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Convert model output to a model_out_tbl class object.

Source: R/as_model_out_tbl.R
as_model_out_tbl.Rd

Convert model output to a model_out_tbl class object.

Usage

as_model_out_tbl(
  tbl,
  model_id_col = NULL,
  output_type_col = NULL,
  output_type_id_col = NULL,
  value_col = NULL,
  sep = "-",
  trim_to_task_ids = FALSE,
  hub_con = NULL,
  task_id_cols = NULL,
  remove_empty = FALSE
)

Arguments

tbl

a data.frame or tibble of model output data returned from a query to a <hub_connection> object.

model_id_col

character string. If a model_id column does not already exist in tbl, the tbl column name containing model_id data. Alternatively, if both a team_abbr and a model_abbr column exist, these will be merged automatically to create a single model_id column.

output_type_col

character string. If an output_type column does not already exist in tbl, the tbl column name containing output_type data.

output_type_id_col

character string. If an output_type_id column does not already exist in tbl, the tbl column name containing output_type_id data.

value_col

character string. If a value column does not already exist in tbl, the tbl column name containing value data.

sep

character string. Character used as separator when concatenating team_abbr and model_abbr column values into a single model_id string. Only applicable if model_id column not present and team_abbr and model_abbr columns are.

trim_to_task_ids

logical. Whether to trim tbl to task ID columns only. Task ID columns can be specified by providing a <hub_connection> class object to hub_con or manually through task_id_cols.

hub_con

a <hub_connection> class object. Only used if trim_to_task_ids = TRUE and tasks IDs should be determined from the hub config.

task_id_cols

a character vector of column names. Only used if trim_to_task_ids = TRUE to manually specify task ID columns to retain. Overrides hub_con argument if provided.

remove_empty

Logical. Whether to remove columns containing only NA.

Value

A model_out_tbl class object.

Examples

if (requireNamespace("hubData", quietly = TRUE)) {
  library(dplyr)
  hub_path <- system.file("testhubs/flusight", package = "hubUtils")
  hub_con <- hubData::connect_hub(hub_path)
  hub_con %>%
    filter(output_type == "quantile", location == "US") %>%
    collect() %>%
    filter(forecast_date == max(forecast_date)) %>%
    as_model_out_tbl()
}
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
#> # A tibble: 92 × 8
#>    model_id     forecast_date horizon target location output_type output_type_id
#>  * <chr>        <date>          <int> <chr>  <chr>    <chr>       <chr>         
#>  1 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.01          
#>  2 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.025         
#>  3 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.05          
#>  4 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.1           
#>  5 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.15          
#>  6 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.2           
#>  7 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.25          
#>  8 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.3           
#>  9 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.35          
#> 10 hub-ensemble 2023-05-08          1 wk ah… US       quantile    0.4           
#> # ℹ 82 more rows
#> # ℹ 1 more variable: value <dbl>