Package org.drools.beliefs.bayes

Examples of org.drools.beliefs.bayes.BayesInstance

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        InternalKnowledgePackage kpkg = (InternalKnowledgePackage) runtime.getKieBase().getKiePackage( cls.getPackage().getName() );
        Map<ResourceType, ResourceTypePackage> map = kpkg.getResourceTypePackages();
        BayesPackage bayesPkg  = (BayesPackage) map.get( ResourceType.BAYES );
        JunctionTree jtree =  bayesPkg.getJunctionTree(cls.getSimpleName());

        BayesInstance instance = new BayesInstance( jtree, cls );
//        instances.put( cls.getName() , instance );

        return instance;
    }
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    public void testNoEvidence() {
        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        JunctionTree jTree = jtBuilder.build();

        JunctionTreeClique jtNode = jTree.getRoot();
        BayesInstance bayesInstance = new BayesInstance(jTree);
        bayesInstance.globalUpdate();

        assertArray(new double[]{0.5, 0.5}, scaleDouble(3, bayesInstance.marginalize("Cloudy").getDistribution()));

        assertArray( new double[]{0.5, 0.5},  scaleDouble( 3,  bayesInstance.marginalize("Rain").getDistribution()  ) );

        assertArray( new double[]{0.7, 0.3},  scaleDouble(3, bayesInstance.marginalize("Sprinkler").getDistribution()) );

        assertArray( new double[]{0.353, 0.647},  scaleDouble( 3,  bayesInstance.marginalize("WetGrass").getDistribution() ) );
    }
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    public void testGrassWetEvidence() {
        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        JunctionTree jTree = jtBuilder.build();

        JunctionTreeClique jtNode = jTree.getRoot();
        BayesInstance bayesInstance = new BayesInstance(jTree);

        bayesInstance.setLikelyhood( "WetGrass", new double[]{1.0, 0.0} );

        bayesInstance.globalUpdate();

        assertArray(new double[]{0.639, 0.361}, scaleDouble(3, bayesInstance.marginalize("Cloudy").getDistribution()));

        assertArray( new double[]{0.881, 0.119},  scaleDouble( 3,  bayesInstance.marginalize("Rain").getDistribution()  ) );

        assertArray( new double[]{0.938, 0.062},  scaleDouble(3, bayesInstance.marginalize("Sprinkler").getDistribution()) );

        assertArray( new double[]{1.0, 0.0},  scaleDouble( 3,  bayesInstance.marginalize("WetGrass").getDistribution() ) );
    }
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    public void testSprinklerEvidence() {
        JunctionTreeBuilder jtBuilder = new JunctionTreeBuilder( graph );
        JunctionTree jTree = jtBuilder.build();

        JunctionTreeClique jtNode = jTree.getRoot();
        BayesInstance bayesInstance = new BayesInstance(jTree);

        bayesInstance.setLikelyhood( "Sprinkler", new double[]{1.0, 0.0} );
        bayesInstance.setLikelyhood( "Cloudy", new double[]{1.0, 0.0} );

        bayesInstance.globalUpdate();

        assertArray(new double[]{1.0, 0.0}, scaleDouble(3, bayesInstance.marginalize("Cloudy").getDistribution()));

        assertArray( new double[]{0.8, 0.2},  scaleDouble( 3,  bayesInstance.marginalize("Rain").getDistribution()  ) );

        assertArray( new double[]{1.0, 0.0},  scaleDouble(3, bayesInstance.marginalize("Sprinkler").getDistribution()) );

        assertArray( new double[]{0.82, 0.18},  scaleDouble( 3,  bayesInstance.marginalize("WetGrass").getDistribution() ) );
    }
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        jtNode1 = jTree.getRoot();
        jtNode2 = jtNode1.getChildren().get(0).getChild();
        jtNode3 = jtNode1.getChildren().get(1).getChild();

        bayesInstance = new BayesInstance(jTree);

        burglaryState = bayesInstance.getVarStates()[burglary.getId()];
        earthquakeState = bayesInstance.getVarStates()[earthquake.getId()];
        alarmState = bayesInstance.getVarStates()[alarm.getId()];
        johnCallsState = bayesInstance.getVarStates()[johnCalls.getId()];
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        assertArray( new double[]{0.002516, 0.997484},   scaleDouble(6, bayesInstance.marginalize("Alarm").getDistribution()) );
    }

    @Test
    public void testAlarmEvidence() {
        BayesInstance bayesInstance = new BayesInstance(jTree);

        bayesInstance.setLikelyhood( "Alarm", new double[]{1.0, 0.0} );

        bayesInstance.globalUpdate();

        assertArray( new double[]{0.9, 0.1}, scaleDouble(3, bayesInstance.marginalize("JohnCalls").getDistribution()) );

        assertArray( new double[]{0.7, 0.3 }, scaleDouble( 3, bayesInstance.marginalize("MaryCalls").getDistribution() ) );

        assertArray( new double[]{0.374, 0.626}, scaleDouble(3, bayesInstance.marginalize("Burglary").getDistribution()) );

        assertArray( new double[]{ 0.231, 0.769}, scaleDouble( 3, bayesInstance.marginalize("Earthquake").getDistribution() ) );

        assertArray( new double[]{1.0, 0.0}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) ); }
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        assertArray( new double[]{1.0, 0.0}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) ); }

    @Test
    public void testEathQuakeEvidence() {
        BayesInstance bayesInstance = new BayesInstance(jTree);

        bayesInstance.setLikelyhood("Earthquake", new double[]{1.0, 0.0});
        bayesInstance.globalUpdate();

        assertArray( new double[]{0.297, 0.703}, scaleDouble(3, bayesInstance.marginalize("JohnCalls").getDistribution()) );

        assertArray( new double[]{0.211, 0.789 }, scaleDouble( 3, bayesInstance.marginalize("MaryCalls").getDistribution() ) );

        assertArray( new double[]{.001, 0.999}, scaleDouble(3, bayesInstance.marginalize("Burglary").getDistribution()) );

        assertArray( new double[]{1.0, 0.0}, scaleDouble( 3, bayesInstance.marginalize("Earthquake").getDistribution() ) );

        assertArray( new double[]{0.291, 0.709}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) );
    }
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        assertArray( new double[]{0.291, 0.709}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) );
    }

    @Test
    public void testJoinCallsEvidence() {
        BayesInstance bayesInstance = new BayesInstance(jTree);

        bayesInstance.setLikelyhood("JohnCalls", new double[]{1.0, 0.0});
        bayesInstance.globalUpdate();

        assertArray( new double[]{1.0, 0.0}, scaleDouble(3, bayesInstance.marginalize("JohnCalls").getDistribution()) );

        assertArray( new double[]{0.04, 0.96 }, scaleDouble( 3, bayesInstance.marginalize("MaryCalls").getDistribution() ) );

        assertArray( new double[]{0.016, 0.984}, scaleDouble(3, bayesInstance.marginalize("Burglary").getDistribution()) );

        assertArray( new double[]{0.011, 0.989}, scaleDouble( 3, bayesInstance.marginalize("Earthquake").getDistribution() ) );

        assertArray( new double[]{0.043, 0.957}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) );
    }
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        assertArray( new double[]{0.043, 0.957}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) );
    }

    @Test
    public void testEarthquakeAndJohnCallsEvidence() {
        BayesInstance bayesInstance = new BayesInstance(jTree);
        bayesInstance.setLikelyhood("JohnCalls", new double[]{1.0, 0.0});
        bayesInstance.setLikelyhood("Earthquake", new double[]{1.0, 0.0});

        bayesInstance.globalUpdate();

        assertArray( new double[]{1.0, 0.0}, scaleDouble(3, bayesInstance.marginalize("JohnCalls").getDistribution()) );

        assertArray( new double[]{0.618, 0.382 }, scaleDouble( 3, bayesInstance.marginalize("MaryCalls").getDistribution() ) );

        assertArray( new double[]{0.003, 0.997}, scaleDouble(3, bayesInstance.marginalize("Burglary").getDistribution()) );

        assertArray( new double[]{ 1.0, 0.0}, scaleDouble( 3, bayesInstance.marginalize("Earthquake").getDistribution() ) );

        assertArray( new double[]{0.881, 0.119}, scaleDouble(3, bayesInstance.marginalize("Alarm").getDistribution()) );
    }
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Related Classes of org.drools.beliefs.bayes.BayesInstance

  • org.drools.beliefs.bayes.example.EarthQuakeTest
  • org.drools.beliefs.bayes.example.SprinkerTest
  • org.drools.beliefs.bayes.runtime.BayesRuntimeImpl
  • org.drools.beliefs.graph.GraphNode
  • java.util.Random
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