Model Validation

Pleione’s parameter calibration scripts call an external script to calculate fitness to experimental data. You could use one of the following script to calculate the fitness of your parameterized model against an independent experimental data set:

python3 -m pleione.bng2-doerror --data foo --sims bar \
--file output.txt --error MWUT --crit utable.txt

OR

python3 -m pleione.kasim-doerror --data foo --sims bar \
--file output.txt --error MWUT --crit utable.txt

OR

python3 -m pleione.nfsim-doerror --data foo --sims bar \
--file output.txt --error MWUT --crit utable.txt

OR

python3 -m pleione.piskas-doerror --data foo --sims bar \
--file output.txt --error MWUT --crit utable.txt

Note

Fitness Function Pleione currently support ten goodness of fit functions. To calculate more than one function, include a comma-only separated list such as MWUT,SSQ. In doing so, this will calculate the contribution of both o more metrics to the overall error and aid to validate of dischard a model calibration. More information in Objective Functions

Note

Need Help? Type python3 -m pleione.$STOCH_ENGINE-doerror --help where $STOCH_ENGINE can be the currently supported stochastic engines: BNG2, NFsim, KaSim and PISKaS (all in lower cases, for instance nfsim-doerror)