This notebook was prepared by Donne Martin. Source and license info is on GitHub.
Input:
add_edge(source, destination, weight)
graph.add_edge(0, 1, 5)
graph.add_edge(0, 4, 3)
graph.add_edge(0, 5, 2)
graph.add_edge(1, 3, 5)
graph.add_edge(1, 4, 4)
graph.add_edge(2, 1, 6)
graph.add_edge(3, 2, 7)
graph.add_edge(3, 4, 8)
Result:
We generally use breadth-first search to determine the shortest path.
Complexity:
Note on space complexity from Wikipedia:
%run ../graph/graph.py
from collections import deque
class GraphBfs(Graph):
def bfs(self, root, visit_func):
if root is None:
return
queue = deque()
queue.append(root)
root.visit_state = State.visited
while queue:
node = queue.popleft()
visit_func(node)
for adjacent_node in node.adj_nodes.values():
if adjacent_node.visit_state == State.unvisited:
queue.append(adjacent_node)
adjacent_node.visit_state = State.visited
%run ../utils/results.py
%%writefile test_bfs.py
import unittest
class TestBfs(unittest.TestCase):
def __init__(self, *args, **kwargs):
super(TestBfs, self).__init__()
self.results = Results()
def test_bfs(self):
nodes = []
graph = GraphBfs()
for id in range(0, 6):
nodes.append(graph.add_node(id))
graph.add_edge(0, 1, 5)
graph.add_edge(0, 4, 3)
graph.add_edge(0, 5, 2)
graph.add_edge(1, 3, 5)
graph.add_edge(1, 4, 4)
graph.add_edge(2, 1, 6)
graph.add_edge(3, 2, 7)
graph.add_edge(3, 4, 8)
graph.bfs(nodes[0], self.results.add_result)
self.assertEqual(str(self.results), "[0, 1, 4, 5, 3, 2]")
print('Success: test_bfs')
def main():
test = TestBfs()
test.test_bfs()
if __name__ == '__main__':
main()
Overwriting test_bfs.py
%run -i test_bfs.py
Success: test_bfs