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// Package bloomfilter is face-meltingly fast, thread-safe,
// marshalable, unionable, probability- and
// optimal-size-calculating Bloom filter in go
//
// https://github.com/steakknife/bloomfilter
//
// Copyright © 2014, 2015, 2018 Barry Allard
//
// MIT license
//
package v2
import (
"math"
"math/bits"
)
// CountBitsUint64s count 1's in b
func CountBitsUint64s(b []uint64) int {
c := 0
for _, x := range b {
c += bits.OnesCount64(x)
}
return c
}
// PreciseFilledRatio is an exhaustive count # of 1's
func (f *Filter) PreciseFilledRatio() float64 {
f.lock.RLock()
defer f.lock.RUnlock()
return float64(CountBitsUint64s(f.bits)) / float64(f.M())
}
// N is how many elements have been inserted
// (actually, how many Add()s have been performed?)
func (f *Filter) N() uint64 {
f.lock.RLock()
defer f.lock.RUnlock()
return f.n
}
// FalsePosititveProbability is the upper-bound probability of false positives
// (1 - exp(-k*(n+0.5)/(m-1))) ** k
func (f *Filter) FalsePosititveProbability() float64 {
k := float64(f.K())
n := float64(f.N())
m := float64(f.M())
return math.Pow(1.0-math.Exp((-k)*(n+0.5)/(m-1)), k)
}
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