loopy belief in progress
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/**
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* @file testLoopyBelief.cpp
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* @brief
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* @author Duy-Nguyen Ta
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* @date Oct 11, 2013
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*/
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#include <gtsam/inference/VariableIndex.h>
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#include <gtsam/discrete/DecisionTreeFactor.h>
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#include <gtsam/discrete/DiscreteFactorGraph.h>
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#include <CppUnitLite/TestHarness.h>
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#include <boost/range/adaptor/map.hpp>
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#include <boost/assign/list_of.hpp>
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#include <iostream>
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#include <fstream>
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using namespace std;
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using namespace boost::assign;
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using namespace gtsam;
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class LoopyBelief {
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typedef std::map<Key, size_t> CorrectedBeliefIndices;
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struct StarGraph {
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DiscreteFactorGraph::shared_ptr star;
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CorrectedBeliefIndices correctedBeliefIndices;
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StarGraph() {
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}
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StarGraph(const DiscreteFactorGraph::shared_ptr& _star,
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const CorrectedBeliefIndices& _beliefIndices) :
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star(_star), correctedBeliefIndices(_beliefIndices) {
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}
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};
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const DiscreteFactorGraph& graph_;
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VariableIndex varIndex_;
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std::map<Key, StarGraph> starGraphs_;
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std::map<Key, DecisionTreeFactor> unary_;
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std::map<Key, DecisionTreeFactor> belief_;
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public:
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LoopyBelief(const DiscreteFactorGraph& graph, const std::map<Key, DiscreteKey>& allDiscreteKeys) :
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graph_(graph), varIndex_(graph) {
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initialize(allDiscreteKeys);
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}
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void iterate() {
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static DiscreteConditional::shared_ptr dummyCond; // unused by-product of elimination
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// Eliminate each star graph
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BOOST_FOREACH(const VariableIndex::value_type& keyFactors, varIndex_) {
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Key key = keyFactors.first;
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// reset belief to the unary factor in the original graph
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belief_[key] = unary_.at(key);
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// keep intermediate messages to divide later
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std::map<Key, DiscreteFactor::shared_ptr> messages;
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// eliminate each neighbor in this star graph one by one
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BOOST_FOREACH(Key neighbor, starGraphs_.at(key).correctedBeliefIndices | boost::adaptors::map_keys) {
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DiscreteFactor::shared_ptr factor;
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boost::tie(dummyCond, factor) = EliminateDiscrete(*starGraphs_.at(key).star,
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Ordering(list_of(neighbor)));
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// store the new factor into messages
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messages.insert(make_pair(neighbor, factor));
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// Belief is the product of all messages and the unary factor
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// Incorporate new the factor to belief
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belief_.at(key) = belief_.at(key) * (*boost::dynamic_pointer_cast<DecisionTreeFactor>(factor));
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}
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// Update the corrected belief for the neighbor's stargraph
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BOOST_FOREACH(Key neighbor, starGraphs_.at(key).correctedBeliefIndices | boost::adaptors::map_keys) {
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DecisionTreeFactor correctedBelief = belief_.at(key)
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/ (*boost::dynamic_pointer_cast<DecisionTreeFactor>(messages.at(neighbor)));
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size_t beliefIndex = starGraphs_.at(neighbor).correctedBeliefIndices.at(
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key);
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starGraphs_.at(neighbor).star->replace(beliefIndex, boost::make_shared<DecisionTreeFactor>(correctedBelief));
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}
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}
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}
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private:
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void initialize(const std::map<Key, DiscreteKey>& allDiscreteKeys) {
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BOOST_FOREACH(Key key, varIndex_ | boost::adaptors::map_keys) {
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// initialize to multiply with other unary factors later
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unary_.insert(make_pair(key, DecisionTreeFactor(allDiscreteKeys.at(key), "1 1")));
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// collect all factors involving this key in the original graph
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DiscreteFactorGraph::shared_ptr star(new DiscreteFactorGraph());
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BOOST_FOREACH(size_t factorIdx, varIndex_[key]) {
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star->push_back(graph_.at(factorIdx));
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if (graph_.at(factorIdx)->size() == 1) {
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unary_.at(key) = unary_.at(key)
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* (*boost::dynamic_pointer_cast<DecisionTreeFactor>(
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graph_.at(factorIdx)));
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}
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}
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// add the belief factor for each other variable in this star graph
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// also record the factor index for later modification
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FastSet<Key> neighbors = star->keys();
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neighbors.erase(key);
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CorrectedBeliefIndices correctedBeliefIndices;
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BOOST_FOREACH(Key neighbor, neighbors) {
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// TODO: default table for keys with more than 2 values?
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star->push_back(
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DecisionTreeFactor(allDiscreteKeys.at(neighbor), "1.0 0.0"));
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correctedBeliefIndices.insert(make_pair(neighbor, star->size() - 1));
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}
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starGraphs_.insert(
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make_pair(key, StarGraph(star, correctedBeliefIndices)));
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}
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}
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};
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/* ************************************************************************* */
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TEST_UNSAFE(LoopyBelief, construction) {
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// Variables: Cloudy, Sprinkler, Rain, Wet
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DiscreteKey C(0, 2), S(1, 2), R(2, 2), W(3, 2);
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// Map from key to DiscreteKey for building belief factor.
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// TODO: this is bad!
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std::map<Key, DiscreteKey> allKeys = map_list_of(0,C)(1,S)(2,R)(3,W);
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// Build graph
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DecisionTreeFactor pC(C, "0.5 0.5");
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DiscreteConditional pSC(S | C = "0.5/0.5 0.9/0.1");
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DiscreteConditional pRC(R | C = "0.8/0.2 0.2/0.8");
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DiscreteConditional pWSR((W | S, R) = "1.0/0.0 0.1/0.9 0.1/0.9 0.01/0.99");
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DiscreteFactorGraph graph;
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graph.push_back(pC);
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graph.push_back(pSC);
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graph.push_back(pRC);
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graph.push_back(pWSR);
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graph.print("graph: ");
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LoopyBelief solver(graph, allKeys);
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// Main loop
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for (size_t iter = 0; iter < 10; ++iter) {
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solver.iterate();
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}
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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