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Slicing the matrix should give a sparse array #11

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giordano opened this issue Jun 25, 2021 · 0 comments
Open

Slicing the matrix should give a sparse array #11

giordano opened this issue Jun 25, 2021 · 0 comments

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@giordano
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giordano commented Jun 25, 2021

julia> m = 10 # Number rows
10

julia> n = 10 # Number columns
10

julia> nz = floor(Int, m * 1.5) # Number of non-zero elements
15

julia> rowptr = vcat(sort!(rand(0:nz, m)), nz);

julia> colval = rand(0:(n-1), nz);

julia> nzval = randn(nz);

julia> A = SparseMatrixCSR{0}(m, n, rowptr, colval, nzval)
10×10 SparseMatrixCSR{0, Float64, Int64} with 15 stored entries:
  [1,  5]  =  0.48371
  [2,  3]  =  1.72291
  [3,  8]  =  0.707065
  [3,  5]  =  0.622569
  [3,  7]  =  1.57136
  [4,  8]  =  -0.262692
  [4,  5]  =  -0.00643953
  [5,  6]  =  -1.15259
  [6,  3]  =  0.0652688
  [6,  2]  =  1.02735
  [7,  2]  =  0.169683
  [9,  6]  =  -0.648538
  [9,  4]  =  -0.647156
  [10,  6]  =  -1.28313
  [10,  7]  =  0.116641

julia> A[1:3, :]
3×10 Matrix{Float64}:
 0.0  0.0  0.0      0.0  0.48371  0.0  0.0      0.0  0.0  0.0
 0.0  0.0  1.72291  0.0  0.0      0.0  0.0      0.0  0.0  0.0
 0.0  0.0  0.0      0.0  0.0      0.0  1.57136  0.0  0.0  0.0

This isn't very convenient, especially since this data structure should allow having a compact representation of a slice of rows. The standard SparseMatrixCSC has compact slicing for both rows and columns:

julia> B = sprandn(rng, 10, 10, 0.2)
10×10 SparseMatrixCSC{Float64, Int64} with 19 stored entries:
                                     -0.0684167   0.0414316                      1.79099     
                                                                                        0.451416
                                                 0.245215                                  
            -0.880614   -0.149248                                                           
                       -0.673498                                               -0.48382     
                                                           -0.679016  -1.93712  -0.468799    
                                                                                          
  0.0442601   0.0607505                                                                     
 -0.839911                                                                      0.715919  0.151704
                                                -1.83668     0.267189                       

julia> B[1:3, :]
3×10 SparseMatrixCSC{Float64, Int64} with 5 stored entries:
                 -0.0684167  0.0414316          1.79099    
                                                      0.451416
                            0.245215                     

julia> B[:, 1:3]
10×3 SparseMatrixCSC{Float64, Int64} with 6 stored entries:
                          
                          
                          
            -0.880614   -0.149248
                       -0.673498
                          
                          
  0.0442601   0.0607505     
 -0.839911                 
                         
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