We are pleased to announce the 0.3.0 release of the neo python package.
Neo is a package for representing electrophysiology data in Python,
together with support for reading a wide range of neurophysiology file
formats, including Spike2, NeuroExplorer, AlphaOmega, Axon, Blackrock,
Plexon, Tdt, and support for writing to a subset of these formats plus
non-proprietary formats including HDF5.
The goal of Neo is to improve interoperability between Python tools for
analyzing, visualizing and generating electrophysiology data (such as
OpenElectrophy, NeuroTools, G-node, Helmholtz, PyNN) by providing a
common, shared object model. In order to be as lightweight a dependency
as possible, Neo is deliberately limited to represention of data, with
no functions for data analysis or visualization.
Neo implements a hierarchical data model well adapted to intracellular
and extracellular electrophysiology and EEG data with support for
multi-electrodes (for example tetrodes). Neo's data objects build on the
quantities_ package, which in turn builds on NumPy by adding support for
physical dimensions. Thus neo objects behave just like normal NumPy
arrays, but with additional metadata, checks for dimensional consistency
and automatic unit conversion.
Release 0.3.0 notes:
* various bug fixes in neo.io
* added ElphyIO
* SpikeTrain performence improved
* An IO class now can return a list of Block (see read_all_blocks in
IOs)
* python3 compatibility improved
Home page: http://neuralensemble.org/neo
Mailing list:
https://groups.google.com/forum/?fromgroups#!forum/neuralensemble
Documentation: http://packages.python.org/neo/
The neo team
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