/* ----------------------------------------------------------------------------

 * 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 JunctionTree-inst.h
 * @date Feb 4, 2010
 * @author Kai Ni
 * @author Frank Dellaert
 * @author Richard Roberts
 * @brief The junction tree, template bodies
 */

#pragma once

#include <gtsam/inference/JunctionTree.h>
#include <gtsam/inference/ClusterTree-inst.h>
#include <gtsam/symbolic/SymbolicConditional.h>
#include <gtsam/symbolic/SymbolicFactor-inst.h>

namespace gtsam {

template <class BAYESTREE, class GRAPH, class ETREE_NODE>
struct ConstructorTraversalData {
  typedef typename JunctionTree<BAYESTREE, GRAPH>::Node Node;
  typedef typename JunctionTree<BAYESTREE, GRAPH>::sharedNode sharedNode;

  ConstructorTraversalData* const parentData;
  sharedNode myJTNode;
  FastVector<SymbolicConditional::shared_ptr> childSymbolicConditionals;
  FastVector<SymbolicFactor::shared_ptr> childSymbolicFactors;

  ConstructorTraversalData(ConstructorTraversalData* _parentData)
      : parentData(_parentData) {}

  // Pre-order visitor function
  static ConstructorTraversalData ConstructorTraversalVisitorPre(
      const boost::shared_ptr<ETREE_NODE>& node,
      ConstructorTraversalData& parentData) {
    // On the pre-order pass, before children have been visited, we just set up
    // a traversal data structure with its own JT node, and create a child
    // pointer in its parent.
    ConstructorTraversalData myData = ConstructorTraversalData(&parentData);
    myData.myJTNode = boost::make_shared<Node>(node->key, node->factors);
    parentData.myJTNode->children.push_back(myData.myJTNode);
    return myData;
  }

  // Post-order visitor function
  static void ConstructorTraversalVisitorPostAlg2(
      const boost::shared_ptr<ETREE_NODE>& ETreeNode,
      const ConstructorTraversalData& myData) {
    // In this post-order visitor, we combine the symbolic elimination results
    // from the elimination tree children and symbolically eliminate the current
    // elimination tree node.  We then check whether each of our elimination
    // tree child nodes should be merged with us.  The check for this is that
    // our number of symbolic elimination parents is exactly 1 less than
    // our child's symbolic elimination parents - this condition indicates that
    // eliminating the current node did not introduce any parents beyond those
    // already in the child.

    // Do symbolic elimination for this node
    class : public FactorGraph<Factor> {}
    symbolicFactors;
    symbolicFactors.reserve(ETreeNode->factors.size() +
                            myData.childSymbolicFactors.size());
    // Add ETree node factors
    symbolicFactors += ETreeNode->factors;
    // Add symbolic factors passed up from children
    symbolicFactors += myData.childSymbolicFactors;

    Ordering keyAsOrdering;
    keyAsOrdering.push_back(ETreeNode->key);
    std::pair<SymbolicConditional::shared_ptr, SymbolicFactor::shared_ptr>
        symbolicElimResult =
            internal::EliminateSymbolic(symbolicFactors, keyAsOrdering);

    // Store symbolic elimination results in the parent
    myData.parentData->childSymbolicConditionals.push_back(
        symbolicElimResult.first);
    myData.parentData->childSymbolicFactors.push_back(
        symbolicElimResult.second);
    sharedNode node = myData.myJTNode;

    // Merge our children if they are in our clique - if our conditional has
    // exactly one fewer parent than our child's conditional.
    size_t myNrFrontals = 1;
    const size_t myNrParents = symbolicElimResult.first->nrParents();
    size_t nrMergedChildren = 0;
    assert(node->children.size() == myData.childSymbolicConditionals.size());
    // Loop over children
    int combinedProblemSize =
        (int)(symbolicElimResult.first->size() * symbolicFactors.size());
    for (size_t i = 0; i < myData.childSymbolicConditionals.size(); ++i) {
      // Check if we should merge the i^th child
      if (myNrParents + myNrFrontals ==
          myData.childSymbolicConditionals[i]->nrParents()) {
        // Get a reference to the i, adjusting the index to account for children
        // previously merged and removed from the i list.
        const Node& child = *node->children[i - nrMergedChildren];
        // Merge keys, factors, and children.
        node->orderedFrontalKeys.insert(node->orderedFrontalKeys.begin(),
                                        child.orderedFrontalKeys.begin(),
                                        child.orderedFrontalKeys.end());
        node->factors.insert(node->factors.end(), child.factors.begin(), child.factors.end());
        node->children.insert(node->children.end(), child.children.begin(), child.children.end());
        // Increment problem size
        combinedProblemSize = std::max(combinedProblemSize, child.problemSize_);
        // Increment number of frontal variables
        myNrFrontals += child.orderedFrontalKeys.size();
        // Remove i from list.
        node->children.erase(node->children.begin() + (i - nrMergedChildren));
        // Increment number of merged children
        ++nrMergedChildren;
      }
    }
    node->problemSize_ = combinedProblemSize;
  }
};

/* ************************************************************************* */
template <class BAYESTREE, class GRAPH>
template <class ETREE_BAYESNET, class ETREE_GRAPH>
JunctionTree<BAYESTREE, GRAPH>::JunctionTree(
    const EliminationTree<ETREE_BAYESNET, ETREE_GRAPH>& eliminationTree) {
  gttic(JunctionTree_FromEliminationTree);
  // Here we rely on the BayesNet having been produced by this elimination tree,
  // such that the conditionals are arranged in DFS post-order.  We traverse the
  // elimination tree, and inspect the symbolic conditional corresponding to
  // each node.  The elimination tree node is added to the same clique with its
  // parent if it has exactly one more Bayes net conditional parent than
  // does its elimination tree parent.

  // Traverse the elimination tree, doing symbolic elimination and merging nodes
  // as we go.  Gather the created junction tree roots in a dummy Node.
  typedef typename EliminationTree<ETREE_BAYESNET, ETREE_GRAPH>::Node ETreeNode;
  typedef ConstructorTraversalData<BAYESTREE, GRAPH, ETreeNode> Data;
  Data rootData(0);
  rootData.myJTNode =
      boost::make_shared<typename Base::Node>();  // Make a dummy node to gather
                                                  // the junction tree roots
  treeTraversal::DepthFirstForest(eliminationTree, rootData,
                                  Data::ConstructorTraversalVisitorPre,
                                  Data::ConstructorTraversalVisitorPostAlg2);

  // Assign roots from the dummy node
  Base::roots_ = rootData.myJTNode->children;

  // Transfer remaining factors from elimination tree
  Base::remainingFactors_ = eliminationTree.remainingFactors();
}

}  // namespace gtsam