basedocs.jl

# This file is a part of Julia. License is MIT: http:https://julialang.org/license

import .Docs: keywords

keywords[:hello] = keywords[:hi] = doc"Hello, Human."

const intro = doc"""
  **Welcome to Julia $(string(VERSION)).** The full manual is available at

      http:https://docs.julialang.org/

  as well many great tutorials and learning resources:

      http:https://julialang.org/learning/

  For help on a specific function or macro, type `?` followed
  by its name, e.g. `?fft`, `?@time` or `?html`, and press
  enter.
  """

keywords[:help] = keywords[:?] = keywords[:julia] = intro

keywords[:using] = doc"""
  `using` will load the given module or package and make some of its names
  available for use (see also `export`). For example:

      using Gadfly

  loads the plotting package, Gadfly, so that the `plot` function can be used.

  Names can be used via dot syntax, whether they are exported or not:

      Gadfly.plot(...)

  If you don't want to use the packages exports directly, see also `import`.
  If you're not sure, `using` is almost definitely what you want.
  """

keywords[:import] = doc"""
      import Gadfly

  `import`, like `using`, will load modules and packages for use. Unlike
  `using`, however, it will *not* make any `export`ed names available for use.
  To use Gadfly's `plot` function after importing it, for example, you have
  to write:

      Gadfly.plot(...)

  Import can also be used with specific names, for example

      import Gadfly: plot, render

  This syntax is used when you want to extend the modules functions with
  new methods.
  """

keywords[:export] = doc"""
  `export` is used within modules and packages to tell Julia which functions
  should be made available to the user. For example:

      module Test
      export foo # foo is exported, but bar isn't
      foo(x) = x
      bar(y) = y
      end

      using Test
      foo(1) # 1
      bar(1) # Error: bar not defined
      Test.bar(1) # 1
  """

keywords[:abstract] = doc"""
  `abstract` declares a type that cannot be instantiated, and serves only as a node in the type graph,
  thereby describing sets of related concrete types: those concrete types which are their descendants.
  Abstract types form the conceptual hierarchy which makes Julia’s type system more than just a collection of object implementations.
  For example:

      abstract Number
      abstract Real <: Number

  `abstract Number` has no supertype, whereas `abstract Real` is an abstract subtype of `Number`.
  """

keywords[:module] = doc"""
  `module` declares a Module, which is a separate global variable workspace.  Within a module, you can control which names from other modules are visible (via importing), and specify which of your names are intended to be public (via exporting). For example:

      module
      import Base.show
      export MyType, foo

      type MyType
          x
      end

      bar(x) = 2x
      foo(a::MyType) = bar(a.x) + 1
      show(io, a::MyType) = print(io, "MyType $(a.x)")
      end

  Modules allow you to create top-level definitions without worrying about name conflicts when your code is used together with somebody else’s.
  """

keywords[:baremodule] = doc"""
  `baremodule` declares a module that does not contain `using Base`, `import Base.call`,
  or a definition of `eval`.  It does still import `Core`.
  """

keywords[:bitstype] = doc"""
  `bitstype` declares a concrete type whose data consists of plain old bits. Classic examples of bits types are integers and floating-point values.  Some example built-in bits type declarations:

      bitstype 32 Char
      bitstype 8  Bool <: Integer

  The first parameter indicates how many bits of storage the type requires. Currently, only sizes that are multiples of 8 bits are supported. The second parameter gives the name of the type.  The `Bool` declaration shows how a bits type can be optionally declared to be a subtype of some supertype.
  """

keywords[:macro] = doc"""
  `macro` defines a method to include generated code in the final body of a program. A macro maps a tuple of arguments to a returned expression, and the resulting expression is compiled directly rather than requiring a runtime `eval()` call. Macro arguments may include expressions, literal values, and symbols. For example:

      macro sayhello(name)
          return :( println("Hello, ", $name) )
      end

  This macro takes one argument: `name`. When `@sayhello` is encountered, the quoted expression is expanded to interpolate the value of the argument into the final expression.
  """

keywords[:const] = doc"""
  `const` is used to declare global variables which are also constant.
  In almost all code (and particularly performance sensitive code)
  global variables should be declared constant in this way.

      const x = 5

  Note that "constant-ness" is not enforced inside containers, so if
  `x` is an array or dictionary (for example) you can still add and remove
  elements.

  Technically, you can even redefine `const` variables, although this will
  generate a warning from the compiler. The only strict requirement is that
  the *type* of the variable does not change, which is why `const` variables
  are much faster than regular globals.
  """

keywords[:function] = doc"""
  Functions are defined with the `function` keyword:

      function add(a, b)
          return a + b
      end

  Or the short form notation:

      add(a, b) = a + b

  The use of the `return` keyword is exactly the same as in other languages,
  but is often optional. When it's not used, the last expression in the function
  body will be returned by default:

      function compare(a, b)
        a == b && return "equal to"
        a < b ? "less than" : "greater than"
      end
  """

keywords[:return] = doc"""
  `return` can be used function bodies to exit early and return a given value,
  e.g.

      function compare(a, b)
          a == b && return "equal to"
          a < b ? "less than" : "greater than"
      end

  In general you can place a `return` statement anywhere within a function
  body, including within deeply nested loops or conditionals, but be careful
  with `do` blocks. For example:

      function test1(xs)
          for x in xs
              iseven(x) && return 2x
          end
      end

      function test2(xs)
          map(xs) do x
              iseven(x) && return 2x
              x
          end
      end

  In the first example, the return breaks out of its enclosing function
  as soon as it hits an even number, so `test1([5,6,7])` returns `12`.

  You might expect the second example to behave the same way, but in fact
  the `return` there only breaks out of the *inner* function (inside the `do`
  block) and gives a value back to `map`. `test2([5,6,7])` then returns `[5,12,7]`.
  """

keywords[:if]  = keywords[:elseif] = keywords[:else] = doc"""
  `if`-`elseif`-`else` performs conditional evaluation, which allows portions of code to be evaluated or not evaluated depending on the value of a boolean expression.
  Here is the anatomy of the `if`-`elseif`-`else` conditional syntax:

      if x < y
          println("x is less than y")
      elseif x > y
          println("x is greater than y")
      else
          println("x is equal to y")
      end

  If the condition expression `x < y` is true, then the corresponding block is evaluated;
  otherwise the condition expression `x > y` is evaluated, and if it is true, the corresponding block is evaluated; if neither expression is true, the `else` block is evaluated.
  The `elseif` and `else` blocks are optional, and as many `elseif` blocks as desired can be used.
  """

keywords[:for] = doc"""
  `for` loops repeatedly evaluate the body of the loop by iterating over a sequence of values.  For example:

      for i in [1,4,0]
          println(i)
      end
  """

keywords[:while] = doc"""
  `while` loops repeatedly evaluate a conditional expression, and continues evaluating the body of the while loop so long as
  the expression remains `true`. If the condition expression is false when the while loop is first reached, the body is never evaluated.
  For example:

      while i <= 5
          println(i)
          i += 1
      end
  """

keywords[:end] = doc"""
  `end` marks the conclusion of a block of expressions.
  In the example below, `end` marks the conclusion of a `function`.

      function foo()
          println("hello, world")
      end

  `end` marks the conclusion of all kinds of expression blocks: `module`, `type`, `begin`, `let`, `for`, etc.

  In addition, `end` may be used when indexing into an array to represent the last index of each dimension:

      x[1:end, 2:end-1]
  """

keywords[:try] = keywords[:catch] = doc"""
  A `try/catch` statement allows for `Exception`s to be tested for. For example, a customized square root function
  can be written to automatically call either the real or complex square root method on demand using `Exception`s:

      f(x) = try
          sqrt(x)
      catch
          sqrt(complex(x, 0))
      end

  `try/catch` statements also allow the `Exception` to be saved in a variable, e.g. `catch y`.

  The `catch` clause is not strictly necessary; when omitted, the default return value is `nothing`.
  The power of the `try/catch` construct lies in the ability to unwind a deeply nested computation
  immediately to a much higher level in the stack of calling functions.
  """

keywords[:finally] = doc"""
  `finally` provides a way to run some code when a given block of code exits, regardless of how it exits.
  For example, here is how we can guarantee that an opened file is closed:

      f = open("file")
      try
          operate_on_file(f)
      finally
          close(f)
      end

  When control leaves the `try` block (for example due to a `return`, or just finishing normally),
  `close(f)` will be executed. If the `try` block exits due to an exception, the exception will continue propagating.
  A `catch` block may be combined with `try` and `finally` as well.
  In this case the `finally` block will run after `catch` has handled the error.
  """

keywords[:break] = doc"""
  `break` breaks out of a loop immediately. For example

      i = 0
      while true
          i += 1
          i > 10 && break
          println(i)
      end

  prints the numbers 1 to 10.
  """

keywords[:continue] = doc"""
  `continue` skips the rest of the current loop, then carries on
  looping. For example

      for i = 1:10
          iseven(i) && continue
          println(i)
      end

  prints the numbers 1, 3, 5..., skipping the even numbers.
  """

keywords[:do] = doc"""
  The `do` keyword creates an anonymous function. For example

      map(1:10) do x
          2x
      end

  is equivalent to `map(x->2x, 1:10)`.

  Use multiple arguments like so:

      map(1:10, 10:20) do x, y
          x + y
      end
  """

keywords[:...] = doc"""
  The "splat" operator, `...`, represents a sequence of arguments. For example

      add(xs...) = reduce(+, xs)

  can take any number of arguments:

      add(1, 2, 3, 4, 5)

  `...` can also be used to apply a function to a sequence of arguments like so:

      add([1, 2, 3]...) # 6
      add(7, 1:100..., 1000:1100...) # 111107
  """

keywords[symbol(";")] = doc"""
  `;` has a similar role in Julia as in many C-like languages,
  and is used to delimit the end of the previous statement.
  `;` is not necessary after new lines, but can be used to
  seperate statements on a single line or to join statements into
  a single expression:

      function foo()
          println("Hello, "); println("World!")
          return true
      end

      foo() = (println("Hello, World!"); true)

    `;` is also used to suppress output in the REPL and similar
    interfaces.
  """

keywords[:(&&)]  = doc"""
    x && y

Short-circuiting boolean AND
"""

keywords[:(||)]  = doc"""
    x || y

Short-circuiting boolean OR
"""

keywords[:ccall] = doc"""
      ccall((symbol, library) or function_pointer, ReturnType, (ArgumentType1, ...), ArgumentValue1, ...)

  Call function in C-exported shared library, specified by
  `(function name, library)` tuple, where each component is a string
  or symbol.

  Note that the argument type tuple must be a literal tuple, and not
  a tuple-valued variable or expression. Alternatively, `ccall` may
  also be used to call a function pointer, such as one returned by
  `dlsym`.

  Each `ArgumentValue` to the `ccall` will be converted to the
  corresponding `ArgumentType`, by automatic insertion of calls to
  `unsafe_convert(ArgumentType, cconvert(ArgumentType,
  ArgumentValue))`. (See also the documentation for each of these
  functions for further details.) In most cases, this simply results
  in a call to `convert(ArgumentType, ArgumentValue)`.
  """

keywords[:begin] = doc"""
  `begin...end` denotes a block of code.

      begin
          println("Hello, ")
          println("World!")
      end

  Usually `begin` will not be necessary, since keywords
  such as `function` and `let` implicitly begin blocks of
  code. See also `;`.
  """

keywords[:type] = doc"""
  At their most basic, Julia types are specified as a name
  and a set of fields.

      type Point
          x
          y
      end

  Fields can have type restrictions, which may be parametised:

      type Point{X}
          x::X
          y::Float64
      end

  Type can also declare an abstract super type via `<:` syntax:

      type Point <: AbstractPoint
          ...

  See the manual for more details, such as information on
  inner constructors.
  """

keywords[:typealias] = doc"""
  Introduce a new name for an already expressible type.
  For example, in `base/boot.jl`, `UInt` is type aliased to either `UInt64` or `UInt32` as appropriate
  for the size of pointers on the system:

      if is(Int,Int64)
          typealias UInt UInt64
      else
          typealias UInt UInt32
      end

  For parametric types, `typealias` can be convenient for providing names in cases where some parameter
  choices are fixed.  In `base` for example:

      typealias Vector{T} Array{T,1}
  """

keywords[:immutable] = doc"""
  `immutable` acts in the same way as `type`, but declares
  that the fields of the type may not be set after construction.
  See `type` and the manual for more information.
  """

# """
# Executes an expression, printing the time it took to
# execute and the total number of bytes its execution caused to be
# allocated. Returns the value of the expression. For example:
#
#     @time begin
#         sleep(1)
#         2+2
#     end
# """
# :@time

doc"""
    @r_str -> Regex
Construct a regex, such as `r"^[a-z]*$"`. The regex also accepts
one or more flags, listed after the ending quote, to change its
behaviour:

  • `i` enables case-insensitive matching
  • `m` treats the `^` and `$` tokens as matching the start and
    and end of individual lines, as opposed to the whole string.
  • `s` allows the `.` modifier to match newlines.
  • `x` enables "comment mode": whitespace is enabled except when
    escaped with `\`, and `#` is treated as starting a comment.

For example, this regex has all three flags enabled:

    julia> match(r"a+.*b+.*?d$"ism, "Goodbye,\nOh, angry,\nBad world\n")
    RegexMatch("angry,\nBad world")
"""
:(r"")

# """
#     push!(collection, items...) → collection
#
# Insert `items` at the end of `collection`.
#
#     push!([1,2,3], 4) == [1,2,3,4]
# """
# push!

if Base.USE_GPL_LIBS

@doc doc"""
    fft(A [, dims])

Performs a multidimensional FFT of the array `A`.  The optional
`dims` argument specifies an iterable subset of dimensions (e.g.
an integer, range, tuple, or array) to transform along.  Most
efficient if the size of `A` along the transformed dimensions is
a product of small primes; see `nextprod()`.  See also
`plan_fft()` for even greater efficiency.

A one-dimensional FFT computes the one-dimensional discrete Fourier
transform (DFT) as defined by

$$\operatorname{DFT}(A)[k] =
  \sum_{n=1}^{\operatorname{length}(A)}
  \exp\left(-i\frac{2\pi
  (n-1)(k-1)}{\operatorname{length}(A)} \right) A[n].$$

A multidimensional FFT simply performs this operation along each
transformed dimension of `A`.

Higher performance is usually possible with multi-threading. Use
`FFTW.set_num_threads(np)` to use `np` threads, if you have `np`
processors.
""" fft

end # USE_GPL_LIBS

"""
    include(path::AbstractString)

Evaluate the contents of a source file in the current context.
During including, a task-local include path is set to the directory
containing the file. Nested calls to `include` will search
relative to that path. All paths refer to files on node 1 when
running in parallel, and files will be fetched from node 1. This
function is typically used to load source interactively, or to
combine files in packages that are broken into multiple source
files.
"""
include_from_node1(::AbstractString)

"""
0 (zero; BrE: `/ˈzɪərəʊ/` or AmE: `/ˈziːroʊ/`) is both a number and the numerical digit used to represent that number in numerals. It fulfills a central role in mathematics as the additive identity of the integers, real numbers, and many other algebraic structures. As a digit, 0 is used as a placeholder in place value systems. Names for the number 0 in English include zero, nought or (US) naught (`/ˈnɔːt/`), nil, or — in contexts where at least one adjacent digit distinguishes it from the letter "O" — oh or o (`/ˈoʊ/`). Informal or slang terms for zero include zilch and zip. Ought and aught (/ˈɔːt/), as well as cipher, have also been used historically.
"""
0