def _findCenter(self, G):
for source in range(G.V()):
maxdist = 0
abfs = BFS(G, source)
for v in range(G.V()):
if abfs.hasPathTo(v):
dist = abfs.distTo(v)
if maxdist < dist:
maxdist = dist
self._maxdistances[source] = maxdist
def _findCenter(self, G): for source in range(G.V()): maxdist = 0 abfs = BFS(G, source) for v in range(G.V()): if abfs.hasPathTo(v): dist = abfs.distTo(v) if maxdist < dist: maxdist = dist self._maxdistances[source] = maxdist
def test(self):
bb = BreadthFirstSearch()
n = 2
m = 1
edges = []
start = 1
self.assertEquals([-1], bb.calculate(n, m, edges, start))
n = 3
m = 1
edges = [[1, 2]]
start=1-1
self.assertEquals([6], bb.calculate(n, m, edges, start))
def setSearchAlgorithm(self, searchAlgorithm):
if searchAlgorithm == "dfs":
self.searchAlgorithm = DepthFirstSearch()
elif searchAlgorithm == "bfs":
self.searchAlgorithm = BreadthFirstSearch()
elif searchAlgorithm == "astar":
self.searchAlgorithm = BestFirstSearch()
def solution(initial):
buildDictOfStates(initial)
buildSymTbls()
G = buildGraph()
source = symTbl[tuple(initial)]
node = symTbl[tuple(final)]
abfs = BFS(G, source)
# path is represented as a list of vertices
path = abfs.pathTo(node)
if path is None: return "No solution"
# actions = [ (1, 2), (2, 3) ]
actions = buildActions(path)
dist = abfs.distTo(node)
print dist
for action in actions:
print '{0} {1}'.format(action[0], action[1])
return dist, actions
def _findDiam(self, G, source): "find length of longest shortest path" abfs = BFS(G, source) node = -1 for v in range(G.V()): if abfs.hasPathTo(v): dist = abfs.distTo(v) if self._max_dist < dist: self._max_dist = dist node = v # node will be set here at least 1x if self._marked[node]: # we returned to this vertex from the other end of the longest path return self._max_dist else: # run BFS on node furthest from source self._marked[node] = True self._findDiam(G, node)
def solution(initial):
buildDictOfStates(initial)
buildSymTbls()
G = buildGraph()
source = symTbl[tuple(initial)]
node = symTbl[tuple(final)]
abfs = BFS(G, source)
# path is represented as a list of vertices
path = abfs.pathTo(node)
if path is None: return "No solution"
# actions = [ (1, 2), (2, 3) ]
actions = buildActions(path)
dist = abfs.distTo(node)
print dist
for action in actions:
print '{0} {1}'.format(action[0], action[1])
return dist, actions
G.addEdge(v, w)
return G
def buildActions(path):
actions = []
for i in range(len(path)-1):
from_state = path[i]
to_state = path[i+1]
# convert state from vertex to form [n1, n2, ...]
from_state = symTbl2[from_state]
to_state = symTbl2[to_state]
for e in d[from_state]:
if e[0] == to_state:
actions.append(e[1])
return actions
buildDictOfStates(initial)
buildSymTbls()
G = buildGraph()
source = symTbl[tuple(initial)]
node = symTbl[tuple(final)]
abfs = BFS(G, source)
# path is represented as a list of vertices
path = abfs.pathTo(node)
if path is None: print "No solution"
# actions = [ (1, 2), (1, 3) ]
actions = buildActions(path)
dist = abfs.distTo(node)
print dist
for action in actions:
print '{0} {1}'.format(action[0], action[1])
def buildActions(path):
actions = []
for i in range(len(path) - 1):
from_state = path[i]
to_state = path[i + 1]
# convert state from vertex to form [n1, n2, ...]
from_state = symTbl2[from_state]
to_state = symTbl2[to_state]
for e in d[from_state]:
if e[0] == to_state:
actions.append(e[1])
return actions
buildDictOfStates(initial)
buildSymTbls()
G = buildGraph()
source = symTbl[tuple(initial)]
node = symTbl[tuple(final)]
abfs = BFS(G, source)
# path is represented as a list of vertices
path = abfs.pathTo(node)
if path is None: print "No solution"
# actions = [ (1, 2), (1, 3) ]
actions = buildActions(path)
dist = abfs.distTo(node)
print dist
for action in actions:
print '{0} {1}'.format(action[0], action[1])
