spykesim 0.1.1

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

# Spykesim [](https://pypi.org/project/spykesim/0.1.0/) [](LICENSE) [](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. 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 This library tested on Ubuntu and MacOS.

For Windows users: Please consider to use Ubuntu via Windows Subsystem for Linux.

# Installation If you do not have Python3.x, 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 (>= 3.5)

• 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