From bd2bfa90dc7bb75cc6cbe8c6b674b7bcf486b519 Mon Sep 17 00:00:00 2001
From: kfiliyork <116465911+kfiliyork@users.noreply.github.com>
Date: Fri, 24 May 2024 17:30:01 -0400
Subject: Sample data and Upload data
---
data.R | 363 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 file changed, 363 insertions(+)
create mode 100644 data.R
(limited to 'data.R')
diff --git a/data.R b/data.R
new file mode 100644
index 0000000..a07372a
--- /dev/null
+++ b/data.R
@@ -0,0 +1,363 @@
+# 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")
+
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