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Apply a Function Safely to Each Sample's Measurements

Source: R/measure-map.R
measure_map_safely.Rd

measure_map_safely() is a fault-tolerant version of measure_map() that captures errors instead of stopping execution. This is useful when exploring data that may have problematic samples.

Usage

measure_map_safely(
  .data,
  .f,
  .cols = NULL,
  ...,
  .otherwise = NULL,
  .error_call = rlang::caller_env()
)

Arguments

.data

A data frame containing one or more measure_list columns.

.f

A function or formula to apply to each sample's measurement tibble.

  • If a function, it is used as-is.

  • If a formula (e.g., ~ { .x$value <- log(.x$value); .x }), it is converted to a function using rlang::as_function().

.cols

<tidy-select> Columns to apply the transformation to. Defaults to all measure_list columns.

...

Additional arguments passed to .f.

.otherwise

Value to use when .f fails for a sample. Default is NULL, which keeps the original (untransformed) measurement.

.error_call

The execution environment for error reporting.

Value

A list with two elements:

  • result: A data frame with transformations applied where successful

  • errors: A tibble with columns column, sample, and error

See also

measure_map() for standard (fail-fast) mapping

Examples

library(recipes)

rec <- recipe(water + fat + protein ~ ., data = meats_long) |>
  update_role(id, new_role = "id") |>
  step_measure_input_long(transmittance, location = vars(channel)) |>
  prep()

baked_data <- bake(rec, new_data = NULL)

# A function that might fail for some samples
risky_transform <- function(x) {
  if (any(x$value < 0)) stop("Negative values not allowed")
  x$value <- log(x$value)
  x
}

# Errors are captured, not thrown
result <- measure_map_safely(baked_data, risky_transform)

# Check which samples failed
if (nrow(result$errors) > 0) {
  print(result$errors)
}