PRISMA

This folder contains an example file to show the preprocessing step
with the sally toolkit (see http://www.mlsec.org/sally/). Before
executing the examples please extract asap.tar.gz to find all data
necessary to understand the processing chain from the raw data
(asap.raw) to the sally file (asap.sally) and the optimized file
(asap.fsally). The asap.sally file can be produced as follows:

sally -c asap.cfg asap.raw asap.sally

this call generates asap.sally from the raw data found in asap.raw. To
speed up the loading of the data in R, one should apply the
sallyPreprocessing.py python script as follows:

python sallyPreprocessing.py asap.sally asap.fsally

Now the data is ready to be efficiently loaded and processed in R.