Add Shiny app dependencies add specify entry point

[Rnaught] / R / server.R

diff --git a/R/server.R b/R/server.R
index ed5ecd7454b8ae73047cc6212ef38725afdd606d..a9ed5216127811c565d31acefde5dda60994309f 100644 (file)
--- a/R/server.R
+++ b/R/server.R
@@ -110,7 +110,7 @@ server <- function(input, output) {
       if (!is.na(serial)) {
         reactive$estimators[[length(reactive$estimators) + 1]] <- list(
           method = "WP", mu = serial, mu_units = input$serialWPUnits,
-          search = list(B = 100, shape.max = 10, scale.max = 10))
+          grid_length = 100, max_shape = 10, max_scale = 10)
         reactive$est_table <- update_est_col(input, output, reactive$data_table,
           reactive$estimators[[length(reactive$estimators)]],
           reactive$est_table)
@@ -142,7 +142,7 @@ server <- function(input, output) {
           output$gridShapeWarn <- shiny::renderText("")
 
         if (is.na(max_scale) || max_scale < 1 / grid_length) {
-          output$gridShapeWarn <- shiny::renderText("Error: The maximum scale
+          output$gridScaleWarn <- shiny::renderText("Error: The maximum scale
             must be at least the reciprocal of the grid length.")
           checks_passed <- FALSE
         }
@@ -153,8 +153,7 @@ server <- function(input, output) {
       if (checks_passed) {
         reactive$estimators[[length(reactive$estimators) + 1]] <- list(
           method = "WP", mu = NA, mu_units = input$serialWPUnits,
-          search = list(B = grid_length, shape.max = max_shape,
-                        scale.max = max_scale))
+          grid_length = grid_length, max_shape = max_shape, max_scale = max_scale)
         reactive$est_table <- update_est_col(input, output, reactive$data_table,
           reactive$estimators[[length(reactive$estimators)]],
           reactive$est_table)
@@ -279,12 +278,15 @@ eval_estimator <- function(input, output, estimator, dataset) {
   else if (estimator$mu_units == "Weeks" && dataset[2] == "Daily")
     serial <- serial * 7
 
-  # White and Panago
+  # White and Pagano
   if (estimator$method == "WP") {
-    estimate <- WP(unlist(dataset[3]), mu = serial, search = estimator$search)
+    estimate <- wp(unlist(dataset[3]), mu = serial, serial = TRUE,
+                   grid_length = estimator$grid_length,
+                   max_shape = estimator$max_shape,
+                   max_scale = estimator$max_scale)
 
     if (!is.na(estimator$mu))
-      estimate <- round(estimate$Rhat, 2)
+      estimate <- round(estimate$r0, 2)
     # Display the estimated mean of the serial distribution if mu was not
     # specified.
     else {
@@ -292,21 +294,21 @@ eval_estimator <- function(input, output, estimator, dataset) {
         mu_units <- "days"
       else
         mu_units <- "weeks"
-      MSI <- sum(estimate$SD$supp * estimate$SD$pmf)
-      estimate <- shiny::HTML(paste0(round(estimate$Rhat, 2), "<br/>(&mu; = ",
+      MSI <- sum(estimate$supp * estimate$pmf)
+      estimate <- shiny::HTML(paste0(round(estimate$r0, 2), "<br/>(&mu; = ",
                                      round(MSI, 2), " ", mu_units, ")"))
     }
   }
   # Sequential Bayes
   else if (estimator$method == "seqB")
-    estimate <- round(seqB(unlist(dataset[3]), mu = serial,
-                           kappa = estimator$kappa)$Rhat, 2)
+    estimate <- round(seq_bayes(unlist(dataset[3]), mu = serial,
+                           kappa = estimator$kappa), 2)
   # Incidence Decay
   else if (estimator$method == "ID")
-    estimate <- round(ID(unlist(dataset[3]), mu = serial), 2)
+    estimate <- round(id(unlist(dataset[3]), mu = serial), 2)
   # Incidence Decay with Exponential Adjustement
   else if (estimator$method == "IDEA")
-    estimate <- round(IDEA(unlist(dataset[3]), mu = serial), 2)
+    estimate <- round(idea(unlist(dataset[3]), mu = serial), 2)
 
   return(estimate)
 }