# EXTRACT_RDS_ONLY.R
# ===================
# Extract and combine daily CI values into combined_CI_data.rds
# Skips raster processing - assumes daily extracted files already exist
#
# Usage: Rscript r_app/extract_rds_only.R [project_dir]
#   - project_dir: Project directory name (e.g., "angata", "aura", "chemba")
#
# Example:
#   Rscript r_app/extract_rds_only.R angata

suppressPackageStartupMessages({
  library(tidyverse)
  library(here)
})

main <- function() {
  # Capture command line arguments
  args <- commandArgs(trailingOnly = TRUE)
  
  # Process project_dir argument
  if (length(args) >= 1 && !is.na(args[1])) {
    project_dir <- as.character(args[1])
  } else {
    project_dir <- "angata"
  }
  
  cat(sprintf("RDS Extraction: project=%s\n", project_dir))
  
  # Source configuration
  tryCatch({
    source("parameters_project.R")
  }, error = function(e) {
    warning("Default source files not found. Attempting to source from 'r_app' directory.")
    tryCatch({
      source("r_app/parameters_project.R")
      warning(paste("Successfully sourced files from 'r_app' directory."))
    }, error = function(e) {
      stop("Failed to source parameters_project.R from both default and 'r_app' directories.")
    })
  })
  
  # Define paths for CI data
  daily_CI_vals_dir <- file.path(
    "laravel_app/storage/app", project_dir,
    "Data/extracted_ci/daily_vals"
  )
  
  cumulative_CI_vals_dir <- file.path(
    "laravel_app/storage/app", project_dir,
    "Data/extracted_ci/cumulative_vals"
  )
  
  cat(sprintf("Daily CI values dir: %s\n", daily_CI_vals_dir))
  cat(sprintf("Cumulative CI values dir: %s\n\n", cumulative_CI_vals_dir))
  
  # Check if daily CI directory exists and has files
  if (!dir.exists(daily_CI_vals_dir)) {
    stop(sprintf("ERROR: Daily CI directory not found: %s", daily_CI_vals_dir))
  }
  
  # List RDS files
  files <- list.files(path = daily_CI_vals_dir, pattern = "^extracted_.*\\.rds$", full.names = TRUE)
  
  if (length(files) == 0) {
    stop(sprintf("ERROR: No extracted CI values found in %s", daily_CI_vals_dir))
  }
  
  cat(sprintf("Found %d daily CI RDS files\n\n", length(files)))
  
  # Create cumulative directory if it doesn't exist
  if (!dir.exists(cumulative_CI_vals_dir)) {
    dir.create(cumulative_CI_vals_dir, recursive = TRUE)
    cat(sprintf("Created directory: %s\n\n", cumulative_CI_vals_dir))
  }
  
  # Combine all RDS files
  cat("Combining daily RDS files...\n")
  combined_data <- files %>%
    purrr::map(readRDS) %>% 
    purrr::list_rbind() %>%
    dplyr::group_by(sub_field)
  
  # Save combined data
  output_path <- file.path(cumulative_CI_vals_dir, "combined_CI_data.rds")
  saveRDS(combined_data, output_path)
  
  cat(sprintf("✓ Combined %d daily files\n", length(files)))
  cat(sprintf("✓ Total rows: %d\n", nrow(combined_data))
  cat(sprintf("✓ Saved to: %s\n\n", output_path))
  
  # Summary
  cat("Summary:\n")
  cat(sprintf("  Fields: %d\n", n_distinct(combined_data$field, na.rm = TRUE)))
  cat(sprintf("  Sub-fields: %d\n", n_distinct(combined_data$sub_field, na.rm = TRUE)))
  cat(sprintf("  Total measurements: %d\n\n", nrow(combined_data)))
  
  cat("✓ RDS extraction complete!\n")
  cat("Next: Run 02b_convert_rds_to_csv.R to convert to CSV\n")
}

if (sys.nframe() == 0) {
  main()
}