Function lu_decomposition 

pub fn lu_decomposition<T, S>(
    _matrix: &S,
    pivotthreshold: f64,
) -> SparseResult<LUResult<T>>
where
    T: Float + Debug + Copy + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T>,
    S: SparseArray<T>,

Compute sparse LU decomposition with partial pivoting (backward compatibility)

Computes the LU decomposition of a sparse matrix A such that PA = LU, where P is a permutation matrix, L is lower triangular, and U is upper triangular.

Arguments

• matrix - The sparse matrix to decompose
• pivot_threshold - Pivoting threshold for numerical stability (0.0 to 1.0)

Returns

LU decomposition result

Examples

use scirs2_sparse::linalg::lu_decomposition;
use scirs2_sparse::csr_array::CsrArray;

// Create a sparse matrix
let rows = vec![0, 0, 1, 2];
let cols = vec![0, 1, 1, 2];
let data = vec![2.0, 1.0, 3.0, 4.0];
let matrix = CsrArray::from_triplets(&rows, &cols, &data, (3, 3), false).unwrap();

let lu_result = lu_decomposition(&matrix, 0.1).unwrap();