Mercurial > hg > camir-aes2014
view toolboxes/FullBNT-1.0.7/bnt/CPDs/@softmax_CPD/convert_to_pot.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
---|---|
date | Tue, 10 Feb 2015 15:05:51 +0000 |
parents | |
children |
line wrap: on
line source
function pot = convert_to_pot(CPD, pot_type, domain, evidence) % CONVERT_TO_POT Convert a softmax CPD to a potential % pots = convert_to_pot(CPD, pot_type, domain, evidence) % % pots = CPD evaluated using evidence(domain) ncases = size(domain,2); assert(ncases==1); % not yet vectorized sz = dom_sizes(CPD); ns = zeros(1, max(domain)); ns(domain) = sz; odom = domain(~isemptycell(evidence(domain))); T = convert_to_table(CPD, domain, evidence); switch pot_type case 'u', pot = upot(domain, sz, T, 0*myones(sz)); case 'd', ns(odom) = 1; pot = dpot(domain, ns(domain), T); case {'c','g'}, % Since we want the output to be a Gaussian, the whole family must be observed. % In other words, the potential is really just a constant. p = T; %p = prob_node(CPD, evidence(domain(end)), evidence(domain(1:end-1))); ns(domain) = 0; pot = cpot(domain, ns(domain), log(p)); case 'cg', T = T(:); ns(odom) = 1; can = cell(1, length(T)); for i=1:length(T) can{i} = cpot([], [], log(T(i))); end ps = domain(1:end-1); dps = ps(CPD.dpndx); cps = ps(CPD.cpndx); ddom = [dps CPD.self]; cdom = cps; pot = cgpot(ddom, cdom, ns, can); case 'scg' T = T(:); ns(odom) = 1; pot_array = cell(1, length(T)); for i=1:length(T) pot_array{i} = scgcpot([], [], T(i)); end pot = scgpot(domain, [], [], ns, pot_array); otherwise, error(['unrecognized pot type ' pot_type]) end