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);
}
}
}
public Graph orient() {
Graph skeleton = GraphUtils.undirectedGraph(getPattern());
Graph graph = new EdgeListGraph(skeleton.getNodes());
List<Node> nodes = skeleton.getNodes();
// Collections.shuffle(nodes);
if (isR1Done()) {
ruleR1(skeleton, graph, nodes);
}
for (Edge edge : skeleton.getEdges()) {
if (!graph.isAdjacentTo(edge.getNode1(), edge.getNode2())) {
graph.addUndirectedEdge(edge.getNode1(), edge.getNode2());
}
}
if (isR2Done()) {
ruleR2(skeleton, graph);
}
if (isMeekDone()) {
new MeekRules().orientImplied(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 void ruleR1(Graph skeleton, Graph graph, List<Node> nodes) {
for (Node node : nodes) {
SortedMap<Double, String> scoreReports = new TreeMap<Double, String>();
List<Node> adj = skeleton.getAdjacentNodes(node);
DepthChoiceGenerator gen = new DepthChoiceGenerator(adj.size(), adj.size());
int[] choice;
double maxScore = Double.NEGATIVE_INFINITY;
List<Node> parents = null;
while ((choice = gen.next()) != null) {
List<Node> _parents = GraphUtils.asList(choice, adj);
double score = score(node, _parents);
scoreReports.put(-score, _parents.toString());
if (score > maxScore) {
maxScore = score;
parents = _parents;
}
}
for (double score : scoreReports.keySet()) {
TetradLogger.getInstance()
.log(
"score",
"For " + node + " parents = " + scoreReports.get(score) + " score = " + -score);
}
TetradLogger.getInstance().log("score", "");
if (parents == null) {
continue;
}
if (normal(node, parents)) continue;
for (Node _node : adj) {
if (parents.contains(_node)) {
Edge parentEdge = Edges.directedEdge(_node, node);
if (!graph.containsEdge(parentEdge)) {
graph.addEdge(parentEdge);
}
}
}
}
}
// 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);
}
}
}
public Graph search(List<Node> nodes) {
long startTime = System.currentTimeMillis();
localScoreCache.clear();
if (!dataSet().getVariables().containsAll(nodes)) {
throw new IllegalArgumentException("All of the nodes must be in " + "the supplied data set.");
}
Graph graph;
if (initialGraph == null) {
graph = new EdgeListGraphSingleConnections(nodes);
} else {
initialGraph = GraphUtils.replaceNodes(initialGraph, variables);
graph = new EdgeListGraphSingleConnections(initialGraph);
}
topGraphs.clear();
buildIndexing(graph);
addRequiredEdges(graph);
score = 0.0;
// Do forward search.
fes(graph, nodes);
// Do backward search.
bes(graph);
long endTime = System.currentTimeMillis();
this.elapsedTime = endTime - startTime;
this.logger.log("graph", "\nReturning this graph: " + graph);
this.logger.log("info", "Elapsed time = " + (elapsedTime) / 1000. + " s");
this.logger.flush();
return graph;
}
private void resolveOneEdgeMax(Graph graph, Node x, Node y, boolean strong, Graph oldGraph) {
if (RandomUtil.getInstance().nextDouble() > 0.5) {
Node temp = x;
x = y;
y = temp;
}
TetradLogger.getInstance().log("info", "\nEDGE " + x + " --- " + y);
SortedMap<Double, String> scoreReports = new TreeMap<Double, String>();
List<Node> neighborsx = graph.getAdjacentNodes(x);
neighborsx.remove(y);
double max = Double.NEGATIVE_INFINITY;
boolean left = false;
boolean right = false;
DepthChoiceGenerator genx = new DepthChoiceGenerator(neighborsx.size(), neighborsx.size());
int[] choicex;
while ((choicex = genx.next()) != null) {
List<Node> condxMinus = GraphUtils.asList(choicex, neighborsx);
List<Node> condxPlus = new ArrayList<Node>(condxMinus);
condxPlus.add(y);
double xPlus = score(x, condxPlus);
double xMinus = score(x, condxMinus);
List<Node> neighborsy = graph.getAdjacentNodes(y);
neighborsy.remove(x);
DepthChoiceGenerator geny = new DepthChoiceGenerator(neighborsy.size(), neighborsy.size());
int[] choicey;
while ((choicey = geny.next()) != null) {
List<Node> condyMinus = GraphUtils.asList(choicey, neighborsy);
// List<Node> parentsY = oldGraph.getParents(y);
// parentsY.remove(x);
// if (!condyMinus.containsAll(parentsY)) {
// continue;
// }
List<Node> condyPlus = new ArrayList<Node>(condyMinus);
condyPlus.add(x);
double yPlus = score(y, condyPlus);
double yMinus = score(y, condyMinus);
// Checking them all at once is expensive but avoids lexical ordering problems in the
// algorithm.
if (normal(y, condyPlus)
|| normal(x, condxMinus)
|| normal(x, condxPlus)
|| normal(y, condyMinus)) {
continue;
}
double delta = 0.0;
if (strong) {
if (yPlus <= xPlus + delta && xMinus <= yMinus + delta) {
double score = combinedScore(xPlus, yMinus);
if (yPlus <= yMinus + delta && xMinus <= xPlus + delta) {
StringBuilder builder = new StringBuilder();
builder.append("\nStrong " + y + "->" + x + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
if (score > max) {
max = score;
left = true;
right = false;
}
} else {
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
}
} else if (xPlus <= yPlus + delta && yMinus <= xMinus + delta) {
double score = combinedScore(yPlus, xMinus);
if (yMinus <= yPlus + delta && xPlus <= xMinus + delta) {
StringBuilder builder = new StringBuilder();
builder.append("\nStrong " + x + "->" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
if (score > max) {
max = score;
left = false;
right = true;
}
} else {
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
}
} else if (yPlus <= xPlus + delta && yMinus <= xMinus + delta) {
double score = combinedScore(yPlus, xMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
} else if (xPlus <= yPlus + delta && xMinus <= yMinus + delta) {
double score = combinedScore(yPlus, xMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
}
} else {
if (yPlus <= xPlus + delta && xMinus <= yMinus + delta) {
double score = combinedScore(xPlus, yMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nWeak " + y + "->" + x + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
if (score > max) {
max = score;
left = true;
right = false;
}
} else if (xPlus <= yPlus + delta && yMinus <= xMinus + delta) {
double score = combinedScore(yPlus, xMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nWeak " + x + "->" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
if (score > max) {
max = score;
left = false;
right = true;
}
} else if (yPlus <= xPlus + delta && yMinus <= xMinus + delta) {
double score = combinedScore(yPlus, xMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
} else if (xPlus <= yPlus + delta && xMinus <= yMinus + delta) {
double score = combinedScore(yPlus, xMinus);
StringBuilder builder = new StringBuilder();
builder.append("\nNo directed edge " + x + "--" + y + " " + score);
builder.append("\n Parents(" + x + ") = " + condxMinus);
builder.append("\n Parents(" + y + ") = " + condyMinus);
scoreReports.put(-score, builder.toString());
}
}
}
}
for (double score : scoreReports.keySet()) {
TetradLogger.getInstance().log("info", scoreReports.get(score));
}
graph.removeEdges(x, y);
if (left) {
graph.addDirectedEdge(y, x);
}
if (right) {
graph.addDirectedEdge(x, y);
}
if (!graph.isAdjacentTo(x, y)) {
graph.addUndirectedEdge(x, y);
}
}
/**
* Calculates the error variance for the given error node, given all of the coefficient values in
* the model.
*
* @param error An error term in the model--i.e. a variable with NodeType.ERROR.
* @return The value of the error variance, or Double.NaN is the value is undefined.
*/
private double calculateErrorVarianceFromParams(Node error) {
error = semGraph.getNode(error.getName());
Node child = semGraph.getChildren(error).get(0);
List<Node> parents = semGraph.getParents(child);
double otherVariance = 0;
for (Node parent : parents) {
if (parent == error) continue;
double coef = getEdgeCoefficient(parent, child);
otherVariance += coef * coef;
}
if (parents.size() >= 2) {
ChoiceGenerator gen = new ChoiceGenerator(parents.size(), 2);
int[] indices;
while ((indices = gen.next()) != null) {
Node node1 = parents.get(indices[0]);
Node node2 = parents.get(indices[1]);
double coef1, coef2;
if (node1.getNodeType() != NodeType.ERROR) {
coef1 = getEdgeCoefficient(node1, child);
} else {
coef1 = 1;
}
if (node2.getNodeType() != NodeType.ERROR) {
coef2 = getEdgeCoefficient(node2, child);
} else {
coef2 = 1;
}
List<List<Node>> treks = GraphUtils.treksIncludingBidirected(semGraph, node1, node2);
double cov = 0.0;
for (List<Node> trek : treks) {
double product = 1.0;
for (int i = 1; i < trek.size(); i++) {
Node _node1 = trek.get(i - 1);
Node _node2 = trek.get(i);
Edge edge = semGraph.getEdge(_node1, _node2);
double factor;
if (Edges.isBidirectedEdge(edge)) {
factor = edgeParameters.get(edge);
} else if (!edgeParameters.containsKey(edge)) {
factor = 1;
} else if (semGraph.isParentOf(_node1, _node2)) {
factor = getEdgeCoefficient(_node1, _node2);
} else {
factor = getEdgeCoefficient(_node2, _node1);
}
product *= factor;
}
cov += product;
}
otherVariance += 2 * coef1 * coef2 * cov;
}
}
return 1.0 - otherVariance <= 0 ? Double.NaN : 1.0 - otherVariance;
}