From dce01ac19a0298388089ce4297a44ef2aa2c4c46 Mon Sep 17 00:00:00 2001 From: Naeem Model Date: Thu, 9 May 2024 20:22:45 +0000 Subject: Revamp Shiny app --- inst/app/scripts/data.R | 236 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 236 insertions(+) create mode 100644 inst/app/scripts/data.R (limited to 'inst/app/scripts/data.R') 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$data_area, header = FALSE, sep = ",") + + names <- trimws(datasets[, 1]) + units <- trimws(datasets[, 2]) + counts <- apply(datasets[, 3:ncol(datasets)], 1, + function(row) { + row <- suppressWarnings(as.integer(row)) + toString(row[!is.na(row) & row >= 0]) + } + ) + + warning_text <- "" + + # Ensure the dataset names are neither blank nor duplicates. + if (anyNA(names) || any(names == "")) { + warning_text <- paste0(warning_text, sep = "
", + "Each row must begin with a non-blank dataset name." + ) + } else { + if (length(unique(names)) != length(names)) { + warning_text <- paste0(warning_text, sep = "
", + "The rows contain duplicate dataset names." + ) + } + if (any(names %in% react_values$data_table[, 1])) { + warning_text <- paste0(warning_text, sep = "
", + "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 = "
", + "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 = "
", + "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 + ) +} -- cgit v1.2.3