set_slack_vars([Var | Vars], !Info).
|
|
|
|
:- pred new_art_var(var::out, lp_info::in, lp_info::out) is det.
|
|
|
|
new_art_var(Var, !Info) :-
|
|
some [!Varset] (
|
|
get_varset(!:Varset, !Info),
|
|
svvarset.new_var(Var, !Varset),
|
|
set_varset(!.Varset, !Info)
|
|
),
|
|
get_art_vars(Vars, !Info),
|
|
set_art_vars([Var | Vars], !Info).
|
|
|
|
:- pred get_varset(varset::out, lp_info::in, lp_info::out) is det.
|
|
|
|
get_varset(Varset, Info, Info) :-
|
|
Info = lp(Varset, _URSVars, _Slack, _Art).
|
|
|
|
:- pred set_varset(varset::in, lp_info::in, lp_info::out) is det.
|
|
|
|
set_varset(Varset, Info0, Info) :-
|
|
Info0 = lp(_Varset, URSVars, Slack, Art),
|
|
Info = lp(Varset, URSVars, Slack, Art).
|
|
|
|
:- pred get_urs_vars(map(var, pair(var))::out, lp_info::in, lp_info::out)
|
|
is det.
|
|
|
|
get_urs_vars(URSVars, Info, Info) :-
|
|
Info = lp(_Varset, URSVars, _Slack, _Art).
|
|
|
|
:- pred set_urs_vars(map(var, pair(var))::in, lp_info::in, lp_info::out)
|
|
is det.
|
|
|
|
set_urs_vars(URSVars, Info0, Info) :-
|
|
Info0 = lp(Varset, _URSVars, Slack, Art),
|
|
Info = lp(Varset, URSVars, Slack, Art).
|
|
|
|
:- pred get_slack_vars(list(var)::out, lp_info::in, lp_info::out) is det.
|
|
|
|
get_slack_vars(Slack, Info, Info) :-
|
|
Info = lp(_Varset, _URSVars, Slack, _Art).
|
|
|
|
:- pred set_slack_vars(list(var)::in, lp_info::in, lp_info::out) is det.
|
|
|
|
set_slack_vars(Slack, Info0, Info) :-
|
|
Info0 = lp(Varset, URSVars, _Slack, Art),
|
|
Info = lp(Varset, URSVars, Slack, Art).
|
|
|
|
:- pred get_art_vars(list(var)::out, lp_info::in, lp_info::out) is det.
|
|
|
|
get_art_vars(Art, Info, Info) :-
|
|
Info = lp(_Varset, _URSVars, _Slack, Art).
|
|
|
|
:- pred set_art_vars(list(var)::in, lp_info::in, lp_info::out) is det.
|
|
|
|
set_art_vars(Art, Info0, Info) :-
|
|
Info0 = lp(Varset, URSVars, Slack, _Art),
|
|
Info = lp(Varset, URSVars, Slack, Art).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
|
|
:- pred between(int::in, int::in, int::out) is nondet.
|
|
|
|
between(Min, Max, I) :-
|
|
Min =< Max,
|
|
(
|
|
I = Min
|
|
;
|
|
Min1 = Min + 1,
|
|
between(Min1, Max, I)
|
|
).
|
|
|
|
%-----------------------------------------------------------------------------%
|
|
%
|
|
% Debugging predicates.
|
|
%
|
|
|
|
:- pred show_tableau(tableau::in, io::di, io::uo) is det.
|
|
|
|
show_tableau(Tableau, !IO) :-
|
|
Tableau = tableau(N, M, _, _, _, _, _),
|
|
io.format("Tableau (%d, %d):\n", [i(N), i(M)], !IO),
|
|
solutions.aggregate(all_rows0(Tableau), show_row(Tableau), !IO).
|
|
|
|
:- pred show_row(tableau::in, int::in, io::di, io::uo) is det.
|
|
|
|
show_row(Tableau, Row, !IO) :-
|
|
solutions.aggregate(all_cols0(Tableau), show_cell(Tableau, Row), !IO),
|
|
io.nl(!IO).
|
|
|
|
:- pred show_cell(tableau::in, int::in, int::in, io::di, io::uo) is det.
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show_cell(Tableau, Row, Col, !IO) :-
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index(Tableau, Row, Col, Val),
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io.format("%2.2f\t", [f(Val)], !IO).
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%-----------------------------------------------------------------------------%
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:- func this_file = string.
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this_file = "lp.m".
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%-----------------------------------------------------------------------------%
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:- end_module lp.
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%-----------------------------------------------------------------------------%
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