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RandomNumbers

Index

Common Functions

Public

# RandomNumbers.RandomNumbers — Module.

Main module for RandomNumbers.jl – a random number generator package for Julia Language.

This module exports two types and four submodules:

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# RandomNumbers.AbstractRNG — Type.

AbstractRNG{T} <: Random.AbstractRNG

The abstract type of Random Number Generators. T indicates the original output type of a RNG.

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# RandomNumbers.WrappedRNG — Type.

WrappedRNG{R, T1, T2} <: AbstractRNG{T2}
WrappedRNG(base_rng, T2)
WrappedRNG(R, T2, args...)

Wrap a RNG which originally provides output in T1 into a RNG that provides output in T2.

Examples

julia> r = Xorshifts.Xorshift128Star(123);

julia> RandomNumbers.output_type(r)
UInt64

julia> r1 = WrappedRNG(r, UInt32);

julia> RandomNumbers.output_type(r1)
UInt32

julia> r2 = WrappedRNG(Xorshifts.Xorshift128Star, UInt32, 123);

julia> RandomNumbers.output_type(r2)
UInt32

julia> @Test.test rand(r1, UInt32, 3) == rand(r2, UInt32, 3)
Test Passed

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# RandomNumbers.output_type — Method.

Get the original output type of a RNG.

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# RandomNumbers.randfloat — Method.

Random number generator for Float16 in [0,1) that samples from all 15360 float16s in that range.

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# RandomNumbers.randfloat — Method.

Random number generator for Float32 in [0,1) that samples from 42*2^23 float32s in [0,1) compared to 2^23 for rand(Float32).

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# RandomNumbers.randfloat — Method.

Random number generator for Float64 in [0,1) that samples from 64*2^52 floats compared to 2^52 for rand(Float64).

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# RandomNumbers.seed_type — Method.

Get the default seed type of a RNG.

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Internal

<a id='RandomNumbers.gen_seed-Union{Tuple{Type{T}}, Tuple{T}} where T<:Number' href='#RandomNumbers.gen_seed-Union{Tuple{Type{T}}, Tuple{T}} where T<:Number'># RandomNumbers.gen_seed — Method.

gen_seed(T[, n])

Generate a tuple of n truly random numbers in type T. If n is missing, return only one number. The "truly" random numbers are provided by the random device of system. See Random.RandomDevice.

Examples

julia> RandomNumbers.gen_seed(UInt64, 2)  # The output should probably be different on different computers.
(0x26aa3fe5e306f725,0x7b9dc3c227d8acc9)

julia> RandomNumbers.gen_seed(UInt32)
0x9ba60fdc

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