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050 N-Queens.py
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050 N-Queens.py
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"""
The n-queens puzzle is the problem of placing n queens on an n*n chessboard such that no two queens attack each other.
Given an integer n, return all distinct solutions to the n-queens puzzle.
Each solution contains a distinct board configuration of the n-queens' placement, where 'Q' and '.' both indicate a
queen and an empty space respectively.
For example,
There exist two distinct solutions to the 4-queens puzzle:
[
[".Q..", // Solution 1
"...Q",
"Q...",
"..Q."],
["..Q.", // Solution 2
"Q...",
"...Q",
".Q.."]
]
"""
__author__ = 'Danyang'
INVALID = -1
QUEEN = 1
DEFAULT = 0
directions = [(+1, +1), (-1, -1), (-1, +1), (+1, -1)]
class Solution:
def solveNQueens(self, n):
"""
backtracking
:param n: integer
:return: a list of lists of string
"""
result = []
current = [[0 for _ in xrange(n)] for _ in xrange(n)]
self.backtrack(0, current, result)
return self.transform2string(result)
def backtrack(self, queen_index, current, result):
"""
Search problem: dfs, backtracking
Python:
notice, the bound should be checked using "if condition" rather than "try-catch" since negative index is acceptable in python
:param queen_index:
:param current: 2D matrix
:param result: list of 2D matrix
:return: Nothing
"""
n = len(current)
if queen_index==n:
result.append(current)
return
for i in xrange(n):
if current[queen_index][i]==INVALID:
continue
# place the queen
new_config = [list(element) for element in current] # new copy
new_config[queen_index][i] = QUEEN
# update invalid position in the new config
for m in xrange(n):
# col
if new_config[m][i]==DEFAULT:
new_config[m][i] = INVALID
# row
if new_config[queen_index][m]==DEFAULT:
new_config[queen_index][m] = INVALID
# diagonal - not optimized
# row = queen_index+m
# col = i+m
# if 0<=row<n and 0<=col<n and new_config[row][col]==DEFAULT: new_config[row][col] = INVALID
#
# row = queen_index-m
# col = i-m
# if 0<=row<n and 0<=col<n and new_config[row][col]==DEFAULT: new_config[row][col] = INVALID
#
# row = queen_index-m
# col = i+m
# if 0<=row<n and 0<=col<n and new_config[row][col]==DEFAULT: new_config[row][col] = INVALID
#
# row = queen_index+m
# col = i-m
# if 0<=row<n and 0<=col<n and new_config[row][col]==DEFAULT: new_config[row][col] = INVALID
# diagonal - optimized
for direction in directions:
row = queen_index+direction[0]*m
col = i+direction[1]*m
if 0<=row<n and 0<=col<n and new_config[row][col]==DEFAULT:
new_config[row][col] = INVALID
# dfs
# backtrack by using clone of the board configuration
self.backtrack(queen_index+1, new_config, result)
def transform2string(self, result):
string_result = []
for configuration in result:
current = []
for row in configuration:
row = map(lambda x: "." if x==-1 else "Q", row)
row = "".join(row)
current.append(row)
string_result.append(current)
return string_result
if __name__=="__main__":
assert Solution().solveNQueens(4)==[['.Q..', '...Q', 'Q...', '..Q.'], ['..Q.', 'Q...', '...Q', '.Q..']]