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yap-6.3/packages/CLPBN/clpbn/matrix_cpt_utils.yap
2012-01-10 17:01:06 +00:00

271 lines
6.7 KiB
Prolog

:- module(clpbn_matrix_utils,
[init_CPT/2,
project_from_CPT/3,
reorder_CPT/5,
get_CPT_sizes/2,
normalise_CPT/2,
multiply_CPTs/4,
divide_CPTs/3,
expand_CPT/4,
reset_CPT_that_disagrees/5,
unit_CPT/2,
sum_out_from_CPT/4,
list_from_CPT/2,
multiply_factors/3,
normalise_possibly_deterministic_CPT/2,
column_from_possibly_deterministic_CPT/3,
multiply_possibly_deterministic_factors/3,
random_CPT/2,
uniform_CPT/2,
uniform_CPT_as_list/2,
normalise_CPT_on_lines/3]).
:- use_module(dists,
[get_dist_domain_size/2,
get_dist_domain/2]).
:- use_module(library(matrix),
[matrix_new/4,
matrix_new_set/4,
matrix_select/4,
matrix_dims/2,
matrix_size/2,
matrix_shuffle/3,
matrix_expand/3,
matrix_op/4,
matrix_dims/2,
matrix_sum/2,
matrix_sum_logs_out/3,
matrix_sum_out/3,
matrix_sum_logs_out_several/3,
matrix_op_to_all/4,
matrix_to_exps2/1,
matrix_to_logs/1,
matrix_set_all_that_disagree/5,
matrix_to_list/2,
matrix_agg_lines/3,
matrix_agg_cols/3,
matrix_op_to_lines/4,
matrix_column/3]).
init_CPT(List, Sizes, TAB) :-
matrix_new(floats, Sizes, List, TAB),
matrix_to_logs(TAB).
init_possibly_deterministic_CPT(List, Sizes, TAB) :-
matrix_new(floats, Sizes, List, TAB).
project_from_CPT(V,tab(Table,Deps,_),tab(NewTable,NDeps,NSzs)) :-
evidence(V,Pos), !,
vnth(Deps, 0, V, N, NDeps),
matrix_select(Table, N, Pos, NewTable),
matrix_dims(NewTable, NSzs).
project_from_CPT(V,tab(Table,Deps,_),tab(NewTable,NDeps,NSzs)) :-
vnth(Deps, 0, V, N, NDeps),
% matrix_to_exps2(Table),
matrix_sum_logs_out(Table, N, NewTable),
% matrix_to_logs(NewTable),
matrix_dims(NewTable, NSzs).
evidence(V, Pos) :-
clpbn:get_atts(V, [evidence(Pos)]).
vnth([V1|Deps], N, V, N, Deps) :-
V == V1, !.
vnth([V1|Deps], N0, V, N, [V1|NDeps]) :-
N1 is N0+1,
vnth(Deps, N1, V, N, NDeps).
reorder_CPT(Vs0,T0,Vs,TF,Sizes) :-
var(Vs), !,
order_vec(Vs0,Vs,Map),
(
Vs == Vs0
->
TF = T0
;
matrix_shuffle(T0,Map,TF)
),
matrix_dims(TF, Sizes).
reorder_CPT(Vs0,T0,Vs,TF,Sizes) :-
mapping(Vs0,Vs,Map),
(
Vs == Vs0
->
TF = T0
;
matrix_shuffle(T0,Map,TF)
),
matrix_dims(TF, Sizes).
order_vec(Vs0,Vs,Map) :-
add_indices(Vs0,0,Is),
keysort(Is,NIs),
get_els(NIs, Vs, Map).
add_indices([],_,[]).
add_indices([V|Vs0],I0,[V-I0|Is]) :-
I is I0+1,
add_indices(Vs0,I,Is).
get_els([], [], []).
get_els([V-I|NIs], [V|Vs], [I|Map]) :-
get_els(NIs, Vs, Map).
mapping(Vs0,Vs,Map) :-
add_indices(Vs0,0,I1s),
add_indices( Vs,I2s),
keysort(I1s,Ks),
keysort(I2s,Ks),
split_map(I2s, Map).
add_indices([],[]).
add_indices([V|Vs0],[V-_|I1s]) :-
add_indices(Vs0,I1s).
split_map([], []).
split_map([_-M|Is], [M|Map]) :-
split_map(Is, Map).
divide_CPTs(Tab1, Tab2, OT) :-
matrix_op(Tab1,Tab2,-,OT).
multiply_CPTs(tab(Tab1, Deps1, Sz1), tab(Tab2, Deps2, Sz2), tab(OT, NDeps, NSz), NTab2) :-
expand_tabs(Deps1, Sz1, Deps2, Sz2, Map1, Map2, NDeps),
matrix_expand_compact(Tab1, Map1, NTab1),
matrix_expand_compact(Tab2, Map2, NTab2),
matrix_op(NTab1,NTab2,+,OT),
matrix_dims(OT,NSz).
expand_tabs([], [], [], [], [], [], []).
expand_tabs([V1|Deps1], [S1|Sz1], [], [], [0|Map1], [S1|Map2], [V1|NDeps]) :-
expand_tabs(Deps1, Sz1, [], [], Map1, Map2, NDeps).
expand_tabs([], [], [V2|Deps2], [S2|Sz2], [S2|Map1], [0|Map2], [V2|NDeps]) :-
expand_tabs([], [], Deps2, Sz2, Map1, Map2, NDeps).
expand_tabs([V1|Deps1], [S1|Sz1], [V2|Deps2], [S2|Sz2], Map1, Map2, NDeps) :-
compare(C,V1,V2),
(C == = ->
NDeps = [V1|MDeps],
Map1 = [0|M1],
Map2 = [0|M2],
NDeps = [V1|MDeps],
expand_tabs(Deps1, Sz1, Deps2, Sz2, M1, M2, MDeps)
;
C == < ->
NDeps = [V1|MDeps],
Map1 = [0|M1],
Map2 = [S1|M2],
NDeps = [V1|MDeps],
expand_tabs(Deps1, Sz1, [V2|Deps2], [S2|Sz2], M1, M2, MDeps)
;
NDeps = [V2|MDeps],
Map1 = [S2|M1],
Map2 = [0|M2],
NDeps = [V2|MDeps],
expand_tabs([V1|Deps1], [S1|Sz1], Deps2, Sz2, M1, M2, MDeps)
).
normalise_CPT(MAT,NMAT) :-
matrix_to_exps2(MAT),
matrix_sum(MAT, Sum),
matrix_op_to_all(MAT, /, Sum, NMAT).
list_from_CPT(MAT, List) :-
matrix_to_list(MAT, List).
expand_CPT(MAT0, Dims0, DimsNew, MAT) :-
generate_map(DimsNew, Dims0, Map),
matrix_expand(MAT0, Map, MAT).
generate_map([], [], []).
generate_map([V|DimsNew], [V0|Dims0], [0|Map]) :- V == V0, !,
generate_map(DimsNew, Dims0, Map).
generate_map([V|DimsNew], Dims0, [Sz|Map]) :-
clpbn:get_atts(V, [dist(Id,_)]),
get_dist_domain_size(Id, Sz),
generate_map(DimsNew, Dims0, Map).
unit_CPT(V,CPT) :-
clpbn:get_atts(V, [dist(Id,_)]),
get_dist_domain_size(Id, Sz),
matrix_new_set(floats,[Sz],1.0,CPT).
reset_CPT_that_disagrees(CPT, Vars, V, Pos, NCPT) :-
vnth(Vars, 0, V, Dim, _),
matrix_set_all_that_disagree(CPT, Dim, Pos, -inf, NCPT).
sum_out_from_CPT(Vs,Table,Deps,tab(NewTable,Vs,Sz)) :-
conversion_matrix(Vs, Deps, Conv),
matrix_sum_logs_out_several(Table, Conv, NewTable),
matrix_dims(NewTable, Sz).
conversion_matrix([], [], []).
conversion_matrix([], [_|Deps], [1|Conv]) :-
conversion_matrix([], Deps, Conv).
conversion_matrix([V|Vs], [V1|Deps], [0|Conv]) :- V==V1, !,
conversion_matrix(Vs, Deps, Conv).
conversion_matrix([V|Vs], [_|Deps], [1|Conv]) :-
conversion_matrix([V|Vs], Deps, Conv).
get_CPT_sizes(CPT, Sizes) :-
matrix_dims(CPT, Sizes).
matrix_expand_compact(M0,Zeros,M0) :-
zero_map(Zeros), !.
matrix_expand_compact(M0,Map,M) :-
matrix_expand(M0, Map, M).
zero_map([]).
zero_map([0|Zeros]) :-
zero_map(Zeros).
col_from_CPT(CPT, Parents, Column) :-
matrix_col(CPT, Parents, Column),
matrix_to_logs(Column).
column_from_possibly_deterministic_CPT(CPT, Parents, Column) :-
matrix_column(CPT, Parents, Column).
multiply_factors(F1, F2, F) :-
matrix_op(F1,F2,+,F).
multiply_possibly_deterministic_factors(F1, F2, F) :-
matrix_op(F1,F2,*,F).
normalise_possibly_deterministic_CPT(MAT,NMAT) :-
matrix_agg_lines(MAT, +, Sum),
matrix_op_to_lines(MAT, Sum, /, NMAT).
random_CPT(Dims, M) :-
mult_all(Dims,1,Size),
generate_random_entries(Size, Randoms),
matrix_new(floats, Dims, Randoms, M1),
normalise_possibly_deterministic_CPT(M1, M).
mult_all([],Size,Size).
mult_all([D|Dims],Size0,Size) :-
Size1 is Size0*D,
mult_all(Dims,Size1,Size).
generate_random_entries(0, []) :- !.
generate_random_entries(Size, [R|Randoms]) :-
R is random,
Size1 is Size-1,
generate_random_entries(Size1, Randoms).
uniform_CPT_as_list(Dims, L) :-
uniform_CPT(Dims, M),
matrix_to_list(M, L).
uniform_CPT(Dims, M) :-
matrix_new_set(floats,Dims,1.0,M1),
normalise_possibly_deterministic_CPT(M1, M).
normalise_CPT_on_lines(MAT0, MAT2, L1) :-
matrix_agg_cols(MAT0, +, MAT1),
matrix_sum(MAT1, SUM),
matrix_op_to_all(MAT1, /, SUM, MAT2),
matrix:matrix_to_list(MAT2,L1).