package rand

Import Path
	math/rand (on go.dev)

Dependency Relation
	imports 5 packages, and imported by 7 packages

Involved Source Files

	    exp.go
	    normal.go
	  d rand.go
		Package rand implements pseudo-random number generators suitable for tasks
		such as simulation, but it should not be used for security-sensitive work.
		
		Random numbers are generated by a [Source], usually wrapped in a [Rand].
		Both types should be used by a single goroutine at a time: sharing among
		multiple goroutines requires some kind of synchronization.
		
		Top-level functions, such as [Float64] and [Int],
		are safe for concurrent use by multiple goroutines.
		
		This package's outputs might be easily predictable regardless of how it's
		seeded. For random numbers suitable for security-sensitive work, see the
		crypto/rand package.

	    rng.go
	    zipf.go
Code Examples

	
		package main
		
		import (
			"fmt"
			"math/rand"
		)
		
		func main() {
			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))])
		}

	Intn
		package main
		
		import (
			"fmt"
			"math/rand"
		)
		
		func main() {
			fmt.Println(rand.Intn(100))
			fmt.Println(rand.Intn(100))
			fmt.Println(rand.Intn(100))
		}

	Perm
		package main
		
		import (
			"fmt"
			"math/rand"
		)
		
		func main() {
			for _, value := range rand.Perm(3) {
				fmt.Println(value)
			}
		
		}

	Shuffle
		package main
		
		import (
			"fmt"
			"math/rand"
			"strings"
		)
		
		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)
		}

	Shuffle_slicesInUnison
		package main
		
		import (
			"fmt"
			"math/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])
			}
		}

	_rand
		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 any) {
				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))
		}


Package-Level Type Names (total 4)

	/* sort by: alphabet | popularity */
	 type Rand (struct)
		A Rand is a source of random numbers.

		Methods (total 16)
			(*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

			(*Rand) Float32() float32
				Float32 returns, as a float32, a pseudo-random number in the half-open interval [0.0,1.0).

			(*Rand) Float64() float64
				Float64 returns, as a float64, a pseudo-random number in the half-open interval [0.0,1.0).

			(*Rand) Int() int
				Int returns a non-negative pseudo-random int.

			(*Rand) Int31() int32
				Int31 returns a non-negative pseudo-random 31-bit integer as an int32.

			(*Rand) Int31n(n int32) int32
				Int31n returns, as an int32, a non-negative pseudo-random number in the half-open interval [0,n).
				It panics if n <= 0.

			(*Rand) Int63() int64
				Int63 returns a non-negative pseudo-random 63-bit integer as an int64.

			(*Rand) Int63n(n int64) int64
				Int63n returns, as an int64, a non-negative pseudo-random number in the half-open interval [0,n).
				It panics if n <= 0.

			(*Rand) Intn(n int) int
				Intn returns, as an int, a non-negative pseudo-random number in the half-open interval [0,n).
				It panics if n <= 0.

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

			(*Rand) Perm(n int) []int
				Perm returns, as a slice of n ints, a pseudo-random permutation of the integers
				in the half-open interval [0,n).

			(*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.

			(*Rand) Seed(seed int64)
				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.

			(*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.

			(*Rand) Uint32() uint32
				Uint32 returns a pseudo-random 32-bit value as a uint32.

			(*Rand) Uint64() uint64
				Uint64 returns a pseudo-random 64-bit value as a uint64.

		Implements (at least 4)
			*Rand : Source
			*Rand : Source64
			*Rand : math/rand/v2.Source
			*Rand : io.Reader
		As Outputs Of (at least one exported)
			func New(src Source) *Rand
		As Inputs Of (at least 4)
			func NewZipf(r *Rand, s float64, v float64, imax uint64) *Zipf
			func math/big.(*Int).Rand(rnd *Rand, n *big.Int) *big.Int
			func testing/quick.Value(t reflect.Type, rand *Rand) (value reflect.Value, ok bool)
			func testing/quick.Generator.Generate(rand *Rand, size int) reflect.Value

	 type Source (interface)
		A Source represents a source of uniformly-distributed
		pseudo-random int64 values in the range [0, 1<<63).
		
		A Source is not safe for concurrent use by multiple goroutines.

		Methods (total 2)
			( Source) Int63() int64
			( Source) Seed(seed int64)
		Implemented By (at least 2)
			*Rand
			 Source64 (interface)
		As Outputs Of (at least one exported)
			func NewSource(seed int64) Source
		As Inputs Of (at least one exported)
			func New(src Source) *Rand

	 type Source64 (interface)
		A Source64 is a [Source] that can also generate
		uniformly-distributed pseudo-random uint64 values in
		the range [0, 1<<64) directly.
		If a [Rand] r's underlying [Source] s implements Source64,
		then r.Uint64 returns the result of one call to s.Uint64
		instead of making two calls to s.Int63.

		Methods (total 3)
			( Source64) Int63() int64
			( Source64) Seed(seed int64)
			( Source64) Uint64() uint64
		Implemented By (at least one exported)
			*Rand
		Implements (at least 2)
			 Source64 : Source
			 Source64 : math/rand/v2.Source

	 type Zipf (struct)
		A Zipf generates Zipf distributed variates.

		Methods (only one)
			(*Zipf) Uint64() uint64
				Uint64 returns a value drawn from the [Zipf] distribution described
				by the [Zipf] object.

		Implements (at least one exported)
			*Zipf : math/rand/v2.Source
		As Outputs Of (at least one exported)
			func NewZipf(r *Rand, s float64, v float64, imax uint64) *Zipf


Package-Level Functions (total 19)

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

	 func Float64() float64
		Float64 returns, as a float64, a pseudo-random number in the half-open interval [0.0,1.0)
		from the default [Source].

	 func Int() int
		Int returns a non-negative pseudo-random int from the default [Source].

	 func Int31() int32
		Int31 returns a non-negative pseudo-random 31-bit integer as an int32
		from the default [Source].

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

	 func Int63() int64
		Int63 returns a non-negative pseudo-random 63-bit integer as an int64
		from the default [Source].

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

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

	 func New(src Source) *Rand
		New returns a new [Rand] that uses random values from src
		to generate other random values.

	 func NewSource(seed int64) Source
		NewSource returns a new pseudo-random [Source] seeded with the given value.
		Unlike the default [Source] used by top-level functions, this source is not
		safe for concurrent use by multiple goroutines.
		The returned [Source] implements [Source64].

	 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 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(n int) []int
		Perm returns, as a slice of n ints, a pseudo-random permutation of the integers
		in the half-open interval [0,n) from the default [Source].

	 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.
		
		Deprecated: For almost all use cases, [crypto/rand.Read] is more appropriate.
		If a deterministic source is required, use [math/rand/v2.ChaCha8.Read].

	 func Seed(seed int64)
		Seed uses the provided seed value to initialize the default Source to a
		deterministic state. Seed values that have the same remainder when
		divided by 2³¹-1 generate the same pseudo-random sequence.
		Seed, unlike the [Rand.Seed] method, is safe for concurrent use.
		
		If Seed is not called, the generator is seeded randomly at program startup.
		
		Prior to Go 1.20, the generator was seeded like Seed(1) at program startup.
		To force the old behavior, call Seed(1) at program startup.
		Alternately, set GODEBUG=randautoseed=0 in the environment
		before making any calls to functions in this package.
		
		Deprecated: As of Go 1.20 there is no reason to call Seed with
		a random value. Programs that call Seed with a known value to get
		a specific sequence of results should use New(NewSource(seed)) to
		obtain a local random generator.
		
		As of Go 1.24 [Seed] is a no-op. To restore the previous behavior set
		GODEBUG=randseednop=0.

	 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.

	 func Uint32() uint32
		Uint32 returns a pseudo-random 32-bit value as a uint32
		from the default [Source].

	 func Uint64() uint64
		Uint64 returns a pseudo-random 64-bit value as a uint64
		from the default [Source].

The pages are generated with Golds v0.7.7-preview. (GOOS=linux GOARCH=amd64)
Golds is a Go 101 project developed by Tapir Liu.
PR and bug reports are welcome and can be submitted to the issue list.
Please follow @zigo_101 (reachable from the left QR code) to get the latest news of Golds.