diff options
Diffstat (limited to 'inst/app/scripts')
| -rw-r--r-- | inst/app/scripts/data.R | 170 | ||||
| -rw-r--r-- | inst/app/scripts/estimators.R | 84 |
2 files changed, 110 insertions, 144 deletions
diff --git a/inst/app/scripts/data.R b/inst/app/scripts/data.R index 02b57c5..c85e27b 100644 --- a/inst/app/scripts/data.R +++ b/inst/app/scripts/data.R @@ -8,12 +8,12 @@ data_logic <- function(input, output, react_values) { 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) } @@ -23,91 +23,58 @@ 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) { +# 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") { @@ -171,8 +138,8 @@ validate_bulk_data <- function(input, output, react_values, data_source) { 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" @@ -225,8 +192,8 @@ load_samples <- function(input, output, react_values) { 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" @@ -236,30 +203,22 @@ load_samples <- function(input, output, react_values) { } # 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$estimates_table[, -(rows_selected + 2)] }) } @@ -276,26 +235,23 @@ export_data <- function(output, react_values) { } # When new datasets are added, evaluate all existing estimators on them and -# add new rows to the estimates table. -update_estimates_rows <- function(datasets, react_values) { - new_rows <- data.frame( - matrix(nrow = nrow(datasets), ncol = ncol(react_values$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 ) } diff --git a/inst/app/scripts/estimators.R b/inst/app/scripts/estimators.R index 171d197..b61f4d4 100644 --- a/inst/app/scripts/estimators.R +++ b/inst/app/scripts/estimators.R @@ -1,6 +1,12 @@ +# Main logic block for estimator-related interactions. estimators_logic <- function(input, output, react_values) { # Initialize a data frame to hold estimates. - react_values$estimates_table <- data.frame(Dataset = character(0)) + react_values$estimates_table <- data.frame( + Estimator = character(0), + `Serial interval` = character(0), + check.names = FALSE + + ) # Initialize a list to hold added estimators. react_values$estimators <- list() @@ -37,9 +43,9 @@ add_estimator <- function(method, new_estimator, output, react_values) { duration = 3, id = "notify-success" ) - # Evaluate all the new estimator on all existing datasets and create a new - # column in the estimates table. - update_estimates_col(new_estimator, react_values) + # Evaluate the new estimator on all existing datasets and create a new row in + # the estimates table. + update_estimates_row(new_estimator, react_values) } # Ensure serial intervals are specified as positive numbers. @@ -176,21 +182,26 @@ convert_mu_units <- function(data_units, estimator_units, mu) { mu } -# Add a column to the estimates table when a new estimator is added. -update_estimates_col <- function(estimator, react_values) { +# Add a row to the estimates table when a new estimator is added. +update_estimates_row <- function(estimator, react_values) { dataset_rows <- seq_len(nrow(react_values$data_table)) - estimates <- dataset_rows + estimates <- c() - for (row in dataset_rows) { - estimate <- eval_estimator(estimator, react_values$data_table[row, ]) - estimates[row] <- estimate + if (nrow(react_values$data_table) > 0) { + estimates <- dataset_rows + for (row in dataset_rows) { + estimate <- eval_estimator(estimator, react_values$data_table[row, ]) + estimates[row] <- estimate + } } - estimates <- data.frame(estimates) - colnames(estimates) <- estimates_col_name(estimates, estimator) + new_row <- data.frame( + t(c(estimator_name(estimator), estimator_mu_text(estimator), estimates)) + ) + colnames(new_row) <- colnames(react_values$estimates_table) - react_values$estimates_table <- cbind( - react_values$estimates_table, estimates + react_values$estimates_table <- rbind( + react_values$estimates_table, new_row ) } @@ -214,7 +225,7 @@ eval_estimator <- function(estimator, dataset) { max_shape = estimator$max_shape, max_scale = estimator$max_scale ) estimated_mu <- round(sum(estimate$supp * estimate$pmf), 2) - estimate <- paste0(round(estimate$r0, 2), " (μ = ", estimated_mu, + estimate <- paste0(round(estimate$r0, 2), " (SI = ", estimated_mu, " ", tolower(dataset[, 2]), ")" ) } else { @@ -226,39 +237,39 @@ eval_estimator <- function(estimator, dataset) { return(estimate) } -# Create the column name of an estimator when it is -# added to the estimates table. -estimates_col_name <- function(estimates, estimator) { +# Create the name of an estimator to be added to the first column of the +# estimates table. +estimator_name <- function(estimator) { if (estimator$method == "id") { - return(paste0("ID", " (μ = ", estimator$mu, " ", - tolower(estimator$mu_units), ")" - )) + return("ID") } else if (estimator$method == "idea") { - return(paste0("IDEA", " (μ = ", estimator$mu, " ", - tolower(estimator$mu_units), ")" - )) + return("IDEA") } else if (estimator$method == "seq_bayes") { - return(paste0("seqB", " (μ = ", estimator$mu, " ", - tolower(estimator$mu_units), ", κ = ", estimator$kappa, ")" - )) + return(paste0("seqB", " (κ = ", estimator$kappa, ")")) } else if (estimator$method == "wp") { if (is.na(estimator$mu)) { return(paste0("WP (", estimator$grid_length, ", ", round(estimator$max_shape, 3), ", ", round(estimator$max_scale, 3), ")" )) } else { - return(paste0("WP", " (μ = ", estimator$mu, " ", - tolower(estimator$mu_units), ")" - )) + return("WP") } } } +# Create the text to be displayed for the serial interval in the second column +# of the estimates table. +estimator_mu_text <- function(estimator) { + if (is.na(estimator$mu)) { + return("—") + } + paste(estimator$mu, tolower(estimator$mu_units)) +} + # Render the estimates table whenever it is updated. render_estimates <- function(output, react_values) { observe({ output$estimates_table <- DT::renderDataTable(react_values$estimates_table, - selection = list(target = "column", selectable = c(0)), escape = FALSE, rownames = FALSE, options = list( columnDefs = list(list(className = "dt-left", targets = "_all")) @@ -267,13 +278,13 @@ render_estimates <- function(output, react_values) { }) } -# Delete columns from the estimates table, -# as well as the corresponding estimators. +# Delete rows from the estimates table and the corresponding estimators. delete_estimators <- function(input, react_values) { observeEvent(input$estimators_delete, { - cols_selected <- input$estimates_table_columns_selected - react_values$estimators <- react_values$estimators[-cols_selected] - react_values$estimates_table[, cols_selected + 1] <- NULL + rows_selected <- input$estimates_table_rows_selected + react_values$estimators <- react_values$estimators[-rows_selected] + react_values$estimates_table <- + react_values$estimates_table[-rows_selected, ] }) } @@ -299,7 +310,6 @@ export_estimates <- function(output, react_values) { # Substitute HTML entity codes with natural names. sub_entity <- function(obj) { - obj <- gsub("μ", "mu", obj) obj <- gsub("κ", "kappa", obj) obj } |