我在ShinyApp中进行了特殊的观察，但不确定为什么会发生或如何解决。 首次启动应用程序时，选择输入并单击操作按钮（转到），会在表中向我显示输出值，这些输出值是错误的。当我再次单击操作按钮而不更改输入时，输出值将更改为正确的值。 该问题似乎仅在我首次启动该应用程序时发生。然后，该应用程序运行良好，并且当我单击时会显示正确的值。我正在复制下面的server.R代码。 谢谢！
server <- function(input, output,session) {
one_or_duration <- eventReactive(input$go,ignoreNULL = FALSE,{
if(input$one_or_duration == "A single measurement"){
"single"}
else if(input$one_or_duration == "Multiple measurements"){
"multiple"}})
nnrti <- eventReactive(input$go,ignoreNULL = FALSE,{
if(input$nnrti == "Yes, include participants on NNRTIs"){
"yes"}
else if(input$nnrti == "No, exclude participants on NNRTIs"){
"no"}})
arm <- eventReactive(input$go,ignoreNULL = FALSE,{
if(input$arm == "Yes, include participants in intervention arms"){
"yes"}
else if(input$arm == "No, exclude participants in intervention arms"){
"no"}})
freq <- eventReactive(input$go,ignoreNULL = FALSE,{
if(input$freq == "Same frequency as observed by authors"){
"same"}
else if(input$freq == "Input expected frequency"){
"diff"}})
pt_class <- eventReactive(input$go,ignoreNULL = FALSE,{
if(input$pt_class == "All study participants"){
"all"}
else if(input$pt_class == "Early treated participants"){
"early"}
else if(input$pt_class == "Chronic treated participants"){
"chronic"}
})
ptcs_plus_ncs <- eventReactive(input$go,ignoreNULL = FALSE,{
if (freq() == "same"){
validate(need(input$vl >= 50, "Please select viral load threshold equal to or greater than 50 copies/mL"))
system(sprintf("python3 new_duration_ctrl.py %s %s %s %s %s %s", input$vl , input$duration, pt_class(), one_or_duration(), nnrti(),arm()))
data <- read.csv("output_all.csv")
data}
else if (freq() == "diff"){
validate(need(input$vl >= 50, "Please select viral load threshold equal to or greater than 50 copies/mL"))
system(sprintf("python3 new_another_freq.py %s", input$expected_freq))
data <- read.csv("output_all.csv")
data}
})
ptc <- eventReactive(input$go,ignoreNULL = FALSE,{
system(sprintf("python3 new_duration_ctrl_ptc.py %s %s %s %s %s %s", input$vl , input$duration, pt_class(), one_or_duration(), nnrti(), arm()))
data <- read.csv("output_ptc.csv")
data
})
nc <- eventReactive(input$go,ignoreNULL = FALSE,{
system(sprintf("python3 new_duration_ctrl_nc.py %s %s %s %s %s %s", input$vl , input$duration, pt_class(), one_or_duration(), nnrti(), arm()))
data <- read.csv("output_nc.csv")
data
})
ptcs_plus_ncs_subset <- eventReactive(input$go,ignoreNULL = FALSE,
{
if(input$weekly == FALSE & freq() == "same")
{
data <- read.csv("output_all.csv")
data_ptc <- read.csv("output_ptc.csv")
data_nc <- read.csv("output_nc.csv")
mytimes <- c("1", "5", "9", "13", "25", "49")
subset1 <- data[mytimes,1:4]
subset2 <- data_ptc[mytimes,2:4]
subset3 <- data_nc[mytimes,2:4]
subset <- cbind(subset1,subset2,subset3)
colnames(subset) <- c("Weeks after treatment interruption", "Percentage with viral suppression (Total)", "Count with viral suppression (Total)", "Count under follow-up (Total)", "Percentage with viral suppression (PTCs)", "Count with viral suppression (PTCs)", "Count under follow-up (PTCs)","Percentage with viral suppression (NCs)", "Count with viral suppression (NCs)", "Count under follow-up (NCs)")
subset
}
else if(input$weekly == TRUE & freq() == "same"){
data <- read.csv("output_all.csv")
data_ptc <- read.csv("output_ptc.csv")
data_nc <- read.csv("output_nc.csv")
mytimes <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49")
subset1 <- data[mytimes,1:4]
subset2 <- data_ptc[mytimes,2:4]
subset3 <- data_nc[mytimes,2:4]
subset <- cbind(subset1,subset2,subset3)
colnames(subset) <- c("Weeks after treatment interruption", "Percentage with viral suppression (Total)", "Count with viral suppression (Total)", "Count under follow-up (Total)", "Percentage with viral suppression (PTCs)", "Count with viral suppression (PTCs)", "Count under follow-up (PTCs)","Percentage with viral suppression (NCs)", "Count with viral suppression (NCs)", "Count under follow-up (NCs)")
subset
}
else if(input$weekly == FALSE & freq() == "diff"){
data <- read.csv("output_all.csv")
data_ptc <- read.csv("output_ptc.csv")
data_nc <- read.csv("output_nc.csv")
mytimes <- c("1", "5", "9", "13", "25", "49")
subset1 <- data[mytimes,1:2]
subset2 <- data_ptc[mytimes,2:4]
subset3 <- data_nc[mytimes,2:4]
subset <- cbind(subset1,subset2,subset3)
colnames(subset) <- c("Weeks after treatment interruption", "Percentage with viral suppression (Total)", "Percentage with viral suppression (PTCs)", "Count with viral suppression (PTCs)", "Count under follow-up (PTCs)","Percentage with viral suppression (NCs)", "Count with viral suppression (NCs)", "Count under follow-up (NCs)")
subset
}
else if(input$weekly == TRUE & freq() == "diff"){
data <- read.csv("output_all.csv")
data_ptc <- read.csv("output_ptc.csv")
data_nc <- read.csv("output_nc.csv")
mytimes <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49")
subset1 <- data[mytimes,1:2]
subset2 <- data_ptc[mytimes,2:4]
subset3 <- data_nc[mytimes,2:4]
subset <- cbind(subset1,subset2,subset3)
colnames(subset) <- c("Weeks after treatment interruption", "Percentage with viral suppression (Total)", "Percentage with viral suppression (PTCs)", "Count with viral suppression (PTCs)", "Count under follow-up (PTCs)","Percentage with viral suppression (NCs)", "Count with viral suppression (NCs)", "Count under follow-up (NCs)")
subset
}
})
output$table <-
DT::renderDataTable({
if (freq()=="same"){
datatable(ptcs_plus_ncs_subset(),
container=
withTags(table(
class = 'display',
thead(
tr(
th(rowspan=2 ,'Weeks after treatment interruption'),
th(colspan = 3, 'Total'),
th(colspan = 3, 'PTCs'),
th(colspan = 3, 'NCs')
),
tr(
lapply(c('Percentage with viral suppression (Total)', 'Count with viral suppression (Total)', 'Count under follow-up (Total)','Percentage with viral suppression (PTCs)', 'Count with viral suppression (PTCs)', 'Count under follow-up (PTCs)','Percentage with viral suppression (NCs)', 'Count with viral suppression (NCs)', 'Count under follow-up (NCs)'), th)
)
)
)),
rownames=FALSE,options = list(paging=FALSE, bInfo=FALSE, lengthChange=FALSE, searching = FALSE,
columnDefs = list(list(className = 'dt-center', targets = "_all")))) %>% formatStyle(colnames(ptcs_plus_ncs_subset())[2],backgroundColor = "gray", color = "#fff", fontWeight = 'bold') %>% formatStyle(colnames(ptcs_plus_ncs_subset())[5],backgroundColor = "red", color = "#fff", fontWeight = 'bold') %>% formatStyle(colnames(ptcs_plus_ncs_subset())[8],backgroundColor = "blue", color = "#fff", fontWeight = 'bold')
}
else if (freq()=="diff")
{
datatable(ptcs_plus_ncs_subset(),
container=
withTags(table(
class = 'display',
thead(
tr(
th(rowspan=2 ,'Weeks after treatment interruption'),
th(colspan = 1, 'Total'),
th(colspan = 3, 'PTCs'),
th(colspan = 3, 'NCs')
),
tr(
lapply(c('Percentage with viral suppression (Total)','Percentage with viral suppression (PTCs)', 'Count with viral suppression (PTCs)', 'Count under follow-up (PTCs)','Percentage with viral suppression (NCs)', 'Count with viral suppression (NCs)', 'Count under follow-up (NCs)'), th)
)
)
)),
rownames=FALSE,options = list(paging=FALSE, bInfo=FALSE, lengthChange=FALSE, searching = FALSE,
columnDefs = list(list(className = 'dt-center', targets = "_all")))) %>% formatStyle(colnames(ptcs_plus_ncs_subset())[2],backgroundColor = "gray", color = "#fff", fontWeight = 'bold') %>% formatStyle(colnames(ptcs_plus_ncs_subset())[3],backgroundColor = "red", color = "#fff", fontWeight = 'bold') %>% formatStyle(colnames(ptcs_plus_ncs_subset())[6],backgroundColor = "blue", color = "#fff", fontWeight = 'bold')
}
})
}