* uniform distribution on [0,1]."
 *
 * <h3>Handling of non-finite values</h3>
 *
 * <p>If any values in the input are {@link Double#NaN NaN} then all values returned are {@link
 * Double#NaN NaN}. (This is the one occasion when the behaviour is not the same as you'd get from
 * sorting with {@link java.util.Arrays#sort(double[]) Arrays.sort(double[])} or {@link

     *    value (whether it is NaN or infinity).
     * 2. If the new value is finite and the previous mean is non-finite then the mean is unchanged
     *    (whether it is NaN or infinity).
     * 3. If both the previous mean and the new value are non-finite and...
     * 3a. ...either or both is NaN (so mean != value) then the new mean is NaN.

   * the arithmetic mean of the population.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains {@link Double#NaN} then the result is {@link Double#NaN}. If it
   * contains both {@link Double#POSITIVE_INFINITY} and {@link Double#NEGATIVE_INFINITY} then the
   * result is {@link Double#NaN}. If it contains {@link Double#POSITIVE_INFINITY} and finite values

    }
    return false;
  }

  /**
   * Returns the base 2 logarithm of a double value.
   *
   * <p>Special cases:
   *
   * <ul>
   *   <li>If {@code x} is NaN or less than zero, the result is NaN.
   *   <li>If {@code x} is positive infinity, the result is positive infinity.
   *   <li>If {@code x} is positive or negative zero, the result is negative infinity.
   * </ul>
   *

import static com.google.common.truth.Truth.assertThat;
import static com.google.common.truth.Truth.assertWithMessage;
import static java.lang.Double.NEGATIVE_INFINITY;
import static java.lang.Double.NaN;
import static java.lang.Double.POSITIVE_INFINITY;
import static java.lang.Math.sqrt;
import static java.util.Arrays.stream;
import static org.junit.Assert.assertThrows;

        ("-inf", 200),
        ("nan", 200),
        ("0", 200),
        ("342", 200),
    ],
)
def test_allow_inf_nan_param_default(value: str, code: int):
    response = client.post(f"/?z={value}")
    assert response.status_code == code, response.text


@pytest.mark.parametrize(
    "value,code",
    [
        ("-1", 200),
        ("inf", 422),
        ("-inf", 422),
        ("nan", 422),
        ("0", 200),

    } else {
      // This is a generalized version of the calculation in add(double, double) above. Note that
      // non-finite inputs will have sumOfProductsOfDeltas = NaN, so non-finite values will result
      // in NaN naturally.
      sumOfProductsOfDeltas +=
          values.sumOfProductsOfDeltas()
              + (values.xStats().mean() - xStats.mean())
                  * (values.yStats().mean() - yStats.mean())

          .that(Doubles.indexOf(new double[] {5.0, value, value, 5.0}, new double[] {value, value}))
          .isEqualTo(1);
    }
    assertThat(Doubles.indexOf(new double[] {5.0, NaN, NaN, 5.0}, new double[] {NaN, NaN}))
        .isEqualTo(-1);
  }

  public void testLastIndexOf() {
    assertThat(Doubles.lastIndexOf(EMPTY, 1.0)).isEqualTo(-1);
    assertThat(Doubles.lastIndexOf(ARRAY1, 2.0)).isEqualTo(-1);

    }

    @Override
    public double slope() {
      return NaN;
    }

    @Override
    public double transform(double x) {
      return NaN;
    }

    @Override
    public LinearTransformation inverse() {
      return this;
    }

    @Override
    public String toString() {
      return "NaN";
    }
  }

   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link
   * Double#NEGATIVE_INFINITY}, or {@link Double#NaN}) then the result is {@link Double#NaN}.
   *
   * @throws IllegalStateException if the dataset is empty
   */
  public double populationCovariance() {
    checkState(count() != 0);
    return sumOfProductsOfDeltas / count();
  }