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Savitzky-Golay Recipe Step

Source: R/savitzky_golay.R
step_savgol.Rd

step_savgol() creates a specification of a recipe step that smooths the spectra, or computes their derivative, with savitzky_golay().

Usage

step_savgol(
  recipe,
  ...,
  window = 11,
  order = 2,
  derivative = 0,
  segments = TRUE,
  role = NA,
  trained = FALSE,
  columns = NULL,
  skip = FALSE,
  id = recipes::rand_id("savgol")
)

Arguments

recipe

A recipe object. The step will be added to the sequence of operations for this recipe.

...

One or more selector functions to choose the predictors (for example, the spectral channels). See recipes::selections().

window

The width of the window, an odd number of channels. Default is 11.

order

The degree of the polynomial, smaller than window. Default is 2.

derivative

The derivative: 0 (smoothing, default), 1 or 2. It must not exceed order.

segments

A logical: filter the segments between gaps of the wavelength axis separately (TRUE, default). Needs wavelengths as names.

role

Not used by this step, since no new variables are created.

trained

A logical indicating whether the step has been trained.

columns

The names of the selected columns, stored once the step has been trained.

skip

A logical. Should the step be skipped when the recipe is baked by recipes::bake()? Keep the default FALSE, so that new data are corrected with the same filter as the training data.

id

A character string that is unique to this step.

Value

An updated version of recipe with the new step added to the sequence of existing steps.

Details

The selected columns form one spectrum per row, and are replaced by the filtered values. Nothing is estimated from the training data. The window, order and derivative can be tuned with tune::tune() (dials parameters window_size(), degree_int() and savgol_derivative()); an even window, as a tuning grid may propose, is increased to the next odd number. tidy() returns the terms, window, order, derivative and id.

See also

savitzky_golay(), step_snv()

Examples

if (rlang::is_installed("recipes")) {
  data(forageLIBS)
  rec <- recipes::recipe(K ~ ., data = forageLIBS[-c(1:10, 12:14)]) |>
    step_savgol(recipes::all_predictors(), window = 11, derivative = 1) |>
    recipes::prep()
  recipes::tidy(rec, number = 1)
}
#> # A tibble: 7,152 × 5
#>    terms       window order derivative id          
#>    <chr>        <dbl> <dbl>      <dbl> <chr>       
#>  1 199.3771616     11     2          1 savgol_seRbJ
#>  2 199.4644141     11     2          1 savgol_seRbJ
#>  3 199.5516666     11     2          1 savgol_seRbJ
#>  4 199.6389192     11     2          1 savgol_seRbJ
#>  5 199.7261717     11     2          1 savgol_seRbJ
#>  6 199.8134242     11     2          1 savgol_seRbJ
#>  7 199.9006767     11     2          1 savgol_seRbJ
#>  8 199.9879292     11     2          1 savgol_seRbJ
#>  9 200.0751817     11     2          1 savgol_seRbJ
#> 10 200.1624343     11     2          1 savgol_seRbJ
#> # ℹ 7,142 more rows