Struct Graph

pub struct Graph {
    pub num_vertices: usize,
    pub edges: Vec<Vec<usize>>,
    pub weights: Option<Vec<Vec<f64>>>,
}

Graph representation for quantum walks

Fields

num_vertices: usize

Number of vertices

edges: Vec<Vec<usize>>

Adjacency list representation

weights: Option<Vec<Vec<f64>>>

Optional edge weights

Implementations

impl Graph

pub fn new(graph_type: GraphType, size: usize) -> Self

Create a new graph of a specific type

pub fn new_empty(num_vertices: usize) -> Self

Create an empty graph with given number of vertices

pub fn add_edge(&mut self, u: usize, v: usize)

Add an undirected edge

pub fn add_weighted_edge(&mut self, u: usize, v: usize, weight: f64)

Add a weighted edge

pub fn degree(&self, vertex: usize) -> usize

Get the degree of a vertex

pub fn adjacency_matrix(&self) -> Array2<f64>

Get the adjacency matrix

pub fn laplacian_matrix(&self) -> Array2<f64>

Get the Laplacian matrix

pub fn normalized_laplacian_matrix(&self) -> Array2<f64>

Get the normalized Laplacian matrix

pub fn transition_matrix(&self) -> Array2<f64>

Get the transition matrix for random walks

pub fn is_bipartite(&self) -> bool

Check if the graph is bipartite

pub fn algebraic_connectivity(&self) -> f64

Calculate the algebraic connectivity (second smallest eigenvalue of Laplacian)

pub fn all_pairs_shortest_paths(&self) -> Array2<f64>

Get shortest path distances between all pairs of vertices

pub fn from_adjacency_matrix(matrix: &Array2<f64>) -> QuantRS2Result<Self>

Create a graph from an adjacency matrix

Trait Implementations

impl Clone for Graph

fn clone(&self) -> Graph

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Graph

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

Formats the value using the given formatter.