Extracellular recordings with multi-electrode arrays is one of the basic
tools of contemporary neuroscience. These recordings are mostly used to monitor
the activities, understood as sequences of emitted action potentials, of many
individual neurons. But the raw data produced by extracellular recordings are
most commonly a mixture of activities from several neurons. In order to get the
activities of the individual contributing neurons, a pre-processing step called
spike sorting is required. We present here a pure Python implementation of a
well tested spike sorting procedure. The latter was designed in a modular way
in order to favour a smooth transition from an interactive sorting, for
instance with IPython, to an automatic one. Surprisingly enough - or sadly
enough, depending on one's view point -, recoding our now 15 years old
procedure into Python was the occasion of major methodological improvements.Comment: Part of the Proceedings of the 7th European Conference on Python in
Science (EuroSciPy 2014), Pierre de Buyl and Nelle Varoquaux editors, (2014
