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Cohort Design Table

Source: R/dataset-cohort.R
pr_design_table.Rd

Reduces a pr_dataset to one row per trial: the chosen metadata fields plus n_frames and duration_s. This is the study design as a table — the object you count, cross-tabulate, and assert against with pr_assert_cohort().

Usage

pr_design_table(dataset, fields = NULL)

Arguments

dataset

A pr_dataset object, or a list of pr_trial objects.

fields

Character vector of metadata field names to include, in the order given. NULL (default) auto-detects: every metadata field that holds a single value in every trial, dropping fields that are missing (NA) throughout — which removes the empty pr_trial defaults such as notes. Fields named n_frames or duration_s are dropped in auto mode and rejected when named explicitly, because both columns are recomputed from the trial itself.

Value

A tibble::tibble with one row per trial and columns fields, n_frames (integer) and duration_s (numeric).

Details

duration_s is the trial's duration field, i.e. diff(range(time)), so a 23432-frame recording at 50 Hz gives 468.62 s (not 468.64 s).

See also

Other cohort functions: pr_assert_cohort(), pr_dataset_filter(), pr_validate_dataset()

Examples

layout <- pr_layout_mat("16")
mk <- function(id, mode, n) {
  pr_trial(
    matrix(1, n, layout$n_sensors),
    time = seq(0, (n - 1) / 50, by = 1 / 50),
    layout = layout,
    metadata = list(ID = id, Mode = mode)
  )
}
ds <- pr_dataset(list(mk("ID001", "MS", 4), mk("ID002", "MH", 6)))
pr_design_table(ds, fields = c("ID", "Mode"))
#> # A tibble: 2 × 4
#>   ID    Mode  n_frames duration_s
#>   <chr> <chr>    <int>      <dbl>
#> 1 ID001 MS           4       0.06
#> 2 ID002 MH           6       0.1