📄 marginalize_pot.m
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function smallpot = marginalize_pot(bigpot, keep, maximize, useC)% MARGINALIZE_POT Marginalize a cpot onto a smaller domain.% smallpot = marginalize_pot(bigpot, keep, maximize, useC)%% The maximize argument is ignored - maxing out a Gaussian is the same as summing it out,% since the mode and mean are equal.% The useC argument is ignored.node_sizes = sparse(1, max(bigpot.domain));node_sizes(bigpot.domain) = bigpot.sizes;sum_over = mysetdiff(bigpot.domain, keep);if sum(node_sizes(sum_over))==0 % isempty(sum_over) %smallpot = bigpot; smallpot = cpot(keep, node_sizes(keep), bigpot.g, bigpot.h, bigpot.K);else [h1, h2, K11, K12, K21, K22] = partition_matrix_vec(bigpot.h, bigpot.K, sum_over, keep, node_sizes); n = length(h1); K11inv = inv(K11); g = bigpot.g + 0.5*(n*log(2*pi) - log(det(K11)) + h1'*K11inv*h1); if length(h2) > 0 % ~isempty(keep) % we are are actually keeping something A = K21*K11inv; h = h2 - A*h1; K = K22 - A*K12; else h = []; K = []; end smallpot = cpot(keep, node_sizes(keep), g, h, K);end
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