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Shift Alignment via Cross-Correlation

Source: R/align.R
step_measure_align_shift.Rd

step_measure_align_shift() creates a specification of a recipe step that aligns spectra by finding the optimal shift using cross-correlation.

Usage

step_measure_align_shift(
  recipe,
  measures = NULL,
  max_shift = 10L,
  reference = c("mean", "median", "first"),
  role = NA,
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("measure_align_shift")
)

Arguments

recipe

A recipe object.

measures

An optional character vector of measure column names.

max_shift

Maximum shift (in points) to consider. Default is 10. Tunable via align_max_shift().

reference

How to determine the reference:

  • "mean" (default): Use the mean spectrum from training

  • "median": Use the median spectrum from training

  • "first": Use the first sample

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 corrects for small linear shifts between spectra, which can occur due to:

  • Wavelength calibration drift

  • Sample positioning differences

  • Temperature effects on instrument

The optimal shift is found by maximizing the cross-correlation between each spectrum and the reference. After shifting, edge values are filled by constant extrapolation.

See also

Other measure-align: step_measure_align_cow(), step_measure_align_dtw(), step_measure_align_ptw(), step_measure_align_reference()

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_align_shift(max_shift = 5) |>
  prep()

bake(rec, new_data = NULL)
#> # A tibble: 215 × 5
#>       id water   fat protein .measures
#>    <int> <dbl> <dbl>   <dbl>    <meas>
#>  1     1  60.5  22.5    16.7 [100 × 2]
#>  2     2  46    40.1    13.5 [100 × 2]
#>  3     3  71     8.4    20.5 [100 × 2]
#>  4     4  72.8   5.9    20.7 [100 × 2]
#>  5     5  58.3  25.5    15.5 [100 × 2]
#>  6     6  44    42.7    13.7 [100 × 2]
#>  7     7  44    42.7    13.7 [100 × 2]
#>  8     8  69.3  10.6    19.3 [100 × 2]
#>  9     9  61.4  19.9    17.7 [100 × 2]
#> 10    10  61.4  19.9    17.7 [100 × 2]
#> # ℹ 205 more rows