inference tests #23

src/test/java/ch/idsia/credici/model/InferenceTest.java

@@ -0,0 +1,107 @@
+package ch.idsia.credici.model;
+
+import ch.idsia.credici.IO;
+import ch.idsia.credici.inference.CausalVE;
+import ch.idsia.credici.inference.CredalCausalApproxLP;
+import ch.idsia.credici.inference.CredalCausalVE;
+import ch.idsia.credici.model.predefined.RandomChainNonMarkovian;
+import ch.idsia.crema.factor.bayesian.BayesianFactor;
+import ch.idsia.crema.factor.credal.linear.IntervalFactor;
+import ch.idsia.crema.factor.credal.vertex.VertexFactor;
+import ch.idsia.crema.utility.RandomUtil;
+import jdk.jshell.spi.ExecutionControl;
+import org.junit.Assert;
+import org.junit.Test;
+
+import java.io.IOException;
+import java.nio.file.Path;
+
+public class InferenceTest {
+
+
+	@Test
+	public void CredalCausalVE() throws InterruptedException, ExecutionControl.NotImplementedException {
+
+		RandomUtil.setRandomSeed(1);
+		StructuralCausalModel m = RandomChainNonMarkovian.buildModel(4, 2, 6);
+
+		int x = 1;
+		int y = 3;
+
+		double[] expected, actual;
+
+		CredalCausalVE inf = new CredalCausalVE(m, m.getEmpiricalProbs());
+
+		expected = new double[]{0.97, 0.03};
+		actual = ((VertexFactor)inf.causalQuery().setTarget(y).setIntervention(x, 0).run()).getData()[0][0];
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+		expected = new double[]{0.010309278350515464};
+		actual = inf.probNecessity(x,y).getData()[0][0];
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+		expected = new double[]{0.25};
+		actual = inf.probSufficiency(x,y).getData()[0][0];
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+		expected = new double[]{0.01};
+		actual = inf.probNecessityAndSufficiency(x,y).getData()[0][0];
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+	}
+	public void CredalCausalApproxLP() throws InterruptedException {
+		RandomUtil.setRandomSeed(1);
+		StructuralCausalModel m = RandomChainNonMarkovian.buildModel(4, 2, 6);
+
+		int x = 1;
+		int y = 3;
+
+		double[] expected, actual;
+
+		CredalCausalApproxLP inf = new CredalCausalApproxLP(m, m.getEmpiricalProbs());
+
+		expected = new double[]{0.97, 0.03};
+		actual = ((IntervalFactor)inf.causalQuery().setTarget(y).setIntervention(x, 0).run()).getDataUpper()[0];
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+
+	}
+
+	public void CausalVE() throws ExecutionControl.NotImplementedException, InterruptedException {
+
+		RandomUtil.setRandomSeed(1);
+		StructuralCausalModel m = RandomChainNonMarkovian.buildModel(4, 2, 6);
+
+		int x = 1;
+		int y = 3;
+
+		double[] expected, actual;
+
+		CausalVE inf = new CausalVE(m);
+
+		expected = new double[]{0.9700000000000001, 0.03 };
+		actual = ((BayesianFactor)inf.causalQuery().setTarget(y).setIntervention(x, 0).run()).getData();
+		Assert.assertArrayEquals(expected,actual,0.000001);
+/*
+
+	expected = new double[]{0.010309278350515464};
+	actual = inf.probNecessity(x,y).getData()[0][0];
+	Assert.assertArrayEquals(expected,actual,0.000001);
+
+
+	expected = new double[]{0.25};
+	actual = inf.probSufficiency(x,y).getData()[0][0];
+	Assert.assertArrayEquals(expected,actual,0.000001);
+*/
+
+		expected = new double[]{0.01};
+		actual = inf.probNecessityAndSufficiency(x,y).getData();
+		Assert.assertArrayEquals(expected,actual,0.000001);
+
+	}
+}