Path Finding Algorithm Visualizer

This project visualizes the A* pathfinding algorithm using the Pygame library. Users can interactively set start and end points, create barriers, and see the optimal path formed in real-time.

Table of Contents

1. Prerequisites
2. Features
3. Usage
4. File Structure
5. Spot Class
6. A* Algorithm

Prerequisites

• Python 3.x
• Pygame (pip install pygame)

Features

• Interactive GUI to set start and end points.
• Ability to create barriers.
• Visualization of the A* algorithm in action.
• Clear board and reset functionality.

Usage

1. Run main.py to start the application.
2. Left-click to set the start (Goldenrod color) and end points (Deep Sky Blue).
3. Continue left-clicking to set barriers (Dark Gray).
4. Right-click on any spot to reset its state.
5. Press SPACE to start the algorithm once the start and end points are set.
6. Press C to clear the entire board and reset.

File Structure

• main.py: The main driver of the program that contains the GUI and handles user inputs.

Spot Class

The Spot class is used to represent each cell on the grid. The various functionalities of the Spot class include:

• Determining the state (start, end, open, closed, barrier).
• Drawing itself on the Pygame window.
• Updating its neighbors.
• Checking neighboring cells for barriers.

A* Algorithm

The implementation utilizes the A* (A-Star) algorithm which uses a heuristic to find the shortest path from the start node to the end node. The specific heuristic used is the Manhattan distance.

The algorithm function carries out the A* search and the reconstruct_path function is used to backtrack from the end node to the start node, displaying the optimal path.

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Note: Ensure that the Pygame library is installed and the main method is located in main.py before running.

Happy Pathfinding!