HI Cora,
Thanks for your reply. You said “There are other keyword arguments to the run function”, but I looked at the Mimi User Guide and at ‘Running a Model’ it only shows ‘run(mymodel)’. It seems I am missing a listing of functions with their descriptions and arguments. Where can I find the other keyword arguments to the ‘run’ function?
I input into Jupyter notebook as per your instructions (I think);
simdef = MimiFUND.getmcs()
Mimi.replaceRV!(simdef, :climatesensitivity, Normal(1.5,0.003))
m = MimiFUND.get_model()
Mimi.addSave!(simdef, :climatedynamics, :climatesensitivity)
sim_results = run(simdef, m, 100);
sim_results[:climatedynamics, :climatesensitivity]
I used a very small std deviation for the normal distribution of climate sensitivity (CS) so I expected the 100 results to be all close to 1.5. The results returned 30 values, averaging 3.52, which is near the FUND default, not my modified CS. The other 70 values were not displayed, only …
How do I get results using my modified CS random variable? Does the command ‘m = MimiFUND.get_model()’ get the default model including the default random variables and overwrite my CS variable?
How do I display all the values? Notebook usually presents a long list of values, such as 300 years of temperatures, in a window with a slider.
I also want to use the the function:
scc = MimiFUND.compute_scco2(m, year = 2020, eta = 0., prtp = 0.05, equity_weights = false, n = 100) which is described at https://github.com/fund-model/MimiFUND.jl/
But when preceding this with Mimi.replaceRV!(simdef, :climatesensitivity, Normal(1.5,0.003))
the compute_scc ignores my CS and uses the FUND default values.
I would like to run the scco2 function in Monte Carlo mode while using my modified CS values. How can I do this?