}
	if count > 0 {
		lrg := XferStats{
			Avg:  lavg / float64(count),
			Curr: lcurr / float64(count),
			Peak: lpeak,
		}
		sml := XferStats{
			Avg:  savg / float64(count),
			Curr: scurr / float64(count),
			Peak: speak,
		}
		qs.XferStats[Large] = lrg
		qs.XferStats[Small] = sml
		qs.XferStats[Total] = XferStats{
			Avg:  (savg + lavg) / float64(count),
			Curr: (lcurr + scurr) / float64(count),

			case uint:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case uint8:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case uint16:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case uint32:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case uint64:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case []byte:

			Buckets: []float64{.05, .1, .25, .5, 1, 2.5, 5, 10},
		},
		[]string{"api"},
	)
	bucketHTTPRequestsDuration = prometheus.NewHistogramVec(
		prometheus.HistogramOpts{
			Name:    "s3_ttfb_seconds",
			Help:    "Time taken by requests served by current MinIO server instance per bucket",
			Buckets: []float64{.05, .1, .25, .5, 1, 2.5, 5, 10},
		},
		[]string{"api", "bucket"},
	)

		Peak:    peak,
		Curr:    curr,
		measure: rx.measure,
		N:       rx.N + o.N,
	}
}

func calcAvg(x, y float64, n1, n2 int64) float64 {
	if n1+n2 == 0 {
		return 0
	}
	avg := (x*float64(n1) + y*float64(n2)) / float64(n1+n2)
	return avg
}

// Add a new transfer
func (rx *XferStats) addSize(sz int64, t time.Duration) {
	if rx.measure == nil {

	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() {

					// Since we are benchmarking n parallel servers we need to multiply by n.
					// This will give an estimate of the total ops/s.
					latency := float64(atomic.LoadInt64(&lat)) / float64(time.Millisecond)
					b.ReportMetric(float64(n)*float64(ops)/spent.Seconds(), "vops/s")
					b.ReportMetric(latency/float64(ops), "ms/op")
				}
			})
		}
	})
	b.Run("rpc", func(b *testing.B) {
		for par := 1; par <= 32; par *= 2 {

func FromArray(a []Value) *Value {
	return &Value{value: a}
}

// ToFloat works for int and float values
func (v Value) ToFloat() (val float64, ok bool) {
	switch x := v.value.(type) {
	case float64:
		return x, true
	case int64:
		return float64(x), true
	}
	return 0, false
}

// ToInt returns the value if int.
func (v Value) ToInt() (val int64, ok bool) {
	val, ok = v.value.(int64)

	}
}

// Metrics contains metrics about the authentication plugin service.
type Metrics struct {
	LastReachableSecs, LastUnreachableSecs float64

	// Last whole minute stats
	TotalRequests, FailedRequests int64
	AvgSuccRTTMs                  float64
	MaxSuccRTTMs                  float64
}

// Metrics reports metrics related to plugin service reachability and stats for the last whole minute

		{Name: "FLOAT32", DBName: "ffloat32", BindNames: []string{"FLOAT32"}, DataType: schema.Float, Creatable: true, Updatable: true, Readable: true, Size: 32, Tag: `gorm:"column:ffloat32"`},
		{Name: "FLOAT64", DBName: "ffloat64", BindNames: []string{"FLOAT64"}, DataType: schema.Float, Creatable: true, Updatable: true, Readable: true, Size: 64, Tag: `gorm:"column:ffloat64"`},

// float32 is the set of all IEEE 754 32-bit floating-point numbers.
type float32 float32

// float64 is the set of all IEEE 754 64-bit floating-point numbers.
type float64 float64

// complex64 is the set of all complex numbers with float32 real and
// imaginary parts.
type complex64 complex64

// complex128 is the set of all complex numbers with float64 real and
// imaginary parts.
type complex128 complex128