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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 = NULL,
  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.

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 <- hubUtils::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>
#>