Adjust indent level and enforce 80-character line limit

3 files changed, 476 insertions, 366 deletions

diff --git a/R/app.R b/R/app.R
index 1bf3e93..feb052f 100644
--- a/R/app.R
+++ b/R/app.R
@@ -2,8 +2,8 @@
 #'
 #' @export
 app <- function() {
-    if (!requireNamespace("shiny", quietly=TRUE))
-        stop("The package 'shiny' must be installed to launch the Rnaught web application.")
+  if (!requireNamespace("shiny", quietly = TRUE))
+    stop("The package 'shiny' must be installed to launch the Rnaught web application.")
 
-    shiny::shinyApp(ui(), server)
+  shiny::shinyApp(ui, server)
 }
diff --git a/R/server.R b/R/server.R
index e8d2970..ed5ecd7 100644
--- a/R/server.R
+++ b/R/server.R
@@ -1,263 +1,312 @@
 #' @importFrom methods is
 #' @importFrom utils read.csv write.csv
 server <- function(input, output) {
-    reactive <- shiny::reactiveValues(
-        data_table=data.frame(Name=character(0), `Reporting Frequency`=character(0), `Case Counts`=numeric(0), check.names=FALSE),
-        est_table=data.frame(Dataset=character(0)),
-        estimators=list()
-    )
-
-    # Validate and add datasets when button is clicked.
-    # Also evaluate the new datasets on existing estimators.
-    shiny::observeEvent(input$addData, {
-        # Option 1: Manual entry.
-        if (input$dataInputMethod == 1) {
-            checks_passed <- TRUE
-
-            # Ensure the dataset name is not blank.
-            if (grepl("^\\s*$", input$dataName)) {
-                output$dataNameWarn <- shiny::renderText("Error: The dataset name cannot be blank.")
-                checks_passed <- FALSE
-            }
-            # Ensure the dataset name is not a duplicate.
-            else if (input$dataName %in% reactive$data_table[,1]) {
-                output$dataNameWarn <- shiny::renderText("Error: There is already a dataset with the specified name.")
-                checks_passed <- FALSE
-            }
-            else
-                output$dataNameWarn <- shiny::renderText("")
-
-            # Ensure the case counts consist only of non-negative integers, separated by commas.
-            counts <- as.numeric(unlist(strsplit(input$dataCounts, split=",")))
-            if (any(is.na(counts)) || any(counts <= 0) || any(counts %% 1 != 0)) {
-                output$dataCountsWarn <- shiny::renderText("Error: The list of case counts should only contain non-negative integers, separated by commas.")
-                checks_passed <- FALSE
-            }
-            # Ensure the case counts contain at least two entries.
-            else if (length(counts) < 2) {
-                output$dataCountsWarn <- shiny::renderText("Error: The list of case counts should contain at least two entries.")
-                checks_passed <- FALSE
-            }
-            else
-                output$dataCountsWarn <- shiny::renderText("")
+  reactive <- shiny::reactiveValues(
+    data_table = data.frame(Name = character(0),
+                            `Reporting Frequency` = character(0),
+                            `Case Counts` = numeric(0), check.names = FALSE),
+    est_table = data.frame(Dataset = character(0)),
+    estimators = list()
+  )
+
+  # Validate and add datasets when button is clicked.
+  # Also evaluate the new datasets on existing estimators.
+  shiny::observeEvent(input$addData, {
+    # Option 1: Manual entry.
+    if (input$dataInputMethod == 1) {
+      checks_passed <- TRUE
+
+      # Ensure the dataset name is not blank.
+      if (grepl("^\\s*$", input$dataName)) {
+        output$dataNameWarn <- shiny::renderText(
+          "Error: The dataset name cannot be blank.")
+        checks_passed <- FALSE
+      }
+      # Ensure the dataset name is not a duplicate.
+      else if (input$dataName %in% reactive$data_table[,1]) {
+        output$dataNameWarn <- shiny::renderText(
+          "Error: There is already a dataset with the specified name.")
+        checks_passed <- FALSE
+      }
+      else
+        output$dataNameWarn <- shiny::renderText("")
+
+      # Ensure the case counts consist only of positive integers, separated by
+      # commas.
+      counts <- as.numeric(unlist(strsplit(input$dataCounts, split = ",")))
+      if (any(is.na(counts)) || any(counts <= 0) || any(counts %% 1 != 0)) {
+        output$dataCountsWarn <- shiny::renderText("Error: The list of case
+          counts should only contain positive integers, separated by commas.")
+        checks_passed <- FALSE
+      }
+      # Ensure the case counts contain at least two entries.
+      else if (length(counts) < 2) {
+        output$dataCountsWarn <- shiny::renderText(
+          "Error: The list of case counts should contain at least two entries.")
+        checks_passed <- FALSE
+      }
+      else
+        output$dataCountsWarn <- shiny::renderText("")
       
-            if (checks_passed)
-                d <- data.frame(input$dataName, input$dataUnits, t(counts))
-        }
+      if (checks_passed)
+        d <- data.frame(input$dataName, input$dataUnits, t(counts))
+    }
 
-        else {
-            checks_passed <- FALSE
-
-            # Option 2: Upload .csv
-            if (input$dataInputMethod == 2)
-                d <- try(read.csv(input$dataUpload$datapath, header=FALSE))
-            # Option 3: Paste .csv
-            else
-                d <- try(read.csv(text=input$dataPaste, header=FALSE))
-
-            if (is(d, "try-error"))
-                output$dataCSVWarn <- shiny::renderText("Error reading file.")
-            else if (ncol(d) < 4 || anyNA(d[,1]) || anyNA(sapply(d[,3:4], as.numeric)) || !all(trimws(d[,2]) %in% c("Daily", "Weekly")))
-                output$dataCSVWarn <- shiny::renderText("Error: The provided .csv file does not match the required format.")
-            else if (length(intersect(reactive$data_table[,1], d[,1])) > 0)
-                output$dataCSVWarn <- shiny::renderText("Error: The provided .csv file contains dataset names which already exist.")
-            else if (length(unique(d[,1])) != length(d[,1]))
-                output$dataCSVWarn <- shiny::renderText("Error: The provided .csv file contains duplicate dataset names.")
-            else {
-                output$dataCSVWarn <- shiny::renderText("")
-                checks_passed <- TRUE
-            }
-        }
+    else {
+      checks_passed <- FALSE
 
-        if (checks_passed) {
-            d[,3:ncol(d)] <- apply(d[,3:ncol(d)], 2, as.numeric)
-            d[,3] <- data.frame(I(lapply(split(d[,3:ncol(d)], 1:nrow(d)), function(x) x[!is.na(x)])))
-            d <- d[,1:3]
-            d[,2] <- trimws(d[,2])
-            colnames(d) <- c("Name", "Reporting Frequency", "Case Counts")
-            reactive$data_table <- rbind(reactive$data_table, d)
-            reactive$est_table <- update_est_row(input, output, d, reactive$estimators, reactive$est_table)
-        }
-    })
-  
-    output$dataTable <- shiny::renderDataTable(reactive$data_table, escape=FALSE)
-    output$estTable <- shiny::renderDataTable(reactive$est_table, escape=FALSE)
+      # Option 2: Upload .csv
+      if (input$dataInputMethod == 2)
+        d <- try(read.csv(input$dataUpload$datapath, header = FALSE))
+      # Option 3: Paste .csv
+      else
+        d <- try(read.csv(text = input$dataPaste, header = FALSE))
+
+      if (is(d, "try-error"))
+        output$dataCSVWarn <- shiny::renderText("Error reading file.")
+      else if (ncol(d) < 4 || anyNA(d[,1]) || anyNA(sapply(d[,3:4], as.numeric))
+               || !all(trimws(d[,2]) %in% c("Daily", "Weekly")))
+        output$dataCSVWarn <- shiny::renderText(
+          "Error: The provided .csv file does not match the required format.")
+      else if (length(intersect(reactive$data_table[,1], d[,1])) > 0)
+        output$dataCSVWarn <- shiny::renderText("Error: The provided .csv file
+          contains dataset names which already exist.")
+      else if (length(unique(d[,1])) != length(d[,1]))
+        output$dataCSVWarn <- shiny::renderText(
+          "Error: The provided .csv file contains duplicate dataset names.")
+      else {
+        output$dataCSVWarn <- shiny::renderText("")
+        checks_passed <- TRUE
+      }
+    }
+
+    if (checks_passed) {
+      d[,3:ncol(d)] <- apply(d[,3:ncol(d)], 2, as.numeric)
+      d[,3] <- data.frame(I(lapply(split(d[,3:ncol(d)], 1:nrow(d)),
+                                   function(x) x[!is.na(x)])))
+      d <- d[,1:3]
+      d[,2] <- trimws(d[,2])
+      colnames(d) <- c("Name", "Reporting Frequency", "Case Counts")
+      reactive$data_table <- rbind(reactive$data_table, d)
+      reactive$est_table <- update_est_row(input, output, d,
+        reactive$estimators, reactive$est_table)
+    }
+  })
   
-    # Download table of estimates as a .csv file.
-    output$downloadEst <- shiny::downloadHandler(
-        filename=function() { paste0("Rnaught-", Sys.Date(), ".csv") },
-        content=function(file) { write.csv(reactive$est_table, file) }
-    )
-
-    shiny::observeEvent(input$addWP, {
-        if (input$serialWPKnown == 1) {
-            serial <- validate_serial(input, output, "serialWPInput", "serialWPWarn")
-            if (!is.na(serial)) {
-                reactive$estimators[[length(reactive$estimators)+1]] <- list(method="WP", mu=serial, search=list(B=100, shape.max=10, scale.max=10), mu_units=input$serialWPUnits)
-                reactive$est_table <- update_est_col(input, output, reactive$data_table, reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
-            }
-        }
-        else {
-            checks_passed <- TRUE
-
-            grid_length <- as.numeric(input$gridLengthInput)
-            max_shape <- as.numeric(input$gridShapeInput)
-            max_scale <- as.numeric(input$gridScaleInput)
-
-            if (is.na(grid_length) || grid_length <= 0 || grid_length %% 1 != 0) {
-                output$gridLengthWarn <- shiny::renderText("Error: The grid size must be a positive integer.")
-                output$gridShapeWarn <- shiny::renderText("")
-                output$gridScaleWarn <- shiny::renderText("")
-                checks_passed <- FALSE
-            }
-            else {
-                output$gridLengthWarn <- shiny::renderText("")
-
-            if (is.na(max_shape) || max_shape < 1 / grid_length) {
-                output$gridShapeWarn <- shiny::renderText("Error: The maximum shape must be at least the reciprocal of the grid length.")
-                checks_passed <- FALSE
-            }
-            else
-                output$gridShapeWarn <- shiny::renderText("")
-
-            if (is.na(max_scale) || max_scale < 1 / grid_length) {
-                output$gridShapeWarn <- shiny::renderText("Error: The maximum scale must be at least the reciprocal of the grid length.")
-                checks_passed <- FALSE
-            }
-            else
-                output$gridScaleWarn <- shiny::renderText("")
-            }
-
-            if (checks_passed) {
-                reactive$estimators[[length(reactive$estimators)+1]] <- list(method="WP", mu=NA, search=list(B=grid_length, shape.max=max_shape, scale.max=max_scale), mu_units=input$serialWPUnits)
-                reactive$est_table <- update_est_col(input, output, reactive$data_table, reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
-            }  
-        }
-    })
-
-    shiny::observeEvent(input$addseqB, {
-        serial <- validate_serial(input, output, "serialseqBInput", "serialseqBWarn")
-        checks_passed <- !is.na(serial)
-    
-        kappa <- as.numeric(input$kappaInput)
-        if (is.na(kappa) || kappa <= 0) {
-            output$kappaWarn <- shiny::renderText("Error: The maximum value must be a positive number.")
-            checks_passed <- FALSE
+  output$dataTable <- shiny::renderDataTable(reactive$data_table,
+                                             escape = FALSE)
+  output$estTable <- shiny::renderDataTable(reactive$est_table,
+                                            escape = FALSE)
+
+  # Download table of estimates as a .csv file.
+  output$downloadEst <- shiny::downloadHandler(
+    filename = function() { paste0("Rnaught-", Sys.Date(), ".csv") },
+    content = function(file) { write.csv(reactive$est_table, file) }
+  )
+
+  shiny::observeEvent(input$addWP, {
+    if (input$serialWPKnown == 1) {
+      serial <- validate_serial(input, output, "serialWPInput", "serialWPWarn")
+      if (!is.na(serial)) {
+        reactive$estimators[[length(reactive$estimators) + 1]] <- list(
+          method = "WP", mu = serial, mu_units = input$serialWPUnits,
+          search = list(B = 100, shape.max = 10, scale.max = 10))
+        reactive$est_table <- update_est_col(input, output, reactive$data_table,
+          reactive$estimators[[length(reactive$estimators)]],
+          reactive$est_table)
+      }
+    }
+    else {
+      checks_passed <- TRUE
+
+      grid_length <- as.numeric(input$gridLengthInput)
+      max_shape <- as.numeric(input$gridShapeInput)
+      max_scale <- as.numeric(input$gridScaleInput)
+
+      if (is.na(grid_length) || grid_length <= 0 || grid_length %% 1 != 0) {
+        output$gridLengthWarn <- shiny::renderText(
+          "Error: The grid size must be a positive integer.")
+        output$gridShapeWarn <- shiny::renderText("")
+        output$gridScaleWarn <- shiny::renderText("")
+        checks_passed <- FALSE
+      }
+      else {
+        output$gridLengthWarn <- shiny::renderText("")
+
+        if (is.na(max_shape) || max_shape < 1 / grid_length) {
+          output$gridShapeWarn <- shiny::renderText("Error: The maximum shape
+            must be at least the reciprocal of the grid length.")
+          checks_passed <- FALSE
         }
         else
-            output$kappaWarn <- shiny::renderText("")
-    
-        if (checks_passed) {
-            reactive$estimators[[length(reactive$estimators)+1]] <- list(method="seqB", mu=serial, kappa=kappa, mu_units=input$serialseqBUnits)
-            reactive$est_table <- update_est_col(input, output, reactive$data_table, reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
-        }
-    })
+          output$gridShapeWarn <- shiny::renderText("")
 
-    shiny::observeEvent(input$addID, {
-        serial <- validate_serial(input, output, "serialIDInput", "serialIDWarn")
-        if (!is.na(serial)) {
-            reactive$estimators[[length(reactive$estimators)+1]] <- list(method="ID", mu=serial, mu_units=input$serialIDUnits)
-            reactive$est_table <- update_est_col(input, output, reactive$data_table, reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
+        if (is.na(max_scale) || max_scale < 1 / grid_length) {
+          output$gridShapeWarn <- shiny::renderText("Error: The maximum scale
+            must be at least the reciprocal of the grid length.")
+          checks_passed <- FALSE
         }
-    })
+        else
+          output$gridScaleWarn <- shiny::renderText("")
+      }
 
-    shiny::observeEvent(input$addIDEA, {
-        serial <- validate_serial(input, output, "serialIDEAInput", "serialIDEAWarn")
-        if (!is.na(serial)) {
-            reactive$estimators[[length(reactive$estimators)+1]] <- list(method="IDEA", mu=serial, mu_units=input$serialIDEAUnits)
-            reactive$est_table <- update_est_col(input, output, reactive$data_table, reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
-        }
-    })
-}
+      if (checks_passed) {
+        reactive$estimators[[length(reactive$estimators) + 1]] <- list(
+          method = "WP", mu = NA, mu_units = input$serialWPUnits,
+          search = list(B = grid_length, shape.max = max_shape,
+                        scale.max = max_scale))
+        reactive$est_table <- update_est_col(input, output, reactive$data_table,
+          reactive$estimators[[length(reactive$estimators)]],
+          reactive$est_table)
+      }  
+    }
+  })
 
-validate_serial <- function(input, output, serialInputId, serialWarnId) {
-    serial <- as.numeric(input[[serialInputId]])
-    if (is.na(serial) || serial <= 0) {
-        output[[serialWarnId]] <- shiny::renderText("Error: The mean serial interval should be a non-negative number.")
-        serial <- NA
+  shiny::observeEvent(input$addseqB, {
+    serial <- validate_serial(input, output, "serialseqBInput",
+                              "serialseqBWarn")
+    checks_passed <- !is.na(serial)
+
+    kappa <- as.numeric(input$kappaInput)
+    if (is.na(kappa) || kappa <= 0) {
+      output$kappaWarn <- shiny::renderText(
+        "Error: The maximum value must be a positive number.")
+      checks_passed <- FALSE
     }
     else
-        output[[serialWarnId]] <- shiny::renderText("") # Clear warning text.
-    
-    return(serial)
+      output$kappaWarn <- shiny::renderText("")
+
+    if (checks_passed) {
+      reactive$estimators[[length(reactive$estimators) + 1]] <- list(
+        method="seqB", mu = serial, kappa = kappa,
+        mu_units = input$serialseqBUnits)
+      reactive$est_table <- update_est_col(input, output, reactive$data_table,
+        reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
+    }
+  })
+
+  shiny::observeEvent(input$addID, {
+    serial <- validate_serial(input, output, "serialIDInput", "serialIDWarn")
+    if (!is.na(serial)) {
+      reactive$estimators[[length(reactive$estimators) + 1]] <- list(
+        method = "ID", mu = serial, mu_units = input$serialIDUnits)
+      reactive$est_table <- update_est_col(input, output, reactive$data_table,
+        reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
+    }
+  })
+
+  shiny::observeEvent(input$addIDEA, {
+    serial <- validate_serial(input, output, "serialIDEAInput",
+                              "serialIDEAWarn")
+    if (!is.na(serial)) {
+      reactive$estimators[[length(reactive$estimators) + 1]] <- list(
+        method = "IDEA", mu = serial, mu_units = input$serialIDEAUnits)
+      reactive$est_table <- update_est_col(input, output, reactive$data_table,
+        reactive$estimators[[length(reactive$estimators)]], reactive$est_table)
+    }
+  })
 }
 
+validate_serial <- function(input, output, serialInputId, serialWarnId) {
+  serial <- as.numeric(input[[serialInputId]])
+  if (is.na(serial) || serial <= 0) {
+    output[[serialWarnId]] <- shiny::renderText(
+      "Error: The mean serial interval should be a positive number.")
+    serial <- NA
+  }
+  else
+    output[[serialWarnId]] <- shiny::renderText("") # Clear warning text.
+
+  return(serial)
+}
+
+# Create a new column in the estimator table when a new estimator is added.
 update_est_col <- function(input, output, datasets, estimator, est_table) {
-    if (nrow(datasets) == 0)
-        new_est_table <- data.frame(matrix(nrow=0, ncol=ncol(est_table)+1))
-    else {
-        estimates <- rep(NA, nrow(datasets))
+  if (nrow(datasets) == 0)
+    new_est_table <- data.frame(matrix(nrow = 0, ncol = ncol(est_table) + 1))
+  else {
+    estimates <- rep(NA, nrow(datasets))
 
     for (row in 1:nrow(datasets))
-        estimates[row] <- eval_estimator(input, output, estimator, datasets[row,])
+      estimates[row] <- eval_estimator(input, output, estimator, datasets[row,])
 
-        if (nrow(est_table) == 0)
-            new_est_table <- cbind(datasets[,1], estimates)
-        else
-            new_est_table <- cbind(est_table, estimates)
-    }
+      if (nrow(est_table) == 0)
+        new_est_table <- cbind(datasets[,1], estimates)
+      else
+        new_est_table <- cbind(est_table, estimates)
+  }
 
-    colnames(new_est_table) <- c(colnames(est_table), shiny::HTML(paste0(estimator$method, "<br/>(&mu; = ", estimator$mu, " ", tolower(estimator$mu_units), ")")))
-    return(new_est_table)
+  colnames(new_est_table) <- c(colnames(est_table), shiny::HTML(
+    paste0(estimator$method, "<br/>(&mu; = ", estimator$mu, " ",
+           tolower(estimator$mu_units), ")")))
+
+  return(new_est_table)
 }
-  
+
+# Create a new row in the estimator table when new datasets are added.
 update_est_row <- function(input, output, datasets, estimators, est_table) {
-    if (length(estimators) == 0) {
-        if (nrow(est_table) == 0)
-            new_est_table <- data.frame(datasets[,1])
-        else
-            new_est_table <- data.frame(c(est_table[,1], datasets[,1]))
+  if (length(estimators) == 0) {
+    if (nrow(est_table) == 0)
+      new_est_table <- data.frame(datasets[,1])
+    else
+      new_est_table <- data.frame(c(est_table[,1], datasets[,1]))
 
-        colnames(new_est_table) <- colnames(est_table)
-    }
-    else {
-        new_est_table <- data.frame(matrix(nrow=nrow(datasets), ncol=length(estimators)))
+    colnames(new_est_table) <- colnames(est_table)
+  }
+  else {
+    new_est_table <- data.frame(matrix(nrow = nrow(datasets),
+                                       ncol = length(estimators)))
 
-        for (row in 1:nrow(datasets))
-            for (col in 1:length(estimators))
-                new_est_table[row, col] <- eval_estimator(input, output, estimators[[col]], datasets[row,])
+    for (row in 1:nrow(datasets))
+      for (col in 1:length(estimators))
+        new_est_table[row, col] <- eval_estimator(input, output,
+          estimators[[col]], datasets[row,])
 
-        new_est_table <- cbind(datasets[,1], new_est_table)
-        colnames(new_est_table) <- colnames(est_table)
-        new_est_table <- rbind(est_table, new_est_table)
-    }
+    new_est_table <- cbind(datasets[,1], new_est_table)
+    colnames(new_est_table) <- colnames(est_table)
+    new_est_table <- rbind(est_table, new_est_table)
+  }
 
-    return(new_est_table)
+  return(new_est_table)
 }
 
+# Evaluate an estimator on a given dataset.
 eval_estimator <- function(input, output, estimator, dataset) {
-    # Adjust serial interval to match time unit of case counts.
-    serial <- estimator$mu
-    if (estimator$mu_units == "Days" && dataset[2] == "Weekly")
-        serial <- serial / 7
-    else if (estimator$mu_units == "Weeks" && dataset[2] == "Daily")
-        serial <- serial * 7
-
-    # White and Panago
-    if (estimator$method == "WP") {
-        estimate <- WP(unlist(dataset[3]), mu=serial, search=estimator$search)
-
-        if (!is.na(estimator$mu))
-            estimate <- round(estimate$Rhat, 2)
-        # Display the estimated mean of the serial distribution if mu was not specified.
-        else {
-            if (dataset[2] == "Daily")
-                mu_units <- "days"
-            else
-                mu_units <- "weeks"
-            MSI <- sum(estimate$SD$supp * estimate$SD$pmf)
-            estimate <- shiny::HTML(paste0(round(estimate$Rhat, 2), "<br/>(&mu; = ", round(MSI, 2), " ", mu_units, ")"))
-        }
+  # Adjust serial interval to match time unit of case counts.
+  serial <- estimator$mu
+  if (estimator$mu_units == "Days" && dataset[2] == "Weekly")
+    serial <- serial / 7
+  else if (estimator$mu_units == "Weeks" && dataset[2] == "Daily")
+    serial <- serial * 7
+
+  # White and Panago
+  if (estimator$method == "WP") {
+    estimate <- WP(unlist(dataset[3]), mu = serial, search = estimator$search)
+
+    if (!is.na(estimator$mu))
+      estimate <- round(estimate$Rhat, 2)
+    # Display the estimated mean of the serial distribution if mu was not
+    # specified.
+    else {
+      if (dataset[2] == "Daily")
+        mu_units <- "days"
+      else
+        mu_units <- "weeks"
+      MSI <- sum(estimate$SD$supp * estimate$SD$pmf)
+      estimate <- shiny::HTML(paste0(round(estimate$Rhat, 2), "<br/>(&mu; = ",
+                                     round(MSI, 2), " ", mu_units, ")"))
     }
-    # Sequential Bayes
-    else if (estimator$method == "seqB")
-        estimate <- round(seqB(unlist(dataset[3]), mu=serial, kappa=estimator$kappa)$Rhat, 2)
-    # Incidence Decay
-    else if (estimator$method == "ID")
-        estimate <- round(ID(unlist(dataset[3]), mu=serial), 2)
-    # Incidence Decay with Exponential Adjustement
-        else if (estimator$method == "IDEA")
-        estimate <- round(IDEA(unlist(dataset[3]), mu=serial), 2)
-
-    return(estimate)
+  }
+  # Sequential Bayes
+  else if (estimator$method == "seqB")
+    estimate <- round(seqB(unlist(dataset[3]), mu = serial,
+                           kappa = estimator$kappa)$Rhat, 2)
+  # Incidence Decay
+  else if (estimator$method == "ID")
+    estimate <- round(ID(unlist(dataset[3]), mu = serial), 2)
+  # Incidence Decay with Exponential Adjustement
+  else if (estimator$method == "IDEA")
+    estimate <- round(IDEA(unlist(dataset[3]), mu = serial), 2)
+
+  return(estimate)
 }
diff --git a/R/ui.R b/R/ui.R
index d6102f9..4e4a500 100644
--- a/R/ui.R
+++ b/R/ui.R
@@ -1,136 +1,197 @@
-ui <- function() {
-    shiny::fluidPage(
-        # Title.
-        shiny::titlePanel(shiny::HTML(paste0("Rnaught: An Estimation Suite for R", shiny::tags$sub("0")))),
-  
-        # Sidebar layout.
-        shiny::sidebarLayout(
-            # Sidebar. Hidden if the 'About' tab is selected.
-            shiny::conditionalPanel(condition="input.tabset != 'About'",
-                shiny::sidebarPanel(id="sidebar",
-                    # Data tab sidebar.
-                    shiny::conditionalPanel(condition="input.tabset == 'Data'",
-                        shiny::h3("Enter data"),
-                        # Data input method selection.
-                        shiny::radioButtons(inputId="dataInputMethod", label="", choices=list("Manually"=1, "Upload a .csv file"=2, "Paste a .csv file"=3)),
-                        # Option 1: Manual entry.
-                        shiny::conditionalPanel(condition="input.dataInputMethod == '1'",
-                            shiny::textInput(inputId="dataName", label="Dataset name"),
-                            shiny::span(shiny::textOutput(outputId="dataNameWarn"), style="color: red;"),
-                            shiny::fluidRow(
-                                shiny::column(8, shiny::textInput(inputId="dataCounts", label=shiny::HTML(paste0(
-                                    "Case counts", shiny::tags$sup("[?]", title="Enter as a comma-separated list of positive integers, with at least two entries. Ex: 1,1,2,3,5,8"))))
-                                ),
-                                shiny::column(4, shiny::selectInput(inputId="dataUnits", label="Reporting frequency", choices=list("Daily", "Weekly")))
-                            ),
-                            shiny::span(shiny::textOutput(outputId="dataCountsWarn"), style="color: red;")
-                        ),
-                        # Option 2: Upload .csv file.
-                        shiny::conditionalPanel(condition="input.dataInputMethod == '2'",
-                            shiny::fileInput(inputId="dataUpload", label="", accept=c("text/csv", "text/comma-separated-values,text/plain", ".csv")),
-                        ),
-                        # Option 3: Paste .csv file.
-                        shiny::conditionalPanel(condition="input.dataInputMethod == '3'",
-                            shiny::textAreaInput(inputId="dataPaste", label="", rows=8, resize="none"),
-                        ),
-                        # Warning text for .csv upload / paste.
-                        shiny::conditionalPanel(condition="['2', '3'].includes(input.dataInputMethod)",
-                            shiny::span(shiny::textOutput(outputId="dataCSVWarn"), style="color: red;"),
-                        ),
-                        # Button to add data.
-                        shiny::actionButton(inputId="addData", label="Add"),
-                    ),
-                    # Estimators tab sidebar (collapsable entries).
-                    shiny::conditionalPanel(condition="input.tabset == 'Estimators'",
-                        shiny::h3("Estimators"),
-                        # WHITE & PANAGO (WP).
-                        shiny::tags$details(
-                            shiny::tags$summary(shiny::h4("White & Panago (WP)")),
-                            shiny::p("This is a description of the method."),
-                            shiny::br(),
-                            shiny::radioButtons(inputId="serialWPKnown", label="Is the mean serial interval known?", inline=TRUE, choices=list("Yes"=1, "No"=2)),
-                            # Known serial interval.
-                            shiny::conditionalPanel(condition="input.serialWPKnown == '1'",
-                                shiny::fluidRow(
-                                    shiny::column(8, shiny::textInput(inputId="serialWPInput", label="Mean Serial Interval")),
-                                    shiny::column(4, shiny::selectInput(inputId="serialWPUnits", label="Time units", choices=list("Days", "Weeks")))
-                                ),
-                                shiny::span(shiny::textOutput(outputId="serialWPWarn"), style="color: red;")
-                            ),
-                            # Unknown serial interval.
-                            shiny::conditionalPanel(condition="input.serialWPKnown == '2'",
-                                shiny::h5("Grid Search Parameters"),
-                                shiny::fluidRow(
-                                    shiny::column(4, shiny::textInput(inputId="gridLengthInput", label="Grid length", value="100")),
-                                    shiny::column(4, shiny::textInput(inputId="gridShapeInput", label="Max. shape", value="10")),
-                                    shiny::column(4, shiny::textInput(inputId="gridScaleInput", label="Max. scale", value="10"))
-                                ),
-                                shiny::fluidRow(
-                                    shiny::column(4, shiny::span(shiny::textOutput(outputId="gridLengthWarn"), style="color: red;")),
-                                    shiny::column(4, shiny::span(shiny::textOutput(outputId="gridShapeWarn"), style="color: red;")),
-                                    shiny::column(4, shiny::span(shiny::textOutput(outputId="gridScaleWarn"), style="color: red;"))
-                                )
-                            ),
-                            shiny::actionButton(inputId="addWP", label="Add")
-                        ),
-                        # SEQUENTIAL BAYES (seqB).
-                        shiny::tags$details(
-                            shiny::tags$summary(shiny::h4("Sequential Bayes (seqB)")),
-                            shiny::p("This is a description of the method."),
-                            shiny::br(),
-                            shiny::fluidRow(
-                                shiny::column(8, shiny::textInput(inputId="serialseqBInput", label="Mean Serial Interval")),
-                                shiny::column(4, shiny::selectInput(inputId="serialseqBUnits", label="Time units", choices=list("Days", "Weeks")))
-                            ),
-                            shiny::span(shiny::textOutput(outputId="serialseqBWarn"), style="color: red;"),
-                            shiny::textInput(inputId="kappaInput", label=shiny::HTML(paste0("Maximum value of the uniform prior",
-                                shiny::tags$sup("[?]", title="This describes the prior belief of R0, and should be set to a higher value if R0 is believed to be larger. (Default: 20)"))),
-                                value="20"
-                            ),
-                            shiny::span(shiny::textOutput(outputId="kappaWarn"), style="color: red;"),
-                            shiny::actionButton(inputId="addseqB", label="Add")
-                        ),
-                        # INCIDENCE DECAY (ID).
-                        shiny::tags$details(
-                            shiny::tags$summary(shiny::h4("Incidence Decay (ID)")),
-                            shiny::p("This is a description of the method."),
-                            shiny::br(),
-                            shiny::fluidRow(
-                                shiny::column(8, shiny::textInput(inputId="serialIDInput", label="Mean Serial Interval")),
-                                shiny::column(4, shiny::selectInput(inputId="serialIDUnits", label="Time units", choices=list("Days", "Weeks")))
-                            ),
-                            shiny::span(shiny::textOutput(outputId="serialIDWarn"), style="color: red;"),
-                            shiny::actionButton(inputId="addID", label="Add")
-                        ),
-                        # INCIDENCE DECAY & EXPONENTIAL ADJUSTEMENT (IDEA).
-                        shiny::tags$details(
-                            shiny::tags$summary(shiny::h4("Incidence Decay and Exponential Adjustement (IDEA)")),
-                            shiny::p("This is a description of the method."),
-                            shiny::br(),
-                            shiny::fluidRow(
-                                shiny::column(8, shiny::textInput(inputId="serialIDEAInput", label="Mean Serial Interval")),
-                                shiny::column(4, shiny::selectInput(inputId="serialIDEAUnits", label="Time units", choices=list("Days", "Weeks")))
-                            ),
-                            shiny::span(shiny::textOutput(outputId="serialIDEAWarn"), style="color: red;"),
-                            shiny::actionButton(inputId="addIDEA", label="Add")
-                        ),
-                        shiny::tags$style(type="text/css", "summary { display: list-item; cursor: pointer; }"),
-                        shiny::tags$style(type="text/css", "summary h4 { display: inline; }")
-                    )
-                )
+ui <- shiny::fluidPage(
+  # Title.
+  shiny::titlePanel(shiny::HTML(
+    paste0("Rnaught: An Estimation Suite for R", shiny::tags$sub("0")))),
+  # Sidebar layout.
+  shiny::sidebarLayout(
+    # Sidebar. Hidden if the 'About' tab is selected.
+    shiny::conditionalPanel(condition = "input.tabset != 'About'",
+      shiny::sidebarPanel(id = "sidebar",
+        # Data tab sidebar.
+        shiny::conditionalPanel(condition = "input.tabset == 'Data'",
+          shiny::h3("Enter data"),
+          # Data input method selection.
+          shiny::radioButtons(inputId = "dataInputMethod", label = "",
+            choices=list("Manually" = 1, "Upload a .csv file" = 2,
+                         "Paste a .csv file" = 3)),
+          # Option 1: Manual entry.
+          shiny::conditionalPanel(condition = "input.dataInputMethod == '1'",
+            shiny::textInput(inputId = "dataName", label = "Dataset name"),
+            shiny::span(shiny::textOutput(outputId = "dataNameWarn"),
+                        style = "color: red;"),
+            shiny::fluidRow(
+              shiny::column(8,
+                shiny::textInput(inputId = "dataCounts", label = shiny::HTML(
+                  paste0("Case counts", shiny::tags$sup("[?]",
+                    title = "Enter as a comma-separated list of positive
+                             integers, with at least two entries.
+                             Example: 1,1,2,3,5,8"))))),
+              shiny::column(4,
+                shiny::selectInput(inputId = "dataUnits",
+                                   label = "Reporting frequency",
+                                   choices = list("Daily", "Weekly")))
             ),
-            # Main panel.
-            shiny::mainPanel(id="main",
-                shiny::tabsetPanel(id="tabset", type="tabs",
-                    shiny::tabPanel("About", shiny::br(), "Hello"),
-                    shiny::tabPanel("Data", shiny::br(), shiny::dataTableOutput(outputId="dataTable"), shiny::tags$style(type="text/css", "#dataTable tfoot { display:none; }")),
-                    shiny::tabPanel("Estimators", shiny::br(),
-                        shiny::dataTableOutput(outputId="estTable"),
-                        shiny::tags$style(type="text/css", "#estTable tfoot { display:none; }"),
-                        shiny::downloadButton(outputId="downloadEst", label="Download table as .csv")
-                    )
-                )
-            )
+            shiny::span(shiny::textOutput(outputId = "dataCountsWarn"),
+                        style = "color: red;")
+          ),
+          # Option 2: Upload .csv file.
+          shiny::conditionalPanel(condition = "input.dataInputMethod == '2'",
+            shiny::fileInput(inputId = "dataUpload", label = "",
+              accept = c("text/csv", "text/comma-separated-values,text/plain",
+                         ".csv")),
+          ),
+          # Option 3: Paste .csv file.
+          shiny::conditionalPanel(condition = "input.dataInputMethod == '3'",
+            shiny::textAreaInput(inputId = "dataPaste", label = "",
+                                 rows = 8, resize = "none"),
+          ),
+          # Warning text for .csv upload / paste.
+          shiny::conditionalPanel(
+            condition = "['2', '3'].includes(input.dataInputMethod)",
+            shiny::span(shiny::textOutput(outputId = "dataCSVWarn"),
+                        style = "color: red;"),
+          ),
+          # Button to add data.
+          shiny::actionButton(inputId = "addData", label = "Add"),
+        ),
+        # Estimators tab sidebar (collapsable entries).
+        shiny::conditionalPanel(condition = "input.tabset == 'Estimators'",
+          shiny::h3("Estimators"),
+          # WHITE & PANAGO (WP).
+          shiny::tags$details(
+            shiny::tags$summary(shiny::h4("White & Panago (WP)")),
+            shiny::p("This is a description of the method."),
+            shiny::br(),
+            shiny::radioButtons(inputId = "serialWPKnown",
+                                label = "Is the mean serial interval known?",
+                                inline = TRUE,
+                                choices = list("Yes" = 1, "No" = 2)),
+            # Known serial interval.
+            shiny::conditionalPanel(condition = "input.serialWPKnown == '1'",
+              shiny::fluidRow(
+                shiny::column(8,
+                  shiny::textInput(inputId = "serialWPInput",
+                                   label = "Mean Serial Interval")),
+                shiny::column(4,
+                  shiny::selectInput(inputId = "serialWPUnits",
+                                     label = "Time units",
+                                     choices = list("Days", "Weeks")))
+              ),
+              shiny::span(shiny::textOutput(outputId = "serialWPWarn"),
+                          style = "color: red;")
+            ),
+            # Unknown serial interval.
+            shiny::conditionalPanel(condition = "input.serialWPKnown == '2'",
+              shiny::h5("Grid Search Parameters"),
+              shiny::fluidRow(
+                shiny::column(4,
+                  shiny::textInput(inputId = "gridLengthInput",
+                                   label = "Grid length", value = "100")),
+                shiny::column(4,
+                  shiny::textInput(inputId = "gridShapeInput",
+                                   label = "Max. shape", value = "10")),
+                shiny::column(4,
+                  shiny::textInput(inputId = "gridScaleInput",
+                                   label = "Max. scale", value = "10"))
+              ),
+              shiny::fluidRow(
+                shiny::column(4,
+                  shiny::span(shiny::textOutput(outputId = "gridLengthWarn"),
+                              style = "color: red;")),
+                shiny::column(4,
+                  shiny::span(shiny::textOutput(outputId = "gridShapeWarn"),
+                              style = "color: red;")),
+                shiny::column(4,
+                  shiny::span(shiny::textOutput(outputId = "gridScaleWarn"),
+                              style = "color: red;"))
+              )
+            ),
+            shiny::actionButton(inputId = "addWP", label = "Add")
+          ),
+          # SEQUENTIAL BAYES (seqB).
+          shiny::tags$details(
+            shiny::tags$summary(shiny::h4("Sequential Bayes (seqB)")),
+            shiny::p("This is a description of the method."),
+            shiny::br(),
+            shiny::fluidRow(
+              shiny::column(8,
+                shiny::textInput(inputId = "serialseqBInput",
+                                 label = "Mean Serial Interval")),
+              shiny::column(4,
+                shiny::selectInput(inputId = "serialseqBUnits",
+                                   label = "Time units",
+                                   choices = list("Days", "Weeks")))
+            ),
+            shiny::span(shiny::textOutput(outputId = "serialseqBWarn"),
+                        style = "color: red;"),
+            shiny::textInput(inputId = "kappaInput", label = shiny::HTML(
+              paste0("Maximum value", shiny::tags$sup("[?]",
+                title = "This describes the prior belief of R0, and should
+                         be set to a higher value if R0 is believed to be
+                         larger. (Default: 20)"))), value = "20"),
+            shiny::span(shiny::textOutput(outputId = "kappaWarn"),
+                        style = "color: red;"),
+            shiny::actionButton(inputId = "addseqB", label = "Add")
+          ),
+          # INCIDENCE DECAY (ID).
+          shiny::tags$details(
+            shiny::tags$summary(shiny::h4("Incidence Decay (ID)")),
+            shiny::p("This is a description of the method."),
+            shiny::br(),
+            shiny::fluidRow(
+              shiny::column(8,
+                shiny::textInput(inputId = "serialIDInput",
+                                 label = "Mean Serial Interval")),
+              shiny::column(4,
+                shiny::selectInput(inputId = "serialIDUnits",
+                                   label = "Time units",
+                                   choices = list("Days", "Weeks")))
+            ),
+            shiny::span(shiny::textOutput(outputId = "serialIDWarn"),
+                        style = "color: red;"),
+            shiny::actionButton(inputId = "addID", label = "Add")
+          ),
+          # INCIDENCE DECAY & EXPONENTIAL ADJUSTEMENT (IDEA).
+          shiny::tags$details(
+            shiny::tags$summary(
+              shiny::h4("Incidence Decay and Exponential Adjustement (IDEA)")),
+            shiny::p("This is a description of the method."),
+            shiny::br(),
+            shiny::fluidRow(
+              shiny::column(8,
+                shiny::textInput(inputId = "serialIDEAInput",
+                                 label = "Mean Serial Interval")),
+              shiny::column(4,
+                shiny::selectInput(inputId = "serialIDEAUnits",
+                                   label = "Time units",
+                                   choices = list("Days", "Weeks")))
+            ),
+            shiny::span(shiny::textOutput(outputId = "serialIDEAWarn"),
+                        style = "color: red;"),
+            shiny::actionButton(inputId = "addIDEA", label = "Add")
+          ),
+          shiny::tags$style(type = "text/css",
+                            "summary { display: list-item; cursor: pointer; }"),
+          shiny::tags$style(type = "text/css",
+                            "summary h4 { display: inline; }")
         )
+      )
+    ),
+    # Main panel.
+    shiny::mainPanel(id = "main",
+      shiny::tabsetPanel(id = "tabset", type = "tabs",
+        shiny::tabPanel("About", shiny::br(), "Hello"),
+        shiny::tabPanel("Data", shiny::br(),
+                        shiny::dataTableOutput(outputId = "dataTable"),
+                        shiny::tags$style(type = "text/css",
+                          "#dataTable tfoot { display:none; }")),
+        shiny::tabPanel("Estimators", shiny::br(),
+                        shiny::dataTableOutput(outputId = "estTable"),
+                        shiny::tags$style(type = "text/css",
+                          "#estTable tfoot { display:none; }"),
+                        shiny::downloadButton(outputId = "downloadEst",
+                                              label = "Download table as .csv"))
+      )
     )
-}
+  )
+)