# CI Analysis Functions - Clean Version
# =====================================
# 
# Functions for interactive CI visualization of Aura fields
# Author: Timon, Date: August 2025

# Load required libraries
library(terra)
library(sf)
library(tmap)
library(dplyr)
library(ggplot2)

# Data Loading Functions
# ======================

#' Get available CI weeks
get_available_ci_weeks <- function(data_dir = "../../../laravel_app/storage/app/aura/weekly_mosaic") {
  files <- list.files(data_dir, pattern = "week_.*_2025\\.tif$", full.names = FALSE)
  week_nums <- as.numeric(gsub("week_(\\d+)_2025\\.tif", "\\1", files))
  return(sort(week_nums))
}

#' Get latest CI week
get_latest_ci_week <- function(data_dir = "../../../laravel_app/storage/app/aura/weekly_mosaic") {
  weeks <- get_available_ci_weeks(data_dir)
  if (length(weeks) == 0) stop("No CI weekly mosaics found")
  return(max(weeks))
}

#' Load CI weekly mosaic
load_ci_weekly <- function(week_num, year = 2025, data_dir = "../../../laravel_app/storage/app/aura/weekly_mosaic") {
  filename <- file.path(data_dir, paste0("week_", week_num, "_", year, ".tif"))
  
  if (!file.exists(filename)) {
    warning(paste("CI file not found:", filename))
    return(NULL)
  }
  
  ci_raster <- rast(filename)
  
  cat("✓ Loaded CI week", week_num, "- layers:", nlyr(ci_raster), "\n")
  cat("  Layer names:", paste(names(ci_raster), collapse = ", "), "\n")
  
  # Extract only the CI band (usually the 5th band: R, G, B, NIR, CI)
  if (nlyr(ci_raster) >= 5) {
    ci_band <- ci_raster[[5]]  # Select the 5th layer (CI)
    names(ci_band) <- paste0("CI_week_", week_num, "_", year)
    cat("  Extracted CI band (layer 5)\n")
    return(ci_band)
  } else if (nlyr(ci_raster) == 1) {
    # If it's already a single band, assume it's CI
    names(ci_raster) <- paste0("CI_week_", week_num, "_", year)
    cat("  Using single band as CI\n")
    return(ci_raster)
  } else {
    warning("Unexpected number of bands. Using first band as CI.")
    ci_band <- ci_raster[[1]]
    names(ci_band) <- paste0("CI_week_", week_num, "_", year)
    return(ci_band)
  }
}

#' Load current and previous week CI data
load_ci_comparison_data <- function(data_dir = "../../../laravel_app/storage/app/aura/weekly_mosaic") {
  latest_week <- get_latest_ci_week(data_dir)
  previous_week <- latest_week - 1
  
  current_ci <- load_ci_weekly(latest_week, data_dir = data_dir)
  previous_ci <- load_ci_weekly(previous_week, data_dir = data_dir)
  
  return(list(
    current_ci = current_ci,
    previous_ci = previous_ci,
    current_week = latest_week,
    previous_week = previous_week
  ))
}

# Visualization Functions
# =======================

#' Create interactive CI map
create_interactive_ci_map <- function(ci_raster, field_boundaries = NULL, title = "CI Map", color_palette = "viridis") {
  tmap_mode("view")
  
  ci_map <- tm_shape(ci_raster) +
    tm_raster(
      title = "CI Value",
      palette = color_palette,
      style = "cont",
      alpha = 0.8
    ) +
    tm_layout(title = title, title.size = 1.2)
  
  if (!is.null(field_boundaries)) {
    ci_map <- ci_map +
      tm_shape(field_boundaries) +
      tm_polygons(
        alpha = 0.1,
        col = NA,
        border.col = "white",
        border.lwd = 2,
        popup.vars = c("Field" = "field", "Sub Field" = "sub_field"),
        id = "field"
      )
  }
  
  return(ci_map)
}

#' Create CI change detection map
create_ci_change_map <- function(current_ci, previous_ci, field_boundaries = NULL, title = "CI Change") {
  
  # Ensure both rasters are single-band
  if (nlyr(current_ci) > 1) {
    current_ci <- current_ci[[1]]
  }
  if (nlyr(previous_ci) > 1) {
    previous_ci <- previous_ci[[1]]
  }
  
  # Calculate change
  ci_change <- current_ci - previous_ci
  
  # Set name for the change raster
  names(ci_change) <- "CI_Change"
  
  change_map <- tm_shape(ci_change) +
    tm_raster(
      title = "CI Change",
      palette = "RdBu",
      style = "cont",
      alpha = 0.8,
      midpoint = 0
    ) +
    tm_layout(title = title, title.size = 1.2)
  
  if (!is.null(field_boundaries)) {
    change_map <- change_map +
      tm_shape(field_boundaries) +
      tm_polygons(
        alpha = 0.1,
        col = NA,
        border.col = "yellow",
        border.lwd = 2,
        popup.vars = c("Field" = "field", "Sub Field" = "sub_field"),
        id = "field"
      )
  }
  
  return(change_map)
}

cat("✓ CI analysis functions loaded successfully\n")