[LeetCode] 533. Lonely Pixel II 孤独的像素 II

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:

1. Row R and column C both contain exactly N black pixels.
2. 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.

Note:

1. The range of width and height of the input 2D array is [1,200].

531. Lonely Pixel I 的拓展，这题多了一个整数N，行和列可以最多含有N个黑元素。

解法：思路和531题一样，还是用一个行和一个列先统计黑元素的个数，然后在遍历一遍图，是黑元素并且行和列都等于N的就加到结果，最后返回结果。这题又多出一个条件2：要保证这N行的黑元素的位置要完全一样，可以一个一个的来比较。好的做法是把行元素转换成字符串或tuple，用一个哈希表记录行元素，然后直接比较行。

0[['W', 'B', 'W', 'B', 'B', 'W'],
1 ['W', 'W', 'B', 'B', 'B', 'W'],
2 ['W', 'B', 'W', 'B', 'B', 'W'],
3 ['W', 'B', 'W', 'W', 'B', 'W']]

Java:

public int findBlackPixel(char[][] picture, int N) {
        int m = picture.length;
        if (m == 0) return 0;
        int n = picture[0].length;
        if (n == 0) return 0;

        Map<String, Integer> map = new HashMap<>();
        int[] colCount = new int[n];

        for (int i = 0; i < m; i++) {
            String key = scanRow(picture, i, N, colCount);
            if (key.length() != 0) {
                map.put(key, map.getOrDefault(key, 0) + 1);
            }
        }

        int result = 0;
        for (String key : map.keySet()) {
            if (map.get(key) == N) {
                for (int j = 0; j < n; j++) {
                    if (key.charAt(j) == 'B' && colCount[j] == N) {
                        result += N;
                    }
                }
            }
        }

        return result;
    }

    private String scanRow(char[][] picture, int row, int target, int[] colCount) {
        int n = picture[0].length;
        int rowCount = 0;
        StringBuilder sb = new StringBuilder();

        for (int j = 0; j < n; j++) {
            if (picture[row][j] == 'B') {
                rowCount++;
                colCount[j]++;
            }
            sb.append(picture[row][j]);
        }

        if (rowCount == target) return sb.toString();
        return "";
    }　　

Java: using hashmap to store the string of rows. So that we don't need to check rule 2

public int findBlackPixel(char[][] picture, int N) {
        if (picture == null || picture.length == 0 || picture[0].length == 0) return 0;
        int m = picture.length, n = picture[0].length;
        int[] cols = new int[n];
        Map<String, Integer> map = new HashMap<>();

        for (int i = 0; i < m; i++) {
            int count = 0;
            StringBuilder sb = new StringBuilder();
            for (int j = 0; j < n; j++) {
                if (picture[i][j] == 'B') {
                    cols[j]++;
                    count++;
                }
                sb.append(picture[i][j]);
            }
            if (count == N) {
                String curRow = sb.toString();
                map.put(curRow, map.getOrDefault(curRow, 0) + 1);
            }
        }

        int res = 0;
        for (String row : map.keySet()) {
            if (map.get(row) != N) continue;
            for (int i = 0; i < n; i++) {
                if (row.charAt(i) == 'B' && cols[i] == N) {
                    res += N;
                }
            }
        }
        return res;
    }　

Python:

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

Python:　　

class Solution(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'))

Python:

class Solution(object):
    def findBlackPixel(self, picture, N):
        """
        :type picture: List[List[str]]
        :type N: int
        :rtype: int
        """
        w, h = len(picture), len(picture[0])
        rows, cols = [0] * w, [0] * h
        for x in range(w):
            for y in range(h):
                if picture[x][y] == 'B':
                    rows[x] += 1
                    cols[y] += 1

        sdict = collections.defaultdict(int)
        for idx, row in enumerate(picture):
            sdict[''.join(row)] += 1

        ans = 0
        for x in range(w):
            row = ''.join(picture[x])
            if sdict[row] != N:
                continue
            for y in range(h):
                if picture[x][y] == 'B':
                    if rows[x] == N:
                        if cols[y] == N:
                            ans += 1
        return ans　　

C++:

class Solution {
public:
    int findBlackPixel(vector<vector<char>>& picture, int N) {
        vector<int> rows = vector<int>(picture.size());
        vector<int> cols = vector<int>(picture[0].size());

        unordered_map<string, int> lookup;
        vector<string> srows;
        for (int i = 0; i < picture.size(); ++i) {
            string s;
            for (int j = 0; j < picture[0].size(); ++j) {
                if (picture[i][j] == 'B') {
                    ++rows[i];
                    ++cols[j];
                }
                s.push_back(picture[i][j]);
            }
            ++lookup[s];
            srows.emplace_back(move(s));
        }

        int result = 0;
        for (int i = 0; i < picture.size(); ++i) {
            if (rows[i] == N && lookup[srows[i]] == N) {
                for (int j = 0; j < picture[0].size(); ++j) {
                     result += picture[i][j] == 'B' && cols[j] == N;
                }
            }
        }
        return result;
    }
};

　　

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[LeetCode] 531. Lonely Pixel I 孤独的像素 I

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