+++ /dev/null
-# Main logic block for data-related interactions.\r
-data_logic <- function(input, output, react_values) {\r
- # Initialize a data frame to hold the datasets.\r
- react_values$data_table <- data.frame(\r
- Name = character(0),\r
- `Time units` = character(0),\r
- `Case counts` = character(0),\r
- check.names = FALSE\r
- )\r
- \r
- render_plot(input, output)\r
- single_entry(input, output, react_values)\r
- bulk_entry(input, output, react_values)\r
- upload_entry(input, output, react_values)\r
- sample_entry(input, output, react_values)\r
- render_data(output, react_values)\r
- delete_data(input, react_values)\r
- export_data(output, react_values)\r
-}\r
-\r
-warnings <- function(df, df_elems) {\r
- \r
- warning_text <- ''\r
- \r
- # Ensure the dataset names are neither blank nor duplicates.\r
- if (anyNA(df_elems[[1]]) || any(df_elems[[1]] == "")) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "Each row must begin with a non-blank dataset name."\r
- )\r
- } \r
- \r
- if (length(unique(df_elems[[1]])) != length(df_elems[[1]])) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "The rows contain duplicate dataset names."\r
- )\r
- }\r
- \r
- if (any(df_elems[[1]] %in% react_values$data_table[, 1])) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "The rows contain dataset names which already exist."\r
- )\r
- }\r
- # Ensure the second entry in each row is a time unit equal to\r
- # "Days" or "Weeks".\r
- if (!all(df_elems[[2]] %in% c("Days", "Weeks"))) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "The second entry in each row must be either 'Days' or 'Weeks'."\r
- )\r
- }\r
- # Ensure the counts in each row have at least one non-negative integer.\r
- if (any(df_elems[[3]] == "")) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "Each row must contain at least one non-negative integer."\r
- )\r
- }\r
- return(warning_text)\r
-}\r
-\r
-\r
-# Convert the input case counts string to an integer vector.\r
-tokenize_counts <- function(counts_str) {\r
- suppressWarnings(as.integer(unlist(strsplit(trimws(counts_str), ","))))\r
-}\r
-\r
-# Render the preview plot for single entry data.\r
-render_plot <- function(input, output) {\r
- observe({\r
- counts <- tokenize_counts(input$data_counts)\r
- if (length(counts) > 0 && !anyNA(counts) && all(counts >= 0)) {\r
- output$data_plot <- renderPlot(\r
- plot(seq_along(counts) - 1, counts, type = "o", pch = 16, col = "black",\r
- xlab = input$data_units, ylab = "Cases", cex.lab = 1.5,\r
- xlim = c(0, max(length(counts) - 1, 1)), ylim = c(0, max(counts, 1))\r
- )\r
- )\r
- } else {\r
- output$data_plot <- renderPlot(\r
- plot(NULL, xlim = c(0, 10), ylim = c(0, 10),\r
- xlab = input$data_units, ylab = "Cases", cex.lab = 1.5\r
- )\r
- )\r
- }\r
- })\r
-}\r
-\r
-# Add a single dataset to the existing table.\r
-single_entry <- function(input, output, react_values) {\r
- observeEvent(input$data_single, {\r
- valid <- TRUE\r
- \r
- # Ensure the dataset name is neither blank nor a duplicate.\r
- name <- trimws(input$data_name)\r
- if (name == "") {\r
- output$data_name_warn <- renderText("The dataset name cannot be blank.")\r
- valid <- FALSE\r
- } else if (name %in% react_values$data_table[, 1]) {\r
- output$data_name_warn <- renderText(\r
- "There is already a dataset with the specified name."\r
- )\r
- valid <- FALSE\r
- } else {\r
- output$data_name_warn <- renderText("")\r
- }\r
- \r
- # Ensure the case counts are specified as a comma-separated of one or more\r
- # non-negative integers.\r
- counts <- tokenize_counts(input$data_counts)\r
- if (length(counts) == 0) {\r
- output$data_counts_warn <- renderText("Case counts cannot be blank.")\r
- valid <- FALSE\r
- } else if (anyNA(counts) || any(counts < 0)) {\r
- output$data_counts_warn <- renderText(\r
- "Case counts can only contain non-negative integers."\r
- )\r
- valid <- FALSE\r
- } else {\r
- output$data_counts_warn <- renderText("")\r
- }\r
- \r
- if (valid) {\r
- # Add the new dataset to the data table.\r
- new_row <- data.frame(name, input$data_units, toString(counts))\r
- colnames(new_row) <- c("Name", "Time units", "Case counts")\r
- react_values$data_table <- rbind(react_values$data_table, new_row)\r
- \r
- # Evaluate all existing estimators on the new dataset and update the\r
- # corresponding row in the estimates table.\r
- update_estimates_rows(new_row, react_values)\r
- \r
- showNotification("Dataset added successfully.",\r
- duration = 3, id = "notify-success"\r
- )\r
- }\r
- })\r
-}\r
-\r
-# Add multiple datasets to the existing table.\r
-bulk_entry <- function(input, output, react_values) {\r
- observeEvent(input$data_bulk, {\r
- tryCatch(\r
- {\r
- datasets <- read.csv(text = input$data_area, header = FALSE, sep = ",")\r
- \r
- names <- trimws(datasets[, 1])\r
- units <- trimws(datasets[, 2])\r
- counts <- apply(datasets[, 3:ncol(datasets)], 1,\r
- function(row) {\r
- row <- suppressWarnings(as.integer(row))\r
- toString(row[!is.na(row) & row >= 0])\r
- }\r
- )\r
- output$data_area_warn <- renderText("")\r
- warning_text <- warnings(datasets, list(names, units, counts))\r
- \r
- if (warning_text == "") {\r
- # Add the new datasets to the data table.\r
- new_rows <- data.frame(names, units, counts)\r
- colnames(new_rows) <- c("Name", "Time units", "Case counts")\r
- react_values$data_table <- rbind(react_values$data_table, new_rows)\r
- \r
- # Evaluate all existing estimators on the new dataset and update the\r
- # corresponding row in the estimates table.\r
- update_estimates_rows(new_rows, react_values)\r
- \r
- showNotification("Datasets added successfully.",\r
- duration = 3, id = "notify-success"\r
- )\r
- } else {\r
- output$data_area_warn <- renderUI(HTML(warning_text))\r
- }\r
- },\r
- error = function(e) {\r
- output$data_area_warn <- renderText(\r
- "The input does not match the required format."\r
- )\r
- }\r
- )\r
- })\r
-}\r
-\r
-# Upload datasets to the existing table.\r
-upload_entry <- function(input, output, react_values) {\r
- observeEvent(input$data_load, {\r
- tryCatch(\r
- {\r
- df <- read.csv(file = input$upload_csv$datapath)\r
- names <- trimws(df[, 1])\r
- units <- trimws(df[, 2])\r
- counts <- sapply(tokenize_counts(df[, 3:ncol(df)]),\r
- function(row) {\r
- row <- suppressWarnings(as.integer(row))\r
- toString(row[!is.na(row) & row >= 0])\r
- }\r
- )\r
- output$data_load_warn <- renderText("")\r
- warning_text <- ''\r
- warning_text <- warnings(df, list(names, units, counts))\r
- \r
- if (warning_text == "") {\r
- \r
- # Add the new datasets to the data table.\r
- new_rows <- read.csv(file = input$upload_csv$datapath)\r
- colnames(new_rows) <- c("Name", "Time units", "Case counts")\r
- react_values$data_table <- rbind(react_values$data_table, new_rows)\r
- \r
- # Evaluate all existing estimators on the new dataset and update the\r
- # corresponding row in the estimates table.\r
- update_estimates_rows(new_rows, react_values)\r
- \r
- showNotification("Datasets added successfully.",\r
- duration = 3, id = "notify-success")\r
- \r
- \r
- } else {\r
- output$data_load_warn <- renderUI(HTML(warning_text)) \r
- }\r
- },\r
- error = function(e) {\r
- output$data_load_warn <- renderText(\r
- "The input does not match the required format."\r
- )\r
- }\r
- )\r
- })\r
-}\r
-\r
-# Add sample datasets to the existing table.\r
-sample_entry <- function(input, output, react_values) {\r
- observeEvent(input$sample_entry, {\r
- tryCatch(\r
- {\r
- # datasets <- read.csv(text = input$sample, header = FALSE, sep = ",")\r
- \r
- names <- c()\r
- units <- c()\r
- counts <-c()\r
- \r
- if (input$march){\r
- names <- append(names, c("Covid-19 March 2020"))\r
- units<-append(units, c("Daily"))\r
- counts<-append(counts,c(covid_cases[1]))}\r
- if (input$april){ names <- append(names, c("Covid-19 April 2020"))\r
- units<-append(units, c("Daily"))\r
- counts<-append(counts,c(covid_cases[2]))}\r
- if (input$may){ names <- append(names, c("Covid-19 May 2020"))\r
- units<-append(units, c("Daily"))\r
- counts<-append(counts,c(covid_cases[3]))}\r
- \r
- \r
- if (input$june){ names <- append(names, c("Covid-19 June 2020"))\r
- units<-append(units, c("Daily"))\r
- counts<-append(counts,c(covid_cases[4]))}\r
- \r
- if (input$july){ names <- append(names, c("Covid-19 July 2020"))\r
- units<-append(units, c("Daily"))\r
- counts<-append(counts,c(covid_cases[5]))}\r
- \r
- warning_text <- ""\r
- \r
- # Ensure the dataset names are not duplicates.\r
- \r
- \r
- if (any(names %in% react_values$data_table[, 1])) {\r
- warning_text <- paste0(warning_text, sep = "<br>",\r
- "The rows contain dataset names which already exist."\r
- )\r
- \r
- }\r
- \r
- \r
- output$sample_area_warn <- renderUI(HTML(warning_text))\r
- \r
- if (warning_text == "") {\r
- # Add the new datasets to the data table.\r
- \r
- new_rows <- data.frame(names, units, counts)\r
- colnames(new_rows) <- c("Name", "Time units", "Case counts")\r
- react_values$data_table <- rbind(react_values$data_table, new_rows)\r
- \r
- # Evaluate all existing estimators on the new dataset and update the\r
- # corresponding row in the estimates table.\r
- update_estimates_rows(new_rows, react_values)\r
- \r
- showNotification("Datasets added successfully.",\r
- duration = 3, id = "notify-success"\r
- )\r
- }\r
- }\r
- )\r
- })\r
-}\r
-\r
-# Render the data table when new datasets are added.\r
-render_data <- function(output, react_values) {\r
- observe({\r
- output$data_table <- DT::renderDataTable(react_values$data_table)\r
- })\r
-}\r
-\r
-# Delete rows in the data table,\r
-# and the corresponding rows in the estimates table.\r
-delete_data <- function(input, react_values) {\r
- observeEvent(input$data_delete, {\r
- new_table <- react_values$data_table[-input$data_table_rows_selected, ]\r
- if (nrow(new_table) > 0) {\r
- rownames(new_table) <- seq_len(nrow(new_table))\r
- }\r
- react_values$data_table <- new_table\r
- \r
- if (ncol(react_values$estimates_table) == 1) {\r
- react_values$estimates_table <- data.frame(\r
- Datasets = react_values$data_table[, 1]\r
- )\r
- } else {\r
- react_values$estimates_table <-\r
- react_values$estimates_table[-input$data_table_rows_selected, ]\r
- }\r
- })\r
-}\r
-\r
-# Export data table as a CSV file.\r
-export_data <- function(output, react_values) {\r
- output$data_export <- downloadHandler(\r
- filename = function() {\r
- paste0("Rnaught_data_", format(Sys.time(), "%y-%m-%d_%H-%M-%S"), ".csv")\r
- },\r
- content = function(file) {\r
- write.csv(react_values$data_table, file, row.names = FALSE)\r
- }\r
- )\r
-}\r
-\r
-# When new datasets are added, evaluate all existing estimators on them and\r
-# add new rows to the estimates table.\r
-update_estimates_rows <- function(datasets, react_values) {\r
- new_rows <- data.frame(\r
- matrix(nrow = nrow(datasets), ncol = ncol(react_values$estimates_table))\r
- )\r
- colnames(new_rows) <- colnames(react_values$estimates_table)\r
- \r
- for (row in seq_len(nrow(datasets))) {\r
- new_rows[row, 1] <- datasets[row, 1]\r
- \r
- if (length(react_values$estimators) > 0) {\r
- for (col in 2:ncol(react_values$estimates_table)) {\r
- new_rows[row, col] <- eval_estimator(\r
- react_values$estimators[[col - 1]], datasets[row, ]\r
- )\r
- }\r
- }\r
- }\r
- \r
- react_values$estimates_table <- rbind(\r
- react_values$estimates_table, new_rows\r
- )\r
-}\r
-#Sample datasets case counts\r
-covid_cases = c("7,1,13,10,6,10,13,28,47,53,62,90,88,130,143,150,186,276,279,350,458,604,570,667,878,883,785,1085,1252",\r
- "1469,1278,1346,1119,1109,1120,1202,1429,1178,1337,1165,1312,1551,1633,1870,1688,1888,1702,1535,1549,1563,1583,1777,1511,1482,1298,1350,1422,1502,1546",\r
- "1499,1330,1232,1205,1101,1306,1317,1187,1115,997,953,903,1086,1101,1198,1133,1219,1057,954,1061,1056,1094,922,884,963,660,762,781,1038,763,827",\r
- "678,656,602,545,557,497,464,411,391,481,402,427,380,322,309,345,358,375,373,300,315,340,288,297,280,330,344,358,242,267",\r
- "315,291,267,284,244,220,269,313,359,343,348,351,277,362,451,443,517,490,457,472,507,509,573,497,425,408,344,493,405,466,455")\r
-\r
render_plot(input, output)
single_entry(input, output, react_values)
- bulk_entry(input, output, react_values)
+ manual_bulk_entry(input, output, react_values)
+ upload_data(input, output, react_values)
+ load_samples(input, output, react_values)
render_data(output, react_values)
delete_data(input, react_values)
export_data(output, react_values)
})
}
-# Add multiple datasets to the existing table.
-bulk_entry <- function(input, output, react_values) {
+manual_bulk_entry <- function(input, output, react_values) {
observeEvent(input$data_bulk, {
- tryCatch(
- {
- datasets <- read.csv(text = input$data_area, header = FALSE, sep = ",")
+ validate_bulk_data(input, output, react_values, "data_area")
+ })
+}
- names <- trimws(datasets[, 1])
- units <- trimws(datasets[, 2])
- counts <- apply(datasets[, 3:ncol(datasets)], 1,
- function(row) {
- row <- suppressWarnings(as.integer(row))
- toString(row[!is.na(row) & row >= 0])
- }
- )
+upload_data <- function(input, output, react_values) {
+ observeEvent(input$data_upload, {
+ validate_bulk_data(input, output, react_values, "data_upload")
+ })
+}
- warning_text <- ""
+validate_bulk_data <- function(input, output, react_values, data_source) {
+ tryCatch(
+ {
+ if (data_source == "data_area") {
+ datasets <- read.csv(text = input$data_area, header = FALSE, sep = ",")
+ } else if (data_source == "data_upload") {
+ datasets <- read.csv(
+ file = input$data_upload$datapath, header = FALSE, sep = ","
+ )
+ }
- # Ensure the dataset names are neither blank nor duplicates.
- if (anyNA(names) || any(names == "")) {
- warning_text <- paste0(warning_text, sep = "<br>",
- "Each row must begin with a non-blank dataset name."
- )
- } else {
- if (length(unique(names)) != length(names)) {
- warning_text <- paste0(warning_text, sep = "<br>",
- "The rows contain duplicate dataset names."
- )
- }
- if (any(names %in% react_values$data_table[, 1])) {
- warning_text <- paste0(warning_text, sep = "<br>",
- "The rows contain dataset names which already exist."
- )
- }
+ names <- trimws(datasets[, 1])
+ units <- trimws(datasets[, 2])
+ counts <- apply(data.frame(datasets[, 3:ncol(datasets)]), 1,
+ function(row) {
+ row <- suppressWarnings(as.integer(row))
+ toString(row[!is.na(row) & row >= 0])
}
+ )
- # Ensure the second entry in each row is a time unit equal to
- # "Days" or "Weeks".
- if (!all(units %in% c("Days", "Weeks"))) {
- warning_text <- paste0(warning_text, sep = "<br>",
- "The second entry in each row must be either 'Days' or 'Weeks'."
+ warning_text <- ""
+
+ # Ensure the dataset names are neither blank nor duplicates.
+ if (anyNA(names) || any(names == "")) {
+ warning_text <- paste0(warning_text,
+ "Each row must begin with a non-blank dataset name.<br>"
+ )
+ } else {
+ if (length(unique(names)) != length(names)) {
+ warning_text <- paste0(warning_text,
+ "The rows contain duplicate dataset names.<br>"
)
}
-
- # Ensure the counts in each row have at least one non-negative integer.
- if (any(counts == "")) {
- warning_text <- paste0(warning_text, sep = "<br>",
- "Each row must contain at least one non-negative integer."
+ if (any(names %in% react_values$data_table[, 1])) {
+ warning_text <- paste0(warning_text,
+ "The rows contain dataset names which already exist.<br>"
)
}
+ }
- output$data_area_warn <- renderUI(HTML(warning_text))
+ # Ensure the second entry in each row is a time unit equal to
+ # "Days" or "Weeks".
+ if (!all(units %in% c("Days", "Weeks"))) {
+ warning_text <- paste0(warning_text,
+ "The second entry in each row must be either 'Days' or 'Weeks'.<br>"
+ )
+ }
- 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)
+ # Ensure the counts in each row have at least one non-negative integer.
+ if (any(counts == "")) {
+ warning_text <- paste0(warning_text,
+ "Each row must contain at least one non-negative integer.<br>"
+ )
+ }
- # Evaluate all existing estimators on the new dataset and update the
- # corresponding row in the estimates table.
- update_estimates_rows(new_rows, react_values)
+ output[[paste0(data_source, "_warn")]] <- renderUI(HTML(warning_text))
- showNotification("Datasets added successfully.",
- duration = 3, id = "notify-success"
- )
- }
- },
- error = function(e) {
- output$data_area_warn <- renderText(
- "The input does not match the required format."
+ if (warning_text == "") {
+ # Add the new datasets to the data table.
+ new_rows <- data.frame(names, units, counts)
+ colnames(new_rows) <- c("Name", "Time units", "Case counts")
+ react_values$data_table <- rbind(react_values$data_table, new_rows)
+
+ # Evaluate all existing estimators on the new datasets and update the
+ # corresponding rows in the estimates table.
+ update_estimates_rows(new_rows, react_values)
+
+ showNotification("Datasets added successfully.",
+ duration = 3, id = "notify-success"
)
}
- )
+ },
+ error = function(e) {
+ output[[paste0(data_source, "_warn")]] <- renderText(
+ "The input does not match the required format."
+ )
+ }
+ )
+}
+
+# Load sample datasets.
+load_samples <- function(input, output, react_values) {
+ observeEvent(input$data_samples, {
+ names <- c()
+ units <- c()
+ counts <- c()
+
+ # COVID-19 Canada, March 2020 (weekly).
+ if (input$covid_canada) {
+ names <- c(names, "COVID-19 Canada 2020/03/03 - 2020/03/31")
+ units <- c(units, "Weeks")
+ counts <- c(counts, toString(Rnaught::COVIDCanada[seq(41, 69, 7), 2]))
+ }
+ # COVID-19 Ontario, March 2020 (weekly).
+ if (input$covid_ontario) {
+ names <- c(names, "COVID-19 Ontario 2020/03/03 - 2020/03/31")
+ units <- c(units, "Weeks")
+ counts <- c(counts,
+ toString(Rnaught::COVIDCanadaPT[seq(10176, 10204, 7), 3])
+ )
+ }
+
+ if (length(names) == 0) {
+ output$data_samples_warn <- renderText(
+ "At least one sample dataset must be selected."
+ )
+ } else if (any(names %in% react_values$data_table[, 1])) {
+ output$data_samples_warn <- renderText(
+ "At least one of the selected dataset names already exist."
+ )
+ } else {
+ output$data_samples_warn <- renderText("")
+
+ 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 sample datasets and update the
+ # corresponding rows in the estimates table.
+ update_estimates_rows(new_rows, react_values)
+
+ showNotification("Datasets added successfully.",
+ duration = 3, id = "notify-success"
+ )
+ }
})
}
git.nmode.ca / Rnaught / commitdiff
