The Electrophys Feature Extraction Library (eFEL) allows neuroscientists to
automatically extract features 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 features to be
calculated. The library will then extract the requested features 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.
