@Test public void testCreationWihtSimpleDescriptor() throws Exception { InputStream generatorDescriptorIn = getClass() .getResourceAsStream("/opennlp/tools/util/featuregen/TestFeatureGeneratorConfig.xml"); // If this fails the generator descriptor could not be found // at the expected location Assert.assertNotNull(generatorDescriptorIn); Collection<String> expectedGenerators = new ArrayList<String>(); expectedGenerators.add(OutcomePriorFeatureGenerator.class.getName()); AggregatedFeatureGenerator aggregatedGenerator = (AggregatedFeatureGenerator) GeneratorFactory.create(generatorDescriptorIn, null); for (AdaptiveFeatureGenerator generator : aggregatedGenerator.getGenerators()) { expectedGenerators.remove(generator.getClass().getName()); // if of kind which requires parameters check that } // If this fails not all expected generators were found and // removed from the expected generators collection Assert.assertEquals(0, expectedGenerators.size()); }
/** * Calls the {@link AdaptiveFeatureGenerator#createFeatures(List, String[], int, String[])} method * on all aggregated {@link AdaptiveFeatureGenerator}s. */ public void createFeatures( List<String> features, String[] tokens, int index, String[] previousOutcomes) { for (AdaptiveFeatureGenerator generator : generators) { generator.createFeatures(features, tokens, index, previousOutcomes); } }
@Test public void testCreationWithCustomGenerator() throws Exception { InputStream generatorDescriptorIn = getClass().getResourceAsStream("/opennlp/tools/util/featuregen/CustomClassLoading.xml"); // If this fails the generator descriptor could not be found // at the expected location Assert.assertNotNull(generatorDescriptorIn); AggregatedFeatureGenerator aggregatedGenerator = (AggregatedFeatureGenerator) GeneratorFactory.create(generatorDescriptorIn, null); Collection<AdaptiveFeatureGenerator> embeddedGenerator = aggregatedGenerator.getGenerators(); Assert.assertEquals(1, embeddedGenerator.size()); for (AdaptiveFeatureGenerator generator : embeddedGenerator) { Assert.assertEquals(TokenFeatureGenerator.class.getName(), generator.getClass().getName()); } }
/** * Calls the {@link AdaptiveFeatureGenerator#updateAdaptiveData(String[], String[])} method on all * aggregated {@link AdaptiveFeatureGenerator}s. */ public void updateAdaptiveData(String[] tokens, String[] outcomes) { for (AdaptiveFeatureGenerator generator : generators) { generator.updateAdaptiveData(tokens, outcomes); } }
/** * Calls the {@link AdaptiveFeatureGenerator#clearAdaptiveData()} method on all aggregated {@link * AdaptiveFeatureGenerator}s. */ public void clearAdaptiveData() { for (AdaptiveFeatureGenerator generator : generators) { generator.clearAdaptiveData(); } }