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Calculate Region Integrals

Source: R/feature-engineering.R
step_measure_integrals.Rd

step_measure_integrals() creates a specification of a recipe step that calculates integrated areas for specified x-axis regions.

Usage

step_measure_integrals(
  recipe,
  regions,
  method = c("trapezoid", "simpson"),
  measures = NULL,
  prefix = "integral_",
  role = "predictor",
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("measure_integrals")
)

Arguments

recipe

A recipe object.

regions

A named or unnamed list of numeric vectors, each of length 2 specifying regions as c(min, max). For example: list(peak1 = c(1000, 1100), peak2 = c(1500, 1600)).

method

Integration method: "trapezoid" (default) or "simpson".

measures

An optional character vector of measure column names.

prefix

Prefix for output column names. Default is "integral_".

role

Role for generated columns. Default is "predictor".

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 integrated area under the curve for each specified region. The result is added as new predictor columns, one per region.

Column naming:

  • If regions are named: prefix + name (e.g., "integral_peak1")

  • If regions are unnamed: prefix + index (e.g., "integral_1")

Integration methods:

  • "trapezoid": Trapezoidal rule, fast and accurate for smooth data

  • "simpson": Simpson's rule, more accurate for smooth curves

See also

Other measure-features: step_measure_bin(), step_measure_moments(), step_measure_ratios()

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_integrals(
    regions = list(low = c(1, 30), mid = c(40, 60), high = c(70, 100))
  ) |>
  prep()

bake(rec, new_data = NULL)
#> # A tibble: 215 × 9
#>       id water   fat protein .measures channel     integral_low integral_mid
#>    <int> <dbl> <dbl>   <dbl>    <meas> <list>             <dbl>        <dbl>
#>  1     1  60.5  22.5    16.7 [100 × 2] <int [100]>         77.1         61.8
#>  2     2  46    40.1    13.5 [100 × 2] <int [100]>         85.0         67.4
#>  3     3  71     8.4    20.5 [100 × 2] <int [100]>         76.1         59.4
#>  4     4  72.8   5.9    20.7 [100 × 2] <int [100]>         83.1         64.6
#>  5     5  58.3  25.5    15.5 [100 × 2] <int [100]>         82.8         67.6
#>  6     6  44    42.7    13.7 [100 × 2] <int [100]>         90.6         72.3
#>  7     7  44    42.7    13.7 [100 × 2] <int [100]>         90.2         72.0
#>  8     8  69.3  10.6    19.3 [100 × 2] <int [100]>         74.3         59.7
#>  9     9  61.4  19.9    17.7 [100 × 2] <int [100]>         98.3         78.8
#> 10    10  61.4  19.9    17.7 [100 × 2] <int [100]>        102.          82.6
#> # ℹ 205 more rows
#> # ℹ 1 more variable: integral_high <dbl>