If date_window_size is 0, this function returns all available forecasts submitted on every day in dates.

load_forecasts(
  models = NULL,
  dates = NULL,
  date_window_size = 0,
  locations = NULL,
  types = NULL,
  targets = NULL,
  source = "zoltar",
  hub_repo_path,
  data_processed_subpath = "data-processed/",
  as_of = NULL,
  hub = c("US", "ECDC"),
  verbose = TRUE
)

Arguments

models

Character vector of model abbreviations. Default all models that submitted forecasts meeting the other criteria.

dates

The forecast date of forecasts to retrieve. A vector of one or more Date objects or character strings in format “YYYY-MM-DD” Default to all valid forecast dates.

date_window_size

The number of days across each date in dates parameter to look for the most recent forecasts. Default to 0, which means to only look at the dates parameter only.

locations

list of location codes. Default to all locations with available forecasts.

types

Character vector specifying type of forecasts to load: "quantile" and/or "point". Default to all valid forecast types.

targets

character vector of targets to retrieve, for example c('1 wk ahead cum death', '2 wk ahead cum death'). Default to NULL which stands for all valid targets.

source

string specifying where forecasts will be loaded from: either "local_hub_repo" or "zoltar". Default to "zoltar".

hub_repo_path

path to local clone of the forecast hub repository

data_processed_subpath

folder within the hub_repo_path that contains forecast submission files. Default to "data-processed/", which is appropriate for the covid19-forecast-hub repository.

as_of

character for date time to load forecasts submitted as of this time from Zoltar. Ignored if source = "local_hub_repo". It could use the format of one of the three examples: "2021-01-01", "2020-01-01 01:01:01" and "2020-01-01 01:01:01 UTC". If you would like to set a timezone, it has to be UTC now. If not, helper function will append the default timezone to your input based on hub parameter. Default to NULL to load the latest version.

hub

character vector, where the first element indicates the hub from which to load forecasts. Possible options are "US" and "ECDC".

verbose

logical to print out diagnostic messages. Default is TRUE.

Value

data.frame with columns model, forecast_date, location, horizon, temporal_resolution, target_variable, target_end_date, type, quantile, value, location_name, population, geo_type, geo_value, abbreviation

Details

If date_window_size is not 0, this function will look for all the latest forecasts that are submitted within window size for each day in dates.

Examples

# Load forecasts from US forecast hub # This call only loads the latest forecast submitted on "2021-07-26" in # a 12-day window w.r.t "2021-7-30". load_forecasts( models = "COVIDhub-ensemble", dates = "2021-07-30", date_window_size = 11, locations = "US", types = c("point", "quantile"), targets = paste(1:4, "wk ahead inc case"), source = "zoltar", verbose = FALSE, as_of = NULL )
#> get_token(): POST: https://zoltardata.com/api-token-auth/
#> get_resource(): GET: https://zoltardata.com/api/projects/
#> get_resource(): GET: https://zoltardata.com/api/project/44/models/
#> get_resource(): GET: https://zoltardata.com/api/project/44/timezeros/
#> # A tibble: 32 × 16 #> model forecast_date location horizon temporal_resolu… target_variable #> <chr> <date> <chr> <chr> <chr> <chr> #> 1 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 2 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 3 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 4 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 5 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 6 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 7 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 8 COVIDhub-ensemble 2021-07-26 US 1 wk inc case #> 9 COVIDhub-ensemble 2021-07-26 US 2 wk inc case #> 10 COVIDhub-ensemble 2021-07-26 US 2 wk inc case #> # … with 22 more rows, and 10 more variables: target_end_date <date>, #> # type <chr>, quantile <dbl>, value <dbl>, location_name <chr>, #> # population <dbl>, geo_type <chr>, geo_value <chr>, abbreviation <chr>, #> # full_location_name <chr>
# Load forecasts from ECDC forecast hub # This function call loads the latest forecasts in each 2-day window # w.r.t "2021-03-08" and "2021-07-27". load_forecasts( models = "ILM-EKF", hub = c("ECDC", "US"), dates = c("2021-03-08", "2021-07-27"), date_window_size = 1, locations = "GB", targets = paste(1:4, "wk ahead inc death"), source = "zoltar" )
#> get_token(): POST: https://zoltardata.com/api-token-auth/
#> get_resource(): GET: https://zoltardata.com/api/projects/
#> get_resource(): GET: https://zoltardata.com/api/project/238/models/
#> get_resource(): GET: https://zoltardata.com/api/project/238/timezeros/
#> # A tibble: 192 × 12 #> model forecast_date location horizon temporal_resolution target_variable #> <chr> <date> <chr> <chr> <chr> <chr> #> 1 ILM-EKF 2021-03-08 GB 1 wk inc death #> 2 ILM-EKF 2021-03-08 GB 1 wk inc death #> 3 ILM-EKF 2021-03-08 GB 1 wk inc death #> 4 ILM-EKF 2021-03-08 GB 1 wk inc death #> 5 ILM-EKF 2021-03-08 GB 1 wk inc death #> 6 ILM-EKF 2021-03-08 GB 1 wk inc death #> 7 ILM-EKF 2021-03-08 GB 1 wk inc death #> 8 ILM-EKF 2021-03-08 GB 1 wk inc death #> 9 ILM-EKF 2021-03-08 GB 1 wk inc death #> 10 ILM-EKF 2021-03-08 GB 1 wk inc death #> # … with 182 more rows, and 6 more variables: target_end_date <date>, #> # type <chr>, quantile <dbl>, value <dbl>, location_name <chr>, #> # population <int>