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
)