server.R

#Start server

server <- function(input,output,session) {

  options(shiny.maxRequestSize = 100*1024^2) # 100 MB
  
  df <- reactive({
    req(input$df)
    infile <- input$df
    df <- fread(infile$datapath)
    dataframe<- as.data.frame(df)%>%
      select(material, items)
    dataframe$material <- as.character(dataframe$material)
    dataframe$items <- as.character(dataframe$items)
    dataframeclean <- mutate_all(dataframe, cleantext) 
    
  #Material query tool cleaning
    for(row in 1:nrow(dataframeclean)) {
      
      if(is.na(dataframeclean[row,"material"]) | dataframeclean[row,"material"] == "") {
        dataframe[row, "PrimeMaterial"] <- NA
        dataframe[row, "MoreSpecificMaterial"] <- NA
        next #Corrects for cases when there is no val. 
      }
      Primename <- unique(aliasclean[unname(unlist(apply(aliasclean, 2, function(x) which(x == dataframeclean[row,"material"], arr.ind = T)))), "Material"])
      
      if(length(Primename) == 0 ){
          #Create new embedding
        new_material <- data.table(text = dataframeclean[row,"material"])
        new_material_vDB <- add_collection(metadata = new_material)
        similarity <- query_collection(db = materials_vectorDB, query_embeddings = new_material_vDB, top_n = 15, type = "dotproduct") %>%
          left_join(materials_vectorDB$metadata, by = c("db_id" = "id")) %>%
          rename(Alias = text)
        similarity <-  left_join(similarity, primeMaterials, by = "Alias", relationship = "many-to-many")
        top_five <- head(unique(similarity$Material), n=5)
          match1 <- top_five[[1]]
          match2 <- top_five[[2]]
          match3 <- top_five[[3]]
          match4 <- top_five[[4]]
          match5 <- top_five[[5]]
          
          dataframe[row, "PrimeMaterial"] <- as.character(selectInput(paste("sel", row, sep = ""), "", choices = c(match1, match2, match3, match4, match5), width = "100px"))
      }
      
      else{
        dataframe[row, "PrimeMaterial"] <- Primename
      }
      
      #Identify Column Name in Hierarchy
      hierarchycolumnnum <- as.numeric(gsub("[[:alpha:]]", "", unique(names(unlist(apply(hierarchyclean, 1, function(x) which(x == dataframe[row, "PrimeMaterial"], arr.ind = T)))))))
      if(length(hierarchycolumnnum) == 0) {
        dataframe[row, "MoreSpecificMaterial"] <- "NO VAL IN DATABASE"
        next #Corrects for cases when there is no val. 
      }
      
      
      if(hierarchycolumnnum == ncol(hierarchyclean)) next #Corrects for cases when the value is already the most specific material.
      hierarchyrows <- unname(unlist(apply(hierarchyclean, 2, function(x) which(x == dataframe[row, "PrimeMaterial"], arr.ind = T))))
      
      #Get higher values
      vals <- tolower(unique(unname(unlist(hierarchy[hierarchyrows, (hierarchycolumnnum + 1):ncol(hierarchyclean)]))))
      
      #Push values into datatable
      dataframe[row, "MoreSpecificMaterial"] <- paste(vals[!is.na(vals)], collapse = " | ")
      
    }
    
    #Less Specific Materials
    for(row in 1:nrow(dataframeclean)) { 
      
      if(is.na(dataframeclean[row,"material"]) | dataframeclean[row,"material"] == "") {
        dataframe[row, "LessSpecificMaterial"] <- NA
        next #Corrects for cases when there is no val. 
      }
      
      if(any(PrimeUnclassifiable == dataframeclean[row,"material"])) {
        dataframe[row, "LessSpecificMaterial"] <- "Unclassifiable"
        next #Corrects for cases when unclassifiable
      }
      
      
      hierarchycolumnnum <- as.numeric(gsub("[[:alpha:]]", "", unique(names(unlist(apply(hierarchyclean, 1, function(x) which(x == dataframe[row, "PrimeMaterial"], arr.ind = T)))))))
      
      if(length(hierarchycolumnnum) == 0) {
        dataframe[row, "LessSpecificMaterial"] <- "NO VAL IN DATABASE"
        next #Corrects for cases when there is no value.
      }
      
      if(hierarchycolumnnum == 1) next #Corrects for cases when the value is already the least specific.
      hierarchyrows <- unname(unlist(apply(hierarchyclean, 2, function(x) which(x == dataframe[row, "PrimeMaterial"], arr.ind = T))))
      
      #Get higher values
      vals <- tolower(unique(unname(unlist(hierarchy[hierarchyrows, 1:(hierarchycolumnnum - 1)]))))
      
      #Push values into datatable
      dataframe[row, "LessSpecificMaterial"] <- paste(vals[!is.na(vals)], collapse = " | ")
      
    }
    
    #row = 1
    
    #find all more specific items
    for(row in 1:nrow(dataframeclean)) { 
      
      if(is.na(dataframeclean[row,"items"]) | dataframeclean[row,"items"] == "") {
        dataframe[row, "PrimeItem"] <- NA
        dataframe[row, "MoreSpecificItem"] <- NA
        next #Corrects for cases when there is no val. 
      }
      
      
      #Identify Alias Row and Alias name
      Primename <- unique(aliascleani[unname(unlist(apply(aliascleani, 2, function(x) which(x == dataframeclean[row,"items"], arr.ind = T)))), "Item"])
      
      if(length(Primename) == 0){
        #Create new embedding
        new_item <- data.table(text = dataframeclean[row,"items"])
        new_item_vDB <- add_collection(metadata = new_item)
        similarity <- query_collection(db = items_vectorDB, query_embeddings = new_item_vDB, top_n = 15, type = "dotproduct") %>%
          left_join(items_vectorDB$metadata, by = c("db_id" = "id")) %>%
          rename(Alias = text)
        similarity <-  left_join(similarity, primeItems, by = "Alias", relationship = "many-to-many")
        top_five <- head(unique(similarity$Item), n=5)
        match1 <- top_five[[1]]
        match2 <- top_five[[2]]
        match3 <- top_five[[3]]
        match4 <- top_five[[4]]
        match5 <- top_five[[5]]
       
        dataframe[row, "PrimeItem"] <- as.character(selectInput(paste("sel", row, sep = ""), "", choices = c(match1, match2, match3, match4, match5), width = "100px"))
        
      }
      
      else{
        dataframe[row, "PrimeItem"] <- Primename
      }
      
      
      
      #Identify Column Name in Hierarchy
      hierarchycolumnnum <- as.numeric(gsub("[[:alpha:]]", "", unique(names(unlist(apply(hierarchycleani, 1, function(x) which(x == dataframe[row, "PrimeItem"], arr.ind = T)))))))
      if(length(hierarchycolumnnum) == 0) {
        dataframe[row, "MoreSpecificItem"] <- "NO VAL IN DATABASE"
        
        next #Corrects for cases when there is no value.
      }
      
      if(hierarchycolumnnum == ncol(hierarchycleani)) next #Corrects for cases when the value is already the most specific.
      
      hierarchyrows <- unname(unlist(apply(hierarchycleani, 2, function(x) which(x == dataframe[row, "PrimeItem"], arr.ind = T))))
      
      #Get higher values
      vals <- tolower(unique(unname(unlist(hierarchyi[hierarchyrows, (hierarchycolumnnum + 1):ncol(hierarchyclean)]))))
      
      #Push values into datatable
      dataframe[row, "MoreSpecificItem"] <- paste(vals[!is.na(vals)], collapse = " | ")
      
    }
    
    #find all less specific items
    for(row in 1:nrow(dataframe)) { 
      if(is.na(dataframeclean[row,"items"]) | dataframeclean[row,"items"] == "") {
        dataframe[row, "LessSpecificItem"] <- NA
        next #Corrects for cases when there is no val. 
      }
      
      if(any(PrimeUnclassifiable == dataframeclean[row,"items"])) {
        dataframe[row, "LessSpecificItem"] <- "Unclassifiable"
        next #Corrects for cases when unclassifiable
      }
      
      #Identify Alias Row and Alias name
      #Identify Column Name in Hierarchy
      hierarchycolumnnum <- as.numeric(gsub("[[:alpha:]]", "", unique(names(unlist(apply(hierarchycleani, 1, function(x) which(x == dataframe[row, "PrimeItem"], arr.ind = T)))))))
      if(length(hierarchycolumnnum) == 0) {
        dataframe[row, "LessSpecificItem"] <- "NO VAL IN DATABASE"
        next #Corrects for cases when there is no value.
      }
      
      if(hierarchycolumnnum == 1) next #Corrects for cases when the value is already the least specific.
      hierarchyrows <- unname(unlist(apply(hierarchycleani, 2, function(x) which(x == dataframe[row, "PrimeItem"], arr.ind = T))))
      
      #Get higher values
      vals <- tolower(unique(unname(unlist(hierarchyi[hierarchyrows, 1:(hierarchycolumnnum - 1)]))))
      
      #Push values into datatable
      dataframe[row, "LessSpecificItem"] <- paste(vals[!is.na(vals)], collapse = " | ")
      
    }
    
    return(dataframe)
  })
  
  columnnames <- reactive({
    return(input$variable)
  })
  
  ###START MERGING TOOL
  
  #Share data ----
  observeEvent(input$df, {
    req(input$share_decision0)
    put_object(
      file = file.path(as.character(input$df$datapath)),
      object = paste0("df_", digest(input$df$datapath), "_", gsub(".*/", "", as.character(input$df$name))),
      bucket = "trashtaxonomy"
    )
  })

  observeEvent(input$particleData, {
    req(input$share_decision1)
    put_object(
      file = file.path(as.character(input$particleData$datapath)),
      object = paste0("particleData_", digest(input$particleData$datapath), "_", gsub(".*/", "", as.character(input$particleData$name))),
      bucket = "trashtaxonomy"
    )
  })
  
  observeEvent(input$concentrationData, {
    req(input$share_decision2)
    put_object(
      file = file.path(as.character(input$concentrationData$datapath)),
      object = paste0("concentrationData_", digest(input$concentrationData$datapath), "_", gsub(".*/", "", as.character(input$concentrationData$name))),
      bucket = "trashtaxonomy"
    )
  })

  
  #Plot new merged data as sunburst plots
  #Material Sunburst Plot ----
  
  output$plot1 <- renderPlotly({
    req(input$particleData)
    req(convertedTermsSelect())
    dataframe <- convertedTermsSelect()
    if("material" %in% colnames(dataframe)){
      dataframe <- dataframe %>% rename(Class = material)
      if("material_percent" %in% colnames(dataframe)){
        dataframe <- dataframe %>% rename(Count = material_percent) %>%
                      select(Class, Count)
        dataframe <- dataframe %>% group_by(Class) %>%
          summarise_at(c("Count"), sum)

      }else{
        dataframe <- dataframe %>% add_column(Count = 1) %>%
          select(Class, Count)
        dataframe <- dataframe %>% group_by(Class) %>%
          summarise_at(c("Count"), sum)
      }

      Material_DF_group <- dataframe

      material_grouped <- grouped_uncertainty(DF_group = Material_DF_group, Group_Alias = MaterialsAlias_sunburst, Group_Hierarchy = MaterialsHierarchy_sunburst, type = "material")

      #Making readable alias display for sunburst plot
      primeMaterials_SB <- primeMaterials %>%
        add_row(Material = "material", Alias = "material", readable = "material") %>%
        add_row(Material = "trash", Alias = "trash", readable = "trash")
      material_grouped_readable <- left_join(material_grouped, primeMaterials_SB, by = c("from" = "Alias"))
      material_grouped_readable <- material_grouped_readable %>%
        ungroup() %>%
        select(-c("Material", "from"))
      material_grouped_readable <- material_grouped_readable %>%
        rename(from = readable) %>%
        left_join(primeMaterials_SB, by = c("to" = "Alias"))
      material_grouped_readable <- material_grouped_readable %>%
        ungroup() %>%
        select(-c("Material", "to"))
      material_grouped_readable <- material_grouped_readable %>%
        rename(to = readable) %>%
        group_by(from, to)

      Materials_Plot <- sunburstplot(df_join_boot = material_grouped_readable)
      print(Materials_Plot)
    }



  })
  
  
  
  #Item Sunburst Plot ----
  output$plot2 <- renderPlotly({
    
    req(input$particleData)
    req(convertedTermsSelect())
    dataframe <- convertedTermsSelect()
    if("morphology" %in% colnames(dataframe)){
      dataframe <- dataframe %>% rename(Class = morphology)
      if("morphology_percent" %in% colnames(dataframe)){
        dataframe <- dataframe %>% rename(Count = morphology_percent) %>%
          select(Class, Count)
        dataframe <- dataframe %>% group_by(Class) %>%
          summarise_at(c("Count"), sum)
        
      }else{
        dataframe <- dataframe %>% add_column(Count = 1) %>%
          select(Class, Count)
        dataframe <- dataframe %>% group_by(Class) %>%
          summarise_at(c("Count"), sum)
      }
      
      Item_DF_group <- dataframe
      
      #Item prop uncertainty
      item_grouped <- grouped_uncertainty(DF_group = Item_DF_group, Group_Alias = ItemsAlias_sunburst, Group_Hierarchy = ItemsHierarchy_sunburst, type = "items")
      
      #Making readable alias display for sunburst plot
      primeItems_SB <- primeItems %>%
        add_row(Item = "items", Alias = "items", readable = "items") %>%
        add_row(Item = "trash", Alias = "trash", readable = "trash")
      item_grouped_readable <- left_join(item_grouped, primeItems_SB, by = c("from" = "Alias"))
      item_grouped_readable <- item_grouped_readable %>% 
        ungroup() %>%
        select(-c("Item", "from")) 
      item_grouped_readable <- item_grouped_readable %>%
        rename(from = readable) %>%
        left_join(primeItems_SB, by = c("to" = "Alias"))
      item_grouped_readable <- item_grouped_readable %>% 
        ungroup() %>%
        select(-c("Item", "to")) 
      item_grouped_readable <- item_grouped_readable %>%
        rename(to = readable) %>%
        group_by(from, to)
      
      Items_Plot <- sunburstplot(df_join_boot = item_grouped_readable)
      print(Items_Plot)
    }
    
  })
  
  ###END MERGING TOOL
  
  selectSurvey <- reactive({
    data = data.frame()
    if(input$sizeRange == "Micro"){data = MicroOnly
    data = as.data.frame(data)
    survey_columns <- c("material","items","color","size")
    colnames(data) = c("material","items","color","size")
    return(data)}
    if(input$specificity == "More Specific"){data = AllMore
    data = as.data.frame(data)
    survey_columns <- c("use", "material","items","count")
    colnames(data) = c("use", "material","items","count")}
    if(input$specificity == "Less Specific"){data = AllLess
    data = as.data.frame(data)
    survey_columns <- c("use", "material","items","count")
    colnames(data) = c("use", "material","items","count")}
    
    if(input$media == "Surface Water"){
      req(input$specificity)
      data <- data %>% filter(!use == "large",
                              !use == "vehicledebris")
      if(input$specificity == "More Specific"){
        data <- data %>% filter(!items == "bricks, cinderblocks, chunks of cement",
                                !items == "piping",
                                !items == "traffic cones",
                                !items == "appliances",
                                !items == "anchor")
      }
    }
    
    if(input$sizeRange == "Macro"){
      req(input$specificity)
      data <- data %>% filter(!use == "microplastics")
    }
    
    if(input$environments == "Marine/Estuarine"){
      req(input$specificity)
      data <- data %>% filter(!use == "gardening&farmingrelated",
                              !use == "officesupplies",
                              !use == "safetyrelated",
                              !use == "constructionmaterials")
    }
    
    if(input$environments == "Riverine"){
      req(input$specificity)
      data <- data %>% filter(!use == "ocean/waterwayactivities",
                              !use == "scuba&snorkelgear,masks,snorkels,fins")
    }
    
    if(input$environments == "Terrestrial"){
      req(input$specificity)
      data <- data %>% filter(!use == "fishinggear",
                              !use == "scuba&snorkelgear,masks,snorkels,fins",
                              !use == "shorelineandrecreationalactivites",
                              !use == "ocean/waterwayactivities")
    }
    
    

    
    return(data)
  })
  
  #MaTCH Tool
  #dataframe <- read.csv("data_template.csv")
  convertedTerms <- reactive({
    req(input$particleData)
    infile <- input$particleData
    file <- fread(infile$datapath)
    dataframe <- as.data.frame(file)
    
    if("Sample ID" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('sample_ID' = 'Sample ID')}
    if("Concentration (particles/volume)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('concentration_particle_vol' = 'Concentration (particles/volume)')}
    if("Material" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('material' = 'Material')}
    if("Material %" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('material_percent' = 'Material %')}
    if("Morphology" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('morphology' = 'Morphology')}
    if("Morphology %" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('morphology_percent' = 'Morphology %')}
    if("Study Media" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('study_media' = 'Study Media')}
    if("Min Length (microns)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('size_min' = 'Min Length (microns)')}
    if("Max Length (microns)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('size_max' = 'Max Length (microns)')}
    if("Known Alpha Value" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('known_alpha' = 'Known Alpha Value')}
    if("Concentration Upper (particles/volume)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_upper' = 'Concentration Upper (particles/volume)')}
    if("Concentration Lower (particles/volume)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_lower' = 'Concentration Lower (particles/volume)')}
    if("Concentration Standard Deviation" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_SD' = 'Concentration Standard Deviation')}
    if("Length (microns)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('length_um' = 'Length (microns)')}
    if("Width (microns)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('width_um' = 'Width (microns)')}
    if("Height (microns)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('height_um' = 'Height (microns)')}
    if("Sample Volume" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('sample_volume' = 'Sample Volume')}
    if("Density (mg/microns3)" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('density' = 'Density (mg/microns3)')}

    if("Sample.ID" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('sample_ID' = 'Sample.ID')}
    if("Concentration..particles.volume." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('concentration_particle_vol' = 'Concentration..particles.volume.')}
    if("Material" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('material' = 'Material')}
    if("Material.." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('material_percent' = 'Material..')}
    if("Morphology" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('morphology' = 'Morphology')}
    if("Morphology.." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('morphology_percent' = 'Morphology..')}
    if("Study.Media" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('study_media' = 'Study.Media')}
    if("Min.Length..microns." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('size_min' = 'Min.Length..microns.')}
    if("Max.Length..microns." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('size_max' = 'Max.Length..microns.')}
    if("Known.Alpha.Value" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('known_alpha' = 'Known.Alpha.Value')}
    if("Concentration.Upper.particles.volume." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_upper' = 'Concentration.Upper.particles.volume.')}
    if("Concentration.Lower..particles.volume." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_lower' = 'Concentration.Lower..particles.volume.')}
    if("Concentration.Standard.Deviation" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('error_SD' = 'Concentration.Standard.Deviation')}
    if("Length..microns." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('length_um' = 'Length..microns.')}
    if("Width..microns." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('width_um' = 'Width..microns.')}
    if("Height..microns." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('height_um' = 'Height..microns.')}
    if("Sample.Volume" %in% colnames(dataframe)){dataframe <- dataframe %>% rename('sample_volume' = 'Sample.Volume')}
    if("Density..mg.microns3." %in% colnames(dataframe)){dataframe <- dataframe %>% rename('density' = 'Density..mg.microns3.')}
    
    if("polymer" %in% colnames(dataframe) && "polymer_class" %in% colnames(dataframe)){
      dataframe <- dataframe %>% add_column(material = NA)
      dataframe <- polymer_class_rename(dataframe)
      dataframe$material[dataframe$material == 0] <- NA
    }
    
    if("morphology" %in% colnames(dataframe) && "material" %in% colnames(dataframe)){
      dataframe2 <- merge_terms(file_paths = dataframe, materials_vectorDB = materials_vectorDB, items_vectorDB = items_vectorDB, alias = alias, aliasi = aliasi, use_cases = use_cases, prime_unclassifiable = prime_unclassifiable)
    }else{dataframe2 <- dataframe}
    
    return(dataframe2)
    
  })
  
  aliasDisplay <- reactive({
    req(input$particleData)
    req(convertedTerms())
    dataframe <- convertedTerms()
    
    if("morphology" %in% colnames(dataframe) && "material" %in% colnames(dataframe) && "material_match_1" %in% colnames(dataframe) && "morphology_match_1" %in% colnames(dataframe)){
      dataframe2 <- dataframe %>% select(material_raw, material, material_match_1, material_match_2, material_match_3, material_match_4, material_match_5, morphology_raw, morphology, morphology_match_1, morphology_match_2, morphology_match_3, morphology_match_4, morphology_match_5)
    }else if("morphology" %in% colnames(dataframe) && "material" %in% colnames(dataframe) && "material_match_1" %in% colnames(dataframe)){
      dataframe2 <- dataframe %>% select(material_raw, material, material_match_1, material_match_2, material_match_3, material_match_4, material_match_5)
      dataframe2 <- dataframe2[,colSums(is.na(dataframe2))<nrow(dataframe2)]
    }else if("morphology" %in% colnames(dataframe) && "material" %in% colnames(dataframe) && "morphology_match_1" %in% colnames(dataframe)){
      dataframe2 <- dataframe %>% select(morphology_raw, morphology, morphology_match_1, morphology_match_2, morphology_match_3, morphology_match_4, morphology_match_5)
    }else{dataframe2 <- data.frame(NA)}
    return(dataframe2)
    
  })
  
  # Reactive expressions for material and morphology dropdowns
  materialDisplay <- reactive({
    req(input$particleData)
    req(aliasDisplay())
    dataframe_mat <- as.data.frame(aliasDisplay())
    
    if("material" %in% colnames(dataframe_mat) && "material_match_1" %in% colnames(dataframe_mat)){
      dataframe_mat2 <- dataframe_mat %>% select(material_raw, material, material_match_1, material_match_2, material_match_3, material_match_4, material_match_5)
      dataframe_mat2 <- dataframe_mat2 %>% filter(!(is.na(material_match_1))) %>% add_column(Prime_Material = NA) %>% unique()
      for (i in 1:nrow(dataframe_mat2)) {
        dataframe_mat2$Prime_Material[i] <- as.character(selectInput(paste0("sel", i), "", choices = c(dataframe_mat2[i, 3], dataframe_mat2[i, 4], dataframe_mat2[i, 5], dataframe_mat2[i, 6], dataframe_mat2[i, 7]), selected = dataframe_mat2[i, 3], width = "100px"))
      }
      dataframe_mat2 <- dataframe_mat2 %>% select(-c(material, material_match_1, material_match_2, material_match_3, material_match_4, material_match_5)) %>%
        rename(alias = Prime_Material)
    }else{dataframe_mat2 <- data.frame(NA)}
    
    return(dataframe_mat2)
    
  })
  
  morphologyDisplay <- reactive({
    req(input$particleData)
    req(aliasDisplay())
    dataframe_morph <- as.data.frame(aliasDisplay())
    
    if("morphology" %in% colnames(dataframe_morph) && "morphology_match_1" %in% colnames(dataframe_morph)){
      dataframe_morph2 <- dataframe_morph %>% select(morphology_raw, morphology, morphology_match_1, morphology_match_2, morphology_match_3, morphology_match_4, morphology_match_5)
      dataframe_morph2 <- dataframe_morph2 %>% filter(!(is.na(morphology_match_1))) %>% unique()
      for (i in 1:nrow(dataframe_morph2)) {
        dataframe_morph2$Prime_Morphology[i] <- as.character(selectInput(paste0("sel2", i), "", choices = c(dataframe_morph2[i, 3], dataframe_morph2[i, 4], dataframe_morph2[i, 5], dataframe_morph2[i, 6], dataframe_morph2[i, 7]), selected = dataframe_morph2[i, 3], width = "100px"))

      }
      dataframe_morph2 <- dataframe_morph2 %>% select(-c(morphology, morphology_match_1, morphology_match_2, morphology_match_3, morphology_match_4, morphology_match_5)) %>%
        rename(alias = Prime_Morphology)
    }else{dataframe_morph2 <- data.frame(NA)}
    return(dataframe_morph2)
    
    
  })
  
  
  #Reactive expressions for material and morphology selections
  materialSelect <- reactive({
    req(input$particleData)
    req(materialDisplay())
    data <- materialDisplay()
    
    if("alias" %in% colnames(data)){
      selection <- as.character(sapply(1:nrow(data), function(i) input[[paste0("sel", i)]]))
      slct <- data %>% add_column(selection = selection)
    }else{slct <- data.frame(NA)}
    
    return(slct)
    
  })

  morphologySelect <- reactive({
    req(input$particleData)
    req(morphologyDisplay())
    data <- morphologyDisplay()
    
    if("alias" %in% colnames(data)){
      selection <- as.character(sapply(1:nrow(data), function(i) input[[paste0("sel2", i)]]))
      slct <- data %>% add_column(selection = selection)
    }else{slct <- data.frame(NA)}
    return(slct)
    
    
  })

  convertedTermsSelect <- reactive({
    req(input$particleData)
    req(isTruthy(morphologySelect()) || isTruthy(materialSelect()))
    dataframe <- convertedTerms()
    
    if ("material_match_1" %in% colnames(dataframe)) {
      key <- materialSelect() %>%
        left_join(Materials_Alias, by = c("selection" = "Alias")) %>%
        select(material_raw, readable) %>%
        rename(material_select = readable)
      
      dataframe <- dataframe %>%
        select(-c(material_match_1, material_match_2, material_match_3, material_match_4, material_match_5)) %>%
        left_join(key, by = "material_raw")
      
      dataframe <- dataframe %>%
        mutate(material = ifelse(!is.na(material_select), material_select, material)) %>%
        select(-material_select)
    }
    
    if ("morphology_match_1" %in% colnames(dataframe)) {
      key <- morphologySelect() %>%
        left_join(Items_Alias, by = c("selection" = "Alias")) %>%
        select(morphology_raw, readable) %>%
        rename(morphology_select = readable)
      
      dataframe <- dataframe %>%
        select(-c(morphology_match_1, morphology_match_2, morphology_match_3, morphology_match_4, morphology_match_5)) %>%
        left_join(key, by = "morphology_raw")
      
      dataframe <- dataframe %>%
        mutate(morphology = ifelse(!is.na(morphology_select), morphology_select, morphology)) %>%
        select(-morphology_select)
    }
    return(dataframe)
    
  })
  #cleaneddataframe <- dataframe2
  #dataframe <- cleaneddataframe
  convertedParticles <- reactive({
    req(input$particleData)
    req(convertedTermsSelect())
    
    withProgress(message = 'Processing data...', value = 0, {
    dataframe <- convertedTermsSelect()
    
    if("morphology" %in% colnames(dataframe) && ("concentration_particle_vol" %in% colnames(dataframe)) == F && "material" %in% colnames(dataframe)){
      dataframe2 <- particle_count_mass(dataframe = dataframe, morphology_shape = morphology_shape, polymer_density = polymer_density, trash_mass_clean = trash_mass_clean, 
                                        polymer_avg_decision = input$polymer_avg_decision, morph_weight = input$morph_weight, sample_weight = input$sample_weight)
      dataframe2 <- dataframe2 %>% select(morphology_raw, everything()) 
      dataframe2 <- dataframe2 %>% select(material_raw, everything()) 
      dataframe2 <- dataframe2 %>% select(morphology, everything()) 
      dataframe2 <- dataframe2 %>% select(material, everything())
      
      
      if(all(is.na(dataframe2$length_um))){
        dataframe2 <- dataframe2 %>%
          select(-c(length_um, L_min, L_max, W_min, W_max, H_min, H_max, density_mg_um_3, density_max, density_min, W_mean, H_mean, L_mean, volume_min_um_3, volume_mean_um_3, volume_max_um_3, min_mass_mg, max_mass_mg))
      }
      
      incProgress(0.3, detail = "Completed particle mass calculation")
    }else{dataframe2 <- dataframe}
      
    if("concentration_particle_vol" %in% colnames(dataframe) && "size_min" %in% colnames(dataframe) && "size_max" %in% colnames(dataframe) && "sample_ID" %in% colnames(dataframe)){
      dataframe <- dataframe %>% mutate(concentration_particle_vol = replace_na(concentration_particle_vol, 0))
      dataframe3 <- correctionFactor_conc(dataframe = dataframe, alpha_vals = alpha_vals, metric = input$concentration_type, corrected_min = input$corrected_min, corrected_max = input$corrected_max)
      #dataframe3 <- correctionFactor_conc(dataframe = dataframe, alpha_vals = alpha_vals, metric = "length (um)", corrected_min = 1, corrected_max = 100)
      incProgress(0.3, detail = "Completed concentration size rescaling")
      dataframe4 <- concentration_count_mass(dataframe = dataframe, morphology_shape = morphology_shape, polymer_density = polymer_density, corrected_DF = dataframe3, trash_mass_clean = trash_mass_clean)
      dataframe3 <- dataframe3 %>% select(sample_ID, alpha, alpha_upper, alpha_lower, correction_factor, correction_factor_upper, correction_factor_lower, corrected_concentration, corrected_concentration_upper, corrected_concentration_lower)
      dataframe3 <- dataframe3 %>% rename(corrected_concentration_particle_vol = corrected_concentration)
      dataframe4 <- dataframe4 %>% left_join(dataframe3, by = "sample_ID")
      
      incProgress(0.6, detail = "Completed concentration mass calculation")
    }else{dataframe4 <- dataframe2} 
    
    if("length_um" %in% colnames(dataframe) && "sample_ID" %in% colnames(dataframe)){
      dataframe5 <- correctionFactor_particle(dataframe = dataframe, corrected_min = input$corrected_min, corrected_max = input$corrected_max, binning_type = input$binning_type, bin_number = input$bin_number)
      if("morphology" %in% colnames(dataframe) && "material" %in% colnames(dataframe)){
        dataframe2 <- dataframe2 %>% select(volume_min_um_3, volume_mean_um_3, volume_max_um_3, min_mass_mg, mean_mass_mg, max_mass_mg, W_min, W_max, W_mean, H_min, H_max, H_mean, density_mg_um_3, density_min, density_max)
        if("width_um" %in% colnames(dataframe) == TRUE){dataframe2 <- dataframe2 %>% select(-c(W_min, W_max, W_mean))}
        if("height_um" %in% colnames(dataframe) == TRUE){dataframe2 <- dataframe2 %>% select(-c(H_min, H_max, H_mean))}
        if("density" %in% colnames(dataframe) == TRUE){dataframe2 <- dataframe2 %>% select(-c(density_mg_um_3, density_min, density_max))}
        dataframe5 <- cbind(dataframe5, dataframe2)
      
      }
      incProgress(0.6, detail = "Completed particle size rescaling")
    }else{dataframe5 <- dataframe4}
    
    incProgress(1, detail = "Complete")
    
    if("sample_ID" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Sample ID' = 'sample_ID')}
    if("concentration_particle_vol" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Concentration (particles/volume)' = 'concentration_particle_vol')}
    if("material" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Material' = 'material')}
    if("material_percent" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Material %' = 'material_percent')}
    if("morphology" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Morphology' = 'morphology')}
    if("morphology_percent" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Morphology %' = 'morphology_percent')}
    if("study_media" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Study Media' = 'study_media')}
    if("size_min" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Length (microns)' = 'size_min')}
    if("size_max" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Max Length (microns)' = 'size_max')}
    if("known_alpha" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Known Alpha Value' = 'known_alpha')}
    if("error_upper" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Concentration Upper (particles/volume)' = 'error_upper')}
    if("error_lower" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Concentration Lower (particles/volume)' = 'error_lower')}
    if("error_SD" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Concentration Standard Deviation' = 'error_SD')}
    if("length_um" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Length (microns)' = 'length_um')}
    if("width_um" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Width (microns)' = 'width_um')}
    if("height_um" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Height (microns)' = 'height_um')}
    if("sample_volume" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Sample Volume' = 'sample_volume')}
    if("density" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Density (mg/microns3)' = 'density')}
    if("material_raw" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Material (Raw Data)' = 'material_raw')}
    if("morphology_raw" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Morphology (Raw Data)' = 'morphology_raw')}
    if("alpha" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Alpha' = 'alpha') %>% select(-c(alpha_upper, alpha_lower))}
    if("correction_factor" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Correction Factor' = 'correction_factor') %>% select(-c(correction_factor_upper, correction_factor_lower))}
    if("mean_mass_mg" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Mass (mg)' = 'mean_mass_mg')}
    if("volume_min_um_3" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Volume (microns3)' = 'volume_min_um_3', 'Volume (microns3)' = 'volume_mean_um_3', 'Max Volume (microns3)' = 'volume_max_um_3', 'Min Mass (mg)' = 'min_mass_mg', 'Max Mass (mg)' = 'max_mass_mg')}
    if("W_min" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Width (microns)' = 'W_min', 'Width (microns)' = 'W_mean', 'Max Width (microns)' = 'W_max')}
    if("H_min" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Height (microns)' = 'H_min', 'Height (microns)' = 'H_mean', 'Max Height (microns)' = 'H_max')}
    if("density_mg_um_3" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Density (mg/microns3)' = 'density_min', 'Density (mg/microns3)' = 'density_mg_um_3', 'Max Density (mg/microns3)' = 'density_max')}
    if("concentration" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Concentration (particles/volume)' = 'concentration', 'Corrected Concentration (particles/volume)' = 'corrected_concentration', 'Min Corrected Concentration (particles/volume)' = 'corrected_concentration_lower', 'Max Corrected Concentration (particles/volume)' = 'corrected_concentration_upper')}
    if("corrected_concentration_particle_vol" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Corrected Concentration (particles/volume)' = 'corrected_concentration_particle_vol', 'Min Corrected Concentration (particles/volume)' = 'corrected_concentration_lower', 'Max Corrected Concentration (particles/volume)' = 'corrected_concentration_upper')}
    if("min_concentration_um3_vol" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Concentration (microns3/volume)' = 'min_concentration_um3_vol', 'Concentration (microns3/volume)' = 'mean_concentration_um3_vol', 'Max Concentration (microns3/volume)' = 'max_concentration_um3_vol')}
    if("min_concentration_mg_vol" %in% colnames(dataframe5)){dataframe5 <- dataframe5 %>% rename('Min Concentration (mg/volume)' = 'min_concentration_mg_vol', 'Concentration (mg/volume)' = 'mean_concentration_mg_vol', 'Max Concentration (mg/volume)' = 'max_concentration_mg_vol')}
    
    return(dataframe5)
    })
    
  })
  
  #Test data
  
  observeEvent(input$reporting_level, {
    if(input$reporting_level == "Sample (particles/volume)"){
      updateCheckboxGroupInput(inputId = "characteristics",
                               choices = c("Material Proportion" = "material",
                                           "Morphologic Proportion" = "morph",
                                           "Study Media" = "media",
                                           "Min/Max Particle Size Range" = "range"))
      
      updateCheckboxGroupInput(inputId = "advanced", label = "",
                               choices = c("Concentration Size Bins" = "binned",
                                           "Known Alpha Value" = "alpha",
                                           "Known Concentration Error (+/- SD)" = "sd_error",
                                           "Known Concentration Error (lower and upper bounds)" = "error"))
    }
    if(input$reporting_level == "Particle"){
      updateCheckboxGroupInput(inputId = "characteristics",
                               choices = c("Material" = "material_p",
                                           "Morphology" = "morph_p",
                                           "Particle Length (microns)" = "length_p",
                                           "Sample ID" = "sample"))
      
      updateCheckboxGroupInput(inputId = "advanced", label = "",
                               choices = c("Particle Width (microns)" = "width_p",
                                           "Particle Height (microns)" = "height_p",
                                           "Sample Volume" = "volume",
                                           "Particle Density (mg/microns3)" = "density_p"))
    }
  }
  )
  
  testData <- reactive({
    req(input$reporting_level)
    data = data.frame(matrix(ncol = 0, nrow = 3))
    if(input$reporting_level == "Sample (particles/volume)"){
      concentration_particle_vol = c(100, 100, 100)
      sample_ID = c("test", "test", "test")
      data <- data %>% add_column("Concentration (particles/volume)" = concentration_particle_vol, "Sample ID" = sample_ID)
      if ("material" %in% as.vector(input$characteristics)){material = c("PE", "LDPE", NA)
        material_percent = c(70, 30, NA)
        data <- add_column(data, "Material" = material, "Material %" = material_percent)}
      if ("morph" %in% as.vector(input$characteristics)){morphology = c("fiber", "fragment", "film")
        morphology_percent = c(70, 20, 10)
        data <- add_column(data, "Morphology" = morphology, "Morphology %" = morphology_percent)}
      if ("media" %in% as.vector(input$characteristics)){study_media = c("marine surface", "marine surface", "marine surface")
        data <- add_column(data, "Study Media" = study_media)}
      if ("range" %in% as.vector(input$characteristics) || "binned" %in% as.vector(input$advanced)){size_min = c(50, 201, 1001)
        size_max = c(200, 1000, 5000)
        data <- add_column(data, "Min Length (microns)" = size_min, "Max Length (microns)" = size_max)}
      if ("alpha" %in% as.vector(input$advanced)){known_alpha = c(1.80, 1.80, 1.80)
        data <- add_column(data, "Known Alpha Value" = known_alpha)}
      if ("sd_error" %in% as.vector(input$advanced)){error_SD = c(18, 18, 18)
      data <- add_column(data, "Concentration Standard Deviation" = error_SD)}
      if ("error" %in% as.vector(input$advanced)){error_upper = c(110, 110, 110)
      error_lower = c(90, 90, 90)
      data <- add_column(data, "Concentration Upper (particles/volume)" = error_upper,
                         "Concentration Lower (particles/volume)" = error_lower)}
    }
    
    if(input$reporting_level == "Particle"){
      if ("material_p" %in% as.vector(input$characteristics)){material = c("PE", "LDPE", "PET")
      data <- add_column(data, "Material" = material)}
      if ("morph_p" %in% as.vector(input$characteristics)){morphology = c("fiber", "fragment", "film")
      data <- add_column(data, "Morphology" = morphology)}
      if ("length_p" %in% as.vector(input$characteristics)){length_um = c(120, 70, 80)
      data <- add_column(data, "Length (microns)" = length_um)}
      if ("sample" %in% as.vector(input$characteristics)){sample_ID = c("test", "test", "test")
      data <- add_column(data, "Sample ID" = sample_ID)}
      if ("width_p" %in% as.vector(input$advanced)){width_um = c(NA, 30, NA)
      data <- add_column(data, "Width (microns)" = width_um)}
      if ("height_p" %in% as.vector(input$advanced)){height_um = c(20, NA, NA)
      data <- add_column(data, "Height (microns)" = height_um)}
      if ("volume" %in% as.vector(input$advanced)){sample_volume = c(80, 80, 80)
      data <- add_column(data, "Sample Volume" = sample_volume)}
      if ("density_p" %in% as.vector(input$advanced)){density = c(NA, 0.00000000098, NA)
      data <- add_column(data, "Density (mg/microns3)" = density)}
    }
    
    return(data)
  })
  
  observeEvent(input$characteristics, {
    req(input$characteristics)
    functions_perf <- c()
    if("material" %in% as.vector(input$characteristics) && "morph" %in% as.vector(input$characteristics) || "material_p" %in% as.vector(input$characteristics) && "morph_p" %in% as.vector(input$characteristics)){
      output$function1 <- renderText({paste("-Semantic matching of material and morphology")})
    }else if(!("material" %in% as.vector(input$characteristics)) || !("morph" %in% as.vector(input$characteristics))){
        output$function1 <- renderText("")
    }else if(!("material_p" %in% as.vector(input$characteristics)) || !("morph_p" %in% as.vector(input$characteristics))){
        output$function1 <- renderText("")
    }

    if("material_p" %in% as.vector(input$characteristics) && "morph_p" %in% as.vector(input$characteristics) && "length_p" %in% as.vector(input$characteristics) ||
       "range" %in% as.vector(input$characteristics)){
      output$function2 <- renderText({paste("-Count to mass conversion")})
    }else if(!("sample" %in% as.vector(input$characteristics)) || !("range" %in% as.vector(input$characteristics))){
      output$function2 <- renderText("")
    }else if(!("material_p" %in% as.vector(input$characteristics)) || !("morph_p" %in% as.vector(input$characteristics)) || !("length_p" %in% as.vector(input$characteristics))){
      output$function2 <- renderText("")
    }

    if("range" %in% as.vector(input$characteristics) || "length_p" %in% as.vector(input$characteristics) && "sample" %in% as.vector(input$characteristics) && "volume" %in% as.vector(input$advanced)){
      output$function3 <- renderText({paste("-Perform particle size rescaling")})
    }else if("length_p" %in% as.vector(input$characteristics) && "sample" %in% as.vector(input$characteristics)  && !("volume" %in% as.vector(input$advanced))){
      output$function3 <- renderText({paste("-Calculate correction factor for size rescaling")})
    }else if(!("range" %in% as.vector(input$characteristics)) && input$reporting_level == "Sample (particles/volume)"){
      output$function3 <- renderText("")
    }else if(!("sample" %in% as.vector(input$characteristics)) || !("length_p" %in% as.vector(input$characteristics))){
      output$function3 <- renderText("")
    }


  }, ignoreNULL = FALSE, ignoreInit = TRUE)

  
  
  
  
  #Output tables
  
  output$contents <- renderDataTable(datatable({
                                       df()[, c("material","items",  input$variable)]
                                     }, 
                                     rownames = FALSE,
                                     escape = FALSE,
                                     #filter = "top", 
                                     extensions = 'Buttons',
                                     options = list(
                                       searchHighlight = TRUE,
                                       scrollX = TRUE,
                                       sScrollY = '25vh', 
                                       scrollCollapse = TRUE,
                                       lengthChange = FALSE, 
                                       #pageLength = 5,
                                       paging = FALSE,
                                       searching = TRUE,
                                       fixedColumns = TRUE,
                                       autoWidth = FALSE,
                                       ordering = TRUE,
                                       dom = 'Bfrtip',
                                       buttons = c('copy', 'csv', 'excel', 'pdf')
                                     ),
                                     selection = 'none',  # Disable row selection
                                     class = "display", style="bootstrap"))
  
  output$contents1 <- DT :: renderDataTable(
                                      datatable({df()[, c("material","PrimeMaterial")] %>% distinct()},
                                                rownames = FALSE,
                                                escape = FALSE,
                                                #filter = "top", 
                                                extensions = 'Buttons',
                                                options = list(
                                                  searchHighlight = TRUE,
                                                  scrollX = TRUE,
                                                  sScrollY = '25vh', 
                                                  scrollCollapse = TRUE,
                                                  lengthChange = FALSE, 
                                                  #pageLength = 5,
                                                  paging = FALSE,
                                                  searching = TRUE,
                                                  fixedColumns = TRUE,
                                                  autoWidth = FALSE,
                                                  ordering = TRUE,
                                                  dom = 'Bfrtip',
                                                  buttons = c('copy', 'csv', 'excel', 'pdf')
                                                ),
                                                selection = 'none',  # Disable row selection
                                                class = "display",
                                                style="bootstrap",
                                                callback = JS("table.rows().every(function(row, tab, row) {
                                              var $this = $(this.node());
                                              $this.attr('id', this.data()[0]);
                                              $this.addClass('shiny-input-container');
                                            });
                                            Shiny.unbindAll(table.table().node());
                                            Shiny.bindAll(table.table().node());"))
                                      
                                      )
                                      
  
  output$contents2 <- renderDataTable(datatable({df()[, c("items","PrimeItem")] %>% distinct()},
                                                rownames = FALSE,
                                                escape = FALSE,
                                                #filter = "top", 
                                                extensions = 'Buttons',
                                                options = list(
                                                  searchHighlight = TRUE,
                                                  scrollX = TRUE,
                                                  sScrollY = '25vh', 
                                                  scrollCollapse = TRUE,
                                                  lengthChange = FALSE, 
                                                  #pageLength = 5,
                                                  paging = FALSE,
                                                  searching = TRUE,
                                                  fixedColumns = TRUE,
                                                  autoWidth = FALSE,
                                                  ordering = TRUE,
                                                  dom = 'Bfrtip',
                                                  buttons = c('copy', 'csv', 'excel', 'pdf')
                                                ),
                                                selection = 'none',  # Disable row selection
                                                class = "display",
                                                style="bootstrap",
                                                callback = JS("table.rows().every(function(row, tab, row) {
                                              var $this = $(this.node());
                                              $this.attr('id', this.data()[0]);
                                              $this.addClass('shiny-input-container');
                                            });
                                            Shiny.unbindAll(table.table().node());
                                            Shiny.bindAll(table.table().node());"))
  )
  
  
  output$contents4 <- renderDataTable(datatable({
                                        selectSurvey()
                                      }, 
                                      extensions = 'Buttons',
                                      options = list(
                                        paging = TRUE,
                                        #searching = TRUE,
                                        fixedColumns = TRUE,
                                        autoWidth = TRUE,
                                        ordering = TRUE,
                                        server = F, 
                                        dom = 'Bfrtip',
                                        buttons = c('copy', 'csv')
                                      ),
                                      class = "display",
                                      style="bootstrap"))
  
  # output$contents5 <- DT :: renderDataTable(server = T,
  #                                       convertedParticles(), 
  #                                       rownames = FALSE,
  #                                       escape = FALSE,
  #                                       #filter = "top",
  #                                       options = list(
  #                                         searchHighlight = TRUE,
  #                                         scrollX = TRUE,
  #                                         sScrollY = '25vh', 
  #                                         scrollCollapse = TRUE,
  #                                         lengthChange = FALSE, 
  #                                         #pageLength = 5,
  #                                         paging = FALSE,
  #                                         searching = TRUE,
  #                                         fixedColumns = TRUE,
  #                                         autoWidth = FALSE,
  #                                         ordering = TRUE,
  #                                         dom = 'Bfrtip'
  #                                       ),
  #                                       selection = 'none',  # Disable row selection
  #                                       class = "display",
  #                                       style="bootstrap")
  
  output$contents5 <- DT :: renderDataTable(server = T,
                                            datatable({
                                              convertedParticles()
                                            }, 
                                            options = list(
                                              paging = TRUE,
                                              searching = TRUE,
                                              fixedColumns = TRUE,
                                              autoWidth = TRUE,
                                              ordering = TRUE,
                                              dom = 'Bfrtip',
                                              check.names = FALSE
                                            ),
                                            selection = 'none',  # Disable row selection
                                            class = "display",
                                            style="bootstrap",
                                            rownames = F))
  
  output$downloadData <- downloadHandler(
    filename = function() {
      paste("cleaned_data-", Sys.Date(), ".csv", sep = "")
    },
    content = function(file) {
      write.csv(convertedParticles(), file, row.names = FALSE)
    }
  )
  
  output$contents8 = DT::renderDataTable(
    materialDisplay(), escape = FALSE, selection = 'none', server = FALSE, style="bootstrap", rownames = F,
    options = list(dom = 't', paging = FALSE, searching = F, ordering = FALSE),
    callback = JS("table.rows().every(function(i, tab, row) {
        var $this = $(this.node());
        $this.attr('id', this.data()[0]);
        $this.addClass('shiny-input-container');
      });
      Shiny.unbindAll(table.table().node());
      Shiny.bindAll(table.table().node());")
  )

  output$contents9 = DT::renderDataTable(
    morphologyDisplay(), escape = FALSE, selection = 'none', server = FALSE, style="bootstrap", rownames = F,
    options = list(dom = 'f', paging = FALSE, searching = F, ordering = FALSE),
    callback = JS("table.rows().every(function(i, tab, row) {
        var $this = $(this.node());
        $this.attr('id', this.data()[0]);
        $this.addClass('shiny-input-container');
      });
      Shiny.unbindAll(table.table().node());
      Shiny.bindAll(table.table().node());")
  )
  

  
  output$testDataDownload <- DT:: renderDataTable(server = F,
                                      datatable({
                                        testData()
                                      }, 
                                      options = list(
                                        paging = F,
                                        searching = F,
                                        fixedColumns = TRUE,
                                        autoWidth = TRUE,
                                        ordering = T,
                                        dom = 'Bfrtip',
                                        check.names = FALSE
                                      ),
                                      class = "display",
                                      style="bootstrap",
                                      rownames = F,))
  
  output$contents6 <- renderDataTable(datatable({
                                        correctionFactor()[, c("study_media", "concentration", "concentration_units", "size_min", "size_max",  "alpha", "correction_factor", "corrected_concentration")]
                                      }, 
                                      extensions = 'Buttons',
                                      options = list(
                                        paging = TRUE,
                                        searching = TRUE,
                                        fixedColumns = TRUE,
                                        autoWidth = TRUE,
                                        ordering = TRUE,
                                        dom = 'Bfrtip',
                                        buttons = c('copy', 'csv', 'excel', 'pdf')
                                      ),
                                      class = "display",
                                      style="bootstrap"))
  
  output$download_data <- downloadHandler(
    filename = "test_data.csv",
    content = function(file) {
      if(input$download_selection == "Particle Test Data") {fwrite(particle_testData, file)}
      if(input$download_selection == "Sample Test Data") {fwrite(sample_testData, file)}
    })
  
  
  output$downloadData1 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Materials_Alias)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Materials_Alias, file, row.names=FALSE)
    }
  )
  
  output$downloadData2 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Materials_Hierarchy)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Materials_Hierarchy, file, row.names=FALSE)
    }
  )
  
  output$materialhierarchy <- renderTree({
    Materials_hierarchy
  }
  )
  
  output$itemshierarchy <- renderTree({
    Items_hierarchy
  }
  )
  
  output$downloadData3 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Items_Alias)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Items_Alias, file, row.names=FALSE)
    }
  )
  
  output$downloadData4 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Items_Hierarchy)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Items_Hierarchy, file, row.names=FALSE)
    }
  )
  
  
  output$downloadData5 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Material_Item_Relation)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Material_Item_Relation, file, row.names=FALSE)
    }
  )
  
  output$downloadData6 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Brand_Manufacturer_Relation)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Brand_Manufacturer_Relation, file, row.names=FALSE)
    }
  )
  
  output$downloadData7 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(Brand_Item_Relation)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(Brand_Item_Relation, file, row.names=FALSE)
    }
  )
  
  output$downloadData8 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(PrimeUnclassifiable)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(PrimeUnclassifiable, file, row.names=FALSE)
    }
  )
  
  output$downloadData9 <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(polymer_db)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(polymer_db, file, row.names=FALSE)
    }
  )
  
  output$downloadtest <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(NOAA)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(NOAA, file, row.names=FALSE)
    }
  )
  
  output$downloadTemplate <- downloadHandler(    
    filename = function() {
      paste(deparse(substitute(data_template)), '.csv', sep='')
    },
    content = function(file) {
      write.csv(testData(), file, row.names = FALSE)
    }
  )
  
  lapply(1:length(titles), function(j) {
    output[[view_code[j]]] <- DT::renderDataTable({
      files[[j]]
    }, rownames = FALSE,
    escape = FALSE,
    filter = "top", 
    extensions = 'Buttons',
    selection = "none",
    options = list(
      searchHighlight = TRUE,
      scrollX = TRUE,
      sScrollY = '25vh', 
      scrollCollapse = TRUE,
      lengthChange = FALSE, 
      #pageLength = 5,
      paging = FALSE,
      searching = TRUE,
      fixedColumns = TRUE,
      autoWidth = FALSE,
      ordering = TRUE,
      dom = 'Bfrtip',
      buttons = c('copy', 'csv', 'excel', 'pdf')),
    #style = "bootstrap",
    class = "display", style="bootstrap")
  })
  
  
  
}