Unit tests #4
Description
A suite of unit tests should be written for the framework (preferably using unittest pytest). At the first instance, this should include:
- checking that the number of species and observables is correctly identified
- checking that the size and shape of the loaded observations is correct (number of observation files, length of time series, number of observables)
- checking that the stoichiometry matrix is correctly constructed
- checking that various expressions are correctly parsed and (for kinetic laws) mapped to appropriate functions
These should be verified against a standard model, probably one of the examples already included. Further tests could:
- check that appropriate warnings/errors are generated when observations are misspecified or when an unsuitable algorithm is chosen
- compare the behaviour of the simulator or the inference engine with expected results [this requires more consideration to ensure good coverage and meaningful comparisons]