Mathematics

    Unary minus operator.

    Examples

    1. julia> -1
    2. -1
    3. julia> -(2)
    4. -2
    5. julia> -[1 2; 3 4]
    6. 2×2 Array{Int64,2}:
    7. -1 -2
    8. -3 -4

    source

    — Function.

    1. +(x, y...)

    Addition operator. x+y+z+... calls this function with all arguments, i.e. +(x, y, z, ...).

    Examples

    1. julia> 1 + 20 + 4
    2. 25
    3. julia> +(1, 20, 4)
    4. 25

    source

    1. dt::Date + t::Time -> DateTime

    The addition of a Date with a Time produces a DateTime. The hour, minute, second, and millisecond parts of the Time are used along with the year, month, and day of the Date to create the new DateTime. Non-zero microseconds or nanoseconds in the Time type will result in an InexactError being thrown.

    Base.:- — Method.

    1. -(x, y)

    Subtraction operator.

    Examples

    1. julia> 2 - 3
    2. -1
    3. julia> -(2, 4.5)
    4. -2.5

    Base.:* — Method.

    1. *(x, y...)

    Multiplication operator. x*y*z*... calls this function with all arguments, i.e. *(x, y, z, ...).

    Examples

    1. julia> 2 * 7 * 8
    2. 112
    3. julia> *(2, 7, 8)
    4. 112

    Base.:/ — Function.

    1. /(x, y)

    Right division operator: multiplication of x by the inverse of y on the right. Gives floating-point results for integer arguments.

    Examples

    1. julia> 1/2
    2. 0.5
    3. julia> 4/2
    4. 2.0
    5. julia> 4.5/2
    6. 2.25

    Base.:\ — Method.

    1. \(x, y)

    Left division operator: multiplication of y by the inverse of x on the left. Gives floating-point results for integer arguments.

    Examples

    1. julia> 3 \ 6
    2. 2.0
    3. julia> inv(3) * 6
    4. 2.0
    5. julia> A = [4 3; 2 1]; x = [5, 6];
    6. julia> A \ x
    7. 2-element Array{Float64,1}:
    8. 6.5
    9. -7.0
    10. julia> inv(A) * x
    11. 2-element Array{Float64,1}:
    12. 6.5
    13. -7.0

    Base.:^ — Method.

    1. ^(x, y)

    Exponentiation operator. If x is a matrix, computes matrix exponentiation.

    If y is an Int literal (e.g. 2 in x^2 or -3 in x^-3), the Julia code x^y is transformed by the compiler to Base.literal_pow(^, x, Val(y)), to enable compile-time specialization on the value of the exponent. (As a default fallback we have Base.literal_pow(^, x, Val(y)) = ^(x,y), where usually ^ == Base.^ unless ^ has been defined in the calling namespace.)

    1. julia> 3^5
    2. 243
    3. julia> A = [1 2; 3 4]
    4. 2×2 Array{Int64,2}:
    5. 1 2
    6. 3 4
    7. julia> A^3
    8. 2×2 Array{Int64,2}:
    9. 37 54
    10. 81 118

    Base.fma — Function.

      Computes x*y+z without rounding the intermediate result x*y. On some systems this is significantly more expensive than x*y+z. fma is used to improve accuracy in certain algorithms. See .

      source

      — Function.

      1. muladd(x, y, z)

      Combined multiply-add: computes x*y+z, but allowing the add and multiply to be merged with each other or with surrounding operations for performance. For example, this may be implemented as an fma if the hardware supports it efficiently. The result can be different on different machines and can also be different on the same machine due to constant propagation or other optimizations. See .

      Examples

      1. julia> muladd(3, 2, 1)
      2. 7
      3. julia> 3 * 2 + 1
      4. 7

      source

      — Method.

      1. inv(x)

      Return the multiplicative inverse of x, such that x*inv(x) or inv(x)*x yields one(x) (the multiplicative identity) up to roundoff errors.

      If x is a number, this is essentially the same as one(x)/x, but for some types inv(x) may be slightly more efficient.

      Examples

      1. julia> inv(2)
      2. 0.5
      3. julia> inv(1 + 2im)
      4. 0.2 - 0.4im
      5. julia> inv(1 + 2im) * (1 + 2im)
      6. 1.0 + 0.0im
      7. julia> inv(2//3)
      8. 3//2

      Julia 1.2

      inv(::Missing) requires at least Julia 1.2.

      Base.div — Function.

      1. div(x, y)
      2. ÷(x, y)

      The quotient from Euclidean division. Computes x/y, truncated to an integer.

      Examples

      1. julia> 9 ÷ 4
      2. 2
      3. julia> -5 ÷ 3
      4. -1

      Base.fld — Function.

      1. fld(x, y)

      Largest integer less than or equal to x/y.

      Examples

      1. julia> fld(7.3,5.5)
      2. 1.0

      Base.cld — Function.

      1. cld(x, y)

      Smallest integer larger than or equal to x/y.

      Examples

      1. julia> cld(5.5,2.2)
      2. 3.0

      Base.mod — Function.

      1. mod(x::Integer, r::AbstractUnitRange)

      Find y in the range r such that $x ≡ y (mod n)$, where n = length(r), i.e. y = mod(x - first(r), n) + first(r).

      See also: .

      Examples

      1. julia> mod(0, Base.OneTo(3))
      2. 3
      3. julia> mod(3, 0:2)
      4. 0

      Julia 1.3

      This method requires at least Julia 1.3.

      source

      1. mod(x, y)
      2. rem(x, y, RoundDown)

      The reduction of x modulo y, or equivalently, the remainder of x after floored division by y, i.e. x - y*fld(x,y) if computed without intermediate rounding.

      The result will have the same sign as y, and magnitude less than abs(y) (with some exceptions, see note below).

      Note

      When used with floating point values, the exact result may not be representable by the type, and so rounding error may occur. In particular, if the exact result is very close to y, then it may be rounded to y.

      1. julia> mod(8, 3)
      2. 2
      3. julia> mod(9, 3)
      4. 0
      5. julia> mod(8.9, 3)
      6. 2.9000000000000004
      7. julia> mod(eps(), 3)
      8. 2.220446049250313e-16
      9. julia> mod(-eps(), 3)
      10. 3.0

      1. rem(x::Integer, T::Type{<:Integer}) -> T
      2. mod(x::Integer, T::Type{<:Integer}) -> T
      3. %(x::Integer, T::Type{<:Integer}) -> T

      Find y::T such that xy (mod n), where n is the number of integers representable in T, and y is an integer in [typemin(T),typemax(T)]. If T can represent any integer (e.g. T == BigInt), then this operation corresponds to a conversion to T.

      Examples

      1. julia> 129 % Int8
      2. -127

      source

      — Function.

      1. rem(x, y)
      2. %(x, y)

      Remainder from Euclidean division, returning a value of the same sign as x, and smaller in magnitude than y. This value is always exact.

      Examples

      1. julia> x = 15; y = 4;
      2. julia> x % y
      3. 3
      4. julia> x == div(x, y) * y + rem(x, y)
      5. true

      source

      — Function.

      1. rem2pi(x, r::RoundingMode)

      Compute the remainder of x after integer division by , with the quotient rounded according to the rounding mode r. In other words, the quantity

      1. x - 2π*round(x/(2π),r)

      without any intermediate rounding. This internally uses a high precision approximation of 2π, and so will give a more accurate result than rem(x,2π,r)

      • if r == RoundNearest, then the result is in the interval $[-π, π]$. This will generally be the most accurate result. See also RoundNearest.

      • if r == RoundToZero, then the result is in the interval $[0, 2π]$ if x is positive,. or $[-2π, 0]$ otherwise. See also .

      • if r == RoundDown, then the result is in the interval $[0, 2π]$. See also RoundDown.

      Examples

      1. julia> rem2pi(7pi/4, RoundNearest)
      2. -0.7853981633974485
      3. julia> rem2pi(7pi/4, RoundDown)
      4. 5.497787143782138

      Base.Math.mod2pi — Function.

      1. mod2pi(x)

      Modulus after division by , returning in the range $[0,2π)$.

      This function computes a floating point representation of the modulus after division by numerically exact , and is therefore not exactly the same as mod(x,2π), which would compute the modulus of x relative to division by the floating-point number .

      Examples

      1. julia> mod2pi(9*pi/4)
      2. 0.7853981633974481

      Base.divrem — Function.

      1. divrem(x, y)

      The quotient and remainder from Euclidean division. Equivalent to (div(x,y), rem(x,y)) or (x÷y, x%y).

      Examples

      1. julia> divrem(3,7)
      2. (0, 3)
      3. julia> divrem(7,3)
      4. (2, 1)

      Base.fldmod — Function.

      1. fldmod(x, y)

      The floored quotient and modulus after division. Equivalent to (fld(x,y), mod(x,y)).

      Base.fld1 — Function.

      1. fld1(x, y)

      Flooring division, returning a value consistent with mod1(x,y)

      See also: , fldmod1.

      Examples

      1. julia> x = 15; y = 4;
      2. julia> fld1(x, y)
      3. 4
      4. julia> x == fld(x, y) * y + mod(x, y)
      5. true
      6. julia> x == (fld1(x, y) - 1) * y + mod1(x, y)
      7. true

      Base.mod1 — Function.

      1. mod1(x, y)

      Modulus after flooring division, returning a value r such that mod(r, y) == mod(x, y) in the range $(0, y]$ for positive y and in the range $[y,0)$ for negative y.

      See also: , fldmod1.

      Examples

      1. julia> mod1(4, 2)
      2. 2
      3. julia> mod1(4, 3)
      4. 1

      Base.fldmod1 — Function.

      1. fldmod1(x, y)

      Return (fld1(x,y), mod1(x,y)).

      See also: , mod1.

      Base.:// — Function.

      1. //(num, den)

      Divide two integers or rational numbers, giving a result.

      Examples

      1. julia> 3 // 5
      2. 3//5
      3. julia> (3 // 5) // (2 // 1)
      4. 3//10

      source

      — Function.

      1. rationalize([T<:Integer=Int,] x; tol::Real=eps(x))

      Approximate floating point number x as a Rational number with components of the given integer type. The result will differ from x by no more than tol.

      Examples

      1. julia> rationalize(5.6)
      2. 28//5
      3. julia> a = rationalize(BigInt, 10.3)
      4. 103//10
      5. julia> typeof(numerator(a))
      6. BigInt

      Base.numerator — Function.

      1. numerator(x)

      Numerator of the rational representation of x.

      Examples

      1. julia> numerator(2//3)
      2. 2
      3. julia> numerator(4)
      4. 4

      Base.denominator — Function.

      1. denominator(x)

      Denominator of the rational representation of x.

      Examples

      1. julia> denominator(2//3)
      2. 3
      3. julia> denominator(4)
      4. 1

      Base.:<< — Function.

      1. <<(x, n)

      Left bit shift operator, x << n. For n >= 0, the result is x shifted left by n bits, filling with 0s. This is equivalent to x * 2^n. For n < 0, this is equivalent to x >> -n.

      Examples

      julia> Int8(3) << 2
      12
      
      julia> bitstring(Int8(3))
      "00000011"
      
      julia> bitstring(Int8(12))
      "00001100"
      

      See also , >>>.

      <<(B::BitVector, n) -> BitVector
      

      Left bit shift operator, B << n. For n >= 0, the result is B with elements shifted n positions backwards, filling with false values. If n < 0, elements are shifted forwards. Equivalent to B >> -n.

      Examples

      julia> B = BitVector([true, false, true, false, false])
      5-element BitArray{1}:
       1
       0
       1
       0
       0
      
      julia> B << 1
      5-element BitArray{1}:
       0
       1
       0
       0
       0
      
      julia> B << -1
      5-element BitArray{1}:
       0
       1
       0
       1
       0
      

      source

      — Function.

      >>(x, n)
      

      Right bit shift operator, x >> n. For n >= 0, the result is x shifted right by n bits, where n >= 0, filling with 0s if x >= 0, 1s if x < 0, preserving the sign of x. This is equivalent to fld(x, 2^n). For n < 0, this is equivalent to x << -n.

      Examples

      julia> Int8(13) >> 2
      3
      
      julia> bitstring(Int8(13))
      "00001101"
      
      julia> bitstring(Int8(3))
      "00000011"
      
      julia> Int8(-14) >> 2
      -4
      
      julia> bitstring(Int8(-14))
      "11110010"
      
      julia> bitstring(Int8(-4))
      "11111100"
      

      See also >>>, .

      source

      >>(B::BitVector, n) -> BitVector
      

      Right bit shift operator, B >> n. For n >= 0, the result is B with elements shifted n positions forward, filling with false values. If n < 0, elements are shifted backwards. Equivalent to B << -n.

      Examples

      julia> B = BitVector([true, false, true, false, false])
      5-element BitArray{1}:
       1
       0
       1
       0
       0
      
      julia> B >> 1
      5-element BitArray{1}:
       0
       1
       0
       1
       0
      
      julia> B >> -1
      5-element BitArray{1}:
       0
       1
       0
       0
       0
      

      Base.:>>> — Function.

      >>>(x, n)
      

      Unsigned right bit shift operator, x >>> n. For n >= 0, the result is x shifted right by n bits, where n >= 0, filling with 0s. For n < 0, this is equivalent to x << -n.

      For integer types, this is equivalent to >>. For integer types, this is equivalent to signed(unsigned(x) >> n).

      Examples

      julia> Int8(-14) >>> 2
      60
      
      julia> bitstring(Int8(-14))
      "11110010"
      
      julia> bitstring(Int8(60))
      "00111100"
      

      BigInts are treated as if having infinite size, so no filling is required and this is equivalent to .

      See also >>, .

      source

      >>>(B::BitVector, n) -> BitVector
      

      Unsigned right bitshift operator, B >>> n. Equivalent to B >> n. See for details and examples.

      source

      — Function.

      Range operator. a:b constructs a range from a to b with a step size of 1 (a UnitRange) , and a:s:b is similar but uses a step size of s (a ).

      : is also used in indexing to select whole dimensions and for Symbol literals, as in e.g. :hello.

      (:)(I::CartesianIndex, J::CartesianIndex)
      

      Construct CartesianIndices from two CartesianIndex.

      Julia 1.1

      This method requires at least Julia 1.1.

      Examples

      julia> I = CartesianIndex(2,1);
      
      julia> J = CartesianIndex(3,3);
      
      julia> I:J
      2×3 CartesianIndices{2,Tuple{UnitRange{Int64},UnitRange{Int64}}}:
       CartesianIndex(2, 1)  CartesianIndex(2, 2)  CartesianIndex(2, 3)
       CartesianIndex(3, 1)  CartesianIndex(3, 2)  CartesianIndex(3, 3)
      

      Base.range — Function.

      range(start[, stop]; length, stop, step=1)
      

      Given a starting value, construct a range either by length or from start to stop, optionally with a given step (defaults to 1, a ). One of length or stop is required. If length, stop, and step are all specified, they must agree.

      If length and stop are provided and step is not, the step size will be computed automatically such that there are length linearly spaced elements in the range (a LinRange).

      If step and stop are provided and length is not, the overall range length will be computed automatically such that the elements are step spaced (a ).

      stop may be specified as either a positional or keyword argument.

      Julia 1.1

      stop as a positional argument requires at least Julia 1.1.

      Examples

      julia> range(1, length=100)
      1:100
      
      julia> range(1, stop=100)
      1:100
      
      julia> range(1, step=5, length=100)
      1:5:496
      
      julia> range(1, step=5, stop=100)
      1:5:96
      
      julia> range(1, 10, length=101)
      1.0:0.09:10.0
      
      julia> range(1, 100, step=5)
      1:5:96
      

      source

      — Type.

      Base.OneTo(n)
      

      Define an AbstractUnitRange that behaves like 1:n, with the added distinction that the lower limit is guaranteed (by the type system) to be 1.

      source

      — Type.

      StepRangeLen{T,R,S}(ref::R, step::S, len, [offset=1]) where {T,R,S}
      StepRangeLen(       ref::R, step::S, len, [offset=1]) where {  R,S}
      

      A range r where r[i] produces values of type T (in the second form, T is deduced automatically), parameterized by a reference value, a step, and the length. By default ref is the starting value r[1], but alternatively you can supply it as the value of r[offset] for some other index 1 <= offset <= len. In conjunction with TwicePrecision this can be used to implement ranges that are free of roundoff error.

      source

      — Function.

      ==(x, y)
      

      Generic equality operator. Falls back to ===. Should be implemented for all types with a notion of equality, based on the abstract value that an instance represents. For example, all numeric types are compared by numeric value, ignoring type. Strings are compared as sequences of characters, ignoring encoding. For collections, == is generally called recursively on all contents, though other properties (like the shape for arrays) may also be taken into account.

      This operator follows IEEE semantics for floating-point numbers: 0.0 == -0.0 and NaN != NaN.

      The result is of type Bool, except when one of the operands is , in which case missing is returned (three-valued logic). For collections, missing is returned if at least one of the operands contains a missing value and all non-missing values are equal. Use or === to always get a Bool result.

      Implementation

      New numeric types should implement this function for two arguments of the new type, and handle comparison to other types via promotion rules where possible.

      falls back to ==, so new methods of == will be used by the Dict type to compare keys. If your type will be used as a dictionary key, it should therefore also implement .

      source

      ==(x)
      

      Create a function that compares its argument to x using , i.e. a function equivalent to y -> y == x.

      The returned function is of type Base.Fix2{typeof(==)}, which can be used to implement specialized methods.

      source

      ==(a::AbstractString, b::AbstractString) -> Bool
      

      Test whether two strings are equal character by character (technically, Unicode code point by code point).

      Examples

      julia> "abc" == "abc"
      true
      
      julia> "abc" == "αβγ"
      false
      

      Base.:!= — Function.

      !=(x, y)
      ≠(x,y)
      

      Not-equals comparison operator. Always gives the opposite answer as .

      Implementation

      New types should generally not implement this, and rely on the fallback definition !=(x,y) = !(x==y) instead.

      Examples

      julia> 3 != 2
      true
      
      julia> "foo" ≠ "foo"
      false
      

      source

      !=(x)
      

      Create a function that compares its argument to x using , i.e. a function equivalent to y -> y != x. The returned function is of type Base.Fix2{typeof(!=)}, which can be used to implement specialized methods.

      Julia 1.2

      This functionality requires at least Julia 1.2.

      source

      — Function.

      !==(x, y)
      ≢(x,y)
      

      Always gives the opposite answer as ===.

      Examples

      julia> a = [1, 2]; b = [1, 2];
      
      julia> a ≢ b
      true
      
      julia> a ≢ a
      false
      

      Base.:< — Function.

      <(x, y)
      

      Less-than comparison operator. Falls back to . Because of the behavior of floating-point NaN values, this operator implements a partial order.

      Implementation

      New numeric types with a canonical partial order should implement this function for two arguments of the new type. Types with a canonical total order should implement isless instead. (x < y) | (x == y)

      Examples

      julia> 'a' < 'b'
      true
      
      julia> "abc" < "abd"
      true
      
      julia> 5 < 3
      false
      

      <(x)
      

      Create a function that compares its argument to x using <, i.e. a function equivalent to y -> y < x. The returned function is of type Base.Fix2{typeof(<)}, which can be used to implement specialized methods.

      Julia 1.2

      This functionality requires at least Julia 1.2.

      Base.:<= — Function.

      <=(x, y)
      ≤(x,y)
      

      Less-than-or-equals comparison operator. Falls back to (x < y) | (x == y).

      Examples

      julia> 'a' <= 'b'
      true
      
      julia> 7 ≤ 7 ≤ 9
      true
      
      julia> "abc" ≤ "abc"
      true
      
      julia> 5 <= 3
      false
      

      <=(x)
      

      Create a function that compares its argument to x using <=, i.e. a function equivalent to y -> y <= x. The returned function is of type Base.Fix2{typeof(<=)}, which can be used to implement specialized methods.

      Julia 1.2

      This functionality requires at least Julia 1.2.

      Base.:> — Function.

      >(x, y)
      

      Greater-than comparison operator. Falls back to y < x.

      Implementation

      Generally, new types should implement instead of this function, and rely on the fallback definition >(x, y) = y < x.

      Examples

      julia> 'a' > 'b'
      false
      
      julia> 7 > 3 > 1
      true
      
      julia> "abc" > "abd"
      false
      
      julia> 5 > 3
      true
      

      source

      >(x)
      

      Create a function that compares its argument to x using , i.e. a function equivalent to y -> y > x. The returned function is of type Base.Fix2{typeof(>)}, which can be used to implement specialized methods.

      Julia 1.2

      This functionality requires at least Julia 1.2.

      source

      — Function.

      >=(x, y)
      ≥(x,y)
      

      Greater-than-or-equals comparison operator. Falls back to y <= x.

      Examples

      julia> 'a' >= 'b'
      false
      
      julia> 7 ≥ 7 ≥ 3
      true
      
      julia> "abc" ≥ "abc"
      true
      
      julia> 5 >= 3
      true
      

      source

      >=(x)
      

      Create a function that compares its argument to x using , i.e. a function equivalent to y -> y >= x. The returned function is of type Base.Fix2{typeof(>=)}, which can be used to implement specialized methods.

      Julia 1.2

      This functionality requires at least Julia 1.2.

      source

      — Function.

      cmp(x,y)
      

      Return -1, 0, or 1 depending on whether x is less than, equal to, or greater than y, respectively. Uses the total order implemented by isless.

      Examples

      julia> cmp(1, 2)
      -1
      
      julia> cmp(2, 1)
      1
      
      julia> cmp(2+im, 3-im)
      ERROR: MethodError: no method matching isless(::Complex{Int64}, ::Complex{Int64})
      [...]
      

      source

      Return -1, 0, or 1 depending on whether x is less than, equal to, or greater than y, respectively. The first argument specifies a less-than comparison function to use.

      cmp(a::AbstractString, b::AbstractString) -> Int
      

      Compare two strings. Return 0 if both strings have the same length and the character at each index is the same in both strings. Return -1 if a is a prefix of b, or if a comes before b in alphabetical order. Return 1 if b is a prefix of a, or if b comes before a in alphabetical order (technically, lexicographical order by Unicode code points).

      julia> cmp("abc", "abc")
      0
      
      julia> cmp("ab", "abc")
      -1
      
      julia> cmp("abc", "ab")
      1
      
      julia> cmp("ab", "ac")
      -1
      
      julia> cmp("ac", "ab")
      1
      
      julia> cmp("α", "a")
      1
      
      julia> cmp("b", "β")
      -1
      

      source

      — Function.

      ~(x)
      

      Bitwise not.

      Examples

      julia> ~4
      -5
      
      julia> ~10
      -11
      
      julia> ~true
      false
      

      source

      — Function.

      &(x, y)
      

      Bitwise and. Implements three-valued logic, returning if one operand is missing and the other is true.

      Examples

      julia> 4 & 10
      0
      
      julia> 4 & 12
      4
      
      julia> true & missing
      missing
      
      julia> false & missing
      false
      

      source

      — Function.

      |(x, y)
      

      Bitwise or. Implements three-valued logic, returning if one operand is missing and the other is false.

      Examples

      julia> 4 | 10
      14
      
      julia> 4 | 1
      5
      
      julia> true | missing
      true
      
      julia> false | missing
      missing
      

      source

      — Function.

      xor(x, y)
      ⊻(x, y)
      

      Bitwise exclusive or of x and y. Implements three-valued logic, returning if one of the arguments is missing.

      The infix operation a ⊻ b is a synonym for xor(a,b), and can be typed by tab-completing \xor or \veebar in the Julia REPL.

      Examples

      julia> xor(true, false)
      true
      
      julia> xor(true, true)
      false
      
      julia> xor(true, missing)
      missing
      
      julia> false ⊻ false
      false
      
      julia> [true; true; false] .⊻ [true; false; false]
      3-element BitArray{1}:
       0
       1
       0
      

      source

      — Function.

      !(x)
      

      Boolean not. Implements three-valued logic, returning if x is missing.

      Examples

      julia> !true
      false
      
      julia> !false
      true
      
      julia> !missing
      missing
      
      julia> .![true false true]
      1×3 BitArray{2}:
       0  1  0
      

      source

      !f::Function
      

      Predicate function negation: when the argument of ! is a function, it returns a function which computes the boolean negation of f.

      Examples

      julia> str = "∀ ε > 0, ∃ δ > 0: |x-y| < δ ⇒ |f(x)-f(y)| < ε"
      "∀ ε > 0, ∃ δ > 0: |x-y| < δ ⇒ |f(x)-f(y)| < ε"
      
      julia> filter(isletter, str)
      "εδxyδfxfyε"
      
      julia> filter(!isletter, str)
      "∀  > 0, ∃  > 0: |-| <  ⇒ |()-()| < "
      

      && — Keyword.

      x && y
      

      Short-circuiting boolean AND.

      || — Keyword.

      x || y
      

      Short-circuiting boolean OR.

      Mathematical Functions

      Base.isapprox — Function.

      isapprox(x, y; rtol::Real=atol>0 ? 0 : √eps, atol::Real=0, nans::Bool=false, norm::Function)
      

      Inexact equality comparison: true if norm(x-y) <= max(atol, rtol*max(norm(x), norm(y))). The default atol is zero and the default rtol depends on the types of x and y. The keyword argument nans determines whether or not NaN values are considered equal (defaults to false).

      For real or complex floating-point values, if an atol > 0 is not specified, rtol defaults to the square root of of the type of x or y, whichever is bigger (least precise). This corresponds to requiring equality of about half of the significand digits. Otherwise, e.g. for integer arguments or if an atol > 0 is supplied, rtol defaults to zero.

      x and y may also be arrays of numbers, in which case norm defaults to the usual norm function in LinearAlgebra, but may be changed by passing a norm::Function keyword argument. (For numbers, norm is the same thing as abs.) When x and y are arrays, if norm(x-y) is not finite (i.e. ±Inf or NaN), the comparison falls back to checking whether all elements of x and y are approximately equal component-wise.

      The binary operator is equivalent to isapprox with the default arguments, and x ≉ y is equivalent to !isapprox(x,y).

      Note that x ≈ 0 (i.e., comparing to zero with the default tolerances) is equivalent to x == 0 since the default atol is 0. In such cases, you should either supply an appropriate atol (or use norm(x) ≤ atol) or rearrange your code (e.g. use x ≈ y rather than x - y ≈ 0). It is not possible to pick a nonzero atol automatically because it depends on the overall scaling (the “units”) of your problem: for example, in x - y ≈ 0, atol=1e-9 is an absurdly small tolerance if x is the radius of the Earth in meters, but an absurdly large tolerance if x is the in meters.

      Examples

      julia> 0.1 ≈ (0.1 - 1e-10)
      true
      
      julia> isapprox(10, 11; atol = 2)
      true
      
      julia> isapprox([10.0^9, 1.0], [10.0^9, 2.0])
      true
      
      julia> 1e-10 ≈ 0
      false
      
      julia> isapprox(1e-10, 0, atol=1e-8)
      true
      

      source

      — Method.

      sin(x)
      

      Compute sine of x, where x is in radians.

      source

      — Method.

      cos(x)
      

      Compute cosine of x, where x is in radians.

      source

      — Method.

      sincos(x)
      

      Simultaneously compute the sine and cosine of x, where the x is in radians.

      source

      — Method.

      tan(x)
      

      Compute tangent of x, where x is in radians.

      source

      — Function.

      sind(x)
      

      Compute sine of x, where x is in degrees.

      source

      — Function.

      cosd(x)
      

      Compute cosine of x, where x is in degrees.

      source

      — Function.

      tand(x)
      

      Compute tangent of x, where x is in degrees.

      source

      — Function.

      sinpi(x)
      

      Compute $\sin(\pi x)$ more accurately than sin(pi*x), especially for large x.

      source

      — Function.

      cospi(x)
      

      Compute $\cos(\pi x)$ more accurately than cos(pi*x), especially for large x.

      source

      — Method.

      sinh(x)
      

      Compute hyperbolic sine of x.

      source

      — Method.

      cosh(x)
      

      Compute hyperbolic cosine of x.

      source

      — Method.

      tanh(x)
      

      Compute hyperbolic tangent of x.

      source

      — Method.

      asin(x)
      

      Compute the inverse sine of x, where the output is in radians.

      source

      — Method.

      acos(x)
      

      Compute the inverse cosine of x, where the output is in radians

      source

      — Method.

      atan(y)
      atan(y, x)
      

      Compute the inverse tangent of y or y/x, respectively.

      For one argument, this is the angle in radians between the positive x-axis and the point (1, y), returning a value in the interval $[-\pi/2, \pi/2]$.

      For two arguments, this is the angle in radians between the positive x-axis and the point (x, y), returning a value in the interval $[-\pi, \pi]$. This corresponds to a standard atan2 function.

      Base.Math.asind — Function.

      asind(x)
      

      Compute the inverse sine of x, where the output is in degrees.

      Base.Math.acosd — Function.

      acosd(x)
      

      Compute the inverse cosine of x, where the output is in degrees.

      Base.Math.atand — Function.

      atand(y)
      atand(y,x)
      

      Compute the inverse tangent of y or y/x, respectively, where the output is in degrees.

      Base.Math.sec — Method.

      sec(x)
      

      Compute the secant of x, where x is in radians.

      Base.Math.csc — Method.

      csc(x)
      

      Compute the cosecant of x, where x is in radians.

      Base.Math.cot — Method.

      cot(x)
      

      Compute the cotangent of x, where x is in radians.

      Base.Math.secd — Function.

      secd(x)
      

      Compute the secant of x, where x is in degrees.

      Base.Math.cscd — Function.

      cscd(x)
      

      Compute the cosecant of x, where x is in degrees.

      Base.Math.cotd — Function.

      cotd(x)
      

      Compute the cotangent of x, where x is in degrees.

      Base.Math.asec — Method.

      asec(x)
      

      Compute the inverse secant of x, where the output is in radians.

      Base.Math.acsc — Method.

      acsc(x)
      

      Compute the inverse cosecant of x, where the output is in radians.

      Base.Math.acot — Method.

      acot(x)
      

      Compute the inverse cotangent of x, where the output is in radians.

      Base.Math.asecd — Function.

      asecd(x)
      

      Compute the inverse secant of x, where the output is in degrees.

      Base.Math.acscd — Function.

      acscd(x)
      

      Compute the inverse cosecant of x, where the output is in degrees.

      Base.Math.acotd — Function.

      acotd(x)
      

      Compute the inverse cotangent of x, where the output is in degrees.

      Base.Math.sech — Method.

      sech(x)
      

      Compute the hyperbolic secant of x.

      Base.Math.csch — Method.

      csch(x)
      

      Compute the hyperbolic cosecant of x.

      Base.Math.coth — Method.

      coth(x)
      

      Compute the hyperbolic cotangent of x.

      Base.asinh — Method.

      asinh(x)
      

      Compute the inverse hyperbolic sine of x.

      Base.acosh — Method.

      acosh(x)
      

      Compute the inverse hyperbolic cosine of x.

      Base.atanh — Method.

      atanh(x)
      

      Compute the inverse hyperbolic tangent of x.

      Base.Math.asech — Method.

      asech(x)
      

      Compute the inverse hyperbolic secant of x.

      Base.Math.acsch — Method.

      acsch(x)
      

      Compute the inverse hyperbolic cosecant of x.

      Base.Math.acoth — Method.

      acoth(x)
      

      Compute the inverse hyperbolic cotangent of x.

      Base.Math.sinc — Function.

      sinc(x)
      

      Compute $\sin(\pi x) / (\pi x)$ if $x \neq 0$, and $1$ if $x = 0$.

      Base.Math.cosc — Function.

      cosc(x)
      

      Compute $\cos(\pi x) / x - \sin(\pi x) / (\pi x^2)$ if $x \neq 0$, and $0$ if $x = 0$. This is the derivative of sinc(x).

      Base.Math.deg2rad — Function.

      deg2rad(x)
      

      Convert x from degrees to radians.

      Examples

      julia> deg2rad(90)
      1.5707963267948966
      

      Base.Math.rad2deg — Function.

      rad2deg(x)
      

      Convert x from radians to degrees.

      Examples

      julia> rad2deg(pi)
      180.0
      

      Base.Math.hypot — Function.

      hypot(x, y)
      

      Compute the hypotenuse $\sqrt{|x|^2+|y|^2}$ avoiding overflow and underflow.

      This code is an implementation of the algorithm described in: An Improved Algorithm for hypot(a,b) by Carlos F. Borges The article is available online at ArXiv at the link

      Examples

      julia> a = Int64(10)^10;
      
      julia> hypot(a, a)
      1.4142135623730951e10
      
      julia> √(a^2 + a^2) # a^2 overflows
      ERROR: DomainError with -2.914184810805068e18:
      sqrt will only return a complex result if called with a complex argument. Try sqrt(Complex(x)).
      Stacktrace:
      [...]
      
      julia> hypot(3, 4im)
      5.0
      

      source

      hypot(x...)
      

      Compute the hypotenuse $\sqrt{\sum |x_i|^2}$ avoiding overflow and underflow.

      Examples

      julia> hypot(-5.7)
      5.7
      
      julia> hypot(3, 4im, 12.0)
      13.0
      

      Base.log — Method.

      log(x)
      

      Compute the natural logarithm of x. Throws for negative Real arguments. Use complex negative arguments to obtain complex results.

      Examples

      julia> log(2)
      0.6931471805599453
      
      julia> log(-3)
      ERROR: DomainError with -3.0:
      log will only return a complex result if called with a complex argument. Try log(Complex(x)).
      Stacktrace:
       [1] throw_complex_domainerror(::Symbol, ::Float64) at ./math.jl:31
      [...]
      

      Base.log — Method.

      log(b,x)
      

      Compute the base b logarithm of x. Throws for negative arguments.

      Examples

      julia> log(4,8)
      1.5
      
      julia> log(4,2)
      0.5
      
      julia> log(-2, 3)
      ERROR: DomainError with -2.0:
      log will only return a complex result if called with a complex argument. Try log(Complex(x)).
      Stacktrace:
       [1] throw_complex_domainerror(::Symbol, ::Float64) at ./math.jl:31
      [...]
      
      julia> log(2, -3)
      ERROR: DomainError with -3.0:
      log will only return a complex result if called with a complex argument. Try log(Complex(x)).
      Stacktrace:
       [1] throw_complex_domainerror(::Symbol, ::Float64) at ./math.jl:31
      [...]
      

      Note

      If b is a power of 2 or 10, or log10 should be used, as these will typically be faster and more accurate. For example,

      julia> log(100,1000000)
      2.9999999999999996
      
      julia> log10(1000000)/2
      3.0
      

      Base.log2 — Function.

      log2(x)
      

      Compute the logarithm of x to base 2. Throws for negative Real arguments.

      Examples

      julia> log2(4)
      2.0
      
      julia> log2(10)
      3.321928094887362
      
      julia> log2(-2)
      ERROR: DomainError with -2.0:
      NaN result for non-NaN input.
      Stacktrace:
       [1] nan_dom_err at ./math.jl:325 [inlined]
      [...]
      

      Base.log10 — Function.

      log10(x)
      

      Compute the logarithm of x to base 10. Throws for negative Real arguments.

      Examples

      julia> log10(100)
      2.0
      
      julia> log10(2)
      0.3010299956639812
      
      julia> log10(-2)
      ERROR: DomainError with -2.0:
      NaN result for non-NaN input.
      Stacktrace:
       [1] nan_dom_err at ./math.jl:325 [inlined]
      [...]
      

      Base.log1p — Function.

      log1p(x)
      

      Accurate natural logarithm of 1+x. Throws for Real arguments less than -1.

      Examples

      julia> log1p(-0.5)
      -0.6931471805599453
      
      julia> log1p(0)
      0.0
      
      julia> log1p(-2)
      ERROR: DomainError with -2.0:
      log1p will only return a complex result if called with a complex argument. Try log1p(Complex(x)).
      Stacktrace:
       [1] throw_complex_domainerror(::Symbol, ::Float64) at ./math.jl:31
      [...]
      

      Base.Math.frexp — Function.

      frexp(val)
      

      Return (x,exp) such that x has a magnitude in the interval $[1/2, 1)$ or 0, and val is equal to $x \times 2^{exp}$.

      Base.exp — Method.

      exp(x)
      

      Compute the natural base exponential of x, in other words $e^x$.

      Examples

      julia> exp(1.0)
      2.718281828459045
      

      Base.exp2 — Function.

      exp2(x)
      

      Compute the base 2 exponential of x, in other words $2^x$.

      Examples

      julia> exp2(5)
      32.0
      

      Base.exp10 — Function.

      exp10(x)
      

      Compute the base 10 exponential of x, in other words $10^x$.

      Examples

      julia> exp10(2)
      100.0
      

      exp10(x)
      

      Compute $10^x$.

      Examples

      julia> exp10(2)
      100.0
      
      julia> exp10(0.2)
      1.5848931924611136
      

      source

      — Function.

      ldexp(x, n)
      

      Compute $x \times 2^n$.

      Examples

      julia> ldexp(5., 2)
      20.0
      

      source

      — Function.

      modf(x)
      

      Return a tuple (fpart, ipart) of the fractional and integral parts of a number. Both parts have the same sign as the argument.

      Examples

      julia> modf(3.5)
      (0.5, 3.0)
      
      julia> modf(-3.5)
      (-0.5, -3.0)
      

      source

      — Function.

      expm1(x)
      

      Accurately compute $e^x-1$.

      source

      — Method.

      round([T,] x, [r::RoundingMode])
      round(x, [r::RoundingMode]; digits::Integer=0, base = 10)
      round(x, [r::RoundingMode]; sigdigits::Integer, base = 10)
      

      Rounds the number x.

      Without keyword arguments, x is rounded to an integer value, returning a value of type T, or of the same type of x if no T is provided. An InexactError will be thrown if the value is not representable by T, similar to .

      If the digits keyword argument is provided, it rounds to the specified number of digits after the decimal place (or before if negative), in base base.

      If the sigdigits keyword argument is provided, it rounds to the specified number of significant digits, in base base.

      The RoundingMode r controls the direction of the rounding; the default is , which rounds to the nearest integer, with ties (fractional values of 0.5) being rounded to the nearest even integer. Note that round may give incorrect results if the global rounding mode is changed (see rounding).

      Examples

      julia> round(1.7)
      2.0
      
      julia> round(Int, 1.7)
      2
      
      julia> round(1.5)
      2.0
      
      julia> round(2.5)
      2.0
      
      julia> round(pi; digits=2)
      3.14
      
      julia> round(pi; digits=3, base=2)
      3.125
      
      julia> round(123.456; sigdigits=2)
      120.0
      
      julia> round(357.913; sigdigits=4, base=2)
      352.0
      

      Note

      Rounding to specified digits in bases other than 2 can be inexact when operating on binary floating point numbers. For example, the value represented by 1.15 is actually less than 1.15, yet will be rounded to 1.2.

      Examples

      julia> x = 1.15
      1.15
      
      julia> @sprintf "%.20f" x
      "1.14999999999999991118"
      
      julia> x < 115//100
      true
      
      julia> round(x, digits=1)
      1.2
      

      Extensions

      To extend round to new numeric types, it is typically sufficient to define Base.round(x::NewType, r::RoundingMode).

      source

      — Type.

      A type used for controlling the rounding mode of floating point operations (via rounding/ functions), or as optional arguments for rounding to the nearest integer (via the round function).

      Base.Rounding.RoundNearest — Constant.

      RoundNearest
      

      The default rounding mode. Rounds to the nearest integer, with ties (fractional values of 0.5) being rounded to the nearest even integer.

      Base.Rounding.RoundNearestTiesAway — Constant.

      RoundNearestTiesAway
      

      Rounds to nearest integer, with ties rounded away from zero (C/C++ behaviour).

      source

      — Constant.

      RoundNearestTiesUp
      

      Rounds to nearest integer, with ties rounded toward positive infinity (Java/JavaScript round behaviour).

      Base.Rounding.RoundToZero — Constant.

      RoundToZero
      

      using this rounding mode is an alias for trunc.

      Base.Rounding.RoundFromZero — Constant.

      RoundFromZero
      

      Rounds away from zero. This rounding mode may only be used with T == BigFloat inputs to .

      Examples

      julia> BigFloat("1.0000000000000001", 5, RoundFromZero)
      1.06
      

      source

      — Constant.

      RoundUp
      

      round using this rounding mode is an alias for .

      source

      — Constant.

      RoundDown
      

      round using this rounding mode is an alias for .

      source

      — Method.

      round(z::Complex[, RoundingModeReal, [RoundingModeImaginary]])
      round(z::Complex[, RoundingModeReal, [RoundingModeImaginary]]; digits=, base=10)
      round(z::Complex[, RoundingModeReal, [RoundingModeImaginary]]; sigdigits=, base=10)
      

      Return the nearest integral value of the same type as the complex-valued z to z, breaking ties using the specified RoundingModes. The first is used for rounding the real components while the second is used for rounding the imaginary components.

      Example

      julia> round(3.14 + 4.5im)
      3.0 + 4.0im
      

      source

      — Function.

      ceil([T,] x)
      ceil(x; digits::Integer= [, base = 10])
      ceil(x; sigdigits::Integer= [, base = 10])
      

      ceil(x) returns the nearest integral value of the same type as x that is greater than or equal to x.

      ceil(T, x) converts the result to type T, throwing an InexactError if the value is not representable.

      digits, sigdigits and base work as for round.

      Base.floor — Function.

      floor([T,] x)
      floor(x; digits::Integer= [, base = 10])
      floor(x; sigdigits::Integer= [, base = 10])
      

      floor(x) returns the nearest integral value of the same type as x that is less than or equal to x.

      floor(T, x) converts the result to type T, throwing an InexactError if the value is not representable.

      digits, sigdigits and base work as for .

      source

      — Function.

      trunc([T,] x)
      trunc(x; digits::Integer= [, base = 10])
      trunc(x; sigdigits::Integer= [, base = 10])
      

      trunc(x) returns the nearest integral value of the same type as x whose absolute value is less than or equal to x.

      trunc(T, x) converts the result to type T, throwing an InexactError if the value is not representable.

      digits, sigdigits and base work as for round.

      Base.unsafe_trunc — Function.

      unsafe_trunc(T, x)
      

      Return the nearest integral value of type T whose absolute value is less than or equal to x. If the value is not representable by T, an arbitrary value will be returned.

      Base.min — Function.

      min(x, y, ...)
      

      Return the minimum of the arguments. See also the function to take the minimum element from a collection.

      Examples

      julia> min(2, 5, 1)
      1
      

      source

      — Function.

      max(x, y, ...)
      

      Return the maximum of the arguments. See also the maximum function to take the maximum element from a collection.

      Examples

      julia> max(2, 5, 1)
      5
      

      Base.minmax — Function.

      minmax(x, y)
      

      Return (min(x,y), max(x,y)). See also: that returns (minimum(x), maximum(x)).

      Examples

      julia> minmax('c','b')
      ('b', 'c')
      

      source

      — Function.

      clamp(x, lo, hi)
      

      Return x if lo <= x <= hi. If x > hi, return hi. If x < lo, return lo. Arguments are promoted to a common type.

      Examples

      julia> clamp.([pi, 1.0, big(10.)], 2., 9.)
      3-element Array{BigFloat,1}:
       3.141592653589793238462643383279502884197169399375105820974944592307816406286198
       2.0
       9.0
      
      julia> clamp.([11,8,5],10,6) # an example where lo > hi
      3-element Array{Int64,1}:
        6
        6
       10
      

      source

      — Function.

      clamp!(array::AbstractArray, lo, hi)
      

      Restrict values in array to the specified range, in-place. See also clamp.

      Base.abs — Function.

      abs(x)
      

      The absolute value of x.

      When abs is applied to signed integers, overflow may occur, resulting in the return of a negative value. This overflow occurs only when abs is applied to the minimum representable value of a signed integer. That is, when x == typemin(typeof(x)), abs(x) == x < 0, not -x as might be expected.

      Examples

      julia> abs(-3)
      3
      
      julia> abs(1 + im)
      1.4142135623730951
      
      julia> abs(typemin(Int64))
      -9223372036854775808
      

      Base.Checked.checked_abs — Function.

      Base.checked_abs(x)
      

      Calculates abs(x), checking for overflow errors where applicable. For example, standard two’s complement signed integers (e.g. Int) cannot represent abs(typemin(Int)), thus leading to an overflow.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_neg — Function.

      Base.checked_neg(x)
      

      Calculates -x, checking for overflow errors where applicable. For example, standard two’s complement signed integers (e.g. Int) cannot represent -typemin(Int), thus leading to an overflow.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_add — Function.

      Base.checked_add(x, y)
      

      Calculates x+y, checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_sub — Function.

      Base.checked_sub(x, y)
      

      Calculates x-y, checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_mul — Function.

      Base.checked_mul(x, y)
      

      Calculates x*y, checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_div — Function.

      Base.checked_div(x, y)
      

      Calculates div(x,y), checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_rem — Function.

      Base.checked_rem(x, y)
      

      Calculates x%y, checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_fld — Function.

      Base.checked_fld(x, y)
      

      Calculates fld(x,y), checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_mod — Function.

      Base.checked_mod(x, y)
      

      Calculates mod(x,y), checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.checked_cld — Function.

      Base.checked_cld(x, y)
      

      Calculates cld(x,y), checking for overflow errors where applicable.

      The overflow protection may impose a perceptible performance penalty.

      Base.Checked.add_with_overflow — Function.

      Base.add_with_overflow(x, y) -> (r, f)
      

      Calculates r = x+y, with the flag f indicating whether overflow has occurred.

      Base.Checked.sub_with_overflow — Function.

      Base.sub_with_overflow(x, y) -> (r, f)
      

      Calculates r = x-y, with the flag f indicating whether overflow has occurred.

      Base.Checked.mul_with_overflow — Function.

      Base.mul_with_overflow(x, y) -> (r, f)
      

      Calculates r = x*y, with the flag f indicating whether overflow has occurred.

      Base.abs2 — Function.

      abs2(x)
      

      Squared absolute value of x.

      Examples

      julia> abs2(-3)
      9
      

      Base.copysign — Function.

      copysign(x, y) -> z
      

      Return z which has the magnitude of x and the same sign as y.

      Examples

      julia> copysign(1, -2)
      -1
      
      julia> copysign(-1, 2)
      1
      

      Base.sign — Function.

      sign(x)
      

      Return zero if x==0 and $x/|x|$ otherwise (i.e., ±1 for real x).

      Base.signbit — Function.

      signbit(x)
      

      Returns true if the value of the sign of x is negative, otherwise false.

      Examples

      julia> signbit(-4)
      true
      
      julia> signbit(5)
      false
      
      julia> signbit(5.5)
      false
      
      julia> signbit(-4.1)
      true
      

      Base.flipsign — Function.

      flipsign(x, y)
      

      Return x with its sign flipped if y is negative. For example abs(x) = flipsign(x,x).

      Examples

      julia> flipsign(5, 3)
      5
      
      julia> flipsign(5, -3)
      -5
      

      Base.sqrt — Method.

      sqrt(x)
      

      Return $\sqrt{x}$. Throws for negative Real arguments. Use complex negative arguments instead. The prefix operator is equivalent to sqrt.

      Examples

      julia> sqrt(big(81))
      9.0
      
      julia> sqrt(big(-81))
      ERROR: DomainError with -81.0:
      NaN result for non-NaN input.
      Stacktrace:
       [1] sqrt(::BigFloat) at ./mpfr.jl:501
      [...]
      
      julia> sqrt(big(complex(-81)))
      0.0 + 9.0im
      

      Base.isqrt — Function.

      isqrt(n::Integer)
      

      Integer square root: the largest integer m such that m*m <= n.

      julia> isqrt(5)
      2
      

      Base.Math.cbrt — Function.

      cbrt(x::Real)
      

      Return the cube root of x, i.e. $x^{1/3}$. Negative values are accepted (returning the negative real root when $x < 0$).

      The prefix operator is equivalent to cbrt.

      Examples

      julia> cbrt(big(27))
      3.0
      
      julia> cbrt(big(-27))
      -3.0
      

      Base.real — Method.

      real(z)
      

      Return the real part of the complex number z.

      Examples

      julia> real(1 + 3im)
      1
      

      Base.imag — Function.

      imag(z)
      

      Return the imaginary part of the complex number z.

      Examples

      julia> imag(1 + 3im)
      3
      

      Base.reim — Function.

      reim(z)
      

      Return both the real and imaginary parts of the complex number z.

      Examples

      julia> reim(1 + 3im)
      (1, 3)
      

      Base.conj — Function.

      conj(z)
      

      Compute the complex conjugate of a complex number z.

      Examples

      julia> conj(1 + 3im)
      1 - 3im
      

      Base.angle — Function.

      angle(z)
      

      Compute the phase angle in radians of a complex number z.

      Examples

      julia> rad2deg(angle(1 + im))
      45.0
      
      julia> rad2deg(angle(1 - im))
      -45.0
      
      julia> rad2deg(angle(-1 - im))
      -135.0
      

      Base.cis — Function.

      cis(z)
      

      Return $\exp(iz)$.

      Examples

      julia> cis(π) ≈ -1
      true
      

      Base.binomial — Function.

      binomial(n::Integer, k::Integer)
      

      The binomial coefficient $\binom{n}{k}$, being the coefficient of the $k$th term in the polynomial expansion of $(1+x)^n$.

      If $n$ is non-negative, then it is the number of ways to choose k out of n items:

      \[\binom{n}{k} = \frac{n!}{k! (n-k)!}\]

      where $n!$ is the function.

      If $n$ is negative, then it is defined in terms of the identity

      \[\binom{n}{k} = (-1)^k \binom{k-n-1}{k}\]

      Examples

      julia> binomial(5, 3)
      10
      
      julia> factorial(5) ÷ (factorial(5-3) * factorial(3))
      10
      
      julia> binomial(-5, 3)
      -35
      

      See also

      External links

      • on Wikipedia.

      source

      — Function.

      factorial(n::Integer)
      

      Factorial of n. If n is an Integer, the factorial is computed as an integer (promoted to at least 64 bits). Note that this may overflow if n is not small, but you can use factorial(big(n)) to compute the result exactly in arbitrary precision.

      Examples

      julia> factorial(6)
      720
      
      julia> factorial(21)
      ERROR: OverflowError: 21 is too large to look up in the table; consider using `factorial(big(21))` instead
      Stacktrace:
      [...]
      
      julia> factorial(big(21))
      51090942171709440000
      

      See also

      External links

      Base.gcd — Function.

      gcd(x,y)
      

      Greatest common (positive) divisor (or zero if x and y are both zero).

      Examples

      julia> gcd(6,9)
      3
      
      julia> gcd(6,-9)
      3
      

      Base.lcm — Function.

      lcm(x,y)
      

      Least common (non-negative) multiple.

      Examples

      julia> lcm(2,3)
      6
      
      julia> lcm(-2,3)
      6
      

      Base.gcdx — Function.

      gcdx(x,y)
      

      Computes the greatest common (positive) divisor of x and y and their Bézout coefficients, i.e. the integer coefficients u and v that satisfy $ux+vy = d = gcd(x,y)$. $gcdx(x,y)$ returns $(d,u,v)$.

      Examples

      julia> gcdx(12, 42)
      (6, -3, 1)
      
      julia> gcdx(240, 46)
      (2, -9, 47)
      

      Note

      Bézout coefficients are not uniquely defined. gcdx returns the minimal Bézout coefficients that are computed by the extended Euclidean algorithm. (Ref: D. Knuth, TAoCP, 2/e, p. 325, Algorithm X.) For signed integers, these coefficients u and v are minimal in the sense that $|u| < |y/d|$ and $|v| < |x/d|$. Furthermore, the signs of u and v are chosen so that d is positive. For unsigned integers, the coefficients u and v might be near their typemax, and the identity then holds only via the unsigned integers’ modulo arithmetic.

      Base.ispow2 — Function.

      ispow2(n::Integer) -> Bool
      

      Test whether n is a power of two.

      Examples

      julia> ispow2(4)
      true
      
      julia> ispow2(5)
      false
      

      Base.nextpow — Function.

      nextpow(a, x)
      

      The smallest a^n not less than x, where n is a non-negative integer. a must be greater than 1, and x must be greater than 0.

      Examples

      julia> nextpow(2, 7)
      8
      
      julia> nextpow(2, 9)
      16
      
      julia> nextpow(5, 20)
      25
      
      julia> nextpow(4, 16)
      16
      

      See also .

      source

      — Function.

      prevpow(a, x)
      

      The largest a^n not greater than x, where n is a non-negative integer. a must be greater than 1, and x must not be less than 1.

      Examples

      julia> prevpow(2, 7)
      4
      
      julia> prevpow(2, 9)
      8
      
      julia> prevpow(5, 20)
      5
      
      julia> prevpow(4, 16)
      16
      

      See also nextpow.

      Base.nextprod — Function.

      nextprod([k_1, k_2,...], n)
      

      Next integer greater than or equal to n that can be written as $\prod k_i^{p_i}$ for integers $p_1$, $p_2$, etc.

      Examples

      julia> nextprod([2, 3], 105)
      108
      
      julia> 2^2 * 3^3
      108
      

      Base.invmod — Function.

      invmod(x,m)
      

      Take the inverse of x modulo m: y such that $x y = 1 \pmod m$, with $div(x,y) = 0$. This is undefined for $m = 0$, or if $gcd(x,m) \neq 1$.

      Examples

      julia> invmod(2,5)
      3
      
      julia> invmod(2,3)
      2
      
      julia> invmod(5,6)
      5
      

      Base.powermod — Function.

      powermod(x::Integer, p::Integer, m)
      

      Compute $x^p \pmod m$.

      Examples

      julia> powermod(2, 6, 5)
      4
      
      julia> mod(2^6, 5)
      4
      
      julia> powermod(5, 2, 20)
      5
      
      julia> powermod(5, 2, 19)
      6
      
      julia> powermod(5, 3, 19)
      11
      

      Base.ndigits — Function.

      ndigits(n::Integer; base::Integer=10, pad::Integer=1)
      

      Compute the number of digits in integer n written in base base (base must not be in [-1, 0, 1]), optionally padded with zeros to a specified size (the result will never be less than pad).

      Examples

      julia> ndigits(12345)
      5
      
      julia> ndigits(1022, base=16)
      3
      
      julia> string(1022, base=16)
      "3fe"
      
      julia> ndigits(123, pad=5)
      5
      

      Base.widemul — Function.

      widemul(x, y)
      

      Multiply x and y, giving the result as a larger type.

      Examples

      julia> widemul(Float32(3.), 4.)
      12.0
      

      Base.Math.@evalpoly — Macro.

      @evalpoly(z, c...)
      

      Evaluate the polynomial $\sum_k c[k] z^{k-1}$ for the coefficients c[1], c[2], …; that is, the coefficients are given in ascending order by power of z. This macro expands to efficient inline code that uses either Horner’s method or, for complex z, a more efficient Goertzel-like algorithm.

      Examples

      julia> @evalpoly(3, 1, 0, 1)
      10
      
      julia> @evalpoly(2, 1, 0, 1)
      5
      
      julia> @evalpoly(2, 1, 1, 1)
      7
      

      Base.FastMath.@fastmath — Macro.

      @fastmath expr
      

      Execute a transformed version of the expression, which calls functions that may violate strict IEEE semantics. This allows the fastest possible operation, but results are undefined – be careful when doing this, as it may change numerical results.

      This sets the , and corresponds to the -ffast-math option in clang. See the notes on performance annotations for more details.

      julia> @fastmath 1+2
      3
      
      julia> @fastmath(sin(3))
      0.1411200080598672