tidynorm (version 0.4.0)

reframe_with_idct: Reframe with IDCT

Description

Reframe data columns using the Inverse Discrete Cosine Transform

Usage

reframe_with_idct(
  .data,
  ...,
  .token_id_col = NULL,
  .by = NULL,
  .param_col = NULL,
  .n = 20,
  .rate = FALSE,
  .accel = FALSE
)

Value

A data frame with the IDCT of the targeted columns along with an additional .time column.

.time

A column from 1 to .n by token

Arguments

.data

A data frame

...

<tidy-select> One or more unquoted expressions separated by commas. These should target the vowel formant.

.token_id_col

<tidy-select> The token ID column.

.by

<tidy-select> A grouping column.

.param_col

A column identifying the DCT parameter number

.n

The size of the outcome of the IDCT

.rate

Whether or not to include the rate of change of signal.

.accel

Whether or not to include acceleration of signal.

Details

This will apply the Inverse Discrete Cosine Transform to the targeted columns. See idct.

Identifying tokens

The IDCT only works on a by-token basis, so there must be a column that uniquely identifies (or, in combination with a .by grouping, uniquely identifies) each individual token. This column should be passed to .token_id_col.

Size of the output

The output of the IDCT can be arbitrarily long as defined by the .n argument. .n can either be an integer, or an unqoted data column.

The Parameter Column

The order of the DCT parameters is crucially important. The optional .param_col will ensure the data is properly arranged.

Examples

library(tidynorm)
library(dplyr)
ggplot2_inst <- require(ggplot2)

speaker_small <- filter(
  speaker_tracks,
  id == 0
)

speaker_dct <- speaker_small |>
  reframe_with_dct(
    F1:F3,
    .by = speaker,
    .token_id_col = id,
    .time_col = t,
    .order = 5
  )

speaker_idct <- speaker_dct |>
  reframe_with_idct(
    F1:F3,
    .by = speaker,
    .token_id_col = id,
    .param_col = .param,
    .n = 20
  )

if (ggplot2_inst) {
  speaker_small |>
    mutate(
      .by = c(speaker, id),
      time_index = row_number()
    ) |>
    ggplot(
      aes(
        time_index, F1
      )
    ) +
    geom_point() +
    labs(
      title = "Original Data"
    )
}

if (ggplot2_inst) {
  speaker_idct |>
    ggplot(
      aes(
        .time, F1
      )
    ) +
    geom_point() +
    labs(
      title = "DCT Smooth Data"
    )
}