Struct AdjList 

pub struct AdjList<N>
where
    N: Num + Default + Clone + Copy + Serialize,
{ /* private fields */ }

Graph represented as Adjacency list. Directly support both direct and undirect graphs. This representation offers a minimal memory foot print - it keeps information only about existing arcs - at the cost of some inefficiencies in some opertations. The memory footprint of an AdJList is always O(|N|) + O(|A|), where |N| is the number of nodes and |A| is the number of arcs in the graph.

Implementations

impl<N> AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

pub fn new_direct(node_count: usize) -> Self

Create a new direct graph with the given number of nodes. The resulting graph will NOT contain arcs. All nodes’ weights are set to num_traits::Num::zero()

pub fn new_undirect(node_count: usize) -> Self

Create a new undirect graph with the given number of nodes. The resulting graph will NOT contain arcs. All nodes’ weights are set to num_traits::Num::zero()

pub fn node_iterator(&self) -> impl Iterator<Item = (usize, N)> + '_

Return an iterator over the nodes.

pub fn arc_iterator(&self) -> impl Iterator<Item = (usize, usize, N)> + '_

Return an iterator over all the arcs in the graph.

pub fn successor_iterator( &self, node: usize, ) -> impl Iterator<Item = (usize, usize, N)> + '_

Return an iterator over the arcs exiting the given nodes.

Trait Implementations

impl<N> ArcCost<N> for &AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn cost(&self, src: usize, dst: usize) -> N

Return the weight associated to given arc.

impl<N> Clone for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize + Clone,

fn clone(&self) -> AdjList<N>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<N> Debug for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize + Debug,

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

Formats the value using the given formatter.

impl<'de, N> Deserialize<'de> for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize + 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> From<AdjList<N>> for MathGraph<N>

where N: Num + Default + Clone + Copy + Serialize,

fn from(adj: AdjList<N>) -> Self

Converts to this type from the input type.

impl<N> From<MathGraph<N>> for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn from(g: MathGraph<N>) -> Self

Converts to this type from the input type.

impl<N> GetGraphType for &AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn graph_type(&self) -> GraphType

impl<N> GetGraphType for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn graph_type(&self) -> GraphType

impl<N> Graph<N> for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn new(node_count: usize, gtype: GraphType) -> Self

Initialize a new directed or undirecte graph with the given number of nodes.

fn add_new_default_arc(&mut self, src: usize, dst: usize)

Create a new arc from src to dst (and from dst to src if the graph is undirected) and associtate with this new arc the cost num_traits::Num::zero()

fn add_new_arc(&mut self, src: usize, dst: usize, weight: N)

Create a new arc from src to dst (and from dst to src if the graph is undirected) and associtate with this new arc the cost weight

fn update_all_arcs_weight<F>(&mut self, f: F)

where F: Fn(usize, usize, N) -> N,

Update all arcs weight using the given callback function. At each function call the first argument is the index of the source node, the second is the index of the destination node and the third is the current weight of the arc. Note: in undirect graph the arc (i, j) is equivalent to the node (j, i) and the implementation should, for efficiency and reduce mistakes, call f for just one arc.

fn update_all_nodes_weight<F>(&mut self, f: F)

where F: Fn(usize, N) -> N,

Update all nodes weights using the given callback function. The first argument to each call is the index of the node and the second is its current weight.

impl<N> GraphVisitor<N> for &AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,

fn node_visitor<F: FnMut(usize, N)>(&self, f: F)

Call function f for each node in the graph. At each call the first argument is a node’s index and the second is the current node weight.

fn arc_visitor<G: FnMut(usize, usize, N)>(&self, g: G)

Call function g for each arc in the graph. At each call the first argument is the source node index, the second is destination node index and the third the current arc weight.

fn node_count(&self) -> usize

Return the number of nodes in the graph.

fn arc_count(&self) -> usize

Return the number of arcs in the graph.

fn total_entries(&self) -> usize

Return the total number of nodes and arcs in the graph.

impl<N> PartialEq for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize + PartialEq,

fn eq(&self, other: &AdjList<N>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<N> Serialize for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize + 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> StructuralPartialEq for AdjList<N>

where N: Num + Default + Clone + Copy + Serialize,