# Jaxtro 🔠- A JAX-based gravitational-wave population inference
[](https://github.com/Qazalbash/jaxtro/actions/workflows/python-package.yml)
[](https://pypi.org/project/jaxtro/)
Jaxtro is a JAX-based gravitational-wave population inference package. It is built on top of [JAXampler](https://github.com/Qazalbash/jaxampler) and provides a high-level interface for sampling from a wide range of gravitational-wave population models.
It is currently under active development and is not ready for production use. If you would like to contribute, please see the [contributing guidelines](CONTRIBUTING.md).
<!-- ## Features
- [x] 🚀 High-Performance Sampling: Leverage the power of JAX for high-speed, accurate sampling.
- [x] 🧩 Versatile Algorithms: A wide range of sampling methods to suit various applications.
- [x] 🔗 Easy Integration: Seamlessly integrates with existing JAX workflows. -->
## Installation
You may install the latest released version of Jaxtro through pip by doing
```bash
pip3 install --upgrade jaxtro
```
You may install the bleeding edge version by cloning this repo, or doing
```bash
pip3 install --upgrade git+https://github.com/Qazalbash/jaxtro
```
If you would like to take advantage of CUDA, you will additionally need to install a specific version of JAX by doing
```bash
pip install --upgrade "jax[cuda12_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html
```
## Requirements
Jaxtro requires Python 3.10 or higher. It also requires the following packages:
```bash
jaxampler
numpy
tqdm
```
The test suite is based on pytest. To run the tests, one needs to install pytest and run `pytest` at the root directory of this repo.
## Citing Jaxtro
If you use Jaxtro in your research, please cite the following paper:
```bibtex
@software{jaxtro2023github,
author = {Meesum Qazalbash, Muhammad Zeeshan},
title = {{jaxtro}: A JAX-based gravitational-wave population inference},
url = {http://github.com/Qazalbash/jaxtro},
version = {0.0.2},
year = {2023}
}
```
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"description": "# Jaxtro \ud83d\udd2d - A JAX-based gravitational-wave population inference\n\n[](https://github.com/Qazalbash/jaxtro/actions/workflows/python-package.yml)\n[](https://pypi.org/project/jaxtro/)\n\nJaxtro is a JAX-based gravitational-wave population inference package. It is built on top of [JAXampler](https://github.com/Qazalbash/jaxampler) and provides a high-level interface for sampling from a wide range of gravitational-wave population models.\n\nIt is currently under active development and is not ready for production use. If you would like to contribute, please see the [contributing guidelines](CONTRIBUTING.md).\n\n<!-- ## Features\n\n- [x] \ud83d\ude80 High-Performance Sampling: Leverage the power of JAX for high-speed, accurate sampling.\n- [x] \ud83e\udde9 Versatile Algorithms: A wide range of sampling methods to suit various applications.\n- [x] \ud83d\udd17 Easy Integration: Seamlessly integrates with existing JAX workflows. -->\n\n## Installation\n\nYou may install the latest released version of Jaxtro through pip by doing\n\n```bash\npip3 install --upgrade jaxtro\n```\n\nYou may install the bleeding edge version by cloning this repo, or doing\n\n```bash\npip3 install --upgrade git+https://github.com/Qazalbash/jaxtro\n```\n\nIf you would like to take advantage of CUDA, you will additionally need to install a specific version of JAX by doing\n\n```bash\npip install --upgrade \"jax[cuda12_pip]\" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html\n```\n\n## Requirements\n\nJaxtro requires Python 3.10 or higher. It also requires the following packages:\n\n```bash\njaxampler\nnumpy\ntqdm\n```\n\nThe test suite is based on pytest. To run the tests, one needs to install pytest and run `pytest` at the root directory of this repo.\n\n## Citing Jaxtro\n\nIf you use Jaxtro in your research, please cite the following paper:\n\n```bibtex\n@software{jaxtro2023github,\n author = {Meesum Qazalbash, Muhammad Zeeshan},\n title = {{jaxtro}: A JAX-based gravitational-wave population inference},\n url = {http://github.com/Qazalbash/jaxtro},\n version = {0.0.2},\n year = {2023}\n}\n```\n",
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