| spectra.pdf | (58781 kb) | spectra from surrogates and estimation |
| spectra.zip | (100 kb) | scripts and other source files |
| spectra.tar.gz | (95 kb) | |
| psf+psr.zip | (78 kb) | Python scripts for Pattern Spectrum Filtering |
| psf+psr.tar.gz | (70 kb) | and Pattern Set Reduction |
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 or later) 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:
spectra
package will also work without this extension module, namely by
falling back on a pure Python replacement, which, however, is
slower by a factor of about 40 or more),pdflatex program,mptopdf command,bash,
awk, tar etc.) and are easy to install
otherwise.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.