Sampling k numbers in range [a, b) without replacement - Two different ways

random_permutation.go

package main

import "fmt"

// Sample k unique integers in range [min, max) by generating
// random numbers between min and max and then taking the first
// k numbers.
// The downside to this algorithm is a temporary
// list has to be kept in memory to store all the number from
// min to max.
// The upside is that the resulting number will be
// in a random order.
func randomInts(min, max, k int, rng *rand.Rand) (ints []int) {
	ints = make([]int, k)
	var choices = rng.Perm(max - min)
	for i := 0; i < k; i++ {
		ints[i] = choices[i] + min
	}
	return
}

func main() {
    var rng = rand.New(rand.NewSource(time.Now().UnixNano()))
    fmt.Println(randomInts(3, 10, 2, rng))   
}

reservoir_sampling.go

package main

import "fmt"

// Sample k unique integers in range [min, max) using reservoir sampling,
// specifically Vitter's Algorithm R.
// The upside is that no temporary list has to be maintained.
// The downside is that the resulting numbers are not necessarily in a
// random order.
func randomInts(min, max, k int, rng *rand.Rand) (ints []int) {
	ints = make([]int, k)
	for i := 0; i < k; i++ {
		ints[i] = i + min
	}
	var j int
	for i := k; i < max-min; i++ {
		j = rng.Intn(i + 1)
		if j < k {
			ints[j] = i + min
		}
	}
	return
}

func main() {
    var rng = rand.New(rand.NewSource(time.Now().UnixNano()))
    fmt.Println(randomInts(3, 10, 2, rng))   
}