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 SDA

OR

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

OR

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

OR

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

Note

Fitness Function

Pleione currently support 9 algebraics and 3 statistical tests as fit functions. To calculate more than one function, include a list such as SDA SSQ CHISQ. In doing so, this will calculate the contribution of both o more metrics to the overall error and aid to validate of discard a model calibration. More information in Objective Functions

Note

All fitness functions

Use the --do_all True argument to calculate all fitness functions included in Pleione. You should provide a table with critical values (see example folder for the one-tail table)

Note

(non-)Rejection matrices

The --report True argument will print to the console relevant calculations for the statistical tests.

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)