https://1drv.ms/w/c/a8770d713b7ef149/EUqovsn-mgZOkTqsLZ9t-SoBpRS528X_dNj1fhHkpcu1zQ?e=p3FIm4

[aiby-jeffrey]

https://1drv.ms/w/c/a8770d713b7ef149/EUqovsn-mgZOkTqsLZ9t-SoBpRS528X_dNj1fhHkpcu1zQ?e=p3FIm4=class TreeNode:
def init(self, value):
self.value = value
self.children = []

def add_child(self, child_node):
    self.children.append(child_node)

Define custom operations

def unminus(a, b):
return a - b

def unadd(a, b):
return a + b

Create tree nodes

root = TreeNode("A1")
root.add_child(TreeNode("A2"))
root.add_child(TreeNode("B1"))

Example of custom operations

result1 = unminus(5, 4)
result2 = unadd(12, 13)

print(f"Result of 5 UNMINUS 4: {result1}")
print(f"Result of 12 UNADD 13: {result2}")

Example of AI model placeholders

def ai_model_vol_pyramid(input_data):
return "Factual Need Input Processed"

def ai_model_prism(input_data):
return "Creative and Imagination Processed"

Using AI model functions

factual_output = ai_model_vol_pyramid("Wikipedia Search")
creative_output = ai_model_prism("Creative Input")

print(f"AI Model VOL.PYRAMID Output: {factual_output}")
print(f"AI Model PRISM Output: {creative_output}")root.left.leftself.valroot.rightself.leftself.rightroot.leftroot.left.rightself.valueroot.rightself.childrenclass Node:
def init(self, key):
self.left = None
self.right = None
self.val = key

Inorder traversal of a binary tree

def inorder_traversal(root):
if root:
# First recur on left child
inorder_traversal(root.left)
# Then print the data of the node
print(root.val, end=' ')
# Finally, recur on right child
inorder_traversal(root.right)

Preorder traversal of a binary tree

def preorder_traversal(root):
if root:
# First print the data of the node
print(root.val, end=' ')
# Then recur on left child
preorder_traversal(root.left)
# Finally, recur on right child
preorder_traversal(root.right)

Postorder traversal of a binary tree

def postorder_traversal(root):
if root:
# First recur on left child
postorder_traversal(root.left)
# Then recur on right child
postorder_traversal(root.right)
# Finally, print the data of the node
print(root.val, end=' ')

Example usage

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

print("Inorder traversal of binary tree is")
inorder_traversal(root)

print("\nPreorder traversal of binary tree is")
preorder_traversal(root)

print("\nPostorder traversal of binary tree is")
postorder_traversal(root)traverse_tree is equal to the UNMINUS and unadd command in JCODEPY my personal ai code language class TreeNode:
def init(self, value):
self.value = value
self.children = []

def add_child(self, child_node):
    self.children.append(child_node)

Define custom operations

def unminus(a, b):
return a - b

def unadd(a, b):
return a + b

Create tree nodes

root = TreeNode("A1")
root.add_child(TreeNode("A2"))
root.add_child(TreeNode("B1"))

Example of custom operations

result1 = unminus(5, 4)
result2 = unadd(12, 13)

print(f"Result of 5 UNMINUS 4: {result1}")
print(f"Result of 12 UNADD 13: {result2}")

Example of AI model placeholders

def ai_model_vol_pyramid(input_data):
return "Factual Need Input Processed"

def ai_model_prism(input_data):
return "Creative and Imagination Processed"

Using AI model functions

factual_output = ai_model_vol_pyramid("Wikipedia Search")
creative_output = ai_model_prism("Creative Input")

print(f"AI Model VOL.PYRAMID Output: {factual_output}")
print(f"AI Model PRISM Output: {creative_output}")125self.valueself.childrenreplacement and reproduction of AI robot in JCODEPY jplayground xaomi sandbox and reproduction in general taking place at [email protected] FACTORIES WORLDWIDE