check.names = FALSE
)
- render_plot(input, output)
- single_entry(input, output, react_values)
- manual_bulk_entry(input, output, react_values)
+ manual_entry(input, output, react_values)
upload_data(input, output, react_values)
load_samples(input, output, react_values)
- render_data(output, react_values)
+ render_data_table(output, react_values)
+ render_plot(input, output, react_values, "Days")
+ render_plot(input, output, react_values, "Weeks")
delete_data(input, react_values)
export_data(output, react_values)
}
suppressWarnings(as.integer(unlist(strsplit(trimws(counts_str), ","))))
}
-# Render the preview plot for single entry data.
-render_plot <- function(input, output) {
+# Render the plots for daily and weekly data when the data table is updated.
+render_plot <- function(input, output, react_values, time_units) {
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$data_units, ylab = "Cases", cex.lab = 1.5,
- xlim = c(0, max(length(counts) - 1, 1)), ylim = c(0, max(counts, 1))
+ datasets <- react_values$data_table[
+ which(react_values$data_table[["Time units"]] == time_units),
+ ]
+
+ data_plot <- plotly::plot_ly(type = "scatter", mode = "lines")
+ if (nrow(datasets) > 0) {
+ for (i in seq_len(nrow(datasets))) {
+ counts <- tokenize_counts(datasets[i, 3])
+ data_plot <- plotly::add_trace(data_plot,
+ x = seq_along(counts) - 1, y = counts, name = datasets[i, 1]
)
- )
- } else {
- output$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)
+ plot_title <- paste(
+ if (time_units == "Days") "Daily" else "Weekly", "case counts"
+ )
- # Evaluate all existing estimators on the new dataset and update the
- # corresponding row in the estimates table.
- update_estimates_rows(new_row, react_values)
+ data_plot <- plotly::layout(data_plot, title = plot_title,
+ xaxis = list(title = time_units), yaxis = list(title = "Cases")
+ )
- showNotification("Dataset added successfully.",
- duration = 3, id = "notify-success"
+ data_plot <- plotly::config(data_plot, displaylogo = FALSE,
+ toImageButtonOptions = list(
+ filename = paste0("Rnaught_data_", tolower(time_units), "_plot")
)
- }
+ )
+
+ output[[paste0("data_plot_", tolower(time_units))]] <-
+ plotly::renderPlotly(data_plot)
})
}
-manual_bulk_entry <- function(input, output, react_values) {
+# Validate and add manually-entered datasets.
+manual_entry <- function(input, output, react_values) {
observeEvent(input$data_bulk, {
- validate_bulk_data(input, output, react_values, "data_area")
+ validate_data(input, output, react_values, "data_area")
})
}
+# Validate and add datasets from a CSV file.
upload_data <- function(input, output, react_values) {
observeEvent(input$data_upload, {
- validate_bulk_data(input, output, react_values, "data_upload")
+ validate_data(input, output, react_values, "data_upload")
})
}
-validate_bulk_data <- function(input, output, react_values, data_source) {
+# Validate datasets and update the data table.
+validate_data <- function(input, output, react_values, data_source) {
tryCatch(
{
if (data_source == "data_area") {
react_values$data_table <- rbind(react_values$data_table, new_rows)
# Evaluate all existing estimators on the new datasets and update the
- # corresponding rows in the estimates table.
- update_estimates_rows(new_rows, react_values)
+ # corresponding columns in the estimates table.
+ update_estimates_cols(new_rows, react_values)
- showNotification("Datasets added successfully.",
- duration = 3, id = "notify-success"
- )
+ showNotification("Datasets added successfully.", duration = 3)
}
},
error = function(e) {
react_values$data_table <- rbind(react_values$data_table, new_rows)
# Evaluate all existing estimators on the sample datasets and update the
- # corresponding rows in the estimates table.
- update_estimates_rows(new_rows, react_values)
+ # corresponding columns in the estimates table.
+ update_estimates_cols(new_rows, react_values)
- showNotification("Datasets added successfully.",
- duration = 3, id = "notify-success"
- )
+ showNotification("Datasets added successfully.", duration = 3)
}
})
}
# Render the data table when new datasets are added.
-render_data <- function(output, react_values) {
+render_data_table <- function(output, react_values) {
observe({
- output$data_table <- DT::renderDataTable(react_values$data_table)
+ output$data_table <- DT::renderDataTable(
+ react_values$data_table, rownames = FALSE
+ )
})
}
-# Delete rows in the data table,
-# and the corresponding rows in the estimates table.
+# Delete rows in the data table and the corresponding columns 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, ]
- }
+ rows_selected <- input$data_table_rows_selected
+ react_values$data_table <- react_values$data_table[-rows_selected, ]
+ react_values$estimates_table <-
+ react_values$estimates_table[, -(rows_selected + 2)]
})
}
}
# When new datasets are added, evaluate all existing estimators on them and
-# add new rows to the estimates table.
-update_estimates_rows <- function(datasets, react_values) {
- new_rows <- data.frame(
- matrix(nrow = nrow(datasets), ncol = ncol(react_values$estimates_table))
+# add new columns to the estimates table.
+update_estimates_cols <- function(datasets, react_values) {
+ new_cols <- data.frame(
+ matrix(nrow = nrow(react_values$estimates_table), ncol = nrow(datasets))
)
- colnames(new_rows) <- colnames(react_values$estimates_table)
-
- for (row in seq_len(nrow(datasets))) {
- new_rows[row, 1] <- datasets[row, 1]
+ colnames(new_cols) <- datasets[, 1]
- if (length(react_values$estimators) > 0) {
- for (col in 2:ncol(react_values$estimates_table)) {
- new_rows[row, col] <- eval_estimator(
- react_values$estimators[[col - 1]], datasets[row, ]
- )
+ if (nrow(new_cols) > 0) {
+ for (row in seq_len(nrow(new_cols))) {
+ estimator <- react_values$estimators[[row]]
+ for (col in seq_len(ncol(new_cols))) {
+ new_cols[row, col] <- eval_estimator(estimator, datasets[col, ])
}
}
}
- react_values$estimates_table <- rbind(
- react_values$estimates_table, new_rows
+ react_values$estimates_table <- cbind(
+ react_values$estimates_table, new_cols
)
}
git.nmode.ca / Rnaught / blobdiff
