Merge pull request 'added points in stats;' (#41) from stats_update into master

Reviewed-on: s464965/WMICraft#41

.gitignore

@@ -150,3 +150,4 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 .idea/
+/algorithms/neural_network/data/

algorithms/a_star.py

@@ -4,25 +4,16 @@ import heapq
 from dataclasses import dataclass, field
 from typing import Tuple, Optional, List
 
-from common.constants import ROWS, COLUMNS
+from algorithms.genetic.const import MAP_ALIASES
+from common.constants import ROWS, COLUMNS, LEFT, RIGHT, UP, DOWN
+from common.helpers import directions
 
-EMPTY_FIELDS = ['s', 'g', ' ']
-LEFT = 'LEFT'
-RIGHT = 'RIGHT'
-UP = 'UP'
-DOWN = 'DOWN'
+EMPTY_FIELDS = [MAP_ALIASES.get("SAND"), MAP_ALIASES.get("GRASS"), ' ']
 
 TURN_LEFT = 'TURN_LEFT'
 TURN_RIGHT = 'TURN_RIGHT'
 FORWARD = 'FORWARD'
 
-directions = {
-    LEFT: (0, -1),
-    RIGHT: (0, 1),
-    UP: (-1, 0),
-    DOWN: (1, 0)
-}
-
 
 @dataclass
 class State:

algorithms/bfs.py

@@ -51,7 +51,7 @@ def graphsearch(initial_state: State, map, goal_list, fringe: List[Node] = None,
     explored_states = set()
     fringe_states = set()
 
-    # root Node
+    # train Node
     fringe.append(Node(initial_state))
     fringe_states.add((initial_state.row, initial_state.column, initial_state.direction))
 
@@ -71,7 +71,7 @@ def graphsearch(initial_state: State, map, goal_list, fringe: List[Node] = None,
             parent = element.parent
 
             while parent is not None:
-                # root's action will be None, don't add it
+                # train's action will be None, don't add it
                 if parent.action is not None:
                     actions_sequence.append(parent.action)
                 parent = parent.parent

algorithms/genetic/common.py

@@ -0,0 +1,142 @@
+from dataclasses import dataclass
+
+import numpy as np
+
+from const import *
+from typing import List, Dict, Tuple
+
+import numpy.typing as npt
+
+
+@dataclass
+class Position:
+    row: int
+    col: int
+
+
+@dataclass
+class Area:
+    position: Position
+    width: int
+    height: int
+
+
+AREAS_TO_CROSS = [
+    # up above left knights spawn
+    Area(position=Position(row=0, col=0),
+         width=KNIGHTS_SPAWN_WIDTH,
+         height=LEFT_KNIGHTS_SPAWN_FIRST_ROW),
+
+    # down below left knights spawn
+    Area(position=Position(row=LEFT_KNIGHTS_SPAWN_FIRST_ROW + KNIGHTS_SPAWN_HEIGHT, col=0),
+         width=KNIGHTS_SPAWN_WIDTH,
+         height=ROWS - LEFT_KNIGHTS_SPAWN_FIRST_ROW - KNIGHTS_SPAWN_HEIGHT),
+
+    # between left knights spawn and castle
+    Area(position=Position(row=0, col=KNIGHTS_SPAWN_WIDTH),
+         width=CASTLE_SPAWN_FIRST_COL - KNIGHTS_SPAWN_WIDTH,
+         height=ROWS),
+
+    # up above castle
+    Area(position=Position(row=0, col=CASTLE_SPAWN_FIRST_COL),
+         width=2,
+         height=CASTLE_SPAWN_FIRST_ROW),
+
+    # down below castle
+    Area(position=Position(row=CASTLE_SPAWN_FIRST_ROW + 2, col=CASTLE_SPAWN_FIRST_COL),
+         width=2,
+         height=ROWS - CASTLE_SPAWN_FIRST_ROW - 2),
+
+    # between castle and right knights spawn
+    Area(position=Position(row=0, col=CASTLE_SPAWN_FIRST_COL + 2),
+         width=RIGHT_KNIGHTS_SPAWN_FIRST_COL - CASTLE_SPAWN_FIRST_COL - 2,
+         height=ROWS),
+
+    # up above right knights spawn
+    Area(position=Position(row=0, col=RIGHT_KNIGHTS_SPAWN_FIRST_COL),
+         width=KNIGHTS_SPAWN_WIDTH,
+         height=RIGHT_KNIGHTS_SPAWN_FIRST_ROW),
+
+    # down below right knights spawn
+    Area(position=Position(row=RIGHT_KNIGHTS_SPAWN_FIRST_ROW + KNIGHTS_SPAWN_HEIGHT, col=RIGHT_KNIGHTS_SPAWN_FIRST_COL),
+         width=KNIGHTS_SPAWN_WIDTH,
+         height=ROWS - RIGHT_KNIGHTS_SPAWN_FIRST_ROW - KNIGHTS_SPAWN_HEIGHT),
+]
+
+
+def dfs(grid: npt.NDArray, visited: Dict[Tuple[int, int], bool], position: Position, rows: int, cols: int) -> None:
+    visited[(position.row, position.col)] = True
+
+    row_vector = [0, 0, 1, -1]
+    col_vector = [-1, 1, 0, 0]
+
+    neighbours = []
+    for i in range(4):
+        rr = position.row + row_vector[i]
+        cc = position.col + col_vector[i]
+        if rr < 0 or rr >= ROWS:
+            continue
+        elif cc < 0 or cc >= COLUMNS:
+            continue
+        else:
+            p = Position(rr, cc)
+            if (p.row, p.col) in visited:
+                neighbours.append(p)
+
+    for neighbour in neighbours:
+        if not visited[(neighbour.row, neighbour.col)]:
+            dfs(grid, visited, neighbour, rows, cols)
+
+
+def get_islands(grid: npt.NDArray, positions: List[Position], rows: int = ROWS, cols: int = COLUMNS) -> List[Position]:
+    """it returns list of all islands roots"""
+    visited = {}
+
+    for position in positions:
+        visited[(position.row, position.col)] = False
+
+    islands = 0
+    roots = []
+    for position in positions:
+        if not visited[(position.row, position.col)]:
+            dfs(grid, visited, position, rows, cols)
+            roots.append(position)
+            islands += 1
+
+    return roots
+
+
+def find_neighbours(grid: npt.NDArray, col: int, row: int) -> List[Position]:
+    dr = [-1, 1, 0, 0]
+    dc = [0, 0, -1, 1]
+
+    neighbours = []
+
+    for i in range(4):
+        rr = row + dr[i]
+        cc = col + dc[i]
+
+        if 0 <= rr < ROWS and 0 <= cc < COLUMNS and grid[rr][cc] == MAP_ALIASES.get('GRASS'):
+            neighbours.append(Position(row=rr, col=cc))
+
+    return neighbours
+
+
+def get_tiles_positions(grid: npt.NDArray):
+    sands = []
+    trees = []
+    waters = []
+    monsters = []
+
+    for row_num in range(len(grid)):
+        for col_num in range(len(grid[row_num])):
+            if grid[row_num][col_num] == MAP_ALIASES.get('WATER'):
+                waters.append(Position(row=row_num, col=col_num))
+            elif grid[row_num][col_num] == MAP_ALIASES.get('TREE'):
+                trees.append(Position(row=row_num, col=col_num))
+            elif grid[row_num][col_num] == MAP_ALIASES.get('SAND'):
+                sands.append(Position(row=row_num, col=col_num))
+            elif grid[row_num][col_num] == MAP_ALIASES.get('MONSTER'):
+                monsters.append(Position(row=row_num, col=col_num))
+
+    return sands, trees, waters, monsters

algorithms/genetic/const.py

@@ -0,0 +1,29 @@
+# map config
+KNIGHTS_PER_TEAM_COUNT = 4
+SAND_COUNT = 21
+WATER_COUNT = 21
+TREE_COUNT = 37
+MONSTERS_COUNT = 2
+CASTLES_COUNT = 1
+ROWS = 19
+COLUMNS = 24
+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_FIRST_ROW = 7
+CASTLE_SPAWN_FIRST_COL = 11
+
+# map aliases
+MAP_ALIASES = {
+    "GRASS": 0,
+    "SAND": 1,
+    "WATER": 2,
+    "TREE": 3,
+    "MONSTER": 4,
+    "CASTLE": 5,
+    "KNIGHT_RED": 6,
+    "KNIGHT_BLUE": 7,
+}

algorithms/genetic/genome.py

@@ -0,0 +1,166 @@
+import math
+import random
+from copy import deepcopy
+from random import randrange
+from typing import List
+
+import numpy as np
+import numpy.typing as npt
+
+from common import Position, get_islands, AREAS_TO_CROSS, find_neighbours, get_tiles_positions
+from const import *
+
+
+class Genome:
+    grid: npt.NDArray
+    knights_red: List[Position]
+    knights_blue: List[Position]
+    waters: List[Position]
+    trees: List[Position]
+    sands: List[Position]
+    monsters: List[Position]
+    fitness: int
+    sand_islands: List[Position]
+    tree_islands: List[Position]
+    water_islands: List[Position]
+
+    def __init__(self):
+        self.grid = np.zeros((ROWS, COLUMNS), dtype=int)
+        self.fitness = 0
+
+        self.knights_red = spawn_objects_in_given_area(
+            grid=self.grid,
+            object_alias=MAP_ALIASES.get("KNIGHT_RED"),
+            objects_count=KNIGHTS_PER_TEAM_COUNT,
+            spawn_position_start=Position(row=LEFT_KNIGHTS_SPAWN_FIRST_ROW, col=LEFT_KNIGHTS_SPAWN_FIRST_COL),
+            width=KNIGHTS_SPAWN_WIDTH,
+            height=KNIGHTS_SPAWN_HEIGHT
+        )
+
+        self.knights_blue = spawn_objects_in_given_area(
+            grid=self.grid,
+            object_alias=MAP_ALIASES.get("KNIGHT_BLUE"),
+            objects_count=KNIGHTS_PER_TEAM_COUNT,
+            spawn_position_start=Position(row=RIGHT_KNIGHTS_SPAWN_FIRST_ROW, col=RIGHT_KNIGHTS_SPAWN_FIRST_COL),
+            width=KNIGHTS_SPAWN_WIDTH,
+            height=KNIGHTS_SPAWN_HEIGHT
+        )
+
+        spawn_objects_in_given_area(
+            grid=self.grid,
+            object_alias=MAP_ALIASES.get("CASTLE"),
+            objects_count=4,
+            spawn_position_start=Position(row=CASTLE_SPAWN_FIRST_ROW, col=CASTLE_SPAWN_FIRST_COL),
+            width=2,
+            height=2
+        )
+
+        self.waters = spawn_objects_in_given_area(grid=self.grid, object_alias=MAP_ALIASES.get("WATER"),
+                                                  objects_count=WATER_COUNT)
+        self.trees = spawn_objects_in_given_area(grid=self.grid, object_alias=MAP_ALIASES.get("TREE"),
+                                                 objects_count=TREE_COUNT)
+        self.sands = spawn_objects_in_given_area(grid=self.grid, object_alias=MAP_ALIASES.get("SAND"),
+                                                 objects_count=SAND_COUNT)
+        self.monsters = spawn_objects_in_given_area(grid=self.grid, object_alias=MAP_ALIASES.get("MONSTER"),
+                                                    objects_count=MONSTERS_COUNT)
+
+        self.sand_islands = get_islands(self.grid, self.sands)
+        self.tree_islands = get_islands(self.grid, self.trees)
+        self.water_islands = get_islands(self.grid, self.waters)
+
+    def update_map(self):
+        self.sands, self.trees, self.waters, self.monsters = get_tiles_positions(self.grid)
+
+        self.sand_islands = get_islands(self.grid, self.sands)
+        self.tree_islands = get_islands(self.grid, self.trees)
+        self.water_islands = get_islands(self.grid, self.waters)
+
+    def calc_fitness(self):
+        score = SAND_COUNT + TREE_COUNT + WATER_COUNT
+        score = score - len(self.sand_islands) - len(self.tree_islands) - len(self.water_islands)
+
+        sands, trees, waters, monsters = get_tiles_positions(self.grid)
+
+        if len(monsters) != MONSTERS_COUNT:
+            self.fitness = 0
+            return
+
+        if len(sands) < SAND_COUNT or len(trees) < TREE_COUNT or len(waters) < WATER_COUNT:
+            self.fitness = 5
+            return
+
+        self.fitness = score
+
+    def crossover(self, partner):
+        # replace a randomly selected part of the grid with partner's part
+        child = Genome()
+        child.grid = deepcopy(self.grid)
+        area_to_cross = random.choice(AREAS_TO_CROSS)
+
+        for row in range(area_to_cross.position.row, area_to_cross.position.row + area_to_cross.height):
+            for col in range(area_to_cross.position.col, area_to_cross.position.col + area_to_cross.width):
+                child.grid[row][col] = partner.grid[row][col]
+
+        child.update_map()
+
+        return child
+
+    def mutate(self, mutation_rate: float):
+        # remove 1 item from a random island and add a neighbor to another island
+        if random.random() < mutation_rate:
+
+            # select islands of the same, random type
+            islands_of_same_type = random.choice([self.sand_islands, self.tree_islands, self.water_islands])
+            random_index = random.randint(0, len(islands_of_same_type) - 1)
+            island = islands_of_same_type[random_index]
+            next_island = islands_of_same_type[(random_index + 1) % len(islands_of_same_type)]
+
+            free_tiles_nearby = find_neighbours(self.grid, next_island.col, next_island.row)
+
+            tile_type = self.grid[island.row][island.col]
+            self.grid[island.row][island.col] = MAP_ALIASES.get('GRASS')
+
+            # todo: if there are no free tiles around then randomize another next_island
+            if len(free_tiles_nearby) > 0:
+                random_free_tile = random.choice(free_tiles_nearby)
+                island.row = random_free_tile.row
+                island.col = random_free_tile.col
+                self.grid[island.row][island.col] = tile_type
+
+                self.update_map()
+
+
+def is_empty(grid: npt.NDArray, position: Position) -> bool:
+    return grid[position.row, position.col] in [MAP_ALIASES.get("GRASS"), MAP_ALIASES.get("SAND")]
+
+
+def is_invalid_area(spawn_position_start, height, width) -> bool:
+    return spawn_position_start.row + height - 1 < 0 or \
+           spawn_position_start.row + height - 1 >= ROWS or \
+           spawn_position_start.col + width - 1 < 0 or \
+           spawn_position_start.col + width - 1 >= COLUMNS
+
+
+def spawn_objects_in_given_area(grid: npt.NDArray,
+                                object_alias: str,
+                                objects_count: int = 1,
+                                spawn_position_start: Position = Position(row=0, col=0),
+                                width: int = COLUMNS,
+                                height: int = ROWS) -> List[Position]:
+    if is_invalid_area(spawn_position_start, height, width):
+        raise ValueError("Invalid spawn area")
+
+    objects_remaining = int(objects_count)
+    positions = []
+
+    while objects_remaining > 0:
+        row = randrange(spawn_position_start.row, spawn_position_start.row + height)
+        col = randrange(spawn_position_start.col, spawn_position_start.col + width)
+        position = Position(row=row, col=col)
+
+        if is_empty(grid=grid, position=position):
+            grid[position.row, position.col] = object_alias
+            positions.append(position)
+            objects_remaining -= 1
+
+    return positions

algorithms/genetic/map_generator.py

@@ -0,0 +1,26 @@
+from algorithms.genetic.genome import Genome
+from algorithms.genetic.map_importer_exporter import export_map
+from population import Population
+
+
+def main() -> None:
+    population_size = 500
+    mutation_rate = 0.3
+
+    population = Population(mutation_rate, population_size, 55)
+
+    while not population.evaluate():
+        # create next generation
+        population.generate()
+
+        # calc fitness
+        population.calc_fitness()
+
+    print(population.best_genome.grid)
+    print("Fitness of the best: ", population.best_genome.fitness)
+
+    export_map(population.best_genome.grid)
+
+
+if __name__ == '__main__':
+    main()

algorithms/genetic/map_importer_exporter.py

@@ -0,0 +1,42 @@
+import json
+import random
+import string
+from datetime import datetime
+from pathlib import Path
+import numpy
+import numpy.typing as npt
+from os import listdir
+from os.path import isfile, join
+
+
+# Save map to file
+def export_map(grid: npt.NDArray):
+    json_data = {"map": grid.tolist()}
+
+    now = datetime.now()
+    file_name = "map_" + now.strftime("%Y_%m_%d_%H_%M_%S") + ".json"
+    path = Path("../../resources/maps/")
+    file_to_open = path / file_name
+
+    with open(file_to_open, "w+") as write_file:
+        json.dump(json_data, write_file)
+    print("Saved map to file " + file_name)
+
+
+def import_random_map() -> object:
+    path = "resources/maps"
+    files = [f for f in listdir(path) if isfile(join(path, f))]
+    random_map_name = random.choice(files)
+    return import_map(random_map_name)
+
+
+# Read map from file
+def import_map(file_name: string) -> object:
+    file_to_open = "resources/maps/" + file_name
+    with open(file_to_open, "r") as read_file:
+        print("Reading map from file " + file_name)
+        decoded_json = json.load(read_file)
+
+        decoded_grid = numpy.asarray(decoded_json["map"])
+        print(decoded_grid)
+    return decoded_grid.tolist()

algorithms/genetic/population.py

@@ -0,0 +1,81 @@
+import random
+from typing import List
+
+import numpy as np
+import numpy.typing as npt
+
+from genome import Genome
+
+
+class Population:
+    population: List[Genome] = []  # array to hold the current population
+    mating_pool: List[Genome] = []  # array which we will use for our "mating pool"
+    generations: int = 0  # number of generations
+    finished: bool = False  # are we finished evolving?
+    mutation_rate: float
+    perfect_score: int
+    best_genome: Genome
+
+    def __init__(self, mutation_rate, population_size, perfect_score=20):
+        self.mutation_rate = mutation_rate
+        self.perfect_score = perfect_score
+
+        for i in range(0, population_size):
+            new_genome = Genome()
+            new_genome.calc_fitness()
+            self.population.append(new_genome)
+
+    # create a new generation
+    def generate(self):
+        max_fitness = 0
+        for genome in self.population:
+            if genome.fitness > max_fitness:
+                max_fitness = genome.fitness
+
+        print("Max fitness of generation " + str(self.generations) + " = " + str(max_fitness))
+
+        # refill the population with children from the mating pool
+        new_population = []
+        for genome in self.population:
+            partner_a = self.accept_reject(max_fitness)
+            partner_b = self.accept_reject(max_fitness)
+            child = partner_a.crossover(partner_b)
+            child.mutate(self.mutation_rate)
+            new_population.append(child)
+
+        self.population = new_population
+        self.generations += 1
+
+    # select random with correct probability from population
+    def accept_reject(self, max_fitness: int):
+        safe_flag = 0
+
+        while safe_flag < 10000:
+            partner = random.choice(self.population)
+            r = random.randint(0, max_fitness)
+
+            if r < partner.fitness:
+                return partner
+
+            safe_flag += 1
+
+    # compute the current "most fit" member of the population
+    def evaluate(self):
+        record = 0
+        best_index = 0
+
+        for index in range(len(self.population)):
+            genome = self.population[index]
+            if genome.fitness > record:
+                record = genome.fitness
+                best_index = index
+
+        self.best_genome = self.population[best_index]
+        if record >= self.perfect_score:
+            self.finished = True
+
+        return self.finished
+
+    def calc_fitness(self):
+        for genome in self.population:
+            genome.calc_fitness()

algorithms/neural_network/lightning_logs/version_23/hparams.yaml

@@ -0,0 +1 @@
+{}

algorithms/neural_network/neural_network.py

@@ -0,0 +1,64 @@
+import torch
+import pytorch_lightning as pl
+import torch.nn as nn
+from torch.optim import SGD, Adam, lr_scheduler
+import torch.nn.functional as F
+from torch.utils.data import DataLoader
+from watersandtreegrass import WaterSandTreeGrass
+from common.constants import DEVICE, BATCH_SIZE, NUM_EPOCHS, LEARNING_RATE, SETUP_PHOTOS, ID_TO_CLASS
+
+
+class NeuralNetwork(pl.LightningModule):
+    def __init__(self, numChannels=3, batch_size=BATCH_SIZE, learning_rate=LEARNING_RATE, num_classes=4):
+        super(NeuralNetwork, self).__init__()
+        self.conv1 = nn.Conv2d(numChannels, 24, (3, 3), padding=1)
+        self.relu1 = nn.ReLU()
+        self.maxpool1 = nn.MaxPool2d((2, 2), stride=2)
+        self.conv2 = nn.Conv2d(24, 48, (3, 3), padding=1)
+        self.relu2 = nn.ReLU()
+        self.fc1 = nn.Linear(48*18*18, 800)
+        self.relu3 = nn.ReLU()
+        self.fc2 = nn.Linear(800, 400)
+        self.relu4 = nn.ReLU()
+        self.fc3 = nn.Linear(400, 4)
+        self.logSoftmax = nn.LogSoftmax(dim=1)
+
+        self.batch_size = batch_size
+        self.learning_rate = learning_rate
+
+    def forward(self, x):
+        x = self.conv1(x)
+        x = self.relu1(x)
+        x = self.maxpool1(x)
+        x = self.conv2(x)
+        x = self.relu2(x)
+        x = x.reshape(x.shape[0], -1)
+        x = self.fc1(x)
+        x = self.relu3(x)
+        x = self.fc2(x)
+        x = self.relu4(x)
+        x = self.fc3(x)
+        x = self.logSoftmax(x)
+        return x
+
+    def configure_optimizers(self):
+        optimizer = Adam(self.parameters(), lr=self.learning_rate)
+        return optimizer
+
+    def training_step(self, batch, batch_idx):
+        x, y = batch
+        scores = self(x)
+        loss = F.nll_loss(scores, y)
+        return loss
+
+    def validation_step(self, batch, batch_idx):
+        x, y = batch
+        scores = self(x)
+        val_loss = F.nll_loss(scores, y)
+        self.log("val_loss", val_loss, on_step=True, on_epoch=True, sync_dist=True)
+
+    def test_step(self, batch, batch_idx):
+        x, y = batch
+        scores = self(x)
+        test_loss = F.nll_loss(scores, y)
+        self.log("test_loss", test_loss, on_step=True, on_epoch=True, sync_dist=True)

algorithms/neural_network/neural_network_interface.py

@@ -0,0 +1,125 @@
+import torch
+import common.helpers
+from common.constants import DEVICE, BATCH_SIZE, NUM_EPOCHS, LEARNING_RATE, SETUP_PHOTOS, ID_TO_CLASS
+from watersandtreegrass import WaterSandTreeGrass
+from torch.utils.data import DataLoader
+from neural_network import NeuralNetwork
+from torchvision.io import read_image, ImageReadMode
+import torch.nn as nn
+from torch.optim import Adam
+import matplotlib.pyplot as plt
+import pytorch_lightning as pl
+from pytorch_lightning.callbacks import EarlyStopping
+import torchvision.transforms.functional as F
+from PIL import Image
+
+
+def check_accuracy_tiles():
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/grass_with_tree.jpg') == 'tree':
+            answer = answer + 1
+    print("Accuracy(%) grass_with_tree.jpg",  answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/grass2.png') == 'grass':
+            answer = answer + 1
+    print("Accuracy(%) grass2.png",  answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/grass3.png') == 'grass':
+            answer = answer + 1
+    print("Accuracy(%) grass3.png",  answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/grass4.png') == 'grass':
+            answer = answer + 1
+    print("Accuracy(%) grass4.png", answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/grass1.png') == 'grass':
+            answer = answer + 1
+    print("Accuracy(%) grass1.png", answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/water.png') == 'water':
+            answer = answer + 1
+    print("Accuracy(%) water.png", answer)
+
+    answer = 0
+    for i in range(100):
+        if what_is_it('../../resources/textures/sand.png') == 'sand':
+            answer = answer + 1
+    print("Accuracy(%) sand.png", answer)
+
+
+def what_is_it(img_path, show_img=False):
+    image = Image.open(img_path).convert('RGB')
+    if show_img:
+        plt.imshow(image)
+        plt.show()
+
+    image = SETUP_PHOTOS(image).unsqueeze(0)
+    model = NeuralNetwork.load_from_checkpoint('./lightning_logs/version_20/checkpoints/epoch=3-step=324.ckpt')
+
+    with torch.no_grad():
+        model.eval()
+        idx = int(model(image).argmax(dim=1))
+        return ID_TO_CLASS[idx]
+
+
+def check_accuracy(tset):
+    model = NeuralNetwork.load_from_checkpoint('./lightning_logs/version_23/checkpoints/epoch=3-step=324.ckpt')
+    num_correct = 0
+    num_samples = 0
+    model = model.to(DEVICE)
+    model.eval()
+
+    with torch.no_grad():
+        for photo, label in tset:
+            photo = photo.to(DEVICE)
+            label = label.to(DEVICE)
+
+            scores = model(photo)
+            predictions = scores.argmax(dim=1)
+            num_correct += (predictions == label).sum()
+            num_samples += predictions.size(0)
+
+        print(f'Got {num_correct} / {num_samples} with accuracy {float(num_correct)/float(num_samples)*100:.2f}%')
+
+
+def check_accuracy_data():
+    trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
+    testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
+    train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
+    test_loader = DataLoader(testset, batch_size=BATCH_SIZE)
+
+    print("Accuracy of train_set:")
+    check_accuracy(train_loader)
+    print("Accuracy of test_set:")
+    check_accuracy(test_loader)
+
+#CNN = NeuralNetwork()
+#common.helpers.createCSV()
+
+#trainer = pl.Trainer(accelerator='gpu', callbacks=EarlyStopping('val_loss'), devices=1, max_epochs=NUM_EPOCHS)
+#trainer = pl.Trainer(accelerator='gpu', devices=1, auto_lr_find=True, max_epochs=NUM_EPOCHS)
+
+#trainset = WaterSandTreeGrass('./data/train_csv_file.csv', transform=SETUP_PHOTOS)
+#testset = WaterSandTreeGrass('./data/test_csv_file.csv', transform=SETUP_PHOTOS)
+#train_loader = DataLoader(trainset, batch_size=BATCH_SIZE, shuffle=True)
+#test_loader = DataLoader(testset, batch_size=BATCH_SIZE)
+#trainer.fit(CNN, train_loader, test_loader)
+#trainer.tune(CNN, train_loader, test_loader)
+
+
+#print(what_is_it('../../resources/textures/grass2.png', True))
+
+#check_accuracy_data()
+
+#check_accuracy_tiles()

algorithms/neural_network/watersandtreegrass.py

@@ -0,0 +1,27 @@
+import torch
+from torch.utils.data import Dataset
+import pandas as pd
+from torchvision.io import read_image, ImageReadMode
+from common.helpers import createCSV
+from PIL import Image
+
+
+class WaterSandTreeGrass(Dataset):
+    def __init__(self, annotations_file, transform=None):
+        createCSV()
+        self.img_labels = pd.read_csv(annotations_file)
+        self.transform = transform
+
+    def __len__(self):
+        return len(self.img_labels)
+
+    def __getitem__(self, idx):
+        image = Image.open(self.img_labels.iloc[idx, 0]).convert('RGB')
+
+        label = torch.tensor(int(self.img_labels.iloc[idx, 1]))
+
+        if self.transform:
+            image = self.transform(image)
+
+        return image, label
+

common/constants.py

@@ -1,10 +1,12 @@
 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 = 300
+TURN_INTERVAL = 200
 
 GRID_CELL_PADDING = 5
 GRID_CELL_SIZE = 36
@@ -63,7 +65,32 @@ ACTION = {
     "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 = 0.000630957344480193
+BATCH_SIZE = 64
+NUM_EPOCHS = 9
+
+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.ToTensor(),
+    transforms.Resize((36, 36)),
+    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()}
+

common/helpers.py

@@ -1,5 +1,21 @@
+from typing import Tuple, List
+
 import pygame
-from common.constants import GRID_CELL_PADDING, GRID_CELL_SIZE, COLUMNS, ROWS
+
+from algorithms.genetic.const import MAP_ALIASES
+from common.constants import GRID_CELL_PADDING, GRID_CELL_SIZE, COLUMNS, ROWS, CLASSES, CLASS_TO_ID
+import csv
+import os
+
+from common.constants import GRID_CELL_PADDING, GRID_CELL_SIZE
+from common.constants import ROWS, COLUMNS, LEFT, RIGHT, UP, DOWN
+
+directions = {
+    LEFT: (0, -1),
+    RIGHT: (0, 1),
+    UP: (-1, 0),
+    DOWN: (1, 0)
+}
 
 
 def draw_text(text, color, surface, x, y, text_size=30, is_bold=False):
@@ -13,6 +29,44 @@ def draw_text(text, color, surface, x, y, text_size=30, is_bold=False):
     surface.blit(textobj, textrect)
 
 
+def createCSV():
+    train_data_path = './data/train'
+    test_data_path = './data/test'
+
+    if os.path.exists(train_data_path):
+        train_csvfile = open('./data/train_csv_file.csv', 'w', newline="")
+        writer = csv.writer(train_csvfile)
+        writer.writerow(["filepath", "type"])
+
+        for class_name in CLASSES:
+            class_dir = train_data_path + "/" + class_name
+            for filename in os.listdir(class_dir):
+                f = os.path.join(class_dir, filename)
+                if os.path.isfile(f):
+                    writer.writerow([f, CLASS_TO_ID[class_name]])
+
+        train_csvfile.close()
+
+    else:
+        print("Brak plików do uczenia")
+
+    if os.path.exists(test_data_path):
+        test_csvfile = open('./data/test_csv_file.csv', 'w', newline="")
+        writer = csv.writer(test_csvfile)
+        writer.writerow(["filepath", "type"])
+
+        for class_name in CLASSES:
+            class_dir = test_data_path + "/" + class_name
+            for filename in os.listdir(class_dir):
+                f = os.path.join(class_dir, filename)
+                if os.path.isfile(f):
+                    writer.writerow([f, CLASS_TO_ID[class_name]])
+
+        test_csvfile.close()
+    else:
+        print("Brak plików do testowania")
+
+
 def print_numbers():
     display_surface = pygame.display.get_surface()
     font = pygame.font.SysFont('Arial', 16)
@@ -45,3 +99,21 @@ def castle_neighbors(map, castle_bottom_right_row, castle_bottom_right_col):
                         continue
                     neighbors.append((new_col, new_row))
     return neighbors
+
+
+def find_neighbours(grid: List[List[int]], col: int, row: int) -> List[Tuple[int, int]]:
+    dr = [-1, 1, 0, 0]
+    dc = [0, 0, -1, 1]
+
+    neighbours = []
+
+    for i in range(4):
+        rr = row + dr[i]
+        cc = col + dc[i]
+
+        if rr < 0 or cc < 0: continue
+        if rr >= ROWS or cc >= COLUMNS: continue
+        if grid[rr][cc] not in [MAP_ALIASES.get("GRASS"), MAP_ALIASES.get("SAND"), '.']: continue
+        neighbours.append((rr, cc))
+
+    return neighbours

learning/dataset_tree_300.csv

@@ -0,0 +1,302 @@
+tower_dist;mob1_dist;mob2_dist;opp1_dist;opp2_dist;opp3_dist;opp4_dist;agent_hp;tower_hp;mob1_hp;mob2_hp;opp1_hp;opp2_hp;opp3_hp;opp4_hp;goal
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+35;21;39;36;36;37;33;10;41;9;4;1;0;7;0;mob1

learning/decision_tree.py

@@ -0,0 +1,78 @@
+from typing import List, Tuple
+
+import pandas as pd
+from sklearn.preprocessing import LabelEncoder
+from sklearn.tree import DecisionTreeClassifier
+
+from common.helpers import castle_neighbors, find_neighbours
+from models.castle import Castle
+from models.knight import Knight
+from models.monster import Monster
+
+
+def manhattan_distance(p1: Tuple[int, int], p2: Tuple[int, int]) -> int:
+    x1, y1 = p1
+    x2, y2 = p2
+    return abs(x1 - x2) + abs(y1 - y2)
+
+
+def parse_hp(hp: int) -> int:
+    return max(0, hp)
+
+
+def parse_idx_of_opp_or_monster(s: str) -> int:
+    return int(s[-1]) - 1
+
+
+class DecisionTree:
+    def __init__(self) -> None:
+        data_frame = pd.read_csv('learning/dataset_tree_1000.csv', delimiter=';')
+        unlabeled_goals = data_frame['goal']
+        self.goals_label_encoder = LabelEncoder()
+        self.goals = self.goals_label_encoder.fit_transform(unlabeled_goals)
+        self.train_set = data_frame.drop('goal', axis='columns')
+        self.model = DecisionTreeClassifier(criterion='entropy')
+        self.model.fit(self.train_set.values, self.goals)
+
+    def predict_move(self, grid: List[List[int]], current_knight: Knight, castle: Castle, monsters: List[Monster],
+                     opponents: List[Knight]) -> \
+            List[Tuple[int, int]]:
+        distance_to_castle = manhattan_distance(current_knight.position, castle.position)
+
+        monsters_parsed = []
+        for monster in monsters:
+            monsters_parsed.append((manhattan_distance(current_knight.position, monster.position), parse_hp(
+                monster.health_bar.current_hp)))
+
+        opponents_parsed = []
+        for opponent in opponents:
+            opponents_parsed.append(
+                (manhattan_distance(current_knight.position, opponent.position),
+                 parse_hp(opponent.health_bar.current_hp)))
+
+        prediction = self.get_prediction(tower_dist=distance_to_castle, tower_hp=castle.health_bar.current_hp,
+                                         mob1_dist=monsters_parsed[0][0], mob1_hp=monsters_parsed[0][1],
+                                         mob2_dist=monsters_parsed[1][0], mob2_hp=monsters_parsed[1][1],
+                                         opp1_dist=opponents_parsed[0][0], opp1_hp=opponents_parsed[0][1],
+                                         opp2_dist=opponents_parsed[1][0], opp2_hp=opponents_parsed[1][1],
+                                         opp3_dist=opponents_parsed[2][0], opp3_hp=opponents_parsed[2][1],
+                                         opp4_dist=opponents_parsed[3][0], opp4_hp=opponents_parsed[3][1],
+                                         agent_hp=current_knight.health_bar.current_hp)
+        print(f'Prediction = {prediction}')
+        if prediction == 'tower':  # castle...
+            return castle_neighbors(grid, castle_bottom_right_row=castle.position[0],
+                                    castle_bottom_right_col=castle.position[1])
+        elif prediction.startswith('opp'):
+            idx = parse_idx_of_opp_or_monster(prediction)
+            return find_neighbours(grid, opponents[idx].position[1], opponents[idx].position[0])
+        else:
+            idx = parse_idx_of_opp_or_monster(prediction)
+            return find_neighbours(grid, monsters[idx].position[1], monsters[idx].position[0])
+
+    def get_prediction(self, tower_dist: int, mob1_dist: int, mob2_dist: int, opp1_dist: int, opp2_dist: int,
+                       opp3_dist: int, opp4_dist: int, agent_hp: int, tower_hp: int, mob1_hp: int, mob2_hp: int,
+                       opp1_hp: int, opp2_hp: int, opp3_hp: int, opp4_hp) -> str:
+        prediction = self.model.predict(
+            [[tower_dist, mob1_dist, mob2_dist, opp1_dist, opp2_dist, opp3_dist, opp4_dist, agent_hp,
+              tower_hp, mob1_hp, mob2_hp, opp1_hp, opp2_hp, opp3_hp, opp4_hp]])
+        return self.goals_label_encoder.inverse_transform(prediction)[0]

logic/game.py

@@ -27,7 +27,6 @@ class Game:
         self.screens = {'credits': Credits(self.screen, self.clock), 'options': Options(self.screen, self.clock)}
 
 
-
     def main_menu(self):
         menu = MainMenu(self.screen, self.clock, self.bg,
                         self.game,
@@ -38,7 +37,6 @@ class Game:
     def game(self):
         logs = Logs(self.screen)
         level = Level(self.screen, logs)
-        stats = Stats(self.screen)
 
         # setup clock for rounds
         NEXT_TURN = pygame.USEREVENT + 1
@@ -46,6 +44,8 @@ class Game:
 
         # create level
         level.create_map()
+        stats = Stats(self.screen, level.list_knights_blue, level.list_knights_red)
+        level.setup_stats(stats)
 
         print_numbers_flag = False
         running = True
@@ -61,8 +61,7 @@ class Game:
                         running = False
                     if event.key == pygame.K_n:
                         print_numbers_flag = not print_numbers_flag
-                    if event.key == pygame.K_r:
-                        stats.red_team_hp_bar.take_dmg(5)
+
                 if event.type == NEXT_TURN:  # is called every 'TURN_INTERVAL' milliseconds
                     level.handle_turn()
 

logic/health_bar.py

@@ -9,7 +9,6 @@ class HealthBar:
         self.rect = rect
         self.screen = screen
         self.current_hp = current_hp
-        self.target_hp = current_hp
         self.max_hp = max_hp
         self.x = self.rect.x
         self.y = self.rect.y
@@ -38,22 +37,22 @@ class HealthBar:
 
         self.health_ratio = self.max_hp / self.width
 
-    def take_dmg(self, dmg_taken):
-        if self.target_hp > 0:
-            self.target_hp -= dmg_taken
-        elif self.target_hp < 0:
-            self.target_hp = 0
+    def take_dmg(self, amount):
+        if self.current_hp - amount > 0:
+            self.current_hp -= amount
+        elif self.current_hp - amount <= 0:
+            self.current_hp = 0
 
     def heal(self, amount):
-        if self.target_hp < self.max_hp:
-            self.target_hp += amount
-        elif self.target_hp > self.max_hp:
-            self.target_hp = self.max_hp
+        if self.current_hp + amount < self.max_hp:
+            self.current_hp += amount
+        elif self.current_hp + amount >= self.max_hp:
+            self.current_hp = self.max_hp
 
     def show(self):
         pygame.Surface.fill(self.screen, BLACK, (self.x-1, self.y-1, self.width+2, self.height+2))
         pygame.Surface.fill(self.screen, RED, (self.x, self.y, self.width, self.height))
-        pygame.Surface.fill(self.screen, GREEN, (self.x, self.y, int(self.target_hp / self.health_ratio), self.height))
+        pygame.Surface.fill(self.screen, GREEN, (self.x, self.y, int(self.current_hp / self.health_ratio), self.height))
 
 
 

logic/knights_queue.py

@@ -10,7 +10,7 @@ class KnightsQueue:
     def dequeue_knight(self):
         if self.both_teams_alive():
             knight = self.queues[self.team_idx_turn].popleft()
-            if knight.max_hp <= 0:
+            if knight.health_bar.current_hp <= 0:
                 return self.dequeue_knight()
             else:
                 self.queues[self.team_idx_turn].append(knight)

logic/level.py

@@ -2,11 +2,12 @@ import random
 
 import pygame
 
-from algorithms.a_star import a_star, State, TURN_RIGHT, TURN_LEFT, FORWARD, UP, DOWN, LEFT, RIGHT
+from algorithms.a_star import a_star, State, TURN_RIGHT, TURN_LEFT, FORWARD
+from algorithms.genetic.const import MAP_ALIASES
+from algorithms.genetic.map_importer_exporter import import_random_map
 from common.constants import *
-from common.helpers import castle_neighbors
+from learning.decision_tree import DecisionTree
 from logic.knights_queue import KnightsQueue
-from logic.spawner import Spawner
 from models.castle import Castle
 from models.knight import Knight
 from models.monster import Monster
@@ -17,10 +18,11 @@ class Level:
     def __init__(self, screen, logs):
         self.screen = screen
         self.logs = logs
+        self.decision_tree = DecisionTree()
         # sprite group setup
         self.sprites = pygame.sprite.LayeredUpdates()
 
-        self.map = [['g' for _ in range(COLUMNS)] for y in range(ROWS)]
+        self.map = []
 
         self.list_knights_blue = []
         self.list_knights_red = []
@@ -29,28 +31,21 @@ class Level:
 
         self.knights_queue = None
 
+        self.stats = None
+
+    def setup_stats(self, stats):
+        self.stats = stats
+
+    def add_points(self, team, points_to_add):
+        if self.stats is not None:
+            self.stats.add_points(team, points_to_add)
+
     def create_map(self):
-        self.generate_map()
+        self.map = import_random_map()
         self.setup_base_tiles()
         self.setup_objects()
         self.knights_queue = KnightsQueue(self.list_knights_blue, self.list_knights_red)
 
-    def generate_map(self):
-        spawner = Spawner(self.map)
-        spawner.spawn_where_possible(['w' for _ in range(NBR_OF_WATER)])
-        spawner.spawn_where_possible(['t' for _ in range(NBR_OF_TREES)])
-        spawner.spawn_where_possible(['s' for _ in range(NBR_OF_SANDS)])
-
-        spawner.spawn_in_area(['k_b' for _ in range(4)], LEFT_KNIGHTS_SPAWN_FIRST_ROW, LEFT_KNIGHTS_SPAWN_FIRST_COL,
-                              KNIGHTS_SPAWN_WIDTH, KNIGHTS_SPAWN_HEIGHT)
-        spawner.spawn_in_area(['k_r' for _ in range(4)], RIGHT_KNIGHTS_SPAWN_FIRST_ROW, RIGHT_KNIGHTS_SPAWN_FIRST_COL,
-                              KNIGHTS_SPAWN_WIDTH, KNIGHTS_SPAWN_HEIGHT)
-
-        spawner.spawn_in_area(['c'], CASTLE_SPAWN_FIRST_ROW, CASTLE_SPAWN_FIRST_COL, CASTLE_SPAWN_WIDTH,
-                              CASTLE_SPAWN_HEIGHT, 2)
-
-        spawner.spawn_where_possible(['m' for _ in range(NBR_OF_MONSTERS)])
-
     def setup_base_tiles(self):
         textures = []
         for texture_path in TILES:
@@ -62,15 +57,15 @@ class Level:
             for col_index, col in enumerate(row):
 
                 # add base tiles, e.g. water, tree, grass
-                if col == "w":
+                if col == MAP_ALIASES.get('WATER'):
                     texture_index = 5
                     texture_surface = textures[texture_index][1]
                     Tile((col_index, row_index), texture_surface, self.sprites, 'w')
-                elif col == "t":
+                elif col == MAP_ALIASES.get('TREE'):
                     texture_index = 6
                     texture_surface = textures[texture_index][1]
                     Tile((col_index, row_index), texture_surface, self.sprites, 't')
-                elif col == "s":
+                elif col == MAP_ALIASES.get('SAND'):
                     texture_index = 4
                     texture_surface = textures[texture_index][1]
                     Tile((col_index, row_index), texture_surface, self.sprites)
@@ -87,42 +82,173 @@ class Level:
             for col_index, col in enumerate(row):
 
                 # add objects, e.g. knights, monsters, castle
-                if col == "k_b":
+                if col == MAP_ALIASES.get('KNIGHT_BLUE'):
                     knight = Knight(self.screen, (col_index, row_index), self.sprites, "blue")
                     self.map[row_index][col_index] = knight
                     self.list_knights_blue.append(knight)
-                elif col == "k_r":
+                elif col == MAP_ALIASES.get('KNIGHT_RED'):
                     knight = Knight(self.screen, (col_index, row_index), self.sprites, "red")
                     self.map[row_index][col_index] = knight
                     self.list_knights_red.append(knight)
-                elif col == "m":
+                elif col == MAP_ALIASES.get('MONSTER'):
                     monster = Monster(self.screen, (col_index, row_index), self.sprites)
                     self.map[row_index][col_index] = monster
                     self.list_monsters.append(monster)
-                elif col == "c":
+                elif col == MAP_ALIASES.get('CASTLE'):
                     castle_count += 1
                     if castle_count == 4:
                         castle = Castle(self.screen, (col_index, row_index), self.sprites)
                         self.map[row_index][col_index] = castle
                         self.list_castles.append(castle)
 
+    #def attack_knight(self, knights_list, positions, current_knight):
+    #    op_pos_1 = current_knight.position[0] - 1, current_knight.position[1]
+    #    positions.append(op_pos_1)
+    #    op_pos_2 = current_knight.position[0], current_knight.position[1] - 1
+    #    positions.append(op_pos_2)
+    #    op_pos_3 = current_knight.position[0] + 1, current_knight.position[1]
+    #    positions.append(op_pos_3)
+    #    op_pos_4 = current_knight.position[0], current_knight.position[1] + 1
+    #    positions.append(op_pos_4)
+    #    for some_knight in knights_list:
+    #        for some_position in positions:
+    #            if (some_knight.position == some_position and some_knight.team != current_knight.team):
+    #                some_knight.health_bar.take_dmg(current_knight.attack)
+    #                if some_knight.health_bar.current_hp == 0:
+    #                    some_knight.kill()
+    #    positions.clear()
+
+    def attack_knight_left(self, knights_list, current_knight):
+        position_left = current_knight.position[0] - 1, current_knight.position[1]
+        for some_knight in knights_list:
+            if (some_knight.position == position_left and some_knight.team != current_knight.team):
+                some_knight.health_bar.take_dmg(current_knight.attack)
+                if some_knight.health_bar.current_hp <= 0:
+                    some_knight.kill()
+                    self.add_points(current_knight.team, 5)
+        for monster in self.list_monsters:
+            if monster.position == position_left:
+                monster.health_bar.take_dmg(current_knight.attack)
+                if monster.health_bar.current_hp <= 0:
+                    monster.kill()
+                    self.add_points(current_knight.team, monster.points)
+                else:
+                    current_knight.health_bar.take_dmg(monster.attack)
+                    if current_knight.health_bar.current_hp <= 0:
+                        current_knight.kill()
+        for castle in self.list_castles:
+            if castle.position == position_left:
+                castle.health_bar.take_dmg(current_knight.attack)
+
+
+    def attack_knight_right(self, knights_list, current_knight):
+        position_right = current_knight.position[0] + 1, current_knight.position[1]
+        for some_knight in knights_list:
+            if (some_knight.position == position_right and some_knight.team != current_knight.team):
+                some_knight.health_bar.take_dmg(current_knight.attack)
+                if some_knight.health_bar.current_hp == 0:
+                    some_knight.kill()
+                    self.add_points(current_knight.team, 5)
+        for monster in self.list_monsters:
+            if monster.position == position_right:
+                monster.health_bar.take_dmg(current_knight.attack)
+                if monster.health_bar.current_hp <= 0:
+                    monster.kill()
+                    self.add_points(current_knight.team, monster.points)
+                else:
+                    current_knight.health_bar.take_dmg(monster.attack)
+                    if current_knight.health_bar.current_hp <= 0:
+                        current_knight.kill()
+        for castle in self.list_castles:
+            if castle.position == position_right:
+                castle.health_bar.take_dmg(current_knight.attack)
+
+    def attack_knight_up(self, knights_list, current_knight):
+        position_up = current_knight.position[0], current_knight.position[1] - 1
+        for some_knight in knights_list:
+            if (some_knight.position == position_up and some_knight.team != current_knight.team):
+                some_knight.health_bar.take_dmg(current_knight.attack)
+                if some_knight.health_bar.current_hp == 0:
+                    some_knight.kill()
+                    self.add_points(current_knight.team, 5)
+        for monster in self.list_monsters:
+            if monster.position == position_up:
+                monster.health_bar.take_dmg(current_knight.attack)
+                if monster.health_bar.current_hp <= 0:
+                    monster.kill()
+                    self.add_points(current_knight.team, monster.points)
+                else:
+                    current_knight.health_bar.take_dmg(monster.attack)
+                    if current_knight.health_bar.current_hp <= 0:
+                        current_knight.kill()
+        for castle in self.list_castles:
+            if castle.position == position_up:
+                castle.health_bar.take_dmg(current_knight.attack)
+
+    def attack_knight_down(self, knights_list, current_knight):
+        position_down = current_knight.position[0], current_knight.position[1] + 1
+        for some_knight in knights_list:
+            if (some_knight.position == position_down and some_knight.team != current_knight.team):
+                some_knight.health_bar.take_dmg(current_knight.attack)
+                if some_knight.health_bar.current_hp == 0:
+                    some_knight.kill()
+                    self.add_points(current_knight.team, 5)
+        for monster in self.list_monsters:
+            if monster.position == position_down:
+                monster.health_bar.take_dmg(current_knight.attack)
+                if monster.health_bar.current_hp <= 0:
+                    monster.kill()
+                    self.add_points(current_knight.team, monster.points)
+                else:
+                    current_knight.health_bar.take_dmg(monster.attack)
+                    if current_knight.health_bar.current_hp <= 0:
+                        current_knight.kill()
+        for castle in self.list_castles:
+            if castle.position == position_down:
+                castle.health_bar.take_dmg(current_knight.attack)
+
     def handle_turn(self):
-        print("next turn")
         current_knight = self.knights_queue.dequeue_knight()
+        knights_list = self.list_knights_red + self.list_knights_blue
+        print("next turn " + current_knight.team)
         knight_pos_x = current_knight.position[0]
         knight_pos_y = current_knight.position[1]
+        positions = []
 
-        castle_cords = (self.list_castles[0].position[0], self.list_castles[0].position[1])
-        goal_list = castle_neighbors(self.map, castle_cords[0], castle_cords[1])  # list of castle neighbors
+        goal_list = self.decision_tree.predict_move(grid=self.map, current_knight=current_knight,
+                                                    monsters=self.list_monsters,
+                                                    opponents=self.list_knights_blue
+                                                    if current_knight.team_alias() == 'k_r' else self.list_knights_red,
+                                                    castle=self.list_castles[0])
+
+        if (len(self.list_knights_blue) == 0 or len(self.list_knights_red) == 0):
+            pygame.quit()
+
+        if len(goal_list) == 0:
+            return
 
         state = State((knight_pos_y, knight_pos_x), current_knight.direction.name)
         action_list = a_star(state, self.map, goal_list)
         print(action_list)
+        print(goal_list)
 
         if len(action_list) == 0:
             return
 
         next_action = action_list.pop(0)
+
+        #if current_knight.health_bar.current_hp != 0:
+        #self.attack_knight(knights_list, positions, current_knight)
+
+        if current_knight.direction.name == UP:
+            self.attack_knight_up(knights_list, current_knight)
+        elif current_knight.direction.name == DOWN:
+            self.attack_knight_down(knights_list, current_knight)
+        elif current_knight.direction.name == RIGHT:
+            self.attack_knight_right(knights_list, current_knight)
+        elif current_knight.direction.name == LEFT:
+            self.attack_knight_left(knights_list, current_knight)
+
         if next_action == TURN_LEFT:
             self.logs.enqueue_log(f'AI {current_knight.team}: Obrót w lewo.')
             current_knight.rotate_left()
@@ -131,9 +257,9 @@ class Level:
             current_knight.rotate_right()
         elif next_action == FORWARD:
             current_knight.step_forward()
-            self.map[knight_pos_y][knight_pos_x] = 'g'
+            self.map[knight_pos_y][knight_pos_x] = MAP_ALIASES.get("GRASS")
 
-            # update knight on map
+                # update knight on map
             if current_knight.direction.name == UP:
                 self.logs.enqueue_log(f'AI {current_knight.team}: Ruch do góry.')
                 self.map[knight_pos_y - 1][knight_pos_x] = current_knight.team_alias()
@@ -147,19 +273,6 @@ class Level:
                 self.logs.enqueue_log(f'AI {current_knight.team}: Ruch w lewo.')
                 self.map[knight_pos_y][knight_pos_x - 1] = current_knight.team_alias()
 
-    def update_health_bars(self):
-        for knight in self.list_knights_blue:
-            knight.health_bar.update()
-
-        for knight in self.list_knights_red:
-            knight.health_bar.update()
-
-        for monster in self.list_monsters:
-            monster.health_bar.update()
-
-        for castle in self.list_castles:
-            castle.health_bar.update()
-
     def update(self):
         bg_width = (GRID_CELL_PADDING + GRID_CELL_SIZE) * COLUMNS + BORDER_WIDTH
         bg_height = (GRID_CELL_PADDING + GRID_CELL_SIZE) * ROWS + BORDER_WIDTH
@@ -167,4 +280,7 @@ class Level:
 
         # update and draw the game
         self.sprites.draw(self.screen)
-        self.update_health_bars()  # has to be called last
+        self.sprites.update()
+
+
+

models/castle.py

@@ -16,5 +16,7 @@ class Castle(pygame.sprite.Sprite):
         position_in_px = (parse_cord(position[0]), parse_cord(position[1]))
         self.rect = self.image.get_rect(center=position_in_px)
         self.max_hp = 80
-        self.current_hp = random.randint(1, self.max_hp)
-        self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
+        self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
+
+    def update(self):
+        self.health_bar.update()

models/knight.py

@@ -7,8 +7,11 @@ from common.helpers import parse_cord
 from logic.health_bar import HealthBar
 
 
-def load_knight_textures():
-    random_index = random.randint(1, 4)
+def load_knight_textures(team):
+    if team == "blue":
+        random_index = 3
+    else:
+        random_index = 4
     states = [
         pygame.image.load(f'resources/textures/knight_{random_index}_up.png').convert_alpha(),  # up = 0
         pygame.image.load(f'resources/textures/knight_{random_index}_right.png').convert_alpha(),  # right = 1
@@ -24,7 +27,7 @@ class Knight(pygame.sprite.Sprite):
         super().__init__(group)
 
         self.direction = Direction.DOWN
-        self.states = load_knight_textures()
+        self.states = load_knight_textures(team)
 
         self.image = self.states[self.direction.value]
         self.position = position
@@ -33,21 +36,35 @@ class Knight(pygame.sprite.Sprite):
         self.rect = self.image.get_rect(topleft=position_in_px)
 
         self.team = team
-        self.max_hp = random.randint(7, 12)
-        self.current_hp = random.randint(1, self.max_hp)
-        self.attack = random.randint(4, 7)
+        self.max_hp = random.randint(9, 13)
+        self.attack = random.randint(2, 4)
         self.defense = random.randint(1, 4)
         self.points = 1
-        self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
+        self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
 
     def rotate_left(self):
         self.direction = self.direction.left()
         self.image = self.states[self.direction.value]
 
+    def update(self):
+        self.health_bar.update()
+
     def rotate_right(self):
         self.direction = self.direction.right()
         self.image = self.states[self.direction.value]
 
+    def take_dmg(self, amount):
+        self.health_bar.take_dmg(amount)
+
+    def heal(self, amount):
+        self.health_bar.heal(amount)
+
+    def get_current_hp(self):
+        return self.health_bar.current_hp
+
+    def get_max_hp(self):
+        return self.health_bar.max_hp
+
     def step_forward(self):
         if self.direction.name == 'UP':
             self.position = (self.position[0], self.position[1] - 1)

models/monster.py

@@ -1,6 +1,7 @@
-import pygame.image
 import random
 
+import pygame.image
+
 from common.helpers import parse_cord
 from logic.health_bar import HealthBar
 
@@ -20,14 +21,14 @@ class Monster(pygame.sprite.Sprite):
         self.image = pygame.transform.scale(self.image, (40, 40))
         position_in_px = (parse_cord(position[0]), parse_cord(position[1]))
         self.rect = self.image.get_rect(topleft=position_in_px)
-
-        self.max_hp = random.randrange(15, 25)
-        self.current_hp = random.randint(1, self.max_hp)
-        self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
-        self.attack = random.randrange(2, 10)
+        self.position = position
+        self.max_hp = random.randrange(15, 20)
+        self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp,
+                                    calculate_xy=True, calculate_size=True)
+        self.attack = random.randrange(4, 6)
         if self.image == monster_images[0]:
             self.max_hp = 20
-            self.attack = 9
+            self.attack = 6
             self.points = 10
         elif self.image == monster_images[1]:
             self.max_hp = 15
@@ -41,3 +42,6 @@ class Monster(pygame.sprite.Sprite):
             self.max_hp = 7
             self.attack = 2
             self.points = 2
+
+    def update(self):
+        self.health_bar.update()

resources/maps/map_2022_06_02_13_27_18.json

@@ -0,0 +1 @@
+{"map": [[0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 3, 3, 0, 0, 1, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 3], [0, 0, 0, 3, 3, 3, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 3], [0, 0, 0, 3, 3, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 4, 0, 0, 0, 2, 0, 3], [0, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2], [0, 0, 3, 3, 3, 0, 0, 0, 3, 3, 3, 3, 0, 2, 2, 2, 0, 0, 0, 0, 0, 7, 2, 0], [0, 0, 0, 6, 0, 0, 0, 2, 2, 2, 0, 5, 5, 0, 2, 0, 0, 2, 2, 2, 2, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 5, 5, 0, 2, 0, 0, 0, 0, 2, 2, 1, 1, 7], [0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 3, 3, 1, 7], [6, 0, 0, 6, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 1, 1, 0], [6, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 3, 3, 0, 0, 0, 0, 3, 3, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 3, 3, 0, 1, 1, 7, 0], [0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 3, 3, 3, 1, 1, 1, 0], [0, 3, 3, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 1, 1, 0, 0], [0, 3, 3, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 4, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}

resources/maps/map_2022_06_06_14_55_49.json

@@ -0,0 +1 @@
+{"map": [[0, 0, 0, 0, 0, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0], [0, 3, 3, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 3, 3, 3, 0, 0, 0, 2, 0, 0, 0, 0, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0], [0, 0, 3, 2, 2, 0, 0, 0, 0, 0, 0, 3, 3, 3, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 2, 2, 3, 0, 0, 0, 0, 0, 0, 3, 0, 0, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 3, 0, 0, 0, 0, 0, 3, 3, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 6, 3, 3, 0, 0, 0, 0, 0, 3, 0, 4, 0, 3, 0, 0, 0, 0, 0, 0, 7, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 5, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 5, 5, 0, 0, 0, 0, 0, 3, 3, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 7, 7, 0, 0], [6, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 3, 7, 0, 0, 0], [0, 0, 6, 6, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 0, 0, 0], [0, 2, 2, 2, 2, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0], [2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 2, 0, 0, 0, 0, 0, 4, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 3, 3, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}

resources/maps/map_2022_06_06_14_58_11.json

@@ -0,0 +1 @@
+{"map": [[0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 3, 3], [0, 0, 0, 0, 2, 0, 0, 0, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 3, 0], [0, 0, 0, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 3, 0, 0, 0, 2, 0], [0, 0, 3, 3, 3, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 2, 0], [0, 0, 3, 0, 3, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 3, 3, 0], [0, 0, 3, 3, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0], [0, 0, 0, 6, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0], [0, 6, 0, 0, 0, 0, 3, 0, 0, 0, 0, 5, 5, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 5, 5, 1, 2, 0, 0, 0, 0, 0, 0, 7, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 3, 0, 0, 0, 4, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0], [0, 0, 3, 3, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 4], [6, 0, 0, 6, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 1, 1, 0, 7, 0, 7, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 1, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 3, 3, 2, 0, 0, 0, 0, 0, 0], [0, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 0, 0], [0, 0, 2, 0, 2, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}

ui/screens/credits.py

@@ -1,6 +1,31 @@
-from ui.screens.screen import Screen
+import pygame
 
+from ui.screens.screen import Screen
+from common.colors import BLACK
+from common.helpers import draw_text
 
 class Credits(Screen):
+
     def __init__(self, screen, clock):
         super().__init__('credits', screen, clock)
+
+    def display_screen(self):
+        running = True
+        while running:
+            self.screen.fill((252, 164, 12))
+            draw_text('Twórcy :', BLACK, self.screen, 520, 150)
+            draw_text('Angelika Iskra', BLACK, self.screen, 520, 250)
+            draw_text('Dawid Korzępa', BLACK, self.screen, 520, 300)
+            draw_text('Juliusz Sadowski', BLACK, self.screen, 520, 350)
+            draw_text('Aleksandra Muczyńska', BLACK, self.screen, 520, 400)
+            draw_text('Jerzy Tomaszewski', BLACK, self.screen, 520, 450)
+            draw_text('Mateusz Konofał', BLACK, self.screen, 520, 500)
+            for event in pygame.event.get():
+                if event.type == pygame.QUIT:
+                    running = False
+                if event.type == pygame.KEYDOWN:
+                    if event.key == pygame.K_ESCAPE:
+                        running = False
+            pygame.display.update()
+            self.clock.tick(60)
+

ui/stats.py

@@ -8,13 +8,23 @@ from common.helpers import draw_text
 
 
 class Stats:
-    def __init__(self, screen):
+    def __init__(self, screen, list_knights_blue, list_knights_red):
         self.grid = []
+        self.list_knights_blue = list_knights_blue
+        self.list_knights_red = list_knights_red
         self.screen = screen
         self.x = (GRID_CELL_PADDING + GRID_CELL_SIZE) * COLUMNS + BORDER_WIDTH + 15
         self.y = 5
-        self.blue_team_hp_bar = HealthBar(self.screen, pygame.Rect(self.x + 30, self.y + 210, 100, 15), current_hp=50, max_hp=100)
-        self.red_team_hp_bar = HealthBar(self.screen, pygame.Rect(self.x + 210, self.y + 210, 100, 15), 100, 100)
+        self.blue_team_hp_bar = HealthBar(self.screen,
+                                          pygame.Rect(self.x + 30, self.y + 210, 100, 15),
+                                          current_hp=sum([knight.get_current_hp() for knight in self.list_knights_blue]),
+                                          max_hp=sum([knight.get_max_hp() for knight in self.list_knights_blue]))
+        self.red_team_hp_bar = HealthBar(self.screen,
+                                         pygame.Rect(self.x + 210, self.y + 210, 100, 15),
+                                         current_hp=sum([knight.get_current_hp() for knight in self.list_knights_red]),
+                                         max_hp=sum([knight.get_max_hp() for knight in self.list_knights_red]))
+        self.blue_team_points = 0
+        self.red_team_points = 0
 
     def update(self):
 
@@ -33,21 +43,25 @@ class Stats:
         draw_text('VS', FONT_DARK, self.screen, self.x + 150, self.y + 120, 36)
 
         # HP bars
-        #pygame.draw.rect(screen, RED, pygame.Rect(x + 30, y + 210, 100, 15), 0, 4)
-        #pygame.draw.rect(screen, RED, pygame.Rect(x + 210, y + 210, 100, 15), 0, 4)
+        self.red_team_hp_bar.take_dmg(self.red_team_hp_bar.current_hp -
+                                      sum([knight.get_current_hp() for knight in self.list_knights_red]))
+        self.blue_team_hp_bar.take_dmg(self.blue_team_hp_bar.current_hp -
+                                       sum([knight.get_current_hp() for knight in self.list_knights_blue]))
         self.red_team_hp_bar.update()
         self.blue_team_hp_bar.update()
 
-
-
         # texts
-        draw_text('Rycerze: 2', FONT_DARK, self.screen, self.x + 35, self.y + 240, 18)
-        draw_text('Fortece: 1', FONT_DARK, self.screen, self.x + 35, self.y + 270, 18)
+        draw_text('Rycerze: ' + str(len(self.list_knights_blue)), FONT_DARK, self.screen, self.x + 35, self.y + 240, 18)  # blue
 
-        draw_text('Rycerze: 4', FONT_DARK, self.screen, self.x + 215, self.y + 240, 18)
-        draw_text('Fortece: 0', FONT_DARK, self.screen, self.x + 215, self.y + 270, 18)
+        draw_text('Rycerze: ' + str(len(self.list_knights_red)), FONT_DARK, self.screen, self.x + 215, self.y + 240, 18)
 
         # points
         pygame.draw.rect(self.screen, ORANGE, pygame.Rect(self.x, self.y + 390, 340, 3))
-        draw_text('PUNKTY: 10', FONT_DARK, self.screen, self.x + 35, self.y + 408, 18, True)
-        draw_text('PUNKTY: 10', FONT_DARK, self.screen, self.x + 215, self.y + 408, 18, True)
+        draw_text('PUNKTY: ' + str(self.blue_team_points), FONT_DARK, self.screen, self.x + 35, self.y + 408, 18, True)
+        draw_text('PUNKTY: ' + str(self.red_team_points), FONT_DARK, self.screen, self.x + 215, self.y + 408, 18, True)
+
+    def add_points(self, team, points):
+        if team == "blue":
+            self.blue_team_points += points
+        else:
+            self.red_team_points += points