803 lines
23 KiB
Prolog
803 lines
23 KiB
Prolog
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/************************************************
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BDDs in CLP(BN)
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A variable is represented by the N possible cases it can take
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V = v(Va, Vb, Vc)
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The generic formula is
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V <- X, Y
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Va <- P*X1*Y1 + Q*X2*Y2 + ...
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**************************************************/
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:- module(clpbn_bdd,
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[bdd/3,
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set_solver_parameter/2,
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init_bdd_solver/4,
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run_bdd_solver/3,
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finalize_bdd_solver/1,
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check_if_bdd_done/1
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]).
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:- use_module(library('clpbn/dists'),
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[dist/4,
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get_dist_domain/2,
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get_dist_domain_size/2,
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get_dist_all_sizes/2,
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get_dist_params/2
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]).
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:- use_module(library('clpbn/display'),
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[clpbn_bind_vals/3]).
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:- use_module(library('clpbn/aggregates'),
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[check_for_agg_vars/2]).
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:- use_module(library(atts)).
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:- use_module(library(hacks)).
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:- use_module(library(lists)).
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:- use_module(library(dgraphs)).
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:- use_module(library(bdd)).
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:- use_module(library(rbtrees)).
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:- use_module(library(bhash)).
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:- use_module(library(matrix)).
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:- dynamic network_counting/1.
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:- attribute order/1.
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check_if_bdd_done(_Var).
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bdd([[]],_,_) :- !.
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bdd([QueryVars], AllVars, AllDiffs) :-
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init_bdd_solver(_, AllVars, _, BayesNet),
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run_bdd_solver([QueryVars], LPs, BayesNet),
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finalize_bdd_solver(BayesNet),
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clpbn_bind_vals([QueryVars], [LPs], AllDiffs).
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init_bdd_solver(_, AllVars0, _, bdd(Term, Leaves, Tops)) :-
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% check_for_agg_vars(AllVars0, AllVars1),
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sort_vars(AllVars0, AllVars, Leaves),
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order_vars(AllVars, 0),
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rb_new(Vars0),
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rb_new(Pars0),
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init_tops(Leaves,Tops),
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get_vars_info(AllVars, Vars0, _Vars, Pars0, _Pars, Leaves, Tops, Term, []).
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order_vars([], _).
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order_vars([V|AllVars], I0) :-
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put_atts(V, [order(I0)]),
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I is I0+1,
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order_vars(AllVars, I).
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init_tops([],[]).
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init_tops(_.Leaves,_.Tops) :-
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init_tops(Leaves,Tops).
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sort_vars(AllVars0, AllVars, Leaves) :-
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dgraph_new(Graph0),
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build_graph(AllVars0, Graph0, Graph),
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dgraph_leaves(Graph, Leaves),
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dgraph_top_sort(Graph, AllVars).
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build_graph([], Graph, Graph).
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build_graph(V.AllVars0, Graph0, Graph) :-
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clpbn:get_atts(V, [dist(_DistId, Parents)]), !,
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dgraph_add_vertex(Graph0, V, Graph1),
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add_parents(Parents, V, Graph1, GraphI),
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build_graph(AllVars0, GraphI, Graph).
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build_graph(_V.AllVars0, Graph0, Graph) :-
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build_graph(AllVars0, Graph0, Graph).
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add_parents([], _V, Graph, Graph).
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add_parents(V0.Parents, V, Graph0, GraphF) :-
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dgraph_add_edge(Graph0, V0, V, GraphI),
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add_parents(Parents, V, GraphI, GraphF).
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get_vars_info([], Vs, Vs, Ps, Ps, _, _) --> [].
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get_vars_info([V|MoreVs], Vs, VsF, Ps, PsF, Lvs, Outs) -->
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{ clpbn:get_atts(V, [dist(DistId, Parents)]) }, !,
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%{writeln(v:DistId:Parents)},
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[DIST],
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{ get_var_info(V, DistId, Parents, Vs, Vs2, Ps, Ps1, Lvs, Outs, DIST) },
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get_vars_info(MoreVs, Vs2, VsF, Ps1, PsF, Lvs, Outs).
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get_vars_info([_|MoreVs], Vs0, VsF, Ps0, PsF, VarsInfo, Lvs, Outs) :-
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get_vars_info(MoreVs, Vs0, VsF, Ps0, PsF, VarsInfo, Lvs, Outs).
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%
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% let's have some fun with avg
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%
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get_var_info(V, avg(Domain), Parents, Vs, Vs2, Ps, Ps, Lvs, Outs, DIST) :- !,
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length(Domain, DSize),
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% run_though_avg(V, DSize, Domain, Parents, Vs, Vs2, Lvs, Outs, DIST).
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top_down_with_tabling(V, DSize, Domain, Parents, Vs, Vs2, Lvs, Outs, DIST).
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% bup_avg(V, DSize, Domain, Parents, Vs, Vs2, Lvs, Outs, DIST).
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% standard random variable
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get_var_info(V, DistId, Parents0, Vs, Vs2, Ps, Ps1, Lvs, Outs, DIST) :-
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% clpbn:get_atts(V, [key(K)]), writeln(V:K:DistId:Parents),
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reorder_vars(Parents0, Parents, Map),
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check_p(DistId, Map, Parms, _ParmVars, Ps, Ps1),
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unbound_parms(Parms, ParmVars),
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check_v(V, DistId, DIST, Vs, Vs1),
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DIST = info(V, Tree, Ev, Values, Formula, ParmVars, Parms),
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% get a list of form [[P00,P01], [P10,P11], [P20,P21]]
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get_parents(Parents, PVars, Vs1, Vs2),
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cross_product(Values, Ev, PVars, ParmVars, Formula0),
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% (numbervars(Formula0,0,_),writeln(formula0:Ev:Formula0), fail ; true),
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get_evidence(V, Tree, Ev, Formula0, Formula, Lvs, Outs).
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%, (numbervars(Formula,0,_),writeln(formula:Formula), fail ; true)
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%
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% reorder all variables and make sure we get a
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% map of how the transfer was done.
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%
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% position zero is output
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%
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reorder_vars(Vs, OVs, Map) :-
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add_pos(Vs, 1, PVs),
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keysort(PVs, SVs),
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remove_key(SVs, OVs, Map).
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add_pos([], _, []).
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add_pos([V|Vs], I0, [K-(I0,V)|PVs]) :-
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get_atts(V,[order(K)]),
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I is I0+1,
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add_pos(Vs, I, PVs).
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remove_key([], [], []).
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remove_key([_-(I,V)|SVs], [V|OVs], [I|Map]) :-
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remove_key(SVs, OVs, Map).
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%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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% use top-down to generate average
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%
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run_though_avg(V, 3, Domain, Parents0, Vs, Vs2, Lvs, Outs, DIST) :-
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reorder_vars(Parents0, Parents, _Map),
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check_v(V, avg(Domain,Parents0), DIST, Vs, Vs1),
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DIST = info(V, Tree, Ev, [V0,V1,V2], Formula, [], []),
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get_parents(Parents, PVars, Vs1, Vs2),
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length(Parents, N),
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generate_3tree(F00, PVars, 0, 0, 0, N, N0, N1, N2, R, (N1+2*N2 =< N/2), (N1+2*(N2+R) =< N/2)),
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simplify_exp(F00, F0),
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% generate_3tree(F1, PVars, 0, 0, 0, N, N0, N1, N2, R, ((N1+2*(N2+R) > N/2, N1+2*N2 < (3*N)/2))),
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generate_3tree(F20, PVars, 0, 0, 0, N, N0, N1, N2, R, (N1+2*(N2+R) >= (3*N)/2), N1+2*N2 >= (3*N)/2),
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% simplify_exp(F20, F2),
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F20=F2,
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Formula0 = [V0=F0*Ev0,V2=F2*Ev2,V1=not(F0+F2)*Ev1],
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Ev = [Ev0,Ev1,Ev2],
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get_evidence(V, Tree, Ev, Formula0, Formula, Lvs, Outs).
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generate_3tree(OUT, _, I00, I10, I20, IR0, N0, N1, N2, R, _Exp, ExpF) :-
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IR is IR0-1,
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satisf(I00, I10, I20, IR, N0, N1, N2, R, ExpF),
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!,
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OUT = 1.
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generate_3tree(OUT, [[P0,P1,P2]], I00, I10, I20, IR0, N0, N1, N2, R, Exp, _ExpF) :-
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IR is IR0-1,
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( satisf(I00+1, I10, I20, IR, N0, N1, N2, R, Exp) ->
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L0 = [P0|L1]
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;
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L0 = L1
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),
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( satisf(I00, I10+1, I20, IR, N0, N1, N2, R, Exp) ->
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L1 = [P1|L2]
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;
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L1 = L2
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),
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( satisf(I00, I10, I20+1, IR, N0, N1, N2, R, Exp) ->
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L2 = [P2]
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;
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L2 = []
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),
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to_disj(L0, OUT).
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generate_3tree(OUT, [[P0,P1,P2]|Ps], I00, I10, I20, IR0, N0, N1, N2, R, Exp, ExpF) :-
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IR is IR0-1,
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( satisf(I00+1, I10, I20, IR, N0, N1, N2, R, Exp) ->
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I0 is I00+1, generate_3tree(O0, Ps, I0, I10, I20, IR, N0, N1, N2, R, Exp, ExpF)
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->
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L0 = [P0*O0|L1]
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;
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L0 = L1
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),
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( satisf(I00, I10+1, I20, IR0, N0, N1, N2, R, Exp) ->
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I1 is I10+1, generate_3tree(O1, Ps, I00, I1, I20, IR, N0, N1, N2, R, Exp, ExpF)
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->
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L1 = [P1*O1|L2]
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;
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L1 = L2
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),
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( satisf(I00, I10, I20+1, IR0, N0, N1, N2, R, Exp) ->
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I2 is I20+1, generate_3tree(O2, Ps, I00, I10, I2, IR, N0, N1, N2, R, Exp, ExpF)
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->
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L2 = [P2*O2]
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;
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L2 = []
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),
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to_disj(L0, OUT).
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satisf(I0, I1, I2, IR, N0, N1, N2, R, Exp) :-
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\+ \+ ( I0 = N0, I1=N1, I2=N2, IR=R, call(Exp) ).
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not_satisf(I0, I1, I2, IR, N0, N1, N2, R, Exp) :-
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\+ ( I0 = N0, I1=N1, I2=N2, IR=R, call(Exp) ).
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%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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% use top-down to generate average
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%
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top_down_with_tabling(V, Size, Domain, Parents0, Vs, Vs2, Lvs, Outs, DIST) :-
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reorder_vars(Parents0, Parents, _Map),
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check_v(V, avg(Domain,Parents), DIST, Vs, Vs1),
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DIST = info(V, Tree, Ev, OVs, Formula, [], []),
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get_parents(Parents, PVars, Vs1, Vs2),
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length(Parents, N),
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Max is (Size-1)*N, % This should be true
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avg_borders(0, Size, Max, Borders),
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b_hash_new(H0),
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avg_trees(0, Max, PVars, Size, F1, 0, Borders, OVs, Ev, H0, H),
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generate_avg_code(H, Formula, F),
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% Formula0 = [V0=F0*Ev0,V2=F2*Ev2,V1=not(F0+F2)*Ev1],
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% Ev = [Ev0,Ev1,Ev2],
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get_evidence(V, Tree, Ev, F1, F, Lvs, Outs).
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avg_trees(Size, _, _, Size, F0, _, F0, [], [], H, H) :- !.
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avg_trees(I0, Max, PVars, Size, [V=O*E|F0], Im, [IM|Borders], [V|OVs], [E|Ev], H0, H) :-
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I is I0+1,
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avg_tree(PVars, 0, Max, Im, IM, Size, O, H0, HI),
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Im1 is IM+1,
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avg_trees(I, Max, PVars, Size, F0, Im1, Borders, OVs, Ev, HI, H).
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avg_tree( _PVars, P, _, Im, IM, _Size, O, H0, H0) :-
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b_hash_lookup(k(P,Im,IM), O=_Exp, H0), !.
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avg_tree([], _P, _Max, _Im, _IM, _Size, 1, H, H).
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avg_tree([Vals|PVars], P, Max, Im, IM, Size, O, H0, HF) :-
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b_hash_insert(H0, k(P,Im,IM), O=Simp, HI),
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MaxI is Max-(Size-1),
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avg_exp(Vals, PVars, 0, P, MaxI, Size, Im, IM, HI, HF, Exp),
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simplify_exp(Exp, Simp).
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avg_exp([], _, _, _P, _Max, _Size, _Im, _IM, H, H, 0).
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avg_exp([Val|Vals], PVars, I0, P0, Max, Size, Im, IM, HI, HF, O) :-
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(Vals = [] -> O=O1 ; O = Val*O1+not(Val)*O2 ),
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Im1 is max(0, Im-I0),
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IM1 is IM-I0,
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( IM1 < 0 -> O1 = 0, H2 = HI; /* we have exceed maximum */
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Im1 > Max -> O1 = 0, H2 = HI; /* we cannot make to minimum */
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Im1 = 0, IM1 > Max -> O1 = 1, H2 = HI; /* we cannot exceed maximum */
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P is P0+1,
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avg_tree(PVars, P, Max, Im1, IM1, Size, O1, HI, H2)
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),
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I is I0+1,
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avg_exp(Vals, PVars, I, P0, Max, Size, Im, IM, H2, HF, O2).
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generate_avg_code(H, Formula, Formula0) :-
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b_hash_to_list(H,L),
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sort(L, S),
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strip_and_add(S, Formula0, Formula).
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strip_and_add([], F, F).
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strip_and_add([_-Exp|S], F0, F) :-
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strip_and_add(S, [Exp|F0], F).
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%%%%%%%%%%%%%%%%%%%%%%%%%
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%
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% use bottom-up dynamic programming to generate average
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%
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bup_avg(V, Size, Domain, Parents0, Vs, Vs2, Lvs, Outs, DIST) :-
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reorder_vars(Parents0, Parents, _),
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check_v(V, avg(Domain,Parents), DIST, Vs, Vs1),
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DIST = info(V, Tree, Ev, OVs, Formula, [], []),
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get_parents(Parents, PVars, Vs1, Vs2),
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length(Parents, N),
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Max is (Size-1)*N, % This should be true
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ArraySize is Max+1,
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functor(Protected, protected, ArraySize),
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avg_domains(0, Size, 0, Max, LDomains),
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Domains =.. [d|LDomains],
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Reach is (Size-1),
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generate_sums(PVars, Size, Max, Reach, Protected, Domains, ArraySize, Sums, F0),
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% bin_sums(PVars, Sums, F00),
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% reverse(F00,F0),
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% easier to do recursion on lists
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Sums =.. [_|LSums],
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generate_avg(0, Size, 0, Max, LSums, OVs, Ev, F1, []),
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reverse(F0, RF0),
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get_evidence(V, Tree, Ev, F1, F2, Lvs, Outs),
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append(RF0, F2, Formula).
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%
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% use binary approach, like what is standard
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%
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bin_sums(Vs, Sums, F) :-
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vs_to_sums(Vs, Sums0),
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bin_sums(Sums0, Sums, F, []).
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vs_to_sums([], []).
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vs_to_sums([V|Vs], [Sum|Sums0]) :-
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Sum =.. [sum|V],
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vs_to_sums(Vs, Sums0).
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bin_sums([Sum], Sum) --> !.
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bin_sums(LSums, Sum) -->
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{ halve(LSums, Sums1, Sums2) },
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bin_sums(Sums1, Sum1),
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bin_sums(Sums2, Sum2),
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sum(Sum1, Sum2, Sum).
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halve(LSums, Sums1, Sums2) :-
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length(LSums, L),
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Take is L div 2,
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head(Take, LSums, Sums1, Sums2).
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head(0, L, [], L) :- !.
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head(Take, [H|L], [H|Sums1], Sum2) :-
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Take1 is Take-1,
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head(Take1, L, Sums1, Sum2).
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sum(Sum1, Sum2, Sum) -->
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{ functor(Sum1, _, M1),
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functor(Sum2, _, M2),
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Max is M1+M2-2,
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Max1 is Max+1,
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Max0 is M2-1,
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functor(Sum, sum, Max1),
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Sum1 =.. [_|PVals] },
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expand_sums(PVals, 0, Max0, Max1, M2, Sum2, Sum).
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%
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% bottom up step by step
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%
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%
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generate_sums([PVals], Size, Max, _, _Protected, _Domains, _, Sum, []) :- !,
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Max is Size-1,
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Sum =.. [sum|PVals].
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generate_sums([PVals|Parents], Size, Max, Reach, Protected, Domains, ASize, NewSums, F) :-
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NewReach is Reach+(Size-1),
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generate_sums(Parents, Size, Max0, NewReach, Protected, Domains, ASize, Sums, F0),
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Max is Max0+(Size-1),
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Max1 is Max+1,
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functor(NewSums, sum, Max1),
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protect_avg(0, Max0, Protected, Domains, ASize, Reach),
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expand_sums(PVals, 0, Max0, Max1, Size, Sums, Protected, NewSums, F, F0).
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protect_avg(Max0,Max0,_Protected, _Domains, _ASize, _Reach) :- !.
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protect_avg(I0, Max0, Protected, Domains, ASize, Reach) :-
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I is I0+1,
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Top is I+Reach,
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( Top > ASize ;
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arg(I, Domains, CD),
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arg(Top, Domains, CD)
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), !,
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arg(I, Protected, yes),
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protect_avg(I, Max0, Protected, Domains, ASize, Reach).
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protect_avg(I0, Max0, Protected, Domains, ASize, Reach) :-
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I is I0+1,
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protect_avg(I, Max0, Protected, Domains, ASize, Reach).
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%
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% outer loop: generate array of sums at level j= Sum[j0...jMax]
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%
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expand_sums(_Parents, Max, _, Max, _Size, _Sums, _P, _NewSums, F0, F0) :- !.
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expand_sums(Parents, I0, Max0, Max, Size, Sums, Prot, NewSums, [O=SUM|F], F0) :-
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I is I0+1,
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arg(I, Prot, P),
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var(P), !,
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|
arg(I, NewSums, O),
|
|
sum_all(Parents, 0, I0, Max0, Sums, List),
|
|
to_disj(List, SUM),
|
|
expand_sums(Parents, I, Max0, Max, Size, Sums, Prot, NewSums, F, F0).
|
|
expand_sums(Parents, I0, Max0, Max, Size, Sums, Prot, NewSums, F, F0) :-
|
|
I is I0+1,
|
|
arg(I, Sums, O),
|
|
arg(I, NewSums, O),
|
|
expand_sums(Parents, I, Max0, Max, Size, Sums, Prot, NewSums, F, F0).
|
|
|
|
%
|
|
%inner loop: find all parents that contribute to A_ji,
|
|
% that is generate Pk*Sum_(j-1)l and k+l st k+l = i
|
|
%
|
|
sum_all([], _, _, _, _, []).
|
|
sum_all([V|Vs], Pos, I, Max0, Sums, [O|List]) :-
|
|
J is I-Pos,
|
|
J >= 0,
|
|
J =< Max0, !,
|
|
J1 is J+1,
|
|
arg(J1, Sums, S0),
|
|
( J < I -> O = V*S0 ; O = S0*V ),
|
|
Pos1 is Pos+1,
|
|
sum_all(Vs, Pos1, I, Max0, Sums, List).
|
|
sum_all([_V|Vs], Pos, I, Max0, Sums, List) :-
|
|
Pos1 is Pos+1,
|
|
sum_all(Vs, Pos1, I, Max0, Sums, List).
|
|
|
|
gen_arg(J, Sums, Max, S0) :-
|
|
gen_arg(0, Max, J, Sums, S0).
|
|
|
|
gen_arg(Max, Max, J, Sums, S0) :- !,
|
|
I is Max+1,
|
|
arg(I, Sums, A),
|
|
( Max = J -> S0 = A ; S0 = not(A)).
|
|
gen_arg(I0, Max, J, Sums, S) :-
|
|
I is I0+1,
|
|
arg(I, Sums, A),
|
|
( I0 = J -> S = A*S0 ; S = not(A)*S0),
|
|
gen_arg(I, Max, J, Sums, S0).
|
|
|
|
|
|
avg_borders(Size, Size, _Max, []) :- !.
|
|
avg_borders(I0, Size, Max, [J|Vals]) :-
|
|
I is I0+1,
|
|
Border is (I*Max)/Size,
|
|
J is integer(round(Border)),
|
|
avg_borders(I, Size, Max, Vals).
|
|
|
|
avg_domains(Size, Size, _J, _Max, []).
|
|
avg_domains(I0, Size, J0, Max, Vals) :-
|
|
I is I0+1,
|
|
Border is (I*Max)/Size,
|
|
fetch_domain_for_avg(J0, Border, J, I0, Vals, ValsI),
|
|
avg_domains(I, Size, J, Max, ValsI).
|
|
|
|
fetch_domain_for_avg(J, Border, J, _, Vals, Vals) :-
|
|
J > Border, !.
|
|
fetch_domain_for_avg(J0, Border, J, I0, [I0|LVals], RLVals) :-
|
|
J1 is J0+1,
|
|
fetch_domain_for_avg(J1, Border, J, I0, LVals, RLVals).
|
|
|
|
generate_avg(Size, Size, _J, _Max, [], [], [], F, F).
|
|
generate_avg(I0, Size, J0, Max, LSums, [O|OVs], [Ev|Evs], [O=Ev*Disj|F], F0) :-
|
|
I is I0+1,
|
|
Border is (I*Max)/Size,
|
|
fetch_for_avg(J0, Border, J, LSums, MySums, RSums),
|
|
to_disj(MySums, Disj),
|
|
generate_avg(I, Size, J, Max, RSums, OVs, Evs, F, F0).
|
|
|
|
fetch_for_avg(J, Border, J, RSums, [], RSums) :-
|
|
J > Border, !.
|
|
fetch_for_avg(J0, Border, J, [S|LSums], [S|MySums], RSums) :-
|
|
J1 is J0+1,
|
|
fetch_for_avg(J1, Border, J, LSums, MySums, RSums).
|
|
|
|
|
|
to_disj([], 0).
|
|
to_disj([V], V).
|
|
to_disj([V,V1|Vs], Out) :-
|
|
to_disj2([V1|Vs], V, Out).
|
|
|
|
to_disj2([V], V0, V0+V).
|
|
to_disj2([V,V1|Vs], V0, Out) :-
|
|
to_disj2([V1|Vs], V0+V, Out).
|
|
|
|
|
|
%
|
|
% look for parameters in the rb-tree, or add a new.
|
|
% distid is the key
|
|
%
|
|
check_p(DistId, Map, Parms, ParmVars, Ps, Ps) :-
|
|
rb_lookup(DistId-Map, theta(Parms, ParmVars), Ps), !.
|
|
check_p(DistId, Map, Parms, ParmVars, Ps, PsF) :-
|
|
get_dist_params(DistId, Parms0),
|
|
get_dist_all_sizes(DistId, Sizes),
|
|
swap_parms(Parms0, Sizes, [0|Map], Parms1),
|
|
length(Parms1, L0),
|
|
get_dist_domain_size(DistId, Size),
|
|
L1 is L0 div Size,
|
|
L is L0-L1,
|
|
initial_maxes(L1, Multipliers),
|
|
copy(L, Multipliers, NextMults, NextMults, Parms1, Parms, ParmVars),
|
|
%writeln(t:Size:Parms0:Parms:ParmVars),
|
|
rb_insert(Ps, DistId-Map, theta(Parms, ParmVars), PsF).
|
|
|
|
swap_parms(Parms0, Sizes, Map, Parms1) :-
|
|
matrix_new(floats, Sizes, Parms0, T0),
|
|
matrix_shuffle(T0,Map,TF),
|
|
matrix_to_list(TF, Parms1).
|
|
|
|
%
|
|
% we are using switches by two
|
|
%
|
|
initial_maxes(0, []) :- !.
|
|
initial_maxes(Size, [1.0|Multipliers]) :- !,
|
|
Size1 is Size-1,
|
|
initial_maxes(Size1, Multipliers).
|
|
|
|
copy(0, [], [], _, _Parms0, [], []) :- !.
|
|
copy(N, [], [], Ms, Parms0, Parms, ParmVars) :-!,
|
|
copy(N, Ms, NewMs, NewMs, Parms0, Parms, ParmVars).
|
|
copy(N, D.Ds, ND.NDs, New, El.Parms0, NEl.Parms, V.ParmVars) :-
|
|
N1 is N-1,
|
|
(El == 0.0 ->
|
|
NEl = 0,
|
|
V = NEl,
|
|
ND = D
|
|
;El == 1.0 ->
|
|
NEl = 1,
|
|
V = NEl,
|
|
ND = 0.0
|
|
;El == 0 ->
|
|
NEl = 0,
|
|
V = NEl,
|
|
ND = D
|
|
;El =:= 1 ->
|
|
NEl = 1,
|
|
V = NEl,
|
|
ND = 0.0,
|
|
V = NEl
|
|
;
|
|
NEl is El/D,
|
|
ND is D-El,
|
|
V = NEl
|
|
),
|
|
copy(N1, Ds, NDs, New, Parms0, Parms, ParmVars).
|
|
|
|
unbound_parms([], []).
|
|
unbound_parms(_.Parms, _.ParmVars) :-
|
|
unbound_parms(Parms, ParmVars).
|
|
|
|
check_v(V, _, INFO, Vs, Vs) :-
|
|
rb_lookup(V, INFO, Vs), !.
|
|
check_v(V, DistId, INFO, Vs0, Vs) :-
|
|
get_dist_domain_size(DistId, Size),
|
|
length(Values, Size),
|
|
length(Ev, Size),
|
|
INFO = info(V, _Tree, Ev, Values, _Formula, _, _),
|
|
rb_insert(Vs0, V, INFO, Vs).
|
|
|
|
get_parents([], [], Vs, Vs).
|
|
get_parents(V.Parents, Values.PVars, Vs0, Vs) :-
|
|
clpbn:get_atts(V, [dist(DistId, _)]),
|
|
check_v(V, DistId, INFO, Vs0, Vs1),
|
|
INFO = info(V, _Parent, _Ev, Values, _, _, _),
|
|
get_parents(Parents, PVars, Vs1, Vs).
|
|
|
|
%
|
|
% construct the formula, this is the key...
|
|
%
|
|
cross_product(Values, Ev, PVars, ParmVars, Formulas) :-
|
|
arrangements(PVars, Arranges),
|
|
apply_parents_first(Values, Ev, ParmCombos, ParmCombos, Arranges, Formulas, ParmVars).
|
|
|
|
%
|
|
% if we have the parent variables with two values, we get
|
|
% [[XP,YP],[XP,YN],[XN,YP],[XN,YN]]
|
|
%
|
|
arrangements([], [[]]).
|
|
arrangements([L1|Ls],O) :-
|
|
arrangements(Ls, LN),
|
|
expand(L1, LN, O, []).
|
|
|
|
expand([], _LN) --> [].
|
|
expand([H|L1], LN) -->
|
|
concatenate_all(H, LN),
|
|
expand(L1, LN).
|
|
|
|
concatenate_all(_H, []) --> [].
|
|
concatenate_all(H, L.LN) -->
|
|
[[H|L]],
|
|
concatenate_all(H, LN).
|
|
|
|
%
|
|
% core of algorithm
|
|
%
|
|
% Values -> Output Vars for BDD
|
|
% Es -> Evidence variables
|
|
% Previous -> top of difference list with parameters used so far
|
|
% P0 -> end of difference list with parameters used so far
|
|
% Pvars -> Parents
|
|
% Eqs -> Output Equations
|
|
% Pars -> Output Theta Parameters
|
|
%
|
|
apply_parents_first([Value], [E], Previous, [], PVars, [Value=Disj*E], Parameters) :- !,
|
|
apply_last_parent(PVars, Previous, Disj),
|
|
flatten(Previous, Parameters).
|
|
apply_parents_first([Value|Values], [E|Ev], Previous, P0, PVars, (Value=Disj*E).Formulas, Parameters) :-
|
|
P0 = [TheseParents|End],
|
|
apply_first_parent(PVars, Disj, TheseParents),
|
|
apply_parents_second(Values, Ev, Previous, End, PVars, Formulas, Parameters).
|
|
|
|
apply_parents_second([Value], [E], Previous, [], PVars, [Value=Disj*E], Parameters) :- !,
|
|
apply_last_parent(PVars, Previous, Disj),
|
|
flatten(Previous, Parameters).
|
|
apply_parents_second([Value|Values], [E|Ev], Previous, P0, PVars, (Value=Disj*E).Formulas, Parameters) :-
|
|
apply_middle_parent(PVars, Previous, Disj, TheseParents),
|
|
% this must be done after applying middle parents because of the var
|
|
% test.
|
|
P0 = [TheseParents|End],
|
|
apply_parents_second(Values, Ev, Previous, End, PVars, Formulas, Parameters).
|
|
|
|
apply_first_parent([Parents], Conj, [Theta]) :- !,
|
|
parents_to_conj(Parents,Theta,Conj).
|
|
apply_first_parent(Parents.PVars, Conj+Disj, Theta.TheseParents) :-
|
|
parents_to_conj(Parents,Theta,Conj),
|
|
apply_first_parent(PVars, Disj, TheseParents).
|
|
|
|
apply_middle_parent([Parents], Other, Conj, [ThetaPar]) :- !,
|
|
skim_for_theta(Other, Theta, _, ThetaPar),
|
|
parents_to_conj(Parents,Theta,Conj).
|
|
apply_middle_parent(Parents.PVars, Other, Conj+Disj, ThetaPar.TheseParents) :-
|
|
skim_for_theta(Other, Theta, Remaining, ThetaPar),
|
|
parents_to_conj(Parents,(Theta),Conj),
|
|
apply_middle_parent(PVars, Remaining, Disj, TheseParents).
|
|
|
|
apply_last_parent([Parents], Other, Conj) :- !,
|
|
parents_to_conj(Parents,(Theta),Conj),
|
|
skim_for_theta(Other, Theta, _, _).
|
|
apply_last_parent(Parents.PVars, Other, Conj+Disj) :-
|
|
parents_to_conj(Parents,(Theta),Conj),
|
|
skim_for_theta(Other, Theta, Remaining, _),
|
|
apply_last_parent(PVars, Remaining, Disj).
|
|
|
|
%
|
|
%
|
|
% simplify stuff, removing process that is cancelled by 0s
|
|
%
|
|
parents_to_conj([], Theta, Theta) :- !.
|
|
parents_to_conj(Ps, Theta, Theta*Conj) :-
|
|
parents_to_conj2(Ps, Conj).
|
|
|
|
parents_to_conj2([P],P) :- !.
|
|
parents_to_conj2(P.Ps,P*Conj) :-
|
|
parents_to_conj2(Ps,Conj).
|
|
|
|
%
|
|
% first case we haven't reached the end of the list so we need
|
|
% to create a new parameter variable
|
|
%
|
|
skim_for_theta([[P|Other]|V], not(P)*New, [Other|_], New) :- var(V), !.
|
|
%
|
|
% last theta, it is just negation of the other ones
|
|
%
|
|
skim_for_theta([[P|Other]], not(P), [Other], _) :- !.
|
|
%
|
|
% recursive case, build-up
|
|
%
|
|
skim_for_theta([[P|Other]|More], not(P)*Ps, [Other|Left], New ) :-
|
|
skim_for_theta(More, Ps, Left, New ).
|
|
|
|
get_evidence(V, Tree, Ev, F0, F, Leaves, Finals) :-
|
|
clpbn:get_atts(V, [evidence(Pos)]), !,
|
|
zero_pos(0, Pos, Ev),
|
|
insert_output(Leaves, V, Finals, Tree, Outs, SendOut),
|
|
get_outs(F0, F, SendOut, Outs).
|
|
% hidden deterministic node, can be removed.
|
|
get_evidence(V, _Tree, Ev, F0, [], _Leaves, _Finals) :-
|
|
clpbn:get_atts(V, [key(K)]),
|
|
functor(K, Name, 2),
|
|
( Name = 'AVG' ; Name = 'MAX' ; Name = 'MIN' ),
|
|
!,
|
|
one_list(Ev),
|
|
eval_outs(F0).
|
|
%% no evidence !!!
|
|
get_evidence(V, Tree, _Values, F0, F1, Leaves, Finals) :-
|
|
insert_output(Leaves, V, Finals, Tree, Outs, SendOut),
|
|
get_outs(F0, F1, SendOut, Outs).
|
|
|
|
zero_pos(_, _Pos, []).
|
|
zero_pos(Pos, Pos, 1.Values) :- !,
|
|
I is Pos+1,
|
|
zero_pos(I, Pos, Values).
|
|
zero_pos(I0, Pos, 0.Values) :-
|
|
I is I0+1,
|
|
zero_pos(I, Pos, Values).
|
|
|
|
one_list([]).
|
|
one_list(1.Ev) :-
|
|
one_list(Ev).
|
|
|
|
%
|
|
% insert a node with the disj of all alternatives, this is only done if node ends up to be in the output
|
|
%
|
|
insert_output([], _V, [], _Out, _Outs, []).
|
|
insert_output(V._Leaves, V0, [Top|_], Top, Outs, [Top = Outs]) :- V == V0, !.
|
|
insert_output(_.Leaves, V, _.Finals, Top, Outs, SendOut) :-
|
|
insert_output(Leaves, V, Finals, Top, Outs, SendOut).
|
|
|
|
|
|
get_outs([V=F], [V=NF|End], End, V) :- !,
|
|
% writeln(f0:F),
|
|
simplify_exp(F,NF).
|
|
get_outs((V=F).Outs, (V=NF).NOuts, End, (F0 + V)) :-
|
|
% writeln(f0:F),
|
|
simplify_exp(F,NF),
|
|
get_outs(Outs, NOuts, End, F0).
|
|
|
|
eval_outs([]).
|
|
eval_outs((V=F).Outs) :-
|
|
simplify_exp(F,NF),
|
|
V = NF,
|
|
eval_outs(Outs).
|
|
|
|
run_bdd_solver([[V]], LPs, bdd(Term, _Leaves, Nodes)) :-
|
|
build_out_node(Nodes, Node),
|
|
findall(Prob, get_prob(Term, Node, V, Prob),TermProbs),
|
|
sumlist(TermProbs, Sum),
|
|
writeln(TermProbs:Sum),
|
|
normalise(TermProbs, Sum, LPs).
|
|
|
|
build_out_node([_Top], []).
|
|
build_out_node([T,T1|Tops], [Top = T*Top]) :-
|
|
build_out_node2(T1.Tops, Top).
|
|
|
|
build_out_node2([Top], Top).
|
|
build_out_node2([T,T1|Tops], T*Top) :-
|
|
build_out_node2(T1.Tops, Top).
|
|
|
|
|
|
get_prob(Term, Node, V, SP) :-
|
|
bind_all(Term, Node, Bindings, V, AllParms, AllParmValues),
|
|
% reverse(AllParms, RAllParms),
|
|
term_variables(AllParms, NVs),
|
|
build_bdd(Bindings, NVs, AllParms, AllParmValues, Bdd),
|
|
bdd_to_probability_sum_product(Bdd, SP),
|
|
bdd_close(Bdd).
|
|
|
|
build_bdd(Bindings, NVs, VTheta, Theta, Bdd) :-
|
|
bdd_from_list(Bindings, NVs, Bdd),
|
|
bdd_size(Bdd, Len),
|
|
number_codes(Len,Codes),
|
|
atom_codes(Name,Codes),
|
|
bdd_print(Bdd, Name),
|
|
writeln(length=Len),
|
|
VTheta = Theta.
|
|
|
|
bind_all([], End, End, _V, [], []).
|
|
bind_all(info(V, _Tree, Ev, _Values, Formula, ParmVars, Parms).Term, End, BindsF, V0, ParmVars.AllParms, Parms.AllTheta) :-
|
|
V0 == V, !,
|
|
set_to_one_zeros(Ev),
|
|
bind_formula(Formula, BindsF, BindsI),
|
|
bind_all(Term, End, BindsI, V0, AllParms, AllTheta).
|
|
bind_all(info(_V, _Tree, Ev, _Values, Formula, ParmVars, Parms).Term, End, BindsF, V0, ParmVars.AllParms, Parms.AllTheta) :-
|
|
set_to_ones(Ev),!,
|
|
bind_formula(Formula, BindsF, BindsI),
|
|
bind_all(Term, End, BindsI, V0, AllParms, AllTheta).
|
|
% evidence: no need to add any stuff.
|
|
bind_all(info(_V, _Tree, _Ev, _Values, Formula, ParmVars, Parms).Term, End, BindsF, V0, ParmVars.AllParms, Parms.AllTheta) :-
|
|
bind_formula(Formula, BindsF, BindsI),
|
|
bind_all(Term, End, BindsI, V0, AllParms, AllTheta).
|
|
|
|
bind_formula([], L, L).
|
|
bind_formula(B.Formula, B.BsF, Bs0) :-
|
|
bind_formula(Formula, BsF, Bs0).
|
|
|
|
set_to_one_zeros([1|Values]) :-
|
|
set_to_zeros(Values).
|
|
set_to_one_zeros([0|Values]) :-
|
|
set_to_one_zeros(Values).
|
|
|
|
set_to_zeros([]).
|
|
set_to_zeros(0.Values) :-
|
|
set_to_zeros(Values).
|
|
|
|
set_to_ones([]).
|
|
set_to_ones(1.Values) :-
|
|
set_to_ones(Values).
|
|
|
|
normalise([], _Sum, []).
|
|
normalise(P.TermProbs, Sum, NP.LPs) :-
|
|
NP is P/Sum,
|
|
normalise(TermProbs, Sum, LPs).
|
|
|
|
finalize_bdd_solver(_).
|
|
|