MatplotKit

MatplotKit is a lightweight Python library designed to enhance Matplotlib with additional features and utilities, making data visualization more convenient and elegant.

Features

• ✨ Decorators for Plot Functions

  • @with_axes decorator automatically handles axes creation
  • Simplifies plot function implementation
  • Customizable figure size support

• 📊 Enhanced Annotations

  • Easy-to-use diagonal line addition
  • More annotation utilities coming soon

• 📈 Taylor Diagram Support

  • Comprehensive implementation of Taylor diagrams
  • Perfect for model evaluation and comparison
  • Customizable styling options

Installation

Install MatplotKit using pip:

pip install matplotkit

Quick Start

Here's a simple example of using MatplotKit:

import matplotlib.pyplot as plt
from matplotkit import with_axes, add_diagonal_line

# Using the decorator to automatically handle axes
@with_axes(figsize=(8, 6))
def scatter_plot(x, y, ax=None):
    ax.scatter(x, y)
    # Add a diagonal line with custom style
    add_diagonal_line(ax, color='red', linestyle='--', alpha=0.5)
    return ax

# Your plotting code
x = [1, 2, 3, 4, 5]
y = [1.1, 2.2, 2.9, 4.1, 5.2]
scatter_plot(x, y)
plt.show()

Requirements

• Python >= 3.8.1
• Matplotlib ~3.0

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

License

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

Author

Shuang (Twist) Song

• Email: SongshGeo@gmail.com
• GitHub: @SongshGeo
• Website: https://cv.songshgeo.com/

Citation

If you use MatplotKit in your research, please cite it as:

@software{matplotkit2024,
  author = {Song, Shuang},
  title = {MatplotKit: Enhanced Matplotlib Utilities},
  year = {2024},
  publisher = {GitHub},
  url = {https://github.com/SongshGeo/matplotkit}
}