Metadata-Version: 2.1
Name: lussac
Version: 2.0.0b5
Summary: Python package for automatic post-processing and merging of multiple spike-sorting analyses.
Author-email: Aurélien Wyngaard <aurelien.wyngaard@gmail.com>
Project-URL: homepage, https://github.com/BarbourLab/lussac
Project-URL: repository, https://github.com/BarbourLab/lussac
Project-URL: documentation, http://lussac.readthedocs.io/
Project-URL: changelog, https://github.com/BarbourLab/lussac/releases
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: networkx >=3.0
Requires-Dist: numpy >=1.23
Requires-Dist: pandas >=1.4.4
Requires-Dist: scikit-learn >=1.1.0
Requires-Dist: scipy >=1.9
Requires-Dist: plotly >=5.8.2
Requires-Dist: kaleido
Requires-Dist: jsmin >=3.0
Requires-Dist: numba >=0.56.2
Requires-Dist: tqdm >=4.64.0
Requires-Dist: requests >=2.28.0
Requires-Dist: overrides >=7.3.1
Requires-Dist: spikeinterface >=0.99.1
Provides-Extra: dev
Requires-Dist: pytest >=7.1.3 ; extra == 'dev'
Requires-Dist: pytest-cov >=4.0.0 ; extra == 'dev'
Requires-Dist: matplotlib ; extra == 'dev'
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Requires-Dist: sphinx >=7.0.1 ; extra == 'dev'
Requires-Dist: sphinxemoji >=0.2.0 ; extra == 'dev'
Requires-Dist: sphinx-rtd-theme >=1.3.0 ; extra == 'dev'

[![Python version](https://img.shields.io/badge/python-3.10%20%7C%203.11-blue.svg)](https://img.shields.io/badge/python-3.10-blue.svg)
[![Documentation Status](https://readthedocs.org/projects/lussac/badge/?version=latest)](http://lussac.readthedocs.io/)
[![Build status](https://github.com/BarbourLab/lussac/actions/workflows/unit-tests-linux.yml/badge.svg)](https://github.com/BarbourLab/lussac/actions/workflows/unit-tests.yml)
[![Coverage report](https://codecov.io/gh/barbourlab/lussac/graphs/badge.svg)](https://app.codecov.io/github/barbourlab/lussac)

# Lussac 2.0

:warning: Lussac 2.0 is in beta! :warning:

You can use the version 1 with `git checkout v1`

Lussac is an **automated** and **configurable** analysis pipeline for post-processing and/or merging multiple spike-sorting analyses. The goal is to improve the **yield** and **quality** of data from multielectrode extracellular recordings by comparing the outputs of different spike-sorting algorithms and/or multiple runs with different parameters. For more information, check out our [preprint](https://www.biorxiv.org/content/10.1101/2022.02.08.479192v1).


## Installation

You can install the latest release version of Lussac:

```bash
# OPTIONAL: Use a conda environment.
conda create -n lussac python=3.11  # Must be >= 3.10
conda activate lussac

pip install lussac
# pip install --upgrade lussac  # To upgrade in case a new version is released.
```

Or if you prefer downloading the latest developmental version:

```bash
# Download Lussac in any directory you want.
git clone https://github.com/BarbourLab/lussac.git --branch dev
cd lussac

# OPTIONAL: Use a conda environment.
conda create -n lussac python=3.11  # Must be >= 3.10
conda activate lussac

# Install Lussac.
pip install -e .[dev]

# To upgrade Lussac.
git pull

# If you want to check whether the installation was successful (optional)
pytest
```


## Documentation

You can find the documentation [here](https://lussac.readthedocs.io/).


## Migration from Lussac1

Lussac2 is not backwards-compatible with Lussac1.  We advise you to make a new conda environment, and to remake your `params.json` file (which is also not backwards-compatible).
