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Given a binary tree where every node has a unique value, and a target key k, find the value of the nearest leaf node to target k in the tree.
Here, nearest to a leaf means the least number of edges travelled on the binary tree to reach any leaf of the tree. Also, a node is called a leaf if it has no children.
In the following examples, the input tree is represented in flattened form row by row. The actual root tree given will be a TreeNode object.
Example 1:
Input:
root = [1, 3, 2], k = 1
Diagram of binary tree:
1
/ \
3 2
Output: 2 (or 3)
Explanation: Either 2 or 3 is the nearest leaf node to the target of 1.
Example 2:
Input:
root = [1], k = 1
Output: 1
Explanation: The nearest leaf node is the root node itself.
Example 3:
Input:
root = [1,2,3,4,null,null,null,5,null,6], k = 2
Diagram of binary tree:
1
/ \
2 3
/
4
/
5
/
6
Output: 3
Explanation: The leaf node with value 3 (and not the leaf node with value 6) is nearest to the node with value 2.
Note:
root represents a binary tree with at least 1 node and at most 1000 nodes.
Every node has a unique node.val in range [1, 1000].
There exists some node in the given binary tree for which node.val == k.
class Solution {
public:
int findClosestLeaf(TreeNode* root, int k) {
int res = -1, mn = INT_MAX;
unordered_map<int, int> m;
m[k] = 0;
find(root, k, m);
helper(root, -1, m, mn, res);
return res;
}
int find(TreeNode* node, int k, unordered_map<int, int>& m) {
if (!node) return -1;
if (node->val == k) return 1;
int r = find(node->left, k, m);
if (r != -1) {
m[node->val] = r;
return r + 1;
}
r = find(node->right, k, m);
if (r != -1) {
m[node->val] = r;
return r + 1;
}
return -1;
}
void helper(TreeNode* node, int cur, unordered_map<int, int>& m, int& mn, int& res) {
if (!node) return;
if (m.count(node->val)) cur = m[node->val];
if (!node->left && !node->right) {
if (mn > cur) {
mn = cur;
res = node->val;
}
}
helper(node->left, cur + 1, m, mn, res);
helper(node->right, cur + 1, m, mn, res);
}
};
Given a binary tree where every node has a unique value, and a target key
k
, find the value of the nearest leaf node to targetk
in the tree.Here, nearest to a leaf means the least number of edges travelled on the binary tree to reach any leaf of the tree. Also, a node is called a leaf if it has no children.
In the following examples, the input tree is represented in flattened form row by row. The actual
root
tree given will be a TreeNode object.Example 1:
Example 2:
Example 3:
Note:
root
represents a binary tree with at least1
node and at most1000
nodes.node.val
in range[1, 1000]
.node.val == k
.这道题让我们找二叉树中最近的叶结点,叶结点就是最底端没有子结点的那个。我们观察题目中的例子3,发现结点2的最近叶结点是其右边的那个结点3,那么传统的二叉树的遍历只能去找其子结点中的叶结点,像这种同一层水平的结点该怎么弄呢?我们知道树的本质就是一种无向图,但是树只提供了父结点到子结点的连接,反过来就不行了,所以只要我们建立了反向连接,就可以用BFS来找最近的叶结点了。明白了这一点后,我们就先来做反向连接吧,用一个哈希map,建立子结点与其父结点之间的映射,其实我们不用做完所有的反向连接,而是做到要求的结点k就行了,因为结点k的子结点可以直接访问,不需要再反过来查找。我们用DFS来遍历结点,并做反向连接,直到遇到结点k时,将其返回。此时我们得到了结点k,并且做好了结点k上面所有结点的反向连接,那么就可以用BFS来找最近的叶结点了,将结点k加入队列queue和已访问集合visited中,然后开始循环,每次取出队首元素,如果是叶结点,说明已经找到了最近叶结点,直接返回;如果左子结点存在,并且不在visited集合中,那么先将其加入集合,然后再加入队列,同理,如果右子结点存在,并且不在visited集合中,那么先将其加入集合,然后再加入队列;再来看其父结点,如果不在visited集合中,那么先将其加入集合,然后再加入队列。因为题目中说了一定会有结点k,所以在循环内部就可以直接返回了,不会有退出循环的可能,但是为表尊重,我们最后还是加上return -1吧, 参见代码如下:
解法一:
下面这种解法也挺巧妙的,虽然没有像上面的解法那样建立所有父结点的反向连接,但是这种解法直接提前算出来了所有父结点到结点k的距离,就比如说例子3中,结点k的父结点只有一个,即为结点1,那么算出其和结点k的距离为1,即建立结点1和距离1之间的映射,另外建立结点k和0之间的映射,这样便于从结点k开始像叶结点统计距离。接下来,我们维护一个最小值mn,表示结点k到叶结点的最小距离,还有结果res,指向那个最小距离的叶结点。下面就开始再次遍历二叉树了,如果当前结点为空, 直接返回。否则先在哈希map中看当前结点是否有映射值,有的话就取出来(如果有,则说明当前结点可能k或者其父结点),如果当前结点是叶结点了,那么我们要用当前距离cur和最小距离mn比较,如果cur更小的话,就将mn更新为cur,将结果res更新为当前结点。否则就对其左右子结点调用递归函数,注意cur要加1,参见代码如下:
解法二:
参考资料:
https://leetcode.com/problems/closest-leaf-in-a-binary-tree/
https://leetcode.com/problems/closest-leaf-in-a-binary-tree/discuss/109960/java-dfs-bfs-27ms
https://leetcode.com/problems/closest-leaf-in-a-binary-tree/discuss/109963/java-short-solution28-ms-solution
LeetCode All in One 题目讲解汇总(持续更新中...)
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