Function eigsh_generalized_enhanced 

pub fn eigsh_generalized_enhanced<T>(
    a_matrix: &SymCsrMatrix<T>,
    b_matrix: &SymCsrMatrix<T>,
    k: Option<usize>,
    which: Option<&str>,
    mode: Option<&str>,
    sigma: Option<T>,
    options: Option<LanczosOptions>,
) -> SparseResult<EigenResult<T>>
where
    T: Float + Debug + Copy + Add<Output = T> + Sub<Output = T> + Mul<Output = T> + Div<Output = T> + Sum + SimdUnifiedOps + SparseElement + PartialOrd + Send + Sync + 'static,

Enhanced generalized eigenvalue solver with additional features

This function provides an enhanced interface to generalized eigenvalue computation with additional transformation modes and options.

Arguments

• a_matrix - The A matrix (left-hand side)
• b_matrix - The B matrix (right-hand side)
• k - Number of eigenvalues to compute
• which - Which eigenvalues to compute
• mode - Transformation mode: “standard”, “buckling”, “cayley”
• sigma - Shift value for shift-invert modes
• options - Additional solver options

Returns

Enhanced generalized eigenvalue computation result

Examples

use scirs2_sparse::linalg::eigsh_generalized_enhanced;
use scirs2_sparse::sym_csr::SymCsrMatrix;

let a_data = vec![5.0, 1.0, 4.0];
let a_indptr = vec![0, 1, 3];
let a_indices = vec![0, 0, 1];
let amatrix = SymCsrMatrix::new(a_data, a_indptr, a_indices, (2, 2)).unwrap();

let b_data = vec![2.0, 0.5, 1.5];
let b_indptr = vec![0, 1, 3];
let b_indices = vec![0, 0, 1];
let bmatrix = SymCsrMatrix::new(b_data, b_indptr, b_indices, (2, 2)).unwrap();

let result = eigsh_generalized_enhanced(
    &amatrix, &bmatrix, Some(2), None, Some("standard"), None, None
).unwrap();