Hi cgastald,cgastald wrote:Hello!
Preferred was off, therefore it was not the problem. I am working more on the network, however in the meantime I have an other question: can I get in the output of the simulation the covariance between patterns, i.e the row data to make figure 3.f?
you can't get that information directly from the output, but you have computed most of it already to get the "pat" file. If you used my example implementation the second column in the rf1.pat file for instance will contain the mean firing rate of the evoked activity during a fixed time window following the stimulation of that pattern. If you haven't used my scripts, it's also straight forward to compute this from the ras files. The rest of the analysis is best done in some higher level programming language such as Python. All that's left to do, is to convert the sparse coordinate form of the pat file into a dense numpy array a by looping over the lines in the pat file and assigning a[$1]=$2 where I wrote $x for the value in the x-th column. Then you have a dense array for each pattern and you can use numpy functions such as cov or corrcoef on them to compute the correlation or covariance matrix. Hope that helps.