alejoe91 / bluepyefe

BluePyEfe: Blue Brain Python E-feature extraction

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BluePyEfe: Blue Brain Python E-feature extraction

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Introduction

BluePyEfe aims at easing the process of reading experimental recordings and extracting batches of electrical features from these recordings. To do so, it combines trace reading functions and features extraction functions from the eFel library.

BluePyEfe outputs protocols and features files in the format used by BluePyOpt for neuron electrical model building.

How to cite

This software is citable using a DOI generated by Zenodo.

Requirements

• Python 3.6+ (still compatible with Python 2.7+)
• Pip (installed by default in newer versions of Python)
• eFEL eFeature Extraction Library (automatically installed by pip)
• Numpy (automatically installed by pip)
• Pandas (automatically installed by pip)
• Scipy (automatically installed by pip)
• Neo (automatically installed by pip)
• The instruction below are written assuming you have access to a command shell on Linux / UNIX / MacOSX / Cygwin

Installation

To install BluePyEfe run:

pip install bluepyefe

Quick Start

For a quick start, have a look at the notebook examples/example.ipynb

Funding

This work has been partially funded by the European Union Seventh Framework Program (FP7/2007­2013) under grant agreement no. 604102 (HBP), and by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreements No. 720270 (Human Brain Project SGA1) and No. 785907 (Human Brain Project SGA2) and by the EBRAINS research infrastructure, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3). This project/research was supported by funding to the Blue Brain Project, a research center of the École polytechnique fédérale de Lausanne (EPFL), from the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology.

Copyright (c) 2016-2021 Blue Brain Project/EPFL