Struct daggy::Dag

pub struct Dag<N, E, Ix: IndexType = DefaultIx> { /* private fields */ }

A Directed acyclic graph (DAG) data structure.

Dag is a thin wrapper around petgraph’s Graph data structure, providing a refined API for dealing specifically with DAGs.

Note: The following documentation is adapted from petgraph’s Graph documentation

Dag is parameterized over the node weight N, edge weight E and index type Ix.

NodeIndex is a type that acts as a reference to nodes, but these are only stable across certain operations. Removing nodes may shift other indices. Adding kids to the Dag keeps all indices stable, but removing a node will force the last node to shift its index to take its place.

The fact that the node indices in the Dag are numbered in a compact interval from 0 to n-1 simplifies some graph algorithms.

The Ix parameter is u32 by default. The goal is that you can ignore this parameter completely unless you need a very large Dag – then you can use usize.

The Dag also offers methods for accessing the underlying Graph, which can be useful for taking advantage of petgraph’s various graph-related algorithms.

Implementations

impl<N, E, Ix> Dag<N, E, Ix> where
    Ix: IndexType, 

pub fn new() -> Self

Create a new, empty Dag.

pub fn with_capacity(nodes: usize, edges: usize) -> Self

Create a new Dag with estimated capacity for its node and edge Vecs.

pub fn from_edges<I>(edges: I) -> Result<Self, WouldCycle<E>> where
    I: IntoIterator,
    I::Item: IntoWeightedEdge<E>,
    <I::Item as IntoWeightedEdge<E>>::NodeId: Into<NodeIndex<Ix>>,
    N: Default, 

Create a Dag from an iterator yielding edges.

Node weights N are set to default values.

Edge weights E may either be specified in the list, or they are filled with default values.

Nodes are inserted automatically to match the edges.

Returns an Err if adding any of the edges would cause a cycle.

pub fn extend_with_edges<I>(&mut self, edges: I) -> Result<(), WouldCycle<E>> where
    I: IntoIterator,
    I::Item: IntoWeightedEdge<E>,
    <I::Item as IntoWeightedEdge<E>>::NodeId: Into<NodeIndex<Ix>>,
    N: Default, 

Extend the Dag with the given edges.

Node weights N are set to default values.

Edge weights E may either be specified in the list, or they are filled with default values.

Nodes are inserted automatically to match the edges.

Returns an Err if adding an edge would cause a cycle.

pub fn from_elements<I>(elements: I) -> Result<Self, WouldCycle<E>> where
    Self: Sized,
    I: IntoIterator<Item = Element<N, E>>, 

Create a Dag from an iterator yielding elements.

Returns an Err if an edge would cause a cycle within the graph.

pub fn map<'a, F, G, N2, E2>(
    &'a self,
    node_map: F,
    edge_map: G
) -> Dag<N2, E2, Ix> where
    F: FnMut(NodeIndex<Ix>, &'a N) -> N2,
    G: FnMut(EdgeIndex<Ix>, &'a E) -> E2, 

Create a new Graph by mapping node and edge weights to new values.

The resulting graph has the same structure and the same graph indices as self.

pub fn filter_map<'a, F, G, N2, E2>(
    &'a self,
    node_map: F,
    edge_map: G
) -> Dag<N2, E2, Ix> where
    F: FnMut(NodeIndex<Ix>, &'a N) -> Option<N2>,
    G: FnMut(EdgeIndex<Ix>, &'a E) -> Option<E2>, 

Create a new Dag by mapping node and edge weights. A node or edge may be mapped to None to exclude it from the resulting Dag.

Nodes are mapped first with the node_map closure, then edge_map is called for the edges that have not had any endpoint removed.

The resulting graph has the structure of a subgraph of the original graph. If no nodes are removed, the resulting graph has compatible node indices.

If neither nodes nor edges are removed, the resulting graph has compatible node indices. If neither nodes nor edges are removed the result has the same graph indices as self.

The resulting graph has the same structure and the same graph indices as self.

pub fn clear(&mut self)

Removes all nodes and edges from the Dag.

pub fn node_count(&self) -> usize

The total number of nodes in the Dag.

pub fn edge_count(&self) -> usize

The total number of edges in the Dag.

pub fn graph(&self) -> &DiGraph<N, E, Ix>

Borrow the Dag’s underlying DiGraph<N, Ix>.

All existing indices may be used to index into this DiGraph the same way they may be used to index into the Dag.

pub fn into_graph(self) -> DiGraph<N, E, Ix>

Take ownership of the Dag and return the internal DiGraph.

All existing indices may be used to index into this DiGraph the same way they may be used to index into the Dag.

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

Add a new node to the Dag with the given weight.

Computes in O(1) time.

Returns the index of the new node.

Note: If you’re adding a new node and immediately adding a single edge to that node from some other node, consider using the add_child or add_parent methods instead for better performance.

Panics if the Graph is at the maximum number of nodes for its index type.

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

Add a new directed edge to the Dag with the given weight.

The added edge will be in the direction a -> b

Checks if the edge would create a cycle in the Graph.

If adding the edge would not cause the graph to cycle, the edge will be added and its EdgeIndex returned.

If adding the edge would cause the graph to cycle, the edge will not be added and instead a WouldCycle<E> error with the given weight will be returned.

In the worst case, petgraph’s is_cyclic_directed function is used to check whether or not adding the edge would create a cycle.

Note: Dag allows adding parallel (“duplicate”) edges. If you want to avoid this, use update_edge instead.

Note: If you’re adding a new node and immediately adding a single edge to that node from some other node, consider using the add_child or add_parent methods instead for better performance.

Panics if either a or b do not exist within the Dag.

Panics if the Graph is at the maximum number of edges for its index type.

pub fn add_edges<I>(
    &mut self,
    edges: I
) -> Result<EdgeIndices<Ix>, WouldCycle<Vec<E>>> where
    I: IntoIterator<Item = (NodeIndex<Ix>, NodeIndex<Ix>, E)>, 

Adds the given directed edges to the Dag, each with their own given weight.

The given iterator should yield a NodeIndex pair along with a weight for each Edge to be added in a tuple.

If we were to describe the tuple as (a, b, weight), the connection would be directed as follows:

a -> b

This method behaves similarly to the add_edge method, however rather than checking whether or not a cycle has been created after adding each edge, it only checks after all edges have been added. This makes it a slightly more performant and ergonomic option that repeatedly calling add_edge.

If adding the edges would not cause the graph to cycle, the edges will be added and their indices returned in an EdgeIndices iterator, yielding indices for each edge in the same order that they were given.

If adding the edges would cause the graph to cycle, the edges will not be added and instead a WouldCycle<Vec<E>> error with the unused weights will be returned. The order of the returned Vec will be the reverse of the given order.

Note: Dag allows adding parallel (“duplicate”) edges. If you want to avoid this, use update_edge instead.

Note: If you’re adding a series of new nodes and edges to a single node, consider using the add_child or add_parent methods instead for greater convenience.

Panics if the Graph is at the maximum number of nodes for its index type.

pub fn update_edge(
    &mut self,
    a: NodeIndex<Ix>,
    b: NodeIndex<Ix>,
    weight: E
) -> Result<EdgeIndex<Ix>, WouldCycle<E>>

Update the edge from nodes a -> b with the given weight.

If the edge doesn’t already exist, it will be added using the add_edge method.

Please read the add_edge for more important details.

Checks if the edge would create a cycle in the Graph.

Computes in O(t + e) time where “t” is the complexity of add_edge and e is the number of edges connected to the nodes a and b.

Returns the index of the edge, or a WouldCycle error if adding the edge would create a cycle.

Note: If you’re adding a new node and immediately adding a single edge to that node from some parent node, consider using the add_child method instead for greater convenience.

Panics if the Graph is at the maximum number of nodes for its index type.

pub fn find_edge(
    &self,
    a: NodeIndex<Ix>,
    b: NodeIndex<Ix>
) -> Option<EdgeIndex<Ix>>

Find and return the index to the edge that describes a -> b if there is one.

Computes in O(e’) time, where e’ is the number of edges connected to the nodes a and b.

pub fn edge_endpoints(
    &self,
    e: EdgeIndex<Ix>
) -> Option<(NodeIndex<Ix>, NodeIndex<Ix>)>

Access the parent and child nodes for the given EdgeIndex.

pub fn clear_edges(&mut self)

Remove all edges.

pub fn add_parent(
    &mut self,
    child: NodeIndex<Ix>,
    edge: E,
    node: N
) -> (EdgeIndex<Ix>, NodeIndex<Ix>)

Add a new edge and parent node to the node at the given NodeIndex.

Returns both the edge’s EdgeIndex and the node’s NodeIndex.

node -> edge -> child

Computes in O(1) time.

This is faster than using add_node and add_edge. This is because we don’t have to check if the graph would cycle when adding an edge to the new node, as we know it it will be the only edge connected to that node.

Panics if the given child node doesn’t exist.

Panics if the Graph is at the maximum number of edges for its index.

pub fn add_child(
    &mut self,
    parent: NodeIndex<Ix>,
    edge: E,
    node: N
) -> (EdgeIndex<Ix>, NodeIndex<Ix>)

Add a new edge and child node to the node at the given NodeIndex. Returns both the edge’s EdgeIndex and the node’s NodeIndex.

child -> edge -> node

Computes in O(1) time.

This is faster than using add_node and add_edge. This is because we don’t have to check if the graph would cycle when adding an edge to the new node, as we know it it will be the only edge connected to that node.

Panics if the given parent node doesn’t exist.

Panics if the Graph is at the maximum number of edges for its index.

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

Borrow the weight from the node at the given index.

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

Mutably borrow the weight from the node at the given index.

pub fn raw_nodes(&self) -> RawNodes<'_, N, Ix>

Read from the internal node array.

pub fn node_weights_mut(&mut self) -> NodeWeightsMut<'_, N, Ix>

An iterator yielding mutable access to all node weights.

The order in which weights are yielded matches the order of their node indices.

pub fn edge_weight(&self, edge: EdgeIndex<Ix>) -> Option<&E>

Borrow the weight from the edge at the given index.

pub fn edge_weight_mut(&mut self, edge: EdgeIndex<Ix>) -> Option<&mut E>

Mutably borrow the weight from the edge at the given index.

pub fn raw_edges(&self) -> RawEdges<'_, E, Ix>

Read from the internal edge array.

pub fn edge_weights_mut(&mut self) -> EdgeWeightsMut<'_, E, Ix>

An iterator yielding mutable access to all edge weights.

The order in which weights are yielded matches the order of their edge indices.

pub fn index_twice_mut<A, B>(
    &mut self,
    a: A,
    b: B
) -> (&mut <DiGraph<N, E, Ix> as Index<A>>::Output, &mut <DiGraph<N, E, Ix> as Index<B>>::Output) where
    DiGraph<N, E, Ix>: IndexMut<A> + IndexMut<B>,
    A: GraphIndex,
    B: GraphIndex, 

Index the Dag by two indices.

Both indices can be either NodeIndexs, EdgeIndexs or a combination of the two.

Panics if the indices are equal or if they are out of bounds.

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

Remove the node at the given index from the Dag and return it if it exists.

Note: Calling this may shift (and in turn invalidate) previously returned node indices!

pub fn remove_edge(&mut self, e: EdgeIndex<Ix>) -> Option<E>

Remove an edge and return its weight, or None if it didn’t exist.

Computes in O(e’) time, where e’ is the size of four particular edge lists, for the nodes of e and the nodes of another affected edge.

pub fn parents(&self, child: NodeIndex<Ix>) -> Parents<N, E, Ix>

A Walker type that may be used to step through the parents of the given child node.

Unlike iterator types, Walkers do not require borrowing the internal Graph. This makes them useful for traversing the Graph while still being able to mutably borrow it.

If you require an iterator, use one of the Walker methods for converting this Walker into a similarly behaving Iterator type.

See the Walker trait for more useful methods.

pub fn children(&self, parent: NodeIndex<Ix>) -> Children<N, E, Ix>

A “walker” object that may be used to step through the children of the given parent node.

Unlike iterator types, Walkers do not require borrowing the internal Graph. This makes them useful for traversing the Graph while still being able to mutably borrow it.

If you require an iterator, use one of the Walker methods for converting this Walker into a similarly behaving Iterator type.

See the Walker trait for more useful methods.

pub fn recursive_walk<F>(
    &self,
    start: NodeIndex<Ix>,
    recursive_fn: F
) -> RecursiveWalk<N, E, Ix, F> where
    F: FnMut(&Self, NodeIndex<Ix>) -> Option<(EdgeIndex<Ix>, NodeIndex<Ix>)>, 

A Walker type that recursively walks the Dag using the given recursive_fn.

See the Walker trait for more useful methods.

Trait Implementations

impl<N: Clone, E: Clone, Ix: Clone + IndexType> Clone for Dag<N, E, Ix>

fn clone(&self) -> Dag<N, E, Ix>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<N, E, Ix> Data for Dag<N, E, Ix> where
    Ix: IndexType, 

type NodeWeight = N

type EdgeWeight = E

impl<N, E, Ix> DataMap for Dag<N, E, Ix> where
    Ix: IndexType, 

fn node_weight(&self, id: Self::NodeId) -> Option<&Self::NodeWeight>

fn edge_weight(&self, id: Self::EdgeId) -> Option<&Self::EdgeWeight>

impl<N, E, Ix> DataMapMut for Dag<N, E, Ix> where
    Ix: IndexType, 

fn node_weight_mut(&mut self, id: Self::NodeId) -> Option<&mut Self::NodeWeight>

fn edge_weight_mut(&mut self, id: Self::EdgeId) -> Option<&mut Self::EdgeWeight>

impl<N: Debug, E: Debug, Ix: Debug + IndexType> Debug for Dag<N, E, Ix>

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

Formats the value using the given formatter.

impl<N, E, Ix> Default for Dag<N, E, Ix> where
    Ix: IndexType, 

fn default() -> Self

Returns the “default value” for a type.

impl<'de, N, E, Ix> Deserialize<'de> for Dag<N, E, Ix> where
    Self: Sized,
    N: Deserialize<'de>,
    E: Deserialize<'de>,
    Ix: IndexType + Deserialize<'de>, 

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error> where
    D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<N, E, Ix> GetAdjacencyMatrix for Dag<N, E, Ix> where
    Ix: IndexType, 

type AdjMatrix = <Graph<N, E, Directed, Ix> as GetAdjacencyMatrix>::AdjMatrix

The associated adjacency matrix type

fn adjacency_matrix(&self) -> Self::AdjMatrix

Create the adjacency matrix

fn is_adjacent(
    &self,
    matrix: &Self::AdjMatrix,
    a: NodeIndex<Ix>,
    b: NodeIndex<Ix>
) -> bool

Return true if there is an edge from a to b, false otherwise.

impl<N, E, Ix> GraphBase for Dag<N, E, Ix> where
    Ix: IndexType, 

type NodeId = NodeIndex<Ix>

node identifier

type EdgeId = EdgeIndex<Ix>

edge identifier

impl<N, E, Ix> GraphProp for Dag<N, E, Ix> where
    Ix: IndexType, 

type EdgeType = Directed

The kind edges in the graph.

fn is_directed(&self) -> bool

impl<N, E, Ix> Index<EdgeIndex<Ix>> for Dag<N, E, Ix> where
    Ix: IndexType, 

type Output = E

The returned type after indexing.

fn index(&self, index: EdgeIndex<Ix>) -> &E

Performs the indexing (container[index]) operation.

impl<N, E, Ix> Index<NodeIndex<Ix>> for Dag<N, E, Ix> where
    Ix: IndexType, 

type Output = N

The returned type after indexing.

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

Performs the indexing (container[index]) operation.

impl<N, E, Ix> IndexMut<EdgeIndex<Ix>> for Dag<N, E, Ix> where
    Ix: IndexType, 

fn index_mut(&mut self, index: EdgeIndex<Ix>) -> &mut E

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

impl<N, E, Ix> IndexMut<NodeIndex<Ix>> for Dag<N, E, Ix> where
    Ix: IndexType, 

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

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

impl<N, E, Ix> Into<Graph<N, E, Directed, Ix>> for Dag<N, E, Ix> where
    Ix: IndexType, 

fn into(self) -> DiGraph<N, E, Ix>

Converts this type into the (usually inferred) input type.

impl<'a, N, E, Ix> IntoEdgeReferences for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

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

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

fn edge_references(self) -> Self::EdgeReferences

impl<'a, N, E, Ix> IntoEdges for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

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

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

impl<'a, N, E, Ix> IntoEdgesDirected for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

type EdgesDirected = Edges<'a, E, Directed, Ix>

fn edges_directed(self, a: Self::NodeId, dir: Direction) -> Self::EdgesDirected

impl<'a, N, E, Ix> IntoNeighbors for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

type Neighbors = Neighbors<'a, E, Ix>

fn neighbors(self, n: NodeIndex<Ix>) -> Self::Neighbors

Return an iterator of the neighbors of node a.

impl<'a, N, E, Ix> IntoNeighborsDirected for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

type NeighborsDirected = Neighbors<'a, E, Ix>

fn neighbors_directed(self, n: NodeIndex<Ix>, d: Direction) -> Self::Neighbors

impl<'a, N, E, Ix> IntoNodeIdentifiers for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

type NodeIdentifiers = NodeIndices<Ix>

fn node_identifiers(self) -> Self::NodeIdentifiers

impl<'a, N, E, Ix> IntoNodeReferences for &'a Dag<N, E, Ix> where
    Ix: IndexType, 

type NodeRef = (NodeIndex<Ix>, &'a N)

type NodeReferences = NodeReferences<'a, N, Ix>

fn node_references(self) -> Self::NodeReferences

impl<N, E, Ix> NodeCount for Dag<N, E, Ix> where
    Ix: IndexType, 

fn node_count(&self) -> usize

impl<N, E, Ix> NodeIndexable for Dag<N, E, Ix> where
    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, ix: NodeIndex<Ix>) -> usize

Convert a to an integer index.

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

Convert i to a node index. i must be a valid value in the graph.

impl<N, E, Ix> Serialize for Dag<N, E, Ix> where
    N: Serialize,
    E: Serialize,
    Ix: IndexType + Serialize, 

fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error> where
    S: Serializer, 

Serialize this value into the given Serde serializer.

impl<N, E, Ix> Visitable for Dag<N, E, Ix> where
    Ix: IndexType, 

type Map = <Graph<N, E, Directed, Ix> as Visitable>::Map

The associated map type

fn visit_map(&self) -> Self::Map

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<'a, N, E, Ix> Walker<&'a Dag<N, E, Ix>> for Children<N, E, Ix> where
    Ix: IndexType, 

type Item = (EdgeIndex<Ix>, NodeIndex<Ix>)

fn walk_next(&mut self, dag: &'a Dag<N, E, Ix>) -> Option<Self::Item>

Advance to the next item

fn iter(self, context: Context) -> WalkerIter<Self, Context> where
    Context: Clone, 

Create an iterator out of the walker and given context.

impl<'a, N, E, Ix> Walker<&'a Dag<N, E, Ix>> for Parents<N, E, Ix> where
    Ix: IndexType, 

type Item = (EdgeIndex<Ix>, NodeIndex<Ix>)

fn walk_next(&mut self, dag: &'a Dag<N, E, Ix>) -> Option<Self::Item>

Advance to the next item

fn iter(self, context: Context) -> WalkerIter<Self, Context> where
    Context: Clone, 

Create an iterator out of the walker and given context.

impl<N, E, Ix> NodeCompactIndexable for Dag<N, E, Ix> where
    Ix: IndexType,