private Graph condense(Graph mimStructure, Graph mimbuildStructure) {
// System.out.println("Uncondensed: " + mimbuildStructure);
Map<Node, Node> substitutions = new HashMap<Node, Node>();
for (Node node : mimbuildStructure.getNodes()) {
for (Node _node : mimStructure.getNodes()) {
if (node.getName().startsWith(_node.getName())) {
substitutions.put(node, _node);
break;
}
substitutions.put(node, node);
}
}
HashSet<Node> nodes = new HashSet<Node>(substitutions.values());
Graph graph = new EdgeListGraph(new ArrayList<Node>(nodes));
for (Edge edge : mimbuildStructure.getEdges()) {
Node node1 = substitutions.get(edge.getNode1());
Node node2 = substitutions.get(edge.getNode2());
if (node1 == node2) continue;
if (graph.isAdjacentTo(node1, node2)) continue;
graph.addEdge(new Edge(node1, node2, edge.getEndpoint1(), edge.getEndpoint2()));
}
// System.out.println("Condensed: " + graph);
return graph;
}
// Cannot be done if the graph changes.
public void setInitialGraph(Graph initialGraph) {
initialGraph = GraphUtils.replaceNodes(initialGraph, variables);
out.println("Initial graph variables: " + initialGraph.getNodes());
out.println("Data set variables: " + variables);
if (!new HashSet<Node>(initialGraph.getNodes()).equals(new HashSet<Node>(variables))) {
throw new IllegalArgumentException("Variables aren't the same.");
}
this.initialGraph = initialGraph;
}
private Graph changeLatentNames(Graph full, Clusters measurements, List<String> latentVarList) {
Graph g2 = null;
try {
g2 = (Graph) new MarshalledObject(full).get();
} catch (IOException e) {
e.printStackTrace();
} catch (ClassNotFoundException e) {
e.printStackTrace();
}
for (int i = 0; i < measurements.getNumClusters(); i++) {
List<String> d = measurements.getCluster(i);
String latentName = latentVarList.get(i);
for (Node node : full.getNodes()) {
if (!(node.getNodeType() == NodeType.LATENT)) {
continue;
}
List<Node> _children = full.getChildren(node);
_children.removeAll(ReidentifyVariables.getLatents(full));
List<String> childNames = getNames(_children);
if (new HashSet<String>(childNames).equals(new HashSet<String>(d))) {
g2.getNode(node.getName()).setName(latentName);
}
}
}
return g2;
}
// ===========================SCORING METHODS===================//
public double scoreDag(Graph graph) {
Graph dag = new EdgeListGraphSingleConnections(graph);
buildIndexing(graph);
double score = 0.0;
for (Node y : dag.getNodes()) {
Set<Node> parents = new HashSet<Node>(dag.getParents(y));
int nextIndex = -1;
for (int i = 0; i < getVariables().size(); i++) {
nextIndex = hashIndices.get(variables.get(i));
}
int parentIndices[] = new int[parents.size()];
Iterator<Node> pi = parents.iterator();
int count = 0;
while (pi.hasNext()) {
Node nextParent = pi.next();
parentIndices[count++] = hashIndices.get(nextParent);
}
if (this.isDiscrete()) {
score += localDiscreteScore(nextIndex, parentIndices);
} else {
score += localSemScore(nextIndex, parentIndices);
}
}
return score;
}
private Graph structure(Graph mim) {
List<Node> latents = new ArrayList<Node>();
for (Node node : mim.getNodes()) {
if (node.getNodeType() == NodeType.LATENT) {
latents.add(node);
}
}
return mim.subgraph(latents);
}
private Graph restrictToEmpiricalLatents(Graph mimStructure, Graph mimbuildStructure) {
Graph _mim = new EdgeListGraph(mimStructure);
for (Node node : mimbuildStructure.getNodes()) {
if (!mimbuildStructure.containsNode(node)) {
_mim.removeNode(node);
}
}
return _mim;
}
private static double characteristicPathLength(Graph g) {
List<Node> nodes = g.getNodes();
int total = 0;
int count = 0;
for (int i = 0; i < nodes.size(); i++) {
for (int j = i; j < nodes.size(); j++) {
int shortest = shortestPath(nodes.get(i), nodes.get(j), g);
total += shortest;
count++;
}
}
return total / (double) count;
}
public void testAlternativeGraphs() {
// UniformGraphGenerator gen = new UniformGraphGenerator(UniformGraphGenerator.ANY_DAG);
// gen.setNumNodes(100);
// gen.setMaxEdges(200);
// gen.setMaxDegree(30);
// gen.setMaxInDegree(30);
// gen.setMaxOutDegree(30);
//// gen.setNumIterations(3000000);
// gen.setResamplingDegree(10);
//
// gen.generate();
//
// Graph graph = gen.getDag();
Graph graph = weightedRandomGraph(250, 400);
List<Integer> degreeCounts = new ArrayList<Integer>();
Map<Integer, Integer> degreeCount = new HashMap<Integer, Integer>();
for (Node node : graph.getNodes()) {
int degree = graph.getNumEdges(node);
degreeCounts.add(degree);
if (degreeCount.get(degree) == null) {
degreeCount.put(degree, 0);
}
degreeCount.put(degree, degreeCount.get(degree) + 1);
}
Collections.sort(degreeCounts);
System.out.println(degreeCounts);
List<Integer> _degrees = new ArrayList<Integer>(degreeCount.keySet());
Collections.sort(_degrees);
for (int i : _degrees) {
int j = degreeCount.get(i);
// System.out.println(i + " " + j);
System.out.println(log(i + 1) + " " + log(j));
}
System.out.println("\nCPL = " + characteristicPathLength(graph));
Graph erGraph = erdosRenyiGraph(200, 200);
System.out.println("\n ER CPL = " + characteristicPathLength(erGraph));
}
/**
* Greedy equivalence search: Start from the empty graph, add edges till model is significant.
* Then start deleting edges till a minimum is achieved.
*
* @return the resulting Pattern.
*/
public Graph search() {
Graph graph;
if (initialGraph == null) {
graph = new EdgeListGraphSingleConnections(getVariables());
} else {
graph = new EdgeListGraphSingleConnections(initialGraph);
}
fireGraphChange(graph);
buildIndexing(graph);
addRequiredEdges(graph);
topGraphs.clear();
storeGraph(graph);
List<Node> nodes = graph.getNodes();
long start = System.currentTimeMillis();
score = 0.0;
// Do forward search.
fes(graph, nodes);
// Do backward search.
bes(graph);
long endTime = System.currentTimeMillis();
this.elapsedTime = endTime - start;
this.logger.log("graph", "\nReturning this graph: " + graph);
this.logger.log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
this.logger.flush();
return graph;
}
private void buildIndexing(Graph graph) {
this.hashIndices = new HashMap<Node, Integer>();
for (Node node : graph.getNodes()) {
this.hashIndices.put(node, variables.indexOf(node));
}
}
