Metadata-Version: 2.4
Name: ExoIris
Version: 1.1.1
Summary: Easy and robust exoplanet transmission spectroscopy.
Author-email: Hannu Parviainen <hannu@iac.es>
License: GPLv3
Project-URL: homepage, https://github.com/hpparvi/ExoIris
Keywords: astronomy,astrophysics,exoplanets
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pytransit>=2.6.15
Requires-Dist: ldtk>=1.8.5
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: numba
Requires-Dist: emcee
Requires-Dist: matplotlib
Requires-Dist: celerite2
Requires-Dist: pandas
Requires-Dist: xarray
Requires-Dist: seaborn
Requires-Dist: astropy
Requires-Dist: uncertainties
Requires-Dist: scikit-learn
Dynamic: license-file

# ExoIris: Fast and Flexible Transmission Spectroscopy in Python

[![Docs](https://readthedocs.org/projects/exoiris/badge/)](https://exoiris.readthedocs.io)
![Python package](https://github.com/hpparvi/ExoIris/actions/workflows/python-package.yml/badge.svg)
[![Contributor Covenant](https://img.shields.io/badge/Contributor%20Covenant-2.0-4baaaa.svg)](CODE_OF_CONDUCT.md)
[![Licence](http://img.shields.io/badge/license-GPLv3-blue.svg?style=flat)](http://www.gnu.org/licenses/gpl-3.0.html)
[![PyPI version](https://badge.fury.io/py/exoiris.svg)](https://pypi.org/project/ExoIris/)
[![DOI](https://zenodo.org/badge/805355873.svg)](https://doi.org/10.5281/zenodo.18598641)

**ExoIris** is a Python package for exoplanet transmission spectroscopy that models the full 2D spectroscopic transit time
series directly, replacing the traditional two-step workflow. It jointly fits spectrophotometric datasets from different
instruments and epochs in a single self-consistent analysis — and does so fast, completing a typical JWST transmission 
spectrum in tens of minutes on a standard desktop.

See the [documentation & Tutorials](https://exoiris.readthedocs.io) for details, examples, and API reference.

![](doc/source/examples/e01/example1.png)

## Installation

```bash
pip install exoiris
```

Development version:

```bash
git clone https://github.com/hpparvi/ExoIris.git && cd ExoIris && pip install -e .
```
---

© 2026 Hannu Parviainen
