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update to version 07312009 of ProbLog.

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Costa Vitor
2009-07-31 12:18:03 -05:00
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commit 98843bea46
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@@ -1,4 +1,210 @@
%%% -*- Mode: Prolog; -*-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% $Date: 2009-07-21 18:30:23 +0200 (Tue, 21 Jul 2009) $
% $Revision: 1805 $
%
% This file is part of ProbLog
% http://dtai.cs.kuleuven.be/problog
%
% ProbLog was developed at Katholieke Universiteit Leuven
%
% Copyright 2009
% Angelika Kimmig, Vitor Santos Costa, Bernd Gutmann
%
% Main authors of this file:
% Angelika Kimmig, Vitor Santos Costa,Bernd Gutmann
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Artistic License 2.0
%
% Copyright (c) 2000-2006, The Perl Foundation.
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% (14) Disclaimer of Warranty: THE PACKAGE IS PROVIDED BY THE COPYRIGHT
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% HOLDER OR CONTRIBUTOR WILL BE LIABLE FOR ANY DIRECT, INDIRECT,
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% OF THE PACKAGE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% ProbLog inference
%
@@ -24,7 +230,8 @@
problog_max/3,
problog_exact/3,
problog_montecarlo/3,
problog_table/1,
problog_answers/2,
problog_table/1,
get_fact_probability/2,
set_fact_probability/2,
get_fact/2,
@@ -32,6 +239,7 @@
non_ground_fact/1,
export_facts/1,
problog_help/0,
show_inference/0,
problog_dir/1,
set_problog_flag/2,
problog_flag/2,
@@ -69,7 +277,7 @@
:- op( 1150, fx, problog_table ).
:- meta_predicate problog_table(:).
%%%%%%%%%%%%%%%%%%%%%%%%
% control predicates on various levels
%%%%%%%%%%%%%%%%%%%%%%%%
@@ -96,6 +304,8 @@
:- dynamic max_proof/1.
% local to problog_montecarlo
:- dynamic mc_prob/1.
% local to problog_answers
:- dynamic answer/1.
% to keep track of the groundings for non-ground facts
:- dynamic grounding_is_known/2.
@@ -103,14 +313,16 @@
:- dynamic dynamic_probability_fact/1.
:- dynamic dynamic_probability_fact_extract/2.
% keep a tab on tabling
:- dynamic problog_tabled/1.
% directory where ProblogBDD executable is located
% automatically set during loading -- assumes it is in same place as this file (problog.yap)
%:- getcwd(PD),retractall(problog_dir(_)),assert(problog_dir(PD)).
:- yap_flag(shared_object_search_path,PD),retractall(problog_dir(_)),assert(problog_dir(PD)).
:- yap_flag(shared_object_search_path,PD),
retractall(problog_dir(_)),
assert(problog_dir(PD)).
%%%%%%%%%%%%%%%%%%%%%%%%
% help
@@ -188,10 +400,12 @@ problog_control(off,X) :-
problog_control(check,X) :-
call(X).
:- problog_control(off,up).
:- problog_control(off,mc).
:- problog_control(off,limit).
:- problog_control(off,remember).
reset_control :-
problog_control(off,up),
problog_control(off,mc),
problog_control(off,limit),
problog_control(off,remember).
:- reset_control.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% nice user syntax Prob::Fact
@@ -216,12 +430,13 @@ problog_control(check,X) :-
user:term_expansion(_P::( _Goal :- _Body ), _Error) :-
throw(error('we do not support this (yet?)!')).
/* this can slow down prolog time by several orders if there's lots of them
user:term_expansion(P::Goal,Goal) :-
P \= t(_),
P =:= 1,
!.
user:term_expansion(P::Goal, problog:ProbFact) :-
*/
user:term_expansion(P::Goal, problog:ProbFact) :-
copy_term((P,Goal),(P_Copy,Goal_Copy)),
functor(Goal, Name, Arity),
atomic_concat([problog_,Name],ProblogName),
@@ -229,7 +444,6 @@ user:term_expansion(P::Goal, problog:ProbFact) :-
append(Args,[LProb],L1),
probclause_id(ID),
ProbFact =.. [ProblogName,ID|L1],
assert_static(prob_for_id(ID,P)),
(
(nonvar(P), P = t(TrueProb))
->
@@ -240,6 +454,8 @@ user:term_expansion(P::Goal, problog:ProbFact) :-
(
ground(P)
->
EvalP is P, % allows one to use ground arithmetic expressions as probabilities
assert_static(prob_for_id(ID,EvalP)), % Prob is fixed -- assert it for quick retrieval
LProb is log(P);
(
% Probability is a variable... check wether it appears in the term
@@ -266,7 +482,7 @@ user:term_expansion(P::Goal, problog:ProbFact) :-
assert(non_ground_fact(ID))
),
problog_predicate(Name, Arity, ProblogName).
% introduce wrapper clause if predicate seen first time
problog_predicate(Name, Arity, _) :-
@@ -278,6 +494,7 @@ problog_predicate(Name, Arity, ProblogName) :-
append(Args,[Prob],L1),
ProbFact =.. [ProblogName,ID|L1],
prolog_load_context(module,Mod),
assert( (Mod:OriginalGoal :- ProbFact,
(
non_ground_fact(ID)
@@ -346,19 +563,22 @@ reset_non_ground_facts :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% access/update the probability of ID's fact
% hardware-access version: naively scan all problog-predicates,
% hardware-access version: naively scan all problog-predicates (except if prob is recorded in static database),
% cut choice points if ID is ground (they'll all fail as ID is unique),
% but not if it isn't (used to iterate over all facts when writing out probabilities for learning)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% using a dummy for the static prob database is more efficient than checking for current_predicate
prob_for_id(dummy,dummy).
get_fact_probability(ID,Prob) :-
ground(ID), !,
prob_for_id(ID,Prob).
ground(ID),
prob_for_id(ID,Prob),
!.
get_fact_probability(ID,Prob) :-
(
ground(ID) ->
get_internal_fact(ID,ProblogTerm,_ProblogName,ProblogArity),!
ground(ID) ->
get_internal_fact(ID,ProblogTerm,_ProblogName,ProblogArity),!
;
get_internal_fact(ID,ProblogTerm,_ProblogName,ProblogArity)
get_internal_fact(ID,ProblogTerm,_ProblogName,ProblogArity)
),
arg(ProblogArity,ProblogTerm,Log),
Prob is exp(Log).
@@ -453,92 +673,103 @@ get_fact_list([ID|IDs],[Fact|Facts]) :-
% if not prunable, calculate probability and
% if threshold exceeded, add stopped derivation to upper bound and fail
% else update state and succeed
%
% do not maintain gloabl variables in montecarlo mode
add_to_proof(ID,Prob) :-
montecarlo_check(ID),
b_getval(problog_steps,MaxSteps),
b_getval(problog_probability, CurrentP),
nb_getval(problog_threshold, CurrentThreshold),
b_getval(problog_current_proof, IDs),
%%%% Bernd, changes for negated ground facts
\+ memberchk(not(ID),IDs),
%%%% Bernd, changes for negated ground facts
( MaxSteps =< 0 ->
fail
(
problog_control(check,mc)
->
montecarlo_check(ID)
;
( memberchk(ID, IDs) ->
true
b_getval(problog_steps,MaxSteps),
b_getval(problog_probability, CurrentP),
nb_getval(problog_threshold, CurrentThreshold),
b_getval(problog_current_proof, IDs),
%%%% Bernd, changes for negated ground facts
\+ memberchk(not(ID),IDs),
%%%% Bernd, changes for negated ground facts
(
MaxSteps =< 0
->
fail
;
(
memberchk(ID, IDs)
->
true
;
\+ prune_check([ID|IDs],1),
multiply_probabilities(CurrentP, Prob, NProb),
( NProb < CurrentThreshold ->
upper_bound([ID|IDs]),
fail
;
b_setval(problog_probability, NProb),
b_setval(problog_current_proof, [ID|IDs])
)
\+ prune_check([ID|IDs],1),
multiply_probabilities(CurrentP, Prob, NProb),
(
NProb < CurrentThreshold
->
upper_bound([ID|IDs]),
fail
;
b_setval(problog_probability, NProb),
b_setval(problog_current_proof, [ID|IDs])
)
),
Steps is MaxSteps-1,
b_setval(problog_steps,Steps)
)
).
%%%% Bernd, changes for negated ground facts
add_to_proof_negated(ID,Prob) :-
(
problog_control(check,mc)
problog_control(check,mc)
->
% the sample has to fail if the fact is negated
\+ montecarlo_check(ID);
true
),
b_getval(problog_steps,MaxSteps),
b_getval(problog_probability, CurrentP),
nb_getval(problog_threshold, CurrentThreshold),
b_getval(problog_current_proof, IDs),
\+ memberchk(ID,IDs),
( MaxSteps =< 0 ->
fail
\+ montecarlo_check(ID)
;
( memberchk(not(ID), IDs) ->
true
b_getval(problog_steps,MaxSteps),
b_getval(problog_probability, CurrentP),
nb_getval(problog_threshold, CurrentThreshold),
b_getval(problog_current_proof, IDs),
\+ memberchk(ID,IDs),
(
MaxSteps =< 0
->
fail
;
(
memberchk(not(ID), IDs)
->
true
;
% \+ prune_check([ID|IDs],1),
InverseProb is log(1 - exp(Prob)),
multiply_probabilities(CurrentP, InverseProb, NProb),
( NProb < CurrentThreshold ->
upper_bound([not(ID)|IDs]), %% checkme
fail
;
b_setval(problog_probability, NProb),
b_setval(problog_current_proof, [not(ID)|IDs])
)
InverseProb is log(1 - exp(Prob)),
multiply_probabilities(CurrentP, InverseProb, NProb),
(
NProb < CurrentThreshold
->
upper_bound([not(ID)|IDs]), %% checkme
fail
;
b_setval(problog_probability, NProb),
b_setval(problog_current_proof, [not(ID)|IDs])
)
),
Steps is MaxSteps-1,
b_setval(problog_steps,Steps)
)
).
%%%% Bernd, changes for negated ground facts
% if in monte carlo mode, check array to see if fact can be used
montecarlo_check(ID) :-
array_element(mc_sample,ID,V),
(
problog_control(check,mc)
->
(
array_element(mc_sample,ID,V),
(
V == 1 -> true
;
V == 2 -> fail
;
new_sample(ID)
)
)
V == 1 -> true
;
true
V == 2 -> fail
;
new_sample(ID)
).
new_sample(ID) :-
@@ -566,15 +797,16 @@ multiply_probabilities(CurrentLogP, LogProb, NLogProb) :-
% this is called by all inference methods before the actual ProbLog goal
% to set up environment for proving
% it resets control flags, method specific values to be set afterwards!
init_problog(Threshold) :-
reset_non_ground_facts,
reset_control,
LT is log(Threshold),
b_setval(problog_probability, 0.0),
b_setval(problog_current_proof, []),
nb_setval(problog_threshold, LT),
problog_flag(maxsteps,MaxS),
b_setval(problog_steps, MaxS),
problog_control(off,limit).
b_setval(problog_steps, MaxS).
% idea: proofs that are refinements of known proof can be pruned as they don't add probability mass
% note that current ptree implementation doesn't provide the check as there's no efficient method known so far...
@@ -694,8 +926,8 @@ eval_dnf(ID,Prob,Status) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_threshold(Goal, Threshold, _, _, _) :-
problog_control(on,up),
init_problog_threshold(Threshold),
problog_control(on,up),
problog_call(Goal),
add_solution,
fail.
@@ -731,8 +963,8 @@ compute_bounds(LP, UP, Status) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_low(Goal, Threshold, _, _) :-
problog_control(off,up),
init_problog_low(Threshold),
problog_control(off,up),
problog_call(Goal),
add_solution,
fail.
@@ -757,9 +989,9 @@ init_problog_low(Threshold) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_delta(Goal, Delta, Low, Up, Status) :-
problog_control(on,up),
problog_flag(first_threshold,InitT),
init_problog_delta(InitT,Delta),
problog_control(on,up),
problog_delta_id(Goal,Status),
delete_ptree(1),
delete_ptree(2),
@@ -885,9 +1117,9 @@ eval_upper(N,UpP,ok) :-
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_max(Goal, Prob, Facts) :-
problog_control(off,up),
problog_flag(first_threshold,InitT),
init_problog_max(InitT),
problog_control(off,up),
problog_max_id(Goal, Prob, FactIDs),
( FactIDs = [_|_] -> get_fact_list(FactIDs,Facts);
Facts = FactIDs).
@@ -963,9 +1195,9 @@ problog_kbest_save(Goal, K, Prob, Status, BDDFile, ParamFile) :-
true).
problog_kbest(Goal, K, Prob, Status) :-
problog_control(off,up),
problog_flag(first_threshold,InitT),
init_problog_kbest(InitT),
problog_control(off,up),
problog_kbest_id(Goal, K),
retract(current_kbest(_,ListFound,_NumFound)),
build_prefixtree(ListFound),
@@ -1078,6 +1310,7 @@ problog_montecarlo(_,_,_) :-
problog_montecarlo(Goal,Delta,Prob) :-
retractall(mc_prob(_)),
nb_getval(probclause_counter,ID), !,
C is ID+1,
static_array(mc_sample,C,char),
@@ -1094,14 +1327,12 @@ montecarlo(Goal,Delta,K,File) :-
problog_control(on,mc),
open(File,write,Log),
format(Log,'# goal: ~q~n#delta: ~w~n',[Goal,Delta]),
format(Log,'# num_programs prob low high diff time cache_size num_pos~2n',[]),
format(Log,'# num_programs prob low high diff time~2n',[]),
close(Log),
statistics(walltime,[T1,_]),
init_ptree(1),
(problog_flag(verbose,true) -> format('search for ~q~n',[Goal]);true),
montecarlo(Goal,Delta,K,0,File,0,T1),
problog_control(off,mc),
delete_ptree(1).
problog_control(off,mc).
% calculate values after K samples
montecarlo(Goal,Delta,K,SamplesSoFar,File,PositiveSoFar,InitialTime) :-
@@ -1117,10 +1348,9 @@ montecarlo(Goal,Delta,K,SamplesSoFar,File,PositiveSoFar,InitialTime) :-
Diff is 2*Epsilon,
statistics(walltime,[T2,_]),
Time is (T2-InitialTime)/1000,
count_ptree(1,CacheSize),
(problog_flag(verbose,true) -> format('~n~w samples~nestimated probability ~w~n95 percent confidence interval [~w,~w]~n',[SamplesNew,Prob,Low,High]);true),
open(File,append,Log),
format(Log,'~w ~8f ~8f ~8f ~8f ~3f ~w ~w~n',[SamplesNew,Prob,Low,High,Diff,Time,CacheSize,Next]),
format(Log,'~w ~8f ~8f ~8f ~8f ~3f~n',[SamplesNew,Prob,Low,High,Diff,Time]),
close(Log),
((Diff<Delta; Diff =:= 0) -> (problog_flag(verbose,true) -> format('Runtime ~w sec~2n',[Time]);true),assert(mc_prob(Prob))
;
@@ -1142,18 +1372,16 @@ mc_prove(A) :- !,
clean_sample :-
reset_static_array(mc_sample),
problog_tabled(P),
problog_tabled(P),%show_table(P),table_statistics(P),get(_),
abolish_table(P),
fail.
clean_sample.
% find new proof
% find new proof -- need to reset control after init
get_some_proof(Goal) :-
init_problog(0),
problog_call(Goal),
b_getval(problog_current_proof,Used),
(Used == [] -> Proof=true; reverse(Used,Proof)),
insert_ptree(Proof,1).
problog_control(on,mc),
problog_call(Goal).
problog_table(M:P) :- !,
problog_table(P,M).
@@ -1170,3 +1398,23 @@ problog_table(P,M) :-
table(M:P),
assert(problog_tabled(M:P)).
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% exact probability of all ground instances of Goal
% output goes to File
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
problog_answers(Goal,File) :-
set_problog_flag(verbose,false),
retractall(answer(_)),
% this will not give the exact prob of Goal!
problog_exact((Goal,ground(Goal),\+problog:answer(Goal),assert(problog:answer(Goal))),_,_),
open(File,write,_,[alias(answer)]),
eval_answers,
close(answer).
eval_answers :-
retract(answer(G)),
problog_exact(G,P,_),
format(answer,'answer(~q,~w).~n',[G,P]),
fail.
eval_answers.