Mathematics
Mathematical Operators
Base.:- — Method.
1. -(x)
Unary minus operator.
Examples
1. julia> -1
2. -1
4. julia> -(2)
5. -2
7. julia> -[1 2; 3 4]
8. 2×2 Array{Int64,2}:
9. -1 -2
10. -3 -4
Base.:+ — 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
4. julia> +(1, 20, 4)
5. 25
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
4. julia> -(2, 4.5)
5. -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
4. julia> *(2, 7, 8)
5. 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
4. julia> 4/2
5. 2.0
7. julia> 4.5/2
8. 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
4. julia> inv(3) * 6
5. 2.0
7. julia> A = [4 3; 2 1]; x = [5, 6];
9. julia> A \ x
10. 2-element Array{Float64,1}:
11. 6.5
12. -7.0
14. julia> inv(A) * x
15. 2-element Array{Float64,1}:
16. 6.5
17. -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
4. julia> A = [1 2; 3 4]
5. 2×2 Array{Int64,2}:
6. 1 2
7. 3 4
9. julia> A^3
10. 2×2 Array{Int64,2}:
11. 37 54
12. 81 118
Base.fma — Function.
1. fma(x, y, z)
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 muladd.
Base.muladd — 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 fma.
Examples
1. julia> muladd(3, 2, 1)
2. 7
4. julia> 3 * 2 + 1
5. 7
Base.inv — 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
4. julia> inv(1 + 2im)
5. 0.2 - 0.4im
7. julia> inv(1 + 2im) * (1 + 2im)
8. 1.0 + 0.0im
10. julia> inv(2//3)
11. 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
4. julia> -5 ÷ 3
5. -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: mod1.
Examples
1. julia> mod(0, Base.OneTo(3))
2. 3
4. julia> mod(3, 0:2)
5. 0
Julia 1.3
This method requires at least Julia 1.3.
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
4. julia> mod(9, 3)
5. 0
7. julia> mod(8.9, 3)
8. 2.9000000000000004
10. julia> mod(eps(), 3)
11. 2.220446049250313e-16
13. julia> mod(-eps(), 3)
14. 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 x ≡ y (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
Base.rem — 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;
3. julia> x % y
4. 3
6. julia> x == div(x, y) * y + rem(x, y)
7. true
Base.Math.rem2pi — Function.
1. rem2pi(x, r::RoundingMode)
Compute the remainder of x after integer division by 2π, 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 alsoRoundNearest. - if
r == RoundToZero, then the result is in the interval $[0, 2π]$ ifxis positive,. or $[-2π, 0]$ otherwise. See alsoRoundToZero. - if
r == RoundDown, then the result is in the interval $[0, 2π]$. See alsoRoundDown. - if
r == RoundUp, then the result is in the interval $[-2π, 0]$. See alsoRoundUp.
Examples
1. julia> rem2pi(7pi/4, RoundNearest)
2. -0.7853981633974485
4. julia> rem2pi(7pi/4, RoundDown)
5. 5.497787143782138
Base.Math.mod2pi — Function.
1. mod2pi(x)
Modulus after division by 2π, returning in the range $[0,2π)$.
This function computes a floating point representation of the modulus after division by numerically exact 2π, 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 2π.
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)
4. julia> divrem(7,3)
5. (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)
Examples
1. julia> x = 15; y = 4;
3. julia> fld1(x, y)
4. 4
6. julia> x == fld(x, y) * y + mod(x, y)
7. true
9. julia> x == (fld1(x, y) - 1) * y + mod1(x, y)
10. 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.
Examples
1. julia> mod1(4, 2)
2. 2
4. julia> mod1(4, 3)
5. 1
Base.fldmod1 — Function.
1. fldmod1(x, y)
Return (fld1(x,y), mod1(x,y)).
Base.:// — Function.
1. //(num, den)
Divide two integers or rational numbers, giving a Rational result.
Examples
1. julia> 3 // 5
2. 3//5
4. julia> (3 // 5) // (2 // 1)
5. 3//10
Base.rationalize — 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
4. julia> a = rationalize(BigInt, 10.3)
5. 103//10
7. julia> typeof(numerator(a))
8. BigInt
Base.numerator — Function.
1. numerator(x)
Numerator of the rational representation of x.
Examples
1. julia> numerator(2//3)
2. 2
4. julia> numerator(4)
5. 4
Base.denominator — Function.
1. denominator(x)
Denominator of the rational representation of x.
Examples
1. julia> denominator(2//3)
2. 3
4. julia> denominator(4)
5. 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"
<<(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
Base.:>> — 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"
>>(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 Unsigned integer types, this is equivalent to >>. For Signed 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 >>.
>>>(B::BitVector, n) -> BitVector
Unsigned right bitshift operator, B >>> n. Equivalent to B >> n. See >> for details and examples.
Base.:: — Function.
(:)(start, [step], stop)
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 StepRange).
: 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 UnitRange). 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 StepRange).
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
Base.OneTo — 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.
Base.StepRangeLen — 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.
Base.:== — 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 missing, 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 isequal 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.
isequal 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 hash.
==(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.
==(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
!=(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)
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 isless. 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
>(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)
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
>=(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.cmp — 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})
[...]
cmp(<, x, y)
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).
Examples
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
Base.:~ — Function.
~(x)
Bitwise not.
Examples
julia> ~4
-5
julia> ~10
-11
julia> ~true
false
Base.:& — Function.
&(x, y)
Bitwise and. Implements three-valued logic, returning missing 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
Base.:| — Function.
|(x, y)
Bitwise or. Implements three-valued logic, returning missing 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
Base.xor — Function.
xor(x, y)
⊻(x, y)
Bitwise exclusive or of x and y. Implements three-valued logic, returning missing 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
Base.:! — Function.
!(x)
Boolean not. Implements three-valued logic, returning missing 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
!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 eps 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 radius of a Hydrogen atom 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
Base.sin — Method.
sin(x)
Compute sine of x, where x is in radians.
Base.cos — Method.
cos(x)
Compute cosine of x, where x is in radians.
Base.Math.sincos — Method.
sincos(x)
Simultaneously compute the sine and cosine of x, where the x is in radians.
Base.tan — Method.
tan(x)
Compute tangent of x, where x is in radians.
Base.Math.sind — Function.
sind(x)
Compute sine of x, where x is in degrees.
Base.Math.cosd — Function.
cosd(x)
Compute cosine of x, where x is in degrees.
Base.Math.tand — Function.
tand(x)
Compute tangent of x, where x is in degrees.
Base.Math.sinpi — Function.
sinpi(x)
Compute $\sin(\pi x)$ more accurately than sin(pi*x), especially for large x.
Base.Math.cospi — Function.
cospi(x)
Compute $\cos(\pi x)$ more accurately than cos(pi*x), especially for large x.
Base.sinh — Method.
sinh(x)
Compute hyperbolic sine of x.
Base.cosh — Method.
cosh(x)
Compute hyperbolic cosine of x.
Base.tanh — Method.
tanh(x)
Compute hyperbolic tangent of x.
Base.asin — Method.
asin(x)
Compute the inverse sine of x, where the output is in radians.
Base.acos — Method.
acos(x)
Compute the inverse cosine of x, where the output is in radians
Base.atan — 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.
[source](https://github.com/JuliaLang/julia/blob/2d5741174ce3e6a394010d2e470e4269ca54607f/bas
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