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sentence-similarity-ii.py 1.27 KB
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Allen Liu 提交于 2018-10-13 01:56 +08:00 . add complexity
# Time: O(n + p)
# Space: O(p)
import itertools
class UnionFind(object):
def __init__(self, n):
self.set = range(n)
def find_set(self, x):
if self.set[x] != x:
self.set[x] = self.find_set(self.set[x]) # path compression.
return self.set[x]
def union_set(self, x, y):
x_root, y_root = map(self.find_set, (x, y))
if x_root == y_root:
return False
self.set[min(x_root, y_root)] = max(x_root, y_root)
return True
class Solution(object):
def areSentencesSimilarTwo(self, words1, words2, pairs):
"""
:type words1: List[str]
:type words2: List[str]
:type pairs: List[List[str]]
:rtype: bool
"""
if len(words1) != len(words2): return False
lookup = {}
union_find = UnionFind(2 * len(pairs))
for pair in pairs:
for p in pair:
if p not in lookup:
lookup[p] = len(lookup)
union_find.union_set(lookup[pair[0]], lookup[pair[1]])
return all(w1 == w2 or
w1 in lookup and w2 in lookup and
union_find.find_set(lookup[w1]) == union_find.find_set(lookup[w2])
for w1, w2 in itertools.izip(words1, words2))
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