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Christian Borgelt's Web Pages

Pattern Spectrum Estimation for CoCoNAD

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spectra.pdf (58781 kb) spectra from surrogates and estimation
spectra.zip (100 kb) spectra.tar.gz (95 kb) scripts and other source files
psf+psr.zip (78 kb) psf+psr.tar.gz (70 kb) Python scripts for Pattern Spectrum Filtering
and Pattern Set Reduction

Description

The document spectra.pdf contains the result diagrams for the complete set of experiments with pattern spectrum estimation for CoCoNAD (Continuous-time Closed Neuron Assembly Detection), as it is described in the paper [Borgelt and Picado-Muiño 2014]. It even contains additional results that go beyond the setup described in the paper, which only considered a recording time of 3s, and list results for 2, 3, 4, and 5s recording time. For each parameter setting, the result of generating and analyzing 10,000 surrograte data sets is shown on the left, the result of pattern spectrum estimation is shown on the right.

The archives spectra.{zip,tar.gz} contain scripts and other source files, with which the experiments were conducted and the document with the result diagrams was created.

The scripts in the archives psf+psr.{zip,tar.gz} implement the full analysis process of parallel (spike) trains/point processes as it is described (although for standard frequent item set mining) in [Picado-Muiño et al. 2013] and [Torre et al. 2013]. A documentation of these scripts can be found here. Call the main script ccn+psf+psr.py without any arguments to obtain a help message that shows the invocation and the available options.

Note that the scripts etc. were developed on/for a GNU/Linux system (Ubuntu 14.04) and thus are directly executable on such a system or a similar one (that is, some other GNU/Linux distribution). Although at least most of the Python scripts should also be working on a Windows system (with the possible exception of the parallelization scripts), most of the other scripts (like the run script, which is the main control script, and the makefile, which controls generating the diagrams from the result data) may need porting to batch files or something similar.

On a GNU/Linux system, the following software needs to be installed to run the experiments:

On such a system the experiments can be run by simply calling the main script run (in the directory spectra) on the command line, which does everything. The execution of the experiments exploits 4-fold parallelization, thus making full use of the quadcore processors basically all modern computers are equipped with. The progress of the experiments can be followed on the command line, to which regular progress messages are written. Once all experiments are completed (which, even on a modern computer system, can take several weeks for all parameter seetings), the result diagrams are created and compiled into the final documents, which are also directly available above.

References