英文:
Generating Random Numbers in Go
问题
我正在尝试在Go中生成随机数(整数),但一直没有成功。我在crypto/rand
中找到了rand
包,看起来是我想要的,但是从文档中我无法确定如何使用它。这是我现在尝试的代码:
b := []byte{}
something, err := rand.Read(b)
fmt.Printf("something = %v\n", something)
fmt.Printf("err = %v\n", err)
但不幸的是,这总是输出:
something = 0
err = <nil>
有没有办法修复这个问题,使其实际生成随机数?或者,有没有办法设置生成的随机数的上限?
英文:
I am trying to generate random numbers (integers) in Go, to no avail. I found the rand
package in crypto/rand
, which seems to be what I want, but I can't tell from the documentation how to use it. This is what I'm trying right now:
b := []byte{}
something, err := rand.Read(b)
fmt.Printf("something = %v\n", something)
fmt.Printf("err = %v\n", err)
But unfortunately this always outputs:
something = 0
err = <nil>
Is there a way to fix this so that it actually generates random numbers? Alternatively, is there a way to set the upper bound on the random numbers this generates?
答案1
得分: 28
根据您的用例,另一个选择是math/rand
包。如果您生成的数字需要完全不可预测,请不要这样做。但是,如果您需要获得可重现的结果,这可能会有所帮助 - 只需传入第一次传入的相同种子。
这是经典的“使用当前时间作为种子生成一个数字”的程序:
package main
import (
"fmt"
"math/rand"
"time"
)
func main() {
rand.Seed(time.Now().Unix())
fmt.Println(rand.Int())
}
英文:
Depending on your use case, another option is the math/rand
package. Don't do this if you're generating numbers that need to be completely unpredictable. It can be helpful if you need to get results that are reproducible, though -- just pass in the same seed you passed in the first time.
Here's the classic "seed the generator with the current time and generate a number" program:
package main
import (
"fmt"
"math/rand"
"time"
)
func main() {
rand.Seed(time.Now().Unix())
fmt.Println(rand.Int())
}
答案2
得分: 27
crypto/rand
只提供了随机数据的二进制流,但是你可以使用 encoding/binary
从中读取整数:
package main
import "encoding/binary"
import "crypto/rand"
func main() {
var n int32
binary.Read(rand.Reader, binary.LittleEndian, &n)
println(n)
}
英文:
crypto/rand
provides only binary stream of random data, but you can read integers from it using encoding/binary
:
package main
import "encoding/binary"
import "crypto/rand"
func main() {
var n int32
binary.Read(rand.Reader, binary.LittleEndian, &n)
println(n)
}
答案3
得分: 17
截至2012年4月1日,lang的稳定版本发布后,您可以执行以下操作:
<code><pre>
package main
import "fmt"
import "time"
import "math/rand"
func main() {
rand.Seed(time.Now().UnixNano()) // 以纳秒为种子获取当前时间
fmt.Println(rand.Intn(100)) // 这将给您一个小于100的整数
}
</pre></code>
英文:
As of 1 april 2012, after the release of the stable version of the lang, you can do the following:
<code><pre>
package main
import "fmt"
import "time"
import "math/rand"
func main() {
rand.Seed(time.Now().UnixNano()) // takes the current time in nanoseconds as the seed
fmt.Println(rand.Intn(100)) // this gives you an int up to but not including 100
}
</pre></code>
答案4
得分: 0
你还可以开发自己的随机数生成器,可以基于一个简单的“荒岛伪随机数生成器”——线性同余生成器。此外,还可以查阅L'Ecuyer(1999)、Mersenne Twister或Tausworthe生成器。
https://en.wikipedia.org/wiki/Pseudorandom_number_generator
(避免使用RANDU,它在20世纪60年代很流行,但生成的随机数在三维空间中落在15个超平面上)。
package pmPRNG
import "errors"
const (
Mersenne31 = 2147483647 // = 2^31-1
Mersenne31Inv = 1.0 / 2147483647.0 // = 4.656612875e-10
// a = 16807
a = 48271
)
// 每个流都有自己的种子
type PRNGStream struct {
state int
}
func PRNGStreamNew(seed int) *PRNGStream {
prng := (&PRNGStream{})
prng.SetSeed(seed)
return prng
}
// 强制种子在[1, 2^31-1]范围内
func (r *PRNGStream) SetSeed(seed int) error {
var err error
if seed < 1 || seed > Mersenne31 {
err = errors.New("Seed OOB")
}
if seed > Mersenne31 {
seed = seed % Mersenne31
}
if seed < 1 {
seed = 1
}
r.state = seed
return err
}
// Dig = Park-Miller DesertIslandGenerator
// 整数种子在[1, 2^31-1]范围内
func (r *PRNGStream) Dig(seed int) float32 {
xprev := r.state // x[i-1]
xnext := (a * xprev) % Mersenne31 // x[i] = (a*x[i-1])%m
r.state = xnext // x[i-1] = x[i]
Ri := float32(xnext) * Mersenne31Inv // 将Ui转换为Ri
return Ri
}
func (r *PRNGStream) Rand() float32 {
r.state = (uint64_t)*r.state * Multby % 0x7fffffff
return float32(r.state) * Mersenne31Inv
}
一些相关链接:
https://en.wikipedia.org/wiki/Lehmer_random_number_generator
您可以使用此函数来更新x[i+1],而不是上面的函数,
val = ((state * 1103515245) + 12345) & 0x7fffffff
(基本上,a、c、m的不同值)
https://www.redhat.com/en/blog/understanding-random-number-generators-and-their-limitations-linux
https://www.iro.umontreal.ca/~lecuyer/myftp/papers/handstat.pdf
https://www.math.utah.edu/~alfeld/Random/Random.html
英文:
You can also develop your own random number generator, perhaps based upon a simple "desert island PRNG", a Linear Congruential Generator. Also, look up L'Ecuyer (1999), Mersenne Twister, or Tausworthe generator...
https://en.wikipedia.org/wiki/Pseudorandom_number_generator
(Avoid RANDU, it was popular in the 1960's, but the random numbers generated fall on 15 hyperplanes in 3-space).
package pmPRNG
import "errors"
const (
Mersenne31 = 2147483647 // = 2^31-1
Mersenne31Inv = 1.0 / 2147483647.0 // = 4.656612875e-10
// a = 16807
a = 48271
)
// Each stream gets own seed
type PRNGStream struct {
state int
}
func PRNGStreamNew(seed int) *PRNGStream {
prng := (&PRNGStream{})
prng.SetSeed(seed)
return prng
}
// enforce seed in [1, 2^31-1]
func (r*PRNGStream) SetSeed(seed int) error {
var err error
if seed < 1 || seed > Mersenne31 {
err = errors.New("Seed OOB")
}
if seed > Mersenne31 { seed = seed % Mersenne31 }
if seed < 1 { seed = 1 }
r.state = seed
return err
}
// Dig = Park-Miller DesertIslandGenerator
// integer seed in [1, 2^31-1]
func (r*PRNGStream) Dig(seed int) float32 {
xprev := r.state // x[i-1]
xnext := (a * xprev) % Mersenne31 // x[i] = (a*x[i-1])%m
r.state = xnext // x[i-1] = x[i]
Ri := float32(xnext) * Mersenne31Inv // convert Ui to Ri
return Ri
}
func (r*PRNGStream) Rand() float32 {
r.state = (uint64_t)*r.state * Multby % 0x7fffffff
return float32(r.state) * Mersenne31Inv
}
A few relevant links:
https://en.wikipedia.org/wiki/Lehmer_random_number_generator
You might use this function to update your x[i+1], instead of the one above,
val = ((state * 1103515245) + 12345) & 0x7fffffff
(basically, different values of a, c, m)
https://www.redhat.com/en/blog/understanding-random-number-generators-and-their-limitations-linux
https://www.iro.umontreal.ca/~lecuyer/myftp/papers/handstat.pdf
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