WeightedRVFDatasetTest.java example

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CoreNLP-master
package edu.stanford.nlp.classify;

import edu.stanford.nlp.ling.RVFDatum;
import edu.stanford.nlp.stats.Counters;
import junit.framework.TestCase;

import java.util.Arrays;

/**
 * TODO(gabor) JavaDoc
 *
 * @author Gabor Angeli
 */
public class WeightedRVFDatasetTest extends TestCase {

  public void testWeightingWorks() {
    WeightedRVFDataset<String, String> dataset = new WeightedRVFDataset<>();
    RVFDatum<String, String> datum1 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum1, 42.0f);
    RVFDatum<String, String> datum2 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum2, 7.3f);
    assertEquals(42.0f, dataset.getWeights()[0], 1e-10);
    assertEquals(7.3f, dataset.getWeights()[1], 1e-10);
  }

  public void testBackwardsCompatibility() {
    RVFDataset<String, String> dataset = new WeightedRVFDataset<>();
    RVFDatum<String, String> datum1 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum1);
    RVFDatum<String, String> datum2 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum2);
    assertEquals(1.0f, ((WeightedRVFDataset<String, String>) dataset).getWeights()[0], 1e-10);
    assertEquals(1.0f, ((WeightedRVFDataset<String, String>) dataset).getWeights()[1], 1e-10);
  }


  public void testMixedCompatibility() {
    WeightedRVFDataset<String, String> dataset = new WeightedRVFDataset<>();
    RVFDatum<String, String> datum1 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum1, 42.0f);
    RVFDatum<String, String> datum2 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum2);
    RVFDatum<String, String> datum3 = newRVFDatum(null, "a", "b", "a");
    dataset.add(datum3, 7.3f);
    assertEquals(42.0f, dataset.getWeights()[0], 1e-10);
    assertEquals(1.0f, dataset.getWeights()[1], 1e-10);
    assertEquals(7.3f, dataset.getWeights()[2], 1e-10);
  }


  private static <L, F> RVFDatum<L, F> newRVFDatum(L label, F ... items) {
    return new RVFDatum<>(Counters.asCounter(Arrays.asList(items)), label);
  }
}