- Notifications
You must be signed in to change notification settings - Fork3
Extended edit similarity measurement for high dimensional discrete-time series signal (e.g., multi-unit spike-train).
License
oist-ncbc/spykesim
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
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 details in the following paper.
https://www.frontiersin.org/articles/10.3389/fninf.2019.00039
This library is re-implementation of the algorithm. The original implementation can be found inthis repo.
This library tested on Ubuntu and MacOS.
For Windows users: Please consider to use Ubuntu viaWindows Subsystem for Linux.
If you do not have Python3.7 on your environment, you may useAnaconda.
Cython andNumpy needs to be preinstalled as these will be used in the installation process.
If you have not installed these packages, run the following:
pip install numpy cython
You can install this library via pip as well:
pip install spykesim
or you may clone and build by yourself:
git clone https://github.com/KeitaW/spykesim.gitcd spykesimpython setup.py build_ext --inplace install
- Python (>= 3.7)
- Numpy(Needs to be preinstalled)
- Cython(Needs to be preinstalled)
- scipy
- tqdm
- h5py
You can find a tutorial indoc.
You can use the following bib entry to cite this work:
@article{Watanabe:2019eq,author = {Watanabe, Keita and Haga, Tatsuya and Tatsuno, Masami and Euston, David R and Fukai, Tomoki},title = {{Unsupervised Detection of Cell-Assembly Sequences by Similarity-Based Clustering}},journal = {Frontiers in Neuroinformatics},year = {2019},volume = {13},month = may}
About
Extended edit similarity measurement for high dimensional discrete-time series signal (e.g., multi-unit spike-train).