def main(*argv):
"Demostration program number 2."
print Demo2.main.__doc__
StackAsArray.main(*argv)
StackAsLinkedList.main(*argv)
QueueAsArray.main(*argv)
QueueAsLinkedList.main(*argv)
DequeAsArray.main(*argv)
DequeAsLinkedList.main(*argv)
return 0
def search(self, initial):
"""
(BreadthFirstSolver, Solution) -> Solution
Does a breadth-first traversal of the solution space
starting from the given node.
"""
queue = QueueAsLinkedList()
queue.enqueue(initial)
while not queue.isEmpty:
current = queue.dequeue()
if current.isComplete:
self.updateBest(current)
else:
for soln in current.successors:
queue.enqueue(soln)
def breadthFirstGenerator(self):
"""
(Tree) -> generator
Yields the keys in this tree in depth-first traversal order.
"""
queue = QueueAsLinkedList()
if not self.isEmpty:
queue.enqueue(self)
while not queue.isEmpty:
head = queue.dequeue()
yield head.key
for i in xrange(head.degree):
child = head.getSubtree(i)
if not child.isEmpty:
queue.enqueue(child)
def breadthFirstTraversal(self, visitor):
"""
(Tree, Visitor) -> None
Makes the given visitor do a breadth-first traversal of this tree.
"""
assert isinstance(visitor, Visitor)
queue = QueueAsLinkedList()
if not self.isEmpty:
queue.enqueue(self)
while not queue.isEmpty and not visitor.isDone:
head = queue.dequeue()
visitor.visit(head.key)
for i in xrange(head.degree):
child = head.getSubtree(i)
if not child.isEmpty:
queue.enqueue(child)
def search(self, initial):
"""
(BreadthFirstBranchAndBoundSolver, Solution) -> Solution
Does a breadth-first traversal of the solution space
starting from the given node.
"""
queue = QueueAsLinkedList()
if initial.isFeasible:
queue.enqueue(initial)
while not queue.isEmpty:
current = queue.dequeue()
if current.isComplete:
self.updateBest(current)
else:
for successor in current.successors:
if successor.isFeasible and \
successor.bound < self._bestObjective:
queue.enqueue(successor)
def search(self, initial):
"""
(BreadthFirstSolver, Solution) -> Solution
Does a breadth-first traversal of the solution space
starting from the given node.
"""
queue = QueueAsLinkedList()
queue.enqueue(initial)
while not queue.isEmpty:
current = queue.dequeue()
if current.isComplete:
self.updateBest(current)
else:
for soln in current.successors:
queue.enqueue(soln)
def breadthFirstGenerator(self):
"""
(Tree) -> generator
Yields the keys in this tree in depth-first traversal order.
"""
queue = QueueAsLinkedList()
if not self.isEmpty:
queue.enqueue(self)
while not queue.isEmpty:
head = queue.dequeue()
yield head.key
for i in xrange(head.degree):
child = head.getSubtree(i)
if not child.isEmpty:
queue.enqueue(child)
def breadthFirstTraversal(self, visitor):
"""
(Tree, Visitor) -> None
Makes the given visitor do a breadth-first traversal of this tree.
"""
assert isinstance(visitor, Visitor)
queue = QueueAsLinkedList()
if not self.isEmpty:
queue.enqueue(self)
while not queue.isEmpty and not visitor.isDone:
head = queue.dequeue()
visitor.visit(head.key)
for i in xrange(head.degree):
child = head.getSubtree(i)
if not child.isEmpty:
queue.enqueue(child)
def breadthFirstTraversal(tree):
"""
(Tree) -> None
Does a breadth-first traversal of a tree and prints the keys.
"""
queue = QueueAsLinkedList()
#! queue.enqueue(tree)
#[
if not tree.isEmpty:
queue.enqueue(tree)
#]
while not queue.isEmpty:
t = queue.dequeue()
print((t.key))
for i in range(t.degree):
subTree = t.getSubtree(i)
#! queue.enqueue(subTree)
#[
if not subTree.isEmpty:
queue.enqueue(subTree)
def breadthFirstTraversal(self, visitor, start):
"""
(Graph, Visitor, Vertex) -> None
Makes the given visitor visit the vertices of this graph
in breadth-first traversal order starting from the given vertex.
"""
assert isinstance(visitor, Visitor)
enqueued = Array(self._numberOfVertices)
for v in xrange(self._numberOfVertices):
enqueued[v] = False
queue = QueueAsLinkedList()
queue.enqueue(self[start])
enqueued[start] = True
while not queue.isEmpty and not visitor.isDone:
v = queue.dequeue()
visitor.visit(v)
for to in v.successors:
if not enqueued[to.number]:
queue.enqueue(to)
enqueued[to.number] = True
def search(self, initial):
"""
(BreadthFirstBranchAndBoundSolver, Solution) -> Solution
Does a breadth-first traversal of the solution space
starting from the given node.
"""
queue = QueueAsLinkedList()
if initial.isFeasible:
queue.enqueue(initial)
while not queue.isEmpty:
current = queue.dequeue()
if current.isComplete:
self.updateBest(current)
else:
for successor in current.successors:
if successor.isFeasible and \
successor.bound < self._bestObjective:
queue.enqueue(successor)
def topologicalOrderTraversal(self, visitor):
"""
(Graph, Visitor) -> None
Makes the given visitor visit the vertices of this graph
in topological order.
"""
inDegree = Array(self.numberOfVertices)
for v in xrange(self.numberOfVertices):
inDegree[v] = 0
for e in self.edges:
inDegree[e.v1.number] += 1
queue = QueueAsLinkedList()
for v in xrange(self.numberOfVertices):
if inDegree[v] == 0:
queue.enqueue(self[v])
while not queue.isEmpty and not visitor.isDone:
v = queue.dequeue()
visitor.visit(v)
for to in v.successors:
inDegree[to.number] -= 1
if inDegree[to.number] == 0:
queue.enqueue(to)
def breadthFirstTraversal(tree):
"""
(Tree) -> None
Does a breadth-first traversal of a tree and prints the keys.
"""
queue = QueueAsLinkedList()
#! queue.enqueue(tree)
#[
if not tree.isEmpty:
queue.enqueue(tree)
#]
while not queue.isEmpty:
t = queue.dequeue()
print t.key
for i in xrange(t.degree):
subTree = t.getSubtree(i)
#! queue.enqueue(subTree)
#[
if not subTree.isEmpty:
queue.enqueue(subTree)
def breadthFirstTraversal(self, visitor, start):
"""
(Graph, Visitor, Vertex) -> None
Makes the given visitor visit the vertices of this graph
in breadth-first traversal order starting from the given vertex.
"""
assert isinstance(visitor, Visitor)
enqueued = Array(self._numberOfVertices)
for v in xrange(self._numberOfVertices):
enqueued[v] = False
queue = QueueAsLinkedList()
queue.enqueue(self[start])
enqueued[start] = True
while not queue.isEmpty and not visitor.isDone:
v = queue.dequeue()
visitor.visit(v)
for to in v.successors:
if not enqueued[to.number]:
queue.enqueue(to)
enqueued[to.number] = True
def topologicalOrderTraversal(self, visitor):
"""
(Graph, Visitor) -> None
Makes the given visitor visit the vertices of this graph
in topological order.
"""
inDegree = Array(self.numberOfVertices)
for v in xrange(self.numberOfVertices):
inDegree[v] = 0
for e in self.edges:
inDegree[e.v1.number] += 1
queue = QueueAsLinkedList()
for v in xrange(self.numberOfVertices):
if inDegree[v] == 0:
queue.enqueue(self[v])
while not queue.isEmpty and not visitor.isDone:
v = queue.dequeue()
visitor.visit(v)
for to in v.successors:
inDegree[to.number] -= 1
if inDegree[to.number] == 0:
queue.enqueue(to)