https://github.com/edujbarrios/astarvisualizer
A star algorithm visualizer using JS, CSS and HTML
https://github.com/edujbarrios/astarvisualizer
Last synced: 7 months ago
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A star algorithm visualizer using JS, CSS and HTML
- Host: GitHub
- URL: https://github.com/edujbarrios/astarvisualizer
- Owner: edujbarrios
- License: mit
- Created: 2024-07-10T17:41:09.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-07-10T17:43:52.000Z (over 1 year ago)
- Last Synced: 2025-02-01T08:48:06.314Z (8 months ago)
- Language: JavaScript
- Size: 8.79 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# A* Algorithm Visualizer
## Overview
This project is a visualizer for the A* pathfinding algorithm. It provides a visual representation of how the algorithm works and allows you to configure various parameters such as speed, heuristic, grid size, cell size, and visualization style.
## Features
- **Speed Control**: Choose between fast, medium, and slow visualization speeds.
- **Heuristic Selection**: Select between Manhattan, Euclidean, and Chebyshev heuristics.
- **Grid Size**: Configure the grid size to be 20x20, 30x30, or 40x40.
- **Cell Size**: Adjust the size of each cell to 20px, 30px, or 40px.
- **Visualization Style**: Choose between default, blue, and dark themes.
- **Path Highlighting**: The shortest path found by the algorithm is highlighted in yellow.
- **Performance Timer**: Displays the time taken to compute the path.
## How to Use
1. **Select Speed**: Choose the speed at which you want the algorithm to be visualized (Fast, Medium, Slow).
2. **Select Heuristic**: Select the heuristic function to be used (Manhattan, Euclidean, Chebyshev).
3. **Grid Size**: Select the size of the grid (20x20, 30x30, 40x40).
4. **Cell Size**: Select the size of each cell (20px, 30px, 40px).
5. **Visualization Style**: Choose the style of visualization (Default, Blue Theme, Dark Theme).
6. **Visualize A***: Click this button to start the visualization of the A* algorithm.
7. **Reset**: Click this button to reset the grid to its initial state.
## Algorithm Description
The A* algorithm is a pathfinding and graph traversal algorithm, which is often used in computer science due to its performance and accuracy. It finds the shortest path from a start node to a goal node by using a heuristic to estimate the cost to reach the goal from the current node.
### Key Features
- **Heuristic Function**: Uses a heuristic function to guide the search towards the goal.
- **Combines Dijkstra and Greedy Best-First Search**: Combines the benefits of Dijkstra's Algorithm and Greedy Best-First-Search.
- **Complete and Optimal**: It is complete and optimal, meaning it will always find the shortest path if one exists.
### How it Works
1. **Initialization**: The algorithm starts with the initial node and explores neighboring nodes.
2. **Priority Queue**: Maintains a priority queue of nodes to be explored, prioritizing nodes with the lowest estimated total cost (current cost + estimated cost to goal).
3. **Path Building**: As it explores nodes, it builds the optimal path incrementally, guaranteeing the shortest path is found if one exists.
## Running the Project
To run the project, simply open the `index.html` file in your web browser.
## License
This project is open source and available under the [MIT License](LICENSE).
## Author
Made by [edujbarrios](https://github.com/edujbarrios).