rand

package
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 Go to latest Published: Jul 3, 2016 License: MIT, BSD-3-Clause Imports: 2 Imported by: 0

Documentation

Overview

Package rand implements pseudo-random number generators.

Random numbers are generated by a Source. Top-level functions, such as Float64 and Int, use a default shared Source that produces a deterministic sequence of values each time a program is run. Use the Seed function to initialize the default Source if different behavior is required for each run. The default Source is safe for concurrent use by multiple goroutines.

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

Example 
package main

import (
	"fmt"
	"math/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: As I see it yes
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. 

package main

import (
	"fmt"
	"math/rand"
	"os"
	"text/tabwriter"
)

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(99))

	// 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())

	// Intn, Int31n, and Int63n 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))

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

Output:

Float32     0.2635776           0.6358173           0.6718283
Float64     0.628605430454327   0.4504798828572669  0.9562755949377957
ExpFloat64  0.3362240648200941  1.4256072328483647  0.24354758816173044
NormFloat64 0.17233959114940064 1.577014951434847   0.04259129641113857
Int31       1501292890          1486668269          182840835
Int63       3546343826724305832 5724354148158589552 5239846799706671610
Uint32      2760229429          296659907           1922395059
Intn(10)    1                   2                   5
Int31n(10)  4                   7                   8
Int63n(10)  7                   6                   3
Perm        [1 4 2 3 0]         [4 2 1 3 0]         [1 2 4 0 3]

Index

Examples

Constants

This section is empty.

Variables

This section is empty.

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 Seed 

func Seed(seed int64)

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).

func Uint32 

func Uint32() uint32

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

Types

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) Seed 

func (r *Rand) Seed(seed int64)

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

func (*Rand) Uint32 

func (r *Rand) Uint32() uint32

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

type Source 

type Source interface {
	Int63() int64
	Seed(seed int64)
}

A Source represents a source of uniformly-distributed pseudo-random int64 values in the range [0, 1<<63).

func NewSource 

func NewSource(seed int64) 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

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