lonely-pixel-ii.py

# Given a picture consisting of black and white pixels, and a positive integer N, 
# find the number of black pixels located at some specific row R and column C that align with all the following rules:

# Row R and column C both contain exactly N black pixels.
# For all rows that have a black pixel at column C, they should be exactly the same as row R
# The picture is represented by a 2D char array consisting of 'B' and 'W', which means black and white pixels respectively.

# Example:
# Input:                                            
#[['W', 'B', 'W', 'B', 'B', 'W'],    
# ['W', 'B', 'W', 'B', 'B', 'W'],    
# ['W', 'B', 'W', 'B', 'B', 'W'],    
# ['W', 'W', 'B', 'W', 'B', 'W']] 

# N = 3
# Output: 6
# Explanation: All the bold 'B' are the black pixels we need (all 'B's at column 1 and 3).
#         0    1    2    3    4    5         column index                                            
# 0    [['W', 'B', 'W', 'B', 'B', 'W'],    
# 1     ['W', 'B', 'W', 'B', 'B', 'W'],    
# 2     ['W', 'B', 'W', 'B', 'B', 'W'],    
# 3     ['W', 'W', 'B', 'W', 'B', 'W']]    
# row index

# Take 'B' at row R = 0 and column C = 1 as an example:
# Rule 1, row R = 0 and column C = 1 both have exactly N = 3 black pixels. 
# Rule 2, the rows have black pixel at column C = 1 are row 0, row 1 and row 2. They are exactly the same as row R = 0.

# Time:  O(m * n)
# Space: O(m * n)

class Solution(object):
    def findBlackPixel(self, picture, N):
        """
        :type picture: List[List[str]]
        :type N: int
        :rtype: int
        """
        rows, cols = [0] * len(picture),  [0] * len(picture[0])
        lookup = collections.defaultdict(int)
        for i in xrange(len(picture)):
            for j in xrange(len(picture[0])):
                if picture[i][j] == 'B':
                    rows[i] += 1
                    cols[j] += 1
            lookup[tuple(picture[i])] += 1

        result = 0
        for i in xrange(len(picture)):
            if rows[i] == N and lookup[tuple(picture[i])] == N:
                for j in xrange(len(picture[0])):
                     result += picture[i][j] == 'B' and cols[j] == N
        return result


class Solution2(object):
    def findBlackPixel(self, picture, N):
        """
        :type picture: List[List[str]]
        :type N: int
        :rtype: int
        """
        lookup = collections.Counter(map(tuple, picture))
        cols = [col.count('B') for col in zip(*picture)]
        return sum(N * zip(row, cols).count(('B', N)) \
                   for row, cnt in lookup.iteritems() \
                   if cnt == N == row.count('B'))