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    Metadata details:
    filename: histogram.go
    path of file: ./repos/fabio/vendor/golang.org/x/net/trace
    
    the code of the file until where you have to start completion: // Copyright 2015 The Go Authors. All rights reserved.
// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package trace

// This file implements histogramming for RPC statistics collection.

import (
	"bytes"
	"fmt"
	"html/template"
	"log"
	"math"
	"sync"

	"golang.org/x/net/internal/timeseries"
)

const (
	bucketCount = 38
)

// histogram keeps counts of values in buckets that are spaced
// out in powers of 2: 0-1, 2-3, 4-7...
// histogram implements timeseries.Observable
type histogram struct {
	sum          int64   // running total of measurements
	sumOfSquares float64 // square of running total
	buckets      []int64 // bucketed values for histogram
	value        int     // holds a single value as an optimization
	valueCount   int64   // number of values recorded for single value
}

// AddMeasurement records a value measurement observation to the histogram.
func (h *histogram) addMeasurement(value int64) {
	// TODO: assert invariant
	h.sum += value
	h.sumOfSquares += float64(value) * float64(value)

	bucketIndex := getBucket(value)

	if h.valueCount == 0 || (h.valueCount > 0 && h.value == bucketIndex) {
		h.value = bucketIndex
		h.valueCount++
	} else {
		h.allocateBuckets()
		h.buckets[bucketIndex]++
	}
}

func (h *histogram) alloc
    
func (h *histogram) percentileBoundary(percentile float64) int64 {
	total := h.total()

	// Corner cases (make sure result is strictly less than Total())
	if total == 0 {
		return 0
	} else if total == 1 {
		return int64(h.average())
	}

	percentOfTotal := round(float64(total) * percentile)
	var runningTotal int64

	for i := range h.buckets {
		value := h.buckets[i]
		runningTotal += value
		if runningTotal == percentOfTotal {
			// We hit an exact bucket boundary. If the next bucket has data, it is a
			// good estimate of the value. If the bucket is empty, we interpolate the
			// midpoint between the next bucket's boundary and the next non-zero
			// bucket. If the remaining buckets are all empty, then we use the
			// boundary for the next bucket as the estimate.
			j := uint8(i + 1)
			min := bucketBoundary(j)
			if runningTotal < total {
				for h.buckets[j] == 0 {
					j++
				}
			}
			max := bucketBoundary(j)
			return min + round(float64(max-min)/2)
		} else if runningTotal > percentOfTotal {
			// The value is in this bucket. Interpolate the value.
			delta := runningTotal - percentOfTotal
			percentBucket := float64(value-delta) / float64(value)
			bucketMin := bucketBoundary(uint8(i))
			nextBucketMin := bucketBoundary(uint8(i + 1))
			bucketSize := nextBucketMin - bucketMin
			return bucketMin + round(percentBucket*float64(bucketSize))
		}
	}
	return bucketBoundary(bucketCount - 1)
}