# 3 Sum Closest
### Source
- leetcode: [3Sum Closest | LeetCode OJ](https://leetcode.com/problems/3sum-closest/)
- lintcode: [(59) 3 Sum Closest](http://www.lintcode.com/en/problem/3-sum-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).
~~~
### 题解1 - 排序 + 2 Sum + 两根指针 + 优化过滤
和 3 Sum 的思路接近,首先对原数组排序,随后将3 Sum 的题拆解为『1 Sum + 2 Sum』的题,对于 Closest 的题使用两根指针而不是哈希表的方法较为方便。对于有序数组来说,在查找 Cloest 的值时其实是有较大的优化空间的。
### Python
~~~
class Solution:
"""
@param numbers: Give an array numbers of n integer
@param target : An integer
@return : return the sum of the three integers, the sum closest target.
"""
def threeSumClosest(self, numbers, target):
result = 2**31 - 1
length = len(numbers)
if length < 3:
return result
numbers.sort()
larger_count = 0
for i, item_i in enumerate(numbers):
start = i + 1
end = length - 1
# optimization 1 - filter the smallest sum greater then target
if start < end:
sum3_smallest = numbers[start] + numbers[start + 1] + item_i
if sum3_smallest > target:
larger_count += 1
if larger_count > 1:
return result
while (start < end):
sum3 = numbers[start] + numbers[end] + item_i
if abs(sum3 - target) < abs(result - target):
result = sum3
# optimization 2 - filter the sum3 closest to target
sum_flag = 0
if sum3 > target:
end -= 1
if sum_flag == -1:
break
sum_flag = 1
elif sum3 < target:
start += 1
if sum_flag == 1:
break
sum_flag = -1
else:
return result
return result
~~~
### 源码分析
1. leetcode 上不让自己导入`sys`包,保险起见就初始化了`result`为还算较大的数,作为异常的返回值。
1. 对数组进行排序。
1. 依次遍历排序后的数组,取出一个元素`item_i`后即转化为『2 Sum Cloest』问题。『2 Sum Cloest』的起始元素索引为`i + 1`,之前的元素不能参与其中。
1. 优化一——由于已经对原数组排序,故遍历原数组时比较最小的三个元素和`target`值,若第二次大于`target`果断就此罢休,后面的值肯定越来越大。
1. 两根指针求『2 Sum Cloest』,比较`sum3`和`result`与`target`的差值的绝对值,更新`result`为较小的绝对值。
1. 再度对『2 Sum Cloest』进行优化,仍然利用有序数组的特点,若处于『一大一小』的临界值时就可以马上退出了,后面的元素与`target`之差的绝对值只会越来越大。
### 复杂度分析
对原数组排序,平均时间复杂度为 O(nlogn)O(n \log n)O(nlogn), 两重`for`循环,由于有两处优化,故最坏的时间复杂度才是 O(n2)O(n^2)O(n2), 使用了`result`作为临时值保存最接近`target`的值,两处优化各使用了一个辅助变量,空间复杂度 O(1)O(1)O(1).
### C++
~~~
class Solution {
public:
int threeSumClosest(vector<int> &num, int target)
{
if (num.size() <= 3) return accumulate(num.begin(), num.end(), 0);
sort (num.begin(), num.end());
int result = 0, n = num.size(), temp;
result = num[0] + num[1] + num[2];
for (int i = 0; i < n - 2; ++i)
{
int j = i + 1, k = n - 1;
while (j < k)
{
temp = num[i] + num[j] + num[k];
if (abs(target - result) > abs(target - temp))
result = temp;
if (result == target)
return result;
( temp > target ) ? --k : ++j;
}
}
return result;
}
};
~~~
### 源码分析
和前面3Sum解法相似,同理使用i,j,k三个指针进行循环。
区别在于3sum中的target为0,这里新增一个变量用于比较哪组数据与target更为相近
### 复杂度分析
时间复杂度同理为O(n2)O(n^2)O(n2)运行时间 16ms
### Reference
- [3Sum Closest | 九章算法](http://www.jiuzhang.com/solutions/3sum-closest/)
- Preface
- Part I - Basics
- Basics Data Structure
- String
- Linked List
- Binary Tree
- Huffman Compression
- Queue
- Heap
- Stack
- Set
- Map
- Graph
- Basics Sorting
- Bubble Sort
- Selection Sort
- Insertion Sort
- Merge Sort
- Quick Sort
- Heap Sort
- Bucket Sort
- Counting Sort
- Radix Sort
- Basics Algorithm
- Divide and Conquer
- Binary Search
- Math
- Greatest Common Divisor
- Prime
- Knapsack
- Probability
- Shuffle
- Basics Misc
- Bit Manipulation
- Part II - Coding
- String
- strStr
- Two Strings Are Anagrams
- Compare Strings
- Anagrams
- Longest Common Substring
- Rotate String
- Reverse Words in a String
- Valid Palindrome
- Longest Palindromic Substring
- Space Replacement
- Wildcard Matching
- Length of Last Word
- Count and Say
- Integer Array
- Remove Element
- Zero Sum Subarray
- Subarray Sum K
- Subarray Sum Closest
- Recover Rotated Sorted Array
- Product of Array Exclude Itself
- Partition Array
- First Missing Positive
- 2 Sum
- 3 Sum
- 3 Sum Closest
- Remove Duplicates from Sorted Array
- Remove Duplicates from Sorted Array II
- Merge Sorted Array
- Merge Sorted Array II
- Median
- Partition Array by Odd and Even
- Kth Largest Element
- Binary Search
- Binary Search
- Search Insert Position
- Search for a Range
- First Bad Version
- Search a 2D Matrix
- Search a 2D Matrix II
- Find Peak Element
- Search in Rotated Sorted Array
- Search in Rotated Sorted Array II
- Find Minimum in Rotated Sorted Array
- Find Minimum in Rotated Sorted Array II
- Median of two Sorted Arrays
- Sqrt x
- Wood Cut
- Math and Bit Manipulation
- Single Number
- Single Number II
- Single Number III
- O1 Check Power of 2
- Convert Integer A to Integer B
- Factorial Trailing Zeroes
- Unique Binary Search Trees
- Update Bits
- Fast Power
- Hash Function
- Count 1 in Binary
- Fibonacci
- A plus B Problem
- Print Numbers by Recursion
- Majority Number
- Majority Number II
- Majority Number III
- Digit Counts
- Ugly Number
- Plus One
- Linked List
- Remove Duplicates from Sorted List
- Remove Duplicates from Sorted List II
- Remove Duplicates from Unsorted List
- Partition List
- Two Lists Sum
- Two Lists Sum Advanced
- Remove Nth Node From End of List
- Linked List Cycle
- Linked List Cycle II
- Reverse Linked List
- Reverse Linked List II
- Merge Two Sorted Lists
- Merge k Sorted Lists
- Reorder List
- Copy List with Random Pointer
- Sort List
- Insertion Sort List
- Check if a singly linked list is palindrome
- Delete Node in the Middle of Singly Linked List
- Rotate List
- Swap Nodes in Pairs
- Remove Linked List Elements
- Binary Tree
- Binary Tree Preorder Traversal
- Binary Tree Inorder Traversal
- Binary Tree Postorder Traversal
- Binary Tree Level Order Traversal
- Binary Tree Level Order Traversal II
- Maximum Depth of Binary Tree
- Balanced Binary Tree
- Binary Tree Maximum Path Sum
- Lowest Common Ancestor
- Invert Binary Tree
- Diameter of a Binary Tree
- Construct Binary Tree from Preorder and Inorder Traversal
- Construct Binary Tree from Inorder and Postorder Traversal
- Subtree
- Binary Tree Zigzag Level Order Traversal
- Binary Tree Serialization
- Binary Search Tree
- Insert Node in a Binary Search Tree
- Validate Binary Search Tree
- Search Range in Binary Search Tree
- Convert Sorted Array to Binary Search Tree
- Convert Sorted List to Binary Search Tree
- Binary Search Tree Iterator
- Exhaustive Search
- Subsets
- Unique Subsets
- Permutations
- Unique Permutations
- Next Permutation
- Previous Permuation
- Unique Binary Search Trees II
- Permutation Index
- Permutation Index II
- Permutation Sequence
- Palindrome Partitioning
- Combinations
- Combination Sum
- Combination Sum II
- Minimum Depth of Binary Tree
- Word Search
- Dynamic Programming
- Triangle
- Backpack
- Backpack II
- Minimum Path Sum
- Unique Paths
- Unique Paths II
- Climbing Stairs
- Jump Game
- Word Break
- Longest Increasing Subsequence
- Palindrome Partitioning II
- Longest Common Subsequence
- Edit Distance
- Jump Game II
- Best Time to Buy and Sell Stock
- Best Time to Buy and Sell Stock II
- Best Time to Buy and Sell Stock III
- Best Time to Buy and Sell Stock IV
- Distinct Subsequences
- Interleaving String
- Maximum Subarray
- Maximum Subarray II
- Longest Increasing Continuous subsequence
- Longest Increasing Continuous subsequence II
- Graph
- Find the Connected Component in the Undirected Graph
- Route Between Two Nodes in Graph
- Topological Sorting
- Word Ladder
- Bipartial Graph Part I
- Data Structure
- Implement Queue by Two Stacks
- Min Stack
- Sliding Window Maximum
- Longest Words
- Heapify
- Problem Misc
- Nuts and Bolts Problem
- String to Integer
- Insert Interval
- Merge Intervals
- Minimum Subarray
- Matrix Zigzag Traversal
- Valid Sudoku
- Add Binary
- Reverse Integer
- Gray Code
- Find the Missing Number
- Minimum Window Substring
- Continuous Subarray Sum
- Continuous Subarray Sum II
- Longest Consecutive Sequence
- Part III - Contest
- Google APAC
- APAC 2015 Round B
- Problem A. Password Attacker
- Microsoft
- Microsoft 2015 April
- Problem A. Magic Box
- Problem B. Professor Q's Software
- Problem C. Islands Travel
- Problem D. Recruitment
- Microsoft 2015 April 2
- Problem A. Lucky Substrings
- Problem B. Numeric Keypad
- Problem C. Spring Outing
- Microsoft 2015 September 2
- Problem A. Farthest Point
- Appendix I Interview and Resume
- Interview
- Resume