library(shiny)
library(dplyr)
library(shinythemes)
library(plotly)

# Generate synthetic data
generate_complex_data <- function() {
  set.seed(123)
  days <- 30
  data <- data.frame(
    day = 1:days,
    date = seq.Date(from = as.Date("2024-01-01"), by = "day", length.out = days),
    footTraffic = sample(200:600, days, replace = TRUE),
    adSpend = sample(400:1200, days, replace = TRUE),
    discountPercent = sample(0:40, days, replace = TRUE),
    socialMediaEngagement = sample(200:1200, days, replace = TRUE),
    competitorDistance = sample(1:15, days, replace = TRUE),
    websiteVisits = sample(400:1000, days, replace = TRUE),
    pricePoint = sample(40:100, days, replace = TRUE),
    stockAvailability = sample(40:100, days, replace = TRUE)
  )

  price_factor <- -1.7 * (data$pricePoint - 70)^2
  foot_traffic_effect <- 2.5 * (data$footTraffic - 200) + 80
  stock_effect <- 0.80 * (data$stockAvailability - 70) + 50

  data$sales <- round(
    foot_traffic_effect + data$adSpend * 0.2 + data$discountPercent * 60 +
      data$socialMediaEngagement * 0.5 + data$competitorDistance * 150 +
      data$websiteVisits * 0.15 + price_factor + stock_effect + runif(days, -40, 40)
  )

  data$sales <- pmax(data$sales, 0)
  return(data)
}

store_data <- generate_complex_data()

# UI
ui <- fluidPage(
  theme = shinytheme("cosmo"),
  titlePanel("Fashion Sales Simulator - Plotly Edition"),
  tabsetPanel(
    tabPanel("Guided Analysis",
             sidebarLayout(
               sidebarPanel(
                 selectInput("selected_metric", "Select a Variable:", 
                             choices = names(store_data)[-c(1,2,10)],
                             selected = "footTraffic"),
                 checkboxInput("show_trend", "Show Linear Trend Line", FALSE)
               ),
               mainPanel(
                 plotlyOutput("guided_plot"),
                 verbatimTextOutput("correlation")
               )
             )
    ),

    tabPanel("Free Exploration",
             sidebarLayout(
               sidebarPanel(
                 selectInput("x_var", "Select X Variable:", choices = names(store_data)[-c(1,2,10)]),
                 selectInput("y_var", "Select Y Variable:", choices = names(store_data)[-c(1,2,10)]),
                 checkboxInput("show_trend_explore", "Show Linear Trend Line", FALSE),
                 actionButton("compute_corr", "Compute Correlation")
               ),
               mainPanel(
                 plotlyOutput("free_explore_plot"),
                 verbatimTextOutput("free_corr_output")
               )
             )
    )
  )
)

# Server
server <- function(input, output, session) {
  compute_correlation <- function(x, y) {
    cor(store_data[[x]], store_data[[y]], use = "complete.obs")
  }

  output$guided_plot <- renderPlotly({
    p <- plot_ly(store_data, x = ~get(input$selected_metric), y = ~sales, type = 'scatter', mode = 'markers',
                 marker = list(color = 'blue')) %>%
      layout(title = paste("Sales vs", input$selected_metric),
             xaxis = list(title = input$selected_metric),
             yaxis = list(title = "Sales"))

    if (input$show_trend) {
      model <- lm(sales ~ get(input$selected_metric), data = store_data)
      trend_line <- data.frame(x = store_data[[input$selected_metric]], y = predict(model))
      trend_line <- trend_line[order(trend_line$x), ]
      p <- p %>% add_lines(x = ~trend_line$x, y = ~trend_line$y, name = "Trend Line", line = list(color = 'red'))
    }
    p
  })

  output$correlation <- renderText({
    corr_value <- compute_correlation(input$selected_metric, "sales")
    paste("Correlation with Sales:", round(corr_value, 3))
  })

  output$free_explore_plot <- renderPlotly({
    p <- plot_ly(store_data, x = ~get(input$x_var), y = ~get(input$y_var), type = 'scatter', mode = 'markers',
                 marker = list(color = 'green4')) %>%
      layout(title = paste(input$x_var, "vs", input$y_var),
             xaxis = list(title = input$x_var),
             yaxis = list(title = input$y_var))

    if (input$show_trend_explore) {
      model <- lm(get(input$y_var) ~ get(input$x_var), data = store_data)
      trend_line <- data.frame(x = store_data[[input$x_var]], y = predict(model))
      trend_line <- trend_line[order(trend_line$x), ]
      p <- p %>% add_lines(x = ~trend_line$x, y = ~trend_line$y, name = "Trend Line", line = list(color = 'red'))
    }
    p
  })

  observeEvent(input$compute_corr, {
    output$free_corr_output <- renderText({
      corr_value <- compute_correlation(input$x_var, input$y_var)
      paste("Correlation between", input$x_var, "and", input$y_var, ":", round(corr_value, 3))
    })
  })
}

shinyApp(ui, server)