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Attach explicit subject identity to signal cases or feature rows

Source: R/feature-input.R
withCaseData.Rd

Establishes a case-to-subject mapping without inferring subjects from case names. Row order is reconciled by exact case ID. A cycle is a case, not an independent subject. Use cohort-derived subject/session keys when available.

Usage

withCaseData(x, case_data)

Arguments

x

A PhysioExperiment or finite numeric case-by-feature matrix with unique nonempty row names used as case IDs.

case_data

Data frame with unique case_id and repeated subject_id. Optional character identity columns are participant_id, session_id, trial_id, side, cycle_id. All supplied columns must be complete. An optional input_case_index from a PhysioML transform is accepted as unique positive whole numbers; signal selection computes its own indices. The table must cover all input cases exactly, before any case selection.

Value

The input with validated identity metadata. Experiments store it in metadata(x)$ml_case_data; matrices store it in attribute case_data. PhysioML input transforms and datasets preserve this information. Ordinary external matrix manipulation is not guaranteed to preserve attributes; reattach the corresponding table after subsetting feature rows.

See also

validateSubjectSplit(), peDataset(), peReducedFeatures()

Examples

# Attach subject identity to a case-by-feature matrix.
features <- matrix(
  stats::rnorm(8), nrow = 2,
  dimnames = list(c("c1", "c2"), c("a", "b", "c", "d"))
)
case_data <- data.frame(case_id = c("c1", "c2"), subject_id = c("s1", "s2"))
labelled <- withCaseData(features, case_data)
attr(labelled, "case_data")
#>   case_id subject_id
#> 1      c1         s1
#> 2      c2         s2