Release 1.0

Project.toml

@@ -1,6 +1,6 @@
 name = "FillArrays"
 uuid = "1a297f60-69ca-5386-bcde-b61e274b549b"
-version = "0.13.11"
+version = "1.0"
 
 [deps]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -9,7 +9,7 @@ SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
-Aqua = "0.5"
+Aqua = "0.5, 0.6"
 julia = "1.6"
 
 [extras]

README.md

@@ -14,12 +14,8 @@ as well as identity matrices.  This package exports the following types:
 
 
 The primary purpose of this package is to present a unified way of constructing
-matrices. For example, to construct a 5-by-5 `CLArray` of all zeros, one would use
-```julia
-julia> CLArray(Zeros(5,5))
-```
-Because `Zeros` is lazy, this can be accomplished on the GPU with no memory transfer.
-Similarly, to construct a 5-by-5 `BandedMatrix` of all zeros with bandwidths `(1,2)`, one would use  
+matrices. 
+For example, to construct a 5-by-5 `BandedMatrix` of all zeros with bandwidths `(1,2)`, one would use  
 ```julia
 julia> BandedMatrix(Zeros(5,5), (1, 2))
 ```

src/FillArrays.jl

@@ -6,7 +6,7 @@ import Base: size, getindex, setindex!, IndexStyle, checkbounds, convert,
     +, -, *, /, \, diff, sum, cumsum, maximum, minimum, sort, sort!,
     any, all, axes, isone, iterate, unique, allunique, permutedims, inv,
     copy, vec, setindex!, count, ==, reshape, _throw_dmrs, map, zero,
-    show, view, in, mapreduce, one, reverse, promote_op
+    show, view, in, mapreduce, one, reverse, promote_op, promote_rule
 
 import LinearAlgebra: rank, svdvals!, tril, triu, tril!, triu!, diag, transpose, adjoint, fill!,
     dot, norm2, norm1, normInf, normMinusInf, normp, lmul!, rmul!, diagzero, AdjointAbsVec, TransposeAbsVec,
@@ -18,7 +18,7 @@ import Base.Broadcast: broadcasted, DefaultArrayStyle, broadcast_shape
 import Statistics: mean, std, var, cov, cor
 
 
-export Zeros, Ones, Fill, Eye, Trues, Falses
+export Zeros, Ones, Fill, Eye, Trues, Falses, OneElement
 
 import Base: oneto
 
@@ -34,6 +34,7 @@ const AbstractFillVecOrMat{T} = Union{AbstractFillVector{T},AbstractFillMatrix{T
 
 ==(a::AbstractFill, b::AbstractFill) = axes(a) == axes(b) && getindex_value(a) == getindex_value(b)
 
+
 @inline function _fill_getindex(F::AbstractFill, kj::Integer...)
     @boundscheck checkbounds(F, kj...)
     getindex_value(F)
@@ -147,15 +148,47 @@ Fill{T,0}(x::T, ::Tuple{}) where T = Fill{T,0,Tuple{}}(x, ()) # ambiguity fix
 @inline axes(F::Fill) = F.axes
 @inline size(F::Fill) = map(length, F.axes)
 
+"""
+    getindex_value(F::AbstractFill)
+
+Return the value that `F` is filled with.
+
+# Examples
+
+```jldoctest
+julia> f = Ones(3);
+
+julia> FillArrays.getindex_value(f)
+1.0
+
+julia> g = Fill(2, 10);
+
+julia> FillArrays.getindex_value(g)
+2
+```
+"""
+getindex_value
+
 @inline getindex_value(F::Fill) = F.value
 
 AbstractArray{T}(F::Fill{V,N}) where {T,V,N} = Fill{T}(convert(T, F.value)::T, F.axes)
 AbstractArray{T,N}(F::Fill{V,N}) where {T,V,N} = Fill{T}(convert(T, F.value)::T, F.axes)
 AbstractFill{T}(F::AbstractFill) where T = AbstractArray{T}(F)
+AbstractFill{T,N}(F::AbstractFill) where {T,N} = AbstractArray{T,N}(F)
+AbstractFill{T,N,Ax}(F::AbstractFill{<:Any,N,Ax}) where {T,N,Ax} = AbstractArray{T,N}(F)
+
+convert(::Type{AbstractFill{T}}, F::AbstractFill) where T = convert(AbstractArray{T}, F)
+convert(::Type{AbstractFill{T,N}}, F::AbstractFill) where {T,N} = convert(AbstractArray{T,N}, F)
+convert(::Type{AbstractFill{T,N,Ax}}, F::AbstractFill{<:Any,N,Ax}) where {T,N,Ax} = convert(AbstractArray{T,N}, F)
 
 copy(F::Fill) = Fill(F.value, F.axes)
 
-""" Throws an error if `arr` does not contain one and only one unique value. """
+"""
+    unique_value(arr::AbstractArray)
+
+Return `only(unique(arr))` without intermediate allocations.
+Throws an error if `arr` does not contain one and only one unique value.
+"""
 function unique_value(arr::AbstractArray)
     if isempty(arr) error("Cannot convert empty array to Fill") end
     val = first(arr)
@@ -262,6 +295,7 @@ for (Typ, funcs, func) in ((:Zeros, :zeros, :zero), (:Ones, :ones, :one))
         @inline $Typ{T,N}(A::AbstractArray{V,N}) where{T,V,N} = $Typ{T,N}(size(A))
         @inline $Typ{T}(A::AbstractArray) where{T} = $Typ{T}(size(A))
         @inline $Typ(A::AbstractArray) = $Typ{eltype(A)}(A)
+        @inline $Typ(::Type{T}, m...) where T = $Typ{T}(m...)
 
         @inline axes(Z::$Typ) = Z.axes
         @inline size(Z::$Typ) = length.(Z.axes)
@@ -273,6 +307,14 @@ for (Typ, funcs, func) in ((:Zeros, :zeros, :zero), (:Ones, :ones, :one))
         copy(F::$Typ) = F
 
         getindex(F::$Typ{T,0}) where T = getindex_value(F)
+
+        promote_rule(::Type{$Typ{T, N, Axes}}, ::Type{$Typ{V, N, Axes}}) where {T,V,N,Axes} = $Typ{promote_type(T,V),N,Axes}
+        function convert(::Type{$Typ{T,N,Axes}}, A::$Typ{V,N,Axes}) where {T,V,N,Axes}
+            convert(T, getindex_value(A)) # checks that the types are convertible
+            $Typ{T,N,Axes}(axes(A))
+        end
+        convert(::Type{$Typ{T,N}}, A::$Typ{V,N,Axes}) where {T,V,N,Axes} = convert($Typ{T,N,Axes}, A)
+        convert(::Type{$Typ{T}}, A::$Typ{V,N,Axes}) where {T,V,N,Axes} = convert($Typ{T,N,Axes}, A)
     end
 end
 
@@ -284,6 +326,8 @@ for TYPE in (:Fill, :AbstractFill, :Ones, :Zeros), STYPE in (:AbstractArray, :Ab
     end
 end
 
+promote_rule(::Type{<:AbstractFill{T, N, Axes}}, ::Type{<:AbstractFill{V, N, Axes}}) where {T,V,N,Axes} = Fill{promote_type(T,V),N,Axes}
+
 """
     fillsimilar(a::AbstractFill, axes)
 
@@ -426,7 +470,8 @@ end
 
 
 ## Array
-Base.Array{T,N}(F::AbstractFill{V,N}) where {T,V,N} = fill(convert(T, getindex_value(F)), size(F))
+Base.Array{T,N}(F::AbstractFill{V,N}) where {T,V,N} =
+    convert(Array{T,N}, fill(convert(T, getindex_value(F)), size(F)))
 
 # These are in case `zeros` or `ones` are ever faster than `fill`
 for (Typ, funcs, func) in ((:Zeros, :zeros, :zero), (:Ones, :ones, :one))
@@ -437,7 +482,7 @@ end
 
 # temporary patch. should be a PR(#48895) to LinearAlgebra
 Diagonal{T}(A::AbstractFillMatrix) where T = Diagonal{T}(diag(A))
-function convert(::Type{T}, A::AbstractFillMatrix) where T<:Diagonal 
+function convert(::Type{T}, A::AbstractFillMatrix) where T<:Diagonal
     checksquare(A)
     isdiag(A) ? T(A) : throw(InexactError(:convert, T, A))
 end
@@ -496,14 +541,14 @@ sum(x::AbstractFill) = getindex_value(x)*length(x)
 sum(f, x::AbstractFill) = length(x) * f(getindex_value(x))
 sum(x::Zeros) = getindex_value(x)
 
-cumsum(x::AbstractFill{<:Any,1}) = range(getindex_value(x); step=getindex_value(x),
-                                                    length=length(x))
+# needed to support infinite case
+steprangelen(st...) = StepRangeLen(st...)
+cumsum(x::AbstractFill{<:Any,1}) = steprangelen(getindex_value(x), getindex_value(x), length(x))
 
 cumsum(x::ZerosVector) = x
 cumsum(x::ZerosVector{Bool}) = x
 cumsum(x::OnesVector{II}) where II<:Integer = convert(AbstractVector{II}, oneto(length(x)))
 cumsum(x::OnesVector{Bool}) = oneto(length(x))
-cumsum(x::AbstractFillVector{Bool}) = cumsum(AbstractFill{Int}(x))
 
 
 #########
@@ -717,4 +762,6 @@ Base.@propagate_inbounds function view(A::AbstractFill{<:Any,N}, I::Vararg{Real,
     fillsimilar(A)
 end
 
+include("oneelement.jl")
+
 end # module

src/fillalgebra.jl

@@ -86,7 +86,6 @@ end
 *(a::ZerosMatrix, b::AbstractMatrix) = mult_zeros(a, b)
 *(a::AbstractMatrix, b::ZerosVector) = mult_zeros(a, b)
 *(a::AbstractMatrix, b::ZerosMatrix) = mult_zeros(a, b)
-*(a::ZerosVector, b::AbstractVector) = mult_zeros(a, b)
 *(a::ZerosMatrix, b::AbstractVector) = mult_zeros(a, b)
 *(a::AbstractVector, b::ZerosMatrix) = mult_zeros(a, b)
 
@@ -160,38 +159,22 @@ function *(a::Transpose{T, <:AbstractVector{T}}, b::ZerosVector{T}) where T<:Rea
 end
 *(a::Transpose{T, <:AbstractMatrix{T}}, b::ZerosVector{T}) where T<:Real = mult_zeros(a, b)
 
-# treat zero separately to support ∞-vectors
-function _zero_dot(a, b)
-    axes(a) == axes(b) || throw(DimensionMismatch("dot product arguments have lengths $(length(a)) and $(length(b))"))
-    zero(promote_type(eltype(a),eltype(b)))
-end
-
-_fill_dot(a::Zeros, b::Zeros) = _zero_dot(a, b)
-_fill_dot(a::Zeros, b) = _zero_dot(a, b)
-_fill_dot(a, b::Zeros) = _zero_dot(a, b)
-_fill_dot(a::Zeros, b::AbstractFill) = _zero_dot(a, b)
-_fill_dot(a::AbstractFill, b::Zeros) = _zero_dot(a, b)
-
-function _fill_dot(a::AbstractFill, b::AbstractFill)
-    axes(a) == axes(b) || throw(DimensionMismatch("dot product arguments have lengths $(length(a)) and $(length(b))"))
-    getindex_value(a)getindex_value(b)*length(b)
-end
-
 # support types with fast sum
-function _fill_dot(a::AbstractFill, b)
+# infinite cases should be supported in InfiniteArrays.jl
+# type issues of Bool dot are ignored at present.
+function _fill_dot(a::AbstractFillVector{T}, b::AbstractVector{V}) where {T,V}
     axes(a) == axes(b) || throw(DimensionMismatch("dot product arguments have lengths $(length(a)) and $(length(b))"))
-    getindex_value(a)sum(b)
+    dot(getindex_value(a), sum(b))
 end
 
-function _fill_dot(a, b::AbstractFill)
+function _fill_dot_rev(a::AbstractVector{T}, b::AbstractFillVector{V}) where {T,V}
     axes(a) == axes(b) || throw(DimensionMismatch("dot product arguments have lengths $(length(a)) and $(length(b))"))
-    sum(a)getindex_value(b)
+    dot(sum(a), getindex_value(b))
 end
 
-
 dot(a::AbstractFillVector, b::AbstractFillVector) = _fill_dot(a, b)
 dot(a::AbstractFillVector, b::AbstractVector) = _fill_dot(a, b)
-dot(a::AbstractVector, b::AbstractFillVector) = _fill_dot(a, b)
+dot(a::AbstractVector, b::AbstractFillVector) = _fill_dot_rev(a, b)
 
 function dot(u::AbstractVector, E::Eye, v::AbstractVector)
     length(u) == size(E,1) && length(v) == size(E,2) ||

src/fillbroadcast.jl

@@ -102,10 +102,6 @@ _broadcasted_zeros(f, a, b) = Zeros{Base.Broadcast.combine_eltypes(f, (a, b))}(b
 _broadcasted_ones(f, a, b) = Ones{Base.Broadcast.combine_eltypes(f, (a, b))}(broadcast_shape(axes(a), axes(b)))
 _broadcasted_nan(f, a, b) = Fill(convert(Base.Broadcast.combine_eltypes(f, (a, b)), NaN), broadcast_shape(axes(a), axes(b)))
 
-# TODO: remove at next breaking version
-_broadcasted_zeros(a, b) = _broadcasted_zeros(+, a, b)
-_broadcasted_ones(a, b) = _broadcasted_ones(+, a, b)
-
 broadcasted(::DefaultArrayStyle, ::typeof(+), a::Zeros, b::Zeros) = _broadcasted_zeros(+, a, b)
 broadcasted(::DefaultArrayStyle, ::typeof(+), a::Ones, b::Zeros) = _broadcasted_ones(+, a, b)
 broadcasted(::DefaultArrayStyle, ::typeof(+), a::Zeros, b::Ones) = _broadcasted_ones(+, a, b)
@@ -247,3 +243,8 @@ broadcasted(::DefaultArrayStyle{N}, ::typeof(Base.literal_pow), ::Base.RefValue{
 broadcasted(::DefaultArrayStyle{N}, ::typeof(Base.literal_pow), ::Base.RefValue{typeof(^)}, r::Ones{T,N}, ::Base.RefValue{Val{k}}) where {T,N,k} = Ones{T}(axes(r))
 broadcasted(::DefaultArrayStyle{N}, ::typeof(Base.literal_pow), ::Base.RefValue{typeof(^)}, r::Zeros{T,N}, ::Base.RefValue{Val{0}}) where {T,N} = Ones{T}(axes(r))
 broadcasted(::DefaultArrayStyle{N}, ::typeof(Base.literal_pow), ::Base.RefValue{typeof(^)}, r::Zeros{T,N}, ::Base.RefValue{Val{k}}) where {T,N,k} = Zeros{T}(axes(r))
+
+# supports structured broadcast
+if isdefined(LinearAlgebra, :fzero)
+    LinearAlgebra.fzero(x::Zeros) = zero(eltype(x))
+end

src/oneelement.jl

@@ -0,0 +1,51 @@
+"""
+    OneElement(val, ind, axesorsize) <: AbstractArray
+
+Represents an array with the specified axes (if its a tuple of `AbstractUnitRange`s)
+or size (if its a tuple of `Integer`s), with a single entry set to `val` and all others equal to zero,
+specified by `ind``.
+"""
+struct OneElement{T,N,I,A} <: AbstractArray{T,N}
+  val::T
+  ind::I
+  axes::A
+  OneElement(val::T, ind::I, axes::A) where {T<:Number, I<:NTuple{N,Int}, A<:NTuple{N,AbstractUnitRange}} where {N} = new{T,N,I,A}(val, ind, axes)
+end
+
+OneElement(val, inds::NTuple{N,Int}, sz::NTuple{N,Integer}) where N = OneElement(val, inds, oneto.(sz))
+"""
+    OneElement(val, ind::Int, n::Int)
+
+Creates a length `n` vector where the `ind` entry is equal to `val`, and all other entries are zero.
+"""
+OneElement(val, ind::Int, len::Int) = OneElement(val, (ind,), (len,))
+"""
+    OneElement(ind::Int, n::Int)
+
+Creates a length `n` vector where the `ind` entry is equal to `1`, and all other entries are zero.
+"""
+OneElement(inds::Int, sz::Int) = OneElement(1, inds, sz)
+OneElement{T}(val, inds::NTuple{N,Int}, sz::NTuple{N,Integer}) where {T,N} = OneElement(convert(T,val), inds, oneto.(sz))
+OneElement{T}(val, inds::Int, sz::Int) where T = OneElement{T}(val, (inds,), (sz,))
+
+"""
+    OneElement{T}(val, ind::Int, n::Int)
+
+Creates a length `n` vector where the `ind` entry is equal to `one(T)`, and all other entries are zero.
+"""
+OneElement{T}(inds::Int, sz::Int) where T = OneElement(one(T), inds, sz)
+
+Base.size(A::OneElement) = map(length, A.axes)
+Base.axes(A::OneElement) = A.axes
+function Base.getindex(A::OneElement{T,N}, kj::Vararg{Int,N}) where {T,N}
+    @boundscheck checkbounds(A, kj...)
+    ifelse(kj == A.ind, A.val, zero(T))
+end
+
+Base.replace_in_print_matrix(o::OneElement{<:Any,2}, k::Integer, j::Integer, s::AbstractString) =
+    o.ind == (k,j) ? s : Base.replace_with_centered_mark(s)
+
+function Base.setindex(A::Zeros{T,N}, v, kj::Vararg{Int,N}) where {T,N}
+    @boundscheck checkbounds(A, kj...)
+    OneElement(convert(T, v), kj, axes(A))
+end