This page provides you with the source codes of the computations underlying

Andrzejak RG, Mormann F, Kreuz T.  2014.  Detecting determinism from point processes. Phys. Rev. E. 90, 062906

If you use the source codes, please make sure that you give a reference to the manuscript. (The correct way to cite this paper is shown above, no page numbers should be given.)

Source code

In order to understand the source code, you should first read the manuscript. To find the pdf-file, please follow the link at the top of this page.

Below you find a Zip-File with all source codes. This includes the function: Andrzejak_PRE_90_062906_MeasureS.m, which calculates the rank-based nonlinear prediction score for spike trains S. To understand how to use it, we recommend to have a look at the function Andrzejak_PRE_90_062906_CALL.m. This allows you to calculate S for the different parameters, systems, and settings as used in Figure 1a-e of our paper. In particular, it calls also the scripts that generate our models, superimposes the spike trains with noise, and so on. Using this script, you should be able to reproduce our Figure 1a-e. 

The source is only partly commented. If you have problems in understanding how certain parts of the code work, please contact us. We will try to comment the corresponding part of the code and upload a new version.

Before publishing the source code, we have simplified it and changed variable names to allow for a better understanding. We are confident that, also with these simplifications, the source code contains no bugs. However, if you encounter problems or bugs, please contact us.  

  • All source codes zipped: link
  • Identical material mirrowed at library page: e-Repositori

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The source codes, data and results on these sites are free of charge for research and education purposes only. Any commercial or military use is prohibited. All resources are provided without any expressed or implied warranty. In no event the authors of the article or any of their host institutions are liable for any damages arising from the use of the software, data or results.