DeDist

DeDist (for Decoding Distributins) is a Python library for analytically calculating the full decoding distribution for a given neural encoding system with Gaussian noise, with arbitrary tuning curves (heterogeneous or homogeneous) and arbitrary noise correlations.

For more information see the paper: S.W. Keemink and M.C.W. Van Rossum (2017) Biases in multivariate neural population codes, ArXiv, https://doi.org/10.1101/113803.

Installation

pip install DeDist

Usage

See the ipython notebooks in the example folder: https://github.com/swkeemink/DeDist/blob/master/Examples/Basic%20Usage%201D.ipynb https://github.com/swkeemink/DeDist/blob/master/Examples/Correlated%20noise%201D.ipynb

License

Unless otherwise stated in individual files, all code is Copyright (c) 2017, Sander Keemink and Mark van Rossum. All rights reserved.

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.