题目描述
矩阵对角线 是一条从矩阵最上面行或者最左侧列中的某个元素开始的对角线,沿右下方向一直到矩阵末尾的元素。例如,矩阵 mat
有 6
行 3
列,从 mat[2][0]
开始的 矩阵对角线 将会经过 mat[2][0]
、mat[3][1]
和 mat[4][2]
。
给你一个 m * n
的整数矩阵 mat
,请你将同一条 矩阵对角线 上的元素按升序排序后,返回排好序的矩阵。
示例 1:
输入:mat = [[3,3,1,1],[2,2,1,2],[1,1,1,2]]
输出:[[1,1,1,1],[1,2,2,2],[1,2,3,3]]
示例 2:
输入:mat = [[11,25,66,1,69,7],[23,55,17,45,15,52],[75,31,36,44,58,8],[22,27,33,25,68,4],[84,28,14,11,5,50]]
输出:[[5,17,4,1,52,7],[11,11,25,45,8,69],[14,23,25,44,58,15],[22,27,31,36,50,66],[84,28,75,33,55,68]]
提示:
m == mat.length
n == mat[i].length
1 <= m, n <= 100
1 <= mat[i][j] <= 100
解法
方法一:排序
我们可以将矩阵中的每条对角线看作一个数组,然后对这些数组进行排序,最后再将排序后的元素填回原矩阵中。
具体地,我们记矩阵的行数为 $m$,列数为 $n$。由于同一条对角线上的任意两个元素 $(i_1, j_1)$ 和 $(i_2, j_2)$ 满足 $j_1 - i_1 = j_2 - i_2$,我们可以根据 $j - i$ 的值来确定每条对角线。为了保证值为正数,我们加上一个偏移量 $m$,即 $m - i + j$。
最后,我们将每条对角线上的元素排序后填回原矩阵中即可。
时间复杂度 $O(m \times n \times \log \min(m, n))$,空间复杂度 $O(m \times n)$。其中 $m$ 和 $n$ 分别是矩阵的行数和列数。
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13 | class Solution:
def diagonalSort(self, mat: List[List[int]]) -> List[List[int]]:
m, n = len(mat), len(mat[0])
g = [[] for _ in range(m + n)]
for i, row in enumerate(mat):
for j, x in enumerate(row):
g[m - i + j].append(x)
for e in g:
e.sort(reverse=True)
for i in range(m):
for j in range(n):
mat[i][j] = g[m - i + j].pop()
return mat
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21 | class Solution {
public int[][] diagonalSort(int[][] mat) {
int m = mat.length, n = mat[0].length;
List<Integer>[] g = new List[m + n];
Arrays.setAll(g, k -> new ArrayList<>());
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
g[m - i + j].add(mat[i][j]);
}
}
for (var e : g) {
Collections.sort(e, (a, b) -> b - a);
}
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
mat[i][j] = g[m - i + j].removeLast();
}
}
return mat;
}
}
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22 | class Solution {
public:
vector<vector<int>> diagonalSort(vector<vector<int>>& mat) {
int m = mat.size(), n = mat[0].size();
vector<int> g[m + n];
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
g[m - i + j].push_back(mat[i][j]);
}
}
for (auto& e : g) {
sort(e.rbegin(), e.rend());
}
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
mat[i][j] = g[m - i + j].back();
g[m - i + j].pop_back();
}
}
return mat;
}
};
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20 | func diagonalSort(mat [][]int) [][]int {
m, n := len(mat), len(mat[0])
g := make([][]int, m+n)
for i, row := range mat {
for j, x := range row {
g[m-i+j] = append(g[m-i+j], x)
}
}
for _, e := range g {
sort.Sort(sort.Reverse(sort.IntSlice(e)))
}
for i, row := range mat {
for j := range row {
k := len(g[m-i+j])
mat[i][j] = g[m-i+j][k-1]
g[m-i+j] = g[m-i+j][:k-1]
}
}
return mat
}
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18 | function diagonalSort(mat: number[][]): number[][] {
const [m, n] = [mat.length, mat[0].length];
const g: number[][] = Array.from({ length: m + n }, () => []);
for (let i = 0; i < m; ++i) {
for (let j = 0; j < n; ++j) {
g[m - i + j].push(mat[i][j]);
}
}
for (const e of g) {
e.sort((a, b) => b - a);
}
for (let i = 0; i < m; ++i) {
for (let j = 0; j < n; ++j) {
mat[i][j] = g[m - i + j].pop()!;
}
}
return mat;
}
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21 | impl Solution {
pub fn diagonal_sort(mut mat: Vec<Vec<i32>>) -> Vec<Vec<i32>> {
let m = mat.len();
let n = mat[0].len();
let mut g: Vec<Vec<i32>> = vec![vec![]; m + n];
for i in 0..m {
for j in 0..n {
g[m - i + j].push(mat[i][j]);
}
}
for e in &mut g {
e.sort_by(|a, b| b.cmp(a));
}
for i in 0..m {
for j in 0..n {
mat[i][j] = g[m - i + j].pop().unwrap();
}
}
mat
}
}
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26 | public class Solution {
public int[][] DiagonalSort(int[][] mat) {
int m = mat.Length;
int n = mat[0].Length;
List<List<int>> g = new List<List<int>>();
for (int i = 0; i < m + n; i++) {
g.Add(new List<int>());
}
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
g[m - i + j].Add(mat[i][j]);
}
}
foreach (var e in g) {
e.Sort((a, b) => b.CompareTo(a));
}
for (int i = 0; i < m; i++) {
for (int j = 0; j < n; j++) {
int val = g[m - i + j][g[m - i + j].Count - 1];
g[m - i + j].RemoveAt(g[m - i + j].Count - 1);
mat[i][j] = val;
}
}
return mat;
}
}
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