Convert a dense matrix A into a sparse matrix with sparsevec(A)

[Parkway]

The doc for the function sparsevec(A) says: 

sparsevec(A)

Convert a dense vector A into a sparse matrix of size m x 1. In julia, sparse vectors are really just sparse matrices with one column.

What does this actually mean? For example, what does the dense vector A = [23.1, 42.67, 8.246, 111.33] get converted to?

[Cameron McBride]

This thread is old, but I was poking through some unread bits and found it. Beyond that, it’s likely a better question for julia-users list (which I’m including here).

Anyhow, the answer is that sparsevec converts a dense matrix into a sparse matrix format where zero values are not explicitly stored. If the vector (or matrix) really is dense, this does not save space.

julia> A = [23.1, 42.67, 8.246, 111.33]

4-element Array{Float64,1}:

  23.1

  42.67

   8.246

 111.33

julia> sparsevec(A)

Sparse vector of length 4 with 4 Float64 nonzero entries:

  [1]  =  23.1

  [2]  =  42.67

  [3]  =  8.246

  [4]  =  111.33

julia> B = [0,0,A...]

6-element Array{Float64,1}:

   0.0

   0.0

  23.1

  42.67

   8.246

 111.33

julia> sparsevec(B)

Sparse vector of length 6 with 4 Float64 nonzero entries:

  [3]  =  23.1

  [4]  =  42.67

  [5]  =  8.246

  [6]  =  111.33

Cameron