pulsarfitpy 0.2.4

A Python library to assist with data analysis and theoretical physics frameworks of the Australian National Telescope Facility (ATNF) Pulsar Catalogue.

pulsarfitpy: An Efficient Physics Informed Framework for Pulsar Analysis

pulsarfitpy is a Python library that uses empirical data from the Australia Telescope National Facility (ATNF) database & psrqpy to predict pulsar behaviors using provided Physics Informed Neural Networks (PINNs). For more data visualization, it also offers accurate polynomial approximations of visualized datasets from two psrqpy query parameters using scikit-learn.

Prerequisites:

• Python (>=3.12)
• NumPy
• Matplotlib
• psrqpy
• scikit-learn
• PyTorch
• SymPy

Install all dependencies by running the following command in the terminal:

pip install numpy matplotlib psrqpy scikit-learn torch sympy

Installation

To install the library, simply run the following in the terminal:

pip install pulsarfitpy

For library usage, import the pulsarfitpy library with:

import pulsarfitpy as pf

Refer to the documentation for further usage of the library.

Contributing

1. Fork the repository.
2. Create a new branch: git checkout -b feature-name.
3. Make your changes.
4. Push your branch: git push origin feature-name.
5. Create a pull request.

Credits

pulsarfitpy was written by Om Kasar, Saumil Sharma, Jonathan Sorenson, and Kason Lai.

Contact

For any questions about the repository, email [e-mail].