diff options
Diffstat (limited to 'sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine')
12 files changed, 216 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Entries new file mode 100644 index 00000000..dce274e1 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Entries @@ -0,0 +1,5 @@ +/enter_evidence.m/1.1.1.1/Wed May 29 15:59:56 2002// +/kalman_inf_engine.m/1.1.1.1/Wed May 29 15:59:56 2002// +/marginal_nodes.m/1.1.1.1/Wed May 29 15:59:56 2002// +/update_engine.m/1.1.1.1/Wed May 29 15:59:56 2002// +D/private//// diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Repository new file mode 100644 index 00000000..674f2eea --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Repository @@ -0,0 +1 @@ +FullBNT/BNT/inference/dynamic/@kalman_inf_engine diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Root new file mode 100644 index 00000000..f3bd14a6 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/CVS/Root @@ -0,0 +1 @@ +:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/enter_evidence.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/enter_evidence.m new file mode 100644 index 00000000..4ba51942 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/enter_evidence.m @@ -0,0 +1,83 @@ +function [engine, loglik] = enter_evidence(engine, evidence, varargin) +% ENTER_EVIDENCE Add the specified evidence to the network (kalman) +% [engine, loglik] = enter_evidence(engine, evidence, ...) +% +% evidence{i,t} = [] if if X(i,t) is hidden, and otherwise contains its observed value (scalar or column vector) +% +% The following optional arguments can be specified in the form of name/value pairs: +% [default value in brackets] +% +% maximize - if 1, does max-product (same as sum-product for Gaussians!), else sum-product [0] +% filter - if 1, do filtering, else smoothing [0] +% +% e.g., engine = enter_evidence(engine, ev, 'maximize', 1) + +maximize = 0; +filter = 0; + +% parse optional params +args = varargin; +nargs = length(args); +if nargs > 0 + for i=1:2:nargs + switch args{i}, + case 'maximize', maximize = args{i+1}; + case 'filter', filter = args{i+1}; + otherwise, + error(['invalid argument name ' args{i}]); + end + end +end + +assert(~maximize); + +bnet = bnet_from_engine(engine); +n = length(bnet.intra); +onodes = bnet.observed; +hnodes = mysetdiff(1:n, onodes); +T = size(evidence, 2); +ns = bnet.node_sizes; +O = sum(ns(onodes)); +data = reshape(cat(1, evidence{onodes,:}), [O T]); + +A = engine.trans_mat; +C = engine.obs_mat; +Q = engine.trans_cov; +R = engine.obs_cov; +init_x = engine.init_state; +init_V = engine.init_cov; + +if filter + [x, V, VV, loglik] = kalman_filter(data, A, C, Q, R, init_x, init_V); +else + [x, V, VV, loglik] = kalman_smoother(data, A, C, Q, R, init_x, init_V); +end + + +% Wrap the posterior inside a potential, so it can be marginalized easily +engine.one_slice_marginal = cell(1,T); +engine.two_slice_marginal = cell(1,T); +ns(onodes) = 0; +ns(onodes+n) = 0; +ss = length(bnet.intra); +for t=1:T + dom = (1:n); + engine.one_slice_marginal{t} = mpot(dom+(t-1)*ss, ns(dom), 1, x(:,t), V(:,:,t)); +end +% for t=1:T-1 +% dom = (1:(2*n)); +% mu = [x(:,t); x(:,t)]; +% Sigma = [V(:,:,t) VV(:,:,t+1)'; +% VV(:,:,t+1) V(:,:,t+1)]; +% engine.two_slice_marginal{t} = mpot(dom+(t-1)*ss, ns(dom), 1, mu, Sigma); +% end +for t=2:T + %dom = (1:(2*n)); + current_slice = hnodes; + next_slice = hnodes + ss; + dom = [current_slice next_slice]; + mu = [x(:,t-1); x(:,t)]; + Sigma = [V(:,:,t-1) VV(:,:,t)'; + VV(:,:,t) V(:,:,t)]; + engine.two_slice_marginal{t-1} = mpot(dom+(t-2)*ss, ns(dom), 1, mu, Sigma); +end diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/kalman_inf_engine.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/kalman_inf_engine.m new file mode 100644 index 00000000..df03a56f --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/kalman_inf_engine.m @@ -0,0 +1,23 @@ +function engine = kalman_inf_engine(bnet) +% KALMAN_INF_ENGINE Inference engine for Linear-Gaussian state-space models. +% engine = kalman_inf_engine(bnet) +% +% 'onodes' specifies which nodes are observed; these must be leaves. +% The remaining nodes are all hidden. All nodes must have linear-Gaussian CPDs. +% The hidden nodes must be persistent, i.e., they must have children in +% the next time slice. In addition, they may not have any children within the current slice, +% except to the observed leaves. In other words, the topology must be isomorphic to a standard LDS. +% +% There are many derivations of the filtering and smoothing equations for Linear Dynamical +% Systems in the literature. I particularly like the following +% - "From HMMs to LDSs", T. Minka, MIT Tech Report, (no date), available from +% ftp://vismod.www.media.mit.edu/pub/tpminka/papers/minka-lds-tut.ps.gz + +[engine.trans_mat, engine.trans_cov, engine.obs_mat, engine.obs_cov, engine.init_state, engine.init_cov] = ... + dbn_to_lds(bnet); + +% This is where we will store the results between enter_evidence and marginal_nodes +engine.one_slice_marginal = []; +engine.two_slice_marginal = []; + +engine = class(engine, 'kalman_inf_engine', inf_engine(bnet)); diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/marginal_nodes.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/marginal_nodes.m new file mode 100644 index 00000000..738c30dc --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/marginal_nodes.m @@ -0,0 +1,25 @@ +function marginal = marginal_nodes(engine, nodes, t) +% MARGINAL_NODES Compute the marginal on the specified query nodes (kalman) +% marginal = marginal_nodes(engine, nodes, t) +% +% 't' specifies the time slice of the earliest node in 'nodes'. +% 'nodes' cannot span more than 2 time slices. +% +% Example: +% Consider a DBN with 2 nodes per slice. +% Then t=2, nodes=[1 3] refers to node 1 in slice 2 and node 1 in slice 3, +% i.e., nodes 3 and 5 in the unrolled network, + +if nargin < 3, t = 1; end + +bnet = bnet_from_engine(engine); +ss = length(bnet.intra); +if all(nodes <= ss) + bigpot = engine.one_slice_marginal{t}; +else + bigpot = engine.two_slice_marginal{t}; +end + +nodes = nodes + (t-1)*ss; +pot = marginalize_pot(bigpot, nodes); +marginal = pot_to_marginal(pot); diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries new file mode 100644 index 00000000..9a351a87 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Entries @@ -0,0 +1,3 @@ +/dbn_to_lds.m/1.1.1.1/Wed May 29 15:59:56 2002// +/extract_params_from_gbn.m/1.1.1.1/Wed May 29 15:59:56 2002// +D diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository new file mode 100644 index 00000000..3f67aee0 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Repository @@ -0,0 +1 @@ +FullBNT/BNT/inference/dynamic/@kalman_inf_engine/private diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root new file mode 100644 index 00000000..f3bd14a6 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/CVS/Root @@ -0,0 +1 @@ +:ext:nsaunier@bnt.cvs.sourceforge.net:/cvsroot/bnt diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m new file mode 100644 index 00000000..6249ac0d --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/dbn_to_lds.m @@ -0,0 +1,26 @@ +function [trans_mat, trans_cov, obs_mat, obs_cov, init_state, init_cov] = dbn_to_lds(bnet) +% DBN_TO_LDS Compute the Linear Dynamical System parameters from the Gaussian DBN. +% [trans_mat, trans_cov, obs_mat, obs_cov, init_state, init_cov] = dbn_to_lds(bnet) + +onodes = bnet.observed; +ss = length(bnet.intra); +num_nodes = ss*2; +assert(isequal(bnet.cnodes_slice, 1:ss)); +[W,D,mu] = extract_params_from_gbn(bnet); + +hnodes = mysetdiff(1:ss, onodes); +bs = bnet.node_sizes(:); % block sizes + +obs_mat = W(block(hnodes,bs), block(onodes,bs))'; +u = block(onodes,bs); +obs_cov = D(u,u); + +trans_mat = W(block(hnodes,bs), block(hnodes + ss, bs))'; +u = block(hnodes + ss, bs); +trans_cov = D(u,u); + +u = block(hnodes,bs); +init_cov = D(u,u); +init_state = mu(u); + + diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m new file mode 100644 index 00000000..86345830 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/private/extract_params_from_gbn.m @@ -0,0 +1,38 @@ +function [B,D,mu] = extract_params_from_gbn(bnet) +% Extract all the local parameters of each Gaussian node, and collect them into global matrices. +% [B,D,mu] = extract_params_from_gbn(bnet) +% +% B(i,j) is a block matrix that contains the transposed weight matrix from node i to node j. +% D(i,i) is a block matrix that contains the noise covariance matrix for node i. +% mu(i) is a block vector that contains the shifted noise mean for node i. + +% In Shachter's model, the mean of each node in the global gaussian is +% the same as the node's local unconditional mean. +% In Alag's model (which we use), the global mean gets shifted. + + +num_nodes = length(bnet.dag); +bs = bnet.node_sizes(:); % bs = block sizes +N = sum(bs); % num scalar nodes + +B = zeros(N,N); +D = zeros(N,N); +mu = zeros(N,1); + +for i=1:num_nodes % in topological order + ps = parents(bnet.dag, i); + e = bnet.equiv_class(i); + %[m, Sigma, weights] = extract_params_from_CPD(bnet.CPD{e}); + s = struct(bnet.CPD{e}); % violate privacy of object + m = s.mean; Sigma = s.cov; weights = s.weights; + if length(ps) == 0 + mu(block(i,bs)) = m; + else + mu(block(i,bs)) = m + weights * mu(block(ps,bs)); + end + B(block(ps,bs), block(i,bs)) = weights'; + D(block(i,bs), block(i,bs)) = Sigma; +end + + + diff --git a/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/update_engine.m b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/update_engine.m new file mode 100644 index 00000000..d89605e7 --- /dev/null +++ b/sourcecodes/bnt-master/BNT/inference/dynamic/@kalman_inf_engine/update_engine.m @@ -0,0 +1,9 @@ +function engine = update_engine(engine, newCPDs) +% UPDATE_ENGINE Update the engine to take into account the new parameters (kalman) +% engine = update_engine(engine, newCPDs) + +engine.inf_engine = update_engine(engine.inf_engine, newCPDs); +[engine.trans_mat, engine.trans_cov, engine.obs_mat, engine.obs_cov, engine.init_state, engine.init_cov] = ... + dbn_to_lds(bnet_from_engine(engine)); + + |