blob: 3519e76a3c80d3aa359ddfde1814c8801ee5bfb4 [file] [log] [blame]
// Copyright 2022 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 benchmath
import "fmt"
// AssumeExact is an assumption that a value can be measured exactly
// and thus has no distribution and does not require repeated sampling.
// It reports a warning if not all values in a sample are equal.
var AssumeExact = assumeExact{}
type assumeExact struct{}
var _ Assumption = assumeExact{}
func (assumeExact) SummaryLabel() string {
// Really the summary is the mode, but the point of this
// assumption is that the summary is the exact value.
return "exact"
func (assumeExact) Summary(s *Sample, confidence float64) Summary {
// Find the sample's mode. This checks if all samples are the
// same, and lets us return a reasonable summary even if they
// aren't all the same.
val, count := s.Values[0], 1
modeVal, modeCount := val, count
for _, v := range s.Values[1:] {
if v == val {
if count > modeCount {
modeVal, modeCount = val, count
} else {
val, count = v, 1
summary := Summary{Center: modeVal, Lo: s.Values[0], Hi: s.Values[len(s.Values)-1], Confidence: 1}
if modeCount != len(s.Values) {
// They're not all the same. Report a warning.
summary.Warnings = []error{fmt.Errorf("exact distribution expected, but values range from %v to %v", s.Values[0], s.Values[len(s.Values)-1])}
return summary
func (assumeExact) Compare(s1, s2 *Sample) Comparison {
return Comparison{P: 0, N1: len(s1.Values), N2: len(s2.Values)}