Merging all Discrete changes

gtsam/discrete/DecisionTreeFactor.h

@@ -127,6 +127,11 @@ namespace gtsam {
 		 */
 		shared_ptr combine(size_t nrFrontals, ADT::Binary op) const;
 
+		void permuteWithInverse(const Permutation& inversePermutation){
+			DiscreteFactor::permuteWithInverse(inversePermutation);
+			Potentials::permute(inversePermutation);
+		}
+
 		/// @}
 	};
 // DecisionTreeFactor

gtsam/discrete/DiscreteConditional.cpp

@@ -46,9 +46,9 @@ namespace gtsam {
 			const DecisionTreeFactor& marginal) :
 			IndexConditional(joint.keys(), joint.size() - marginal.size()), Potentials(
 					ISDEBUG("DiscreteConditional::COUNT") ? joint : joint / marginal) {
-		assert(nrFrontals() == 1);
+//		assert(nrFrontals() == 1);
 		if (ISDEBUG("DiscreteConditional::DiscreteConditional")) cout
-				<< (firstFrontalKey()) << endl;
+				<< (firstFrontalKey()) << endl;	//TODO Print all keys
 	}
 
 	/* ******************************************************************************** */
@@ -75,10 +75,47 @@ namespace gtsam {
 
 	/* ******************************************************************************** */
 	void DiscreteConditional::solveInPlace(Values& values) const {
-		assert(nrFrontals() == 1);
+//		assert(nrFrontals() == 1);
-		Index j = (firstFrontalKey());
+//		Index j = (firstFrontalKey());
-		size_t mpe = solve(values); // Solve for variable
+//		size_t mpe = solve(values); // Solve for variable
-		values[j] = mpe; // store result in partial solution
+//		values[j] = mpe; // store result in partial solution
+
+		// TODO: is this really the fastest way? I think it is.
+		ADT pFS = choose(values); // P(F|S=parentsValues)
+
+		// Initialize
+		Values mpe;
+		Values frontalVals;
+		BOOST_FOREACH(Index j, frontals()) {
+			frontalVals[j] = 0;
+		}
+		double maxP = 0;
+
+		while (1) {
+			double pValueS = pFS(frontalVals); // P(F=value|S=parentsValues)
+			// Update MPE solution if better
+			if (pValueS > maxP) {
+				maxP = pValueS;
+				mpe = frontalVals;
+			}
+
+			size_t j = 0;
+			for (j = 0; j < nrFrontals(); j++) {
+				Index idx = frontals()[j];
+				frontalVals[idx]++;
+				if (frontalVals[idx] < cardinality(idx))
+					break;
+				//Wrap condition
+				frontalVals[idx] = 0;
+			}
+			if (j == nrFrontals())
+				break;
+		}
+
+		//set values (inPlace) to mpe
+		BOOST_FOREACH(Index j, frontals()) {
+			values[j] = mpe[j];
+		}
 	}
 
 	/* ******************************************************************************** */

gtsam/discrete/DiscreteFactor.h

@@ -98,6 +98,14 @@ namespace gtsam {
 
 		virtual operator DecisionTreeFactor() const = 0;
 
+		/**
+		 * Permutes the factor, but for efficiency requires the permutation
+		 * to already be inverted.
+		 */
+		virtual void permuteWithInverse(const Permutation& inversePermutation){
+			IndexFactor::permuteWithInverse(inversePermutation);
+		}
+
 		/// @}
 	};
 // DiscreteFactor

gtsam/discrete/DiscreteFactorGraph.cpp

@@ -24,69 +24,71 @@
 
 namespace gtsam {
 
-// Explicitly instantiate so we don't have to include everywhere
+	// Explicitly instantiate so we don't have to include everywhere
-template class FactorGraph<DiscreteFactor> ;
+	template class FactorGraph<DiscreteFactor> ;
-template class EliminationTree<DiscreteFactor> ;
+	template class EliminationTree<DiscreteFactor> ;
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-DiscreteFactorGraph::DiscreteFactorGraph() {
+	DiscreteFactorGraph::DiscreteFactorGraph() {
-}
+	}
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-DiscreteFactorGraph::DiscreteFactorGraph(
+	DiscreteFactorGraph::DiscreteFactorGraph(
-		const BayesNet<DiscreteConditional>& bayesNet) :
+			const BayesNet<DiscreteConditional>& bayesNet) :
-		FactorGraph<DiscreteFactor>(bayesNet) {
+			FactorGraph<DiscreteFactor>(bayesNet) {
-}
+	}
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-FastSet<Index> DiscreteFactorGraph::keys() const {
+	FastSet<Index> DiscreteFactorGraph::keys() const {
-	FastSet<Index> keys;
+		FastSet<Index> keys;
-	BOOST_FOREACH(const sharedFactor& factor, *this)
+		BOOST_FOREACH(const sharedFactor& factor, *this)
-	if (factor) keys.insert(factor->begin(), factor->end());
+		if (factor) keys.insert(factor->begin(), factor->end());
-	return keys;
+		return keys;
-}
+	}
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-DecisionTreeFactor DiscreteFactorGraph::product() const {
+	DecisionTreeFactor DiscreteFactorGraph::product() const {
-	DecisionTreeFactor result;
+		DecisionTreeFactor result;
-	BOOST_FOREACH(const sharedFactor& factor, *this)
+		BOOST_FOREACH(const sharedFactor& factor, *this)
-		if (factor) result = (*factor) * result;
+			if (factor) result = (*factor) * result;
-	return result;
+		return result;
-}
+	}
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-double DiscreteFactorGraph::operator()(
+	double DiscreteFactorGraph::operator()(
-		const DiscreteFactor::Values &values) const {
+			const DiscreteFactor::Values &values) const {
-	double product = 1.0;
+		double product = 1.0;
-	BOOST_FOREACH( const sharedFactor& factor, factors_ )
+		BOOST_FOREACH( const sharedFactor& factor, factors_ )
-		product *= (*factor)(values);
+			product *= (*factor)(values);
-	return product;
+		return product;
-}
+	}
 
-/* ************************************************************************* */
+	/* ************************************************************************* */
-pair<DiscreteConditional::shared_ptr, DecisionTreeFactor::shared_ptr>  //
+	pair<DiscreteConditional::shared_ptr, DecisionTreeFactor::shared_ptr>  //
-EliminateDiscrete(const FactorGraph<DiscreteFactor>& factors, size_t num) {
+	EliminateDiscrete(const FactorGraph<DiscreteFactor>& factors, size_t num) {
 
-	// PRODUCT: multiply all factors
+		// PRODUCT: multiply all factors
-	tic(1, "product");
+		tic(1, "product");
-	DecisionTreeFactor product;
+		DecisionTreeFactor product;
-	BOOST_FOREACH(const DiscreteFactor::shared_ptr& factor, factors)
+		BOOST_FOREACH(const DiscreteFactor::shared_ptr& factor, factors){
-		product = (*factor) * product;
+			product = (*factor) * product;
-	toc(1, "product");
+		}
 
-	// sum out frontals, this is the factor on the separator
+		toc(1, "product");
-	tic(2, "sum");
-	DecisionTreeFactor::shared_ptr sum = product.sum(num);
-	toc(2, "sum");
 
-	// now divide product/sum to get conditional
+		// sum out frontals, this is the factor on the separator
-	tic(3, "divide");
+		tic(2, "sum");
-	DiscreteConditional::shared_ptr cond(new DiscreteConditional(product, *sum));
+		DecisionTreeFactor::shared_ptr sum = product.sum(num);
-	toc(3, "divide");
+		toc(2, "sum");
-	tictoc_finishedIteration();
 
-	return make_pair(cond, sum);
+		// now divide product/sum to get conditional
-}
+		tic(3, "divide");
+		DiscreteConditional::shared_ptr cond(new DiscreteConditional(product, *sum));
+		toc(3, "divide");
+		tictoc_finishedIteration();
+
+		return make_pair(cond, sum);
+	}
 
 /* ************************************************************************* */
 } // namespace

gtsam/discrete/DiscreteFactorGraph.h

@@ -86,7 +86,6 @@ public:
 			if (factors_[i] != NULL) factors_[i]->print(ss.str());
 		}
 	}
-
 };
 // DiscreteFactorGraph
 

gtsam/discrete/DiscreteMarginals.h

@@ -21,6 +21,8 @@
 #pragma once
 
 #include <gtsam/discrete/DiscreteFactorGraph.h>
+#include <gtsam/inference/GenericMultifrontalSolver.h>
+#include <gtsam/linear/GaussianBayesTree.h>
 
 namespace gtsam {
 
@@ -35,27 +37,43 @@ namespace gtsam {
 
   public:
 
-    /** Construct a marginals class.
+	/** Construct a marginals class.
-     * @param graph The factor graph defining the full joint density on all variables.
+	 * @param graph The factor graph defining the full joint density on all variables.
-     */
+	 */
-    DiscreteMarginals(const DiscreteFactorGraph& graph) {
+	DiscreteMarginals(const DiscreteFactorGraph& graph) {
-    }
+		typedef JunctionTree<DiscreteFactorGraph> DiscreteJT;
+		GenericMultifrontalSolver<DiscreteFactor, DiscreteJT> solver(graph);
+		bayesTree_ = *solver.eliminate(&EliminateDiscrete);
+		//bayesTree_.print();
+		cout << "Discrete Marginal Constructor Finished" << endl;
+	}
 
-    /** print */
+	/** Compute the marginal of a single variable */
-    void print(const std::string& str = "DiscreteMarginals: ") const {
+	DiscreteFactor::shared_ptr operator()(Index variable) const {
-    }
+		// Compute marginal
+		DiscreteFactor::shared_ptr marginalFactor;
+		marginalFactor = bayesTree_.marginalFactor(variable, &EliminateDiscrete);
+		return marginalFactor;
+	}
 
-    /** Compute the marginal of a single variable */
+	/** Compute the marginal of a single variable
-    DiscreteFactor::shared_ptr operator()(Index variable) const {
+	 * 	@param KEY DiscreteKey of the Variable
-      DiscreteFactor::shared_ptr p;
+	 * 	@return Vector of marginal probabilities
-      return p;
+	 */
-    }
+	Vector marginalProbabilities(const DiscreteKey& key) const {
+		// Compute marginal
+		DiscreteFactor::shared_ptr marginalFactor;
+		marginalFactor = bayesTree_.marginalFactor(key.first, &EliminateDiscrete);
 
-    /** Compute the marginal of a single variable */
+		//Create result
-    Vector marginalProbabilities(Index variable) const {
+		Vector vResult(key.second);
-      Vector v;
+		for (size_t state = 0; state < key.second ; ++ state) {
-      return v;
+			DiscreteFactor::Values values;
-    }
+			values[key.first] = state;
+			vResult(state) = (*marginalFactor)(values);
+		}
+		return vResult;
+	}
 
   };
 

gtsam/discrete/DiscreteSequentialSolver.cpp

@@ -52,6 +52,24 @@ namespace gtsam {
 
 		return solution;
 	}
+
+	/* ************************************************************************* */
+	Vector DiscreteSequentialSolver::marginalProbabilities(
+			const DiscreteKey& key) const {
+		// Compute marginal
+		DiscreteFactor::shared_ptr marginalFactor;
+		marginalFactor = Base::marginalFactor(key.first, &EliminateDiscrete);
+
+		//Create result
+		Vector vResult(key.second);
+		for (size_t state = 0; state < key.second; ++state) {
+			DiscreteFactor::Values values;
+			values[key.first] = state;
+			vResult(state) = (*marginalFactor)(values);
+		}
+		return vResult;
+	}
+
 /* ************************************************************************* */
 
 }

gtsam/discrete/DiscreteSequentialSolver.h

@@ -74,7 +74,6 @@ namespace gtsam {
 			return Base::eliminate(&EliminateDiscrete);
 		}
 
-#ifdef BROKEN
 		/**
 		 * Compute the marginal joint over a set of variables, by integrating out
 		 * all of the other variables.  This function returns the result as a factor
@@ -94,7 +93,13 @@ namespace gtsam {
 		DiscreteFactor::shared_ptr marginalFactor(Index j) const {
 			return Base::marginalFactor(j, &EliminateDiscrete);
 		}
-#endif
+
+		/**
+		 * Compute the marginal density over a variable, by integrating out
+		 * all of the other variables. This function returns the result as a
+		 * Vector of the probability values.
+		 */
+		Vector marginalProbabilities(const DiscreteKey& key) const;
 
 		/**
 		 * Compute the MPE solution of the DiscreteFactorGraph.  This

gtsam/discrete/Potentials.cpp

@@ -60,5 +60,28 @@ namespace gtsam {
 	}
 
 	/* ************************************************************************* */
+	void Potentials::permute(const Permutation& permutation) {
+		// Permute the _cardinalities (TODO: Inefficient Consider Improving)
+		DiscreteKeys keys;
+		map<Index, Index> ordering;
+
+		// Get the orginal keys from cardinalities_
+		BOOST_FOREACH(const DiscreteKey& key, cardinalities_)
+			keys & key;
+
+		// Perform Permutation
+		BOOST_FOREACH(DiscreteKey& key, keys) {
+			ordering[key.first] = permutation[key.first];
+			//cout << key.first << " -> " << ordering[key.first] << endl;
+			key.first = ordering[key.first];
+		}
+
+		// Change *this
+		AlgebraicDecisionTree<Index> permuted((*this), ordering);
+		*this = permuted;
+		cardinalities_ = keys.cardinalities();
+	}
+
+	/* ************************************************************************* */
 
 } // namespace gtsam

gtsam/discrete/Potentials.h

@@ -20,6 +20,7 @@
 #include <gtsam/discrete/AlgebraicDecisionTree.h>
 #include <gtsam/discrete/DiscreteKey.h>
 #include <gtsam/base/types.h>
+#include <gtsam/inference/Permutation.h>
 
 #include <boost/shared_ptr.hpp>
 #include <set>
@@ -68,6 +69,13 @@ namespace gtsam {
 
 		size_t cardinality(Index j) const { return cardinalities_.at(j);}
 
+		/*
+		 * @brief Permutes the keys in Potentials
+		 *
+		 * This permutes the Indices and performs necessary re-ordering of ADD.
+		 */
+		void permute(const Permutation& perm);
+
 	}; // Potentials
 
 } // namespace gtsam