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similar-string-groups.py
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similar-string-groups.py
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# Time: O(n^2 * l) ~ O(n * l^4)
# Space: O(n) ~ O(n * l^3)
# Two strings X and Y are similar if we can swap two letters
# (in different positions) of X, so that it equals Y.
#
# For example, "tars" and "rats" are similar (swapping at positions 0 and 2),
# and "rats" and "arts" are similar, but "star" is not similar to
# "tars", "rats", or "arts".
#
# Together, these form two connected groups by similarity:
# {"tars", "rats", "arts"} and {"star"}.
# Notice that "tars" and "arts" are in the same group
# even though they are not similar.
# Formally, each group is such that a word is in the group
# if and only if it is similar
# to at least one other word in the group.
#
# We are given a list A of unique strings.
# Every string in A is an anagram of every other string in A.
# How many groups are there?
#
# Example 1:
#
# Input: ["tars","rats","arts","star"]
# Output: 2
#
# Note:
# - A.length <= 2000
# - A[i].length <= 1000
# - A.length * A[i].length <= 20000
# - All words in A consist of lowercase letters only.
# - All words in A have the same length and are anagrams of each other.
# - The judging time limit has been increased for this question.
import collections
import itertools
try:
xrange # Python 2
except NameError:
xrange = range # Python 3
class UnionFind(object):
def __init__(self, n):
self.set = range(n)
self.__size = 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)
self.__size -= 1
return True
def size(self):
return self.__size
class Solution(object):
def numSimilarGroups(self, A):
def isSimilar(a, b):
diff = 0
for x, y in itertools.izip(a, b):
if x != y:
diff += 1
if diff > 2:
return False
return diff == 2
N, L = len(A), len(A[0])
union_find = UnionFind(N)
if N < L*L:
for (i1, word1), (i2, word2) in \
itertools.combinations(enumerate(A), 2):
if isSimilar(word1, word2):
union_find.union_set(i1, i2)
else:
buckets = collections.defaultdict(list)
lookup = set()
for i in xrange(len(A)):
word = list(A[i])
if A[i] not in lookup:
buckets[A[i]].append(i)
lookup.add(A[i])
for j1, j2 in itertools.combinations(xrange(L), 2):
word[j1], word[j2] = word[j2], word[j1]
buckets["".join(word)].append(i)
word[j1], word[j2] = word[j2], word[j1]
for word in A: # Time: O(n * l^4)
for i1, i2 in itertools.combinations(buckets[word], 2):
union_find.union_set(i1, i2)
return union_find.size()