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app.R
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app.R
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#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# https://shiny.posit.co/
#
# library(shiny)
library(bslib)
library(tidyverse)
library(Polychrome)
library(farver)
# Prep data ----
suppressWarnings({
becker2010_wide <- read_csv("data/becker2010.csv",
col_types = str_flatten(c(
"cccccncccncnn", rep("ccnnnn", 14), "_nnnnnn"
)))
})
vow_names <- becker2010_wide %>%
select(V1OS:V14F4) %>%
colnames()
vow_values <-
rep(c("vowel", "vowel_ps", "f1", "f2", "f3", "f4"), 14)
spec <- tibble(.name = vow_names,
.value = vow_values)
becker2010 <- becker2010_wide %>%
pivot_longer_spec(spec, values_drop_na = TRUE) %>%
group_by(Language) %>%
mutate(
f1_z = (f1 - mean(f1, na.rm = TRUE)) / sd(f1, na.rm = TRUE),
f2_z = (f2 - mean(f2, na.rm = TRUE)) / sd(f2, na.rm = TRUE),
f3_z = (f3 - mean(f3, na.rm = TRUE)) / sd(f3, na.rm = TRUE)
) %>%
ungroup() |>
drop_na(f1, f2)
fill_pal <- as.character(green.armytage.colors(n = 17))
col_pal <- ifelse(decode_colour(fill_pal, to = "hcl")[, "l"] > 50, "black", "white")
f2_lims <- c(2500, 500)
f1_lims <- c(900, 150)
# UI ----
ui <- page_navbar(
fillable = FALSE,
title = "Vowel formants",
id = "nav",
## Sidebar ----
sidebar = sidebar(
conditionalPanel(
"input.nav === 'Languages'",
"Data from Becker-Kristal 2010.",
h3("Settings"),
selectInput("language", "Language",
choices = sort(unique(
becker2010$Language
))),
selectInput("dialect", "Variety", sort(unique(
becker2010$Dialect
)))
),
conditionalPanel(
"input.nav === 'Systems'",
"Data from Becker-Kristal 2010.",
h3("Settings"),
selectInput("language", "Language",
choices = sort(unique(
becker2010$Language
))),
selectInput("dialect", "Variety", sort(unique(
becker2010$Dialect
)))
)
),
## Languages ----
nav_panel(
"Languages",
card(card_header("Vowel plot"),
plotOutput("vowelPlot")),
card(card_header("Formant means"),
tableOutput("vowelTable"))
),
## Systems ----
nav_panel(
"Systems",
"Test"
)
)
# Server ----
server <- function(input, output, session) {
observe({
updateSelectInput(session, "dialect", choices = as.character(becker2010$Dialect[becker2010$Language == input$language]))
})
filter_data <- reactive({
if (input$dialect != "NA") {
lang_data <- filter(
becker2010,
Language == input$language,
Dialect == input$dialect
)
} else {
lang_data <- filter(
becker2010,
Language == input$language
)
}
lang_data <- lang_data |>
group_by(vowel) |>
summarise(
f1 = mean(f1, na.rm = TRUE),
f2 = mean(f2, na.rm = TRUE),
f3 = mean(f3, na.rm = TRUE),
f4 = mean(f4, na.rm = TRUE)
) |>
arrange(vowel)
return(lang_data)
})
# Vowel Plot
output$vowelPlot <- renderPlot({
lang_data <- filter_data()
if (max(lang_data$f1) > f1_lims[1]) {
f1_lims[1] <- max(lang_data$f1) + 10
}
if (max(lang_data$f2) > f2_lims[1]) {
f2_lims[1] <- max(lang_data$f2) + 10
}
lang_data |>
ggplot(aes(f2, f1, label = vowel, fill = vowel, colour = vowel)) +
geom_label(size = 6) +
scale_x_reverse(limits = f2_lims, position = "top") +
scale_y_reverse(limits = f1_lims, position = "right") +
scale_fill_manual(values = alpha(fill_pal, 0.7)) +
scale_colour_manual(values = col_pal) +
theme_light() +
labs(x = "F2 (Hz)", y = "F1 (Hz)") +
theme(legend.position = "none") +
coord_fixed(ratio = 2.5)
})
output$vowelTable <- renderTable({
lang_data <- filter_data()
lang_data
},
digits = 0)
}
# Run ----
shinyApp(ui = ui, server = server)