From 9cf25e707fbd49d357cf295ad62f83d805c59c2c Mon Sep 17 00:00:00 2001 From: Naeem Model Date: Sun, 26 May 2024 02:38:19 +0000 Subject: Update Shiny app - Refactor data upload and sample data - Create custom data upload button - Create script.js - Change Shiny notification colour - Bug fix: ensure the case counts in bulk data that have only one row are treated as a data frame, by wrapping them in 'data.frame' before passing to 'apply' --- data.R | 363 ----------------------------------------------------------------- 1 file changed, 363 deletions(-) delete mode 100644 data.R (limited to 'data.R') diff --git a/data.R b/data.R deleted file mode 100644 index a07372a..0000000 --- a/data.R +++ /dev/null @@ -1,363 +0,0 @@ -# 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") - -- cgit v1.2.3