# State-based harvest detection considering crop lifecycle
# Detects: GROWING → MATURING → DECLINING → HARVEST → RECOVERING
suppressPackageStartupMessages({
  library(readxl)
  library(dplyr)
  library(tidyr)
  library(lubridate)
  library(terra)
  library(sf)
  library(here)
})

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

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

# Read pre-extracted CI data
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),
    week = isoweek(date),
    year = isoyear(date)
  ) %>%
  select(
    field_id = field,
    date,
    week,
    year,
    mean_ci = FitData
  ) %>%
  filter(!is.na(mean_ci), !is.na(date), !is.na(field_id)) %>%
  arrange(field_id, date)

cat("Loaded", nrow(time_series_daily), "daily observations\n\n")

# ==============================================================================
# STATE-BASED HARVEST DETECTION
# ==============================================================================

detect_harvest_stateful <- function(daily_ts, field_name,
                                    mature_ci = 3.5,        # CI > this = mature crop
                                    harvest_ci = 2.5,       # CI < this = harvest phase
                                    mature_window = 30,     # Days to confirm mature state
                                    decline_rate = -0.02,   # CI/day decline rate to detect pre-harvest
                                    harvest_min_days = 14,  # Minimum days below harvest_ci (increased to delay detection)
                                    recovery_threshold = 3.0) {  # CI rising above this = recovery
  
  field_ts <- daily_ts %>%
    filter(field_id == field_name) %>%
    arrange(date) %>%
    mutate(
      # Smoothing: 7-day rolling median to reduce noise
      ci_smooth = zoo::rollmedian(mean_ci, k = 7, fill = NA, align = "center"),
      ci_smooth = ifelse(is.na(ci_smooth), mean_ci, ci_smooth),
      
      # Trend: 14-day rolling slope (CI change rate)
      ci_trend = (ci_smooth - lag(ci_smooth, 14)) / 14,
      
      # Rolling statistics for context
      ci_mean_60d = zoo::rollmean(ci_smooth, k = 60, fill = NA, align = "right"),
      ci_max_60d = zoo::rollmax(ci_smooth, k = 60, fill = NA, align = "right")
    )
  
  if (nrow(field_ts) < 100) {
    return(tibble(
      field_id = character(),
      harvest_date = as.Date(character()),
      harvest_week = numeric(),
      harvest_year = numeric(),
      state = character(),
      ci_at_harvest = numeric()
    ))
  }
  
  # State machine: track crop lifecycle states
  field_ts <- field_ts %>%
    mutate(
      # Define states based on CI level and trend
      is_mature = ci_smooth > mature_ci & ci_mean_60d > mature_ci,
      is_declining = ci_trend < decline_rate & !is.na(ci_trend),
      is_harvest = ci_smooth < harvest_ci,
      is_recovering = ci_smooth > recovery_threshold & ci_trend > 0.01
    )
  
  # Detect harvest events: MATURE phase → CI drops below threshold → declare harvest
  harvests <- tibble()
  i <- mature_window + 1
  last_harvest_date <- as.Date("1900-01-01")
  consecutive_low_days <- 0
  potential_harvest_start <- NA
  
  while (i <= nrow(field_ts)) {
    current_date <- field_ts$date[i]
    days_since_last_harvest <- as.numeric(current_date - last_harvest_date)
    
    # Only look for new harvest if enough time has passed (min 6 months)
    if (days_since_last_harvest > 180) {
      
      # Check if currently in low CI period
      if (field_ts$is_harvest[i]) {
        if (consecutive_low_days == 0) {
          # Start of new low period - check if came from mature state
          recent_was_mature <- any(field_ts$is_mature[(max(1,i-60)):(i-1)], na.rm = TRUE)
          
          if (recent_was_mature) {
            potential_harvest_start <- current_date
            consecutive_low_days <- 1
          }
        } else {
          consecutive_low_days <- consecutive_low_days + 1
        }
        
        # Declare harvest after consecutive low days threshold met
        if (consecutive_low_days == harvest_min_days) {
          harvests <- bind_rows(harvests, tibble(
            field_id = field_name,
            harvest_date = potential_harvest_start,
            harvest_week = isoweek(potential_harvest_start),
            harvest_year = isoyear(potential_harvest_start),
            state = "APPROACHING",  # Stage 1: CI declining, harvest approaching
            alert_message = "⚠️ Field CI declining - harvest expected in 2-4 weeks",
            ci_at_harvest = field_ts$ci_smooth[field_ts$date == potential_harvest_start],
            low_days = consecutive_low_days
          ))
          
          last_harvest_date <- potential_harvest_start
        }
      } else {
        # CI rose above threshold - reset counter
        consecutive_low_days <- 0
        potential_harvest_start <- NA
      }
    }
    
    i <- i + 1
  }
  
  # ============================================================================
  # STAGE 2: Detect harvest completion (CI stabilized at low level)
  # ============================================================================
  
  # For each detected "APPROACHING" harvest, check if we can upgrade to "COMPLETED"
  if (nrow(harvests) > 0) {
    for (h in 1:nrow(harvests)) {
      if (harvests$state[h] == "APPROACHING") {
        approach_date <- harvests$harvest_date[h]
        
        # Look 7-21 days after approach detection for stabilization
        stable_window <- field_ts %>%
          filter(date >= approach_date + 7, date <= approach_date + 21)
        
        if (nrow(stable_window) >= 7) {
          # Calculate stability: low CI with low variability
          stable_window <- stable_window %>%
            mutate(
              ci_sd_7d = zoo::rollapply(ci_smooth, width = 7, FUN = sd, fill = NA, align = "center")
            )
          
          # Check if CI is stable (SD < 0.3) and low (< 2.0) for at least 7 days
          stable_days <- stable_window %>%
            filter(!is.na(ci_sd_7d), ci_sd_7d < 0.3, ci_smooth < 2.0) %>%
            nrow()
          
          if (stable_days >= 7) {
            # Upgrade to COMPLETED
            harvests$state[h] <- "COMPLETED"
            harvests$alert_message[h] <- "✓ Harvest likely completed in recent days - CI stable at low level"
          }
        }
      }
    }
  }
  
  # Remove the low_days column before returning to match expected schema
  harvests <- harvests %>% select(-low_days, -alert_message)
  
  return(harvests)
}

cat("Running state-based harvest detection...\n")
all_harvests <- lapply(unique(time_series_daily$field_id), function(field_name) {
  detect_harvest_stateful(daily_ts = time_series_daily, field_name)
}) %>% bind_rows()

cat("Detected", nrow(all_harvests), "harvest events\n")
cat("  APPROACHING (CI declining):", sum(all_harvests$state == "APPROACHING"), "\n")
cat("  COMPLETED (CI stable low):", sum(all_harvests$state == "COMPLETED"), "\n\n")

# ==============================================================================
# COMPARE WITH ACTUAL HARVEST DATA
# ==============================================================================

harvest_actual_all <- 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_data <- unique(field_boundaries_sf$field)

harvest_actual <- harvest_actual_all %>%
  filter(field %in% fields_with_data) %>%
  filter(!is.na(season_end)) %>%
  mutate(
    actual_harvest_week = isoweek(season_end),
    actual_harvest_year = isoyear(season_end)
  )

cat("=== COMPARISON: STATE-BASED DETECTION vs ACTUAL ===\n\n")

harvest_actual2 <- harvest_actual %>%
  select(field, actual_week = actual_harvest_week, actual_year = actual_harvest_year)

harvest_detected2 <- all_harvests %>%
  select(field_id, detected_week = harvest_week, detected_year = harvest_year, 
         state, ci_at_harvest)

comparison <- harvest_actual2 %>%
  full_join(
    harvest_detected2,
    by = c("field" = "field_id", "actual_year" = "detected_year")
  ) %>%
  mutate(
    week_difference_signed = ifelse(!is.na(actual_week) & !is.na(detected_week), 
                                    detected_week - actual_week, NA),  # Negative = detected early
    week_difference = abs(week_difference_signed),
    status = case_when(
      !is.na(actual_week) & !is.na(detected_week) & week_difference <= 2 ~ "✓ MATCHED",
      !is.na(actual_week) & !is.na(detected_week) & week_difference > 2 ~ paste0("⚠ MISMATCH (", ifelse(week_difference_signed < 0, week_difference_signed, paste0("+", week_difference_signed)), "w)"),
      is.na(actual_week) & !is.na(detected_week) ~ "⚠ FALSE POSITIVE",
      !is.na(actual_week) & is.na(detected_week) ~ "✗ MISSED",
      TRUE ~ "Unknown"
    )
  ) %>%
  select(field, actual_year, actual_week, detected_week, week_diff = week_difference_signed,
         status, state, ci_at_harvest) %>%
  filter(!is.na(actual_week)) %>%  # Only compare against actual recorded harvests
  arrange(field, actual_year)

cat("Filtered to only fields with recorded harvest dates\n")
cat("(Removed rows where actual_week = NA)\n\n")
print(comparison, n = 100)

cat("\n\n=== SUMMARY STATISTICS (FILTERED DATA ONLY) ===\n")
matched <- sum(comparison$status == "✓ MATCHED", na.rm = TRUE)
false_pos <- sum(comparison$status == "⚠ FALSE POSITIVE", na.rm = TRUE)
missed <- sum(comparison$status == "✗ MISSED", na.rm = TRUE)
mismatch <- sum(grepl("MISMATCH", comparison$status), na.rm = TRUE)

cat("Total actual harvest events (with records):", nrow(harvest_actual), "\n")
cat("Total rows in filtered comparison:", nrow(comparison), "\n\n")

cat("✓ MATCHED (±2 weeks):", matched, "\n")
cat("⚠ WEEK MISMATCH (>2 weeks):", mismatch, "\n")
cat("⚠ FALSE POSITIVES:", false_pos, "\n")
cat("✗ MISSED:", missed, "\n\n")

if (nrow(harvest_actual) > 0) {
  cat("Detection rate:", round(100 * (matched + mismatch) / nrow(harvest_actual), 1), "%\n")
  cat("Accuracy (within 2 weeks):", round(100 * matched / nrow(harvest_actual), 1), "%\n")
}

cat("\n\nDetection approach: STATE-BASED\n")
cat("States: MATURE (CI>3.5) → DECLINING (slope<-0.02) → HARVEST (CI<2.5) → RECOVERY (CI rising)\n")
cat("Natural duplicate prevention: Must be 6+ months since last harvest to enter new cycle\n")
cat("Confirmation: Only counts as harvest if followed by recovery (CI rising)\n")