/**
* <<<<<<< HEAD ���ߵ�valueֵ���й��� ======= 按边的value值进行过滤 >>>>>>> seuvislogwws/master
*
* @param filter
* @return
*/
public SankeyGraph FilterByEdgeValue(double filter) {
Set<Integer> nodeset = new HashSet<Integer>();
Iterator<? extends Edge> iterator_links = this.links.iterator();
while (iterator_links.hasNext()) {
Edge edge = iterator_links.next();
double value = ((StreamEdge) edge).getValue();
if (value < filter) iterator_links.remove(); // �Ƴ��
else {
nodeset.add(edge.getSource());
nodeset.add(edge.getTarget());
}
}
Iterator<? extends Node> iterator_nodes = this.nodes.iterator();
while (iterator_nodes.hasNext()) {
Node node = iterator_nodes.next();
if (!nodeset.contains(node.getName())) { // ����nodes��
iterator_nodes.remove();
}
}
// System.out.println( "���˺�nodes�Ĵ�С�� "+this.nodes.size());
// �����˹���json����ٴΰ�node��name��0��ʼ�ź�
int index = 0;
for (Node n : this.nodes) {
int old_name = n.getName();
int new_name = index++;
n.setName(new_name);
for (Edge e : this.links) {
if (e.getSource() == old_name) e.setSource(new_name);
if (e.getTarget() == old_name) e.setTarget(new_name);
}
}
return this;
}
private void calculateArrowsForward(Node x, Node y, Graph graph) {
clearArrow(x, y);
if (!knowledgeEmpty()) {
if (getKnowledge().isForbidden(x.getName(), y.getName())) {
return;
}
}
List<Node> naYX = getNaYX(x, y, graph);
List<Node> t = getTNeighbors(x, y, graph);
DepthChoiceGenerator gen = new DepthChoiceGenerator(t.size(), t.size());
int[] choice;
while ((choice = gen.next()) != null) {
List<Node> s = GraphUtils.asList(choice, t);
if (!knowledgeEmpty()) {
if (!validSetByKnowledge(y, s)) {
continue;
}
}
double bump = insertEval(x, y, s, naYX, graph);
if (bump > 0.0) {
Arrow arrow = new Arrow(bump, x, y, s, naYX);
sortedArrows.add(arrow);
addLookupArrow(x, y, arrow);
}
}
}
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;
}
/**
* Use background knowledge to decide if an insert or delete operation does not orient edges in a
* forbidden direction according to prior knowledge. If some orientation is forbidden in the
* subset, the whole subset is forbidden.
*/
private boolean validSetByKnowledge(Node y, List<Node> subset) {
for (Node node : subset) {
if (getKnowledge().isForbidden(node.getName(), y.getName())) {
return false;
}
}
return true;
}
/**
* Transforms a maximally directed pattern (PDAG) represented in graph <code>g</code> into an
* arbitrary DAG by modifying <code>g</code> itself. Based on the algorithm described in
* Chickering (2002) "Optimal structure identification with greedy search" Journal of Machine
* Learning Research. R. Silva, June 2004
*/
public static void pdagToDag(Graph g) {
Graph p = new EdgeListGraph(g);
List<Edge> undirectedEdges = new ArrayList<Edge>();
for (Edge edge : g.getEdges()) {
if (edge.getEndpoint1() == Endpoint.TAIL
&& edge.getEndpoint2() == Endpoint.TAIL
&& !undirectedEdges.contains(edge)) {
undirectedEdges.add(edge);
}
}
g.removeEdges(undirectedEdges);
List<Node> pNodes = p.getNodes();
do {
Node x = null;
for (Node pNode : pNodes) {
x = pNode;
if (p.getChildren(x).size() > 0) {
continue;
}
Set<Node> neighbors = new HashSet<Node>();
for (Edge edge : p.getEdges()) {
if (edge.getNode1() == x || edge.getNode2() == x) {
if (edge.getEndpoint1() == Endpoint.TAIL && edge.getEndpoint2() == Endpoint.TAIL) {
if (edge.getNode1() == x) {
neighbors.add(edge.getNode2());
} else {
neighbors.add(edge.getNode1());
}
}
}
}
if (neighbors.size() > 0) {
Collection<Node> parents = p.getParents(x);
Set<Node> all = new HashSet<Node>(neighbors);
all.addAll(parents);
if (!GraphUtils.isClique(all, p)) {
continue;
}
}
for (Node neighbor : neighbors) {
Node node1 = g.getNode(neighbor.getName());
Node node2 = g.getNode(x.getName());
g.addDirectedEdge(node1, node2);
}
p.removeNode(x);
break;
}
pNodes.remove(x);
} while (pNodes.size() > 0);
}
private double pValue(Node node, List<Node> parents) {
List<Double> _residuals = new ArrayList<Double>();
Node _target = node;
List<Node> _regressors = parents;
Node target = getVariable(variables, _target.getName());
List<Node> regressors = new ArrayList<Node>();
for (Node _regressor : _regressors) {
Node variable = getVariable(variables, _regressor.getName());
regressors.add(variable);
}
DATASET:
for (int m = 0; m < dataSets.size(); m++) {
RegressionResult result = regressions.get(m).regress(target, regressors);
TetradVector residualsSingleDataset = result.getResiduals();
for (int h = 0; h < residualsSingleDataset.size(); h++) {
if (Double.isNaN(residualsSingleDataset.get(h))) {
continue DATASET;
}
}
DoubleArrayList _residualsSingleDataset =
new DoubleArrayList(residualsSingleDataset.toArray());
double mean = Descriptive.mean(_residualsSingleDataset);
double std =
Descriptive.standardDeviation(
Descriptive.variance(
_residualsSingleDataset.size(),
Descriptive.sum(_residualsSingleDataset),
Descriptive.sumOfSquares(_residualsSingleDataset)));
for (int i2 = 0; i2 < _residualsSingleDataset.size(); i2++) {
// _residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2) - mean) /
// std);
if (isMeanCenterResiduals()) {
_residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2) - mean));
}
// _residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2)));
}
for (int k = 0; k < _residualsSingleDataset.size(); k++) {
_residuals.add(_residualsSingleDataset.get(k));
}
}
double[] _f = new double[_residuals.size()];
for (int k = 0; k < _residuals.size(); k++) {
_f[k] = _residuals.get(k);
}
return new AndersonDarlingTest(_f).getP();
}
public void printSiblings() {
if (parent == null) System.out.println("Siblings: " + parent);
else {
System.out.print("Siblings: ");
ArrayList<Node> siblings = parent.getChildren();
if (siblings.isEmpty()) System.out.print("null");
else {
for (int i = 0; i < siblings.size(); ++i) {
Node child = siblings.get(i);
if (!child.getName().equals(name)) System.out.print(child.getName() + "\t");
}
}
System.out.println();
}
}
public boolean isViolatedBy(Graph graph) {
for (Edge edge : graph.getEdges()) {
if (!edge.isDirected()) {
continue;
}
Node from = Edges.getDirectedEdgeTail(edge);
Node to = Edges.getDirectedEdgeHead(edge);
if (isForbidden(from.getName(), to.getName())) {
return true;
}
}
return false;
}
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;
}
private List<String> getNames(List<Node> nodes) {
List<String> names = new ArrayList<String>();
for (Node node : nodes) {
names.add(node.getName());
}
return names;
}
private Node getVariable(List<Node> variables, String name) {
for (Node node : variables) {
if (name.equals(node.getName())) {
return node;
}
}
return null;
}
/** Returns the string in nodelist which matches string in BK. */
public static Node translate(String a, List<Node> nodes) {
for (Node node : nodes) {
if ((node.getName()).equals(a)) {
return node;
}
}
return null;
}
/**
* Helper method. Appears to check if an arrowpoint is permitted by background knowledge.
*
* @param x The possible other node.
* @param y The possible point node.
* @return Whether the arrowpoint is allowed.
*/
private boolean isArrowpointAllowed(Node x, Node y) {
if (graph.getEndpoint(x, y) == Endpoint.ARROW) {
return true;
}
if (graph.getEndpoint(x, y) == Endpoint.TAIL) {
return false;
}
if (graph.getEndpoint(y, x) == Endpoint.ARROW) {
if (!knowledge.isForbidden(x.getName(), y.getName())) return true;
}
if (graph.getEndpoint(y, x) == Endpoint.TAIL) {
if (!knowledge.isForbidden(x.getName(), y.getName())) return true;
}
return graph.getEndpoint(y, x) == Endpoint.CIRCLE;
}
private String reportIfDiscrete(Graph dag, DataSet dataSet) {
List vars = dataSet.getVariables();
Map<String, DiscreteVariable> nodesToVars = new HashMap<String, DiscreteVariable>();
for (int i = 0; i < dataSet.getNumColumns(); i++) {
DiscreteVariable var = (DiscreteVariable) vars.get(i);
String name = var.getName();
Node node = new GraphNode(name);
nodesToVars.put(node.getName(), var);
}
BayesPm bayesPm = new BayesPm(new Dag(dag));
List<Node> nodes = bayesPm.getDag().getNodes();
for (Node node : nodes) {
Node var = nodesToVars.get(node.getName());
if (var instanceof DiscreteVariable) {
DiscreteVariable var2 = nodesToVars.get(node.getName());
int numCategories = var2.getNumCategories();
List<String> categories = new ArrayList<String>();
for (int j = 0; j < numCategories; j++) {
categories.add(var2.getCategory(j));
}
bayesPm.setCategories(node, categories);
}
}
BayesProperties properties = new BayesProperties(dataSet, dag);
properties.setGraph(dag);
NumberFormat nf = NumberFormat.getInstance();
nf.setMaximumFractionDigits(4);
StringBuilder buf = new StringBuilder();
buf.append("\nP-value = ").append(properties.getLikelihoodRatioP());
buf.append("\nDf = ").append(properties.getPValueDf());
buf.append("\nChi square = ").append(nf.format(properties.getPValueChisq()));
buf.append("\nBIC score = ").append(nf.format(properties.getBic()));
buf.append("\n\nH0: Completely disconnected graph.");
return buf.toString();
}
public void printChildren() {
System.out.print("Children: ");
if (children.isEmpty()) System.out.print("null");
else {
for (int i = 0; i < children.size(); ++i) {
Node child = children.get(i);
System.out.print(child.getName() + "\t");
}
}
System.out.println();
}
// Invalid if then nodes or graph changes.
private void calculateArrowsBackward(Node x, Node y, Graph graph) {
if (x == y) {
return;
}
if (!graph.isAdjacentTo(x, y)) {
return;
}
if (!knowledgeEmpty()) {
if (!getKnowledge().noEdgeRequired(x.getName(), y.getName())) {
return;
}
}
List<Node> naYX = getNaYX(x, y, graph);
clearArrow(x, y);
List<Node> _naYX = new ArrayList<Node>(naYX);
DepthChoiceGenerator gen = new DepthChoiceGenerator(_naYX.size(), _naYX.size());
int[] choice;
while ((choice = gen.next()) != null) {
List<Node> H = GraphUtils.asList(choice, _naYX);
if (!knowledgeEmpty()) {
if (!validSetByKnowledge(y, H)) {
continue;
}
}
double bump = deleteEval(x, y, H, naYX, graph);
if (bump > 0.0) {
Arrow arrow = new Arrow(bump, x, y, H, naYX);
sortedArrows.add(arrow);
addLookupArrow(x, y, arrow);
}
}
}
/**
* Constructs a new FCI search for the given independence test and background knowledge and a list
* of variables to search over.
*/
public Rfci(IndependenceTest independenceTest, List<Node> searchVars) {
if (independenceTest == null || knowledge == null) {
throw new NullPointerException();
}
this.independenceTest = independenceTest;
this.variables.addAll(independenceTest.getVariables());
Set<Node> remVars = new HashSet<Node>();
for (Node node1 : this.variables) {
boolean search = false;
for (Node node2 : searchVars) {
if (node1.getName().equals(node2.getName())) {
search = true;
}
}
if (!search) {
remVars.add(node1);
}
}
this.variables.removeAll(remVars);
}
private void initializeArrowsBackward(Graph graph) {
sortedArrows.clear();
lookupArrows.clear();
for (Edge edge : graph.getEdges()) {
Node x = edge.getNode1();
Node y = edge.getNode2();
if (!knowledgeEmpty()) {
if (!getKnowledge().noEdgeRequired(x.getName(), y.getName())) {
continue;
}
}
if (Edges.isDirectedEdge(edge)) {
calculateArrowsBackward(x, y, graph);
} else {
calculateArrowsBackward(x, y, graph);
calculateArrowsBackward(y, x, graph);
}
}
}
private void buildNameToNodeListTable(Node curNode) throws IOException {
String fullName = curNode.getName();
String parent = curNode.getParent();
String separator = System.getProperty("file.separator");
if (parent != null) {
if (!fullName.startsWith(parent)) {
throw new RuntimeException(
"Internal error: parent of file name \""
+ fullName
+ "\" does not match file name \""
+ parent
+ "\"");
}
int len = parent.length();
if (!parent.endsWith(separator)) {
len += separator.length();
}
String fileName = fullName.substring(len);
if (fileName == null) {
throw new RuntimeException("Internal error: file name was empty");
}
List nodeList = (List) nameToNodeListTable.get(fileName);
if (nodeList == null) {
nodeList = new Vector();
nameToNodeListTable.put(fileName, nodeList);
}
nodeList.add(curNode);
} else {
if (curNode != rootNode) {
throw new RuntimeException(
"Internal error: parent of file + \"" + fullName + "\"" + " was null");
}
}
if (curNode.isDirectory()) {
Iterator iter = curNode.getChildren();
if (iter != null) {
while (iter.hasNext()) {
buildNameToNodeListTable((Node) iter.next());
}
}
}
}
public static void arrangeByKnowledgeTiers(Graph graph, Knowledge knowledge) {
if (knowledge.getNumTiers() == 0) {
throw new IllegalArgumentException("There are no Tiers to arrange.");
}
List<Node> nodes = graph.getNodes();
List<String> varNames = new ArrayList<String>();
int ySpace = 500 / knowledge.getNumTiers();
ySpace = ySpace < 50 ? 50 : ySpace;
for (Node node1 : nodes) {
varNames.add(node1.getName());
}
List<String> notInTier = knowledge.getVarsNotInTier(varNames);
int x = 0;
int y = 50 - ySpace;
if (notInTier.size() > 0) {
y += ySpace;
for (String name : notInTier) {
x += 90;
Node node = graph.getNode(name);
if (node != null) {
node.setCenterX(x);
node.setCenterY(y);
}
}
}
for (int i = 0; i < knowledge.getNumTiers(); i++) {
List<String> tier = knowledge.getTier(i);
y += ySpace;
x = -25;
for (String name : tier) {
x += 90;
Node node = graph.getNode(name);
if (node != null) {
node.setCenterX(x);
node.setCenterY(y);
}
}
}
}
public static void buildDefinitions(Session session) {
log.info("started building node definitions");
String nodeName = "";
try {
allNodes = new HashMap<String, VNodeDefinition>();
Node rootNode = session.getNode("/jcr:system/jcr:nodeTypes");
NodeIterator nodeIterator = rootNode.getNodes();
while (nodeIterator.hasNext()) {
Node node = nodeIterator.nextNode();
nodeName = node.getName();
VNodeDefinition vNodeDefinition = new VNodeDefinition(node);
customizeDefinition(vNodeDefinition); // possibly customize this definition
allNodes.put(nodeName, vNodeDefinition);
}
log.info("finished building nodes");
} catch (RepositoryException re) {
log.warn("Could not build node definitions, died at " + nodeName, re);
} finally {
if (session != null) session.logout();
}
}
private JCRNodeWrapper dereference(JCRNodeWrapper parent, String refPath)
throws RepositoryException {
JCRStoreProvider provider = parent.getProvider();
JCRNodeWrapper wrapper;
Node referencedNode = parent.getRealNode().getProperty("j:node").getNode();
String fullPath = parent.getPath() + DEREF_SEPARATOR + refPath;
if (parent.getPath().startsWith(referencedNode.getPath())) {
throw new PathNotFoundException(fullPath);
}
String refRootName = StringUtils.substringBefore(refPath, "/");
if (!referencedNode.getName().equals(refRootName)) {
throw new PathNotFoundException(fullPath);
}
refPath = StringUtils.substringAfter(refPath, "/");
if (refPath.equals("")) {
wrapper = provider.getNodeWrapper(referencedNode, fullPath, parent, this);
} else {
Node node = referencedNode.getNode(refPath);
wrapper = provider.getNodeWrapper(node, fullPath, null, this);
}
sessionCacheByPath.put(fullPath, wrapper);
return wrapper;
}
/** Do an actual deletion (Definition 13 from Chickering, 2002). */
private void delete(Node x, Node y, List<Node> subset, Graph graph, double bump) {
Edge trueEdge = null;
if (trueGraph != null) {
Node _x = trueGraph.getNode(x.getName());
Node _y = trueGraph.getNode(y.getName());
trueEdge = trueGraph.getEdge(_x, _y);
}
if (log && verbose) {
Edge oldEdge = graph.getEdge(x, y);
String label = trueGraph != null && trueEdge != null ? "*" : "";
TetradLogger.getInstance()
.log(
"deletedEdges",
(graph.getNumEdges() - 1)
+ ". DELETE "
+ oldEdge
+ " "
+ subset
+ " ("
+ bump
+ ") "
+ label);
out.println(
(graph.getNumEdges() - 1)
+ ". DELETE "
+ oldEdge
+ " "
+ subset
+ " ("
+ bump
+ ") "
+ label);
} else {
int numEdges = graph.getNumEdges() - 1;
if (numEdges % 50 == 0) out.println(numEdges);
}
graph.removeEdge(x, y);
for (Node h : subset) {
Edge oldEdge = graph.getEdge(y, h);
graph.removeEdge(y, h);
graph.addDirectedEdge(y, h);
if (log) {
TetradLogger.getInstance()
.log("directedEdges", "--- Directing " + oldEdge + " to " + graph.getEdge(y, h));
}
if (verbose) {
out.println("--- Directing " + oldEdge + " to " + graph.getEdge(y, h));
}
if (Edges.isUndirectedEdge(graph.getEdge(x, h))) {
if (!graph.isAdjacentTo(x, h))
throw new IllegalArgumentException("Not adjacent: " + x + ", " + h);
oldEdge = graph.getEdge(x, h);
graph.removeEdge(x, h);
graph.addDirectedEdge(x, h);
if (log) {
TetradLogger.getInstance()
.log("directedEdges", "--- Directing " + oldEdge + " to " + graph.getEdge(x, h));
}
if (verbose) {
out.println("--- Directing " + oldEdge + " to " + graph.getEdge(x, h));
}
}
}
}
private double localScoreB(Node node, List<Node> parents) {
double score = 0.0;
double maxScore = Double.NEGATIVE_INFINITY;
Node _target = node;
List<Node> _regressors = parents;
Node target = getVariable(variables, _target.getName());
List<Node> regressors = new ArrayList<Node>();
for (Node _regressor : _regressors) {
Node variable = getVariable(variables, _regressor.getName());
regressors.add(variable);
}
DATASET:
for (int m = 0; m < dataSets.size(); m++) {
RegressionResult result = regressions.get(m).regress(target, regressors);
TetradVector residualsSingleDataset = result.getResiduals();
DoubleArrayList _residualsSingleDataset =
new DoubleArrayList(residualsSingleDataset.toArray());
for (int h = 0; h < residualsSingleDataset.size(); h++) {
if (Double.isNaN(residualsSingleDataset.get(h))) {
continue DATASET;
}
}
double mean = Descriptive.mean(_residualsSingleDataset);
double std =
Descriptive.standardDeviation(
Descriptive.variance(
_residualsSingleDataset.size(),
Descriptive.sum(_residualsSingleDataset),
Descriptive.sumOfSquares(_residualsSingleDataset)));
for (int i2 = 0; i2 < _residualsSingleDataset.size(); i2++) {
_residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2) - mean) / std);
}
double[] _f = new double[_residualsSingleDataset.size()];
for (int k = 0; k < _residualsSingleDataset.size(); k++) {
_f[k] = _residualsSingleDataset.get(k);
}
DoubleArrayList f = new DoubleArrayList(_f);
for (int k = 0; k < f.size(); k++) {
f.set(k, Math.abs(f.get(k)));
}
double _mean = Descriptive.mean(f);
double diff = _mean - Math.sqrt(2.0 / Math.PI);
score += diff * diff;
if (score > maxScore) {
maxScore = score;
}
}
double avg = score / dataSets.size();
return avg;
}
/* Print the current type graph to the dotfile */
public void printDot(String title, Call call) {
boolean printUnifications = false;
PrintStream ps = PointsToAnalysis.v().file;
if (ps == null) return;
ps.println("\ndigraph F {");
ps.println(" size = \"7,7\"; rankdir = LR;");
ps.println(" orientation = landscape;");
ps.println(" subgraph cluster1 {");
ps.println(" \"Method: " + method.getName() + "\" [color=white];");
if (nodes.isEmpty()) {
ps.println(" \"empty graph\" [color = white];");
ps.println(" }");
ps.println("}");
return;
}
for (Node node : nodes) {
if (!printUnifications && !node.isRep()) continue;
String color = "style=filled,fillcolor=";
if (node.isheap && node.hasallocs) color += "red,";
else if (node.isheap) color += "orange,";
else if (node.hasallocs) color += "grey,";
else color += "white,";
// if (node.istouched) color = "khaki";
// if (node.hassync) color = "khaki";
String shape = "shape=";
if (node.istouched) shape += "box";
else shape += "ellipse";
ps.println(" o" + node.id + "[label = \"" + node.getName() + "\"," + color + shape + "];");
}
ps.println(" }");
Map<Integer, Map<Integer, String>> labels = new HashMap<Integer, Map<Integer, String>>();
for (Field f : fedges.keySet())
for (FieldEdge e : fedges.get(f)) {
if (labels.containsKey(e.src.id)) {
if (labels.get(e.src.id).containsKey(e.dst.id)) {
labels.get(e.src.id).put(e.dst.id, "*");
// labels.get(e.src.id).get(e.dst.id) + ", " +
// e.field.getName());
} else labels.get(e.src.id).put(e.dst.id, e.field.getName());
} else {
Map<Integer, String> is = new HashMap<Integer, String>();
is.put(e.dst.id, e.field.getName());
labels.put(e.src.id, is);
}
}
for (Integer i : labels.keySet())
for (Integer j : labels.get(i).keySet())
ps.print(
" o"
+ i
+ " -> o"
+ j
+ "[label=\""
+ labels.get(i).get(j)
+ "\",style=solid,color=black];");
for (Call ce : cedges.keySet())
for (CallEdge e : cedges.get(ce)) {
if (!(e.call instanceof VirtualCallExpr)) continue;
// if (!e.call.equals(call)) continue;
ps.print(
" o"
+ e.src.id
+ " -> o"
+ e.dst.id
+ "[label=\""
+ e.call
+ "\",style=solid,color=red];");
}
if (printUnifications)
for (Node node : nodes)
if (node.parent != null)
ps.println(" o" + node.id + " -> o" + node.parent.id + " [color = blue];");
ps.println("}");
}
private double andersonDarlingPASquareStarB(Node node, List<Node> parents) {
List<Double> _residuals = new ArrayList<Double>();
Node _target = node;
List<Node> _regressors = parents;
Node target = getVariable(variables, _target.getName());
List<Node> regressors = new ArrayList<Node>();
for (Node _regressor : _regressors) {
Node variable = getVariable(variables, _regressor.getName());
regressors.add(variable);
}
double sum = 0.0;
DATASET:
for (int m = 0; m < dataSets.size(); m++) {
RegressionResult result = regressions.get(m).regress(target, regressors);
TetradVector residualsSingleDataset = result.getResiduals();
for (int h = 0; h < residualsSingleDataset.size(); h++) {
if (Double.isNaN(residualsSingleDataset.get(h))) {
continue DATASET;
}
}
DoubleArrayList _residualsSingleDataset =
new DoubleArrayList(residualsSingleDataset.toArray());
double mean = Descriptive.mean(_residualsSingleDataset);
double std =
Descriptive.standardDeviation(
Descriptive.variance(
_residualsSingleDataset.size(),
Descriptive.sum(_residualsSingleDataset),
Descriptive.sumOfSquares(_residualsSingleDataset)));
// By centering the individual residual columns, all moments of the mixture become weighted
// averages of the moments
// of the individual columns.
// http://en.wikipedia.org/wiki/Mixture_distribution#Finite_and_countable_mixtures
for (int i2 = 0; i2 < _residualsSingleDataset.size(); i2++) {
// _residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2) - mean) /
// std);
// _residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2)) / std);
if (isMeanCenterResiduals()) {
_residualsSingleDataset.set(i2, (_residualsSingleDataset.get(i2) - mean));
}
}
double[] _f = new double[_residuals.size()];
for (int k = 0; k < _residuals.size(); k++) {
_f[k] = _residuals.get(k);
}
sum += new AndersonDarlingTest(_f).getASquaredStar();
}
return sum / dataSets.size();
}
// serial.
private void insert(Node x, Node y, List<Node> t, Graph graph, double bump) {
if (graph.isAdjacentTo(x, y)) {
return; // The initial graph may already have put this edge in the graph.
// throw new IllegalArgumentException(x + " and " + y + " are already adjacent in
// the graph.");
}
Edge trueEdge = null;
if (trueGraph != null) {
Node _x = trueGraph.getNode(x.getName());
Node _y = trueGraph.getNode(y.getName());
trueEdge = trueGraph.getEdge(_x, _y);
}
graph.addDirectedEdge(x, y);
if (log) {
String label = trueGraph != null && trueEdge != null ? "*" : "";
TetradLogger.getInstance()
.log(
"insertedEdges",
graph.getNumEdges()
+ ". INSERT "
+ graph.getEdge(x, y)
+ " "
+ t
+ " "
+ bump
+ " "
+ label);
} else {
int numEdges = graph.getNumEdges() - 1;
if (verbose) {
if (numEdges % 50 == 0) out.println(numEdges);
}
}
if (verbose) {
String label = trueGraph != null && trueEdge != null ? "*" : "";
out.println(
graph.getNumEdges()
+ ". INSERT "
+ graph.getEdge(x, y)
+ " "
+ t
+ " "
+ bump
+ " "
+ label);
} else {
int numEdges = graph.getNumEdges() - 1;
if (verbose) {
if (numEdges % 50 == 0) out.println(numEdges);
}
}
for (Node _t : t) {
Edge oldEdge = graph.getEdge(_t, y);
if (oldEdge == null) throw new IllegalArgumentException("Not adjacent: " + _t + ", " + y);
graph.removeEdge(_t, y);
graph.addDirectedEdge(_t, y);
if (log && verbose) {
TetradLogger.getInstance()
.log("directedEdges", "--- Directing " + oldEdge + " to " + graph.getEdge(_t, y));
out.println("--- Directing " + oldEdge + " to " + graph.getEdge(_t, y));
}
}
}
/**
* Transforms a DAG represented in graph <code>graph</code> into a maximally directed pattern
* (PDAG) by modifying <code>g</code> itself. Based on the algorithm described in Chickering
* (2002) "Optimal structure identification with greedy search" Journal of Machine Learning
* Research. It works for both BayesNets and SEMs. R. Silva, June 2004
*/
public static void dagToPdag(Graph graph) {
// do topological sort on the nodes
Graph graphCopy = new EdgeListGraph(graph);
Node orderedNodes[] = new Node[graphCopy.getNodes().size()];
int count = 0;
while (graphCopy.getNodes().size() > 0) {
Set<Node> exogenousNodes = new HashSet<Node>();
for (Node next : graphCopy.getNodes()) {
if (graphCopy.isExogenous(next)) {
exogenousNodes.add(next);
orderedNodes[count++] = graph.getNode(next.getName());
}
}
graphCopy.removeNodes(new ArrayList<Node>(exogenousNodes));
}
// ordered edges - improvised, inefficient implementation
count = 0;
Edge edges[] = new Edge[graph.getNumEdges()];
boolean edgeOrdered[] = new boolean[graph.getNumEdges()];
Edge orderedEdges[] = new Edge[graph.getNumEdges()];
for (Edge edge : graph.getEdges()) {
edges[count++] = edge;
}
for (int i = 0; i < edges.length; i++) {
edgeOrdered[i] = false;
}
while (count > 0) {
for (Node orderedNode : orderedNodes) {
for (int k = orderedNodes.length - 1; k >= 0; k--) {
for (int q = 0; q < edges.length; q++) {
if (!edgeOrdered[q]
&& edges[q].getNode1() == orderedNodes[k]
&& edges[q].getNode2() == orderedNode) {
edgeOrdered[q] = true;
orderedEdges[orderedEdges.length - count] = edges[q];
count--;
}
}
}
}
}
// label edges
boolean compelledEdges[] = new boolean[graph.getNumEdges()];
boolean reversibleEdges[] = new boolean[graph.getNumEdges()];
for (int i = 0; i < graph.getNumEdges(); i++) {
compelledEdges[i] = false;
reversibleEdges[i] = false;
}
for (int i = 0; i < graph.getNumEdges(); i++) {
if (compelledEdges[i] || reversibleEdges[i]) {
continue;
}
Node x = orderedEdges[i].getNode1();
Node y = orderedEdges[i].getNode2();
for (int j = 0; j < orderedEdges.length; j++) {
if (orderedEdges[j].getNode2() == x && compelledEdges[j]) {
Node w = orderedEdges[j].getNode1();
if (!graph.isParentOf(w, y)) {
for (int k = 0; k < orderedEdges.length; k++) {
if (orderedEdges[k].getNode2() == y) {
compelledEdges[k] = true;
break;
}
}
} else {
for (int k = 0; k < orderedEdges.length; k++) {
if (orderedEdges[k].getNode1() == w && orderedEdges[k].getNode2() == y) {
compelledEdges[k] = true;
break;
}
}
}
}
if (compelledEdges[i]) {
break;
}
}
if (compelledEdges[i]) {
continue;
}
boolean foundZ = false;
for (Edge orderedEdge : orderedEdges) {
Node z = orderedEdge.getNode1();
if (z != x && orderedEdge.getNode2() == y && !graph.isParentOf(z, x)) {
compelledEdges[i] = true;
for (int k = i + 1; k < graph.getNumEdges(); k++) {
if (orderedEdges[k].getNode2() == y && !reversibleEdges[k]) {
compelledEdges[k] = true;
}
}
foundZ = true;
break;
}
}
if (!foundZ) {
reversibleEdges[i] = true;
for (int j = i + 1; j < orderedEdges.length; j++) {
if (!compelledEdges[j] && orderedEdges[j].getNode2() == y) {
reversibleEdges[j] = true;
}
}
}
}
// undirect edges that are reversible
for (int i = 0; i < reversibleEdges.length; i++) {
if (reversibleEdges[i]) {
graph.setEndpoint(orderedEdges[i].getNode1(), orderedEdges[i].getNode2(), Endpoint.TAIL);
graph.setEndpoint(orderedEdges[i].getNode2(), orderedEdges[i].getNode1(), Endpoint.TAIL);
}
}
}
private void addRequiredEdges(Graph graph) {
if (true) return;
if (knowledgeEmpty()) return;
for (Iterator<KnowledgeEdge> it = getKnowledge().requiredEdgesIterator(); it.hasNext(); ) {
KnowledgeEdge next = it.next();
Node nodeA = graph.getNode(next.getFrom());
Node nodeB = graph.getNode(next.getTo());
if (!graph.isAncestorOf(nodeB, nodeA)) {
graph.removeEdges(nodeA, nodeB);
graph.addDirectedEdge(nodeA, nodeB);
TetradLogger.getInstance()
.log("insertedEdges", "Adding edge by knowledge: " + graph.getEdge(nodeA, nodeB));
}
}
for (Edge edge : graph.getEdges()) {
final String A = edge.getNode1().getName();
final String B = edge.getNode2().getName();
if (knowledge.isForbidden(A, B)) {
Node nodeA = edge.getNode1();
Node nodeB = edge.getNode2();
if (nodeA != null
&& nodeB != null
&& graph.isAdjacentTo(nodeA, nodeB)
&& !graph.isChildOf(nodeA, nodeB)) {
if (!graph.isAncestorOf(nodeA, nodeB)) {
graph.removeEdges(nodeA, nodeB);
graph.addDirectedEdge(nodeB, nodeA);
TetradLogger.getInstance()
.log("insertedEdges", "Adding edge by knowledge: " + graph.getEdge(nodeB, nodeA));
}
}
if (!graph.isChildOf(nodeA, nodeB)
&& getKnowledge().isForbidden(nodeA.getName(), nodeB.getName())) {
if (!graph.isAncestorOf(nodeA, nodeB)) {
graph.removeEdges(nodeA, nodeB);
graph.addDirectedEdge(nodeB, nodeA);
TetradLogger.getInstance()
.log("insertedEdges", "Adding edge by knowledge: " + graph.getEdge(nodeB, nodeA));
}
}
} else if (knowledge.isForbidden(B, A)) {
Node nodeA = edge.getNode2();
Node nodeB = edge.getNode1();
if (nodeA != null
&& nodeB != null
&& graph.isAdjacentTo(nodeA, nodeB)
&& !graph.isChildOf(nodeA, nodeB)) {
if (!graph.isAncestorOf(nodeA, nodeB)) {
graph.removeEdges(nodeA, nodeB);
graph.addDirectedEdge(nodeB, nodeA);
TetradLogger.getInstance()
.log("insertedEdges", "Adding edge by knowledge: " + graph.getEdge(nodeB, nodeA));
}
}
if (!graph.isChildOf(nodeA, nodeB)
&& getKnowledge().isForbidden(nodeA.getName(), nodeB.getName())) {
if (!graph.isAncestorOf(nodeA, nodeB)) {
graph.removeEdges(nodeA, nodeB);
graph.addDirectedEdge(nodeB, nodeA);
TetradLogger.getInstance()
.log("insertedEdges", "Adding edge by knowledge: " + graph.getEdge(nodeB, nodeA));
}
}
}
}
}
public void printParent() {
if (parent == null) System.out.println("Parent: " + parent);
else System.out.println("Parent: " + parent.getName());
}