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yap-6.3/packages/cplint/approx/exact.pl

236 lines
6.6 KiB
Prolog

/*==============================================================================
* LPAD and CP-Logic reasoning suite
* File best.pl
* Goal oriented interpreter for LPADs based on SLDNF
* Copyright (c) 2009, Stefano Bragaglia
*============================================================================*/
:- dynamic rule/4, def_rule/2.
/* EXTERNAL FILE
* -------------
* The following libraries are required by the program to work fine.
*/
:- use_module(library(lists)).
:- use_module(library(system)).
:- use_module(library(ugraphs)).
:- use_module(params).
:- use_module(tptree_lpad).
:- use_module(utility).
% :- source.
% :- yap_flag(single_var_warnings, on).
/* SOLVING PREDICATES
* ------------------
* The predicates in this section solve any given problem with several class of
* algorithms.
*
* Note: the original predicates (no more need and eligible to be deleted) have
* been moved to the end of the file.
*/
/* solve(GoalsList, Prob, ResTime, BddTime)
* ----------------------------------------
* This predicate computes the probability of a given list of goals using an
* exact algorithm. It also returns the number of handled BDDs (trivial but
* present for simmetry with other solving predicates), CPUTime spent in
* performing resolution and in handling the BDDs.
*
* INPUT
* - GoalsList: given list of goal to work on.
*
* OUTPUT
* - Prob: the resulting exact probability for the given list of goals.
* - Count: number of BDDs handled by the algorithm (trivial, since it's always 1).
* - ResTime: cpu time spent on performing resolution.
* - BddTime: cpu time spent on handling BDDs.
*/
solve(GoalsList, Prob, ResTime, BddTime) :-
% Resetting the clocks...
statistics(walltime, [_, _]),
% Performing resolution...
findall(Deriv, exact(GoalsList, Deriv), List),
% Taking elapsed times...
statistics(walltime, [_, ElapResTime]),
ResTime is ElapResTime/1000,
% Building and solving equivalent bdds...
init_ptree(1),
fatto(List),
insert_list_ptree(List, 1),
bdd_ptree_map(1, 'bdd.txt', 'bdd.par', 'bdd.map'),
delete_ptree(1),
run_file('bdd.txt','bdd.par', Temp),
(Temp == timeout ->
Prob is -1.0;
Prob is Temp),
% Taking elapsed times
statistics(walltime, [_, ElapBddTime]),
BddTime is ElapBddTime/1000.
/* exact(GoalsList, CIn, COut) takes a list of goals and an input C set
and returns an output C set
The C set is a list of triple (N, R, S) where
- N is the index of the head atom used, starting from 0
- R is the index of the non ground rule used, starting from 1
- S is the substitution of rule R, in the form of a list whose elements
are of the form 'VarName'=value
*/
exact(GoalsList, Deriv) :-
exact(GoalsList, [], Deriv).
exact([], C, C) :- !.
exact([bagof(V, EV^G, L)|T], CIn, COut) :- !,
list2and(GL, G),
bagof((V, C), EV^exact(GL, CIn, C), LD),
length(LD, N),
build_initial_graph(N, GrIn),
build_graph(LD, 0, GrIn, Gr),
clique(Gr, Clique),
build_Cset(LD, Clique, L, [], C1),
remove_duplicates_eq(C1, C2),
exact(T, C2, COut).
exact([bagof(V, G, L)|T], CIn, COut) :- !,
list2and(GL, G),
bagof((V, C), exact(GL, CIn, C), LD),
length(LD, N),
build_initial_graph(N, GrIn),
build_graph(LD, 0, GrIn, Gr),
clique(Gr, Clique),
build_Cset(LD, Clique, L, [], C1),
remove_duplicates_eq(C1, C2),
exact(T, C2, COut).
exact([setof(V, EV^G, L)|T], CIn, COut) :- !,
list2and(GL, G),
setof((V, C), EV^exact(GL, CIn, C), LD),
length(LD, N),
build_initial_graph(N, GrIn),
build_graph(LD, 0, GrIn, Gr),
clique(Gr, Clique),
build_Cset(LD, Clique, L1, [], C1),
remove_duplicates(L1, L),
exact(T, C1, COut).
exact([setof(V, G, L)|T], CIn, COut) :- !,
list2and(GL, G),
setof((V, C), exact(GL, CIn, C), LD),
length(LD, N),
build_initial_graph(N, GrIn),
build_graph(LD, 0, GrIn, Gr),
clique(Gr, Clique),
build_Cset(LD, Clique, L1, [], C1),
remove_duplicates(L1, L),
exact(T, C1, COut).
exact([\+ H|T], CIn, COut) :-
builtin(H), !,
call((\+ H)),
exact(T, CIn, COut).
exact([\+ H |T], CIn, COut) :- !,
list2and(HL, H),
findall(D, find_deriv(HL, D), L),
choose_clauses(CIn, L, C1),
exact(T, C1, COut).
exact([H|T], CIn, COut) :-
builtin(H), !,
call(H),
exact(T, CIn, COut).
exact([H|T], CIn, COut) :-
def_rule(H, B),
append(B, T, NG),
exact(NG, CIn, COut).
exact([H|T], CIn, COut) :-
find_rule(H, (R, S, N), B, CIn),
solve_pres(R, S, N, B, T, CIn, COut).
solve_pres(R, S, N, B, T, CIn, COut) :-
member_eq((N, R, S), CIn), !,
append(B, T, NG),
exact(NG, CIn, COut).
solve_pres(R, S, N, B, T, CIn, COut) :-
append(CIn, [(N, R, S)], C1),
append(B, T, NG),
exact(NG, C1, COut).
/* find_rule(G, (R, S, N), Body, C)
* --------------------------------
* This predicate takes a goal G and the current C set and returns the index R
* of a disjunctive rule resolving with G together with the index N of the
* resolving head, the substitution S and the Body of the rule.
*/
find_rule(H, (R, S, N), Body, C) :-
rule(H, _P, N, R, S, _NH, _Head, Body),
not_already_present_with_a_different_head(N, R, S, C).
/* run_file(BDDFile, BDDParFile, Prob)
* -----------------------------------
* This predicate calls for the resolution of a BDD via file.
*/
run_file(BDDFile, BDDParFile, Prob) :-
ResultFile = 'result.txt',
library_directory(Dir),
setting(timeout, BDDTime),
(BDDTime = no ->
atomic_concat([Dir, '/LPADBDD -l ', BDDFile, ' -i ', BDDParFile,' > ', ResultFile], Command);
atomic_concat([Dir, '/LPADBDD -l ', BDDFile, ' -i ', BDDParFile,' -t ', BDDTime,' > ', ResultFile], Command)),
%statistics(walltime,_),
shell(Command, Return),
(Return =\= 0 ->
Status = timeout,
Prob = Status;
see(ResultFile),
read(elapsed_construction(_TimeConstruction)),
read(probability(Prob)),
read(elapsed_traversing(_TimeTraversing)),
seen,
%write(probability(Prob)),nl,
%read(_),
%delete_file(ResultFile),
Status = ok
% format("Construction time ~f traversing time ~f~Number",[TimeConstruction, TimeTraversing])
).
%statistics(walltime,[_,E3]),
%format(user,'~w ms BDD processing~Number',[E3]),
% format("Status ~a~Number",[Status]).
/* insert_list_ptree([Head|Tail], Trie)
* ------------------------------------
* This predicate inserts the given list in a trie.
*/
insert_list_ptree([], _Trie).
insert_list_ptree([Head|Tail], Trie) :-
reverse(Head, Head1),
insert_ptree(Head1, Trie),
insert_list_ptree(Tail, Trie).