Numbers
Standard Numeric Types
A type tree for all subtypes of Number in Base is shown below. Abstract types have been marked, the rest are concrete types.
Number (Abstract Type)
├─ Complex
└─ Real (Abstract Type)
├─ AbstractFloat (Abstract Type)
│ ├─ Float16
│ ├─ Float32
│ ├─ Float64
│ └─ BigFloat
├─ Integer (Abstract Type)
│ ├─ Bool
│ ├─ Signed (Abstract Type)
│ │ ├─ Int8
│ │ ├─ Int16
│ │ ├─ Int32
│ │ ├─ Int64
│ │ ├─ Int128
│ │ └─ BigInt
│ └─ Unsigned (Abstract Type)
│ ├─ UInt8
│ ├─ UInt16
│ ├─ UInt32
│ ├─ UInt64
│ └─ UInt128
├─ Rational
└─ AbstractIrrational (Abstract Type)
└─ IrrationalAbstract number types
Core.Number — TypeNumberAbstract supertype for all number types.
Core.Real — TypeReal <: NumberAbstract supertype for all real numbers.
Core.AbstractFloat — TypeAbstractFloat <: RealAbstract supertype for all floating point numbers.
Core.Integer — TypeInteger <: RealAbstract supertype for all integers.
Core.Signed — TypeSigned <: IntegerAbstract supertype for all signed integers.
Core.Unsigned — TypeUnsigned <: IntegerAbstract supertype for all unsigned integers.
Base.AbstractIrrational — TypeAbstractIrrational <: RealNumber type representing an exact irrational value, which is automatically rounded to the correct precision in arithmetic operations with other numeric quantities.
Subtypes MyIrrational <: AbstractIrrational should implement at least ==(::MyIrrational, ::MyIrrational), hash(x::MyIrrational, h::UInt), and convert(::Type{F}, x::MyIrrational) where {F <: Union{BigFloat,Float32,Float64}}.
If a subtype is used to represent values that may occasionally be rational (e.g. a square-root type that represents √n for integers n will give a rational result when n is a perfect square), then it should also implement isinteger, iszero, isone, and == with Real values (since all of these default to false for AbstractIrrational types), as well as defining hash to equal that of the corresponding Rational.
Concrete number types
Core.Float16 — TypeFloat16 <: AbstractFloat16-bit floating point number type (IEEE 754 standard).
Binary format: 1 sign, 5 exponent, 10 fraction bits.
Core.Float32 — TypeFloat32 <: AbstractFloat32-bit floating point number type (IEEE 754 standard).
Binary format: 1 sign, 8 exponent, 23 fraction bits.
Core.Float64 — TypeFloat64 <: AbstractFloat64-bit floating point number type (IEEE 754 standard).
Binary format: 1 sign, 11 exponent, 52 fraction bits.
Base.MPFR.BigFloat — TypeBigFloat <: AbstractFloatArbitrary precision floating point number type.
Core.Bool — TypeBool <: IntegerBoolean type, containing the values true and false.
Bool is a kind of number: false is numerically equal to 0 and true is numerically equal to 1. Moreover, false acts as a multiplicative "strong zero":
julia> false == 0
true
julia> true == 1
true
julia> 0 * NaN
NaN
julia> false * NaN
0.0Core.Int8 — TypeInt8 <: Signed8-bit signed integer type.
Core.UInt8 — TypeUInt8 <: Unsigned8-bit unsigned integer type.
Core.Int16 — TypeInt16 <: Signed16-bit signed integer type.
Core.UInt16 — TypeUInt16 <: Unsigned16-bit unsigned integer type.
Core.Int32 — TypeInt32 <: Signed32-bit signed integer type.
Core.UInt32 — TypeUInt32 <: Unsigned32-bit unsigned integer type.
Core.Int64 — TypeInt64 <: Signed64-bit signed integer type.
Core.UInt64 — TypeUInt64 <: Unsigned64-bit unsigned integer type.
Core.Int128 — TypeInt128 <: Signed128-bit signed integer type.
Core.UInt128 — TypeUInt128 <: Unsigned128-bit unsigned integer type.
Base.GMP.BigInt — TypeBigInt <: SignedArbitrary precision integer type.
Base.Complex — TypeComplex{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 — TypeRational{T<:Integer} <: RealRational number type, with numerator and denominator of type T. Rationals are checked for overflow.
Base.Irrational — TypeIrrational{sym} <: AbstractIrrationalNumber type representing an exact irrational value denoted by the symbol sym, such as π, ℯ and γ.
See also AbstractIrrational.
Data Formats
Base.digits — Functiondigits([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)).
See also ndigits, digits!, and for base 2 also bitstring, count_ones.
Examples
julia> digits(10)
2-element Vector{Int64}:
0
1
julia> digits(10, base = 2)
4-element Vector{Int64}:
0
1
0
1
julia> digits(-256, base = 10, pad = 5)
5-element Vector{Int64}:
-6
-5
-2
0
0
julia> n = rand(-999:999);
julia> n == evalpoly(13, digits(n, base = 13))
trueBase.digits! — Functiondigits!(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 Vector{Int64}:
0
1
0
1
julia> digits!([2, 2, 2, 2, 2, 2], 10, base = 2)
6-element Vector{Int64}:
0
1
0
1
0
0Base.bitstring — Functionbitstring(n)A string giving the literal bit representation of a primitive type.
See also count_ones, count_zeros, digits.
Examples
julia> bitstring(Int32(4))
"00000000000000000000000000000100"
julia> bitstring(2.2)
"0100000000000001100110011001100110011001100110011001100110011010"Base.parse — Functionparse(::Type{Platform}, triplet::AbstractString)Parses a string platform triplet back into a Platform object.
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.
parse(Bool, str) requires at least Julia 1.1.
Examples
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 — Functiontryparse(type, str; base)Like parse, but returns either a value of the requested type, or nothing if the string does not contain a valid number.
Base.big — Functionbig(x)Convert a number to a maximum precision representation (typically BigInt or BigFloat). See BigFloat for information about some pitfalls with floating-point numbers.
Base.signed — Functionsigned(T::Integer)Convert an integer bitstype to the signed type of the same size.
Examples
julia> signed(UInt16)
Int16
julia> signed(UInt64)
Int64signed(x)Convert a number to a signed integer. If the argument is unsigned, it is reinterpreted as signed without checking for overflow.
Base.unsigned — Functionunsigned(T::Integer)Convert an integer bitstype to the unsigned type of the same size.
Examples
julia> unsigned(Int16)
UInt16
julia> unsigned(UInt64)
UInt64Base.float — Methodfloat(x)Convert a number or array to a floating point data type.
See also: complex, oftype, convert.
Examples
julia> float(1:1000)
1.0:1.0:1000.0
julia> float(typemax(Int32))
2.147483647e9Base.Math.significand — Functionsignificand(x)Extract the significand (a.k.a. mantissa) of a floating-point number. If x is a non-zero finite number, then the result will be a number of the same type and sign as x, and whose absolute value is on the interval $[1,2)$. Otherwise x is returned.
Examples
julia> significand(15.2)
1.9
julia> significand(-15.2)
-1.9
julia> significand(-15.2) * 2^3
-15.2
julia> significand(-Inf), significand(Inf), significand(NaN)
(-Inf, Inf, NaN)Base.Math.exponent — Functionexponent(x) -> IntReturns the largest integer y such that 2^y ≤ abs(x). For a normalized floating-point number x, this corresponds to the exponent of x.
Examples
julia> exponent(8)
3
julia> exponent(64//1)
6
julia> exponent(6.5)
2
julia> exponent(16.0)
4
julia> exponent(3.142e-4)
-12Base.complex — Methodcomplex(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 Vector{Complex{Int64}}:
1 + 0im
2 + 0im
3 + 0imBase.bswap — Functionbswap(n)Reverse the byte order of n.
(See also ntoh and hton to convert between the current native byte order and big-endian order.)
Examples
julia> a = bswap(0x10203040)
0x40302010
julia> bswap(a)
0x10203040
julia> string(1, base = 2)
"1"
julia> string(bswap(1), base = 2)
"100000000000000000000000000000000000000000000000000000000"Base.hex2bytes — Functionhex2bytes(itr)Given an iterable itr 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 itr gives the value of one byte in the return vector.
The length of itr must be even, and the returned array has half of the length of itr. See also hex2bytes! for an in-place version, and bytes2hex for the inverse.
Calling hex2bytes with iterators producing UInt8 values requires Julia 1.7 or later. In earlier versions, you can collect the iterator before calling hex2bytes.
Examples
julia> s = string(12345, base = 16)
"3039"
julia> hex2bytes(s)
2-element Vector{UInt8}:
0x30
0x39
julia> a = b"01abEF"
6-element Base.CodeUnits{UInt8, String}:
0x30
0x31
0x61
0x62
0x45
0x46
julia> hex2bytes(a)
3-element Vector{UInt8}:
0x01
0xab
0xefBase.hex2bytes! — Functionhex2bytes!(dest::AbstractVector{UInt8}, itr)Convert an iterable itr of bytes representing a hexadecimal string to its binary representation, similar to hex2bytes except that the output is written in-place to dest. The length of dest must be half the length of itr.
Calling hex2bytes! with iterators producing UInt8 requires version 1.7. In earlier versions, you can collect the iterable before calling instead.
Base.bytes2hex — Functionbytes2hex(itr) -> String
bytes2hex(io::IO, itr)Convert an iterator itr of bytes to its hexadecimal string representation, either returning a String via bytes2hex(itr) or writing the string to an io stream via bytes2hex(io, itr). The hexadecimal characters are all lowercase.
Calling bytes2hex with arbitrary iterators producing UInt8 values requires Julia 1.7 or later. In earlier versions, you can collect the iterator before calling bytes2hex.
Examples
julia> a = string(12345, base = 16)
"3039"
julia> b = hex2bytes(a)
2-element Vector{UInt8}:
0x30
0x39
julia> bytes2hex(b)
"3039"General Number Functions and Constants
Base.one — Functionone(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.
See also the identity function, and I in LinearAlgebra for the identity matrix.
Examples
julia> one(3.7)
1.0
julia> one(Int)
1
julia> import Dates; one(Dates.Day(1))
1Base.oneunit — Functiononeunit(x::T)
oneunit(T::Type)Return 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).
Examples
julia> oneunit(3.7)
1.0
julia> import Dates; oneunit(Dates.Day)
1 dayBase.zero — Functionzero(x)
zero(::Type)Get the additive identity element for the type of x (x can also specify the type itself).
See also iszero, one, oneunit, oftype.
Examples
julia> zero(1)
0
julia> zero(big"2.0")
0.0
julia> zero(rand(2,2))
2×2 Matrix{Float64}:
0.0 0.0
0.0 0.0Base.im — ConstantimThe imaginary unit.
See also: imag, angle, complex.
Examples
julia> im * im
-1 + 0im
julia> (2.0 + 3im)^2
-5.0 + 12.0imBase.MathConstants.pi — Constantπ
piThe constant pi.
Unicode π can be typed by writing \pi then pressing tab in the Julia REPL, and in many editors.
See also: sinpi, sincospi, deg2rad.
Examples
julia> pi
π = 3.1415926535897...
julia> 1/2pi
0.15915494309189535Base.MathConstants.ℯ — Constantℯ
eThe constant ℯ.
Unicode ℯ can be typed by writing \euler and pressing tab in the Julia REPL, and in many editors.
Examples
julia> ℯ
ℯ = 2.7182818284590...
julia> log(ℯ)
1
julia> ℯ^(im)π ≈ -1
trueBase.MathConstants.catalan — ConstantcatalanCatalan's constant.
Examples
julia> Base.MathConstants.catalan
catalan = 0.9159655941772...
julia> sum(log(x)/(1+x^2) for x in 1:0.01:10^6) * 0.01
0.9159466120554123Base.MathConstants.eulergamma — Constantγ
eulergammaEuler's constant.
Examples
julia> Base.MathConstants.eulergamma
γ = 0.5772156649015...
julia> dx = 10^-6;
julia> sum(-exp(-x) * log(x) for x in dx:dx:100) * dx
0.5772078382499133Base.MathConstants.golden — Constantφ
goldenThe golden ratio.
Examples
julia> Base.MathConstants.golden
φ = 1.6180339887498...
julia> (2ans - 1)^2 ≈ 5
trueBase.Inf — ConstantInf, Inf64Positive infinity of type Float64.
See also: isfinite, typemax, NaN, Inf32.
Examples
julia> π/0
Inf
julia> +1.0 / -0.0
-Inf
julia> ℯ^-Inf
0.0Base.Inf64 — ConstantInf, Inf64Positive infinity of type Float64.
See also: isfinite, typemax, NaN, Inf32.
Examples
julia> π/0
Inf
julia> +1.0 / -0.0
-Inf
julia> ℯ^-Inf
0.0Base.Inf32 — ConstantInf32Positive infinity of type Float32.
Base.Inf16 — ConstantInf16Positive infinity of type Float16.
Base.NaN — ConstantNaN, NaN64A not-a-number value of type Float64.
See also: isnan, missing, NaN32, Inf.
Examples
julia> 0/0
NaN
julia> Inf - Inf
NaN
julia> NaN == NaN, isequal(NaN, NaN), NaN === NaN
(false, true, true)Base.NaN64 — ConstantNaN, NaN64A not-a-number value of type Float64.
See also: isnan, missing, NaN32, Inf.
Examples
julia> 0/0
NaN
julia> Inf - Inf
NaN
julia> NaN == NaN, isequal(NaN, NaN), NaN === NaN
(false, true, true)Base.NaN32 — ConstantNaN32A not-a-number value of type Float32.
Base.NaN16 — ConstantNaN16A not-a-number value of type Float16.
Base.issubnormal — Functionissubnormal(f) -> BoolTest whether a floating point number is subnormal.
An IEEE floating point number is subnormal when its exponent bits are zero and its significand is not zero.
Examples
julia> floatmin(Float32)
1.1754944f-38
julia> issubnormal(1.0f-37)
false
julia> issubnormal(1.0f-38)
trueBase.isfinite — Functionisfinite(f) -> BoolTest whether a number is finite.
Examples
julia> isfinite(5)
true
julia> isfinite(NaN32)
falseBase.isinf — FunctionBase.isnan — Functionisnan(f) -> BoolTest whether a number value is a NaN, an indeterminate value which is neither an infinity nor a finite number ("not a number").
Base.iszero — Functioniszero(x)Return true if x == zero(x); if x is an array, this checks whether all of the elements of x are zero.
See also: isone, isinteger, isfinite, isnan.
Examples
julia> iszero(0.0)
true
julia> iszero([1, 9, 0])
false
julia> iszero([false, 0, 0])
trueBase.isone — Functionisone(x)Return true if x == one(x); if x is an array, this checks whether x is an identity matrix.
Examples
julia> isone(1.0)
true
julia> isone([1 0; 0 2])
false
julia> isone([1 0; 0 true])
trueBase.nextfloat — Functionnextfloat(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.
See also: prevfloat, eps, issubnormal.
Base.prevfloat — Functionprevfloat(x::AbstractFloat, n::Integer)The result of n iterative applications of prevfloat to x if n >= 0, or -n applications of nextfloat if n < 0.
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 — Functionisinteger(x) -> BoolTest whether x is numerically equal to some integer.
Examples
julia> isinteger(4.0)
trueBase.isreal — Functionisreal(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(1 - 3im)
false
julia> isreal(Inf + 0im)
true
julia> isreal([4.; complex(0,1)])
falseCore.Float32 — MethodFloat32(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 — MethodFloat64(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.Rounding.rounding — Functionrounding(T)Get the current floating point rounding mode for type T, controlling the rounding of basic arithmetic functions (+, -, *, / and sqrt) and type conversion.
See RoundingMode for available modes.
Base.Rounding.setrounding — Methodsetrounding(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 is currently only supported for T == BigFloat.
This function is not thread-safe. It will affect code running on all threads, but its behavior is undefined if called concurrently with computations that use the setting.
Base.Rounding.setrounding — Methodsetrounding(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.
Base.Rounding.get_zero_subnormals — Functionget_zero_subnormals() -> BoolReturn false if operations on subnormal floating-point values ("denormals") obey rules for IEEE arithmetic, and true if they might be converted to zeros.
This function only affects the current thread.
Base.Rounding.set_zero_subnormals — Functionset_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).
This function only affects the current thread.
Integers
Base.count_ones — Functioncount_ones(x::Integer) -> IntegerNumber of ones in the binary representation of x.
Examples
julia> count_ones(7)
3
julia> count_ones(Int32(-1))
32Base.count_zeros — Functioncount_zeros(x::Integer) -> IntegerNumber of zeros in the binary representation of x.
Examples
julia> count_zeros(Int32(2 ^ 16 - 1))
16
julia> count_zeros(-1)
0Base.leading_zeros — Functionleading_zeros(x::Integer) -> IntegerNumber of zeros leading the binary representation of x.
Examples
julia> leading_zeros(Int32(1))
31Base.leading_ones — Functionleading_ones(x::Integer) -> IntegerNumber of ones leading the binary representation of x.
Examples
julia> leading_ones(UInt32(2 ^ 32 - 2))
31Base.trailing_zeros — Functiontrailing_zeros(x::Integer) -> IntegerNumber of zeros trailing the binary representation of x.
Examples
julia> trailing_zeros(2)
1Base.trailing_ones — Functiontrailing_ones(x::Integer) -> IntegerNumber of ones trailing the binary representation of x.
Examples
julia> trailing_ones(3)
2Base.isodd — Functionisodd(x::Number) -> BoolReturn true if x is an odd integer (that is, an integer not divisible by 2), and false otherwise.
Non-Integer arguments require Julia 1.7 or later.
Examples
julia> isodd(9)
true
julia> isodd(10)
falseBase.iseven — Functioniseven(x::Number) -> BoolReturn true if x is an even integer (that is, an integer divisible by 2), and false otherwise.
Non-Integer arguments require Julia 1.7 or later.
Examples
julia> iseven(9)
false
julia> iseven(10)
trueCore.@int128_str — Macro@int128_str strParse str as an Int128. Throw an ArgumentError if the string is not a valid integer.
Examples
julia> int128"123456789123"
123456789123
julia> int128"123456789123.4"
ERROR: LoadError: ArgumentError: invalid base 10 digit '.' in "123456789123.4"
[...]Core.@uint128_str — Macro@uint128_str strParse str as an UInt128. Throw an ArgumentError if the string is not a valid integer.
Examples
julia> uint128"123456789123"
0x00000000000000000000001cbe991a83
julia> uint128"-123456789123"
ERROR: LoadError: ArgumentError: invalid base 10 digit '-' in "-123456789123"
[...]BigFloats and BigInts
The BigFloat and BigInt types implements arbitrary-precision floating point and integer arithmetic, respectively. For BigFloat the GNU MPFR library is used, and for BigInt the GNU Multiple Precision Arithmetic Library (GMP) is used.
Base.MPFR.BigFloat — MethodBigFloat(x::Union{Real, AbstractString} [, rounding::RoundingMode=rounding(BigFloat)]; [precision::Integer=precision(BigFloat)])Create an arbitrary precision floating point number from x, with precision precision. The rounding argument specifies the direction in which the result should be rounded if the conversion cannot be done exactly. If not provided, these are set by the current global values.
BigFloat(x::Real) is the same as convert(BigFloat,x), except if x itself is already BigFloat, in which case it will return a value with the precision set to the current global precision; convert will always return x.
BigFloat(x::AbstractString) is identical to parse. This is provided for convenience since decimal literals are converted to Float64 when parsed, so BigFloat(2.1) may not yield what you expect.
See also:
precision as a keyword argument requires at least Julia 1.1. In Julia 1.0 precision is the second positional argument (BigFloat(x, precision)).
Examples
julia> BigFloat(2.1) # 2.1 here is a Float64
2.100000000000000088817841970012523233890533447265625
julia> BigFloat("2.1") # the closest BigFloat to 2.1
2.099999999999999999999999999999999999999999999999999999999999999999999999999986
julia> BigFloat("2.1", RoundUp)
2.100000000000000000000000000000000000000000000000000000000000000000000000000021
julia> BigFloat("2.1", RoundUp, precision=128)
2.100000000000000000000000000000000000007Base.precision — Functionprecision(num::AbstractFloat; base::Integer=2)
precision(T::Type; base::Integer=2)Get the precision of a floating point number, as defined by the effective number of bits in the significand, or the precision of a floating-point type T (its current default, if T is a variable-precision type like BigFloat).
If base is specified, then it returns the maximum corresponding number of significand digits in that base.
The base keyword requires at least Julia 1.8.
Base.MPFR.setprecision — Functionsetprecision([T=BigFloat,] precision::Int; base=2)Set the precision (in bits, by default) to be used for T arithmetic. If base is specified, then the precision is the minimum required to give at least precision digits in the given base.
This function is not thread-safe. It will affect code running on all threads, but its behavior is undefined if called concurrently with computations that use the setting.
The base keyword requires at least Julia 1.8.
setprecision(f::Function, [T=BigFloat,] precision::Integer; base=2)Change the T arithmetic precision (in the given base) 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
Note: nextfloat(), prevfloat() do not use the precision mentioned by setprecision.
The base keyword requires at least Julia 1.8.
Base.GMP.BigInt — MethodBigInt(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.
Examples
julia> parse(BigInt, "42")
42
julia> big"313"
313
julia> BigInt(10)^19
10000000000000000000Core.@big_str — Macro@big_str strParse a string into a BigInt or BigFloat, and throw an ArgumentError if the string is not a valid number. For integers _ is allowed in the string as a separator.
Examples
julia> big"123_456"
123456
julia> big"7891.5"
7891.5
julia> big"_"
ERROR: ArgumentError: invalid number format _ for BigInt or BigFloat
[...]