Metadata-Version: 2.1
Name: nemos
Version: 0.1.0
Summary: Toolbox for basic Generalized Linear Models (GLMs) for neural data analysis
Author-email: Edoardo Balzani <ebalzani@flatironinstitute.org>, William Broderick <wbroderick@flatironinstitute.org>, Guillaume Vejo <gviejo@flatironinstitute.org>, Alex Williams <alex.h.williams@nyu.edu>
License: MIT License
        
        Copyright (c) 2023 William F. Broderick
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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Keywords: neuroscience,Poisson-GLM
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
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![LOGO](CCN-logo-wText.png)

# nemos
NEural MOdelS, a statistical modeling framework for neuroscience.

## Disclaimer
This is an alpha version, the code is in active development and the API is subject to change.

## Setup

To install, clone this repo and install using `pip`:

``` sh
git clone git@github.com:flatironinstitute/nemos.git
cd nemos/
pip install -e .
```

If you have a GPU, you may need to install jax separately to get the proper
build. The following has worked for me on a Flatiron Linux workstation: `conda
install jax cuda-nvcc -c conda-forge -c nvidia`. Note this should be done
without `jax` and `jaxlib` already installed, so either run this before the
earlier `pip install` command or uninstall them first (`pip uninstall jax
jaxlib`). See [jax docs](https://github.com/google/jax#conda-installation) for
details (the `pip` instructions did not work for me).

![FOOT](CCN-letterFoot.png)
