Calling additional functions in Shiny - r

Question

I developed a simple shiny app that take as inputs a score my_x on a distribution with mean my_mean and standard deviation my_sd. As output, the app return a Lattice plot with a Normal Standard distribution with the corresponding z-score of my_x. Please find the code for the app on GitHub.
Now, I would like to add a second functionality to the app:
By checking a checkboxInput I would calculate, for example, the pnorm of the inputs and shade the relative area of the graph.
I wrote the code for the graph (here an example of the expected result), but I cannot figure out how to make it work in Shiny. In particular, I cannot figure how to make the function activated with the checkbox working properly with the first function drawing the graph.
library(lattice)
e4a <- seq(60, 170, length = 10000)
e4b <- dnorm(e4a, 110, 15)
#z-score is calculated with the inputs listed above:
z_score <- (my_x - my_mean)/my_sd
plot_e4d <- xyplot(e4b ~ e4a,
type = "l",
main = "Plot 4",
scales = list(x = list(at = seq(60, 170, 10)), rot = 45),
panel = function(x,y, ...){
panel.xyplot(x,y, ...)
panel.abline(v = c(z_score, 110), lty = 2)
xx <- c(60, x[x>=60 & x<=z_score], z_score)
yy <- c(0, y[x>=60 & x<=z_score], 0)
panel.polygon(xx,yy, ..., col='red')
})
print(plot_e4d)

Answer 1

I found a functioning solution. I am pretty sure that it is not the most efficient, but it works. It consists of an if/else statement within the server function calling the plot. I would like to thank #zx8754 for the inspiration.
Here is the ui.r file:
library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Standard Normal"),
sidebarPanel(
numericInput('mean', 'Your mean', 0),
numericInput('sd', 'Your standard deviation', 0),
numericInput('x', 'Your score', 0),
checkboxInput('p1', label = 'Probability of getting a score smaller than x or z', value = FALSE)
),
mainPanel(
h3('Standard Normal'),
plotOutput('sdNorm'),
h4('Your z-score is:'),
verbatimTextOutput('z'),
h4('Your lower tail probability is:'),
verbatimTextOutput('p1')
))
)
And the server.R file:
library(lattice)
shinyServer(
function(input, output){
output$sdNorm <- renderPlot({
dt1 <- seq(-3, 3, length = 1000)
dt2 <- dnorm(dt1, 0, 1)
my_mean <- input$mean
my_sd <- input$sd
my_x <- input$x
z <- (my_x - my_mean)/my_sd
if(input$p1){
xyplot(dt2 ~ dt1,
type = "l",
main = "Lower tail probability",
panel = function(x,y, ...){
panel.xyplot(x,y, ...)
panel.abline(v = c(z, 0), lty = 2)
xx <- c(-3, x[x>=-3 & x<=z], z)
yy <- c(0, y[x>=-3 & x<=z], 0)
panel.polygon(xx,yy, ..., col='red')
})
}else{
xyplot(dt2 ~ dt1,
type = "l",
main = "Standard Normal Distribution",
panel = function(x, ...){
panel.xyplot(x, ...)
panel.abline(v = c(z, 0), lty = 2)
})
}
})
output$z = renderPrint({
my_mean <- input$mean
my_sd <- input$sd
my_x <- input$x
z <- (my_x - my_mean)/my_sd
z
})
output$p1 <- renderPrint({
if(input$p1){
my_mean <- input$mean
my_sd <- input$sd
my_x <- input$x
p1 <- 1- pnorm(my_x, my_mean, my_sd)
p1
} else {
p1 <- NULL
}
})
}
)

Answer 2

This should work:
library(shiny)
library(lattice)
shinyApp(
ui = {
pageWithSidebar(
headerPanel("Standard Normal"),
sidebarPanel(
numericInput('mean', 'Your mean', 80),
numericInput('sd', 'Your standard deviation', 2),
numericInput('x', 'Your score', 250),
checkboxInput("zScoreArea", label = "Area under z-score", value = TRUE)
),
mainPanel(
h3('Standard Normal'),
plotOutput('sdNorm'),
h4('Your z-score is:'),
verbatimTextOutput('z_score')
))
},
server = {
function(input, output){
#data
dt1 <- seq(60, 170, length = 10000)
dt2 <- dnorm(dt1, 110, 15)
#xyplot panel= function()
myfunc <- reactive({
if(input$zScoreArea){
function(x,y, ...){
panel.xyplot(x,y, ...)
panel.abline( v = c(z_score(), 110), lty = 2)
xx <- c(60, x[x >= 60 & x <= z_score()], z_score())
yy <- c(0, y[x >= 60 & x <= z_score()], 0)
panel.polygon(xx,yy, ..., col='red')
}
}else{
function(x, ...){
panel.xyplot(x, ...)
panel.abline(v = c(z_score(), 110), lty = 2)}
}
})
#reactive z_score for plotting
z_score <- reactive({
my_mean <- input$mean
my_sd <- input$sd
my_x <- input$x
#return z score
(my_x - my_mean)/my_sd
})
output$sdNorm <- renderPlot({
xyplot(dt2 ~ dt1,
type = "l",
main = "Plot 4",
scales = list(x = list(at = seq(60, 170, 10)), rot = 45),
panel = myfunc()
)
})
output$z_score = renderPrint({ z_score() })
}
}
)