Struct ScaledLaplacian 

pub struct ScaledLaplacian {
    pub entries: Vec<(usize, usize, f64)>,
    pub n: usize,
    pub lambda_max: f64,
}

Scaled Laplacian for Chebyshev approximation L_scaled = 2L/λ_max - I (eigenvalues in [-1, 1])

Fields

entries: Vec<(usize, usize, f64)>

Sparse representation: (row, col, value)

n: usize

Matrix dimension

lambda_max: f64

Estimated maximum eigenvalue

Implementations

impl ScaledLaplacian

pub fn from_adjacency(adj: &[f64], n: usize) -> Self

Build from adjacency matrix (dense)

pub fn from_sparse_adjacency(edges: &[(usize, usize, f64)], n: usize) -> Self

Build from sparse adjacency list

pub fn apply(&self, x: &[f64]) -> Vec<f64>

Apply scaled Laplacian to vector: y = L_scaled * x

pub fn lambda_max(&self) -> f64

Get original (unscaled) maximum eigenvalue estimate

Trait Implementations

impl Clone for ScaledLaplacian

fn clone(&self) -> ScaledLaplacian

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for ScaledLaplacian

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.