ShinyApp/app.R

In martin-vasilev/readingET: Automatic pre-processing of eye-movement reading data

library(shiny)
library(shinyalert)

# Define UI for dataset viewer app ----
ui <- fluidPage(
  
  # App title ----
  titlePanel("Pre-processing of single line reading data"),
  h4('Currently works only with data recorded with Eyetrack'),
  
  # Sidebar layout with a input and output definitions ----
  sidebarLayout(
    
    # Sidebar panel for inputs ----
    sidebarPanel(
      
      # X screen Resolution:
      numericInput("ResX", "X screen resolution (in pixels):", 1920, min = 1, max = 10000),
      verbatimTextOutput("value1"),

      # Y screen Resolution:
      numericInput("ResY", "Y screen resolution (in pixels):", 1080, min = 1, max = 10000),
      verbatimTextOutput("value2"),
      # 
      # Y screen Resolution:
      numericInput("maxtrial", "Maximum number of trials:", 120, min = 1, max = 10000),
      verbatimTextOutput("value3"),
      
      # Y screen Resolution:
      numericInput("tBlink", "Blink detection cut-off (in ms):", 50, min = 1, max = 500),
      verbatimTextOutput("value4"),
      
      # asc file input:
      fileInput("file1", "Choose .asc files",
                multiple = T,
                accept = c("text/csv",
                           "text/comma-separated-values,text/plain",
                           ".csv")),
      textInput("filename", "Output file name", "raw_fix.csv")
    ),
    
    # Main panel for displaying outputs ----
    mainPanel(
      useShinyalert(),
      tags$head(tags$style(type="text/css", "
             #loadmessage {
                           position: fixed;
                           top: 0px;
                           left: 0px;
                           width: 100%;
                           padding: 5px 0px 5px 0px;
                           text-align: center;
                           font-weight: bold;
                           font-size: 100%;
                           color: #000000;
                           background-color: #CCFF66;
                           z-index: 105;
                           }
                           ")),
      conditionalPanel(condition="$('html').hasClass('shiny-busy')",
                       tags$div("Processing data...",id="loadmessage")),
      h4('Extracted data output:'),
      # Output: Verbatim text for data summary ----
      tableOutput('table'),
      conditionalPanel("output.fileUploaded",
                       downloadButton("downloadData", "Download Data"))
      #downloadButton("downloadData", "Download Data")
      
    )
  )
)

# Define server logic to summarize and view selected dataset ----
server <- function(input, output) {
  
  # set max seze to 100 MB to allow uploading larger files:
  options(shiny.maxRequestSize=100*1024^2)
  
 
  datasetInput <- reactive({
    
    raw_fix<- NULL
    plot=TRUE
    dataFile= NULL
    file1 = input$file1
    
    if (is.null(file1)) {
      return(cat("Please upload data file"))
    }else{


      #AlldataFiles = readLines(file1$datapath)
      
      source("https://raw.githubusercontent.com/martin-vasilev/EMreading/master/R/utility.R")
      
      for(i in 1:nrow(file1)){
        dataFile<- readLines(input$file1[[i, 'datapath']])
        inFile <- input$file1
        filename= stringi::stri_extract_first(str = inFile$name[i], regex = ".*(?=\\.)")
        
        #head(dataFile)
        trial_db<- trial_info(dataFile, input$maxtrial)
        #head(trial_db)
        
        for(j in 1:nrow(trial_db)){ # for each item
          if(j!= nrow(trial_db)){
            time= 1000*2
          }else{
            time= 1000*2
          }
          shinyalert(
            title = paste("Subject", i, "Trial", j, "Filename: ", filename),
            text = "",
            closeOnEsc = TRUE,
            closeOnClickOutside = FALSE,
            html = FALSE,
            type = "info",
            showConfirmButton = FALSE,
            showCancelButton = FALSE,
            timer = time,
            imageUrl = "",
            animation = F
          )
          
          text<- get_text(dataFile[trial_db$ID[j]:trial_db$start[j]]) # get text details (Eyetrack)
          
          if(text[1]!=0){ # if trial contained text
            try(coords<- get_coord(text)) # extract text coordinates
            map<- coord_map(coords, x=input$ResX, y= input$ResY) # map them to pixels on the screen
            
            # Extract raw fixations from data and map them to the text:
            try(raw_fix_temp<- parse_fix(dataFile, map, coords, trial_db[j,], i,
                                         input$ResX, input$ResY, input$tBlink, SL= TRUE))
            
            # Combine fixations:
            if(is.null(raw_fix_temp)){
              next;
            }
            #raw_fix_temp$sub<- i
            raw_fix_temp$dataFile= filename

            raw_fix<- rbind(raw_fix, raw_fix_temp)
            
            
          } else{ # if there was no text in trial, just extract fixations
            try(raw_fix_temp<- parse_fix(dataFile, map=0, coords=0, trial_db[j,], i, input$ResX,
                                         input$ResY, input$tBlink, hasText=FALSE, SL= TRUE))
            if(is.null(raw_fix_temp)){
              next;
            }
            #raw_fix_temp$sub<- i
            raw_fix_temp$dataFile= filename
            raw_fix<- rbind(raw_fix, raw_fix_temp)
            # create picture of fixations:
            
            #if(length(raw_fix_temp)>1 & plot==TRUE){ # if data was extracted from trial
            #  plot_fix(coords, raw_fix_temp, i, j, ResX, ResY, hasText = FALSE)
            #}
          }
          
          #cat(toString(j)); cat(" ")
        } # end of item loop
      }
      
      
    }
    return(raw_fix)

  })
  
  output$table <- renderTable({
    head(datasetInput())
  })
  
  output$downloadData <- downloadHandler(
    filename = function() {
      input$filename
    },
    content = function(file) {
      write.csv(datasetInput(), file)
    }
  )
  
  getData <- reactive({
    if(is.null(input$file1))
    {return(NULL)}
    else {return(1)}
  })
  
  output$fileUploaded <- reactive({
    return(!is.null(getData()))
  })
  outputOptions(output, 'fileUploaded', suspendWhenHidden=FALSE)
  
}

# Create Shiny app ----
shinyApp(ui = ui, server = server)