comments | difficulty | edit_url | tags | ||
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true |
中等 |
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给你一个按照非递减顺序排列的整数数组 nums
,和一个目标值 target
。请你找出给定目标值在数组中的开始位置和结束位置。
如果数组中不存在目标值 target
,返回 [-1, -1]
。
你必须设计并实现时间复杂度为 O(log n)
的算法解决此问题。
示例 1:
输入:nums = [5,7,7,8,8,10]
, target = 8
输出:[3,4]
示例 2:
输入:nums = [5,7,7,8,8,10]
, target = 6
输出:[-1,-1]
示例 3:
输入:nums = [], target = 0 输出:[-1,-1]
提示:
0 <= nums.length <= 105
-109 <= nums[i] <= 109
nums
是一个非递减数组-109 <= target <= 109
我们可以进行两次二分查找,分别查找出左边界和右边界。
时间复杂度
以下是二分查找的两个通用模板:
模板 1:
boolean check(int x) {
}
int search(int left, int right) {
while (left < right) {
int mid = (left + right) >> 1;
if (check(mid)) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
}
模板 2:
boolean check(int x) {
}
int search(int left, int right) {
while (left < right) {
int mid = (left + right + 1) >> 1;
if (check(mid)) {
left = mid;
} else {
right = mid - 1;
}
}
return left;
}
做二分题目时,可以按照以下套路:
- 写出循环条件
$left < right$ ; - 循环体内,不妨先写
$mid = \lfloor \frac{left + right}{2} \rfloor$ ; - 根据具体题目,实现
$check()$ 函数(有时很简单的逻辑,可以不定义$check$ ),想一下究竟要用$right = mid$ (模板$1$ ) 还是$left = mid$ (模板$2$ ); - 如果$right = mid$ ,那么写出 else 语句$left = mid + 1$ ,并且不需要更改 mid 的计算,即保持$mid = \lfloor \frac{left + right}{2} \rfloor$ ; - 如果$left = mid$ ,那么写出 else 语句$right = mid - 1$ ,并且在$mid$ 计算时补充 +1,即$mid = \lfloor \frac{left + right + 1}{2} \rfloor$ ; - 循环结束时,
$left$ 与$right$ 相等。
注意,这两个模板的优点是始终保持答案位于二分区间内,二分结束条件对应的值恰好在答案所处的位置。 对于可能无解的情况,只要判断二分结束后的
class Solution:
def searchRange(self, nums: List[int], target: int) -> List[int]:
l = bisect_left(nums, target)
r = bisect_left(nums, target + 1)
return [-1, -1] if l == r else [l, r - 1]
class Solution {
public int[] searchRange(int[] nums, int target) {
int l = search(nums, target);
int r = search(nums, target + 1);
return l == r ? new int[] {-1, -1} : new int[] {l, r - 1};
}
private int search(int[] nums, int x) {
int left = 0, right = nums.length;
while (left < right) {
int mid = (left + right) >>> 1;
if (nums[mid] >= x) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
}
}
class Solution {
public:
vector<int> searchRange(vector<int>& nums, int target) {
int l = lower_bound(nums.begin(), nums.end(), target) - nums.begin();
int r = lower_bound(nums.begin(), nums.end(), target + 1) - nums.begin();
if (l == r) return {-1, -1};
return {l, r - 1};
}
};
func searchRange(nums []int, target int) []int {
l := sort.SearchInts(nums, target)
r := sort.SearchInts(nums, target+1)
if l == r {
return []int{-1, -1}
}
return []int{l, r - 1}
}
function searchRange(nums: number[], target: number): number[] {
const search = (x: number): number => {
let [left, right] = [0, nums.length];
while (left < right) {
const mid = (left + right) >> 1;
if (nums[mid] >= x) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
};
const l = search(target);
const r = search(target + 1);
return l === r ? [-1, -1] : [l, r - 1];
}
impl Solution {
pub fn search_range(nums: Vec<i32>, target: i32) -> Vec<i32> {
let n = nums.len();
let search = |x| {
let mut left = 0;
let mut right = n;
while left < right {
let mid = left + (right - left) / 2;
if nums[mid] < x {
left = mid + 1;
} else {
right = mid;
}
}
left
};
let l = search(target);
let r = search(target + 1);
if l == r {
return vec![-1, -1];
}
vec![l as i32, (r - 1) as i32]
}
}
/**
* @param {number[]} nums
* @param {number} target
* @return {number[]}
*/
var searchRange = function (nums, target) {
function search(x) {
let left = 0,
right = nums.length;
while (left < right) {
const mid = (left + right) >> 1;
if (nums[mid] >= x) {
right = mid;
} else {
left = mid + 1;
}
}
return left;
}
const l = search(target);
const r = search(target + 1);
return l == r ? [-1, -1] : [l, r - 1];
};
class Solution {
/**
* @param integer[] $nums
* @param integer $target
* @return integer[]
*/
function searchRange($nums, $target) {
$min = -1;
$max = -1;
foreach ($nums as $key => $value) {
if ($value == $target) {
if ($min == -1) {
$min = $key;
}
if ($key > $max) {
$max = $key;
}
}
}
return [$min, $max];
}
}