112 lines
2.7 KiB
Prolog
112 lines
2.7 KiB
Prolog
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:- module(clpbn_display,
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[clpbn_bind_vals/3]).
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:- use_module(library(lists),
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[member/2]).
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:- use_module(library(clpbn/dists),
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[get_dist_domain/2]).
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:- use_module(library(clpbn),
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[use_parfactors/1]).
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:- use_module(library(maplist)).
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:- use_module(library(atts)).
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:- attribute posterior/4.
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%
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% what is actually output
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%
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attribute_goal(V, G) :-
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clpbn:suppress_attribute_display(false),
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get_atts(V, [posterior(Vs,Vals,Ps,AllDiffs)]),
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massage_out(Vs, Vals, Ps, G, AllDiffs, V).
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massage_out([], _Ev, _, Out, _, _V) :- !,
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out_query_evidence(Out).
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massage_out(Vs, [D], [P], O, AllDiffs, _) :- !,
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gen_eqs(Vs,D,Eqs),
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add_alldiffs(AllDiffs,Eqs,CEqs),
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out_query_evidence(Out),
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( Out = true -> O = (p(CEqs)=P) ; O = (p(CEqs)=P, Out) ).
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massage_out(Vs, [D|Ds], [P|Ps], (p(CEqs)=P,G) , AllDiffs, V) :-
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gen_eqs(Vs,D,Eqs),
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add_alldiffs(AllDiffs,Eqs,CEqs),
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massage_out(Vs, Ds, Ps, G, AllDiffs, V).
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out_query_evidence(Out) :-
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catch(b_getval(clpbn_query_variables, f(QVs,Evidence)), _, fail), !,
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foldl( process_qv(Evidence), QVs, [], OL),
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list_to_conj(OL, Out).
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out_query_evidence(true).
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process_qv(Evidence, V, L0, LF) :-
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clpbn:get_atts(V,[key(K)]),
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member(K=Ev, Evidence), !,
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pfl:skolem(K,Dom),
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foldl2( add_goal(V,Ev), Dom, 0, _, L0, LF ).
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process_qv(_Ev, _V, L, L).
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list_to_conj([], true).
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list_to_conj([O], O) :- !.
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list_to_conj([O|OL], (O,Out)) :-
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list_to_conj(OL, Out).
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add_goal(V, Ev, DVal, Ev, I, L, [(p(V=DVal) = 1.0)|L]) :- !,
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I is Ev+1.
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add_goal(V, _Ev, DVal, I0, I, L, [(p(V=DVal) = 0.0)|L]) :- !,
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I is I0+1.
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gen_eqs([V], [D], (V=D)) :- !.
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gen_eqs([V], D, (V=D)) :- !.
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gen_eqs([V|Vs], [D|Ds], ((V=D),Eqs)) :-
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gen_eqs(Vs,Ds,Eqs).
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add_alldiffs([],Eqs,Eqs) :- !.
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add_alldiffs(AllDiffs,Eqs,(Eqs/alldiff(AllDiffs))).
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clpbn_bind_vals([],[],_).
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clpbn_bind_vals([Vs|MoreVs],[Ps|MorePs],AllDiffs) :-
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clpbn_bind_vals2(Vs, Ps, AllDiffs),
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clpbn_bind_vals(MoreVs,MorePs,AllDiffs).
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clpbn_bind_vals2([],_,_) :- !.
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% simple case, we want a distribution on a single variable.
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clpbn_bind_vals2([V],Ps,AllDiffs) :-
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use_parfactors(on), !,
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clpbn:get_atts(V, [key(K)]),
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pfl:skolem(K,Vals),
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put_atts(V, posterior([V], Vals, Ps, AllDiffs)).
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% complex case, we want a joint distribution, do it on a leader.
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% should split on cliques ?
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clpbn_bind_vals2(Vs,Ps,AllDiffs) :-
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get_all_combs(Vs, Vals),
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Vs = [V|_],
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put_atts(V, posterior(Vs, Vals, Ps, AllDiffs)).
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get_all_combs(Vs, Vals) :-
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get_all_doms(Vs,Ds),
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findall(L,ms(Ds,L),Vals).
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get_all_doms([], []).
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get_all_doms([V|Vs], [D|Ds]) :-
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clpbn:get_atts(V, [dist(Id,_)]), !,
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get_dist_domain(Id,D),
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get_all_doms(Vs, Ds).
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get_all_doms([V|Vs], [D|Ds]) :-
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clpbn:get_atts(V, [key(K)]),
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pfl:skolem(K,D),
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get_all_doms(Vs, Ds).
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ms([], []).
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ms([H|L], [El|Els]) :-
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member(El,H),
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ms(L, Els).
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