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Match model output tbl data to their model tasks in config_tasks.

Source: R/match_tbl_to_model_task.R
match_tbl_to_model_task.Rd

Split and match model output tbl data to their corresponding model tasks in config_tasks. Useful for performing model task specific checks on model output. For v3 samples, the output_type_id column is set to NA for sample outputs.

Usage

match_tbl_to_model_task(
  tbl,
  config_tasks,
  round_id,
  output_types = NULL,
  derived_task_ids = get_config_derived_task_ids(config_tasks, round_id),
  all_character = TRUE
)

Arguments

tbl

a tibble/data.frame of the contents of the file being validated.

config_tasks

a list version of the content's of a hub's tasks.json config file, accessed through the "config_tasks" attribute of a <hub_connection> object or function hubUtils::read_config().

round_id

Character string. Round identifier. If the round is set to round_id_from_variable: true, IDs are values of the task ID defined in the round's round_id property of config_tasks. Otherwise should match round's round_id value in config. Ignored if hub contains only a single round.

output_types

Character vector of output type names to include. Use to subset for grids for specific output types.

derived_task_ids

Character vector of derived task ID names (task IDs whose values depend on other task IDs) to ignore. Columns for such task ids will contain NAs. Defaults to extracting derived task IDs from config_tasks. See get_config_derived_task_ids() for more details.

all_character

Logical. Whether to return all character column.

Value

A list containing a tbl_df of model output data matched to a model task with one element per round model task.

Examples

hub_path <- system.file("testhubs/samples", package = "hubValidations")
tbl <- read_model_out_file(
  file_path = "flu-base/2022-10-22-flu-base.csv",
  hub_path, coerce_types = "chr"
)
config_tasks <- read_config(hub_path, "tasks")
match_tbl_to_model_task(tbl, config_tasks, round_id = "2022-10-22")
#> [[1]]
#> # A tibble: 60 × 8
#>    reference_date target            horizon location target_end_date output_type
#>    <chr>          <chr>             <chr>   <chr>    <chr>           <chr>      
#>  1 2022-10-22     wk flu hosp rate… 0       US       2022-10-22      pmf        
#>  2 2022-10-22     wk flu hosp rate… 0       01       2022-10-22      pmf        
#>  3 2022-10-22     wk flu hosp rate… 0       02       2022-10-22      pmf        
#>  4 2022-10-22     wk flu hosp rate… 0       04       2022-10-22      pmf        
#>  5 2022-10-22     wk flu hosp rate… 0       05       2022-10-22      pmf        
#>  6 2022-10-22     wk flu hosp rate… 1       US       2022-10-29      pmf        
#>  7 2022-10-22     wk flu hosp rate… 1       01       2022-10-29      pmf        
#>  8 2022-10-22     wk flu hosp rate… 1       02       2022-10-29      pmf        
#>  9 2022-10-22     wk flu hosp rate… 1       04       2022-10-29      pmf        
#> 10 2022-10-22     wk flu hosp rate… 1       05       2022-10-29      pmf        
#> # ℹ 50 more rows
#> # ℹ 2 more variables: output_type_id <chr>, value <chr>
#> 
#> [[2]]
#> # A tibble: 1,530 × 8
#>    reference_date target          horizon location target_end_date output_type
#>    <chr>          <chr>           <chr>   <chr>    <chr>           <chr>      
#>  1 2022-10-22     wk inc flu hosp 0       US       2022-10-22      mean       
#>  2 2022-10-22     wk inc flu hosp 0       01       2022-10-22      mean       
#>  3 2022-10-22     wk inc flu hosp 0       02       2022-10-22      mean       
#>  4 2022-10-22     wk inc flu hosp 0       04       2022-10-22      mean       
#>  5 2022-10-22     wk inc flu hosp 0       05       2022-10-22      mean       
#>  6 2022-10-22     wk inc flu hosp 1       US       2022-10-29      mean       
#>  7 2022-10-22     wk inc flu hosp 1       01       2022-10-29      mean       
#>  8 2022-10-22     wk inc flu hosp 1       02       2022-10-29      mean       
#>  9 2022-10-22     wk inc flu hosp 1       04       2022-10-29      mean       
#> 10 2022-10-22     wk inc flu hosp 1       05       2022-10-29      mean       
#> # ℹ 1,520 more rows
#> # ℹ 2 more variables: output_type_id <chr>, value <chr>
#> 
match_tbl_to_model_task(tbl, config_tasks,
  round_id = "2022-10-22",
  output_types = "sample"
)
#> [[1]]
#> NULL
#> 
#> [[2]]
#> # A tibble: 1,500 × 8
#>    reference_date target          horizon location target_end_date output_type
#>    <chr>          <chr>           <chr>   <chr>    <chr>           <chr>      
#>  1 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  2 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  3 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  4 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  5 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  6 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  7 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  8 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#>  9 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#> 10 2022-10-22     wk inc flu hosp 0       US       2022-10-22      sample     
#> # ℹ 1,490 more rows
#> # ℹ 2 more variables: output_type_id <chr>, value <chr>
#>