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542_01Matrix.py
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542_01Matrix.py
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from collections import deque
class Solution(object):
def updateMatrix(self, matrix):
"""
:type matrix: List[List[int]]
:rtype: List[List[int]]
"""
# BFS approach
"""
From 0 in each cell, we don't need to update the matrix
With nested for loop iteration, when we find cell containing 1, we can apply BFS on those cells
"""
R, C = len(matrix), len(matrix[0])
queue = deque()
visited = set()
# Instead invoking BFS for each 1 cell, flip the problem to start from 0 to get to closest 1
# => This allows to run a single BFS that emerges from different places, all 0 in the matrix
# => so first all the 0 and distance in the queue and append to visited
# if not visited, they are all 1 cell
for r, row in enumerate(matrix):
for c, val in enumerate(row):
if val == 0:
queue.append((r, c, 0))
visited.add((r, c))
while queue:
r, c, d = queue.popleft()
# in four directions
for nr, nc in ((r-1,c), (r,c-1), (r+1,c), (r,c+1)):
# boundary check and when on 1 cell and if its not visited
if 0 <= nr < R and 0 <= nc < C and matrix[nr][nc] == 1 and (nr, nc) not in visited:
matrix[nr][nc] = d + 1
queue.append((nr, nc, d+1))
visited.add((nr, nc))
return matrix
# O(r, c) / O(r, c)
if __name__ == '__main__':
input = [
[0,0,0],
[0,1,0],
[1,1,1]
]
print(Solution().updateMatrix(input))