size_t UPGMpp::messagesLBP(CGraph &graph,
TInferenceOptions &options,
vector<vector<VectorXd> > &messages ,
bool maximize,
const vector<size_t> &tree)
{
const vector<CNodePtr> nodes = graph.getNodes();
const vector<CEdgePtr> edges = graph.getEdges();
multimap<size_t,CEdgePtr> edges_f = graph.getEdgesF();
size_t N_nodes = nodes.size();
size_t N_edges = edges.size();
bool is_tree = (tree.size()>0) ? true : false;
//graph.computePotentials();
//
// Build the messages structure
//
double totalSumOfMsgs = 0;
if ( !messages.size() )
messages.resize( N_edges);
for ( size_t i = 0; i < N_edges; i++ )
{
if ( !messages[i].size() )
{
messages[i].resize(2);
size_t ID1, ID2;
edges[i]->getNodesID(ID1,ID2);
// Messages from first node of the edge to the second one, so the size of
// the message has to be the same as the number of classes of the second node.
double N_classes = graph.getNodeWithID( ID2 )->getPotentials( options.considerNodeFixedValues ).rows();
messages[i][0].resize( N_classes );
messages[i][0].fill(1.0/N_classes);
// Just the opposite as before.
N_classes = graph.getNodeWithID( ID1 )->getPotentials( options.considerNodeFixedValues ).rows();
messages[i][1].resize( N_classes );
messages[i][1].fill(1.0/N_classes);
}
totalSumOfMsgs += messages[i][0].rows() + messages[i][1].rows();
}
// cout << "Initial Messages:" << endl;
// for ( size_t i=0; i < messages.size(); i++)
// for ( size_t j=0; j < messages[i].size(); j++)
// for ( size_t k=0; k < messages[i][j].size(); k++ )
// cout << messages[i][j][k] << " ";
vector<vector<VectorXd> > previousMessages;
if ( options.particularS["order"] == "RBP" )
{
previousMessages = messages;
for ( size_t i = 0; i < previousMessages.size(); i++ )
{
previousMessages[i][0].fill(0);
previousMessages[i][1].fill(0);
}
}
//
// Iterate until convergence or a certain maximum number of iterations is reached
//
size_t iteration;
// cout << endl;
for ( iteration = 0; iteration < options.maxIterations; iteration++ )
{
// cout << "Messages " << iteration << ":" << endl;
// for ( size_t i=0; i < messages.size(); i++)
// for ( size_t j=0; j < messages[i].size(); j++)
// for ( size_t k=0; k < messages[i][j].size(); k++ )
// cout << messages[i][j][k] << " ";
// cout << endl;
// Variables used by Residual Belief Propagation
int edgeWithMaxDiffIndex = -1;
VectorXd associatedMessage;
bool from1to2;
double maxDifference = -1;
//
// Iterate over all the nodes
//
for ( size_t nodeIndex = 0; nodeIndex < N_nodes; nodeIndex++ )
{
const CNodePtr nodePtr = graph.getNode( nodeIndex );
size_t nodeID = nodePtr->getID();
// Check if we are calibrating a tree, and so if the node is not member of the tree,
// so we dont have to update its messages
if ( is_tree && ( std::find(tree.begin(), tree.end(), nodeID ) == tree.end() ) )
continue;
NEIGHBORS_IT neighbors;
neighbors = edges_f.equal_range(nodeID);
//cout << " Sending messages ... " << endl;
//
// Send a message to each neighbor
//
for ( multimap<size_t,CEdgePtr>::iterator itNeigbhor = neighbors.first;
itNeigbhor != neighbors.second;
itNeigbhor++ )
{
// cout << "sending msg to neighbor..." << endl;
VectorXd nodePotPlusIncMsg = nodePtr->getPotentials( options.considerNodeFixedValues );
// cout << "nodePotPlusIncMsg Orig: " << nodePotPlusIncMsg.transpose() << endl;
size_t neighborID;
size_t ID1, ID2;
CEdgePtr edgePtr( (*itNeigbhor).second );
edgePtr->getNodesID(ID1,ID2);
( ID1 == nodeID ) ? neighborID = ID2 : neighborID = ID1;
// cout << "all ready" << endl;
// Check if we are calibrating a tree, and so if the neighbor node
// is not member of the tree, so we dont have to update its messages
if ( is_tree && ( std::find(tree.begin(), tree.end(), neighborID ) == tree.end() ))
continue;
//
// Compute the message from current node as a product of all the
// incoming messages less the one from the current neighbor
// plus the node potential of the current node.
//
for ( multimap<size_t,CEdgePtr>::iterator itNeigbhor2 = neighbors.first;
itNeigbhor2 != neighbors.second;
itNeigbhor2++ )
{
size_t ID11, ID12;
CEdgePtr edgePtr2( (*itNeigbhor2).second );
edgePtr2->getNodesID(ID11,ID12);
size_t edgeIndex = graph.getEdgeIndex( edgePtr2->getID() );
// cout << "Edge index: " << edgeIndex << endl << "node pot" << nodePotPlusIncMsg << endl;
// cout << "Node ID: " << nodeID << " node11 " << ID11 << " node12 " << ID12 << endl;
CNodePtr n1,n2;
edgePtr2->getNodes(n1,n2);
// cout << "Node 1 type: " << n1->getType()->getID() << " label " << n1->getType()->getLabel() << endl;
// cout << "Node 2 type: " << n2->getType()->getID() << " label " << n2->getType()->getLabel() << endl;
// Check if the current neighbor appears in the edge
if ( ( neighborID != ID11 ) && ( neighborID != ID12 ) )
{
if ( nodeID == ID11 )
{
// cout << "nodePotPlusIncMsg Prod: " << messages[ edgeIndex ][ 1 ].transpose() << endl;
// cout << "nodePotPlusIncMsg Bis : " << messages[ edgeIndex ][ 0 ].transpose() << endl;
nodePotPlusIncMsg =
nodePotPlusIncMsg.cwiseProduct(messages[ edgeIndex ][ 1 ]);
// cout << "nodePotPlusIncMsg Prod2: " << nodePotPlusIncMsg.transpose() << endl;
}
else // nodeID == ID2
{
// cout << "nodePotPlusIncMsg Prod: " << messages[ edgeIndex ][ 0 ].transpose() << endl;
// cout << "nodePotPlusIncMsg Bis : " << messages[ edgeIndex ][ 1 ].transpose() << endl;
nodePotPlusIncMsg =
nodePotPlusIncMsg.cwiseProduct(messages[ edgeIndex ][ 0 ]);
// cout << "nodePotPlusIncMsg Prod2: " << nodePotPlusIncMsg.transpose() << endl;
}
}
}
// cout << "Node pot" << endl;
//cout << "Node pot" << nodePotPlusIncMsg << endl;
//
// Take also the potential between the two nodes
//
MatrixXd edgePotentials;
if ( nodeID != ID1 )
edgePotentials = edgePtr->getPotentials();
else
edgePotentials = edgePtr->getPotentials().transpose();
VectorXd newMessage;
size_t edgeIndex = graph.getEdgeIndex( edgePtr->getID() );
// cout << "get new message" << endl;
if ( !maximize )
{
// Multiply both, and update the potential
// cout << "Edge potentials:" << edgePotentials.transpose() << endl;
// cout << "nodePotPlusIncMsg:" << nodePotPlusIncMsg.transpose() << endl;
newMessage = edgePotentials * nodePotPlusIncMsg;
// Normalize new message
if (newMessage.sum())
newMessage = newMessage / newMessage.sum();
//cout << "New message 3:" << newMessage.transpose() << endl;
}
else
{
if ( nodeID == ID1 )
newMessage.resize(messages[ edgeIndex ][0].rows());
else
newMessage.resize(messages[ edgeIndex ][1].rows());
for ( size_t row = 0; row < edgePotentials.rows(); row++ )
{
double maxRowValue = std::numeric_limits<double>::min();
for ( size_t col = 0; col < edgePotentials.cols(); col++ )
{
double value = edgePotentials(row,col)*nodePotPlusIncMsg(col);
if ( value > maxRowValue )
maxRowValue = value;
}
newMessage(row) = maxRowValue;
}
// Normalize new message
if (newMessage.sum())
newMessage = newMessage / newMessage.sum();
//cout << "New message: " << endl << newMessage << endl;
}
//
// Set the message!
//
VectorXd smoothedOldMessage(newMessage.rows());
smoothedOldMessage.setZero();
double smoothing = options.particularD["smoothing"];
if ( smoothing != 0 )
if ( nodeID == ID1 )
newMessage = newMessage + (1-smoothing) * messages[ edgeIndex ][0];
else
newMessage = newMessage + (1-smoothing) * messages[ edgeIndex ][1];
//cout << "New message:" << endl << newMessage << endl << "Smoothed" << endl << smoothedOldMessage << endl;
// If residual belief propagation is activated, just check if the
// newMessage is the one with the higest residual till the
// moment. Otherwise, set the new message as the current one
if ( options.particularS["order"] == "RBP" )
{
if ( nodeID == ID1 )
{
VectorXd differences = messages[edgeIndex][0] - newMessage;
double difference = differences.cwiseAbs().sum();
if ( difference > maxDifference )
{
from1to2 = true;
edgeWithMaxDiffIndex = edgeIndex;
maxDifference = difference;
associatedMessage = newMessage;
}
}
else
{
VectorXd differences = messages[edgeIndex][1] - newMessage;
double difference = differences.cwiseAbs().sum();
if ( difference > maxDifference )
{
from1to2 = false;
edgeWithMaxDiffIndex = edgeIndex;
maxDifference = difference;
associatedMessage = newMessage;
}
}
}
else
{
// cout << newMessage.cols() << " " << newMessage.rows() << endl;
// cout << "edgeIndex" << edgeIndex << endl;
if ( nodeID == ID1 )
{
// cout << messages[ edgeIndex ][0].cols() << " " << messages[ edgeIndex ][0].rows() << endl;
messages[ edgeIndex ][0] = newMessage;
}
else
{
// cout << messages[ edgeIndex ][1].cols() << " " << messages[ edgeIndex ][1].rows() << endl;
messages[ edgeIndex ][1] = newMessage;
}
// cout << "Wop " << endl;
}
}
} // Nodes
if ( options.particularS["order"] == "RBP" && ( edgeWithMaxDiffIndex =! -1 ))
{
if ( from1to2 )
messages[ edgeWithMaxDiffIndex ][0] = associatedMessage;
else
messages[ edgeWithMaxDiffIndex ][1] = associatedMessage;
}
//
// Check convergency!!
//
double newTotalSumOfMsgs = 0;
for ( size_t i = 0; i < N_edges; i++ )
{
newTotalSumOfMsgs += messages[i][0].sum() + messages[i][1].sum();
}
//printf("%4.10f\n",std::abs( totalSumOfMsgs - newTotalSumOfMsgs ));
if ( std::abs( totalSumOfMsgs - newTotalSumOfMsgs ) <
options.convergency )
break;
totalSumOfMsgs = newTotalSumOfMsgs;
// Show messages
/*cout << "Iteration:" << iteration << endl;
for ( size_t i = 0; i < messages.size(); i++ )
{
cout << messages[i][0] << " " << messages[i][1] << endl;
}*/
} // Iterations
return 1;
}
/** Method for getting a bound graph from the one stored into the object.
* \param boundGraph: resulting graph, it must be empty when the method
* is called.
* \param nodesToBound: a map containing as key the id of a node, and
* as value the class/state to be bound.
*/
void getBoundGraph( CGraph &boundGraph,
std::map<size_t,size_t> nodesToBound )
{
// Check that the graph is empty
assert( boundGraph.getNodes().size() == 0 );
// Copy the graph into boundGraph
// Copy nodes
for ( size_t node = 0; node < m_nodes.size(); node++ )
{
CNodePtr nodePtr(new CNode(*m_nodes[node]));
boundGraph.addNode( nodePtr );
}
// Copy edges
for ( size_t edge = 0; edge < m_edges.size(); edge++ )
{
CEdgePtr edgePtr( new CEdge(*m_edges[edge]));
boundGraph.addEdge( edgePtr );
}
// Okey, now iterate over the nodes to be bound, removing then from
// the resulting graph by expanding the potential associated with
// their bound state
for ( std::map<size_t,size_t>::iterator it = nodesToBound.begin();
it != nodesToBound.end();
it++ )
{
size_t nodeID = it->first;
size_t nodeState = it->second;
// Potential of the state to be bounded
double nodePotential = boundGraph.getNodeWithID( nodeID )->getPotentials()( nodeState );
// Iterate over the neighbours, updating their node potentials
// according to the state of the node to be bound and its potential
pair<multimap<size_t,CEdgePtr>::iterator,multimap<size_t,CEdgePtr>::iterator > neighbors;
neighbors = boundGraph.getEdgesF().equal_range(nodeID);
for ( multimap<size_t,CEdgePtr>::iterator it = neighbors.first;
it != neighbors.second;
it++ )
{
CEdgePtr edgePtr( (*it).second );
Eigen::MatrixXd edgePotentials = edgePtr->getPotentials();
size_t ID1, ID2;
edgePtr->getNodesID(ID1,ID2);
// If the node to be bound is the first one appearing in the
// edge.
if ( ID1 == nodeID )
{
CNodePtr nodePtr = boundGraph.getNodeWithID( ID2 );
Eigen::VectorXd boundPotentials = edgePotentials.row(nodeState).transpose()*nodePotential;
Eigen::VectorXd newPotentials = nodePtr->getPotentials().cwiseProduct(boundPotentials);
nodePtr->setPotentials( newPotentials );
}
else // If it is the second one in the edge
{
CNodePtr nodePtr = boundGraph.getNodeWithID( ID1 );
Eigen::VectorXd boundPotentials = edgePotentials.col( nodeState )*nodePotential;
Eigen::VectorXd newPotentials = nodePtr->getPotentials().cwiseProduct(boundPotentials);
nodePtr->setPotentials( newPotentials );
}
}
// Now that the potential of the state of the node to bound
// has been expanded, delete the node from the graph.
boundGraph.deleteNode( nodeID );
}
}
