Metadata-Version: 2.1
Name: cosmonet
Version: 0.1.0
Summary: Astronomical Light Curve Classification using Physics-Informed Neural Networks
Home-page: https://github.com/cosmonet-team/cosmonet
Author: CosmoNet Team
Author-email: cosmonet-team@example.com
License: Apache 2.0
Project-URL: Bug Reports, https://github.com/cosmonet-team/cosmonet/issues
Project-URL: Source, https://github.com/cosmonet-team/cosmonet
Project-URL: Documentation, https://cosmonet.readthedocs.io/
Keywords: astronomy,machine-learning,neural-networks,light-curves,classification
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Astronomy
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: license.txt

# CosmoNet

[![PyPI version](https://badge.fury.io/py/cosmonet.svg)](https://badge.fury.io/py/cosmonet)
[![Python versions](https://img.shields.io/pypi/pyversions/cosmonet.svg)](https://pypi.org/project/cosmonet/)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

CosmoNet is a Python package for astronomical light curve classification using Physics-Informed Neural Networks (PINNs). It combines traditional statistical features with physics-based features derived from astronomical principles to achieve high-accuracy classification of astronomical transients.

## Features

- **Physics-Informed Features**: Incorporates domain knowledge from astronomy
- **Multi-Model Ensemble**: Combines multiple machine learning models
- **Time Series Analysis**: Specialized features for light curve temporal patterns
- **Redshift Correction**: Accounts for cosmological effects
- **Extreme Event Detection**: Identifies significant flux variations
- **Research-Ready**: Generates publication-quality figures and analysis

## Installation

```bash
pip install cosmonet

