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
)