Struct petgraph::csr::Csr

pub struct Csr<N = (), E = (), Ty = Directed, Ix = DefaultIx> {
    column: Vec<NodeIndex<Ix>>,
    edges: Vec<E>,
    row: Vec<usize>,
    node_weights: Vec<N>,
    edge_count: usize,
    ty: PhantomData<Ty>,
}

Compressed Sparse Row ([CSR]) is a sparse adjacency matrix graph.

CSR is parameterized over:

• Associated data N for nodes and E for edges, called weights. The associated data can be of arbitrary type.
• Edge type Ty that determines whether the graph edges are directed or undirected.
• Index type Ix, which determines the maximum size of the graph.

Using O(|E| + |V|) space.

Self loops are allowed, no parallel edges.

Fast iteration of the outgoing edges of a vertex. [CSR]: https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_sparse_row_(CSR,_CRS_or_Yale_format)

Fields

column: Vec<NodeIndex<Ix>>

Column of next edge

edges: Vec<E>

weight of each edge; lock step with column

row: Vec<usize>

Index of start of row Always node_count + 1 long. Last element is always equal to column.len()

node_weights: Vec<N>

edge_count: usize

ty: PhantomData<Ty>

Implementations

impl<N, E, Ty, Ix> Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

pub fn new() -> Self

Create an empty Csr.

pub fn with_nodes(n: usize) -> Self

where N: Default,

Create a new Csr with n nodes. N must implement Default for the weight of each node.

Example

use petgraph::csr::Csr;
use petgraph::prelude::*;


let graph = Csr::<u8,()>::with_nodes(5);
assert_eq!(graph.node_count(),5);
assert_eq!(graph.edge_count(),0);

assert_eq!(graph[0],0);
assert_eq!(graph[4],0);

impl<N, E, Ix> Csr<N, E, Directed, Ix>

where Ix: IndexType,

pub fn from_sorted_edges<Edge>(edges: &[Edge]) -> Result<Self, EdgesNotSorted>

where Edge: Clone + IntoWeightedEdge<E, NodeId = NodeIndex<Ix>>, N: Default,

Create a new Csr from a sorted sequence of edges

Edges must be sorted and unique, where the sort order is the default order for the pair (u, v) in Rust (u has priority).

Computes in O(|E| + |V|) time.

Example

use petgraph::csr::Csr;
use petgraph::prelude::*;


let graph = Csr::<(),()>::from_sorted_edges(&[
                    (0, 1), (0, 2),
                    (1, 0), (1, 2), (1, 3),
                    (2, 0),
                    (3, 1),
]);

impl<N, E, Ty, Ix> Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

pub fn node_count(&self) -> usize

pub fn edge_count(&self) -> usize

pub fn is_directed(&self) -> bool

pub fn clear_edges(&mut self)

Remove all edges

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

Adds a new node with the given weight, returning the corresponding node index.

pub fn add_edge( &mut self, a: NodeIndex<Ix>, b: NodeIndex<Ix>, weight: E, ) -> bool

where E: Clone,

Return true if the edge was added

If you add all edges in row-major order, the time complexity is O(|V|·|E|) for the whole operation.

Panics if a or b are out of bounds.

fn add_edge_(&mut self, a: NodeIndex<Ix>, b: NodeIndex<Ix>, weight: E) -> bool

fn find_edge_pos( &self, a: NodeIndex<Ix>, b: NodeIndex<Ix>, ) -> Result<usize, usize>

pub fn contains_edge(&self, a: NodeIndex<Ix>, b: NodeIndex<Ix>) -> bool

Computes in O(log |V|) time.

Panics if the node a does not exist.

fn neighbors_range(&self, a: NodeIndex<Ix>) -> Range<usize>

fn neighbors_of(&self, a: NodeIndex<Ix>) -> (usize, &[Ix])

pub fn out_degree(&self, a: NodeIndex<Ix>) -> usize

Computes in O(1) time.

Panics if the node a does not exist.

pub fn neighbors_slice(&self, a: NodeIndex<Ix>) -> &[NodeIndex<Ix>]

Computes in O(1) time.

Panics if the node a does not exist.

pub fn edges_slice(&self, a: NodeIndex<Ix>) -> &[E]

Computes in O(1) time.

Panics if the node a does not exist.

pub fn edges(&self, a: NodeIndex<Ix>) -> Edges<'_, E, Ty, Ix>

Return an iterator of all edges of a.

• Directed: Outgoing edges from a.
• Undirected: All edges connected to a.

Panics if the node a does not exist.
Iterator element type is EdgeReference<E, Ty, Ix>.

Trait Implementations

impl<N: Clone, E: Clone, Ty, Ix: Clone> Clone for Csr<N, E, Ty, Ix>

fn clone(&self) -> Self

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N, E, Ty, Ix> Data for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type NodeWeight = N

type EdgeWeight = E

impl<N: Debug, E: Debug, Ty: Debug, Ix: Debug> Debug for Csr<N, E, Ty, Ix>

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

Formats the value using the given formatter.

impl<N, E, Ty, Ix> Default for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

fn default() -> Self

Returns the “default value” for a type.

impl<N, E, Ty, Ix> GraphBase for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type NodeId = Ix

node identifier

type EdgeId = usize

edge identifier

impl<N, E, Ty, Ix> GraphProp for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type EdgeType = Ty

The kind edges in the graph.

fn is_directed(&self) -> bool

impl<N, E, Ty, Ix> Index<Ix> for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type Output = N

The returned type after indexing.

fn index(&self, ix: NodeIndex<Ix>) -> &N

Performs the indexing (container[index]) operation.

impl<N, E, Ty, Ix> IndexMut<Ix> for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

fn index_mut(&mut self, ix: NodeIndex<Ix>) -> &mut N

Performs the mutable indexing (container[index]) operation.

impl<'a, N, E, Ty, Ix> IntoEdgeReferences for &'a Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type EdgeRef = EdgeReference<'a, E, Ty, Ix>

type EdgeReferences = EdgeReferences<'a, E, Ty, Ix>

fn edge_references(self) -> Self::EdgeReferences

impl<'a, N, E, Ty, Ix> IntoEdges for &'a Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type Edges = Edges<'a, E, Ty, Ix>

fn edges(self, a: Self::NodeId) -> Self::Edges

impl<'a, N, E, Ty, Ix> IntoNeighbors for &'a Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

fn neighbors(self, a: Self::NodeId) -> Self::Neighbors

Return an iterator of all neighbors of a.

• Directed: Targets of outgoing edges from a.
• Undirected: Opposing endpoints of all edges connected to a.

Panics if the node a does not exist.
Iterator element type is NodeIndex<Ix>.

type Neighbors = Neighbors<'a, Ix>

impl<'a, N, E, Ty, Ix> IntoNodeIdentifiers for &'a Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type NodeIdentifiers = NodeIdentifiers<Ix>

fn node_identifiers(self) -> Self::NodeIdentifiers

impl<N, E, Ty, Ix> NodeCount for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

fn node_count(&self) -> usize

impl<N, E, Ty, Ix> NodeIndexable for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

fn node_bound(&self) -> usize

Return an upper bound of the node indices in the graph (suitable for the size of a bitmap).

fn to_index(&self, a: Self::NodeId) -> usize

Convert a to an integer index.

fn from_index(&self, ix: usize) -> Self::NodeId

Convert i to a node index

impl<N, E, Ty, Ix> Visitable for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,

type Map = FixedBitSet

The associated map type

fn visit_map(&self) -> FixedBitSet

Create a new visitor map

fn reset_map(&self, map: &mut Self::Map)

Reset the visitor map (and resize to new size of graph if needed)

impl<N, E, Ty, Ix> NodeCompactIndexable for Csr<N, E, Ty, Ix>

where Ty: EdgeType, Ix: IndexType,