# 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")