# Wood Cut
### Source
- lintcode: [(183) Wood Cut](http://www.lintcode.com/en/problem/wood-cut/)
### Problem
Given n pieces of wood with length `L[i]` (integer array). Cut them into smallpieces to guarantee you could have equal or more than k pieces with the samelength. What is the longest length you can get from the n pieces of wood?Given L & k, return the maximum length of the small pieces.
#### Example
For `L=[232, 124, 456]`, `k=7`, return `114`.
#### Note
You couldn't cut wood into float length.
#### Challenge
O(n log Len), where Len is the longest length of the wood.
### 题解 - 二分搜索
这道题要直接想到二分搜素其实不容易,但是看到题中 Challenge 的提示后你大概就能想到往二分搜索上靠了。首先来分析下题意,题目意思是说给出 n 段木材`L[i]`, 将这 n 段木材切分为至少 k 段,这 k 段等长,求能从 n 段原材料中获得的最长单段木材长度。以 k=7 为例,要将 L 中的原材料分为7段,能得到的最大单段长度为114, 232/114 = 2, 124/114 = 1, 456/114 = 4, 2 + 1 + 4 = 7.
理清题意后我们就来想想如何用算法的形式表示出来,显然在计算如`2`, `1`, `4`等分片数时我们进行了取整运算,在计算机中则可以使用下式表示:∑i=1nL[i]l≥k\sum _{i = 1} ^{n} \frac {L[i]}{l} \geq k∑i=1nlL[i]≥k
其中 lll 为单段最大长度,显然有 1≤l≤max(L[i])1 \leq l \leq max(L[i])1≤l≤max(L[i]). 单段长度最小为1,最大不可能超过给定原材料中的最大木材长度。
****> 注意求和与取整的顺序,是先求 `L[i]/l`的单个值,而不是先对`L[i]`求和。
分析到这里就和题 [Sqrt x](http://algorithm.yuanbin.me/zh-cn/binary_search/sqrt_x.html) 差不多一样了,要求的是 lll 的最大可能取值,同时 lll 可以看做是从有序序列`[1, max(L[i])]`的一个元素,典型的二分搜素!
P.S. 关于二分搜索总结在 [Binary Search](http://algorithm.yuanbin.me/zh-cn/basics_algorithm/binary_search.html) 一小节,直接套用『模板二——最优化』即可。
### Python
~~~
class Solution:
"""
@param L: Given n pieces of wood with length L[i]
@param k: An integer
return: The maximum length of the small pieces.
"""
def woodCut(self, L, k):
if sum(L) < k:
return 0
max_len = max(L)
start, end = 1, max_len
while start + 1 < end:
mid = start + (end - start) / 2
pieces_sum = sum([len_i / mid for len_i in L])
if pieces_sum < k:
end = mid
else:
start = mid
# corner case
if end == 2 and sum([len_i / 2 for len_i in L]) >= k:
return 2
return start
~~~
### Java
~~~
public class Solution {
/**
*@param L: Given n pieces of wood with length L[i]
*@param k: An integer
*return: The maximum length of the small pieces.
*/
public int woodCut(int[] L, int k) {
if (L == null || L.length == 0) return 0;
int lb = 0, ub = Integer.MAX_VALUE;
while (lb + 1 < ub) {
int mid = lb + (ub - lb) / 2;
if (C(L, k, mid)) {
lb = mid;
} else {
ub = mid;
}
}
return lb;
}
// whether it cut with length x and get more than k pieces
private boolean C(int[] L, int k, int x) {
int sum = 0;
for (int l : L) {
sum += l / x;
}
return sum >= k;
}
}
~~~
### 源码分析
定义私有方法`C`为切分为 x 长度时能否大于等于 k 段。若满足条件则更新`lb`, 由于 lb 和 ub 的初始化技巧使得我们无需单独对最后的 lb 和 ub 单独求和判断。九章算法网站上的方法初始化为1和某最大值,还需要单独判断,虽然不会出bug, 但稍显复杂。这个时候lb, ub初始化为两端不满足条件的值的优雅之处就体现出来了。
### 复杂度分析
遍历求和时间复杂度为 O(n)O(n)O(n), 二分搜索时间复杂度为 O(logmax(L))O(\log max(L))O(logmax(L)). 故总的时间复杂度为 O(nlogmax(L))O(n \log max(L))O(nlogmax(L)). 空间复杂度 O(1)O(1)O(1).
### Reference
- [Binary Search](http://algorithm.yuanbin.me/zh-cn/basics_algorithm/binary_search.html)
- 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