Examples with Sentiment com.amplifyframework.predictions.models.Sentiment used on opensource projects

Example 6 with Sentiment

use of com.amplifyframework.predictions.models.Sentiment in project amplify-android by aws-amplify.

the class TextClassificationTest method testFetchSentiment.

/**
 * Test that fetchSentiment() can do the following.
 *
 *  - Choose the output with highest score,
 *  - obtain the column index,
 *  - obtain the label located at that index,
 *  - convert the label into {@link SentimentType}, and
 *  - return appropriate {@link Sentiment}
 *
 * @throws Exception if sentiment fetch fails
 */
@Test
// Double comparison delta epsilon
@SuppressWarnings("MagicNumber")
public void testFetchSentiment() throws Exception {
    // List of labels to expect
    final List<String> labels = Arrays.asList("negative", "positive", "unknown1", "unknown2");
    // Mock random confidence score
    final float confidenceScore = new Random().nextFloat();
    // Make mock interpreter set confidence score for
    // "positive" label into pre-determined random value
    doAnswer(invocation -> {
        float[][] output = invocation.getArgument(1, float[][].class);
        output[0][labels.indexOf("positive")] = confidenceScore;
        return null;
    }).when(mockInterpreter).run(any(), any(float[][].class));
    // Make mock dictionary return any valid input format
    when(mockDictionary.tokenizeInputText(anyString())).thenReturn(new float[0][]);
    // Make mock labels emulate an actual list of labels
    when(mockLabels.size()).thenReturn(labels.size());
    when(mockLabels.get(anyInt())).thenAnswer(invocation -> labels.get(invocation.getArgument(0)));
    // Assert that detected sentiment is positive
    Sentiment sentiment = service.fetchSentiment(RandomString.string());
    assertEquals(SentimentType.POSITIVE, sentiment.getValue());
    assertEquals(confidenceScore * 100, sentiment.getConfidence(), 1E-5);
}