Given a binary tree, we install cameras on the nodes of the tree.

Each camera at a node can monitor its parent, itself, and its immediate children.

Calculate the minimum number of cameras needed to monitor all nodes of the tree.

Example 1:

Input: [0,0,null,0,0]
Output: 1
Explanation: One camera is enough to monitor all nodes if placed as shown. Example 2:
Input: [0,0,null,0,null,0,null,null,0]
Output: 2
Explanation: At least two cameras are needed to monitor all nodes of the tree. The above image shows one of the valid configurations of camera placement.

Note:

    1. The number of nodes in the given tree will be in the range [1, 1000].
    2. Every node has value 0.

做了很久,还是写不出来,看了网上的答案。确实很精妙。利用了返回值表达了三种状态,利用引用存储最后结果。

还有一点就是在放相机的时候,在递归函数里,父节点一定比节点有优势,能放父节点一定放父节点,拿叶节点来

举例,此时如果放叶节点,能影响到的点只有它本身和父节点,而父节点能影响到子节点,本身,和它的父节点。

所以这是一个贪心算法。

class Solution {
public:
int minCameraCover(TreeNode* root) {
int sum=;
if(dfs(root,sum)==) sum++;// if root is not monitored, we place an additional camera here
return sum;
} int dfs(TreeNode * tr, int& sum){
if(!tr) return ;
int l=dfs(tr->left,sum), r=dfs(tr->right,sum);
if(l==||r==){// if at least 1 child is not monitored, we need to place a camera at current node
sum++;
return ;
}else if(l==||r==){// if at least 1 child has camera, the current node if monitored. Thus, we don't need to place a camera here
return ;
}else{// if both children are monitored but have no camera, we don't need to place a camera here. We place the camera at its parent node at the higher level.
return ;
}
return -;// this return statement won't be triggered
}
};

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