578 lines
15 KiB
Prolog
578 lines
15 KiB
Prolog
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:- module(clpbn, [{}/1,
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clpbn_flag/2,
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set_clpbn_flag/2,
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clpbn_flag/3,
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clpbn_key/2,
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clpbn_language/1,
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clpbn_init_solver/4,
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clpbn_run_solver/3,
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clpbn_finalize_solver/1,
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clpbn_init_solver/5,
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clpbn_run_solver/4,
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clpbn_init_graph/1,
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probability/2,
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conditional_probability/3,
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op( 500, xfy, with)]).
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:- use_module(library(atts)).
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:- use_module(library(lists)).
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:- use_module(library(terms)).
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%
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% avoid the overhead of using goal_expansion/2.
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%
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:- multifile
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user:term_expansion/2.
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:- dynamic
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user:term_expansion/2.
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:- attribute key/1, dist/2, evidence/1.
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:- use_module('clpbn/ve',
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[ve/3,
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check_if_ve_done/1,
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init_ve_solver/4,
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run_ve_solver/3
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]).
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:- use_module('clpbn/bp',
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[bp/3,
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check_if_bp_done/1,
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init_bp_solver/4,
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run_bp_solver/3,
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finalize_bp_solver/1
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]).
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:- use_module('clpbn/fove',
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[fove/3,
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check_if_fove_done/1,
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init_fove_solver/4,
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run_fove_solver/3,
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finalize_fove_solver/1
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]).
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:- use_module('clpbn/jt',
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[jt/3,
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init_jt_solver/4,
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run_jt_solver/3
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]).
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:- use_module('clpbn/bdd',
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[bdd/3,
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init_bdd_solver/4,
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run_bdd_solver/3
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]).
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:- use_module('clpbn/bnt',
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[do_bnt/3,
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check_if_bnt_done/1
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]).
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:- use_module('clpbn/gibbs',
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[gibbs/3,
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check_if_gibbs_done/1,
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init_gibbs_solver/4,
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run_gibbs_solver/3
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]).
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:- use_module('clpbn/pgrammar',
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[init_pcg_solver/4,
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run_pcg_solver/3,
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pcg_init_graph/0
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]).
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:- use_module('clpbn/graphs',
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[
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clpbn2graph/1
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]).
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:- use_module('clpbn/dists',
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[
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dist/4,
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get_dist/4,
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get_evidence_position/3,
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get_evidence_from_position/3,
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additive_dists/6
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]).
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:- use_module('clpbn/evidence',
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[
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store_evidence/1,
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add_stored_evidence/2,
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incorporate_evidence/2,
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check_stored_evidence/2,
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put_evidence/2
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]).
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:- use_module('clpbn/utils',
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[
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sort_vars_by_key/3
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]).
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:- use_module('clpbn/graphviz',
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[clpbn2gviz/4]).
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:- use_module(clpbn/ground_factors,
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[generate_bn/2]).
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:- dynamic solver/1,output/1,use/1,suppress_attribute_display/1, parameter_softening/1, em_solver/1, use_parfactors/1.
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solver(ve).
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em_solver(ve).
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:- meta_predicate probability(:,-), conditional_probability(:,:,-).
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%output(xbif(user_error)).
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%output(gviz(user_error)).
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output(no).
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suppress_attribute_display(false).
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parameter_softening(m_estimate(10)).
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use_parfactors(off).
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clpbn_flag(Flag,Option) :-
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clpbn_flag(Flag, Option, Option).
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set_clpbn_flag(Flag,Option) :-
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clpbn_flag(Flag, _, Option).
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clpbn_flag(output,Before,After) :-
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retract(output(Before)),
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assert(output(After)).
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clpbn_flag(solver,Before,After) :-
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retract(solver(Before)),
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assert(solver(After)).
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clpbn_flag(language,Before,After) :-
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retract(clpbn_language(Before)),
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assert(clpbn_language(After)).
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clpbn_flag(em_solver,Before,After) :-
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retract(em_solver(Before)),
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assert(em_solver(After)).
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clpbn_flag(bnt_solver,Before,After) :-
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retract(bnt:bnt_solver(Before)),
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assert(bnt:bnt_solver(After)).
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clpbn_flag(bnt_path,Before,After) :-
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retract(bnt:bnt_path(Before)),
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assert(bnt:bnt_path(After)).
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clpbn_flag(bnt_model,Before,After) :-
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retract(bnt:bnt_model(Before)),
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assert(bnt:bnt_model(After)).
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clpbn_flag(suppress_attribute_display,Before,After) :-
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retract(suppress_attribute_display(Before)),
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assert(suppress_attribute_display(After)).
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clpbn_flag(parameter_softening,Before,After) :-
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retract(parameter_softening(Before)),
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assert(parameter_softening(After)).
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clpbn_flag(use_factors,Before,After) :-
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retract(use_parfactors(Before)),
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assert(use_parfactors(After)).
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{_} :-
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solver(none), !.
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{Var = Key with Dist} :-
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put_atts(El,[key(Key),dist(DistInfo,Parents)]),
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dist(Dist, DistInfo, Key, Parents),
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add_evidence(Var,Key,DistInfo,El)
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% ,writeln({Var = Key with Dist})
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.
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%
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% make sure a query variable is reachable by the garbage collector.
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%
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% we use a mutable variable to avoid unnecessary trailing.
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%
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store_var(El) :-
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nb_current(clpbn_qvars, Mutable),
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nonvar(Mutable), !,
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get_mutable(Tail, Mutable),
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update_mutable(El.Tail, Mutable).
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store_var(El) :-
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init_clpbn_vars(El).
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init_clpbn_vars(El) :-
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create_mutable(El, Mutable),
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b_setval(clpbn_qvars, Mutable).
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check_constraint(Constraint, _, _, Constraint) :- var(Constraint), !.
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check_constraint((A->D), _, _, (A->D)) :- var(A), !.
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check_constraint((([A|B].L)->D), Vars, NVars, (([A|B].NL)->D)) :- !,
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check_cpt_input_vars(L, Vars, NVars, NL).
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check_constraint(Dist, _, _, Dist).
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check_cpt_input_vars([], _, _, []).
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check_cpt_input_vars([V|L], Vars, NVars, [NV|NL]) :-
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replace_var(Vars, V, NVars, NV),
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check_cpt_input_vars(L, Vars, NVars, NL).
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replace_var([], V, [], V).
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replace_var([V|_], V0, [NV|_], NV) :- V == V0, !.
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replace_var([_|Vars], V, [_|NVars], NV) :-
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replace_var(Vars, V, NVars, NV).
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add_evidence(V,Key,Distinfo,NV) :-
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nonvar(V), !,
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get_evidence_position(V, Distinfo, Pos),
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check_stored_evidence(Key, Pos),
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store_var(NV),
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clpbn:put_atts(NV,evidence(Pos)).
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add_evidence(V,K,_,V) :-
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add_stored_evidence(K,V),
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store_var(V).
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clpbn_marginalise(V, Dist) :-
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attributes:all_attvars(AVars),
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project_attributes([V], AVars),
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clpbn_display:get_atts(V, posterior(_,_,Dist,_)).
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%
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% called by top-level
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% or by call_residue/2
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%
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project_attributes(GVars, AVars0) :-
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suppress_attribute_display(false),
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generate_vars(GVars, AVars0, AVars),
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AVars = [_|_],
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solver(Solver),
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( GVars = [_|_] ; Solver = graphs), !,
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clpbn_vars(AVars, DiffVars, AllVars),
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get_clpbn_vars(GVars,CLPBNGVars0),
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simplify_query_vars(CLPBNGVars0, CLPBNGVars),
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(output(xbif(XBifStream)) -> clpbn2xbif(XBifStream,ve,AllVars) ; true),
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(output(gviz(XBifStream)) -> clpbn2gviz(XBifStream,sort,AllVars,GVars) ; true),
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(
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Solver = graphs
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->
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write_out(Solver, [[]], AllVars, DiffVars)
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;
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write_out(Solver, [CLPBNGVars], AllVars, DiffVars)
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).
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project_attributes(_, _).
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generate_vars(GVars, _, NewAVars) :-
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use_parfactors(on),
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clpbn_flag(solver, Solver), Solver \= fove, !,
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generate_bn(GVars, NewAVars).
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generate_vars(_GVars, AVars, AVars).
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clpbn_vars(AVars, DiffVars, AllVars) :-
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sort_vars_by_key(AVars,SortedAVars,DiffVars),
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incorporate_evidence(SortedAVars, AllVars).
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get_clpbn_vars([V|GVars],[V|CLPBNGVars]) :-
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get_atts(V, [key(_)]), !,
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get_clpbn_vars(GVars,CLPBNGVars).
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get_clpbn_vars([_|GVars],CLPBNGVars) :-
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get_clpbn_vars(GVars,CLPBNGVars).
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get_clpbn_vars([],[]).
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get_clpbn_vars([V|GVars],[V|CLPBNGVars]) :-
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get_atts(V, [key(_)]), !,
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get_clpbn_vars(GVars,CLPBNGVars).
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get_clpbn_vars([_|GVars],CLPBNGVars) :-
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get_clpbn_vars(GVars,CLPBNGVars).
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simplify_query_vars(LVs0, LVs) :-
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sort(LVs0,LVs1),
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get_rid_of_ev_vars(LVs1,LVs).
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%
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% some variables might already have evidence in the data-base.
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%
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get_rid_of_ev_vars([],[]).
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get_rid_of_ev_vars([V|LVs0],LVs) :-
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clpbn:get_atts(V, [dist(Id,_),evidence(Pos)]), !,
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get_evidence_from_position(Ev, Id, Pos),
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clpbn_display:put_atts(V, [posterior([],Ev,[],[])]), !,
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get_rid_of_ev_vars(LVs0,LVs).
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get_rid_of_ev_vars([V|LVs0],[V|LVs]) :-
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get_rid_of_ev_vars(LVs0,LVs).
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% do nothing if we don't have query variables to compute.
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write_out(graphs, _, AVars, _) :-
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clpbn2graph(AVars).
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write_out(ve, GVars, AVars, DiffVars) :-
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ve(GVars, AVars, DiffVars).
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write_out(jt, GVars, AVars, DiffVars) :-
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jt(GVars, AVars, DiffVars).
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write_out(bdd, GVars, AVars, DiffVars) :-
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bdd(GVars, AVars, DiffVars).
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write_out(bp, GVars, AVars, DiffVars) :-
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bp(GVars, AVars, DiffVars).
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write_out(gibbs, GVars, AVars, DiffVars) :-
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gibbs(GVars, AVars, DiffVars).
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write_out(bnt, GVars, AVars, DiffVars) :-
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do_bnt(GVars, AVars, DiffVars).
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write_out(fove, GVars, AVars, DiffVars) :-
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fove(GVars, AVars, DiffVars).
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get_bnode(Var, Goal) :-
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get_atts(Var, [key(Key),dist(Dist,Parents)]),
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get_dist(Dist,_,Domain,CPT),
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(Parents = [] -> X = tab(Domain,CPT) ; X = tab(Domain,CPT,Parents)),
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dist_goal(X, Key, Goal0),
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include_evidence(Var, Goal0, Key, Goal).
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include_evidence(Var, Goal0, Key, ((Key:-Ev),Goal0)) :-
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get_atts(Var, [evidence(Ev)]), !.
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include_evidence(_, Goal0, _, Goal0).
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dist_goal(Dist, Key, (Key=NDist)) :-
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term_variables(Dist, DVars),
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process_vars(DVars, DKeys),
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my_copy_term(Dist,DVars, NDist,DKeys).
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my_copy_term(V, DVars, Key, DKeys) :-
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find_var(DVars, V, Key, DKeys).
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my_copy_term(A, _, A, _) :- atomic(A), !.
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my_copy_term(T, Vs, NT, Ks) :-
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T =.. [Na|As],
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my_copy_terms(As, Vs, NAs, Ks),
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NT =.. [Na|NAs].
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my_copy_terms([], _, [], _).
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my_copy_terms([A|As], Vs, [NA|NAs], Ks) :-
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my_copy_term(A, Vs, NA, Ks),
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my_copy_terms(As, Vs, NAs, Ks).
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find_var([V1|_], V, Key, [Key|_]) :- V1 == V, !.
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find_var([_|DVars], V, Key, [_|DKeys]) :-
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find_var(DVars, V, Key, DKeys).
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process_vars([], []).
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process_vars([V|Vs], [K|Ks]) :-
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process_var(V, K),
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process_vars(Vs, Ks).
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process_var(V, K) :- get_atts(V, [key(K)]), !.
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% oops: this variable has no attributes.
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process_var(V, _) :- throw(error(instantiation_error,clpbn(attribute_goal(V)))).
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%
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% unify a CLPBN variable with something.
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%
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verify_attributes(Var, T, Goal) :-
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get_atts(Var, [key(Key),dist(Dist,Parents)]), !,
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/* oops, someone trying to bind a clpbn constrained variable */
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bind_clpbn(T, Var, Key, Dist, Parents, Goal).
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verify_attributes(_, _, []).
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bind_clpbn(T, Var, _, _, _, do_not_bind_variable([put_evidence(T,Var)])) :-
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nonvar(T),
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!.
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bind_clpbn(T, Var, Key, Dist, Parents, []) :- var(T),
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get_atts(T, [key(Key1),dist(Dist1,Parents1)]),
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(
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bind_clpbns(Key, Dist, Parents, Key1, Dist1, Parents1)
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->
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(
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get_atts(T, [evidence(Ev1)]) ->
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bind_evidence_from_extra_var(Ev1,Var)
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;
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get_atts(Var, [evidence(Ev)]) ->
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bind_evidence_from_extra_var(Ev,T)
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;
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true
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)
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;
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fail
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).
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bind_clpbn(_, Var, _, _, _, _, []) :-
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use(bnt),
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check_if_bnt_done(Var), !.
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bind_clpbn(_, Var, _, _, _, _, []) :-
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use(ve),
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check_if_ve_done(Var), !.
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bind_clpbn(_, Var, _, _, _, _, []) :-
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use(bp),
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check_if_bp_done(Var), !.
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bind_clpbn(_, Var, _, _, _, _, []) :-
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use(jt),
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check_if_ve_done(Var), !.
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bind_clpbn(_, Var, _, _, _, _, []) :-
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use(bdd),
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check_if_bdd_done(Var), !.
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bind_clpbn(T, Var, Key0, _, _, _, []) :-
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get_atts(Var, [key(Key)]), !,
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(
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Key = Key0 -> true
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;
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% let us not loose whatever we had.
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put_evidence(T,Var)
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).
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fresh_attvar(Var, NVar) :-
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get_atts(Var, LAtts),
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put_atts(NVar, LAtts).
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% I will now allow two CLPBN variables to be bound together.
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%bind_clpbns(Key, Dist, Parents, Key, Dist, Parents).
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bind_clpbns(Key, Dist, Parents, Key1, Dist1, Parents1) :-
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Key == Key1, !,
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get_dist(Dist,_Type,_Domain,_Table),
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get_dist(Dist1,_Type1,_Domain1,_Table1),
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Dist = Dist1,
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Parents = Parents1.
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bind_clpbns(Key, _, _, _, Key1, _, _, _) :-
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Key\=Key1, !, fail.
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bind_clpbns(_, _, _, _, _, _, _, _) :-
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format(user_error, 'unification of two bayesian vars not supported~n', []).
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same_parents([],[]).
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same_parents([P|Parents],[P1|Parents1]) :-
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same_node(P,P1),
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same_parents(Parents,Parents1).
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same_node(P,P1) :- P == P1, !.
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same_node(P,P1) :-
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get_atts( P,[key(K)]),
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get_atts(P1,[key(K)]),
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P = P1.
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bind_evidence_from_extra_var(Ev1,Var) :-
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get_atts(Var, [evidence(Ev0)]), !,
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Ev0 = Ev1.
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bind_evidence_from_extra_var(Ev1,Var) :-
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put_atts(Var, [evidence(Ev1)]).
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user:term_expansion((A :- {}), ( :- true )) :- !, % evidence
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prolog_load_context(module, M),
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store_evidence(M:A).
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clpbn_key(Var,Key) :-
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get_atts(Var, [key(Key)]).
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%
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% This is a routine to start a solver, called by the learning procedures (ie, em).
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% LVs is a list of lists of variables one is interested in eventually marginalising out
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% Vs0 gives the original graph
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% AllDiffs gives variables that are not fully constrainted, ie, we don't fully know
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% the key. In this case, we assume different instances will be bound to different
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% values at the end of the day.
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%
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clpbn_init_solver(LVs, Vs0, VarsWithUnboundKeys, State) :-
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solver(Solver),
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clpbn_init_solver(Solver, LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(gibbs, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_gibbs_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(ve, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_ve_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(bp, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_bp_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(jt, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_jt_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(bdd, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_bdd_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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clpbn_init_solver(pcg, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_pcg_solver(LVs, Vs0, VarsWithUnboundKeys, State).
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|
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%
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% LVs is the list of lists of variables to marginalise
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% Vs is the full graph
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% Ps are the probabilities on LVs.
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%
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%
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clpbn_run_solver(LVs, LPs, State) :-
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solver(Solver),
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clpbn_run_solver(Solver, LVs, LPs, State).
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clpbn_run_solver(gibbs, LVs, LPs, State) :-
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run_gibbs_solver(LVs, LPs, State).
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clpbn_run_solver(ve, LVs, LPs, State) :-
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run_ve_solver(LVs, LPs, State).
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|
|
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clpbn_run_solver(bp, LVs, LPs, State) :-
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run_bp_solver(LVs, LPs, State).
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|
|
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clpbn_run_solver(jt, LVs, LPs, State) :-
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run_jt_solver(LVs, LPs, State).
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|
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clpbn_run_solver(bdd, LVs, LPs, State) :-
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run_bdd_solver(LVs, LPs, State).
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|
|
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clpbn_run_solver(pcg, LVs, LPs, State) :-
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run_pcg_solver(LVs, LPs, State).
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|
|
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add_keys(Key1+V1,_Key2,Key1+V1).
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|
|
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clpbn_init_graph(pcg) :- !,
|
|
pcg_init_graph.
|
|
clpbn_init_graph(_).
|
|
|
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clpbn_finalize_solver(State) :-
|
|
solver(bp), !,
|
|
functor(State, _, Last),
|
|
arg(Last, State, Info),
|
|
finalize_bp_solver(Info).
|
|
clpbn_finalize_solver(_State).
|
|
|
|
probability(Goal, Prob) :-
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|
findall(Prob, do_probability(Goal, [], Prob), [Prob]).
|
|
|
|
conditional_probability(Goal, ListOfGoals, Prob) :-
|
|
\+ ground(ListOfGoals), !,
|
|
throw(error(ground(ListOfGoals),conditional_probability(Goal, ListOfGoals, Prob))).
|
|
conditional_probability(Goal, ListOfGoals, Prob) :-
|
|
findall(Prob, do_probability(Goal, ListOfGoals, Prob), [Prob]).
|
|
|
|
do_probability(Goal, ListOfGoals, Prob) :-
|
|
evidence_to_var(Goal, C, NGoal, V),
|
|
call_residue(run( ListOfGoals, NGoal), Vars), !,
|
|
match_probability(Vars, C, V, Prob).
|
|
|
|
run(ListOfGoals,Goal) :-
|
|
do(ListOfGoals),
|
|
call(Goal).
|
|
|
|
do(M:ListOfGoals) :-
|
|
do(ListOfGoals, M).
|
|
do([]).
|
|
|
|
do([], _M).
|
|
do(G.ListOfGoals, M) :-
|
|
M:G,
|
|
do(ListOfGoals, M).
|
|
|
|
evidence_to_var(M:Goal, C, M:VItem, V) :- !,
|
|
evidence_to_var(Goal, C, VItem, V).
|
|
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).
|
|
|
|
match_probability([p(V0=C)=Prob|_], C, V, Prob) :-
|
|
V0 == V,
|
|
!.
|
|
match_probability([_|Probs], C, V, Prob) :-
|
|
match_probability(Probs, C, V, Prob).
|
|
|
|
:- dynamic clpbn_language/1.
|
|
|
|
pfl_not_clpbn :-
|
|
clpbn_language(clpbn), !,
|
|
throw(error(pfl('should be called before clpbn'))).
|
|
pfl_not_clpbn :-
|
|
assert(clpbn_language(pfl)).
|
|
|
|
clpbn_not_pfl :-
|
|
clpbn_language(pfl), !.
|
|
clpbn_not_pfl :-
|
|
assert(clpbn_language(clpbn)).
|
|
|
|
:- clpbn_not_pfl.
|
|
|