| Documentation | Linux/macOS/Windows/FreeBSD | Coverage | DOI |
|---|---|---|---|
  |
  |
 |
 |
A straightforward interface to the SuiteSparse Matrix Collection.
References
Davis, Timothy A. and Hu, Yifan (2011). The University of Florida sparse matrix collection. ACM Transactions on Mathematical Software, 38(1), 1--25. 10.1145/2049662.2049663
How to Cite
If you use SuiteSparseMatrixCollection.jl in your work, please cite using the format given in CITATION.bib.
How to install
pkg> add SuiteSparseMatrixCollection pkg> test SuiteSparseMatrixCollection
Updating the database
Clone this repository, activate the utils environment and run gen_db.jl to check if the database needs to be updated.
Updating Artifacts.toml
Clone this repository, activate the utils environment and run gen_artifacts.jl to check if Artifacts.toml needs to be updated.
Examples
julia> using SuiteSparseMatrixCollection julia> # name-based selection can be done with `ssmc_matrices()` julia> ssmc = ssmc_db() julia> ssmc_matrices(ssmc, "HB", "bcsstk") # all matrices whose group contains "HB" and name contains "bcsstk" julia> ssmc_matrices(ssmc, "", "bcsstk") # all matrices whose name contains "bcsstk" julia> ssmc_matrices(ssmc, "HB", "") # all matrices whose group contains "HB" julia> # select symmetric positive definite matrices with ≤ 100 rows and columns julia> tiny = ssmc[(ssmc.numerical_symmetry .== 1) .& (ssmc.positive_definite.== true) .& (ssmc.real .== true) .& (ssmc.nrows .≤ 100), :] julia> # fetch the matrices selects in MatrixMarket format julia> paths = fetch_ssmc(tiny, format="MM") # matrices are downloaded in paths julia> downloaded_matrices = installed_ssmc() # name of all downloaded matrices julia> delete_ssmc("HB", "bcsstk02") # delete the matrix "bcsstk02" of group "HB" julia> delete_all_ssmc() # delete all matrices from the SuiteSparseMatrixCollection
Matrices are available in formats:
"RB": the Rutherford-Boeing format;"MM": the MatrixMarket format.
Use DataFrames syntax to further examine a list of selected matrices:
julia> tiny[!, [:name, :nrows, :ncols, :positive_definite, :lower_bandwidth]] 12×5 DataFrame │ Row │ name │ nrows │ ncols │ positive_definite │ lower_bandwidth │ │ │ String │ Int64 │ Int64 │ Bool │ Int64 │ ├─────┼───────────────┼───────┼───────┼───────────────────┼─────────────────┤ │ 1 │ bcsstk01 │ 48 │ 48 │ 1 │ 35 │ │ 2 │ bcsstk02 │ 66 │ 66 │ 1 │ 65 │ │ 3 │ bcsstm02 │ 66 │ 66 │ 1 │ 0 │ │ 4 │ nos4 │ 100 │ 100 │ 1 │ 13 │ │ 5 │ ex5 │ 27 │ 27 │ 1 │ 20 │ │ 6 │ mesh1e1 │ 48 │ 48 │ 1 │ 47 │ │ 7 │ mesh1em1 │ 48 │ 48 │ 1 │ 47 │ │ 8 │ mesh1em6 │ 48 │ 48 │ 1 │ 47 │ │ 9 │ LF10 │ 18 │ 18 │ 1 │ 3 │ │ 10 │ LFAT5 │ 14 │ 14 │ 1 │ 5 │ │ 11 │ Trefethen_20b │ 19 │ 19 │ 1 │ 16 │ │ 12 │ Trefethen_20 │ 20 │ 20 │ 1 │ 16 │
Matrices in Rutherford-Boeing format can be opened with HarwellRutherfordBoeing.jl:
pkg> add HarwellRutherfordBoeing julia> using HarwellRutherfordBoeing julia> matrix = ssmc[ssmc.name .== "bcsstk01", :] 1×30 DataFrame. Omitted printing of 17 columns │ Row │ group │ nnzdiag │ nrows │ numerical_symmetry │ amd_vnz │ binary │ structural_rank │ is_nd │ is_graph │ RB_type │ lower_bandwidth │ explicit_zeros │ amd_flops │ │ │ String │ Int64 │ Int64 │ Float64 │ Int64 │ Bool │ Int64 │ Bool │ Bool │ String │ Int64 │ Int64 │ Float64 │ ├─────┼────────┼─────────┼───────┼────────────────────┼─────────┼────────┼─────────────────┼───────┼──────────┼─────────┼─────────────────┼────────────────┼───────────┤ │ 1 │ HB │ 48 │ 48 │ 1.0 │ 651 │ 0 │ 48 │ 1 │ 0 │ rsa │ 35 │ 0 │ 6009.0 │ julia> path = fetch_ssmc(matrix, format="RB") 1-element Array{String,1}: "/Users/dpo/dev/JSO/SuiteSparseMatrixCollection.jl/src/../data/RB/HB/bcsstk01" julia> A = RutherfordBoeingData(joinpath(path[1], "$(matrix.name[1]).rb")) Rutherford-Boeing data 23 of type rsa 48 rows, 48 cols, 224 nonzeros
Matrices in MM format can be opened with MatrixMarket.jl.