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start translating julia into japanese
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Yuichi Motoyama
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ja-jp/julia-jp.html.markdown
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---
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language: Julia
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contributors:
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- ["Leah Hanson", "http://leahhanson.us"]
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filename: learnjulia.jl
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---
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Julia is a new homoiconic functional language focused on technical computing.
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While having the full power of homoiconic macros, first-class functions, and low-level control, Julia is as easy to learn and use as Python.
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This is based on the current development version of Julia, as of October 18th, 2013.
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```ruby
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# Single line comments start with a hash (pound) symbol.
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#= Multiline comments can be written
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by putting '#=' before the text and '=#'
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after the text. They can also be nested.
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=#
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####################################################
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## 1. Primitive Datatypes and Operators
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####################################################
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# Everything in Julia is a expression.
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# There are several basic types of numbers.
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3 # => 3 (Int64)
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3.2 # => 3.2 (Float64)
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2 + 1im # => 2 + 1im (Complex{Int64})
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2//3 # => 2//3 (Rational{Int64})
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# All of the normal infix operators are available.
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1 + 1 # => 2
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8 - 1 # => 7
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10 * 2 # => 20
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35 / 5 # => 7.0
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5 / 2 # => 2.5 # dividing an Int by an Int always results in a Float
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div(5, 2) # => 2 # for a truncated result, use div
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5 \ 35 # => 7.0
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2 ^ 2 # => 4 # power, not bitwise xor
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12 % 10 # => 2
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# Enforce precedence with parentheses
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(1 + 3) * 2 # => 8
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# Bitwise Operators
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~2 # => -3 # bitwise not
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3 & 5 # => 1 # bitwise and
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2 | 4 # => 6 # bitwise or
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2 $ 4 # => 6 # bitwise xor
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2 >>> 1 # => 1 # logical shift right
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2 >> 1 # => 1 # arithmetic shift right
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2 << 1 # => 4 # logical/arithmetic shift left
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# You can use the bits function to see the binary representation of a number.
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bits(12345)
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# => "0000000000000000000000000000000000000000000000000011000000111001"
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bits(12345.0)
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# => "0100000011001000000111001000000000000000000000000000000000000000"
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# Boolean values are primitives
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true
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false
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# Boolean operators
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!true # => false
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!false # => true
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1 == 1 # => true
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2 == 1 # => false
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1 != 1 # => false
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2 != 1 # => true
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1 < 10 # => true
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1 > 10 # => false
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2 <= 2 # => true
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2 >= 2 # => true
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# Comparisons can be chained
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1 < 2 < 3 # => true
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2 < 3 < 2 # => false
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# Strings are created with "
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"This is a string."
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# Character literals are written with '
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'a'
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# A string can be indexed like an array of characters
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"This is a string"[1] # => 'T' # Julia indexes from 1
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# However, this is will not work well for UTF8 strings,
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# so iterating over strings is recommended (map, for loops, etc).
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# $ can be used for string interpolation:
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"2 + 2 = $(2 + 2)" # => "2 + 2 = 4"
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# You can put any Julia expression inside the parenthesis.
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# Another way to format strings is the printf macro.
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@printf "%d is less than %f" 4.5 5.3 # 5 is less than 5.300000
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# Printing is easy
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println("I'm Julia. Nice to meet you!")
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####################################################
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## 2. Variables and Collections
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####################################################
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# You don't declare variables before assigning to them.
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some_var = 5 # => 5
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some_var # => 5
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# Accessing a previously unassigned variable is an error
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try
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some_other_var # => ERROR: some_other_var not defined
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catch e
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println(e)
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end
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# Variable names start with a letter.
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# After that, you can use letters, digits, underscores, and exclamation points.
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SomeOtherVar123! = 6 # => 6
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# You can also use unicode characters
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☃ = 8 # => 8
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# These are especially handy for mathematical notation
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2 * π # => 6.283185307179586
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# A note on naming conventions in Julia:
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#
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# * Word separation can be indicated by underscores ('_'), but use of
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# underscores is discouraged unless the name would be hard to read
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# otherwise.
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#
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# * Names of Types begin with a capital letter and word separation is shown
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# with CamelCase instead of underscores.
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#
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# * Names of functions and macros are in lower case, without underscores.
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#
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# * Functions that modify their inputs have names that end in !. These
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# functions are sometimes called mutating functions or in-place functions.
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# Arrays store a sequence of values indexed by integers 1 through n:
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a = Int64[] # => 0-element Int64 Array
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# 1-dimensional array literals can be written with comma-separated values.
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b = [4, 5, 6] # => 3-element Int64 Array: [4, 5, 6]
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b[1] # => 4
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b[end] # => 6
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# 2-dimentional arrays use space-separated values and semicolon-separated rows.
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matrix = [1 2; 3 4] # => 2x2 Int64 Array: [1 2; 3 4]
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# Add stuff to the end of a list with push! and append!
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push!(a,1) # => [1]
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push!(a,2) # => [1,2]
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push!(a,4) # => [1,2,4]
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push!(a,3) # => [1,2,4,3]
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append!(a,b) # => [1,2,4,3,4,5,6]
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# Remove from the end with pop
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pop!(b) # => 6 and b is now [4,5]
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# Let's put it back
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push!(b,6) # b is now [4,5,6] again.
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a[1] # => 1 # remember that Julia indexes from 1, not 0!
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# end is a shorthand for the last index. It can be used in any
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# indexing expression
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a[end] # => 6
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# we also have shift and unshift
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shift!(a) # => 1 and a is now [2,4,3,4,5,6]
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unshift!(a,7) # => [7,2,4,3,4,5,6]
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# Function names that end in exclamations points indicate that they modify
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# their argument.
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arr = [5,4,6] # => 3-element Int64 Array: [5,4,6]
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sort(arr) # => [4,5,6]; arr is still [5,4,6]
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sort!(arr) # => [4,5,6]; arr is now [4,5,6]
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# Looking out of bounds is a BoundsError
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try
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a[0] # => ERROR: BoundsError() in getindex at array.jl:270
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a[end+1] # => ERROR: BoundsError() in getindex at array.jl:270
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catch e
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println(e)
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end
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# Errors list the line and file they came from, even if it's in the standard
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# library. If you built Julia from source, you can look in the folder base
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# inside the julia folder to find these files.
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# You can initialize arrays from ranges
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a = [1:5] # => 5-element Int64 Array: [1,2,3,4,5]
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# You can look at ranges with slice syntax.
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a[1:3] # => [1, 2, 3]
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a[2:end] # => [2, 3, 4, 5]
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# Remove elements from an array by index with splice!
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arr = [3,4,5]
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splice!(arr,2) # => 4 ; arr is now [3,5]
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# Concatenate lists with append!
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b = [1,2,3]
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append!(a,b) # Now a is [1, 2, 3, 4, 5, 1, 2, 3]
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# Check for existence in a list with in
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in(1, a) # => true
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# Examine the length with length
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length(a) # => 8
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# Tuples are immutable.
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tup = (1, 2, 3) # => (1,2,3) # an (Int64,Int64,Int64) tuple.
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tup[1] # => 1
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try:
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tup[1] = 3 # => ERROR: no method setindex!((Int64,Int64,Int64),Int64,Int64)
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catch e
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println(e)
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end
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# Many list functions also work on tuples
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length(tup) # => 3
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tup[1:2] # => (1,2)
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in(2, tup) # => true
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# You can unpack tuples into variables
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a, b, c = (1, 2, 3) # => (1,2,3) # a is now 1, b is now 2 and c is now 3
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# Tuples are created even if you leave out the parentheses
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d, e, f = 4, 5, 6 # => (4,5,6)
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# A 1-element tuple is distinct from the value it contains
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(1,) == 1 # => false
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(1) == 1 # => true
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# Look how easy it is to swap two values
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e, d = d, e # => (5,4) # d is now 5 and e is now 4
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# Dictionaries store mappings
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empty_dict = Dict() # => Dict{Any,Any}()
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# You can create a dictionary using a literal
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filled_dict = ["one"=> 1, "two"=> 2, "three"=> 3]
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# => Dict{ASCIIString,Int64}
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# Look up values with []
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filled_dict["one"] # => 1
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# Get all keys
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keys(filled_dict)
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# => KeyIterator{Dict{ASCIIString,Int64}}(["three"=>3,"one"=>1,"two"=>2])
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# Note - dictionary keys are not sorted or in the order you inserted them.
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# Get all values
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values(filled_dict)
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# => ValueIterator{Dict{ASCIIString,Int64}}(["three"=>3,"one"=>1,"two"=>2])
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# Note - Same as above regarding key ordering.
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# Check for existence of keys in a dictionary with in, haskey
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in(("one", 1), filled_dict) # => true
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in(("two", 3), filled_dict) # => false
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haskey(filled_dict, "one") # => true
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haskey(filled_dict, 1) # => false
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# Trying to look up a non-existant key will raise an error
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try
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filled_dict["four"] # => ERROR: key not found: four in getindex at dict.jl:489
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catch e
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println(e)
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end
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# Use the get method to avoid that error by providing a default value
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# get(dictionary,key,default_value)
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get(filled_dict,"one",4) # => 1
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get(filled_dict,"four",4) # => 4
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# Use Sets to represent collections of unordered, unique values
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empty_set = Set() # => Set{Any}()
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# Initialize a set with values
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filled_set = Set(1,2,2,3,4) # => Set{Int64}(1,2,3,4)
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# Add more values to a set
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push!(filled_set,5) # => Set{Int64}(5,4,2,3,1)
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# Check if the values are in the set
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in(2, filled_set) # => true
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in(10, filled_set) # => false
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# There are functions for set intersection, union, and difference.
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other_set = Set(3, 4, 5, 6) # => Set{Int64}(6,4,5,3)
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intersect(filled_set, other_set) # => Set{Int64}(3,4,5)
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union(filled_set, other_set) # => Set{Int64}(1,2,3,4,5,6)
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setdiff(Set(1,2,3,4),Set(2,3,5)) # => Set{Int64}(1,4)
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####################################################
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## 3. Control Flow
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####################################################
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# Let's make a variable
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some_var = 5
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# Here is an if statement. Indentation is not meaningful in Julia.
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if some_var > 10
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println("some_var is totally bigger than 10.")
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elseif some_var < 10 # This elseif clause is optional.
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println("some_var is smaller than 10.")
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else # The else clause is optional too.
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println("some_var is indeed 10.")
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end
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# => prints "some var is smaller than 10"
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# For loops iterate over iterables.
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# Iterable types include Range, Array, Set, Dict, and String.
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for animal=["dog", "cat", "mouse"]
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println("$animal is a mammal")
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# You can use $ to interpolate variables or expression into strings
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end
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# prints:
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# dog is a mammal
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# cat is a mammal
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# mouse is a mammal
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# You can use 'in' instead of '='.
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for animal in ["dog", "cat", "mouse"]
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println("$animal is a mammal")
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end
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# prints:
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# dog is a mammal
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# cat is a mammal
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# mouse is a mammal
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for a in ["dog"=>"mammal","cat"=>"mammal","mouse"=>"mammal"]
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println("$(a[1]) is a $(a[2])")
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end
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# prints:
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# dog is a mammal
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# cat is a mammal
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# mouse is a mammal
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for (k,v) in ["dog"=>"mammal","cat"=>"mammal","mouse"=>"mammal"]
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println("$k is a $v")
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end
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# prints:
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# dog is a mammal
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# cat is a mammal
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# mouse is a mammal
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# While loops loop while a condition is true
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x = 0
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while x < 4
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println(x)
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x += 1 # Shorthand for x = x + 1
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end
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# prints:
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# 0
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# 1
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# 2
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# 3
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# Handle exceptions with a try/catch block
|
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try
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error("help")
|
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catch e
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println("caught it $e")
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end
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# => caught it ErrorException("help")
|
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|
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|
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####################################################
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## 4. Functions
|
||||
####################################################
|
||||
|
||||
# The keyword 'function' creates new functions
|
||||
#function name(arglist)
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# body...
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#end
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function add(x, y)
|
||||
println("x is $x and y is $y")
|
||||
|
||||
# Functions return the value of their last statement
|
||||
x + y
|
||||
end
|
||||
|
||||
add(5, 6) # => 11 after printing out "x is 5 and y is 6"
|
||||
|
||||
# You can define functions that take a variable number of
|
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# positional arguments
|
||||
function varargs(args...)
|
||||
return args
|
||||
# use the keyword return to return anywhere in the function
|
||||
end
|
||||
# => varargs (generic function with 1 method)
|
||||
|
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varargs(1,2,3) # => (1,2,3)
|
||||
|
||||
# The ... is called a splat.
|
||||
# We just used it in a function definition.
|
||||
# It can also be used in a fuction call,
|
||||
# where it will splat an Array or Tuple's contents into the argument list.
|
||||
Set([1,2,3]) # => Set{Array{Int64,1}}([1,2,3]) # produces a Set of Arrays
|
||||
Set([1,2,3]...) # => Set{Int64}(1,2,3) # this is equivalent to Set(1,2,3)
|
||||
|
||||
x = (1,2,3) # => (1,2,3)
|
||||
Set(x) # => Set{(Int64,Int64,Int64)}((1,2,3)) # a Set of Tuples
|
||||
Set(x...) # => Set{Int64}(2,3,1)
|
||||
|
||||
|
||||
# You can define functions with optional positional arguments
|
||||
function defaults(a,b,x=5,y=6)
|
||||
return "$a $b and $x $y"
|
||||
end
|
||||
|
||||
defaults('h','g') # => "h g and 5 6"
|
||||
defaults('h','g','j') # => "h g and j 6"
|
||||
defaults('h','g','j','k') # => "h g and j k"
|
||||
try
|
||||
defaults('h') # => ERROR: no method defaults(Char,)
|
||||
defaults() # => ERROR: no methods defaults()
|
||||
catch e
|
||||
println(e)
|
||||
end
|
||||
|
||||
# You can define functions that take keyword arguments
|
||||
function keyword_args(;k1=4,name2="hello") # note the ;
|
||||
return ["k1"=>k1,"name2"=>name2]
|
||||
end
|
||||
|
||||
keyword_args(name2="ness") # => ["name2"=>"ness","k1"=>4]
|
||||
keyword_args(k1="mine") # => ["k1"=>"mine","name2"=>"hello"]
|
||||
keyword_args() # => ["name2"=>"hello","k1"=>4]
|
||||
|
||||
# You can combine all kinds of arguments in the same function
|
||||
function all_the_args(normal_arg, optional_positional_arg=2; keyword_arg="foo")
|
||||
println("normal arg: $normal_arg")
|
||||
println("optional arg: $optional_positional_arg")
|
||||
println("keyword arg: $keyword_arg")
|
||||
end
|
||||
|
||||
all_the_args(1, 3, keyword_arg=4)
|
||||
# prints:
|
||||
# normal arg: 1
|
||||
# optional arg: 3
|
||||
# keyword arg: 4
|
||||
|
||||
# Julia has first class functions
|
||||
function create_adder(x)
|
||||
adder = function (y)
|
||||
return x + y
|
||||
end
|
||||
return adder
|
||||
end
|
||||
|
||||
# This is "stabby lambda syntax" for creating anonymous functions
|
||||
(x -> x > 2)(3) # => true
|
||||
|
||||
# This function is identical to create_adder implementation above.
|
||||
function create_adder(x)
|
||||
y -> x + y
|
||||
end
|
||||
|
||||
# You can also name the internal function, if you want
|
||||
function create_adder(x)
|
||||
function adder(y)
|
||||
x + y
|
||||
end
|
||||
adder
|
||||
end
|
||||
|
||||
add_10 = create_adder(10)
|
||||
add_10(3) # => 13
|
||||
|
||||
|
||||
# There are built-in higher order functions
|
||||
map(add_10, [1,2,3]) # => [11, 12, 13]
|
||||
filter(x -> x > 5, [3, 4, 5, 6, 7]) # => [6, 7]
|
||||
|
||||
# We can use list comprehensions for nicer maps
|
||||
[add_10(i) for i=[1, 2, 3]] # => [11, 12, 13]
|
||||
[add_10(i) for i in [1, 2, 3]] # => [11, 12, 13]
|
||||
|
||||
####################################################
|
||||
## 5. Types
|
||||
####################################################
|
||||
|
||||
# Julia has a type system.
|
||||
# Every value has a type; variables do not have types themselves.
|
||||
# You can use the `typeof` function to get the type of a value.
|
||||
typeof(5) # => Int64
|
||||
|
||||
# Types are first-class values
|
||||
typeof(Int64) # => DataType
|
||||
typeof(DataType) # => DataType
|
||||
# DataType is the type that represents types, including itself.
|
||||
|
||||
# Types are used for documentation, optimizations, and dispatch.
|
||||
# They are not statically checked.
|
||||
|
||||
# Users can define types
|
||||
# They are like records or structs in other languages.
|
||||
# New types are defined using the `type` keyword.
|
||||
|
||||
# type Name
|
||||
# field::OptionalType
|
||||
# ...
|
||||
# end
|
||||
type Tiger
|
||||
taillength::Float64
|
||||
coatcolor # not including a type annotation is the same as `::Any`
|
||||
end
|
||||
|
||||
# The default constructor's arguments are the properties
|
||||
# of the type, in the order they are listed in the definition
|
||||
tigger = Tiger(3.5,"orange") # => Tiger(3.5,"orange")
|
||||
|
||||
# The type doubles as the constructor function for values of that type
|
||||
sherekhan = typeof(tigger)(5.6,"fire") # => Tiger(5.6,"fire")
|
||||
|
||||
# These struct-style types are called concrete types
|
||||
# They can be instantiated, but cannot have subtypes.
|
||||
# The other kind of types is abstract types.
|
||||
|
||||
# abstract Name
|
||||
abstract Cat # just a name and point in the type hierarchy
|
||||
|
||||
# Abstract types cannot be instantiated, but can have subtypes.
|
||||
# For example, Number is an abstract type
|
||||
subtypes(Number) # => 6-element Array{Any,1}:
|
||||
# Complex{Float16}
|
||||
# Complex{Float32}
|
||||
# Complex{Float64}
|
||||
# Complex{T<:Real}
|
||||
# ImaginaryUnit
|
||||
# Real
|
||||
subtypes(Cat) # => 0-element Array{Any,1}
|
||||
|
||||
# Every type has a super type; use the `super` function to get it.
|
||||
typeof(5) # => Int64
|
||||
super(Int64) # => Signed
|
||||
super(Signed) # => Real
|
||||
super(Real) # => Number
|
||||
super(Number) # => Any
|
||||
super(super(Signed)) # => Number
|
||||
super(Any) # => Any
|
||||
# All of these type, except for Int64, are abstract.
|
||||
|
||||
# <: is the subtyping operator
|
||||
type Lion <: Cat # Lion is a subtype of Cat
|
||||
mane_color
|
||||
roar::String
|
||||
end
|
||||
|
||||
# You can define more constructors for your type
|
||||
# Just define a function of the same name as the type
|
||||
# and call an existing constructor to get a value of the correct type
|
||||
Lion(roar::String) = Lion("green",roar)
|
||||
# This is an outer constructor because it's outside the type definition
|
||||
|
||||
type Panther <: Cat # Panther is also a subtype of Cat
|
||||
eye_color
|
||||
Panther() = new("green")
|
||||
# Panthers will only have this constructor, and no default constructor.
|
||||
end
|
||||
# Using inner constructors, like Panther does, gives you control
|
||||
# over how values of the type can be created.
|
||||
# When possible, you should use outer constructors rather than inner ones.
|
||||
|
||||
####################################################
|
||||
## 6. Multiple-Dispatch
|
||||
####################################################
|
||||
|
||||
# In Julia, all named functions are generic functions
|
||||
# This means that they are built up from many small methods
|
||||
# Each constructor for Lion is a method of the generic function Lion.
|
||||
|
||||
# For a non-constructor example, let's make a function meow:
|
||||
|
||||
# Definitions for Lion, Panther, Tiger
|
||||
function meow(animal::Lion)
|
||||
animal.roar # access type properties using dot notation
|
||||
end
|
||||
|
||||
function meow(animal::Panther)
|
||||
"grrr"
|
||||
end
|
||||
|
||||
function meow(animal::Tiger)
|
||||
"rawwwr"
|
||||
end
|
||||
|
||||
# Testing the meow function
|
||||
meow(tigger) # => "rawwr"
|
||||
meow(Lion("brown","ROAAR")) # => "ROAAR"
|
||||
meow(Panther()) # => "grrr"
|
||||
|
||||
# Review the local type hierarchy
|
||||
issubtype(Tiger,Cat) # => false
|
||||
issubtype(Lion,Cat) # => true
|
||||
issubtype(Panther,Cat) # => true
|
||||
|
||||
# Defining a function that takes Cats
|
||||
function pet_cat(cat::Cat)
|
||||
println("The cat says $(meow(cat))")
|
||||
end
|
||||
|
||||
pet_cat(Lion("42")) # => prints "The cat says 42"
|
||||
try
|
||||
pet_cat(tigger) # => ERROR: no method pet_cat(Tiger,)
|
||||
catch e
|
||||
println(e)
|
||||
end
|
||||
|
||||
# In OO languages, single dispatch is common;
|
||||
# this means that the method is picked based on the type of the first argument.
|
||||
# In Julia, all of the argument types contribute to selecting the best method.
|
||||
|
||||
# Let's define a function with more arguments, so we can see the difference
|
||||
function fight(t::Tiger,c::Cat)
|
||||
println("The $(t.coatcolor) tiger wins!")
|
||||
end
|
||||
# => fight (generic function with 1 method)
|
||||
|
||||
fight(tigger,Panther()) # => prints The orange tiger wins!
|
||||
fight(tigger,Lion("ROAR")) # => prints The orange tiger wins!
|
||||
|
||||
# Let's change the behavior when the Cat is specifically a Lion
|
||||
fight(t::Tiger,l::Lion) = println("The $(l.mane_color)-maned lion wins!")
|
||||
# => fight (generic function with 2 methods)
|
||||
|
||||
fight(tigger,Panther()) # => prints The orange tiger wins!
|
||||
fight(tigger,Lion("ROAR")) # => prints The green-maned lion wins!
|
||||
|
||||
# We don't need a Tiger in order to fight
|
||||
fight(l::Lion,c::Cat) = println("The victorious cat says $(meow(c))")
|
||||
# => fight (generic function with 3 methods)
|
||||
|
||||
fight(Lion("balooga!"),Panther()) # => prints The victorious cat says grrr
|
||||
try
|
||||
fight(Panther(),Lion("RAWR")) # => ERROR: no method fight(Panther,Lion)
|
||||
catch
|
||||
end
|
||||
|
||||
# Also let the cat go first
|
||||
fight(c::Cat,l::Lion) = println("The cat beats the Lion")
|
||||
# => Warning: New definition
|
||||
# fight(Cat,Lion) at none:1
|
||||
# is ambiguous with
|
||||
# fight(Lion,Cat) at none:2.
|
||||
# Make sure
|
||||
# fight(Lion,Lion)
|
||||
# is defined first.
|
||||
#fight (generic function with 4 methods)
|
||||
|
||||
# This warning is because it's unclear which fight will be called in:
|
||||
fight(Lion("RAR"),Lion("brown","rarrr")) # => prints The victorious cat says rarrr
|
||||
# The result may be different in other versions of Julia
|
||||
|
||||
fight(l::Lion,l2::Lion) = println("The lions come to a tie")
|
||||
fight(Lion("RAR"),Lion("brown","rarrr")) # => prints The lions come to a tie
|
||||
|
||||
|
||||
# Under the hood
|
||||
# You can take a look at the llvm and the assembly code generated.
|
||||
|
||||
square_area(l) = l * l # square_area (generic function with 1 method)
|
||||
|
||||
square_area(5) #25
|
||||
|
||||
# What happens when we feed square_area an integer?
|
||||
code_native(square_area, (Int32,))
|
||||
# .section __TEXT,__text,regular,pure_instructions
|
||||
# Filename: none
|
||||
# Source line: 1 # Prologue
|
||||
# push RBP
|
||||
# mov RBP, RSP
|
||||
# Source line: 1
|
||||
# movsxd RAX, EDI # Fetch l from memory?
|
||||
# imul RAX, RAX # Square l and store the result in RAX
|
||||
# pop RBP # Restore old base pointer
|
||||
# ret # Result will still be in RAX
|
||||
|
||||
code_native(square_area, (Float32,))
|
||||
# .section __TEXT,__text,regular,pure_instructions
|
||||
# Filename: none
|
||||
# Source line: 1
|
||||
# push RBP
|
||||
# mov RBP, RSP
|
||||
# Source line: 1
|
||||
# vmulss XMM0, XMM0, XMM0 # Scalar single precision multiply (AVX)
|
||||
# pop RBP
|
||||
# ret
|
||||
|
||||
code_native(square_area, (Float64,))
|
||||
# .section __TEXT,__text,regular,pure_instructions
|
||||
# Filename: none
|
||||
# Source line: 1
|
||||
# push RBP
|
||||
# mov RBP, RSP
|
||||
# Source line: 1
|
||||
# vmulsd XMM0, XMM0, XMM0 # Scalar double precision multiply (AVX)
|
||||
# pop RBP
|
||||
# ret
|
||||
#
|
||||
# Note that julia will use floating point instructions if any of the
|
||||
# arguements are floats.
|
||||
# Let's calculate the area of a circle
|
||||
circle_area(r) = pi * r * r # circle_area (generic function with 1 method)
|
||||
circle_area(5) # 78.53981633974483
|
||||
|
||||
code_native(circle_area, (Int32,))
|
||||
# .section __TEXT,__text,regular,pure_instructions
|
||||
# Filename: none
|
||||
# Source line: 1
|
||||
# push RBP
|
||||
# mov RBP, RSP
|
||||
# Source line: 1
|
||||
# vcvtsi2sd XMM0, XMM0, EDI # Load integer (r) from memory
|
||||
# movabs RAX, 4593140240 # Load pi
|
||||
# vmulsd XMM1, XMM0, QWORD PTR [RAX] # pi * r
|
||||
# vmulsd XMM0, XMM0, XMM1 # (pi * r) * r
|
||||
# pop RBP
|
||||
# ret
|
||||
#
|
||||
|
||||
code_native(circle_area, (Float64,))
|
||||
# .section __TEXT,__text,regular,pure_instructions
|
||||
# Filename: none
|
||||
# Source line: 1
|
||||
# push RBP
|
||||
# mov RBP, RSP
|
||||
# movabs RAX, 4593140496
|
||||
# Source line: 1
|
||||
# vmulsd XMM1, XMM0, QWORD PTR [RAX]
|
||||
# vmulsd XMM0, XMM1, XMM0
|
||||
# pop RBP
|
||||
# ret
|
||||
#
|
||||
```
|
||||
|
||||
## Further Reading
|
||||
|
||||
You can get a lot more detail from [The Julia Manual](http://docs.julialang.org/en/latest/manual/)
|
||||
|
||||
The best place to get help with Julia is the (very friendly) [mailing list](https://groups.google.com/forum/#!forum/julia-users).
|
||||
Loading…
Reference in New Issue
Block a user