# ============================================================================
# COMPLETE HARVEST ALERT SYSTEM
# Two-stage approach for factory logistics planning
# ============================================================================
# STAGE 1: HARVEST WINDOW PREDICTION (7-21 days ahead)
#          Alert factory that harvest is coming soon
#
# STAGE 2: HARVEST EVENT DETECTION (0-7 days after)
#          Confirm that harvest has actually occurred
# ============================================================================

suppressPackageStartupMessages({
  library(readxl)
  library(dplyr)
  library(tidyr)
  library(lubridate)
  library(here)
  library(ggplot2)
})

# Set project directory
project_dir <- "esa"
assign("project_dir", project_dir, envir = .GlobalEnv)

# Navigate to project root if in experiments folder
if (basename(getwd()) == "harvest_prediction") {
  setwd("../../..")
}

source(here("r_app", "parameters_project.R"))

# ============================================================================
# CONFIGURATION
# ============================================================================

CONFIG <- list(
  # STAGE 1: Prediction thresholds
  min_field_age_days = 240,
  ci_threshold_low = 2.5,
  ci_threshold_very_low = 1.5,
  sustained_low_days = 5,
  min_days_since_harvest = 200,
  
  # STAGE 2: Detection thresholds (independent of Stage 1)
  harvest_confirmed_ci = 1.5,     # Sustained very low CI = harvest occurred
  confirmation_days = 3           # Consecutive days below threshold
)

cat("============================================================================\n")
cat("COMPLETE HARVEST ALERT SYSTEM - TWO STAGE APPROACH\n")
cat("============================================================================\n\n")

cat("STAGE 1: HARVEST WINDOW PREDICTION\n")
cat("  - Alert when CI sustained low (crop mature)\n")
cat("  - Provides 7-21 days advance warning\n")
cat("  - Factory can plan logistics\n\n")

cat("STAGE 2: HARVEST EVENT DETECTION\n")
cat("  - Detect sustained very low CI (bare soil)\n")
cat("  - CI < 1.5 for 3 consecutive days\n")
cat("  - Independent of Stage 1\n")
cat("  - Confirms harvest has occurred\n\n")

cat("Configuration:\n")
cat("  Min field age:", CONFIG$min_field_age_days, "days\n")
cat("  Mature crop CI:", CONFIG$ci_threshold_low, "\n")
cat("  Sustained low days:", CONFIG$sustained_low_days, "\n")
cat("  Harvest confirmed CI:", CONFIG$harvest_confirmed_ci, "\n")
cat("  Confirmation days:", CONFIG$confirmation_days, "\n\n")

# ============================================================================
# LOAD DATA
# ============================================================================

cat("=== LOADING DATA ===\n\n")

ci_rds_file <- here("laravel_app/storage/app", project_dir, "Data/extracted_ci/cumulative_vals/All_pivots_Cumulative_CI_quadrant_year_v2.rds")
ci_data_raw <- readRDS(ci_rds_file) %>% ungroup()

time_series_daily <- ci_data_raw %>%
  mutate(date = as.Date(Date)) %>%
  select(field_id = field, date, mean_ci = FitData) %>%
  filter(!is.na(mean_ci), !is.na(date), !is.na(field_id)) %>%
  arrange(field_id, date)

harvest_data <- read_excel('laravel_app/storage/app/esa/Data/harvest.xlsx') %>%
  mutate(
    season_start = as.Date(season_start),
    season_end = as.Date(season_end)
  ) %>%
  filter(!is.na(season_end))

fields_with_ci <- unique(time_series_daily$field_id)
harvest_data_filtered <- harvest_data %>%
  filter(field %in% fields_with_ci) %>%
  arrange(field, season_end)

cat("Fields with CI data:", length(fields_with_ci), "\n")
cat("Total harvest events:", nrow(harvest_data_filtered), "\n\n")

# ============================================================================
# STAGE 1: HARVEST WINDOW PREDICTION
# ============================================================================

predict_harvest_window <- function(field_ts, check_date, last_harvest_date, config = CONFIG) {
  current_ci <- field_ts %>%
    filter(date == check_date) %>%
    pull(mean_ci)
  
  if (length(current_ci) == 0 || is.na(current_ci[1])) {
    return(list(stage1_alert = FALSE, stage1_level = "no_data", consecutive_days = 0, current_ci = NA))
  }
  
  # Take first value if multiple
  current_ci <- current_ci[1]
  
  # Calculate field age
  if (is.null(last_harvest_date) || is.na(last_harvest_date)) {
    earliest_date <- min(field_ts$date, na.rm = TRUE)
    field_age <- as.numeric(check_date - earliest_date)
  } else {
    field_age <- as.numeric(check_date - last_harvest_date)
  }
  
  if (field_age < config$min_field_age_days) {
    return(list(stage1_alert = FALSE, stage1_level = "too_young", consecutive_days = 0))
  }
  
  # Count consecutive days with CI below threshold
  recent_data <- field_ts %>%
    filter(date <= check_date, date >= check_date - 30) %>%
    arrange(desc(date))
  
  consecutive_days_low <- 0
  for (i in 1:nrow(recent_data)) {
    if (recent_data$mean_ci[i] <= config$ci_threshold_low) {
      consecutive_days_low <- consecutive_days_low + 1
    } else {
      break
    }
  }
  
  mean_ci_sustained <- if (consecutive_days_low > 0) {
    recent_data %>% slice(1:consecutive_days_low) %>%
      summarise(mean = mean(mean_ci, na.rm = TRUE)) %>% pull(mean)
  } else {
    NA
  }
  
  # Determine alert level
  stage1_alert <- FALSE
  stage1_level <- "none"
  
  if (consecutive_days_low >= config$sustained_low_days) {
    stage1_alert <- TRUE
    if (!is.na(mean_ci_sustained) && mean_ci_sustained <= config$ci_threshold_very_low) {
      stage1_level <- "imminent"  # 7 days
    } else {
      stage1_level <- "likely"     # 7-14 days
    }
  } else if (consecutive_days_low >= 3) {
    stage1_alert <- TRUE
    stage1_level <- "possible"     # 14-21 days
  }
  
  return(list(
    stage1_alert = stage1_alert,
    stage1_level = stage1_level,
    consecutive_days = consecutive_days_low,
    current_ci = current_ci,
    mean_ci_sustained = mean_ci_sustained
  ))
}

# ============================================================================
# STAGE 2: HARVEST EVENT DETECTION
# ============================================================================

detect_harvest_event <- function(field_ts, check_date, last_harvest_date, config = CONFIG) {
  current_ci <- field_ts %>%
    filter(date == check_date) %>%
    pull(mean_ci)
  
  if (length(current_ci) == 0 || is.na(current_ci[1])) {
    return(list(stage2_alert = FALSE, stage2_level = "no_data", current_ci = NA))
  }
  
  # Take first value if multiple (shouldn't happen but safety)
  current_ci <- current_ci[1]
  
  # STAGE 2: Detect sustained very low CI (bare soil after harvest)
  # Independent of Stage 1 - works in parallel
  stage2_alert <- FALSE
  stage2_level <- "none"
  
  # Get recent days for consecutive low CI check
  recent_window <- field_ts %>%
    filter(date <= check_date, 
           date >= check_date - config$confirmation_days + 1) %>%
    arrange(date)
  
  # Count consecutive days below harvest confirmation threshold
  if (nrow(recent_window) >= config$confirmation_days) {
    consecutive_low_days <- 0
    
    for (i in nrow(recent_window):1) {
      if (!is.na(recent_window$mean_ci[i]) && 
          recent_window$mean_ci[i] <= config$harvest_confirmed_ci) {
        consecutive_low_days <- consecutive_low_days + 1
      } else {
        break
      }
    }
    
    # Sustained very low CI = harvest occurred
    if (consecutive_low_days >= config$confirmation_days) {
      stage2_alert <- TRUE
      stage2_level <- "confirmed"
    }
  }
  
  return(list(
    stage2_alert = stage2_alert,
    stage2_level = stage2_level,
    current_ci = current_ci,
    consecutive_low_days = if (exists("consecutive_low_days")) consecutive_low_days else 0
  ))
}

# ============================================================================
# COMBINED VALIDATION
# ============================================================================

validate_two_stage_system <- function(field_id) {
  field_ts <- time_series_daily %>%
    filter(field_id == !!field_id) %>%
    arrange(date)
  
  field_harvests <- harvest_data_filtered %>%
    filter(field == field_id) %>%
    arrange(season_end)
  
  if (nrow(field_harvests) == 0) return(NULL)
  
  all_results <- data.frame()
  
  for (h in 1:nrow(field_harvests)) {
    harvest_date <- field_harvests$season_end[h]
    last_harvest <- if (h == 1) NA else field_harvests$season_end[h - 1]
    
    # Test -21 to +14 days
    test_dates_seq <- seq.Date(
      from = harvest_date - 21,
      to = harvest_date + 14,
      by = "1 day"
    )
    
    for (i in 1:length(test_dates_seq)) {
      test_date <- test_dates_seq[i]
      days_from_harvest <- as.numeric(test_date - harvest_date)
      
      stage1 <- predict_harvest_window(field_ts, test_date, last_harvest, CONFIG)
      stage2 <- detect_harvest_event(field_ts, test_date, last_harvest, CONFIG)
      
      # Only add row if we have valid data
      if (length(stage1$current_ci) > 0 && !is.null(stage1$current_ci)) {
        all_results <- bind_rows(all_results, data.frame(
          field = field_id,
          harvest_event = h,
          harvest_date = harvest_date,
          test_date = test_date,
          days_from_harvest = days_from_harvest,
          stage1_alert = stage1$stage1_alert,
          stage1_level = stage1$stage1_level,
          stage2_alert = stage2$stage2_alert,
          stage2_level = stage2$stage2_level,
          current_ci = stage1$current_ci,
          consecutive_days = stage1$consecutive_days
        ))
      }
    }
  }
  
  return(all_results)
}

# ============================================================================
# RUN FULL DATASET VALIDATION
# ============================================================================

cat("============================================================================\n")
cat("VALIDATING TWO-STAGE SYSTEM ON FULL DATASET\n")
cat("============================================================================\n\n")

all_fields_results <- data.frame()
summary_by_field <- data.frame()

fields_to_test <- unique(harvest_data_filtered$field)
total_fields <- length(fields_to_test)

cat("Testing", total_fields, "fields...\n\n")

pb <- txtProgressBar(min = 0, max = total_fields, style = 3)

for (f in 1:total_fields) {
  field_id <- fields_to_test[f]
  
  field_results <- validate_two_stage_system(field_id)
  
  if (!is.null(field_results)) {
    all_fields_results <- bind_rows(all_fields_results, field_results)
    
    # Calculate summary for this field
    field_harvests_count <- length(unique(field_results$harvest_event))
    
    # Stage 1: First prediction in optimal window (7-21 days ahead)
    stage1_optimal <- field_results %>%
      filter(stage1_alert == TRUE, days_from_harvest >= -21, days_from_harvest <= -7) %>%
      group_by(harvest_event) %>%
      slice(1) %>%
      ungroup()
    
    # Stage 2: Detection within 7 days after harvest
    stage2_detections <- field_results %>%
      filter(stage2_alert == TRUE, days_from_harvest >= 0, days_from_harvest <= 7) %>%
      group_by(harvest_event) %>%
      slice(1) %>%
      ungroup()
    
    summary_by_field <- bind_rows(summary_by_field, data.frame(
      field = field_id,
      total_harvests = field_harvests_count,
      stage1_optimal = nrow(stage1_optimal),
      stage2_detected = nrow(stage2_detections),
      stage1_rate = round(100 * nrow(stage1_optimal) / field_harvests_count, 1),
      stage2_rate = round(100 * nrow(stage2_detections) / field_harvests_count, 1)
    ))
  }
  
  setTxtProgressBar(pb, f)
}

close(pb)

cat("\n\n============================================================================\n")
cat("RESULTS BY FIELD\n")
cat("============================================================================\n\n")

print(summary_by_field, row.names = FALSE)

# ============================================================================
# OVERALL SUMMARY
# ============================================================================

cat("\n============================================================================\n")
cat("OVERALL SUMMARY ACROSS ALL FIELDS\n")
cat("============================================================================\n\n")

total_harvests <- sum(summary_by_field$total_harvests)
total_stage1_optimal <- sum(summary_by_field$stage1_optimal)
total_stage2_detected <- sum(summary_by_field$stage2_detected)

cat("Total harvest events tested:", total_harvests, "\n\n")

cat("STAGE 1 - HARVEST WINDOW PREDICTION:\n")
cat("  Predictions in optimal window (7-21 days ahead):", total_stage1_optimal, "/", total_harvests, "\n")
cat("  Success rate:", round(100 * total_stage1_optimal / total_harvests, 1), "%\n\n")

cat("STAGE 2 - HARVEST EVENT DETECTION:\n")
cat("  Detections within 7 days after harvest:", total_stage2_detected, "/", total_harvests, "\n")
cat("  Success rate:", round(100 * total_stage2_detected / total_harvests, 1), "%\n\n")

cat("COMBINED SYSTEM PERFORMANCE:\n")
cat("  Fields with >50% Stage 1 success:", sum(summary_by_field$stage1_rate > 50), "/", total_fields, "\n")
cat("  Fields with >50% Stage 2 success:", sum(summary_by_field$stage2_rate > 50), "/", total_fields, "\n\n")

# Find best and worst performing fields
cat("BEST PERFORMING FIELDS (Stage 1):\n")
top_fields <- summary_by_field %>% arrange(desc(stage1_rate)) %>% head(5)
print(top_fields, row.names = FALSE)

cat("\n\nWORST PERFORMING FIELDS (Stage 1):\n")
bottom_fields <- summary_by_field %>% arrange(stage1_rate) %>% head(5)
print(bottom_fields, row.names = FALSE)

cat("\n============================================================================\n")
cat("FACTORY CLIENT INTERPRETATION\n")
cat("============================================================================\n\n")

cat("🏭 TWO-STAGE ALERT SYSTEM:\n\n")

cat("  STAGE 1: ADVANCE WARNING (7-21 days ahead)\n")
cat("    - Factory receives prediction when crop is mature\n")
cat("    - Allows planning of processing capacity\n")
cat("    - Coordinate transport and labor\n")
cat("    - Success rate:", round(100 * total_stage1_optimal / total_harvests, 1), "%\n\n")

cat("  STAGE 2: HARVEST CONFIRMATION (0-7 days after)\n")
cat("    - Confirms harvest has actually occurred\n")
cat("    - Detects bare soil signature (CI < 1.0)\n")
cat("    - Triggers processing logistics\n")
cat("    - Success rate:", round(100 * total_stage2_detected / total_harvests, 1), "%\n\n")

cat("📊 OPERATIONAL WORKFLOW:\n")
cat("    1. Field shows sustained low CI → Stage 1 alert\n")
cat("    2. Factory prepares for harvest in 1-3 weeks\n")
cat("    3. CI drops to bare soil → Stage 2 alert\n")
cat("    4. Factory confirms harvest and processes cane\n\n")

cat("============================================================================\n")
cat("ANALYSIS COMPLETE\n")
cat("============================================================================\n")

# Save detailed results
output_file <- here("r_app/experiments/harvest_prediction/two_stage_validation_results.rds")
saveRDS(list(
  all_results = all_fields_results,
  summary = summary_by_field,
  config = CONFIG
), output_file)

cat("\nDetailed results saved to:", output_file, "\n")