## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed("magick")'
#| echo: false
knitr::knit_hooks$set(crop = knitr::hook_pdfcrop)


## -----------------------------------------------------------------------------
#| message: false
library(tidynorm)
library(dplyr)
library(tidyr)


## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
library(ggplot2)
library(ggdensity)


## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| include: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| code-fold: true
#| code-summary: color palette
options(
  ggplot2.discrete.colour = c(
    lapply(
      1:6,
      \(x) c(
        "#4477AA", "#EE6677", "#228833",
        "#CCBB44", "#66CCEE", "#AA3377"
      )[1:x]
    )
  ),
  ggplot2.discrete.fill = c(
    lapply(
      1:6,
      \(x) c(
        "#4477AA", "#EE6677", "#228833",
        "#CCBB44", "#66CCEE", "#AA3377"
      )[1:x]
    )
  )
)

theme_set(
  theme_minimal(base_size = 16) +
    theme(
      panel.grid = element_blank()
    )
)


## -----------------------------------------------------------------------------
speaker_data |>
  summarise(
    .by = c(speaker, vowel),
    across(
      F1:F3,
      \(x)mean(x, na.rm = T)
    )
  ) ->
speaker_means


## -----------------------------------------------------------------------------
#| code-fold: true
#| code-summary: Plotting Code
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| fig-align: center
#| out-width: 80%
speaker_means |>
  filter(
    vowel %in% c("IY", "UW", "AE", "AA")
  ) |>
  ggplot(
    aes(F2, F1)
  ) +
  geom_label(
    aes(
      label = vowel,
      fill = speaker
    ),
    color = "white"
  ) +
  scale_y_reverse() +
  scale_x_reverse()


## -----------------------------------------------------------------------------
#| code-fold: true
#| code-summary: Vowel Comparison
speaker_means |>
  filter(
    vowel %in% c("IY", "UW", "AE", "AA")
  ) |>
  pivot_longer(
    F1:F3,
    names_to = ".formant_name",
    values_to = ".formant"
  ) |>
  pivot_wider(
    names_from = vowel,
    values_from = .formant
  ) |>
  arrange(
    .formant_name
  )


## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| fig-align: center
#| out-width: 80%
#| code-fold: true
#| code-summary: Plotting code
speaker_centers <- speaker_data |>
  summarise(
    .by = speaker,
    across(
      F1:F3,
      ~ mean(.x, na.rm = T)
    )
  )

speaker_data |>
  ggplot(
    aes(F2, F1, color = speaker)
  ) +
  stat_hdr(
    probs = c(0.95, 0.8, 0.5),
    fill = NA,
    alpha = 1,
    linewidth = 1
  ) +
  geom_point(
    data = speaker_centers,
    size = 5
  ) +
  scale_x_reverse() +
  scale_y_reverse()


## -----------------------------------------------------------------------------
speaker_data_centered <- speaker_data |>
  mutate(
    .by = speaker,
    across(
      F1:F3,
      ~ .x - mean(.x, na.rm = T)
    )
  )


## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| fig-align: center
#| out-width: 80%
#| code-fold: true
#| code-summary: Plotting code
speaker_data_centered |>
  ggplot(
    aes(F2, F1, color = speaker)
  ) +
  stat_hdr(
    probs = c(0.95, 0.8, 0.5),
    fill = NA,
    alpha = 1,
    linewidth = 1
  ) +
  geom_point(
    data = tibble(),
    aes(x = 0, y = 0),
    color = "black",
    size = 5,
  ) +
  scale_y_reverse() +
  scale_x_reverse()


## -----------------------------------------------------------------------------
speaker_data_scaled <- speaker_data |>
  mutate(
    .by = speaker,
    across(
      F1:F3,
      ~ .x / sd(.x, na.rm = T)
    )
  )


## -----------------------------------------------------------------------------
#| eval: !expr 'rlang::is_installed(c("ggplot2", "ggdensity"))'
#| fig-align: center
#| out-width: 80%
#| code-fold: true
#| code-summary: Plotting code
speaker_data_scaled |>
  mutate(
    .by = speaker,
    across(
      F1:F3,
      ~ (.x - mean(.x, na.rm = T)) / sd(.x, na.rm = T)
    )
  ) |>
  ggplot(
    aes(F2, F1, color = speaker)
  ) +
  stat_hdr(
    probs = c(0.95, 0.8, 0.5),
    fill = NA,
    alpha = 1,
    linewidth = 1
  ) +
  geom_point(
    data = tibble(),
    aes(x = 0, y = 0),
    color = "black",
    size = 5,
  ) +
  scale_y_reverse() +
  scale_x_reverse()


## -----------------------------------------------------------------------------
speaker_data |>
  norm_generic(
    F1:F3,
    .by = speaker,
    .by_formant = FALSE,
    .by_token = FALSE,
    .L = 0,
    .S = mean(
      .formant / (.formant_num - 0.5),
      na.rm = T
    ),
    .names = "{.formant}_df"
  ) ->
speaker_df_norm


## -----------------------------------------------------------------------------
ggplot(
  speaker_df_norm,
  aes(F2_df, F1_df, color = speaker)
) +
  stat_hdr(
    probs = c(0.95, 0.8, 0.5),
    fill = NA,
    alpha = 1,
    linewidth = 1
  ) +
  scale_y_reverse() +
  scale_x_reverse()