Core.Number
Core.Real
Core.AbstractFloat
Core.Integer
Core.Signed
Core.Unsigned
Core.Float16
Core.Float32
Core.Float64
Base.BigFloat
Core.Bool
Core.Int8
Core.UInt8
Core.Int16
Core.UInt16
Core.Int32
Core.UInt32
Core.Int64
Core.UInt64
Core.Int128
Core.UInt128
Base.BigInt
Base.Complex
Base.Rational
Base.Irrational
Base.bin
Base.hex
Base.dec
Base.oct
Base.base
Base.digits
Base.digits!
Base.bits
Base.parse(::Type, ::Any, ::Any)
Base.tryparse
Base.big
Base.signed
Base.unsigned
Base.float(::Any)
Base.Math.significand
Base.Math.exponent
Base.complex(::Complex)
Base.bswap
Base.hex2bytes
Base.hex2bytes!
Base.bytes2hex
Base.one
Base.oneunit
Base.zero
Base.im
Base.MathConstants.pi
Base.MathConstants.ℯ
Base.MathConstants.catalan
Base.MathConstants.eulergamma
Base.MathConstants.golden
Base.Inf
Base.Inf32
Base.Inf16
Base.NaN
Base.NaN32
Base.NaN16
Base.issubnormal
Base.isfinite
Base.isinf
Base.isnan
Base.iszero
Base.isone
Base.nextfloat
Base.prevfloat
Base.isinteger
Base.isreal
Core.Float32(::Any)
Core.Float64(::Any)
Base.GMP.BigInt(::Any)
Base.MPFR.BigFloat(::Any)
Base.Rounding.rounding
Base.Rounding.setrounding(::Type, ::Any)
Base.Rounding.setrounding(::Function, ::Type, ::RoundingMode)
Base.Rounding.get_zero_subnormals
Base.Rounding.set_zero_subnormals
Base.countones
Base.countzeros
Base.leading_zeros
Base.leading_ones
Base.trailing_zeros
Base.trailing_ones
Base.isodd
Base.iseven
The BigFloat
type implements arbitrary-precision floating-point arithmetic using
the GNU MPFR library.
Base.precision
Base.MPFR.precision(::Type{BigFloat})
Base.MPFR.setprecision
Base.MPFR.BigFloat(x, prec::Int)
BigFloat(x::Union{Integer, AbstractFloat, String}, rounding::RoundingMode)
Base.MPFR.BigFloat(x, prec::Int, rounding::RoundingMode)
Base.MPFR.BigFloat(x::String)
Random number generation in Julia uses the Mersenne Twister library
via MersenneTwister
objects. Julia has a global RNG, which is used by default. Other RNG types
can be plugged in by inheriting the AbstractRNG
type; they can then be used to have multiple
streams of random numbers. Besides MersenneTwister
, Julia also provides the RandomDevice
RNG
type, which is a wrapper over the OS provided entropy.
Most functions related to random generation accept an optional AbstractRNG
as the first argument,
rng
, which defaults to the global one if not provided. Morever, some of them accept optionally
dimension specifications dims...
(which can be given as a tuple) to generate arrays of random
values.
A MersenneTwister
or RandomDevice
RNG can generate random numbers of the following types:
Float16
, Float32
, Float64
, BigFloat
, Bool
,
Int8
, UInt8
, Int16
, UInt16
, Int32
,
UInt32
, Int64
, UInt64
, Int128
, UInt128
,
BigInt
(or complex numbers of those types).
Random floating point numbers are generated uniformly in [0, 1)
. As BigInt
represents
unbounded integers, the interval must be specified (e.g. rand(big(1:6))
).
Base.Random.srand
Base.Random.MersenneTwister
Base.Random.RandomDevice
Base.Random.rand
Base.Random.rand!
Base.Random.bitrand
Base.Random.randn
Base.Random.randn!
Base.Random.randexp
Base.Random.randexp!
Base.Random.randjump