Skip to main content

Python module that offers functions for measuring the similarity between two segmented multi-neuronal spiking activities.

Project description

# <img src=”docs/spykesim_logo/wtext/spykesim_wtext.svg” width=”320px”> [![PyPI](https://img.shields.io/pypi/v/spykesim.svg)](https://pypi.org/project/spykesim/) [![MIT License](http://img.shields.io/badge/license-MIT-blue.svg?style=flat)](LICENSE) [![Build Status](https://travis-ci.org/KeitaW/spykesim.svg?branch=master)](https://travis-ci.org/KeitaW/spykesim)

spykesim is a Python module that offers functions for measuring the similarity between two segmented multi-neuronal spiking activities.

Edit similarity measurement is implemented. You can find details in the following paper.

bioArxiv: https://www.biorxiv.org/content/early/2017/10/30/202655

This library is re-implementation of the algorithm. The original implementation can be found in [this repo](https://github.com/KeitaW/Chaldea).

# Supported Operating Systems This library tested on Ubuntu and MacOS.

For Windows users: Please consider to use Ubuntu via [Windows Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/install-win10).

# Installation If you do not have Python3.6 on your environment, you may use [Anaconda](https://www.anaconda.com/distribution/).

[Cython](https://github.com/cython/cython) and [Numpy](https://github.com/numpy/numpy) needs to be preinstalled as these will be used in the installation process.

If you have not installed these packages, run the following: `bash pip install numpy cython ` You can install this library via pip as well: `bash pip install spykesim ` or you may clone and build by yourself: `bash git clone https://github.com/KeitaW/spykesim.git cd spykesim python setup.py build_ext --inplace install `

## Dependencies

  • Python (>= 3.6)
  • Numpy(Needs to be preinstalled)
  • Cython(Needs to be preinstalled)
  • scipy
  • tqdm
  • h5py

# Tutorial You can find a tutorial in [doc](https://github.com/KeitaW/spykesim/blob/master/docs/tutorial.ipynb).

# Citation You can use the following bib entry to cite this work: ` @article{Watanabe:2017bla, author = {Watanabe, Keita and Haga, Tatsuya and Euston, David R and Tatsuno, Masami and Fukai, Tomoki}, title = {{Unsupervised detection of cell-assembly sequences with edit similarity score}}, year = {2017}, pages = {202655}, month = oct } `

#

This project uses the following repository as a template.

https://github.com/kennethreitz/samplemod Copyright (c) 2017, Kenneth Reitz

Project details


Download files

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

Files for spykesim, version 1.0.0
Filename, size File type Python version Upload date Hashes
Filename, size spykesim-1.0.0.tar.gz (12.8 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page