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// Copyright 2021 syzkaller project authors. All rights reserved.
// Use of this source code is governed by Apache 2 LICENSE that can be found in the LICENSE file.
// Package sample provides various statistical operations and algorithms.
package sample
import (
"math"
"sort"
)
// Sample represents a single sample - set of data points collected during an experiment.
type Sample struct {
Xs []float64
Sorted bool
}
func (s *Sample) Percentile(p float64) float64 {
s.Sort()
// The code below is taken from golang.org/x/perf/internal/stats
// Unfortunately, that package is internal and we cannot just import and use it.
N := float64(len(s.Xs))
n := 1/3.0 + p*(N+1/3.0) // R8
kf, frac := math.Modf(n)
k := int(kf)
if k <= 0 {
return s.Xs[0]
} else if k >= len(s.Xs) {
return s.Xs[len(s.Xs)-1]
}
return s.Xs[k-1] + frac*(s.Xs[k]-s.Xs[k-1])
}
func (s *Sample) Median() float64 {
return s.Percentile(0.5)
}
// Remove outliers by the Tukey's fences method.
func (s *Sample) RemoveOutliers() *Sample {
if len(s.Xs) < 4 {
// If the data set is too small, we cannot reliably detect outliers anyway.
return s.Copy()
}
s.Sort()
Q1 := s.Percentile(0.25)
Q3 := s.Percentile(0.75)
minValue := Q1 - 1.5*(Q3-Q1)
maxValue := Q3 + 1.5*(Q3-Q1)
xs := []float64{}
for _, value := range s.Xs {
if value >= minValue && value <= maxValue {
xs = append(xs, value)
}
}
return &Sample{
Xs: xs,
Sorted: s.Sorted,
}
}
func (s *Sample) Copy() *Sample {
return &Sample{
Xs: append([]float64{}, s.Xs...),
Sorted: s.Sorted,
}
}
func (s *Sample) Sort() {
if !s.Sorted {
sort.Slice(s.Xs, func(i, j int) bool { return s.Xs[i] < s.Xs[j] })
s.Sorted = true
}
}
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