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function cache = score_init_cache(N,L)
% SCORE_INIT_CACHE generate an empty cache for local computation in structure learning
% cache = score_init_cache(number_of_nodes,cache_size)
%
% For 2 nodes with cache of size 5 :
%
% cache =
% Nw b 0 0 0 --> Nw=number of writings in cache (+1) and b==1 iff the cache is full
% 0 0 1 -239.12 1 --> 1st familly in the cache (node 1 without parents) calculate with bic
% 0 0 2 -318.98 1
% 1 0 2 -189.23 2 --> 3rd familly in the cache (node 2 with 1 as parent) calculate with bayesian
% 0 1 1 -251.09 1
% 0 0 0 0 0 --> empty entry
% | | | | |
% | | | | |___> scoring function : 1 for 'bic', 2 for 'bayesian', ...
% | | | |__________> local score of the familly
% | | |_________________> son node of the familly
% | |__________________________> ==1 iff node 2 is parent of son node
% |______________________________> ==1 iff node 1 is parent of son node
%
%
% V1.1 : 6 may 2003 (O. Francois - francois.olivier.c.h@gmail.com, Ph. Leray - philippe.leray@univ-nantes.fr)
%
%
cache=zeros(L+1,N+3);
cache(1,1)=2;
% using a sparse matrix does not improve performances
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