}

  public void testCheckNonNegative_positiveDouble() {
    MathPreconditions.checkNonNegative("double", 1d);
  }

  public void testCheckNonNegative_negativeDouble() {
    assertThrows(
        IllegalArgumentException.class, () -> MathPreconditions.checkNonNegative("double", -1d));
  }

  public void testCheckNonNegative_nanDouble() {
    assertThrows(
        IllegalArgumentException.class,

  }

  public void testCheckNonNegative_positiveDouble() {
    MathPreconditions.checkNonNegative("double", 1d);
  }

  public void testCheckNonNegative_negativeDouble() {
    assertThrows(
        IllegalArgumentException.class, () -> MathPreconditions.checkNonNegative("double", -1d));
  }

  public void testCheckNonNegative_nanDouble() {
    assertThrows(
        IllegalArgumentException.class,

					<select id="as_timestamp" name="as.timestamp" class="form-control">
						<option value=""><la:message key="labels.advance_search_timestamp_default" /></option>
						<option value="[now-1d/d TO *]"
							<c:if test="${as.timestamp.contains('[now-1d/d TO *]')}">selected</c:if>
						><la:message key="labels.advance_search_timestamp_pastday" /></option>
						<option value="[now-1w/d TO *]"

    setDefault(Integer.class, 1);
    setDefault(long.class, 1L);
    setDefault(Long.class, 1L);
    setDefault(float.class, 1F);
    setDefault(Float.class, 1F);
    setDefault(double.class, 1D);
    setDefault(Double.class, 1D);
    setDefault(Class.class, Class.class);
  }

  /**
   * Sets the default value for {@code type}. The default value isn't used in testing {@link

    String QUERY_FACET_FIELDS_MISSING = "query.facet.fields.missing";

    /** The key of the configuration. e.g. labels.facet_timestamp_title:labels.facet_timestamp_1day=timestamp:[now/d-1d TO *]	labels.facet_timestamp_1week=timestamp:[now/d-7d TO *]	labels.facet_timestamp_1month=timestamp:[now/d-1M TO *]	labels.facet_timestamp_1year=timestamp:[now/d-1y TO *]<br>

        the batch.
    *   Support indicator column in boosted trees.
    *   Prevent `tf.gradients()` from backpropagating through integer tensors.
    *   LinearOperator[1D,2D,3D]Circulant added to `tensorflow.linalg`.
    *   Conv3D, Conv3DBackpropInput, Conv3DBackpropFilter now supports
        arbitrary.
    *   Added `tf.train.Checkpoint` for reading/writing object-based