LeeCode数组问题:二分查找
LeeCode 704 二分查找
题目描述:
给定一个
n
个元素有序的(升序)整型数组nums
和一个目标值target
,写一个函数搜索nums
中的target
,如果目标值存在返回下标,否则返回-1
标签: 数组、二分查找
建立模型:
该题为一个简单的二分查找实现,注意边界处理即可。
编码实现
/* Java实现 */
class Solution {
public int search(int[] nums, int target) {
if (nums.length == 0 || target < nums[0] || target > nums[nums.length - 1]) {
return -1;
}
int low = 0, high = nums.length - 1;
while (low <= high) {
int mid = low + (high - low) / 2;
if (nums[mid] < target) {
low = mid + 1;
}
else if (nums[mid] > target) {
high = mid - 1;
}
else {
return mid;
}
}
return -1; //未搜索到则不存在返回-1
}
}
# Python实现
class Solution:
def search(self, nums: List[int], target: int) -> int:
if len(nums) == 0 or target < nums[0] or target > nums[len(nums) - 1]:
return -1
low, high = 0, len(nums) - 1
while low <= high:
mid = low + (high - low) // 2
if nums[mid] < target:
low = mid + 1
elif nums[mid] > target:
high = mid - 1
else:
return mid
return -1
LeeCode 35 插入搜索位置
题目描述:
给定一个排序数组和一个目标值,在数组中找到目标值,并返回其索引。如果目标值不存在于数组中,返回它将会被按顺序插入的位置。
标签:数组、二分查找
建立模型:
该题也是一个简单二分查找模型,只是对返回值稍做变化。
编码实现
/* Java实现 */
class Solution {
public int searchInsert(int[] nums, int target) {
if (nums.length == 0 || target < nums[0]) {
return 0;
}
if (target > nums[nums.length - 1]) {
return nums.length;
}
int low = 0, high = nums.length - 1;
while (low <= high) {
int mid = low + (high - low) / 2;
if (nums[mid] < target) {
low = mid + 1;
}
else if (nums[mid] > target) {
high = mid - 1;
}
else {
return mid;
}
}
return low;
}
}
# Python实现
class Solution:
def searchInsert(self, nums: List[int], target: int) -> int:
if not nums or target < nums[0]:
return 0
if target > nums[len(nums) - 1]:
return len(nums)
low, high = 0, len(nums) - 1
while low <= high:
mid = low + (high - low) // 2
if nums[mid] < target:
low = mid + 1
elif nums[mid] > target:
high = mid - 1
else:
return mid
return low
LeeCode 34 查找元素的第一个和最后一个位置
题目描述:
给定一个按照升序排列的整数数组
nums
,和一个目标值target
。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]
。
标签:数组、二分查找
建立模型:
- 与其他二分查找的不同之处在目标值可能存在多个,单纯的二分查找无法确定目标值的位置。
- 在执行
binarySearchLast
时,需注意对mid
的变化。
编码实现
/* Java实现 */
class Solution {
public int[] searchRange(int[] nums, int target) {
if (nums.length == 0 || target < nums[0] or target > nums[nums.length - 1]) {
return new int[] {-1, -1};
}
return new int[]{binarySearchFirst(nums, target), binarySearchLast(nums, target)};
}
public int binarySearchFirst(int[] nums, int target) {
int left = 0, right = nums.length - 1;
while (left < right) {
int mid = left + (right - left) / 2;
if (nums[mid] >= target) {
right = mid;
}
else {
left = mid + 1;
}
}
if (nums[left] == target) {
return left;
}
return -1;
}
public int binarySearchLast(int[] nums, int target) {
int left = 0, right = nums.length - 1;
while (left < right) {
int mid = left + (right - left + 1) / 2; // +1实现mid的右移, 避免进入死循环
if (nums[mid] <= target) {
left = mid;
}
else {
right = mid - 1;
}
}
if (nums[left] == target) {
return left;
}
return -1;
}
}
# Python实现
class Solution:
def searchRange(self, nums: List[int], target: int) -> List[int]:
if target < nums[0] or target > nums[len(nums) - 1]:
return [-1, -1]
return [self.binarySearchFirst(nums, target), self.binarySearchLast(nums, target)]
def binarySearchFirst(self, nums: List[int], target: int) -> int:
low, high = 0, len(nums) - 1
while low < high:
mid = low + (high - low) // 2 # 在偶数个数时取左边的为mid
if nums[mid] >= target:
high = mid
else:
low = mid + 1
return low if nums[low] == target else -1
def binarySearchLast(self, nums: List[int], target: int) -> int:
low, high = 0, len(nums) - 1
while low < high:
mid = low + (high - low + 1) // 2 # 在偶数个数时取右边的为mid
if nums[mid] <= target:
low = mid
else:
high = mid - 1
return low if nums[low] == target else -1