我正在开发一个闪亮的应用程序，并且observeEvent()在创建全部源自的多个输入的复杂表达式时遇到功能上的困难selectInput()。
我的问题是一些内的表达式的observeEvent()功能在启动时触发，导致事件过早执行（即我actionButton()在启动时禁用，因为它应该是，但是当选择的至少一个输入变为启用时，理想我想希望仅在选择所有输入后才启用它）。如下所示：
observeEvent({
#input$cohort_file
input$cohort_IDvar
input$cohort_index_date
input$cohort_EOF_date
input$cohort_EOF_type
input$cohort_Y_name
input$cohort_L0
}, {
enable("set_cohort_button")
})
作为参考，我使用shinyjsgithub上@daattali提供的包来启用/禁用actionButton()。
除最后一个输入（即input$cohort_L0）外的所有内容似乎都在启动时进行了初始化，因此仅在选中时observeEvent()启用。如果您运行我的应用程序并从上到下按顺序选择输入，那么它似乎可以正常工作。当我决定随机选择输入时，我才发现它并没有达到预期的工作，并且发现选择是我需要选择启用的唯一输入。actionButtoninput$cohort_L0observeEvent()input$cohort_L0actionButton()
代码的UI部分如下所示：
# Variable selection
selectInput('cohort_IDvar', 'ID', choices = ''),
selectInput('cohort_index_date', 'Index date', choices = ''),
selectInput('cohort_EOF_date', 'End of follow-up date', choices = ''),
selectInput('cohort_EOF_type', 'End of follow-up reason', choices = ''),
selectInput('cohort_Y_name', 'Outcome', choices = ''),
selectInput('cohort_L0', 'Baseline covariate measurements', choices = '', multiple=TRUE, selectize=TRUE),
我正在observe()收集一个上传数据集的列名，将其定向selectInput()为如下所示：
### Collecting column names of dataset and making them selectable input
observe({
value <- c("",names(cohort_data()))
updateSelectInput(session,"cohort_IDvar",choices = value)
updateSelectInput(session,"cohort_index_date",choices = value)
updateSelectInput(session,"cohort_EOF_date",choices = value)
updateSelectInput(session,"cohort_EOF_type",choices = value)
updateSelectInput(session,"cohort_L0",choices = value)
})
我已经研究过使用参数，ignoreInit = TRUE但对于在其中包含多个表达式的情况，它没有任何作用observeEvent()。我也考虑过强制不进行默认选择，selectInput()但是没有运气。
因此，我的两部分问题是observEvent()当仅选择所有输入时如何执行/如何阻止启动时初始化输入？
我的整个代码：
library(shiny)
library(shinyjs)
ui <- fluidPage(
useShinyjs(),
navbarPage("Test",
tabPanel("Cohort",
sidebarLayout(
sidebarPanel(
fileInput("cohort_file", "Choose CSV File",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
# Horizontal line ----
tags$hr(),
# Variable selection
selectInput('cohort_IDvar', 'ID', choices = ''),
selectInput('cohort_index_date', 'Index date', choices = ''),
selectInput('cohort_EOF_date', 'End of follow-up date', choices = ''),
selectInput('cohort_EOF_type', 'End of follow-up reason', choices = ''),
selectInput('cohort_Y_name', 'Outcome', choices = ''),
selectInput('cohort_L0', 'Baseline covariate measurements', choices = '', multiple=TRUE, selectize=TRUE),
# Horizontal line ----
tags$hr(),
disabled(
actionButton("set_cohort_button","Set cohort")
)
#actionButton("refresh_cohort_button","Refresh")
),
mainPanel(
DT::dataTableOutput("cohort_table"),
tags$div(id = 'cohort_r_template')
)
)
)
)
)
server <- function(input, output, session) {
################################################
################# Cohort code
################################################
cohort_data <- reactive({
inFile_cohort <- input$cohort_file
if (is.null(inFile_cohort))
return(NULL)
df <- read.csv(inFile_cohort$datapath,
sep = ',')
return(df)
})
rv <- reactiveValues(cohort.data = NULL)
rv <- reactiveValues(cohort.id = NULL)
rv <- reactiveValues(cohort.index.date = NULL)
rv <- reactiveValues(cohort.eof.date = NULL)
rv <- reactiveValues(cohort.eof.type = NULL)
### Creating a reactiveValue of the loaded dataset
observeEvent(input$cohort_file, rv$cohort.data <- cohort_data())
### Displaying loaded dataset in UI
output$cohort_table <- DT::renderDataTable({
df <- cohort_data()
DT::datatable(df,options=list(scrollX=TRUE, scrollCollapse=TRUE))
})
### Collecting column names of dataset and making them selectable input
observe({
value <- c("",names(cohort_data()))
updateSelectInput(session,"cohort_IDvar",choices = value)
updateSelectInput(session,"cohort_index_date",choices = value)
updateSelectInput(session,"cohort_EOF_date",choices = value)
updateSelectInput(session,"cohort_EOF_type",choices = value)
updateSelectInput(session,"cohort_L0",choices = value)
})
### Creating selectable input for Outcome based on End of Follow-Up unique values
observeEvent(input$cohort_EOF_type,{
updateSelectInput(session,"cohort_Y_name",choices = unique(cohort_data()[,input$cohort_EOF_type]))
})
### Series of observeEvents for creating vector reactiveValues of selected column
observeEvent(input$cohort_IDvar, {
rv$cohort.id <- cohort_data()[,input$cohort_IDvar]
})
observeEvent(input$cohort_index_date, {
rv$cohort.index.date <- cohort_data()[,input$cohort_index_date]
})
observeEvent(input$cohort_EOF_date, {
rv$cohort.eof.date <- cohort_data()[,input$cohort_EOF_date]
})
observeEvent(input$cohort_EOF_type, {
rv$cohort.eof.type <- cohort_data()[,input$cohort_EOF_type]
})
### ATTENTION: Following eventReactive not needed for example so commenting out
### Setting id and eof.type as characters and index.date and eof.date as Dates
#cohort_data_final <- eventReactive(input$set_cohort_button,{
# rv$cohort.data[,input$cohort_IDvar] <- as.character(rv$cohort.id)
# rv$cohort.data[,input$cohort_index_date] <- as.Date(rv$cohort.index.date)
# rv$cohort.data[,input$cohort_EOF_date] <- as.Date(rv$cohort.eof.date)
# rv$cohort.data[,input$cohort_EOF_type] <- as.character(rv$cohort.eof.type)
# return(rv$cohort.data)
#})
### Applying desired R function
#set_cohort <- eventReactive(input$set_cohort_button,{
#function::setCohort(data.table::as.data.table(cohort_data_final()), input$cohort_IDvar, input$cohort_index_date, input$cohort_EOF_date, input$cohort_EOF_type, input$cohort_Y_name, input$cohort_L0)
#})
### R code template of function
cohort_code <- eventReactive(input$set_cohort_button,{
paste0("cohort <- setCohort(data = as.data.table(",input$cohort_file$name,"), IDvar = ",input$cohort_IDvar,", index_date = ",input$cohort_index_date,", EOF_date = ",input$cohort_EOF_date,", EOF_type = ",input$cohort_EOF_type,", Y_name = ",input$cohort_Y_name,", L0 = c(",paste0(input$cohort_L0,collapse=","),"))")
})
### R code template output fo UI
output$cohort_code <- renderText({
paste0("cohort <- setCohort(data = as.data.table(",input$cohort_file$name,"), IDvar = ",input$cohort_IDvar,", index_date = ",input$cohort_index_date,", EOF_date = ",input$cohort_EOF_date,", EOF_type = ",input$cohort_EOF_type,", Y_name = ",input$cohort_Y_name,", L0 = c(",paste0(input$cohort_L0,collapse=","),"))")
})
### Disables cohort button when "Set cohort" button is clicked
observeEvent(input$set_cohort_button, {
disable("set_cohort_button")
})
### Disables cohort button if different dataset is loaded
observeEvent(input$cohort_file, {
disable("set_cohort_button")
})
### This is where I run into trouble
observeEvent({
#input$cohort_file
input$cohort_IDvar
input$cohort_index_date
input$cohort_EOF_date
input$cohort_EOF_type
input$cohort_Y_name
input$cohort_L0
}, {
enable("set_cohort_button")
})
### Inserts heading and R template code in UI when "Set cohort" button is clicked
observeEvent(input$set_cohort_button, {
insertUI(
selector = '#cohort_r_template',
ui = tags$div(id = "cohort_insertUI",
h3("R Template Code"),
verbatimTextOutput("cohort_code"))
)
})
### Removes heading and R template code in UI when new file is uploaded or when input is changed
observeEvent({
input$cohort_file
input$cohort_IDvar
input$cohort_index_date
input$cohort_EOF_date
input$cohort_EOF_type
input$cohort_Y_name
input$cohort_L0
}, {
removeUI(
selector = '#cohort_insertUI'
)
})
}
# Run the application
shinyApp(ui = ui, server = server)
您作为触发事件传递给observeEvent的代码块是
{
input$cohort_IDvar
input$cohort_index_date
input$cohort_EOF_date
input$cohort_EOF_type
input$cohort_Y_name
input$cohort_L0
}
这意味着，就像任何其他反应式代码块一样，当这些值中的任何一个发生更改时，该反应式块都被视为无效，因此观察者将触发。因此，您所看到的行为是有道理的。
听起来您想要的是仅在设置所有值时才执行。听起来好像很好地使用了该req()功能！尝试这样的事情：
observe({
req(input$cohort_IDvar, input$cohort_index_date, input$cohort_EOF_date, ...)
enable("set_cohort_button")
})
请注意，shinyjs::enable()具体而言，您可以改用shinyjs::toggleState()函数。我认为在这种情况下，该req()功能是更好的选择。
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