LeetCode Day28 Search for a Range
阿新 • • 發佈:2018-11-06
class Solution {
public:
vector<int> searchRange(vector<int>& nums, int target) {
int left=0,right=nums.size()-1,mid;
while(left<=right){
mid=(left+right)/2;
if(target==nums[mid]){
int i=mid,j=mid;
while (target==nums[i-1]&&i>0) i--;
while(target==nums[j+1]&&j<nums.size()-1) j++;
return {i,j};
}
else if(target>nums[mid]) left=mid+1;
else right=mid-1;
}
return {-1,-1};
}
};
上面的演算法不是嚴格意義上的O(logn)的演算法,因為在最壞的情況下會變成O(n),比如當數組裡的數全是目標值的話,從中間向兩邊找邊界就會一直遍歷完整個陣列,那麼我們下面來看一種真正意義上的O(logn)的演算法,使用兩次二分查詢法,第一次找到左邊界,第二次呼叫找到右邊界即可,具體程式碼如下:
class Solution {
public:
vector<int> searchRange(vector<int>& nums, int target) {
if(nums.empty()) return {-1,-1};
vector<int> res(2, -1);
int left = 0, right = nums.size() - 1;
while (left < right) {
int mid = left + (right - left) / 2;
if (nums[mid] < target) left = mid + 1;
else right = mid;
}
if (nums[right] != target) return res;
res[0] = right;
right = nums.size()-1;
while (left < right) {
int mid =(right + left) / 2+1;//整型除法只會向下取整,現改為向上取整,保證中間值一直>left,可以一直向右檢查
if (nums[mid] == target) left = mid;//只存在>或==的情況
else right= mid-1;
}
res[1] = left;
return res;
}
};