Nothing
# Gap statistic computation module
ui_gapstat <- function() {
ns <- NS("gapstat")
tabPanel("Gap stat",
value = "gapstat",
verticalLayout(fluidRow(
column(
3,
numericInput(
ns("gap_B"),
"Bootstrap samples:",
value = 500,
min = 50,
step = 50
)
),
column(
2,
actionButton(
ns("compute_gap"),
"Compute",
style = "margin-top: 25px")
),
column(
4,
selectizeInput(
ns("gap_method"),
"Optimal k method:",
choices = c(
"firstSEmax",
"Tibs2001SEmax",
"globalSEmax",
"firstmax",
"globalmax"
)
)
)
) %>% shinyhelper::helper(type = "markdown", content = "gap_help"),
plotOutput(ns("gap_plot")) %>% withSpinner()
)
)
}
server_gapstat <- function(id, selected_data, clusters) {
moduleServer(id, function(input, output, session) {
# Wait for user input instead of computing automatically
gap_result <- eventReactive(input$compute_gap, {
isolate({
df <- selected_data()
clustered_data <- clusters()
})
validate(need(input$gap_B > 0,
"Bootstrap samples must be greater than 0."))
compute_gapstat(df, clustered_data, input$gap_B)
})
output$gap_plot <- renderPlot({
req(gap_result())
gap_table <- gap_result()
if (isTruthy(input$gap_method)) {
optimal_k <- cluster::maxSE(gap_table$gap,
gap_table$SE.sim,
method = input$gap_method)
} else {
optimal_k <- NULL
}
line_plot(gap_table, "k", "gap", xintercept = optimal_k) +
labs(y = "Gap statistic")
})
})
}
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