398 lines
11 KiB
Prolog
398 lines
11 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_init_solver/4,
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clpbn_run_solver/3,
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clpbn_init_solver/5,
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clpbn_run_solver/4]).
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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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:- op( 500, xfy, with).
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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, starter/0.
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:- use_module('clpbn/vel',
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[vel/3,
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check_if_vel_done/1,
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init_vel_solver/4,
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run_vel_solver/3
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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/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/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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]).
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:- use_module('clpbn/evidence',
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[
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store_evidence/1,
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incorporate_evidence/2,
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check_stored_evidence/2,
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add_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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:- dynamic solver/1,output/1,use/1,suppress_attribute_display/1, parameter_softening/1, em_solver/1.
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solver(vel).
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em_solver(vel).
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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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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(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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{_} :-
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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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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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clpbn:put_atts(NV,evidence(Pos)).
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add_evidence(V,K,_,V) :-
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add_evidence(K,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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vel: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, AVars) :-
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suppress_attribute_display(false),
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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,vel,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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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([],[]).
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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(vel, GVars, AVars, DiffVars) :-
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vel(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(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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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, Goali),
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include_starter(Var, Goali, 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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include_starter(Var, Goal0, Key, ((:-Key),Goal0)) :-
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get_atts(Var, [starter]), !.
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include_starter(_, 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, Goals) :-
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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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Goals = [],
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bind_clpbn(T, Var, Key, Dist, Parents).
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verify_attributes(_, _, []).
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bind_clpbn(T, Var, _, _, _) :- nonvar(T),
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!, ( add_evidence(Var,T) -> true ; writeln(T:Var), fail ).
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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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bind_clpbns(Key, Dist, Parents, Key1, Dist1, Parents1),
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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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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(vel),
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check_if_vel_done(Var), !.
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bind_clpbn(_, Var, _, _, _, _) :-
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use(jt),
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check_if_vel_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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add_evidence(Var,T)
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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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same_parents(Parents,Parents1)
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->
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true
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;
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throw(error(domain_error(bayesian_domain),bind_clpbns(var(Dist, Key, Type, Domain, Table, Parents),var(Dist1, Key1, Type1, Domain1, Table1, Parents1))))
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).
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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(vel, LVs, Vs0, VarsWithUnboundKeys, State) :-
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init_vel_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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%
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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, State),
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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(vel, LVs, LPs, State) :-
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run_vel_solver(LVs, LPs, State).
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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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