library(shiny)
library(plotly)
library(gridlayout)
library(bslib)
library(DT)
library(rsconnect)
library(baseballr)
library(dplyr)
library(tidyverse)
library(rvest)
library(ggplot2)
library(janitor)
library(ggthemes)
library(ggpubr)
library(jsonlite)
library(utils)
library(grid)
library(gridExtra)
library(png)
library(xgboost)
library(httr)
library(jpeg)
library(zoo)  # For rolling mean calculation

pdf(file = NULL)
Sys.setenv(TZ='EST')

# Helper functions
download_and_process_image <- function(url) {
  tryCatch({
    response <- GET(url)
    content_type <- http_type(response)
    
    if (content_type %in% c("image/png", "image/jpeg")) {
      temp_file <- tempfile(fileext = ifelse(content_type == "image/png", ".png", ".jpg"))
      writeBin(content(response, "raw"), temp_file)
      
      if (content_type == "image/png") {
        img <- readPNG(temp_file)
      } else {
        img <- readJPEG(temp_file)
      }
      
      return(list(img = img, type = content_type))
    } else {
      warning(paste("Unsupported image type:", content_type))
      return(NULL)
    }
  }, error = function(e) {
    warning(paste("Error processing image:", e$message))
    return(NULL)
  })
}

is_barrel <- function(df) {
  df$barrel <- with(df, ifelse(hit_angle <= 50 & hit_speed >= 97 & hit_speed * 1.5 - 
                                 hit_angle >= 117 & hit_speed + hit_angle >= 123, 1, 0))
  return(df)
}

VAA <- function(milbtotal){
  milbtotal <- milbtotal %>%
    mutate(VAA = -atan((vz0+(az*(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))-vy0)/
                               ay))/(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))))*(180/pi))
} 

pitcher_summary <- function(game_pk,date){
  gdate <- as.Date.character(date)
  gdate <- as.Date(gdate)
  tmilb <- mlb_pbp(game_pk)
  tmilb <- tmilb %>%
    filter(type == "pitch")
  tmilb <- tmilb %>%
    select(matchup.batter.fullName,matchup.batter.id,matchup.pitcher.fullName,
           matchup.pitcher.id,result.event,details.description,details.type.description,
           result.description,pitchData.startSpeed,pitchData.plateTime,pitchData.zone,
           pitchData.breaks.spinRate,pitchData.extension, pitchData.coordinates.pX,
           pitchData.coordinates.pZ,pitchData.coordinates.x0, pitchData.coordinates.y0,
           pitchData.coordinates.z0,pitchData.coordinates.aX,pitchData.coordinates.aY,
           pitchData.coordinates.aZ,pitchData.coordinates.vX0,pitchData.coordinates.vZ0,
           pitchData.coordinates.vY0,pitchData.coordinates.pfxX,pitchData.coordinates.pfxZ,
           pitchData.breaks.breakVerticalInduced,pitchData.breaks.breakHorizontal,
           hitData.launchSpeed,hitData.launchAngle,hitData.totalDistance,details.isInPlay,
           last.pitch.of.ab,pitchData.breaks.spinDirection,matchup.pitchHand.code)
  colnames(tmilb) <- c("Batter Name","Batter ID","Pitcher Name","Pitcher ID",
                       "result","description","pitch_name","des","start_speed",
                       "plateTime","zone","spin_rate","extension","px","pz","x0",
                       "y0","z0","ax","ay","az","vx0","vz0","vy0","pfxX","pfxZ",
                       "IVB","HB","hit_speed","hit_angle","hit_distance","inPlay",
                       "lastPitch","spinDirection","phand")
  tmilb <- is_barrel(tmilb)
  tmilb <- tmilb %>%
    mutate(is_strike_swinging = ifelse(description == "Swinging Strike" |
                                         description == "Foul Tip",TRUE,FALSE))
  tmilb <- tmilb %>%
    mutate(date = gdate)
  return(tmilb)
}

break_plot <- function(game){
  ggplot(game, aes(x = HB, y = IVB, color = pitch_name)) +
    geom_point(size = 2) +
    geom_vline(xintercept = 0, color = "lightblue", linewidth = 1, linetype = 4) +
    geom_hline(yintercept = 0, color = "lightblue", linewidth = 1, linetype = 4) +
    labs(x = "Horizontal Break (in)", y = "Induced Vertical Break (in)", 
         title = "Pitch Movement") +
    xlim(-25, 25) +
    ylim(-25, 25) +
    # scale_x_continuous(breaks = seq(-20, 20, by = 20)) +
    # scale_y_continuous(breaks = seq(-20, 20, by = 20)) +
    theme_minimal() +
    theme(
      legend.position = "bottom",
      plot.title = element_text(hjust = 0.5, face = "bold"),
      panel.grid.minor = element_line(color = "gray", size = 0.25, linetype = 1),
      aspect.ratio = 1  # This ensures the plot is square
    ) +
    guides(color = guide_legend(title = "Pitch Type", nrow = 1))
}

pitch_plot <- function(game){
  ggplot(game, aes(x = px, y = pz, color = pitch_name)) +
    geom_point(size = 3.5) +
    geom_segment(aes(x = -0.71, xend = 0.71, y = 1.5, yend = 1.5)) +
    geom_segment(aes(x = -0.71, xend = 0.71, y = 3.6, yend = 3.6)) +
    geom_segment(aes(x = 0.71, xend = 0.71, y = 1.5, yend = 3.6)) +
    geom_segment(aes(x = -0.71, xend = -0.71, y = 1.5, yend = 3.6)) +
    labs(x = NULL, y = NULL, title = "Pitch Location") +
    xlim(-3, 3) +
    ylim(0.2, 4) +
    coord_fixed(ratio = 1) +
    theme_minimal() +
    theme(
      legend.position = "bottom",
      plot.title = element_text(hjust = 0.5, face = "bold"),
      axis.text = element_blank(),
      axis.ticks = element_blank()
    ) +
    guides(color = guide_legend(title = "Pitch Type", nrow = 1))
}

# Load models
# FB <- xgb.load('FB.model')
# Off <- xgb.load('Off.model')
# Break <- xgb.load('Break.model')
model <- xgb.load('TimStuff2.model')

calculate_VAA <- function(vz0, ay, az, vy0, y0) {
  -atan((vz0+(az*(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))-vy0)/
                ay))/(-sqrt((vy0*vy0)-(2*ay*(y0-(17/12))))))*(180/pi)
}

calculate_EAA <- function(extension) {
  extension / 6.3
}

calculate_SADiff <- function(pfxX, pfxZ, spinDirection) {
  inSA <- atan2(pfxZ, pfxX) * 180/pi + 90
  inSA <- ifelse(inSA < 0, inSA + 360, inSA)
  SADiff <- spinDirection - inSA
  SADiff <- ifelse(SADiff > 180, SADiff - 360, SADiff)
  SADiff <- ifelse(SADiff < -180, SADiff + 360, SADiff)
  return(SADiff)
}

scale_TimStuff <- function(raw_score, model_mean, model_sd) {
  scaled_score <- (raw_score - model_mean) / model_sd
  result <- 100 - (scaled_score * 10)
  return(result)
}

calculate_primary <- function(data){
  data <- data %>%
    group_by(pitch_name, `Pitcher Name`, `Pitcher ID`, date) %>%
    mutate(
      pitch_count = n(),
      avg_start_speed = mean(start_speed, na.rm = TRUE),
      avg_IVB = mean(IVB, na.rm = TRUE),
      avg_HB = mean(HB, na.rm = TRUE)
    ) %>%
    ungroup() %>%
    group_by(`Pitcher Name`, `Pitcher ID`, date) %>%
    mutate(
      is_highest_occurrence = case_when(
        pitch_count == max(pitch_count) ~ 1,
        TRUE ~ 0
      )
    ) %>%
    mutate(
      is_highest_occurrence = case_when(
        is_highest_occurrence == 1 & pitch_count == max(pitch_count[is_highest_occurrence == 1]) & 
          avg_start_speed == max(avg_start_speed[is_highest_occurrence == 1]) ~ 1,
        TRUE ~ 0
      )
    ) %>%
    mutate(
      primary_speed = avg_start_speed[is_highest_occurrence == 1][1],
      primary_IVB = avg_IVB[is_highest_occurrence == 1][1],
      primary_HB = avg_HB[is_highest_occurrence == 1][1]
    ) %>%
    ungroup()
}

calculate_timstuff <- function(game) {
  game <- calculate_primary(game)
  game <- game %>%
    mutate(VAA = calculate_VAA(vz0, ay, az, vy0, y0),
           EAA = calculate_EAA(extension),
           SADiff = calculate_SADiff(pfxX, pfxZ, spinDirection),
           team_fielding_id = ifelse(description %in% c("Called Strike", "Swinging Strike", "Swinging Strike (Blocked)"), 1, 0),
           swing = ifelse(description %in% c("Foul", "Foul Pitchout", "In play, no out", "In play, out(s)", "In play, run(s)", "Swinging Strike", "Swinging Strike (Blocked)", "Foul Tip"), 1, 0),
           is_strike_swinging = ifelse(is_strike_swinging, 1, 0),
           Pitch = pitch_name,
           ishandL = ifelse(phand == "L",1,0))
  
  feature_vars <- c("ishandL","start_speed", "IVB", "HB", "EAA", "x0", "z0", "spin_rate","SADiff","primary_speed","primary_IVB","primary_HB")
  complete_rows <- complete.cases(game[, feature_vars])
  game_complete <- game[complete_rows, ]
  game_na <- game[!complete_rows,]
  game_na$TimStuff <- NA
  
  rhp <- game_complete
  
  rhp$TimStuff <- scale_TimStuff(predict(model, as.matrix(cbind(rhp$ishandL,rhp$start_speed, rhp$IVB, rhp$HB, rhp$EAA, rhp$x0, rhp$z0, rhp$spin_rate, rhp$SADiff,rhp$primary_speed,rhp$primary_IVB,rhp$primary_HB))), -0.00249975,  0.007566558)
  
  game_complete <- rbind(rhp,game_na)
  return(game_complete)
}

summary_table <- function(game) {
  rows <- nrow(game)
  game <- calculate_primary(game)
  game <- calculate_timstuff(game)
  sumtable <- game %>%
    mutate(team_fielding_id = ifelse(description == "Called Strike" |
                                       description == "Swinging Strike" |
                                       description == "Swinging Strike (Blocked)", 1, 0)) %>%
    mutate(swing = ifelse(description == "Foul" |
                            description == "Foul Pitchout" |
                            description == "In play, no out" |
                            description == "In play, out(s)" | 
                            description == "In play, run(s)" | 
                            description == "Swinging Strike" | 
                            description == "swinging Strike (Blocked)" |
                            description == "Foul Tip", 1, 0)) %>%
    mutate(is_strike_swinging = ifelse(is_strike_swinging == TRUE, 1, 0)) %>%
    mutate(Pitch = pitch_name) %>%
    rowwise() %>%
    group_by(Pitch) %>%
    summarize(
      Pitches = n(),
      'Pitch%' = round(sum(Pitches)/sum(rows) * 100, digits = 1),
      'Avg. Velo' = round(mean(start_speed, na.rm = TRUE), digits = 1),
      'Spin Rate' = round(mean(spin_rate, na.rm = TRUE), digits = 0),
      'Extension' = round(mean(extension, na.rm = TRUE), digits = 1),
      'IVB' = round(mean(IVB, na.rm = TRUE), digits = 1),
      'HB' = round(mean(HB, na.rm = TRUE), digits = 1),
      'VAA' = round(mean(VAA, na.rm = TRUE), digits = 1),
      'CSW%' = round(sum(team_fielding_id, na.rm = TRUE) / sum(!is.na(team_fielding_id)) * 100, digits = 1),
      'Whiff%' = round(sum(is_strike_swinging, na.rm = TRUE) / sum(swing, na.rm = TRUE) * 100, digits = 1),
      'TimStuff+' = round(mean(TimStuff, na.rm = TRUE), digits = 0)
    ) %>%
    arrange(-Pitches)
  
  result <- sumtable %>%
    select(Pitch, Pitches, `Pitch%`, `Avg. Velo`, `Spin Rate`, Extension,IVB, HB, VAA, `CSW%`, `Whiff%`, `TimStuff+`) %>%
    rename(
      "Type" = Pitch,
      "#" = Pitches,
      "Velo" = `Avg. Velo`,
      "Spin" = `Spin Rate`,
      "Ext" = Extension,
      "Use%" = `Pitch%`
    ) %>%
    mutate(
      "Use%" = paste0(`Use%`, "%"),
      "Spin" = format(round(Spin), big.mark = ","),
      Velo = round(Velo, 1),
      Ext = round(Ext, 1),
      IVB = round(IVB, 1),
      HB = round(HB, 1),
      VAA = round(VAA, 1),
      `CSW%` = paste0(`CSW%`, "%"),
      `Whiff%` = paste0(`Whiff%`, "%")
    ) %>%
    arrange(desc(`#`))
  
  return(result)
}

# Initialize schedule data
mlbid <- mlb_schedule(season = 2024, level_ids = "1")
mlbteamH <- mlbid %>%
  select(teams_home_team_name)
mlbteamH <- distinct(mlbteamH)
mlbteamA <- mlbid %>%
  select(teams_away_team_name)
mlbteamA <- distinct(mlbteamA)

aaaid <- mlb_schedule(season = 2024, level_ids = "11")
aaateamH <- aaaid %>%
  select(teams_home_team_name)
aaateamH <- distinct(aaateamH)
aaateamA <- aaaid %>%
  select(teams_away_team_name)
aaateamA <- distinct(aaateamA)

fslid <- mlb_schedule(season = 2024, level_ids = "14")
fslid <- fslid %>%
  filter(teams_home_team_name == "Daytona Tortugas" |
           teams_home_team_name == "Jupiter Hammerheads" |
           teams_home_team_name == "Palm Beach Cardinals" |
           teams_home_team_name == "St. Lucie Mets" |
           teams_home_team_name == "Bradenton Marauders" |
           teams_home_team_name == "Clearwater Threshers" |
           teams_home_team_name == "Dunedin Blue Jays" |
           teams_home_team_name == "Fort Myers Mighty Mussels" |
           teams_home_team_name == "Lakeland Flying Tigers" |
           teams_home_team_name == "Tampa Tarpons")
fslteamH <- fslid %>%
  select(teams_home_team_name)
fslteamH <- distinct(fslteamH)
fslteamA <- fslid %>%
  select(teams_away_team_name)
fslteamA <- distinct(fslteamA)

sbid <- mlb_schedule(season = 2024, level_ids = "22")
sbteamH <- sbid %>%
  select(teams_home_team_name)
sbteamH <- distinct(sbteamH)
sbteamA <- sbid %>%
  select(teams_away_team_name)
sbteamA <- distinct(sbteamA)

# UI Definition
ui <- fluidPage(
  theme = bs_theme(version = 5, bootswatch = "flatly"),
  titlePanel("2024 MLB/AAA/FSL Summary Cards"),
  sidebarLayout(
    sidebarPanel(
      width = 3,
      dateInput("date", "Date:", value = Sys.Date()),
      selectizeInput("level", "Level:", 
                     c("MLB", "AAA", "FSL", "College (Statcast Parks Only)"),
                     options = list(
                       placeholder = 'Select a level',
                       onInitialize = I('function() { this.setValue(""); }')
                     )),
      selectizeInput("homeT", "Home Team:", NULL),
      selectizeInput("awayT", "Away Team:", NULL),
      selectizeInput("gamenum", "Game Number:", c("1", "2")),
      actionButton("update", "Find Pitcher", icon("magnifying-glass"),
                   class = "btn-primary btn-block"),
      selectizeInput("pitcher", "Pitcher Name:", NULL),
      #textInput("title", "Card Title"),
      actionButton("update1", "Make Card", icon("plus"),
                   class = "btn-success btn-block"),
      downloadButton("downloadPlot", "Download Card", class = "btn-info btn-block")
    ),
    mainPanel(
      plotOutput("combinedPlot", height = "900px", width = "100%")
    )
  )
)

server <- function(input, output, session) {
  observeEvent(input$level, {
    if(input$level == "AAA"){
      updateSelectizeInput(session, "homeT", "Home Team:", choices = aaateamH[,1])
      updateSelectizeInput(session, "awayT", "Away Team:", choices = aaateamA[,1])
    }
    if(input$level == "FSL"){
      updateSelectizeInput(session, "homeT", "Home Team:", choices = fslteamH[,1])
      updateSelectizeInput(session, "awayT", "Away Team:", choices = fslteamA[,1])
    }
    if(input$level == "MLB"){
      updateSelectizeInput(session, "homeT", "Home Team:", choices = mlbteamH[,1])
      updateSelectizeInput(session, "awayT", "Away Team:", choices = mlbteamA[,1])
    }
    if(input$level == "College (Statcast Parks Only)"){
      updateSelectizeInput(session, "homeT", "Home Team:", choices = sbteamH[,1])
      updateSelectizeInput(session, "awayT", "Away Team:", choices = sbteamA[,1])
    }
  })
  
  game_data <- reactiveVal()
  
  observeEvent(input$update, {
    tryCatch({
      if(input$level == "AAA"){
        pname <- aaaid %>%
          filter(date == input$date) %>%
          filter(teams_home_team_name == input$homeT) %>%
          filter(teams_away_team_name == input$awayT) %>%
          filter(game_number == input$gamenum)
        pname <- pitcher_summary(pname[,6], input$date)
      }
      if(input$level == "FSL"){
        pname <- fslid %>%
          filter(date == input$date) %>%
          filter(teams_home_team_name == input$homeT) %>%
          filter(teams_away_team_name == input$awayT) %>%
          filter(game_number == input$gamenum)
        pname <- pitcher_summary(pname[,6], input$date)
      }
      if(input$level == "MLB"){
        pname <- mlbid %>%
          filter(date == as.character.Date(input$date)) %>%
          filter(teams_home_team_name == input$homeT) %>%
          filter(teams_away_team_name == input$awayT) %>%
          filter(game_number == input$gamenum)
        pname <- pitcher_summary(pname[,6], input$date)
      }
      if(input$level == "College (Statcast Parks Only)"){
        pname <- sbid %>%
          filter(date == input$date) %>%
          filter(teams_home_team_name == input$homeT) %>%
          filter(teams_away_team_name == input$awayT) %>%
          filter(game_number == input$gamenum)
        pname <- pitcher_summary(pname[,6], input$date)
      }
      
      if(nrow(pname) == 0) {
        showNotification("No pitchers found for the selected game.", type = "warning")
      } else {
        updateSelectizeInput(session, "pitcher", "Pitcher:", choices = unique(pname$`Pitcher Name`))
        game_data(pname)
      }
    }, error = function(e) {
      showNotification(paste("Error finding pitchers:", e$message), type = "error")
    })
  })
  
  rolling_timstuff <- reactive({
    req(input$update1, game_data())
    game <- game_data() %>% filter(`Pitcher Name` == input$pitcher)
    game <- calculate_timstuff(game)
    game %>%
      arrange(date) %>%
      group_by(pitch_name) %>%
      mutate(rolling_timstuff = rollmean(TimStuff, k = 5, fill = NA, align = "right"),
             pitch_number = row_number()) %>%
      ungroup()  # Make sure to ungroup after the grouping operations
  })
  
  combinedPlot <- reactiveVal()
  observeEvent(input$update1, {
    req(game_data())
    tryCatch({
      game <- game_data() %>% filter(`Pitcher Name` == input$pitcher)
      
      if(nrow(game) == 0) {
        showNotification("No data available for the selected pitcher.", type = "warning")
        return()
      }
      
      break_plot <- break_plot(game) +
        theme(legend.position = "none")
      
      pitch_plot <- pitch_plot(game) +
        theme(legend.position = "none")
      
      # Create a formatted table
      table_data <- summary_table(game)
      num_rows <- nrow(table_data)
      
      table_plot <- tableGrob(table_data, rows = NULL, theme = ttheme_minimal(
        core = list(fg_params = list(hjust = 0.5, x = 0.5), bg_params = list(fill = "white")),
        colhead = list(fg_params = list(hjust = 0.5, x = 0.5, fontface = "bold"), bg_params = list(fill = "#f0f0f0")),
        rowhead = list(fg_params = list(hjust = 0.5, x = 0.5), bg_params = list(fill = "white"))
      ))
      
      # Set a fixed total height for the table, adjusting row heights based on number of pitches
      total_height <- unit(1, "npc")
      row_height <- total_height / (num_rows + 1)  # +1 for header row
      table_plot$heights <- unit(rep(row_height, num_rows + 1), "npc")
      
      # Adjust column widths
      table_plot$widths <- unit(c(0.1, 0.06, 0.06, 0.08, 0.1, 0.06, 0.08, 0.08, 0.08, 0.1, 0.1, 0.1), "npc")
      
      # Add alternating row colors
      for(i in seq(2, nrow(table_plot), 2)) {
        table_plot$grobs[[i]]$gp$fill <- "#f9f9f9"
      }
      
      id <- as.character(game$`Pitcher ID`[1])
      
      mlb_url <- paste0("https://midfield.mlbstatic.com/v1/people/", id, "/mlb/300?circle=false")
      milb_url <- paste0("https://midfield.mlbstatic.com/v1/people/", id, "/milb/300?circle=false")
      
      img_result <- download_and_process_image(mlb_url)
      if (is.null(img_result)) {
        img_result <- download_and_process_image(milb_url)
      }
      
      if (!is.null(img_result)) {
        img_grob <- rasterGrob(img_result$img, interpolate = TRUE)
      } else {
        img_grob <- textGrob("Image not available", gp = gpar(col = "red", fontsize = 20))
      }
      
      # Create the rolling TimStuff+ graph
      rolling_data <- rolling_timstuff()
      timstuff_plot <- ggplot(rolling_data, aes(x = pitch_number, y = rolling_timstuff, color = pitch_name)) +
        geom_line(size = 1) +
        geom_point(size = 1) +
        theme_minimal() +
        labs(title = "5-Pitch Rolling TimStuff+",
             x = "Pitch Number", y = "TimStuff+") +
        ylim(70, 130) +
        scale_x_continuous(breaks = seq(5, 55, by = 5), limits = c(5,NA)) +
        theme(
          plot.title = element_text(hjust = 0.5, face = "bold"),
          legend.position = "none",
          panel.grid.major.x = element_line(color = "gray", size = 0.5)
        )
      
      # Create title and data source text
      title_text <- textGrob(
        paste(input$pitcher, format(input$date, "%m/%d/%y"), "Summary Card by @TimStats"),
        gp = gpar(fontsize = 16, fontface = "bold")
      )
      data_source_text <- textGrob(
        "Data: MLB",
        gp = gpar(fontsize = 8),
        x = unit(1, "npc") - unit(2, "mm"),
        y = unit(2, "mm"),
        just = c("right", "bottom")
      )
      
      # Create a horizontal legend
      legend <- get_legend(
        ggplot(rolling_data, aes(x = pitch_number, y = rolling_timstuff, color = pitch_name)) +
          geom_point(size = 5) +
          theme(legend.position = "bottom",
                legend.title = element_blank(),
                text = element_text(size = 12.5),
                #legend.key.size = unit(.5,"cm"),
                legend.box = "horizontal" ) +
          guides(color = guide_legend(nrow = 1))
      )
      
      # Combine all plots
      combined <- grid.arrange(
        arrangeGrob(
          arrangeGrob(
            img_grob,
            title_text,
            ncol = 1,
            heights = c(4, 1)
          ),
          pitch_plot,
          ncol = 2,
          widths = c(1, 1)
        ),
        arrangeGrob(
          break_plot,
          timstuff_plot,
          ncol = 2,
          widths = c(1, 1)
        ),
        #arrangeGrob(
        legend,
        #),
        #arrangeGrob(
        table_plot,
        #),
        data_source_text,
        nrow = 5,
        heights = c(1.2, 1.2, 0.05, 1.1, 0.05)  # Adjusted these values
      )
      combinedPlot(combined)
      
      output$combinedPlot <- renderPlot({
        grid.draw(combinedPlot())
      })
    }, error = function(e) {
      showNotification(paste("Error generating card:", e$message), type = "error")
    })
  })
  
  output$downloadPlot <- downloadHandler(
    filename = function() {
      paste("baseball_card_", Sys.Date(), ".png", sep = "")
    },
    content = function(file) {
      ggsave(file, plot = combinedPlot(), width = 18, height = 12, dpi = 300)
    }
  )
}

shinyApp(ui, server)