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 {

			if intA > result {
				result = intA
			}
		}
		v.setInt(result)
		return nil
	}

	floatV, _ := v.ToFloat()
	floatA, _ := a.ToFloat()
	var result float64
	if !isMax {
		result = math.Min(floatV, floatA)
	} else {
		result = math.Max(floatV, floatA)
	}
	v.setFloat(result)
	return nil
}

func inferTypeAsTimestamp(v *Value) error {
	if s, ok := v.ToString(); ok {

	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() {

		if globalExpiryState != nil {
			expPendingTasks.Value = float64(globalExpiryState.PendingTasks())
			expMissedTasks.Value = float64(globalExpiryState.stats.MissedTasks())
			expMissedFreeVersions.Value = float64(globalExpiryState.stats.MissedFreeVersTasks())
			expMissedTierJournalTasks.Value = float64(globalExpiryState.stats.MissedTierJournalTasks())
			expNumWorkers.Value = float64(globalExpiryState.stats.NumWorkers())
		}

			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"},
	)

	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)
	}

		return err
	}

	m.Set(memTotal, float64(memMetrics.Total))
	m.Set(memUsed, float64(memMetrics.Used))
	usedPerc := float64(memMetrics.Used) * 100 / float64(memMetrics.Total)
	m.Set(memUsedPerc, usedPerc)
	m.Set(memFree, float64(memMetrics.Free))
	m.Set(memBuffers, float64(memMetrics.Buffers))
	m.Set(memCache, float64(memMetrics.Cache))
	m.Set(memShared, float64(memMetrics.Shared))

	m.readsPerSec = float64(ioStats.ReadIOs) / durationSecs
	m.readsKBPerSec = float64(ioStats.ReadSectors) * float64(sectorSize) / kib / durationSecs
	if ioStats.ReadIOs > 0 {
		m.readsAwait = float64(ioStats.ReadTicks) / float64(ioStats.ReadIOs)
	}

	m.writesPerSec = float64(ioStats.WriteIOs) / durationSecs
	m.writesKBPerSec = float64(ioStats.WriteSectors) * float64(sectorSize) / kib / durationSecs

				}
			case float64:
				field.ReflectValueOf(ctx, value).SetFloat(data)
			case float32:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int64:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int8:
				field.ReflectValueOf(ctx, value).SetFloat(float64(data))
			case int16:

		m.expMovingAvg = float64(bytesSinceLastWindow) / duration.Seconds()
		return
	}

	increment := float64(bytesSinceLastWindow) / duration.Seconds()
	m.expMovingAvg = exponentialMovingAverage(betaBucket, m.expMovingAvg, increment)
}

// exponentialMovingAverage calculates the exponential moving average
func exponentialMovingAverage(beta, previousAvg, incrementAvg float64) float64 {