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Copy path1135-connecting-cities-with-minimum-cost.py
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1135-connecting-cities-with-minimum-cost.py
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class UnionFind:
def __init__(self, n):
self.parent = [i for i in range(n)]
self.rank = [0 for _ in range(n)]
def find(self, p):
while p != self.parent[p]:
self.parent[p] = self.parent[self.parent[p]]
p = self.parent[p]
return p
def union(self, p, q):
root_p = self.find(p)
root_q = self.find(q)
if root_p == root_q:
return
if self.rank[root_p] > self.rank[root_q]:
self.parent[root_q] = root_p
elif self.rank[root_p] < self.rank[root_q]:
self.parent[root_p] = root_q
else:
self.parent[root_p] = root_q
self.rank[root_q] += 1
def is_connected(self, p, q):
return self.find(p) == self.find(q)
class Solution:
def minimumCost(self, n: int, connections: List[List[int]]) -> int:
connections.sort(key = lambda x: x[2])
uf = UnionFind(n)
mst = []
res = 0
for p, q, w in connections:
p -= 1
q -= 1
if not uf.is_connected(p, q):
uf.union(p, q)
mst.append((p, q, w))
res += w
return res if len(mst) == n - 1 else - 1
# time O(ElogE)
# space O(E + V)
# using graph and kruskal and mst and union find