Even more simplifications

JuliaLang · Jan 21, 2017 · aa8d3a1 · aa8d3a1
1 parent 149f8aa
commit aa8d3a1
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Showing 2 changed files with 4 additions and 9 deletions.
diff --git a/base/broadcast.jl b/base/broadcast.jl
@@ -33,10 +33,10 @@ containertype(ct1, ct2) = promote_containertype(containertype(ct1), containertyp
 @inline containertype(ct1, ct2, cts...) = promote_containertype(containertype(ct1), containertype(ct2, cts...))
 
 promote_containertype(ct1, ct2) = Array
+promote_containertype{T<:AbstractArray}(::Type{T}, ::Type{Tuple}) = Array
+promote_containertype{T<:AbstractArray}(::Type{Tuple}, ::Type{T}) = Array
 promote_containertype(::Type{Array}, ::Type{VecOrMat}) = Array
 promote_containertype(::Type{VecOrMat}, ::Type{Array}) = Array
-promote_containertype(::Type{VecOrMat}, ::Type{Tuple}) = Array
-promote_containertype(::Type{Tuple}, ::Type{VecOrMat}) = Array
 promote_containertype{T<:Array}(::Type{T}, ::ScalarType) = T
 promote_containertype{T<:Array}(::ScalarType, ::Type{T}) = T
 promote_containertype(::Type{Tuple}, ::ScalarType) = Tuple
@@ -52,7 +52,7 @@ broadcast_indices(A) = broadcast_indices(containertype(A), A)
 broadcast_indices(::ScalarType, A) = ()
 broadcast_indices(::Type{Tuple}, A) = (OneTo(length(A)),)
 broadcast_indices(::Type{Array}, A::Ref) = ()
-broadcast_indices{T<:Array}(::Type{T}, A) = indices(A)
+broadcast_indices{T<:AbstractArray}(::Type{T}, A) = indices(A)
 @inline broadcast_indices(A, B...) = broadcast_shape((), broadcast_indices(A), map(broadcast_indices, B)...)
 # shape (i.e., tuple-of-indices) inputs
 broadcast_shape(shape::Tuple) = shape

diff --git a/base/sparse/higherorderfns.jl b/base/sparse/higherorderfns.jl
@@ -5,8 +5,7 @@ module HigherOrderFns
 # This module provides higher order functions specialized for sparse arrays,
 # particularly map[!]/broadcast[!] for SparseVectors and SparseMatrixCSCs at present.
 import Base: map, map!, broadcast, broadcast!
-import Base.Broadcast: _containertype, promote_containertype,
-    broadcast_indices, broadcast_c, broadcast_c!
+import Base.Broadcast: _containertype, promote_containertype, broadcast_c, broadcast_c!
 
 using Base: front, tail, to_shape
 using ..SparseArrays: SparseVector, SparseMatrixCSC, AbstractSparseArray,
@@ -857,8 +856,6 @@ end
 
 # (9) broadcast[!] over combinations of broadcast scalars and sparse vectors/matrices
 
-# broadcast shape promotion for combinations of sparse arrays and other types
-broadcast_indices(::Type{AbstractSparseArray}, A) = indices(A)
 # broadcast container type promotion for combinations of sparse arrays and other types
 _containertype{T<:SparseVecOrMat}(::Type{T}) = AbstractSparseArray
 # combinations of sparse arrays with broadcast scalars should yield sparse arrays
@@ -868,9 +865,7 @@ promote_containertype{T<:AbstractSparseArray}(::Type{Any}, ::Type{T}) = Abstract
 promote_containertype{T<:AbstractSparseArray}(::Type{T}, ::Type{Any}) = AbstractSparseArray
 # combinations of sparse arrays with anything else should fall back to generic dense broadcast
 promote_containertype{T<:AbstractSparseArray}(::Type{Array}, ::Type{T}) = Array
-promote_containertype{T<:AbstractSparseArray}(::Type{Tuple}, ::Type{T}) = Array
 promote_containertype{T<:AbstractSparseArray}(::Type{T}, ::Type{Array}) = Array
-promote_containertype{T<:AbstractSparseArray}(::Type{T}, ::Type{Tuple}) = Array
 
 # broadcast[!] entry points for combinations of sparse arrays and other (scalar) types
 @inline function broadcast_c{T<:AbstractSparseArray,N}(f, ::Type{T}, mixedargs::Vararg{Any,N})