For example, given array S = {-1 0 1 2 -1 -4}, A solution set is: (-1, 0, 1) (-1, -1, 2)
3 sum 题目, 首先想到的是转化为2sum的题目,时间复杂度是O(n^2),并且看要求的结果集,如果是element集合,需要先对array进行sort,在整个算法过程中,对相同的element进行deduplicate。如果是index集合,则不能进行sort,因为这样index会乱,并且不用对element deduplicate。
为了在程序运行的时候效率达到最高,需要在每一处指针移动的时候考虑到deduplicate的运算。在3sum中, 一共是3个指针在移动,i指针控制第一个元素,start 和end指针都是在2sum里面出现的指针,每次这三个指针移动的时候,都要看current element是否和下一个element相等,如果相等移动指针。
class Solution {
public:
vector<vector<int>> threeSum(vector<int>& nums) {
vector<vector<int>> rst;
//snaity check
if (nums.size() < 3) return rst;
sort(nums.begin(), nums.end());
for (int i = 0; i < nums.size()-2; i++) {
//deduplicate : 1
if (i > 0 && nums[i] == nums[i-1]) continue;
int target = 0 - nums[i];
int start = i +1;
int end = nums.size()-1;
while (start < end) {
vector<int> buf;
if (nums[start] + nums[end] > target){
end--;
//deduplicate: 2
if (nums[end] == nums[end+1]) end--;
}
else if (nums[start] + nums[end] < target){
start++;
//deduplicate: 3
if (nums[start] == nums[start-1]) start++;
}
else {
buf.push_back(nums[i]);
buf.push_back(nums[start]);
buf.push_back(nums[end]);
rst.push_back(buf);
start++;
end--;
//deduplicate: 4
while (start < end && nums[start] == nums[start-1]) start++;
while (start < end && nums[end] == nums[end+1]) end--;
}
}
}
return rst;
}
};
time complexity: O(n^2)
space complexity: O(n)
3Sum closest:
Given an array S of n integers, find three integers in S such that the sum is closest to a given number, target. Return the sum of the three integers. You may assume that each input would have exactly one solution.
For example, given array S = {-1 2 1 -4}, and target = 1. The sum that is closest to the target is 2. (-1 + 2 + 1 = 2).
这一题和求3sum closest相似,但是在每次移动指针之前要找到此时的最近差值,minimal closet。class Solution {
public:
int threeSumClosest(vector<int>& nums, int target) {
int rst = 0;
//sanity check
if (nums.size() < 3) return 0;
sort(nums.begin(), nums.end());
int closest = INT_MAX;
for (int i = 0; i < nums.size()-2; i++) {
//deduplicate1
if (i > 0 && nums[i] == nums[i-1]) continue;
int newtarget = target-nums[i];
int start = i+1;
int end = nums.size()-1;
while (start < end) {
if (nums[start] + nums[end] == newtarget) return target;
if (abs(nums[start] + nums[end] + nums[i] - target) < closest) {
closest = abs(nums[start] + nums[end] + nums[i] - target);
rst = nums[start] + nums[end] + nums[i];
}
if (nums[start] + nums[end] < newtarget) {
start++;
if (nums[start] == nums[start-1]) start++;
} else {
end--;
if (nums[end] == nums[end+1]) end--;
}
}
}
return rst;
}
};
time complexity: O (n^2)
space complexity: O(1)
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