Struct DiGraph 

pub struct DiGraph<N: Node, E: EdgeWeight, Ix: IndexType = u32> { /* private fields */ }

A directed graph structure

Implementations

impl<N: Node + Debug, E: EdgeWeight, Ix: IndexType> DiGraph<N, E, Ix>

pub fn new() -> Self

Create a new empty directed graph

pub fn add_node(&mut self, node: N) -> NodeIndex<Ix>

Add a node to the graph

pub fn add_edge(&mut self, source: N, target: N, weight: E) -> Result<()>

Add a directed edge from source to target with a given weight

pub fn nodes(&self) -> Vec<&N>

Get all nodes in the graph

pub fn node_count(&self) -> usize

Number of nodes in the graph

pub fn edge_count(&self) -> usize

Number of edges in the graph

pub fn contains_node(&self, node: &N) -> bool

Check if the graph contains a specific node

pub fn has_node(&self, node: &N) -> bool

Check if the graph has a specific node (alias for contains_node)

pub fn inner(&self) -> &PetGraph<N, E, Directed, Ix>

Get the internal petgraph structure for more advanced operations

pub fn neighbors(&self, node: &N) -> Result<Vec<N>>

where N: Clone,

Get neighbors of a node

pub fn successors(&self, node: &N) -> Result<Vec<N>>

where N: Clone,

Get successors (outgoing neighbors) of a node

pub fn predecessors(&self, node: &N) -> Result<Vec<N>>

where N: Clone,

Get predecessors (incoming neighbors) of a node

pub fn edge_weight(&self, source: &N, target: &N) -> Result<E>

where E: Clone,

Get the weight of an edge between two nodes

pub fn edges(&self) -> Vec<Edge<N, E>>

where N: Clone, E: Clone,

Get all edges in the graph

pub fn has_edge(&self, source: &N, target: &N) -> bool

Check if an edge exists between two nodes

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

Get the degree of a node (total number of incident edges)

pub fn node_index(&self, node: &N) -> Option<NodeIndex<Ix>>

Get the node index for a specific node

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

where E: Clone + Into<f64>,

Get the adjacency matrix of the graph

pub fn out_degree_vector(&self) -> Array1<usize>

Get the out-degree vector (number of outgoing edges for each node)

pub fn in_degree_vector(&self) -> Array1<usize>

Get the in-degree vector (number of incoming edges for each node)

Trait Implementations

impl<N: Node + Debug, E: EdgeWeight, Ix: IndexType> Default for DiGraph<N, E, Ix>

fn default() -> Self

Returns the “default value” for a type.

impl<N, E, Ix: IndexType> WeightedOps<N, E> for DiGraph<N, E, Ix>

where N: Clone + Debug + Node, E: Clone + Debug + Into<f64> + From<f64> + PartialOrd + Zero + Add<Output = E> + Div<f64, Output = E> + Mul<f64, Output = E> + EdgeWeight,

fn weight_statistics(&self) -> Result<WeightStatistics<E>>

Calculate weight statistics for the graph

fn filter_by_weight( &self, min_weight: Option<E>, maxweight: Option<E>, ) -> Result<Self>

Filter edges by weight threshold

fn edges_by_weight(&self, ascending: bool) -> Result<Vec<(N, N, E)>>

Get edges sorted by weight

fn subgraph_by_weight_range(&self, min_weight: E, maxweight: E) -> Result<Self>

Extract subgraph with edges in weight range

fn normalize_weights(&self, method: NormalizationMethod) -> Result<Self>

Normalize edge weights using specified method

fn transform_weights(&self, transform: WeightTransform) -> Result<Self>

Transform edge weights using specified transformation

fn weight_distribution(&self, bins: usize) -> Result<Vec<(E, usize)>>

Get weight distribution as histogram

fn weighted_degree_centrality(&self) -> Result<HashMap<N, f64>>

Calculate weight-based centrality measures

fn total_weight(&self) -> Result<E>

Get total weight of the graph

fn average_weight(&self) -> Result<f64>

Get average edge weight