Introduction to Trees

Trees are hierarchical data structures that have a root node and contain child nodes. In programming, trees are used to represent relationships and hierarchies between data elements. They are particularly useful in the fields of robotics and computer vision due to their ability to model complex relationships.

Tree Terminology

Before we dive deeper into trees, let's familiarize ourselves with some common terminology:

• Root: The topmost node of a tree.
• Child: A node directly connected to another node when moving away from the root.
• Parent: The converse notion of a child.
• Leaf: A node with no children.
• Branch: A subset of nodes reachable from the root.
• Path: A sequence of nodes and edges connecting a node with a descendant.

Python Example

Here's an example of calculating the Euclidean distance between two points using a tree-like structure. This example demonstrates the use of trees in the field of computer vision:

1# Python code here
2
3import numpy as np
4
5def calculate_distance(point1, point2):
6    distance = np.sqrt(np.sum(np.square(point2 - point1)))
7    return distance
8
9point1 = np.array([1, 2, 3])
10point2 = np.array([4, 5, 6])
11distance = calculate_distance(point1, point2)
12print(distance)

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import numpy as np

​

# Python code here

​

def calculate_distance(point1, point2):

    distance = np.sqrt(np.sum(np.square(point2 - point1)))

    return distance

​

point1 = np.array([1, 2, 3])

point2 = np.array([4, 5, 6])

distance = calculate_distance(point1, point2)

print(distance)