public FindOneFactorClustersWithCausalIndicators(
DataSet dataSet, TestType testType, double alpha) {
if (dataSet.isContinuous()) {
this.variables = dataSet.getVariables();
this.test = new ContinuousTetradTest(dataSet, testType, alpha);
this.indTest = new IndTestFisherZ(dataSet, alpha);
this.alpha = alpha;
this.testType = testType;
this.dataModel = dataSet;
if (testType == TestType.TETRAD_DELTA) {
deltaTest = new DeltaTetradTest(dataSet);
deltaTest.setCacheFourthMoments(false);
}
this.cov = new CovarianceMatrix(dataSet);
} else if (dataSet.isDiscrete()) {
this.variables = dataSet.getVariables();
this.test = new DiscreteTetradTest(dataSet, alpha);
this.indTest = new IndTestChiSquare(dataSet, alpha);
this.alpha = alpha;
this.testType = testType;
this.dataModel = dataSet;
if (testType == TestType.TETRAD_DELTA) {
deltaTest = new DeltaTetradTest(dataSet);
deltaTest.setCacheFourthMoments(false);
}
}
}
private boolean testVanishing(int x, int y, int z, int w) {
if (testType == TestType.TETRAD_DELTA) {
Tetrad t1 =
new Tetrad(variables.get(x), variables.get(y), variables.get(z), variables.get(w));
Tetrad t2 =
new Tetrad(variables.get(x), variables.get(y), variables.get(w), variables.get(z));
double p = deltaTest.getPValue(t1, t2);
return p > alpha;
} else {
return test.tetradHolds(x, y, z, w) && test.tetradHolds(x, y, w, z);
}
}
private Void findSeeds() {
Tetrad tetrad = null;
List<Node> empty = new ArrayList();
if (variables.size() < 4) {
Set<Set<Integer>> ESeeds = new HashSet<Set<Integer>>();
}
Map<Node, Set<Node>> adjacencies;
if (depth == -2) {
adjacencies = new HashMap<Node, Set<Node>>();
for (Node node : variables) {
HashSet<Node> _nodes = new HashSet<Node>(variables);
_nodes.remove(node);
adjacencies.put(node, _nodes);
}
} else {
// System.out.println("Running PC adjacency search...");
Graph graph = new EdgeListGraph(variables);
Fas fas = new Fas(graph, indTest);
fas.setVerbose(false);
fas.setDepth(depth); // 1?
adjacencies = fas.searchMapOnly();
// System.out.println("...done.");
}
List<Integer> allVariables = new ArrayList<Integer>();
for (int i = 0; i < variables.size(); i++) allVariables.add(i);
log("Finding seeds.", true);
ChoiceGenerator gen = new ChoiceGenerator(allVariables.size(), 3);
int[] choice;
CHOICE:
while ((choice = gen.next()) != null) {
int n1 = allVariables.get(choice[0]);
int n2 = allVariables.get(choice[1]);
int n3 = allVariables.get(choice[2]);
Node v1 = variables.get(choice[0]);
Node v2 = variables.get(choice[1]);
Node v3 = variables.get(choice[2]);
Set<Integer> triple = triple(n1, n2, n3);
if (!clique(triple, adjacencies)) {
continue;
}
boolean EPure = true;
boolean CPure1 = true;
boolean CPure2 = true;
boolean CPure3 = true;
for (int o : allVariables) {
if (triple.contains(o)) {
continue;
}
Node v4 = variables.get(o);
tetrad = new Tetrad(v1, v2, v3, v4);
if (deltaTest.getPValue(tetrad) > alpha) {
EPure = false;
if (indTest.isDependent(v1, v4, empty)) {
CPure1 = false;
}
if (indTest.isDependent(v2, v4, empty)) {
CPure2 = false;
}
}
tetrad = new Tetrad(v1, v3, v2, v4);
if (deltaTest.getPValue(tetrad) > alpha) {
EPure = false;
if (indTest.isDependent(v3, v4, empty)) {
CPure3 = false;
}
}
if (!(EPure || CPure1 || CPure2 || CPure3)) {
continue CHOICE;
}
}
HashSet<Integer> _cluster = new HashSet<Integer>(triple);
if (verbose) {
log("++" + variablesForIndices(new ArrayList<Integer>(triple)), false);
}
if (EPure) {
ESeeds.add(_cluster);
}
if (!EPure) {
if (CPure1) {
Set<Integer> _cluster1 = new HashSet<Integer>(n2, n3);
_cluster1.addAll(CSeeds.get(n1));
CSeeds.set(n1, _cluster1);
}
if (CPure2) {
Set<Integer> _cluster2 = new HashSet<Integer>(n1, n3);
_cluster2.addAll(CSeeds.get(n2));
CSeeds.set(n2, _cluster2);
}
if (CPure3) {
Set<Integer> _cluster3 = new HashSet<Integer>(n1, n2);
_cluster3.addAll(CSeeds.get(n3));
CSeeds.set(n3, _cluster3);
}
}
}
return null;
}