- Preface
- FAQ
- Guidelines for Contributing
- Contributors
- Part I - Basics
- Basics Data Structure
- String
- Linked List
- Binary Tree
- Huffman Compression
- Queue
- Heap
- Stack
- Set
- Map
- Graph
- Basics Sorting
- 算法复习——排序
- 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
- Bitmap
- 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
- Add Two Numbers
- 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
- Palindrome Linked List
- 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
- Permutation Index
- Permutation Index II
- Permutation Sequence
- Unique Binary Search Trees II
- 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
- Follow up
- 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
- Maximal Square
- 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
- APAC 2016 Round D
- Problem A. Dynamic Grid
- 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
- 術語表
Single Number II
Source
- leetcode: Single Number II | LeetCode OJ
- lintcode: (83) Single Number II
Problem
Given 3*n + 1
numbers, every numbers occurs triple times except one, find it.
Example
Given [1,1,2,3,3,3,2,2,4,1]
return 4
Challenge
One-pass, constant extra space.
题解 1 - 逐位处理
上题 Single Number 用到了二进制中异或的运算特性,这题给出的元素数目为 3*n + 1
,因此我们很自然地想到如果有种运算能满足「三三运算」为 0 该有多好!对于三个相同的数来说,其相加的和必然是 3 的倍数,仅仅使用这一个特性还不足以将单数找出来,我们再来挖掘隐含的信息。以 3 为例,若使用不进位加法,三个 3 相加的结果为:
0011
0011
0011
----
0033
注意到其中的奥义了么?三个相同的数相加,不仅其和能被 3 整除,其二进制位上的每一位也能被 3 整除!因此我们只需要一个和 int
类型相同大小的数组记录每一位累加的结果即可。时间复杂度约为 O((3n+1)⋅sizeof(int)⋅8)O((3n+1)\cdot sizeof(int) \cdot 8)O((3n+1)⋅sizeof(int)⋅8)
Python
class Solution(object):
def singleNumber(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
if nums is None:
return 0
result = 0
for i in xrange(32):
bit_i_sum = 0
for num in nums:
bit_i_sum += ((num >> i) & 1)
result |= ((bit_i_sum % 3) << i)
return self.twos_comp(result, 32)
def twos_comp(self, val, bits):
"""
compute the 2's compliment of int value val
e.g. -4 ==> 11100 == -(10000) + 01100
"""
return -(val & (1 << (bits - 1))) | (val & ((1 << (bits - 1)) - 1))
C++
class Solution {
public:
/**
* @param A : An integer array
* @return : An integer
*/
int singleNumberII(vector<int> &A) {
if (A.empty()) {
return 0;
}
int result = 0, bit_i_sum = 0;
for (int i = 0; i != 8 * sizeof(int); ++i) {
bit_i_sum = 0;
for (int j = 0; j != A.size(); ++j) {
// get the *i*th bit of A
bit_i_sum += ((A[j] >> i) & 1);
}
// set the *i*th bit of result
result |= ((bit_i_sum % 3) << i);
}
return result;
}
};
源码解析
- 异常处理
- 循环处理返回结果
result
的int
类型的每一位,要么自增 1,要么保持原值。注意i
最大可取 8⋅sizeof(int)−18 \cdot sizeof(int) - 18⋅sizeof(int)−1, 字节数=>位数的转换 - 对第
i
位处理完的结果模 3 后更新result
的第i
位,由于result
初始化为 0,故使用或操作即可完成
Python 中的整数表示理论上可以是无限的(求出处),所以移位计算得到最终结果时需要转化为 2 的补码。此方法参考自 Two's Complement in Python
Reference
Single Number II - Leetcode Discuss 中抛出了这么一道扩展题:
Given an array of integers, every element appears k times except for one. Find that single one which appears l times.
@ranmocy 给出了如下经典解:
We need a array x[i]
with size k
for saving the bits appears i
times. For every input number a, generate the new counter by x[j] = (x[j-1] & a) | (x[j] & ~a)
. Except x[0] = (x[k] & a) | (x[0] & ~a)
.
In the equation, the first part indicates the the carries from previous one. The second part indicates the bits not carried to next one.
Then the algorithms run in O(kn)
and the extra space O(k)
.
Java
public class Solution {
public int singleNumber(int[] A, int k, int l) {
if (A == null) return 0;
int t;
int[] x = new int[k];
x[0] = ~0;
for (int i = 0; i < A.length; i++) {
t = x[k-1];
for (int j = k-1; j > 0; j--) {
x[j] = (x[j-1] & A[i]) | (x[j] & ~A[i]);
}
x[0] = (t & A[i]) | (x[0] & ~A[i]);
}
return x[l];
}
}
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