+++ /dev/null
-#' @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$dataNameWarn <- shiny::renderText("")
-
- # Ensure the case counts consist only of positive integers, separated by
- # commas.
- counts <- as.numeric(unlist(strsplit(input$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$dataUnits, t(counts))
- }
-
- else {
- checks_passed <- FALSE
-
- # Option 2: Upload .csv
- if (input$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$dataCSVWarn <- shiny::renderText("")
- checks_passed <- TRUE
- }
- }
-
- if (checks_passed) {
- d[,3:ncol(d)] <- apply(d[,3:ncol(d)], 2, as.numeric)
- d[,3] <- data.frame(I(lapply(split(d[,3:ncol(d)], 1:nrow(d)),
- function(x) x[!is.na(x)])))
- d <- d[,1:3]
- d[,2] <- trimws(d[,2])
- colnames(d) <- c("Name", "Reporting Frequency", "Case Counts")
- reactive$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)
-
- # 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$serialWPUnits,
- grid_length = 100, max_shape = 10, max_scale = 10)
- reactive$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$gridShapeWarn <- shiny::renderText("")
-
- if (is.na(max_scale) || max_scale < 1 / grid_length) {
- output$gridScaleWarn <- 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$estimators) + 1]] <- list(
- method = "WP", mu = NA, mu_units = input$serialWPUnits,
- grid_length = grid_length, max_shape = max_shape, max_scale = max_scale)
- 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
- }
- 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$est_table)
- }
- })
-
- shiny::observeEvent(input$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$est_table)
- }
- })
-}
-
-validate_serial <- function(input, output, serialInputId, serialWarnId) {
- serial <- as.numeric(input[[serialInputId]])
- if (is.na(serial) || serial <= 0) {
- output[[serialWarnId]] <- shiny::renderText(
- "Error: The mean serial interval should be a positive number.")
- serial <- NA
- }
- else
- output[[serialWarnId]] <- shiny::renderText("") # Clear warning text.
-
- return(serial)
-}
-
-# Create a new column in the estimator table when a new estimator is added.
-update_est_col <- function(input, output, datasets, estimator, est_table) {
- if (nrow(datasets) == 0)
- new_est_table <- data.frame(matrix(nrow = 0, ncol = ncol(est_table) + 1))
- else {
- estimates <- rep(NA, nrow(datasets))
-
- for (row in 1:nrow(datasets))
- estimates[row] <- eval_estimator(input, output, estimator, datasets[row,])
-
- if (nrow(est_table) == 0)
- new_est_table <- cbind(datasets[,1], estimates)
- else
- new_est_table <- cbind(est_table, estimates)
- }
-
- colnames(new_est_table) <- c(colnames(est_table), shiny::HTML(
- paste0(estimator$method, "<br/>(μ = ", 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]))
-
- 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,])
-
- 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)
-}
-
-# 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$mu_units == "Weeks" && dataset[2] == "Daily")
- serial <- serial * 7
-
- # White and Pagano
- if (estimator$method == "WP") {
- estimate <- wp(unlist(dataset[3]), mu = serial, serial = TRUE,
- grid_length = estimator$grid_length,
- max_shape = estimator$max_shape,
- max_scale = estimator$max_scale)
-
- if (!is.na(estimator$mu))
- estimate <- round(estimate$r0, 2)
- # Display the estimated mean of the serial distribution if mu was not
- # specified.
- else {
- if (dataset[2] == "Daily")
- mu_units <- "days"
- else
- mu_units <- "weeks"
- MSI <- sum(estimate$supp * estimate$pmf)
- estimate <- shiny::HTML(paste0(round(estimate$r0, 2), "<br/>(μ = ",
- round(MSI, 2), " ", mu_units, ")"))
- }
- }
- # Sequential Bayes
- else if (estimator$method == "seqB")
- estimate <- round(seq_bayes(unlist(dataset[3]), mu = serial,
- kappa = estimator$kappa), 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)
-}
+++ /dev/null
-ui <- function() {
- shiny::fluidPage(
- # Title.
- shiny::titlePanel(shiny::HTML(
- paste0("Rnaught: An Estimation Suite for R", shiny::tags$sub("0")))),
- # Sidebar layout.
- shiny::sidebarLayout(
- # Sidebar. Hidden if the 'About' tab is selected.
- shiny::conditionalPanel(condition = "input.tabset != 'About'",
- shiny::sidebarPanel(id = "sidebar", data_sidebar(), est_sidebar())),
- # Main panel.
- shiny::mainPanel(id = "main",
- shiny::tabsetPanel(id = "tabset", type = "tabs",
- shiny::tabPanel("About", shiny::br(), "Hello"),
- shiny::tabPanel("Data", shiny::br(),
- shiny::dataTableOutput(outputId = "dataTable"),
- shiny::tags$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"))
- )
- )
- )
- )
-}
-
-# Data tab sidebar.
-data_sidebar <- function() {
- 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 = help_tool("Case counts", paste0("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")))
- ),
- 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.
-est_sidebar <- function() {
- shiny::conditionalPanel(condition = "input.tabset == 'Estimators'",
- shiny::h3("Estimators"),
- WP_collapse(),
- seqB_collapse(),
- ID_collapse(),
- IDEA_collapse(),
-
- shiny::tags$style(type = "text/css",
- "summary { display: list-item; cursor: pointer; }"),
- shiny::tags$style(type = "text/css", "summary h4 { display: inline; }")
- )
-}
-
-# Collapsable entry for White & Pagano (WP) method.
-WP_collapse <- function() {
- shiny::tags$details(
- shiny::tags$summary(shiny::h4("White & Pagano (WP)")),
- shiny::p("Method due to White and Pagano (2008), assumes a branching process
- based model. Serial distribution can be assumed known or can be
- estimated using maximum likelihood; When serial interval is
- unknown the method takes longer to compute, though is still
- real-time."),
- shiny::br(),
- shiny::radioButtons(inputId = "serialWPKnown",
- label = "Is the mean serial interval known?",
- inline = TRUE, choices = list("Yes" = 1, "No" = 2)),
- # Known serial interval.
- shiny::conditionalPanel(condition = "input.serialWPKnown == '1'",
- serial_fields("WP")),
- # Unknown serial interval.
- shiny::conditionalPanel(condition = "input.serialWPKnown == '2'",
- shiny::h5("Grid Search Parameters"),
- shiny::fluidRow(
- shiny::column(4, shiny::textInput(inputId = "gridLengthInput",
- label = "Grid length", value = "100")),
- shiny::column(4, shiny::textInput(inputId = "gridShapeInput",
- label = "Max. shape", value = "10")),
- shiny::column(4, shiny::textInput(inputId = "gridScaleInput",
- label = "Max. scale", value = "10"))
- ),
- shiny::fluidRow(
- shiny::column(4, shiny::span(shiny::textOutput(
- outputId = "gridLengthWarn"), style = "color: red;")),
- shiny::column(4, shiny::span(shiny::textOutput(
- outputId = "gridShapeWarn"), style = "color: red;")),
- shiny::column(4, shiny::span(shiny::textOutput(
- outputId = "gridScaleWarn"), style = "color: red;"))
- )
- ),
- shiny::actionButton(inputId = "addWP", label = "Add")
- )
-}
-
-# Collapsable entry for Sequential Bayes (seqB) method.
-seqB_collapse <- function() {
- shiny::tags$details(
- shiny::tags$summary(shiny::h4("Sequential Bayes (seqB)")),
- shiny::p("This is a description of the method."),
- shiny::br(),
- serial_fields("seqB"),
- shiny::textInput(inputId = "kappaInput",
- label = help_tool("Maximum value", paste0("This describes the prior ",
- "belief of R0, and should be set to a higher value if R0 is believed ",
- "be larger. (Default: 20)")), value = "20"),
- shiny::span(shiny::textOutput(outputId = "kappaWarn"),
- style = "color: red;"),
- shiny::actionButton(inputId = "addseqB", label = "Add")
- )
-}
-
-# Collapsable entry for Incidence Decay (ID) method.
-ID_collapse <- function() {
- shiny::tags$details(
- shiny::tags$summary(shiny::h4("Incidence Decay (ID)")),
- shiny::p("This is a description of the method."),
- shiny::br(),
- serial_fields("ID"),
- shiny::actionButton(inputId = "addID", label = "Add")
- )
-}
-
-# Collapsable entry for Incidence Decay & Exponential Adjustment (IDEA) method.
-IDEA_collapse <- function() {
- shiny::tags$details(
- shiny::tags$summary(
- shiny::h4("Incidence Decay and Exponential Adjustment (IDEA)")),
- shiny::p("This is a description of the method."),
- shiny::br(),
- serial_fields("IDEA"),
- shiny::actionButton(inputId = "addIDEA", label = "Add")
- )
-}
-
-# Input fields and warning text for the mean serial interval.
-serial_fields <- function(method) {
- shiny::HTML(paste0(
- shiny::fluidRow(
- shiny::column(8, shiny::textInput(
- inputId = paste0("serial", method, "Input"),
- label = "Mean Serial Interval")),
- shiny::column(4, shiny::selectInput(
- inputId = paste0("serial", method, "Units"),
- label = "Time units", choices = list("Days", "Weeks")))
- ),
- shiny::span(shiny::textOutput(outputId = paste0("serial", method, "Warn")),
- style = "color: red;")
- ))
-}
-
-# Display help information on hover.
-help_tool <- function(label, help_text) {
- shiny::HTML(paste0(label, shiny::tags$sup("[?]", title = help_text)))
-}
git.nmode.ca / Rnaught / commitdiff
