547 lines
18 KiB
Prolog
547 lines
18 KiB
Prolog
/* $Id: aggregate.pl,v 1.4 2008-07-22 23:34:49 vsc Exp $
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Part of SWI-Prolog
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Author: Jan Wielemaker
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E-mail: wielemak@science.uva.nl
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WWW: http://www.swi-prolog.org
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Copyright (C): 2008, University of Amsterdam
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License
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as published by the Free Software Foundation; either version 2
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of the License, or (at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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As a special exception, if you link this library with other files,
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compiled with a Free Software compiler, to produce an executable, this
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library does not by itself cause the resulting executable to be covered
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by the GNU General Public License. This exception does not however
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invalidate any other reasons why the executable file might be covered by
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the GNU General Public License.
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*/
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:- module(aggregate,
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[ foreach/2, % :Generator, :Goal
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aggregate/3, % +Templ, :Goal, -Result
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aggregate/4, % +Templ, +Discrim, :Goal, -Result
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aggregate_all/3, % +Templ, :Goal, -Result
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aggregate_all/4, % +Templ, +Discrim, :Goal, -Result
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free_variables/4 % :Generator, :Template, +Vars0, -Vars
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]).
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:- use_module(library(ordsets)).
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:- use_module(library(maplist)).
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:- use_module(library(pairs)).
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:- use_module(library(error)).
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:- use_module(library(lists)).
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:- meta_predicate
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foreach(0,0),
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aggregate(?,0,-),
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aggregate(?,?,0,-),
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aggregate_all(?,0,-),
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aggregate_all(?,?,0,-).
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/** <module> Aggregation operators on backtrackable predicates
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@ingroup SWILibrary
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This library provides aggregating operators over the solutions of a
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predicate. The operations are a generalisation of the bagof/3, setof/3
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and findall/3 built-in predicates. The defined aggregation operations
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are counting, computing the sum, minimum, maximum, a bag of solutions
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and a set of solutions. We first give a simple example, computing the
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country with the smallest area:
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==
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average_country_area(Name, Area) :-
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aggregate(min(A, N), country(N, A), min(Area, Name)).
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==
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There are four aggregation predicates, distinguished on two properties.
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$ aggregate vs. aggregate_all :
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The aggregate predicates use setof/3 (aggregate/4) or bagof/3
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(aggregate/3), dealing with existential qualified variables
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(Var^Goal) and providing multiple solutions for the remaining free
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variables in Goal. The aggregate_all/3 predicate uses findall/3,
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implicitely qualifying all free variables and providing exactly one
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solution, while aggregate_all/4 uses sort/2 over solutions and
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Distinguish (see below) generated using findall/3.
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$ The Distinguish argument :
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The versions with 4 arguments provide a Distinguish argument that
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allow for keeping duplicate bindings of a variable in the result.
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For example, if we wish to compute the total population of all
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countries we do not want to loose results because two countries
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have the same population. Therefore we use:
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==
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aggregate(sum(P), Name, country(Name, P), Total)
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==
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All aggregation predicates support the following operator below in
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Template. In addition, they allow for an arbitrary named compound term
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where each of the arguments is a term from the list below. I.e. the term
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r(min(X), max(X)) computes both the minimum and maximum binding for X.
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* count
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Count number of solutions. Same as sum(1).
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* sum(Expr)
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Sum of Expr for all solutions.
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* min(Expr)
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Minimum of Expr for all solutions.
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* min(Expr, Witness)
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A term min(Min, Witness), where Min is the minimal version
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of Expr over all Solution and Witness is any other template
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the applied to the solution that produced Min. If multiple
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solutions provide the same minimum, Witness corresponds to
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the first solution.
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* max(Expr)
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Maximum of Expr for all solutions.
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* max(Expr, Witness)
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As min(Expr, Witness), but producing the maximum result.
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* set(X)
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An ordered set with all solutions for X.
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* bag(X)
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A list of all solutions for X.
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---+++ Acknowledgements
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_|The development of this library was sponsored by SecuritEase,
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http://www.securitease.com
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@compat Quintus, SICStus 4. The forall/2 is a SWI-Prolog built-in and
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term_variables/3 is a SWI-Prolog with a *|different definition|*.
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@tbd Analysing the aggregation template and compiling a predicate
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for the list aggregation can be done at compile time.
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@tbd aggregate_all/3 can be rewritten to run in constant space using
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non-backtrackable assignment on a term.
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*/
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/*******************************
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* AGGREGATE *
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*******************************/
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%% aggregate(+Template, :Goal, -Result) is nondet.
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%
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% Aggregate bindings in Goal according to Template. The aggregate/3
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% version performs bagof/3 on Goal.
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aggregate(Template, Goal0, Result) :-
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template_to_pattern(bag, Template, Pattern, Goal0, Goal, Aggregate),
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bagof(Pattern, Goal, List),
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aggregate_list(Aggregate, List, Result).
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%% aggregate(+Template, +Discriminator, :Goal, -Result) is nondet.
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%
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% Aggregate bindings in Goal according to Template. The aggregate/3
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% version performs setof/3 on Goal.
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aggregate(Template, Discriminator, Goal0, Result) :-
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template_to_pattern(bag, Template, Pattern, Goal0, Goal, Aggregate),
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setof(Discriminator-Pattern, Goal, Pairs),
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pairs_values(Pairs, List),
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aggregate_list(Aggregate, List, Result).
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%% aggregate_all(+Template, :Goal, -Result) is semidet.
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%
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% Aggregate bindings in Goal according to Template. The aggregate_all/3
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% version performs findall/3 on Goal.
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aggregate_all(Template, Goal0, Result) :-
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template_to_pattern(all, Template, Pattern, Goal0, Goal, Aggregate),
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findall(Pattern, Goal, List),
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aggregate_list(Aggregate, List, Result).
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%% aggregate_all(+Template, +Discriminator, :Goal, -Result) is semidet.
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%
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% Aggregate bindings in Goal according to Template. The aggregate_all/3
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% version performs findall/3 followed by sort/2 on Goal.
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aggregate_all(Template, Discriminator, Goal0, Result) :-
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template_to_pattern(all, Template, Pattern, Goal0, Goal, Aggregate),
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findall(Discriminator-Pattern, Goal, Pairs0),
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sort(Pairs0, Pairs),
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pairs_values(Pairs, List),
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aggregate_list(Aggregate, List, Result).
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template_to_pattern(_All, Template, Pattern, Goal0, Goal, Aggregate) :-
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template_to_pattern(Template, Pattern, Post, Vars, Aggregate),
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existential_vars(Goal0, Goal1, AllVars, Vars),
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clean_body((Goal1, Post), Goal2),
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add_existential_vars(AllVars, Goal2, Goal).
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existential_vars(Var, Var) -->
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{ var(Var) }, !.
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existential_vars(Var^G0, G) --> !,
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[Var],
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existential_vars(G0, G).
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existential_vars(G, G) -->
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[].
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add_existential_vars([], G, G).
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add_existential_vars([H|T], G0, H^G1) :-
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add_existential_vars(T, G0, G1).
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%% clean_body(+Goal0, -Goal) is det.
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%
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% Remove redundant =true= from Goal0.
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clean_body((Goal0,Goal1), Goal) :- !,
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clean_body(Goal0, GoalA),
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clean_body(Goal1, GoalB),
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( GoalA == true
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-> Goal = GoalB
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; GoalB == true
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-> Goal = GoalA
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; Goal = (GoalA,GoalB)
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).
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clean_body(Goal, Goal).
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%% template_to_pattern(+Template, -Pattern, -Post, -Vars, -Agregate)
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%
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% Determine which parts of the goal we must remember in the
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% findall/3 pattern.
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%
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% @param Post is a body-term that evaluates expressions to reduce
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% storage requirements.
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% @param Vars is a list of intermediate variables that must be
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% added to the existential variables for bagof/3.
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% @param Agregate defines the aggregation operation to execute.
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template_to_pattern(sum(X), X, true, [], sum) :- var(X), !.
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template_to_pattern(sum(X0), X, X is X0, [X0], sum) :- !.
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template_to_pattern(count, 1, true, [], count) :- !.
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template_to_pattern(min(X), X, true, [], min) :- var(X), !.
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template_to_pattern(min(X0), X, X is X0, [X0], min) :- !.
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template_to_pattern(min(X0, Witness), X-Witness, X is X0, [X0], min_witness) :- !.
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template_to_pattern(max(X0), X, X is X0, [X0], max) :- !.
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template_to_pattern(max(X0, Witness), X-Witness, X is X0, [X0], max_witness) :- !.
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template_to_pattern(set(X), X, true, [], set) :- !.
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template_to_pattern(bag(X), X, true, [], bag) :- !.
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template_to_pattern(Term, Pattern, Goal, Vars, term(MinNeeded, Functor, AggregateArgs)) :-
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compound(Term), !,
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Term =.. [Functor|Args0],
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templates_to_patterns(Args0, Args, Goal, Vars, AggregateArgs),
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needs_one(AggregateArgs, MinNeeded),
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Pattern =.. [Functor|Args].
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template_to_pattern(Term, _, _, _, _) :-
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type_error(aggregate_template, Term).
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templates_to_patterns([], [], true, [], []).
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templates_to_patterns([H0], [H], G, Vars, [A]) :- !,
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template_to_pattern(H0, H, G, Vars, A).
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templates_to_patterns([H0|T0], [H|T], (G0,G), Vars, [A0|A]) :-
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template_to_pattern(H0, H, G0, V0, A0),
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append(V0, RV, Vars),
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templates_to_patterns(T0, T, G, RV, A).
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%% needs_one(+Ops, -OneOrZero)
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%
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% If one of the operations in Ops needs at least one answer,
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% unify OneOrZero to 1. Else 0.
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needs_one(Ops, 1) :-
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member(Op, Ops),
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needs_one(Op), !.
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needs_one(_, 0).
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needs_one(min).
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needs_one(min_witness).
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needs_one(max).
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needs_one(max_witness).
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%% aggregate_list(+Op, +List, -Answer) is semidet.
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%
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% Aggregate the answer from the list produced by findall/3,
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% bagof/3 or setof/3. The latter two cases deal with compound
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% answers.
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%
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% @tbd Compile code for incremental state update, which we will use
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% for aggregate_all/3 as well. We should be using goal_expansion
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% to generate these clauses.
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aggregate_list(bag, List0, List) :- !,
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List = List0.
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aggregate_list(set, List, Set) :- !,
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sort(List, Set).
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aggregate_list(sum, List, Sum) :-
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sumlist(List, Sum).
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aggregate_list(count, List, Count) :-
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length(List, Count).
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aggregate_list(max, List, Sum) :-
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max_list(List, Sum).
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aggregate_list(max_witness, List, max(Max, Witness)) :-
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max_pair(List, Max, Witness).
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aggregate_list(min, List, Sum) :-
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min_list(List, Sum).
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aggregate_list(min_witness, List, min(Min, Witness)) :-
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min_pair(List, Min, Witness).
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aggregate_list(term(0, Functor, Ops), List, Result) :- !,
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maplist(state0, Ops, StateArgs, FinishArgs),
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State0 =.. [Functor|StateArgs],
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aggregate_term_list(List, Ops, State0, Result0),
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finish_result(Ops, FinishArgs, Result0, Result).
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aggregate_list(term(1, Functor, Ops), [H|List], Result) :-
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H =.. [Functor|Args],
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maplist(state1, Ops, Args, StateArgs, FinishArgs),
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State0 =.. [Functor|StateArgs],
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aggregate_term_list(List, Ops, State0, Result0),
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finish_result(Ops, FinishArgs, Result0, Result).
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aggregate_term_list([], _, State, State).
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aggregate_term_list([H|T], Ops, State0, State) :-
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step_term(Ops, H, State0, State1),
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aggregate_term_list(T, Ops, State1, State).
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%% min_pair(+Pairs, -Key, -Value) is det.
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%% max_pair(+Pairs, -Key, -Value) is det.
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%
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% True if Key-Value has the smallest/largest key in Pairs. If
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% multiple pairs share the smallest/largest key, the first pair is
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% returned.
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min_pair([M0-W0|T], M, W) :-
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min_pair(T, M0, W0, M, W).
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min_pair([], M, W, M, W).
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min_pair([M0-W0|T], M1, W1, M, W) :-
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( M0 > M1
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-> min_pair(T, M0, W0, M, W)
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; min_pair(T, M1, W1, M, W)
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).
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max_pair([M0-W0|T], M, W) :-
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max_pair(T, M0, W0, M, W).
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max_pair([], M, W, M, W).
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max_pair([M0-W0|T], M1, W1, M, W) :-
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( M0 > M1
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-> max_pair(T, M0, W0, M, W)
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; max_pair(T, M1, W1, M, W)
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).
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%% step(+AggregateAction, +New, +State0, -State1).
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step(bag, X, [X|L], L).
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step(set, X, [X|L], L).
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step(count, _, X0, X1) :-
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succ(X0, X1).
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step(sum, X, X0, X1) :-
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X1 is X0+X.
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step(max, X, X0, X1) :-
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X1 is max(X0, X).
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step(min, X, X0, X1) :-
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X1 is min(X0, X).
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step(max_witness, X-W, X0-W0, X1-W1) :-
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( X > X0
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-> X1 = X, W1 = W
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; X1 = X0, W1 = W0
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).
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step(min_witness, X-W, X0-W0, X1-W1) :-
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( X < X0
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-> X1 = X, W1 = W
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; X1 = X0, W1 = W0
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).
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step(term(Ops), Row, Row0, Row1) :-
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step_term(Ops, Row, Row0, Row1).
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step_term(Ops, Row, Row0, Row1) :-
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functor(Row, Name, Arity),
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functor(Row1, Name, Arity),
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step_list(Ops, 1, Row, Row0, Row1).
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step_list([], _, _, _, _).
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step_list([Op|OpT], Arg, Row, Row0, Row1) :-
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arg(Arg, Row, X),
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arg(Arg, Row0, X0),
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arg(Arg, Row1, X1),
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step(Op, X, X0, X1),
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succ(Arg, Arg1),
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step_list(OpT, Arg1, Row, Row0, Row1).
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finish_result(Ops, Finish, R0, R) :-
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functor(R0, Functor, Arity),
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functor(R, Functor, Arity),
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finish_result(Ops, Finish, 1, R0, R).
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finish_result([], _, _, _, _).
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finish_result([Op|OpT], [F|FT], I, R0, R) :-
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arg(I, R0, A0),
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arg(I, R, A),
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finish_result1(Op, F, A0, A),
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succ(I, I2),
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finish_result(OpT, FT, I2, R0, R).
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finish_result1(bag, Bag0, [], Bag) :- !,
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Bag = Bag0.
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finish_result1(set, Bag, [], Set) :- !,
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sort(Bag, Set).
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finish_result1(max_witness, _, M-W, R) :- !,
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R = max(M,W).
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finish_result1(min_witness, _, M-W, R) :- !,
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R = min(M,W).
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finish_result1(_, _, A, A).
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%% state0(+Op, -State, -Finish)
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state0(bag, L, L).
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state0(set, L, L).
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state0(count, 0, _).
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state0(sum, 0, _).
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%% state1(+Op, +First, -State, -Finish)
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state1(bag, X, [X|L], L).
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state1(set, X, [X|L], L).
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state1(_, X, X, _).
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/*******************************
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* FOREACH *
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*******************************/
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%% foreach(:Generator, :Goal)
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%
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% True if the conjunction of instances of Goal using the bindings
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% from Generator is true. Unlike forall/2, which runs a
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% failure-driven loop that proves Goal for each solution of
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% Generator, foreach creates a conjunction. Each member of the
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% conjunction is a copy of Goal, where the variables it shares
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% with Generator are filled with the values from the corresponding
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% solution.
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%
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% The implementation executes forall/2 if Goal does not contain
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% any variables that are not shared with Generator.
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%
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% Here is an example:
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%
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% ==
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% ?- foreach(between(1,4,X), dif(X,Y)), Y = 5.
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% Y = 5
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% ?- foreach(between(1,4,X), dif(X,Y)), Y = 3.
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% No
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% ==
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%
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% @bug Goal is copied repeatetly, which may cause problems if
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% attributed variables are involved.
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foreach(Generator, Goal0) :-
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strip_module(Goal0, M, G),
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Goal = M:G,
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term_variables(Generator, GenVars0), sort(GenVars0, GenVars),
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term_variables(Goal, GoalVars0), sort(GoalVars0, GoalVars),
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ord_subtract(GoalVars, GenVars, SharedGoalVars),
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( SharedGoalVars == []
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-> \+ (Generator, \+Goal) % = forall(Generator, Goal)
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; ord_intersection(GenVars, GoalVars, SharedVars),
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Templ =.. [v|SharedVars],
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SharedTempl =.. [v|SharedGoalVars],
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findall(Templ, Generator, List),
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prove_list(List, Templ, SharedTempl, Goal)
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|
).
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|
prove_list([], _, _, _).
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prove_list([H|T], Templ, SharedTempl, Goal) :-
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|
copy_term(Templ+SharedTempl+Goal,
|
|
H+SharedTempl+Copy),
|
|
Copy,
|
|
prove_list(T, Templ, SharedTempl, Goal).
|
|
|
|
|
|
%% free_variables(:Generator, +Template, +VarList0, -VarList) is det.
|
|
%
|
|
% In order to handle variables properly, we have to find all the
|
|
% universally quantified variables in the Generator. All variables
|
|
% as yet unbound are universally quantified, unless
|
|
%
|
|
% 1. they occur in the template
|
|
% 2. they are bound by X^P, setof, or bagof
|
|
%
|
|
% free_variables(Generator, Template, OldList, NewList) finds this
|
|
% set, using OldList as an accumulator.
|
|
%
|
|
% @author Richard O'Keefe
|
|
% @author Jan Wielemaker (made some SWI-Prolog enhancements)
|
|
% @license Public domain (from DEC10 library).
|
|
% @tbd Distinguish between control-structures and data terms.
|
|
% @tbd Exploit our built-in term_variables/2 at some places?
|
|
|
|
free_variables(Term, Bound, VarList, [Term|VarList]) :-
|
|
var(Term),
|
|
term_is_free_of(Bound, Term),
|
|
list_is_free_of(VarList, Term), !.
|
|
free_variables(Term, _Bound, VarList, VarList) :-
|
|
var(Term), !.
|
|
free_variables(Term, Bound, OldList, NewList) :-
|
|
explicit_binding(Term, Bound, NewTerm, NewBound), !,
|
|
free_variables(NewTerm, NewBound, OldList, NewList).
|
|
free_variables(Term, Bound, OldList, NewList) :-
|
|
functor(Term, _, N),
|
|
free_variables(N, Term, Bound, OldList, NewList).
|
|
|
|
free_variables(0, _, _, VarList, VarList) :- !.
|
|
free_variables(N, Term, Bound, OldList, NewList) :-
|
|
arg(N, Term, Argument),
|
|
free_variables(Argument, Bound, OldList, MidList),
|
|
M is N-1, !,
|
|
free_variables(M, Term, Bound, MidList, NewList).
|
|
|
|
% explicit_binding checks for goals known to existentially quantify
|
|
% one or more variables. In particular \+ is quite common.
|
|
|
|
explicit_binding(\+ _Goal, Bound, fail, Bound ) :- !.
|
|
explicit_binding(not(_Goal), Bound, fail, Bound ) :- !.
|
|
explicit_binding(Var^Goal, Bound, Goal, Bound+Var) :- !.
|
|
explicit_binding(setof(Var,Goal,Set), Bound, Goal-Set, Bound+Var) :- !.
|
|
explicit_binding(bagof(Var,Goal,Bag), Bound, Goal-Bag, Bound+Var) :- !.
|
|
|
|
%% term_is_free_of(+Term, +Var) is semidet.
|
|
%
|
|
% True if Var does not appear in Term. This has been rewritten
|
|
% from the DEC10 library source to exploit our non-deterministic
|
|
% arg/3.
|
|
|
|
term_is_free_of(Term, Var) :-
|
|
\+ var_in_term(Term, Var).
|
|
|
|
var_in_term(Term, Var) :-
|
|
Var == Term, !.
|
|
var_in_term(Term, Var) :-
|
|
compound(Term),
|
|
genarg(_, Term, Arg),
|
|
var_in_term(Arg, Var), !.
|
|
|
|
|
|
%% list_is_free_of(+List, +Var) is semidet.
|
|
%
|
|
% True if Var is not in List.
|
|
|
|
list_is_free_of([Head|Tail], Var) :-
|
|
Head \== Var, !,
|
|
list_is_free_of(Tail, Var).
|
|
list_is_free_of([], _).
|
|
|
|
|
|
% term_variables(+Term, +Vars0, -Vars) is det.
|
|
%
|
|
% True if Vars is the union of variables in Term and Vars0.
|
|
% We cannot have this as term_variables/3 is already defined
|
|
% as a difference-list version of term_variables/2.
|
|
|
|
%term_variables(Term, Vars0, Vars) :-
|
|
% term_variables(Term+Vars0, Vars).
|