Standard generics for DiseasyEnsemble objects

Standard generics for DiseasyEnsemble objects

Usage

# S3 method for class 'DiseasyEnsemble'
print(x, n = 5, width = 200, ...)

# S3 method for class 'DiseasyEnsemble'
summary(object, ...)

# S3 method for class 'DiseasyEnsemble'
predict(
  object,
  observable,
  prediction_length,
  stratification = NULL,
  context_length = 30,
  by_model = FALSE,
  ...
)

# S3 method for class 'DiseasyEnsemble'
plot(
  x,
  observable,
  prediction_length,
  stratification = NULL,
  context_length = 30,
  by_model = FALSE,
  ...
)

Arguments

x, object

(DiseasyEnsemble)
Ensemble object to print, summarise or plot.

n

(integer(1))
The number of models to produce output for.

width

(integer(1))
The maximum number of characters to print.

...

(Any)
Unused. Required to match the generic signature.

observable

(character)
The observable to provide data or prediction for.

prediction_length

(numeric)
The number of days to predict. The prediction start is defined by last_queryable_date of the ?DiseasyObservables R6 class.

stratification

(list(quosures) or NULL)
Use rlang::quos(...) to specify stratification. If given, expressions in stratification evaluated to give the stratification level.

context_length

(integer(1))
Number of days prior to prediction to plot observable for.

by_model

(logical(1))
Should the plot be stratified by model?

Value

NULL (called for side effects)

data.frame-like object with columns with the predictions for the observable from the ensemble by date, stratification and model (optional).

Examples

  observables <- DiseasyObservables$new(
    diseasystore = DiseasystoreSeirExample,
    conn = DBI::dbConnect(duckdb::duckdb())
  )

  # Set the reference date in the observables module
  observables$set_last_queryable_date(
    observables$ds$min_start_date + 30
  )

  # Create a DiseasyEnsemble object
  ensemble <- combineasy(
    model_templates = list(DiseasyModelG0, DiseasyModelG1),
    modules = tidyr::expand_grid(
      observables = list(observables)
    )
  )

  print(ensemble)
#> DiseasyEnsemble: DiseasyModelG0 (hash: dce1d), DiseasyModelG1 (hash: 108b6) 

  summary(ensemble)
#> DiseasyEnsemble consisting of:
#> DiseasyModelG0: 1 
#> DiseasyModelG1: 1 

  plot(ensemble, "n_positive", prediction_length = 30)


  rm(ensemble, observables)