Universal Data Analyzer (UDA) emerged in 2014 from the need to statistically evaluated data create by OMNeT++. Evaluation of real-world measurements carried out by FlowPing was required later. That time modular architecture was designed and implemented. Currently, UDA's public functions allow evaluation of OMNeT++ and FlowPing measurements.
Processed files are returned in DataFrame format for further analysis.
Current OMNeT++ modul can read .sca, .vec, and .vci files. Histogram measurements are on TODO.
In order to use UDA, required Python libraries need to be installed. Then UDA data loaders can be used. For example, OMNeT++ project loader:
from uda.loaders.omnetpp import Omnetpp
o= Omnetpp(SIMNAME, RUNID)
vec_df_= o.vec.getDataFrame()
vci_df_= o.vci.getDataFrame()
sca_df_= o.sca.getDataFrame()More sofisticated analysis using OMNeT++ loader can be seen in Examples
- Implementation of OMNeT++ histogram format