I prepared rather simple shiny application which resembles the problem in my much more complex application.
The three necessary components of my application are:
The number, i.e. year, can be changed in two different ways: by 1) adding a value in the textInput or 2) by clicking the action button
When the year is changed by the actionButtion, it must automatically change current value in the textInput box
When the year is changed by the textInput, reactive value for the
action button must reset to zero.
I have two observeEvents which both target two reactive values. The problem is, if I click the actionButton several times too quickly, this creates a loop of switching between those two events.
Is there any efficient tool available in Shiny which help in such situations? E.g. to prevent users to click on the button prior the execution of task.
# import libraries
library(shiny)
library(ggplot2)
library(dplyr)
ui <- shinyUI(fluidPage(
sidebarLayout(
sidebarPanel(
uiOutput("ui_year"),
uiOutput("ui_plus")
),
mainPanel(
plotOutput("plot1")
)
)))
server <- shinyServer(function(input, output) {
# Generate random data
data <- data.frame(
year = seq(1900, 2000),
value = runif(n = 101, min = -3, max = 3)
)
# Define two reactive values: add and year
rv <- reactiveValues()
rv$add <- 0
rv$year <- 2000
# render actionButton
output$ui_plus <- renderUI({
actionButton(inputId = "add",
label = paste0(""),
icon = icon("plus"))
})
# render textInput
output$ui_year <- renderUI({
textInput(inputId = "year_1", label = NULL,
value = eval(parse( text = rv$year)),
width = "100%",
placeholder = NULL)
})
# Define two observe events, based on A) action button and B) textInput
observeEvent(input$year_1, {
rv$year <- input$year_1
rv$add <- 0
})
observeEvent(input$add, {
rv$add <- rv$add + 1
rv$year <- as.numeric(rv$year) + 1
})
# Render output
output$plot1 <- renderPlot({
sumValue <- as.numeric(rv$year) + as.numeric(rv$add)
ggplot(data, aes(x = year, y = value)) + geom_line()+ annotate("text", x = -Inf, y = Inf, hjust = -0.2, vjust = 1, label = sumValue )
})
})
shinyApp(ui = ui, server = server)
Related
I am attempting to create a shiny app with editable cells where the underlying data frame updates depending on user input. I asked a similar question earlier and was pointed to this link.
My app:
library(shiny)
library(tidyverse)
library(DT)
ui <- fluidPage(
# Application title
titlePanel("blah"),
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30)
),
# Show a plot of the generated distribution
mainPanel(
DT::DTOutput('ex_table'),
)
)
)
server <- function(input, output,session) {
example_data <- data.frame(x = rnorm(10, 0, 1) %>% round) %>% mutate(y = x + 1)
output$ex_table <- DT::renderDT(example_data, selection = 'none', editable = TRUE)
# from https://yihui.shinyapps.io/DT-edit/
observeEvent(input$ex_table_cell_edit, {
example_data <<- editData(example_data, input$ex_table, 'ex_table', rownames = FALSE)
})
}
# Run the application
shinyApp(ui = ui, server = server)
This app loads when you press run in rstudio. But when trying to edit a cell in column x, the app crashes with error message 'Warning: Error in split.default: first argument must be a vector'.
This is the problem code block:
# from https://yihui.shinyapps.io/DT-edit/
observeEvent(input$ex_table_cell_edit, {
example_data <<- editData(example_data, input$ex_table, 'ex_table', rownames = FALSE)
})
Screens:
The app loads up fine. Y is always x + 1 due to the data frame definition:
example_data <- data.frame(x = rnorm(10, 0, 1) %>% round) %>% mutate(y = x + 1)
When a user edits the x column, I wouldlike the y column to update to be whatever x is plus one:
When I press enter, desired behavior is to have y = 101.
Per the link suggested, https://yihui.shinyapps.io/DT-edit/, I'd prefer to use editData() as opposed to what was provided in my previous post, because editData() approach looks simpler and more readable.
But when I try it my shiny app always crashes?
Your existing program works fine if you put rownames=FALSE in output$ex_table. However, it only allows you to edit table cells. If you still want to maintain the dependency y=x+1, you need to define like #Waldi did in his answer earlier. Also, once you modify, you need to feed it back to the output via replaceData() of Proxy or define a reactiveValues object as shown below.
ui <- fluidPage(
# Application title
titlePanel("blah"),
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30)
),
# Show a plot of the generated distribution
mainPanel(
DTOutput('ex_table'),
)
)
)
server <- function(input, output,session) {
DF1 <- reactiveValues(data=NULL)
example_data <- data.frame(x = rnorm(10, 0, 1) %>% round) %>% mutate(y = x + 1)
DF1$data <- example_data
output$ex_table <- renderDT(DF1$data, selection = 'none', editable = TRUE, rownames = FALSE)
observeEvent(input$ex_table_cell_edit, {
info = input$ex_table_cell_edit
str(info)
i = info$row
j = info$col + 1 ## offset by 1
example_data <<- editData(example_data, input$ex_table_cell_edit, 'ex_table', rownames = FALSE)
if(j==1){example_data[i,j+1]<<-as.numeric(example_data[i,j])+1} ### y = x + 1 dependency
DF1$data <- example_data
})
}
# Run the application
shinyApp(ui = ui, server = server)
I want to create a small shiny app to explore a scoring function that I am writing for a set of data observations. This is my first shiny app so bear with me.
What I want to show is the data table where one column is computed by a function (let's say f(x) = x^2 + y) where x is another (numeric) column in the table and y should be adjustable with a slider in the sidebar.
I want to make the table reactive, so that as soon as the slider is adjusted, the content that is displayed will be updated. Does anyone have a link to a tutorial (I could not find a similar problem) or a suggestion how to handle this. If so, please let me know!
This is the code I have so far:
library(shiny)
#### INIT ####
x <- 1
y <- 0.5
z <- 2
df <- data.frame(
a=1:10,
b=10:1
)
df['score'] <- df[,x]^y + z
#### UI ####
ui <- fluidPage(
title = "Examples of DataTables",
sidebarLayout(
sidebarPanel(
sliderInput("x", "x:",
min = 0, max = ncol(df),
value = 1),
sliderInput("y", "y:",
min = 1, max = 10,
value = 1),
sliderInput("z", "z:",
min = 1, max = 100,
value = 20)
),
mainPanel(
tabsetPanel(
id = 'dataset',
tabPanel("df", dataTableOutput("df"))
)
)
)
)
#### SERVER ####
server <- function(input, output) {
sliderValues <- reactive({
df['score'] <- df[,input$x]^input$y + input$z
})
sliderValues()
output$df<- renderDataTable(df)
}
#### RUN ####
shinyApp(ui = ui, server = server)
Just make the data.frame you actually plot reactive. For example
server <- function(input, output) {
calcualtedValues <- reactive({
df['score'] <- df[,input$x]^input$y + input$z
df
})
output$df<- renderDataTable(calcualtedValues())
}
Here the calcualtedValues reactive element returns a new data.frame when the input is updated, and then you actually render that updated data.frame rather than the original data.frame each time.
I'm working on a shiny app that accepts a DNA sequence (e.g. "ACTGACTG"), does some calculations and plots the result when a button is clicked. When I store a Biostrings::DNAString in a reactiveValues object, my shiny app only reacts to changes if the number of characters of the sequence changes, e.g. if "AA" is entered first, the plot doesn't change if "CC" is then entered but does change if "AAAA" is entered. It responds to all changes if I store the object as a character. Here's a simplified example:
library(shiny)
library(shinyBS)
library(Biostrings)
library(ggplot2)
ui <- fluidPage(
sidebarLayout(
sidebarPanel(
ref_seqs <- textInput("ref_seqs", "Sequence", width = "100%",
value = NULL, placeholder = "ATGCTGCTGGTTATTAGATTAGT"),
run_guide <- bsButton("run", 'Run', type = "action",
style = "success", block = TRUE)
),
mainPanel(
plotOutput("reference")
)
)
)
server <- function(input, output) {
ref <- reactiveValues(sq = NULL)
dat <- reactive({
req(input$run)
chrs <- strsplit(as.character(ref$sq),"")[[1]]
data.frame(label = chrs, x = seq_along(chrs))
})
observeEvent(input$run, {
ref$sq <- Biostrings::DNAString(input$ref_seqs)
#ref$sq <- input$ref_seqs
})
output$reference <- renderPlot({
ggplot(dat(), aes(x = x, y = factor(1), label = label)) + geom_text(size = 12)
})
}
shinyApp(ui = ui, server = server)
If I comment out the line ref$sq <- Biostrings::DNAString(input$ref_seqs) and uncomment the line below it, the plot updates upon changes.
Can anyone explain why this happens? Do reactiveValues only work with base types? Thanks!
I have a randomly generated data.frame. The user can modify a slider to choose the number of points. Then I plot this data.frame.
I want to add a button than when clicked, it performs a modification in the previous randomly generated data.frame (but without regenerating the data.frame). The modification is a voronoid relaxation, and it should be performed once per each time the button is clicked and the graph generated.
Until now, I have not achieved anything similar...
ui.R
library(shiny)
# Define UI for application that draws a histogram
shinyUI(fluidPage(
# Application title
titlePanel("Map Generator:"),
# Sidebar with a slider input for the number of bins
sidebarLayout(
sidebarPanel(
p("Select the power p to generate 2^p points."),
sliderInput("NumPoints",
"Number of points:",
min = 1,
max = 10,
value = 9),
actionButton("GenPoints", "Generate"),
actionButton("LloydAlg", "Relaxe")
),
# Show a plot of the generated distribution
mainPanel(
plotOutput("distPlot",height = 700, width = "auto")
)
)
))
server.R
library(shiny)
library(deldir)
shinyServer(function(input, output) {
observeEvent(input$NumPoints,{
x = data.frame(X = runif(2^input$NumPoints,1,1E6),
Y = runif(2^input$NumPoints,1,1E6))
observeEvent(input$LloydAlg, {
x = tile.centroids(tile.list(deldir(x)))
})
output$distPlot <- renderPlot({
plot(x,pch = 20,asp=1,xlim=c(0,1E6),ylim = c(0,1E6))
})
})
})
Of course there is something that I must be doing wrong, but I am quite new into shiny I can't figure it out what I am doing wrong...
This should work (even though I am pretty sure this could be improved):
shinyServer(function(input, output) {
library(deldir)
data = data.frame(
X = runif(2^9, 1, 1E6),
Y = runif(2^9, 1, 1E6)
)
rv <- reactiveValues(x = data)
observeEvent(input$GenPoints, {
rv$x <- data.frame(
X = runif(2^input$NumPoints,1,1E6),
Y = runif(2^input$NumPoints,1,1E6)
)
})
observeEvent(input$LloydAlg, {
rv$x = tile.centroids(tile.list(deldir(rv$x)))
})
output$distPlot <- renderPlot({
plot(rv$x,pch = 20,asp=1,xlim=c(0,1E6),ylim = c(0,1E6))
})
})
So first I initialize the points to plot. I use runif(2^9, 1, 1E6) because the starting value of the sliderInput is 9 all the time.
I also removed the observeEvent from the sliderInput and moved it to the GenPoints actionButton.
I have a shiny app in which the user selects a bunch of inputs, such as the x range, y range, types of scaling and the selection of a particular subset of the data set through a drop down list.
This is all done through the use of reactives. X and Y range slider inputs react to changes in the selection of the data set because the minimum and maximum have to be found again. This takes maybe about 1-2 seconds while the shiny app is working and the user chooses a different option in the drop down list. During those 1-2 seconds, the plot switches to plotting the selected new subset of data with the old x and y range before quickly switching to the correct plot once the x and y range sliders change.
A fix would be to just refresh the plot on a button by isolating everything else. But would there be a way to keep the plot reactive to changes, but just wait until all the dependent things have finished calculating?
Thanks
This is the plot:
output$plot1 <- rCharts::renderChart2({
if(!is.null(input$date_of_interest) &&
!is.null(input$xrange) &&
!is.null(input$yrange) &&
!is.null(data()) &&
isolate(valid_date_of_interest())) {
filtered_data<- dplyr::filter(isolate(data()), id==input$choice)
p <- tryCatch(plot_high_chart(
data,
first_date_of_interest = input$date_of_interest,
ylim = input$yrange,
xlim = input$xrange),
error = function(e) e,
warning = function(w) w)
if(!inherits(p, "error") && !inherits(p, "warning")) {
return(p)
}
}
return(rCharts::Highcharts$new())
})
and x range(y range is similar):
output$xrange <- renderUI({
if(!is.null(input$date_of_interest) &&
!is.null(input$choice) &&
!is.null(valid_date_of_interest()) &&
isolate(valid_date_of_interest())) {
temp_data <- dplyr::filter(isolate(data()), date == input$date_of_interest)
temp <- data.table::data.table(temp_data, key = "child.id")
the_days <- as.double(as.Date(temp$last.tradeable.dt) - as.Date(temp$date))
min_days <- min(the_days,na.rm=TRUE)
max_days <- max(the_days,na.rm=TRUE)
sliderInput("xrange",
"Days Range (X Axis)",
step = 1,
min = 0,
max = max_days + 10,
value = c(min_days,max_days)
)
}
})
and the input choice:
output$choice<- renderUI({
selectInput("choice",
"Choose:",
unique(data$id),
selected = 1
)
})
Some direction and suggestions to implement would be useful. I've thought about having global variables such as x_range_updated, y_range_updated, that are set to false in the code for output$choice and then set to true in the code for output$xrange, etc. And then have plot1 depend on them being true. Other suggestions to approach this problem would be appreciated.
Edit 2019-02-14
Since Shiny 1.0.0 (released after I originally wrote this answer), there is now a debounce function which adds functionality to help with this kind of task. For the most part, this avoids the need for the code I originally wrote, although under the hood it works in a similar manner. However, as far as I can tell, debounce doesn't offer any way of short-circuiting the delay with a redraw action button along the lines of what I'd done here. I've therefore created a modified version of debounce that offers this functionality:
library(shiny)
library(magrittr)
# Redefined in global namespace since it's not exported from shiny
`%OR%` <- shiny:::`%OR%`
debounce_sc <- function(r, millis, priority = 100, domain = getDefaultReactiveDomain(), short_circuit = NULL)
{
force(r)
force(millis)
if (!is.function(millis)) {
origMillis <- millis
millis <- function() origMillis
}
v <- reactiveValues(trigger = NULL, when = NULL)
firstRun <- TRUE
observe({
r()
if (firstRun) {
firstRun <<- FALSE
return()
}
v$when <- Sys.time() + millis()/1000
}, label = "debounce tracker", domain = domain, priority = priority)
# New code here to short circuit the timer when the short_circuit reactive
# triggers
if (inherits(short_circuit, "reactive")) {
observe({
short_circuit()
v$when <- Sys.time()
}, label = "debounce short circuit", domain = domain, priority = priority)
}
# New code ends
observe({
if (is.null(v$when))
return()
now <- Sys.time()
if (now >= v$when) {
v$trigger <- isolate(v$trigger %OR% 0) %% 999999999 +
1
v$when <- NULL
}
else {
invalidateLater((v$when - now) * 1000)
}
}, label = "debounce timer", domain = domain, priority = priority)
er <- eventReactive(v$trigger, {
r()
}, label = "debounce result", ignoreNULL = FALSE, domain = domain)
primer <- observe({
primer$destroy()
er()
}, label = "debounce primer", domain = domain, priority = priority)
er
}
This then permits a simplified shiny application. I've switched to the single file mode of working, but the UI remains the same as the original one.
ui <- fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30),
selectInput("column", "Column", colnames(faithful), selected = "waiting"),
actionButton("redraw", "Redraw")
),
mainPanel(
plotOutput("distPlot")
)
)
)
server <- function(input, output, session) {
reac <- reactive(list(bins = input$bins, column = input$column)) %>%
debounce_sc(5000, short_circuit = reactive(input$redraw))
# Only triggered by the debounced reactive
output$distPlot <- renderPlot({
x <- faithful[, reac()$column]
bins <- seq(min(x), max(x), length.out = reac()$bins + 1)
hist(x, breaks = bins, col = 'darkgray', border = 'white',
main = sprintf("Histogram of %s", reac()$column))
})
}
shinyApp(ui, server)
Original version (pre Shiny 1.0.0)
You haven't provided a reproducible example, so I've gone with something based on the Shiny faithful example that is the default in RStudio. The solution I've got will always have a (configurable) 5 second delay between an input changing and the graph being redrawn. Each change in input resets the timer. There's also a redraw button for the impatient which redraws the graph immediately. The values of the reactive value 'redraw' and the inputs are shown in the console every time an input changes or the timer ticks. This should be removed for production use. Hopefully this meets your needs!
library(shiny)
shinyUI(fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
sliderInput("bins",
"Number of bins:",
min = 1,
max = 50,
value = 30),
selectInput("column", "Column", colnames(faithful), selected = "waiting"),
actionButton("redraw", "Redraw")
),
mainPanel(
plotOutput("distPlot")
)
)
))
server.R
library(shiny)
shinyServer(function(input, output, session) {
reac <- reactiveValues(redraw = TRUE, bins = isolate(input$bins), column = isolate(input$column))
# If any inputs are changed, set the redraw parameter to FALSE
observe({
input$bins
input$column
reac$redraw <- FALSE
})
# This event will also fire for any inputs, but will also fire for
# a timer and with the 'redraw now' button.
# The net effect is that when an input is changed, a 5 second timer
# is started. This will be reset any time that a further input is
# changed. If it is allowed to lapse (or if the button is pressed)
# then the inputs are copied into the reactiveValues which in turn
# trigger the plot to be redrawn.
observe({
invalidateLater(5000, session)
input$bins
input$column
input$redraw
isolate(cat(reac$redraw, input$bins, input$column, "\n"))
if (isolate(reac$redraw)) {
reac$bins <- input$bins
reac$column <- input$column
} else {
isolate(reac$redraw <- TRUE)
}
})
# Only triggered when the copies of the inputs in reac are updated
# by the code above
output$distPlot <- renderPlot({
x <- faithful[, reac$column]
bins <- seq(min(x), max(x), length.out = reac$bins + 1)
hist(x, breaks = bins, col = 'darkgray', border = 'white',
main = sprintf("Histogram of %s", reac$column))
})
})