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More generic SparseMatrixCSC and SparseVector #33918

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2b8ce54
loose type bound
Nov 22, 2019
0a15549
add Printf to test deps
Nov 22, 2019
71ecc4d
rm Manifest
Nov 22, 2019
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3 changes: 2 additions & 1 deletion stdlib/SparseArrays/Project.toml
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Expand Up @@ -6,9 +6,10 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

[extras]
Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

[targets]
test = ["Dates", "Test", "InteractiveUtils"]
test = ["Dates", "Test", "InteractiveUtils", "Printf"]
39 changes: 23 additions & 16 deletions stdlib/SparseArrays/src/sparsematrix.jl
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Expand Up @@ -16,23 +16,26 @@ Matrix type for storing sparse matrices in the
of constructing SparseMatrixCSC is through the [`sparse`](@ref) function.
See also [`spzeros`](@ref), [`spdiagm`](@ref) and [`sprand`](@ref).
"""
struct SparseMatrixCSC{Tv,Ti<:Integer} <: AbstractSparseMatrixCSC{Tv,Ti}
struct SparseMatrixCSC{Tv,Ti<:Integer,
ColPtr <: AbstractVector{Ti},
RowVal <: AbstractVector{Ti},
NZVal <: AbstractVector{Tv}} <: AbstractSparseMatrixCSC{Tv,Ti}
m::Int # Number of rows
n::Int # Number of columns
colptr::Vector{Ti} # Column i is in colptr[i]:(colptr[i+1]-1)
rowval::Vector{Ti} # Row indices of stored values
nzval::Vector{Tv} # Stored values, typically nonzeros
colptr::ColPtr # Column i is in colptr[i]:(colptr[i+1]-1)
rowval::RowVal # Row indices of stored values
nzval::NZVal # Stored values, typically nonzeros

function SparseMatrixCSC{Tv,Ti}(m::Integer, n::Integer, colptr::Vector{Ti},
rowval::Vector{Ti}, nzval::Vector{Tv}) where {Tv,Ti<:Integer}
function SparseMatrixCSC{Tv,Ti}(m::Integer, n::Integer, colptr::AbstractVector{Ti},
rowval::AbstractVector{Ti}, nzval::AbstractVector{Tv}) where {Tv,Ti<:Integer}
@noinline throwsz(str, lbl, k) =
throw(ArgumentError("number of $str ($lbl) must be ≥ 0, got $k"))
m < 0 && throwsz("rows", 'm', m)
n < 0 && throwsz("columns", 'n', n)
new(Int(m), Int(n), colptr, rowval, nzval)
new{Tv, Ti, typeof(colptr), typeof(rowval), typeof(nzval)}(Int(m), Int(n), colptr, rowval, nzval)
end
end
function SparseMatrixCSC(m::Integer, n::Integer, colptr::Vector, rowval::Vector, nzval::Vector)
function SparseMatrixCSC(m::Integer, n::Integer, colptr::AbstractVector, rowval::AbstractVector, nzval::AbstractVector)
Tv = eltype(nzval)
Ti = promote_type(eltype(colptr), eltype(rowval))
sparse_check_Ti(m, n, Ti)
Expand All @@ -52,7 +55,7 @@ function sparse_check_Ti(m::Integer, n::Integer, Ti::Type)
0 ≤ n && (!isbitstype(Ti) || n ≤ typemax(Ti)) || throwTi("number of columns", "n", n)
end

function sparse_check(n::Integer, colptr::Vector{Ti}, rowval, nzval) where Ti
function sparse_check(n::Integer, colptr::AbstractVector{Ti}, rowval, nzval) where Ti
sparse_check_length("colptr", colptr, n+1, String) # don't check upper bound
ckp = Ti(1)
ckp == colptr[1] || throw(ArgumentError("$ckp == colptr[1] != 1"))
Expand Down Expand Up @@ -248,9 +251,9 @@ end

## Reshape

function sparse_compute_reshaped_colptr_and_rowval(colptrS::Vector{Ti}, rowvalS::Vector{Ti},
mS::Int, nS::Int, colptrA::Vector{Ti},
rowvalA::Vector{Ti}, mA::Int, nA::Int) where Ti
function sparse_compute_reshaped_colptr_and_rowval(colptrS::AbstractVector{Ti}, rowvalS::AbstractVector{Ti},
mS::Int, nS::Int, colptrA::AbstractVector{Ti},
rowvalA::AbstractVector{Ti}, mA::Int, nA::Int) where Ti
lrowvalA = length(rowvalA)
maxrowvalA = (lrowvalA > 0) ? maximum(rowvalA) : zero(Ti)
((length(colptrA) == (nA+1)) && (maximum(colptrA) <= (lrowvalA+1)) && (maxrowvalA <= mA)) || throw(BoundsError())
Expand Down Expand Up @@ -3468,11 +3471,15 @@ function _spdiagm(size, kv::Pair{<:Integer,<:AbstractVector}...)
end

## expand a colptr or rowptr into a dense index vector
function expandptr(V::Vector{<:Integer})
if V[1] != 1 throw(ArgumentError("first index must be one")) end
function expandptr(V::AbstractVector{<:Integer})
if V[1] != 1
throw(ArgumentError("first index must be one"))
end
res = similar(V, (Int64(V[end]-1),))
for i in 1:(length(V)-1), j in V[i]:(V[i+1] - 1); res[j] = i end
res
for i in 1:(length(V)-1), j in V[i]:(V[i+1] - 1)
res[j] = i
end
return res
end


Expand Down
12 changes: 6 additions & 6 deletions stdlib/SparseArrays/src/sparsevector.jl
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Expand Up @@ -14,20 +14,20 @@ import LinearAlgebra: promote_to_array_type, promote_to_arrays_

Vector type for storing sparse vectors.
"""
struct SparseVector{Tv,Ti<:Integer} <: AbstractSparseVector{Tv,Ti}
struct SparseVector{Tv,Ti<:Integer,NZInd<:AbstractVector{Ti},NZVal<:AbstractVector{Tv}} <: AbstractSparseVector{Tv,Ti}
n::Int # Length of the sparse vector
nzind::Vector{Ti} # Indices of stored values
nzval::Vector{Tv} # Stored values, typically nonzeros
nzind::NZInd # Indices of stored values
nzval::NZVal # Stored values, typically nonzeros

function SparseVector{Tv,Ti}(n::Integer, nzind::Vector{Ti}, nzval::Vector{Tv}) where {Tv,Ti<:Integer}
function SparseVector{Tv,Ti}(n::Integer, nzind::AbstractVector{Ti}, nzval::AbstractVector{Tv}) where {Tv,Ti<:Integer}
n >= 0 || throw(ArgumentError("The number of elements must be non-negative."))
length(nzind) == length(nzval) ||
throw(ArgumentError("index and value vectors must be the same length"))
new(convert(Int, n), nzind, nzval)
new{Tv, Ti, typeof(nzind), typeof(nzval)}(convert(Int, n), nzind, nzval)
end
end

SparseVector(n::Integer, nzind::Vector{Ti}, nzval::Vector{Tv}) where {Tv,Ti} =
SparseVector(n::Integer, nzind::AbstractVector{Ti}, nzval::AbstractVector{Tv}) where {Tv,Ti} =
SparseVector{Tv,Ti}(n, nzind, nzval)

# Define an alias for a view of a whole column of a SparseMatrixCSC. Many methods can be written for the
Expand Down