loopy belief in progress

release/4.3a0
Duy-Nguyen Ta 2013-10-12 05:49:11 +00:00
parent 830ff38b80
commit b161a106c7
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/**
* @file testLoopyBelief.cpp
* @brief
* @author Duy-Nguyen Ta
* @date Oct 11, 2013
*/
#include <gtsam/inference/VariableIndex.h>
#include <gtsam/discrete/DecisionTreeFactor.h>
#include <gtsam/discrete/DiscreteFactorGraph.h>
#include <CppUnitLite/TestHarness.h>
#include <boost/range/adaptor/map.hpp>
#include <boost/assign/list_of.hpp>
#include <iostream>
#include <fstream>
using namespace std;
using namespace boost::assign;
using namespace gtsam;
class LoopyBelief {
typedef std::map<Key, size_t> CorrectedBeliefIndices;
struct StarGraph {
DiscreteFactorGraph::shared_ptr star;
CorrectedBeliefIndices correctedBeliefIndices;
StarGraph() {
}
StarGraph(const DiscreteFactorGraph::shared_ptr& _star,
const CorrectedBeliefIndices& _beliefIndices) :
star(_star), correctedBeliefIndices(_beliefIndices) {
}
};
const DiscreteFactorGraph& graph_;
VariableIndex varIndex_;
std::map<Key, StarGraph> starGraphs_;
std::map<Key, DecisionTreeFactor> unary_;
std::map<Key, DecisionTreeFactor> belief_;
public:
LoopyBelief(const DiscreteFactorGraph& graph, const std::map<Key, DiscreteKey>& allDiscreteKeys) :
graph_(graph), varIndex_(graph) {
initialize(allDiscreteKeys);
}
void iterate() {
static DiscreteConditional::shared_ptr dummyCond; // unused by-product of elimination
// Eliminate each star graph
BOOST_FOREACH(const VariableIndex::value_type& keyFactors, varIndex_) {
Key key = keyFactors.first;
// reset belief to the unary factor in the original graph
belief_[key] = unary_.at(key);
// keep intermediate messages to divide later
std::map<Key, DiscreteFactor::shared_ptr> messages;
// eliminate each neighbor in this star graph one by one
BOOST_FOREACH(Key neighbor, starGraphs_.at(key).correctedBeliefIndices | boost::adaptors::map_keys) {
DiscreteFactor::shared_ptr factor;
boost::tie(dummyCond, factor) = EliminateDiscrete(*starGraphs_.at(key).star,
Ordering(list_of(neighbor)));
// store the new factor into messages
messages.insert(make_pair(neighbor, factor));
// Belief is the product of all messages and the unary factor
// Incorporate new the factor to belief
belief_.at(key) = belief_.at(key) * (*boost::dynamic_pointer_cast<DecisionTreeFactor>(factor));
}
// Update the corrected belief for the neighbor's stargraph
BOOST_FOREACH(Key neighbor, starGraphs_.at(key).correctedBeliefIndices | boost::adaptors::map_keys) {
DecisionTreeFactor correctedBelief = belief_.at(key)
/ (*boost::dynamic_pointer_cast<DecisionTreeFactor>(messages.at(neighbor)));
size_t beliefIndex = starGraphs_.at(neighbor).correctedBeliefIndices.at(
key);
starGraphs_.at(neighbor).star->replace(beliefIndex, boost::make_shared<DecisionTreeFactor>(correctedBelief));
}
}
}
private:
void initialize(const std::map<Key, DiscreteKey>& allDiscreteKeys) {
BOOST_FOREACH(Key key, varIndex_ | boost::adaptors::map_keys) {
// initialize to multiply with other unary factors later
unary_.insert(make_pair(key, DecisionTreeFactor(allDiscreteKeys.at(key), "1 1")));
// collect all factors involving this key in the original graph
DiscreteFactorGraph::shared_ptr star(new DiscreteFactorGraph());
BOOST_FOREACH(size_t factorIdx, varIndex_[key]) {
star->push_back(graph_.at(factorIdx));
if (graph_.at(factorIdx)->size() == 1) {
unary_.at(key) = unary_.at(key)
* (*boost::dynamic_pointer_cast<DecisionTreeFactor>(
graph_.at(factorIdx)));
}
}
// add the belief factor for each other variable in this star graph
// also record the factor index for later modification
FastSet<Key> neighbors = star->keys();
neighbors.erase(key);
CorrectedBeliefIndices correctedBeliefIndices;
BOOST_FOREACH(Key neighbor, neighbors) {
// TODO: default table for keys with more than 2 values?
star->push_back(
DecisionTreeFactor(allDiscreteKeys.at(neighbor), "1.0 0.0"));
correctedBeliefIndices.insert(make_pair(neighbor, star->size() - 1));
}
starGraphs_.insert(
make_pair(key, StarGraph(star, correctedBeliefIndices)));
}
}
};
/* ************************************************************************* */
TEST_UNSAFE(LoopyBelief, construction) {
// Variables: Cloudy, Sprinkler, Rain, Wet
DiscreteKey C(0, 2), S(1, 2), R(2, 2), W(3, 2);
// Map from key to DiscreteKey for building belief factor.
// TODO: this is bad!
std::map<Key, DiscreteKey> allKeys = map_list_of(0,C)(1,S)(2,R)(3,W);
// Build graph
DecisionTreeFactor pC(C, "0.5 0.5");
DiscreteConditional pSC(S | C = "0.5/0.5 0.9/0.1");
DiscreteConditional pRC(R | C = "0.8/0.2 0.2/0.8");
DiscreteConditional pWSR((W | S, R) = "1.0/0.0 0.1/0.9 0.1/0.9 0.01/0.99");
DiscreteFactorGraph graph;
graph.push_back(pC);
graph.push_back(pSC);
graph.push_back(pRC);
graph.push_back(pWSR);
graph.print("graph: ");
LoopyBelief solver(graph, allKeys);
// Main loop
for (size_t iter = 0; iter < 10; ++iter) {
solver.iterate();
}
}
/* ************************************************************************* */
int main() {
TestResult tr;
return TestRegistry::runAllTests(tr);
}
/* ************************************************************************* */