Open ChrisRackauckas opened 1 year ago
TA3 data requests for TA1. For June 1st 2021 – June 1st, 2022, we need the following:
TA2 model JSONs can be found at https://github.com/DARPA-ASKEM/program-milestones/issues/9
Vaccination data: https://github.com/DARPA-ASKEM/program-milestones/pull/11
@ChrisRackauckas Where are the results associated with the "real" training/test dataset? I only see placeholder synthetic results. https://chrisrackauckas.github.io/ASKEM_Evaluation_Staging/dev/Scenario3/Evaluation_Scenario_3/#Question-1
It just merged 8 minutes ago: https://github.com/ChrisRackauckas/ASKEM_Evaluation_Staging/pull/67. You can start running the script if you want to see it, takes just about 5 minutes. The full bound found that the TA2 model swap didn't pass a unit test due to a tolerance that was a bit too low (https://github.com/ChrisRackauckas/ASKEM_Evaluation_Staging/actions/runs/4067984576) and that needs to be fixed for the full builder to run again (already triggered https://github.com/ChrisRackauckas/ASKEM_Evaluation_Staging/actions/runs/4067975452/jobs/7005966223)
The MITRE scenario specified "explore the space of closely related models that incorporate either deaths, hospitalizations, or both."
TA2 provided SIR, SIRD, SIRH, SIRDH variants and (as I understand) MITRE expects calibration and testing on all of them. Your notebook only considered SIR vs. SIRDH. Can you provide the test performance metric (L2 norm) for all these variants against the test dataset?
Yes, that's in the files already if you look at the code.
Where is that? I'm looking at here: https://chrisrackauckas.github.io/ASKEM_Evaluation_Staging/dev/Scenario3/Evaluation_Scenario_3/#Question-2:-Add-Hospitalizations-and-Deaths
I only see
norm(solve(_prob, saveat = t_test)[S] - data_test[1][2]) + norm(solve(_prob, saveat = t_test)[I] - data_test[2][2]) + norm(solve(_prob, saveat = t_test)[R] - data_test[3][2])
norm(solve(_prob2, saveat = t_test)[S] - data_test[1][2]) + norm(solve(_prob2, saveat = t_test)[I] - data_test[2][2]) + norm(solve(_prob2, saveat = t_test)[R] - data_test[3][2]) + norm(solve(_prob2, saveat = t_test)[H] - data_test[4][2]) + norm(solve(_prob2, saveat = t_test)[D] - data_test[5][2])
I was expecting to see the same as above but for _probN
where N
is for each of SIR, SIRH, SIRD, SIRDH
.
That's the later questions. Question 2 only has those two models if I'm reading the text correctly. Are you asking about Question 6?
Nope, these models are meant for the Question 2 as I understand. Otherwise, it'd be a rather poor model-space selection process to just select between 2 things.