# library(readr)
library(tidyr)
library(parsnip)
library(workflows)
library(xgboost)
library(shiny)
library(shinyWidgets)
library(bslib)
library(dplyr)
library(echarts4r)

# df <- readr::read_csv("data/dummy_data.csv")
# b <- board_folder(path = ".")
# v <- b |> 
#   vetiver_pin_read(name = "MoE")

model <- readRDS("MoE-model.rds")

ui <- fluidPage(
  # theme = bs_theme(bootswatch = "minty"),
  title = "Simulation of Study Success",
  # sidebar = sidebar(width = "20%", 
  #   , 
  #   hr()
  # ),
  column(6, 
    h1("Input"), 
    wellPanel(
      style = "background-color: transparent;", 
      fluidRow(
        style = "display: flex;", 
          prettySwitch("sex", "Male?", fill = TRUE, status = "primary"), 
          prettySwitch("playgroup", "Playgroup", fill = TRUE, status = "primary"), 
          prettySwitch("preelementary_school", "Pre-Elementary School", fill = TRUE, status = "primary"), 
          prettySwitch("gov_scholarship_holder", "Gov. Scholarship Holder", fill = TRUE, status = "primary"), 
          prettySwitch("parents_spc_need", "Parent have special needs?", fill = TRUE, status = "primary")
        ), 
        fluidRow(
          style = "display: flex;", 
          selectInput("parents_occupation_category", "Parents Occupation Category", 
                      choices = c("Civil Servants", "Labor Workers", "Private Employee"), 
                    width = "33.333%"),  
          numericInput("household_income", "Household Income", 4000000, min = 0, max = 19949598, 
                      width = "33.333%"), 
          selectInput("parents_education_level_cat", "Parent Education Level", 
                      choices = c("Bachelor", "Diploma", "Master/Doctorate", "Senior Highschool", "Junior Highschool", "Elementary School", "Unschooled"), 
                      width = "33.333%")
        ), 
        fluidRow(
          style = "display: flex;", 
          selectInput("school_location", "School Location", choices = c("Rural", "Urban"), width = "50%"), 
          numericInput("home_sch_dist", "School Distance (km)", value = 3, min = 0, width = "50%")
        ), 
        fluidRow(
          selectInput("highsch_major", "Highschool Major", width = "60%", 
                    choices = c("Natural Science", "Social Sciences", "Language Studies")), 
                  ), 
        fluidRow(
          style = "display: flex;", 
          numericInput("math_score", "Math Score", 50, min = 0, max = 100, width = "20%"), 
          numericInput("science_score", "Science Score", 50, min = 0, max = 100, width = "20%"), 
          numericInput("english_score", "English Score", 50, min = 0, max = 100, width = "20%"),
          numericInput("indonesian_score", "Bahasa Indonesia Score", 50, min = 0, max = 100, width = "20%"),
          numericInput("social_score", "Social Score", 50, min = 0, max = 100, width = "20%")
        ), 
        fluidRow(selectInput("university", "University", choices = c("Private", "Public")))

    ),
  ), 
  column(6, 
    h1("Output"), 
    wellPanel(
      echarts4rOutput("gpa_plot"), 
      style = "background-color: transparent;"
    )
  )
  # tableOutput("tblout") 
)

server <- function(input, output, session) {

  output$gpa_plot <- renderEcharts4r(
    {
      x <- data.frame(
        playgroup = ifelse(input$playgroup, "Yes", "No"),  
        preelementary_school = ifelse(input$preelementary_school, "Yes", "No"),
        gov_scholarship_holder = ifelse(input$gov_scholarship_holder, "Yes", "No"),
        home_sch_dist = input$home_sch_dist, 
        sex = ifelse(input$sex, "Male", "Female"), 
        school_location  = input$school_location, 
        parents_spc_need = ifelse(input$parents_spc_need, "Yes", "No"),
        highsch_major = input$highsch_major, 
        parents_occupation_category = input$parents_occupation_category, 
        household_income = input$household_income, 
        parents_educatioin_level_category = input$parents_education_level_cat, 
        math_score = input$math_score, 
        science_score = input$science_score, 
        english_score = input$english_score, 
        indonesian_score = input$indonesian_score, 
        social_score = input$social_score, 
        university = input$university
      )
  
      x <- x |> 
        tidyr::expand_grid(univ_major = c("International Relations", "IT Department", "Law Department", "Psychology Department", "Statistic and Data Science"))
      augment(x = model, new_data = x) |> 
              arrange(desc(.pred)) |> 
              slice_head(n = 5) |> 
              mutate(predict_GPA = round(.pred, 2)) |> 
              e_charts(univ_major) |> 
              e_bar(predict_GPA, label = list(show = TRUE)) |> 
        e_flip_coords() |> 
        e_x_axis(name = "Predicted GPA Final", nameLocation = "center", 
                  nameGap = 30, min = 0, max = 4, interval = 0.5) |>
        e_y_axis(name = "Univ. Major Schema", nameLocation = "start", inverse = TRUE) |> 
        e_grid(left = "20%", right = "5%") |> 
        e_legend(show = FALSE)
    }
  )
}

shinyApp(ui, server)