public boolean removeEdge(Edge edge) {
if (!Edges.isDirectedEdge(edge))
throw new IllegalArgumentException("Only directed edges are expected in the model.");
Node node1 = Edges.getDirectedEdgeTail(edge);
Node node2 = Edges.getDirectedEdgeHead(edge);
NodeId id1 = getNodeId(node1);
NodeId id2 = getNodeId(node2);
int lag = id1.getLag() - id2.getLag();
boolean removed = false;
for (int _lag = 0; _lag <= getMaxLag(); _lag++) {
Node from = getNode(id1.getName(), _lag + lag);
Node to = getNode(id2.getName(), _lag);
if (from != null && to != null) {
Edge _edge = getGraph().getEdge(from, to);
if (_edge != null) {
boolean b = getGraph().removeEdge(_edge);
removed = removed || b;
}
}
}
return removed;
}
private void thenHasEdges(String... expectedEdges) {
assertEquals(expectedEdges.length, edges.getCount());
for (int i = 0; i < expectedEdges.length; i++) {
Edge actualEdge = edges.getEdge(i);
Edge expectedEdge = parseEdge(expectedEdges[i]);
assertEquals(actualEdge, expectedEdge);
}
}
private int getDistance(Vertex node, Vertex target) {
for (Edges edge : edges) {
if (edge.getStart().equals(node) && edge.getDestination().equals(target)) {
return edge.getWeight();
}
}
throw new RuntimeException("Error");
}
public boolean containsParameter(Edge edge) {
if (Edges.isBidirectedEdge(edge)) {
edge =
Edges.bidirectedEdge(
semGraph.getExogenous(edge.getNode1()), semGraph.getExogenous(edge.getNode2()));
}
return edgeParameters.keySet().contains(edge);
}
public void setParameterValue(Edge edge, double value) {
if (Edges.isDirectedEdge(edge)) {
setEdgeCoefficient(edge.getNode1(), edge.getNode2(), value);
} else if (Edges.isBidirectedEdge(edge)) {
setErrorCovariance(edge.getNode1(), edge.getNode2(), value);
} else {
throw new IllegalArgumentException(
"Only directed and bidirected edges are supported: " + edge);
}
}
private List<Vertex> getNeighbors(Vertex node) {
List<Vertex> neighbors = new ArrayList<Vertex>();
for (Edges edge : edges) {
if (edge.getStart().equals(node) && !isSettled(edge.getDestination())) {
neighbors.add(edge.getDestination());
}
}
return neighbors;
}
/**
* @return Returns the error covariance matrix of the model. i.e. [a][b] is the covariance of E_a
* and E_b, with [a][a] of course being the variance of E_a. THESE ARE NOT PARAMETERS OF THE
* MODEL; THEY ARE CALCULATED. Note that elements of this matrix may be Double.NaN; this
* indicates that these elements cannot be calculated.
*/
private TetradMatrix errCovar(Map<Node, Double> errorVariances) {
List<Node> variableNodes = getVariableNodes();
List<Node> errorNodes = new ArrayList<Node>();
for (Node node : variableNodes) {
errorNodes.add(semGraph.getExogenous(node));
}
TetradMatrix errorCovar = new TetradMatrix(errorVariances.size(), errorVariances.size());
for (int index = 0; index < errorNodes.size(); index++) {
Node error = errorNodes.get(index);
double variance = getErrorVariance(error);
errorCovar.set(index, index, variance);
}
for (int index1 = 0; index1 < errorNodes.size(); index1++) {
for (int index2 = 0; index2 < errorNodes.size(); index2++) {
Node error1 = errorNodes.get(index1);
Node error2 = errorNodes.get(index2);
Edge edge = semGraph.getEdge(error1, error2);
if (edge != null && Edges.isBidirectedEdge(edge)) {
double covariance = getErrorCovariance(error1, error2);
errorCovar.set(index1, index2, covariance);
}
}
}
return errorCovar;
}
/**
* Sets the covariance for the a<->b edge to the given covariance, if within range. Otherwise does
* nothing.
*
* @param a a <-> b
* @param b a <-> b
* @param covar The covariance of a <-> b.
* @return true if the coefficent was set (i.e. was within range), false if not.
*/
public boolean setErrorCovariance(Node a, Node b, final double covar) {
Edge edge = Edges.bidirectedEdge(semGraph.getExogenous(a), semGraph.getExogenous(b));
if (edgeParameters.get(edge) == null) {
throw new IllegalArgumentException("Not a covariance parameter in this model: " + edge);
}
if (editingEdge == null || !edge.equals(editingEdge)) {
range = getParameterRange(edge);
editingEdge = edge;
}
if (covar > range.getLow() && covar < range.getHigh()) {
edgeParameters.put(edge, covar);
return true;
} else {
return false;
}
// if (!paramInBounds(edge, coef)) {
// edgeParameters.put(edge, d);
// return false;
// }
//
// edgeParameters.put(edge, coef);
// return true;
// if (!paramInBounds(edge, covar)) {
// edgeParameters.put(edge, d);
// return false;
// }
//
// edgeParameters.put(edge, covar);
// return true;
}
/**
* Sets the coefficient for the a->b edge to the given coefficient, if within range. Otherwise
* does nothing.
*
* @param a a -> b
* @param b a -> b
* @param coef The coefficient of a -> b.
* @return true if the coefficent was set (i.e. was within range), false if not.
*/
public boolean setEdgeCoefficient(Node a, Node b, final double coef) {
Edge edge = Edges.directedEdge(a, b);
if (edgeParameters.get(edge) == null) {
throw new NullPointerException("Not a coefficient parameter in this model: " + edge);
}
if (editingEdge == null || !edge.equals(editingEdge)) {
range = getParameterRange(edge);
editingEdge = edge;
}
if (coef > range.getLow() && coef < range.getHigh()) {
edgeParameters.put(edge, coef);
return true;
}
return false;
// if (!paramInBounds(edge, coef)) {
// edgeParameters.put(edge, d);
// return false;
// }
//
// edgeParameters.put(edge, coef);
// return true;
}
public TimeLagGraphWrapper(GraphWrapper graphWrapper) {
if (graphWrapper == null) {
throw new NullPointerException("No graph wrapper.");
}
TimeLagGraph graph = new TimeLagGraph();
Graph _graph = graphWrapper.getGraph();
for (Node node : _graph.getNodes()) {
Node _node = node.like(node.getName() + ":0");
_node.setNodeType(node.getNodeType());
graph.addNode(_node);
}
for (Edge edge : _graph.getEdges()) {
if (!Edges.isDirectedEdge(edge)) {
throw new IllegalArgumentException();
}
Node from = edge.getNode1();
Node to = edge.getNode2();
Node _from = graph.getNode(from.getName(), 1);
Node _to = graph.getNode(to.getName(), 0);
graph.addDirectedEdge(_from, _to);
}
this.graph = graph;
}
public static Graph erdosRenyiGraph(int n, int e) {
List<Node> nodes = new ArrayList<Node>();
for (int i = 0; i < n; i++) nodes.add(new GraphNode("X" + i));
Graph graph = new EdgeListGraph(nodes);
for (int e0 = 0; e0 < e; e0++) {
int i1 = RandomUtil.getInstance().nextInt(n);
int i2 = RandomUtil.getInstance().nextInt(n);
if (i1 == i2) {
e0--;
continue;
}
Edge edge = Edges.undirectedEdge(nodes.get(i1), nodes.get(i2));
if (graph.containsEdge(edge)) {
e0--;
continue;
}
graph.addEdge(edge);
}
return graph;
}
private boolean existsUnblockedSemiDirectedPath(Node from, Node to, List<Node> cond, Graph G) {
Queue<Node> Q = new LinkedList<Node>();
Set<Node> V = new HashSet<Node>();
Q.offer(from);
V.add(from);
while (!Q.isEmpty()) {
Node t = Q.remove();
if (t == to) return true;
for (Node u : G.getAdjacentNodes(t)) {
Edge edge = G.getEdge(t, u);
Node c = Edges.traverseSemiDirected(t, edge);
if (c == null) continue;
if (cond.contains(c)) continue;
if (c == to) return true;
if (!V.contains(c)) {
V.add(c);
Q.offer(c);
}
}
}
return false;
}
private void addEdge(String a, String b) {
try {
edges.add(createEdge(a, b));
} catch (Throwable t) {
this.t = t;
}
}
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 boolean isUndirected(Graph graph, Node x, Node y) {
List<Edge> edges = graph.getEdges(x, y);
if (edges.size() == 1) {
Edge edge = graph.getEdge(x, y);
return Edges.isUndirectedEdge(edge);
}
return false;
}
/**
* @param a a->b
* @param b a->b
* @return The coefficient for a->b.
*/
public double getErrorCovariance(Node a, Node b) {
Edge edge = Edges.bidirectedEdge(semGraph.getExogenous(a), semGraph.getExogenous(b));
Double d = edgeParameters.get(edge);
if (d == null) {
throw new IllegalArgumentException("Not a covariance parameter in this model: " + edge);
}
return d;
}
public boolean setMaxLag(int maxLag) {
if (maxLag < 0) {
throw new IllegalArgumentException("Max lag must be at least 0: " + maxLag);
}
List<Node> lag0Nodes = getLag0Nodes();
boolean changed = false;
if (maxLag > this.getMaxLag()) {
this.maxLag = maxLag;
for (Node node : lag0Nodes) {
addNode(node);
}
for (Node node : lag0Nodes) {
List<Edge> edges = getGraph().getEdges(node);
for (Edge edge : edges) {
boolean b = addEdge(edge);
changed = changed || b;
}
}
} else if (maxLag < this.getMaxLag()) {
for (Node node : lag0Nodes) {
List<Edge> edges = getGraph().getEdges(node);
for (Edge edge : edges) {
Node tail = Edges.getDirectedEdgeTail(edge);
if (getNodeId(tail).getLag() > maxLag) {
getGraph().removeEdge(edge);
// throw new IllegalArgumentException("This edge has lag greater
// than the new maxLag: " + edge +
// " Please remove first.");
}
}
}
for (Node _node : getNodes()) {
if (getNodeId(_node).getLag() > maxLag) {
boolean b = getGraph().removeNode(_node);
changed = changed || b;
}
}
this.maxLag = maxLag;
}
getPcs().firePropertyChange("editingFinished", null, null);
return changed;
}
/**
* @param a a->b
* @param b a->b
* @return The coefficient for a->b.
*/
public double getEdgeCoefficient(Node a, Node b) {
Edge edge = Edges.directedEdge(a, b);
Double d = edgeParameters.get(edge);
if (d == null) {
return Double.NaN;
// throw new IllegalArgumentException("Not a directed edge in this model: " +
// edge);
}
return d;
}
private Graph pickDag(Graph graph) {
SearchGraphUtils.basicPattern(graph, false);
addRequiredEdges(graph);
boolean containsUndirected;
do {
containsUndirected = false;
for (Edge edge : graph.getEdges()) {
if (Edges.isUndirectedEdge(edge)) {
containsUndirected = true;
graph.removeEdge(edge);
Edge _edge = Edges.directedEdge(edge.getNode1(), edge.getNode2());
graph.addEdge(_edge);
}
}
meekOrient(graph, getKnowledge());
} while (containsUndirected);
return graph;
}
public boolean addEdge(Edge edge) {
if (!Edges.isDirectedEdge(edge)) {
throw new IllegalArgumentException("Only directed edges supported: " + edge);
}
if (!lag0Nodes.contains(edge.getNode2())) {
throw new IllegalArgumentException("Edges into the current time lag only: " + edge);
}
Node node1 = Edges.getDirectedEdgeTail(edge);
Node node2 = Edges.getDirectedEdgeHead(edge);
NodeId id1 = getNodeId(node1);
NodeId id2 = getNodeId(node2);
int lag = id1.getLag() - id2.getLag();
if (lag < 0) {
throw new IllegalArgumentException("Backward edges not permitted: " + edge);
}
for (int _lag = getNodeId(node2).getLag() % getNumInitialLags();
_lag <= getMaxLag() - lag;
_lag += getNumInitialLags()) {
Node from = getNode(id1.getName(), _lag + lag);
Node to = getNode(id2.getName(), _lag);
if (from == null || to == null) {
continue;
}
Edge _edge = Edges.directedEdge(from, to);
if (!getGraph().containsEdge(_edge)) {
getGraph().addDirectedEdge(from, to);
}
}
return true;
}
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);
}
}
}
}
}
private void uncorrelationExogenousVariables() {
Graph graph = getWorkbench().getGraph();
Set<Edge> edges = graph.getEdges();
for (Edge edge : edges) {
if (Edges.isBidirectedEdge(edge)) {
try {
graph.removeEdge(edge);
} catch (Exception e) {
// Ignore.
}
}
}
}
/** @return a string representation of the coefficients and variances of the model. */
public String toString() {
StringBuilder buf = new StringBuilder();
NumberFormat nf = NumberFormatUtil.getInstance().getNumberFormat();
buf.append("\nStandardized SEM:");
buf.append("\n\nEdge coefficients (parameters):\n");
for (Edge edge : edgeParameters.keySet()) {
if (!Edges.isDirectedEdge(edge)) {
continue;
}
buf.append("\n" + edge + " " + nf.format(edgeParameters.get(edge)));
}
buf.append("\n\nError covariances (parameters):\n");
for (Edge edge : edgeParameters.keySet()) {
if (!Edges.isBidirectedEdge(edge)) {
continue;
}
buf.append("\n" + edge + " " + nf.format(edgeParameters.get(edge)));
}
buf.append("\n\nError variances (calculated):\n");
for (Node error : getErrorNodes()) {
double variance = getErrorVariance(error);
buf.append("\n" + error + " " + (Double.isNaN(variance) ? "Undefined" : nf.format(variance)));
}
buf.append("\n");
return buf.toString();
}
public static Graph weightedRandomGraph(int n, int e) {
List<Node> nodes = new ArrayList<Node>();
for (int i = 0; i < n; i++) nodes.add(new GraphNode("X" + i));
Graph graph = new EdgeListGraph(nodes);
for (int e0 = 0; e0 < e; e0++) {
int i1 = weightedRandom(nodes, graph);
// int i2 = RandomUtil.getInstance().nextInt(n);
int i2 = weightedRandom(nodes, graph);
if (!(shortestPath(nodes.get(i1), nodes.get(i2), graph) < 9)) {
e0--;
continue;
}
if (i1 == i2) {
e0--;
continue;
}
Edge edge = Edges.undirectedEdge(nodes.get(i1), nodes.get(i2));
if (graph.containsEdge(edge)) {
e0--;
continue;
}
graph.addEdge(edge);
}
for (Edge edge : graph.getEdges()) {
Node n1 = edge.getNode1();
Node n2 = edge.getNode2();
if (!graph.isAncestorOf(n2, n1)) {
graph.removeEdge(edge);
graph.addDirectedEdge(n1, n2);
} else {
graph.removeEdge(edge);
graph.addDirectedEdge(n2, n1);
}
}
return graph;
}
public boolean setNumInitialLags(int numInitialLags) {
if (numInitialLags < 1) {
throw new IllegalArgumentException(
"The number of initial lags must be at least 1: " + numInitialLags);
}
if (numInitialLags == this.numInitialLags) return false;
List<Node> lag0Nodes = getLag0Nodes();
boolean changed = false;
for (Node node : lag0Nodes) {
NodeId id = getNodeId(node);
for (int lag = 1; lag <= getMaxLag(); lag++) {
Node _node = getNode(id.getName(), lag);
List<Node> nodesInto = getGraph().getNodesInTo(_node, Endpoint.ARROW);
for (Node _node2 : nodesInto) {
Edge edge = Edges.directedEdge(_node2, _node);
boolean b = getGraph().removeEdge(edge);
changed = changed || b;
}
}
}
this.numInitialLags = numInitialLags;
for (Node node : lag0Nodes) {
for (int lag = 0; lag < numInitialLags; lag++) {
List<Edge> edges = getGraph().getEdges(node);
for (Edge edge : edges) {
boolean b = addEdge(edge);
changed = changed || b;
}
}
}
getPcs().firePropertyChange("editingFinished", null, null);
return changed;
}
public boolean removeHighLagEdges(int maxLag) {
List<Node> lag0Nodes = getLag0Nodes();
boolean changed = false;
for (Node node : lag0Nodes) {
List<Edge> edges = getGraph().getEdges(node);
for (Edge edge : new ArrayList<Edge>(edges)) {
Node tail = Edges.getDirectedEdgeTail(edge);
if (getNodeId(tail).getLag() > maxLag) {
boolean b = getGraph().removeEdge(edge);
changed = changed || b;
}
}
}
return changed;
}
/**
* Find all nodes that are connected to Y by an undirected edge that are adjacent to X (that is,
* by undirected or directed edge).
*/
private static List<Node> getNaYX(Node x, Node y, Graph graph) {
List<Edge> yEdges = graph.getEdges(y);
List<Node> nayx = new ArrayList<Node>();
for (Edge edge : yEdges) {
if (!Edges.isUndirectedEdge(edge)) {
continue;
}
Node z = edge.getDistalNode(y);
if (!graph.isAdjacentTo(z, x)) {
continue;
}
nayx.add(z);
}
return nayx;
}
/** Get all nodes that are connected to Y by an undirected edge and not adjacent to X. */
private static List<Node> getTNeighbors(Node x, Node y, Graph graph) {
List<Edge> yEdges = graph.getEdges(y);
List<Node> tNeighbors = new ArrayList<Node>();
for (Edge edge : yEdges) {
if (!Edges.isUndirectedEdge(edge)) {
continue;
}
Node z = edge.getDistalNode(y);
if (graph.isAdjacentTo(z, x)) {
continue;
}
tNeighbors.add(z);
}
return tNeighbors;
}
private void correlateExogenousVariables() {
Graph graph = getWorkbench().getGraph();
if (graph instanceof Dag) {
JOptionPane.showMessageDialog(
JOptionUtils.centeringComp(), "Cannot add bidirected edges to DAG's.");
return;
}
List<Node> nodes = graph.getNodes();
List<Node> exoNodes = new LinkedList<Node>();
for (int i = 0; i < nodes.size(); i++) {
Node node = nodes.get(i);
if (graph.isExogenous(node)) {
exoNodes.add(node);
}
}
for (int i = 0; i < exoNodes.size(); i++) {
loop:
for (int j = i + 1; j < exoNodes.size(); j++) {
Node node1 = exoNodes.get(i);
Node node2 = exoNodes.get(j);
List<Edge> edges = graph.getEdges(node1, node2);
for (int k = 0; k < edges.size(); k++) {
Edge edge = edges.get(k);
if (Edges.isBidirectedEdge(edge)) {
continue loop;
}
}
graph.addBidirectedEdge(node1, node2);
}
}
}
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);
}
}
}
