diff options
Diffstat (limited to 'inst/app/scripts')
| -rw-r--r-- | inst/app/scripts/data.R | 236 | ||||
| -rw-r--r-- | inst/app/scripts/estimators.R | 305 |
2 files changed, 541 insertions, 0 deletions
diff --git a/inst/app/scripts/data.R b/inst/app/scripts/data.R new file mode 100644 index 0000000..06cb256 --- /dev/null +++ b/inst/app/scripts/data.R @@ -0,0 +1,236 @@ +# Main logic block for data-related interactions. +data_logic <- function(input, output, react_values) { + # Initialize a data frame to hold the datasets. + react_values$data_table <- data.frame( + Name = character(0), + `Time units` = character(0), + `Case counts` = character(0), + check.names = FALSE + ) + + render_plot(input, output) + single_entry(input, output, react_values) + bulk_entry(input, output, react_values) + render_data(output, react_values) + delete_data(input, react_values) + export_data(output, react_values) +} + +# Convert the input case counts string to an integer vector. +tokenize_counts <- function(counts_str) { + suppressWarnings(as.integer(unlist(strsplit(trimws(counts_str), ",")))) +} + +# Render the preview plot for single entry data. +render_plot <- function(input, output) { + observe({ + counts <- tokenize_counts(input$data_counts) + if (length(counts) > 0 && !anyNA(counts) && all(counts >= 0)) { + output$data_plot <- renderPlot( + plot(seq_along(counts) - 1, counts, type = "o", pch = 16, col = "red", + xlab = input$data_units, ylab = "Cases", cex.lab = 1.5, + xlim = c(0, max(length(counts) - 1, 1)), ylim = c(0, max(counts, 1)) + ) + ) + } else { + output$data_plot <- renderPlot( + plot(NULL, xlim = c(0, 10), ylim = c(0, 10), + xlab = input$data_units, ylab = "Cases", cex.lab = 1.5 + ) + ) + } + }) +} + +# Add a single dataset to the existing table. +single_entry <- function(input, output, react_values) { + observeEvent(input$data_single, { + valid <- TRUE + + # Ensure the dataset name is neither blank nor a duplicate. + name <- trimws(input$data_name) + if (name == "") { + output$data_name_warn <- renderText("The dataset name cannot be blank.") + valid <- FALSE + } else if (name %in% react_values$data_table[, 1]) { + output$data_name_warn <- renderText( + "There is already a dataset with the specified name." + ) + valid <- FALSE + } else { + output$data_name_warn <- renderText("") + } + + # Ensure the case counts are specified as a comma-separated of one or more + # non-negative integers. + counts <- tokenize_counts(input$data_counts) + if (length(counts) == 0) { + output$data_counts_warn <- renderText("Case counts cannot be blank.") + valid <- FALSE + } else if (anyNA(counts) || any(counts < 0)) { + output$data_counts_warn <- renderText( + "Case counts can only contain non-negative integers." + ) + valid <- FALSE + } else { + output$data_counts_warn <- renderText("") + } + + if (valid) { + # Add the new dataset to the data table. + new_row <- data.frame(name, input$data_units, toString(counts)) + colnames(new_row) <- c("Name", "Time units", "Case counts") + react_values$data_table <- rbind(react_values$data_table, new_row) + + # Evaluate all existing estimators on the new dataset and update the + # corresponding row in the estimates table. + update_estimates_rows(new_row, react_values) + + showNotification("Dataset added successfully.", + duration = 3, id = "notify-success" + ) + } + }) +} + +# Add multiple datasets to the existing table. +bulk_entry <- function(input, output, react_values) { + observeEvent(input$data_bulk, { + tryCatch( + { + datasets <- read.csv(text = input$data_area, header = FALSE, sep = ",") + + names <- trimws(datasets[, 1]) + units <- trimws(datasets[, 2]) + counts <- apply(datasets[, 3:ncol(datasets)], 1, + function(row) { + row <- suppressWarnings(as.integer(row)) + toString(row[!is.na(row) & row >= 0]) + } + ) + + warning_text <- "" + + # Ensure the dataset names are neither blank nor duplicates. + if (anyNA(names) || any(names == "")) { + warning_text <- paste0(warning_text, sep = "<br>", + "Each row must begin with a non-blank dataset name." + ) + } else { + if (length(unique(names)) != length(names)) { + warning_text <- paste0(warning_text, sep = "<br>", + "The rows contain duplicate dataset names." + ) + } + if (any(names %in% react_values$data_table[, 1])) { + warning_text <- paste0(warning_text, sep = "<br>", + "The rows contain dataset names which already exist." + ) + } + } + + # Ensure the second entry in each row is a time unit equal to + # "Days" or "Weeks". + if (!all(units %in% c("Days", "Weeks"))) { + warning_text <- paste0(warning_text, sep = "<br>", + "The second entry in each row must be either 'Days' or 'Weeks'." + ) + } + + # Ensure the counts in each row have at least one non-negative integer. + if (any(counts == "")) { + warning_text <- paste0(warning_text, sep = "<br>", + "Each row must contain at least one non-negative integer." + ) + } + + output$data_area_warn <- renderUI(HTML(warning_text)) + + if (warning_text == "") { + # Add the new datasets to the data table. + new_rows <- data.frame(names, units, counts) + colnames(new_rows) <- c("Name", "Time units", "Case counts") + react_values$data_table <- rbind(react_values$data_table, new_rows) + + # Evaluate all existing estimators on the new dataset and update the + # corresponding row in the estimates table. + update_estimates_rows(new_rows, react_values) + + showNotification("Datasets added successfully.", + duration = 3, id = "notify-success" + ) + } + }, + error = function(e) { + output$data_area_warn <- renderText( + "The input does not match the required format." + ) + } + ) + }) +} + +# Render the data table when new datasets are added. +render_data <- function(output, react_values) { + observe({ + output$data_table <- DT::renderDataTable(react_values$data_table) + }) +} + +# Delete rows in the data table, +# and the corresponding rows in the estimates table. +delete_data <- function(input, react_values) { + observeEvent(input$data_delete, { + new_table <- react_values$data_table[-input$data_table_rows_selected, ] + if (nrow(new_table) > 0) { + rownames(new_table) <- seq_len(nrow(new_table)) + } + react_values$data_table <- new_table + + if (ncol(react_values$estimates_table) == 1) { + react_values$estimates_table <- data.frame( + Datasets = react_values$data_table[, 1] + ) + } else { + react_values$estimates_table <- + react_values$estimates_table[-input$data_table_rows_selected, ] + } + }) +} + +# Export data table as a CSV file. +export_data <- function(output, react_values) { + output$data_export <- downloadHandler( + filename = function() { + paste0("Rnaught_data_", format(Sys.time(), "%y-%m-%d_%H-%M-%S"), ".csv") + }, + content = function(file) { + write.csv(react_values$data_table, file, row.names = FALSE) + } + ) +} + +# When new datasets are added, evaluate all existing estimators on them and +# add new rows to the estimates table. +update_estimates_rows <- function(datasets, react_values) { + new_rows <- data.frame( + matrix(nrow = nrow(datasets), ncol = ncol(react_values$estimates_table)) + ) + colnames(new_rows) <- colnames(react_values$estimates_table) + + for (row in seq_len(nrow(datasets))) { + new_rows[row, 1] <- datasets[row, 1] + + if (length(react_values$estimators) > 0) { + for (col in 2:ncol(react_values$estimates_table)) { + new_rows[row, col] <- eval_estimator( + react_values$estimators[[col - 1]], datasets[row, ] + ) + } + } + } + + react_values$estimates_table <- rbind( + react_values$estimates_table, new_rows + ) +} diff --git a/inst/app/scripts/estimators.R b/inst/app/scripts/estimators.R new file mode 100644 index 0000000..171d197 --- /dev/null +++ b/inst/app/scripts/estimators.R @@ -0,0 +1,305 @@ +estimators_logic <- function(input, output, react_values) { + # Initialize a data frame to hold estimates. + react_values$estimates_table <- data.frame(Dataset = character(0)) + # 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$estimators[[i]])) { + showNotification("Error: This estimator has already been added.", + duration = 3, id = "notify-error" + ) + return() + } + } + + # Add the new estimator to the list of estimators. + react_values$estimators[[num_estimators + 1]] <- new_estimator + + showNotification("Estimator added successfully.", + duration = 3, id = "notify-success" + ) + + # Evaluate all the new estimator on all existing datasets and create a new + # column in the estimates table. + update_estimates_col(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 <= 0) { + output$kappa_warn <- renderText( + "The maximum prior must be a positive number." + ) + } else if (!is.null(mu)) { + output$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$max_scale_warn <- renderText("") + } + + if (valid) { + new_estimator <- list(method = "wp", mu = NA, grid_length = grid_length, + max_shape = max_shape, max_scale = max_scale + ) + add_estimator("wp", new_estimator, output, react_values) + } + } + }) +} + +# Convert an estimator's specified serial interval to match the time units of +# the given dataset. +convert_mu_units <- function(data_units, estimator_units, mu) { + if (data_units == "Days" && estimator_units == "Weeks") { + return(mu * 7) + } else if (data_units == "Weeks" && estimator_units == "Days") { + return(mu / 7) + } + mu +} + +# Add a column to the estimates table when a new estimator is added. +update_estimates_col <- function(estimator, react_values) { + dataset_rows <- seq_len(nrow(react_values$data_table)) + estimates <- dataset_rows + + for (row in dataset_rows) { + estimate <- eval_estimator(estimator, react_values$data_table[row, ]) + estimates[row] <- estimate + } + + estimates <- data.frame(estimates) + colnames(estimates) <- estimates_col_name(estimates, estimator) + + react_values$estimates_table <- cbind( + react_values$estimates_table, estimates + ) +} + +# Evaluate the specified estimator on the given dataset. +eval_estimator <- function(estimator, dataset) { + cases <- as.integer(unlist(strsplit(dataset[, 3], ","))) + + if (estimator$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) + estimate <- paste0(round(estimate$r0, 2), " (μ = ", estimated_mu, + " ", tolower(dataset[, 2]), ")" + ) + } else { + mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu) + estimate <- round(Rnaught::wp(cases, mu), 2) + } + } + + return(estimate) +} + +# Create the column name of an estimator when it is +# added to the estimates table. +estimates_col_name <- function(estimates, estimator) { + if (estimator$method == "id") { + return(paste0("ID", " (μ = ", estimator$mu, " ", + tolower(estimator$mu_units), ")" + )) + } else if (estimator$method == "idea") { + return(paste0("IDEA", " (μ = ", estimator$mu, " ", + tolower(estimator$mu_units), ")" + )) + } else if (estimator$method == "seq_bayes") { + return(paste0("seqB", " (μ = ", estimator$mu, " ", + tolower(estimator$mu_units), ", 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(paste0("WP", " (μ = ", estimator$mu, " ", + tolower(estimator$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, + selection = list(target = "column", selectable = c(0)), + escape = FALSE, rownames = FALSE, + options = list( + columnDefs = list(list(className = "dt-left", targets = "_all")) + ), + ) + }) +} + +# Delete columns from the estimates table, +# as well as the corresponding estimators. +delete_estimators <- function(input, react_values) { + observeEvent(input$estimators_delete, { + cols_selected <- input$estimates_table_columns_selected + react_values$estimators <- react_values$estimators[-cols_selected] + react_values$estimates_table[, cols_selected + 1] <- NULL + }) +} + +# Export estimates table as a CSV file. +export_estimates <- function(output, react_values) { + output$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("μ", "mu", obj) + obj <- gsub("κ", "kappa", obj) + obj +} |