gtsam/gtsam/inference/SymbolicSequentialSolver.h

72 lines
2.6 KiB
C++

/* ----------------------------------------------------------------------------
* GTSAM Copyright 2010, Georgia Tech Research Corporation,
* Atlanta, Georgia 30332-0415
* All Rights Reserved
* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
* See LICENSE for the license information
* -------------------------------------------------------------------------- */
/**
* @file SymbolicSequentialSolver.h
* @author Richard Roberts
* @date Oct 21, 2010
*/
#pragma once
#include <gtsam/inference/GenericSequentialSolver.h>
#include <gtsam/inference/SymbolicFactorGraph.h>
namespace gtsam {
class SymbolicSequentialSolver : GenericSequentialSolver<IndexFactor> {
protected:
typedef GenericSequentialSolver<IndexFactor> Base;
public:
/**
* Construct the solver for a factor graph. This builds the junction
* tree, which does the symbolic elimination, identifies the cliques,
* and distributes all the factors to the right cliques.
*/
SymbolicSequentialSolver(const SymbolicFactorGraph& factorGraph) : Base(factorGraph) {};
/**
* Construct the solver with a shared pointer to a factor graph and to a
* VariableIndex. The solver will store these pointers, so this constructor
* is the fastest.
*/
SymbolicSequentialSolver(const SymbolicFactorGraph::shared_ptr& factorGraph,
const VariableIndex::shared_ptr& variableIndex) : Base(factorGraph, variableIndex) {};
/** Print to cout */
void print(const std::string& name = "SymbolicSequentialSolver: ") const { Base::print(name); };
/** Test whether is equal to another */
bool equals(const SymbolicSequentialSolver& other, double tol = 1e-9) const { return Base::equals(other, tol); };
/**
* Eliminate the factor graph sequentially. Uses a column elimination tree
* to recursively eliminate.
*/
SymbolicBayesNet::shared_ptr eliminate() const { return Base::eliminate(&EliminateSymbolic); };
/**
* Compute the marginal joint over a set of variables, by integrating out
* all of the other variables. Returns the result as a factor graph.
*/
SymbolicFactorGraph::shared_ptr jointFactorGraph(const std::vector<Index>& js) const { return Base::jointFactorGraph(js, &EliminateSymbolic); };
/**
* Compute the marginal Gaussian density over a variable, by integrating out
* all of the other variables. This function returns the result as a factor.
*/
IndexFactor::shared_ptr marginalFactor(Index j) const { return Base::marginalFactor(j, &EliminateSymbolic); };
};
}