225 lines
5.5 KiB
Prolog
225 lines
5.5 KiB
Prolog
%
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% This module defines PFL, the Prolog Factor Language.
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%
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%
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:- module(pfl,
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[op(550,yfx,@),
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op(550,yfx,::),
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op(1150,fx,bayes),
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op(1150,fx,markov),
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factor/6,
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skolem/2,
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defined_in_factor/2,
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get_pfl_cpt/5, % given id and keys, return new keys and cpt
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get_pfl_parameters/2, % given id return par factor parameter
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new_pfl_parameters/2, % given id set new parameters
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get_first_pvariable/2, % given id get firt pvar (useful in bayesian)
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get_factor_pvariable/2, % given id get any pvar
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add_ground_factor/5 %add a new bayesian variable (for now)
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]).
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:- reexport(library(clpbn),
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[clpbn_flag/2 as pfl_flag,
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set_clpbn_flag/2 as set_pfl_flag,
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set_solver/1,
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set_em_solver/1,
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conditional_probability/3,
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pfl_init_solver/5,
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pfl_run_solver/3
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]).
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:- reexport(library(clpbn/aggregates),
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[avg_factors/5]).
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:- reexport('clpbn/horus',
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[set_horus_flag/2]).
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:- ( % if clp(bn) has done loading, we're top-level
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predicate_property(set_pfl_flag(_,_), imported_from(clpbn))
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->
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% we're using factor language
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% set appropriate flag
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set_pfl_flag(use_factors,on)
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;
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% we're within clp(bn), no need to do anything
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true
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).
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:- use_module(library(atts)).
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:- use_module(library(lists),
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[nth0/3,
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append/3,
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member/2
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]).
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:- dynamic factor/6, skolem_in/2, skolem/2, preprocess/3, evidence/2, id/1.
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user:term_expansion( bayes((Formula ; Phi ; Constraints)), pfl:factor(bayes,Id,FList,FV,Phi,Constraints)) :-
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!,
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term_variables(Formula, FreeVars),
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FV =.. [''|FreeVars],
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new_id(Id),
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process_args(Formula, Id, 0, _, FList, []).
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user:term_expansion( markov((Formula ; Phi ; Constraints)), pfl:factor(markov,Id,FList,FV,Phi,Constraints)) :-
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!,
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term_variables(Formula, FreeVars),
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FV =.. [''|FreeVars],
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new_id(Id),
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process_args(Formula, Id, 0, _, FList, []).
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user:term_expansion( Id@N, L ) :-
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atom(Id), number(N), !,
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N1 is N + 1,
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findall(G,generate_entity(1, N1, Id, G), L).
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user:term_expansion( Goal, [] ) :-
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preprocess(Goal, Sk,Var), !,
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(ground(Goal) -> true ; throw(error('non ground evidence',Goal))),
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% prolog_load_context(module, M),
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assert(pfl:evidence(Sk,Var)).
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Id@N :-
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generate_entity(0, N, Id, G),
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assert_static(user:G),
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fail.
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_Id@_N.
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add_ground_factor(bayes, Domain, Vars, CPT, Id) :-
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Vars = [K|_],
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( skolem(K,_Domain) -> true ; assert(skolem(K, Domain)) ),
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new_id(Id),
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asserta(skolem_in(K, Id)),
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assert(factor(bayes, Id, Vars, [], CPT, [])).
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skolem(_Id:Key,Dom) :- skolem(Key, Dom).
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defined_in_factor(Key, Factor) :-
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skolem_in(Key, Id),
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factor(bayes, Id, [Key|FList], FV, Phi, Constraints), !,
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Factor = factor(bayes, Id, [Key|FList], FV, Phi, Constraints).
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defined_in_factor(Key, Factor) :-
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skolem_in(Key, Id),
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factor(markov, Id, FList, FV, Phi, Constraints),
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member(Key, FList),
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Factor = factor(markov, Id, FList, FV, Phi, Constraints).
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generate_entity(N, N, _, _) :- !.
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generate_entity(I0, _N, Id, T) :-
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atomic_concat(p, I0, P),
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T =.. [Id, P].
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generate_entity(I0, N, Id, T) :-
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I is I0+1,
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generate_entity(I, N, Id, T).
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id(0).
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new_id(Id) :-
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retract(id(Id0)),
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Id is Id0+1,
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assert(id(Id)).
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process_args(V, _Id, _I0, _I ) --> { var(V) }, !,
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{ throw(error(instantiation_error,pfl:process_args)) }.
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process_args((Arg1,V), Id, I0, I ) --> { var(V) }, !,
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{ I is I0+1 },
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process_arg(Arg1, Id, I),
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[V].
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process_args((Arg1,Arg2), Id, I0, I ) --> !,
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process_args(Arg1, Id, I0, I1),
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process_args(Arg2, Id, I1, I).
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process_args(Arg1, Id, I0, I ) -->
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{ I is I0+1 },
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process_arg(Arg1, Id, I).
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process_arg(Sk::D, Id, _I) -->
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!,
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{
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new_skolem(Sk,D),
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assert(skolem_in(Sk, Id))
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},
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[Sk].
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process_arg(Sk, Id, _I) -->
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!,
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{
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% if :: been used before for this skolem
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% just keep on using it,
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% otherwise, assume it is t,f
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( \+ \+ skolem(Sk,_D) -> true ; new_skolem(Sk,[t,f]) ),
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assert(skolem_in(Sk, Id))
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},
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[Sk].
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new_skolem(Sk,D) :-
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copy_term(Sk, Sk1),
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skolem(Sk1, D1),
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functor(Sk1,N,A),
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functor(Sk ,N,A),
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!,
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( D1 = D -> true ; throw(pfl(permission_error(redefining_domain(Sk),D:D1)))).
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new_skolem(Sk,D) :-
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functor(Sk ,N,A),
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functor(NSk ,N,A),
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interface_predicate(NSk),
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assert(skolem(NSk, D)).
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interface_predicate(Sk) :-
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Sk =.. SKAs,
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append(SKAs, [Var], ESKAs),
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ESk =.. ESKAs,
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assert(preprocess(ESk, Sk, Var)),
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% transform from PFL to CLP(BN) call
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assert_static((user:ESk :-
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evidence(Sk,Ev) -> Ev = Var;
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var(Var) -> insert_atts(Var,Sk) ;
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add_evidence(Sk,Var)
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)).
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insert_atts(Var,Sk) :-
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clpbn:put_atts(Var,[key(Sk)]).
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add_evidence(Sk,Var) :-
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skolem(Sk,D),
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once(nth0(E,D,Var)),
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clpbn:put_atts(_V,[key(Sk),evidence(E)]).
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%% get_pfl_cpt(Id, Keys, Ev, NewKeys, Out) :-
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%% factor(_Type,Id,[Key|_],_FV,avg,_Constraints), !,
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%% Keys = [Key|Parents],
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%% writeln(Key:Parents),
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%% avg_factors(Key, Parents, 0.0, Ev, NewKeys, Out).
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get_pfl_cpt(Id, Keys, _, Keys, Out) :-
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get_pfl_parameters(Id,Out).
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get_pfl_parameters(Id,Out) :-
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factor(_Type,Id,_FList,_FV,Phi,_Constraints),
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( Phi = [_|_] -> Phi = Out ; call(user:Phi, Out) ).
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new_pfl_parameters(Id, NewPhi) :-
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retract(factor(Type,Id,FList,FV,_Phi,Constraints)),
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assert(factor(Type,Id,FList,FV,NewPhi,Constraints)),
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fail.
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new_pfl_parameters(_Id, _NewPhi).
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get_pfl_factor_sizes(Id, DSizes) :-
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factor(_Type, Id, FList, _FV, _Phi, _Constraints),
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get_sizes(FList, DSizes).
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get_sizes([], []).
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get_sizes(Key.FList, Sz.DSizes) :-
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skolem(Key, Domain),
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length(Domain, Sz),
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get_sizes(FList, DSizes).
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% only makes sense for bayesian networks
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get_first_pvariable(Id,Var) :-
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factor(_Type, Id,Var._FList,_FV,_Phi,_Constraints).
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% only makes sense for bayesian networks
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get_factor_pvariable(Id,Var) :-
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factor(_Type, Id,FList,_FV,_Phi,_Constraints),
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member(Var, FList).
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