给你两个 m x n
的二进制矩阵 grid1
和 grid2
,它们只包含 0
(表示水域)和 1
(表示陆地)。一个 岛屿 是由 四个方向 (水平或者竖直)上相邻的 1
组成的区域。任何矩阵以外的区域都视为水域。
如果 grid2
的一个岛屿,被 grid1
的一个岛屿 完全 包含,也就是说 grid2
中该岛屿的每一个格子都被 grid1
中同一个岛屿完全包含,那么我们称 grid2
中的这个岛屿为 子岛屿 。
请你返回 grid2
中 子岛屿 的 数目 。
示例 1:
输入:grid1 = [[1,1,1,0,0],[0,1,1,1,1],[0,0,0,0,0],[1,0,0,0,0],[1,1,0,1,1]], grid2 = [[1,1,1,0,0],[0,0,1,1,1],[0,1,0,0,0],[1,0,1,1,0],[0,1,0,1,0]] 输出:3 解释:如上图所示,左边为 grid1 ,右边为 grid2 。 grid2 中标红的 1 区域是子岛屿,总共有 3 个子岛屿。
示例 2:
输入:grid1 = [[1,0,1,0,1],[1,1,1,1,1],[0,0,0,0,0],[1,1,1,1,1],[1,0,1,0,1]], grid2 = [[0,0,0,0,0],[1,1,1,1,1],[0,1,0,1,0],[0,1,0,1,0],[1,0,0,0,1]] 输出:2 解释:如上图所示,左边为 grid1 ,右边为 grid2 。 grid2 中标红的 1 区域是子岛屿,总共有 2 个子岛屿。
提示:
m == grid1.length == grid2.length
n == grid1[i].length == grid2[i].length
1 <= m, n <= 500
grid1[i][j]
和grid2[i][j]
都要么是0
要么是1
。
BFS、DFS 或者并查集。
BFS - Flood Fill 算法:
class Solution:
def countSubIslands(self, grid1: List[List[int]], grid2: List[List[int]]) -> int:
def bfs(i, j):
q = deque([(i, j)])
grid2[i][j] = 0
ans = True
while q:
i, j = q.popleft()
if grid1[i][j] == 0:
ans = False
for a, b in [[0, -1], [0, 1], [1, 0], [-1, 0]]:
x, y = i + a, j + b
if 0 <= x < m and 0 <= y < n and grid2[x][y]:
q.append((x, y))
grid2[x][y] = 0
return ans
m, n = len(grid1), len(grid1[0])
return sum(grid2[i][j] and bfs(i, j) for i in range(m) for j in range(n))
DFS:
class Solution:
def countSubIslands(self, grid1: List[List[int]], grid2: List[List[int]]) -> int:
def dfs(i, j):
ans = grid1[i][j] == 1
grid2[i][j] = 0
for a, b in [[0, -1], [0, 1], [-1, 0], [1, 0]]:
x, y = i + a, j + b
if 0 <= x < m and 0 <= y < n and grid2[x][y] == 1 and not dfs(x, y):
ans = False
return ans
m, n = len(grid1), len(grid1[0])
return sum(grid2[i][j] == 1 and dfs(i, j) for i in range(m) for j in range(n))
并查集:
class Solution:
def countSubIslands(self, grid1: List[List[int]], grid2: List[List[int]]) -> int:
def find(x):
if p[x] != x:
p[x] = find(p[x])
return p[x]
m, n = len(grid1), len(grid1[0])
p = list(range(m * n))
for i in range(m):
for j in range(n):
if grid2[i][j]:
for a, b in [[0, 1], [1, 0]]:
x, y = i + a, j + b
if x < m and y < n and grid2[x][y]:
p[find(x * n + y)] = find(i * n + j)
s = [0] * (m * n)
for i in range(m):
for j in range(n):
if grid2[i][j]:
s[find(i * n + j)] = 1
for i in range(m):
for j in range(n):
root = find(i * n + j)
if s[root] and grid1[i][j] == 0:
s[root] = 0
return sum(s)
BFS - Flood Fill 算法:
class Solution {
public int countSubIslands(int[][] grid1, int[][] grid2) {
int m = grid1.length;
int n = grid1[0].length;
int ans = 0;
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (grid2[i][j] == 1 && bfs(i, j, m, n, grid1, grid2)) {
++ans;
}
}
}
return ans;
}
private boolean bfs(int i, int j, int m, int n, int[][] grid1, int[][] grid2) {
Queue<int[]> q = new ArrayDeque<>();
grid2[i][j] = 0;
q.offer(new int[]{i, j});
boolean ans = true;
int[] dirs = {-1, 0, 1, 0, -1};
while (!q.isEmpty()) {
int[] p = q.poll();
i = p[0];
j = p[1];
if (grid1[i][j] == 0) {
ans = false;
}
for (int k = 0; k < 4; ++k) {
int x = i + dirs[k];
int y = j + dirs[k + 1];
if (x >= 0 && x < m && y >= 0 && y < n && grid2[x][y] == 1) {
q.offer(new int[]{x, y});
grid2[x][y] = 0;
}
}
}
return ans;
}
}
DFS:
class Solution {
public int countSubIslands(int[][] grid1, int[][] grid2) {
int m = grid1.length;
int n = grid1[0].length;
int ans = 0;
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (grid2[i][j] == 1 && dfs(i, j, m, n, grid1, grid2)) {
++ans;
}
}
}
return ans;
}
private boolean dfs(int i, int j, int m, int n, int[][] grid1, int[][] grid2) {
boolean ans = grid1[i][j] == 1;
grid2[i][j] = 0;
int[] dirs = {-1, 0, 1, 0, -1};
for (int k = 0; k < 4; ++k) {
int x = i + dirs[k];
int y = j + dirs[k + 1];
if (x >= 0 && x < m && y >= 0 && y < n && grid2[x][y] == 1 && !dfs(x, y, m, n, grid1, grid2)) {
ans = false;
}
}
return ans;
}
}
并查集:
class Solution {
private int[] p;
public int countSubIslands(int[][] grid1, int[][] grid2) {
int m = grid1.length;
int n = grid1[0].length;
p = new int[m * n];
for (int i = 0; i < p.length; ++i) {
p[i] = i;
}
int[] dirs = {1, 0, 1};
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (grid2[i][j] == 1) {
for (int k = 0; k < 2; ++k) {
int x = i + dirs[k];
int y = j + dirs[k + 1];
if (x < m && y < n && grid2[x][y] == 1) {
p[find(x * n + y)] = find(i * n + j);
}
}
}
}
}
int[] s = new int[m * n];
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (grid2[i][j] == 1) {
s[find(i * n + j)] = 1;
}
}
}
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
int root = find(i * n + j);
if (s[root] == 1 && grid1[i][j] == 0) {
s[root] = 0;
}
}
}
int ans = 0;
for (int i = 0; i < s.length; ++i) {
ans += s[i];
}
return ans;
}
private int find(int x) {
if (p[x] != x) {
p[x] = find(p[x]);
}
return p[x];
}
}
function countSubIslands(grid1: number[][], grid2: number[][]): number {
let m = grid1.length,
n = grid1[0].length;
let ans = 0;
for (let i = 0; i < m; ++i) {
for (let j = 0; j < n; ++j) {
if (grid2[i][j] == 1 && dfs(grid1, grid2, i, j)) {
++ans;
}
}
}
return ans;
}
function dfs(
grid1: number[][],
grid2: number[][],
i: number,
j: number,
): boolean {
let m = grid1.length,
n = grid1[0].length;
let ans = true;
if (grid1[i][j] == 0) {
ans = false;
}
grid2[i][j] = 0;
for (let [dx, dy] of [
[0, 1],
[0, -1],
[1, 0],
[-1, 0],
]) {
let x = i + dx,
y = j + dy;
if (x < 0 || x > m - 1 || y < 0 || y > n - 1 || grid2[x][y] == 0) {
continue;
}
if (!dfs(grid1, grid2, x, y)) {
ans = false;
}
}
return ans;
}
BFS - Flood Fill 算法:
class Solution {
public:
int countSubIslands(vector<vector<int>>& grid1, vector<vector<int>>& grid2) {
int m = grid1.size();
int n = grid1[0].size();
int ans = 0;
for (int i = 0; i < m; ++i)
for (int j = 0; j < n; ++j)
ans += (grid2[i][j] == 1 && bfs(i, j, m, n, grid1, grid2));
return ans;
}
bool bfs(int i, int j, int m, int n, vector<vector<int>>& grid1, vector<vector<int>>& grid2) {
queue<pair<int, int>> q;
q.push({i, j});
grid2[i][j] = 0;
bool ans = true;
vector<int> dirs = {-1, 0, 1, 0, -1};
while (!q.empty()) {
auto p = q.front();
q.pop();
i = p.first;
j = p.second;
if (grid1[i][j] == 0) ans = false;
for (int k = 0; k < 4; ++k) {
int x = i + dirs[k], y = j + dirs[k + 1];
if (x >= 0 && x < m && y >= 0 && y < n && grid2[x][y]) {
q.push({x, y});
grid2[x][y] = 0;
}
}
}
return ans;
}
};
DFS:
class Solution {
public:
int countSubIslands(vector<vector<int>>& grid1, vector<vector<int>>& grid2) {
int m = grid1.size();
int n = grid1[0].size();
int ans = 0;
for (int i = 0; i < m; ++i)
for (int j = 0; j < n; ++j)
if (grid2[i][j] == 1 && dfs(i, j, m, n, grid1, grid2))
++ans;
return ans;
}
bool dfs(int i, int j, int m, int n, vector<vector<int>>& grid1, vector<vector<int>>& grid2) {
bool ans = grid1[i][j];
grid2[i][j] = 0;
vector<int> dirs = {-1, 0, 1, 0, -1};
for (int k = 0; k < 4; ++k)
{
int x = i + dirs[k], y = j + dirs[k + 1];
if (x >= 0 && x < m && y >= 0 && y < n && grid2[x][y] && !dfs(x, y, m, n, grid1, grid2))
ans = false;
}
return ans;
}
};
BFS - Flood Fill 算法:
func countSubIslands(grid1 [][]int, grid2 [][]int) int {
m, n := len(grid1), len(grid1[0])
ans := 0
bfs := func(i, j int) bool {
q := [][]int{{i, j}}
grid2[i][j] = 0
res := true
dirs := []int{-1, 0, 1, 0, -1}
for len(q) > 0 {
i, j = q[0][0], q[0][1]
if grid1[i][j] == 0 {
res = false
}
q = q[1:]
for k := 0; k < 4; k++ {
x, y := i+dirs[k], j+dirs[k+1]
if x >= 0 && x < m && y >= 0 && y < n && grid2[x][y] == 1 {
q = append(q, []int{x, y})
grid2[x][y] = 0
}
}
}
return res
}
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
if grid2[i][j] == 1 && bfs(i, j) {
ans++
}
}
}
return ans
}
DFS:
func countSubIslands(grid1 [][]int, grid2 [][]int) int {
m, n := len(grid1), len(grid1[0])
ans := 0
var dfs func(i, j int) bool
dfs = func(i, j int) bool {
res := grid1[i][j] == 1
grid2[i][j] = 0
dirs := []int{-1, 0, 1, 0, -1}
for k := 0; k < 4; k++ {
x, y := i+dirs[k], j+dirs[k+1]
if x >= 0 && x < m && y >= 0 && y < n && grid2[x][y] == 1 && !dfs(x, y) {
res = false
}
}
return res
}
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
if grid2[i][j] == 1 && dfs(i, j) {
ans++
}
}
}
return ans
}