G.add_edges_from(edges)
# You must change here if there is a different cost per edge
CostperEdge = [1 for i in range(len(edges))]
# Adding the respective cost for each edge in the graph
for u, v in edges:
G.add_weighted_edges_from([(u, v, CostperEdge[edges.index((u, v))])])
positions = plotGraph(G, 1, None)
# Creating an problem object based on FindPath class
Problema = FindPath(G)
# Creating an object for breadth first search algorithm for ``FindPath`` problem
SearchObj = breadth_first_search(Problema)
start = 'Pouso Alegre'
target = 'Campinas'
print('\nSearching %s starting from %s...' % (target, start))
solution, path, path_edges = SearchObj.search(start, target)
print('Done!\n')
if solution:
print('Path found!')
printPath(path, start)
for u, v in edges:
if (u, v) not in path_edges:
G.remove_edge(u, v)
plotGraph(G, 1, positions)
else:
print('Path not found!')
from SearchAlgorithms.data_structures import Failure
from problem1 import problem as pr
from SearchAlgorithms import breadth_first_search as b
p = pr.Problem()
sol = b.breadth_first_search(p)
if isinstance(sol, Failure):
print('BFS failed.')
else:
print('BFS:')
print("visited = {} , expanded = {} , max_memory = {} , path_cost = {}".
format(sol.visited, sol.expanded, sol.max_memory, sol.path_cost))
print('Path:')
for node in sol.best_path:
print(node.state, end='')
print(' , ', end=' ')