inst/twonorm/server.R

In dswalter/stats250: An Interactive Environment for Learning Statistics

# This is the server logic for a Shiny web application.
# You can find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com
#

library(shiny)
library(ggplot2)

shinyServer(function(input, output) {

  #output$distPlot <- renderPlot({

    # generate bins based on input$bins from ui.R
   # x    <- faithful[, 2]
    #bins <- seq(min(x), max(x), length.out = input$bins + 1)

    # draw the histogram with the specified number of bins
  #  hist(x, breaks = bins, col = 'darkgray', border = 'white')

  #})

  rng<-seq(-250,250,0.1)
  rngdf<-data.frame(rng)
  normalplot<-ggplot(data=rngdf,aes(x=rng))+xlim(-75,75)+ylim(0,0.10)+
    ylab("Density")+xlab("Range of X values")+ggtitle("Normal Density")
  
  
  output$twonormPlot<-renderPlot({
    
    #make a normal distribution based on inputs.
    oneyvals<-dnorm(x=rng,mean=input$onemean,sd=input$onesdev)
    onenewdf<-data.frame(rng,oneyvals)
    twoyvals<-dnorm(x=rng,mean=input$twomean,sd=input$twosdev)
    twonewdf<-data.frame(rng,twoyvals)
    normalplot+geom_ribbon(data=onenewdf,aes(ymin=0,ymax=oneyvals),fill="red",alpha=0.6)+
      geom_ribbon(data=twonewdf,aes(ymin=0,ymax=twoyvals),fill="blue",alpha=0.6)
  })
  
  output$meanPlot<-renderPlot({
    
    #make a normal distribution based on inputs.
    yvals<-dnorm(x=rng,mean=input$meanonly,sd=10)
    newdf<-data.frame(rng,yvals)
    normalplot+geom_ribbon(data=newdf,aes(ymin=0,ymax=yvals),color="#5C246E",fill="#5c246e")
  })

  output$sdPlot<-renderPlot({
    
    #make a normal distribution based on inputs.
    yvals<-dnorm(x=rng,mean=0,sd=input$sdonly)
    newdf<-data.frame(rng,yvals)
    normalplot+geom_ribbon(data=newdf,aes(ymin=0,ymax=yvals),color="#5C246E",fill="#5c246e")
  })
  
  })