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'

1 files changed, 0 insertions, 363 deletions

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 = "<br>",

-                           "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 = "<br>",

-                           "The rows contain duplicate dataset names."

-    )

-  }

-  

-  if (any(df_elems[[1]] %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(df_elems[[2]] %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(df_elems[[3]] == "")) {

-    warning_text <- paste0(warning_text, sep = "<br>",

-                           "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 = "<br>",

-                                 "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")

-