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astar_path(G, source, target, heuristic=None, weight='weight')

There may be more than one shortest path. This returns only one.

Parameters

G : NetworkX graph
source : node

Starting node for path

target : node

Ending node for path

heuristic : function

A function to evaluate the estimate of the distance from the a node to the target. The function takes two nodes arguments and must return a number.

weight : string or function

If this is a string, then edge weights will be accessed via the edge attribute with this key (that is, the weight of the edge joining u to :None:None:`v` will be G.edges[u, v][weight] ). If no such edge attribute exists, the weight of the edge is assumed to be one. If this is a function, the weight of an edge is the value returned by the function. The function must accept exactly three positional arguments: the two endpoints of an edge and the dictionary of edge attributes for that edge. The function must return a number.

Raises

NetworkXNoPath

If no path exists between source and target.

Returns a list of nodes in a shortest path between source and target using the A* ("A-star") algorithm.

See Also

dijkstra_path
shortest_path

Examples

>>> G = nx.path_graph(5)
... print(nx.astar_path(G, 0, 4)) [0, 1, 2, 3, 4]
>>> G = nx.grid_graph(dim=[3, 3])  # nodes are two-tuples (x,y)
... nx.set_edge_attributes(G, {e: e[1][0] * 2 for e in G.edges()}, "cost")
... def dist(a, b):
...  (x1, y1) = a
...  (x2, y2) = b
...  return ((x1 - x2) ** 2 + (y1 - y2) ** 2) ** 0.5
... print(nx.astar_path(G, (0, 0), (2, 2), heuristic=dist, weight="cost")) [(0, 0), (0, 1), (0, 2), (1, 2), (2, 2)]
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.shortest_paths.astar.astar_path networkx.algorithms.shortest_paths.astar.astar_path_length

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /networkx/algorithms/shortest_paths/astar.py#12
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