Skip to main content

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

Project description

# Spykesim ![PyPI](https://img.shields.io/pypi/v/spykesim.svg)

spykesim is a Python module that offers functions for measuring the similarity between two segmented multi-neuronal spiking activities. Extended edit similarity measurement is implemented. You can find the details in the following paper. bioArxiv: https://www.biorxiv.org/content/early/2017/10/30/202655 # Supported Operating Systems Ubuntu and MacOS. For Windows users: Please consider to use Ubuntu via Windows Subsystem for Linux.

# Installation You can install via pip. `python pip install spykesim `

## Dependencies

  • Python (>= 3.5)
  • Cython
  • Numpy
  • tqdm

# 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 0.1.0
Filename, size File type Python version Upload date Hashes
Filename, size spykesim-0.1.0.tar.gz (14.3 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