Struct daggy::Dag

pub struct Dag<N, E, Ix: IndexType = DefIndex> {
    // some fields omitted
}

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.

Methods

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

fn new() -> Self

Create a new, empty Dag.

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

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

fn clear(&mut self)

Removes all nodes and edges from the Dag.

fn node_count(&self) -> usize

The total number of nodes in the Dag.

fn edge_count(&self) -> usize

The total number of edgees in the Dag.

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

Borrow the Dag's underlying PetGraph<N, Ix>. All existing indices may be used to index into this PetGraph the same way they may be used to index into the Dag.

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

Take ownership of the Dag and return the internal PetGraph. All existing indices may be used to index into this PetGraph the same way they may be used to index into the Dag.

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.

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.

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_edges 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.

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.

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.

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

Access the parent and child nodes for the given EdgeIndex.

fn clear_edges(&mut self)

Remove all edges.

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.

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.

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

Borrow the weight from the node at the given index.

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

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

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

Read from the internal node array.

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.

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

Borrow the weight from the edge at the given index.

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

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

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

Read from the internal edge array.

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.

fn index_twice_mut<A, B>(&mut self, a: A, b: B) -> (&mut PetGraph<N, E, Ix>::Output, &mut PetGraph<N, E, Ix>::Output) where PetGraph<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.

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!

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.

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.

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.

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, 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

The method for the indexing (Foo[Bar]) 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

The method for the indexing (Foo[Bar]) operation

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

The method for the indexing (Foo[Bar]) 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

The method for the indexing (Foo[Bar]) operation

Derived Implementations

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

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

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.