[pull] master from wisdompeak:master #78

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		[2277.Closest-Node-to-Path-in-Tree](https://github.com/wisdompeak/LeetCode/tree/master/Tree/2277.Closest-Node-to-Path-in-Tree) (H-)
		[2313.Minimum-Flips-in-Binary-Tree-to-Get-Result](https://github.com/wisdompeak/LeetCode/tree/master/Tree/2313.Minimum-Flips-in-Binary-Tree-to-Get-Result) (H)
		[2322.Minimum-Score-After-Removals-on-a-Tree](https://github.com/wisdompeak/LeetCode/tree/master/Tree/2322.Minimum-Score-After-Removals-on-a-Tree) (H-)
	[2458.Height-of-Binary-Tree-After-Subtree-Removal-Queries](https://github.com/wisdompeak/LeetCode/tree/master/Tree/2458.Height-of-Binary-Tree-After-Subtree-Removal-Queries) (M+)
		* ``Path in a tree``
		[543.Diameter-of-Binary-Tree](https://github.com/wisdompeak/LeetCode/tree/master/Tree/543.Diameter-of-Binary-Tree) (M)
		[124.Binary-Tree-Maximum-Path-Sum](https://github.com/wisdompeak/LeetCode/tree/master/Tree/124.Binary-Tree-Maximum-Path-Sum) (M)
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	/**
	* Definition for a binary tree node.
	* struct TreeNode {
	* int val;
	* TreeNode *left;
	* TreeNode *right;
	* TreeNode() : val(0), left(nullptr), right(nullptr) {}
	* TreeNode(int x) : val(x), left(nullptr), right(nullptr) {}
	* TreeNode(int x, TreeNode left, TreeNode right) : val(x), left(left), right(right) {}
	* };
	*/
	class Solution {
	unordered_map<int,vector<int>>d2h;
	int depth[100005];
	int height[100005];
	public:
	vector<int> treeQueries(TreeNode* root, vector<int>& queries)
	{
	dfs_height(root, 0);
	for (auto& [d, hs] : d2h)
	sort(hs.rbegin(), hs.rend());

	vector<int>rets;
	for (int node: queries)
	{
	int d = depth[node];
	int h = height[node];
	if (d2h[d].size()==1)
	rets.push_back(d - 1);
	else if (d2h[d][0] == h)
	rets.push_back(d2h[d][1] + d);
	else
	rets.push_back(d2h[d][0] + d);
	}
	return rets;

	}

	int dfs_height(TreeNode* node, int d)
	{
	if (node==NULL) return -1;
	int h = max(dfs_height(node->left, d+1), dfs_height(node->right, d+1)) + 1;
	d2h[d].push_back(h);
	depth[node->val] = d;
	height[node->val] = h;
	return h;
	}
	};

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	### 2458.Height-of-Binary-Tree-After-Subtree-Removal-Queries

	我们定义一个节点的height表示从它到叶子节点的最大距离,depth表示从它到root的距离。

	我们移除node节点对应的子树后,剩下的树的高度其实就取决于与它同depth的节点的height。所以我们将所有处在同depth的节点的height都提前收集好,那么就很容易找到其他子树的最大height。

	特别注意,如果某个深度的节点只有一个,那么将其移除后,剩下树的最大高度就是该节点的depth-1.

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