What is inorder Traversal and implementation

Introduction

 

In this blog, we would discuss What is inorder Traversal and implementation. Inorder traversal is a method for visiting all the nodes of a binary tree in order. The nodes are visited in the order left-child-right-sibling. Inorder traversal can be used to print out the contents of a binary tree in sorted order since the leftmost child is always the smallest value and the rightmost child is always the largest value.

 

 

To perform an inorder traversal, we first visit the left child, then the node itself, and finally the right child. If a node has no left child, we visit the node itself and then its right child. If a node has no right child, we visit the node itself and then its left child.

 

 

 

 

What is Inorder traversal?

 

Inorder traversal is a tree traversal algorithm that visits each node in a tree in the order of its left child, the node itself, and its right child. This type of traversal is used to create a sorted list of the nodes in a tree, as the nodes are visited in order from left to right. To perform an inorder traversal, we first check if the current node has a left child. If so, we recursively call the inorder traversal function on the left child. Next, we visit the node itself, and then we recursively call the inorder traversal function on the right child.

 

 

This algorithm can be implemented using a stack, which allows us to keep track of the nodes that still need to be visited. We start by pushing the root node onto the stack. Then, as long as the stack is not empty, we pop off the top node and visit it. If the node has a left child, we push the left child onto the stack. If the node has the right child, we push the right child onto the stack. This process continues until all of the nodes in the tree have been visited. The time complexity of this algorithm is O(n), where n is the number of nodes in the tree. The space complexity is O(n), as we need to store all of the nodes in the stack.

 

 

 

Implementation of Inorder Traversal

 

class Node:
    def __init__(self, key):
        self.left = None
        self.right = None
        self.val = key
  
  
# A function to do inorder tree traversal
def printInorder(root):
  
    if root:
        printInorder(root.left)
        print(root.val),
        printInorder(root.right)

root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.left = Node(4)
root.left.right = Node(5)

  
print("\nInorder traversal of binary tree is")
printInorder(root)

 

Output

 

 

 

Applications of Inorder Traversal

 

One common application of in-order traversal is in the creation of a binary search tree. In a binary search tree, the left child of a node contains a value less than the node’s value, and the right child of a node contains a value greater than the node’s value. By traversing the tree in order, we can guarantee that the nodes will be processed in sorted order, which makes it easy to find a specific value in the tree. Another application of in-order traversal is in the evaluation of mathematical expressions that are represented by trees. In this case, the inorder traversal is used to process the operands in the correct order (i.e. left to right).

 

 

Finally, in-order traversal can be used to find the kth smallest element in a binary search tree. This is because the in-order traversal of a binary search tree will result in the nodes being processed in sorted order. Thus, we can simply keep track of the number of nodes processed so far and return the kth node when we reach it.

 

 

Inorder traversal can also be used to find the kth smallest element in a binary search tree, as long as k is less than the number of nodes in the tree. To do this, you simply keep track of the number of nodes visited so far, and when you visit the kth node, you know that it is the kth smallest element in the tree. There are other applications for inorder traversal as well, such as for creating a mirror image of a binary tree, or for finding the successor of a given node in a binary search tree.

 

 

Also, read about the inception network.