Coin

coin.go

package main

import (
	"encoding/json"
	"fmt"
	"io/ioutil"
	"math/rand"
	"os"
)

const (
	FLIPS = 1e6
)

type FlipArray struct {
	Flips []int
}

func flip() bool {
	return rand.Intn(2) == 0
}

func average(array []int) float64 {
	sum := float64(0)
	for _, value := range array {
		sum += float64(value)
	}
	return float64(sum) / float64(len(array))
}

func main() {
	flipsT := make([]int, 0, FLIPS)
	flips := 0
	heads := 0
	for i := 0; i < FLIPS; i++ {
		for heads < 10 {
			if flip() {
				heads++
			} else {
				heads = 0
			}
			flips++
		}
		flipsT = append(flipsT, flips)
		flips = 0
		heads = 0
		if i%1000 == 0 {
			fmt.Println(i)
		}
	}
	fmt.Println()
	fmt.Println(average(flipsT))

	f := FlipArray{flipsT}
	b, err := json.Marshal(f)
	if err != nil {
		panic(err)
	}

	err = ioutil.WriteFile("output.json", b, os.ModePerm)
	if err != nil {
		panic(err)
	}
}

coinParallel.go

package main

import (
	"fmt"
	"math/rand"
	"time"
)

const (
	FLIPS = 1e6
	CORES = 5
)

func flip() bool {
	return rand.Intn(2) == 0
}

func get10() int {
	heads := 0
	flips := 0
	for heads < 10 {
		if flip() {
			heads++
		} else {
			heads = 0
		}
		flips++
	}
	return flips
}

func runBatch(n int, c chan int) {
	for i := 0; i < n; i++ {
		c <- get10()
	}
}

func average(array []int) float64 {
	sum := 0
	for _, value := range array {
		sum += value
	}
	return float64(sum) / float64(len(array))
}

func main() {
	flipsT := make([]int, 0, FLIPS)
	results := make(chan int, 1000)
	batchSize := FLIPS / CORES
	for i := 0; i < CORES; i++ {
		go runBatch(batchSize, results)
	}

	i := 0
	for {
		i++
		if i%1000 == 0 {
			fmt.Println(i)
		}
		select {
		case result := <-results:
			flipsT = append(flipsT, result)
		case <-time.After(time.Second):
			break
		}
	}
	fmt.Println()
	fmt.Println(average(flipsT))

}

crypto-rand.go

package main

import "encoding/binary"
import "crypto/rand"

func main() {
	var n int32
	binary.Read(rand.Reader, binary.LittleEndian, &n)
	println(n)
}

visu.py

import numpy as np
import matplotlib.pyplot as plt

import json


with open("output.json", "r") as f:
  read_data = f.read()
  
data = np.array(json.loads(read_data)["Flips"], dtype="int32")
print data

data = data[~(data > 15000)]

print np.max(data)
print np.min(data)
print np.mean(data)

y = np.bincount(data)
ii = np.nonzero(y)
print y
print ii
ii = ii[0]
print ii
op = np.vstack((ii, y[ii]))
x = op[0]
y = np.log(op[1])
fit = np.polyfit(x,y,1)
print fit
print str(np.e**fit[1]) + "e^(" + str(fit[0]) + "x)"

fit_fn = np.poly1d(fit)
plt.plot(x,y, 'yo', x, fit_fn(x), '--k')
# n, bins, patches = plt.hist(data, 100, normed=1, facecolor="green")

plt.show()