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-hypernode.com/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.dev0.tar.gz (67.5 kB view details)

Uploaded Source

Built Distribution

klusta-3.0.dev0-py2.py3-none-any.whl (82.9 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file klusta-3.0.dev0.tar.gz.

File metadata

  • Download URL: klusta-3.0.dev0.tar.gz
  • Upload date:
  • Size: 67.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for klusta-3.0.dev0.tar.gz
Algorithm Hash digest
SHA256 c21a890879e82e8a3bf440ae240f9dc987199e3030191b25026a9ff29486a08d
MD5 6cdce50ab49d3c63408cbc2812ec6fa0
BLAKE2b-256 3c5c769856b7258f074af844a2069742d7364cf1dc8080eedea81b8da39c8d59

See more details on using hashes here.

File details

Details for the file klusta-3.0.dev0-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for klusta-3.0.dev0-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 d58ee0f6610bad939bbb862b6f8db8c4fd79e96a6faed2f2aac9d89f4ffb4864
MD5 8edaaa560936a58521f139a194129bc8
BLAKE2b-256 c86582c7b8477280cb08f54653b4322f72298f696c97a21982acc06f5438795e

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