@Before public void setUpNetwork() { input1 = new BernoulliVertex(0.25); input2 = new BernoulliVertex(0.75); output = input1.or(input2); connectedGraph = output.getConnectedGraph(); network = new BayesianNetwork(connectedGraph); }
@Test public void youCanLabelVertices() { BooleanVertex a = new BernoulliVertex(0.5); BooleanVertex b = new BernoulliVertex(0.5); BooleanVertex ored = a.or(b); BooleanVertex unlabelled = ored.or(a); Vertex retrieved; VertexLabel labelA = new VertexLabel(LABEL_A); VertexLabel labelB = new VertexLabel(LABEL_B); VertexLabel labelOr = new VertexLabel(LABEL_ORED); a.setLabel(labelA); b.setLabel(labelB); ored.setLabel(labelOr); BayesianNetwork net = new BayesianNetwork(a.getConnectedGraph()); retrieved = net.getVertexByLabel(labelA); assertThat(retrieved, is(a)); retrieved = net.getVertexByLabel(labelB); assertThat(retrieved, is(b)); retrieved = net.getVertexByLabel(labelOr); assertThat(retrieved, is(ored)); retrieved = net.getVertexByLabel(null); assertThat(retrieved, nullValue()); }
@Test(expected = IllegalArgumentException.class) public void labelErrorsDetected() { BooleanVertex a = new BernoulliVertex(0.5); BooleanVertex b = new BernoulliVertex(0.5); BooleanVertex ored = a.or(b); a.setLabel(LABEL_A); b.setLabel(LABEL_A); BayesianNetwork net = new BayesianNetwork(a.getConnectedGraph()); }
B.observe(true); KeanuProbabilisticModel model = new KeanuProbabilisticModel(C.getConnectedGraph()); NetworkSamples posteriorSamples = Keanu.Sampling.MetropolisHastings.withDefaultConfigFor(model).getPosteriorSamples( model, BayesianNetwork bayesianNetwork = new BayesianNetwork(C.getConnectedGraph()); bayesianNetwork.probeForNonZeroProbability(10);
KeanuProbabilisticModel model = new KeanuProbabilisticModel(wetGrass.getConnectedGraph()); NetworkSamples posteriorSamples = Keanu.Sampling.MetropolisHastings.withDefaultConfigFor(model).getPosteriorSamples( model,