---

Pathfinding Algorithm Visualizer

This is a visualizer tool for various pathfinding algorithms, implemented using Pygame. It allows you to see how algorithms like A*, Dijkstra, Breadth-First Search (BFS), and Depth-First Search (DFS) explore the grid to find the shortest path between two points. The tool also includes interactive features to create barriers, reset the grid, and choose the algorithm.

Features

• Visualization of Algorithms: Visualize A*, Dijkstra, BFS, and DFS in real-time.
• Interactive Grid: Click to create barriers, set start/end points, and reset the grid.
• Algorithm Selection: Choose the pathfinding algorithm from a dropdown menu.
• User Controls:
  • Left Click: Set the start, end, and barriers on the grid.
  • Right Click: Remove barriers or reset points.
  • Run Button: Start the selected algorithm.
  • Reset Button: Reset the grid and start a new simulation.

Algorithms

• A*: A heuristic-based algorithm that combines the cost to reach a node and the estimated cost to reach the goal.
• Dijkstra: A classic algorithm that guarantees the shortest path in a weighted grid (works the same as A* without a heuristic).
• Breadth-First Search (BFS): Explores all possible paths one step at a time, ensuring the shortest path in unweighted grids.
• Depth-First Search (DFS): Explores as far as possible along each branch before backtracking. Does not guarantee the shortest path.

Prerequisites

• Python 3.x
• Pygame

Installation

1. Clone the repository:

   git clone https://github.com/sahil352005/Pathfinding-Simulation.git

2. Install Pygame:

   pip install pygame

   or

   python -m pip install pygame-ce

3. Run the script:

   python main.py

Usage

1. Set start and end points: Use the left mouse button to place the start (orange) and end (turquoise) points.
2. Create barriers: Use the left mouse button to draw barriers (black) that the pathfinder cannot pass through.
3. Run the algorithm: Select an algorithm from the dropdown menu, then click the "Run" button to see the visualization.
4. Reset the grid: Click the "Reset" button to clear the grid and start a new simulation.

Controls

• Left Click: Set the start, end, and barriers.
• Right Click: Reset grid cells.
• 'C' Key: Clear the entire grid.
• Run Button: Execute the chosen algorithm.
• Reset Button: Reset the grid and simulation.

Screenshots

Known Issues

• The simulation may not reset entirely if run multiple times. This can be resolved by pressing the Reset button before starting a new algorithm run.

Future Enhancements

• Add more pathfinding algorithms (e.g., Greedy Best-First Search).
• Allow diagonal movement between grid cells.
• Implement weighted grids with varying terrain costs.

License

This project is licensed under the MIT License - see the LICENSE file for details.

---

Contributors

• https://github.com/sahil352005
• https://github.com/Lonwwolf14
• https://github.com/Vedashree14