3.2. The stochastic modelling framework

3.2.1. The static stochastic modelling class

Go to the folder framework in your folder containing the exercise data. For static stochastic modelling, you can use the template script stochStaticMod.py. Open the script, and run it. Type dir to see the contents of the folder.

Question: The model class contains a number of methods. In which section (method) do we need to put calculations representing processes (or importing data) that are stochastic, without time? Idem, purely deterministic calculations without uncertainty?

  1. Stochastic without time: premcloop. Deterministic: initial.

  2. Stochastic without time: postmcloop. Deterministic: initial.

  3. Stochastic without time: initial. Deterministic: initial.

  4. Stochastic without time: initial. Deterministic: premcloop.

Correct answers: d.

Feedback: Premcloop: deterministic calculations done at the start. Intial: is run for each Monte Carlo realization, in this case for 10 MC runs. Postmcloop: calculates sample statistics at the end.

3.2.2. The dynamic stochastic modelling class

In the same framework folder, open and run stochDynamicMod.py. It is a template script for dynamic stochastic modelling.

Question: What is the dynamic method doing in the stochDynamicMod.py script?

  1. It is run for each Monte Carlo realization, and each time step.

  2. It is run for the first Monte Carlo realization, for each time step.

  3. It is run for each Monte Carlo realization, without time steps.

  4. It passes information from the initial to the postmcloop.

Correct answers: a.

Feedback: none