Metadata-Version: 2.1
Name: jnotype
Version: 0.1.0
Summary: Jnotype: probabilistic modeling of high-dimensional binary data.
Author: Paweł Czyż
Requires-Python: >=3.9,<3.13
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: arviz (>=0.15.1,<0.16.0)
Requires-Dist: jax (>=0.4.6,<0.5.0)
Requires-Dist: jaxlib (>=0.4.6,<0.5.0)
Requires-Dist: jaxtyping (>=0.2.14,<0.3.0)
Requires-Dist: matplotlib (>=3.7.1,<4.0.0)
Requires-Dist: numpy (>=1.24.2,<2.0.0)
Requires-Dist: numpyro (>=0.15.3,<0.16.0)
Requires-Dist: polyagamma (>=1.3.5,<2.0.0)
Requires-Dist: tqdm (>=4.65.0,<5.0.0)
Requires-Dist: xarray (>=2023.3.0,<2024.0.0)
Description-Content-Type: text/markdown

[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)
[![build](https://github.com/cbg-ethz/Jnotype/actions/workflows/test.yml/badge.svg)](https://github.com/cbg-ethz/Jnotype/actions/workflows/test.yml)
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# Jnotype

[JAX](https://github.com/google/jax)-powered Python package for exploratory analysis of binary data.
This includes genotype data, binary images, and data sets used in ecology.

**Note:** this package is in early development stage.

  - **Source code:** [https://github.com/cbg-ethz/Jnotype](https://github.com/cbg-ethz/Jnotype)
  - **Bug reports:** [https://github.com/cbg-ethz/Jnotype/issues](https://github.com/cbg-ethz/Jnotype/issues)

## Installation

**Note:** The package has not reached a stable API yet. Frequent changes may appear 

We recommend setting up a new [virtual environment](https://docs.python.org/3/library/venv.html). You can install the package using PIP:

```bash
$ python -m pip install 'jnotype @ git+https://github.com/cbg-ethz/jnotype'
```

However, this will install the CPU version of JAX.
To use GPU, you may need to follow the [official JAX installation tutorial](https://github.com/google/jax#pip-installation-gpu-cuda-installed-via-pip-easier).

## Getting started

Directory `examples/` contains [Quarto](https://quarto.org/) notebooks, which demonstrate basic functionalities of the package.


