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flip-game-ii.py
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flip-game-ii.py
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# Time: O(n + c^2)
# Space: O(c)
import itertools
import re
# The best theory solution (DP, O(n + c^2)) could be seen here:
# https://leetcode.com/discuss/64344/theory-matters-from-backtracking-128ms-to-dp-0m
class Solution(object):
def canWin(self, s):
g, g_final = [0], 0
for p in itertools.imap(len, re.split('-+', s)):
while len(g) <= p:
# Theorem 2: g[game] = g[subgame1]^g[subgame2]^g[subgame3]...
# and find first missing number.
g += min(set(xrange(p)) - {x^y for x, y in itertools.izip(g[:len(g)/2], g[-2:-len(g)/2-2:-1])}),
g_final ^= g[p]
return g_final > 0 # Theorem 1: First player must win iff g(current_state) != 0
# Time: O(n + c^3 * 2^c * logc), n is length of string, c is count of "++"
# Space: O(c * 2^c)
# hash solution.
# We have total O(2^c) game strings,
# and each hash key in hash table would cost O(c),
# each one has O(c) choices to the next one,
# and each one would cost O(clogc) to sort,
# so we get O((c * 2^c) * (c * clogc)) = O(c^3 * 2^c * logc) time.
# To cache the results of all combinations, thus O(c * 2^c) space.
class Solution2(object):
def canWin(self, s):
"""
:type s: str
:rtype: bool
"""
lookup = {}
def canWinHelper(consecutives): # O(2^c) time
consecutives = tuple(sorted(c for c in consecutives if c >= 2)) # O(clogc) time
if consecutives not in lookup:
lookup[consecutives] = any(not canWinHelper(consecutives[:i] + (j, c-2-j) + consecutives[i+1:]) # O(c) time
for i, c in enumerate(consecutives) # O(c) time
for j in xrange(c - 1)) # O(c) time
return lookup[consecutives] # O(c) time
# re.findall: O(n) time, canWinHelper: O(c) in depth
return canWinHelper(map(len, re.findall(r'\+\++', s)))
# Time: O(c * n * c!), n is length of string, c is count of "++"
# Space: O(c * n), recursion would be called at most c in depth.
# Besides, it costs n space for modifying string at each depth.
class Solution3(object):
def canWin(self, s):
"""
:type s: str
:rtype: bool
"""
i, n = 0, len(s) - 1
is_win = False
while not is_win and i < n: # O(n) time
if s[i] == '+':
while not is_win and i < n and s[i+1] == '+': # O(c) time
# t(n, c) = c * (t(n, c-1) + n) + n = ...
# = c! * t(n, 0) + n * c! * (c + 1) * (1/0! + 1/1! + ... 1/c!)
# = n * c! + n * c! * (c + 1) * O(e) = O(c * n * c!)
is_win = not self.canWin(s[:i] + '--' + s[i+2:]) # O(n) space
i += 1
i += 1
return is_win