Integrate Peak Areas

step_measure_peaks_integrate() creates a specification of a recipe step that calculates the area under each detected peak.

Usage

step_measure_peaks_integrate(
  recipe,
  method = c("trapezoid", "simpson"),
  baseline = c("local", "none", "global"),
  measures = NULL,
  role = NA,
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("measure_peaks_integrate")
)

Arguments

recipe

A recipe object.

method

Integration method. One of "trapezoid" (default) or "simpson".

baseline

Baseline handling. One of "local" (linear interpolation between peak bases), "none" (integrate to zero), or "global" (use minimum value as baseline).

measures

Optional character vector of measure column names.

role

Not used.

trained

Logical indicating if the step has been trained.

skip

Logical. Should the step be skipped when baking?

id

Unique step identifier.

Value

An updated recipe with the new step added.

Details

This step calculates the area under each peak detected by step_measure_peaks_detect(). The areas are stored in the area column of the .peaks tibble.

Integration methods:

• "trapezoid": Trapezoidal rule integration. Fast and accurate for well-resolved peaks.

• "simpson": Simpson's rule integration. More accurate for smooth curves but requires odd number of points.

Baseline handling:

• "local": Subtracts a linear baseline connecting the left and right peak bases before integration.

• "none": Integrates directly to y=0.

• "global": Subtracts the minimum value in the peak region.

See also

Other peak-operations: step_measure_peaks_detect(), step_measure_peaks_filter(), step_measure_peaks_to_table()

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)) |>
  step_measure_peaks_detect(min_height = 0.5) |>
  step_measure_peaks_integrate() |>
  prep()

result <- bake(rec, new_data = NULL)