Core.AbstractArray
Base.AbstractVector
Base.AbstractMatrix
Base.AbstractVecOrMat
Core.Array
Core.Array(::UndefInitializer, ::Any)
Core.Array(::Nothing, ::Any)
Core.Array(::Missing, ::Any)
Core.UndefInitializer
Core.undef
Base.Vector
Base.Vector(::UndefInitializer, ::Any)
Base.Vector(::Nothing, ::Any)
Base.Vector(::Missing, ::Any)
Base.Matrix
Base.Matrix(::UndefInitializer, ::Any, ::Any)
Base.Matrix(::Nothing, ::Any, ::Any)
Base.Matrix(::Missing, ::Any, ::Any)
Base.VecOrMat
Core.DenseArray
Base.DenseVector
Base.DenseMatrix
Base.DenseVecOrMat
Base.StridedArray
Base.StridedVector
Base.StridedMatrix
Base.StridedVecOrMat
Base.GenericMemory
Base.Memory
Base.memoryref
Base.Slices
Base.RowSlices
Base.ColumnSlices
Base.getindex(::Type, ::Any...)
Base.zeros
Base.ones
Base.BitArray
Base.BitArray(::UndefInitializer, ::Integer...)
Base.BitArray(::Any)
Base.trues
Base.falses
Base.fill
Base.fill!
Base.empty
Base.similar
Base.ndims
Base.size
Base.axes(::Any)
Base.axes(::AbstractArray, ::Any)
Base.length(::AbstractArray)
Base.keys(::AbstractArray)
Base.eachindex
Base.IndexStyle
Base.IndexLinear
Base.IndexCartesian
Base.conj!
Base.stride
Base.strides
See also the [dot syntax for vectorizing functions](@ref man-vectorized);
for example, f.(args...) implicitly calls broadcast(f, args...).
Rather than relying on "vectorized" methods of functions like sin
to operate on arrays, you should use sin.(a) to vectorize via broadcast.
Base.broadcast
Base.Broadcast.broadcast!
Base.@__dot__
Base.Broadcast.BroadcastFunction
For specializing broadcast on custom types, see
Base.BroadcastStyle
Base.Broadcast.AbstractArrayStyle
Base.Broadcast.ArrayStyle
Base.Broadcast.DefaultArrayStyle
Base.Broadcast.broadcastable
Base.Broadcast.combine_axes
Base.Broadcast.combine_styles
Base.Broadcast.result_style
Base.getindex(::AbstractArray, ::Any...)
Base.setindex!(::AbstractArray, ::Any, ::Any...)
Base.nextind
Base.prevind
Base.copyto!(::AbstractArray, ::CartesianIndices, ::AbstractArray, ::CartesianIndices)
Base.copy!
Base.isassigned
Base.Colon
Base.CartesianIndex
Base.CartesianIndices
Base.Dims
Base.LinearIndices
Base.to_indices
Base.checkbounds
Base.checkindex
Base.elsize
A “view” is a data structure that acts like an array (it is a subtype of AbstractArray), but the underlying data is actually
part of another array.
For example, if x is an array and v = @view x[1:10], then v acts like a 10-element array, but its data is actually
accessing the first 10 elements of x. Writing to a view, e.g. v[3] = 2, writes directly to the underlying array x
(in this case modifying x[3]).
Slicing operations like x[1:10] create a copy by default in Julia. @view x[1:10] changes it to make a view. The
@views macro can be used on a whole block of code (e.g. @views function foo() .... end or @views begin ... end)
to change all the slicing operations in that block to use views. Sometimes making a copy of the data is faster and
sometimes using a view is faster, as described in the [performance tips](@ref man-performance-views).
Base.view
Base.@view
Base.@views
Base.parent
Base.parentindices
Base.selectdim
Base.reinterpret
Base.reshape
Base.insertdims
Base.dropdims
Base.vec
Base.SubArray
Base.cat
Base.vcat
Base.hcat
Base.hvcat
Base.hvncat
Base.stack
Base.vect
Base.circshift
Base.circshift!
Base.circcopy!
Base.findall(::Any)
Base.findall(::Function, ::Any)
Base.findfirst(::Any)
Base.findfirst(::Function, ::Any)
Base.findlast(::Any)
Base.findlast(::Function, ::Any)
Base.findnext(::Any, ::Integer)
Base.findnext(::Function, ::Any, ::Integer)
Base.findprev(::Any, ::Integer)
Base.findprev(::Function, ::Any, ::Integer)
Base.permutedims
Base.permutedims!
Base.PermutedDimsArray
Base.promote_shape
Base.accumulate
Base.accumulate!
Base.cumprod
Base.cumprod!
Base.cumsum
Base.cumsum!
Base.diff
Base.repeat
Base.rot180
Base.rotl90
Base.rotr90
Base.mapslices
Base.eachrow
Base.eachcol
Base.eachslice
Base.invperm
Base.isperm
Base.permute!(::Any, ::AbstractVector)
Base.invpermute!
Base.reverse(::AbstractVector; kwargs...)
Base.reverseind
Base.reverse!