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, a LockedSource, is safe for concurrent use by multiple goroutines, but Sources created by NewSource are not. However, Sources are small and it is reasonable to have a separate Source for each goroutine, seeded differently, to avoid locking.
For random numbers suitable for security-sensitive work, see the crypto/rand package.
Example ¶
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.
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 ¶
- func ExpFloat64() float64
- func Float32() float32
- func Float64() float64
- func Int() int
- func Int31() int32
- func Int31n(n int32) int32
- func Int63() int64
- func Int63n(n int64) int64
- func Intn(n int) int
- func NormFloat64() float64
- func Perm(n int) []int
- func Read(p []byte) (n int, err error)
- func Seed(seed uint64)
- func Shuffle(n int, swap func(i, j int))
- func Uint32() uint32
- func Uint64() uint64
- type LockedSource
- type PCGSource
- type Rand
- func (r *Rand) ExpFloat64() float64
- func (r *Rand) Float32() float32
- func (r *Rand) Float64() float64
- func (r *Rand) Int() int
- func (r *Rand) Int31() int32
- func (r *Rand) Int31n(n int32) int32
- func (r *Rand) Int63() int64
- func (r *Rand) Int63n(n int64) int64
- func (r *Rand) Intn(n int) int
- func (r *Rand) NormFloat64() float64
- func (r *Rand) Perm(n int) []int
- func (r *Rand) Read(p []byte) (n int, err error)
- func (r *Rand) Seed(seed uint64)
- func (r *Rand) Shuffle(n int, swap func(i, j int))
- func (r *Rand) Uint32() uint32
- func (r *Rand) Uint64() uint64
- func (r *Rand) Uint64n(n uint64) uint64
- type Source
- type Zipf
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 Int31 ¶
func Int31() int32
Int31 returns a non-negative pseudo-random 31-bit integer as an int32 from the default Source.
func Int31n ¶
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 ¶
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 ¶
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 ¶
Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n) from the default Source.
func Read ¶
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 ¶
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 ¶
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) ¶
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
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 ¶
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) 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 ¶
MarshalBinary returns the binary representation of the current state of the generator.
func (*PCGSource) Seed ¶
Seed uses the provided seed value to initialize the generator to a deterministic state.
func (*PCGSource) UnmarshalBinary ¶
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 (*Rand) ExpFloat64 ¶
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) Int31n ¶
Int31n returns, as an int32, a non-negative pseudo-random number in [0,n). It panics if n <= 0.
func (*Rand) Int63n ¶
Int63n returns, as an int64, a non-negative pseudo-random number in [0,n). It panics if n <= 0.
func (*Rand) Intn ¶
Intn returns, as an int, a non-negative pseudo-random number in [0,n). It panics if n <= 0.
func (*Rand) NormFloat64 ¶
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 ¶
Perm returns, as a slice of n ints, a pseudo-random permutation of the integers [0,n).
func (*Rand) Read ¶
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 ¶
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 ¶
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.
type Source ¶
A Source represents a source of uniformly-distributed pseudo-random int64 values in the range [0, 1<<64).
type Zipf ¶
type Zipf struct {
// contains filtered or unexported fields
}
A Zipf generates Zipf distributed variates.