A Python library for enhancing Matplotlib with additional features.
Project description
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_axesdecorator 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}
}
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