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More whitespace cleanups

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This commit is contained in:
Tiago Gomes 2012-12-20 23:19:10 +00:00
parent 421d6f72ee
commit 01d8f8e178
61 changed files with 209 additions and 210 deletions
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26
packages/CLPBN/clpbn.yap
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@ -221,14 +221,14 @@ set_em_solver(Solver) :-
%
% we use a mutable variable to avoid unnecessary trailing.
%
store_var(El) :-
nb_current(clpbn_qvars, Mutable),
store_var(El) :-
nb_current(clpbn_qvars, Mutable),
nonvar(Mutable), !,
get_mutable(Tail, Mutable),
update_mutable(El.Tail, Mutable).
store_var(El) :-
store_var(El) :-
init_clpbn_vars(El).
init_clpbn_vars(El) :-
create_mutable(El, Mutable),
b_setval(clpbn_qvars, Mutable).
@ -278,7 +278,7 @@ project_attributes(GVars0, _AVars0) :-
b_setval(clpbn_query_variables, f(GVars0,Evidence)),
simplify_query(GVars0, GVars),
(
GKeys = []
GKeys = []
->
GVars0 = [V|_],
clpbn_display:put_atts(V, [posterior([],[],[],[])])
@ -378,7 +378,7 @@ call_ground_solver(cbp, GVars, GoalKeys, Keys, Factors, Evidence) :- !,
call_ground_solver(Solver, GVars, _GoalKeys, Keys, Factors, Evidence) :-
% fall back to traditional solver
b_hash_new(Hash0),
foldl(gvar_in_hash, GVars, Hash0, HashI),
foldl(gvar_in_hash, GVars, Hash0, HashI),
foldl(key_to_var, Keys, AllVars, HashI, Hash1),
foldl(evidence_to_v, Evidence, _EVars, Hash1, Hash),
%writeln(Keys:AllVars),
@ -432,7 +432,7 @@ write_out(Solver, _, _, _) :-
%
gvar_in_hash(V, Hash0, Hash) :-
get_atts(V, [key(K)]),
b_hash_insert(Hash0, K, V, Hash).
b_hash_insert(Hash0, K, V, Hash).
key_to_var(K, V, Hash0, Hash0) :-
b_hash_lookup(K, V, Hash0), !.
@ -496,12 +496,12 @@ process_vars([V|Vs], [K|Ks]) :-
process_var(V, K),
process_vars(Vs, Ks).
process_var(V, K) :- get_atts(V, [key(K)]), !.
process_var(V, K) :- get_atts(V, [key(K)]), !.
% oops: this variable has no attributes.
process_var(V, _) :- throw(error(instantiation_error,clpbn(attribute_goal(V)))).
%
% unify a CLPBN variable with something.
% unify a CLPBN variable with something.
%
verify_attributes(Var, T, Goal) :-
get_atts(Var, [key(Key),dist(Dist,Parents)]), !,
@ -641,7 +641,7 @@ clpbn_init_solver(pcg, LVs, Vs0, VarsWithUnboundKeys, State) :-
%
% LVs is the list of lists of variables to marginalise
% Vs is the full graph
% Ps are the probabilities on LVs.
% Ps are the probabilities on LVs.
%
clpbn_run_solver(LVs, LPs, State) :-
solver(Solver),
@ -708,7 +708,7 @@ pfl_run_solver(LVs, LPs, State) :-
pfl_run_solver(LVs, LPs, State, ve) :- !,
run_ve_ground_solver(LVs, LPs, State).
pfl_run_solver(LVs, LPs, State, hve) :- !,
run_horus_ground_solver(LVs, LPs, State).
@ -732,7 +732,7 @@ add_keys(Key1+V1,_Key2,Key1+V1).
probability(Goal, Prob) :-
findall(Prob, do_probability(Goal, [], Prob), [Prob]).
conditional_probability(Goal, ListOfGoals, Prob) :-
\+ ground(Goal),
throw(error(ground(Goal),conditional_probability(Goal, ListOfGoals, Prob))).
@ -766,7 +766,7 @@ evidence_to_var(Goal, C, VItem, V) :-
Goal =.. [L|Args],
variabilise_last(Args, C, NArgs, V),
VItem =.. [L|NArgs].
variabilise_last([Arg], Arg, [V], V).
variabilise_last([Arg1,Arg2|Args], Arg, Arg1.NArgs, V) :-
variabilise_last(Arg2.Args, Arg, NArgs, V).

8
packages/CLPBN/clpbn/aggregates.yap
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@ -96,11 +96,11 @@ find_ev(_Evs, Key, RemKeys, [Key|RemKeys], Ev, Ev).
% +final CPT
% - New Parents
% + - list of new keys
%
%
avg_table(Vars, OVars, Domain, Key, TotEvidence, Softness, Vars, Vs, Vs, Id) :-
length(Domain, SDomain),
int_power(Vars, SDomain, 1, TabSize),
TabSize =< 256,
TabSize =< 256,
/* case gmp is not there !! */
TabSize > 0, !,
average_cpt(Vars, OVars, Domain, TotEvidence, Softness, CPT),
@ -170,7 +170,7 @@ cpt_min([_|Vars], Key, Els0, CPT, Vs, NewVs) :-
build_avg_table(Vars, OVars, Domain, _, TotEvidence, Softness, CPT, Vars, Vs, Vs) :-
length(Domain, SDomain),
int_power(Vars, SDomain, 1, TabSize),
TabSize =< 256,
TabSize =< 256,
/* case gmp is not there !! */
TabSize > 0, !,
average_cpt(Vars, OVars, Domain, TotEvidence, Softness, CPT).
@ -304,7 +304,7 @@ get_ds_lengths([],[]).
get_ds_lengths([V|Vs],[Sz|Lengs]) :-
get_vdist_size(V, Sz),
get_ds_lengths(Vs,Lengs).
fill_in_average(Lengs, N, Base, MCPT) :-
generate(Lengs, Case),
average(Case, N, Base, Val),

38
packages/CLPBN/clpbn/bdd.yap
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@ -9,12 +9,12 @@ V = v(Va, Vb, Vc)
The generic formula is
V <- X, Y
V <- X, Y
Va <- P*X1*Y1 + Q*X2*Y2 + ...
**************************************************/
:- module(clpbn_bdd,
@ -80,8 +80,8 @@ bdds(bdd).
%
% QVars: all query variables?
%
%
%
%
init_bdd_ground_solver(QueryKeys, AllKeys, Factors, Evidence, bdd(QueryKeys, AllKeys, Factors, Evidence)).
%
@ -161,7 +161,7 @@ sort_keys(AllFs, AllVars, Leaves) :-
dgraph_top_sort(Graph, AllVars).
add_node(f([K|Parents],_,_,_), Graph0, Graph) :-
dgraph_add_vertex(Graph0, K, Graph1),
dgraph_add_vertex(Graph0, K, Graph1),
foldl(add_edge(K), Parents, Graph1, Graph).
add_edge(K, K0, Graph0, Graph) :-
@ -176,7 +176,7 @@ sort_vars(AllVars0, AllVars, Leaves) :-
build_graph([], Graph, Graph).
build_graph([V|AllVars0], Graph0, Graph) :-
clpbn:get_atts(V, [dist(_DistId, Parents)]), !,
dgraph_add_vertex(Graph0, V, Graph1),
dgraph_add_vertex(Graph0, V, Graph1),
add_parents(Parents, V, Graph1, GraphI),
build_graph(AllVars0, GraphI, Graph).
build_graph(_V.AllVars0, Graph0, Graph) :-
@ -184,7 +184,7 @@ build_graph(_V.AllVars0, Graph0, Graph) :-
add_parents([], _V, Graph, Graph).
add_parents([V0|Parents], V, Graph0, GraphF) :-
dgraph_add_edge(Graph0, V0, V, GraphI),
dgraph_add_edge(Graph0, V0, V, GraphI),
add_parents(Parents, V, GraphI, GraphF).
get_keys_info([], _, _, _, Vs, Vs, Ps, Ps, _, _) --> [].
@ -378,7 +378,7 @@ avg_tree([Vals|PVars], P, Max, Im, IM, Size, O, H0, HF) :-
MaxI is Max-(Size-1),
avg_exp(Vals, PVars, 0, P, MaxI, Size, Im, IM, HI, HF, Exp),
simplify_exp(Exp, Simp).
avg_exp([], _, _, _P, _Max, _Size, _Im, _IM, H, H, 0).
avg_exp([Val|Vals], PVars, I0, P0, Max, Size, Im, IM, HI, HF, O) :-
(Vals = [] -> O=O1 ; O = Val*O1+not(Val)*O2 ),
@ -434,7 +434,7 @@ bup_avg(V, Size, Domain, Parents0, Vs, Vs2, Lvs, Outs, DIST) :-
bin_sums(Vs, Sums, F) :-
vs_to_sums(Vs, Sums0),
bin_sums(Sums0, Sums, F, []).
vs_to_sums([], []).
vs_to_sums([V|Vs], [Sum|Sums0]) :-
Sum =.. [sum|V],
@ -536,7 +536,7 @@ sum_all([_V|Vs], Pos, I, Max0, Sums, List) :-
gen_arg(J, Sums, Max, S0) :-
gen_arg(0, Max, J, Sums, S0).
gen_arg(Max, Max, J, Sums, S0) :- !,
I is Max+1,
arg(I, Sums, A),
@ -647,19 +647,19 @@ copy(N, [], [], Ms, Parms0, Parms, ParmVars) :-!,
copy(N, Ms, NewMs, NewMs, Parms0, Parms, ParmVars).
copy(N, D.Ds, ND.NDs, New, El.Parms0, NEl.Parms, V.ParmVars) :-
N1 is N-1,
(El == 0.0 ->
(El == 0.0 ->
NEl = 0,
V = NEl,
ND = D
;El == 1.0 ->
;El == 1.0 ->
NEl = 1,
V = NEl,
ND = 0.0
;El == 0 ->
;El == 0 ->
NEl = 0,
V = NEl,
ND = D
;El =:= 1 ->
;El =:= 1 ->
NEl = 1,
V = NEl,
ND = 0.0,
@ -818,7 +818,7 @@ get_key_evidence(V, Evs, _, Tree, Ev, F0, F, Leaves, Finals) :-
%% deterministic(V, DistId),
%% !,
%% one_list(Ev),
%% eval_outs(F0).
%% eval_outs(F0).
%% no evidence !!!
get_key_evidence(V, _, _, Tree, _Values, F0, F1, Leaves, Finals) :-
insert_output(Leaves, V, Finals, Tree, Outs, SendOut),
@ -836,14 +836,14 @@ get_evidence(V, _Tree, Ev, F0, [], _Leaves, _Finals) :-
( Name = 'AVG' ; Name = 'MAX' ; Name = 'MIN' ),
!,
one_list(Ev),
eval_outs(F0).
eval_outs(F0).
%% no evidence !!!
get_evidence(V, Tree, _Values, F0, F1, Leaves, Finals) :-
insert_output(Leaves, V, Finals, Tree, Outs, SendOut),
get_outs(F0, F1, SendOut, Outs).
zero_pos(_, _Pos, []).
zero_pos(Pos, Pos, [1|Values]) :- !,
zero_pos(Pos, Pos, [1|Values]) :- !,
I is Pos+1,
zero_pos(I, Pos, Values).
zero_pos(I0, Pos, [0|Values]) :-
@ -855,7 +855,7 @@ one_list(1.Ev) :-
one_list(Ev).
%
% insert a node with the disj of all alternatives, this is only done if node ends up to be in the output
% insert a node with the disj of all alternatives, this is only done if node ends up to be in the output
%
insert_output([], _V, [], _Out, _Outs, []).
insert_output(V._Leaves, V0, [Top|_], Top, Outs, [Top = Outs]) :- V == V0, !.
@ -1057,7 +1057,7 @@ generate_exclusions([V0|SeenVs], V) -->
build_cnf(CNF, IVs, Indics, AllParms, AllParmValues, Val) :-
%(numbervars(CNF,1,_), writeln(cnf_to_ddnnf(CNF, Vars, IVs, [], F)), fail ; true ),
cnf_to_ddnnf(CNF, AllParms, F),
cnf_to_ddnnf(CNF, AllParms, F),
AllParms = AllParmValues,
IVs = Indics,
term_variables(CNF, Extra),

8
packages/CLPBN/clpbn/bnt.yap
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@ -101,7 +101,7 @@ do_bnt(QueryVars, AllVars, AllDiffs) :-
add_evidence(SortedVertices, Size, NumberedVertices),
marginalize(QueryVars, SortedVertices, NumberedVertices, Ps),
clpbn_bind_vals(QueryVars, Ps, AllDiffs).
create_bnt_graph(AllVars, Representatives) :-
create_bnt_graph(AllVars, Representatives, _, _, _).
@ -320,7 +320,7 @@ get_sizes_and_ids([V|Parents],[Id-V|Ids]) :-
extract_vars([], L, L).
extract_vars([_-V|NIds], NParents, Vs) :-
extract_vars(NIds, [V|NParents], Vs).
mkcpt(BayesNet, I, Tab) :-
(BayesNet.'CPD'({I})) <-- tabular_CPD(BayesNet,I,Tab).
@ -336,7 +336,7 @@ create_class_vector([], [], [],[]).
create_class_vector([V|Graph], [I|Is], [Id|Classes], [Id-v(V,I,Parents)|Sets]) :-
clpbn:get_atts(V, [dist(Id,Parents)]),
create_class_vector(Graph, Is,Classes,Sets).
representatives([],[]).
representatives([Class-Rep|Reps1],[Class-Rep|Reps]) :-
nonrepresentatives(Reps1, Class, Reps2),
@ -390,7 +390,7 @@ mk_evidence([V|L], [I|Is], [ar(1,I,EvVal1)|LN]) :-
mk_evidence(L, Is, LN).
mk_evidence([_|L], [_|Is], LN) :-
mk_evidence(L, Is, LN).
evidence_val(Ev,Val,[Ev|_],Val) :- !.
evidence_val(Ev,I0,[_|Domain],Val) :-
I1 is I0+1,

2
packages/CLPBN/clpbn/discrete_utils.yap
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@ -24,7 +24,7 @@ propagate_evidence(V, Evs) :-
clpbn:get_atts(V, [evidence(Ev),dist(Id,_)]), !,
get_dist_domain(Id, Out),
generate_szs_with_evidence(Out,Ev,0,Evs,Found),
(var(Found) ->
(var(Found) ->
clpbn:get_atts(V, [key(K)]),
throw(clpbn(evidence_does_not_match,K,Ev,[Out]))
;

2
packages/CLPBN/clpbn/display.yap
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@ -78,7 +78,7 @@ clpbn_bind_vals([Vs|MoreVs],[Ps|MorePs],AllDiffs) :-
clpbn_bind_vals2([],_,_) :- !.
% simple case, we want a distribution on a single variable.
clpbn_bind_vals2([V],Ps,AllDiffs) :-
clpbn_bind_vals2([V],Ps,AllDiffs) :-
use_parfactors(on), !,
clpbn:get_atts(V, [key(K)]),
pfl:skolem(K,Vals),

2
packages/CLPBN/clpbn/dists.yap
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@ -90,7 +90,7 @@ where Id is the id,
dna for [a,c,g,t]
rna for [a,c,g,u]
reals
********************************************/

6
packages/CLPBN/clpbn/evidence.yap
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@ -31,7 +31,7 @@
:- dynamic node/3, edge/2, evidence/2.
%
% new evidence storage algorithm. The idea is that instead of
% new evidence storage algorithm. The idea is that instead of
% redoing all the evidence every time we query the network, we shall
% keep a precompiled version around.
%
@ -51,9 +51,9 @@ compute_evidence(_,PreviousSolver) :-
set_clpbn_flag(solver, PreviousSolver).
get_clpbn_vars(G, Vars) :-
% attributes:all_attvars(Vars0),
% attributes:all_attvars(Vars0),
once(G),
attributes:all_attvars(Vars).
attributes:all_attvars(Vars).
evidence_error(Ball,PreviousSolver) :-
set_clpbn_flag(solver,PreviousSolver),

14
packages/CLPBN/clpbn/gibbs.yap
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@ -137,7 +137,7 @@ graph_representation([V|Vs], Graph, I0, Keys, [I-IParents|TGraph]) :-
graph_representation(Vs, Graph, I, Keys, TGraph).
write_pars([]).
write_pars([V|Parents]) :-
write_pars([V|Parents]) :-
clpbn:get_atts(V, [key(K),dist(I,_)]),write(K:I),nl,
write_pars(Parents).
@ -149,7 +149,7 @@ get_sizes([V|Parents], [Sz|Szs]) :-
parent_indices([], _, []).
parent_indices([V|Parents], Keys, [I|IParents]) :-
rb_lookup(V, I, Keys),
rb_lookup(V, I, Keys),
parent_indices(Parents, Keys, IParents).
@ -174,7 +174,7 @@ propagate2parents([V|NewParents], Table, Variables, Graph, Keys) :-
propagate2parents(NewParents,Table, Variables, Graph, Keys).
add2graph(V, Vals, Table, IParents, Graph, Keys) :-
rb_lookup(V, Index, Keys),
rb_lookup(V, Index, Keys),
(var(Vals) -> true ; length(Vals,Sz)),
arg(Index, Graph, var(V,Index,_,Vals,Sz,VarSlot,_,_,_)),
member(tabular(Table,Index,IParents), VarSlot), !.
@ -239,7 +239,7 @@ mult_list([Sz|Sizes],Mult0,Mult) :-
MultI is Sz*Mult0,
mult_list(Sizes,MultI,Mult).
% compile node as set of facts, faster execution
% compile node as set of facts, faster execution
compile_var(TotSize,I,_Vals,Sz,CPTs,Parents,_Sizes,Graph) :-
TotSize < 1024*64, TotSize > 0, !,
multiply_all(I,Parents,CPTs,Sz,Graph).
@ -367,8 +367,8 @@ generate_est_mults([], [], _, [], 1).
generate_est_mults([V|Vs], [I|Is], Graph, [M0|Mults], M) :-
arg(V,Graph,var(_,I,_,_,Sz,_,_,_,_)),
generate_est_mults(Vs, Is, Graph, Mults, M0),
M is M0*Sz.
M is M0*Sz.
gen_e0(0,[]) :- !.
gen_e0(Sz,[0|E0L]) :-
Sz1 is Sz-1,
@ -531,7 +531,7 @@ add_up_mes(Counts,[me(_,_,Cs)|Chains], Add) :-
sum_lists(Counts, Cs, NCounts),
add_up_mes(NCounts, Chains, Add).
sum_lists([],[],[]).
sum_lists([],[],[]).
sum_lists([Count|Counts], [C|Cs], [NC|NCounts]) :-
NC is Count+C,
sum_lists(Counts, Cs, NCounts).

2
packages/CLPBN/clpbn/graphviz.yap
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@ -50,7 +50,7 @@ output_parents1(Stream,[V|L]) :-
put_code(Stream, 0' ), %'
output_parents1(Stream,L).
output_v(V,Stream) :-
output_v(V,Stream) :-
clpbn:get_atts(V,[key(Key)]),
output_key(Stream,Key).

2
packages/CLPBN/clpbn/horus.yap
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@ -1,7 +1,7 @@
/*******************************************************
Horus Interface
********************************************************/
:- module(clpbn_horus,

2
packages/CLPBN/clpbn/horus_ground.yap
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@ -4,7 +4,7 @@
- Variable Elimination
- Belief Propagation
- Counting Belief Propagation
********************************************************/
:- module(clpbn_horus_ground,

4
packages/CLPBN/clpbn/jt.yap
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@ -98,7 +98,7 @@ jt(LLVs,Vs0,AllDiffs) :-
init_jt_solver(LLVs, Vs0, _, State) :-
check_for_agg_vars(Vs0, Vs1),
check_for_agg_vars(Vs0, Vs1),
init_influences(Vs1, G, RG),
maplist(init_jt_solver_for_question(G, RG), LLVs, State).
@ -163,7 +163,7 @@ initial_graph(_,Parents, CPTs) :-
% from the very beginning.
dgraph_transpose(V1, V2),
dgraph_to_ugraph(V2, Parents).
problem_graph([], []).
problem_graph([V|BNet], GraphF) :-

8
packages/CLPBN/clpbn/matrix_cpt_utils.yap
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@ -87,7 +87,7 @@ evidence(V, Pos) :-
clpbn:get_atts(V, [evidence(Pos)]).
vnth([V1|Deps], N, V, N, Deps) :-
V == V1, !.
V == V1, !.
vnth([V1|Deps], N0, V, N, [V1|NDeps]) :-
N1 is N0+1,
vnth(Deps, N1, V, N, NDeps).
@ -207,9 +207,9 @@ generate_map([V|DimsNew], [V0|Dims0], [0|Map]) :- V == V0, !,
generate_map(DimsNew, Dims0, Map).
generate_map([V|DimsNew], Dims0, [Sz|Map]) :-
clpbn:get_atts(V, [dist(Id,_)]),
clpbn_dist:get_dist_domain_size(Id, Sz),
clpbn_dist:get_dist_domain_size(Id, Sz),
generate_map(DimsNew, Dims0, Map).
unit_CPT(V,CPT) :-
clpbn:get_atts(V, [dist(Id,_)]),
clpbn_dist:get_dist_domain_size(Id, Sz),
@ -287,7 +287,7 @@ uniform_CPT(Dims, M) :-
normalise_possibly_deterministic_CPT(M1, M).
normalise_CPT_on_lines(MAT0, MAT2, L1) :-
matrix_agg_cols(MAT0, +, MAT1),
matrix_agg_cols(MAT0, +, MAT1),
matrix_sum(MAT1, SUM),
matrix_op_to_all(MAT1, /, SUM, MAT2),
matrix:matrix_to_list(MAT2,L1).

4
packages/CLPBN/clpbn/numbers.yap
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@ -1,7 +1,7 @@
:- module(clpbn_numbers,
[keys_to_numbers/7,
keys_to_numbers/9,
[keys_to_numbers/7,
keys_to_numbers/9,
lists_of_keys_to_ids/6
]).

2
packages/CLPBN/clpbn/pgrammar.yap
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@ -176,7 +176,7 @@ get_internal(S, InternalS, Arg) :-
extract_probability(p(Id,Goals), P) :-
id(Id,_,P0,_),
LogP0 is log(P0),
LogP0 is log(P0),
extract_logprobability(Goals, LogP0, LogP),
P is exp(LogP).

10
packages/CLPBN/clpbn/table.yap
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@ -37,11 +37,11 @@
clpbn_tabled_clause_ref(:.?,?),
clpbn_tabled_retract(:),
clpbn_tabled_abolish(:),
clpbn_tabled_asserta(:),
clpbn_tabled_assertz(:),
clpbn_tabled_asserta(:,-),
clpbn_tabled_assertz(:,-),
clpbn_tabled_number_of_clauses(:,-),
clpbn_tabled_asserta(:),
clpbn_tabled_assertz(:),
clpbn_tabled_asserta(:,-),
clpbn_tabled_assertz(:,-),
clpbn_tabled_number_of_clauses(:,-),
clpbn_is_tabled(:).
:- use_module(library(terms),

4
packages/CLPBN/clpbn/utils.yap
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@ -66,7 +66,7 @@ merge_same_key([K1-V1,K2-V2|Vs], SortedAVars, Ks, UnifiableVars) :-
attributes:fast_unify_attributed(V1,V2),
merge_same_key([K1-V1|Vs], SortedAVars, Ks, UnifiableVars).
merge_same_key([K1-V1,K2-V2|Vs], [V1|SortedAVars], Ks, [K1|UnifiableVars]) :-
(in_keys(K1, Ks) ; \+ \+ K1 == K2), !,
(in_keys(K1, Ks) ; \+ \+ K1 == K2), !,
add_to_keys(K1, Ks, NKs),
merge_same_key([K2-V2|Vs], SortedAVars, NKs, UnifiableVars).
merge_same_key([K-V|Vs], [V|SortedAVars], Ks, UnifiableVars) :-
@ -74,7 +74,7 @@ merge_same_key([K-V|Vs], [V|SortedAVars], Ks, UnifiableVars) :-
merge_same_key(Vs, SortedAVars, NKs, UnifiableVars).
in_keys(K1,[K|_]) :- \+ \+ K1 = K, !.
in_keys(K1,[_|Ks]) :-
in_keys(K1,[_|Ks]) :-
in_keys(K1,Ks).
add_to_keys(K1, Ks, Ks) :- ground(K1), !.

22
packages/CLPBN/clpbn/ve.yap
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@ -11,7 +11,7 @@
all tables they connect to;
multiply their size
order by size
*********************************/
:- module(clpbn_ve,
@ -134,7 +134,7 @@ evtotree(K=V,Ev0,Ev) :-
factor_to_graph( f(Nodes, Sizes, _Pars0, Id), Factors0, Factors, Edges0, Edges, I0, I) :-
I is I0+1,
pfl:get_pfl_parameters(Id, Pars0),
init_CPT(Pars0, Sizes, CPT0),
init_CPT(Pars0, Sizes, CPT0),
reorder_CPT(Nodes, CPT0, FIPs, CPT, _),
F = f(I0, FIPs, CPT),
rb_insert(Factors0, I0, F, Factors),
@ -196,7 +196,7 @@ id_to_factor(VMap, V-I, IF0, IF, Fs0, Fs, Evs0, Evs) :-
get_dist_params(D, Pars0),
get_dist_domain_size(D, DS),
maplist(parent_to_id(VMap), Ps, Sizes, IPs),
init_CPT(Pars0, [DS|Sizes], CPT0),
init_CPT(Pars0, [DS|Sizes], CPT0),
reorder_CPT([I|IPs], CPT0, FIPs, CPT, _),
rb_insert(Fs0, IF0, f(IF0, FIPs, CPT), Fs),
IF is IF0+1.
@ -261,7 +261,7 @@ solve([_|LQVs], FIds, Bigraph, Ev, LPs) :-
do_solve(IQVs, IVs, bigraph(OldVs, IF, _Fs), Ev, Ps) :-
% get only what is relevant to query,
project_to_query_related(IVs, OldVs, SVs, Fs1),
project_to_query_related(IVs, OldVs, SVs, Fs1),
% and also prune using evidence
rb_visit(Ev, EvL),
foldl2(clean_v_ev, EvL, Fs1, Fs2, SVs, EVs),
@ -300,9 +300,9 @@ run_ve_solver(_, LLPs, state(LQVs, LVs, _VMap, Bigraph, Ev)) :-
%
solve_ve([IQVs|_], [IVs|_], bigraph(OldVs, IF, _Fs), Ev, Ps) :-
% get only what is relevant to query,
project_to_query_related(IVs, OldVs, SVs, Fs1),
project_to_query_related(IVs, OldVs, SVs, Fs1),
% and also prune using evidence
foldl2(clean_v_ev, Ev, Fs1, Fs2, SVs, EVs),
foldl2(clean_v_ev, Ev, Fs1, Fs2, SVs, EVs),
% eliminate
eliminate(IQVs, digraph(EVs, IF, Fs2), Dist),
% writeln(m:Dist),matrix:matrix_to_list(Dist,LD),writeln(LD),
@ -319,7 +319,7 @@ solve_ve([_|MoreLVs], [_|MoreLVis], Digraph, Ev, Ps) :-
project_to_query_related(IVs0, OldVs, NVs, NFs) :-
sort(IVs0, IVs),
rb_new(Vs0),
foldl(cp_to_vs, IVs, Vs0, AuxVs),
foldl(cp_to_vs, IVs, Vs0, AuxVs),
rb_new(NFs0),
foldl(simplify_graph_node(OldVs, AuxVs), IVs, VFs, NFs0, NFs),
list_to_rbtree(VFs, NVs).
@ -343,14 +343,14 @@ simplify_graph_node(OldVs, NVs, V, V-RemFs, NFs0, NFs) :-
%
% Two cases: first time factor comes up: all its vars must be in subgraph
% second case: second time it comes up, it must be already in graph
%
% args: +Factor F, +current V (int), +rbtree with all Vs,
%
% args: +Factor F, +current V (int), +rbtree with all Vs,
% -Factors in new Graph, +factors in current graph, -rbtree of factors
%
%
check_factor(V, NVs, F, NFs0, NFs, RemFs, NewRemFs) :-
F = f(IF, [V|More], _), !,
(
(
checklist(check_v(NVs), More)
->
rb_insert(NFs0, IF, F, NFs),
@ -361,7 +361,7 @@ check_factor(V, NVs, F, NFs0, NFs, RemFs, NewRemFs) :-
).
check_factor(_V, _NVs, F, NFs, NFs, RemFs, NewRemFs) :-
F = f(Id, _, _),
(
(
rb_lookup(Id, F, NFs)
->
NewRemFs = [F|RemFs]

2
packages/CLPBN/clpbn/vmap.yap
View File

@ -12,7 +12,7 @@
:- use_module(library(maplist)).
%
% vmap: map V->I
% vmap: map V->I
% contiguous Vs to contiguous integers
%
init_vmap(vmap(0,Empty)) :-

2
packages/CLPBN/examples/School/parlearn.yap
View File

@ -41,4 +41,4 @@ write_cpts([CPT|CPTs]) :-
matrix_to_list(CPT,L),
format('CPT=~w~n',[L]),
write_cpts(CPTs).

2
packages/CLPBN/examples/School/parschema.pfl
View File

@ -55,7 +55,7 @@ professor_popularity(P,A) :- pop(P,A).
course_difficulty(P,A) :- diff(P,A).
student_intelligence(P,A) :- int(P,A).
course_rating(C,X) :- rat(C,X).
registration_grade(R,A) :-

8
packages/CLPBN/examples/city.pfl
View File

@ -75,17 +75,17 @@ hair_color_table(
/* high low */
/* dark */ [ 0.05, 0.1,
/* bright */ 0.95, 0.9 ]).
car_color_table(
/* dark bright */
/* dark */ [ 0.9, 0.2,
/* bright */ 0.1, 0.8 ]).
height_table(
/* male female */
/* tall */ [ 0.6, 0.4,
/* short */ 0.4, 0.6 ]).
shoe_size_table(
/* tall short */
/* big */ [ 0.9, 0.1,
@ -99,7 +99,7 @@ descn_table(
/* car_color(P), hair_color(P), height(P), guilty(P) */
/* fits */ [ 0.99, 0.5, 0.23, 0.88, 0.41, 0.3, 0.76, 0.87,
/* fits */ 0.44, 0.43, 0.29, 0.72, 0.23, 0.91, 0.95, 0.92,
/* dont_fit */ 0.01, 0.5, 0.77, 0.12, 0.59, 0.7, 0.24, 0.13,
/* dont_fit */ 0.01, 0.5, 0.77, 0.12, 0.59, 0.7, 0.24, 0.13,
/* dont_fit */ 0.56, 0.57, 0.71, 0.28, 0.77, 0.09, 0.05, 0.08 ]).
witness_table(

9
packages/CLPBN/horus/BayesBall.h
View File

@ -4,7 +4,6 @@
#include <vector>
#include <queue>
#include <list>
#include <map>
#include "FactorGraph.h"
#include "BayesBallGraph.h"
@ -15,8 +14,8 @@ using namespace std;
struct ScheduleInfo
{
ScheduleInfo (BBNode* n, bool vfp, bool vfc) :
node(n), visitedFromParent(vfp), visitedFromChild(vfc) { }
ScheduleInfo (BBNode* n, bool vfp, bool vfc)
: node(n), visitedFromParent(vfp), visitedFromChild(vfc) { }
BBNode* node;
bool visitedFromParent;
@ -30,7 +29,7 @@ typedef queue<ScheduleInfo, list<ScheduleInfo>> Scheduling;
class BayesBall
{
public:
BayesBall (FactorGraph& fg)
BayesBall (FactorGraph& fg)
: fg_(fg) , dag_(fg.getStructure())
{
dag_.clear();
@ -63,7 +62,7 @@ inline void
BayesBall::scheduleParents (const BBNode* n, Scheduling& sch) const
{
const vector<BBNode*>& ps = n->parents();
for (vector<BBNode*>::const_iterator it = ps.begin();
for (vector<BBNode*>::const_iterator it = ps.begin();
it != ps.end(); ++it) {
sch.push (ScheduleInfo (*it, false, true));
}

6
packages/CLPBN/horus/BayesBallGraph.h
View File

@ -30,15 +30,15 @@ class BBNode : public Var
void addChild (BBNode* c) { childs_.push_back (c); }
bool isVisited (void) const { return visited_; }
void setAsVisited (void) { visited_ = true; }
bool isMarkedOnTop (void) const { return markedOnTop_; }
void markOnTop (void) { markedOnTop_ = true; }
bool isMarkedOnBottom (void) const { return markedOnBottom_; }
void markOnBottom (void) { markedOnBottom_ = true; }
void clear (void) { visited_ = markedOnTop_ = markedOnBottom_ = false; }

6
packages/CLPBN/horus/BeliefProp.cpp
View File

@ -146,7 +146,7 @@ BeliefProp::getFactorJoint (
if (Globals::logDomain) {
Util::exp (jointDist);
}
return jointDist;
return jointDist;
}
@ -185,7 +185,7 @@ BeliefProp::runSolver (void)
}
if (Globals::verbosity > 0) {
if (nIters_ < BpOptions::maxIter) {
cout << "Belief propagation converged in " ;
cout << "Belief propagation converged in " ;
cout << nIters_ << " iterations" << endl;
} else {
cout << "The maximum number of iterations was hit, terminating..." ;
@ -459,7 +459,7 @@ void
BeliefProp::printLinkInformation (void) const
{
for (size_t i = 0; i < links_.size(); i++) {
BpLink* l = links_[i];
BpLink* l = links_[i];
cout << l->toString() << ":" << endl;
cout << " curr msg = " ;
cout << l->message() << endl;

4
packages/CLPBN/horus/BeliefProp.h
View File

@ -17,7 +17,7 @@ class BpLink
{
public:
BpLink (FacNode* fn, VarNode* vn)
{
{
fac_ = fn;
var_ = vn;
v1_.resize (vn->range(), LogAware::log (1.0 / vn->range()));
@ -46,7 +46,7 @@ class BpLink
residual_ = LogAware::getMaxNorm (v1_,v2_);
}
virtual void updateMessage (void)
virtual void updateMessage (void)
{
swap (currMsg_, nextMsg_);
}

24
packages/CLPBN/horus/ConstraintTree.cpp
View File

@ -190,7 +190,7 @@ ConstraintTree::ConstraintTree (
ConstraintTree::ConstraintTree (vector<vector<string>> names)
{
assert (names.empty() == false);
assert (names.front().empty() == false);
assert (names.front().empty() == false);
unsigned nrLvs = names[0].size();
for (size_t i = 0; i < nrLvs; i++) {
logVars_.push_back (LogVar (i));
@ -201,7 +201,7 @@ ConstraintTree::ConstraintTree (vector<vector<string>> names)
Tuple t;
for (size_t j = 0; j < names[i].size(); j++) {
assert (names[i].size() == nrLvs);
t.push_back (LiftedUtils::getSymbol (names[i][j]));
t.push_back (LiftedUtils::getSymbol (names[i][j]));
}
addTuple (t);
}
@ -266,7 +266,7 @@ ConstraintTree::moveToTop (const LogVars& lvs)
assert (pos != logVars_.size());
for (size_t j = pos; j-- > i; ) {
swapLogVar (logVars_[j]);
}
}
}
}
@ -318,7 +318,7 @@ ConstraintTree::join (ConstraintTree* ct, bool oneTwoOne)
} else {
moveToTop (intersect.elements());
ct->moveToTop (intersect.elements());
Tuples tuples;
CTNodes appendNodes;
getTuples (ct->root(), Tuples(), intersect.size(),
@ -455,7 +455,7 @@ ConstraintTree::singletons (void)
if (isSingleton (logVars_[i])) {
singletons.insert (logVars_[i]);
}
}
}
return singletons;
}
@ -585,13 +585,13 @@ ConstraintTree::isCountNormalized (const LogVarSet& Ys)
if (countTuples (*it) != count) {
return false;
}
}
}
return true;
}
unsigned
unsigned
ConstraintTree::getConditionalCount (const LogVarSet& Ys)
{
assert (isCountNormalized (Ys));
@ -792,7 +792,7 @@ ConstraintTree::jointCountNormalize (
}
for (size_t i = 0; i < normCts1.size(); i++) {
unsigned j;
unsigned j;
for (j = 0; counts1[i] + counts2[j] != N; j++) ;
// cout << "joint-count(" << counts1[i] ;
// cout << "," << counts2[j] << ")" << endl;
@ -947,7 +947,7 @@ ConstraintTree::getNodesBelow (CTNode* fromHere) const
CTNodes
ConstraintTree::getNodesAtLevel (unsigned level) const
ConstraintTree::getNodesAtLevel (unsigned level) const
{
assert (level <= logVars_.size());
if (level == 0) {
@ -1057,7 +1057,7 @@ ConstraintTree::join (
} else {
tupleFounded = join (*it, tuple, currIdx + 1, appendNode);
}
}
}
return tupleFounded;
}
@ -1065,7 +1065,7 @@ ConstraintTree::join (
void
ConstraintTree::getTuples (
CTNode* n,
CTNode* n,
Tuples currTuples,
unsigned stopLevel,
Tuples& tuplesCollected,
@ -1147,7 +1147,7 @@ ConstraintTree::split (
CTNode* n2,
CTChilds& commChilds,
CTChilds& exclChilds,
unsigned stopLevel)
unsigned stopLevel)
{
CTChilds& childs1 = n1->childs();
for (CTChilds::const_iterator chIt1 = childs1.begin();

5
packages/CLPBN/horus/CountingBp.cpp
View File

@ -47,8 +47,7 @@ CountingBp::printSolverFlags (void) const
ss << ",max_iter=" << BpOptions::maxIter;
ss << ",accuracy=" << BpOptions::accuracy;
ss << ",log_domain=" << Util::toString (Globals::logDomain);
ss << ",chkif=" <<
Util::toString (CountingBp::checkForIdenticalFactors);
ss << ",chkif=" << Util::toString (CountingBp::checkForIdenticalFactors);
ss << "]" ;
cout << ss.str() << endl;
}
@ -139,7 +138,7 @@ CountingBp::setInitialColors (void)
VarColorMap::iterator it = colorMap.find (range);
if (it == colorMap.end()) {
it = colorMap.insert (make_pair (
range, Colors (range + 1, -1))).first;
range, Colors (range + 1, -1))).first;
}
unsigned idx = varNodes[i]->hasEvidence()
? varNodes[i]->getEvidence()

6
packages/CLPBN/horus/ElimGraph.cpp
View File

@ -28,7 +28,7 @@ ElimGraph::ElimGraph (const vector<Factor*>& factors)
}
if (neighbors (n1, n2) == false) {
addEdge (n1, n2);
}
}
}
}
if (vids.size() == 1) {
@ -86,7 +86,7 @@ ElimGraph::print (void) const
cout << " " << neighs[j]->label();
}
cout << endl;
}
}
}
@ -142,7 +142,7 @@ ElimGraph::getEliminationOrder (
Factors::const_iterator first = factors.begin();
Factors::const_iterator end = factors.end();
for (; first != end; ++first) {
Util::addToVector (allVids, (*first)->arguments());
Util::addToVector (allVids, (*first)->arguments());
}
TinySet<VarId> elimOrder (allVids);
elimOrder -= TinySet<VarId> (excludedVids);

4
packages/CLPBN/horus/Factor.h
View File

@ -143,7 +143,7 @@ class TFactor
assert (idx != args_.size());
assert (obsIdx < ranges_[idx]);
Params newps;
newps.reserve (params_.size() / ranges_[idx]);
newps.reserve (params_.size() / ranges_[idx]);
Indexer indexer (ranges_);
for (unsigned i = 0; i < obsIdx; ++i) {
indexer.incrementDimension (idx);
@ -285,7 +285,7 @@ class Factor : public TFactor<VarId>
void sumOutLastVariable (void);
void sumOutArgs (const vector<bool>& mask);
void clone (const Factor& f);
};

6
packages/CLPBN/horus/FactorGraph.cpp
View File

@ -171,7 +171,7 @@ FactorGraph::readFromLibDaiFormat (const char* fileName)
std::reverse (vids.begin(), vids.end());
Factor f (vids, ranges, params);
std::reverse (vids.begin(), vids.end());
f.reorderArguments (vids);
f.reorderArguments (vids);
addFactor (f);
}
is.close();
@ -188,7 +188,7 @@ FactorGraph::addFactor (const Factor& factor)
for (size_t i = 0; i < vids.size(); i++) {
VarMap::const_iterator it = varMap_.find (vids[i]);
if (it != varMap_.end()) {
addEdge (it->second, fn);
addEdge (it->second, fn);
} else {
VarNode* vn = new VarNode (vids[i], fn->factor().range (i));
addVarNode (vn);
@ -293,7 +293,7 @@ FactorGraph::exportToGraphViz (const char* fileName) const
}
for (size_t i = 0; i < facNodes_.size(); i++) {
out << '"' << facNodes_[i]->getLabel() << '"' ;
out << " [label=\"" << facNodes_[i]->getLabel();
out << " [label=\"" << facNodes_[i]->getLabel();
out << "\"" << ", shape=box]" << endl;
}
for (size_t i = 0; i < facNodes_.size(); i++) {

2
packages/CLPBN/horus/FactorGraph.h
View File

@ -76,7 +76,7 @@ class FactorGraph
const FacNodes& facNodes (void) const { return facNodes_; }
void setFactorsAsBayesian (void) { bayesFactors_ = true; }
bool bayesianFactors (void) const { return bayesFactors_; }
size_t nrVarNodes (void) const { return varNodes_.size(); }

6
packages/CLPBN/horus/Histogram.cpp
View File

@ -59,10 +59,10 @@ HistogramSet::reset (void)
vector<Histogram>
vector<Histogram>
HistogramSet::getHistograms (unsigned N, unsigned R)
{
HistogramSet hs (N, R);
HistogramSet hs (N, R);
unsigned H = hs.nrHistograms();
vector<Histogram> histograms;
histograms.reserve (H);
@ -135,7 +135,7 @@ HistogramSet::maxCount (size_t idx) const
}
return size_ - sum;
}
void

2
packages/CLPBN/horus/HorusCli.cpp
View File

@ -77,7 +77,7 @@ readFactorGraph (FactorGraph& fg, const char* s)
} else if (extension == "fg") {
fg.readFromLibDaiFormat (fileName.c_str());
} else {
cerr << "Error: the probabilistic graphical model must be " ;
cerr << "Error: the probabilistic graphical model must be " ;
cerr << "defined either in a UAI or libDAI file." << endl;
exit (EXIT_FAILURE);
}

12
packages/CLPBN/horus/HorusYap.cpp
View File

@ -57,7 +57,7 @@ createLiftedNetwork (void)
}
ParfactorList* pfList = new ParfactorList (parfactors);
if (Globals::verbosity > 2) {
Util::printHeader ("SHATTERED PARFACTORS");
pfList->print();
@ -91,7 +91,7 @@ createGroundNetwork (void)
// read the ranges
Ranges ranges = readUnsignedList (YAP_ArgOfTerm (2, factor));
// read the parameters
Params params = readParameters (YAP_ArgOfTerm (3, factor));
Params params = readParameters (YAP_ArgOfTerm (3, factor));
// read dist id
unsigned distId = (unsigned) YAP_IntOfTerm (YAP_ArgOfTerm (4, factor));
fg->addFactor (Factor (varIds, ranges, params, distId));
@ -126,7 +126,7 @@ runLiftedSolver (void)
LiftedNetwork* network = (LiftedNetwork*) YAP_IntOfTerm (YAP_ARG1);
ParfactorList pfListCopy (*network->first);
LiftedOperations::absorveEvidence (pfListCopy, *network->second);
LiftedSolver* solver = 0;
switch (Globals::liftedSolver) {
case LiftedSolverType::LVE: solver = new LiftedVe (pfListCopy); break;
@ -181,7 +181,7 @@ int
runGroundSolver (void)
{
FactorGraph* fg = (FactorGraph*) YAP_IntOfTerm (YAP_ARG1);
vector<VarIds> tasks;
YAP_Term taskList = YAP_ARG2;
while (taskList != YAP_TermNil()) {
@ -407,7 +407,7 @@ readParfactor (YAP_Term pfTerm)
}
// read the parameters
const Params& params = readParameters (YAP_ArgOfTerm (4, pfTerm));
const Params& params = readParameters (YAP_ArgOfTerm (4, pfTerm));
// read the constraint
Tuples tuples;
@ -478,7 +478,7 @@ readLiftedEvidence (
obsFormulas.push_back (ObservedFormula (functor, evidence, args));
}
observedList = YAP_TailOfTerm (observedList);
}
}
}

2
packages/CLPBN/horus/Indexer.h
View File

@ -167,7 +167,7 @@ class MapIndexer
}
}
}
template <typename T>
MapIndexer (
const vector<T>& allArgs,

2
packages/CLPBN/horus/LiftedKc.cpp
View File

@ -128,7 +128,7 @@ double
LeafNode::weight (void) const
{
assert (clause_->isUnit());
if (clause_->posCountedLogVars().empty() == false
if (clause_->posCountedLogVars().empty() == false
|| clause_->negCountedLogVars().empty() == false) {
if (SetOrNode::isSet() == false) {
// return a NaN if we have a SetOrNode

4
packages/CLPBN/horus/LiftedOperations.cpp
View File

@ -60,7 +60,7 @@ LiftedOperations::runWeakBayesBall (
const Grounds& query)
{
queue<PrvGroup> todo; // groups to process
set<PrvGroup> done; // processed or in queue
set<PrvGroup> done; // processed or in queue
for (size_t i = 0; i < query.size(); i++) {
ParfactorList::iterator it = pfList.begin();
while (it != pfList.end()) {
@ -225,7 +225,7 @@ LiftedOperations::absorve (
absorvedPfs.push_back (0);
}
break;
}
}
g->constr()->moveToTop (formulas[i].logVars());
std::pair<ConstraintTree*, ConstraintTree*> res;

2
packages/CLPBN/horus/LiftedOperations.h
View File

@ -10,7 +10,7 @@ class LiftedOperations
ParfactorList& pfList, const Grounds& query);
static void runWeakBayesBall (
ParfactorList& pfList, const Grounds&);
ParfactorList& pfList, const Grounds&);
static void absorveEvidence (
ParfactorList& pfList, ObservedFormulas& obsFormulas);

2
packages/CLPBN/horus/LiftedUtils.cpp
View File

@ -61,7 +61,7 @@ ostream& operator<< (ostream &os, const Symbol& s)
ostream& operator<< (ostream &os, const LogVar& X)
{
const string labels[] = {
"A", "B", "C", "D", "E", "F",
"A", "B", "C", "D", "E", "F",
"G", "H", "I", "J", "K", "M" };
(X >= 12) ? os << "X_" << X.id_ : os << labels[X];
return os;

4
packages/CLPBN/horus/LiftedUtils.h
View File

@ -51,7 +51,7 @@ class LogVar
}
bool valid (void) const
{
{
return id_ != Util::maxUnsigned();
}
@ -145,7 +145,7 @@ class Substitution
return X;
}
bool containsReplacementFor (LogVar X) const
bool containsReplacementFor (LogVar X) const
{
return Util::contains (subs_, X);
}

6
packages/CLPBN/horus/LiftedVe.cpp
View File

@ -133,7 +133,7 @@ ProductOperator::toString (void)
stringstream ss;
ss << "just multiplicate " ;
ss << (*g1_)->getAllGroups();
ss << " x " ;
ss << " x " ;
ss << (*g2_)->getAllGroups();
ss << " [cost=" << std::exp (getLogCost()) << "]" << endl;
return ss.str();
@ -155,7 +155,7 @@ ProductOperator::validOp (Parfactor* g1, Parfactor* g2)
}
size_t idx1 = g1->indexOfGroup (intersect[i]);
size_t idx2 = g2->indexOfGroup (intersect[i]);
if (g1->range (idx1) != g2->range (idx2)) {
if (g1->range (idx1) != g2->range (idx2)) {
return false;
}
}
@ -713,7 +713,7 @@ LiftedVe::getBestOperation (const Grounds& query)
if ((bestOp == 0) || (cost < bestCost)) {
bestOp = validOps[i];
bestCost = cost;
}
}
}
if (bestCost > largestCost_) {
largestCost_ = bestCost;

4
packages/CLPBN/horus/LiftedVe.h
View File

@ -9,7 +9,7 @@ class LiftedOperator
{
public:
virtual ~LiftedOperator (void) { }
virtual double getLogCost (void) = 0;
virtual void apply (void) = 0;
@ -55,7 +55,7 @@ class ProductOperator : public LiftedOperator
class SumOutOperator : public LiftedOperator
{
public:
SumOutOperator (PrvGroup group, ParfactorList& pfList)
SumOutOperator (PrvGroup group, ParfactorList& pfList)
: group_(group), pfList_(pfList) { }
double getLogCost (void);

12
packages/CLPBN/horus/LiftedWCNF.cpp
View File

@ -195,7 +195,7 @@ Clause::isPositiveCountedLogVar (LogVar X) const
assert (constr_.logVarSet().contains (X));
return posCountedLvs_.contains (X);
}
bool
@ -235,7 +235,7 @@ Clause::ipgCandidates (void) const
LogVarSet allLvs = constr_.logVarSet();
allLvs -= ipgLvs_;
allLvs -= posCountedLvs_;
allLvs -= negCountedLvs_;
allLvs -= negCountedLvs_;
for (size_t i = 0; i < allLvs.size(); i++) {
bool valid = true;
for (size_t j = 0; j < literals_.size(); j++) {
@ -262,7 +262,7 @@ Clause::logVarTypes (size_t litIdx) const
if (posCountedLvs_.contains (lvs[i])) {
types.push_back (LogVarType::POS_LV);
} else if (negCountedLvs_.contains (lvs[i])) {
types.push_back (LogVarType::NEG_LV);
types.push_back (LogVarType::NEG_LV);
} else {
types.push_back (LogVarType::FULL_LV);
}
@ -391,7 +391,7 @@ LiftedWCNF::LiftedWCNF (const ParfactorList& pfList)
{
addIndicatorClauses (pfList);
addParameterClauses (pfList);
/*
// INCLUSION-EXCLUSION TEST
clauses_.clear();
@ -579,7 +579,7 @@ LiftedWCNF::addParameterClauses (const ParfactorList& pfList)
// ¬θxi|u1,...,un v λu2 -> tempClause
double posWeight = (**it)[indexer];
addWeight (paramVarLid, posWeight, LogAware::one());
Clause* clause1 = new Clause (*(*it)->constr());
for (unsigned i = 0; i < groups.size(); i++) {
@ -593,7 +593,7 @@ LiftedWCNF::addParameterClauses (const ParfactorList& pfList)
tempClause->addLiteralComplemented (Literal (
paramVarLid, (*it)->constr()->logVars()));
tempClause->addLiteral (Literal (lid, (*it)->argument(i).logVars()));
clauses_.push_back (tempClause);
clauses_.push_back (tempClause);
}
clause1->addLiteral (Literal (paramVarLid, (*it)->constr()->logVars()));
clauses_.push_back (clause1);

20
packages/CLPBN/horus/Parfactor.cpp
View File

@ -8,7 +8,7 @@
Parfactor::Parfactor (
const ProbFormulas& formulas,
const Params& params,
const Params& params,
const Tuples& tuples,
unsigned distId)
{
@ -221,7 +221,7 @@ Parfactor::countConvert (LogVar X)
assert (constr_->isCountNormalized (X));
assert (constr_->getConditionalCount (X) > 1);
assert (canCountConvert (X));
unsigned N = constr_->getConditionalCount (X);
unsigned R = ranges_[fIdx];
unsigned H = HistogramSet::nrHistograms (N, R);
@ -336,7 +336,7 @@ Parfactor::fullExpand (LogVar X)
sumIndexes.push_back (HistogramSet::findIndex (hist, originHists));
++ indexer;
}
expandPotential (fIdx, std::pow (R, N), sumIndexes);
ProbFormula f = args_[fIdx];
@ -360,7 +360,7 @@ Parfactor::reorderAccordingGrounds (const Grounds& grounds)
ProbFormulas newFormulas;
for (size_t i = 0; i < grounds.size(); i++) {
for (size_t j = 0; j < args_.size(); j++) {
if (grounds[i].functor() == args_[j].functor() &&
if (grounds[i].functor() == args_[j].functor() &&
grounds[i].arity() == args_[j].arity()) {
constr_->moveToTop (args_[j].logVars());
if (constr_->containsTuple (grounds[i].args())) {
@ -424,7 +424,7 @@ Parfactor::indexOfGround (const Ground& ground) const
{
size_t idx = args_.size();
for (size_t i = 0; i < args_.size(); i++) {
if (args_[i].functor() == ground.functor() &&
if (args_[i].functor() == ground.functor() &&
args_[i].arity() == ground.arity()) {
constr_->moveToTop (args_[i].logVars());
if (constr_->containsTuple (ground.args())) {
@ -806,7 +806,7 @@ Parfactor::simplifyParfactor (size_t fIdx1, size_t fIdx2)
while (indexer.valid()) {
if (indexer[fIdx1] == indexer[fIdx2]) {
params_.push_back (backup[indexer]);
}
}
++ indexer;
}
for (size_t i = 0; i < args_[fIdx2].logVars().size(); i++) {
@ -829,7 +829,7 @@ Parfactor::getAlignLogVars (Parfactor* g1, Parfactor* g2)
TinySet<size_t> matchedI;
TinySet<size_t> matchedJ;
ProbFormulas& formulas1 = g1->arguments();
ProbFormulas& formulas2 = g2->arguments();
ProbFormulas& formulas2 = g2->arguments();
for (size_t i = 0; i < formulas1.size(); i++) {
for (size_t j = 0; j < formulas2.size(); j++) {
if (formulas1[i].group() == formulas2[j].group() &&
@ -882,7 +882,7 @@ Parfactor::alignLogicalVars (Parfactor* g1, Parfactor* g2)
LogVar freeLogVar (0);
Substitution theta1, theta2;
for (size_t i = 0; i < alignLvs1.size(); i++) {
bool b1 = theta1.containsReplacementFor (alignLvs1[i]);
bool b1 = theta1.containsReplacementFor (alignLvs1[i]);
bool b2 = theta2.containsReplacementFor (alignLvs2[i]);
if (b1 == false && b2 == false) {
theta1.add (alignLvs1[i], freeLogVar);
@ -911,11 +911,11 @@ Parfactor::alignLogicalVars (Parfactor* g1, Parfactor* g2)
}
// handle this type of situation:
// g1 = p(X), q(X) ; X in {(p1),(p2)}
// g1 = p(X), q(X) ; X in {(p1),(p2)}
// g2 = p(X), q(Y) ; (X,Y) in {(p1,p2),(p2,p1)}
LogVars discardedLvs1 = theta1.getDiscardedLogVars();
for (size_t i = 0; i < discardedLvs1.size(); i++) {
if (g1->constr()->isSingleton (discardedLvs1[i]) &&
if (g1->constr()->isSingleton (discardedLvs1[i]) &&
g1->nrFormulas (discardedLvs1[i]) == 1) {
g1->constr()->remove (discardedLvs1[i]);
} else {

2
packages/CLPBN/horus/Parfactor.h
View File

@ -115,7 +115,7 @@ class Parfactor : public TFactor<ProbFormula>
static void alignLogicalVars (Parfactor*, Parfactor*);
ConstraintTree* constr_;
};

12
packages/CLPBN/horus/ParfactorList.cpp
View File

@ -9,7 +9,7 @@ ParfactorList::ParfactorList (const ParfactorList& pfList)
while (it != pfList.end()) {
addShattered (new Parfactor (**it));
++ it;
}
}
}
@ -74,7 +74,7 @@ ParfactorList::insertShattered (
list<Parfactor*>::iterator
ParfactorList::remove (list<Parfactor*>::iterator it)
ParfactorList::remove (list<Parfactor*>::iterator it)
{
return pfList_.erase (it);
}
@ -418,7 +418,7 @@ ParfactorList::shatter (Parfactor* g1, Parfactor* g2)
if (formulas1[i].sameSkeletonAs (formulas2[j])) {
std::pair<Parfactors, Parfactors> res;
res = shatter (i, g1, j, g2);
if (res.first.empty() == false ||
if (res.first.empty() == false ||
res.second.empty() == false) {
return res;
}
@ -470,7 +470,7 @@ ParfactorList::shatter (
ConstraintTree* exclCt1 = split1.second;
if (commCt1->empty()) {
// disjoint
// disjoint
delete commCt1;
delete exclCt1;
return { };
@ -549,11 +549,11 @@ ParfactorList::shatter (
Parfactor* newPf = new Parfactor (g, cts[i]);
if (cts[i]->nrLogVars() == g->constr()->nrLogVars() + 1) {
newPf->expand (f.countedLogVar(), X_new1, X_new2);
assert (g->constr()->getConditionalCount (f.countedLogVar()) ==
assert (g->constr()->getConditionalCount (f.countedLogVar()) ==
cts[i]->getConditionalCount (X_new1) +
cts[i]->getConditionalCount (X_new2));
} else {
assert (g->constr()->getConditionalCount (f.countedLogVar()) ==
assert (g->constr()->getConditionalCount (f.countedLogVar()) ==
cts[i]->getConditionalCount (f.countedLogVar()));
}
newPf->setNewGroups();

7
packages/CLPBN/horus/ProbFormula.cpp
View File

@ -61,7 +61,7 @@ ProbFormula::countedLogVar (void) const
}
void
ProbFormula::setCountedLogVar (LogVar lv)
{
@ -92,9 +92,10 @@ ProbFormula::rename (LogVar oldName, LogVar newName)
}
bool operator== (const ProbFormula& f1, const ProbFormula& f2)
{
return f1.group_ == f2.group_ &&
{
return f1.group_ == f2.group_ &&
f1.logVars_ == f2.logVars_;
}

8
packages/CLPBN/horus/ProbFormula.h
View File

@ -12,11 +12,11 @@ typedef unsigned long PrvGroup;
class ProbFormula
{
public:
ProbFormula (Symbol f, const LogVars& lvs, unsigned range)
ProbFormula (Symbol f, const LogVars& lvs, unsigned range)
: functor_(f), logVars_(lvs), range_(range),
countedLogVar_(), group_(numeric_limits<PrvGroup>::max()) { }
ProbFormula (Symbol f, unsigned r)
ProbFormula (Symbol f, unsigned r)
: functor_(f), range_(r), group_(numeric_limits<PrvGroup>::max()) { }
Symbol functor (void) const { return functor_; }
@ -76,10 +76,10 @@ typedef vector<ProbFormula> ProbFormulas;
class ObservedFormula
{
public:
ObservedFormula (Symbol f, unsigned a, unsigned ev)
ObservedFormula (Symbol f, unsigned a, unsigned ev)
: functor_(f), arity_(a), evidence_(ev), constr_(a) { }
ObservedFormula (Symbol f, unsigned ev, const Tuple& tuple)
ObservedFormula (Symbol f, unsigned ev, const Tuple& tuple)
: functor_(f), arity_(tuple.size()), evidence_(ev), constr_(arity_)
{
constr_.addTuple (tuple);

8
packages/CLPBN/horus/TinySet.h
View File

@ -21,7 +21,7 @@ class TinySet
TinySet (const Compare& cmp = Compare())
: vec_(), cmp_(cmp) { }
TinySet (const T& t, const Compare& cmp = Compare())
TinySet (const T& t, const Compare& cmp = Compare())
: vec_(1, t), cmp_(cmp) { }
TinySet (const vector<T>& elements, const Compare& cmp = Compare())
@ -153,12 +153,12 @@ class TinySet
{
return vec_[i];
}
T& operator[] (typename vector<T>::size_type i)
{
return vec_[i];
}
T front (void) const
{
return vec_.front();
@ -219,7 +219,7 @@ class TinySet
return ! (s1.vec_ == s2.vec_);
}
friend std::ostream& operator << (std::ostream& out, const TinySet& s)
friend std::ostream& operator<< (std::ostream& out, const TinySet& s)
{
out << "{" ;
typename vector<T>::size_type i;

4
packages/CLPBN/horus/Util.cpp
View File

@ -140,7 +140,7 @@ nrDigits (int num)
{
unsigned count = 1;
while (num >= 10) {
num /= 10;
num /= 10;
count ++;
}
return count;
@ -166,7 +166,7 @@ parametersToString (const Params& v, unsigned precision)
{
stringstream ss;
ss.precision (precision);
ss << "[" ;
ss << "[" ;
for (size_t i = 0; i < v.size(); i++) {
if (i != 0) ss << ", " ;
ss << v[i];

4
packages/CLPBN/horus/Util.h
View File

@ -373,8 +373,8 @@ void operator^=(std::vector<T>& v, int iexp)
template <typename T>
std::ostream& operator << (std::ostream& os, const vector<T>& v)
template <typename T>
std::ostream& operator<< (std::ostream& os, const vector<T>& v)
{
os << "[" ;
os << Util::elementsToString (v, ", ");

6
packages/CLPBN/horus/Var.cpp
View File

@ -49,7 +49,7 @@ Var::isValidState (const string& stateName)
void
Var::setEvidence (int ev)
Var::setEvidence (int ev)
{
assert (ev < (int) range_);
evidence_ = ev;
@ -58,8 +58,8 @@ Var::setEvidence (int ev)
void
Var::setEvidence (const string& ev)
{
Var::setEvidence (const string& ev)
{
States states = Var::getVarInfo (varId_).states;
for (size_t i = 0; i < states.size(); i++) {
if (states[i] == ev) {

2
packages/CLPBN/horus/VarElim.cpp
View File

@ -70,7 +70,7 @@ VarElim::createFactorList (void)
factorList_.push_back (new Factor (facNodes[i]->factor()));
const VarNodes& neighs = facNodes[i]->neighbors();
for (size_t j = 0; j < neighs.size(); j++) {
unordered_map<VarId, vector<size_t>>::iterator it
unordered_map<VarId, vector<size_t>>::iterator it
= varFactors_.find (neighs[j]->varId());
if (it == varFactors_.end()) {
it = varFactors_.insert (make_pair (

4
packages/CLPBN/horus/WeightedBp.cpp
View File

@ -132,7 +132,7 @@ WeightedBp::maxResidualSchedule (void)
}
}
// in counting bp, the message that a variable X sends to
// to a factor F depends on the message that F sent to the X
// to a factor F depends on the message that F sent to the X
const BpLinks& links = ninf(link->facNode())->getLinks();
for (size_t i = 0; i < links.size(); i++) {
if (links[i]->varNode() != link->varNode()) {
@ -258,7 +258,7 @@ WeightedBp::getVarToFactorMsg (const BpLink* _link) const
if ( ! (l->facNode() == dst && l->index() == link->index())) {
msg *= l->powMessage();
if (Constants::SHOW_BP_CALCS) {
cout << " x " << l->nextMessage() << "^" << link->weight();
cout << " x " << l->nextMessage() << "^" << link->weight();
}
}
}

4
packages/CLPBN/horus/WeightedBp.h
View File

@ -6,7 +6,7 @@
class WeightedLink : public BpLink
{
public:
WeightedLink (FacNode* fn, VarNode* vn, size_t idx, unsigned weight)
WeightedLink (FacNode* fn, VarNode* vn, size_t idx, unsigned weight)
: BpLink (fn, vn), index_(idx), weight_(weight),
pwdMsg_(vn->range(), LogAware::one()) { }
@ -16,7 +16,7 @@ class WeightedLink : public BpLink
const Params& powMessage (void) const { return pwdMsg_; }
void updateMessage (void)
void updateMessage (void)
{
pwdMsg_ = *nextMsg_;
swap (currMsg_, nextMsg_);

10
packages/CLPBN/learning/aleph_params.yap
View File

@ -50,7 +50,7 @@
%
% Tell Aleph not to use default solver during saturation
%
% all work will be done by EM
% all work will be done by EM
%:- set_clpbn_flag(solver,none).
%
@ -123,7 +123,7 @@ add_new_clause(_,(H :- B),_,_) :-
asserta(user:(H :- IB))
),
user:setting(verbosity,V),
( V >= 1 ->
( V >= 1 ->
user:p_message('CLP(BN) Theory'),
functor(H,N,Ar), listing(user:N/Ar)
;
@ -138,7 +138,7 @@ update_tabled_theory(H) :-
clpbn_tabled_assertz((user:(H:-NB))),
fail.
update_tabled_theory(_).
update_theory(H) :-
clause(user:H,B,Ref),
add_correct_cpt(B,NB),
@ -161,7 +161,7 @@ correct_tab(p(Vs,_,Ps),K,p(Vs,TDist,Ps)) :-
get_dist_key(Id, K),
get_dist_params(Id, TDist).
% user-defined cost function, Aleph knows about this (and only about this).
% user-defined cost function, Aleph knows about this (and only about this).
user:cost((H :- B),Inf,Score) :-
domain(H, K, V, D),
check_info(Inf),
@ -261,7 +261,7 @@ rewrite_body((A,B), (user:NA,NB), [V|Vs], [D|Ds], Tail) :-
rewrite_body(B, NB, Vs, Ds, Tail).
rewrite_body((A,B), (user:A,NB), Vs, Ds, Tail) :- !,
rewrite_body(B,NB, Vs, Ds, Tail).
rewrite_body(A,(user:NA,Tail), [V], [D], Tail) :-
rewrite_body(A,(user:NA,Tail), [V], [D], Tail) :-
rewrite_goal(A, V, D, NA), !.
rewrite_body(A, (user:A,Tail), [], [], Tail).

12
packages/CLPBN/learning/em.yap
View File

@ -33,7 +33,7 @@
[generate_network/5,
f/3
]).
:- use_module(library('clpbn/utils'),
[check_for_hidden_vars/3,
sort_vars_by_key/3
@ -46,7 +46,7 @@
compute_likelihood/3,
soften_sample/2
]).
:- use_module(library(bhash),
[b_hash_new/1,
b_hash_lookup/3,
@ -198,7 +198,7 @@ ltables([Id-T|Tables], [Key-LTable|FTables]) :-
generate_dists(Factors, EList, AllDists, AllInfo, MargVars) :-
b_hash_new(Ev0),
b_hash_new(Ev0),
foldl(elist_to_hash, EList, Ev0, Ev),
maplist(process_factor(Ev), Factors, Dists0),
sort(Dists0, Dists1),
@ -220,7 +220,7 @@ fetch_evidence(_Ev, K, Ns, NonEvs, [K|NonEvs]) :-
domain_to_number(_, I0, I0, I) :-
I is I0+1.
% collect the different dists we are going to learn next.
different_dists(AllVars, AllDists, AllInfo, MargVars) :-
@ -232,9 +232,9 @@ different_dists(AllVars, AllDists, AllInfo, MargVars) :-
%
% V -> to Id defining V. We get:
% the random variables that are parents
% the cases that can happen, eg if we have A <- B, C
% the cases that can happen, eg if we have A <- B, C
% A and B are boolean w/o evidence, and C is f, the cases could be
% [0,0,1], [0,1,1], [1,0,0], [1,1,0],
% [0,0,1], [0,1,1], [1,0,0], [1,1,0],
% Hiddens will be C
%
all_dists([], _, []).

2
packages/CLPBN/learning/mle.yap
View File

@ -57,7 +57,7 @@ mk_sample(AllVars, SortedSample) :-
msort(Sample, SortedSample).
%
% assumes we have full data, meaning evidence for every variable
% assumes we have full data, meaning evidence for every variable
%
add2sample([], []).
add2sample([V|Vs],[val(Id,[Ev|EParents])|Vals]) :-

4
packages/CLPBN/pfl.yap
View File

@ -50,7 +50,7 @@
append/3,
member/2
]).
:- dynamic factor/6, skolem_in/2, skolem/2, preprocess/3, evidence/2, id/1.
user:term_expansion( bayes((Formula ; Phi ; Constraints)), pfl:factor(bayes,Id,FList,FV,Phi,Constraints)) :-
@ -178,7 +178,7 @@ add_evidence(Sk,Var) :-
clpbn:put_atts(_V,[key(Sk),evidence(E)]).
%% get_pfl_cpt(Id, Keys, Ev, NewKeys, Out) :-
%% get_pfl_cpt(Id, Keys, Ev, NewKeys, Out) :-
%% factor(_Type,Id,[Key|_],_FV,avg,_Constraints), !,
%% Keys = [Key|Parents],
%% writeln(Key:Parents),