Delay Reaction in R shiny - r

Question

library(shiny)
library(ggplot2)
ui <- shinyUI(fluidPage(
titlePanel("Central Limit Theorem Simulation"),
sidebarLayout(
sidebarPanel(
numericInput("sample_size", "Size of each random sample\n(max: 100)",
value = 30, min = 1, max = 100, step = 1),
sliderInput("simulation", "The number of simulation",
value = 100, min = 100, max = 1000, step = 1),
numericInput("bins", "Number of bins in the histogram\n(max: 50)",
value = 20, min = 1, max = 50, step = 1),
selectInput("sample_dist", "Population Distribution where each sample is from",
choices = c("Bernoulli","Poisson", "Normal", "Uniform") ),
conditionalPanel(condition = 'input.sample_dist == "Bernoulli"',
textInput("prob", "Parameter (p)") ),
conditionalPanel(condition = 'input.sample_dist == "Poisson"',
textInput("lambda", "Parameter (lambda)") ),
conditionalPanel(condition = 'input.sample_dist == "Normal"',
textInput("mu", "Parameter (mu)"),
textInput("sigma", "Parameter (sigma)") ),
conditionalPanel(condition = 'input.sample_dist == "Uniform"',
textInput("min_a", "Parameter (a)"),
textInput("max_b", "parameter (b)") ),
actionButton("update", "Update Simulation")
),
mainPanel(
tabsetPanel(type = "pills",
tabPanel("mean of random sample mean", br(),
textOutput(outputId = "output_mean")),
tabPanel("variance of random sample mean", br(),
textOutput(outputId = "output_var")),
tabPanel("summary table", br(),
tableOutput(outputId = "output_table")),
tabPanel("sample matrix", br(),
verbatimTextOutput(outputId = "output_sample")),
tabPanel("histogram of random normal sample", br(),
plotOutput(outputId = "output_hist"))
)
)
)
))
server <- shinyServer(function(input, output) {
# Return the random sample
rsample <- eventReactive(input$update, {
if (isolate(input$sample_dist == "Bernoulli") ) {
rsample <- isolate(rbinom(n = input$sample_size * input$simulation,
size = 1, as.numeric(input$prob) ) )
} else if (isolate(input$sample_dist == "Poisson") ) {
rsample <- isolate(rpois(n = input$sample_size * input$simulation,
as.numeric(input$lambda) ) )
} else if (isolate(input$sample_dist == "Normal") ) {
rsample <- isolate(rnorm(n = input$sample_size * input$simulation,
mean = as.numeric(input$mu), sd = as.numeric(input$sigma) ) )
} else {
rsample <- isolate(runif(n = input$sample_size * input$simulation,
min = as.numeric(input$min_a), max = as.numeric(input$max_b) ) )
}
rsample
})
# Return the random sample matrix
rsamplematrix <- reactive({
matrix(rsample(), nrow = isolate(input$simulation) )
})
# output mean of sample mean
output$output_mean <- renderText({
sample_mean <- rowMeans(rsamplematrix())
mean(sample_mean)
})
# output variance of sample mean
output$output_var <- renderText({
sample_mean <- rowMeans(rsamplematrix())
var(sample_mean)
})
# output summary table of sample mean
output$output_table <- renderTable({
sample_mean <- rowMeans(rsamplematrix())
data.frame(mean(sample_mean), var(sample_mean))
})
# output the first 5 rows and 5 columns of the sample matrix
output$output_sample <- renderPrint({
k = rsamplematrix()
k[1:5, 1:5]
})
# output histogram of sample mean
output$output_hist <- renderPlot({
sample_mean <- rowMeans(rsamplematrix())
ggplot(data.frame(sample_mean), aes(x = sample_mean, y = ..density..)) +
geom_histogram(bins = isolate(input$bins), fill = "steelblue", col = "white")
})
})
shinyApp(ui = ui, server = server)
The code runs well, but there is a little problem with respect to Delay Reaction.
Suppose I run the simulation of binomial distribution with parameter=0.5, then all output would be generated. Then I choose a different distribution (for instance, normal distribution), before I render values to the parameters and click action button, the histogram plot is becoming grey for around a second. t seems that the server function is running although there is no change at all after that second.
What I wish is that when the distribution choice is made, the reaction are supposed to be delayed. So the server function should not run unless the action Button is clicked.
How can I fix this?