Software developed as part of this project, or related to the work of this project, will be made available here.
|Spiky is a Graphical user interface (Matlab), developed by Dr. Thomas Kreuz, which can be used to calculate and visualize the ISI and SPIKE distance as well as SPIKE-Synchronization between two (or more) spike trains. Links to the Spiky Facebook group and YouTube channel can be found here:PySpike is a Python library for the numerical analysis of spike train similarity. It provides functions to compute multivariate profiles, distance matrices, as well as averaging and general spike train processing. All computation intensive parts are implemented in C via cython to reach a competitive performance (factor 100-200 over plain Python). PySpike has been developed by Mario Mulansky and Thomas Kreuz. Supporting documentation can be found here: http://arxiv.org/pdf/1603.03293v2.pdfcSPIKE is an easy to use spike train analysis software, and has been developed by COSMOS ESR Eero Satuvuori (project 9). It is run on Matlab command line and it uses MEX files with C++ backends for speed. cSPIKE implements functions such as ISI-distance, SPIKE-distance, SPIKE synchronization and their adaptive variants as well as basic functions for plotting spike trains and profiles.|
|Two libraries, both written in Rust by ESR Janis Goldschmidt. The first is for solving ODEs, the second is for performing Gram-Schmidt Orthonormalizationrust-freude: ODE librarygram_schmidt: Gram-Schmidt Orthonormalization|
|Source code from the Nonlinear Time Series Analysis Group at Universitat Pompeu Fabra|
DAMOCO: Data Analysis with Models Of Coupled Oscillators
MATLAB Toolbox for multivariate time series analysis
Björn Kralemann, Michael Rosenblum, Arkady Pikovsky