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New simplified config format #72
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…ha. It just worked because it used last config value> fixed
This was referenced Oct 3, 2023
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Config Structure changes
The concept of scenario for outcomes is phased out. One config = One structure. Only modifiers can be changed.
The configs sections are described below. There are four types of runs but users should only be advised to do either (seir+outcomes) or (seir+outcomes+inference).
So what is the purpose of the StackedModifier if every intervention is applied ?
Note that the config elements can be put in any order
So how do the new modifiers sections work. There are two possibilities:
A. Simple config (one config = one run, no modifiers scenarios)
if the key
scenarios:
is not present undermodifiers_seir
ormodifiers_outcomes
, then All modifiers under this sections are runs.B. Multiple scenarios config
if the key
scenarios:
is present undermodifiers_seir
ormodifiers_outcomes
, then the user can specify a scenario to be run at runtime. Only modifiers under this scenario are runs.If the user does not specify a scenario, all combinations of
modifiers_seir
andmodifiers_outcomes
are runs (2 of each makes 4 runs)substructure:
Outcomes
Probabilities
The
distribution: fixed
can be omitted:is still valid but can be abbreviated
this applies to all probabilities distributions for gempyor: modifiers, outcomes, parameters, ...
Nomenclature changes
Interventions
changed
and removed ReduceR0
The
template
is now calledmethod
to be consistent with initial_conditions.In a
StackedModifiers
the different scenario used to be listed underscenarios
-> this has been changed tomodifiers
For a ModifierModifier,
baseline_scenario
has changed tobaseline_modifer
For outcomes intervention_param_name has been changed to modifier_parameter
geoid:
change geoid to subpop
affected_geoids > subpop
place > subpop
For
spatial_setup
,popnode_key
is deprecated (alwayspopulation
) and codenames is deprecated (alwayssubpop
)Outcomes
duration_name
>outcome_prevalence_name
Initial Conditions
SetInitialCondition comp changed to mc_name
Fitting initial conditions
initial_conditions:
method: SetInitialConditionsFolderDraw
seeding_file_type: init
perturbation:
distribution: truncnorm
mean: 0
sd: 0.02
a: -1
b: 1
and in the initial initial condition files are csvs or parquet like
subpop,mc_name,amount,pertub
AK, R_age_01_19, .3, TRUE
AK, S_age_01_19, remain, FALSE
...
Parameters:
timeserie
>timeseries
intervention_overlap_operation
>stacked_modifier_method
Filestructure:
we don't nest scenarios in folder (e.g
{setup_name}/{npi_scenario}/...
now we have a single folder depth
/{setup_name}_{seir_modifiers_scenario}_{outcome_modifiers_scenario}/
. if one of the modifier scenario does not exist (cause no modifiers for e.g seir, or because no scenario for said modifiers) then we just don't write it.TODO
from @alsnhll in #62
Useful messages
https://iddynamicsjhu.slack.com/archives/GU0SBC2AC/p1693600672108579?thread_ts=1693399856.162839&cid=GU0SBC2AC Alison
https://iddynamicsjhu.slack.com/archives/GU0SBC2AC/p1693223628997289 Koji
BIG TODO that needs discussion
From Alison:
Consider changing the valence/sign of interventions. Currently, if the value is given as positive, this results in a REDUCTION of the parameter. This made sense when the interventions were called REDUCE, but now they are called MODIFY, so it is confusing that the default is negative and if you want an increase, you have to give a NEGATIVE value.
In ModifierModifier, change the name of baseline_scenario to baseline_intervention