+++ /dev/null
-# Main logic block for estimator-related interactions.
-estimators_logic <- function(input, output, react_values) {
- # Initialize a data frame to hold estimates.
- react_values$estimates_table <- data.frame(
- Estimator = character(0),
- `Serial interval` = character(0),
- check.names = FALSE
-
- )
- # Initialize a list to hold added estimators.
- react_values$estimators <- list()
-
- add_id(input, output, react_values)
- add_idea(input, output, react_values)
- add_seq_bayes(input, output, react_values)
- add_wp(input, output, react_values)
-
- render_estimates(output, react_values)
- delete_estimators(input, react_values)
- export_estimates(output, react_values)
-}
-
-# If an estimator is added, ensure it is not a duplicate and add it to the list
-# of estimators. This function should be called at the end of each
-# estimator-specific 'add' function, after validating their parameters.
-add_estimator <- function(method, new_estimator, output, react_values) {
- num_estimators <- length(react_values$estimators)
-
- # Check whether the new estimator is a duplicate, and warn if so.
- for (i in seq_len(num_estimators)) {
- if (identical(new_estimator, react_values$estimators[[i]])) {
- showNotification(
- "Error: This estimator has already been added.", duration = 3
- )
- return()
- }
- }
-
- # Add the new estimator to the list of estimators.
- react_values$estimators[[num_estimators + 1]] <- new_estimator
-
- showNotification("Estimator added successfully.", duration = 3)
-
- # Evaluate the new estimator on all existing datasets and create a new row in
- # the estimates table.
- update_estimates_row(new_estimator, react_values)
-}
-
-# Ensure serial intervals are specified as positive numbers.
-validate_mu <- function(method, input, output) {
- mu <- suppressWarnings(as.numeric(trimws(input[[paste0("mu_", method)]])))
- if (is.na(mu) || mu <= 0) {
- output[[paste0("mu_", method, "_warn")]] <- renderText(
- "The serial interval must be a positive number."
- )
- return(NULL)
- }
- output[[paste0("mu_", method, "_warn")]] <- renderText("")
- mu
-}
-
-# Incidence Decay (ID).
-add_id <- function(input, output, react_values) {
- observeEvent(input$add_id, {
- mu <- validate_mu("id", input, output)
- if (!is.null(mu)) {
- new_estimator <- list(
- method = "id", mu = mu, mu_units = input$mu_id_units
- )
- add_estimator("id", new_estimator, output, react_values)
- }
- })
-}
-
-# Incidence Decay and Exponential Adjustment (IDEA).
-add_idea <- function(input, output, react_values) {
- observeEvent(input$add_idea, {
- mu <- validate_mu("idea", input, output)
- if (!is.null(mu)) {
- new_estimator <- list(
- method = "idea", mu = mu, mu_units = input$mu_idea_units
- )
- add_estimator("idea", new_estimator, output, react_values)
- }
- })
-}
-
-# Sequential Bayes (seqB).
-add_seq_bayes <- function(input, output, react_values) {
- observeEvent(input$add_seq_bayes, {
- mu <- validate_mu("seq_bayes", input, output)
-
- kappa <- trimws(input$kappa)
- kappa <- if (kappa == "") 20 else suppressWarnings(as.numeric(kappa))
-
- if (is.na(kappa) || kappa < 1) {
- output$kappa_warn <- renderText(
- "The maximum prior must be a number greater than or equal to 1."
- )
- } else if (!is.null(mu)) {
- output$kappa_warn <- renderText("")
- new_estimator <- list(
- method = "seq_bayes", mu = mu,
- mu_units = input$mu_seq_bayes_units, kappa = kappa
- )
- add_estimator("seq_bayes", new_estimator, output, react_values)
- }
- })
-}
-
-# White and Pagano (WP).
-add_wp <- function(input, output, react_values) {
- observeEvent(input$add_wp, {
- if (input$wp_mu_known == "Yes") {
- mu <- validate_mu("wp", input, output)
- if (!is.null(mu)) {
- new_estimator <- list(method = "wp",
- mu = mu, mu_units = input$mu_wp_units
- )
- add_estimator("wp", new_estimator, output, react_values)
- }
- } else {
- grid_length <- trimws(input$grid_length)
- max_shape <- trimws(input$max_shape)
- max_scale <- trimws(input$max_scale)
-
- suppressWarnings({
- grid_length <- if (grid_length == "") 100 else as.numeric(grid_length)
- max_shape <- if (max_shape == "") 10 else as.numeric(max_shape)
- max_scale <- if (max_scale == "") 10 else as.numeric(max_scale)
- })
-
- valid <- TRUE
-
- if (is.na(grid_length) || grid_length <= 0) {
- output$grid_length_warn <- renderText(
- "The grid length must be a positive integer."
- )
- valid <- FALSE
- } else {
- output$grid_length_warn <- renderText("")
- }
-
- if (is.na(max_shape) || max_shape <= 0) {
- output$max_shape_warn <- renderText(
- "The maximum shape must be a positive number."
- )
- valid <- FALSE
- } else {
- output$max_shape_warn <- renderText("")
- }
-
- if (is.na(max_scale) || max_scale <= 0) {
- output$max_scale_warn <- renderText(
- "The maximum scale must be a positive number."
- )
- valid <- FALSE
- } else {
- output$max_scale_warn <- renderText("")
- }
-
- if (valid) {
- new_estimator <- list(method = "wp", mu = NA, grid_length = grid_length,
- max_shape = max_shape, max_scale = max_scale
- )
- add_estimator("wp", new_estimator, output, react_values)
- }
- }
- })
-}
-
-# Convert an estimator's specified serial interval to match the time units of
-# the given dataset.
-convert_mu_units <- function(data_units, estimator_units, mu) {
- if (data_units == "Days" && estimator_units == "Weeks") {
- return(mu * 7)
- } else if (data_units == "Weeks" && estimator_units == "Days") {
- return(mu / 7)
- }
- mu
-}
-
-# Add a row to the estimates table when a new estimator is added.
-update_estimates_row <- function(estimator, react_values) {
- dataset_rows <- seq_len(nrow(react_values$data_table))
- estimates <- c()
-
- if (nrow(react_values$data_table) > 0) {
- estimates <- dataset_rows
- for (row in dataset_rows) {
- estimate <- eval_estimator(estimator, react_values$data_table[row, ])
- estimates[row] <- estimate
- }
- }
-
- new_row <- data.frame(
- t(c(estimator_name(estimator), estimator_mu_text(estimator), estimates))
- )
- colnames(new_row) <- colnames(react_values$estimates_table)
-
- react_values$estimates_table <- rbind(
- react_values$estimates_table, new_row
- )
-}
-
-# Evaluate the specified estimator on the given dataset.
-eval_estimator <- function(estimator, dataset) {
- cases <- as.integer(unlist(strsplit(dataset[, 3], ",")))
-
- tryCatch(
- {
- if (estimator$method == "id") {
- mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
- estimate <- round(Rnaught::id(cases, mu), 2)
- } else if (estimator$method == "idea") {
- mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
- estimate <- round(Rnaught::idea(cases, mu), 2)
- } else if (estimator$method == "seq_bayes") {
- mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
- estimate <- round(Rnaught::seq_bayes(cases, mu, estimator$kappa), 2)
- } else if (estimator$method == "wp") {
- if (is.na(estimator$mu)) {
- estimate <- Rnaught::wp(cases, serial = TRUE,
- grid_length = estimator$grid_length,
- max_shape = estimator$max_shape, max_scale = estimator$max_scale
- )
- estimated_mu <- round(sum(estimate$supp * estimate$pmf), 2)
- mu_units <- if (dataset[, 2] == "Days") "day(s)" else "week(s)"
- estimate <- paste0(
- round(estimate$r0, 2), " (SI = ", estimated_mu, " ", mu_units, ")"
- )
- } else {
- mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
- estimate <- round(Rnaught::wp(cases, mu), 2)
- }
- }
-
- return(estimate)
- }, error = function(e) {
- showNotification(
- paste0(toString(e),
- " [Estimator: ", sub(" .*", "", estimator_name(estimator)),
- ", Dataset: ", dataset[, 1], "]"
- ), duration = 6
- )
- return("—")
- }
- )
-}
-
-# Create the name of an estimator to be added to the first column of the
-# estimates table.
-estimator_name <- function(estimator) {
- if (estimator$method == "id") {
- return("ID")
- } else if (estimator$method == "idea") {
- return("IDEA")
- } else if (estimator$method == "seq_bayes") {
- return(paste0("seqB", " (κ = ", estimator$kappa, ")"))
- } else if (estimator$method == "wp") {
- if (is.na(estimator$mu)) {
- return(paste0("WP (", estimator$grid_length, ", ",
- round(estimator$max_shape, 3), ", ", round(estimator$max_scale, 3), ")"
- ))
- } else {
- return("WP")
- }
- }
-}
-
-# Create the text to be displayed for the serial interval in the second column
-# of the estimates table.
-estimator_mu_text <- function(estimator) {
- if (is.na(estimator$mu)) {
- return("—")
- }
- mu_units <- if (estimator$mu_units == "Days") "day(s)" else "week(s)"
- paste(estimator$mu, mu_units)
-}
-
-# Render the estimates table whenever it is updated.
-render_estimates <- function(output, react_values) {
- observe({
- output$estimates_table <- DT::renderDataTable(react_values$estimates_table,
- escape = FALSE, rownames = FALSE,
- options = list(
- columnDefs = list(list(className = "dt-left", targets = "_all"))
- ),
- )
- })
-}
-
-# Delete rows from the estimates table and the corresponding estimators.
-delete_estimators <- function(input, react_values) {
- observeEvent(input$estimators_delete, {
- rows_selected <- input$estimates_table_rows_selected
- react_values$estimators <- react_values$estimators[-rows_selected]
- react_values$estimates_table <-
- react_values$estimates_table[-rows_selected, ]
- })
-}
-
-# Export estimates table as a CSV file.
-export_estimates <- function(output, react_values) {
- output$estimates_export <- downloadHandler(
- filename = function() {
- paste0(
- "Rnaught_estimates_", format(Sys.time(), "%y-%m-%d_%H-%M-%S"), ".csv"
- )
- },
- content = function(file) {
- output_table <- data.frame(
- lapply(react_values$estimates_table, sub_entity)
- )
- colnames(output_table) <- sub_entity(
- colnames(react_values$estimates_table)
- )
- write.csv(output_table, file, row.names = FALSE)
- }
- )
-}
-
-# Substitute HTML entity codes with natural names.
-sub_entity <- function(obj) {
- obj <- gsub("κ", "kappa", obj)
- obj
-}
git.nmode.ca / Rnaught / blobdiff
