assertThat(ONE_VALUE_STATS.populationVariance()).isEqualTo(0.0);
    assertThat(Stats.of(POSITIVE_INFINITY).populationVariance()).isNaN();
    assertThat(Stats.of(NEGATIVE_INFINITY).populationVariance()).isNaN();
    assertThat(Stats.of(NaN).populationVariance()).isNaN();
    assertThat(TWO_VALUES_STATS.populationVariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_SQUARES_OF_DELTAS / 2);

        assertWithMessage("mean of %s", values).that(mean).isNaN();
        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity() && values.hasAnyNegativeInfinity()) {
        assertWithMessage("mean of %s", values).that(mean).isNaN();
        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity()) {

import static java.lang.Double.MAX_EXPONENT;
import static java.lang.Double.MIN_EXPONENT;
import static java.lang.Double.POSITIVE_INFINITY;
import static java.lang.Double.doubleToRawLongBits;
import static java.lang.Double.isNaN;
import static java.lang.Double.longBitsToDouble;
import static java.lang.Math.getExponent;
import static java.lang.Math.max;

import com.google.common.annotations.GwtIncompatible;

     * @param analyzeType Type of analysis (for logging)
     * @param isLast Whether this is the last buffer
     */
    private void processBuffer(final SuggestAnalyzer analyzer, final String field, final String lang, final boolean useReading,
            final List<AnalyzeToken> tokens, final StringBuilder buf, final String analyzeType, final boolean isLast) {
        try {

        assertWithMessage("mean of %s", values).that(mean).isNaN();
        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity() && values.hasAnyNegativeInfinity()) {
        assertWithMessage("mean of %s", values).that(mean).isNaN();
        assertWithMessage("mean by addAll(Stats) of %s", values).that(meanByAddAllStats).isNaN();
      } else if (values.hasAnyPositiveInfinity()) {

    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)

    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)

        // copySign(x, 1.0) is a branch-free version of abs(x), but with different NaN semantics
        || (a == b) // needed to ensure that infinities equal themselves
        || (Double.isNaN(a) && Double.isNaN(b));
  }

  /**
   * Compares {@code a} and {@code b} "fuzzily," with a tolerance for nearly-equal values.
   *

      assertTrue(Double.isNaN(DoubleMath.log2(-d)));
    }
  }

  public void testLog2Zero() {
    assertThat(DoubleMath.log2(0.0)).isNegativeInfinity();
    assertThat(DoubleMath.log2(-0.0)).isNegativeInfinity();
  }

  public void testLog2NaNInfinity() {
    assertThat(DoubleMath.log2(Double.POSITIVE_INFINITY)).isPositiveInfinity();
    assertTrue(Double.isNaN(DoubleMath.log2(Double.NEGATIVE_INFINITY)));

      if (values.hasAnyNonFinite()) {
        assertWithMessage("population covariance of %s", values).that(populationCovariance).isNaN();
        assertWithMessage("population covariance by addAll(PairedStats) of %s", values)
            .that(populationCovarianceByAddAllPartitionedPairedStats)
            .isNaN();
      } else {
        assertWithMessage("population covariance of %s", values)
            .that(populationCovariance)