# Main logic block for data-related interactions. data_logic <- function(input, output, react_values) { # Initialize a data frame to hold the datasets. react_values$data_table <- data.frame( Name = character(0), `Time units` = character(0), `Case counts` = character(0), check.names = FALSE ) render_plot(input, output) single_entry(input, output, react_values) bulk_entry(input, output, react_values) upload_entry(input, output, react_values) sample_entry(input, output, react_values) render_data(output, react_values) delete_data(input, react_values) export_data(output, react_values) } warnings <- function(df, df_elems) { warning_text <- '' # Ensure the dataset names are neither blank nor duplicates. if (anyNA(df_elems[[1]]) || any(df_elems[[1]] == "")) { warning_text <- paste0(warning_text, sep = "
", "Each row must begin with a non-blank dataset name." ) } if (length(unique(df_elems[[1]])) != length(df_elems[[1]])) { warning_text <- paste0(warning_text, sep = "
", "The rows contain duplicate dataset names." ) } if (any(df_elems[[1]] %in% react_values$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(df_elems[[2]] %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(df_elems[[3]] == "")) { warning_text <- paste0(warning_text, sep = "
", "Each row must contain at least one non-negative integer." ) } return(warning_text) } # 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 = "black", 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]) } ) output$data_area_warn <- renderText("") warning_text <- warnings(datasets, list(names, units, counts)) if (warning_text == "") { # Add the new datasets to the data table. new_rows <- data.frame(names, units, counts) colnames(new_rows) <- c("Name", "Time units", "Case counts") react_values$data_table <- rbind(react_values$data_table, new_rows) # Evaluate all existing estimators on the new dataset and update the # corresponding row in the estimates table. update_estimates_rows(new_rows, react_values) showNotification("Datasets added successfully.", duration = 3, id = "notify-success" ) } else { output$data_area_warn <- renderUI(HTML(warning_text)) } }, error = function(e) { output$data_area_warn <- renderText( "The input does not match the required format." ) } ) }) } # Upload datasets to the existing table. upload_entry <- function(input, output, react_values) { observeEvent(input$data_load, { tryCatch( { df <- read.csv(file = input$upload_csv$datapath) names <- trimws(df[, 1]) units <- trimws(df[, 2]) counts <- sapply(tokenize_counts(df[, 3:ncol(df)]), function(row) { row <- suppressWarnings(as.integer(row)) toString(row[!is.na(row) & row >= 0]) } ) output$data_load_warn <- renderText("") warning_text <- '' warning_text <- warnings(df, list(names, units, counts)) if (warning_text == "") { # Add the new datasets to the data table. new_rows <- read.csv(file = input$upload_csv$datapath) colnames(new_rows) <- c("Name", "Time units", "Case counts") react_values$data_table <- rbind(react_values$data_table, new_rows) # Evaluate all existing estimators on the new dataset and update the # corresponding row in the estimates table. update_estimates_rows(new_rows, react_values) showNotification("Datasets added successfully.", duration = 3, id = "notify-success") } else { output$data_load_warn <- renderUI(HTML(warning_text)) } }, error = function(e) { output$data_load_warn <- renderText( "The input does not match the required format." ) } ) }) } # Add sample datasets to the existing table. sample_entry <- function(input, output, react_values) { observeEvent(input$sample_entry, { tryCatch( { # datasets <- read.csv(text = input$sample, header = FALSE, sep = ",") names <- c() units <- c() counts <-c() if (input$march){ names <- append(names, c("Covid-19 March 2020")) units<-append(units, c("Daily")) counts<-append(counts,c(covid_cases[1]))} if (input$april){ names <- append(names, c("Covid-19 April 2020")) units<-append(units, c("Daily")) counts<-append(counts,c(covid_cases[2]))} if (input$may){ names <- append(names, c("Covid-19 May 2020")) units<-append(units, c("Daily")) counts<-append(counts,c(covid_cases[3]))} if (input$june){ names <- append(names, c("Covid-19 June 2020")) units<-append(units, c("Daily")) counts<-append(counts,c(covid_cases[4]))} if (input$july){ names <- append(names, c("Covid-19 July 2020")) units<-append(units, c("Daily")) counts<-append(counts,c(covid_cases[5]))} warning_text <- "" # Ensure the dataset names are not duplicates. if (any(names %in% react_values$data_table[, 1])) { warning_text <- paste0(warning_text, sep = "
", "The rows contain dataset names which already exist." ) } output$sample_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" ) } } ) }) } # 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 ) } #Sample datasets case counts covid_cases = c("7,1,13,10,6,10,13,28,47,53,62,90,88,130,143,150,186,276,279,350,458,604,570,667,878,883,785,1085,1252", "1469,1278,1346,1119,1109,1120,1202,1429,1178,1337,1165,1312,1551,1633,1870,1688,1888,1702,1535,1549,1563,1583,1777,1511,1482,1298,1350,1422,1502,1546", "1499,1330,1232,1205,1101,1306,1317,1187,1115,997,953,903,1086,1101,1198,1133,1219,1057,954,1061,1056,1094,922,884,963,660,762,781,1038,763,827", "678,656,602,545,557,497,464,411,391,481,402,427,380,322,309,345,358,375,373,300,315,340,288,297,280,330,344,358,242,267", "315,291,267,284,244,220,269,313,359,343,348,351,277,362,451,443,517,490,457,472,507,509,573,497,425,408,344,493,405,466,455")