This packages provides an alternative implementation of SparseMatrices that maintains a vector of SparseVectors. Such an implementation is best used when all matrix operations require access to just one column each.
using SparseVectorMatrix
# Random Generation
a = svmrand(100, 100, 0.1)
# Getindex
a[:, 1] # Returns an entire column quickly
a[1, :] # Returns an entire row, but slowly.
# SetIndex
a[:, 1] = 1:100 # Assign an entire column quickly.
a[1, :] = 1:100 # Assign an entire row, by slowly.
#Concatenation
b = svmrand(100, 100, 0.1)
hcat(a, b) # Concatenates horizontally. Very fast.
vcat(a, b) # Concatenates vertically. Not as fast.
arr = [svmrand(100, 100, 0.1) for i in 1:4]
hvcat((2,2), arr..) # Grid Concatenation. Quite fast.- svmrand (Similar to sprand)
- getindex
- setindex
- hcat
- vcat
- hvcat
- A bunch of other basic methods like nnz, size, full, etc.
include("benchmarks/run.jl")