server.R 9.88 KB
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# 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(shinyjs) #http://deanattali.com/shinyjs/
library(data.table)
library(ggplot2)
library(plotly)

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# increase file upload limit
options(shiny.maxRequestSize = 30 * 1024 ^ 2)
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source('auxfunc.R')

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shinyServer(function(input, output, session) {
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  useShinyjs()
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  # This is only set at session start
  # we use this as a way to determine which input was
  # clicked in the dataInBoth reactive
  counter <- reactiveValues(
    # The value of inDataGen1,2 actionButton is the number of times they were pressed
    dataGen1     = isolate(input$inDataGen1),
    dataLoadNuc  = isolate(input$inButLoadNuc)
    #dataLoadStim = isolate(input$inButLoadStim)
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  )
  
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  # This button will reset the inFileLoad
  observeEvent(input$inButReset, {
    reset("inFileLoadNuc")  # reset is a shinyjs function
    #reset("inButLoadStim")  # reset is a shinyjs function
  })
  
  # generate random dataset 1
  dataGen1 <- eventReactive(input$inDataGen1, {
    cat("dataGen1\n")
    
    return(userDataGen())
  })
  
  # load main data file
  dataLoadNuc <- eventReactive(input$inButLoadNuc, {
    cat("dataLoadNuc\n")
    locFilePath = input$inFileLoadNuc$datapath
    
    counter$dataLoadNuc <- input$inButLoadNuc - 1
    
    if (is.null(locFilePath) || locFilePath == '')
      return(NULL)
    else {
      return(fread(locFilePath))
    }
  })
  
  # load stimulation pattern
  # dataLoadStim <- eventReactive(input$inButLoadStim, {
  #   cat("dataLoadStim\n")
  #   locFilePath = input$inFileLoadStim$datapath
  #   counter$dataLoadStim <- input$inButLoadStim - 1
  #   
  #   return(fread(locFilePath))
  # })
  
  dataInBoth <- reactive({
    # Without direct references to inDataGen1,2 and inFileLoad, inDataGen2
    #    does not trigger running this reactive once inDataGen1 is used.
    # This is one of the more nuanced areas of reactive programming in shiny
    #    due to the if else logic, it isn't fetched once inDataGen1 is available
    # The morale is use direct retrieval of inputs to guarantee they are available
    #    for if else logic checks!
    
    locInGen1 = input$inDataGen1
    locInLoadNuc = input$inButLoadNuc
    #locInLoadStim = input$inButLoadStim
    
    cat(
      "dataInBoth\ninGen1: ",
      locInGen1,
      "   prev=",
      isolate(counter$dataGen1),
      "\ninDataNuc: ",
      locInLoadNuc,
      "   prev=",
      isolate(counter$dataLoadNuc),
      # "\ninDataStim: ",
      # locInLoadStim,
      # "   prev=",
      # isolate(counter$dataLoadStim),
      "\n"
    )
    
    # isolate the checks of counter reactiveValues
    # as we set the values in this same reactive
    if (locInGen1 != isolate(counter$dataGen1)) {
      cat("dataInBoth if inDataGen1\n")
      dm = dataGen1()
      # no need to isolate updating the counter reactive values!
      counter$dataGen1 <- locInGen1
    } else if (locInLoadNuc != isolate(counter$dataLoadNuc)) {
      cat("dataInBoth if inDataLoadNuc\n")
      dm = dataLoadNuc()
      # no need to isolate updating the counter reactive values!
      counter$dataLoadNuc <- locInLoadNuc
    } else {
      cat("dataInBoth else\n")
      dm = NULL
    }
    return(dm)
  })
  
  # return column names of the main dt
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  getDataNucCols <- reactive({
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    cat(file = stderr(), 'getDataNucCols: in\n')
    loc.dt = dataInBoth()
    
    if (is.null(loc.dt))
      return(NULL)
    else
      return(colnames(loc.dt))
  })
  
  # return dt with an added column with unique track object label
  dataMod <- reactive({
    cat(file=stderr(), 'dataMod\n')
    loc.dt = dataInBoth()
    
    if(is.null(loc.dt))
      return(NULL)
    
    loc.dt[, trackObjectsLabelUni := paste(sprintf("%03d", get(input$inSelSite)),
                                           sprintf("%04d", get(input$inSelTrackLabel)),
                                           sep = "_")]
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    return(loc.dt)
  })

  

  
  # This button will reset the inFileLoad
  observeEvent(input$butReset, {
    reset("inFileLoadNuc")  # reset is a shinyjs function
    #    reset("inFileStimLoad")  # reset is a shinyjs function
    
  })
  
  # generate random dataset 1
  dataGen1 <- eventReactive(input$inDataGen1, {
    cat("dataGen1\n")
    
    return(userDataGen())
  })
  
  
  # prepare data for plotting time courses
  # returns dt with these columns:
  # realtime - selected from input
  # y - measurement selected from input (can be a single column or result of an operation on two cols)
  # id - trackObjectsLabelUni (created in dataMod)
  # group - grouping variable from input
  data4trajPlot <- reactive({
    cat(file=stderr(), 'data4trajPlot\n')
    
    loc.dt = dataMod()
    if(is.null(loc.dt))
      return(NULL)
    
    
    if(input$inSelMath == '')
      loc.s.y = input$inSelMeas1
    else if (input$inSelMath == '1 / ')
      loc.s.y = paste0(input$inSelMath, input$inSelMeas1)
    else
      loc.s.y = paste0(input$inSelMeas1, input$inSelMath, input$inSelMeas2)
    
    # create expression for parsing
    # creates a merged column based on other columns from input
    # used for grouping of plot facets
    loc.s.gr = sprintf("paste(%s, sep=';')", paste(input$inSelGroup, sep = '', collapse = ','))
    
    loc.s.rt = input$inSelTime
    
    loc.out = loc.dt[, .(
      y = eval(parse(text = loc.s.y)),
      id = trackObjectsLabelUni,
      group = eval(parse(text = loc.s.gr)),
      realtime = eval(parse(text = loc.s.rt))
    )]
    
    # remove rows with NA
    return(loc.out[complete.cases(loc.out)])
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  })
  
  output$varSelSite = renderUI({
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    cat(file = stderr(), 'UI varSelSite\n')
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    locCols = getDataNucCols()
    locColSel = locCols[locCols %like% 'ite'][1] # index 1 at the end in case more matches; select 1st
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    cat(locColSel, '\n')
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    selectInput(
      'inSelSite',
      'Select FOV (e.g. Metadata_Site or Metadata_Series):',
      locCols,
      width = '100%',
      selected = locColSel
    )
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  })
  
  output$varSelTrackLabel = renderUI({
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    cat(file = stderr(), 'UI varSelTrackLabel\n')
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    locCols = getDataNucCols()
    locColSel = locCols[locCols %like% 'rack'][1] # index 1 at the end in case more matches; select 1st
    
    cat(locColSel, '\n')
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    selectInput(
      'inSelTrackLabel',
      'Select Track Label (e.g. objNuc_Track_ObjectsLabel):',
      locCols,
      width = '100%',
      selected = locColSel
    )
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  })
  
  output$varSelTime = renderUI({
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    cat(file = stderr(), 'UI varSelTime\n')
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    locCols = getDataNucCols()
    locColSel = locCols[locCols %like% 'ime'][1] # index 1 at the end in case more matches; select 1st
    
    cat(locColSel, '\n')
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    selectInput(
      'inSelTime',
      'Select X-axis (e.g. RealTime):',
      locCols,
      width = '100%',
      selected = locColSel
    )
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  })
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  # This is main field to select plot facet grouping
  # It's typically a column with the entire experimental description,
  # e.g. in Yannick's case it's Stim_All_Ch or Stim_All_S.
  # In Coralie's case it's a combination of 3 columns called Stimulation_...
  output$varSelGroup = renderUI({
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    cat(file = stderr(), 'UI varSelGroup\n')
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    locCols = getDataNucCols()
    
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    if (!is.null(locCols)) {
      locColSel = locCols[locCols %like% 'ite']
      if (length(locColSel) == 0)
        locColSel = locCols[locCols %like% 'eries'][1] # index 1 at the end in case more matches; select 1st
      else if (length(locColSel) > 1) {
        locColSel = locColSel[1]
      }
      #    cat('UI varSelGroup::locColSel ', locColSel, '\n')
      selectInput(
        'inSelGroup',
        'Select one or more facet groupings (e.g. Site, Well, Channel):',
        locCols,
        width = '100%',
        selected = locColSel,
        multiple = TRUE
      )
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    }
    
  })
  
  
  output$varSelMeas1 = renderUI({
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    cat(file = stderr(), 'UI varSelMeas1\n')
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    locCols = getDataNucCols()
    
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    if (!is.null(locCols)) {
      locColSel = locCols[locCols %like% 'objCyto_Intensity_MeanIntensity_imErkCor.*'][1] # index 1 at the end in case more matches; select 1st
      #    cat(locColSel, '\n')
      selectInput(
        'inSelMeas1',
        'Select Y-axis:',
        locCols,
        width = '100%',
        selected = locColSel
      )
    }
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  })
  
  
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  output$varSelMeas2 = renderUI({
    cat(file = stderr(), 'UI varSelMeas2\n')
    locCols = getDataNucCols()
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    if (!is.null(locCols) &&
        !(input$inSelMath %in% c('', '1 / '))) {
      locColSel = locCols[locCols %like% 'objNuc_Intensity_MeanIntensity_imErkCor.*'][1] # index 1 at the end in case more matches; select 1st
      #    cat(locColSel, '\n')
      selectInput(
        'inSelMeas2',
        'Select 2nd opernad for Y-axis',
        locCols,
        width = '100%',
        selected = locColSel
      )
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    }
  })
  
  
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  output$uiPlot = renderUI({
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    plotlyOutput("plotTraj", width = paste0(input$inPlotWidth, '%'), height = paste0(input$inPlotHeight, 'px'))
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  })
  
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  output$plotTraj <- renderPlotly({
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    cat(file=stderr(), 'plotTraj: in\n')
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    locBut = input$butGo
    
    if (locBut == 0) {
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      cat(file=stderr(), 'plotTraj: Go button not pressed\n')
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      return(NULL)
    }
    
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    loc.dt = isolate(data4trajPlot())
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    cat("plotScatter on to plot\n\n")
    if (is.null(loc.dt)) {
      cat(file=stderr(), 'plotTraj: dt is NULL\n')
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      return(NULL)
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    }
    
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    cat(file=stderr(), 'plotTraj:dt not NULL\n')
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    p.out = myGgplotTraj(
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      dt.arg = loc.dt,
      x.arg = 'realtime',
      y.arg = 'y',
      group.arg = "id",
      facet.arg = 'group',
      facet.ncol.arg = input$inPlotTrajFacetNcol,
      xlab.arg = 'Time (min)'
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    )
    
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    # This is required to avoid 
    # "Warning: Error in <Anonymous>: cannot open file 'Rplots.pdf'"
    # When running on a server. Based on:
    # https://github.com/ropensci/plotly/issues/494
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    if (names(dev.cur()) != "null device") dev.off()
    pdf(NULL)
    
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    p.out.ly = plotly_build(p.out)
    return(p.out.ly)
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  })
  
})