from enum import Enum
import torchvision.transforms as transforms
import torch

GAME_TITLE = 'WMICraft'
WINDOW_HEIGHT = 800
WINDOW_WIDTH = 1360
FPS_COUNT = 60
TURN_INTERVAL = 500

GRID_CELL_PADDING = 5
GRID_CELL_SIZE = 36
ROWS = 19
COLUMNS = 24

BORDER_WIDTH = 10
BORDER_RADIUS = 5

KNIGHTS_SPAWN_WIDTH = 4
KNIGHTS_SPAWN_HEIGHT = 7
LEFT_KNIGHTS_SPAWN_FIRST_ROW = 6
LEFT_KNIGHTS_SPAWN_FIRST_COL = 0
RIGHT_KNIGHTS_SPAWN_FIRST_ROW = 6
RIGHT_KNIGHTS_SPAWN_FIRST_COL = 20

CASTLE_SPAWN_WIDTH = 6
CASTLE_SPAWN_HEIGHT = 5
CASTLE_SPAWN_FIRST_ROW = 7
CASTLE_SPAWN_FIRST_COL = 9

NBR_OF_WATER = 16
NBR_OF_TREES = 20
NBR_OF_MONSTERS = 2
NBR_OF_SANDS = 35

TILES = [
    'grass1.png',
    'grass2.png',
    'grass3.png',
    'grass4.png',
    'sand.png',
    'water.png',
    'grass_with_tree.jpg',
]


class Direction(Enum):
    UP = 0
    RIGHT = 1
    DOWN = 2
    LEFT = 3

    def right(self):
        v = (self.value + 1) % 4
        return Direction(v)

    def left(self):
        v = (self.value - 1) % 4
        return Direction(v)


ACTION = {
    "rotate_left": -1,
    "rotate_right": 1,
    "go": 0,
}

LEFT = 'LEFT'
RIGHT = 'RIGHT'
UP = 'UP'
DOWN = 'DOWN'

# HEALTH_BAR
BAR_ANIMATION_SPEED = 1
BAR_WIDTH_MULTIPLIER = 0.9  # (0;1>
BAR_HEIGHT_MULTIPLIER = 0.1


#NEURAL_NETWORK
LEARNING_RATE = 0.13182567385564073
BATCH_SIZE = 64
NUM_EPOCHS = 50

DEVICE = torch.device('cuda') if torch.cuda.is_available() else torch.device('cpu')
print("Using ", DEVICE)
CLASSES = ['grass', 'sand', 'tree', 'water']

SETUP_PHOTOS = transforms.Compose([
    transforms.Resize(36),
    transforms.CenterCrop(36),
    transforms.ToPILImage(),
    transforms.ToTensor(),
    transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])
])

ID_TO_CLASS = {i: j for i, j in enumerate(CLASSES)}
CLASS_TO_ID = {value: key for key, value in ID_TO_CLASS.items()}