64 lines
1.4 KiB
Prolog
64 lines
1.4 KiB
Prolog
%
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% Utilities for learning
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%
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:- module(clpbn_learn_utils, [run_all/1,
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clpbn_vars/2,
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normalise_counts/2,
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compute_likelihood/3]).
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:- use_module(library(matrix),
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[matrix_agg_lines/3,
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matrix_op_to_lines/4,
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matrix_to_logs/2,
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matrix_op/4,
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matrix_sum/2]).
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:- meta_predicate run_all(:).
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run_all([]).
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run_all([G|Gs]) :-
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call(G),
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run_all(Gs).
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run_all(M:Gs) :-
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run_all(Gs,M).
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run_all([],_).
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run_all([G|Gs],M) :-
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call(M:G),
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run_all(Gs,M).
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clpbn_vars(Vs,BVars) :-
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get_clpbn_vars(Vs,CVs),
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keysort(CVs,KVs),
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merge_vars(KVs,BVars).
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get_clpbn_vars([],[]).
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get_clpbn_vars([V|GVars],[K-V|CLPBNGVars]) :-
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clpbn:get_atts(V, [key(K)]), !,
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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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merge_vars([],[]).
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merge_vars([K-V|KVs],[V|BVars]) :-
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get_var_has_same_key(KVs,K,V,KVs0),
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merge_vars(KVs0,BVars).
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get_var_has_same_key([K-V|KVs],K,V,KVs0) :- !,
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get_var_has_same_key(KVs,K,V,KVs0).
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get_var_has_same_key(KVs,_,_,KVs).
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normalise_counts(MAT,NMAT) :-
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matrix_agg_lines(MAT, +, Sum),
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matrix_op_to_lines(MAT, Sum, /, NMAT).
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compute_likelihood(Table0, NewTable, DeltaLik) :-
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matrix:matrix_to_list(Table0,L0), writeln(L0),
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matrix:matrix_to_list(NewTable,L1), writeln(L1),
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matrix_to_logs(NewTable, Logs),
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matrix_op(Table0, Logs, *, Logs),
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matrix_sum(Logs, DeltaLik).
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