题目

Write an efficient algorithm that searches for a value in an m x n matrix. This matrix has the following properties:

  • Integers in each row are sorted from left to right.
  • The first integer of each row is greater than the last integer of the previous row.

Example 1:

  1. Input:
  2. matrix = [
  3. [1, 3, 5, 7],
  4. [10, 11, 16, 20],
  5. [23, 30, 34, 50]
  6. ]
  7. target = 3
  8. Output: true

Example 2:

  1. Input:
  2. matrix = [
  3. [1, 3, 5, 7],
  4. [10, 11, 16, 20],
  5. [23, 30, 34, 50]
  6. ]
  7. target = 13
  8. Output: false

题意

判断在一个行元素递增、列元素也递增的矩阵中能否找到目标值。

思路

有序序列中找值那肯定是要用二分法,不过可以有两种二分查找的方式:

  1. 先一个二分找到目标值应该在的行,再一个二分在该行中查找目标值。
  2. 由于矩阵的特殊性(行递增,且下一行元素都比上一行元素大),可以将矩阵直接当成长度为 m*n 的一维数组处理。
  3. 分治法,从左下角开始搜索,target更大则向右走,target更小则向上走(该题里实际就是暴力遍历)。

代码实现

Java

矩阵二分

  1. class Solution {
  2. public boolean searchMatrix(int[][] matrix, int target) {
  3. int m = matrix.length;
  4. if (m == 0) return false;
  5. int n = matrix[0].length;
  6. if (n == 0) return false;
  7. if (target < matrix[0][0]) {
  8. return false;
  9. }
  10. // 先找行
  11. int left = 0, right = m - 1;
  12. while (left <= right) {
  13. int mid = (left + right) / 2;
  14. if (target < matrix[mid][0]) {
  15. right = mid - 1;
  16. } else if (target > matrix[mid][0]) {
  17. left = mid + 1;
  18. } else {
  19. return true;
  20. }
  21. }
  22. int r = left - 1;
  23. // 再找列
  24. left = 0;
  25. right = n - 1;
  26. while (left <= right) {
  27. int mid = (left + right) / 2;
  28. if (target < matrix[r][mid]) {
  29. right = mid - 1;
  30. } else if (target > matrix[r][mid]) {
  31. left = mid + 1;
  32. } else {
  33. return true;
  34. }
  35. }
  36. return false;
  37. }
  38. }

一维二分

  1. class Solution {
  2. public boolean searchMatrix(int[][] matrix, int target) {
  3. int m = matrix.length;
  4. if (m == 0) return false;
  5. int n = matrix[0].length;
  6. if (n == 0) return false;
  7. int left = 0, right = m * n - 1;
  8. while (left <= right) {
  9. int mid = (left + right) / 2;
  10. // 一维坐标转换为二维坐标
  11. int x = mid / n;
  12. int y = mid % n;
  13. if (target < matrix[x][y]) {
  14. right = mid - 1;
  15. } else if (target > matrix[x][y]) {
  16. left = mid + 1;
  17. } else {
  18. return true;
  19. }
  20. }
  21. return false;
  22. }
  23. }

JavaScript

矩阵二分

  1. /**
  2. * @param {number[][]} matrix
  3. * @param {number} target
  4. * @return {boolean}
  5. */
  6. var searchMatrix = function (matrix, target) {
  7. if (matrix.length === 0 || matrix[0].length === 0) {
  8. return false
  9. }
  10. let m = matrix.length
  11. let n = matrix[0].length
  12. let left = 0
  13. let right = m - 1
  14. while (left <= right) {
  15. let mid = Math.trunc((right - left) / 2) + left
  16. if (matrix[mid][0] < target) {
  17. left = mid + 1
  18. } else if (matrix[mid][0] > target) {
  19. right = mid - 1
  20. } else {
  21. return true
  22. }
  23. }
  24. if (right >= 0) {
  25. let row = right
  26. left = 0
  27. right = n - 1
  28. while (left <= right) {
  29. let mid = Math.trunc((right - left) / 2) + left
  30. if (matrix[row][mid] < target) {
  31. left = mid + 1
  32. } else if (matrix[row][mid] > target) {
  33. right = mid - 1
  34. } else {
  35. return true
  36. }
  37. }
  38. }
  39. return false
  40. }

分治法

  1. /**
  2. * @param {number[][]} matrix
  3. * @param {number} target
  4. * @return {boolean}
  5. */
  6. var searchMatrix = function (matrix, target) {
  7. if (matrix.length === 0 || matrix[0].length === 0) {
  8. return false
  9. }
  10. let m = matrix.length, n = matrix[0].length
  11. let i = m - 1, j = 0
  12. while (i >= 0 && j < n) {
  13. if (matrix[i][j] < target) {
  14. j++
  15. } else if (matrix[i][j] > target) {
  16. i--
  17. } else {
  18. return true
  19. }
  20. }
  21. return false
  22. }