Reputation: 6709
I have a dictionary representing a directed graph. For example...
myDict = {'foo': ['hello', 'stack'], 'bar' : ['over', 'flow']}
This means that the 'foo' node points to 'hello' and 'stack' while the 'bar' node points to 'over' and 'flow'.
I have also written code for performing a breadth first search to find the shortest path between any two nodes...
from collections import deque
def breadthFirstSearch(graph, start, end):
q = deque()
path = (start, )
q.append(path)
visited = set([start])
while q:
path = q.popleft()
last_node = path[-1]
if last_node == end:
return path
for node in graph[last_node]:
if node not in visited:
visited.add(node)
q.append(path + (node,))
print 'There is no path from ' + start + ' to ' + end + '.'
return None
My question is: Is it possible to modify this breadth first search so as it gives me the largest shortest path and the start and end nodes for that path?
Upvotes: 1
Views: 3312
Reputation: 14215
Your problem is called the "graph diameter problem."
Breadth-first search creates a breadth-first search tree. The longest tree path between two nodes is, in general, going to be longer than the longest path between them because of the presence of non-tree edges. So no, you can't get BFS to do that directly.
BFS will nail it for trees, but it's slightly nontrivial.
There's a variant called "lexicographic breadth-first search" that can find the diameter of some restricted classes of graphs. Those graph classes that I've run into where LBFS works tended to look a lot like trees.
EDIT: You can, of course, run BFS once starting from each node and figure out the longest of the paths that BFS reports. Or you could use the extremely elegant Floyd-Warshall algorithm.
Upvotes: 1