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yap-6.3/packages/CLPBN/clpbn/evidence.yap
2013-04-15 19:12:53 -05:00

153 lines
3.6 KiB
Prolog

%
%
%
%
:- module(clpbn_evidence,
[store_evidence/1,
incorporate_evidence/2,
check_stored_evidence/2,
add_stored_evidence/2,
put_evidence/2
]).
:- use_module(library(clpbn),
[{}/1,
clpbn_flag/3,
set_clpbn_flag/2
]).
:- use_module(library('clpbn/dists'),
[get_dist/4]).
:- use_module(library(rbtrees),
[rb_new/1,
rb_lookup/3,
rb_insert/4
]).
:- meta_predicate store_evidence(:).
:- dynamic node/3, edge/2, evidence/2.
%
% 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.
%
% the format is as follows:
% evidence_store:parent(Key,ParentList,[EvidenceChildren])
%
%
store_evidence(G) :-
clpbn_flag(solver,PreviousSolver, graphs),
compute_evidence(G, PreviousSolver).
compute_evidence(G, PreviousSolver) :-
catch(get_clpbn_vars(G, Vars), Ball, evidence_error(Ball,PreviousSolver)), !,
store_graph(Vars), !,
set_clpbn_flag(solver, PreviousSolver).
compute_evidence(_,PreviousSolver) :-
set_clpbn_flag(solver, PreviousSolver).
get_clpbn_vars(G, Vars) :-
% attributes:all_attvars(Vars0),
once(G),
attributes:all_attvars(Vars).
evidence_error(Ball,PreviousSolver) :-
set_clpbn_flag(solver,PreviousSolver),
throw(Ball).
store_graph([]).
store_graph([V|Vars]) :-
clpbn:get_atts(V,[key(K),dist(Id,Vs)]),
\+ node(K, Id, _), !,
translate_vars(Vs,TVs),
assert(node(K,Id,TVs)),
( clpbn:get_atts(V,[evidence(Ev)]) -> assert(evidence(K,Ev)) ; true),
add_links(TVs,K),
store_graph(Vars).
store_graph([_|Vars]) :-
store_graph(Vars).
translate_vars([],[]).
translate_vars([V|Vs],[K|Ks]) :-
clpbn:get_atts(V, [key(K)]),
translate_vars(Vs,Ks).
add_links([],_).
add_links([K0|TVs],K) :-
edge(K,K0), !,
add_links(TVs,K).
add_links([K0|TVs],K) :-
assert(edge(K,K0)),
add_links(TVs,K).
incorporate_evidence(Vs,AllVs) :-
rb_new(Cache0),
create_open_list(Vs, OL, FL, Cache0, CacheI),
do_variables(OL, FL, CacheI),
extract_vars(OL, AllVs).
create_open_list([], L, L, C, C).
create_open_list([V|Vs], [K-V|OL], FL, C0, CF) :-
clpbn:get_atts(V,[key(K)]),
add_stored_evidence(K, V),
rb_insert(C0, K, V, CI),
create_open_list(Vs, OL, FL, CI, CF).
do_variables([], [], _) :- !.
do_variables([K-V|Vs], Vf, C0) :-
check_for_evidence(K, V, Vf, Vff, C0, Ci),
do_variables(Vs, Vff, Ci).
extract_vars([], []).
extract_vars([_-V|Cache], [V|AllVs]) :-
extract_vars(Cache, AllVs).
%make sure that we are consistent
check_stored_evidence(K, Ev) :-
evidence(K, Ev0), !,
Ev0 = Ev.
check_stored_evidence(_, _).
add_stored_evidence(K, V) :-
evidence(K, Ev), !,
put_evidence(Ev, V).
add_stored_evidence(_, _).
check_for_evidence(_, V, Vf, Vf, C, C) :-
clpbn:get_atts(V, [evidence(_)]), !.
check_for_evidence(K, _, Vf0, Vff, C0, Ci) :-
findall(Rt,edge(Rt,K),Rts),
add_variables(Rts, _, Vf0, Vff, C0, Ci).
add_variables([], [], Vf, Vf, C, C).
add_variables([K|TVs], [V|NTVs], Vf0, Vff, C0, Cf) :-
rb_lookup(K, V, C0), !,
add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
add_variables([K|TVs], [V|NTVs], [K-V|Vf0], Vff, C0, Cf) :-
rb_insert(C0, K, V, C1),
create_new_variable(K, V, Vf0, Vf1, C1, C2),
add_variables(TVs, NTVs, Vf1, Vff, C2, Cf).
create_new_variable(K, V, Vf0, Vff, C0, Cf) :-
node(K, Id, TVs),
writeln(add:K:Id),
get_dist(Id,_,Dom,CPT), !,
{ V = K with p(Dom, CPT, NTVs) },
add_stored_evidence(K, V),
add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
create_new_variable(K, V, Vf0, Vff, C0, Cf) :-
node(K, Id, TVs),
Id =.. [Na,Dom],
Dist =.. [Na,Dom,NTVs],
{ V = K with Dist },
add_stored_evidence(K, V),
add_variables(TVs, NTVs, Vf0, Vff, C0, Cf).
put_evidence(Ev, V) :-
clpbn:put_atts(V, [evidence(Ev)]).