diff options
| -rw-r--r-- | R/server.R | 314 | ||||
| -rw-r--r-- | R/ui.R | 192 |
2 files changed, 0 insertions, 506 deletions
diff --git a/R/server.R b/R/server.R deleted file mode 100644 index a9ed521..0000000 --- a/R/server.R +++ /dev/null @@ -1,314 +0,0 @@ -#' @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) -} @@ -1,192 +0,0 @@ -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))) -} |