load_forecasts.Rd
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 )
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 |
locations | list of location codes. Default to all locations with available forecasts. |
types | Character vector specifying type of forecasts to load: |
targets | character vector of targets to retrieve, for example
|
source | string specifying where forecasts will be loaded from: either
|
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 |
as_of | character for date time to load forecasts submitted as of this time from Zoltar.
Ignored if |
hub | character vector, where the first element indicates the hub
from which to load forecasts. Possible options are |
verbose | logical to print out diagnostic messages. Default is |
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
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
.
# 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 )#>#>#>#>#> # 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" )#>#>#>#>#> # 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>