(Not sure if/how these scripts need to be modified to make then amenable this kind of usage).
/hsi-effects
The aim here is to produce a summary figure of the effect of disallowing each TREATMENT_ID from being run, compared to when all TREATEMENT_IDs can run, in terms of the different in deaths/dalys by age/sex. Code is under development: https://github.com/UCL/TLOmodel/issues/515
I propose the following two work flows to be developed using the comment-trigger workflow:
/scale-run
Run the model at scale (50k) using
scale_run.py
, 2010-2030, cycling through:multiple seeds
multiple health-system configurations:
disable_and_reject_all=True
mode=0
,mode=2
And posting errors to the comments.
[I think this might be done already?]
/calib
Generate the standard set of graphics that we are using to assess the calibration of the model to demographic and epidemiological data.
1) Run
long_run_all_diseases.py
2) Run the scripts in this folder and post the figures from each to the comment thread:
(One of which
analysis_hsi_descriptions.py
under development in https://github.com/UCL/TLOmodel/pull/436).(Not sure if/how these scripts need to be modified to make then amenable this kind of usage).
/hsi-effects The aim here is to produce a summary figure of the effect of disallowing each
TREATMENT_ID
from being run, compared to when allTREATEMENT_ID
s can run, in terms of the different in deaths/dalys by age/sex. Code is under development: https://github.com/UCL/TLOmodel/issues/515