updated version of the game. new aim to the plant. new algorithm that looking for the closest plant, new models for the plant-block and the field-block etc
10
README.md
@ -1,10 +0,0 @@
|
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# si23traktor
|
||||
|
||||
Projekt zaliczeniowy przedmiotu Sztuczna Inteligencja w semestrze letnim 2023.
|
||||
|
||||
Skład zespołu:
|
||||
- Jakub Chmielecki
|
||||
- Mikołaj Mazur
|
||||
- Szymon Szczubkowski
|
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- Tobiasz Przybylski
|
||||
- Aliaksei Shauchenka
|
BIN
__pycache__/chicken.cpython-310.pyc
Normal file
BIN
__pycache__/field_block.cpython-310.pyc
Normal file
85
blocks.py
@ -1,85 +0,0 @@
|
||||
import pygame
|
||||
import random
|
||||
from pygame.math import Vector2
|
||||
import soil
|
||||
|
||||
|
||||
class Blocks:
|
||||
|
||||
def __init__(self, parent_screen,cell_size):
|
||||
self.parent_screen = parent_screen
|
||||
self.flower_image = pygame.image.load(r'resources/flower.png').convert_alpha()
|
||||
self.flower_image = pygame.transform.scale(self.flower_image, (cell_size, cell_size))
|
||||
|
||||
self.stone_image = pygame.image.load(r'resources/stone.png').convert_alpha()
|
||||
self.stone_image = pygame.transform.scale(self.stone_image, (cell_size, cell_size))
|
||||
|
||||
self.leaf_image = pygame.image.load(r'resources/dead.png').convert_alpha()
|
||||
self.leaf_image = pygame.transform.scale(self.leaf_image, (cell_size, cell_size))
|
||||
|
||||
self.alive_leaf_image = pygame.image.load(r'resources/alive.png').convert_alpha()
|
||||
self.alive_leaf_image = pygame.transform.scale(self.alive_leaf_image, (cell_size, cell_size))
|
||||
|
||||
self.fawn_seed_image = pygame.image.load(r'resources/fawn_seed.png').convert_alpha()
|
||||
self.fawn_seed_image = pygame.transform.scale(self.fawn_seed_image, (cell_size, cell_size))
|
||||
|
||||
self.fawn_wheat_image = pygame.image.load(r'resources/fawn_wheat.png').convert_alpha()
|
||||
self.fawn_wheat_image = pygame.transform.scale(self.fawn_wheat_image, (cell_size, cell_size))
|
||||
|
||||
self.red_image = pygame.image.load(r'resources/redBush.png').convert_alpha()
|
||||
self.red_image = pygame.transform.scale(self.red_image, (cell_size, cell_size))
|
||||
|
||||
self.soil = soil.Soil()
|
||||
|
||||
|
||||
def locate_blocks(self, blocks_number, cell_number, body):
|
||||
for i in range(blocks_number):
|
||||
self.x = random.randint(0, cell_number-1)
|
||||
self.y = random.randint(0, cell_number-1)
|
||||
self.pos = [self.x,self.y]
|
||||
body.append(self.pos)
|
||||
#entire_block.update({self.x : 1}) # for now it may lay on each other,
|
||||
#print(entire_block)
|
||||
|
||||
def place_blocks(self, parent_screen, cell_size, body, color): #drawing blocks
|
||||
for block in body:
|
||||
x = int(block[0] * cell_size)
|
||||
y = int(block[1] * cell_size)
|
||||
if color == 'leaf':
|
||||
self.parent_screen.blit(self.leaf_image, (x, y))
|
||||
if color == 'alive':
|
||||
self.parent_screen.blit(self.alive_leaf_image, (x, y))
|
||||
if color == 'stone':
|
||||
self.parent_screen.blit(self.stone_image, (x, y))
|
||||
if color == 'flower':
|
||||
self.parent_screen.blit(self.flower_image, (x, y))
|
||||
if color == 'fawn_seed':
|
||||
self.parent_screen.blit(self.fawn_seed_image, (x, y))
|
||||
if color == 'fawn_wheat':
|
||||
self.parent_screen.blit(self.fawn_wheat_image, (x, y))
|
||||
if color == 'red':
|
||||
self.parent_screen.blit(self.red_image, (x, y))
|
||||
|
||||
|
||||
|
||||
# if color == 'potato':
|
||||
# pass
|
||||
|
||||
def locate_soil(self, name, acidity, irrigation, blocks_number):
|
||||
# for block in blocks_number:
|
||||
self.soil.set_name(name)
|
||||
self.soil.set_irrigation(irrigation)
|
||||
self.soil.set_acidity(acidity)
|
||||
|
||||
def get_soil_info(self):
|
||||
return self.soil
|
||||
|
||||
def draw_lines(self, parent_screen, cell_size): # background lines
|
||||
for i in range(1, 10):
|
||||
pygame.draw.line(self.parent_screen, (228, 253, 227), (cell_size * i, 0), (cell_size * i, parent_screen), 1)
|
||||
pygame.draw.line(self.parent_screen, (228, 253, 227), (0, cell_size * i), (parent_screen, cell_size * i), 1)
|
||||
|
||||
|
||||
|
||||
|
||||
|
BIN
chicken/__pycache__/chicken.cpython-310.pyc
Normal file
@ -1,10 +1,10 @@
|
||||
import pygame
|
||||
import random
|
||||
|
||||
class Tractor:
|
||||
def __init__(self, parent_screen, cell_size):
|
||||
self.parent_screen = parent_screen
|
||||
self.lastVisitedBlocks = [] # tractor stores last 3 visited blocks
|
||||
class Chicken:
|
||||
def __init__(self, surface, cell_size, cell_number):
|
||||
self.surface = surface
|
||||
self.lastVisitedBlocks = [] # Chicken stores last 3 visited blocks
|
||||
|
||||
self.up = pygame.image.load(r'resources/up.png').convert_alpha()
|
||||
self.down = pygame.image.load(r'resources/down.png').convert_alpha()
|
||||
@ -16,30 +16,26 @@ class Tractor:
|
||||
self.left = pygame.transform.scale(self.left, (cell_size+2, cell_size+2))
|
||||
self.right = pygame.transform.scale(self.right, (cell_size+4, cell_size+1))
|
||||
|
||||
self.x = cell_size*2 # to-check: start pos may be written explicit
|
||||
self.y = cell_size*2
|
||||
#self.pos = Vector2(self.x, self.y)
|
||||
self.x = 1 # to-check: start pos may be written explicit
|
||||
self.y = 1
|
||||
self.angle = 180
|
||||
self.direction = 'up'
|
||||
self.image = self.down
|
||||
self.step = 0
|
||||
self.lastVisitedBlocks = [] # as tractor moves it stores last 3 coordinates
|
||||
|
||||
|
||||
def draw(self):
|
||||
self.parent_screen.blit(self.image, (self.x, self.y)) # rotate tractor
|
||||
|
||||
|
||||
def move(self, direction, cell_size, cell_number):
|
||||
self.cell_size = cell_size
|
||||
self.cell_number = cell_number
|
||||
|
||||
def move(self, direction):
|
||||
print('MOVE')
|
||||
if direction == 'move':
|
||||
if self.angle == 0 and self.y != 0:
|
||||
self.y -= cell_size
|
||||
if self.angle == 90 and self.x != (cell_number-1)*cell_size:
|
||||
self.x += cell_size
|
||||
if self.angle == 180 and self.y != (cell_number-1)*cell_size:
|
||||
self.y += cell_size
|
||||
self.y -= 1
|
||||
if self.angle == 90 and self.x != (self.cell_number-1):
|
||||
self.x += 1
|
||||
if self.angle == 180 and self.y != (self.cell_number-1):
|
||||
self.y += 1
|
||||
if self.angle == 270 and self.x != 0:
|
||||
self.x -= cell_size
|
||||
self.x -= 1
|
||||
if direction == 'right':
|
||||
self.angle += 90
|
||||
if self.angle == 360:
|
||||
@ -62,35 +58,13 @@ class Tractor:
|
||||
print(self.x, self.y)
|
||||
print(self.step)
|
||||
|
||||
|
||||
def water(self, body_before, body_after, cell_size):
|
||||
self.pos = [self.x/cell_size, self.y/cell_size]
|
||||
if self.pos in body_before:
|
||||
body_before.remove(self.pos)
|
||||
body_after.append(self.pos)
|
||||
print('HERE!')
|
||||
#print(body)
|
||||
|
||||
def put_seed(self, body, seed_body, cell_size):
|
||||
#self.step = 0
|
||||
self.pos = [self.x/cell_size, self.y/cell_size]
|
||||
if self.pos in body:
|
||||
#body.remove(self.pos)
|
||||
seed_body.append(self.pos)
|
||||
print('HERE IS THE SEED!')
|
||||
|
||||
def harvest(self, seed_body, wheat_body, cell_size):
|
||||
self.pos = [self.x/cell_size, self.y/cell_size]
|
||||
if self.pos in seed_body:
|
||||
seed_body.remove(self.pos)
|
||||
wheat_body.append(self.pos)
|
||||
print('HERE IS THE WHEAT!')
|
||||
|
||||
|
||||
def water(self, xy , plant_list):
|
||||
for obj in plant_list:
|
||||
if obj.xy == xy:
|
||||
obj.state = 1
|
||||
|
||||
def walk(self):
|
||||
choice = ['up', 'down', 'left', 'right']
|
||||
|
||||
if self.x == 450:
|
||||
choice.pop(3)
|
||||
if self.x == 0:
|
||||
@ -99,6 +73,8 @@ class Tractor:
|
||||
choice.pop(0)
|
||||
if self.y == 450:
|
||||
choice.pop(1)
|
||||
|
||||
self.direction = random.choice(choice)
|
||||
self.move(self.direction)
|
||||
self.move(self.direction)
|
||||
|
||||
def draw(self):
|
||||
self.surface.blit(self.image, (self.x * self.cell_size, self.y * self.cell_size)) # rotate tractor
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@ -1,73 +0,0 @@
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||||
class Node:
|
||||
def __init__(self, state, parent='', action=''):
|
||||
self.state = state
|
||||
self.parent = parent
|
||||
self.action = action
|
||||
|
||||
|
||||
class Search:
|
||||
def __init__(self, cell_size, cell_number):
|
||||
self.cell_size = cell_size
|
||||
self.cell_number = cell_number
|
||||
|
||||
def succ(self, state):
|
||||
x = state[0]
|
||||
y = state[1]
|
||||
angle = state[2]
|
||||
match(angle):
|
||||
case 'UP':
|
||||
possible = [['left', x, y, 'LEFT'], ['right', x, y, 'RIGHT']]
|
||||
if y != 0: possible.append(['move', x, y - self.cell_size, 'UP'])
|
||||
return possible
|
||||
case 'RIGHT':
|
||||
possible = [['left', x, y, 'UP'], ['right', x, y, 'DOWN']]
|
||||
if x != self.cell_size*(self.cell_number-1): possible.append(['move', x + self.cell_size, y, 'RIGHT'])
|
||||
return possible
|
||||
case 'DOWN':
|
||||
possible = [['left', x, y, 'RIGHT'], ['right', x, y, 'LEFT']]
|
||||
if y != self.cell_size*(self.cell_number-1): possible.append(['move', x, y + self.cell_size, 'DOWN'])
|
||||
return possible
|
||||
case 'LEFT':
|
||||
possible = [['left', x, y, 'DOWN'], ['right', x, y, 'UP']]
|
||||
if x != 0: possible.append(['move', x - self.cell_size, y, 'LEFT'])
|
||||
return possible
|
||||
|
||||
def graphsearch(self, istate, goaltest):
|
||||
x = istate[0]
|
||||
y = istate[1]
|
||||
angle = istate[2]
|
||||
|
||||
fringe = [Node([x, y, angle])] # queue (moves/states to check)
|
||||
fringe_state = [fringe[0].state]
|
||||
explored = []
|
||||
|
||||
while True:
|
||||
if len(fringe) == 0:
|
||||
return False
|
||||
|
||||
elem = fringe.pop(0)
|
||||
fringe_state.pop(0)
|
||||
|
||||
# if goal_test(elem.state):
|
||||
# return
|
||||
# print(elem.state[0], elem.state[1], elem.state[2])
|
||||
if elem.state[0] == goaltest[0] and elem.state[1] == goaltest[1]: # checks if we reached the given point
|
||||
steps = []
|
||||
while elem.parent:
|
||||
steps.append([elem.action, elem.state[0], elem.state[1]]) # should return only elem.action in prod
|
||||
elem = elem.parent
|
||||
|
||||
steps.reverse()
|
||||
print(steps) # only for dev
|
||||
return steps
|
||||
|
||||
explored.append(elem.state)
|
||||
|
||||
for (action, state_x, state_y, state_angle) in self.succ(elem.state):
|
||||
if [state_x, state_y, state_angle] not in fringe_state and \
|
||||
[state_x, state_y, state_angle] not in explored:
|
||||
x = Node([state_x, state_y, state_angle])
|
||||
x.parent = elem
|
||||
x.action = action
|
||||
fringe.append(x)
|
||||
fringe_state.append(x.state)
|
69
land.py
@ -1,69 +0,0 @@
|
||||
import pygame
|
||||
import random
|
||||
|
||||
class Land:
|
||||
def __init__(self, parent_screen, cell_size, cell_number, all_soil_body, irrigation):
|
||||
self.parent_screen = parent_screen
|
||||
self.cell_number = cell_number
|
||||
self.cell_size = cell_size
|
||||
self._irrigation = irrigation
|
||||
self.all_soil_body = all_soil_body
|
||||
|
||||
self.grass_image = pygame.image.load(r'resources/grass.png').convert_alpha()
|
||||
self.grass_image = pygame.transform.scale(self.grass_image, (cell_size, cell_size))
|
||||
|
||||
# self.bad_grass_image = pygame.image.load(r'resources/bad_grass.png').convert()
|
||||
# self.bad_grass_image = pygame.transform.scale(self.bad_grass_image, (cell_size, cell_size))
|
||||
|
||||
self.black_earth_image = pygame.image.load(r'resources/grass.png').convert()
|
||||
self.black_earth_image = pygame.transform.scale(self.black_earth_image, (cell_size, cell_size))
|
||||
|
||||
self.green_earth_image = pygame.image.load(r'resources/grass.png').convert()
|
||||
self.green_earth_image = pygame.transform.scale(self.green_earth_image, (cell_size, cell_size))
|
||||
|
||||
self.fawn_soil_image = pygame.image.load(r'resources/fawn_soil.png').convert()
|
||||
self.fawn_soil_image = pygame.transform.scale(self.fawn_soil_image, (cell_size, cell_size))
|
||||
|
||||
self.fen_soil_image = pygame.image.load(r'resources/grass.png').convert()
|
||||
self.fen_soil_image = pygame.transform.scale(self.fen_soil_image, (cell_size, cell_size))
|
||||
|
||||
|
||||
def locate_soil(self, soil_body): # finds free places(coordinates) for soil and adds them to soil_body[]
|
||||
number_of_blocs_for_each_soil = 50
|
||||
|
||||
if number_of_blocs_for_each_soil > (self.cell_number * self.cell_number) // 4:
|
||||
number_of_blocs_for_each_soil = (self.cell_number * self.cell_number) // 4
|
||||
print('Number of soil blocks exceeds the number of fields!')
|
||||
|
||||
for i in range(number_of_blocs_for_each_soil): # can't be more than: (cell_number * cell_number) // soil_types
|
||||
while True:
|
||||
rand_x = random.randint(0, self.cell_number - 1) # to-check
|
||||
rand_y = random.randint(0, self.cell_number - 1)
|
||||
if [rand_x, rand_y] not in self.all_soil_body:
|
||||
self.all_soil_body.append([rand_x, rand_y])
|
||||
soil_body.append([rand_x, rand_y])
|
||||
break
|
||||
|
||||
def place_soil(self, soil_body, soil_name):
|
||||
for body in soil_body:
|
||||
x = int(body[0] * self.cell_size)
|
||||
y = int(body[1] * self.cell_size)
|
||||
if soil_name == 'black_earth':
|
||||
self.parent_screen.blit(self.black_earth_image, (x, y))
|
||||
if soil_name == 'green_earth':
|
||||
self.parent_screen.blit(self.green_earth_image, (x, y))
|
||||
if soil_name == 'fawn_soil':
|
||||
self.parent_screen.blit(self.fawn_soil_image, (x, y))
|
||||
if soil_name == 'fen_soil':
|
||||
self.parent_screen.blit(self.fen_soil_image, (x, y))
|
||||
|
||||
def set_and_place_block_of_grass(self, name):
|
||||
for i in range(0, self.cell_number):
|
||||
for k in range(0, self.cell_number):
|
||||
if [k, i] not in self.all_soil_body:
|
||||
x = int(k * self.cell_size)
|
||||
y = int(i * self.cell_size)
|
||||
if name == 'good':
|
||||
self.parent_screen.blit(self.grass_image, (x, y))
|
||||
if name == 'bad':
|
||||
self.parent_screen.blit(self.bad_grass_image, (x, y))
|
@ -1,51 +0,0 @@
|
||||
from collections import Counter
|
||||
|
||||
def tree_learn(examples, attributes, default_class):
|
||||
if len(examples) == 0:
|
||||
return default_class
|
||||
|
||||
if all(examples[0][-1] == example[-1] for example in examples):
|
||||
return examples[0][-1]
|
||||
|
||||
if len(attributes) == 0:
|
||||
class_counts = Counter(example[-1] for example in examples)
|
||||
majority_class = class_counts.most_common(1)[0][0]
|
||||
return majority_class
|
||||
|
||||
# Choose the attribute A as the root of the decision tree
|
||||
A = select_attribute(attributes, examples)
|
||||
|
||||
tree = {A: {}}
|
||||
new_attributes = [attr for attr in attributes if attr != A]
|
||||
new_default_class = Counter(example[-1] for example in examples).most_common(1)[0][0]
|
||||
|
||||
for value in get_attribute_values(A):
|
||||
new_examples = [example for example in examples if example[attributes.index(A)] == value]
|
||||
subtree = tree_learn(new_examples, new_attributes, new_default_class)
|
||||
tree[A][value] = subtree
|
||||
|
||||
return tree
|
||||
|
||||
# Helper function: Select the best attribute based on a certain criterion (e.g., information gain)
|
||||
def select_attribute(attributes, examples):
|
||||
# Implement your attribute selection criterion here
|
||||
pass
|
||||
|
||||
# Helper function: Get the possible values of an attribute from the examples
|
||||
def get_attribute_values(attribute):
|
||||
# Implement your code to retrieve the attribute values from the examples here
|
||||
pass
|
||||
|
||||
# Example usage with coordinates
|
||||
examples = [
|
||||
[1, 2, 'A'],
|
||||
[3, 4, 'A'],
|
||||
[5, 6, 'B'],
|
||||
[7, 8, 'B']
|
||||
]
|
||||
|
||||
attributes = ['x', 'y']
|
||||
default_class = 'unknown'
|
||||
|
||||
decision_tree = tree_learn(examples, attributes, default_class)
|
||||
print(decision_tree)
|
239
main.py
@ -1,160 +1,64 @@
|
||||
import os
|
||||
import pygame
|
||||
import random
|
||||
import land
|
||||
import tractor
|
||||
import blocks
|
||||
import astar_search
|
||||
import neural_network.inference
|
||||
import chicken.chicken as chick
|
||||
from pygame.locals import *
|
||||
|
||||
examples = [
|
||||
['piasek', 'sucha', 'jalowa', 'żółty'],
|
||||
['czarnoziem', 'wilgotna', 'bogata', 'brazowa'],
|
||||
['rzedzina', 'wilgotna', 'bogata', 'zielona'],
|
||||
['gleby murszowe', 'wilgotna', 'bogata', 'szara'],
|
||||
['pustynne gleby', 'sucha', 'jalowa', 'pomarańczowa'],
|
||||
['torfowiska', 'sucha', 'jalowa', 'czerwona']
|
||||
]
|
||||
|
||||
attributes = ['typ_gleby', 'wilgotność', 'zawartość_składników', 'kolor']
|
||||
|
||||
# Tworzenie obiektu TreeLearn i nauka drzewa decyzyjnego
|
||||
# tree_learner = TreeLearn()
|
||||
# default_class = 'nieznane'
|
||||
|
||||
# tree_learner.train(examples, attributes, default_class)
|
||||
|
||||
class TreeLearn:
|
||||
def __init__(self):
|
||||
self.tree = None
|
||||
|
||||
def train(self, examples, attributes, default_class):
|
||||
self.tree = self.build_tree(examples, attributes, default_class)
|
||||
|
||||
def build_tree(self, examples, attributes, default_class):
|
||||
if not examples:
|
||||
return Node(default_class)
|
||||
|
||||
if self.all_same_class(examples):
|
||||
return Node(examples[0][-1])
|
||||
|
||||
if not attributes:
|
||||
class_counts = self.get_class_counts(examples)
|
||||
default_class = max(class_counts, key=class_counts.get)
|
||||
return Node(default_class)
|
||||
|
||||
best_attribute = self.choose_attribute(examples, attributes)
|
||||
root = Node(best_attribute)
|
||||
|
||||
attribute_values = self.get_attribute_values(examples, best_attribute)
|
||||
|
||||
for value in attribute_values:
|
||||
new_examples = self.filter_examples(examples, best_attribute, value)
|
||||
new_attributes = attributes[:]
|
||||
new_attributes.remove(best_attribute)
|
||||
new_default_class = max(self.get_class_counts(new_examples), key=lambda k: class_counts.get(k, 0))
|
||||
|
||||
subtree = self.build_tree(new_examples, new_attributes, new_default_class)
|
||||
root.add_child(value, subtree)
|
||||
|
||||
return root
|
||||
|
||||
def all_same_class(self, examples):
|
||||
return len(set([example[-1] for example in examples])) == 1
|
||||
|
||||
def get_class_counts(self, examples):
|
||||
class_counts = {}
|
||||
for example in examples:
|
||||
class_label = example[-1]
|
||||
class_counts[class_label] = class_counts.get(class_label, 0) + 1
|
||||
return class_counts
|
||||
|
||||
def choose_attribute(self, examples, attributes):
|
||||
# Placeholder for attribute selection logic
|
||||
return attributes[0]
|
||||
|
||||
def get_attribute_values(self, examples, attribute):
|
||||
return list(set([example[attribute] for example in examples]))
|
||||
|
||||
def filter_examples(self, examples, attribute, value):
|
||||
return [example for example in examples if example[attribute] == value]
|
||||
from models import plant
|
||||
from methods import field_settings
|
||||
import neural_network.inference
|
||||
import models.plant as plant
|
||||
import methods.plants_settings as plants_settings
|
||||
import methods.graph_search as graph_search
|
||||
|
||||
|
||||
class Node:
|
||||
def __init__(self, label):
|
||||
self.label = label
|
||||
self.children = {}
|
||||
|
||||
def add_child(self, value, child):
|
||||
self.children[value] = child
|
||||
#import models.field_block as field_block
|
||||
|
||||
|
||||
class Game:
|
||||
cell_size = 50
|
||||
cell_number = 15 # horizontally
|
||||
blocks_number = 20
|
||||
|
||||
dry_grass_number = 50
|
||||
wet_grass_number = (cell_number*cell_number) - dry_grass_number
|
||||
|
||||
def __init__(self):
|
||||
|
||||
self.dead_leaf_body = []
|
||||
self.green_leaf_body = []
|
||||
self.stone_body = []
|
||||
self.flower_body = []
|
||||
self.dead_grass_body = []
|
||||
self.grass_body = []
|
||||
self.red_block = [] #aim block
|
||||
|
||||
self.fawn_seed_body = []
|
||||
self.fawn_wheat_body = []
|
||||
|
||||
self.black_earth_body = []
|
||||
self.green_earth_body = []
|
||||
self.fawn_soil_body = []
|
||||
self.fen_soil_body = []
|
||||
self.allBodyPos = []
|
||||
|
||||
self.entire_block = {}
|
||||
|
||||
# initialize a window
|
||||
pygame.init()
|
||||
self.surface = pygame.display.set_mode((self.cell_size*self.cell_number, self.cell_size*self.cell_number))
|
||||
|
||||
# finds places for every type soil and grass
|
||||
self.black_earth = land.Land(self.surface, self.cell_size, self.cell_number, self.allBodyPos, 100)
|
||||
self.black_earth.locate_soil(self.black_earth_body)
|
||||
self.green_earth = land.Land(self.surface, self.cell_size, self.cell_number, self.allBodyPos, 100)
|
||||
self.green_earth.locate_soil(self.green_earth_body)
|
||||
self.fawn_soil = land.Land(self.surface, self.cell_size, self.cell_number, self.allBodyPos, 100)
|
||||
self.fawn_soil.locate_soil(self.fawn_soil_body)
|
||||
self.fen_soil = land.Land(self.surface, self.cell_size, self.cell_number, self.allBodyPos, 100)
|
||||
self.fen_soil.locate_soil(self.fen_soil_body)
|
||||
self.grass = land.Land(self.surface, self.cell_size, self.cell_number, self.allBodyPos, 100)
|
||||
self.grass_list = []
|
||||
self.plant_list = []
|
||||
self.stone_list = []
|
||||
self.aim_list = []
|
||||
|
||||
self.blocks = blocks.Blocks(self.surface, self.cell_size)
|
||||
self.blocks.locate_blocks(self.blocks_number, self.cell_number, self.dead_leaf_body)
|
||||
self.blocks.locate_blocks(self.blocks_number, self.cell_number, self.stone_body)
|
||||
self.blocks.locate_blocks(self.blocks_number, self.cell_number, self.flower_body)
|
||||
self.Field = field_settings.FieldSettings(self.surface, self.cell_size, self.cell_number)
|
||||
self.Field.locate_field(self.grass_list, 0, self.wet_grass_number) # wet grass
|
||||
self.Field.locate_field(self.grass_list, 1, self.dry_grass_number) # dry grass
|
||||
|
||||
#self.blocks.locate_blocks(1, self.cell_number, self.red_block)
|
||||
self.Plants = plants_settings.PlantsSettings(self.surface, self.cell_size, self.cell_number)
|
||||
|
||||
self.Plants.locate_plant(self.plant_list, 'wheat', self.blocks_number)
|
||||
self.Plants.locate_plant(self.plant_list, 'flower', self.blocks_number)
|
||||
self.Plants.locate_plant(self.plant_list, 'bush', self.blocks_number)
|
||||
|
||||
# self.potato = blocks.Blocks(self.surface, self.cell_size)
|
||||
# self.potato.locate_soil('black earth', 6, 1, [])
|
||||
#self.Plants.locate_plant(self.plant_list, 'aim', 1)
|
||||
|
||||
self.tractor = tractor.Tractor(self.surface, self.cell_size)
|
||||
self.tractor.draw()
|
||||
self.Plants.locate_aim(self.aim_list, 0, 0)
|
||||
|
||||
self.Plants.locate_plant(self.stone_list, 'stone', self.blocks_number)
|
||||
|
||||
#self.image_wheat = self.Plants.wheat_watered()
|
||||
self.chicken = chick.Chicken(self.surface, self.cell_size, self.cell_number)
|
||||
self.chicken.draw()
|
||||
|
||||
def run(self):
|
||||
# print(self.potato.get_soil_info().get_name())
|
||||
# print(self.potato.get_soil_info().get_acidity())
|
||||
# print(self.potato.get_soil_info().get_irrigation())
|
||||
running = True
|
||||
clock = pygame.time.Clock()
|
||||
move_chicken_event = pygame.USEREVENT + 1
|
||||
pygame.time.set_timer(move_chicken_event, 500) # chicken moves every 1000 ms
|
||||
self.search_object = graph_search.Search(self.cell_size, self.cell_number)
|
||||
chicken_next_moves = []
|
||||
|
||||
move_tractor_event = pygame.USEREVENT + 1
|
||||
pygame.time.set_timer(move_tractor_event, 500) # tractor moves every 1000 ms
|
||||
tractor_next_moves = []
|
||||
astar_search_object = astar_search.Search(self.cell_size, self.cell_number)
|
||||
|
||||
veggies = dict()
|
||||
veggies_debug = dict()
|
||||
@ -165,35 +69,29 @@ class Game:
|
||||
if event.type == KEYDOWN:
|
||||
if pygame.key.get_pressed()[K_ESCAPE]:
|
||||
running = False
|
||||
# in case we want to use keyboard
|
||||
if pygame.key.get_pressed()[K_UP]:
|
||||
# self.tractor.move('up', self.cell_size, self.cell_number)
|
||||
self.tractor.move('move', self.cell_size, self.cell_number)
|
||||
# self.chicken.move('up', self.cell_size, self.cell_number)
|
||||
self.chicken.move('move', self.cell_size, self.cell_number)
|
||||
# if pygame.key.get_pressed()[K_DOWN]:
|
||||
# self.tractor.move('down', self.cell_size, self.cell_number)
|
||||
# self.chicken.move('down', self.cell_size, self.cell_number)
|
||||
if pygame.key.get_pressed()[K_LEFT]:
|
||||
self.tractor.move('left', self.cell_size, self.cell_number)
|
||||
self.chicken.move('left', self.cell_size, self.cell_number)
|
||||
if pygame.key.get_pressed()[K_RIGHT]:
|
||||
self.tractor.move('right', self.cell_size, self.cell_number)
|
||||
self.chicken.move('right', self.cell_size, self.cell_number)
|
||||
if pygame.key.get_pressed()[K_SPACE]:
|
||||
self.tractor.water(self.dead_leaf_body, self.green_leaf_body, self.cell_size)
|
||||
# self.tractor.water(self.grass_body, self.dead_grass_body, self.cell_size)
|
||||
if pygame.key.get_pressed()[K_q]:
|
||||
self.tractor.harvest(self.fawn_seed_body, self.fawn_wheat_body, self.cell_size)
|
||||
self.tractor.put_seed(self.fawn_soil_body, self.fawn_seed_body, self.cell_size)
|
||||
if event.type == move_tractor_event:
|
||||
if len(tractor_next_moves) == 0:
|
||||
random_x = random.randrange(0, self.cell_number * self.cell_size, 50)
|
||||
random_y = random.randrange(0, self.cell_number * self.cell_size, 50)
|
||||
print("Generated target: ",random_x, random_y)
|
||||
if self.red_block:
|
||||
self.red_block.pop()
|
||||
self.red_block.append([random_x/50, random_y/50])
|
||||
# below line should be later moved into tractor.py
|
||||
self.chicken.water(self.dead_leaf_body, self.green_leaf_body, self.cell_size)
|
||||
|
||||
if event.type == move_chicken_event:
|
||||
if len(chicken_next_moves) == 0:
|
||||
|
||||
angles = {0: 'UP', 90: 'RIGHT', 270: 'LEFT', 180: 'DOWN'}
|
||||
#bandaid to know about stones
|
||||
tractor_next_moves = astar_search_object.astarsearch(
|
||||
[self.tractor.x, self.tractor.y, angles[self.tractor.angle]], [random_x, random_y], self.stone_body, self.flower_body)
|
||||
closest_wheat = self.search_object.closest_point(self.chicken.x, self.chicken.y, 'wheat', self.plant_list)
|
||||
self.aim_list[0].xy[0] = closest_wheat[0]
|
||||
self.aim_list[0].xy[1] = closest_wheat[1]
|
||||
chicken_next_moves = self.search_object.astarsearch(
|
||||
[self.chicken.x, self.chicken.y, angles[self.chicken.angle]], [closest_wheat[0], closest_wheat[1]], self.stone_list, self.plant_list)
|
||||
|
||||
#neural_network
|
||||
current_veggie = next(os.walk('./neural_network/images/test'))[1][random.randint(0, len(next(os.walk('./neural_network/images/test'))[1])-1)]
|
||||
if(current_veggie in veggies_debug):
|
||||
veggies_debug[current_veggie]+=1
|
||||
@ -207,34 +105,23 @@ class Game:
|
||||
else:
|
||||
veggies[predicted_veggie] = 1
|
||||
print("Debug veggies: ", veggies_debug, "Predicted veggies: ", veggies)
|
||||
|
||||
else:
|
||||
self.tractor.move(tractor_next_moves.pop(0)[0], self.cell_size, self.cell_number)
|
||||
self.chicken.move(chicken_next_moves.pop(0)[0])
|
||||
if len(chicken_next_moves) == 0:
|
||||
self.chicken.water([self.aim_list[0].xy[0], self.aim_list[0].xy[1]], self.plant_list)
|
||||
print(self.chicken.x, self.chicken.y)
|
||||
|
||||
elif event.type == QUIT:
|
||||
running = False
|
||||
|
||||
self.surface.fill((123, 56, 51)) # background color
|
||||
self.grass.set_and_place_block_of_grass('good')
|
||||
self.black_earth.place_soil(self.black_earth_body, 'black_earth')
|
||||
self.green_earth.place_soil(self.green_earth_body, 'green_earth')
|
||||
self.fawn_soil.place_soil(self.fawn_soil_body, 'fawn_soil')
|
||||
self.fen_soil.place_soil(self.fen_soil_body, 'fen_soil')
|
||||
self.Field.draw_grass(self.grass_list)
|
||||
self.Plants.draw_plant(self.plant_list)
|
||||
self.Plants.draw_plant(self.stone_list)
|
||||
|
||||
self.Plants.draw_aim(self.aim_list)
|
||||
|
||||
# plants examples
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.dead_leaf_body, 'leaf')
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.green_leaf_body, 'alive')
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.stone_body, 'stone')
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.flower_body, 'flower')
|
||||
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.red_block, 'red')
|
||||
|
||||
# seeds
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.fawn_seed_body, 'fawn_seed')
|
||||
|
||||
# wheat
|
||||
self.blocks.place_blocks(self.surface, self.cell_size, self.fawn_wheat_body, 'fawn_wheat')
|
||||
|
||||
self.tractor.draw()
|
||||
self.chicken.draw()
|
||||
pygame.display.update()
|
||||
|
||||
|
||||
|
BIN
methods/__pycache__/field_settings.cpython-310.pyc
Normal file
BIN
methods/__pycache__/graph_search.cpython-310.pyc
Normal file
BIN
methods/__pycache__/plant_settings.cpython-310.pyc
Normal file
BIN
methods/__pycache__/plants_settings.cpython-310.pyc
Normal file
41
methods/field_settings.py
Normal file
@ -0,0 +1,41 @@
|
||||
import pygame
|
||||
import random
|
||||
import models.field_block as field_block
|
||||
|
||||
|
||||
class FieldSettings:
|
||||
def __init__(self, surface, cell_size, cell_number):
|
||||
self.wet_grass_image = pygame.image.load(r'resources/grass.png').convert_alpha()
|
||||
self.wet_grass_image = pygame.transform.scale(self.wet_grass_image, (cell_size, cell_size))
|
||||
|
||||
self.dry_grass_image = pygame.image.load(r'resources/dry_grass.png').convert()
|
||||
self.dry_grass_image = pygame.transform.scale(self.dry_grass_image, (cell_size, cell_size))
|
||||
|
||||
self.cell_number = cell_number
|
||||
self.cell_size = cell_size
|
||||
self.surface = surface
|
||||
self.all_blocks = []
|
||||
|
||||
def locate_field(self, field_list, state, num_of_blocks): # finds open space (coordinates)
|
||||
|
||||
for i in range(num_of_blocks):
|
||||
while True:
|
||||
rand_x = random.randint(0, self.cell_number - 1) # to-check
|
||||
rand_y = random.randint(0, self.cell_number - 1)
|
||||
if [rand_x, rand_y] not in self.all_blocks:
|
||||
self.all_blocks.append([rand_x, rand_y])
|
||||
if state == 0:
|
||||
self.block = field_block.FieldBlock(
|
||||
i, 'wet', 0, self.wet_grass_image, rand_x, rand_y
|
||||
)
|
||||
if state == 1:
|
||||
self.block = field_block.FieldBlock(
|
||||
i, 'dry', 1, self.dry_grass_image, rand_x, rand_y
|
||||
)
|
||||
field_list.append(self.block)
|
||||
break
|
||||
|
||||
|
||||
def draw_grass(self, field_list):
|
||||
for obj in field_list:
|
||||
self.surface.blit(obj.image, (int(obj.xy[0] * self.cell_size), int(obj.xy[1] * self.cell_size)))
|
@ -17,19 +17,19 @@ class Search:
|
||||
match(angle):
|
||||
case 'UP':
|
||||
possible = [['left', x, y, 'LEFT'], ['right', x, y, 'RIGHT']]
|
||||
if y != 0: possible.append(['move', x, y - self.cell_size, 'UP'])
|
||||
if y != 0: possible.append(['move', x, y - 1, 'UP'])
|
||||
return possible
|
||||
case 'RIGHT':
|
||||
possible = [['left', x, y, 'UP'], ['right', x, y, 'DOWN']]
|
||||
if x != self.cell_size*(self.cell_number-1): possible.append(['move', x + self.cell_size, y, 'RIGHT'])
|
||||
if x != (self.cell_number-1): possible.append(['move', x + 1, y, 'RIGHT'])
|
||||
return possible
|
||||
case 'DOWN':
|
||||
possible = [['left', x, y, 'RIGHT'], ['right', x, y, 'LEFT']]
|
||||
if y != self.cell_size*(self.cell_number-1): possible.append(['move', x, y + self.cell_size, 'DOWN'])
|
||||
if y != (self.cell_number-1): possible.append(['move', x, y + 1, 'DOWN'])
|
||||
return possible
|
||||
case 'LEFT':
|
||||
possible = [['left', x, y, 'DOWN'], ['right', x, y, 'UP']]
|
||||
if x != 0: possible.append(['move', x - self.cell_size, y, 'LEFT'])
|
||||
if x != 0: possible.append(['move', x - 1, y, 'LEFT'])
|
||||
return possible
|
||||
|
||||
def cost(self, node, stones, goal, flowers):
|
||||
@ -48,7 +48,7 @@ class Search:
|
||||
return abs(node.state[0] - goal[0]) + abs(node.state[1] - goal[1])
|
||||
|
||||
#bandaid to know about stones
|
||||
def astarsearch(self, istate, goaltest, cStones, cFlowers):
|
||||
def astarsearch(self, istate, goaltest, stone_list, plant_list):
|
||||
|
||||
#to be expanded
|
||||
def cost_old(x, y):
|
||||
@ -56,14 +56,21 @@ class Search:
|
||||
return 10
|
||||
else:
|
||||
return 1
|
||||
|
||||
|
||||
x = istate[0]
|
||||
y = istate[1]
|
||||
angle = istate[2]
|
||||
stones = []
|
||||
flowers = []
|
||||
|
||||
stones = [(x*50, y*50) for (x, y) in cStones]
|
||||
flowers = [(x*50, y*50) for (x, y) in cFlowers]
|
||||
for obj in stone_list:
|
||||
stones.append((obj.xy[0]*50, obj.xy[1]*50))
|
||||
for obj in plant_list:
|
||||
if obj.name == 'flower':
|
||||
flowers.append((obj.xy[0]*50, obj.xy[1]*50))
|
||||
|
||||
# stones = [(x*50, y*50) for (x, y) in stone_list]
|
||||
# flowers = [(x*50, y*50) for (x, y) in plant_list]
|
||||
|
||||
print(stones)
|
||||
|
||||
@ -113,3 +120,17 @@ class Search:
|
||||
if fringe[i][0].state == x.state:
|
||||
if fringe[i][1] > priority:
|
||||
fringe[i] = (x, priority)
|
||||
|
||||
|
||||
def closest_point(self, x, y, name, plant_list):
|
||||
self.max_distance = self.cell_number*self.cell_number
|
||||
for obj in plant_list:
|
||||
if obj.name == name:
|
||||
if obj.state == 0:
|
||||
self.distance = (abs(obj.xy[0] - x) + abs(obj.xy[1] - y))
|
||||
if self.distance <= self.max_distance:
|
||||
self.max_distance = self.distance
|
||||
x_close = obj.xy[0]
|
||||
y_close = obj.xy[1]
|
||||
#print("distance: ",self.distance, obj.xy[0], "+", obj.xy[1], "-" ,x, "+",y)
|
||||
return (x_close, y_close)
|
86
methods/plants_settings.py
Normal file
@ -0,0 +1,86 @@
|
||||
import pygame
|
||||
import random
|
||||
import models.field_block as field_block
|
||||
import models.plant as plant
|
||||
|
||||
|
||||
|
||||
class PlantsSettings:
|
||||
def __init__(self, surface, cell_size, cell_number):
|
||||
self.cell_number = cell_number
|
||||
self.cell_size = cell_size
|
||||
self.surface = surface
|
||||
self.all_blocks = []
|
||||
|
||||
self.flower_image = pygame.image.load(r'resources/flower.png').convert_alpha()
|
||||
self.flower_image = pygame.transform.scale(self.flower_image, (self.cell_size, self.cell_size))
|
||||
|
||||
self.stone_image = pygame.image.load(r'resources/stone.png').convert_alpha()
|
||||
self.stone_image = pygame.transform.scale(self.stone_image, (self.cell_size, self.cell_size))
|
||||
|
||||
self.bush_image = pygame.image.load(r'resources/bush.png').convert_alpha()
|
||||
self.bush_image = pygame.transform.scale(self.bush_image, (self.cell_size, self.cell_size))
|
||||
|
||||
self.ivy_image = pygame.image.load(r'resources/ivy.png').convert_alpha()
|
||||
self.ivy_image = pygame.transform.scale(self.ivy_image, (self.cell_size, self.cell_size))
|
||||
|
||||
self.wheat_dead_image = pygame.image.load(r'resources/wheat_dead.png').convert_alpha()
|
||||
self.wheat_dead_image = pygame.transform.scale(self.wheat_dead_image, (self.cell_size, self.cell_size))
|
||||
self.wheat_image = pygame.image.load(r'resources/wheat.png').convert_alpha()
|
||||
self.wheat_image = pygame.transform.scale(self.wheat_image, (self.cell_size, self.cell_size))
|
||||
|
||||
self.aim_image = pygame.image.load(r'resources/aim.png').convert_alpha()
|
||||
self.aim_image = pygame.transform.scale(self.aim_image, (self.cell_size, self.cell_size))
|
||||
|
||||
def locate_plant(self, field_list, name, num_of_blocks): # finds open space (coordinates)
|
||||
|
||||
for i in range(num_of_blocks):
|
||||
while True:
|
||||
rand_x = random.randint(0, self.cell_number - 1) # to check
|
||||
rand_y = random.randint(0, self.cell_number - 1)
|
||||
if [rand_x, rand_y] not in self.all_blocks:
|
||||
self.all_blocks.append([rand_x, rand_y])
|
||||
if name == 'wheat':
|
||||
self.block = plant.Plant(
|
||||
i, name, 0, self.wheat_dead_image, self.wheat_image, rand_x, rand_y, False
|
||||
)
|
||||
if name == 'ivy':
|
||||
self.block = plant.Plant(
|
||||
i, name, 1, self.ivy_image, self.ivy_image, rand_x, rand_y, False
|
||||
)
|
||||
if name == 'flower':
|
||||
self.block = plant.Plant(
|
||||
i, name, 1, self.flower_image, self.flower_image, rand_x, rand_y, False
|
||||
)
|
||||
if name == 'stone':
|
||||
self.block = plant.Plant(
|
||||
i, name, 1, self.stone_image, self.stone_image, rand_x, rand_y, False
|
||||
)
|
||||
if name == 'buch':
|
||||
self.block = plant.Plant(
|
||||
i, name, 1, self.bush_image, self.bush_image, rand_x, rand_y, False
|
||||
)
|
||||
if name == 'aim':
|
||||
self.block = plant.Plant(
|
||||
999, name, 1, self.aim_image, self.aim_image, rand_x, rand_y, False
|
||||
)
|
||||
field_list.append(self.block)
|
||||
break
|
||||
|
||||
def locate_aim(self, field_list, x, y):
|
||||
self.block = plant.Plant(
|
||||
999, 'aim', 1, self.aim_image, self.aim_image, x, y, False
|
||||
)
|
||||
field_list.append(self.block)
|
||||
|
||||
def draw_plant(self, field_list):
|
||||
for obj in field_list:
|
||||
if obj.state == 0:
|
||||
self.surface.blit(obj.image_state_zero, (int(obj.xy[0] * self.cell_size), int(obj.xy[1] * self.cell_size)))
|
||||
if obj.state == 1:
|
||||
self.surface.blit(obj.image_state_one, (int(obj.xy[0] * self.cell_size), int(obj.xy[1] * self.cell_size)))
|
||||
|
||||
def draw_aim(self, aim_list):
|
||||
x = int(aim_list[0].xy[0] * self.cell_size)
|
||||
y = int(aim_list[0].xy[1] * self.cell_size)
|
||||
self.surface.blit(self.aim_image, (x, y)) # rotate tractor
|
BIN
models/__pycache__/field_block.cpython-310.pyc
Normal file
BIN
models/__pycache__/plant.cpython-310.pyc
Normal file
8
models/field_block.py
Normal file
@ -0,0 +1,8 @@
|
||||
class FieldBlock:
|
||||
def __init__(self, id, name, state, image, x, y):
|
||||
self.id = id
|
||||
self.name = name
|
||||
self.state = state
|
||||
self.image = image
|
||||
self.xy = [x, y]
|
||||
|
10
models/plant.py
Normal file
@ -0,0 +1,10 @@
|
||||
class Plant:
|
||||
def __init__(self, id, name, state, image_zero, image_one, x, y, empty):
|
||||
self.id = id
|
||||
self.name = name
|
||||
self.state = state
|
||||
self.image_state_zero = image_zero
|
||||
self.image_state_one = image_one
|
||||
self.xy = [x, y]
|
||||
self.empty = empty
|
||||
|
BIN
neural_network/.DS_Store
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neural_network/__pycache__/inference.cpython-310.pyc
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neural_network/__pycache__/model.cpython-310.pyc
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neural_network/images/.DS_Store
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