我正在Rstudio中使用Shiny编写我的第一个代码，它需要一个文件输入（CSV文件，并在主面板中打印绘图。打印绘图后，我试图打印传递给绘图以观察其变量的变量的值我无法执行的值，它将在Rstudio控制台中打印出来；其次，我正在寻找创建这些变量的数据框，并下载包含这些值的CSV文件。希望我已经解释了该查询。我正在复制下面的代码
我能够在浏览器中打印绘图。但是变量正在控制台（rstudio）中打印出来，我需要在绘图下的浏览器窗口中使用它们，并下载包含这些变量数据框的CSV文件。如果有人可以指导我，我将不胜感激。
structure(list(Point1 = c(9999, 9999, 433.333, 9999, 1433.333,
33.333, 4283.333, 9999, 33.333, 9999, 9999, 9999, 9999, 0.033,
1323.333, 883.333, 9999, 9999, 9999, 9999, 433.333, 1433.333,
0.633, 9999, 9999, 9999, 33.333, 9999, 133.333, 433.333, 433.333,
0.003, 4023.333, 33.333, 423.333, 1323.333, 423.333, 1323.333,
4323.333, 2073.333, 1323.333, 1323.333, 1323.333, 1323.333, 1323.333,
33.333, 123.333, 3363.333, 123.333, 0.333, 423.333), Point2 = c(4433.333,
4433.333, 133.333, 4133.333, 433.333, 3.333, 1283.333, 4433.333,
3.333, 4433.333, 4433.333, 4433.333, 4433.333, 0.003, 423.333,
433.333, 4433.333, 4433.333, 4433.333, 4433.333, 133.333, 433.333,
0.333, 4358.333, 4433.333, 4433.333, 3.333, 4433.333, 33.333,
133.333, 133.333, NA, 1323.333, 3.333, 123.333, 423.333, 123.333,
423.333, 1323.333, 1323.333, 423.333, 423.333, 423.333, 423.333,
423.333, 3.333, 33.333, 1323.333, 33.333, 0.033, 123.333), OUTP1 = c(NA,
NA, 1L, NA, 1L, 1L, 1L, NA, 1L, NA, NA, NA, NA, 1L, 1L, 1L, NA,
NA, NA, NA, 1L, 1L, 1L, NA, NA, NA, 1L, NA, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), Types = c(NA, NA, 3L, NA, 3L, 3L, 3L, NA, 3L, NA, NA,
NA, NA, 3L, 3L, 3L, NA, NA, NA, NA, 3L, 3L, 3L, NA, NA, NA, 3L,
NA, 3L, 3L, 3L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L)), .Names = c("Point1", "Point2",
"OUTP1", "Types"), class = "data.frame", row.names = c(NA, -51L
))
options(scipen=999)
library(survival)
ui <- bootstrapPage(
titlePanel("Survival analysis step1"),
tags$hr(),
sidebarPanel(
fileInput("file1", "Choose CSV File",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
tags$hr(),
checkboxInput("header", "Header", TRUE),
radioButtons("sep", "Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'"),
selected = '"'),
tags$hr(),
radioButtons("disp", "Display",
choices = c(Head = "head",
All = "all"),
selected = "head")
),
mainPanel(
plotOutput('plot'),
textOutput("selected_var")
)
)
server <- function(input, output) {
output$plot <- renderPlot({
req(input$file1)
testpeanut1 <- read.csv(input$file1$datapath,
header = input$header,
sep = input$sep,
quote = input$quote)
print(dput(testpeanut1))
testpeanut1[is.na(testpeanut1)]<-"0"
testpeanut1$modified_Point1<-ifelse(as.numeric(testpeanut1$Types) ==2, as.numeric(testpeanut1$Point2), as.numeric(testpeanut1$Point1))
testpeanut1$modified_Point2<-ifelse(as.numeric(testpeanut1$Types) ==2, as.numeric(testpeanut1$Point1), as.numeric(testpeanut1$Point2))
set.seed(1234567)
testpeanut1$Survial_analysis_obj<-Surv(as.numeric(testpeanut1$modified_Point2),as.numeric(testpeanut1$modified_Point1), as.numeric(testpeanut1$Types), type="interval")
model_log_N_obj<-survreg(formula= testpeanut1$Survial_analysis_obj~1, data=testpeanut1, dist="lognormal")
new1<-data.frame(1)
predmodel_log_N_obj<-predict(model_log_N_obj, newdata=new1, type='quantile', p=seq(0.001,0.99, by=0.0001), se.fit=TRUE)
plot(predmodel_log_N_obj$fit, seq(0.001,0.99, by=0.0001),
type="l", col=2, lty=1, lwd=2, xlim=c(0.00001,100000000),
main="Plot description",
xlab="Caption",
ylab = "probability",
log="x", xaxt = "n", yaxt = "n")
lines(exp(log(predmodel_log_N_obj$fit)+1.96* (predmodel_log_N_obj$se.fit)/ predmodel_log_N_obj$fit),seq(0.001,0.99, by=0.0001), type="l", col=2, lty=2)
lines(exp(log(predmodel_log_N_obj$fit)-1.96* (predmodel_log_N_obj$se.fit)/ predmodel_log_N_obj$fit),seq(0.001,0.99, by=0.0001), type="l", col=2, lty=2)
ED01_log_N_obj<-predict(model_log_N_obj, newdata=new1, type='quantile', p=0.01, se.fit=TRUE) #0.18
print(ED01_log_N_obj)
ED01_log_N_CL_obj <- exp(log(ED01_log_N_obj$fit)-1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
print(ED01_log_N_CL_obj)
#ED01 upper confidence level - 0.75
ED01_log_N_CU_obj<- exp(log(ED01_log_N_obj$fit)+1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
print(ED01_log_N_CU_obj)
df<-data.frame(ED01_log_N_CU_obj)
df$ED01_log_N_CL_obj<-ED01_log_N_CL_obj
df$ED01_log_N_objfit<-ED01_log_N_obj$fit
dput(testpeanut1)
})
output$selected_var <- renderText("ED01_log_N_obj")
}
shinyApp(ui = ui, server = server)
单击按钮等或作为下载链接，可在浏览器和CSV文件中打印并打印变量。
答案 0 :(得分：0)
我猜您只在控制台中获得了输出，而不是Shiny，因为您使用了print而不是将它们放入renderXXX。我尝试将您更新的数据用作csv输入，以下应该可以工作。数据后有“（）”，因为它是一个响应值，您可以像函数一样调用它。另外，您可能需要编辑下载文件的扩展名。我没有时间清理代码，因此仍然有冗余。希望它会有所帮助。
library(survival)
library(shiny)
ui <- bootstrapPage(
titlePanel("Survival analysis step1"),
tags$hr(),
sidebarPanel(
fileInput("file1", "Choose CSV File",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
tags$hr(),
checkboxInput("header", "Header", TRUE),
radioButtons("sep", "Separator",
choices = c(Comma = ",",
Semicolon = ";",
Tab = "\t"),
selected = ","),
radioButtons("quote", "Quote",
choices = c(None = "",
"Double Quote" = '"',
"Single Quote" = "'"),
selected = '"'),
tags$hr(),
radioButtons("disp", "Display",
choices = c(Head = "head",
All = "all"),
selected = "head"),
downloadButton("downloadData", "Download")
),
mainPanel(
plotOutput('plot'),
tableOutput("selected_var")
)
)
server <- function(input, output) {
data <- reactive({
req(input$file1)
testpeanut1 <- read.csv(input$file1$datapath,
header = input$header,
sep = input$sep,
quote = input$quote)
testpeanut1[is.na(testpeanut1)] <- "0"
testpeanut1$modified_Point1 <- ifelse(as.numeric(testpeanut1$Types)==2, as.numeric(testpeanut1$Point2), as.numeric(testpeanut1$Point1))
testpeanut1$modified_Point2 <- ifelse(as.numeric(testpeanut1$Types)==2, as.numeric(testpeanut1$Point1), as.numeric(testpeanut1$Point2))
testpeanut1$Survial_analysis_obj <- Surv(as.numeric(testpeanut1$modified_Point2),as.numeric(testpeanut1$modified_Point1), as.numeric(testpeanut1$Types), type="interval")
model_log_N_obj<-survreg(formula= testpeanut1$Survial_analysis_obj~1, data=testpeanut1, dist="lognormal")
new1<-data.frame(1)
predmodel_log_N_obj<-predict(model_log_N_obj, newdata=new1, type='quantile', p=seq(0.001,0.99, by=0.0001), se.fit=TRUE)
ED01_log_N_obj <- predict(model_log_N_obj, newdata=new1, type='quantile', p=0.01, se.fit=TRUE) #0.18
ED01_log_N_CL_obj <- exp(log(ED01_log_N_obj$fit)-1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
#ED01 upper confidence level - 0.75
ED01_log_N_CU_obj <- exp(log(ED01_log_N_obj$fit)+1.96* (ED01_log_N_obj$se.fit)/ ED01_log_N_obj$fit)
dfOut<-data.frame(ED01_log_N_CU_obj)
dfOut$ED01_log_N_CL_obj<-ED01_log_N_CL_obj
dfOut$ED01_log_N_objfit<-ED01_log_N_obj$fit
return(list(df = testpeanut1,
predmodel = predmodel_log_N_obj,
summary = dfOut))
})
output$plot <- renderPlot({
plot(data()$predmodel$fit, seq(0.001,0.99, by=0.0001),
type="l", col=2, lty=1, lwd=2, xlim=c(0.00001,100000000),
main="Plot description",
xlab="Caption",
ylab = "probability",
log="x", xaxt = "n", yaxt = "n")
lines(exp(log(data()$predmodel$fit)+1.96* (data()$predmodel$se.fit)/ data()$predmodel$fit),seq(0.001,0.99, by=0.0001), type="l", col=2, lty=2)
lines(exp(log(data()$predmodel$fit)-1.96* (data()$predmodel$se.fit)/ data()$predmodel$fit),seq(0.001,0.99, by=0.0001), type="l", col=2, lty=2)
})
output$selected_var <- renderTable(data()$summary)
output$downloadData <- downloadHandler(
filename = "output.csv",
content = function(file) {
write.csv(data()$df, file, row.names = FALSE)
},
contentType = "text/csv"
)
}
shinyApp(ui = ui, server = server)