From e920b3e514e717fc05ed524267d3b53e272fec51 Mon Sep 17 00:00:00 2001
From: Naeem Model <me@nmode.ca>
Date: Mon, 6 Jan 2025 23:55:43 +0000
Subject: Update web app entry point

- Rename 'app' -> 'web'
- Return shiny app object in entry point function
---
 inst/app/scripts/estimators.R | 327 ------------------------------------------
 1 file changed, 327 deletions(-)
 delete mode 100644 inst/app/scripts/estimators.R

(limited to 'inst/app/scripts/estimators.R')

diff --git a/inst/app/scripts/estimators.R b/inst/app/scripts/estimators.R
deleted file mode 100644
index 7c457ea..0000000
--- a/inst/app/scripts/estimators.R
+++ /dev/null
@@ -1,327 +0,0 @@
-# Main logic block for estimator-related interactions.
-estimators_logic <- function(input, output, react_values) {
-  # Initialize a data frame to hold estimates.
-  react_values$estimates_table <- data.frame(
-    Estimator = character(0),
-    `Serial interval` = character(0),
-    check.names = FALSE
-
-  )
-  # Initialize a list to hold added estimators.
-  react_values$estimators <- list()
-
-  add_id(input, output, react_values)
-  add_idea(input, output, react_values)
-  add_seq_bayes(input, output, react_values)
-  add_wp(input, output, react_values)
-
-  render_estimates(output, react_values)
-  delete_estimators(input, react_values)
-  export_estimates(output, react_values)
-}
-
-# If an estimator is added, ensure it is not a duplicate and add it to the list
-# of estimators. This function should be called at the end of each
-# estimator-specific 'add' function, after validating their parameters.
-add_estimator <- function(method, new_estimator, output, react_values) {
-  num_estimators <- length(react_values$estimators)
-
-  # Check whether the new estimator is a duplicate, and warn if so.
-  for (i in seq_len(num_estimators)) {
-    if (identical(new_estimator, react_values$estimators[[i]])) {
-      showNotification(
-        "Error: This estimator has already been added.", duration = 3
-      )
-      return()
-    }
-  }
-
-  # Add the new estimator to the list of estimators.
-  react_values$estimators[[num_estimators + 1]] <- new_estimator
-
-  showNotification("Estimator added successfully.", duration = 3)
-
-  # Evaluate the new estimator on all existing datasets and create a new row in
-  # the estimates table.
-  update_estimates_row(new_estimator, react_values)
-}
-
-# Ensure serial intervals are specified as positive numbers.
-validate_mu <- function(method, input, output) {
-  mu <- suppressWarnings(as.numeric(trimws(input[[paste0("mu_", method)]])))
-  if (is.na(mu) || mu <= 0) {
-    output[[paste0("mu_", method, "_warn")]] <- renderText(
-      "The serial interval must be a positive number."
-    )
-    return(NULL)
-  }
-  output[[paste0("mu_", method, "_warn")]] <- renderText("")
-  mu
-}
-
-# Incidence Decay (ID).
-add_id <- function(input, output, react_values) {
-  observeEvent(input$add_id, {
-    mu <- validate_mu("id", input, output)
-    if (!is.null(mu)) {
-      new_estimator <- list(
-        method = "id", mu = mu, mu_units = input$mu_id_units
-      )
-      add_estimator("id", new_estimator, output, react_values)
-    }
-  })
-}
-
-# Incidence Decay and Exponential Adjustment (IDEA).
-add_idea <- function(input, output, react_values) {
-  observeEvent(input$add_idea, {
-    mu <- validate_mu("idea", input, output)
-    if (!is.null(mu)) {
-      new_estimator <- list(
-        method = "idea", mu = mu, mu_units = input$mu_idea_units
-      )
-      add_estimator("idea", new_estimator, output, react_values)
-    }
-  })
-}
-
-# Sequential Bayes (seqB).
-add_seq_bayes <- function(input, output, react_values) {
-  observeEvent(input$add_seq_bayes, {
-    mu <- validate_mu("seq_bayes", input, output)
-
-    kappa <- trimws(input$kappa)
-    kappa <- if (kappa == "") 20 else suppressWarnings(as.numeric(kappa))
-
-    if (is.na(kappa) || kappa < 1) {
-      output$kappa_warn <- renderText(
-        "The maximum prior must be a number greater than or equal to 1."
-      )
-    } else if (!is.null(mu)) {
-      output$kappa_warn <- renderText("")
-      new_estimator <- list(
-        method = "seq_bayes", mu = mu,
-        mu_units = input$mu_seq_bayes_units, kappa = kappa
-      )
-      add_estimator("seq_bayes", new_estimator, output, react_values)
-    }
-  })
-}
-
-# White and Pagano (WP).
-add_wp <- function(input, output, react_values) {
-  observeEvent(input$add_wp, {
-    if (input$wp_mu_known == "Yes") {
-      mu <- validate_mu("wp", input, output)
-      if (!is.null(mu)) {
-        new_estimator <- list(method = "wp",
-          mu = mu, mu_units = input$mu_wp_units
-        )
-        add_estimator("wp", new_estimator, output, react_values)
-      }
-    } else {
-      grid_length <- trimws(input$grid_length)
-      max_shape <- trimws(input$max_shape)
-      max_scale <- trimws(input$max_scale)
-
-      suppressWarnings({
-        grid_length <- if (grid_length == "") 100 else as.numeric(grid_length)
-        max_shape <- if (max_shape == "") 10 else as.numeric(max_shape)
-        max_scale <- if (max_scale == "") 10 else as.numeric(max_scale)
-      })
-
-      valid <- TRUE
-
-      if (is.na(grid_length) || grid_length <= 0) {
-        output$grid_length_warn <- renderText(
-          "The grid length must be a positive integer."
-        )
-        valid <- FALSE
-      } else {
-        output$grid_length_warn <- renderText("")
-      }
-
-      if (is.na(max_shape) || max_shape <= 0) {
-        output$max_shape_warn <- renderText(
-          "The maximum shape must be a positive number."
-        )
-        valid <- FALSE
-      } else {
-        output$max_shape_warn <- renderText("")
-      }
-
-      if (is.na(max_scale) || max_scale <= 0) {
-        output$max_scale_warn <- renderText(
-          "The maximum scale must be a positive number."
-        )
-        valid <- FALSE
-      } else {
-        output$max_scale_warn <- renderText("")
-      }
-
-      if (valid) {
-        new_estimator <- list(method = "wp", mu = NA, grid_length = grid_length,
-          max_shape = max_shape, max_scale = max_scale
-        )
-        add_estimator("wp", new_estimator, output, react_values)
-      }
-    }
-  })
-}
-
-# Convert an estimator's specified serial interval to match the time units of
-# the given dataset.
-convert_mu_units <- function(data_units, estimator_units, mu) {
-  if (data_units == "Days" && estimator_units == "Weeks") {
-    return(mu * 7)
-  } else if (data_units == "Weeks" && estimator_units == "Days") {
-    return(mu / 7)
-  }
-  mu
-}
-
-# 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$data_table))
-  estimates <- c()
-
-  if (nrow(react_values$data_table) > 0) {
-    estimates <- dataset_rows
-    for (row in dataset_rows) {
-      estimate <- eval_estimator(estimator, react_values$data_table[row, ])
-      estimates[row] <- estimate
-    }
-  }
-
-  new_row <- data.frame(
-    t(c(estimator_name(estimator), estimator_mu_text(estimator), estimates))
-  )
-  colnames(new_row) <- colnames(react_values$estimates_table)
-
-  react_values$estimates_table <- rbind(
-    react_values$estimates_table, new_row
-  )
-}
-
-# Evaluate the specified estimator on the given dataset.
-eval_estimator <- function(estimator, dataset) {
-  cases <- as.integer(unlist(strsplit(dataset[, 3], ",")))
-
-  tryCatch(
-    {
-      if (estimator$method == "id") {
-        mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
-        estimate <- round(Rnaught::id(cases, mu), 2)
-      } else if (estimator$method == "idea") {
-        mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
-        estimate <- round(Rnaught::idea(cases, mu), 2)
-      } else if (estimator$method == "seq_bayes") {
-        mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
-        estimate <- round(Rnaught::seq_bayes(cases, mu, estimator$kappa), 2)
-      } else if (estimator$method == "wp") {
-        if (is.na(estimator$mu)) {
-          estimate <- Rnaught::wp(cases, serial = TRUE,
-            grid_length = estimator$grid_length,
-            max_shape = estimator$max_shape, max_scale = estimator$max_scale
-          )
-          estimated_mu <- round(sum(estimate$supp * estimate$pmf), 2)
-          mu_units <- if (dataset[, 2] == "Days") "day(s)" else "week(s)"
-          estimate <- paste0(
-            round(estimate$r0, 2), " (SI = ", estimated_mu, " ", mu_units, ")"
-          )
-        } else {
-          mu <- convert_mu_units(dataset[, 2], estimator$mu_units, estimator$mu)
-          estimate <- round(Rnaught::wp(cases, mu), 2)
-        }
-      }
-
-      return(estimate)
-    }, error = function(e) {
-      showNotification(
-        paste0(toString(e),
-          " [Estimator: ", sub(" .*", "", estimator_name(estimator)),
-          ", Dataset: ", dataset[, 1], "]"
-        ), duration = 6
-      )
-      return("—")
-    }
-  )
-}
-
-# Create the name of an estimator to be added to the first column of the
-# estimates table.
-estimator_name <- function(estimator) {
-  if (estimator$method == "id") {
-    return("ID")
-  } else if (estimator$method == "idea") {
-    return("IDEA")
-  } else if (estimator$method == "seq_bayes") {
-    return(paste0("seqB", " (&#954; = ", estimator$kappa, ")"))
-  } else if (estimator$method == "wp") {
-    if (is.na(estimator$mu)) {
-      return(paste0("WP (", estimator$grid_length, ", ",
-        round(estimator$max_shape, 3), ", ", round(estimator$max_scale, 3), ")"
-      ))
-    } else {
-      return("WP")
-    }
-  }
-}
-
-# Create the text to be displayed for the serial interval in the second column
-# of the estimates table.
-estimator_mu_text <- function(estimator) {
-  if (is.na(estimator$mu)) {
-    return("—")
-  }
-  mu_units <- if (estimator$mu_units == "Days") "day(s)" else "week(s)"
-  paste(estimator$mu, 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,
-      escape = FALSE, rownames = FALSE,
-      options = list(
-        columnDefs = list(list(className = "dt-left", targets = "_all"))
-      ),
-    )
-  })
-}
-
-# Delete rows from the estimates table and the corresponding estimators.
-delete_estimators <- function(input, react_values) {
-  observeEvent(input$estimators_delete, {
-    rows_selected <- input$estimates_table_rows_selected
-    react_values$estimators <- react_values$estimators[-rows_selected]
-    react_values$estimates_table <-
-      react_values$estimates_table[-rows_selected, ]
-  })
-}
-
-# Export estimates table as a CSV file.
-export_estimates <- function(output, react_values) {
-  output$estimates_export <- downloadHandler(
-    filename = function() {
-      paste0(
-        "Rnaught_estimates_", format(Sys.time(), "%y-%m-%d_%H-%M-%S"), ".csv"
-      )
-    },
-    content = function(file) {
-      output_table <- data.frame(
-        lapply(react_values$estimates_table, sub_entity)
-      )
-      colnames(output_table) <- sub_entity(
-        colnames(react_values$estimates_table)
-      )
-      write.csv(output_table, file, row.names = FALSE)
-    }
-  )
-}
-
-# Substitute HTML entity codes with natural names.
-sub_entity <- function(obj) {
-  obj <- gsub("&#954;", "kappa", obj)
-  obj
-}
-- 
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