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Introduce test and plot data collection for Gaussian CPDAG case for local Markov Blanket using Local Graph Confusion statistics #1778

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May 24, 2024
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Introduce test and plot data collection for Gaussian CPDAG case for local Markov Blanket using Local Graph Confusion statistics #1778

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30 changes: 30 additions & 0 deletions tetrad-lib/src/test/java/edu/cmu/tetrad/test/TestCheckMarkov.java
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Original file line number Diff line number Diff line change
Expand Up @@ -470,4 +470,34 @@ public void testGaussianDAGPrecisionRecallForLocalOnMarkovBlanket2() {
System.out.println("Rejects size: " + rejects.size());
}

@Test
public void testGaussianCPDAGPrecisionRecallForLocalOnMarkovBlanket2() {
Graph trueGraph = RandomGraph.randomDag(10, 0, 10, 100, 100, 100, false);
// The completed partially directed acyclic graph (CPDAG) for the given DAG.
Graph trueGraphCPDAG = GraphTransforms.dagToCpdag(trueGraph);
System.out.println("Test True Graph: " + trueGraph);
System.out.println("Test True Graph CPDAG: " + trueGraphCPDAG);

SemPm pm = new SemPm(trueGraph);
// Parameters without additional setting default tobe Gaussian
SemIm im = new SemIm(pm, new Parameters());
DataSet data = im.simulateData(1000, false);
edu.cmu.tetrad.search.score.SemBicScore score = new SemBicScore(data, false);
score.setPenaltyDiscount(2);
Graph estimatedCpdag = new PermutationSearch(new Boss(score)).search();
System.out.println("Test Estimated CPDAG Graph: " + estimatedCpdag);
System.out.println("~~~~~~~~~~~~~~~~~~~~~~~~~~~~");

IndependenceTest fisherZTest = new IndTestFisherZ(data, 0.05);
MarkovCheck markovCheck = new MarkovCheck(estimatedCpdag, fisherZTest, ConditioningSetType.MARKOV_BLANKET);
// ADTest pass/fail threshold default to be 0.05. shuffleThreshold default to be 0.5
// List<List<Node>> accepts_rejects = markovCheck.getAndersonDarlingTestAcceptsRejectsNodesForAllNodes2(fisherZTest, estimatedCpdag, 0.05, 0.5);
List<List<Node>> accepts_rejects = markovCheck.getAndersonDarlingTestAcceptsRejectsNodesForAllNodesPlotData2(fisherZTest, estimatedCpdag, trueGraph, 0.05, 0.3);

List<Node> accepts = accepts_rejects.get(0);
List<Node> rejects = accepts_rejects.get(1);
System.out.println("Accepts size: " + accepts.size());
System.out.println("Rejects size: " + rejects.size());
}

}