influenceDiagram_tpl.h

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#include <agrum/ID/influenceDiagram.h>
#include <cstdio>
#include <iostream>

namespace gum {

  // ===========================================================================
  // Constructors / Destructors
  // ===========================================================================

  /*
   * Default constructor.
   */
  template < typename GUM_SCALAR >
  INLINE InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram() : DAGmodel() {
    GUM_CONSTRUCTOR(InfluenceDiagram);
  }

  /*
   * Destructor.
   */
  template < typename GUM_SCALAR >
  InfluenceDiagram< GUM_SCALAR >::~InfluenceDiagram() {
    GUM_DESTRUCTOR(InfluenceDiagram);
    _removeTables();
  }

  /*
   * Copy Constructor
   */
  template < typename GUM_SCALAR >
  InfluenceDiagram< GUM_SCALAR >::InfluenceDiagram(
     const InfluenceDiagram< GUM_SCALAR >& source) :
      DAGmodel(source),
      __variableMap(source.__variableMap) {
    GUM_CONS_CPY(InfluenceDiagram);
    _copyTables(source);
  }

  /*
   * Copy Operator
   */
  template < typename GUM_SCALAR >
  InfluenceDiagram< GUM_SCALAR >& InfluenceDiagram< GUM_SCALAR >::operator=(
     const InfluenceDiagram< GUM_SCALAR >& source) {
    if (this != &source) {
      DAGmodel::operator=(source);
      // Removing previous potentials
      _removeTables();
      __potentialMap.clear();
      __utilityMap.clear();

      __variableMap = source.__variableMap;

      // Copying tables
      _copyTables(source);
    }

    return *this;
  }

  /*
   * Removing ancient table
   */
  template < typename GUM_SCALAR >
  void InfluenceDiagram< GUM_SCALAR >::_removeTables() {
    for (const auto node: _dag.nodes()) {
      if (isChanceNode(node))
        delete &cpt(node);
      else if (isUtilityNode(node))
        delete &utility(node);
    }
  }

  /*
   * Copying tables from another influence diagram
   */
  template < typename GUM_SCALAR >
  void InfluenceDiagram< GUM_SCALAR >::_copyTables(
     const InfluenceDiagram< GUM_SCALAR >& IDsource) {
    // Copying potentials
    for (const auto& pot: IDsource.__potentialMap) {
      // Instanciation of the node's CPT
      auto potentialCpy = new Potential< GUM_SCALAR >;
      (*potentialCpy) << variable(pot.first);

      // Addition of the parents
      for (const auto par: _dag.parents(pot.first))
        (*potentialCpy) << variable(par);

      // Filling up of the table
      Instantiation srcInst(*pot.second);
      Instantiation cpyInst(*potentialCpy);

      for (cpyInst.setFirst(); !cpyInst.end(); cpyInst.inc()) {
        for (Idx i = 0; i < cpyInst.nbrDim(); i++) {
          NodeId id = nodeId(cpyInst.variable(i));
          srcInst.chgVal(IDsource.variable(id), cpyInst.val(i));
        }

        potentialCpy->set(cpyInst, (*pot.second)[srcInst]);
      }

      // Adding cpt to cpt map
      __potentialMap.set(pot.first, potentialCpy);
    }

    // Copying Utilities
    for (const auto& uti: IDsource.__utilityMap) {
      // Instanciation of the node's CPT
      auto utilityCpy = new Potential< GUM_SCALAR >;
      (*utilityCpy) << variable(uti.first);

      // Addition of the parents
      for (const auto par: _dag.parents(uti.first))
        (*utilityCpy) << variable(par);

      // Filling up of the table
      Instantiation srcInst(*uti.second);

      Instantiation cpyInst(*utilityCpy);

      for (cpyInst.setFirst(); !cpyInst.end(); cpyInst.inc()) {
        for (Idx i = 0; i < cpyInst.nbrDim(); i++) {
          NodeId id = nodeId(cpyInst.variable(i));
          srcInst.chgVal(IDsource.variable(id), cpyInst.val(i));
        }

        utilityCpy->set(cpyInst, (*uti.second)[srcInst]);
      }

      // Adding cpt to cpt map
      __utilityMap.set(uti.first, utilityCpy);
    }
  }

  template < typename GUM_SCALAR >
  std::string InfluenceDiagram< GUM_SCALAR >::toDot() const {
    std::stringstream output;
    std::stringstream decisionNode;
    std::stringstream utilityNode;
    std::stringstream chanceNode;
    std::stringstream arcstream;
    output << "digraph \"";

    try {
      output << this->property("name") << "\" {" << std::endl;
    } catch (NotFound&) { output << "no_name\" {" << std::endl; }

    output << "  node [bgcolor=\"#AAAAAA\", style=filled];" << std::endl;

    decisionNode << "node [shape = box];" << std::endl;

    utilityNode << "node [shape = diamond];" << std::endl;
    chanceNode << "node [shape = ellipse];" << std::endl;
    std::string tab = "  ";

    for (const auto node: _dag.nodes()) {
      if (isChanceNode(node))
        chanceNode << tab << "\"" << variable(node).name() << "\""
                   << ";";
      else if (isUtilityNode(node))
        utilityNode << tab << "\"" << variable(node).name() << "\""
                    << ";";
      else
        decisionNode << tab << "\"" << variable(node).name() << "\""
                     << ";";

      if (_dag.children(node).size() > 0)
        for (const auto chi: _dag.children(node))
          arcstream << tab << "\"" << variable(node).name() << "\""
                    << " -> "
                    << "\"" << variable(chi).name() << "\";" << std::endl;
    }

    output << decisionNode.str() << std::endl
           << utilityNode.str() << std::endl
           << chanceNode.str() << std::endl
           << arcstream.str() << std::endl
           << "}" << std::endl;

    return output.str();
  }

  template < typename GUM_SCALAR >
  std::string InfluenceDiagram< GUM_SCALAR >::toString() const {
    std::stringstream output;

    output << "Influence Diagram{" << std::endl;
    output << "  chance: " << chanceNodeSize() << "," << std::endl;
    output << "  utility: " << utilityNodeSize() << "," << std::endl;
    output << "  decision: " << decisionNodeSize() << "," << std::endl;
    output << "  arcs: " << dag().sizeArcs() << "," << std::endl;

    double dSize = log10DomainSize();

    if (dSize > 6)
      output << "  domainSize: 10^" << dSize;
    else
      output << "  domainSize: " << std::round(std::pow(10.0, dSize));

    output << std::endl << "}";

    return output.str();
  }

  // ===========================================================================
  // Variable manipulation methods.
  // ===========================================================================

  /*
   * Returns the CPT of a chance variable.
   */
  template < typename GUM_SCALAR >
  INLINE const Potential< GUM_SCALAR >&
               InfluenceDiagram< GUM_SCALAR >::cpt(NodeId varId) const {
    return *(__potentialMap[varId]);
  }

  /*
   * Returns the utility table of a utility node.
   */
  template < typename GUM_SCALAR >
  INLINE const Potential< GUM_SCALAR >&
               InfluenceDiagram< GUM_SCALAR >::utility(NodeId varId) const {
    return *(__utilityMap[varId]);
  }

  /*
   * Return true if node is a utility one
   */
  template < typename GUM_SCALAR >
  INLINE bool InfluenceDiagram< GUM_SCALAR >::isUtilityNode(NodeId varId) const {
    return __utilityMap.exists(varId);
  }

  /*
   * Return true if node is a utility one
   */
  template < typename GUM_SCALAR >
  INLINE bool InfluenceDiagram< GUM_SCALAR >::isDecisionNode(NodeId varId) const {
    bool ret = true;

    if (isUtilityNode(varId) || isChanceNode(varId)) ret = false;

    return ret;
  }

  /*
   * Return true if node is a chance one
   */
  template < typename GUM_SCALAR >
  INLINE bool InfluenceDiagram< GUM_SCALAR >::isChanceNode(NodeId varId) const {
    return __potentialMap.exists(varId);
  }

  /*
   * Returns the number of utility nodes
   */
  template < typename GUM_SCALAR >
  INLINE Size InfluenceDiagram< GUM_SCALAR >::utilityNodeSize() const {
    return __utilityMap.size();
  }

  /*
   * Returns the number of chance nodes
   */
  template < typename GUM_SCALAR >
  INLINE Size InfluenceDiagram< GUM_SCALAR >::chanceNodeSize() const {
    return __potentialMap.size();
  }

  /*
   * Returns the number of decision nodes
   */
  template < typename GUM_SCALAR >
  INLINE Size InfluenceDiagram< GUM_SCALAR >::decisionNodeSize() const {
    return (size() - __utilityMap.size() - __potentialMap.size());
  }

  /*
   * Returns a constant reference to the VariableNodeMap of this Influence
   * Diagram
   */
  template < typename GUM_SCALAR >
  INLINE const VariableNodeMap&
               InfluenceDiagram< GUM_SCALAR >::variableNodeMap() const {
    return __variableMap;
  }

  /*
   * Returns a constant reference over a variable given it's node id.
   */
  template < typename GUM_SCALAR >
  INLINE const DiscreteVariable&
               InfluenceDiagram< GUM_SCALAR >::variable(NodeId id) const {
    return __variableMap[id];
  }

  /*
   * Return id node from discrete var pointer.
   */
  template < typename GUM_SCALAR >
  INLINE NodeId
     InfluenceDiagram< GUM_SCALAR >::nodeId(const DiscreteVariable& var) const {
    return __variableMap.get(var);
  }

  // Getter by name
  template < typename GUM_SCALAR >
  INLINE NodeId
     InfluenceDiagram< GUM_SCALAR >::idFromName(const std::string& name) const {
    return __variableMap.idFromName(name);
  }

  // Getter by name
  template < typename GUM_SCALAR >
  INLINE const DiscreteVariable& InfluenceDiagram< GUM_SCALAR >::variableFromName(
     const std::string& name) const {
    return __variableMap.variableFromName(name);
  }

  /*
   * Add a chance variable, it's associate node and it's CPT. The id of the new
   * variable is automatically generated.
   */
  template < typename GUM_SCALAR >
  NodeId InfluenceDiagram< GUM_SCALAR >::add(const DiscreteVariable& var,
                                             NodeId                  varId) {
    return addChanceNode(var, varId);
  }

  /*
   * Add a utility variable, it's associate node and it's UT. The id of the new
   * variable is automatically generated.
   * @Throws : Gum::InvalidArgument if var has more than one state
   */
  template < typename GUM_SCALAR >
  NodeId
     InfluenceDiagram< GUM_SCALAR >::addUtilityNode(const DiscreteVariable& var,
                                                    NodeId varId) {
    MultiDimArray< GUM_SCALAR >* newMultiDim = new MultiDimArray< GUM_SCALAR >();
    NodeId                       res = 0;

    try {
      res = addUtilityNode(var, newMultiDim, varId);
    } catch (Exception&) {
      delete newMultiDim;
      throw;
    }

    return res;
  }

  /*
   * Add a decision variable. The id of the new
   * variable is automatically generated.
   */
  template < typename GUM_SCALAR >
  NodeId
     InfluenceDiagram< GUM_SCALAR >::addDecisionNode(const DiscreteVariable& var,
                                                     NodeId varId) {
    return _addNode(var, varId);
  }

  /*
   * Add a chance variable, it's associate node and it's CPT. The id of the new
   * variable is automatically generated.
   */
  template < typename GUM_SCALAR >
  NodeId InfluenceDiagram< GUM_SCALAR >::addChanceNode(const DiscreteVariable& var,
                                                       NodeId varId) {
    MultiDimArray< GUM_SCALAR >* newMultiDim = new MultiDimArray< GUM_SCALAR >();
    NodeId                       res = 0;

    try {
      res = addChanceNode(var, newMultiDim, varId);
    } catch (Exception&) {
      delete newMultiDim;
      throw;
    }

    return res;
  }

  /*
   * Add a chance variable, it's associate node and it's CPT. The id of the new
   * variable is automatically generated.
   */
  template < typename GUM_SCALAR >
  NodeId InfluenceDiagram< GUM_SCALAR >::addChanceNode(
     const DiscreteVariable&               var,
     MultiDimImplementation< GUM_SCALAR >* aContent,
     NodeId                                DesiredId) {
    NodeId proposedId = _addNode(var, DesiredId);

    Potential< GUM_SCALAR >* varcpt = new Potential< GUM_SCALAR >(aContent);
    (*varcpt) << variable(proposedId);
    __potentialMap.insert(proposedId, varcpt);

    return proposedId;
  }

  /*
   * Add a utility variable, it's associate node and it's UT. The id of the new
   * variable is automatically generated.
   * @Throws : Gum::InvalidArgument if var has more than one state
   */
  template < typename GUM_SCALAR >
  NodeId InfluenceDiagram< GUM_SCALAR >::addUtilityNode(
     const DiscreteVariable&               var,
     MultiDimImplementation< GUM_SCALAR >* aContent,
     NodeId                                DesiredId) {
    if (var.domainSize() != 1) {
      GUM_ERROR(InvalidArgument,
                "Utility var have no state ( which implicates a "
                "single label for data output reasons ).");
    }

    NodeId proposedId = _addNode(var, DesiredId);

    Potential< GUM_SCALAR >* varut = new Potential< GUM_SCALAR >(aContent);

    (*varut) << variable(proposedId);

    __utilityMap.insert(proposedId, varut);

    return proposedId;
  }

  /*
   * Add a node
   */
  template < typename GUM_SCALAR >
  NodeId
     InfluenceDiagram< GUM_SCALAR >::_addNode(const DiscreteVariable& variableType,
                                              NodeId                  DesiredId) {
    // None thread safe code!
    NodeId proposedId;

    if (DesiredId == 0)
      proposedId = _dag.nextNodeId();
    else
      proposedId = DesiredId;

    __variableMap.insert(proposedId, variableType);

    _dag.addNodeWithId(proposedId);

    // end critical section
    return proposedId;
  }

  /*
   * Erase a Variable from the network and remove the variable from
   * all childs of id.
   * If no variable matches the id, then nothing is done.
   */
  template < typename GUM_SCALAR >
  void InfluenceDiagram< GUM_SCALAR >::erase(NodeId varId) {
    if (__variableMap.exists(varId)) {
      // Reduce the variable child's CPT or Utility Table if necessary
      for (const auto chi: _dag.children(varId))
        if (isChanceNode(chi))
          __potentialMap[chi]->erase(variable(varId));
        else if (isUtilityNode(chi))
          __utilityMap[chi]->erase(variable(varId));

      if (isChanceNode(varId)) {
        delete __potentialMap[varId];
        __potentialMap.erase(varId);
      } else if (isUtilityNode(varId)) {
        delete __utilityMap[varId];
        __utilityMap.erase(varId);
      }

      __variableMap.erase(varId);
      _dag.eraseNode(varId);
    }
  }

  /*
   * Erase a Variable from the network and remove the variable from
   * all childs of var.
   * If no variable matches, then nothing is done.
   */
  template < typename GUM_SCALAR >
  INLINE void InfluenceDiagram< GUM_SCALAR >::erase(const DiscreteVariable& var) {
    erase(__variableMap.get(var));
  }

  /* we allow the user to change the name of a variable
   */
  template < typename GUM_SCALAR >
  INLINE void InfluenceDiagram< GUM_SCALAR >::changeVariableName(
     NodeId id, const std::string& new_name) {
    __variableMap.changeName(id, new_name);
  }

  // ===========================================================================
  // @name Arc manipulation methods.
  // ===========================================================================
  /*
   * Add an arc in the ID, and update diagram's chance nodes cpt if necessary.
   */
  template < typename GUM_SCALAR >
  INLINE void InfluenceDiagram< GUM_SCALAR >::addArc(NodeId tail, NodeId head) {
    if (isUtilityNode(tail)) {
      GUM_ERROR(InvalidArc, "Tail cannot be a utility node");
    }

    _dag.addArc(tail, head);

    if (isChanceNode(head))
      // Add parent in the child's CPT
      (*(__potentialMap[head])) << variable(tail);
    else if (isUtilityNode(head))
      // Add parent in the child's UT
      (*(__utilityMap[head])) << variable(tail);
  }

  /*
   * Removes an arc in the ID, and update diagram chance nodes cpt if necessary.
   *
   * If (tail, head) doesn't exist, the nothing happens.
   */
  template < typename GUM_SCALAR >
  INLINE void InfluenceDiagram< GUM_SCALAR >::eraseArc(const Arc& arc) {
    if (_dag.existsArc(arc)) {
      NodeId head = arc.head(), tail = arc.tail();
      _dag.eraseArc(arc);

      if (isChanceNode(head))
        // Removes parent in the child's CPT
        (*(__potentialMap[head])) >> variable(tail);
      else if (isUtilityNode(head))
        // Removes parent in the child's UT
        (*(__utilityMap[head])) >> variable(tail);
    }
  }

  /*
   * Removes an arc in the ID, and update diagram chance nodes cpt if necessary.
   *
   * If (tail, head) doesn't exist, the nothing happens.
   */
  template < typename GUM_SCALAR >
  INLINE void InfluenceDiagram< GUM_SCALAR >::eraseArc(NodeId tail, NodeId head) {
    eraseArc(Arc(tail, head));
  }

  // ===========================================================================
  // Graphical methods
  // ===========================================================================

  /*
   * The node's id are coherent with the variables and nodes of the topology.
   */
  template < typename GUM_SCALAR >
  void InfluenceDiagram< GUM_SCALAR >::_moralGraph(UndiGraph& graph) const {
    for (const auto node: _dag.nodes())
      if (!isUtilityNode(node)) graph.addNodeWithId(node);

    for (const auto node: _dag.nodes()) {
      if (!isDecisionNode(node))
        for (const auto par: _dag.parents(node)) {
          if (isChanceNode(node)) graph.addEdge(node, par);

          for (const auto par2: _dag.parents(node))
            if (par != par2) graph.addEdge(par, par2);
        }
    }
  }

  /*
   * True if a directed path exist with all decison nodes
   */
  template < typename GUM_SCALAR >
  bool InfluenceDiagram< GUM_SCALAR >::decisionOrderExists() const {
    const Sequence< NodeId >& order = topologicalOrder(true);

    // Finding first decision node
    Sequence< NodeId >::const_iterator orderIter = order.begin();

    while ((orderIter != order.end()) && (!isDecisionNode(*orderIter)))
      ++orderIter;

    if (orderIter == order.end()) return true;

    NodeId parentDecision = (*orderIter);
    ++orderIter;

    // Checking path between decisions nodes
    while (orderIter != order.end()) {
      if (isDecisionNode(*orderIter)) {
        if (!existsPathBetween(parentDecision, *orderIter)) return false;

        parentDecision = *orderIter;
      }

      ++orderIter;
    }

    return true;
  }

  /*
   * Returns true if a path exists between source and destination
   */
  template < typename GUM_SCALAR >
  bool InfluenceDiagram< GUM_SCALAR >::existsPathBetween(NodeId src,
                                                         NodeId dest) const {
    List< NodeId > nodeFIFO;
    // mark[node] contains 0 if not visited
    // mark[node] = predecessor if visited
    NodeProperty< int > mark = _dag.nodesProperty((int)-1);
    NodeId              current;

    mark[src] = (int)src;
    nodeFIFO.pushBack(src);

    while (!nodeFIFO.empty()) {
      current = nodeFIFO.front();
      nodeFIFO.popFront();

      for (const auto new_one: _dag.children(current)) {
        if (mark[new_one] != -1)
          continue;   // if this node is already marked, continue

        mark[new_one] = (int)current;

        if (new_one == dest) break;   // if we reach *orderIter, stop.

        nodeFIFO.pushBack(new_one);
      }
    }

    if (mark[dest] == -1) return false;

    return true;
  }

  /*
   * Returns the decision graph
   */
  template < typename GUM_SCALAR >
  gum::DAG* InfluenceDiagram< GUM_SCALAR >::getDecisionGraph() const {
    gum::DAG* temporalGraph = new gum::DAG();

    for (const auto node: _dag.nodes()) {
      if (isDecisionNode(node)) {
        if (!temporalGraph->existsNode(node)) temporalGraph->addNodeWithId(node);

        for (const auto chi: _getChildrenDecision(node)) {
          if (!temporalGraph->existsNode(chi)) temporalGraph->addNodeWithId(chi);

          temporalGraph->addArc(node, chi);
        }
      }
    }

    return temporalGraph;
  }

  /*
   * Returns the list of children decision for a given nodeId
   */
  template < typename GUM_SCALAR >
  Sequence< NodeId > InfluenceDiagram< GUM_SCALAR >::_getChildrenDecision(
     NodeId parentDecision) const {
    Sequence< NodeId > childrenSeq;

    List< NodeId > nodeFIFO;
    NodeId         current;

    // mark[node] contains false if not visited
    // mark[node] contains true if visited
    NodeProperty< bool > mark = _dag.nodesProperty(false);

    mark[parentDecision] = true;

    nodeFIFO.pushBack(parentDecision);

    while (!nodeFIFO.empty()) {
      current = nodeFIFO.front();
      nodeFIFO.popFront();

      for (const auto new_one: _dag.children(current)) {
        if (mark[new_one]) continue;   // if this node is already marked, continue

        mark[new_one] = true;

        if (!isDecisionNode(new_one))
          nodeFIFO.pushBack(new_one);
        else
          childrenSeq.insert(new_one);
      }
    }

    return childrenSeq;
  }

  /*
   * Returns the sequence of decision nodes
   * @throw NotFound if such a sequence does not exist
   */
  template < typename GUM_SCALAR >
  std::vector< NodeId >* InfluenceDiagram< GUM_SCALAR >::getDecisionOrder() const {
    if (!decisionOrderExists()) { GUM_ERROR(NotFound, "No decision path exists"); }

    std::vector< NodeId >* decisionSequence = new std::vector< NodeId >();

    for (const auto elt: topologicalOrder(false))
      if (isDecisionNode(elt)) decisionSequence->push_back(elt);

    return decisionSequence;
  }

  /*
   * Returns partial temporal ordering
   * @throw NotFound if such a sequence does not exist
   */
  template < typename GUM_SCALAR >
  const List< NodeSet >&
     InfluenceDiagram< GUM_SCALAR >::getPartialTemporalOrder(bool clear) const {
    if (clear) {
      __temporalOrder.clear();

      std::vector< NodeId >* decisionOrder = getDecisionOrder();
      NodeSet                nodeList = _dag.asNodeSet();

      for (Idx i = 0; i < decisionOrder->size(); i++) {
        NodeSet partialOrderedSet;

        for (const auto par: _dag.parents(decisionOrder->at(i))) {
          if (nodeList.contains(par) && isChanceNode(par)) {
            partialOrderedSet.insert(par);
            nodeList.erase(par);
          }
        }

        if (!partialOrderedSet.empty())
          __temporalOrder.pushFront(partialOrderedSet);

        NodeSet decisionSet;

        decisionSet.insert(decisionOrder->at(i));

        __temporalOrder.pushFront(decisionSet);
      }

      NodeSet lastSet;   //= new gum::NodeSet();

      for (const auto node: nodeList)
        if (isChanceNode(node)) lastSet.insert(node);

      if (!lastSet.empty()) __temporalOrder.pushFront(lastSet);
    }

    return __temporalOrder;
  }
}   // namespace gum