Electrophys Feature Extraction Library
The Electrophys Feature Extract Library (eFEL) allows neuroscientists to automatically extract eFeatures from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the eFeatures to be calculated. The library will then extract the requested eFeatures and return the values to the user.
The core of the library is written in C++, and a Python wrapper is included. At the moment we provide a way to automatically compile and install the library as a Python module. Soon instructions will be added on how to link C++ code directly with the eFEL.
The source code of the eFEL is located on github: BlueBrain/eFEL
- eFeature descriptions
- Python API
- Developer’s Guide