wozek/wozek.py

import pygame
import sys
import random
import os
import time
from collections import deque
import heapq
from classes import *
import numpy as np
import pandas as pd
import math
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
import category_encoders
from sklearn import metrics
from sklearn import tree

class Node():
    def __init__(self,position,rotation,action,parent,cost):
        self.position=position
        self.rotation=rotation
        self.action=action
        self.parent=parent
        self.cost=cost

    def __lt__(self, other):
            return (self.cost < other.cost)
    def __le__(self, other):
            return (self.cost <= other.cost)

# Initialize Pygame
pygame.init()

# Constants
TILE_SIZE = 96  # Size of a square tile in pixels
GRID_WIDTH, GRID_HEIGHT = 16,8 # Grid dimensions
SCREEN_WIDTH, SCREEN_HEIGHT = GRID_WIDTH * TILE_SIZE, GRID_HEIGHT * TILE_SIZE
FPS = 60  # Frames per second

# Setup display
screen = pygame.display.set_mode((SCREEN_WIDTH, SCREEN_HEIGHT))
pygame.display.set_caption('Forklift Game')

# Clock
clock = pygame.time.Clock()

# Function to load and scale images
def load_image(name, scale=None):
    """Loads an image and optionally scales it."""
    image = pygame.image.load(name).convert_alpha()
    if scale:
        image = pygame.transform.scale(image, scale)
    return image

# Placeholder for images (will be loaded after video mode set)
forklift_image_full = None
freight_images_full = None

# Game variables
forklift_pos = [7, 0]
rotation='E'# Adjusted starting position of the forklift
carrying_freight = False
carried_freight = None
freight_positions = {}  # Dictionary to keep track of freight positions and types


tile_cost={}
tile_cost[(8,0)]=10
tile_cost[(7,1)]=10
tile_cost[(6,1)]=3
tile_cost[(5,0)]=10


# Load images
def load_images():
    global forklift_image_full, freight_images_full
    global rotation
    if rotation=='E':
        forklift_image_full = load_image('forkliftE.png', (TILE_SIZE, TILE_SIZE))
    elif rotation=='W':
        forklift_image_full = load_image('forkliftW.png', (TILE_SIZE, TILE_SIZE))
    elif rotation=='N':
        forklift_image_full = load_image('forkliftN.png', (TILE_SIZE, TILE_SIZE))
    elif rotation=='S':
        forklift_image_full = load_image('forkliftS.png', (TILE_SIZE, TILE_SIZE))
    #forklift_image_full = load_image('forklift.png', (TILE_SIZE, TILE_SIZE))
    freight_images_full = {
        'clothes': load_image('clothes.png', (TILE_SIZE, TILE_SIZE)),
        'fruit': load_image('fruit.png', (TILE_SIZE, TILE_SIZE)),
        'nuclear_waste': load_image('nuclear_waste.png', (TILE_SIZE, TILE_SIZE)),
        'car_parts': load_image('car_parts.png', (TILE_SIZE, TILE_SIZE)),
    }

# Initialize or reset game elements
def init_game():
    freight_positions.clear()
    load_images()  # Ensure images are loaded after video mode set
    reset_truck_bed_freight()

# Reset freight on the truck bed
def reset_truck_bed_freight():
    types = list(freight_images_full.keys())
    for x in range(12, 16):
        freight_positions[(x, 0)] = random.choice(types)

# Drawing functions
def draw_board():
    screen.fill((255, 255, 255))
    for x in range(GRID_WIDTH):
        for y in range(GRID_HEIGHT):
            pygame.draw.rect(screen, (0, 0, 0), pygame.Rect(x * TILE_SIZE, y * TILE_SIZE, TILE_SIZE, TILE_SIZE), 1)

def draw_truck_bed_and_racks():
    for x in range(12, 16):
        pygame.draw.rect(screen, (0, 0, 255), (x * TILE_SIZE, 0, TILE_SIZE, TILE_SIZE))
    for y in range(5, 8):
        for x in range(GRID_WIDTH):
            pygame.draw.rect(screen, (165, 42, 42), (x * TILE_SIZE, y * TILE_SIZE, TILE_SIZE, TILE_SIZE))
    for key in tile_cost:
        x=key[0]
        y=key[1]
        pygame.draw.rect(screen, (10*tile_cost[key], 130, 100), (x * TILE_SIZE, y * TILE_SIZE, TILE_SIZE, TILE_SIZE))


def draw_forklift_and_freight():
    x, y = forklift_pos
    if carrying_freight:
        # Draw smaller images when carrying freight
        small_size = (TILE_SIZE // 2, TILE_SIZE // 2)
        forklift_small = pygame.transform.scale(forklift_image_full, small_size)
        freight_small = pygame.transform.scale(freight_images_full[carried_freight], small_size)
        screen.blit(forklift_small, (x * TILE_SIZE, y * TILE_SIZE + TILE_SIZE // 2))
        screen.blit(freight_small, (x * TILE_SIZE + TILE_SIZE // 2, y * TILE_SIZE))
    else:
        screen.blit(forklift_image_full, (x * TILE_SIZE, y * TILE_SIZE))

def draw_freight():
    for (x, y), freight_type in freight_positions.items():
        screen.blit(freight_images_full[freight_type], (x * TILE_SIZE, y * TILE_SIZE))

# Game mechanics
def move_forklift():
    global forklift_pos
    if(rotation=='E'):
        new_pos=[forklift_pos[0]+1,forklift_pos[1]]
    elif(rotation=='W'):
        new_pos=[forklift_pos[0]-1,forklift_pos[1]]
    elif(rotation=='N'):
        new_pos=[forklift_pos[0],forklift_pos[1]+1]
    elif (rotation == 'S'):
        new_pos = [forklift_pos[0], forklift_pos[1] - 1]
    #new_pos = [forklift_pos[0] + dx, forklift_pos[1] + dy]
    if 0 <= new_pos[0] < GRID_WIDTH and 0 <= new_pos[1] < GRID_HEIGHT:
        forklift_pos = new_pos
def rotate_forklift(x):
    global rotation
    rot=['N','E','S','W']
    rots=rot.index(rotation)
    if x=='R':
        if rots==0:
            x=rot[3]
        else:
            x=rot[rots-1]

    elif x=='L':
        if rots==3:
            x=rot[0]
        else:
            x=rot[rots+1]
    rotation=x
def handle_freight():
    global carrying_freight, carried_freight, freight_positions
    pos_tuple = tuple(forklift_pos)
    if carrying_freight:
        if pos_tuple not in freight_positions:
            freight_positions[pos_tuple] = carried_freight
            carrying_freight = False
            carried_freight = None
    else:
        if pos_tuple in freight_positions:
            carried_freight = freight_positions.pop(pos_tuple)
            carrying_freight = True

#searching for successors
def succ(current_node):
    current_rotation=current_node.rotation
    x=current_node.position[0]
    y=current_node.position[1]
    current_cost=tile_cost.get((x,y),1)
    successors=[]
    if(current_rotation=="N"):
        if(y>0):
            pos=[]
            pos.append(x)

            pos.append(y-1)
            action='FW'
            successor=Node(pos,current_rotation,action,current_node,current_cost)
            successors.append(successor)
        if(x>0):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation='W'
            action='L'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)
        if(x<15):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation='E'
            action='R'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)


    elif (current_rotation == "S"):
        if (y < 7):
            pos = []
            pos.append(x)
            pos.append(y + 1)
            action = 'FW'
            successor = Node(pos, current_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (x <15):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'E'
            action='L'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (x > 0):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'W'
            action = 'R'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)

    elif (current_rotation == "E"):
        if (x <15):
            pos = []
            pos.append(x+1)
            pos.append(y)
            action = 'FW'
            successor = Node(pos, current_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (y <7):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'S'
            action='R'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (y >0):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'N'
            action = 'L'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)

    elif (current_rotation == "W"):
        if (x > 0):
            pos = []
            pos.append(x-1)
            pos.append(y)
            action = 'FW'
            successor = Node(pos, current_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (y >0):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'N'
            action='R'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)
        if (y <7):
            pos = []
            pos.append(x)
            pos.append(y)
            new_rotation = 'S'
            action = 'L'
            successor = Node(pos, new_rotation,action,current_node,current_cost)
            successors.append(successor)

    return successors

def distance(current_node,target):
    return abs(current_node.position[0]-target.position[0])+abs(current_node.position[1]-target.position[1])

#bfs
def bfs(isstate,final):
    fringe=deque()
    fringe.append(isstate)
    path=[]
    explored=[]
    while(True):
        if(len(fringe)==0):
            return False
        node=fringe.popleft()
        if(node.position[0]==final.position[0] and node.position[1]==final.position[1]):
            while(node.parent!=None):
                path.append(node)
                node=node.parent
            return path
        explored.append(node)
        successors=succ(node)
        for successor in successors:
            if (successor not in fringe and successor not in explored):
                fringe.append(successor)
def astar(isstate,final):
    fringe=[]
    heapq.heappush(fringe,(0,isstate))
    path = []
    explored = []
    total_cost={isstate:0}
    while(True):
        if (len(fringe) == 0):
            return False
        a,node =heapq.heappop(fringe)
        if (node.position[0] == final.position[0] and node.position[1] == final.position[1]):
            while (node.parent != None):
                path.append(node)
                node = node.parent
            return path
        explored.append(node)
        successors = succ(node)
        for successor in successors:
            new_cost=total_cost[node]+successor.cost
            if (successor not in explored or new_cost<total_cost.get(successor,float('inf'))):
                total_cost[successor]=new_cost
                p=new_cost+distance(successor,final)
                heapq.heappush(fringe,(p,successor))

#drzewko
cols=['Height', 'Width', 'Depth', 'Weight', 'Damage', 'Label_State', 'Content', 'Value']
tree_data_base = pd.read_csv('paczki.csv')
x=tree_data_base.drop(columns='Acceptance')
y=tree_data_base['Acceptance']
x_train,x_test,y_train,y_test=train_test_split(x,y,test_size=0.4)
# Create Decision Tree classifer object
encoder = category_encoders.OrdinalEncoder(cols=cols)

x_train = encoder.fit_transform(x_train)

x_test = encoder.transform(x_test)

clf = DecisionTreeClassifier(criterion='entropy')
clf = clf.fit(x_train,y_train)

#Predict the response for test dataset
y_pred = clf.predict(x_test)
print("Accuracy:",metrics.accuracy_score(y_test, y_pred))

text_tree=tree.export_text(clf)
print(text_tree)
# Train Decision Tree Classifer
#clf = clf.fit(x_train,y_train)

"""def entropy(data):
    labels = data.iloc[:, -1]  # Ostatnia kolumna zawiera etykiety klas i pomija 1 wiersz bo jest tytulowy
    counts = labels.value_counts() #tu zlicza wszystkie opcje
    probabilities = counts / len(labels)    
    entropy = -sum(probabilities * np.log2(probabilities))
    return entropy

def information_gain(data, attribute):
    total_entropy = entropy(data)
    values = data[attribute].unique()   #przypisujemy wszystkie opcje danego atrybutu np wyoski/niski/sredni
    weighted_entropy = 0
    for value in values:
        subset = data[data[attribute] == value]  # przypisujesz wszystkie wiersze danego value do  subset
        subset_entropy = entropy(subset)
        weighted_entropy += (len(subset) / len(data)) * subset_entropy
    return (total_entropy - weighted_entropy)"""




# Main game loop
def game_loop():
    init_game()
    current=Node(forklift_pos,rotation,'start',None,0)
    final=Node([10,5],'N','final',None,0)
    path=astar(current,final)
    path.reverse()
    for node in path:
        print(node.action)
    i=0
    running = True
    while running:
        for event in pygame.event.get():
            if event.type == pygame.QUIT:
                running = False
            elif event.type == pygame.KEYDOWN:
                if event.key == pygame.K_LEFT:
                    rotate_forklift('L')
                    load_images()
                elif event.key == pygame.K_RIGHT:
                    rotate_forklift('R')
                    load_images()
                elif event.key == pygame.K_UP:
                    move_forklift()
                elif event.key == pygame.K_SPACE:
                    handle_freight()
                elif event.key == pygame.K_r:
                    reset_truck_bed_freight()

        draw_board()
        draw_truck_bed_and_racks()
        draw_freight()
        draw_forklift_and_freight()
        pygame.display.flip()
        clock.tick(FPS)
        if(i<len(path)):
            nod=path[i]
            if(nod.action=='FW'):
                move_forklift()
            elif(nod.action=='L'):
                rotate_forklift('L')
                load_images()
            elif(nod.action=='R'):
                rotate_forklift('R')
                load_images()
            i=i+1
            pygame.time.wait(500)

    pygame.quit()
    sys.exit()

game_loop()