Closed mattlee821 closed 4 years ago
ismirsehregal
commented
4 years ago Very interesting. I'm having a similar issue. After updating to shinycssloaders version 0.3 the choices of my selectizeInput's in some of my apps were no longer populated (the choices should be loaded from .rds files - it seemed the UI rendering was blocked). I switched to addSpinner() from shinyWidgets by now, which is working fine.
daattali
commented
4 years ago Is this potentially related to #39? Could you try to do what I suggested in this comment to see if it's affected by the same issue?
mattlee821
commented
4 years ago I've put withSpinner() back in and tried the following as suggested in #39
Using remotes::install_github("andrewsali/shinycssloaders", ref="8779ff0f0ad32b0731c06067e35fa65d85f66a89") leads to a working app.
Using remotes::install_github("andrewsali/shinycssloaders", ref="9565546494f3395a257546312313929ec0bbf968") leads to a working app
Using install.packages("shinycssloaders") leads to a broken app
Using remotes::install_github("andrewsali/shinycssloaders") leads to a broken app
daattali
commented
4 years ago Do you have a small reproducible sample code that you used for these tests?
mattlee821
commented
4 years ago I've copied straight from the app as minimally as I can get to reproduce. Line 215 has withSpinner() on.
data <- data.frame(this = 1:10, is = 1:10, some = 1:10, great = 1:10, example = 1:10, data = 1:10)
write.table(data, "/Users/ml16847/Downloads/data_frame.txt",
row.names = FALSE, col.names = TRUE, quote = FALSE, sep = "\t")
# load libraries ====
library(shiny)
library(shinydashboard)
library(shinyLP)
library(shinythemes)
library(plotly)
library(ggplot2)
library(data.table)
library(circlize)
library(dplyr)
library(stringr)
library(fs)
library(rmarkdown)
library(markdown)
library(data.table)
install.packages("shinycssloaders")
library(shinycssloaders)
#------------------------------------------------------------------------------#
ui <- navbarPage(
title = "",
theme = shinytheme("flatly"),
fluid = TRUE,
selected = "MR Viz",
inverse = FALSE,
# ANALYSIS ====
tabPanel(title = "Analysis",
## UPLOAD YOUR DATA ====
tabPanel(titlePanel(h5("Step 1")),
sidebarLayout(
## > sidebar panel ====
sidebarPanel(
helpText("Select paramaters for data upload then upload data. Functions based on R read.table()."),
checkboxInput(
inputId = 'header',
label = 'Header',
value = TRUE
),
checkboxInput(inputId = "stringAsFactors", "stringAsFactors", FALSE),
radioButtons(
inputId = 'sep',
label = 'Separator',
choices = c(
Comma = ',',
Semicolon = ';',
Tab = '\t',
Space = ''
),
selected = '\t'
),
radioButtons(
inputId = "quote",
label = "Quote",
choices = c(
None = "",
"Double Quote" = '"',
"Single Quote" = "'"
),
selected = '"'
),
fileInput(
inputId = "file1",
label = "Track 1",
multiple = TRUE,
accept = c(
"text/csv",
"text/comma-separated-values",
"text/plain",
".csv"
)
),
fileInput(
inputId = "file2",
label = "Track 2",
multiple = TRUE,
accept = c(
"text/csv",
"text/comma-separated-values",
"text/plain",
".csv"
)
),
fileInput(
inputId = "file3",
label = "Track 3",
multiple = TRUE,
accept = c(
"text/csv",
"text/comma-separated-values",
"text/plain",
".csv")
),
helpText("Select paramaters for Circos plot"),
selectInput("track_number",
"Number of tracks",
choices = c(1,2,3),
selected = 1),
selectInput("label_column",
"Label:",
choices="",
selected = ""),
selectInput("section_column",
"Group:",
choices="",
selected = ""),
selectInput("estimate_column",
"Estimate:",
choices="",
selected = ""),
selectInput("pvalue_column",
"P-value:",
choices="",
selected = ""),
numericInput("pvalue_adjustment",
"P-value adjustment:",
value = 123),
textOutput("pval"),
br(),
selectInput("confidence_interval_lower_column",
"Lower confidence interval:",
choices="",
selected = ""),
selectInput("confidence_interval_upper_column",
"Upper confidence interval:",
choices="",
selected = ""),
h4("Legend paramaters"),
radioButtons(
inputId = 'legend',
label = 'Legend',
choices = c(
Yes = 'TRUE',
No = 'FALSE'),
selected = 'FALSE'),
textInput("track2_label",
"Track 2 legend label",
value = "Example1"),
textInput("track3_label",
"Track 3 legend label",
value = "Example2"),
textInput("track4_label",
"Track 4 legend label",
value = "Example3"),
textInput("pvalue_label",
"P-value threshold label",
value = "P > 123"),
textOutput("pval_label"),
br(),
actionButton("circosbutton","Plot")
),
## > main panel ====
mainPanel(
tabsetPanel(
tabPanel("Track 1",
conditionalPanel(
condition = "output.file_imported",
h4("Description of uploaded data"),
textOutput("rowcount"),
textOutput("colcount"),
br(),
h4("First rows of uploaded data"),
tableOutput(outputId = "data1"),
br(),
h4("Volcano plot of uploaded data"),
plotlyOutput("volcanoplot1")
)),
tabPanel("Track 2",
conditionalPanel(
condition = "output.file_imported2",
h4("Description of uploaded data"),
textOutput("rowcount2"),
textOutput("colcount2"),
br(),
h4("First rows of uploaded data"),
tableOutput(outputId = "data2"),
br(),
h4("Volcano plot of uploaded data"),
plotlyOutput("volcanoplot2")
)),
tabPanel("Track 3",
conditionalPanel(
condition = "output.file_imported3",
h4("Description of uploaded data"),
textOutput("rowcount3"),
textOutput("colcount3"),
br(),
h4("First rows of uploaded data"),
tableOutput(outputId = "data3"),
br(),
h4("Volcano plot of uploaded data"),
plotlyOutput("volcanoplot3")
)),
tabPanel(withSpinner(uiOutput("pdf")))
)
)
)
)
)
)
#------------------------------------------------------------------------------#
server <- shinyServer(function(input, output, session) {
# HOME ====
# Download example dataset
output$downloadexampledata1 <- downloadHandler(
filename = function() {
paste0("exampledata1.txt")
},
content = function(file) {
file.copy("exampledata1.txt", file)
},
contentType = NA
)
output$downloadexampledata2 <- downloadHandler(
filename = function() {
paste0("exampledata2.txt")
},
content = function(file) {
file.copy("exampledata2.txt", file)
},
contentType = NA
)
output$downloadexampledata3 <- downloadHandler(
filename = function() {
paste0("exampledata3.txt")
},
content = function(file) {
file.copy("exampledata3.txt", file)
},
contentType = NA
)
# ANALYSIS ====
# UPLOAD YOUR DATA ====
# > sidebar panel ====
# Read data from multiple .csv/.txt files
track2_data1 <- eventReactive(input$file1, {
rbindlist(
lapply(
input$file1$datapath,
FUN = read.csv,
header = input$header,
sep = input$sep,
quote = input$quote
),
use.names = TRUE,
fill = TRUE
)
})
track3_data1 <- eventReactive(input$file2, {
rbindlist(
lapply(
input$file2$datapath,
FUN = read.csv,
header = input$header,
sep = input$sep,
quote = input$quote
),
use.names = TRUE,
fill = TRUE
)
})
track4_data1 <- eventReactive(input$file3, {
rbindlist(
lapply(
input$file3$datapath,
FUN = read.csv,
header = input$header,
sep = input$sep,
quote = input$quote
),
use.names = TRUE,
fill = TRUE
)
})
# > main panel ====
# >> Track 1 ====
# Define conditional element to show main panel only when file(s) uploaded
output$file_imported <- reactive({
return(!is.null(input$file1))
})
outputOptions(output, "file_imported", suspendWhenHidden = FALSE)
# Create data to describe the imported dataset
output$rowcount <-
renderText(paste("Total number of rows in uploaded file(s):", nrow(track2_data1())))
output$colcount <-
renderText(paste("Total number of columns in uploaded file(s):", ncol(track2_data1())))
# Render head of imported dataset
output$data1 <- renderTable({
track2_data1() %>% head
})
# Render volcano plot
observeEvent(input$file1,
handlerExpr = {
output$volcanoplot1 <- renderPlotly({
volcanoplot <- plot_ly(
data = track2_data1(),
type = "scatter",
colors = NULL,
alpha = NULL,
x = track2_data1()$beta,
y = -log10(track2_data1()$Pvalue),
text = track2_data1()$outcome_name,
mode = "markers"
) %>%
layout(xaxis = list(title = "effect_estimate"),
yaxis = list(title = "-log10(p-value)"))
})
})
# >> Track 2 ====
# Define conditional element to show main panel only when file(s) uploaded
output$file_imported2 <- reactive({
return(!is.null(input$file2))
})
outputOptions(output, "file_imported2", suspendWhenHidden = FALSE)
# Create data to describe the imported dataset
output$rowcount2 <-
renderText(paste("Total number of rows in uploaded file(s):", nrow(track3_data1())))
output$colcount2 <-
renderText(paste("Total number of columns in uploaded file(s):", ncol(track3_data1())))
# Render head of imported dataset
output$data2 <- renderTable({
track3_data1() %>% head
})
# Render volcano plot
observeEvent(input$file2,
handlerExpr = {
output$volcanoplot2 <- renderPlotly({
volcanoplot <- plot_ly(
data = track3_data1(),
type = "scatter",
colors = NULL,
alpha = NULL,
x = track3_data1()$beta,
y = -log10(track3_data1()$Pvalue),
text = track3_data1()$outcome_name,
mode = "markers"
) %>%
layout(xaxis = list(title = "effect_estimate"),
yaxis = list(title = "-log10(p-value)"))
})
})
# >> Track 3 ====
# Define conditional element to show main panel only when file(s) uploaded
output$file_imported3 <- reactive({
return(!is.null(input$file3))
})
outputOptions(output, "file_imported3", suspendWhenHidden = FALSE)
# Create data to describe the imported dataset
output$rowcount3 <-
renderText(paste("Total number of rows in uploaded file(s):", nrow(track4_data1())))
output$colcount3 <-
renderText(paste("Total number of columns in uploaded file(s):", ncol(track4_data1())))
# Render head of imported dataset
output$data3 <- renderTable({
track4_data1() %>% head
})
# Render volcano plot
observeEvent(input$file3,
handlerExpr = {
output$volcanoplot3 <- renderPlotly({
volcanoplot <- plot_ly(
data = track4_data1(),
type = "scatter",
colors = NULL,
alpha = NULL,
x = track4_data1()$beta,
y = -log10(track4_data1()$Pvalue),
text = track4_data1()$outcome_name,
mode = "markers"
) %>%
layout(xaxis = list(title = "effect_estimate"),
yaxis = list(title = "-log10(p-value)"))
})
})
# CIRCOS PARAMETERS ====
# > sidebar panel ====
output$pval <- renderText(paste0("New threshold: 0.05/", input$pvalue_adjustment, " = ", round(0.05/input$pvalue_adjustment, digits = 8))
)
output$pval_label <- renderText(paste0("P > 0.05/", input$pvalue_adjustment))
# When the first file is uploaded, pass the column headings to the selectInput widgets
observeEvent(input$file1, {
updateSelectInput(session,
"label_column",
choices = c("",colnames(track2_data1())))
updateSelectInput(session,
"section_column",
choices = c("",colnames(track2_data1())))
updateSelectInput(session,
"estimate_column",
choices = c("",colnames(track2_data1())))
updateSelectInput(session,
"pvalue_column",
choices = c("",colnames(track2_data1())))
updateSelectInput(session,
"confidence_interval_lower_column",
choices = c("",colnames(track2_data1())))
updateSelectInput(session,
"confidence_interval_upper_column",
choices = c("",colnames(track2_data1())))
}
)
# Because the my_circos_plot() function expects a column number rather than name,
# which is what the selectInput widgets return, use the following functions to convert the
# column name into the column number
label_column_number <- reactive({which(colnames(track2_data1())==input$label_column)})
section_column_number <- reactive({which(colnames(track2_data1())==input$section_column)})
estimate_column_number <- reactive({which(colnames(track2_data1())==input$estimate_column)})
pvalue_column_number <- reactive({which(colnames(track2_data1())==input$pvalue_column)})
confidence_interval_lower_column_number <- reactive({which(colnames(track2_data1())==input$confidence_interval_lower_column)})
confidence_interval_upper_column_number <- reactive({which(colnames(track2_data1())==input$confidence_interval_upper_column)})
output$pdf <- renderUI({
if(file.exists(outfile)){
tags$iframe(src=outfile,style="height:600px; width:100%")}
})
outfile <- tempfile("myfile", fileext = ".pdf", tmpdir ="www")
observeEvent(input$circosbutton,
handlerExpr = {
output$pdf <- renderUI({
pdf(outfile, width = 35, height = 35, pointsize = 30)
isolate({
my_circos_plot(
track_number = input$track_number,
track2_data1 = track2_data1(),
track3_data1 = track3_data1(),
track4_data1 = track4_data1(),
section_column = section_column_number(), # This returns the column number, as defined above.
label_column = label_column_number(),
estimate_column = estimate_column_number(),
pvalue_column = pvalue_column_number(),
pvalue_adjustment = (0.05/input$pvalue_adjustment),
confidence_interval_lower_column = confidence_interval_lower_column_number(),
confidence_interval_upper_column = confidence_interval_upper_column_number(),
legend = input$legend,
track2_label = input$track2_label,
track3_label = input$track3_label,
track4_label = input$track4_label,
pvalue_label = input$pvalue_label)
})
dev.off()
if(file.exists(outfile)){
tags$iframe(src=str_sub(outfile,5),style="height:800px; width:100%")}
})
})
# Return a list containing the filename
onStop(function() {
unlink(outfile, recursive = TRUE)
})
# > main panel ====
# Keep shiny app awake ====
output$keepAlive <- renderText({
req(input$count)
paste("keep alive ", input$count)
})
})
#------------------------------------------------------------------------------#
shinyApp(ui = ui, server = server)Could you try to shorten that to a ~20 line app that only contains the essentials for seeing the issue?
On Mon., Jan. 27, 2020, 02:17 matt, notifications@github.com wrote:
I've copied straight from the app as minimally as I can get to reproduce. Line 215 has withSpinner() on.
data <- data.frame(this = 1:10, is = 1:10, some = 1:10, great = 1:10, example = 1:10, data = 1:10) write.table(data, "/Users/ml16847/Downloads/data_frame.txt", row.names = FALSE, col.names = TRUE, quote = FALSE, sep = "\t")
load libraries ====
library(shiny) library(shinydashboard) library(shinyLP) library(shinythemes) library(plotly) library(ggplot2) library(data.table) library(circlize) library(dplyr) library(stringr) library(fs) library(rmarkdown) library(markdown) library(data.table)
install.packages("shinycssloaders") library(shinycssloaders)
------------------------------------------------------------------------------
ui <- navbarPage( title = "", theme = shinytheme("flatly"), fluid = TRUE, selected = "MR Viz", inverse = FALSE,
ANALYSIS ====
tabPanel(title = "Analysis",
## UPLOAD YOUR DATA ==== tabPanel(titlePanel(h5("Step 1")), sidebarLayout( ## > sidebar panel ==== sidebarPanel( helpText("Select paramaters for data upload then upload data. Functions based on R read.table()."), checkboxInput( inputId = 'header', label = 'Header', value = TRUE ), checkboxInput(inputId = "stringAsFactors", "stringAsFactors", FALSE), radioButtons( inputId = 'sep', label = 'Separator', choices = c( Comma = ',', Semicolon = ';', Tab = '\t', Space = '' ), selected = '\t' ), radioButtons( inputId = "quote", label = "Quote", choices = c( None = "", "Double Quote" = '"', "Single Quote" = "'" ), selected = '"' ), fileInput( inputId = "file1", label = "Track 1", multiple = TRUE, accept = c( "text/csv", "text/comma-separated-values", "text/plain", ".csv" ) ), fileInput( inputId = "file2", label = "Track 2", multiple = TRUE, accept = c( "text/csv", "text/comma-separated-values", "text/plain", ".csv" ) ), fileInput( inputId = "file3", label = "Track 3", multiple = TRUE, accept = c( "text/csv", "text/comma-separated-values", "text/plain", ".csv") ), helpText("Select paramaters for Circos plot"), selectInput("track_number", "Number of tracks", choices = c(1,2,3), selected = 1), selectInput("label_column", "Label:", choices="", selected = ""), selectInput("section_column", "Group:", choices="", selected = ""), selectInput("estimate_column", "Estimate:", choices="", selected = ""), selectInput("pvalue_column", "P-value:", choices="", selected = ""), numericInput("pvalue_adjustment", "P-value adjustment:", value = 123), textOutput("pval"), br(), selectInput("confidence_interval_lower_column", "Lower confidence interval:", choices="", selected = ""), selectInput("confidence_interval_upper_column", "Upper confidence interval:", choices="", selected = ""), h4("Legend paramaters"), radioButtons( inputId = 'legend', label = 'Legend', choices = c( Yes = 'TRUE', No = 'FALSE'), selected = 'FALSE'), textInput("track2_label", "Track 2 legend label", value = "Example1"), textInput("track3_label", "Track 3 legend label", value = "Example2"), textInput("track4_label", "Track 4 legend label", value = "Example3"), textInput("pvalue_label", "P-value threshold label", value = "P > 123"), textOutput("pval_label"), br(), actionButton("circosbutton","Plot") ), ## > main panel ==== mainPanel( tabsetPanel( tabPanel("Track 1", conditionalPanel( condition = "output.file_imported", h4("Description of uploaded data"), textOutput("rowcount"), textOutput("colcount"), br(), h4("First rows of uploaded data"), tableOutput(outputId = "data1"), br(), h4("Volcano plot of uploaded data"), plotlyOutput("volcanoplot1") )), tabPanel("Track 2", conditionalPanel( condition = "output.file_imported2", h4("Description of uploaded data"), textOutput("rowcount2"), textOutput("colcount2"), br(), h4("First rows of uploaded data"), tableOutput(outputId = "data2"), br(), h4("Volcano plot of uploaded data"), plotlyOutput("volcanoplot2") )), tabPanel("Track 3", conditionalPanel( condition = "output.file_imported3", h4("Description of uploaded data"), textOutput("rowcount3"), textOutput("colcount3"), br(), h4("First rows of uploaded data"), tableOutput(outputId = "data3"), br(), h4("Volcano plot of uploaded data"), plotlyOutput("volcanoplot3") )), tabPanel(withSpinner(uiOutput("pdf"))) ) ) ) )) )
------------------------------------------------------------------------------
server <- shinyServer(function(input, output, session) {
HOME ====
Download example dataset
output$downloadexampledata1 <- downloadHandler( filename = function() { paste0("exampledata1.txt") }, content = function(file) { file.copy("exampledata1.txt", file) }, contentType = NA )
output$downloadexampledata2 <- downloadHandler( filename = function() { paste0("exampledata2.txt") }, content = function(file) { file.copy("exampledata2.txt", file) }, contentType = NA )
output$downloadexampledata3 <- downloadHandler( filename = function() { paste0("exampledata3.txt") }, content = function(file) { file.copy("exampledata3.txt", file) }, contentType = NA )
ANALYSIS ====
UPLOAD YOUR DATA ====
> sidebar panel ====
Read data from multiple .csv/.txt files
track2_data1 <- eventReactive(input$file1, { rbindlist( lapply( input$file1$datapath, FUN = read.csv, header = input$header, sep = input$sep, quote = input$quote ), use.names = TRUE, fill = TRUE ) })
track3_data1 <- eventReactive(input$file2, { rbindlist( lapply( input$file2$datapath, FUN = read.csv, header = input$header, sep = input$sep, quote = input$quote ), use.names = TRUE, fill = TRUE )
})
track4_data1 <- eventReactive(input$file3, { rbindlist( lapply( input$file3$datapath, FUN = read.csv, header = input$header, sep = input$sep, quote = input$quote ), use.names = TRUE, fill = TRUE )
})
> main panel ====
>> Track 1 ====
Define conditional element to show main panel only when file(s) uploaded
output$file_imported <- reactive({ return(!is.null(input$file1)) })
outputOptions(output, "file_imported", suspendWhenHidden = FALSE)
Create data to describe the imported dataset
output$rowcount <- renderText(paste("Total number of rows in uploaded file(s):", nrow(track2_data1()))) output$colcount <- renderText(paste("Total number of columns in uploaded file(s):", ncol(track2_data1())))
Render head of imported dataset
output$data1 <- renderTable({ track2_data1() %>% head })
Render volcano plot
observeEvent(input$file1, handlerExpr = { output$volcanoplot1 <- renderPlotly({ volcanoplot <- plot_ly( data = track2_data1(), type = "scatter", colors = NULL, alpha = NULL, x = track2_data1()$beta, y = -log10(track2_data1()$Pvalue), text = track2_data1()$outcome_name, mode = "markers" ) %>% layout(xaxis = list(title = "effect_estimate"), yaxis = list(title = "-log10(p-value)")) }) })
>> Track 2 ====
Define conditional element to show main panel only when file(s) uploaded
output$file_imported2 <- reactive({ return(!is.null(input$file2)) })
outputOptions(output, "file_imported2", suspendWhenHidden = FALSE)
Create data to describe the imported dataset
output$rowcount2 <- renderText(paste("Total number of rows in uploaded file(s):", nrow(track3_data1()))) output$colcount2 <- renderText(paste("Total number of columns in uploaded file(s):", ncol(track3_data1())))
Render head of imported dataset
output$data2 <- renderTable({ track3_data1() %>% head })
Render volcano plot
observeEvent(input$file2, handlerExpr = { output$volcanoplot2 <- renderPlotly({ volcanoplot <- plot_ly( data = track3_data1(), type = "scatter", colors = NULL, alpha = NULL, x = track3_data1()$beta, y = -log10(track3_data1()$Pvalue), text = track3_data1()$outcome_name, mode = "markers" ) %>% layout(xaxis = list(title = "effect_estimate"), yaxis = list(title = "-log10(p-value)")) }) })
>> Track 3 ====
Define conditional element to show main panel only when file(s) uploaded
output$file_imported3 <- reactive({ return(!is.null(input$file3)) })
outputOptions(output, "file_imported3", suspendWhenHidden = FALSE)
Create data to describe the imported dataset
output$rowcount3 <- renderText(paste("Total number of rows in uploaded file(s):", nrow(track4_data1()))) output$colcount3 <- renderText(paste("Total number of columns in uploaded file(s):", ncol(track4_data1())))
Render head of imported dataset
output$data3 <- renderTable({ track4_data1() %>% head })
Render volcano plot
observeEvent(input$file3, handlerExpr = { output$volcanoplot3 <- renderPlotly({ volcanoplot <- plot_ly( data = track4_data1(), type = "scatter", colors = NULL, alpha = NULL, x = track4_data1()$beta, y = -log10(track4_data1()$Pvalue), text = track4_data1()$outcome_name, mode = "markers" ) %>% layout(xaxis = list(title = "effect_estimate"), yaxis = list(title = "-log10(p-value)")) }) })
CIRCOS PARAMETERS ====
> sidebar panel ====
output$pval <- renderText(paste0("New threshold: 0.05/", input$pvalue_adjustment, " = ", round(0.05/input$pvalue_adjustment, digits = 8)) ) output$pval_label <- renderText(paste0("P > 0.05/", input$pvalue_adjustment))
When the first file is uploaded, pass the column headings to the selectInput widgets
observeEvent(input$file1, { updateSelectInput(session, "label_column", choices = c("",colnames(track2_data1())))
updateSelectInput(session, "section_column", choices = c("",colnames(track2_data1()))) updateSelectInput(session, "estimate_column", choices = c("",colnames(track2_data1()))) updateSelectInput(session, "pvalue_column", choices = c("",colnames(track2_data1()))) updateSelectInput(session, "confidence_interval_lower_column", choices = c("",colnames(track2_data1()))) updateSelectInput(session, "confidence_interval_upper_column", choices = c("",colnames(track2_data1())))} )
Because the my_circos_plot() function expects a column number rather than name,
which is what the selectInput widgets return, use the following functions to convert the
column name into the column number
label_column_number <- reactive({which(colnames(track2_data1())==input$label_column)}) section_column_number <- reactive({which(colnames(track2_data1())==input$section_column)}) estimate_column_number <- reactive({which(colnames(track2_data1())==input$estimate_column)}) pvalue_column_number <- reactive({which(colnames(track2_data1())==input$pvalue_column)}) confidence_interval_lower_column_number <- reactive({which(colnames(track2_data1())==input$confidence_interval_lower_column)}) confidence_interval_upper_column_number <- reactive({which(colnames(track2_data1())==input$confidence_interval_upper_column)})
output$pdf <- renderUI({ if(file.exists(outfile)){ tags$iframe(src=outfile,style="height:600px; width:100%")} })
outfile <- tempfile("myfile", fileext = ".pdf", tmpdir ="www")
observeEvent(input$circosbutton, handlerExpr = { output$pdf <- renderUI({ pdf(outfile, width = 35, height = 35, pointsize = 30) isolate({ my_circos_plot( track_number = input$track_number, track2_data1 = track2_data1(), track3_data1 = track3_data1(), track4_data1 = track4_data1(), section_column = section_column_number(), # This returns the column number, as defined above. label_column = label_column_number(), estimate_column = estimate_column_number(), pvalue_column = pvalue_column_number(), pvalue_adjustment = (0.05/input$pvalue_adjustment), confidence_interval_lower_column = confidence_interval_lower_column_number(), confidence_interval_upper_column = confidence_interval_upper_column_number(), legend = input$legend, track2_label = input$track2_label, track3_label = input$track3_label, track4_label = input$track4_label, pvalue_label = input$pvalue_label) })
dev.off() if(file.exists(outfile)){ tags$iframe(src=str_sub(outfile,5),style="height:800px; width:100%")} }) })Return a list containing the filename
onStop(function() { unlink(outfile, recursive = TRUE) })
> main panel ====
Keep shiny app awake ====
output$keepAlive <- renderText({ req(input$count) paste("keep alive ", input$count) })
})
------------------------------------------------------------------------------
shinyApp(ui = ui, server = server)
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daattali
commented
4 years ago Version 9565546494f3395a257546312313929ec0bbf968 works for you but the CRAN version doesn't? That's extremely strange because there are no difference in the code between the two. The only difference between the two versions is in the README and metadata, but the code is identical. I would really need a reproducible example to troubleshoot this.
DomnechFinney
commented
4 years ago I also have an issue with new update, where spinner would not show using chrome but it would in IE.
I tried mattlee821 suggestion: remotes::install_github("andrewsali/shinycssloaders", ref="8779ff0f0ad32b0731c06067e35fa65d85f66a89")
and suprisingly it fixed it. Maybe its a browser compatibility issue.
daattali
commented
4 years ago Does installing the latest github version fix it, because the latest github version fixed another similar issue? If not, can you post a minimal reproducible example please?
DomnechFinney
commented
4 years ago I figured out my issue. I updated shinycssloaders from 0.2 to 0.3 but didnt restart my RStudio session. When I ran remotes::install_github("andrewsali/shinycssloaders", ref="8779ff0f0ad32b0731c06067e35fa65d85f66a89") it was downgrading to back to 0.2, and then it would work. :/ So now my 0.3 version is working perfectly. Thanks
daattali
commented
4 years ago @ismirsehregal @mattlee821 did you have any reproducible examples showing the problem?
daattali
commented
4 years ago I would really appreciate if one of you could show me some code that breaks with the new version. Otherwise I'll consider this fixed
ismirsehregal
commented
4 years ago @daattali today I took some more time to search for the issue and finally found what is causing the problem for me.
If I source the following example with the latest github version of shinycssloaders the spinner is hidden right from the beginning.
library(shiny)
library(shinycssloaders)
ui <- fluidPage(
withSpinner(uiOutput("dummyid"))
)
server = function(input, output, session){}
app <- shinyApp(ui, server)
runApp(app, host ="0.0.0.0", port = 80, launch.browser = TRUE) # causes hidden spinner
The same code works as expected in version 0.2.0.
Commenting out the last line using runApp and running app directly fixes the issue for the dev-version.
daattali
commented
4 years ago That's very strange. When I run your code, I do see the spinner. If you add an output$dummyid to the server, it still doesn't work? What browser+OS are you on?
ismirsehregal
commented
4 years ago I'll check. This is on Windows 10 7 + Chrome.
ismirsehregal
commented
4 years ago Using this:
library(shiny)
library(shinycssloaders)
ui <- fluidPage(
withSpinner(uiOutput("dummyid"))
)
server = function(input, output, session){
output$dummyid <- renderUI({
Sys.sleep(5)
"result"
})
}
app <- shinyApp(ui, server)
runApp(app, host ="0.0.0.0", port = 80, launch.browser = TRUE) # causes hidden spinnerIts the same effect:
daattali
commented
4 years ago So you're saying that for you running runApp() always breaks shinycssloaders? Can you open a separate issue for this? This issue is "withSpinner() removes reactive element of uploading data and selecting column names" and I don't think you're seeing that behaviour. Can I close this issue?
ismirsehregal
commented
4 years ago Sure, no problem.
withSpinner() removes reactive element of uploading data and selecting column names
I saw that behaviour with the latest cran version - but this is indeed fixed with the latest dev version for me, but this problem was still left.
ismirsehregal
commented
4 years ago Sorry, it's windows 7 and I just tried the same on a windows 10 system and can't reproduce the same behaviour. Seems to be related with using port 80 - here is the new issue.
mattlee821
commented
4 years ago I would really appreciate if one of you could show me some code that breaks with the new version. Otherwise I'll consider this fixed
Sorry - i've tried to find a minimal reproducible example of this but it seems to work each time. I'm okay with closing the issue as the fix here (and the fact no code has changes) is stable and as I can't reproduce it I'm going to assume theres an issue elsewhere in my apps cod:
Version
9565546494f3395a257546312313929ec0bbf968works for you but the CRAN version doesn't? That's extremely strange because there are no difference in the code between the two. The only difference between the two versions is in the README and metadata, but the code is identical. I would really need a reproducible example to troubleshoot this.
Issue related to my post on Stack Overflow recently. In short, when uploading data to my shiny app, drop down lists should be populated with the column names of the uploaded data frame. This worked on 23/01/2020. As of 24/01/2020 the column names no longer populated the drop down lists. I found that removing
withSpinner()from myui.Rfixed this issue. I know a recent update was pushed so wondering if this broke the app or if something else is going on where removingwithSpinner()is allowing reactivity to work within the Shiny app.Thanks!