Struct petgraph::csr::Csr [−][src]
Expand description
Compressed Sparse Row (CSR
) is a sparse adjacency matrix graph.
CSR
is parameterized over:
- Associated data
N
for nodes andE
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.
Implementations
pub fn from_sorted_edges<Edge>(edges: &[Edge]) -> Result<Self, EdgesNotSorted> where
Edge: Clone + IntoWeightedEdge<E, NodeId = NodeIndex<Ix>>,
N: Default,
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),
]);
Remove all edges
Adds a new node with the given weight, returning the corresponding node index.
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.
Computes in O(log |V|) time.
Panics if the node a
does not exist.
Computes in O(1) time.
Panics if the node a
does not exist.
Computes in O(1) time.
Panics if the node a
does not exist.
Computes in O(1) time.
Panics if the node a
does not exist.
Return an iterator of all edges of a
.
Directed
: Outgoing edges froma
.Undirected
: All edges connected toa
.
Panics if the node a
does not exist.
Iterator element type is EdgeReference<E, Ty, Ix>
.
Trait Implementations
type NodeWeight = N
type EdgeWeight = E
Return the number of edges in the graph.
impl<'a, N, E, Ty, Ix> GetAdjacencyMatrix for &'a Csr<N, E, Ty, Ix> where
Ix: IndexType,
Ty: EdgeType,
impl<'a, N, E, Ty, Ix> GetAdjacencyMatrix for &'a Csr<N, E, Ty, Ix> where
Ix: IndexType,
Ty: EdgeType,
The adjacency matrix for Csr is a bitmap that’s computed by
.adjacency_matrix()
.
type AdjMatrix = FixedBitSet
type AdjMatrix = FixedBitSet
The associated adjacency matrix type
Create the adjacency matrix
Return true if there is an edge from a
to b
, false otherwise. Read more
type EdgeType = Ty
type EdgeType = Ty
The kind edges in the graph.
impl<'a, N, E, Ty, Ix> IntoEdgeReferences for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
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>
impl<'a, N, E, Ty, Ix> IntoNeighbors for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
impl<'a, N, E, Ty, Ix> IntoNeighbors for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
Return an iterator of all neighbors of a
.
Directed
: Targets of outgoing edges froma
.Undirected
: Opposing endpoints of all edges connected toa
.
Panics if the node a
does not exist.
Iterator element type is NodeIndex<Ix>
.
impl<'a, N, E, Ty, Ix> IntoNodeIdentifiers for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
impl<'a, N, E, Ty, Ix> IntoNodeIdentifiers for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
type NodeIdentifiers = NodeIdentifiers<Ix>
impl<'a, N, E, Ty, Ix> IntoNodeReferences for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
impl<'a, N, E, Ty, Ix> IntoNodeReferences for &'a Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
type NodeReferences = NodeReferences<'a, N, Ix>
Return an upper bound of the node indices in the graph (suitable for the size of a bitmap). Read more
Convert i
to a node index. i
must be a valid value in the graph.
type Map = FixedBitSet
type Map = FixedBitSet
The associated map type
Create a new visitor map
impl<N, E, Ty, Ix> NodeCompactIndexable for Csr<N, E, Ty, Ix> where
Ty: EdgeType,
Ix: IndexType,
Auto Trait Implementations
impl<N, E, Ty, Ix> RefUnwindSafe for Csr<N, E, Ty, Ix> where
E: RefUnwindSafe,
Ix: RefUnwindSafe,
N: RefUnwindSafe,
Ty: RefUnwindSafe,
impl<N, E, Ty, Ix> UnwindSafe for Csr<N, E, Ty, Ix> where
E: UnwindSafe,
Ix: UnwindSafe,
N: UnwindSafe,
Ty: UnwindSafe,
Blanket Implementations
Mutably borrows from an owned value. Read more