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Dynamic Time Warping Alignment

Source: R/align.R
step_measure_align_dtw.Rd

step_measure_align_dtw() creates a specification of a recipe step that aligns spectra using Dynamic Time Warping (DTW). This method can handle non-linear distortions in the x-axis.

Usage

step_measure_align_dtw(
  recipe,
  measures = NULL,
  reference = c("mean", "median", "first"),
  window_type = c("none", "sakoechiba", "slantedband"),
  window_size = 10L,
  role = NA,
  trained = FALSE,
  skip = FALSE,
  id = recipes::rand_id("measure_align_dtw")
)

Arguments

recipe

A recipe object.

measures

An optional character vector of measure column names.

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

window_type

Windowing constraint for DTW. One of "none" (default), "sakoechiba", or "slantedband".

window_size

Window size for constrained DTW. Default is 10.

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

DTW finds the optimal non-linear alignment between two sequences by minimizing a distance measure while allowing warping of the time/x-axis.

This is useful for:

  • Chromatographic peak alignment

  • Correcting non-linear retention time shifts

  • Aligning spectra with complex distortions

Requires the dtw package to be installed.

See also

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

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_dtw() |>
  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