Labels map[string]string

	// value captured in current cycle
	Current float64

	// Used when system provides cumulative (since uptime) values
	// helps in calculating the current value by comparing the new
	// cumulative value with previous one
	Cumulative float64

	Max   float64
	Avg   float64
	Sum   float64
	Count uint64
}

func init() {

	// label to "s3".

	m.Set(apiRejectedAuthTotal, float64(httpStats.TotalS3RejectedAuth), "type", "s3")
	m.Set(apiRejectedTimestampTotal, float64(httpStats.TotalS3RejectedTime), "type", "s3")
	m.Set(apiRejectedHeaderTotal, float64(httpStats.TotalS3RejectedHeader), "type", "s3")
	m.Set(apiRejectedInvalidTotal, float64(httpStats.TotalS3RejectedInvalid), "type", "s3")
	m.Set(apiRequestsWaitingTotal, float64(httpStats.S3RequestsInQueue), "type", "s3")

*/

// Sinh returns the hyperbolic sine of x.
//
// Special cases are:
//
//	Sinh(±0) = ±0
//	Sinh(±Inf) = ±Inf
//	Sinh(NaN) = NaN
func Sinh(x float64) float64 {
	if haveArchSinh {
		return archSinh(x)
	}
	return sinh(x)
}

func sinh(x float64) float64 {
	// The coefficients are #2029 from Hart & Cheney. (20.36D)
	const (
		P0 = -0.6307673640497716991184787251e+6
		P1 = -0.8991272022039509355398013511e+5

	return a + b
}

func f4(a, b int, c float64) int {
	return (a+b)/2 + int(c)
}

func f5(a int) int {
	return 5
}

func f6(a int) (r int) {
	return 6
}

func f7(a int) (x int, y float64) {
	return 7, 7.0
}


func f8(a int) (x int, y float64) {
	return 8, 8.0
}

type T struct {
	x, y int
}

func (t *T) m10(a int, b float64) int {
	return (t.x + a) * (t.y + int(b))
}

			//  likely underflow to zero

			tmp := float64(n)
			v := 2 / x
			tmp = tmp * Log(Abs(v*tmp))
			if tmp < 7.09782712893383973096e+02 {
				for i := n - 1; i > 0; i-- {
					di := float64(i + i)
					a, b = b, b*di/x-a
				}
			} else {
				for i := n - 1; i > 0; i-- {
					di := float64(i + i)
					a, b = b, b*di/x-a
					// scale b to avoid spurious overflow

	m.Set(usageTotalBytes, float64(clusterSize))
	m.Set(usageObjectsCount, float64(clusterObjectsCount))
	m.Set(usageVersionsCount, float64(clusterVersionsCount))
	m.Set(usageDeleteMarkersCount, float64(clusterDeleteMarkersCount))
	m.Set(usageBucketsCount, float64(clusterBuckets))
	for k, v := range clusterObjectSizesHistogram {
		m.Set(usageSizeDistribution, float64(v), "range", k)
	}

		m.Set(processStartTimeSeconds, float64(startTime))
	}
}

func loadProcIOMetrics(ctx context.Context, io procfs.ProcIO, m MetricValues) {
	if io.RChar > 0 {
		m.Set(processIORCharBytes, float64(io.RChar))
	}

	if io.ReadBytes > 0 {
		m.Set(processIOReadBytes, float64(io.ReadBytes))
	}

	if io.WChar > 0 {
		m.Set(processIOWCharBytes, float64(io.WChar))
	}

	if io.WriteBytes > 0 {

type T struct {
	a int
	S
}

//go:noinline
func (s *S) M(a int, x [2]int, b float64, y [2]float64) (S, int, [2]int, float64, [2]float64) {
	return *s, a, x, b, y
}

var s S = 42
var t = &T{S: s}

var fn = (*T).M // force a method wrapper

func main() {
	a := 123
	x := [2]int{456, 789}
	b := 1.2
	y := [2]float64{3.4, 5.6}
	s1, a1, x1, b1, y1 := fn(t, a, x, b, y)

type Zipf struct {
	r            *Rand
	imax         float64
	v            float64
	q            float64
	s            float64
	oneminusQ    float64
	oneminusQinv float64
	hxm          float64
	hx0minusHxm  float64
}

func (z *Zipf) h(x float64) float64 {
	return math.Exp(z.oneminusQ*math.Log(z.v+x)) * z.oneminusQinv
}

func (z *Zipf) hinv(x float64) float64 {

//
// The true inverse cumulative sum will be in the range [lower, upper).
func (d *mud) approxInvCumulativeSum() (float64, float64, bool) {
	if d.trackBucket == len(d.hist) {
		return math.NaN(), math.NaN(), false
	}
	return float64(d.trackBucket) / mudDegree, float64(d.trackBucket+1) / mudDegree, true
}

// invCumulativeSum returns x such that the integral of d from -∞ to x