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Merged
elecbug merged 2 commits into from
Nov 20, 2025
Merged

Update v0.8.3 #31

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bf231f4
feat: update random
elecbug Nov 20, 2025
f732953
feat: update random
elecbug Nov 20, 2025
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78 changes: 39 additions & 39 deletions p2p/helper.go
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Original file line number Diff line number Diff line change
Expand Up @@ -5,58 +5,58 @@ import (
"math/rand"
)

// LogNormalRand generates a log-normally distributed random number
// with given mu and sigma parameters.
func LogNormalRand(mu, sigma float64, src rand.Source) float64 {
r := rand.New(src)

u1 := r.Float64()
u2 := r.Float64()
z := math.Sqrt(-2.0*math.Log(u1)) * math.Cos(2*math.Pi*u2)

return math.Exp(mu + sigma*z)
}

// PoissonRand generates a Poisson-distributed random integer
// with given lambda parameter.
func PoissonRand(lambda float64, src rand.Source) int {
// Poisson(λ): discrete distribution.
func PoissonRandom(lambda float64) int {
L := math.Exp(-lambda)
k := 0
p := 1.0

r := rand.New(src)

for p > L {
k++
p *= r.Float64()
p *= rand.Float64()
}

return k - 1
}

// ExponentialRand generates an exponentially distributed random number
// with given rate parameter.
func ExponentialRand(rate float64, src rand.Source) float64 {
r := rand.New(src)
u := r.Float64()
return -math.Log(1-u) / rate
// LogNormal(μ, σ): continuous distribution.
func LogNormalRand(mu, sigma float64) float64 {
u1 := rand.Float64()
u2 := rand.Float64()
z := math.Sqrt(-2.0*math.Log(u1)) * math.Cos(2*math.Pi*u2)
return math.Exp(mu + sigma*z)
}

// UniformRand generates a uniformly distributed random number
// between min and max.
func UniformRand(min, max float64, src rand.Source) float64 {
r := rand.New(src)
return min + r.Float64()*(max-min)
// Exponential(λ): continuous distribution.
func ExponentialRandom(lambda float64) float64 {
u := rand.Float64()
return -math.Log(1.0-u) / lambda
}

// NormalRand generates a normally distributed random number
// with given mean and standard deviation.
func NormalRand(mean, stddev float64, src rand.Source) float64 {
r := rand.New(src)

u1 := r.Float64()
u2 := r.Float64()
// Normal(μ, σ): Box-Muller transform.
func NormalRandom(mu, sigma float64) float64 {
u1 := rand.Float64()
u2 := rand.Float64()
z := math.Sqrt(-2.0*math.Log(u1)) * math.Cos(2*math.Pi*u2)
return mu + sigma*z
}

// Binomial(n, p): discrete distribution.
func BinomialRandom(n int, p float64) int {
count := 0
for i := 0; i < n; i++ {
if rand.Float64() < p {
count++
}
}
return count
}

// Uniform(a, b): continuous distribution.
func UniformRandom(a, b float64) float64 {
return a + (b-a)*rand.Float64()
}

return mean + stddev*z
// Pareto(xm, α): continuous heavy-tailed distribution.
func ParetoRandom(xm, alpha float64) float64 {
u := rand.Float64()
return xm / math.Pow(1.0-u, 1.0/alpha)
}
11 changes: 4 additions & 7 deletions p2p/p2p_test.go
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,6 @@ import (
"encoding/json"
"fmt"
"math"
"math/rand"
"os"
"testing"
"time"
Expand All @@ -18,10 +17,9 @@ func TestGenerateNetwork(t *testing.T) {
sg := standard_graph.NewStandardGraph()
g := sg.ErdosRenyiGraph(1000, 50.000/1000, true)
t.Logf("Generated graph with %d nodes and %d edges\n", len(g.Nodes()), g.EdgeCount())
src := rand.NewSource(time.Now().UnixNano())

nodeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.5, src) }
edgeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.3, src) }
nodeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.5) }
edgeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.3) }

nw, err := p2p.GenerateNetwork(g, nodeLatency, edgeLatency, &p2p.Config{GossipFactor: 0.35})
if err != nil {
Expand Down Expand Up @@ -88,10 +86,9 @@ func TestMetrics(t *testing.T) {
sg := standard_graph.NewStandardGraph()
g := sg.ErdosRenyiGraph(1000, 50.000/1000, true)
t.Logf("Generated graph with %d nodes and %d edges\n", len(g.Nodes()), g.EdgeCount())
src := rand.NewSource(time.Now().UnixNano())

nodeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.5, src) }
edgeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.3, src) }
nodeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.5) }
edgeLatency := func() float64 { return p2p.LogNormalRand(math.Log(100), 0.3) }

nw, err := p2p.GenerateNetwork(g, nodeLatency, edgeLatency, &p2p.Config{GossipFactor: 0.35})
if err != nil {
Expand Down