Examples with FeatureDomain org.kie.kogito.explainability.model.domain.FeatureDomain used on opensource projects

Example 6 with FeatureDomain

use of org.kie.kogito.explainability.model.domain.FeatureDomain in project kogito-apps by kiegroup.

the class CounterfactualEntityFactoryTest method testDoubleFactory.

@Test
void testDoubleFactory() {
    final double value = 5.5;
    final FeatureDomain domain = NumericalFeatureDomain.create(0.0, 10.0);
    final Feature feature = FeatureFactory.newNumericalFeature("double-feature", value, domain);
    final CounterfactualEntity counterfactualEntity = CounterfactualEntityFactory.from(feature);
    assertTrue(counterfactualEntity instanceof DoubleEntity);
    assertEquals(value, counterfactualEntity.asFeature().getValue().asNumber());
}

Example 7 with FeatureDomain

use of org.kie.kogito.explainability.model.domain.FeatureDomain in project kogito-apps by kiegroup.

the class CounterfactualScoreCalculatorTest method testNullIntegerInput.

/**
 * Null values for input Integer features should not be accepted as valid
 */
@Test
void testNullIntegerInput() throws ExecutionException, InterruptedException {
    List<Feature> features = new ArrayList<>();
    List<FeatureDomain> featureDomains = new ArrayList<>();
    List<Boolean> constraints = new ArrayList<>();
    // f-1
    features.add(FeatureFactory.newNumericalFeature("f-1", 1.0));
    featureDomains.add(NumericalFeatureDomain.create(0.0, 10.0));
    constraints.add(false);
    // f-2
    features.add(FeatureFactory.newNumericalFeature("f-2", null));
    featureDomains.add(NumericalFeatureDomain.create(0, 10));
    constraints.add(false);
    // f-3
    features.add(FeatureFactory.newBooleanFeature("f-3", true));
    featureDomains.add(EmptyFeatureDomain.create());
    constraints.add(false);
    PredictionInput input = new PredictionInput(features);
    PredictionFeatureDomain domains = new PredictionFeatureDomain(featureDomains);
    IllegalArgumentException exception = assertThrows(IllegalArgumentException.class, () -> {
        CounterfactualEntityFactory.createEntities(input);
    });
    assertEquals("Null numeric features are not supported in counterfactuals", exception.getMessage());
}

Example 8 with FeatureDomain

use of org.kie.kogito.explainability.model.domain.FeatureDomain in project kogito-apps by kiegroup.

the class CounterfactualScoreCalculatorTest method testGoalSizeSmaller.

/**
 * Using a smaller number of features in the goals (1) than the model's output (2) should
 * throw an {@link IllegalArgumentException} with the appropriate message.
 */
@Test
void testGoalSizeSmaller() throws ExecutionException, InterruptedException {
    final CounterFactualScoreCalculator scoreCalculator = new CounterFactualScoreCalculator();
    PredictionProvider model = TestUtils.getFeatureSkipModel(0);
    List<Feature> features = new ArrayList<>();
    List<FeatureDomain> featureDomains = new ArrayList<>();
    List<Boolean> constraints = new ArrayList<>();
    // f-1
    features.add(FeatureFactory.newNumericalFeature("f-1", 1.0));
    featureDomains.add(NumericalFeatureDomain.create(0.0, 10.0));
    constraints.add(false);
    // f-2
    features.add(FeatureFactory.newNumericalFeature("f-2", 2.0));
    featureDomains.add(NumericalFeatureDomain.create(0.0, 10.0));
    constraints.add(false);
    // f-3
    features.add(FeatureFactory.newBooleanFeature("f-3", true));
    featureDomains.add(EmptyFeatureDomain.create());
    constraints.add(false);
    PredictionInput input = new PredictionInput(features);
    PredictionFeatureDomain domains = new PredictionFeatureDomain(featureDomains);
    List<CounterfactualEntity> entities = CounterfactualEntityFactory.createEntities(input);
    List<Output> goal = new ArrayList<>();
    goal.add(new Output("f-2", Type.NUMBER, new Value(2.0), 0.0));
    List<PredictionOutput> predictionOutputs = model.predictAsync(List.of(input)).get();
    assertEquals(1, goal.size());
    // A single prediction is expected
    assertEquals(1, predictionOutputs.size());
    // Single prediction with two features
    assertEquals(2, predictionOutputs.get(0).getOutputs().size());
    final CounterfactualSolution solution = new CounterfactualSolution(entities, features, model, goal, UUID.randomUUID(), UUID.randomUUID(), 0.0);
    IllegalArgumentException exception = assertThrows(IllegalArgumentException.class, () -> {
        scoreCalculator.calculateScore(solution);
    });
    assertEquals("Prediction size must be equal to goal size", exception.getMessage());
}

Example 9 with FeatureDomain

use of org.kie.kogito.explainability.model.domain.FeatureDomain in project kogito-apps by kiegroup.

the class ConversionUtilsTest method testToFeatureDomain_UnitFixedNumber.

@Test
void testToFeatureDomain_UnitFixedNumber() {
    FeatureDomain featureDomain = ConversionUtils.toFeatureDomain(new CounterfactualSearchDomainUnitValue("integer", "integer", true, null));
    assertTrue(featureDomain instanceof EmptyFeatureDomain);
}

Example 10 with FeatureDomain

use of org.kie.kogito.explainability.model.domain.FeatureDomain in project kogito-apps by kiegroup.

the class ConversionUtilsTest method testToFeatureDomain_UnitRangeDouble.

@Test
void testToFeatureDomain_UnitRangeDouble() {
    FeatureDomain featureDomain = ConversionUtils.toFeatureDomain(new CounterfactualSearchDomainUnitValue("double", "double", true, new CounterfactualDomainRange(DoubleNode.valueOf(-273.15), DoubleNode.valueOf(Double.MAX_VALUE))));
    assertTrue(featureDomain instanceof NumericalFeatureDomain);
    NumericalFeatureDomain numericalFeatureDomain = (NumericalFeatureDomain) featureDomain;
    assertEquals(-273.15, numericalFeatureDomain.getLowerBound());
    assertEquals(Double.MAX_VALUE, numericalFeatureDomain.getUpperBound());
    assertNull(numericalFeatureDomain.getCategories());
}