Documentation ¶
Overview ¶
64-bit version of the math/rand package with MersenneTwister support. This is a fork of the original go math/rand package whith the following features:
- Use 64bit sources of random numbers (instead of 63bit) - Add a `Uint64()` method to the Rand type - Add a Mersenne Twister source.
With the exception of the Uint63()->Uint64() conversion for sources, all code that works with the original package does not require any changes to work with this package and produces the same stream of random numbers.
I try to modify the original files of the math/rand package as little as possible (keep the diff short) and apply/port all changes/fixes in Go's original math/rand package to this package.
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.
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.Int63(), r.Int63(), r.Int63()) // 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 5927547564735367388 637072299495207830 4128311955958246186 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 ¶
- 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 Seed(seed uint64)
- func Uint32() uint32
- func Uint64() uint64
- type MT19937_64
- 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) Seed(seed uint64)
- func (r *Rand) Uint32() uint32
- func (r *Rand) 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 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).
Types ¶
type MT19937_64 ¶
type MT19937_64 struct {
// contains filtered or unexported fields
}
Mersenne Twister random number source (MT19937-64) A very popular random number generator, suitable for Monte Carlo simulations.
func NewMersenneTwister ¶
func NewMersenneTwister(seed uint64) *MT19937_64
NewSource returns a new Mersenne Twister Source seeded with the given value.
func (*MT19937_64) Seed ¶
func (mt *MT19937_64) Seed(seed uint64)
Seed uses the provided seed value to initialize the Mersenne Twister to a deterministic state.
func (*MT19937_64) SeedSlice ¶
func (mt *MT19937_64) SeedSlice(seed []uint64)
Seed uses the provided slice of seed values to initialize the Mersenne Twister to a deterministic state.
func (*MT19937_64) Uint64 ¶
func (mt *MT19937_64) Uint64() uint64
Uint64 returns a non-negative pseudo-random 64-bit integer as an uint64.
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) Seed ¶
Seed uses the provided seed value to initialize the generator to a deterministic state.
type Source ¶
A Source represents a source of uniformly-distributed pseudo-random uint64 values in the range [0, 1<<64).