我正在尝试构建一个工具，用户可以在其中选择多个参数（例如合作伙伴，预算，月份，年份），并获取下个月指标的预定值。
我已经建立了一些外部功能来执行任务。每个函数执行一些任务，并将数据传递到下一个函数，最后一个函数构建四个模型，使用这些模型进行预测，构建ggplots并将它们存储在一个列表中，这些函数一旦运行就可以访问。
如何提取要通过Shiny App显示的图表和预测？
用户界面：
ui <- fluidPage(
titlePanel("Forecasting Tool"),
sidebarLayout(
sidebarPanel(
selectInput("Partner", h3("Partner"),
choices = list("all", "dsp","search","social"), selected = "all"),
numericInput("Budget",
h3("Budget"),
value = 10000),
selectInput("Month", h3("Month"),
choices = list("January", "February", "March", "April","May",
"June", "July", "August", "September", "October",
"November", "December"),
selected = "January"),
selectInput("Year", h3("Year"),
choices = list(2018,2019),
selected = 2019),
submitButton("Submit"), h3("")),
mainPanel(plotOutput("plot"))
)
)
如何构建服务器功能，使其能够识别出submit按钮已被触发并运行外部功能？
我的最终函数称为reg_mod，它会触发所有其他函数，然后返回列表中的最终对象（图表，预测等），其输入如下：
reg_mod(partner, budget, month, year)
我可以根据用户输入访问对象并将其输出到服务器功能中吗？例如：
plot = reg_mod(input$Partner, input$Budget, input$Month, input$year)
output$plot = renderPlot(plot[[1]])
其中plot[[1]]调用第一个对象，它是来自reg_mod的情节
编辑：
因此，这是一个辅助函数的示例，该函数创建一些数据并输出一个绘图，我想要将该绘图导出到一个闪亮的App中，与我想要执行的操作类似。 （请注意，唯一的月份选择选项是“八月”，而2017年很好，可以只运行应用程序并运行默认值。）
Helper = function(partner, budget, month, year){
nums = seq(0 , 10, length.out = 100)
Registrations = 5 + 2*rnorm(100, 20, 7)*nums
dates = seq.Date(as.Date("2017-01-01"), as.Date("2017-04-10"), by ="days")
Registrations = data.frame(Date = dates, Registrations = Registrations)
if(partner == "dsp" & month == "August" & year == 2017){
Registrations$Registrations = 0.5*budget*Registrations$Registrations
}
if(partner == "search" & month == "August" & year == 2017){
Registrations$Registrations = 2*budget*Registrations$Registrations
}
if(partner == "social" & month == "August" & year == 2017){
Registrations$Registrations = budget*Registrations$Registrations
}
Plot = ggplot(data = Registrations, aes(x = Date)) +
geom_line(aes(y = Registrations, colour = "Actual"), size = 1)
List_Read = list("Plot" = Plot)
return(List_Read)
}
这是我的UI和服务器功能：
library(shiny)
library(ggplot2)
# Define UI for application that outputs ggplot
ui <- fluidPage(
titlePanel("Forecasting Tool"),
sidebarLayout(
sidebarPanel(
selectInput("Partner", h3("Partner"),
choices = list("all", "dsp","search","social"), selected="dsp"),
numericInput("Budget",
h3("Budget"),
value = 100),
selectInput("Month", h3("Month"),
choices = list("January", "February", "March", "April","May",
"June", "July", "August", "September", "October", "November",
"December"),
selected = "August"),
selectInput("Year", h3("Year"),
choices = list(2017,2018),
selected = 2017),
submitButton("Submit"), h3("")),
mainPanel(plotOutput("plot"))
)
)
# Define server logic required to output ggplot from helper function
server <- function(input, output, session) {
source("C:/Users/ksiopes/Documents/Ad Hoc/Survival/Prefinal Insights
Function Files/For Shiny Function/Testing/Helper3.R",
local = FALSE)
plot_List = eventReactive(input$Submit,{
Helper(input$Partner, input$Budget, input$Month, input$Year)
})
#Output the plot
output$plot<- renderPlot({
plot = plot_List()
plot[[1]]
})
}
# Run the application
shinyApp(ui = ui, server = server)
编辑2：
library(shiny)
library(ggplot2)
source("C:/Users/ksiopes/Documents/Ad Hoc/Survival/Prefinal Insights
Function Files/For Shiny Function/Testing/Helper3.R", local = TRUE)
# Define UI for application that uses function to create random data and
output ggplot
ui <- fluidPage(
titlePanel("Forecasting Tool"),
sidebarLayout(
sidebarPanel(
selectInput("Partner", h3("Partner"),
choices = list("all", "dsp","search","social"), selected =
"dsp"),
numericInput("Budget",
h3("Budget"),
value = 100),
selectInput("Month", h3("Month"),
choices = list("January", "February", "March",
"April","May", "June", "July", "August", "September",
"October", "November", "December"),
selected = "August"),
selectInput("Year", h3("Year"),
choices = list(2017,2018),
selected = 2017),
submitButton("Submit"), h3("")),
mainPanel(plotOutput("plot"))
)
)
# Define server logic required to run sourced function and output ggplot
server <- function(input, output, session) {
plot_List = eventReactive(input$Submit,{
Helper(input$Partner, input$Budget, input$Month, input$Year)
})
#Output the plot
output$plot<- renderPlot({
plot = plot_List()
plot[[1]]
})
}
# Run the application
shinyApp(ui = ui, server = server)
答案 0 :(得分：2)
这是有关如何执行此操作的通用框架：
将外部函数加载到闪亮的应用程序中需要一些额外的工作，而不是本地脚本，但并不需要太多。我们仍然可以使用源函数，唯一的区别是必须设置local=T，并且该函数必须放置在app目录中。该函数的来源之一，我们可以相对容易地将用户输入传递给它。
步骤1） 将具有功能的脚本保存在应用程序目录中（server.R和ui.R或app.R所在的位置）
步骤2） 源函数
#Basically source the path to the function file you put in the app directory
source("your-app-dir/functions.R")
步骤3） 使用该功能，输出绘图
server.R
server<-function(input,output,session){
#Function reg_mod in this file
source("your-app-dir/functions.R")
#Assuming the return of reg_mod is correct
plot_List<-eventReactive(input$Submit, {
reg_mod(input$Partner, input$Budget, input$Month, input$year)
})
#Output the plot
output$plot<- renderPlot({
plot<-plot_List()
plot[[1]]
})
}
可以在here
中找到有关在Shiny中使用外部功能的其他帮助。在此示例中here有关使用反应性环境的其他帮助
编辑：
解决该图形无法渲染的问题是，由于使用了错误的ui元素，因此您没有激活要运行的函数。应该是actionButton而不是submitButton
actionButton("Submit", "Submit"),改用它
完整代码
library(shiny)
library(ggplot2)
source("Helper3.R", local = TRUE)
# Define UI for application that uses function to create random data and
ui <- fluidPage(
titlePanel("Forecasting Tool"),
sidebarLayout(
sidebarPanel(
selectInput("Partner", h3("Partner"),
choices = list("all", "dsp","search","social"), selected =
"dsp"),
numericInput("Budget",
h3("Budget"),
value = 100),
selectInput("Month", h3("Month"),
choices = list("January", "February", "March",
"April","May", "June", "July", "August", "September",
"October", "November", "December"),
selected = "August"),
selectInput("Year", h3("Year"),
choices = list(2017,2018),
selected = 2017),
actionButton("Submit", "Submit"),
h3("")),
mainPanel(plotOutput("plot"))
)
)
# Define server logic required to run sourced function and output ggplot
server <- function(input, output, session) {
plot_List<-eventReactive(input$Submit, {
print("ran")
Helper(input$Partner, input$Budget, input$Month, input$Year)
})
#Output the plot
output$plot<- renderPlot({
plot = plot_List()
plot[[1]]
})
}
# Run the application
shinyApp(ui = ui, server = server)