Numbers
Standard Numeric Types
Abstract number types
Core.Number — Type.NumberAbstract supertype for all number types.
Core.Real — Type.Real <: NumberAbstract supertype for all real numbers.
Core.AbstractFloat — Type.AbstractFloat <: RealAbstract supertype for all floating point numbers.
Core.Integer — Type.Integer <: RealAbstract supertype for all integers.
Core.Signed — Type.Signed <: IntegerAbstract supertype for all signed integers.
Core.Unsigned — Type.Unsigned <: IntegerAbstract supertype for all unsigned integers.
Base.AbstractIrrational — Type.AbstractIrrational <: RealNumber type representing an exact irrational value.
Concrete number types
Core.Float16 — Type.Float16 <: AbstractFloat16-bit floating point number type.
Core.Float32 — Type.Float32 <: AbstractFloat32-bit floating point number type.
Core.Float64 — Type.Float64 <: AbstractFloat64-bit floating point number type.
Base.MPFR.BigFloat — Type.BigFloat <: AbstractFloatArbitrary precision floating point number type.
Core.Bool — Type.Bool <: IntegerBoolean type.
Core.Int8 — Type.Int8 <: Signed8-bit signed integer type.
Core.UInt8 — Type.UInt8 <: Unsigned8-bit unsigned integer type.
Core.Int16 — Type.Int16 <: Signed16-bit signed integer type.
Core.UInt16 — Type.UInt16 <: Unsigned16-bit unsigned integer type.
Core.Int32 — Type.Int32 <: Signed32-bit signed integer type.
Core.UInt32 — Type.UInt32 <: Unsigned32-bit unsigned integer type.
Core.Int64 — Type.Int64 <: Signed64-bit signed integer type.
Core.UInt64 — Type.UInt64 <: Unsigned64-bit unsigned integer type.
Core.Int128 — Type.Int128 <: Signed128-bit signed integer type.
Core.UInt128 — Type.UInt128 <: Unsigned128-bit unsigned integer type.
Base.GMP.BigInt — Type.BigInt <: SignedArbitrary precision integer type.
Base.Complex — Type.Complex{T<:Real} <: NumberComplex number type with real and imaginary part of type T.
ComplexF16, ComplexF32 and ComplexF64 are aliases for Complex{Float16}, Complex{Float32} and Complex{Float64} respectively.
Base.Rational — Type.Rational{T<:Integer} <: RealRational number type, with numerator and denominator of type T.
Base.Irrational — Type.Irrational{sym} <: AbstractIrrationalNumber type representing an exact irrational value denoted by the symbol sym.
Data Formats
Base.digits — Function.digits([T<:Integer], n::Integer; base::T = 10, pad::Integer = 1)Return an array with element type T (default Int) of the digits of n in the given base, optionally padded with zeros to a specified size. More significant digits are at higher indices, such that n == sum([digits[k]*base^(k-1) for k=1:length(digits)]).
Examples
julia> digits(10, base = 10)
2-element Array{Int64,1}:
0
1
julia> digits(10, base = 2)
4-element Array{Int64,1}:
0
1
0
1
julia> digits(10, base = 2, pad = 6)
6-element Array{Int64,1}:
0
1
0
1
0
0Base.digits! — Function.digits!(array, n::Integer; base::Integer = 10)Fills an array of the digits of n in the given base. More significant digits are at higher indices. If the array length is insufficient, the least significant digits are filled up to the array length. If the array length is excessive, the excess portion is filled with zeros.
Examples
julia> digits!([2,2,2,2], 10, base = 2)
4-element Array{Int64,1}:
0
1
0
1
julia> digits!([2,2,2,2,2,2], 10, base = 2)
6-element Array{Int64,1}:
0
1
0
1
0
0Base.bitstring — Function.bitstring(n)A string giving the literal bit representation of a number.
Examples
julia> bitstring(4)
"0000000000000000000000000000000000000000000000000000000000000100"
julia> bitstring(2.2)
"0100000000000001100110011001100110011001100110011001100110011010"Base.parse — Function.parse(type, str; base)Parse a string as a number. For Integer types, a base can be specified (the default is 10). For floating-point types, the string is parsed as a decimal floating-point number. Complex types are parsed from decimal strings of the form "R±Iim" as a Complex(R,I) of the requested type; "i" or "j" can also be used instead of "im", and "R" or "Iim" are also permitted. If the string does not contain a valid number, an error is raised.
julia> parse(Int, "1234")
1234
julia> parse(Int, "1234", base = 5)
194
julia> parse(Int, "afc", base = 16)
2812
julia> parse(Float64, "1.2e-3")
0.0012
julia> parse(Complex{Float64}, "3.2e-1 + 4.5im")
0.32 + 4.5imBase.tryparse — Function.Base.big — Function.Base.signed — Function.signed(x)Convert a number to a signed integer. If the argument is unsigned, it is reinterpreted as signed without checking for overflow.
Base.unsigned — Function.unsigned(x) -> UnsignedConvert a number to an unsigned integer. If the argument is signed, it is reinterpreted as unsigned without checking for negative values.
Examples
julia> unsigned(-2)
0xfffffffffffffffe
julia> unsigned(2)
0x0000000000000002
julia> signed(unsigned(-2))
-2Base.float — Method.float(x)Convert a number or array to a floating point data type.
Base.Math.significand — Function.significand(x)Extract the significand(s) (a.k.a. mantissa), in binary representation, of a floating-point number. If x is a non-zero finite number, then the result will be a number of the same type on the interval $[1,2)$. Otherwise x is returned.
Examples
julia> significand(15.2)/15.2
0.125
julia> significand(15.2)*8
15.2Base.Math.exponent — Function.exponent(x) -> IntGet the exponent of a normalized floating-point number.
Base.complex — Method.complex(r, [i])Convert real numbers or arrays to complex. i defaults to zero.
Examples
julia> complex(7)
7 + 0im
julia> complex([1, 2, 3])
3-element Array{Complex{Int64},1}:
1 + 0im
2 + 0im
3 + 0imBase.bswap — Function.bswap(n)Byte-swap an integer. Flip the bits of its binary representation.
Examples
julia> a = bswap(4)
288230376151711744
julia> bswap(a)
4
julia> string(1, base = 2)
"1"
julia> string(bswap(1), base = 2)
"100000000000000000000000000000000000000000000000000000000"Base.hex2bytes — Function.hex2bytes(s::Union{AbstractString,AbstractVector{UInt8}})Given a string or array s of ASCII codes for a sequence of hexadecimal digits, returns a Vector{UInt8} of bytes corresponding to the binary representation: each successive pair of hexadecimal digits in s gives the value of one byte in the return vector.
The length of s must be even, and the returned array has half of the length of s. See also hex2bytes! for an in-place version, and bytes2hex for the inverse.
Examples
julia> s = string(12345, base = 16)
"3039"
julia> hex2bytes(s)
2-element Array{UInt8,1}:
0x30
0x39
julia> a = b"01abEF"
6-element Base.CodeUnits{UInt8,String}:
0x30
0x31
0x61
0x62
0x45
0x46
julia> hex2bytes(a)
3-element Array{UInt8,1}:
0x01
0xab
0xefBase.hex2bytes! — Function.hex2bytes!(d::AbstractVector{UInt8}, s::Union{String,AbstractVector{UInt8}})Convert an array s of bytes representing a hexadecimal string to its binary representation, similar to hex2bytes except that the output is written in-place in d. The length of s must be exactly twice the length of d.
Base.bytes2hex — Function.bytes2hex(bin_arr::Array{UInt8, 1}) -> StringConvert an array of bytes to its hexadecimal representation. All characters are in lower-case.
Examples
julia> a = string(12345, base = 16)
"3039"
julia> b = hex2bytes(a)
2-element Array{UInt8,1}:
0x30
0x39
julia> bytes2hex(b)
"3039"General Number Functions and Constants
Base.one — Function.one(x)
one(T::type)Return a multiplicative identity for x: a value such that one(x)*x == x*one(x) == x. Alternatively one(T) can take a type T, in which case one returns a multiplicative identity for any x of type T.
If possible, one(x) returns a value of the same type as x, and one(T) returns a value of type T. However, this may not be the case for types representing dimensionful quantities (e.g. time in days), since the multiplicative identity must be dimensionless. In that case, one(x) should return an identity value of the same precision (and shape, for matrices) as x.
If you want a quantity that is of the same type as x, or of type T, even if x is dimensionful, use oneunit instead.
julia> one(3.7)
1.0
julia> one(Int)
1
julia> import Dates; one(Dates.Day(1))
1Base.oneunit — Function.oneunit(x::T)
oneunit(T::Type)Returns T(one(x)), where T is either the type of the argument or (if a type is passed) the argument. This differs from one for dimensionful quantities: one is dimensionless (a multiplicative identity) while oneunit is dimensionful (of the same type as x, or of type T).
julia> oneunit(3.7)
1.0
julia> import Dates; oneunit(Dates.Day)
1 dayBase.zero — Function.zero(x)Get the additive identity element for the type of x (x can also specify the type itself).
julia> zero(1)
0
julia> zero(big"2.0")
0.0
julia> zero(rand(2,2))
2×2 Array{Float64,2}:
0.0 0.0
0.0 0.0Base.im — Constant.imThe imaginary unit.
Examples
julia> im * im
-1 + 0imBase.MathConstants.pi — Constant.π
piThe constant pi.
julia> pi
π = 3.1415926535897...Base.MathConstants.ℯ — Constant.ℯ
eThe constant ℯ.
julia> ℯ
ℯ = 2.7182818284590...Base.MathConstants.catalan — Constant.catalanCatalan's constant.
julia> Base.MathConstants.catalan
catalan = 0.9159655941772...Base.MathConstants.eulergamma — Constant.γ
eulergammaEuler's constant.
julia> Base.MathConstants.eulergamma
γ = 0.5772156649015...Base.MathConstants.golden — Constant.φ
goldenThe golden ratio.
julia> Base.MathConstants.golden
φ = 1.6180339887498...Base.Inf — Constant.InfPositive infinity of type Float64.
Base.Inf32 — Constant.Inf32Positive infinity of type Float32.
Base.Inf16 — Constant.Inf16Positive infinity of type Float16.
Base.NaN — Constant.NaNA not-a-number value of type Float64.
Base.NaN32 — Constant.NaN32A not-a-number value of type Float32.
Base.NaN16 — Constant.NaN16A not-a-number value of type Float16.
Base.issubnormal — Function.issubnormal(f) -> BoolTest whether a floating point number is subnormal.
Base.isfinite — Function.isfinite(f) -> BoolTest whether a number is finite.
julia> isfinite(5)
true
julia> isfinite(NaN32)
falseBase.isinf — Function.isinf(f) -> BoolTest whether a number is infinite.
Base.isnan — Function.isnan(f) -> BoolTest whether a floating point number is not a number (NaN).
Base.iszero — Function.iszero(x)Return true if x == zero(x); if x is an array, this checks whether all of the elements of x are zero.
julia> iszero(0.0)
trueBase.isone — Function.isone(x)Return true if x == one(x); if x is an array, this checks whether x is an identity matrix.
julia> isone(1.0)
trueBase.nextfloat — Function.nextfloat(x::AbstractFloat, n::Integer)The result of n iterative applications of nextfloat to x if n >= 0, or -n applications of prevfloat if n < 0.
nextfloat(x::AbstractFloat)Return the smallest floating point number y of the same type as x such x < y. If no such y exists (e.g. if x is Inf or NaN), then return x.
Base.prevfloat — Function.prevfloat(x::AbstractFloat)Return the largest floating point number y of the same type as x such y < x. If no such y exists (e.g. if x is -Inf or NaN), then return x.
Base.isinteger — Function.isinteger(x) -> BoolTest whether x is numerically equal to some integer.
julia> isinteger(4.0)
trueBase.isreal — Function.isreal(x) -> BoolTest whether x or all its elements are numerically equal to some real number including infinities and NaNs. isreal(x) is true if isequal(x, real(x)) is true.
Examples
julia> isreal(5.)
true
julia> isreal(Inf + 0im)
true
julia> isreal([4.; complex(0,1)])
falseCore.Float32 — Method.Float32(x [, mode::RoundingMode])Create a Float32 from x. If x is not exactly representable then mode determines how x is rounded.
Examples
julia> Float32(1/3, RoundDown)
0.3333333f0
julia> Float32(1/3, RoundUp)
0.33333334f0See RoundingMode for available rounding modes.
Core.Float64 — Method.Float64(x [, mode::RoundingMode])Create a Float64 from x. If x is not exactly representable then mode determines how x is rounded.
Examples
julia> Float64(pi, RoundDown)
3.141592653589793
julia> Float64(pi, RoundUp)
3.1415926535897936See RoundingMode for available rounding modes.
Base.GMP.BigInt — Method.BigInt(x)Create an arbitrary precision integer. x may be an Int (or anything that can be converted to an Int). The usual mathematical operators are defined for this type, and results are promoted to a BigInt.
Instances can be constructed from strings via parse, or using the big string literal.
julia> parse(BigInt, "42")
42
julia> big"313"
313Base.MPFR.BigFloat — Method.BigFloat(x)Create an arbitrary precision floating point number. x may be an Integer, a Float64 or a BigInt. The usual mathematical operators are defined for this type, and results are promoted to a BigFloat.
Note that because decimal literals are converted to floating point numbers when parsed, BigFloat(2.1) may not yield what you expect. You may instead prefer to initialize constants from strings via parse, or using the big string literal.
julia> BigFloat(2.1)
2.100000000000000088817841970012523233890533447265625
julia> big"2.1"
2.099999999999999999999999999999999999999999999999999999999999999999999999999986Base.Rounding.rounding — Function.Base.Rounding.setrounding — Method.setrounding(T, mode)Set the rounding mode of floating point type T, controlling the rounding of basic arithmetic functions (+, -, *, / and sqrt) and type conversion. Other numerical functions may give incorrect or invalid values when using rounding modes other than the default RoundNearest.
Note that this may affect other types, for instance changing the rounding mode of Float64 will change the rounding mode of Float32. See RoundingMode for available modes.
This feature is still experimental, and may give unexpected or incorrect values.
Base.Rounding.setrounding — Method.setrounding(f::Function, T, mode)Change the rounding mode of floating point type T for the duration of f. It is logically equivalent to:
old = rounding(T)
setrounding(T, mode)
f()
setrounding(T, old)See RoundingMode for available rounding modes.
This feature is still experimental, and may give unexpected or incorrect values. A known problem is the interaction with compiler optimisations, e.g.
julia> setrounding(Float64,RoundDown) do
1.1 + 0.1
end
1.2000000000000002Here the compiler is constant folding, that is evaluating a known constant expression at compile time, however the rounding mode is only changed at runtime, so this is not reflected in the function result. This can be avoided by moving constants outside the expression, e.g.
julia> x = 1.1; y = 0.1;
julia> setrounding(Float64,RoundDown) do
x + y
end
1.2Base.Rounding.get_zero_subnormals — Function.get_zero_subnormals() -> BoolReturns false if operations on subnormal floating-point values ("denormals") obey rules for IEEE arithmetic, and true if they might be converted to zeros.
Base.Rounding.set_zero_subnormals — Function.set_zero_subnormals(yes::Bool) -> BoolIf yes is false, subsequent floating-point operations follow rules for IEEE arithmetic on subnormal values ("denormals"). Otherwise, floating-point operations are permitted (but not required) to convert subnormal inputs or outputs to zero. Returns true unless yes==true but the hardware does not support zeroing of subnormal numbers.
set_zero_subnormals(true) can speed up some computations on some hardware. However, it can break identities such as (x-y==0) == (x==y).
Integers
Base.count_ones — Function.count_ones(x::Integer) -> IntegerNumber of ones in the binary representation of x.
julia> count_ones(7)
3Base.count_zeros — Function.count_zeros(x::Integer) -> IntegerNumber of zeros in the binary representation of x.
julia> count_zeros(Int32(2 ^ 16 - 1))
16Base.leading_zeros — Function.leading_zeros(x::Integer) -> IntegerNumber of zeros leading the binary representation of x.
julia> leading_zeros(Int32(1))
31Base.leading_ones — Function.leading_ones(x::Integer) -> IntegerNumber of ones leading the binary representation of x.
julia> leading_ones(UInt32(2 ^ 32 - 2))
31Base.trailing_zeros — Function.trailing_zeros(x::Integer) -> IntegerNumber of zeros trailing the binary representation of x.
julia> trailing_zeros(2)
1Base.trailing_ones — Function.trailing_ones(x::Integer) -> IntegerNumber of ones trailing the binary representation of x.
julia> trailing_ones(3)
2Base.isodd — Function.isodd(x::Integer) -> BoolReturn true if x is odd (that is, not divisible by 2), and false otherwise.
julia> isodd(9)
true
julia> isodd(10)
falseBase.iseven — Function.iseven(x::Integer) -> BoolReturn true is x is even (that is, divisible by 2), and false otherwise.
julia> iseven(9)
false
julia> iseven(10)
trueBigFloats
The BigFloat type implements arbitrary-precision floating-point arithmetic using the GNU MPFR library.
Base.precision — Function.precision(num::AbstractFloat)Get the precision of a floating point number, as defined by the effective number of bits in the mantissa.
Base.precision — Method.precision(BigFloat)Get the precision (in bits) currently used for BigFloat arithmetic.
Base.MPFR.setprecision — Function.setprecision([T=BigFloat,] precision::Int)Set the precision (in bits) to be used for T arithmetic.
setprecision(f::Function, [T=BigFloat,] precision::Integer)Change the T arithmetic precision (in bits) for the duration of f. It is logically equivalent to:
old = precision(BigFloat)
setprecision(BigFloat, precision)
f()
setprecision(BigFloat, old)Often used as setprecision(T, precision) do ... end
Base.MPFR.BigFloat — Method.BigFloat(x, prec::Int)Create a representation of x as a BigFloat with precision prec.
Base.MPFR.BigFloat — Method.BigFloat(x, rounding::RoundingMode)Create a representation of x as a BigFloat with the current global precision and rounding mode rounding.
Base.MPFR.BigFloat — Method.BigFloat(x, prec::Int, rounding::RoundingMode)Create a representation of x as a BigFloat with precision prec and rounding mode rounding.
Base.MPFR.BigFloat — Method.BigFloat(x::String)Create a representation of the string x as a BigFloat.