library(shiny)
library(dplyr)
library(data.table)
library(xgboost)
library(caret)
library(shinythemes)
calculate_timstuff <- function(data, pitch_type) {
    data_matrix <- as.matrix(data)
    if (pitch_type == "Offspeed") {
      mod <- xgb.load('Off.model')
      prediction <- predict(mod, data_matrix)
      timstuff <- (50 - (prediction - -0.002239657) / 0.01043216 * 10)
    } else {
      mod <- xgb.load('FB.model')
      prediction <- predict(mod, data_matrix)
      timstuff <- (50 - (prediction - -0.0011801) / 0.007989927 * 10)
    }
    return(timstuff)
  }
ui <- fluidPage(
  theme = shinytheme("flatly"),
  
  # Application title
  titlePanel("TimStuff Fastball/Offspeed Calculator"),
  
  # Sidebar with inputs
  sidebarLayout(
    sidebarPanel(
      width = 4,
      radioButtons("pitch", "Pitch Type", choices = c("Fastball", "Offspeed"), inline = TRUE),
      radioButtons("phand", "Hand", choices = c("R", "L"), inline = TRUE),
      
      numericInput("velo", "Velocity (mph)", value = 90, min = 70, max = 110, step = 1),
      numericInput("ivb", "Induced Vertical Break (in)", value = 16, min = -20, max = 30, step = 0.1),
      numericInput("hb", "Horizontal Break (in)", value = 6, min = -20, max = 20, step = 0.1),
      numericInput("spinrate", "Spin Rate (rpm)", value = 2300, min = 1000, max = 3500, step = 10),
      numericInput("ext", "Extension (ft)", value = 6, min = 5, max = 8, step = 0.1),
      numericInput("spinaxisdiff", "Spin Axis Difference (°)", value = 0, min = -180, max = 180, step = 1),
      numericInput("x0", "Horizontal Release Point (ft)", value = 0, min = -5, max = 5, step = 0.1),
      numericInput("z0", "Vertical Release Point (ft)", value = 5, min = 3, max = 8, step = 0.1),
      selectInput("feature_to_vary", "Select Feature to Vary:",
            choices = c("Velocity" = "start_speed",
                        "Induced Vertical Break" = "IVB",
                        "Horizontal Break" = "HB",
                        "Spin Rate" = "spin_rate",
                        "Extension" = "EAA",
                        "Spin Axis Difference" = "SADiff",
                        "Horizontal Release Point" = "x0",
                        "Vertical Release Point" = "z0"))
    ),
    
    # Main panel with output
    mainPanel(
      width = 8,
      wellPanel(
        h3("Results"),
        verbatimTextOutput("stuff"),
        plotOutput("feature_impact", height = "400px")  # Placeholder for future visualization
      )
    )
  )
)

server <- function(input, output) {
  observeEvent(input$pitch, {
    output$stuff <- renderText({
      data <- data.frame(
        start_speed = input$velo,
        IVB = input$ivb,
        HB = ifelse(input$phand == "L", -input$hb, input$hb),
        EAA = input$ext / 6.3,
        x0 = ifelse(input$phand == "L", -input$x0, input$x0),
        z0 = input$z0,
        spin_rate = input$spinrate,
        SADiff = input$spinaxisdiff
      )
      
      data <- as.matrix(data)
      
      if (input$pitch == "Offspeed") {
        mod <- xgb.load('Off.model')
        prediction <- predict(mod, data)
        TimStuff <- (50 - (prediction - -0.002239657) / 0.01043216 * 10)
      } else {
        mod <- xgb.load('FB.model')
        prediction <- predict(mod, data)
        TimStuff <- (50 - (prediction - -0.0011801) / 0.007989927 * 10)
      }
      
      paste("TimStuff:", round(TimStuff, 2), "\n20-80 Scale, 50 is Average, 1 SD is 10")
    })
    
    # Add this new reactive expression
    # Add this new reactive expression
  feature_range <- reactive({
    ranges <- list(
      start_speed = c(70, 110),
      IVB = c(-20, 30),
      HB = c(-20, 20),
      spin_rate = c(1000, 3500),
      EAA = c(5/6.3, 8/6.3),
      SADiff = c(-180, 180),
      x0 = c(-5, 5),
      z0 = c(3, 8)
    )
    ranges[[input$feature_to_vary]]
  })

  # Update the feature_impact plot
  output$feature_impact <- renderPlot({
    # Create base data frame with current inputs
    base_data <- data.frame(
      start_speed = input$velo,
      IVB = input$ivb,
      HB = ifelse(input$phand == "L", -input$hb, input$hb),
      EAA = input$ext / 6.3,
      x0 = ifelse(input$phand == "L", -input$x0, input$x0),
      z0 = input$z0,
      spin_rate = input$spinrate,
      SADiff = input$spinaxisdiff
    )
    
    # Generate sequence for the selected feature
    feature_seq <- seq(feature_range()[1], feature_range()[2], length.out = 100)
    
    # Calculate TimStuff for the sequence
    varied_data <- do.call(rbind, replicate(100, base_data, simplify = FALSE))
    varied_data[[input$feature_to_vary]] <- feature_seq
    timstuff <- calculate_timstuff(varied_data, input$pitch)
    
    # Create plot data
    plot_data <- data.frame(
      Feature = names(base_data)[which(names(base_data) == input$feature_to_vary)],
      Value = feature_seq,
      TimStuff = timstuff
    )
    
    # Create plot
    ggplot(plot_data, aes(x = Value, y = TimStuff)) +
      geom_line(color = "blue", size = 1) +
      geom_point(aes(x = base_data[[input$feature_to_vary]], 
                     y = calculate_timstuff(base_data, input$pitch)),
                 color = "red", size = 3) +
      theme_minimal() +
      ylim(0,100) +
      labs(title = paste("Impact of", input$feature_to_vary, "on TimStuff"),
           x = input$feature_to_vary, y = "TimStuff") +
      theme(text = element_text(size = 14))
  })
  })
}

# Run the application 
shinyApp(ui = ui, server = server)