This function generates a sparse matrix with a specified number of rows and columns, a given sparsity level, and a distribution function for the non-zero values.
Usage
simulate_sparse_matrix(
nrow,
ncol,
sparsity = 0.95,
distribution_fun = function(n) stats::rpois(n, lambda = 0.5) + 1,
decimal = 0,
seed = 1
)Arguments
- nrow
Number of rows in the matrix.
- ncol
Number of columns in the matrix.
- sparsity
Proportion of zero elements (sparsity level). Default is 0.95, meaning 95% of elements are zero (5% are non-zero).
- distribution_fun
Function to generate non-zero values.
- decimal
Numeric value, default is
0. Controls the number of decimal places in the generated values. If set to0, values will be integers. When decimal > 0, random decimal parts are uniformly distributed across the full range.- seed
Random seed for reproducibility.
Examples
simulate_sparse_matrix(1000, 500) |>
check_sparsity()
#> [1] 0.95
simulate_sparse_matrix(10, 10, decimal = 1)
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#> [[ suppressing 10 column names ‘col_1’, ‘col_2’, ‘col_3’ ... ]]
#>
#> row_1 1.8 . . . . . . . . .
#> row_2 . . . . . . . . . .
#> row_3 . . . . . . . . . .
#> row_4 . . . 1.5 . . . . . .
#> row_5 . . . . . . . . . .
#> row_6 . . . . . . . . . .
#> row_7 . . . . . . . . 1.7 .
#> row_8 . . . . . . 2.7 . . .
#> row_9 . . . 2.4 . . . . . .
#> row_10 . . . . . . . . . .
simulate_sparse_matrix(10, 10, decimal = 5)
#> 10 x 10 sparse Matrix of class "dgCMatrix"
#> [[ suppressing 10 column names ‘col_1’, ‘col_2’, ‘col_3’ ... ]]
#>
#> row_1 1.76984 . . . . . . . . .
#> row_2 . . . . . . . . . .
#> row_3 . . . . . . . . . .
#> row_4 . . . 1.4977 . . . . . .
#> row_5 . . . . . . . . . .
#> row_6 . . . . . . . . . .
#> row_7 . . . . . . . . 1.71762 .
#> row_8 . . . . . . 2.68702 . . .
#> row_9 . . . 2.3841 . . . . . .
#> row_10 . . . . . . . . . .