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A Julia package for sparse multidimensional arrays, aimed particularly at the setting of
very sparse and higher-dimensional arrays (e.g. tensor algebra). This is not a replacement
nor a competitor to Julia's SparseArrays standard library and the SparseMatrixCSC
format.
The current interface, which is subject to breaking changes, exports a type
SparseArray{T,N} <: AbstractArray{T,N}. This type uses a hash table (Dict from Julia's
Base, could change) to store keys (of type CartesianIndex{N}) and values (of type T)
of the non-zero data (i.e. a dictionary-of-keys storage format), and is thus supposed to
have O(1) access time for getting and setting individual values. Other storage formats for
sparse arrays could in the future be experimented with.
SparseArray instances have a number of method definitions, mostly indexing, basic
arithmetic and methods from the LinearAlgebra standard library. Aside from matrix
multiplication, there are no specific matrix methods (such as matrix factorizations) and you
are probably better off with SparseMatrixCSC from SparseArrays if your problem can be
cast in terms of matrices and vectors. There is a fast conversion path from
SparseMatrixCSC to SparseArray (but not yet the other way around).
Objects of type SparseArray are fully compatible with the interface from
TensorOperations.jl, and thus with the
@tensor macro for multidimensional tensor contractions.
There are only three new methods exported by this package, which are nonzero_keys,
nonzero_values and nonzero_pairs which export iterators (not necessarily editable or
indexable vectors) over the keys, values and key-value pairs of the nonzero entries of the
array. These can be used to define new optimized methods.