如何根据闪亮的用户输入从同一分布生成两个图？
How to produce two plots from the same distribution based on user input in shiny?
我正在尝试根据用户提供的数据生成的同一分布生成两个图 - 可能会发生变化。我希望这两个图使用相同的分布，但我不知道如何使第一个分布对第二个 renderPlot 函数可见。显然，我不能只是重用代码并创建另一个分布，因为它不会是相同的数据。
ui.R
library(shiny)
shinyUI(fluidPage(
headerPanel(title = "Test"),
sidebarLayout(
sidebarPanel(
sliderInput("input.a", "A", min = 0, max = 100, value = 50),
sliderInput("input.b", "B", min = 0, max = 100, value = 50),
sliderInput("input.c", "C", min = 0, max = 100, value = 50)
),
mainPanel(
tabsetPanel( type = "tabs", #Open panel
tabPanel("Distributions 1",plotOutput("hist1.plot"))
),
tabsetPanel( type = "tabs", #Open panel
tabPanel("Distributions 2",plotOutput("hist2.plot"))
)
) # close mainPanel
) # close sidebarLayout
) # close fluidPage
) # close shinyUI
server.R
library(dplyr)
library(tidyr)
library(plyr)
library(ggplot2)
shinyServer(function(input,output){ # open shiny server
output$hist1.plot = renderPlot({
# open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(a,b,c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
output$hist2.plot = renderPlot({ # open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(a,b,c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
}) # close shinyServer
使用 reactiveValues() 从输入创建分布，然后在观察者内部创建分布。这样，两个图都可以使用相同的分布。
server.R
library(dplyr)
library(tidyr)
library(plyr)
library(ggplot2)
shinyServer(function(input,output){ # open shiny server
vals <- reactiveValues()
observe({vals$a = runif(1000,1,(input$input.a))
vals$b = runif(1000,1,(input$input.b))
vals$c = runif(1000,1,(input$input.c))
})
output$hist1.plot = renderPlot({
# open renderPlot
amount = c(vals$a, vals$b, vals$c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
output$hist2.plot = renderPlot({ # open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(vals$a, vals$b, vals$c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
}) # close shinyServer
我正在尝试根据用户提供的数据生成的同一分布生成两个图 - 可能会发生变化。我希望这两个图使用相同的分布，但我不知道如何使第一个分布对第二个 renderPlot 函数可见。显然，我不能只是重用代码并创建另一个分布，因为它不会是相同的数据。
ui.R
library(shiny)
shinyUI(fluidPage(
headerPanel(title = "Test"),
sidebarLayout(
sidebarPanel(
sliderInput("input.a", "A", min = 0, max = 100, value = 50),
sliderInput("input.b", "B", min = 0, max = 100, value = 50),
sliderInput("input.c", "C", min = 0, max = 100, value = 50)
),
mainPanel(
tabsetPanel( type = "tabs", #Open panel
tabPanel("Distributions 1",plotOutput("hist1.plot"))
),
tabsetPanel( type = "tabs", #Open panel
tabPanel("Distributions 2",plotOutput("hist2.plot"))
)
) # close mainPanel
) # close sidebarLayout
) # close fluidPage
) # close shinyUI
server.R
library(dplyr)
library(tidyr)
library(plyr)
library(ggplot2)
shinyServer(function(input,output){ # open shiny server
output$hist1.plot = renderPlot({
# open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(a,b,c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
output$hist2.plot = renderPlot({ # open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(a,b,c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
}) # close shinyServer
使用 reactiveValues() 从输入创建分布，然后在观察者内部创建分布。这样，两个图都可以使用相同的分布。
server.R
library(dplyr)
library(tidyr)
library(plyr)
library(ggplot2)
shinyServer(function(input,output){ # open shiny server
vals <- reactiveValues()
observe({vals$a = runif(1000,1,(input$input.a))
vals$b = runif(1000,1,(input$input.b))
vals$c = runif(1000,1,(input$input.c))
})
output$hist1.plot = renderPlot({
# open renderPlot
amount = c(vals$a, vals$b, vals$c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
output$hist2.plot = renderPlot({ # open renderPlot
a = runif(1000,1,(input$input.a))
b = runif(1000,1,(input$input.b))
c = runif(1000,1,(input$input.c))
amount = c(vals$a, vals$b, vals$c)
cat = c(rep("a",1000), rep("b",1000), rep("c",1000))
hist.data = data.frame(amount,cat)
names(hist.data) = c("amount","cat")
hist.data$cat = factor(hist.data$cat, levels = c("a","b","c"))
pricedata = ddply(hist.data, c("cat"), summarize, avg = mean(amount), minus.stdev = mean(amount)-sd(amount),
plus.stdev = mean(amount) + sd(amount))
pricedata = pricedata[order(pricedata$avg),]
ggplot(hist.data, aes(x=amount, fill = cat))+
geom_histogram(color="white", alpha = .8, position = 'identity', binwidth = 5)+
theme_test()+
geom_vline(aes(xintercept = avg), data = pricedata, color = "black", size = 1)+
geom_vline(aes(xintercept = minus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
geom_vline(aes(xintercept = plus.stdev), data = pricedata, color = "black", size = .75, linetype = "dotted")+
facet_grid(cat ~., scales = "free")+
scale_y_continuous(expand = c(0,0),name = "Count")+
scale_x_continuous(labels = scales::dollar, name="\nAmount", limits = c(0,100))
}) #close renderPlot
}) # close shinyServer