Metadata-Version: 2.1
Name: torchtree
Version: 1.0.0.post3
Summary: Phylogenetic inference with pytorch
Home-page: https://github.com/4ment/torchtree
Author: Mathieu Fourment
Author-email: mathieu.fourment@uts.edu.au
License: GPL3
Keywords: phylogenetics,variational,Bayes,pytorch
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
Provides-Extra: test
License-File: LICENSE

# torchtree

[![Python package](https://github.com/4ment/torchtree/actions/workflows/python-package.yml/badge.svg)](https://github.com/4ment/torchtree/actions/workflows/python-package.yml)

## Installation

### Use an Anaconda environment (Optional)
```bash
conda env create -f environment.yml
conda activate torchtree
```

### The easy way
To install the latest stable version, run
```bash
pip install torchtree
```

### Using the source code
```bash
git clone https://github.com/4ment/torchtree
cd torchtree
pip install .
```

## Check install
```bash
torchtree --help
```

## Quick start
torchtree will approximate the posterior distribution of an unrooted tree with a JC69 substitution model using variational inference 
```bash
torchtree examples/advi/fluA.json
```

The JSON file can be generated using the torchtree CLI
```bash
torchtree-cli advi -i data/fluA.fa -t data/fluA.tree > fluA.json
```

