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AbstractSparseMatrixCSC.md

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AbstractSparseMatrixCSC{Tv,Ti<:Integer} <: AbstractSparseMatrix{Tv,Ti}

Supertype for matrix with compressed sparse column (CSC).

!!! compat "Julia 1.4" AbstractSparseMatrixCSC requires at least Julia 1.4.

AbstractSparseMatrixCSC interface

In addition to the [Abstract array interface](@ref man-interface-array), every AbstractSparseMatrixCSC subtype TS must provide the following methods:

  • [size(::TS)](@ref size)
  • [coloffsets(::TS) :: AbstractVector{<:Ti}](@ref coloffsets)
  • [rowvals(::TS) :: AbstractVector{<:Ti}](@ref rowvals)
  • [nonzeros(::TS) :: AbstractVector{<:Tv}](@ref nonzeros)

Other sparse matrix methods such as nzrange and nnz are automatically defined in terms of above functions.

Assumed invariance

To use algorithms defined in SparseArrays, a matrix A of type AbstractSparseMatrixCSC must satisfy the following constraints.

Matrix A and all vectors constituting A have one-based indexing

@assert !has_offset_axes(A)
@assert !has_offset_axes(coloffsets(A))
@assert !has_offset_axes(rowvals(A))
@assert !has_offset_axes(nonzeros(A))

Row indices in rowval(A) for each column are sorted

for col in axes(A, 2)
    @assert issorted(rowval(A)[nzrange(A, col)])
end

Column pointers in coloffsets(A) are increasing, started at 1

@assert coloffsets(A)[1] === 1
@assert all(diff(coloffsets(A)) .>= 0)

Row index vector rowvals(A) and non-zero value vector nonzeros(A) are long enough

@assert nnz(A) <= length(rowvals(A))
@assert nnz(A) <= length(nonzeros(A))

Indices for rows, rowvals(A) and nonzeros(A) are representable by Ti

@assert size(A, 1) <= typemax(Ti)
@assert nnz(A) <= typemax(Ti)