From 8c12c6939aab9106db14ec2d11d983bc5b29fb2c Mon Sep 17 00:00:00 2001 From: Niall Sheridan Date: Sun, 7 Jul 2019 21:33:44 +0100 Subject: Switch to modules --- vendor/golang.org/x/net/trace/histogram.go | 365 ----------------------------- 1 file changed, 365 deletions(-) delete mode 100644 vendor/golang.org/x/net/trace/histogram.go (limited to 'vendor/golang.org/x/net/trace/histogram.go') diff --git a/vendor/golang.org/x/net/trace/histogram.go b/vendor/golang.org/x/net/trace/histogram.go deleted file mode 100644 index 9bf4286..0000000 --- a/vendor/golang.org/x/net/trace/histogram.go +++ /dev/null @@ -1,365 +0,0 @@ -// 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) allocateBuckets() { - if h.buckets == nil { - h.buckets = make([]int64, bucketCount) - h.buckets[h.value] = h.valueCount - h.value = 0 - h.valueCount = -1 - } -} - -func log2(i int64) int { - n := 0 - for ; i >= 0x100; i >>= 8 { - n += 8 - } - for ; i > 0; i >>= 1 { - n += 1 - } - return n -} - -func getBucket(i int64) (index int) { - index = log2(i) - 1 - if index < 0 { - index = 0 - } - if index >= bucketCount { - index = bucketCount - 1 - } - return -} - -// Total returns the number of recorded observations. -func (h *histogram) total() (total int64) { - if h.valueCount >= 0 { - total = h.valueCount - } - for _, val := range h.buckets { - total += int64(val) - } - return -} - -// Average returns the average value of recorded observations. -func (h *histogram) average() float64 { - t := h.total() - if t == 0 { - return 0 - } - return float64(h.sum) / float64(t) -} - -// Variance returns the variance of recorded observations. -func (h *histogram) variance() float64 { - t := float64(h.total()) - if t == 0 { - return 0 - } - s := float64(h.sum) / t - return h.sumOfSquares/t - s*s -} - -// StandardDeviation returns the standard deviation of recorded observations. -func (h *histogram) standardDeviation() float64 { - return math.Sqrt(h.variance()) -} - -// PercentileBoundary estimates the value that the given fraction of recorded -// observations are less than. -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) -} - -// Median returns the estimated median of the observed values. -func (h *histogram) median() int64 { - return h.percentileBoundary(0.5) -} - -// Add adds other to h. -func (h *histogram) Add(other timeseries.Observable) { - o := other.(*histogram) - if o.valueCount == 0 { - // Other histogram is empty - } else if h.valueCount >= 0 && o.valueCount > 0 && h.value == o.value { - // Both have a single bucketed value, aggregate them - h.valueCount += o.valueCount - } else { - // Two different values necessitate buckets in this histogram - h.allocateBuckets() - if o.valueCount >= 0 { - h.buckets[o.value] += o.valueCount - } else { - for i := range h.buckets { - h.buckets[i] += o.buckets[i] - } - } - } - h.sumOfSquares += o.sumOfSquares - h.sum += o.sum -} - -// Clear resets the histogram to an empty state, removing all observed values. -func (h *histogram) Clear() { - h.buckets = nil - h.value = 0 - h.valueCount = 0 - h.sum = 0 - h.sumOfSquares = 0 -} - -// CopyFrom copies from other, which must be a *histogram, into h. -func (h *histogram) CopyFrom(other timeseries.Observable) { - o := other.(*histogram) - if o.valueCount == -1 { - h.allocateBuckets() - copy(h.buckets, o.buckets) - } - h.sum = o.sum - h.sumOfSquares = o.sumOfSquares - h.value = o.value - h.valueCount = o.valueCount -} - -// Multiply scales the histogram by the specified ratio. -func (h *histogram) Multiply(ratio float64) { - if h.valueCount == -1 { - for i := range h.buckets { - h.buckets[i] = int64(float64(h.buckets[i]) * ratio) - } - } else { - h.valueCount = int64(float64(h.valueCount) * ratio) - } - h.sum = int64(float64(h.sum) * ratio) - h.sumOfSquares = h.sumOfSquares * ratio -} - -// New creates a new histogram. -func (h *histogram) New() timeseries.Observable { - r := new(histogram) - r.Clear() - return r -} - -func (h *histogram) String() string { - return fmt.Sprintf("%d, %f, %d, %d, %v", - h.sum, h.sumOfSquares, h.value, h.valueCount, h.buckets) -} - -// round returns the closest int64 to the argument -func round(in float64) int64 { - return int64(math.Floor(in + 0.5)) -} - -// bucketBoundary returns the first value in the bucket. -func bucketBoundary(bucket uint8) int64 { - if bucket == 0 { - return 0 - } - return 1 << bucket -} - -// bucketData holds data about a specific bucket for use in distTmpl. -type bucketData struct { - Lower, Upper int64 - N int64 - Pct, CumulativePct float64 - GraphWidth int -} - -// data holds data about a Distribution for use in distTmpl. -type data struct { - Buckets []*bucketData - Count, Median int64 - Mean, StandardDeviation float64 -} - -// maxHTMLBarWidth is the maximum width of the HTML bar for visualizing buckets. -const maxHTMLBarWidth = 350.0 - -// newData returns data representing h for use in distTmpl. -func (h *histogram) newData() *data { - // Force the allocation of buckets to simplify the rendering implementation - h.allocateBuckets() - // We scale the bars on the right so that the largest bar is - // maxHTMLBarWidth pixels in width. - maxBucket := int64(0) - for _, n := range h.buckets { - if n > maxBucket { - maxBucket = n - } - } - total := h.total() - barsizeMult := maxHTMLBarWidth / float64(maxBucket) - var pctMult float64 - if total == 0 { - pctMult = 1.0 - } else { - pctMult = 100.0 / float64(total) - } - - buckets := make([]*bucketData, len(h.buckets)) - runningTotal := int64(0) - for i, n := range h.buckets { - if n == 0 { - continue - } - runningTotal += n - var upperBound int64 - if i < bucketCount-1 { - upperBound = bucketBoundary(uint8(i + 1)) - } else { - upperBound = math.MaxInt64 - } - buckets[i] = &bucketData{ - Lower: bucketBoundary(uint8(i)), - Upper: upperBound, - N: n, - Pct: float64(n) * pctMult, - CumulativePct: float64(runningTotal) * pctMult, - GraphWidth: int(float64(n) * barsizeMult), - } - } - return &data{ - Buckets: buckets, - Count: total, - Median: h.median(), - Mean: h.average(), - StandardDeviation: h.standardDeviation(), - } -} - -func (h *histogram) html() template.HTML { - buf := new(bytes.Buffer) - if err := distTmpl().Execute(buf, h.newData()); err != nil { - buf.Reset() - log.Printf("net/trace: couldn't execute template: %v", err) - } - return template.HTML(buf.String()) -} - -var distTmplCache *template.Template -var distTmplOnce sync.Once - -func distTmpl() *template.Template { - distTmplOnce.Do(func() { - // Input: data - distTmplCache = template.Must(template.New("distTmpl").Parse(` - - - - - - - -
Count: {{.Count}}Mean: {{printf "%.0f" .Mean}}StdDev: {{printf "%.0f" .StandardDeviation}}Median: {{.Median}}
-
- -{{range $b := .Buckets}} -{{if $b}} - - - - - - - - - -{{end}} -{{end}} -
[{{.Lower}},{{.Upper}}){{.N}}{{printf "%#.3f" .Pct}}%{{printf "%#.3f" .CumulativePct}}%
-`)) - }) - return distTmplCache -} -- cgit v1.2.3