Skip to main content

Spike detection and automatic clustering for spike sorting

Project description

# Klusta: automatic spike sorting up to 64 channels

[![Build Status](https://img.shields.io/travis/kwikteam/klusta.svg)](https://travis-ci.org/kwikteam/klusta) [![codecov.io](https://img.shields.io/codecov/c/github/kwikteam/klusta.svg)](http://codecov.io/github/kwikteam/klusta?branch=master) [![Documentation Status](https://readthedocs.org/projects/klusta/badge/?version=latest)](http://klusta.readthedocs.org/en/latest/) [![PyPI release](https://img.shields.io/pypi/v/klusta.svg)](https://pypi.python.org/pypi/klusta) [![GitHub release](https://img.shields.io/github/release/kwikteam/klusta.svg)](https://github.com/kwikteam/klusta/releases/latest)

[klusta](https://github.com/kwikteam/klusta) is an open source automatic spike sorting package for multielectrode neurophysiological recordings that scales to probes with up to 64 interdependent channels.

We are also working actively on more sophisticated algorithms that will scale to hundreds/thousands of channels. This work is being done within the [phy project](https://github.com/kwikteam/phy), which is still experimental at this point.

## Overview

klusta implements the following features:

  • Kwik: An HDF5-based file format that stores the results of a spike sorting session.

  • Spike detection (also known as SpikeDetekt): an algorithm designed for relatively large probes, based on a flood-fill algorithm in the adjacency graph formed by the recording sites in the probe.

  • Automatic clustering (also known as Masked KlustaKwik): an automatic clustering algorithm designed for high-dimensional structured datasets.

## GUI

You will need a GUI to visualize the spike sorting results. No GUI is included in this repository.

We have developed two GUI programs:

  • [KlustaViewa](https://github.com/klusta-team/klustaviewa): scales up to 64 channels, well-tested by many users over the last few years.

  • phy KwikGUI: scales to hundreds/thousands of channels, still experimental. We will add a link when this GUI is ready (later in 2016).

## Technical details

klusta is written in pure Python. The clustering code, written in Python and Cython, currently lives in [another repository](https://github.com/kwikteam/klustakwik2/).

## Getting started

You will find installation instructions and a quick start guide in the [documentation](http://klusta.readthedocs.org/en/latest/) (work in progress).

## Links

## Credits

klusta is developed by [Cyrille Rossant](http://cyrille.rossant.net), [Shabnam Kadir](https://iris.ucl.ac.uk/iris/browse/profile?upi=SKADI56), [Dan Goodman](http://thesamovar.net/), [Max Hunter](https://iris.ucl.ac.uk/iris/browse/profile?upi=MLDHU99), and [Kenneth Harris](https://iris.ucl.ac.uk/iris/browse/profile?upi=KDHAR02), in the [Cortexlab](https://www.ucl.ac.uk/cortexlab), University College London.

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

klusta-3.0.1.tar.gz (69.0 kB view details)

Uploaded Source

Built Distribution

klusta-3.0.1-py2.py3-none-any.whl (84.5 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file klusta-3.0.1.tar.gz.

File metadata

  • Download URL: klusta-3.0.1.tar.gz
  • Upload date:
  • Size: 69.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for klusta-3.0.1.tar.gz
Algorithm Hash digest
SHA256 61f47ac4df8da2fdf3cb237d465ff09f57dc7b4950ad737c9eaca03ffc82678c
MD5 cee58dc1efbf1fa2e3c9204445874966
BLAKE2b-256 ce44144b94580d85ee1fe694c7c2f06d83b5dbb3a9e331d0bb2e03a6ee8268a1

See more details on using hashes here.

File details

Details for the file klusta-3.0.1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for klusta-3.0.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 270b559bee77a9aad559fed6bcf4fd1489c1cbd942c2a6d63695c6299027957e
MD5 c825bb9903ca70524088ccc14f7ea9a7
BLAKE2b-256 759a0b23eca7d61df0da12fef4ce846684e4a89d576f6a5deb05253a69fd076f

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