public void test1() {
for (int r = 0; r < 1; r++) {
Graph mim = DataGraphUtils.randomSingleFactorModel(5, 5, 6, 0, 0, 0);
Graph mimStructure = structure(mim);
SemImInitializationParams params = new SemImInitializationParams();
params.setCoefRange(.5, 1.5);
SemPm pm = new SemPm(mim);
SemIm im = new SemIm(pm, params);
DataSet data = im.simulateData(300, false);
String algorithm = "FOFC";
Graph searchGraph;
List<List<Node>> partition;
if (algorithm.equals("FOFC")) {
FindOneFactorClusters fofc =
new FindOneFactorClusters(data, TestType.TETRAD_WISHART, 0.001);
searchGraph = fofc.search();
partition = fofc.getClusters();
} else if (algorithm.equals("BPC")) {
TestType testType = TestType.TETRAD_WISHART;
TestType purifyType = TestType.TETRAD_BASED2;
BuildPureClusters bpc = new BuildPureClusters(data, 0.001, testType, purifyType);
searchGraph = bpc.search();
partition = MimUtils.convertToClusters2(searchGraph);
} else {
throw new IllegalStateException();
}
List<String> latentVarList = reidentifyVariables(mim, data, partition, 2);
System.out.println(partition);
System.out.println(latentVarList);
System.out.println("True\n" + mimStructure);
Graph mimbuildStructure;
for (int mimbuildMethod : new int[] {3, 4}) {
if (mimbuildMethod == 1) {
System.out.println("Mimbuild 1\n");
Clusters measurements = ClusterUtils.mimClusters(searchGraph);
IndTestMimBuild test = new IndTestMimBuild(data, 0.001, measurements);
MimBuild mimbuild = new MimBuild(test, new Knowledge2());
Graph full = mimbuild.search();
full = changeLatentNames(full, measurements, latentVarList);
mimbuildStructure = structure(full);
System.out.println(
"SHD = "
+ SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure));
System.out.println("Estimated\n" + mimbuildStructure);
System.out.println();
}
// else if (mimbuildMethod == 2) {
// System.out.println("Mimbuild 2\n");
// Mimbuild2 mimbuild = new Mimbuild2();
// mimbuild.setAlpha(0.001);
// mimbuildStructure = mimbuild.search(partition, latentVarList, data);
// TetradMatrix latentcov = mimbuild.getLatentsCov();
// List<String> latentnames = mimbuild.getLatentNames();
// System.out.println("\nCovariance over the latents");
// System.out.println(MatrixUtils.toStringSquare(latentcov.toArray(),
// latentnames));
// System.out.println("Estimated\n" + mimbuildStructure);
// System.out.println("SHD = " +
// SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure));
// System.out.println();
// }
else if (mimbuildMethod == 3) {
System.out.println("Mimbuild 3\n");
Mimbuild2 mimbuild = new Mimbuild2();
mimbuild.setAlpha(0.001);
mimbuild.setMinClusterSize(3);
mimbuildStructure = mimbuild.search(partition, latentVarList, new CovarianceMatrix(data));
ICovarianceMatrix latentcov = mimbuild.getLatentsCov();
System.out.println("\nCovariance over the latents");
System.out.println(latentcov);
System.out.println("Estimated\n" + mimbuildStructure);
System.out.println(
"SHD = "
+ SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure));
System.out.println();
} else if (mimbuildMethod == 4) {
System.out.println("Mimbuild Trek\n");
MimbuildTrek mimbuild = new MimbuildTrek();
mimbuild.setAlpha(0.1);
mimbuild.setMinClusterSize(3);
mimbuildStructure = mimbuild.search(partition, latentVarList, new CovarianceMatrix(data));
ICovarianceMatrix latentcov = mimbuild.getLatentsCov();
System.out.println("\nCovariance over the latents");
System.out.println(latentcov);
System.out.println("Estimated\n" + mimbuildStructure);
System.out.println(
"SHD = "
+ SearchGraphUtils.structuralHammingDistance(mimStructure, mimbuildStructure));
System.out.println();
} else {
throw new IllegalStateException();
}
}
}
}
public void rtest3() {
Node x = new GraphNode("X");
Node y = new GraphNode("Y");
Node z = new GraphNode("Z");
Node w = new GraphNode("W");
List<Node> nodes = new ArrayList<Node>();
nodes.add(x);
nodes.add(y);
nodes.add(z);
nodes.add(w);
Graph g = new EdgeListGraph(nodes);
g.addDirectedEdge(x, y);
g.addDirectedEdge(x, z);
g.addDirectedEdge(y, w);
g.addDirectedEdge(z, w);
Graph maxGraph = null;
double maxPValue = -1.0;
ICovarianceMatrix maxLatentCov = null;
Graph mim = DataGraphUtils.randomMim(g, 8, 0, 0, 0, true);
// Graph mim = DataGraphUtils.randomSingleFactorModel(5, 5, 8, 0, 0, 0);
Graph mimStructure = structure(mim);
SemPm pm = new SemPm(mim);
System.out.println("\n\nTrue graph:");
System.out.println(mimStructure);
SemImInitializationParams params = new SemImInitializationParams();
params.setCoefRange(0.5, 1.5);
SemIm im = new SemIm(pm, params);
int N = 1000;
DataSet data = im.simulateData(N, false);
CovarianceMatrix cov = new CovarianceMatrix(data);
for (int i = 0; i < 1; i++) {
ICovarianceMatrix _cov = DataUtils.reorderColumns(cov);
List<List<Node>> partition;
FindOneFactorClusters fofc = new FindOneFactorClusters(_cov, TestType.TETRAD_WISHART, .001);
fofc.search();
partition = fofc.getClusters();
System.out.println(partition);
List<String> latentVarList = reidentifyVariables(mim, data, partition, 2);
Mimbuild2 mimbuild = new Mimbuild2();
mimbuild.setAlpha(0.001);
// mimbuild.setMinimumSize(5);
// To test knowledge.
// Knowledge knowledge = new Knowledge2();
// knowledge.setEdgeForbidden("L.Y", "L.W", true);
// knowledge.setEdgeRequired("L.Y", "L.Z", true);
// mimbuild.setKnowledge(knowledge);
Graph mimbuildStructure = mimbuild.search(partition, latentVarList, _cov);
double pValue = mimbuild.getpValue();
System.out.println(mimbuildStructure);
System.out.println("P = " + pValue);
System.out.println("Latent Cov = " + mimbuild.getLatentsCov());
if (pValue > maxPValue) {
maxPValue = pValue;
maxGraph = new EdgeListGraph(mimbuildStructure);
maxLatentCov = mimbuild.getLatentsCov();
}
}
System.out.println("\n\nTrue graph:");
System.out.println(mimStructure);
System.out.println("\nBest graph:");
System.out.println(maxGraph);
System.out.println("P = " + maxPValue);
System.out.println("Latent Cov = " + maxLatentCov);
System.out.println();
}