我在 python 中使用了一个简单的 heapq,并在其上实现了lt函数的自定义元素。
class Edge:
def __init__(self, cost, u, v):
self.u = u
self.v = v
self.cost = cost
def weight(self):
w = self.cost
v = self.v
while v.parent is not None:
w += v.const
v = v.parent
return w
def __lt__(self, other):
return self.weight() < other.weight()
然后我在另一个名为 P 的数组中保留一堆这些元素:
class Vertex:
def __init__(self, node=None):
#other stuff omited #####
self.P = []
def add_incoming_nodes(self, subgraph):
for node, costs in subgraph.items():
#if costs[self.vertex] is not 0: #node is not self
#push endpoints of the edge from another vertex to this vertex
heapq.heappush(self.P, Edge(costs[self.vertex], node, self))
问题是当我堆放一个元素时,我希望它是我数组中的最小元素,对吗?但是这个断言在这里失败了
#select arbitrary vertex
a = all_nodes[0]
while a.P: #while P[a] is not ∅
edge = heapq.heappop(a.P)
for a_edge in a.P:
assert edge.weight() < a_edge.weight()