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32 changed files with 107 additions and 1047 deletions

1
.gitignore vendored
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@ -150,4 +150,3 @@ 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/

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@ -4,11 +4,10 @@ import heapq
from dataclasses import dataclass, field
from typing import Tuple, Optional, List
from algorithms.genetic.const import MAP_ALIASES
from common.constants import ROWS, COLUMNS, LEFT, RIGHT, UP, DOWN
from common.helpers import directions
EMPTY_FIELDS = [MAP_ALIASES.get("SAND"), MAP_ALIASES.get("GRASS"), ' ']
EMPTY_FIELDS = ['s', 'g', ' ']
TURN_LEFT = 'TURN_LEFT'
TURN_RIGHT = 'TURN_RIGHT'

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

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@ -1,142 +0,0 @@
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

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@ -1,29 +0,0 @@
# 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,
}

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@ -1,166 +0,0 @@
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

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@ -1,26 +0,0 @@
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()

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@ -1,42 +0,0 @@
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()

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@ -1,81 +0,0 @@
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()

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@ -1,64 +0,0 @@
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)

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@ -1,125 +0,0 @@
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()

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@ -1,27 +0,0 @@
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

View File

@ -1,12 +1,10 @@
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 = 200
TURN_INTERVAL = 300
GRID_CELL_PADDING = 5
GRID_CELL_SIZE = 36
@ -65,32 +63,12 @@ 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()}
LEFT = 'LEFT'
RIGHT = 'RIGHT'
UP = 'UP'
DOWN = 'DOWN'

View File

@ -2,11 +2,6 @@ from typing import Tuple, List
import pygame
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
@ -29,44 +24,6 @@ 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)
@ -101,7 +58,7 @@ def castle_neighbors(map, castle_bottom_right_row, castle_bottom_right_col):
return neighbors
def find_neighbours(grid: List[List[int]], col: int, row: int) -> List[Tuple[int, int]]:
def find_neighbours(grid: List[List[str]], col: int, row: int) -> List[Tuple[int, int]]:
dr = [-1, 1, 0, 0]
dc = [0, 0, -1, 1]
@ -113,7 +70,7 @@ def find_neighbours(grid: List[List[int]], col: int, row: int) -> List[Tuple[int
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
if grid[rr][cc] not in ['g', 's', '.']: continue
neighbours.append((rr, cc))
return neighbours

View File

@ -34,7 +34,7 @@ class DecisionTree:
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],
def predict_move(self, grid: List[List[str]], 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)
@ -42,23 +42,22 @@ class DecisionTree:
monsters_parsed = []
for monster in monsters:
monsters_parsed.append((manhattan_distance(current_knight.position, monster.position), parse_hp(
monster.health_bar.current_hp)))
monster.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)))
(manhattan_distance(current_knight.position, opponent.position), parse_hp(opponent.current_hp)))
prediction = self.get_prediction(tower_dist=distance_to_castle, tower_hp=castle.health_bar.current_hp,
prediction = self.get_prediction(tower_dist=distance_to_castle, tower_hp=castle.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}')
agent_hp=current_knight.current_hp)
print(prediction)
if prediction == 'tower': # castle...
return castle_neighbors(grid, castle_bottom_right_row=castle.position[0],
castle_bottom_right_col=castle.position[1])

View File

@ -27,6 +27,7 @@ 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,
@ -37,6 +38,7 @@ 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
@ -44,8 +46,6 @@ 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
@ -61,7 +61,8 @@ 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()

View File

@ -9,6 +9,7 @@ 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
@ -37,22 +38,22 @@ class HealthBar:
self.health_ratio = self.max_hp / self.width
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 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 heal(self, amount):
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
if self.target_hp < self.max_hp:
self.target_hp += amount
elif self.target_hp > self.max_hp:
self.target_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.current_hp / self.health_ratio), self.height))
pygame.Surface.fill(self.screen, GREEN, (self.x, self.y, int(self.target_hp / self.health_ratio), self.height))

View File

@ -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.health_bar.current_hp <= 0:
if knight.max_hp <= 0:
return self.dequeue_knight()
else:
self.queues[self.team_idx_turn].append(knight)

View File

@ -3,11 +3,10 @@ import random
import pygame
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 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
@ -22,7 +21,7 @@ class Level:
# sprite group setup
self.sprites = pygame.sprite.LayeredUpdates()
self.map = []
self.map = [['g' for _ in range(COLUMNS)] for y in range(ROWS)]
self.list_knights_blue = []
self.list_knights_red = []
@ -31,21 +30,28 @@ 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.map = import_random_map()
self.generate_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:
@ -57,15 +63,15 @@ class Level:
for col_index, col in enumerate(row):
# add base tiles, e.g. water, tree, grass
if col == MAP_ALIASES.get('WATER'):
if col == "w":
texture_index = 5
texture_surface = textures[texture_index][1]
Tile((col_index, row_index), texture_surface, self.sprites, 'w')
elif col == MAP_ALIASES.get('TREE'):
elif col == "t":
texture_index = 6
texture_surface = textures[texture_index][1]
Tile((col_index, row_index), texture_surface, self.sprites, 't')
elif col == MAP_ALIASES.get('SAND'):
elif col == "s":
texture_index = 4
texture_surface = textures[texture_index][1]
Tile((col_index, row_index), texture_surface, self.sprites)
@ -82,148 +88,37 @@ class Level:
for col_index, col in enumerate(row):
# add objects, e.g. knights, monsters, castle
if col == MAP_ALIASES.get('KNIGHT_BLUE'):
if col == "k_b":
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 == MAP_ALIASES.get('KNIGHT_RED'):
elif col == "k_r":
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 == MAP_ALIASES.get('MONSTER'):
elif col == "m":
monster = Monster(self.screen, (col_index, row_index), self.sprites)
self.map[row_index][col_index] = monster
self.list_monsters.append(monster)
elif col == MAP_ALIASES.get('CASTLE'):
elif col == "c":
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 = []
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,
opponents=self.list_knights_red
if current_knight.team_alias == 'k_r' else self.list_knights_blue,
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
@ -236,19 +131,6 @@ class Level:
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()
@ -257,9 +139,9 @@ class Level:
current_knight.rotate_right()
elif next_action == FORWARD:
current_knight.step_forward()
self.map[knight_pos_y][knight_pos_x] = MAP_ALIASES.get("GRASS")
self.map[knight_pos_y][knight_pos_x] = 'g'
# 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()
@ -273,6 +155,19 @@ 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
@ -280,7 +175,4 @@ class Level:
# update and draw the game
self.sprites.draw(self.screen)
self.sprites.update()
self.update_health_bars() # has to be called last

View File

@ -16,7 +16,5 @@ 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.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()
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)

View File

@ -7,11 +7,8 @@ from common.helpers import parse_cord
from logic.health_bar import HealthBar
def load_knight_textures(team):
if team == "blue":
random_index = 3
else:
random_index = 4
def load_knight_textures():
random_index = random.randint(1, 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
@ -27,7 +24,7 @@ class Knight(pygame.sprite.Sprite):
super().__init__(group)
self.direction = Direction.DOWN
self.states = load_knight_textures(team)
self.states = load_knight_textures()
self.image = self.states[self.direction.value]
self.position = position
@ -36,35 +33,21 @@ class Knight(pygame.sprite.Sprite):
self.rect = self.image.get_rect(topleft=position_in_px)
self.team = team
self.max_hp = random.randint(9, 13)
self.attack = random.randint(2, 4)
self.max_hp = random.randint(7, 12)
self.current_hp = random.randint(1, self.max_hp)
self.attack = random.randint(4, 7)
self.defense = random.randint(1, 4)
self.points = 1
self.health_bar = HealthBar(screen, self.rect, current_hp=self.max_hp, max_hp=self.max_hp, calculate_xy=True, calculate_size=True)
self.health_bar = HealthBar(screen, self.rect, current_hp=self.current_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)

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@ -22,13 +22,14 @@ class Monster(pygame.sprite.Sprite):
position_in_px = (parse_cord(position[0]), parse_cord(position[1]))
self.rect = self.image.get_rect(topleft=position_in_px)
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,
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(4, 6)
self.attack = random.randrange(2, 10)
if self.image == monster_images[0]:
self.max_hp = 20
self.attack = 6
self.attack = 9
self.points = 10
elif self.image == monster_images[1]:
self.max_hp = 15
@ -42,6 +43,3 @@ class Monster(pygame.sprite.Sprite):
self.max_hp = 7
self.attack = 2
self.points = 2
def update(self):
self.health_bar.update()

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

View File

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

View File

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

View File

@ -1,31 +1,6 @@
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)

View File

@ -8,23 +8,13 @@ from common.helpers import draw_text
class Stats:
def __init__(self, screen, list_knights_blue, list_knights_red):
def __init__(self, screen):
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=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
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)
def update(self):
@ -43,25 +33,21 @@ class Stats:
draw_text('VS', FONT_DARK, self.screen, self.x + 150, self.y + 120, 36)
# HP bars
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]))
#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.update()
self.blue_team_hp_bar.update()
# texts
draw_text('Rycerze: ' + str(len(self.list_knights_blue)), FONT_DARK, self.screen, self.x + 35, self.y + 240, 18) # blue
draw_text('Rycerze: ' + str(len(self.list_knights_red)), FONT_DARK, self.screen, self.x + 215, self.y + 240, 18)
# 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: 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)
# points
pygame.draw.rect(self.screen, ORANGE, pygame.Rect(self.x, self.y + 390, 340, 3))
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
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)