145 lines
3.2 KiB
Prolog
145 lines
3.2 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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factor/5,
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skolem/2,
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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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op(550,yfx,::),
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op(1150,fx,bayes),
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op(1150,fx,markov),
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op(1150,fx,parfactor)]).
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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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:- dynamic factor/5, skolem_in/2, skolem/2, preprocess/3, evidence/2, id/1.
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:- reexport(library(clpbn),
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[clpbn_flag/2,
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clpbn_flag/2 as pfl_flag,
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set_clpbn_flag/2,
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set_clpbn_flag/2 as set_pfl_flag]).
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:- set_pfl_flag(use_factors,on).
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:- pfl_not_clpbn.
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user:term_expansion( bayes((Formula ; Phi ; Constraints)), pfl:factor(Id,FList,FV,Phi,Constraints)) :-
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!,
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term_variables(Formula, FreeVars),
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FV =.. [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(Id,FList,FV,Phi,Constraints)) :-
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!,
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term_variables(Formula, FreeVars),
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FV =.. [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( 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(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((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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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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Sk1 =@= Sk,
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!,
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D1 = D.
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new_skolem(Sk,D) :-
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interface_predicate(Sk),
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assert(skolem(Sk, 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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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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).
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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_parameters(Id,Out) :-
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factor(Id,_FList,_FV,Phi,_Constraints),
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writeln(factor(Id,_FList,_FV,_Phi,_Constraints)),
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( is_list(Phi) -> Out = Phi ; call(user:Phi, Out) ).
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new_pfl_parameters(Id, NewPhi) :-
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retract(factor(Id,FList,FV,_Phi,Constraints)),
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assert(factor(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(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(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(Id,FList,_FV,_Phi,_Constraints),
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member(Var, FList).
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