rand_sparse

rand_sparse([rng], [T], dims...;
    radius=1.0, sparsity=0.1, std=1.0, return_sparse=false)

Create and return a random sparse reservoir matrix. The matrix will be of size specified by dims, with specified sparsity and scaled spectral radius according to radius.

Arguments

• rng: Random number generator. Default is Utils.default_rng()from WeightInitializers.
• T: Type of the elements in the reservoir matrix. Default is Float32.
• dims: Dimensions of the reservoir matrix.

Keyword arguments

• radius: The desired spectral radius of the reservoir. Defaults to 1.0.
• sparsity: The sparsity level of the reservoir matrix, controlling the fraction of zero elements. Defaults to 0.1.
• return_sparse: flag for returning a sparse matrix. true requires SparseArrays to be loaded. Default is false.

Examples

Changing the sparsity:

julia> res_matrix = rand_sparse(5, 5; sparsity = 0.5)
5×5 Matrix{Float32}:
 0.0        0.0        0.0        0.0      0.0
 0.0        0.794565   0.0        0.26164  0.0
 0.0        0.0       -0.931294   0.0      0.553706
 0.723235  -0.524727   0.0        0.0      0.0
 1.23723    0.0        0.181824  -1.5478   0.465328

julia> res_matrix = rand_sparse(5, 5; sparsity = 0.2)
5×5 Matrix{Float32}:
 0.0       0.0        0.0   0.0      0.0
 0.0       0.853184   0.0   0.0      0.0
 0.0       0.0       -1.0   0.0      0.0
 0.776591  0.0        0.0   0.0      0.0
 0.0       0.0        0.0  -1.66199  0.499657

julia> res_matrix = rand_sparse(5, 5; sparsity = 0.8)
5×5 Matrix{Float32}:
 0.0        0.229011   0.625026    -0.660061  -1.39078
 -0.295761   0.32544    0.0          0.107163   0.0
 0.766352   1.44836   -0.381442    -0.435473   0.226788
 0.296224  -0.214919   0.00956791   0.0        0.210393
 0.506746   0.0        0.0744718   -0.633951   0.19059

Returning a sparse matrix:

julia> using SparseArrays

julia> res_matrix = rand_sparse(5, 5; sparsity = 0.4, return_sparse = true)
5×5 SparseMatrixCSC{Float32, Int64} with 10 stored entries:
  ⋅          ⋅          ⋅          ⋅        ⋅
  ⋅         0.794565    ⋅         0.26164   ⋅
  ⋅          ⋅        -0.931294    ⋅       0.553706
 0.723235  -0.524727    ⋅          ⋅        ⋅
 1.23723     ⋅         0.181824  -1.5478   0.465328