# Binary Tree Maximum Path Sum
### Source
- lintcode: [(94) Binary Tree Maximum Path Sum](http://www.lintcode.com/en/problem/binary-tree-maximum-path-sum/)
~~~
Given a binary tree, find the maximum path sum.
The path may start and end at any node in the tree.
Example
Given the below binary tree,
1
/ \
2 3
Return 6.
~~~
### 題解1 - 遞歸中僅返回子樹路徑長度
如題目右側的四顆半五角星所示,本題屬于中等偏難的那一類題。題目很短,要求返回最大路徑和。咋看一下感覺使用遞歸應該很快就能搞定,實則不然,**因為從題目來看路徑和中不一定包含根節點!也就是說可以起止于樹中任一連通節點。**
弄懂題意后我們就來剖析剖析,本著由簡入難的原則,我們先來分析若路徑和包含根節點,如何才能使其路徑和達到最大呢?選定根節點后,路徑和中必然包含有根節點的值,剩下的部分則為左子樹和右子樹,要使路徑和最大,則必然要使左子樹和右子樹中的路徑長度都取最大。
****> 注意區分包含根節點的路徑和(題目要的答案)和左子樹/右子樹部分的路徑長度(答案的一個組成部分)。路徑和=根節點+左子樹路徑長度+右子樹路徑長度
~~~
-10
/ \
2 -3
/ \ / \
3 4 5 7
~~~
如上所示,包含根節點`-10`的路徑和組成的節點應為`4 -> 2 -> -10 <- -3 <- 7`, 對于左子樹而言,其可能的路徑組成節點為`3 -> 2`或`4 -> 2`, 而不是像根節點的路徑和那樣為`3 -> 2 <- 4`. 這種差異也就造成了我們不能很愉快地使用遞歸來求得最大路徑和。
我們使用分治的思想來分析路徑和/左子樹/右子樹,設 f(root)f(root)f(root) 為`root`的子樹到`root`節點(含)路徑長度的最大值,那么我們有f(root)=root?>val+max(f(root?>left),?f(root?>right))f(root) = root->val + \max (f(root->left), ~f(root->right))f(root)=root?>val+max(f(root?>left),?f(root?>right))
遞歸模型已初步建立起來,接下來就是分析如何將左右子樹的路徑長度和最終題目要求的「路徑和」掛鉤。設 g(root)g(root)g(root) 為當「路徑和」中根節點為`root`時的值,那么我們有g(root)=root?>val+f(root?>left)+f(root?>right)g(root) = root->val + f(root->left) + f(root->right)g(root)=root?>val+f(root?>left)+f(root?>right)
順著這個思路,我們可以遍歷樹中的每一個節點求得 g(node)g(node)g(node) 的值,輸出最大值即可。如果不采取任何記憶化存儲的措施,其時間復雜度必然是指數級別的。嗯,先來看看這個思路的具體實現,后續再對其進行優化。遍歷節點我們使用遞歸版的前序遍歷,求單邊路徑長度采用遞歸。
### C++ Recursion + Iteration(Not Recommended)
**Time Limit Exceeded**
~~~
/**
* Definition of TreeNode:
* class TreeNode {
* public:
* int val;
* TreeNode *left, *right;
* TreeNode(int val) {
* this->val = val;
* this->left = this->right = NULL;
* }
* }
*/
class Solution {
public:
/**
* @param root: The root of binary tree.
* @return: An integer
*/
int maxPathSum(TreeNode *root) {
if (NULL == root) {
return 0;
}
int result = INT_MIN;
stack<TreeNode *> s;
s.push(root);
while (!s.empty()) {
TreeNode *node = s.top();
s.pop();
int temp_path_sum = node->val + singlePathSum(node->left) \
+ singlePathSum(node->right);
if (temp_path_sum > result) {
result = temp_path_sum;
}
if (NULL != node->right) s.push(node->right);
if (NULL != node->left) s.push(node->left);
}
return result;
}
private:
int singlePathSum(TreeNode *root) {
if (NULL == root) {
return 0;
}
int path_sum = max(singlePathSum(root->left), singlePathSum(root->right));
return max(0, (root->val + path_sum));
}
};
~~~
### 源碼分析
注意`singlePathSum`中最后的返回值,如果其路徑長度`path_sum`比0還小,那么取這一段路徑反而會減少最終的路徑和,故不應取這一段,我們使用0表示這一隱含意義。
### 題解2 - 遞歸中同時返回子樹路徑長度和路徑和
### C++ using std::pair
上題求路徑和和左右子樹路徑長度是分開求得的,因此導致了時間復雜度劇增的惡劣情況,從題解的遞推關系我們可以看出其實是可以在一次遞歸調用過程中同時求得路徑和和左右子樹的路徑長度的,只不過此時遞歸程序需要返回的不再是一個值,而是路徑長度和路徑和這一組值!C++中我們可以使用`pair`或者自定義新的數據類型來相對優雅的解決。
~~~
/**
* Definition of TreeNode:
* class TreeNode {
* public:
* int val;
* TreeNode *left, *right;
* TreeNode(int val) {
* this->val = val;
* this->left = this->right = NULL;
* }
* }
*/
class Solution {
private:
pair<int, int> helper(TreeNode *root) {
if (NULL == root) {
return make_pair(0, INT_MIN);
}
pair<int, int> leftTree = helper(root->left);
pair<int, int> rightTree = helper(root->right);
int single_path_sum = max(leftTree.first, rightTree.first) + root->val;
single_path_sum = max(0, single_path_sum);
int max_sub_sum = max(leftTree.second, rightTree.second);
int max_path_sum = root->val + leftTree.first + rightTree.first;
max_path_sum = max(max_sub_sum, max_path_sum);
return make_pair(single_path_sum, max_path_sum);
}
public:
/**
* @param root: The root of binary tree.
* @return: An integer
*/
int maxPathSum(TreeNode *root) {
if (NULL == root) {
return 0;
}
return helper(root).second;
}
};
~~~
### 源碼分析
除了使用`pair`對其進行封裝,也可使用嵌套類新建一包含單路徑長度和全局路徑和兩個變量的類,不過我用 C++寫的沒編譯過... 老是提示`...private`,遂用`pair`改寫之。建議使用`class`而不是`pair`封裝`single_path_sum`和`max_path_sum`[pair_is_harmful](#).
這種方法難以理解的地方在于這種實現方式的正確性,較為關鍵的語句為`max_path_sum = max(max_sub_sum, max_path_sum)`, 這行代碼是如何體現題目中以下的這句話的呢?
> The path may start and end at any node in the tree.
簡單來講,題解2從兩個方面予以保證:
1. 采用「冒泡」法返回不經過根節點的路徑和的較大值。
1. 遞推子樹路徑長度(不變值)而不是到該節點的路徑和(有可能變化),從而保證了這種解法的正確性。
如果還不理解的建議就以上面那個根節點為-10的例子畫一畫。
### C++ using self-defined class
~~~
/**
* Definition of TreeNode:
* class TreeNode {
* public:
* int val;
* TreeNode *left, *right;
* TreeNode(int val) {
* this->val = val;
* this->left = this->right = NULL;
* }
* }
*/
class Solution {
class ResultType {
public:
int singlePath, maxPath;
ResultType(int s, int m):singlePath(s), maxPath(m) {}
};
private:
ResultType helper(TreeNode *root) {
if (root == NULL) {
ResultType *nullResult = new ResultType(0, INT_MIN);
return *nullResult;
}
// Divide
ResultType left = helper(root->left);
ResultType right = helper(root->right);
// Conquer
int singlePath = max(left.singlePath, right.singlePath) + root->val;
singlePath = max(singlePath, 0);
int maxPath = max(left.maxPath, right.maxPath);
maxPath = max(maxPath, left.singlePath + right.singlePath + root->val);
ResultType *result = new ResultType(singlePath, maxPath);
return *result;
}
public:
int maxPathSum(TreeNode *root) {
ResultType result = helper(root);
return result.maxPath;
}
};
~~~
### 源碼分析
1. 如果不用 `ResultType *XXX = new ResultType ...` 再 `return *XXX` 的方式,則需要在自定義 class 中重載 `new` operator。
1. 如果遇到 `...private` 的編譯錯誤,則是因為自定義 class 中需要把成員聲明為 public,否則需要把訪問這個成員的函數也做 class 內部處理。
### Reference
- pair_is_harmful
> .
[std::pair considered harmful! ? Modern Maintainable Code](http://maintainablecode.logdown.com/posts/158531-stdpair-considered-harmful)
> - 作者指出了
`pair`
> 不能濫用的原因,如不可維護,信息量小。
[ ?](# "Jump back to footnote [pair_is_harmful] in the text.")
- [Binary Tree Maximum Path Sum | 九章算法](http://www.jiuzhang.com/solutions/binary-tree-maximum-path-sum/)
- 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