Skip to main content

Neo is a package for representing electrophysiology data in Python, together with support for reading a wide range of neurophysiology file formats

Project description

Neo is a Python package for working with 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 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 is used by a number of other software tools, including SpykeViewer (data analysis and visualization), Elephant (data analysis), the G-node suite (databasing), PyNN (simulations), tridesclous (spike sorting) and ephyviewer (data visualization). OpenElectrophy (data analysis and visualization) uses an older version of neo.

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.

A project with similar aims but for neuroimaging file formats is NiBabel.

Code status

Core Test Status (Github Actions) IO Test Status (Github Actions) Unit Test Coverage

More information

For installation instructions, see doc/source/install.rst

To cite Neo in publications, see CITATION.txt

copyright:

Copyright 2010-2024 by the Neo team, see doc/source/authors.rst.

license:

3-Clause Revised BSD License, see LICENSE.txt for details.

Funding

Development of Neo has been partially funded by the European Union Sixth Framework Program (FP6) under grant agreement FETPI-015879 (FACETS), by the European Union Seventh Framework Program (FP7/2007­-2013) under grant agreements no. 269921 (BrainScaleS) and 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), No. 785907 (Human Brain Project SGA2) and No. 945539 (Human Brain Project SGA3), and by the European Union’s Research and Innovation Program Horizon Europe Grant Agreement No. 101147319 (EBRAINS 2.0).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

neo-0.13.4.tar.gz (5.0 MB view details)

Uploaded Source

Built Distribution

neo-0.13.4-py3-none-any.whl (655.1 kB view details)

Uploaded Python 3

File details

Details for the file neo-0.13.4.tar.gz.

File metadata

  • Download URL: neo-0.13.4.tar.gz
  • Upload date:
  • Size: 5.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.15

File hashes

Hashes for neo-0.13.4.tar.gz
Algorithm Hash digest
SHA256 b7264acb7ba7eeaa0a8e91a15ae4dbc8b4dd56c3e38bc7d1cc0442dc5b71dd72
MD5 d4cd0a269556319692097e0be78c44b2
BLAKE2b-256 e00de973b7e8464b6f1d88022c46040f203d93c0b080af0e33702bb11873dbbb

See more details on using hashes here.

File details

Details for the file neo-0.13.4-py3-none-any.whl.

File metadata

  • Download URL: neo-0.13.4-py3-none-any.whl
  • Upload date:
  • Size: 655.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.15

File hashes

Hashes for neo-0.13.4-py3-none-any.whl
Algorithm Hash digest
SHA256 4589460ecfcaee414c937f9b8d67241b9d6210958ebfa3cfeaa55a118e5afecb
MD5 4f96d496840495cddf9f4dff5e9eed7a
BLAKE2b-256 ec83935e43425f36caf7c9ab4cb63e7be33840b19617b559f11b03ad4b0e6686

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page