Small extensions of the Bellman-Ford routines in NetworkX, primarily for convenience (https://networkx.github.io).
Project description
This package provides a few small extensions of the Bellman-Ford routines in NetworkX, primarily for convenience.
Installation
bellmanford is available on PyPI:
pip install bellmanfordUsage
bellman_ford
length, nodes, negative_cycle = bellman_ford(G, source, target, weight='weight')Compute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm.
Parameters
G : NetworkX graph
pred : dict - Keyed by node to predecessor in the path
dist : dict - Keyed by node to the distance from the source
source: node label - Source node
target: node label - Target node
weight : string - Edge data key corresponding to the edge weight
Returns
length : numeric - Length of a negative cycle if one exists; otherwise length of a shortest path.
nodes : list - Nodes in a negative edge cycle (in order) if one exists; otherwise nodes in a shortest path.
negative_cycle : bool - True if a negative edge cycle exists, otherwise False.
Examples
>>> import networkx as nx
>>> G = nx.path_graph(5, create_using = nx.DiGraph())
>>> bf.bellman_ford(G, source=0, target=4)
(3, [1, 2, 3, 4], False)negative_edge_cycle
length, nodes, negative_cycle = negative_edge_cycle(G, weight='weight')If there is a negative edge cycle anywhere in G, returns True. Also returns the total weight of the cycle and the nodes in the cycle.
Parameters
G : NetworkX graph
weight : string, optional (default = 'weight') - Edge data key corresponding to the edge weight
Returns
length : numeric - Length of a negative edge cycle if one exists, otherwise None.
nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None.
negative_cycle : bool - True if a negative edge cycle exists, otherwise False.
Examples
>>> import networkx as nx
>>> import bellmanford as bf
>>> G = nx.cycle_graph(5, create_using = nx.DiGraph())
>>> print(bf.negative_edge_cycle(G))
(None, [], False)
>>> G[1][2]['weight'] = -7
>>> print(bf.negative_edge_cycle(G))
(-3, [4, 0, 1, 2, 3, 4], True)
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