/**
 * @file    SymbolicSequentialSolver.h
 * @brief   
 * @author  Richard Roberts
 * @created 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:

  SymbolicSequentialSolver(const FactorGraph<IndexFactor>& factorGraph);

  /**
   * Eliminate the factor graph sequentially.  Uses a column elimination tree
   * to recursively eliminate.
   */
  BayesNet<IndexConditional>::shared_ptr eliminate() const;

  /**
   * 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 marginal(Index j) const;

  /**
   * Compute the marginal joint over a set of variables, by integrating out
   * all of the other variables.  This function returns the result as an upper-
   * triangular R factor and right-hand-side, i.e. a GaussianBayesNet with
   * R*x = d.  To get a mean and covariance matrix, use jointStandard(...)
   */
  SymbolicFactorGraph::shared_ptr joint(const std::vector<Index>& js) const;

};

}