How to apply the actionButton to update my Shiny in R? - r

Question

This is my reproducible example :
#http://gekkoquant.com/2012/05/26/neural-networks-with-r-simple-example/
library("neuralnet")
require(ggplot2)
setwd(dirname(rstudioapi::getSourceEditorContext()$path))
#Going to create a neural network to perform sqare rooting
#Type ?neuralnet for more information on the neuralnet library
#Generate 50 random numbers uniformly distributed between 0 and 100
#And store them as a dataframe
traininginput <- as.data.frame(runif(50, min=0, max=100))
trainingoutput <- sqrt(traininginput)
#Column bind the data into one variable
trainingdata <- cbind(traininginput,trainingoutput)
colnames(trainingdata) <- c("Input","Output")
#Train the neural network
net.sqrt <- neuralnet(Output~Input,trainingdata, hidden=c(input$w, input$b), threshold=0.01)
print(net.sqrt)
#Plot the neural network
plot(net.sqrt)
#Test the neural network on some test data
testdata <- as.data.frame((1:13)^2) #Generate some squared numbers
net.results <- predict(net.sqrt, testdata) #Run them through the neural network
#Lets see what properties net.sqrt has
class(net.results)
#Lets see the results
print(net.results)
#Lets display a better version of the results
cleanoutput <- cbind(testdata,sqrt(testdata),
as.data.frame(net.results))
colnames(cleanoutput) <- c("Input","ExpectedOutput","NeuralNetOutput")
head(cleanoutput)
lm1<- lm(NeuralNetOutput~ ExpectedOutput, data = cleanoutput)
ggplot(data = cleanoutput, aes(x= ExpectedOutput, y= NeuralNetOutput)) + geom_point() +
geom_abline(intercept = 0, slope = 1
, color="brown", size=0.5)
And this is the code I tried in shiny :
library(shiny)
library("neuralnet")
require(ggplot2)
ui <- fluidPage(
fluidRow(
column(width = 12, class = "well",
h4("Neural Network Plot"),
plotOutput("main_plot"),
hr(),
numericInput(inputId = "w",
label = "Weight(w):",
value = 5),
numericInput(inputId = "b",
label = "Biased(b):",
value = 5),
actionButton("update", "Update View"))))
#--------------------------------------------------------------------------------------------
server <- function(input, output) {
output$main_plot <- renderPlot({
traininginput <- as.data.frame(runif(50, min=0, max=100))
trainingoutput <- sqrt(traininginput)
trainingdata <- cbind(traininginput,trainingoutput)
colnames(trainingdata) <- c("Input","Output")
net.sqrt <- neuralnet(Output~Input,trainingdata, hidden=c(input$w, input$b), threshold=0.01)
print(net.sqrt)
plot(net.sqrt)
testdata <- as.data.frame((1:13)^2) #Generate some squared numbers
net.results <- predict(net.sqrt, testdata) #Run them through the neural network
class(net.results)
print(net.results)
cleanoutput <- cbind(testdata,sqrt(testdata),
as.data.frame(net.results))
colnames(cleanoutput) <- c("Input","ExpectedOutput","NeuralNetOutput")
head(cleanoutput)
lm1<- lm(NeuralNetOutput~ ExpectedOutput, data = cleanoutput)
ggplot(data = cleanoutput, aes(x= ExpectedOutput, y= NeuralNetOutput)) + geom_point() +
geom_abline(intercept = 0, slope = 1
, color="brown", size=0.5)})}
shinyApp(ui,server)
I wish to add an actionButton that really works so that I can Update my view instead of let it update automatically. What should I put inside my server.R ?
In the line 20 of the reproducible example, the variable w and bis the values I wish to control in the shiny server.
And is there a better to present my script? As I am quite new to shiny, I hope I can get some little guide/hints from anyone of you..

Answer 1

See the documentation example for the actionButton, specifically how isolate is being used there. This is the code from the example for posterity:
ui <- fluidPage(
sliderInput("obs", "Number of observations", 0, 1000, 500),
actionButton("goButton", "Go!"),
plotOutput("distPlot")
)
server <- function(input, output) {
output$distPlot <- renderPlot({
# Take a dependency on input$goButton. This will run once initially,
# because the value changes from NULL to 0.
input$goButton
# Use isolate() to avoid dependency on input$obs
dist <- isolate(rnorm(input$obs))
hist(dist)
})
}
Normally when you would move slider, shiny would update the histogram "continuously". As you isolate this variable, it waits on a button press.