Numbers

    Abstract supertype for all number types.

    Core.Real — Type

    Abstract supertype for all real numbers.

    Core.AbstractFloat — Type

    1. AbstractFloat <: Real

    Abstract supertype for all floating point numbers.

    Core.Integer — Type

    1. Integer <: Real

    Abstract supertype for all integers.

    Core.Signed — Type

    1. Signed <: Integer

    Abstract supertype for all signed integers.

    Core.Unsigned — Type

    1. Unsigned <: Integer

    Abstract supertype for all unsigned integers.

    Base.AbstractIrrational — Type

    1. AbstractIrrational <: Real

    Number 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 to equal that of the corresponding Rational.

    source

    Core.Float16 — Type

    1. Float16 <: AbstractFloat

    16-bit floating point number type (IEEE 754 standard).

    Binary format: 1 sign, 5 exponent, 10 fraction bits.

    Core.Float32 — Type

    1. Float32 <: AbstractFloat

    32-bit floating point number type (IEEE 754 standard).

    Binary format: 1 sign, 8 exponent, 23 fraction bits.

    Core.Float64 — Type

    1. Float64 <: AbstractFloat

    64-bit floating point number type (IEEE 754 standard).

    Binary format: 1 sign, 11 exponent, 52 fraction bits.

    Base.MPFR.BigFloat — Type

    1. BigFloat <: AbstractFloat

    Arbitrary precision floating point number type.

    Core.Bool — Type

    1. Bool <: Integer

    Boolean 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”:

    1. julia> false == 0
    2. true
    3. julia> true == 1
    4. true
    5. julia> 0 * NaN
    6. NaN
    7. julia> false * NaN
    8. 0.0

    See also: , iszero, .

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    — Type

    1. Int8 <: Signed

    8-bit signed integer type.

    source

    — Type

    1. UInt8 <: Unsigned

    8-bit unsigned integer type.

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    — Type

    1. Int16 <: Signed

    16-bit signed integer type.

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    — Type

    1. UInt16 <: Unsigned

    16-bit unsigned integer type.

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    — Type

    1. Int32 <: Signed

    32-bit signed integer type.

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    — Type

    1. UInt32 <: Unsigned

    32-bit unsigned integer type.

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    — Type

    1. Int64 <: Signed

    64-bit signed integer type.

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    — Type

    1. UInt64 <: Unsigned

    64-bit unsigned integer type.

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    — Type

    1. Int128 <: Signed

    128-bit signed integer type.

    source

    — Type

    1. UInt128 <: Unsigned

    128-bit unsigned integer type.

    source

    — Type

    1. BigInt <: Signed

    Arbitrary precision integer type.

    source

    — Type

    1. Complex{T<:Real} <: Number

    Complex 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.

    See also: Real, , real.

    Base.Rational — Type

    1. Rational{T<:Integer} <: Real

    Rational number type, with numerator and denominator of type T. Rationals are checked for overflow.

    Base.Irrational — Type

    1. Irrational{sym} <: AbstractIrrational

    Number type representing an exact irrational value denoted by the symbol sym, such as , and .

    See also [@irrational], AbstractIrrational.

    — Function

    1. 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)).

    See also ndigits, , and for base 2 also bitstring, .

    Examples

    1. julia> digits(10)
    2. 2-element Vector{Int64}:
    3. 0
    4. 1
    5. julia> digits(10, base = 2)
    6. 4-element Vector{Int64}:
    7. 0
    8. 1
    9. 0
    10. 1
    11. julia> digits(-256, base = 10, pad = 5)
    12. 5-element Vector{Int64}:
    13. -6
    14. -5
    15. -2
    16. 0
    17. 0
    18. julia> n = rand(-999:999);
    19. julia> n == evalpoly(13, digits(n, base = 13))
    20. true

    source

    — Function

    1. 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

    1. julia> digits!([2, 2, 2, 2], 10, base = 2)
    2. 4-element Vector{Int64}:
    3. 0
    4. 1
    5. 0
    6. 1
    7. julia> digits!([2, 2, 2, 2, 2, 2], 10, base = 2)
    8. 6-element Vector{Int64}:
    9. 0
    10. 1
    11. 0
    12. 1
    13. 0
    14. 0

    source

    — Function

    1. bitstring(n)

    A string giving the literal bit representation of a primitive type.

    See also count_ones, , digits.

    Examples

    1. julia> bitstring(Int32(4))
    2. "00000000000000000000000000000100"
    3. julia> bitstring(2.2)
    4. "0100000000000001100110011001100110011001100110011001100110011010"

    Base.parse — Function

    1. parse(::Type{Platform}, triplet::AbstractString)

    Parses a string platform triplet back into a Platform object.

    1. 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 1.1

    parse(Bool, str) requires at least Julia 1.1.

    Examples

    1. julia> parse(Int, "1234")
    2. 1234
    3. julia> parse(Int, "1234", base = 5)
    4. 194
    5. julia> parse(Int, "afc", base = 16)
    6. 2812
    7. julia> parse(Float64, "1.2e-3")
    8. 0.0012
    9. julia> parse(Complex{Float64}, "3.2e-1 + 4.5im")
    10. 0.32 + 4.5im

    source

    — Function

    1. tryparse(type, str; base)

    Like parse, but returns either a value of the requested type, or if the string does not contain a valid number.

    source

    — Function

    1. big(x)

    Convert a number to a maximum precision representation (typically BigInt or BigFloat). See for information about some pitfalls with floating-point numbers.

    source

    — Function

    1. signed(T::Integer)

    Convert an integer bitstype to the signed type of the same size.

    Examples

    1. julia> signed(UInt16)
    2. Int16
    3. julia> signed(UInt64)
    4. Int64

    source

    1. signed(x)

    Convert a number to a signed integer. If the argument is unsigned, it is reinterpreted as signed without checking for overflow.

    See also: , sign, .

    source

    — Function

    1. unsigned(T::Integer)

    Convert an integer bitstype to the unsigned type of the same size.

    Examples

    1. julia> unsigned(Int16)
    2. UInt16
    3. julia> unsigned(UInt64)
    4. UInt64

    source

    — Method

    1. float(x)

    Convert a number or array to a floating point data type.

    See also: complex, , convert.

    1. julia> float(1:1000)
    2. 1.0:1.0:1000.0
    3. julia> float(typemax(Int32))
    4. 2.147483647e9

    Base.Math.significand — Function

    1. significand(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

    Base.Math.exponent — Function

    1. exponent(x::AbstractFloat) -> Int

    Get the exponent of a normalized floating-point number. Returns the largest integer y such that 2^y ≤ abs(x).

    Examples

    1. julia> exponent(6.5)
    2. 2
    3. julia> exponent(16.0)
    4. 4

    Base.complex — Method

    1. complex(r, [i])

    Convert real numbers or arrays to complex. i defaults to zero.

    Examples

    1. julia> complex(7)
    2. 7 + 0im
    3. julia> complex([1, 2, 3])
    4. 1 + 0im
    5. 2 + 0im
    6. 3 + 0im

    Base.bswap — Function

    1. bswap(n)

    Reverse the byte order of n.

    (See also and hton to convert between the current native byte order and big-endian order.)

    Examples

    1. julia> a = bswap(0x10203040)
    2. 0x40302010
    3. julia> bswap(a)
    4. 0x10203040
    5. julia> string(1, base = 2)
    6. "1"
    7. julia> string(bswap(1), base = 2)
    8. "100000000000000000000000000000000000000000000000000000000"

    Base.hex2bytes — Function

    1. hex2bytes(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 for an in-place version, and bytes2hex for the inverse.

    Julia 1.7

    Calling hex2bytes with iterators producing values requires Julia 1.7 or later. In earlier versions, you can collect the iterator before calling hex2bytes.

    Examples

    1. julia> s = string(12345, base = 16)
    2. "3039"
    3. julia> hex2bytes(s)
    4. 2-element Vector{UInt8}:
    5. 0x30
    6. 0x39
    7. julia> a = b"01abEF"
    8. 6-element Base.CodeUnits{UInt8, String}:
    9. 0x30
    10. 0x31
    11. 0x61
    12. 0x62
    13. 0x45
    14. 0x46
    15. julia> hex2bytes(a)
    16. 3-element Vector{UInt8}:
    17. 0x01
    18. 0xab
    19. 0xef

    Base.hex2bytes! — Function

    1. hex2bytes!(dest::AbstractVector{UInt8}, itr)

    Convert an iterable itr of bytes representing a hexadecimal string to its binary representation, similar to except that the output is written in-place to dest. The length of dest must be half the length of itr.

    Julia 1.7

    Calling hex2bytes! with iterators producing UInt8 requires version 1.7. In earlier versions, you can collect the iterable before calling instead.

    source

    — Function

    1. bytes2hex(itr) -> String
    2. 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.

    Julia 1.7

    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

    1. julia> a = string(12345, base = 16)
    2. "3039"
    3. julia> b = hex2bytes(a)
    4. 2-element Vector{UInt8}:
    5. 0x30
    6. 0x39
    7. julia> bytes2hex(b)
    8. "3039"

    source

    Base.one — Function

    1. one(x)
    2. 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 instead.

    See also the identity function, and I in for the identity matrix.

    Examples

    1. julia> one(3.7)
    2. 1.0
    3. julia> one(Int)
    4. 1
    5. julia> import Dates; one(Dates.Day(1))
    6. 1

    source

    — Function

    1. oneunit(x::T)
    2. 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).

    Examples

    1. julia> oneunit(3.7)
    2. 1.0
    3. julia> import Dates; oneunit(Dates.Day)
    4. 1 day

    Base.zero — Function

    1. zero(x)
    2. zero(::Type)

    Get the additive identity element for the type of x (x can also specify the type itself).

    See also , one, , oftype.

    Examples

    1. julia> zero(1)
    2. 0
    3. julia> zero(big"2.0")
    4. 0.0
    5. julia> zero(rand(2,2))
    6. 2×2 Matrix{Float64}:
    7. 0.0 0.0
    8. 0.0 0.0

    Base.im — Constant

    1. im

    The imaginary unit.

    See also: , angle, .

    Examples

    1. julia> im * im
    2. -1 + 0im
    3. julia> (2.0 + 3im)^2
    4. -5.0 + 12.0im

    source

    — Constant

    1. π
    2. pi

    The constant pi.

    Unicode π can be typed by writing \pi then pressing tab in the Julia REPL, and in many editors.

    See also: sinpi, , deg2rad.

    Examples

    1. julia> pi
    2. π = 3.1415926535897...
    3. julia> 1/2pi
    4. 0.15915494309189535

    Base.MathConstants.ℯ — Constant

    1. e

    The constant ℯ.

    Unicode can be typed by writing \euler and pressing tab in the Julia REPL, and in many editors.

    See also: , cis, .

    Examples

    1. julia>
    2. = 2.7182818284590...
    3. julia> log(ℯ)
    4. 1
    5. julia> ℯ^(im -1
    6. true

    source

    — Constant

    1. catalan

    Catalan’s constant.

    Examples

    1. julia> Base.MathConstants.catalan
    2. catalan = 0.9159655941772...
    3. julia> sum(log(x)/(1+x^2) for x in 1:0.01:10^6) * 0.01
    4. 0.9159466120554123

    source

    — Constant

    1. γ
    2. eulergamma

    Euler’s constant.

    Examples

    1. julia> Base.MathConstants.eulergamma
    2. γ = 0.5772156649015...
    3. julia> dx = 10^-6;
    4. julia> sum(-exp(-x) * log(x) for x in dx:dx:100) * dx
    5. 0.5772078382499133

    source

    — Constant

    1. φ
    2. golden

    The golden ratio.

    Examples

    1. julia> Base.MathConstants.golden
    2. φ = 1.6180339887498...
    3. julia> (2ans - 1)^2 5
    4. true

    source

    — Constant

    1. Inf, Inf64

    Positive infinity of type Float64.

    See also: , typemax, , Inf32.

    Examples

    1. julia> π/0
    2. Inf
    3. julia> +1.0 / -0.0
    4. -Inf
    5. julia> ℯ^-Inf
    6. 0.0

    Base.Inf32 — Constant

    1. Inf32

    Positive infinity of type .

    source

    — Constant

    1. Inf16

    Positive infinity of type Float16.

    Base.NaN — Constant

    1. NaN, NaN64

    A not-a-number value of type .

    See also: isnan, , NaN32, .

    Examples

    1. NaN
    2. julia> Inf - Inf
    3. NaN
    4. julia> NaN == NaN, isequal(NaN, NaN), NaN === NaN
    5. (false, true, true)

    source

    — Constant

    1. NaN32

    A not-a-number value of type Float32.

    Base.NaN16 — Constant

    1. NaN16

    A not-a-number value of type .

    source

    — Function

    1. issubnormal(f) -> Bool

    Test whether a floating point number is subnormal.

    source

    — Function

    1. isfinite(f) -> Bool

    Test whether a number is finite.

    Examples

    1. julia> isfinite(5)
    2. true
    3. julia> isfinite(NaN32)
    4. false

    source

    — Function

    1. isinf(f) -> Bool

    Test whether a number is infinite.

    See also: Inf, , isfinite, .

    source

    — Function

    1. isnan(f) -> Bool

    Test whether a number value is a NaN, an indeterminate value which is neither an infinity nor a finite number (“not a number”).

    See also: iszero, , isinf, .

    source

    — Function

    1. iszero(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, , isfinite, .

    Examples

    1. julia> iszero(0.0)
    2. true
    3. julia> iszero([1, 9, 0])
    4. false
    5. julia> iszero([false, 0, 0])
    6. true

    source

    — Function

    1. isone(x)

    Return true if x == one(x); if x is an array, this checks whether x is an identity matrix.

    Examples

    source

    — Function

    1. 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.

    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: , eps, .

    source

    — Function

    1. prevfloat(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.

    1. 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.

    source

    — Function

    1. isinteger(x) -> Bool

    Test whether x is numerically equal to some integer.

    Examples

    1. julia> isinteger(4.0)
    2. true

    source

    — Function

    1. isreal(x) -> Bool

    Test 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

    1. julia> isreal(5.)
    2. true
    3. julia> isreal(Inf + 0im)
    4. true
    5. julia> isreal([4.; complex(0,1)])
    6. false

    source

    — Method

    1. Float32(x [, mode::RoundingMode])

    Create a Float32 from x. If x is not exactly representable then mode determines how x is rounded.

    Examples

    1. julia> Float32(1/3, RoundDown)
    2. 0.3333333f0
    3. julia> Float32(1/3, RoundUp)
    4. 0.33333334f0

    See RoundingMode for available rounding modes.

    Core.Float64 — Method

    1. Float64(x [, mode::RoundingMode])

    Create a Float64 from x. If x is not exactly representable then mode determines how x is rounded.

    Examples

    1. julia> Float64(pi, RoundDown)
    2. 3.141592653589793
    3. julia> Float64(pi, RoundUp)
    4. 3.1415926535897936

    See for available rounding modes.

    source

    — Function

    1. rounding(T)

    Get the current floating point rounding mode for type T, controlling the rounding of basic arithmetic functions (+, , *, and sqrt) and type conversion.

    See for available modes.

    source

    — Method

    1. 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 .

    Note that this is currently only supported for T == BigFloat.

    Warning

    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.

    source

    — Method

    1. setrounding(f::Function, T, mode)

    Change the rounding mode of floating point type T for the duration of f. It is logically equivalent to:

    1. old = rounding(T)
    2. setrounding(T, mode)
    3. f()
    4. setrounding(T, old)

    See RoundingMode for available rounding modes.

    Base.Rounding.get_zero_subnormals — Function

    1. get_zero_subnormals() -> Bool

    Return false if operations on subnormal floating-point values (“denormals”) obey rules for IEEE arithmetic, and true if they might be converted to zeros.

    Warning

    This function only affects the current thread.

    Base.Rounding.set_zero_subnormals — Function

    1. set_zero_subnormals(yes::Bool) -> Bool

    If 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).

    Warning

    This function only affects the current thread.

    — Function

    1. count_ones(x::Integer) -> Integer

    Number of ones in the binary representation of x.

    Examples

    1. julia> count_ones(7)
    2. 3
    3. julia> count_ones(Int32(-1))
    4. 32

    source

    — Function

    1. count_zeros(x::Integer) -> Integer

    Number of zeros in the binary representation of x.

    Examples

    1. julia> count_zeros(Int32(2 ^ 16 - 1))
    2. 16
    3. julia> count_zeros(-1)
    4. 0

    source

    — Function

    1. leading_zeros(x::Integer) -> Integer

    Number of zeros leading the binary representation of x.

    Examples

    1. julia> leading_zeros(Int32(1))
    2. 31

    source

    — Function

    1. leading_ones(x::Integer) -> Integer

    Number of ones leading the binary representation of x.

    Examples

    1. julia> leading_ones(UInt32(2 ^ 32 - 2))
    2. 31

    source

    — Function

    1. trailing_zeros(x::Integer) -> Integer

    Number of zeros trailing the binary representation of x.

    Examples

    1. julia> trailing_zeros(2)
    2. 1

    source

    — Function

    1. trailing_ones(x::Integer) -> Integer

    Number of ones trailing the binary representation of x.

    Examples

    1. julia> trailing_ones(3)
    2. 2

    source

    — Function

    1. isodd(x::Number) -> Bool

    Return true if x is an odd integer (that is, an integer not divisible by 2), and false otherwise.

    Julia 1.7

    Non-Integer arguments require Julia 1.7 or later.

    Examples

    1. julia> isodd(9)
    2. true
    3. julia> isodd(10)
    4. false

    source

    — Function

    1. iseven(x::Number) -> Bool

    Return true if x is an even integer (that is, an integer divisible by 2), and false otherwise.

    Julia 1.7

    Non-Integer arguments require Julia 1.7 or later.

    Examples

    1. julia> iseven(9)
    2. false
    3. julia> iseven(10)
    4. true

    source

    — Macro

    1. @int128_str str
    2. @int128_str(str)

    @int128_str parses a string into a Int128. Throws an ArgumentError if the string is not a valid integer.

    source

    — Macro

    1. @uint128_str str
    2. @uint128_str(str)

    @uint128_str parses a string into a UInt128. Throws an ArgumentError if the string is not a valid integer.

    source

    The BigFloat and types implements arbitrary-precision floating point and integer arithmetic, respectively. For BigFloat the is used, and for BigInt the is used.

    Base.MPFR.BigFloat — Method

    1. BigFloat(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 . 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:

    Julia 1.1

    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

    1. julia> BigFloat(2.1) # 2.1 here is a Float64
    2. 2.100000000000000088817841970012523233890533447265625
    3. julia> BigFloat("2.1") # the closest BigFloat to 2.1
    4. 2.099999999999999999999999999999999999999999999999999999999999999999999999999986
    5. julia> BigFloat("2.1", RoundUp)
    6. 2.100000000000000000000000000000000000000000000000000000000000000000000000000021
    7. julia> BigFloat("2.1", RoundUp, precision=128)
    8. 2.100000000000000000000000000000000000007

    Base.precision — Function

    1. precision(num::AbstractFloat; base::Integer=2)
    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 ).

    If base is specified, then it returns the maximum corresponding number of significand digits in that base.

    Julia 1.8

    The base keyword requires at least Julia 1.8.

    source

    — Function

    1. setprecision([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.

    Warning

    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.

    Julia 1.8

    The base keyword requires at least Julia 1.8.

    source

    1. 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:

    1. old = precision(BigFloat)
    2. setprecision(BigFloat, precision)
    3. f()
    4. setprecision(BigFloat, old)

    Often used as setprecision(T, precision) do ... end

    Note: nextfloat(), prevfloat() do not use the precision mentioned by setprecision.

    Julia 1.8

    The base keyword requires at least Julia 1.8.

    Base.GMP.BigInt — Method

    1. 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 .

    Instances can be constructed from strings via parse, or using the big string literal.

    Examples

    1. julia> parse(BigInt, "42")
    2. 42
    3. julia> big"313"
    4. 313
    5. julia> BigInt(10)^19
    6. 10000000000000000000

    Core.@big_str — Macro

    1. @big_str(str)

    Parse a string into a or BigFloat, and throw an if the string is not a valid number. For integers _ is allowed in the string as a separator.