func Less[T Ordered](x, y T) bool {
	return (isNaN(x) && !isNaN(y)) || x < y
}

// Compare returns
//
//	-1 if x is less than y,
//	 0 if x equals y,
//	+1 if x is greater than y.
//
// For floating-point types, a NaN is considered less than any non-NaN,
// a NaN is considered equal to a NaN, and -0.0 is equal to 0.0.
func Compare[T Ordered](x, y T) int {
	xNaN := isNaN(x)
	yNaN := isNaN(y)
	if xNaN {
		if yNaN {
			return 0

    assertThat(ONE_VALUE_STATS.populationVariance()).isWithin(0.0).of(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);

		return archHypot(p, q)
	}
	return hypot(p, q)
}

func hypot(p, q float64) float64 {
	p, q = Abs(p), Abs(q)
	// special cases
	switch {
	case IsInf(p, 1) || IsInf(q, 1):
		return Inf(1)
	case IsNaN(p) || IsNaN(q):
		return NaN()
	}
	if p < q {
		p, q = q, p
	}
	if p == 0 {
		return 0
	}
	q = q / p
	return p * Sqrt(1+q*q)

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

			t.Errorf("min(%v, %v) = %v, want %v", tt.max, tt.min, z, tt.min)
		}
	}
	for _, x := range all {
		if z := min(nan, x); !math.IsNaN(z) {
			t.Errorf("min(%v, %v) = %v, want %v", nan, x, z, nan)
		}
		if z := min(x, nan); !math.IsNaN(z) {
			t.Errorf("min(%v, %v) = %v, want %v", nan, x, z, nan)
		}
	}
}

func TestMaxFloat(t *testing.T) {
	for _, tt := range tests {

//
//	x[i] < x[j] || (math.IsNaN(x[i]) && !math.IsNaN(x[j]))
func (x Float64Slice) Less(i, j int) bool { return x[i] < x[j] || (isNaN(x[i]) && !isNaN(x[j])) }
func (x Float64Slice) Swap(i, j int)      { x[i], x[j] = x[j], x[i] }

// isNaN is a copy of math.IsNaN to avoid a dependency on the math package.
func isNaN(f float64) bool {
	return f != f
}

    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)

func _SliceEqual[Elem comparable](s1, s2 []Elem) bool {
	if len(s1) != len(s2) {
		return false
	}
	for i, v1 := range s1 {
		v2 := s2[i]
		if v1 != v2 {
			isNaN := func(f Elem) bool { return f != f }
			if !isNaN(v1) || !isNaN(v2) {
				return false
			}
		}
	}
	return true
}

// A Graph is a collection of nodes. A node may have an arbitrary number

		} else {
			j = h // preserves x[j] >= target
		}
	}
	// i == j, x[i-1] < target, and x[j] (= x[i]) >= target  =>  answer is i.
	return i, i < n && (x[i] == target || (isNaN(x[i]) && isNaN(target)))
}

// BinarySearchFunc works like [BinarySearch], but uses a custom comparison
// function. The slice must be sorted in increasing order, where "increasing"

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