Support using colon to omit a dimension in reshape (#19919)

* Support using colon to omit a dimension in reshape

Closes #16790.

* Add NEWS.md

NEWS.md

@@ -186,6 +186,10 @@ Library improvements
   `cumprod`. Also known as a [scan](https://en.wikipedia.org/wiki/Prefix_sum)
   operation ([#18931]).
 
+  * `reshape` now allows specifying one dimension with a `Colon()` (`:`) for the new shape, in which case
+    that dimension's length will be computed such that its product with all the other dimensions is equal
+    to the length of the original array ([#19919]).
+
   * New `titlecase` function, which capitalizes the first character of each word within a string ([#19469]).
 
   * `any` and `all` now always short-circuit, and `mapreduce` never short-circuits ([#19543]).

base/docs/helpdb/Base.jl

@@ -446,39 +446,6 @@ See also [`zeros`](@ref), [`similar`](@ref).
 """
 ones
 
-"""
-    reshape(A, dims)
-
-Create an array with the same data as the given array, but with different dimensions.
-
-```jldoctest
-julia> A = collect(1:16)
-16-element Array{Int64,1}:
-  1
-  2
-  3
-  4
-  5
-  6
-  7
-  8
-  9
- 10
- 11
- 12
- 13
- 14
- 15
- 16
-
-julia> reshape(A, (2, 8))
-2×8 Array{Int64,2}:
- 1  3  5  7   9  11  13  15
- 2  4  6  8  10  12  14  16
-```
-"""
-reshape
-
 """
     randsubseq!(S, A, p)
 

base/reshapedarray.jl

@@ -36,10 +36,79 @@ start(R::ReshapedArrayIterator) = start(R.iter)
 end
 length(R::ReshapedArrayIterator) = length(R.iter)
 
+"""
+    reshape(A, dims...)
+    reshape(A, dims)
+
+Return an array with the same data as the given array, but with different dimensions.
+
+The new dimensions may be specified either as a list of arguments or as a shape
+tuple. At most one dimension may be specified with a `:`, in which case its
+length is computed such that its product with all the specified dimensions is
+equal to the length of the original array A.
+
+```jldoctest
+julia> A = collect(1:16)
+16-element Array{Int64,1}:
+  1
+  2
+  3
+  4
+  5
+  6
+  7
+  8
+  9
+ 10
+ 11
+ 12
+ 13
+ 14
+ 15
+ 16
+
+julia> reshape(A, (4, 4))
+4×4 Array{Int64,2}:
+ 1  5   9  13
+ 2  6  10  14
+ 3  7  11  15
+ 4  8  12  16
+
+julia> reshape(A, 2, :)
+2×8 Array{Int64,2}:
+ 1  3  5  7   9  11  13  15
+ 2  4  6  8  10  12  14  16
+```
+
+"""
+reshape
+
 reshape(parent::AbstractArray, dims::IntOrInd...) = reshape(parent, dims)
 reshape(parent::AbstractArray, shp::NeedsShaping) = reshape(parent, to_shape(shp))
 reshape(parent::AbstractArray, dims::Dims)        = _reshape(parent, dims)
 
+# Allow missing dimensions with Colon():
+reshape(parent::AbstractArray, dims::Int...) = reshape(parent, dims)
+reshape(parent::AbstractArray, dims::Union{Int,Colon}...) = reshape(parent, dims)
+reshape(parent::AbstractArray, dims::Tuple{Vararg{Union{Int,Colon}}}) = _reshape(parent, _reshape_uncolon(parent, dims))
+# Recursively move dimensions to pre and post tuples, splitting on the Colon
+@inline _reshape_uncolon(A, dims) = _reshape_uncolon(A, (), nothing, (), dims)
+@inline _reshape_uncolon(A, pre, c::Void,  post, dims::Tuple{Any, Vararg{Any}}) =
+    _reshape_uncolon(A, (pre..., dims[1]), c, post, tail(dims))
+@inline _reshape_uncolon(A, pre, c::Void,  post, dims::Tuple{Colon, Vararg{Any}}) =
+    _reshape_uncolon(A, pre, dims[1], post, tail(dims))
+@inline _reshape_uncolon(A, pre, c::Colon, post, dims::Tuple{Any, Vararg{Any}}) =
+    _reshape_uncolon(A, pre, c, (post..., dims[1]), tail(dims))
+_reshape_uncolon(A, pre, c::Colon, post, dims::Tuple{Colon, Vararg{Any}}) =
+    throw(DimensionMismatch("new dimensions $((pre..., c, post..., dims...)) may only have at most one omitted dimension specified by Colon()"))
+@inline function _reshape_uncolon(A, pre, c::Colon, post, dims::Tuple{})
+    sz, remainder = divrem(length(A), prod(pre)*prod(post))
+    remainder == 0 || _throw_reshape_colon_dimmismatch(A, pre, post)
+    (pre..., sz, post...)
+end
+_throw_reshape_colon_dimmismatch(A, pre, post) =
+    throw(DimensionMismatch("array size $(length(A)) must be divisible by the product of the new dimensions $((pre..., :, post...))"))
+
 reshape{T,N}(parent::AbstractArray{T,N}, ndims::Type{Val{N}}) = parent
 function reshape{T,AN,N}(parent::AbstractArray{T,AN}, ndims::Type{Val{N}})
     reshape(parent, rdims((), indices(parent), Val{N}))

test/arrayops.jl

@@ -135,6 +135,27 @@ end
         @test isa(reshape(s, Val{N}), Base.ReshapedArray{Int,N})
     end
 end
+@testset "reshape with colon" begin
+    # Reshape with an omitted dimension
+    let A = linspace(1, 60, 60)
+        @test size(reshape(A, :))         == (60,)
+        @test size(reshape(A, :, 1))      == (60, 1)
+        @test size(reshape(A, (:, 2)))    == (30, 2)
+        @test size(reshape(A, 3, :))      == (3, 20)
+        @test size(reshape(A, 2, 3, :))   == (2, 3, 10)
+        @test size(reshape(A, (2, :, 5))) == (2, 6, 5)
+        @test_throws DimensionMismatch reshape(A, 7, :)
+        @test_throws DimensionMismatch reshape(A, :, 2, 3, 4)
+        @test_throws DimensionMismatch reshape(A, (:, :))
+
+        B = rand(2,2,2,2)
+        @test size(reshape(B, :)) == (16,)
+        @test size(reshape(B, :, 4)) == (4, 4)
+        @test size(reshape(B, (2, 1, :))) == (2, 1, 8)
+        @test_throws DimensionMismatch reshape(B, 3, :)
+        @test_throws DimensionMismatch reshape(B, :, :, 2, 2)
+    end
+end
 
 @test reshape(1:5, (5,)) === 1:5
 @test reshape(1:5, 5) === 1:5