merge conflict resolved app.R updated

.gitignore

@@ -5,6 +5,9 @@
 .Ruserdata
 .positai
 .png
+.DS_Store
+www/.DS_Store
+dev/www/.DS_Store
 man
 docs
 pkgdown

dev/app.R

@@ -340,7 +340,10 @@ server <- function(input, output, session) {
           tabPanel(
             "Report",
             h4("Settings for report"),
-            downloadButton("downloadXLReport", label = "Download 4PL PDF report", class = "butt"),
+            useShinyjs(),
+            actionButton("btn", "Download 4PL PDF report", icon = icon("download")),
+            downloadButton("downloadXLReport", style = "visibility: hidden;"),
+            #downloadButton("downloadXLReport", label = "Download 4PL PDF report", class = "butt"),
             tags$style(type = "text/css", "#downloadXLReport {background-color: orange; color: black;font-family: Courier New}"),
             downloadButton("downloadXLReportLin", label = "Download linear PLA PDF report", class = "butt"),
             tags$style(type = "text/css", "#downloadXLReportLin {background-color: #4FCBD9; color: black;font-family: Courier New}"),
@@ -582,6 +585,7 @@ server <- function(input, output, session) {
                   title = "Upload multiple worksheets", status = "warning", solidHeader = TRUE, width = 12, "Please upload your EXCEL file here",
                   fileInput("MiFile", "", accept = ".xlsx")
                 )
+
               )
             )
           ),
@@ -594,25 +598,26 @@ server <- function(input, output, session) {
                   title = "ANOVA table", status = "primary", solidHeader = TRUE, width = 12,
                   tableOutput("Anovatab")
                 ),
-                column(
+
-                  4,
+                column(8,
-                  h3("Confidence intervals"),
+                  # h3("Confidence intervals"),
-                  tableOutput("CIs"),
+                  # tableOutput("CIs"),
-                  "The confidence interval table is interaactive for changes in: variability slider (%SD), potency of test-slider,
+                  # "The confidence interval table is interaactive for changes in: variability slider (%SD), potency of test-slider,
-                                       and 'Adjust the dilutions'-slider",
+                  #                      and 'Adjust the dilutions'-slider",
-                  tableOutput("optimalDils"),
+                  # tableOutput("optimalDils"),
+                  plotOutput("sigPlotREF"),
                   selectInput(inputId = "scenario", label = "Select an 'optimal' scenario:", choices = c("scenario 2", "scenario 3", "scenario 6", "steep slope"))
                 ),
-                column(
+                column(5,
-                  5,
                    plotOutput("plotfordilutions"),
-                  h4("in grey: most extreme bend point lines of theoretical samples with 50% and 200% potency"),
+                  # h4("in grey: most extreme bend point lines of theoretical samples with 50% and 200% potency"),
-                  sliderInput("dilslider", "Adjust the dilutions(+-change in %)", min = -100, max = 100, value = 0, step = 1, round = 0),
+                  # sliderInput("dilslider", "Adjust the dilutions(+-change in %)", min = -100, max = 100, value = 0, step = 1, round = 0),
-                  checkboxInput("fixupper", "Fix highest concentration (if unticked, the center is fixed)", FALSE),
+                  # checkboxInput("fixupper", "Fix highest concentration (if unticked, the center is fixed)", FALSE),
-                  h5("Dilution factors"),
+                  # h5("Dilution factors"),
-                  tableOutput("adjlogdil"),
+                  # tableOutput("adjlogdil"),
-                  "Short guidance: wider dilution ranges increase the CIs of rel. potency, and decrease the CIs of upper and lower asymptote ratios, as well as Hill's slope ratios", br(),
+                  # "Short guidance: wider dilution ranges increase the CIs of rel. potency, and decrease the CIs of upper and lower asymptote ratios, as well as Hill's slope ratios", br(),
-                  "Narrower dilution ranges decrease the CIs of rel. potency, and increase the CIs of upper and lower asymptote ratios, ands Hill's slope ratios",
+                  # "Narrower dilution ranges decrease the CIs of rel. potency, and increase the CIs of upper and lower asymptote ratios, ands Hill's slope ratios",
+
                 ),
                 column(
                   3,
@@ -2107,12 +2112,15 @@ server <- function(input, output, session) {
   #### Dilutions Simulator ----
   output$plotfordilutions <- renderPlot({
     if (!is.null(Dat$Mws)) {
+
+
     AllXL <- Dat$Mws
-    }
     AllSheets <- Dat$Msheets
     
+    URMcoefsL <- list()
     
     for (N_WS in 1:length(AllXL)) {
+   
     datWS <- as.data.frame(AllXL[[N_WS]])
     
     cn <- colnames(datWS)
@@ -2133,29 +2141,36 @@ server <- function(input, output, session) {
     }
     Dat$datWS2 <- datWS2
     
-      FITs <- Fitting_FUNC(datWS2, TransFlag = FALSE)
+    FITs <- Fitting_FUNC(datWS2, TransFlag = F)
  
     pot_est <- FITs[[3]]
     potU_est <- FITs[[4]]
     # unrestricted
     SU_mu <- FITs[[2]]
-      URMcoeffs <- SU_mu$coefficients
+    URMcoefs1 <- SU_mu$coefficients
+    URMcoefs <- t(matrix(unlist(URMcoefs1[,1])))
+    URMcoefs_ <- cbind(AllSheets[[N_WS]], URMcoefs)
+    URMcoefsL[[N_WS]] <- URMcoefs_
     
-      X <- seq(min(log(datWS23$log_dose)), max(log(datWS2$log_dose)), 0.1)
+    X <- seq(min(datWS2$log_dose), max(datWS2$log_dose), 0.1)
-      sigRef <- URMcoefs[1, 1] + (URMcoefs1[4, 1] - URMcoefs[1, 1]) / (1 + exp(URMcoefs[2, 1] * (URMcoefs[3, 1] - X)))
+    sigRef <- URMcoefs[1,1] + (URMcoefs[1,3]-URMcoefs[1,1])/(1+exp(URMcoefs[1,2]*(URMcoefs[1,4]-X)))
-      sigTest1 <- URMcoefs[5, 1] + (URMcoefs[8, 1] - URMcoefs[5, 1]) / (1 + exp(URMcoefs[6, 1] * (URMcoefs[7, 1] - X)))
+    sigTest1 <- URMcoefs[1,5] + (URMcoefs[1,7]-URMcoefs[1,5])/(1+exp(URMcoefs[1,6]*(URMcoefs[1,4] - URMcoefs[1,8]-X)))
-
+    #browser()  
-      dfPlotsigRef <- data.frame(X = X, sigRef = sigRef, Prod = pdfInd)
+    dfPlotsigRef <- data.frame(X=X, sigRef = sigRef, Sheet = AllSheets[[N_WS]])
-      dfPlotsigTest <- data.frame(X = X, sigTest = sigTest1, Prod = AllSheets[[N_WS]])
+    dfPlotsigTest <- data.frame(X=X, sigTest = sigTest1, Sheet = AllSheets[[N_WS]])
     
     if (!exists("SIGrefDF")) SIGrefDF <- dfPlotsigRef else SIGrefDF <- rbind(SIGrefDF, dfPlotsigRef)
     if (!exists("SIGtestDF")) SIGtestDF <- dfPlotsigTest else SIGtestDF <- rbind(SIGtestDF,dfPlotsigTest)
 
-      EC50TEST <- as.numeric(c(URMcoefsDF[, 8]))
+    } #for N_WS
+    
+    #browser()   
+    URMcoefsDF <- t(matrix(unlist(URMcoefsL),nrow=9))
+    EC50TEST <- as.numeric(URMcoefsDF[,5]) - as.numeric(URMcoefsDF[,9])
     # EC50TEST <- EC50TEST[!EC50TEST %in% boxplot.stats(EC50TEST)$out]
-      EC50REF <- as.numeric(URMcoefsDF[, 4])
+    EC50REF <- as.numeric(URMcoefsDF[,5])
     # EC50REF <- EC50REF[!EC50REF %in% boxplot.stats(EC50REF)$out]
-      UasREF <- as.numeric(URMcoefsDF[, 5])
+    UasREF <- as.numeric(URMcoefsDF[,4])
     # UasREF <- UasREF[!UasREF %in% boxplot.stats(UasREF)$out]
     LasREF <- as.numeric(URMcoefsDF[,2])
     # LasREF <- LasREF[!LasREF %in% boxplot.stats(LasREF)$out]
@@ -2165,24 +2180,25 @@ server <- function(input, output, session) {
     # Dat$CalcPot <- CalcPot
     # 
     #### sigmoid plots ----
+    
     Slope <- as.numeric(URMcoefsDF[1,3])
-      # if (Slope > 0) {
+    if (Slope > 0) {
-      #   x_UA <- max(X); x_LA <- min(X)
+      x_UA <- max(X); x_LA <- min(X)
-      # } else { x_UA <- min(X); x_LA <- max(X) }
+    } else { x_UA <- min(X); x_LA <- max(X) }
-      #
+    
-      # p1 <- ggplot(SIGrefDF, aes(x_X, y=sigRef, col=as.factor(Prod))) +
+    p1 <- ggplot(SIGrefDF, aes(x=X, y=sigRef, col=as.factor(Sheet))) +
-      #   geom_line() +
+      geom_line() +
-      #   annotate("text", label="x", x=x_UA, y=UasREF, alpha=0.2) +
+      annotate("text", label="x", x=x_UA, y=UasREF, alpha=0.2) +
-      #   annotate("text", label="o", x=x_LA, y=LasREF, alpha=0.2) +
+      annotate("text", label="o", x=x_LA, y=LasREF, alpha=0.2) +
-      #   geom_vline(xintercept = EC50REF, alpha = 0.2) +
+      geom_vline(xintercept = EC50REF, alpha = 0.2) +
-      #   xlab("dilutions") +
+      xlab("dilutions") +
-      #   ggtitle("Plot of all calculated reference fits (unrestricted model, in gray vertical lines: EC50)") +
+      ggtitle("Plot of all calculated reference fits (unrestricted model, in gray vertical lines: EC50)") +
-      #   theme_bw() +
+      theme_bw() +
-      #   theme(axis.text = element_text(face = "bold", size = 15),
+      theme(axis.text = element_text(face = "bold", size = 15),
-      #         plot.title = element_text(size = 15, face = "bold"))
+            plot.title = element_text(size = 15, face = "bold"))
-      #
+
-      # output$sigPlotREF <- renderPlot({ p1 })
+    output$sigPlotREF <- renderPlot({ p1 })
-      #
+
     # PLOTS$sigPlotREF <- p1
     # 
     # p2 <- ggplot(SIGtestDF, aes(x_X, y=sigTest, col=as.factor(Prod))) +
@@ -2201,195 +2217,174 @@ server <- function(input, output, session) {
     # PLOTS$sigPlotTEST <- p2
     
     
-      dils <- tab$log_dose
+    # dils <- tab$log_dose
-      min_y <- min(tab[, 1:3])
+    # min_y <- min(tab[, 1:3])
-      max_y <- max(tab[, 1:3])
+    # max_y <- max(tab[, 1:3])
-
+    # 
-      if (input$fixupper) {
+    # if (input$fixupper) {
-        dils_av <- dils - max(dils)
+    #   dils_av <- dils - max(dils)
-        dils_av_ <- dils_av * (input$dilslider / 100 + 1)
+    #   dils_av_ <- dils_av * (input$dilslider / 100 + 1)
-        dils2 <- round(dils_av_ + max(dils), 4)
+    #   dils2 <- round(dils_av_ + max(dils), 4)
-        dilfactors <- 1 / exp(dils2 - lag(dils2))
+    #   dilfactors <- 1 / exp(dils2 - lag(dils2))
-      } else {
+    # } else {
-        if (!is.null(Dat$cfordils)) {
+    #   if (!is.null(Dat$cfordils)) {
-          av <- Dat$cfordils
+    #     av <- Dat$cfordils
-        } else {
+    #   } else {
-          av <- (min(dils) + max(dils)) / 2
+    #     av <- (min(dils) + max(dils)) / 2
-        }
+    #   }
-        dils_av <- dils - av
+    #   dils_av <- dils - av
-        dils_avsc <- dils_av * (input$dilslider / 100 + 1)
+    #   dils_avsc <- dils_av * (input$dilslider / 100 + 1)
-        dils2 <- dils_avsc + av
+    #   dils2 <- dils_avsc + av
-        dilfactors <- 1 / exp(dils2 - lag(dils2))
+    #   dilfactors <- 1 / exp(dils2 - lag(dils2))
-      }
+    # }
-    } # for N_WS
  
     
-    Dat$newDils <- dils2
    
-    sigmoid <- sigmoid()
     
-    BPs <- Dat$bendpoints
+    #Dat$newDils <- dils2
-    EC50REF <- (BPs[2] + BPs[1]) / 2
-    Einh <- abs((BPs[2] - BPs[1]) / 5)
-    asyml <- EC50REF - 2 * (EC50REF - BPs[1])
-    asymu <- EC50REF + 2 * (EC50REF - BPs[1])
 
-    det_sig <- Dat$coeffs_UN
 
-    if (is.null(Dat$coeffs_UN)) {
+    #sigmoid <- sigmoid()
-      SAMPLE50 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] + 0.693147) - dils2)))
+
-      SAMPLE200 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] - 0.693147) - dils2)))
+    # BPs <- Dat$bendpoints
-      Xbend50l <- sigmoid[7] + 0.693147 - 1.5434 / sigmoid[5]
+    # EC50REF <- (BPs[2] + BPs[1]) / 2
-      Xbend200l <- sigmoid[7] - 0.693147 - 1.5434 / sigmoid[5]
+    # Einh <- abs((BPs[2] - BPs[1]) / 5)
-      Xbend50u <- sigmoid[7] + 0.693147 + 1.5434 / sigmoid[5]
+    # asyml <- EC50REF - 2 * (EC50REF - BPs[1])
-      Xbend200u <- sigmoid[7] - 0.693147 + 1.5434 / sigmoid[5]
+    # asymu <- EC50REF + 2 * (EC50REF - BPs[1])
-      Xbend50 <- max(Xbend50l, Xbend50u)
+    # 
-      Xbend200 <- min(Xbend200l, Xbend200u)
+    # det_sig <- Dat$coeffs_UN
-      dummy <- plot_f(tab)
+    # 
-    } else {
+    # if (is.null(Dat$coeffs_UN)) {
-      SAMPLE50 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] + 0.693147 - dils2)))
+    #   SAMPLE50 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] + 0.693147) - dils2)))
-      SAMPLE200 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] - 0.693147 - dils2)))
+    #   SAMPLE200 <- sigmoid[1] + (sigmoid[3] - sigmoid[1]) / (1 + exp(sigmoid[5] * ((sigmoid[7] - 0.693147) - dils2)))
-      Xbend50l <- det_sig[7] + 0.693147 - 1.5434 / det_sig[1]
+    #   Xbend50l <- sigmoid[7] + 0.693147 - 1.5434 / sigmoid[5]
-      Xbend200l <- det_sig[7] - 0.693147 - 1.5434 / det_sig[1]
+    #   Xbend200l <- sigmoid[7] - 0.693147 - 1.5434 / sigmoid[5]
-      Xbend50u <- det_sig[7] + 0.693147 + 1.5434 / det_sig[1]
+    #   Xbend50u <- sigmoid[7] + 0.693147 + 1.5434 / sigmoid[5]
-      Xbend200u <- det_sig[7] - 0.693147 + 1.5434 / det_sig[1]
+    #   Xbend200u <- sigmoid[7] - 0.693147 + 1.5434 / sigmoid[5]
-      Xbend50 <- max(Xbend50l, Xbend50u)
+    #   Xbend50 <- max(Xbend50l, Xbend50u)
-      Xbend200 <- min(Xbend200l, Xbend200u)
+    #   Xbend200 <- min(Xbend200l, Xbend200u)
-      dummy <- plot_f(tab)
+    #   dummy <- plot_f(tab)
+    # } else {
+    #   SAMPLE50 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] + 0.693147 - dils2)))
+    #   SAMPLE200 <- det_sig[3] + (det_sig[5] - det_sig[3]) / (1 + exp(det_sig[1] * (det_sig[7] - 0.693147 - dils2)))
+    #   Xbend50l <- det_sig[7] + 0.693147 - 1.5434 / det_sig[1]
+    #   Xbend200l <- det_sig[7] - 0.693147 - 1.5434 / det_sig[1]
+    #   Xbend50u <- det_sig[7] + 0.693147 + 1.5434 / det_sig[1]
+    #   Xbend200u <- det_sig[7] - 0.693147 + 1.5434 / det_sig[1]
+    #   Xbend50 <- max(Xbend50l, Xbend50u)
+    #   Xbend200 <- min(Xbend200l, Xbend200u)
+    #   dummy <- plot_f(tab)
+    # }
+    # 
+    # 
+    # pl_df <- cbind(dils2, SAMPLE50, SAMPLE200)
+    # 
+    # 
+    # output$adjlogdil <- renderTable({
+    #   adjlogdilfactors <- round(dilfactors, 3)
+    #   adjlogdils <- round(dils2, 3)
+    #   adjdils <- round(exp(dils2), 3)
+    #   DilsTable <- data.frame(
+    #     "adjusted ln(dilutions)" = adjlogdils,
+    #     "adjusted ln_dilution_factors" = adjlogdilfactors,
+    #     "adjusted dilutions" = adjdils
+    #   )
+    #   DilsTable
+    # })
+
+    # if (!is.null(Dat$p2)) {
+    #   p2 <- Dat$p2
+    #   p_dil <- p2 +
+    #     annotate("pointrange", x = dils2, y = rep(min_y, length(dils2)), xmin = min(dils2), xmax = max(dils2)) +
+    #     annotate("text", x = dils2, y = rep(min_y + (max_y - min_y) * 0.05, length(dils2)), label = as.character(round(dils2, 3))) +
+    #     annotate("text",
+    #       x = dils2[-1] + (max(dils2) - min(dils2)) * 0.05,
+    #       y = rep(min_y + (max_y - min_y) * 0.1, length(dils2[-1])),
+    #       label = as.character(round(dilfactors[-1], 3))
+    #     ) +
+    #     geom_line(
+    #       data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE50), color = "grey15", linetype = 2,
+    #       inherit.aes = F
+    #     ) +
+    #     geom_line(
+    #       data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE200), color = "grey15", linetype = 2,
+    #       inherit.aes = F
+    #     ) +
+    #     geom_vline(xintercept = c(Xbend50, Xbend200), col = "grey15", linetype = 2) +
+    #     {
+    #       if (input$scenario == "scenario 6") {
+    #         annotate("pointrange",
+    #           x = optdils2, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils2)),
+    #           xmin = min(optdils2), xmax = max(optdils2), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "scenario 6") {
+    #         annotate("text",
+    #           x = optdils2, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils2)),
+    #           label = as.character(round(optdils2, 3)), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "scenario 2") {
+    #         annotate("pointrange",
+    #           x = optdils, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils)),
+    #           xmin = min(optdils), xmax = max(optdils), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "scenario 2") {
+    #         annotate("text",
+    #           x = optdils, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils)),
+    #           label = as.character(round(optdils, 3)), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "scenario 3") {
+    #         annotate("pointrange",
+    #           x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils_3)),
+    #           xmin = min(optdils_3), xmax = max(optdils_3), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "scenario 3") {
+    #         annotate("text",
+    #           x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils_3)),
+    #           label = as.character(round(optdils_3, 3)), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "steep slope") {
+    #         annotate("pointrange",
+    #           x = optdils3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils3)),
+    #           xmin = min(optdils3), xmax = max(optdils3), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     {
+    #       if (input$scenario == "steep slope") {
+    #         annotate("text",
+    #           x = optdils3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils3)),
+    #           label = as.character(round(optdils3, 3)), color = "seagreen"
+    #         )
+    #       }
+    #     } +
+    #     annotate("text",
+    #       x = optdils[1], y = (max_y + min_y) * 0.5,
+    #       label = paste("in green: optimal \n dilutions acc. to Whitepaper\n", input$scenario), color = "seagreen",
+    #       size = 14 / .pt, fontface = "bold"
+    #     )
+    # }
+    #print(p_dil)
+   # }
     }
 
-
-    pl_df <- cbind(dils2, SAMPLE50, SAMPLE200)
-
-    # scenario2
-    eqSpac <- abs((BPs[1] - BPs[2]) / 5)
-    optdils <- c((asyml + BPs[1]) / 2, BPs[1], BPs[1] + 1 * eqSpac, BPs[1] + 2 * eqSpac, BPs[1] + 3 * eqSpac, BPs[1] + 4 * eqSpac, BPs[2], (asymu + BPs[2]) / 2)
-    # scenario 3
-    eqSpac_3 <- abs((BPs[1] - BPs[2]) / 3)
-    optdils_3 <- c(BPs[1] - 2 * eqSpac_3, BPs[1] - eqSpac_3, BPs[1], BPs[1] + 1 * eqSpac_3, BPs[1] + 2 * eqSpac_3, BPs[2], BPs[2] + eqSpac_3, BPs[2] + 2 * eqSpac_3)
-    # scenario 6
-    Einh2 <- abs(((BPs[2] - BPs[1]) * 0.7) / 5)
-    eqSpac2 <- (2 * 0.7 / Einh) / 3
-    optdils2 <- c((asyml + BPs[1]) / 2, BPs[1], EC50REF - 1.5 * Einh2, EC50REF - 0.5 * Einh2, EC50REF + 0.5 * Einh2, EC50REF + 1.5 * Einh2, BPs[2], (asymu + BPs[2]) / 2)
-    # steep slope
-    eqSpac3 <- (abs(Xbend200 - Xbend50)) / 5
-    optdils3 <- c(Xbend200 - eqSpac3, Xbend200, Xbend200 + 1 * eqSpac3, Xbend200 + 2 * eqSpac3, Xbend200 + 3 * eqSpac3, Xbend200 + 4 * eqSpac3, Xbend50, Xbend50 + eqSpac3)
-
-    output$extremebps <- renderTable({
-      ExtremeBPs <- c(Xbend50, Xbend200)
-      DF2 <- data.frame(sample = c("50% sample (right)", "200% sample (left)"), Extreme_BPs = ExtremeBPs)
-      DF2
-    })
-
-    optD <- data.frame(cbind(optdils, optdils_3, optdils2, optdils3))
-    colnames(optD) <- c("scenario2", "scenario3", "scenario6", "steep slope")
-
-    output$optimalDils <- renderTable({
-      optD
-    })
-
-    output$adjlogdil <- renderTable({
-      adjlogdilfactors <- round(dilfactors, 3)
-      adjlogdils <- round(dils2, 3)
-      adjdils <- round(exp(dils2), 3)
-      DilsTable <- data.frame(
-        "adjusted ln(dilutions)" = adjlogdils,
-        "adjusted ln_dilution_factors" = adjlogdilfactors,
-        "adjusted dilutions" = adjdils
-      )
-      DilsTable
-    })
-
-    if (!is.null(Dat$p2)) {
-      p2 <- Dat$p2
-      p_dil <- p2 +
-        annotate("pointrange", x = dils2, y = rep(min_y, length(dils2)), xmin = min(dils2), xmax = max(dils2)) +
-        annotate("text", x = dils2, y = rep(min_y + (max_y - min_y) * 0.05, length(dils2)), label = as.character(round(dils2, 3))) +
-        annotate("text",
-          x = dils2[-1] + (max(dils2) - min(dils2)) * 0.05,
-          y = rep(min_y + (max_y - min_y) * 0.1, length(dils2[-1])),
-          label = as.character(round(dilfactors[-1], 3))
-        ) +
-        geom_line(
-          data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE50), color = "grey15", linetype = 2,
-          inherit.aes = FALSE
-        ) +
-        geom_line(
-          data = as.data.frame(pl_df), aes(x = dils2, y = SAMPLE200), color = "grey15", linetype = 2,
-          inherit.aes = FALSE
-        ) +
-        geom_vline(xintercept = c(Xbend50, Xbend200), col = "grey15", linetype = 2) +
-        {
-          if (input$scenario == "scenario 6") {
-            annotate("pointrange",
-              x = optdils2, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils2)),
-              xmin = min(optdils2), xmax = max(optdils2), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "scenario 6") {
-            annotate("text",
-              x = optdils2, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils2)),
-              label = as.character(round(optdils2, 3)), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "scenario 2") {
-            annotate("pointrange",
-              x = optdils, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils)),
-              xmin = min(optdils), xmax = max(optdils), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "scenario 2") {
-            annotate("text",
-              x = optdils, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils)),
-              label = as.character(round(optdils, 3)), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "scenario 3") {
-            annotate("pointrange",
-              x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils_3)),
-              xmin = min(optdils_3), xmax = max(optdils_3), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "scenario 3") {
-            annotate("text",
-              x = optdils_3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils_3)),
-              label = as.character(round(optdils_3, 3)), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "steep slope") {
-            annotate("pointrange",
-              x = optdils3, y = rep(min_y + (max_y - min_y) * 0.2, length(optdils3)),
-              xmin = min(optdils3), xmax = max(optdils3), color = "seagreen"
-            )
-          }
-        } +
-        {
-          if (input$scenario == "steep slope") {
-            annotate("text",
-              x = optdils3, y = rep(min_y + (max_y - min_y) * 0.25, length(optdils3)),
-              label = as.character(round(optdils3, 3)), color = "seagreen"
-            )
-          }
-        } +
-        annotate("text",
-          x = optdils[1], y = (max_y + min_y) * 0.5,
-          label = paste("in green: optimal \n dilutions acc. to Whitepaper\n", input$scenario), color = "seagreen",
-          size = 14 / .pt, fontface = "bold"
-        )
-    }
-    print(p_dil)
   })
 
   #### Dilutions CI table ----
@@ -2642,21 +2637,28 @@ server <- function(input, output, session) {
 
   #### download XL 4PL report----
 
-  observe({
+  observeEvent(input$btn, {
-    if (is.null(Dat$FITsFlag)) {
-      return(NULL)
-    }
     if(!Dat$FITsFlag) {
-      browser()
+      runjs("$('#downloadXLReport')[0].click();")
+    } else {
+      showModal(modalDialog(
+        title = "No 4PL model to Download",
+        "Please select other data before download.",
+        easyClose = TRUE,
+        footer = NULL
+      ))
+    }
+  })
+  
     output$downloadXLReport <- downloadHandler(
       filename = paste0("Report_4PLEvaluation", Dat$RepIdentifier, ".pdf"),
       content = function(file) {
         tpdr <- tempdir()
         tempReport <- file.path(tpdr, "Doc_BioassayReport.Rmd")
-          file.copy("Doc_BioassayReport.Rmd", tempReport, overwrite = TRUE)
+        file.copy("Doc_BioassayReport.Rmd", tempReport, overwrite = T)
   
         tempReportc <- file.path(tpdr, "logov2.png")
-          file.copy("logov2.png", tempReportc, overwrite = TRUE)
+        file.copy("logov2.png", tempReportc, overwrite = T)
   
         rmarkdown::render(tempReport,
           output_file = file,
@@ -2672,8 +2674,8 @@ server <- function(input, output, session) {
         )
       }
     )
-    }
+ 
-  })
+
 
   #### download XL Lin report----