RFC: Deprecate Array(T, dims...)

base/array.jl

@@ -25,6 +25,15 @@ typealias DenseVecOrMat{T} Union{DenseVector{T}, DenseMatrix{T}}
 
 import Core: arraysize, arrayset, arrayref
 
+"""
+ Array{T,N}(dims)
+
+Construct an uninitialized `N`-dimensional dense array with element type `T`. `dims` may
+be a tuple or a series of integer arguments corresponding to the length in each dimension.
+If the rank `N` is omitted, i.e. `Array{T}(dims)`, the rank is determined based on `dims`.
+"""
+Array
+
 vect() = Array{Any,1}(0)
 vect{T}(X::T...) = T[ X[i] for i=1:length(X) ]
 

base/asyncmap.jl

@@ -246,7 +246,7 @@ end
 
 # Special handling for some types.
 function asyncmap(f, s::AbstractString; kwargs...)
- s2=Array(Char, length(s))
+ s2 = Array{Char,1}(length(s))
  asyncmap!(f, s2, s; kwargs...)
  return convert(String, s2)
 end

base/boot.jl

@@ -330,13 +330,6 @@ typealias NTuple{N,T} Tuple{Vararg{T,N}}
 (::Type{Array{T,1}}){T}() = Array{T,1}(0)
 (::Type{Array{T,2}}){T}() = Array{T,2}(0, 0)
 
-# TODO: possibly turn these into deprecations
-Array{T,N}(::Type{T}, d::NTuple{N,Int}) = Array{T,N}(d)
-Array{T}(::Type{T}, d::Int...) = Array(T, d)
-Array{T}(::Type{T}, m::Int) = Array{T,1}(m)
-Array{T}(::Type{T}, m::Int,n::Int) = Array{T,2}(m,n)
-Array{T}(::Type{T}, m::Int,n::Int,o::Int) = Array{T,3}(m,n,o)
-
 # primitive Symbol constructors
 function Symbol(s::String)
  return ccall(:jl_symbol_n, Ref{Symbol}, (Ptr{UInt8}, Int),

base/deprecated.jl

@@ -1741,4 +1741,23 @@ end
 export @test_approx_eq
 # END code from base/test.jl
 
+# Deprecate Array(T, dims...) in favor of proper type constructors
+@deprecate Array{T,N}(::Type{T}, d::NTuple{N,Int}) Array{T,N}(d)
+@deprecate Array{T}(::Type{T}, d::Int...) Array{T,length(d)}(d...)
+@deprecate Array{T}(::Type{T}, m::Int) Array{T,1}(m)
+@deprecate Array{T}(::Type{T}, m::Int,n::Int) Array{T,2}(m,n)
+@deprecate Array{T}(::Type{T}, m::Int,n::Int,o::Int) Array{T,3}(m,n,o)
+@deprecate Array{T}(::Type{T}, d::Integer...) Array{T,length(d)}(convert(Tuple{Vararg{Int}}, d))
+@deprecate Array{T}(::Type{T}, m::Integer) Array{T,1}(Int(m))
+@deprecate Array{T}(::Type{T}, m::Integer,n::Integer) Array{T,2}(Int(m),Int(n))
+@deprecate Array{T}(::Type{T}, m::Integer,n::Integer,o::Integer) Array{T,3}(Int(m),Int(n),Int(o))
+
+# Likewise for SharedArrays
+@deprecate SharedArray{T,N}(::Type{T}, dims::Dims{N}; kwargs...) SharedArray{T,N}(dims; kwargs...)
+@deprecate SharedArray{T}(::Type{T}, dims::Int...; kwargs...) SharedArray{T,length(dims)}(dims...; kwargs...)
+@deprecate(SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,Int}, offset; kwargs...),
+ SharedArray{T,N}(filename, dims, offset; kwargs...))
+@deprecate(SharedArray{T}(filename::AbstractString, ::Type{T}, dims::NTuple, offset; kwargs...),
+ SharedArray{T,length(dims)}(filename, dims, offset; kwargs...))
+
 # End deprecations scheduled for 0.6

base/docs/helpdb/Base.jl

@@ -1676,15 +1676,6 @@ by `show` generally includes Julia-specific formatting and type information.
 """
 show(x)
 
-"""
- Array(dims)
-
-`Array{T}(dims)` constructs an uninitialized dense array with element type `T`. `dims` may
-be a tuple or a series of integer arguments. The syntax `Array(T, dims)` is also available,
-but deprecated.
-"""
-Array
-
 """
  issubtype(type1, type2)
 

base/libc.jl

@@ -277,7 +277,7 @@ if is_windows()
  const FORMAT_MESSAGE_FROM_SYSTEM = UInt32(0x1000)
  const FORMAT_MESSAGE_IGNORE_INSERTS = UInt32(0x200)
  const FORMAT_MESSAGE_MAX_WIDTH_MASK = UInt32(0xFF)
- lpMsgBuf = Array(Ptr{UInt16})
+ lpMsgBuf = Array{Ptr{UInt16},0}()
  lpMsgBuf[1] = 0
  len = ccall(:FormatMessageW,stdcall,UInt32,(Cint, Ptr{Void}, Cint, Cint, Ptr{Ptr{UInt16}}, Cint, Ptr{Void}),
  FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS | FORMAT_MESSAGE_MAX_WIDTH_MASK,

base/sharedarray.jl

@@ -28,19 +28,8 @@ type SharedArray{T,N} <: DenseArray{T,N}
  end
 end
 
-(::Type{SharedArray{T}}){T,N}(d::NTuple{N,Int}; kwargs...) =
- SharedArray(T, d; kwargs...)
-(::Type{SharedArray{T}}){T}(d::Integer...; kwargs...) =
- SharedArray(T, d; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer; kwargs...) =
- SharedArray(T, m; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer, n::Integer; kwargs...) =
- SharedArray(T, m, n; kwargs...)
-(::Type{SharedArray{T}}){T}(m::Integer, n::Integer, o::Integer; kwargs...) =
- SharedArray(T, m, n, o; kwargs...)
-
 """
- SharedArray(T::Type, dims::NTuple; init=false, pids=Int[])
+ SharedArray{T,N}(dims::NTuple; init=false, pids=Int[])
 
 Construct a `SharedArray` of a bitstype `T` and size `dims` across the processes specified
 by `pids` - all of which have to be on the same host.
@@ -52,8 +41,39 @@ computation with the master process acting as a driver.
 
 If an `init` function of the type `initfn(S::SharedArray)` is specified, it is called on all
 the participating workers.
+
+ SharedArray{T,N}(filename::AbstractString, dims::NTuple, [offset=0]; mode=nothing, init=false, pids=Int[])
+
+Construct a `SharedArray` backed by the file `filename`, with element
+type `T` (must be a `bitstype`) and size `dims`, across the processes
+specified by `pids` - all of which have to be on the same host. This
+file is mmapped into the host memory, with the following consequences:
+
+- The array data must be represented in binary format (e.g., an ASCII
+ format like CSV cannot be supported)
+
+- Any changes you make to the array values (e.g., `A[3] = 0`) will
+ also change the values on disk
+
+If `pids` is left unspecified, the shared array will be mapped across
+all processes on the current host, including the master. But,
+`localindexes` and `indexpids` will only refer to worker
+processes. This facilitates work distribution code to use workers for
+actual computation with the master process acting as a driver.
+
+`mode` must be one of `"r"`, `"r+"`, `"w+"`, or `"a+"`, and defaults
+to `"r+"` if the file specified by `filename` already exists, or
+`"w+"` if not. If an `init` function of the type
+`initfn(S::SharedArray)` is specified, it is called on all the
+participating workers. You cannot specify an `init` function if the
+file is not writable.
+
+`offset` allows you to skip the specified number of bytes at the
+beginning of the file.
 """
-function SharedArray{T,N}(::Type{T}, dims::Dims{N}; init=false, pids=Int[])
+SharedArray
+
+function (::Type{SharedArray{T,N}}){T,N}(dims::Dims{N}; init=false, pids=Int[])
  isbits(T) || throw(ArgumentError("type of SharedArray elements must be bits types, got $(T)"))
 
  pids, onlocalhost = shared_pids(pids)
@@ -110,39 +130,20 @@ function SharedArray{T,N}(::Type{T}, dims::Dims{N}; init=false, pids=Int[])
  S
 end
 
-SharedArray(T, I::Int...; kwargs...) = SharedArray(T, I; kwargs...)
-
-"""
- SharedArray(filename::AbstractString, T::Type, dims::NTuple, [offset=0]; mode=nothing, init=false, pids=Int[])
-
-Construct a `SharedArray` backed by the file `filename`, with element
-type `T` (must be a `bitstype`) and size `dims`, across the processes
-specified by `pids` - all of which have to be on the same host. This
-file is mmapped into the host memory, with the following consequences:
-
-- The array data must be represented in binary format (e.g., an ASCII
- format like CSV cannot be supported)
-
-- Any changes you make to the array values (e.g., `A[3] = 0`) will
- also change the values on disk
-
-If `pids` is left unspecified, the shared array will be mapped across
-all processes on the current host, including the master. But,
-`localindexes` and `indexpids` will only refer to worker
-processes. This facilitates work distribution code to use workers for
-actual computation with the master process acting as a driver.
-
-`mode` must be one of `"r"`, `"r+"`, `"w+"`, or `"a+"`, and defaults
-to `"r+"` if the file specified by `filename` already exists, or
-`"w+"` if not. If an `init` function of the type
-`initfn(S::SharedArray)` is specified, it is called on all the
-participating workers. You cannot specify an `init` function if the
-file is not writable.
+(::Type{SharedArray{T,N}}){T,N}(I::Integer...; kwargs...) =
+ SharedArray{T,N}(I; kwargs...)
+(::Type{SharedArray{T}}){T}(d::NTuple; kwargs...) =
+ SharedArray{T,length(d)}(d; kwargs...)
+(::Type{SharedArray{T}}){T}(I::Integer...; kwargs...) =
+ SharedArray{T,length(I)}(I; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer; kwargs...) =
+ SharedArray{T,1}(m; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer, n::Integer; kwargs...) =
+ SharedArray{T,2}(m, n; kwargs...)
+(::Type{SharedArray{T}}){T}(m::Integer, n::Integer, o::Integer; kwargs...) =
+ SharedArray{T,3}(m, n, o; kwargs...)
 
-`offset` allows you to skip the specified number of bytes at the
-beginning of the file.
-"""
-function SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,Int},
+function (::Type{SharedArray{T,N}}){T,N}(filename::AbstractString, dims::NTuple{N,Int},
  offset::Integer=0; mode=nothing, init=false, pids::Vector{Int}=Int[])
  if !isabspath(filename)
  throw(ArgumentError("$filename is not an absolute path; try abspath(filename)?"))
@@ -208,6 +209,10 @@ function SharedArray{T,N}(filename::AbstractString, ::Type{T}, dims::NTuple{N,In
  S
 end
 
+(::Type{SharedArray{T}}){T,N}(filename::AbstractString, dims::NTuple{N,Int}, offset::Integer=0;
+ mode=nothing, init=false, pids::Vector{Int}=Int[]) =
+ SharedArray{T,N}(filename, dims, offset; mode=mode, init=init, pids=pids)
+
 function initialize_shared_array(S, onlocalhost, init, pids)
  if onlocalhost
  init_loc_flds(S)
@@ -246,6 +251,7 @@ typealias SharedMatrix{T} SharedArray{T,2}
 
 length(S::SharedArray) = prod(S.dims)
 size(S::SharedArray) = S.dims
+ndims(S::SharedArray) = length(S.dims)
 linearindexing{S<:SharedArray}(::Type{S}) = LinearFast()
 
 function reshape{T,N}(a::SharedArray{T}, dims::NTuple{N,Int})
@@ -307,21 +313,21 @@ localindexes(S::SharedArray) = S.pidx > 0 ? range_1dim(S, S.pidx) : 1:0
 unsafe_convert{T}(::Type{Ptr{T}}, S::SharedArray) = unsafe_convert(Ptr{T}, sdata(S))
 
 function convert(::Type{SharedArray}, A::Array)
- S = SharedArray(eltype(A), size(A))
+ S = SharedArray{eltype(A),ndims(A)}(size(A))
  copy!(S, A)
 end
 function convert{T}(::Type{SharedArray{T}}, A::Array)
- S = SharedArray(T, size(A))
+ S = SharedArray{T,ndims(A)}(size(A))
  copy!(S, A)
 end
 function convert{TS,TA,N}(::Type{SharedArray{TS,N}}, A::Array{TA,N})
- S = SharedArray(TS, size(A))
+ S = SharedArray{TS,ndims(A)}(size(A))
  copy!(S, A)
 end
 
 function deepcopy_internal(S::SharedArray, stackdict::ObjectIdDict)
  haskey(stackdict, S) && return stackdict[S]
- R = SharedArray(eltype(S), size(S); pids = S.pids)
+ R = SharedArray{eltype(S),ndims(S)}(size(S); pids = S.pids)
  copy!(sdata(R), sdata(S))
  stackdict[S] = R
  return R
@@ -468,16 +474,16 @@ end
 
 # convenience constructors
 function shmem_fill(v, dims; kwargs...)
- SharedArray(typeof(v), dims; init = S->fill!(S.loc_subarr_1d, v), kwargs...)
+ SharedArray{typeof(v),length(dims)}(dims; init = S->fill!(S.loc_subarr_1d, v), kwargs...)
 end
 shmem_fill(v, I::Int...; kwargs...) = shmem_fill(v, I; kwargs...)
 
 # rand variant with range
 function shmem_rand(TR::Union{DataType, UnitRange}, dims; kwargs...)
  if isa(TR, UnitRange)
- SharedArray(Int, dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+ SharedArray{Int,length(dims)}(dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
  else
- SharedArray(TR, dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+ SharedArray{TR,length(dims)}(dims; init = S -> map!(x -> rand(TR), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
  end
 end
 shmem_rand(TR::Union{DataType, UnitRange}, i::Int; kwargs...) = shmem_rand(TR, (i,); kwargs...)
@@ -487,7 +493,7 @@ shmem_rand(dims; kwargs...) = shmem_rand(Float64, dims; kwargs...)
 shmem_rand(I::Int...; kwargs...) = shmem_rand(I; kwargs...)
 
 function shmem_randn(dims; kwargs...)
- SharedArray(Float64, dims; init = S-> map!(x -> randn(), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
+ SharedArray{Float64,length(dims)}(dims; init = S-> map!(x -> randn(), S.loc_subarr_1d, S.loc_subarr_1d), kwargs...)
 end
 shmem_randn(I::Int...; kwargs...) = shmem_randn(I; kwargs...)
 

base/sparse/sparsematrix.jl

@@ -1390,7 +1390,7 @@ speye_scaled(diag, m::Integer, n::Integer) = speye_scaled(typeof(diag), diag, m,
 function speye_scaled(T, diag, m::Integer, n::Integer)
  ((m < 0) || (n < 0)) && throw(ArgumentError("invalid array dimensions"))
  nnz = min(m,n)
- colptr = Array(Int, 1+n)
+ colptr = Array{Int,1}(1+n)
  colptr[1:nnz+1] = 1:nnz+1
  colptr[nnz+2:end] = nnz+1
  SparseMatrixCSC(Int(m), Int(n), colptr, Vector{Int}(1:nnz), fill!(Vector{T}(nnz), diag))

base/sparse/sparsevector.jl

@@ -563,7 +563,7 @@ end
 
 function find{Tv,Ti}(x::SparseVector{Tv,Ti})
  numnz = nnz(x)
- I = Array(Ti, numnz)
+ I = Array{Ti,1}(numnz)
 
  nzind = x.nzind
  nzval = x.nzval
@@ -587,8 +587,8 @@ end
 function findnz{Tv,Ti}(x::SparseVector{Tv,Ti})
  numnz = nnz(x)
 
- I = Array(Ti, numnz)
- V = Array(Tv, numnz)
+ I = Array{Ti,1}(numnz)
+ V = Array{Tv,1}(numnz)
 
  nzind = x.nzind
  nzval = x.nzval

base/sysimg.jl

@@ -99,12 +99,6 @@ include("subarray.jl")
 (::Type{Matrix{T}}){T}(m::Integer, n::Integer) = Matrix{T}(Int(m), Int(n))
 (::Type{Matrix})(m::Integer, n::Integer) = Matrix{Any}(Int(m), Int(n))
 
-# TODO: possibly turn these into deprecations
-Array{T}(::Type{T}, d::Integer...) = Array(T, convert(Tuple{Vararg{Int}}, d))
-Array{T}(::Type{T}, m::Integer) = Array{T,1}(Int(m))
-Array{T}(::Type{T}, m::Integer,n::Integer) = Array{T,2}(Int(m),Int(n))
-Array{T}(::Type{T}, m::Integer,n::Integer,o::Integer) = Array{T,3}(Int(m),Int(n),Int(o))
-
 # numeric operations
 include("hashing.jl")
 include("rounding.jl")

doc/src/manual/parallel-computing.md

@@ -312,7 +312,7 @@ Parallel for loops like these must be avoided. Fortunately, [Shared Arrays](@ref
 to get around this limitation:
 
 ```julia
-a = SharedArray(Float64,10)
+a = SharedArray{Float64}(10)
 @parallel for i=1:10
  a[i] = i
 end
@@ -720,10 +720,10 @@ just returns the object itself, so it's safe to use [`sdata()`](@ref) on any `Ar
 The constructor for a shared array is of the form:
 
 ```julia
-SharedArray(T::Type, dims::NTuple; init=false, pids=Int[])
+SharedArray{T,N}(dims::NTuple; init=false, pids=Int[])
 ```
 
-which creates a shared array of a bits type `T` and size `dims` across the processes specified
+which creates an `N`-dimensional shared array of a bits type `T` and size `dims` across the processes specified
 by `pids`. Unlike distributed arrays, a shared array is accessible only from those participating
 workers specified by the `pids` named argument (and the creating process too, if it is on the
 same host).
@@ -741,7 +741,7 @@ julia> addprocs(3)
  3
  4
 
-julia> S = SharedArray(Int, (3,4), init = S -> S[Base.localindexes(S)] = myid())
+julia> S = SharedArray{Int,2}((3,4), init = S -> S[Base.localindexes(S)] = myid())
 3×4 SharedArray{Int64,2}:
  2 2 3 4
  2 3 3 4
@@ -762,7 +762,7 @@ convenient for splitting up tasks among processes. You can, of course, divide th
 you wish:
 
 ```julia
-julia> S = SharedArray(Int, (3,4), init = S -> S[indexpids(S):length(procs(S)):length(S)] = myid())
+julia> S = SharedArray{Int,2}((3,4), init = S -> S[indexpids(S):length(procs(S)):length(S)] = myid())
 3×4 SharedArray{Int64,2}:
  2 2 2 2
  3 3 3 3
@@ -861,8 +861,8 @@ end
 If we create `SharedArray`s and time these functions, we get the following results (with `julia -p 4`):
 
 ```julia
-q = SharedArray(Float64, (500,500,500))
-u = SharedArray(Float64, (500,500,500))
+q = SharedArray{Float64,3}((500,500,500))
+u = SharedArray{Float64,3}((500,500,500))
 
 # Run once to JIT-compile
 advection_serial!(q, u)

src/julia-syntax.scm

@@ -2242,7 +2242,7 @@
  ,.(map (lambda (v r) `(= ,v (call (top length) ,r))) lengths rv)
  (scope-block
  (block
- (= ,result (call (core Array) ,atype ,@lengths))
+ (= ,result (call (curly Array ,atype ,(length lengths)) ,@lengths))
  (= ,ri 1)
  ,(construct-loops (reverse ranges) (reverse rv) is states (reverse lengths))
  ,result)))))