update funcs

app.R

@@ -23,7 +23,7 @@ source("create_patient_module.R")
 source("about.R")
 source("funcs.R")
 
-dummy_df <- read_csv("dummy_df.csv",show_col_types = FALSE) 
+dummy_df <- read_csv("dummy_df.csv",show_col_types = FALSE)
 
 # load git data ####
 git_token <- Sys.getenv("GITHUB_PAT")
@@ -85,14 +85,7 @@ server <- function(input, output, session) {
   shiny::observe(session$setCurrentTheme(
     if (isTRUE(input$dark_mode)) dark else light
   ))
-  
-  shiny::observe({
-    updateSliderInput(session = session, 
-                      "sum_drug", 
-                      min = (input$drug_nervous+input$drug_muscle+input$drug_antineoplastic))
-    
-  })
-  
+
   inputData <- create_patient_Server("inputs")
   
   output$risk_vb <- renderUI({

create_patient_module.R

@@ -287,6 +287,13 @@ create_patient_Server <- function(id) {
   moduleServer(
     id,
     function(input, output, session) {
+      shiny::observe({
+        updateSliderInput(session = session, 
+                          "sum_drug", 
+                          min = (input$drug_nervous+input$drug_muscle+input$drug_antineoplastic))
+        
+      })
+      
       data <- reactive({
         sector <- ifelse(input$sector == "General",
                          sample(c("General","Religious Jewish"), size = 1),

funcs.R

@@ -3,7 +3,7 @@ library(sn)
 library(readr)
 
 prob_df <- read_csv("prob_df.csv",show_col_types = FALSE) %>%
-  mutate(model_prob = round(model_prob, 3)) %>%
+  mutate(model_prob = round(model_prob, 5)) %>%
   group_by(model_prob) %>%
   summarise(cal_prob = mean(cal_prob))
 
@@ -71,7 +71,8 @@ plot_close_side <- function(df, bkg_col = "white",txt_col = "black",
 
 syn_df <- function(dummy_df, df, model) {
   find_closest_n(dummy_df, model, 
-                 prob = generate_model(df, model), n = 1)  %>%
+                 prob = generate_model(df, model), 
+                 n = 1)  %>%
     bind_rows(df %>%
                 mutate(prob = generate_model(df, model))) %>%
     mutate(group = factor(c("dummy", "input"),
@@ -82,7 +83,7 @@ syn_df <- function(dummy_df, df, model) {
                                TRUE ~ "Codeine"),
            label = paste0(ifelse(gender_Male == 1, "Male", "Female"), ", Age ",RE_age, 
                           "\nGeneric: ", generic,
-                          "\nProbability ",round(prob,1),"%")
+                          "\nProbability ",round(prob,2),"%")
     ) %>%
     select(group,label,n_diagnosis, img_n, drug_antineoplastic, drug_muscle, n_visits) %>%
     pivot_longer(