gistfile1.txt

library(shiny)
library(tidyverse)
library(gridExtra)

ui <- fluidPage(
  titlePanel("Frequency Decryption: A Broken Algorithm"),
  tags$br(),
  tags$br(),
  
  
  sidebarLayout(
    sidebarPanel(
      textAreaInput(inputId = "ins", 
                    label="insert cipher text here", 
                    width = "400px", 
                    height = "500px",
                    placeholder = "ciphertext")
    ),
    mainPanel(
      tags$div(tags$p((textOutput(outputId = "outs"))),
               tags$div(class="header", checked=NA,
                        tags$h3("How does this algorithm work?"),
                        tags$p("And why doesn't it work?"),
                        tags$br(),
                        tags$p("The decryption algorithm is based on the frequency 
                               with which letters appear in English speech and prose.
                               Letters like E, T, A, and O are much more common than 
                               J, X, Q, and Z, and their frequencies follow a distribution.
                               This is actually true for every language, and is one of the
                               ways in which linguists determine whether an unknown language
                               is real or a hoax. What this algorithm does is take your 
                               ciphertext and re-sort it based on letter frequency, then
                               transposes those letters based on the frequency in the 
                               English language."),
                        tags$p("So if the most common letter in your ciphertext is Q, then 
                               it will be replaced with the most common letter in English, E."),
                        tags$p("So why doesn't it work? Because the frequencies given are 
                               based on standard English speech overall-- even encrypted text
                               with tens of thousands of words still doesn't always approximate
                               the actual frequencies of letters in English speech."),
                        tags$p("If you use this tool with a big enough sample, you'll find 
                               whispers of real words start to become apparent, but even
                               common words like 'the' will still end up looking silly, like
                               'tde'.")
                        ),
               plotOutput("c3"),
               plotOutput("c1c2")
      )
    )
  )
)


server <- function(input, output){
  library(shiny)
  library(tidyverse)
  library(gridExtra)
  
  freq.sort<-function(x){
    english.by.frequency <- "etaoinshrdlcumwfgypbvkjxqz" 
    cleaned <-  gsub(pattern = "\\W|\\d", replace = "",  tolower(x))
    letter.frequencies <- substring(cleaned, 1:nchar(cleaned),1:nchar(cleaned))
    tab <- sort(table(letter.frequencies), decreasing = TRUE)
    ordered_characters <- dimnames(tab)$letter.frequencies
    ordered_in_a_string <- paste(ordered_characters, collapse = "")
    excess    <- (26 - nchar(ordered_in_a_string))
    addendum1 <- rep.int("_", excess)
    addendum2 <- paste(addendum1, collapse="")
    final     <- paste(ordered_in_a_string, addendum2, sep="")
    cipher <- chartr(final,english.by.frequency,x) 
    finaltext <- cat(cipher)
    return(finaltext)
  }
  
  
  
  output$outs <- renderPrint({
    freq.sort(input$ins)
  })
  #######################
  # code for the Eng graph
  lets<-c("e",	"t",	"a",	"o",	"i",	"n",	"s",	"h",	"r",	"d",	"l",	"c",	"u",	"m",	"w",	"f",	"g",	"y",	"p",	"b",	"v",	"k",	"j",	"x",	"q",	"z")
  percs<-c(12.702,	9.056,	8.167,	7.507,	6.966,	6.749,	6.327,	6.094,	5.987,	4.253,	4.025,	2.782,	2.758,	2.406,	2.36,	2.228,	2.015,	1.974,	1.929,	1.492,	0.978,	0.772,	0.153,	0.15,	0.095,	0.074)
  
  eng<-data.frame(lets,percs)

  output$c3 <- renderPlot({
    ggplot(eng, aes(x = reorder(lets, -percs), y = percs, fill = percs)) + 
      geom_col() + 
      scale_fill_gradient(low = "#DCCD59", high = "#2F3316")+
      labs(x = "letter",
           y = "frequency",
           title = "Frequency of Letters in Standard English",
           subtitle = "By Percent") 
  })
  ############# end #############
  ##### creates -- or tries-- the data frame of letter frequencies
  create_data_frame<-function(x){
    cleaned <-  gsub(pattern = "\\W|\\d", replace = "",  tolower(x))
    let.freqs <- substring(cleaned, 1:nchar(cleaned),1:nchar(cleaned))
    tab <- sort(table(let.freqs), decreasing = TRUE)
    dat <- as.data.frame(tab) 
    return(dat)
  }
  #####################################################################
  dat1<-reactive({create_data_frame(input$ins)})
  dat2<-reactive({create_data_frame(input$ins)})
  #dat2<-reactive({create_data_frame(output$outs)})
  

  
  output$c1c2 <- renderPlot({
    grid.arrange(
      ggplot(dat1(), aes(let.freqs, Freq, fill = Freq))+
        geom_col() + 
        scale_fill_gradient(low = "#C35521", high = "#3F1F11")+
        labs(x = "letter",
             y = "frequency",
             title = "Frequency of Letters in your Encrypted text",
             subtitle = "By Absolute Count"),
      ggplot(dat2(), aes(let.freqs, Freq, fill = Freq))+
        geom_col() + 
        scale_fill_gradient(low = "#1E120F", high = "#A04445")+
        labs(x = "letter",
             y = "frequency",
             title = "Frequency of Letters in your Encrypted text",
             subtitle = "By Absolute Count")
    )
  })
}

shinyApp(ui = ui, server = server)