from google_map import GoogleMap
from pathlib import Path
from position import Position
from simulator import Simulator
from time import sleep
from trajectory_drawer import TrajectoryDrawer
from utility import cv2_to_pil
from vision_chunk import VisionChunk
from visualization import VisualizationManager
from yandex_map import YandexMap

import argparse
import autopilot
import constants
import cv2
import matplotlib.pyplot as plt
import numpy as np
import pickle
import random
import utility

def make_global_photo(filename, initial_zoom=13):
    google_map = GoogleMap(initial_zoom=initial_zoom)
    google_map.save_photo(filename)
    google_map.destroy()

def get_trajectory_points(bg_img: str) -> list[(float, float)]:
    trajectoryDrawer = TrajectoryDrawer(bg_img)
    trajectoryDrawer.show()
    trajectoryDrawer.wait()
    points = list(map(lambda p: [p[0] / trajectoryDrawer.img.shape[1], p[1] / trajectoryDrawer.img.shape[0]], trajectoryDrawer.points))
    return points

def build(name: str):

    # Создание папки с информацией о маршруте
    dir = Path('trajectories')
    if not dir.exists(): dir.mkdir()
    dir /= name
    assert not dir.exists()
    dir.mkdir()
    dir_chunks = dir / 'chunks'
    dir_chunks.mkdir()

    # make_global_photo('map.jpg', 15)
    points = get_trajectory_points('map.jpg')
    google_map = GoogleMap(initial_zoom=15)

    # Начнём симуляцию полёта с первой точки
    google_map.make_as_center(*points[0])
    sleep(3)
    google_map.scroll(0.5, 0.5, 10, True)
    sleep(2)
    geo = google_map.get_geolocation()
    google_map.open(geo['lat'], geo['lon'], 18)
    sleep(20)

    width, height = google_map.get_size()
    points_coords = np.array(list(map(lambda p: [
            (p[0] - points[0][0]) * width, (points[0][1] - p[1]) * height
        ], points)))

    points_coords *= constants.GOOGLE_PIXEL_RATIO_15
    points_coords_pixel = points_coords / constants.GOOGLE_PIXEL_RATIO_18

    pilot = autopilot.AutoPilot(points_coords_pixel)
    simulator = Simulator(google_map)
    pilot.target_idx = 0

    pilot.pos = simulator.pos.copy()
    command = pilot.make_command()

    positions: list[Position] = []

    print("points_coords_pixel:", points_coords_pixel)
    for i in range(100000):

        if command.stop:
            break

        # simulator.handle(command.dangle, command.velocity)
        chunk = simulator.get_chunk()
        pilot.pos = simulator.pos.copy()
        command = pilot.make_command()
        command.velocity /= constants.GOOGLE_PIXEL_RATIO_18

        print("Position:", simulator.pos)
        
        # Save Image
        chunk.save_image(dir_chunks / f"chunk_{len(positions)}.png")
        positions.append(simulator.pos)

        simulator.handle(command.dangle, command.velocity)
        sleep(1.5)

    data = {
        'points': points_coords,
        'chunk_positions': positions,
        'initial_geolocation': geo
    }

    file_positions = dir / 'positions.pkl'
    with file_positions.open('wb') as file:
        pickle.dump(data, file)

    with file_positions.open('rb') as file:
        r = pickle.load(file)
        print(r)

    sleep(15)
    google_map.destroy()

def run(name: str):
    dir = Path('trajectories')
    assert dir.exists()
    dir /= name
    assert dir.exists()
    dir_chunks = dir / 'chunks'
    file_positions = dir / 'positions.pkl'

    with file_positions.open('rb') as file:
        data = pickle.load(file)
    
    initial_geolocation = data['initial_geolocation']
    chunks: list[VisionChunk] = []
    for i in range(len(data['chunk_positions'])):
        chunk = VisionChunk.load_image(dir_chunks / f"chunk_{i}.png")
        chunk.pos = data['chunk_positions'][i]
    
    points = data['points'] / constants.YANDEX_PIXEL_RATIO_18

    yandex_map = YandexMap(initial_geolocation['lat'], initial_geolocation['lon'], 18)
    sleep(10)

    vis_manager = VisualizationManager()
    width, height = yandex_map.get_size()
    pilot = autopilot.AutoPilot(points, chunks, vis_manager)
    simulator = Simulator(yandex_map)
    pilot.target_idx = 0

    chunk = simulator.get_chunk()
    command = pilot.handle(chunk)

    vis_manager.update_display()
    vis_manager.pause(1)

    vis_manager.set_target_points(points)

    proc_time = np.array([])

    zoom_next_event = random.randint(5, 10)

    errors = []
    chunk_errors = []
    chunk_improves = []

    last_chunk_index = 0

    for i in range(10000000000):
        print(f"Image #{i}")
        if i == zoom_next_event:
            r = random.randint(0, 1)
            direction = ['up', 'down'][r]
            # simulator.change_zoom(direction)
            zoom_next_event = i + random.randint(20, 40)


        # if i > 0:
        #     simulator.set_pitch(np.sin(i / 10) * 5)
        #     simulator.set_roll(np.sin(i / 15) * 5)
        #     simulator.set_zoom(1.0 + np.sin(i / 10) * 0.3)

        if command.stop:
            break

        # simulator.handle(command.dangle, command.velocity)
        chunk = simulator.get_chunk()
        command = pilot.handle(chunk)
        command.velocity /= constants.YANDEX_PIXEL_RATIO_18

        proc_time = np.append(proc_time, command.proccessing_time)
        
        # Save Image
        chunk.save_image(Path('images') / f"photo_{i}.png")

        vis_manager.update_display()
        vis_manager.pause(0.2)

        vis_manager.set_target_index(pilot.target_idx)
        vis_manager.update_drone_trajectory(pilot.pos.x, pilot.pos.y)
        vis_manager.update_global_map(simulator.pos.x, simulator.pos.y)
        vis_manager.update_error_plot(i, pilot.pos.x, pilot.pos.y, simulator.pos.x, simulator.pos.y)

        errors.append(np.hypot(pilot.pos.x - simulator.pos.x, pilot.pos.y - simulator.pos.y))
        if last_chunk_index != pilot.target_idx:
            last_chunk_index = pilot.target_idx
            chunk_errors.append(errors[-1])
            chunk_improves.append(errors[-1] - errors[max(len(errors) - 2, 0)])

        vis_manager.update_display()
        vis_manager.pause(0.2)

        last_proc_times = proc_time[-10:]
        print("Average FPS:", 1 / last_proc_times.mean())
        print("Pilot coords:", pilot.pos)
        print("Simulator coords:", simulator.pos)
        simulator.handle(command.dangle, command.velocity)

    print("Errors:", errors)
    print("MSE:", (np.array(errors) ** 2).mean())
    print("RMSE:", (np.array(errors) ** 2).mean() ** 0.5)
    print("Chunk errors:", chunk_errors)
    print("Chunk error improves:", chunk_improves)
    print("Average FPS:", 1 / proc_time.mean())
    vis_manager.show_final()


def main(mode: str, name: str):
    if name is None:
        name = utility.generate_folder_name()

    if mode == 'build' or mode == 'standalone':
        build(name)

    if mode == 'run' or mode == 'standalone':
        run(name)

def parse_args():
    """Парсер аргументов командной строки"""
    parser = argparse.ArgumentParser(description='Обработка траекторий')

    # Добавляем обязательный аргумент --mode
    parser.add_argument(
        '--mode',
        type=str,
        required=True,
        choices=['standalone', 'build', 'run'],
        help='Режим работы: standalone, build или run'
    )

    # Добавляем опциональный аргумент --name
    parser.add_argument(
        '--name',
        type=str,
        help='Название траектории (обязательно для режимов build и run)'
    )

    # Парсим аргументы
    args = parser.parse_args()

    # Проверяем, что для build и run указан --name
    if args.mode in ['build', 'run'] and not args.name:
        parser.error(f"--name обязателен для режима {args.mode}")

    return args

if __name__ == "__main__":
    args = parse_args()
    main(args.mode, args.name)