@Test
public void shouldPrefixEveryElementInIteratorAndNothingMore() {
Iterator<Integer> incrementing = generatorFactory.boundedIncrementing(0, 2, 10);
Iterator<String> prefixing = generatorFactory.prefix(incrementing, "pre");
assertThat(prefixing.next(), is("pre0"));
assertThat(prefixing.next(), is("pre2"));
assertThat(prefixing.next(), is("pre4"));
assertThat(prefixing.next(), is("pre6"));
assertThat(prefixing.next(), is("pre8"));
assertThat(prefixing.next(), is("pre10"));
assertThat(prefixing.hasNext(), is(false));
assertThat(incrementing.hasNext(), is(false));
}
@Override
public Iterator<List<String>> getGeneratorImpl(GeneratorFactory generatorFactory) {
Tuple2<Double, String> p1 = Tuple.tuple2(1.0, "1");
Tuple2<Double, String> p2 = Tuple.tuple2(1.0, "2");
Tuple2<Double, String> p3 = Tuple.tuple2(1.0, "3");
ArrayList<Tuple2<Double, String>> items = new ArrayList<Tuple2<Double, String>>();
items.add(p1);
items.add(p2);
items.add(p3);
Iterator<Integer> amountToRetrieveGenerator = generatorFactory.uniform(0, 3);
Iterator<List<String>> generator =
generatorFactory.weightedDiscreteList(items, amountToRetrieveGenerator);
return generator;
}
@Test(expected = GeneratorException.class)
public void emptyConstructorTest() {
// Given
GeneratorFactory generatorFactory = new GeneratorFactory(new RandomDataGeneratorFactory());
Iterator<Integer> amountToRetrieveGenerator = generatorFactory.uniform(0, 3);
ArrayList<Tuple2<Double, String>> emptyItems = new ArrayList<Tuple2<Double, String>>();
Iterator<List<String>> generator =
generatorFactory.weightedDiscreteList(emptyItems, amountToRetrieveGenerator);
// When
generator.next();
// Then
assertEquals("Empty DiscreteGenerator should throw exception on next()", false, true);
}
@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());
}
/**
* Tests the creation from a descriptor which contains an unkown element. The creation should fail
* with an {@link InvalidFormatException}
*/
@Test(expected = IOException.class)
public void testCreationWithUnkownElement() throws IOException {
InputStream descIn =
getClass()
.getResourceAsStream(
"/opennlp/tools/util/featuregen/FeatureGeneratorConfigWithUnkownElement.xml");
try {
GeneratorFactory.create(descIn, null);
} finally {
descIn.close();
}
}
public class ExampleTest {
@Rule
public Generator<Tuple2<Integer, String>> tuples =
GeneratorFactory.tuples(asList(1, 2, 3, 4), asList("a", "b", "c"));
@Test
public void testSomething() throws Exception {
assertTrue(tuples.value()._1 % 2 == 0 || tuples.value()._2.length() > 2);
}
@Test
public void throwingUp() {
throw new RuntimeException();
}
}
@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());
}
}
