Merge branch 'master' of ssh://git.dcc.fc.up.pt/yap-6.3

This commit is contained in:
Vítor Santos Costa 2013-09-09 22:11:39 +01:00
commit a685b265b9

View File

@ -86,16 +86,16 @@ sl(File):-
),
% write('Initial theory'),nl,
% write_rules(R1,user_output),
learn_struct(DB,R1,R2,CLL2),
learn_params(DB,R2,R,CLL),
learn_struct(DB,R1,R2,Score2),
learn_params(DB,R2,R,Score),
statistics(walltime,[_,WT]),
WTS is WT/1000,
format("~nRefinement CLL ~f - CLL after EMBLEM ~f~n",[CLL2,CLL]),
format("~nRefinement score ~f - score after EMBLEM ~f~n",[Score2,Score]),
format("Total execution time ~f~n~n",[WTS]),
write_rules(R,user_output),
listing(setting/2),
open(FileOut,write,Stream),
format(Stream,'/* SLIPCASE Final CLL ~f~n',[CLL]),
format(Stream,'/* SLIPCOVER Final score ~f~n',[Score]),
format(Stream,'Execution time ~f~n',[WTS]),
tell(Stream),
listing(setting/2),
@ -111,7 +111,7 @@ gen_fixed([(H,B,BL)|T],[rule(R,H,B,BL)|T1]):-
get_next_rule_number(R),
gen_fixed(T,T1).
learn_struct_only(DB,R1,R,CLL):- %+R1:initial theory of the form [rule(NR,[h],[b]],...], -R:final theory of the same form, -CLL
learn_struct_only(DB,R1,R,Score):- %+R1:initial theory of the form [rule(NR,[h],[b]],...], -R:final theory of the same form, -CLL
format("Clause search~n~n",[]),
setting(max_iter,M),
setting(depth_bound,DepthB),
@ -126,7 +126,7 @@ learn_struct_only(DB,R1,R,CLL):- %+R1:initial theory of the form [rule(NR,[h],
set(depth_bound,DepthB),
format("Theory search~n~n",[]),
setting(max_iter_structure,MS),
cycle_structure(TCL,[HCL],S,-inf,DB,R2,CLL,MS),
cycle_structure(TCL,[HCL],S,-inf,DB,R2,Score,MS),
format("Best target theory~n~n",[]),
write_rules(R2,user_output),
length(BG,NBG),
@ -135,7 +135,7 @@ learn_struct_only(DB,R1,R,CLL):- %+R1:initial theory of the form [rule(NR,[h],
append(R2,BG2,R).
learn_struct(DB,R1,R,CLL):- %+R1:initial theory of the form [rule(NR,[h],[b]],...], -R:final theory of the same form, -CLL
learn_struct(DB,R1,R,Score):- %+R1:initial theory of the form [rule(NR,[h],[b]],...], -R:final theory of the same form, -CLL
format("Clause search~n~n",[]),
setting(max_iter,M),
setting(depth_bound,DepthB),
@ -150,7 +150,7 @@ learn_struct(DB,R1,R,CLL):- %+R1:initial theory of the form [rule(NR,[h],[b]],
set(depth_bound,DepthB),
format("Theory search~n~n",[]),
setting(max_iter_structure,MS),
cycle_structure(TCL,[HCL],S,-inf,DB,R2,CLL,MS),
cycle_structure(TCL,[HCL],S,-inf,DB,R2,Score,MS),
format("Best target theory~n~n",[]),
write_rules(R2,user_output),
setting(background_clauses,NBG1),
@ -183,7 +183,7 @@ cycle_structure([(RH,_CLL)|RT],R0,S0,SP0,DB,R,S,M):-
format("Theory iteration ~d",[M]),nl,nl,
write('Already scored, updated refinement'),nl,
write_rules(R3,user_output),
write('Score (CLL) '),write(Score),nl,nl,nl,
write('Score '),write(Score),nl,nl,nl,
(Score>S0->
R4=R3,
S4=Score,
@ -196,7 +196,7 @@ cycle_structure([(RH,_CLL)|RT],R0,S0,SP0,DB,R,S,M):-
M1 is M-1,
cycle_structure(RT,R4,S4,SP1,DB,R,S,M1).
cycle_structure([(RH,_CLL)|RT],R0,S0,SP0,DB,R,S,M):-
cycle_structure([(RH,_Score)|RT],R0,S0,SP0,DB,R,S,M):-
format("Theory iteration ~d",[M]),nl,nl,
generate_clauses([RH|R0],R2,0,[],Th1),
format("Initial theory~n~n",[]),
@ -218,17 +218,17 @@ cycle_structure([(RH,_CLL)|RT],R0,S0,SP0,DB,R,S,M):-
),
setting(random_restarts_number,N),
format("~nInitial CLL ~f~n~n",[CLL0]),
random_restarts(N,Nodes,CLL0,CLL,initial,Par,LE), %output:CLL,Par
format("CLL after EMBLEM = ~f~n",[CLL]),
random_restarts(N,Nodes,CLL0,Score,initial,Par,LE), %output:CLL,Par
format("Score after EMBLEM = ~f~n",[Score]),
retract_all(Th1),
retract_all(R2),!,
end,
update_theory(R2,Par,R3),
write('updated Theory'),nl,
write_rules(R3,user_output), %definite rules without probabilities in the head are not written
(CLL>S0->
(Score>S0->
R4=R3,
S4=CLL,
S4=Score,
SP1=S0,
write('New best score'),nl
;
@ -236,7 +236,7 @@ cycle_structure([(RH,_CLL)|RT],R0,S0,SP0,DB,R,S,M):-
S4=S0,
SP1=SP0
),
store_refinement([RH|R0],R3,CLL),
store_refinement([RH|R0],R3,Score),
M1 is M-1,
cycle_structure(RT,R4,S4,SP1,DB,R,S,M1).
@ -259,15 +259,15 @@ em(File):-
set(compiling,off),
set(verbosity,3),
statistics(walltime,[_,_]),
learn_params(DB,R0,R,CLL),
learn_params(DB,R0,R,Score),
statistics(walltime,[_,CT]),
CTS is CT/1000,
format("EM: Final CLL ~f~n",[CLL]),
format("EM: Final score ~f~n",[Score]),
format("Execution time ~f~n~n",[CTS]),
write_rules(R,user_output),
listing(setting/2),
open(FileOut,write,Stream),
format(Stream,'/* EMBLEM Final CLL ~f~n',[CLL]),
format(Stream,'/* EMBLEM Final score ~f~n',[Score]),
format(Stream,'Execution time ~f~n',[CTS]),
tell(Stream),
listing(setting/2),
@ -277,7 +277,7 @@ em(File):-
write_rules(R,Stream1),
close(Stream1).
learn_params(DB,R0,R,CLL):- %Parameter Learning
learn_params(DB,R0,R,Score):- %Parameter Learning
generate_clauses(R0,R1,0,[],Th0),
assert_all(Th0),
assert_all(R1),!,
@ -295,7 +295,7 @@ learn_params(DB,R0,R,CLL):- %Parameter Learning
derive_bdd_nodes(DB,NEx,[],Nodes,0,_CLL0),!
),
setting(random_restarts_number,N),
random_restarts(N,Nodes,-inf,CLL,initial,Par,LE), %computes new parameters Par
random_restarts(N,Nodes,-inf,Score,initial,Par,LE), %computes new parameters Par
end,
retract_all(Th0),
retract_all(R1),!,
@ -368,7 +368,7 @@ score_clause_refinements([R1|T],Nrev,NRef,DB,NB0,NB,CL0,CL,CLBG0,CLBG):- %scans
format('Score ref. ~d of ~d~n',[Nrev,NRef]),
write('Already scored, updated refinement'),nl,
write_rules([R3],user_output),
write('Score (CLL) '),write(Score),nl,nl,nl,
write('Score '),write(Score),nl,nl,nl,
setting(beamsize,BS),
insert_in_order(NB0,(R3,Score),BS,NB1),
Nrev1 is Nrev+1,
@ -396,12 +396,11 @@ score_clause_refinements([R1|T],Nrev,NRef,DB,NB0,NB,CL0,CL,CLBG0,CLBG):-
),
format("Initial CLL ~f~n",[CLL0]),
setting(random_restarts_REFnumber,N),
random_restarts_ref(N,Nodes,CLL0,CLL,initial,Par,LE),
random_restarts_ref(N,Nodes,CLL0,Score,initial,Par,LE),
end,
update_theory([R2],Par,[R3]),
write('Updated refinement'),nl,
write_rules([R3],user_output),
Score = CLL,
write('Score (CLL) '),write(Score),nl,nl,nl,
retract_all(Th1),
retract_all([R2]),!,