如何使用R闪亮的无功输入调整ctree的输出?
我的尝试
UI:
rm(list=ls())
library(shiny)
library(party)
# Define the overall UI
shinyUI(fluidPage(
titlePanel("Unbiased Recursive Partitioning"),
sidebarLayout(
sidebarPanel(
actionButton("go", "Plot URP-Ctree")
),
mainPanel(
# Create a new row for the URP plot.
sliderInput("sliderWidth", label = "", min = 10, max = 3000, value = 1000),
sliderInput("sliderHeight", label = "", min = 10, max = 3000, value = 1000),
plotOutput("plot")
))
)
)
服务器:
# server.R
rm(list=ls())
CCS<-c(41, 45, 50, 50, 38, 42, 50, 43, 37, 22, 42, 48, 47, 48, 50, 47, 41, 50, 45, 45, 39, 45, 46, 48, 50, 47, 50, 21, 48, 50, 48, 48, 48, 46, 36, 38, 50, 39, 44, 44, 50, 49, 40, 48, 48, 45, 39, 40, 44, 39, 40, 44, 42, 39, 49, 50, 50, 48, 48, 47, 48, 47, 44, 41, 50, 47, 50, 41, 50, 44, 47, 50, 24, 40, 43, 37, 44, 32, 43, 42, 44, 38, 42, 45, 50, 47, 46, 43,
37, 47, 37, 45, 41, 50, 42, 32, 43, 48, 45, 45, 28, 44,38, 41, 45, 48, 48, 47 ,49, 16, 45, 50, 47, 50, 43, 49, 50)
X1.2Weeks<-c(NA,NA,NA,NA,NA,1,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,2,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,NA,NA,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,2,2,1,2,2,2)
X2.2Weeks<-c(NA,NA,NA,NA,NA,NA,2,2,2,NA,NA,2,2,2,2,2,2,NA,2,2,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,NA,NA,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2)
X3.2Weeks<-c(NA,35,40,NA,10,NA,31,NA,14,NA,NA,15,17,NA,NA,16,10,15,14,39,17,35,14,14,22,10,15,0,34,23,13,35,32,2,14,10,14,10,10,10,40,10,13,13,10,10,10,13,13,25,10,35,NA,13,NA,10,40,0,0,20,40,10,14,40,10,10,10,10,13,10,8,NA,NA,14,NA,10,28,10,10,15,15,16,10,10,35,16,NA,NA,NA,NA,30,19,14,30,10,10,8,10,21,10,10,35,15,34,10,39,NA,10,10,6,16,10,10,10,10,34,10)
X4.2Weeks<-c(NA,NA,511,NA,NA,NA,NA,NA,849,NA,NA,NA,NA,1324,1181,832,1005,166,204,1253,529,317,294,NA,514,801,534,1319,272,315,572,96,666,236,842,980,290,843,904,528,27,366,540,560,659,107,63,20,1184,1052,214,46,139,310,872,891,651,687,434,1115,1289,455,764,938,1188,105,757,719,1236,982,710,NA,NA,632,NA,546,747,941,1257,99,133,61,249,NA,NA,1080,NA,645,19,107,486,1198,276,777,738,1073,539,1096,686,505,104,5,55,553,1023,1333,NA,NA,969,691,1227,1059,358,991,1019,NA,1216)
x4.3Weeks<-c(NA,NA,511,NA,NA,NA,NA,NA,0,NA,NA,72,NA,1324,1181,832,1005,166,204,1253,529,317,294,NA,514,801,534,1319,272,315,572,96,666,236,842,980,290,843,904,528,27,366,540,560,659,107,63,20,1184,1052,214,46,139,310,872,891,651,687,434,1115,1289,455,764,938,1188,105,757,719,1236,982,710,NA,NA,632,NA,546,747,941,1257,99,133,61,249,NA,NA,1080,NA,645,19,107,486,1198,276,777,738,1073,539,1096,686,505,104,5,55,553,1023,1333,NA,NA,969,691,1227,1059,358,991,1019,NA,1216)
dat<-as.data.frame(cbind(CCS,X1.2Weeks,X2.2Weeks,X3.2Weeks,X4.2Weeks,x4.3Weeks))
library(shiny)
library(party)
shinyServer(function(input, output, clientData, session) {
sliderWidth<-reactive({
as.integer(input$sliderWidth)
})
sliderHeight<-reactive({
as.integer(input$sliderHeight)
})
# Construct URP-Ctree
output$plot <- renderPlot({
if(input$go==0){
return()
}
else {
isolate({
an<-"CCS"
# Only columns with "2Weeks" as part of their title are selected as predictors
control_preds<-"2Weeks"
preds<-names(dat)[grepl(paste(control_preds),names(dat))]
datSubset<-subset(dat,dat[,an]!="NA")
anchor <- datSubset[,an]
predictors <- datSubset[,preds]
urp<-ctree(anchor~., data=data.frame(anchor,predictors))
plot(urp)
})
}
},height = 500, width = 500)
# },height = sliderHeight(), width = sliderWidth())<-- Causes error
})
运行上面的代码,单击按钮后应该得到一个ctree。然而,滑块不做任何事情。如果将renderPlot的高度和宽度参数更改为500以外的值,则绘图的大小会发生变化。如何将高度和宽度置于滑块的控制之下?
当我尝试在最后一行使用height = sliderHeight(), width = sliderWidth()
运行服务器时,我得到:
Error in .getReactiveEnvironment()$currentContext() :
Operation not allowed without an active reactive context. (You tried to do something that can only be done from inside a reactive expression or observer.)
我因为使用了反应性表达而感到困惑。
答案 0 :(得分:0)
两个月后,我付给我最好的朋友500美元来解决这个问题。下面的代码我不知道为什么反应式表达式中的反应式表达式解决了这个问题。 ui保持不变。
# server.R
rm(list=ls())
CCS<-c(41, 45, 50, 50, 38, 42, 50, 43, 37, 22, 42, 48, 47, 48, 50, 47, 41, 50, 45, 45, 39, 45, 46, 48, 50, 47, 50, 21, 48, 50, 48, 48, 48, 46, 36, 38, 50, 39, 44, 44, 50, 49, 40, 48, 48, 45, 39, 40, 44, 39, 40, 44, 42, 39, 49, 50, 50, 48, 48, 47, 48, 47, 44, 41, 50, 47, 50, 41, 50, 44, 47, 50, 24, 40, 43, 37, 44, 32, 43, 42, 44, 38, 42, 45, 50, 47, 46, 43,
37, 47, 37, 45, 41, 50, 42, 32, 43, 48, 45, 45, 28, 44,38, 41, 45, 48, 48, 47 ,49, 16, 45, 50, 47, 50, 43, 49, 50)
X1.2Weeks<-c(NA,NA,NA,NA,NA,1,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,2,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,NA,NA,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,1,2,2,2,2,2,1,1,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,2,2,1,2,2,2)
X2.2Weeks<-c(NA,NA,NA,NA,NA,NA,2,2,2,NA,NA,2,2,2,2,2,2,NA,2,2,2,2,2,NA,2,2,2,2,2,2,2,NA,NA,NA,NA,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,NA,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,2,2,2,2,2,2,1,2,2,2,2,2,2,2)
X3.2Weeks<-c(NA,35,40,NA,10,NA,31,NA,14,NA,NA,15,17,NA,NA,16,10,15,14,39,17,35,14,14,22,10,15,0,34,23,13,35,32,2,14,10,14,10,10,10,40,10,13,13,10,10,10,13,13,25,10,35,NA,13,NA,10,40,0,0,20,40,10,14,40,10,10,10,10,13,10,8,NA,NA,14,NA,10,28,10,10,15,15,16,10,10,35,16,NA,NA,NA,NA,30,19,14,30,10,10,8,10,21,10,10,35,15,34,10,39,NA,10,10,6,16,10,10,10,10,34,10)
X4.2Weeks<-c(NA,NA,511,NA,NA,NA,NA,NA,849,NA,NA,NA,NA,1324,1181,832,1005,166,204,1253,529,317,294,NA,514,801,534,1319,272,315,572,96,666,236,842,980,290,843,904,528,27,366,540,560,659,107,63,20,1184,1052,214,46,139,310,872,891,651,687,434,1115,1289,455,764,938,1188,105,757,719,1236,982,710,NA,NA,632,NA,546,747,941,1257,99,133,61,249,NA,NA,1080,NA,645,19,107,486,1198,276,777,738,1073,539,1096,686,505,104,5,55,553,1023,1333,NA,NA,969,691,1227,1059,358,991,1019,NA,1216)
x4.3Weeks<-c(NA,NA,511,NA,NA,NA,NA,NA,0,NA,NA,72,NA,1324,1181,832,1005,166,204,1253,529,317,294,NA,514,801,534,1319,272,315,572,96,666,236,842,980,290,843,904,528,27,366,540,560,659,107,63,20,1184,1052,214,46,139,310,872,891,651,687,434,1115,1289,455,764,938,1188,105,757,719,1236,982,710,NA,NA,632,NA,546,747,941,1257,99,133,61,249,NA,NA,1080,NA,645,19,107,486,1198,276,777,738,1073,539,1096,686,505,104,5,55,553,1023,1333,NA,NA,969,691,1227,1059,358,991,1019,NA,1216)
dat<-as.data.frame(cbind(CCS,X1.2Weeks,X2.2Weeks,X3.2Weeks,X4.2Weeks,x4.3Weeks))
library(shiny)
library(party)
shinyServer(function(input, output, clientData, session) {
sliderWidth<-reactive({
as.integer(input$sliderWidth)
})
sliderHeight<-reactive({
as.integer(input$sliderHeight)
})
# Construct URP-Ctree
output$plot <- renderPlot({
if(input$go==0){
return()
}
else {
isolate({
an<-"CCS"
# Only columns with "2Weeks" as part of their title are selected as predictors
control_preds<-"2Weeks"
preds<-names(dat)[grepl(paste(control_preds),names(dat))]
datSubset<-subset(dat,dat[,an]!="NA")
anchor <- datSubset[,an]
predictors <- datSubset[,preds]
urp<-ctree(anchor~., data=data.frame(anchor,predictors))
plot(urp)
})
}
}, height = reactive({sliderHeight()}), width = reactive({sliderWidth()}))
})
你可以在宽度和高度参数中看到,所有需要的是我对自身的反应调用是在反应式表达式中。