如果用递归遍历一直遍历到最后左边一个然后取值,这样不一定是对的,因为这样取到的左叶子的值不一定是最后一层的左叶子。如果使用递归法,如何判断是最后一行呢,其实就是深度最大的叶子节点一定是最后一行。所以我们需要在递归中传入一个deep层数来表示当前遍历到的树的深度,只有深度最深的左叶子的值才是我们想要的。
class Solution {
private int Deep = -1;
private int value = 0;
public int findBottomLeftValue(TreeNode root) {
value = root.val;
findLeftValue(root, 0);
return value;
}
public void findLeftValue(TreeNode root, int deep){
if(root == null) return;
if(root.left == null && root.right == null){
if(deep > Deep){
value = root.val;
Deep = deep;
}
}
if(root.left != null) findLeftValue(root.left, deep + 1);
if(root.right != null) findLeftValue(root.right, deep + 1);
}
}
如果把每条路径上的和都加起来再与target做对比代码相对来说会更难写点,所以可以直接减去路径上根节点的值,当target值为0且已经走到了某个叶子结点时,说明这条路径已经到头了,我们可以找到一条总和为target的路径。
class Solution {
public boolean hasPathSum(TreeNode root, int targetSum) {
if(root == null){
return false;
}
targetSum -= root.val;
if(root.left == null && root.right == null){
return targetSum == 0;
}
if(root.left != null){
boolean left = hasPathSum(root.left, targetSum);
if(left){
return true;
}
}
if(root.right != null){
boolean right = hasPathSum(root.right, targetSum);
if(right){
return true;
}
}
return false;
}
}
class Solution {
public List<List<Integer>> pathSum(TreeNode root, int targetSum) {
List<List<Integer>> res = new ArrayList<>();
if(root == null) return res;
List<Integer> path = new LinkedList<>();
preorderdfs(root, targetSum, res, path);
return res;
}
public void preorderdfs(TreeNode root, int targetSum, List<List<Integer>> res, List<Integer> path){
path.add(root.val);
if(root.left == null && root.right == null){
if(targetSum - root.val == 0){
res.add(new ArrayList<>(path));
}
return;
}
if(root.left != null){
preorderdfs(root.left, targetSum - root.val, res, path);
path.remove(path.size() - 1);
}
if (root.right != null) {
preorderdfs(root.right, targetSum - root.val, res, path);
path.remove(path.size() - 1); // 回溯
}
}
}
class Solution {
Map<Integer, Integer> map;
public TreeNode buildTree(int[] inorder, int[] postorder) {
map = new HashMap<>();
for(int i = 0; i < inorder.length; i ++){
map.put(inorder[i], i);
}
return findNode(inorder, 0, inorder.length, postorder, 0, postorder.length);
}
public TreeNode findNode(int[] inorder, int inBegin, int inEnd, int[] postorder, int postBegin, int postEnd){
if(inBegin >= inEnd || postBegin >= postEnd){
return null;
}
int rootIndex = map.get(postorder[postEnd - 1]);
TreeNode root = new TreeNode(inorder[rootIndex]);
int lenOfLeft = rootIndex - inBegin;
root.left = findNode(inorder, inBegin, rootIndex,
postorder, postBegin, postBegin + lenOfLeft);
root.right = findNode(inorder, rootIndex + 1, inEnd,
postorder, postBegin + lenOfLeft, postEnd - 1);
return root;
}
}
class Solution {
Map<Integer, Integer> map;
public TreeNode buildTree(int[] preorder, int[] inorder) {
map = new HashMap<>();
for (int i = 0; i < inorder.length; i++) { // 用map保存中序序列的数值对应位置
map.put(inorder[i], i);
}
return findNode(preorder, 0, preorder.length, inorder, 0, inorder.length); // 前闭后开
}
public TreeNode findNode(int[] preorder, int preBegin, int preEnd, int[] inorder, int inBegin, int inEnd) {
// 参数里的范围都是前闭后开
if (preBegin >= preEnd || inBegin >= inEnd) { // 不满足左闭右开,说明没有元素,返回空树
return null;
}
int rootIndex = map.get(preorder[preBegin]); // 找到前序遍历的第一个元素在中序遍历中的位置
TreeNode root = new TreeNode(inorder[rootIndex]); // 构造结点
int lenOfLeft = rootIndex - inBegin; // 保存中序左子树个数,用来确定前序数列的个数
root.left = findNode(preorder, preBegin + 1, preBegin + lenOfLeft + 1,
inorder, inBegin, rootIndex);
root.right = findNode(preorder, preBegin + lenOfLeft + 1, preEnd,
inorder, rootIndex + 1, inEnd);
return root;
}
}