Numbers For Individual Iterations

[gaianoseworthy]

I'm not 100% sure if this is better as a feature request or just a standard issue, but I'll tag feature require either way.

Would there be a way (or could there be a way) to extract the number of susceptible individuals in a network after, let's say, 100 iterations? This would be useful for if we want to develop a probability distribution of the model given certain settings.

[GiulioRossetti]

Such value can be obtained by aggregating individual iterations results in the proper way for basically any of the model compartments (as done, for instance, when building the trends for visualization purposes).

Actually, if I'm not mistaken, for the susceptible class build_trend will allow you to compute such value. Just run the simulation for N iterations, build the trends, and access the last susceptible count. After that, you can execute other iterations if you need to continue the simulation and once finished - to visualize the overall results - extend the original iterations' set with the novel one.

Maybe I missed something in your question, though.

[gaianoseworthy]

@GiulioRossetti Thank you for your comment! I got it all figured out!
As a quick followup, is there any way to automatically end the simulation if every person is either susceptible or removed?

[GiulioRossetti]

Unfortunately, there is not.

However you can implement something like that following a same logic as before. For instance, you can execute an iteration (or a bunch of them) within a loop and impose as exit condition the value of an indicator you build starting from the trend counters (e.g., considering a simple SIR model, controlling when S=0 or when R=N)

[gaianoseworthy]

Ah okay, thank you for the quick replies and all the help!