package rand

import "golang.org/x/exp/rand"

Package rand implements pseudo-random number generators.

For random numbers suitable for security-sensitive work, see the crypto/rand package.

Deprecated: use the math/rand/v2 package instead. This package is scheduled to be tagged and deleted, per https://go.dev/issue/61716.

Example

Code:play  

package main

import (
	"fmt"

	"golang.org/x/exp/rand"
)

func main() {
	rand.Seed(42) // Try changing this number!
	answers := []string{
		"It is certain",
		"It is decidedly so",
		"Without a doubt",
		"Yes definitely",
		"You may rely on it",
		"As I see it yes",
		"Most likely",
		"Outlook good",
		"Yes",
		"Signs point to yes",
		"Reply hazy try again",
		"Ask again later",
		"Better not tell you now",
		"Cannot predict now",
		"Concentrate and ask again",
		"Don't count on it",
		"My reply is no",
		"My sources say no",
		"Outlook not so good",
		"Very doubtful",
	}
	fmt.Println("Magic 8-Ball says:", answers[rand.Intn(len(answers))])
}

Output:

Magic 8-Ball says: Most likely
Example (Rand)

This example shows the use of each of the methods on a *Rand. The use of the global functions is the same, without the receiver.

Code:play  

package main

import (
	"fmt"
	"os"
	"text/tabwriter"

	"golang.org/x/exp/rand"
)

func main() {
	// Create and seed the generator.
	// Typically a non-fixed seed should be used, such as time.Now().UnixNano().
	// Using a fixed seed will produce the same output on every run.
	r := rand.New(rand.NewSource(1234))

	// The tabwriter here helps us generate aligned output.
	w := tabwriter.NewWriter(os.Stdout, 1, 1, 1, ' ', 0)
	defer w.Flush()
	show := func(name string, v1, v2, v3 interface{}) {
		fmt.Fprintf(w, "%s\t%v\t%v\t%v\n", name, v1, v2, v3)
	}

	// Float32 and Float64 values are in [0, 1).
	show("Float32", r.Float32(), r.Float32(), r.Float32())
	show("Float64", r.Float64(), r.Float64(), r.Float64())

	// ExpFloat64 values have an average of 1 but decay exponentially.
	show("ExpFloat64", r.ExpFloat64(), r.ExpFloat64(), r.ExpFloat64())

	// NormFloat64 values have an average of 0 and a standard deviation of 1.
	show("NormFloat64", r.NormFloat64(), r.NormFloat64(), r.NormFloat64())

	// Int31, Int63, and Uint32 generate values of the given width.
	// The Int method (not shown) is like either Int31 or Int63
	// depending on the size of 'int'.
	show("Int31", r.Int31(), r.Int31(), r.Int31())
	show("Int63", r.Int63(), r.Int63(), r.Int63())
	show("Uint32", r.Uint32(), r.Uint32(), r.Uint32())
	show("Uint64", r.Uint64(), r.Uint64(), r.Uint64())

	// Intn, Int31n, Int63n and Uint64n limit their output to be < n.
	// They do so more carefully than using r.Int()%n.
	show("Intn(10)", r.Intn(10), r.Intn(10), r.Intn(10))
	show("Int31n(10)", r.Int31n(10), r.Int31n(10), r.Int31n(10))
	show("Int63n(10)", r.Int63n(10), r.Int63n(10), r.Int63n(10))
	show("Uint64n(10)", r.Uint64n(10), r.Uint64n(10), r.Uint64n(10))

	// Perm generates a random permutation of the numbers [0, n).
	show("Perm", r.Perm(5), r.Perm(5), r.Perm(5))
}

Output:

Float32     0.030719291          0.47512934           0.031019364
Float64     0.6906635660087743   0.9898818576905045   0.2683634639782333
ExpFloat64  1.24979080914592     0.3451975160045876   0.5456817760595064
NormFloat64 0.879221333732727    -0.01508980368383761 -1.962250558270421
Int31       2043816560           1870670250           1334960143
Int63       7860766611810691572  1466711535823962239  3836585920276818709
Uint32      2051241581           751073909            1353986074
Uint64      10802154207635843641 14398820303406316826 11052107950969057042
Intn(10)    3                    0                    1
Int31n(10)  3                    8                    1
Int63n(10)  4                    6                    0
Uint64n(10) 2                    9                    4
Perm        [1 3 4 0 2]          [2 4 0 3 1]          [3 2 0 4 1]

Index

Examples

Functions

func ExpFloat64 

func ExpFloat64() float64

ExpFloat64 returns an exponentially distributed float64 in the range (0, +math.MaxFloat64] with an exponential distribution whose rate parameter (lambda) is 1 and whose mean is 1/lambda (1) from the default Source. To produce a distribution with a different rate parameter, callers can adjust the output using: 

sample = ExpFloat64() / desiredRateParameter

func Float32 

func Float32() float32

Float32 returns, as a float32, a pseudo-random number in [0.0,1.0) from the default Source.

func Float64 

func Float64() float64

Float64 returns, as a float64, a pseudo-random number in [0.0,1.0) from the default Source.

func Int 

func Int() int

Int returns a non-negative pseudo-random int from the default Source.

func Int31 

func Int31() int32

Int31 returns a non-negative pseudo-random 31-bit integer as an int32 from the default Source.

func Int31n 

func Int31n(n int32) int32

Int31n returns, as an int32, a non-negative pseudo-random number in [0,n) from the default Source. It panics if n <= 0.

func Int63 

func Int63() int64

Int63 returns a non-negative pseudo-random 63-bit integer as an int64 from the default Source.

func Int63n 

func Int63n(n int64) int64

Int63n returns, as an int64, a non-negative pseudo-random number in [0,n) from the default Source. It panics if n <= 0.

func Intn 

func Intn(n int) int

Intn returns, as an int, a non-negative pseudo-random number in [0,n) from the default Source. It panics if n <= 0.

func NormFloat64 

func NormFloat64() float64

NormFloat64 returns a normally distributed float64 in the range [-math.MaxFloat64, +math.MaxFloat64] with standard normal distribution (mean = 0, stddev = 1) from the default Source. To produce a different normal distribution, callers can adjust the output using: 

sample = NormFloat64() * desiredStdDev + desiredMean

func Perm 

func Perm(n int) []int

Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n) from the default Source.

func Read 

func Read(p []byte) (n int, err error)

Read generates len(p) random bytes from the default Source and writes them into p. It always returns len(p) and a nil error. Read, unlike the Rand.Read method, is safe for concurrent use.

func Seed 

func Seed(seed uint64)

Seed uses the provided seed value to initialize the default Source to a deterministic state. If Seed is not called, the generator behaves as if seeded by Seed(1). Seed, unlike the Rand.Seed method, is safe for concurrent use.

func Shuffle 

func Shuffle(n int, swap func(i, j int))

Shuffle pseudo-randomizes the order of elements using the default Source. n is the number of elements. Shuffle panics if n < 0. swap swaps the elements with indexes i and j.

Example

Code:play  

package main

import (
	"fmt"
	"strings"

	"golang.org/x/exp/rand"
)

func main() {
	words := strings.Fields("ink runs from the corners of my mouth")
	rand.Shuffle(len(words), func(i, j int) {
		words[i], words[j] = words[j], words[i]
	})
	fmt.Println(words)

}

Output:

[ink corners of from mouth runs the my]
Example (SlicesInUnison)

Code:play  

package main

import (
	"fmt"

	"golang.org/x/exp/rand"
)

func main() {
	numbers := []byte("12345")
	letters := []byte("ABCDE")
	// Shuffle numbers, swapping corresponding entries in letters at the same time.
	rand.Shuffle(len(numbers), func(i, j int) {
		numbers[i], numbers[j] = numbers[j], numbers[i]
		letters[i], letters[j] = letters[j], letters[i]
	})
	for i := range numbers {
		fmt.Printf("%c: %c\n", letters[i], numbers[i])
	}

}

Output:

D: 4
A: 1
E: 5
B: 2
C: 3

func Uint32 

func Uint32() uint32

Uint32 returns a pseudo-random 32-bit value as a uint32 from the default Source.

func Uint64 

func Uint64() uint64

Uint64 returns a pseudo-random 64-bit value as a uint64 from the default Source.

Types

type LockedSource 

type LockedSource struct {
	// contains filtered or unexported fields
}

LockedSource is an implementation of Source that is concurrency-safe. A Rand using a LockedSource is safe for concurrent use.

The zero value of LockedSource is valid, but should be seeded before use.

Example

Code:play  

package main

import (
	"fmt"

	"golang.org/x/exp/rand"
)

func main() {
	r := rand.New(new(rand.LockedSource))
	r.Seed(42) // Try changing this number!
	answers := []string{
		"It is certain",
		"It is decidedly so",
		"Without a doubt",
		"Yes definitely",
		"You may rely on it",
		"As I see it yes",
		"Most likely",
		"Outlook good",
		"Yes",
		"Signs point to yes",
		"Reply hazy try again",
		"Ask again later",
		"Better not tell you now",
		"Cannot predict now",
		"Concentrate and ask again",
		"Don't count on it",
		"My reply is no",
		"My sources say no",
		"Outlook not so good",
		"Very doubtful",
	}
	fmt.Println("Magic 8-Ball says:", answers[r.Intn(len(answers))])
}

Output:

Magic 8-Ball says: Most likely

func (*LockedSource) Read 

func (s *LockedSource) Read(p []byte, readVal *uint64, readPos *int8) (n int, err error)

Read implements Read for a LockedSource.

func (*LockedSource) Seed 

func (s *LockedSource) Seed(seed uint64)

func (*LockedSource) Uint64 

func (s *LockedSource) Uint64() (n uint64)

type PCGSource 

type PCGSource struct {
	// contains filtered or unexported fields
}

PCGSource is an implementation of a 64-bit permuted congruential generator as defined in 

PCG: A Family of Simple Fast Space-Efficient Statistically Good
Algorithms for Random Number Generation
Melissa E. O’Neill, Harvey Mudd College
http://www.pcg-random.org/pdf/toms-oneill-pcg-family-v1.02.pdf

The generator here is the congruential generator PCG XSL RR 128/64 (LCG) as found in the software available at http://www.pcg-random.org/. It has period 2^128 with 128 bits of state, producing 64-bit values. Is state is represented by two uint64 words.

func (*PCGSource) MarshalBinary 

func (pcg *PCGSource) MarshalBinary() ([]byte, error)

MarshalBinary returns the binary representation of the current state of the generator.

func (*PCGSource) Seed 

func (pcg *PCGSource) Seed(seed uint64)

Seed uses the provided seed value to initialize the generator to a deterministic state.

func (*PCGSource) Uint64 

func (pcg *PCGSource) Uint64() uint64

Uint64 returns a pseudo-random 64-bit unsigned integer as a uint64.

func (*PCGSource) UnmarshalBinary 

func (pcg *PCGSource) UnmarshalBinary(data []byte) error

UnmarshalBinary sets the state of the generator to the state represented in data.

type Rand 

type Rand struct {
	// contains filtered or unexported fields
}

A Rand is a source of random numbers.

func New 

func New(src Source) *Rand

New returns a new Rand that uses random values from src to generate other random values.

func (*Rand) ExpFloat64 

func (r *Rand) ExpFloat64() float64

ExpFloat64 returns an exponentially distributed float64 in the range (0, +math.MaxFloat64] with an exponential distribution whose rate parameter (lambda) is 1 and whose mean is 1/lambda (1). To produce a distribution with a different rate parameter, callers can adjust the output using: 

sample = ExpFloat64() / desiredRateParameter

func (*Rand) Float32 

func (r *Rand) Float32() float32

Float32 returns, as a float32, a pseudo-random number in [0.0,1.0).

func (*Rand) Float64 

func (r *Rand) Float64() float64

Float64 returns, as a float64, a pseudo-random number in [0.0,1.0).

func (*Rand) Int 

func (r *Rand) Int() int

Int returns a non-negative pseudo-random int.

func (*Rand) Int31 

func (r *Rand) Int31() int32

Int31 returns a non-negative pseudo-random 31-bit integer as an int32.

func (*Rand) Int31n 

func (r *Rand) Int31n(n int32) int32

Int31n returns, as an int32, a non-negative pseudo-random number in [0,n). It panics if n <= 0.

func (*Rand) Int63 

func (r *Rand) Int63() int64

Int63 returns a non-negative pseudo-random 63-bit integer as an int64.

func (*Rand) Int63n 

func (r *Rand) Int63n(n int64) int64

Int63n returns, as an int64, a non-negative pseudo-random number in [0,n). It panics if n <= 0.

func (*Rand) Intn 

func (r *Rand) Intn(n int) int

Intn returns, as an int, a non-negative pseudo-random number in [0,n). It panics if n <= 0.

func (*Rand) NormFloat64 

func (r *Rand) NormFloat64() float64

NormFloat64 returns a normally distributed float64 in the range [-math.MaxFloat64, +math.MaxFloat64] with standard normal distribution (mean = 0, stddev = 1). To produce a different normal distribution, callers can adjust the output using: 

sample = NormFloat64() * desiredStdDev + desiredMean

func (*Rand) Perm 

func (r *Rand) Perm(n int) []int

Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n).

func (*Rand) Read 

func (r *Rand) Read(p []byte) (n int, err error)

Read generates len(p) random bytes and writes them into p. It always returns len(p) and a nil error. Read should not be called concurrently with any other Rand method unless the underlying source is a LockedSource.

func (*Rand) Seed 

func (r *Rand) Seed(seed uint64)

Seed uses the provided seed value to initialize the generator to a deterministic state. Seed should not be called concurrently with any other Rand method.

func (*Rand) Shuffle 

func (r *Rand) Shuffle(n int, swap func(i, j int))

Shuffle pseudo-randomizes the order of elements. n is the number of elements. Shuffle panics if n < 0. swap swaps the elements with indexes i and j.

func (*Rand) Uint32 

func (r *Rand) Uint32() uint32

Uint32 returns a pseudo-random 32-bit value as a uint32.

func (*Rand) Uint64 

func (r *Rand) Uint64() uint64

Uint64 returns a pseudo-random 64-bit integer as a uint64.

func (*Rand) Uint64n 

func (r *Rand) Uint64n(n uint64) uint64

Uint64n returns, as a uint64, a pseudo-random number in [0,n). It is guaranteed more uniform than taking a Source value mod n for any n that is not a power of 2.

type Source 

type Source interface {
	Uint64() uint64
	Seed(seed uint64)
}

A Source represents a source of uniformly-distributed pseudo-random int64 values in the range [0, 1<<64).

func NewSource 

func NewSource(seed uint64) Source

NewSource returns a new pseudo-random Source seeded with the given value.

type Zipf 

type Zipf struct {
	// contains filtered or unexported fields
}

A Zipf generates Zipf distributed variates.

func NewZipf 

func NewZipf(r *Rand, s float64, v float64, imax uint64) *Zipf

NewZipf returns a Zipf variate generator. The generator generates values k ∈ [0, imax] such that P(k) is proportional to (v + k) ** (-s). Requirements: s > 1 and v >= 1.

func (*Zipf) Uint64 

func (z *Zipf) Uint64() uint64

Uint64 returns a value drawn from the Zipf distribution described by the Zipf object.

Source Files

exp.go normal.go rand.go rng.go zipf.go

Version
v0.0.0-20250218142911-aa4b98e5adaa (latest)
Published
Feb 18, 2025
Platform
linux/amd64
Imports
5 packages
Last checked
2 days ago –

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