Zaktualizuj 'src/dimensions.py'

- END of bugfixing

with Michał Malinowski

AI/GeneticAlgorithm.py

@@ -0,0 +1,156 @@
+import keyboard as keyboard
+
+import field as F
+from ga_methods import *
+from src import mapschema as maps
+
+
+# Genetic Algorithm
+def genetic_algorithm_setup(field):
+    population_units = ["", "w", "p", "s"]
+
+    # TODO REPREZENTACJA OSOBNIKA - MACIERZ ROZKłADU PLONÓW
+    population_text = []
+    population_text_single = []
+
+    population_size = 10
+
+    # Populate the population_text array
+    for k in range(population_size):
+        population_text_single = []
+        for row in range(D.GSIZE):
+            population_text_single.append([])
+            for column in range(D.GSIZE):
+                population_text_single[row].append(random.choice(population_units))
+        population_text.append(population_text_single)
+
+    """
+    Genetic algorithm parameters:
+        Mating pool size
+        Population size
+    """
+
+    # units per population in generation
+    best_outputs = []
+    num_generations = 100
+    num_parents = 4
+
+    # iterative var
+    generation = 0
+    stop = 0
+    # TODO WARUNEK STOPU
+    while generation < num_generations and stop < 3:
+        if keyboard.is_pressed('space'):
+            generation += 1
+
+            print("Generation : ", generation)
+            # Measuring the fitness of each chromosome in the population.
+
+            # population Fitness
+            fitness = []
+
+            for i in range(0, population_size):
+                fitness.append((i, population_fitness(population_text[i], field, population_size)))
+
+            print("Fitness")
+            print(fitness)
+
+            best = sorted(fitness, key=lambda tup: tup[1], reverse=True)[0:num_parents]
+
+            # Leaderboard only
+            best_outputs.append(best[0][1])
+
+            # The best result in the current iteration.
+            print("Best result : ", best[0])
+
+            # TODO METODA WYBORU OSOBNIKA - RANKING
+            # Selecting the best parents in the population for mating.
+            parents = [population_text[i[0]] for i in best]
+            parents_copy = copy.deepcopy(parents)
+            print("Parents")
+            for i in range(0, len(parents)):
+                print('\n'.join([''.join(['{:4}'.format(item) for item in row])
+                                 for row in parents[i]]))
+                print("")
+
+            # Generating next generation using crossover.
+            offspring_x = random.randint(1, D.GSIZE - 2)
+            offspring_y = random.randint(1, D.GSIZE - 2)
+
+            # TODO OPERATOR KRZYŻOWANIA
+            offspring_crossover = crossover(parents)
+            print("Crossover")
+            for i in range(0, len(offspring_crossover)):
+                print('\n'.join([''.join(['{:4}'.format(item) for item in row])
+                                 for row in offspring_crossover[i]]))
+                print("")
+
+            # TODO OPERATOR MUTACJI
+            offspring_mutation = mutation(population_units, offspring_crossover, population_size - num_parents,
+                                          num_mutations=10)
+            print("Mutation")
+            for i in range(0, len(offspring_mutation)):
+                print('\n'.join([''.join(['{:4}'.format(item) for item in row])
+                                 for row in offspring_mutation[i]]))
+                print("")
+
+            population_text_copy = copy.deepcopy(population_text)
+            unused_indexes = [i for i in range(0, population_size) if i not in [j[0] for j in best]]
+            # Creating next generation
+            population_text = []
+            for k in parents_copy:
+                population_text.append(k)
+            for k in range(0, len(offspring_mutation)):
+                population_text.append(offspring_mutation[k])
+            while len(population_text) < population_size:
+                x = random.choice(unused_indexes)
+                population_text.append(population_text_copy[x])
+                unused_indexes.remove(x)
+
+            # TODO WARUNEK STOPU
+            stop = 0
+            if generation > 10:
+                if best_outputs[-1] / best_outputs[-2] < 1.001:
+                    stop += 1
+                if best_outputs[-1] / best_outputs[-3] < 1.001:
+                    stop += 1
+                if best_outputs[-2] / best_outputs[-3] < 1.001:
+                    stop += 1
+
+    # final Fitness
+    fitness = []
+    for i in range(0, population_size):
+        fitness.append((i, population_fitness(population_text[i], field, population_size)))
+
+    print("Final Fitness")
+    print(fitness)
+
+    best = sorted(fitness, key=lambda tup: tup[1])[0:num_parents]
+
+    print("Best solution : ", )
+    for i in range(0, D.GSIZE):
+        print(population_text[best[0][0]][i])
+    print("Best solution fitness : ", best[0][1])
+
+    pretty_printer(best_outputs)
+
+    # TODO REALLY return best iteration of field
+    return 0
+
+
+if __name__ == "__main__":
+
+    # Define the map of the field
+    mapschema = maps.createField()
+
+    # Create field array
+    field = []
+
+    # Populate the field array
+    for row in range(D.GSIZE):
+        field.append([])
+        for column in range(D.GSIZE):
+            fieldbit = F.Field(row, column, mapschema[column][row])
+            field[row].append(fieldbit)
+
+    genetic_algorithm_setup(field)

AI/NN_accuracy.py

@@ -0,0 +1,48 @@
+import torch
+import torchvision
+import torchvision.transforms as transforms
+import torch.nn as nn
+import torch.nn.functional as F
+import torch.optim as optim
+import numpy as np
+from matplotlib.pyplot import imshow
+import os
+import PIL
+import numpy as np
+from matplotlib.pyplot import imshow
+import neural_network
+from matplotlib.pyplot import imshow
+
+
+# wcześniej grader.py
+# Get accuracy for neural_network model 'network_model.pth'
+def NN_accuracy():
+    # Create the model
+    net = neural_network.Net()
+
+    # Load state_dict
+    neural_network.load_network_from_structure(net)
+
+    # Set model to eval
+    net.eval()
+
+    device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+    folderlist = os.listdir(os.path.dirname(__file__) + "\\test")
+
+    tested = 0
+    correct = 0
+
+    for folder in folderlist:
+        for file in os.listdir(os.path.dirname(__file__) + "\\test\\" + folder):
+            if neural_network.result_from_network(net, os.path.dirname(__file__) + "\\test\\" + folder + "\\" + file) == folder:
+                correct += 1
+                tested += 1
+            else:
+                tested += 1
+
+    print(correct/tested)
+
+
+if __name__ == "__main__":
+    NN_accuracy()

AI/decision_tree.py

@@ -0,0 +1,87 @@
+# used in Plant
+
+def decision_tree(plant):
+    if plant.field.hydration == 4:
+        if plant.is_healthy == 1:
+            if plant.field.tractor_there == 0:
+                if plant.ticks == 0:
+                    return 0
+                elif plant.ticks == 1:
+                    return 1
+            elif plant.field.tractor_there == 1:
+                return 0
+        elif plant.is_healthy == 0:
+            return 0
+    elif plant.field.hydration == 2:
+        if plant.species == "sorrel":
+            if plant.ticks == 1:
+                if plant.is_healthy == 1:
+                    return 1
+                elif plant.is_healthy == 0:
+                    return 0
+            elif plant.ticks == 0:
+                return 0
+        elif plant.species == "potato":
+            return 0
+        elif plant.species == "wheat":
+            return 0
+        elif plant.species == "strawberry":
+            return 0
+    elif plant.field.hydration == 1:
+        if plant.species == "potato":
+            return 0
+        elif plant.species == "strawberry":
+            if plant.ticks == 1:
+                return -1
+            elif plant.ticks == 0:
+                return 0
+        elif plant.species == "wheat":
+            return 0
+        elif plant.species == "sorrel":
+            if plant.is_healthy == 0:
+                return 0
+            elif plant.is_healthy == 1:
+                if plant.field.tractor_there == 0:
+                    if plant.ticks == 0:
+                        return 0
+                    elif plant.ticks == 1:
+                        return 1
+                elif plant.field.tractor_there == 1:
+                    return 0
+    elif plant.field.hydration == 3:
+        if plant.ticks == 1:
+            if plant.field.tractor_there == 0:
+                if plant.is_healthy == 1:
+                    if plant.species == "potato":
+                        if plant.field.fertility == 1:
+                            return 1
+                        elif plant.field.fertility == 0:
+                            return 0
+                    elif plant.species == "strawberry":
+                        return 1
+                    elif plant.species == "sorrel":
+                        return 1
+                    elif plant.species == "wheat":
+                        return 1
+                elif plant.is_healthy == 0:
+                    return 0
+            elif plant.field.tractor_there == 1:
+                return 0
+        elif plant.ticks == 0:
+            return 0
+    elif plant.field.hydration == 5:
+        if plant.field.tractor_there == 1:
+            return 0
+        elif plant.field.tractor_there == 0:
+            if plant.is_healthy == 0:
+                return 0
+            elif plant.is_healthy == 1:
+                if plant.ticks == 1:
+                    return 1
+                elif plant.ticks == 0:
+                    return 0
+    elif plant.field.hydration == 0:
+        if plant.ticks == 0:
+            return 0
+        elif plant.ticks == 1:
+            return -1

AI/ga_methods.py

@@ -0,0 +1,103 @@
+import copy
+import random
+
+import matplotlib
+import matplotlib.pyplot
+import numpy
+
+import src.dimensions as D
+
+
+# Genetic Algorithm methods
+
+def local_fitness(field, x, y, plants_case):
+    soil_value = 0
+    if field[x][y].field_type == "soil":
+        soil_value = 1
+    else:
+        soil_value = 0.5
+
+    if plants_case[x][y] == "":
+        plant_value = 0
+    elif plants_case[x][y] == "w":
+        plant_value = 1
+    elif plants_case[x][y] == "p":
+        plant_value = 2
+    elif plants_case[x][y] == "s":
+        plant_value = 3
+    else:
+        plant_value = 1
+
+    neighbour_bonus = 1
+
+    if x - 1 >= 0:
+        if plants_case[x][y] == plants_case[x - 1][y]:
+            neighbour_bonus += 1
+    if x + 1 < D.GSIZE:
+        if plants_case[x][y] == plants_case[x + 1][y]:
+            neighbour_bonus += 1
+    if y - 1 >= 0:
+        if plants_case[x][y] == plants_case[x][y - 1]:
+            neighbour_bonus += 1
+    if y + 1 < D.GSIZE:
+        if plants_case[x][y] == plants_case[x][y + 1]:
+            neighbour_bonus += 1
+
+    local_fitness_value = (soil_value + plant_value) * (0.5 * neighbour_bonus + 1)
+    return local_fitness_value
+
+
+def population_fitness(population_text_local, field, population_size):
+    # Calculating the fitness value of each solution in the current population.
+    # The fitness function calulates the sum of products between each input and its corresponding weight.
+    fitness = []
+
+    for k in range(population_size):
+        population_values_single = []
+        population_values_single_row = []
+        fitness_row = []
+
+        for i in range(0, D.GSIZE):
+            for j in range(0, D.GSIZE):
+                population_values_single_row.append(local_fitness(field, i, j, population_text_local))
+            population_values_single.append(population_values_single_row)
+
+        for i in range(D.GSIZE):
+            fitness_row.append(sum(population_values_single[i]))
+        fitness = sum(fitness_row)
+    return fitness
+
+
+def crossover(local_parents):
+    ret = []
+    for i in range(0, len(local_parents)):
+        child = copy.deepcopy(local_parents[i])
+        # Vertical randomization
+        width = random.randint(1, D.GSIZE // len(local_parents))  # width of stripes
+        indexes_parents = numpy.random.permutation(range(0, len(local_parents)))  # sorting of stripes
+        beginning = random.randint(0, len(local_parents[0]) - width * len(
+            local_parents))  # point we start putting the stripes from
+        for x in indexes_parents:
+            child[beginning:beginning + width] = local_parents[x][beginning:beginning + width]
+            beginning += width
+        ret.append(child)
+    return ret
+
+
+def mutation(population_units, offspring_crossover, num_mutants, num_mutations=10):
+    for case in range(0, len(offspring_crossover)):
+        for mutation in range(0, num_mutations):
+            mutation_x = random.randint(0, D.GSIZE - 1)
+            mutation_y = random.randint(0, D.GSIZE - 1)
+            mutation_value = random.choice(population_units)
+            offspring_crossover[case][mutation_x][mutation_y] = mutation_value
+            num_mutants -= 1
+
+    return offspring_crossover
+
+
+def pretty_printer(best_outputs):
+    matplotlib.pyplot.plot(best_outputs)
+    matplotlib.pyplot.xlabel("Iteration")
+    matplotlib.pyplot.ylabel("Fitness")
+    matplotlib.pyplot.show()

AI/id3.py

@@ -1,30 +1,35 @@
-from cases import *
-from collections import Counter
-import operator
-from types import prepare_class
-import numpy as np
 import copy
+import operator
+from collections import Counter
+
+import numpy as np
+
+from src.cases import *
+
 
 class Node:
     def __init__(self, Class, tag=None):
         self.Class = Class
         self.childs = []
 
-def classes_of_cases (cases):
+
+def classes_of_cases(cases):
     classes = []
     for case in cases:
         if case.Class not in classes:
             classes.append(case.Class)
     return classes
 
-def count_classes (cases):
+
+def count_classes(cases):
     classes = []
     for case in cases:
         classes.append(case.Class)
     c = Counter(classes)
     return max(c.items(), key=operator.itemgetter(1))[0]
 
-def chose_attribute (cases, attributes):
+
+def chose_attribute(cases, attributes):
     a = ""
     max = float("-inf")
     for attribute in attributes:
@@ -33,7 +38,8 @@ def chose_attribute (cases, attributes):
             a = attribute
     return a
 
-def I (cases):
+
+def I(cases):
     i = 0
     all = len(cases)
     classes = classes_of_cases(cases)
@@ -42,9 +48,10 @@ def I (cases):
         for case in cases:
             if case.Class == Class:
                 noc += 1
-        i -= (noc/all)*np.log2(noc/all)
+        i -= (noc / all) * np.log2(noc / all)
     return i
 
+
 def E(cases, attribute):
     e = 0
     values = []
@@ -57,9 +64,9 @@ def E(cases, attribute):
         for case in cases:
             if case.values[index] == value:
                 ei.append(case)
-        e += (len(ei)/len(cases))*I(ei)
+        e += (len(ei) / len(cases)) * I(ei)
     return e
-        
+
 
 def treelearn(cases, attributes, default_class):
     if cases == []:
@@ -86,15 +93,16 @@ def treelearn(cases, attributes, default_class):
         for case in cases:
             if case.values[index] == value:
                 new_case = copy.deepcopy(case)
-                new_case.values = case.values[:index] + case.values[index+1:]
-                new_case.attributes = case.attributes[:index] + case.attributes[index+1:]
+                new_case.values = case.values[:index] + case.values[index + 1:]
+                new_case.attributes = case.attributes[:index] + case.attributes[index + 1:]
                 new_cases.append(new_case)
-        new_attributes = attributes[:index] + attributes[index+1 :]
+        new_attributes = attributes[:index] + attributes[index + 1:]
         child = treelearn(new_cases, new_attributes, new_default_class)
         t.childs.append([child, value])
 
     return t
 
+
 def pretty_print(root, n):
     if len(root.childs) == 0:
         for _ in range(n):
@@ -104,19 +112,15 @@ def pretty_print(root, n):
         for _ in range(n):
             print("    ", end="")
         if child != root.childs[0]:
-            print("el", end= "")
+            print("el", end="")
         if len(str(child[1])) > 1:
             print("if self." + str(root.Class) + " == \"" + str(child[1]) + "\":")
         else:
             print("if self." + str(root.Class) + " == " + str(child[1]) + ":")
-        pretty_print(child[0], n+1)
+        pretty_print(child[0], n + 1)
 
 
-tree = treelearn(cases, attributes, 0)
-pretty_print(tree, 0)
-
-
-    
-
-    
-    
+# Get view of decision_tree.py
+if __name__ == "__main__":
+    tree = treelearn(cases, attributes, 0)
+    pretty_print(tree, 0)

AI/neural_network.py

@@ -2,7 +2,7 @@ import torch
 import torchvision
 import torchvision.transforms as transforms
 import torch.nn as nn
-import torch.nn.functional as f
+import torch.nn.functional as F
 import torch.optim as optim
 import numpy as np
 from matplotlib.pyplot import imshow
@@ -21,38 +21,47 @@ class Negative(object):
     
     def __call__(self, img):
         return to_negative(img)
-
-def plotdigit(image):
-    img = np.reshape(image, (-1, 100))
-    imshow(img, cmap='Greys')
-
+       
 transform = transforms.Compose([Negative(), transforms.ToTensor()])
 train_set = torchvision.datasets.ImageFolder(root='train', transform=transform)
-classes = ("apple", "potato")
+classes = ("pepper", "potato", "strawberry", "tomato")
 
-BATCH_SIZE = 2
+BATCH_SIZE = 4
 train_loader = torch.utils.data.DataLoader(train_set, batch_size=BATCH_SIZE, shuffle=True, num_workers=0)
 
 device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 class Net(nn.Module):
     def __init__(self):
-        super(Net, self).__init__()
-        self.flatten = nn.Flatten()
-        self.linear_relu_stack = nn.Sequential(
-            nn.Linear(3*100*100, 512),
+        super().__init__()
+        self.network = nn.Sequential(
+            nn.Conv2d(3, 32, kernel_size=3, padding=1), #3 channels to 32 channels
             nn.ReLU(),
-            nn.Linear(512, 512),
+            nn.Conv2d(32, 64, kernel_size=3, stride=1, padding=1),
             nn.ReLU(),
-            nn.Linear(512, 2),
-            nn.ReLU()
-        )
-        self.linear_relu_stack = self.linear_relu_stack.to(device)
+            nn.MaxPool2d(2, 2), # output: 64 channels x 50 x 50 image size - decrease
 
-    def forward(self, x):
-        x = self.flatten(x).to(device)
-        logits = self.linear_relu_stack(x).to(device)
-        return logits
+            nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1), #increase power of model 
+            nn.ReLU(),
+            nn.MaxPool2d(2, 2), # output: 128 x 25 x 25
+
+            nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1),
+            nn.ReLU(),
+            nn.Conv2d(256, 256, kernel_size=3, stride=1, padding=1),
+            nn.ReLU(),
+            nn.MaxPool2d(5, 5), # output: 256 x 5 x 5
+
+            nn.Flatten(), #a single vector 256*5*5,
+            nn.Linear(256*5*5, 1024),
+            nn.ReLU(),
+            nn.Linear(1024, 512),
+            nn.ReLU(),
+            nn.Linear(512, 4))
+        
+    def forward(self, xb):
+        return self.network(xb)
  
 def training_network():
     net = Net()
@@ -61,7 +70,7 @@ def training_network():
     criterion = nn.CrossEntropyLoss()
     optimizer = optim.SGD(net.parameters(), lr=0.001, momentum=0.9)
  
-    for epoch in range(4):
+    for epoch in range(10):
         running_loss = 0.0
         for i, data in enumerate(train_loader, 0):
             inputs, labels = data[0].to(device), data[1].to(device)
@@ -72,7 +81,7 @@ def training_network():
             optimizer.step()
  
             running_loss += loss.item()
-            if i % 2000 == 1999:
+            if i % 200 == 199:
                 print('[%d, %5d] loss: %.3f' % (epoch + 1, i + 1, running_loss))
                 running_loss = 0.0
  
@@ -82,8 +91,8 @@ def training_network():
  
 def result_from_network(net, loaded_image):
     image = PIL.Image.open(loaded_image)
-    pil_to_tensor = transforms.ToTensor()(image.convert("RGB")).unsqueeze_(0)
-    outputs = net(pil_to_tensor.to(device))
+    pil_to_tensor = transforms.Compose([Negative(), transforms.ToTensor()])(image.convert("RGB")).unsqueeze_(0)
+    outputs = net(pil_to_tensor)
  
     return classes[torch.max(outputs, 1)[1]]
  
@@ -99,5 +108,4 @@ def load_network_from_structure(network):
  
 if __name__ == "__main__":
     print(torch.cuda.is_available())
-    training_network()
-    
+    training_network()

basic_grid.py

@@ -1,156 +0,0 @@
-# Import the pygame module
-import pygame
-
-# Import pygame.locals for easier access to key coordinates
-from pygame.locals import (
-    K_UP,
-    K_LEFT,
-    K_RIGHT,
-    K_ESCAPE,
-    KEYDOWN,
-    QUIT
-)
-
-# Import other files from project
-import field as F
-import tractor as T
-import plant as P
-import colors as C
-import dimensions as D
-import node as N
-import mapschema as maps
-
-# Initialize pygame
-pygame.init()
-
-# Name the window
-pygame.display.set_caption("Inteligentny Traktor")
-
-# Create the screen object
-# The size is determined by the constant SCREEN_WIDTH and SCREEN_HEIGHT
-screen = pygame.display.set_mode((D.SCREEN_WIDTH, D.SCREEN_HEIGHT))
-
-# Define the map of the field
-mapschema = maps.createField()
-
-# Create field array
-field = []
-
-# Populate the field array
-for row in range(D.GSIZE):
-    field.append([])
-    for column in range(D.GSIZE):
-        fieldbit = F.Field(row, column, mapschema[column][row])
-        field[row].append(fieldbit)
-
-# Create Tractor object
-tractor = T.Tractor(field, [0,0])
-
-# Define the map of plants
-mapschema = maps.createPlants()
-
-# Createt plants array
-plants = []
-
-# Populate the plants array
-for row in range(D.GSIZE):
-    plants.append([])
-    for column in range(D.GSIZE):
-        if mapschema[column][row] != 0:
-            plantbit = P.Plant(field[row][column], mapschema[column][row])
-            plants[row].append(plantbit)
-
-# Create list for tractor instructions
-path = []
-
-# Variable to keep the main loop running
-RUNNING = True
-
-# Variable conroling timed eventes
-TICKER = 0
-
-# Initialize clock
-clock = pygame.time.Clock()
-
-
-# Main loop
-while RUNNING:
-
-    # Look at every event in the queue
-    for event in pygame.event.get():
-        # Did the user hit a key?
-        if event.type == KEYDOWN:
-            # Was it the Escape key? If so, stop the loop.
-            if event.key == K_ESCAPE:
-                RUNNING = False
-        # Did the user click the window close button? If so, stop the loop.
-        elif event.type == QUIT:
-            RUNNING = False
-
-    # Create key Node that will be used to calculate tractor instructions
-    processor = N.Node(field, tractor.position, tractor.direction)
-
-    # If path is empty or nonexistent, create new one
-    if path is None or len(path) == 0:
-        path = processor.findPathToPlant()
-
-    # control tractor by poping instructions from path list
-    if path is not None:
-        if path[0] == "move":
-            tractor.move()
-            path.pop(0)
-        elif path[0] =="left":
-            tractor.rotate_left()
-            path.pop(0)
-        elif path[0] == "right":
-            tractor.rotate_right()
-            path.pop(0)
-        elif path[0] == "hydrate":
-            tractor.hydrate(field)
-            path.pop(0)
-        else:
-            path.pop(0)
-
-    # Get all keys pressed at a time CURRENTLY UNUSED
-    pressed_keys = pygame.key.get_pressed()
-    
-    # control tractor with pressed keys CURRENTLY UNUSED
-    if pressed_keys[K_UP]:
-        tractor.move()
-    elif pressed_keys[K_LEFT]:
-        tractor.rotate_left()
-    elif pressed_keys[K_RIGHT]:
-        tractor.rotate_right()
-
-    # Set the screen background
-    screen.fill(C.DBROWN)
-
-    # Draw the field
-    for row in range(D.GSIZE):
-        for column in range(D.GSIZE):
-            screen.blit(field[row][column].surf, field[row][column].rect)
-
-    # Draw the tactor
-    screen.blit(tractor.surf, tractor.rect)
-
-    # Plants grow with every 10th tick, then they are drawn
-    for row in plants:
-        for plant in row:
-            plant.tick()
-            plant.grow()
-            screen.blit(plant.surf, plant.rect)
-    
-    # Field are drying with every 100th tick
-    if TICKER == 0:
-        for row in range(D.GSIZE):
-            for column in range(D.GSIZE):
-                field[row][column].dehydrate()
-
-    # Increment ticker 
-    TICKER = (TICKER + 1)%100
-
-    # Update the screen
-    pygame.display.flip()
-
-    # Ensure program maintains a stable framerate
-    clock.tick(8)

cases.py

@@ -1,259 +0,0 @@
-class Case:
-    def __init__(self, values, attributes, Class):
-        self.values = values
-        self.attributes = attributes
-        self.Class = Class
-
-attributes = ["field.hydration", "field.fertility", "species", "ticks", "is_healthy", "field.tractor_there"]
-
-cases = [Case([4, 0, "potato", 0, 1, 0], attributes, 0),
-Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([4, 1, "wheat", 0, 0, 1], attributes, 0),
-Case([1, 1, "potato", 1, 0, 1], attributes, 0),
-Case([2, 1, "potato", 0, 0, 1], attributes, 0),
-Case([2, 0, "potato", 0, 1, 0], attributes, 0),
-Case([1, 1, "strawberry", 1, 0, 1], attributes, -1),
-Case([1, 0, "wheat", 1, 1, 1], attributes, 0),
-Case([2, 0, "wheat", 1, 0, 1], attributes, 0),
-Case([1, 1, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 1, "potato", 1, 1, 0], attributes, 1),
-Case([2, 1, "strawberry", 1, 0, 0], attributes, 0),
-Case([4, 0, "wheat", 1, 1, 1], attributes, 0),
-Case([4, 1, "wheat", 1, 0, 1], attributes, 0),
-Case([5, 1, "potato", 1, 1, 1], attributes, 0),
-Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
-Case([1, 1, "sorrel", 1, 0, 0], attributes, 0),
-Case([0, 0, "sorrel", 0, 0, 1], attributes, 0),
-Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([0, 1, "sorrel", 0, 1, 1], attributes, 0),
-Case([0, 1, "strawberry", 1, 1, 0], attributes, -1),
-Case([2, 0, "sorrel", 0, 1, 1], attributes, 0),
-Case([4, 0, "wheat", 1, 0, 1], attributes, 0),
-Case([5, 0, "wheat", 0, 0, 0], attributes, 0),
-Case([0, 0, "strawberry", 1, 0, 0], attributes, -1),
-Case([4, 0, "sorrel", 1, 0, 0], attributes, 0),
-Case([3, 0, "sorrel", 0, 0, 1], attributes, 0),
-Case([3, 1, "potato", 1, 0, 1], attributes, 0),
-Case([4, 1, "potato", 0, 0, 1], attributes, 0),
-Case([1, 1, "wheat", 0, 1, 1], attributes, 0),
-Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
-Case([2, 0, "wheat", 0, 0, 0], attributes, 0),
-Case([5, 1, "potato", 1, 1, 1], attributes, 0),
-Case([4, 1, "strawberry", 0, 0, 1], attributes, 0),
-Case([1, 0, "potato", 1, 1, 0], attributes, 0),
-Case([4, 1, "sorrel", 1, 1, 1], attributes, 0),
-Case([0, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
-Case([4, 0, "sorrel", 1, 0, 0], attributes, 0),
-Case([5, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 1, "wheat", 1, 1, 1], attributes, 0),
-Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([4, 0, "potato", 0, 0, 1], attributes, 0),
-Case([5, 1, "wheat", 1, 1, 1], attributes, 0),
-Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 0, "sorrel", 0, 0, 1], attributes, 0),
-Case([0, 0, "potato", 1, 1, 1], attributes, -1),
-Case([4, 0, "strawberry", 1, 1, 1], attributes, 0),
-Case([2, 1, "strawberry", 1, 0, 1], attributes, 0),
-Case([2, 1, "wheat", 0, 0, 1], attributes, 0),
-Case([2, 1, "sorrel", 1, 1, 0], attributes, 1),
-Case([1, 0, "potato", 1, 0, 1], attributes, 0),
-Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
-Case([4, 1, "potato", 1, 1, 1], attributes, 0),
-Case([0, 0, "strawberry", 1, 0, 1], attributes, -1),
-Case([0, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([1, 1, "wheat", 0, 1, 0], attributes, 0),
-Case([0, 0, "sorrel", 1, 1, 0], attributes, -1),
-Case([2, 0, "sorrel", 0, 0, 1], attributes, 0),
-Case([5, 1, "wheat", 1, 1, 1], attributes, 0),
-Case([2, 0, "strawberry", 0, 1, 0], attributes, 0),
-Case([2, 1, "wheat", 0, 0, 1], attributes, 0),
-Case([3, 0, "potato", 1, 0, 1], attributes, 0),
-Case([5, 0, "wheat", 1, 1, 1], attributes, 0),
-Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
-Case([0, 0, "wheat", 0, 0, 0], attributes, 0),
-Case([5, 0, "potato", 1, 1, 0], attributes, 1),
-Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 1, "sorrel", 0, 1, 0], attributes, 0),
-Case([2, 1, "potato", 1, 1, 1], attributes, 0),
-Case([5, 0, "strawberry", 1, 1, 0], attributes, 1),
-Case([5, 0, "wheat", 0, 0, 0], attributes, 0),
-Case([5, 0, "wheat", 1, 1, 0], attributes, 1),
-Case([2, 0, "potato", 1, 0, 0], attributes, 0),
-Case([3, 1, "wheat", 0, 1, 0], attributes, 0),
-Case([3, 0, "potato", 1, 1, 1], attributes, 0),
-Case([0, 1, "sorrel", 1, 1, 1], attributes, -1),
-Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([2, 1, "strawberry", 0, 1, 0], attributes, 0),
-Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
-Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
-Case([4, 0, "strawberry", 1, 0, 1], attributes, 0),
-Case([3, 1, "potato", 0, 0, 1], attributes, 0),
-Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([5, 1, "wheat", 1, 0, 1], attributes, 0),
-Case([5, 0, "potato", 1, 0, 1], attributes, 0),
-Case([3, 0, "potato", 0, 0, 1], attributes, 0),
-Case([1, 0, "wheat", 0, 1, 0], attributes, 0),
-Case([5, 0, "sorrel", 0, 1, 1], attributes, 0),
-Case([4, 0, "potato", 0, 1, 0], attributes, 0),
-Case([0, 0, "strawberry", 0, 0, 0], attributes, 0),
-Case([5, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([4, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([1, 1, "strawberry", 1, 1, 0], attributes, -1),
-Case([5, 0, "strawberry", 1, 0, 0], attributes, 0),
-Case([5, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
-Case([3, 1, "potato", 1, 0, 1], attributes, 0),
-Case([1, 0, "sorrel", 0, 0, 0], attributes, 0),
-Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
-Case([0, 0, "wheat", 0, 0, 1], attributes, 0),
-Case([1, 0, "potato", 0, 0, 0], attributes, 0),
-Case([1, 1, "sorrel", 0, 1, 0], attributes, 0),
-Case([0, 1, "strawberry", 0, 1, 0], attributes, 0),
-Case([5, 1, "potato", 1, 0, 1], attributes, 0),
-Case([2, 0, "strawberry", 1, 1, 1], attributes, 0),
-Case([4, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
-Case([1, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([4, 0, "wheat", 0, 0, 0], attributes, 0),
-Case([4, 0, "strawberry", 0, 1, 0], attributes, 0),
-Case([0, 0, "sorrel", 1, 0, 1], attributes, -1),
-Case([1, 0, "strawberry", 0, 1, 0], attributes, 0),
-Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([2, 1, "potato", 0, 0, 0], attributes, 0),
-Case([3, 1, "strawberry", 1, 1, 0], attributes, 1),
-Case([1, 0, "sorrel", 1, 1, 1], attributes, 0),
-Case([5, 1, "strawberry", 1, 1, 0], attributes, 1),
-Case([2, 0, "wheat", 1, 1, 1], attributes, 0),
-Case([5, 1, "strawberry", 0, 1, 0], attributes, 0),
-Case([1, 1, "wheat", 0, 1, 1], attributes, 0),
-Case([1, 1, "potato", 0, 1, 0], attributes, 0),
-Case([4, 0, "potato", 1, 1, 0], attributes, 1),
-Case([2, 1, "strawberry", 0, 0, 1], attributes, 0),
-Case([0, 1, "potato", 0, 0, 1], attributes, 0),
-Case([3, 0, "sorrel", 1, 0, 1], attributes, 0),
-Case([4, 0, "wheat", 1, 0, 1], attributes, 0),
-Case([5, 1, "sorrel", 1, 0, 0], attributes, 0),
-Case([1, 0, "sorrel", 1, 0, 0], attributes, 0),
-Case([5, 0, "sorrel", 1, 0, 1], attributes, 0),
-Case([2, 1, "potato", 1, 0, 1], attributes, 0),
-Case([1, 0, "potato", 1, 1, 1], attributes, 0),
-Case([4, 0, "wheat", 1, 1, 0], attributes, 1),
-Case([0, 0, "sorrel", 0, 1, 0], attributes, 0),
-Case([2, 0, "wheat", 0, 0, 1], attributes, 0),
-Case([0, 1, "potato", 1, 0, 1], attributes, -1),
-Case([0, 1, "sorrel", 1, 0, 1], attributes, -1),
-Case([1, 1, "potato", 0, 0, 1], attributes, 0),
-Case([3, 0, "sorrel", 1, 1, 1], attributes, 0),
-Case([0, 0, "potato", 1, 0, 1], attributes, -1),
-Case([4, 0, "potato", 0, 0, 1], attributes, 0),
-Case([0, 0, "strawberry", 1, 0, 0], attributes, -1),
-Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([5, 0, "potato", 0, 1, 1], attributes, 0),
-Case([2, 0, "potato", 0, 0, 0], attributes, 0),
-Case([0, 1, "potato", 1, 0, 0], attributes, -1),
-Case([1, 0, "potato", 0, 0, 1], attributes, 0),
-Case([4, 0, "sorrel", 1, 0, 1], attributes, 0),
-Case([1, 0, "potato", 1, 0, 0], attributes, 0),
-Case([5, 1, "potato", 1, 0, 1], attributes, 0),
-Case([2, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([0, 1, "potato", 1, 1, 1], attributes, -1),
-Case([5, 1, "strawberry", 0, 1, 0], attributes, 0),
-Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 0, "strawberry", 1, 0, 0], attributes, 0),
-Case([0, 1, "strawberry", 0, 0, 1], attributes, 0),
-Case([0, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
-Case([1, 0, "potato", 0, 0, 1], attributes, 0),
-Case([1, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([0, 1, "strawberry", 1, 0, 1], attributes, -1),
-Case([1, 1, "potato", 0, 0, 1], attributes, 0),
-Case([0, 0, "wheat", 0, 0, 1], attributes, 0),
-Case([4, 1, "sorrel", 1, 1, 1], attributes, 0),
-Case([5, 1, "wheat", 0, 0, 1], attributes, 0),
-Case([5, 1, "strawberry", 0, 0, 0], attributes, 0),
-Case([4, 1, "wheat", 0, 0, 1], attributes, 0),
-Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([1, 1, "potato", 1, 1, 0], attributes, 0),
-Case([0, 1, "sorrel", 1, 0, 0], attributes, -1),
-Case([5, 0, "sorrel", 1, 0, 0], attributes, 0),
-Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([0, 0, "potato", 0, 0, 0], attributes, 0),
-Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
-Case([4, 0, "strawberry", 0, 0, 1], attributes, 0),
-Case([2, 0, "potato", 1, 0, 0], attributes, 0),
-Case([4, 0, "strawberry", 0, 0, 0], attributes, 0),
-Case([0, 1, "strawberry", 0, 1, 1], attributes, 0),
-Case([1, 1, "wheat", 1, 1, 0], attributes, 0),
-Case([3, 0, "potato", 0, 1, 0], attributes, 0),
-Case([1, 1, "wheat", 0, 1, 0], attributes, 0),
-Case([1, 1, "sorrel", 0, 0, 1], attributes, 0),
-Case([3, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([3, 1, "wheat", 0, 0, 0], attributes, 0),
-Case([1, 0, "wheat", 0, 1, 1], attributes, 0),
-Case([5, 1, "potato", 1, 0, 1], attributes, 0),
-Case([5, 0, "wheat", 0, 0, 1], attributes, 0),
-Case([2, 1, "sorrel", 0, 1, 0], attributes, 0),
-Case([5, 0, "sorrel", 1, 0, 0], attributes, 0),
-Case([1, 0, "potato", 1, 1, 1], attributes, 0),
-Case([5, 1, "wheat", 1, 1, 0], attributes, 1),
-Case([3, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([5, 0, "wheat", 0, 0, 1], attributes, 0),
-Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([1, 0, "potato", 1, 1, 1], attributes, 0),
-Case([0, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([5, 1, "potato", 1, 1, 0], attributes, 1),
-Case([2, 0, "wheat", 0, 1, 0], attributes, 0),
-Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 0, "potato", 1, 1, 0], attributes, 0),
-Case([1, 1, "potato", 0, 0, 0], attributes, 0),
-Case([2, 1, "potato", 0, 1, 0], attributes, 0),
-Case([2, 1, "wheat", 0, 1, 0], attributes, 0),
-Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([2, 0, "wheat", 1, 1, 1], attributes, 0),
-Case([5, 0, "wheat", 1, 1, 0], attributes, 1),
-Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([0, 1, "potato", 0, 0, 0], attributes, 0),
-Case([5, 1, "strawberry", 1, 1, 1], attributes, 0),
-Case([4, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([5, 1, "sorrel", 0, 0, 1], attributes, 0),
-Case([1, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([5, 0, "strawberry", 1, 0, 1], attributes, 0),
-Case([5, 0, "wheat", 1, 0, 1], attributes, 0),
-Case([2, 0, "potato", 1, 0, 1], attributes, 0),
-Case([3, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
-Case([0, 1, "strawberry", 0, 1, 1], attributes, 0),
-Case([3, 0, "wheat", 0, 1, 0], attributes, 0),
-Case([4, 1, "potato", 1, 1, 1], attributes, 0),
-Case([3, 0, "potato", 0, 0, 1], attributes, 0),
-Case([2, 1, "strawberry", 1, 1, 0], attributes, 0),
-Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
-Case([4, 1, "wheat", 1, 0, 1], attributes, 0),
-Case([2, 0, "potato", 0, 1, 0], attributes, 0),
-Case([5, 0, "sorrel", 0, 1, 1], attributes, 0),
-Case([0, 1, "wheat", 1, 1, 0], attributes, -1),
-Case([5, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([2, 0, "potato", 0, 0, 0], attributes, 0),
-Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
-Case([4, 1, "potato", 0, 1, 1], attributes, 0),
-Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
-Case([1, 1, "strawberry", 1, 0, 1], attributes, -1),
-Case([3, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([5, 1, "wheat", 1, 0, 0], attributes, 0),
-Case([4, 0, "sorrel", 1, 1, 0], attributes, 1),
-Case([2, 1, "sorrel", 1, 0, 0], attributes, 0),
-Case([0, 1, "wheat", 0, 1, 0], attributes, 0),
-Case([5, 0, "potato", 1, 1, 0], attributes, 1),
-Case([3, 1, "strawberry", 0, 1, 0], attributes, 0),
-Case([5, 1, "strawberry", 0, 0, 0], attributes, 0),
-Case([4, 1, "potato", 1, 1, 1], attributes, 0),
-Case([5, 1, "potato", 1, 0, 1], attributes, 0),
-Case([5, 1, "potato", 1, 1, 1], attributes, 0),
-Case([0, 0, "sorrel", 0, 0, 0], attributes, 0),
-Case([1, 1, "sorrel", 1, 1, 0], attributes, 1),
-Case([0, 1, "potato", 0, 1, 0], attributes, 0),
-Case([4, 1, "strawberry", 1, 1, 1], attributes, 0),
-Case([0, 0, "wheat", 0, 1, 1], attributes, 0),
-Case([3, 0, "wheat", 1, 1, 0], attributes, 1)]

field.py

@@ -1,6 +1,6 @@
 import pygame
-from colors import *
-from dimensions import *
+from src.colors import *
+from src.dimensions import *
 
 class Field(pygame.sprite.Sprite):
     def __init__(self, row, column, field_type):
@@ -24,36 +24,62 @@ class Field(pygame.sprite.Sprite):
         self.position = [row, column]
         self.hydration = 0
         self.planted = 0
-        self.fertility = 1
+        self.fertility = 0
         self.tractor_there = False
 
     def hydrate(self):
         if self.field_type == "soil" and self.hydration <= 5:
-            self.hydration += 1
-            if self.hydration == 0:
-                self.surf.fill(BROWN0)
-            if self.hydration == 1:
-                self.surf.fill(BROWN1)
-            if self.hydration == 2:
-                self.surf.fill(BROWN2)
-            if self.hydration == 3:
-                self.surf.fill(BROWN3)
-            if self.hydration == 4 or self.hydration == 5:
-                self.surf.fill(BROWN4)
+                self.hydration += 1
+                if self.fertility == 1:
+                    if self.hydration == 0:
+                        self.surf.fill(REDDISH0)
+                        self.fertility = 0
+                    if self.hydration == 1:
+                        self.surf.fill(REDDISH1)
+                    if self.hydration == 2:
+                        self.surf.fill(REDDISH2)
+                    if self.hydration == 3:
+                        self.surf.fill(REDDISH3)
+                    if self.hydration == 4 or self.hydration == 5:
+                        self.surf.fill(REDDISH4)
+                else:
+                    if self.hydration == 0:
+                        self.surf.fill(BROWN0)
+                    if self.hydration == 1:
+                        self.surf.fill(BROWN1)
+                    if self.hydration == 2:
+                        self.surf.fill(BROWN2)
+                    if self.hydration == 3:
+                        self.surf.fill(BROWN3)
+                    if self.hydration == 4 or self.hydration == 5:
+                        self.surf.fill(BROWN4)
     
     def dehydrate(self):
-        if self.field_type == "soil" and self.hydration > 0:
-            self.hydration -= 1
-            if self.hydration == 0:
-                self.surf.fill(BROWN0)
-            if self.hydration == 1:
-                self.surf.fill(BROWN1)
-            if self.hydration == 2:
-                self.surf.fill(BROWN2)
-            if self.hydration == 3:
-                self.surf.fill(BROWN3)
-            if self.hydration == 4 or self.hydration == 5:
-                self.surf.fill(BROWN4)
+            if self.field_type == "soil" and self.hydration > 0:
+                self.hydration -= 1
+                if self.fertility == 1:
+                    if self.hydration == 0:
+                        self.surf.fill(REDDISH0)
+                        self.fertility = 0
+                    if self.hydration == 1:
+                        self.surf.fill(REDDISH1)
+                    if self.hydration == 2:
+                        self.surf.fill(REDDISH2)
+                    if self.hydration == 3:
+                        self.surf.fill(REDDISH3)
+                    if self.hydration == 4 or self.hydration == 5:
+                        self.surf.fill(REDDISH4)
+                else:
+                    if self.hydration == 0:
+                        self.surf.fill(BROWN0)
+                    if self.hydration == 1:
+                        self.surf.fill(BROWN1)
+                    if self.hydration == 2:
+                        self.surf.fill(BROWN2)
+                    if self.hydration == 3:
+                        self.surf.fill(BROWN3)
+                    if self.hydration == 4 or self.hydration == 5:
+                        self.surf.fill(BROWN4)
     
     def free(self):
         self.planted = 0

grader.py

@@ -1,65 +0,0 @@
-import torch
-import torchvision
-import torchvision.transforms as transforms
-import torch.nn as nn
-import torch.nn.functional as f
-import torch.optim as optim
-import numpy as np
-from matplotlib.pyplot import imshow
-import os
-import PIL
-import numpy as np
-import neural_network
-from matplotlib.pyplot import imshow
-
-# Create the model
-model = neural_network.Net()
-
-# Load state_dict
-neural_network.load_network_from_structure(model)
-
-# Create the preprocessing transformation here
-transform = transforms.Compose([neural_network.Negative(), transforms.ToTensor()])
-
-# load your image(s)
-img = PIL.Image.open('test\\0_100.jpg')
-img2 = PIL.Image.open('test\\1_100.jpg')
-img3 = PIL.Image.open('test\\4_100.jpg')
-img4 = PIL.Image.open('test\\5_100.jpg')
-
-# Transform
-input = transform(img)
-input2 = transform(img2)
-input3 = transform(img3)
-input4 = transform(img4)
-
-# unsqueeze batch dimension, in case you are dealing with a single image
-input = input.unsqueeze(0)
-input2 = input2.unsqueeze(0)
-input3 = input3.unsqueeze(0)
-input4 = input4.unsqueeze(0)
-
-# Set model to eval
-model.eval()
-
-# Get prediction
-output = model(input)
-output2 = model(input2)
-output3 = model(input3)
-output4 = model(input4)
-
-print(output)
-index = output.cpu().data.numpy().argmax()
-print(index)
-
-print(output2)
-index = output2.cpu().data.numpy().argmax()
-print(index)
-
-print(output3)
-index = output3.cpu().data.numpy().argmax()
-print(index)
-
-print(output4)
-index = output4.cpu().data.numpy().argmax()
-print(index)

main.py

@@ -0,0 +1,160 @@
+# Import the pygame module
+import pygame
+# Import pygame.locals for easier access to key coordinates
+from pygame.locals import (
+    K_UP,
+    K_LEFT,
+    K_RIGHT,
+    K_ESCAPE,
+    KEYDOWN,
+    QUIT
+)
+
+
+# Import other files from project
+import field as F
+import node as N
+import plant as P
+import src.colors as C
+import src.dimensions as D
+import AI.GeneticAlgorithm as ga
+import AI.neural_network as nn
+import tractor as T
+from src import mapschema as maps
+
+if __name__ == "__main__":
+    # Initialize pygame
+    pygame.init()
+
+    # Name the window
+    pygame.display.set_caption("Inteligentny Traktor")
+
+    # Create the screen object
+    # The size is determined by the constant SCREEN_WIDTH and SCREEN_HEIGHT
+    screen = pygame.display.set_mode((D.SCREEN_WIDTH, D.SCREEN_HEIGHT))
+
+    # Define the map of the field
+    mapschema = maps.createField()
+
+    # Create field array
+    field = []
+
+    # Populate the field array
+    for row in range(D.GSIZE):
+        field.append([])
+        for column in range(D.GSIZE):
+            fieldbit = F.Field(row, column, mapschema[column][row])
+            field[row].append(fieldbit)
+
+    # genetic_algorithm_setup(field)
+    num_of_plants = 0
+    plant_pops = []
+    best_plant_pop = []
+
+    goal_gen = 100
+    best_plant_pop, plant_pops, num_of_plants, fitness = ga.genetic_algorithm_setup(field, plant_pops, goal_gen)
+
+    net = nn.Net()
+    nn.load_network_from_structure(net)
+    net.eval()
+
+    # Create Tractor object
+    tractor = T.Tractor(field, [0, 0])
+
+    # Define the map of plants
+    mapschema = maps.createPlants()
+
+    # Create plants array
+    plants = []
+
+    # Populate the plants array
+    for row in range(D.GSIZE):
+        plants.append([])
+        for column in range(D.GSIZE):
+            if best_plant_pop[column][row] != "":
+                plantbit = P.Plant(field[row][column], best_plant_pop[column][row])
+                plants[row].append(plantbit)
+            else:
+                plants[row].append(0)
+
+    # Create list for tractor instructions
+    path = []
+
+    # Variable to keep the main loop running
+    RUNNING = True
+
+    # Variable conroling timed eventes
+    TICKER = 0
+
+    # Initialize clock
+    clock = pygame.time.Clock()
+
+    # Main loop
+    while RUNNING:
+
+        for event in pygame.event.get():
+            # Did the user hit a key?
+            if event.type == KEYDOWN:
+                # Was it the Escape key? If so, stop the loop.
+                if event.key == K_ESCAPE:
+                    RUNNING = False
+            # Did the user click the window close button? If so, stop the loop.
+            elif event.type == QUIT:
+                RUNNING = False
+
+        # Create key Node that will be used to calculate tractor instructions
+        processor = N.Node(field, tractor.position, tractor.direction)
+
+        # If path is empty or nonexistent, create new one
+        if path is None or len(path) == 0:
+            path = processor.findPathToPlant()
+
+        # control tractor by poping instructions from path list
+        if path is not None:
+            if path[0] == "move":
+                tractor.move()
+            elif path[0] == "left":
+                tractor.rotate_left()
+            elif path[0] == "right":
+                tractor.rotate_right()
+            elif path[0] == "hydrate":
+                tractor.hydrate(field)
+            elif path[0] == "fertilize":
+                if plants[tractor.position[1]][tractor.position[0]]:
+                    tractor.fertilize(field, plants, nn.result_from_network(net, plants[tractor.position[0]][tractor.position[1]].testimage))
+            path.pop(0)
+
+
+        # Set the screen background
+        screen.fill(C.DBROWN)
+
+        # Draw the field
+        for row in range(D.GSIZE):
+            for column in range(D.GSIZE):
+                screen.blit(field[row][column].surf, field[row][column].rect)
+
+        # Draw the tactor
+        screen.blit(tractor.surf, tractor.rect)
+
+        # Plants grow with every 10th tick, then they are drawn
+        for row in plants:
+            for plant in row:
+                if plant != 0:
+                    plant.tick()
+                    plant.grow()
+                    screen.blit(plant.surf, plant.rect)
+
+        # Field are drying with every 100th tick
+        if TICKER == 0:
+            for row in range(D.GSIZE):
+                for column in range(D.GSIZE):
+                    field[row][column].dehydrate()
+
+        # Increment ticker
+        TICKER = (TICKER + 1) % 100
+
+        # Update the screen
+        pygame.display.flip()
+
+        # Ensure program maintains a stable framerate
+        clock.tick(35)

mapschema.py

@@ -1,27 +0,0 @@
-def createField():
-    field = [["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "soil", "soil"],
-    ["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "soil", "soil"],
-    ["soil", "soil", "soil", "soil", "soil", "road", "road", "road", "road", "road"],
-    ["rocks", "rocks", "rocks", "rocks", "soil", "road", "soil", "soil", "rocks", "soil"],
-    ["soil", "soil", "soil", "soil", "soil", "road", "rocks", "rocks", "soil", "soil"],
-    ["soil", "soil", "soil", "pond", "rocks", "road", "rocks", "soil", "soil", "rocks"],
-    ["rocks", "pond", "pond", "pond", "pond", "road", "rocks", "soil", "soil", "rocks"],
-    ["road", "road", "road", "road", "road", "road", "rocks", "soil", "soil", "soil"],
-    ["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "rocks", "rocks"],
-    ["soil", "soil", "soil", "soil", "soil", "rocks", "soil", "rocks", "rocks", "soil"]
-    ]
-    return field
-
-def createPlants():
-    field = [["wheat", "wheat", "wheat", "wheat", "wheat", "wheat", 0, "strawberry", "strawberry", "strawberry"],
-    ["wheat", "wheat", "wheat", "wheat", "wheat", "wheat", 0, "strawberry", "strawberry", "strawberry"],
-    ["wheat", "wheat", "wheat", "wheat", 0, 0, 0, 0, 0, 0],
-    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
-    ["wheat", "wheat", "wheat", "wheat", 0, 0, 0, 0, 0, 0],
-    ["wheat", "wheat", "wheat", 0, 0, 0, 0, "potato", "potato", 0],
-    [0, 0, 0, 0, 0, 0, 0, "potato", "potato", 0],
-    [0, 0, 0, 0, 0, 0, 0, "potato", "potato", "potato"],
-    ["strawberry", "strawberry", "strawberry", "strawberry", "strawberry", 0, 0, "potato", 0, 0],
-    ["strawberry", "strawberry", "strawberry", "strawberry", "strawberry", 0, 0, 0, 0, 0]
-    ]
-    return field

node.py

@@ -1,10 +1,12 @@
-from dimensions import *
 import heapq
 
+from src.dimensions import *
+
 
 def getTotalCost(x):
     return x.totalCost
 
+
 def showPath(node, goal):
     path = node.findPath(goal)
     for x in path:
@@ -12,36 +14,38 @@ def showPath(node, goal):
         print(x.rotation, end=" ")
         print(x.action)
     print("***")
-    
 
-def succesor (node):
+
+def succesor(node):
     succesors = []
-    if node.position[0]+node.rotation[0] in range(0,GSIZE) and node.position[1]+node.rotation[1] in range(0,GSIZE):
-        child = Node(node.field, [node.position[0]+node.rotation[0], node.position[1]+node.rotation[1]], node.rotation)
+    if node.position[0] + node.rotation[0] in range(0, GSIZE) and node.position[1] + node.rotation[1] in range(0,
+                                                                                                               GSIZE):
+        child = Node(node.field, [node.position[0] + node.rotation[0], node.position[1] + node.rotation[1]],
+                     node.rotation)
         child.action = "move"
         succesors.append(child)
-    if node.rotation == [1,0]:
-        child = Node(node.field, node.position, [0,-1])
+    if node.rotation == [1, 0]:
+        child = Node(node.field, node.position, [0, -1])
         child.action = "left"
         succesors.append(child)
-        child = Node(node.field, node.position, [0,1])
+        child = Node(node.field, node.position, [0, 1])
         child.action = "right"
         succesors.append(child)
-    if node.rotation == [0,1]:
+    if node.rotation == [0, 1]:
         child = Node(node.field, node.position, [-1, 0])
         succesors.append(child)
         child.action = "right"
         child = Node(node.field, node.position, [1, 0])
         child.action = "left"
         succesors.append(child)
-    if node.rotation == [-1,0]:
-        child = Node(node.field, node.position, [0,-1])
+    if node.rotation == [-1, 0]:
+        child = Node(node.field, node.position, [0, -1])
         succesors.append(child)
         child.action = "right"
-        child = Node(node.field, node.position, [0,1])
+        child = Node(node.field, node.position, [0, 1])
         child.action = "left"
         succesors.append(child)
-    if node.rotation == [0,-1]:
+    if node.rotation == [0, -1]:
         child = Node(node.field, node.position, [-1, 0])
         child.action = "left"
         succesors.append(child)
@@ -50,7 +54,8 @@ def succesor (node):
         succesors.append(child)
     return succesors
 
-class Node():
+
+class Node:
     def __init__(self, field, position, rotation):
         self.parent = 0
         self.startCost = 0
@@ -88,7 +93,7 @@ class Node():
                     path.append(current)
                     current = current.parent
                 return path[::-1]
-            
+
             children = succesor(currentNode)
 
             perm = 0
@@ -102,8 +107,8 @@ class Node():
                     continue
                 child.parent = currentNode
                 child.startCost = currentNode.startCost + child.field[child.position[0]][child.position[1]].moveCost
-                child.heuristic = abs(goal[0]-child.position[0]) + abs(goal[1]-child.position[1])
-                child.totalCost = child.startCost+child.heuristic
+                child.heuristic = abs(goal[0] - child.position[0]) + abs(goal[1] - child.position[1])
+                child.totalCost = child.startCost + child.heuristic
 
                 for openNode in openList:
                     if child.position == openNode.position and child.rotation == openNode.rotation and child.action == openNode.action and child.startCost > openNode.startCost:
@@ -131,16 +136,19 @@ class Node():
 
             closedList.append(currentNode)
 
-            if currentNode.field[currentNode.position[0]][currentNode.position[1]].planted and currentNode.field[currentNode.position[0]][currentNode.position[1]].hydration < 2:
+            if currentNode.field[currentNode.position[0]][currentNode.position[1]].planted and \
+                currentNode.field[currentNode.position[0]][currentNode.position[1]].field_type == "soil" and \
+                    currentNode.field[currentNode.position[0]][currentNode.position[1]].hydration < 2:
                 path = []
                 for _ in range(currentNode.field[currentNode.position[0]][currentNode.position[1]].hydration, 4):
                     path.append("hydrate")
+                path.append("fertilize")
                 current = currentNode
                 while current is not None:
                     path.append(current.action)
                     current = current.parent
                 return path[::-1]
-            
+
             children = succesor(currentNode)
 
             perm = 0
@@ -154,8 +162,9 @@ class Node():
                     continue
                 child.parent = currentNode
                 child.startCost = currentNode.startCost + child.field[child.position[0]][child.position[1]].moveCost
-                child.heuristic = abs(startNode.position[0]-child.position[0]) + abs(startNode.position[1]-child.position[1])
-                child.totalCost = child.startCost+child.heuristic
+                child.heuristic = abs(startNode.position[0] - child.position[0]) + abs(
+                    startNode.position[1] - child.position[1])
+                child.totalCost = child.startCost + child.heuristic
 
                 for openNode in openList:
                     if child.position == openNode.position and child.rotation == openNode.rotation and child.action == openNode.action and child.startCost >= openNode.startCost:
@@ -166,4 +175,58 @@ class Node():
                     perm = 0
                     continue
 
-                heapq.heappush(openList, child)      
+                heapq.heappush(openList, child)
+
+    def findPathToPlantSpot(self, goals):
+        startNode = Node(self.field, self.position, self.rotation)
+
+        openList = []
+        closedList = []
+
+        startNode.parent = None
+
+        heapq.heappush(openList, startNode)
+
+        while len(openList) > 0:
+            currentNode = heapq.heappop(openList)
+
+            closedList.append(currentNode)
+
+            if not currentNode.field[currentNode.position[0]][currentNode.position[1]].planted and \
+                    goals[currentNode.position[0]][currentNode.position[1]] != "":
+                path = []
+                path.append("plant")
+                current = currentNode
+                while current is not None:
+                    path.append(current.action)
+                    current = current.parent
+                return path[::-1]
+
+            children = succesor(currentNode)
+
+            perm = 0
+            for child in children:
+                for closedChild in closedList:
+                    if child.position == closedChild.position and child.rotation == closedChild.rotation and child.action == closedChild.action:
+                        perm = 1
+                        break
+                if perm == 1:
+                    perm = 0
+                    continue
+                child.parent = currentNode
+                child.startCost = currentNode.startCost + child.field[child.position[0]][child.position[1]].moveCost
+                child.heuristic = abs(startNode.position[0] - child.position[0]) + abs(
+                    startNode.position[1] - child.position[1])
+                child.totalCost = child.startCost + child.heuristic
+
+                for openNode in openList:
+                    if child.position == openNode.position and child.rotation == openNode.rotation and child.action == openNode.action and child.startCost >= openNode.startCost:
+                        perm = 1
+                        break
+
+                if perm == 1:
+                    perm = 0
+                    continue
+
+                heapq.heappush(openList, child)
+        

plant.py

@@ -1,29 +1,32 @@
-import pygame
-from colors import *
-from dimensions import *
-from sprites import *
+import os
+import random
+
+from AI.decision_tree import *
+from src.dimensions import *
+from src.sprites import *
+from src.colors import *
+
+path = os.path.dirname(__file__) + "\\src\\test\\"
 
 class Plant(pygame.sprite.Sprite):
     def __init__(self, field, species):
-        super(Plant, self).__init__()
         self.species = species
-        if self.species == "wheat":
-            self.growth_speed = 1.5
-            self.humidity_needed = 2
+        if self.species == "tomato":
             self.img0 = wheat_img_0
             self.img1 = wheat_img_1
             self.img2 = wheat_img_2
             self.img3 = wheat_img_3
         elif self.species == "potato":
-            self.growth_speed = 1
-            self.humidity_needed = 1
             self.img0 = potato_img_0
             self.img1 = potato_img_1
             self.img2 = potato_img_2
             self.img3 = potato_img_3
         elif self.species == "strawberry":
-            self.growth_speed = 0.8
-            self.humidity_needed = 1
+            self.img0 = strawberry_img_0
+            self.img1 = strawberry_img_1
+            self.img2 = strawberry_img_2
+            self.img3 = strawberry_img_3
+        elif self.species == "pepper":
             self.img0 = strawberry_img_0
             self.img1 = strawberry_img_1
             self.img2 = strawberry_img_2
@@ -38,6 +41,8 @@ class Plant(pygame.sprite.Sprite):
         field.planted = True
         self.tickscount = 0
         self.ticks = 0
+        self.path = path + self.species + "\\"
+        self.testimage = self.path + random.choice(os.listdir(self.path))
 
     def dtree(self):
         if self.field.hydration == 4:
@@ -52,7 +57,7 @@ class Plant(pygame.sprite.Sprite):
             elif self.is_healthy == 0:
                 return 0
         elif self.field.hydration == 2:
-            if self.species == "sorrel":
+            if self.species == "pepper":
                 if self.ticks == 1:
                     if self.is_healthy == 1:
                         return 1
@@ -62,7 +67,7 @@ class Plant(pygame.sprite.Sprite):
                     return 0
             elif self.species == "potato":
                 return 0
-            elif self.species == "wheat":
+            elif self.species == "tomato":
                 return 0
             elif self.species == "strawberry":
                 return 0
@@ -74,9 +79,9 @@ class Plant(pygame.sprite.Sprite):
                     return -1
                 elif self.ticks == 0:
                     return 0
-            elif self.species == "wheat":
+            elif self.species == "tomato":
                 return 0
-            elif self.species == "sorrel":
+            elif self.species == "pepper":
                 if self.is_healthy == 0:
                     return 0
                 elif self.is_healthy == 1:
@@ -98,9 +103,9 @@ class Plant(pygame.sprite.Sprite):
                                 return 0
                         elif self.species == "strawberry":
                             return 1
-                        elif self.species == "sorrel":
+                        elif self.species == "pepper":
                             return 1
-                        elif self.species == "wheat":
+                        elif self.species == "tomato":
                             return 1
                     elif self.is_healthy == 0:
                         return 0
@@ -146,6 +151,7 @@ class Plant(pygame.sprite.Sprite):
             self.growth = 4
         if self.growth < 0:
             self.growth = 0
+
         self.update()
 
     def tick(self):
@@ -153,3 +159,6 @@ class Plant(pygame.sprite.Sprite):
         if self.tickscount >= 25:
             self.tickscount = 0
             self.ticks = 1
+
+    def remove(self):
+        self.field.planted = False

src/cases.py

@@ -0,0 +1,260 @@
+class Case:
+    def __init__(self, values, attributes, Class):
+        self.values = values
+        self.attributes = attributes
+        self.Class = Class
+
+
+attributes = ["field.hydration", "field.fertility", "species", "ticks", "is_healthy", "field.tractor_there"]
+
+cases = [Case([4, 0, "potato", 0, 1, 0], attributes, 0),
+         Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([4, 1, "wheat", 0, 0, 1], attributes, 0),
+         Case([1, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([2, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([2, 0, "potato", 0, 1, 0], attributes, 0),
+         Case([1, 1, "strawberry", 1, 0, 1], attributes, -1),
+         Case([1, 0, "wheat", 1, 1, 1], attributes, 0),
+         Case([2, 0, "wheat", 1, 0, 1], attributes, 0),
+         Case([1, 1, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 1, "potato", 1, 1, 0], attributes, 1),
+         Case([2, 1, "strawberry", 1, 0, 0], attributes, 0),
+         Case([4, 0, "wheat", 1, 1, 1], attributes, 0),
+         Case([4, 1, "wheat", 1, 0, 1], attributes, 0),
+         Case([5, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
+         Case([1, 1, "sorrel", 1, 0, 0], attributes, 0),
+         Case([0, 0, "sorrel", 0, 0, 1], attributes, 0),
+         Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([0, 1, "sorrel", 0, 1, 1], attributes, 0),
+         Case([0, 1, "strawberry", 1, 1, 0], attributes, -1),
+         Case([2, 0, "sorrel", 0, 1, 1], attributes, 0),
+         Case([4, 0, "wheat", 1, 0, 1], attributes, 0),
+         Case([5, 0, "wheat", 0, 0, 0], attributes, 0),
+         Case([0, 0, "strawberry", 1, 0, 0], attributes, -1),
+         Case([4, 0, "sorrel", 1, 0, 0], attributes, 0),
+         Case([3, 0, "sorrel", 0, 0, 1], attributes, 0),
+         Case([3, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([4, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([1, 1, "wheat", 0, 1, 1], attributes, 0),
+         Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
+         Case([2, 0, "wheat", 0, 0, 0], attributes, 0),
+         Case([5, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([4, 1, "strawberry", 0, 0, 1], attributes, 0),
+         Case([1, 0, "potato", 1, 1, 0], attributes, 0),
+         Case([4, 1, "sorrel", 1, 1, 1], attributes, 0),
+         Case([0, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
+         Case([4, 0, "sorrel", 1, 0, 0], attributes, 0),
+         Case([5, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 1, "wheat", 1, 1, 1], attributes, 0),
+         Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([4, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([5, 1, "wheat", 1, 1, 1], attributes, 0),
+         Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 0, "sorrel", 0, 0, 1], attributes, 0),
+         Case([0, 0, "potato", 1, 1, 1], attributes, -1),
+         Case([4, 0, "strawberry", 1, 1, 1], attributes, 0),
+         Case([2, 1, "strawberry", 1, 0, 1], attributes, 0),
+         Case([2, 1, "wheat", 0, 0, 1], attributes, 0),
+         Case([2, 1, "sorrel", 1, 1, 0], attributes, 1),
+         Case([1, 0, "potato", 1, 0, 1], attributes, 0),
+         Case([4, 0, "strawberry", 1, 0, 0], attributes, 0),
+         Case([4, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([0, 0, "strawberry", 1, 0, 1], attributes, -1),
+         Case([0, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([1, 1, "wheat", 0, 1, 0], attributes, 0),
+         Case([0, 0, "sorrel", 1, 1, 0], attributes, -1),
+         Case([2, 0, "sorrel", 0, 0, 1], attributes, 0),
+         Case([5, 1, "wheat", 1, 1, 1], attributes, 0),
+         Case([2, 0, "strawberry", 0, 1, 0], attributes, 0),
+         Case([2, 1, "wheat", 0, 0, 1], attributes, 0),
+         Case([3, 0, "potato", 1, 0, 1], attributes, 0),
+         Case([5, 0, "wheat", 1, 1, 1], attributes, 0),
+         Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
+         Case([0, 0, "wheat", 0, 0, 0], attributes, 0),
+         Case([5, 0, "potato", 1, 1, 0], attributes, 1),
+         Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 1, "sorrel", 0, 1, 0], attributes, 0),
+         Case([2, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([5, 0, "strawberry", 1, 1, 0], attributes, 1),
+         Case([5, 0, "wheat", 0, 0, 0], attributes, 0),
+         Case([5, 0, "wheat", 1, 1, 0], attributes, 1),
+         Case([2, 0, "potato", 1, 0, 0], attributes, 0),
+         Case([3, 1, "wheat", 0, 1, 0], attributes, 0),
+         Case([3, 0, "potato", 1, 1, 1], attributes, 0),
+         Case([0, 1, "sorrel", 1, 1, 1], attributes, -1),
+         Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([2, 1, "strawberry", 0, 1, 0], attributes, 0),
+         Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
+         Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
+         Case([4, 0, "strawberry", 1, 0, 1], attributes, 0),
+         Case([3, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([5, 1, "wheat", 1, 0, 1], attributes, 0),
+         Case([5, 0, "potato", 1, 0, 1], attributes, 0),
+         Case([3, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([1, 0, "wheat", 0, 1, 0], attributes, 0),
+         Case([5, 0, "sorrel", 0, 1, 1], attributes, 0),
+         Case([4, 0, "potato", 0, 1, 0], attributes, 0),
+         Case([0, 0, "strawberry", 0, 0, 0], attributes, 0),
+         Case([5, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([4, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([1, 1, "strawberry", 1, 1, 0], attributes, -1),
+         Case([5, 0, "strawberry", 1, 0, 0], attributes, 0),
+         Case([5, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
+         Case([3, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([1, 0, "sorrel", 0, 0, 0], attributes, 0),
+         Case([3, 0, "wheat", 0, 1, 1], attributes, 0),
+         Case([0, 0, "wheat", 0, 0, 1], attributes, 0),
+         Case([1, 0, "potato", 0, 0, 0], attributes, 0),
+         Case([1, 1, "sorrel", 0, 1, 0], attributes, 0),
+         Case([0, 1, "strawberry", 0, 1, 0], attributes, 0),
+         Case([5, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([2, 0, "strawberry", 1, 1, 1], attributes, 0),
+         Case([4, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
+         Case([1, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([4, 0, "wheat", 0, 0, 0], attributes, 0),
+         Case([4, 0, "strawberry", 0, 1, 0], attributes, 0),
+         Case([0, 0, "sorrel", 1, 0, 1], attributes, -1),
+         Case([1, 0, "strawberry", 0, 1, 0], attributes, 0),
+         Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([2, 1, "potato", 0, 0, 0], attributes, 0),
+         Case([3, 1, "strawberry", 1, 1, 0], attributes, 1),
+         Case([1, 0, "sorrel", 1, 1, 1], attributes, 0),
+         Case([5, 1, "strawberry", 1, 1, 0], attributes, 1),
+         Case([2, 0, "wheat", 1, 1, 1], attributes, 0),
+         Case([5, 1, "strawberry", 0, 1, 0], attributes, 0),
+         Case([1, 1, "wheat", 0, 1, 1], attributes, 0),
+         Case([1, 1, "potato", 0, 1, 0], attributes, 0),
+         Case([4, 0, "potato", 1, 1, 0], attributes, 1),
+         Case([2, 1, "strawberry", 0, 0, 1], attributes, 0),
+         Case([0, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([3, 0, "sorrel", 1, 0, 1], attributes, 0),
+         Case([4, 0, "wheat", 1, 0, 1], attributes, 0),
+         Case([5, 1, "sorrel", 1, 0, 0], attributes, 0),
+         Case([1, 0, "sorrel", 1, 0, 0], attributes, 0),
+         Case([5, 0, "sorrel", 1, 0, 1], attributes, 0),
+         Case([2, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([1, 0, "potato", 1, 1, 1], attributes, 0),
+         Case([4, 0, "wheat", 1, 1, 0], attributes, 1),
+         Case([0, 0, "sorrel", 0, 1, 0], attributes, 0),
+         Case([2, 0, "wheat", 0, 0, 1], attributes, 0),
+         Case([0, 1, "potato", 1, 0, 1], attributes, -1),
+         Case([0, 1, "sorrel", 1, 0, 1], attributes, -1),
+         Case([1, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([3, 0, "sorrel", 1, 1, 1], attributes, 0),
+         Case([0, 0, "potato", 1, 0, 1], attributes, -1),
+         Case([4, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([0, 0, "strawberry", 1, 0, 0], attributes, -1),
+         Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([5, 0, "potato", 0, 1, 1], attributes, 0),
+         Case([2, 0, "potato", 0, 0, 0], attributes, 0),
+         Case([0, 1, "potato", 1, 0, 0], attributes, -1),
+         Case([1, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([4, 0, "sorrel", 1, 0, 1], attributes, 0),
+         Case([1, 0, "potato", 1, 0, 0], attributes, 0),
+         Case([5, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([2, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([0, 1, "potato", 1, 1, 1], attributes, -1),
+         Case([5, 1, "strawberry", 0, 1, 0], attributes, 0),
+         Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 0, "strawberry", 1, 0, 0], attributes, 0),
+         Case([0, 1, "strawberry", 0, 0, 1], attributes, 0),
+         Case([0, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
+         Case([1, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([1, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([0, 1, "strawberry", 1, 0, 1], attributes, -1),
+         Case([1, 1, "potato", 0, 0, 1], attributes, 0),
+         Case([0, 0, "wheat", 0, 0, 1], attributes, 0),
+         Case([4, 1, "sorrel", 1, 1, 1], attributes, 0),
+         Case([5, 1, "wheat", 0, 0, 1], attributes, 0),
+         Case([5, 1, "strawberry", 0, 0, 0], attributes, 0),
+         Case([4, 1, "wheat", 0, 0, 1], attributes, 0),
+         Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([1, 1, "potato", 1, 1, 0], attributes, 0),
+         Case([0, 1, "sorrel", 1, 0, 0], attributes, -1),
+         Case([5, 0, "sorrel", 1, 0, 0], attributes, 0),
+         Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([0, 0, "potato", 0, 0, 0], attributes, 0),
+         Case([0, 0, "strawberry", 1, 1, 1], attributes, -1),
+         Case([4, 0, "strawberry", 0, 0, 1], attributes, 0),
+         Case([2, 0, "potato", 1, 0, 0], attributes, 0),
+         Case([4, 0, "strawberry", 0, 0, 0], attributes, 0),
+         Case([0, 1, "strawberry", 0, 1, 1], attributes, 0),
+         Case([1, 1, "wheat", 1, 1, 0], attributes, 0),
+         Case([3, 0, "potato", 0, 1, 0], attributes, 0),
+         Case([1, 1, "wheat", 0, 1, 0], attributes, 0),
+         Case([1, 1, "sorrel", 0, 0, 1], attributes, 0),
+         Case([3, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([3, 1, "wheat", 0, 0, 0], attributes, 0),
+         Case([1, 0, "wheat", 0, 1, 1], attributes, 0),
+         Case([5, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([5, 0, "wheat", 0, 0, 1], attributes, 0),
+         Case([2, 1, "sorrel", 0, 1, 0], attributes, 0),
+         Case([5, 0, "sorrel", 1, 0, 0], attributes, 0),
+         Case([1, 0, "potato", 1, 1, 1], attributes, 0),
+         Case([5, 1, "wheat", 1, 1, 0], attributes, 1),
+         Case([3, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([5, 0, "wheat", 0, 0, 1], attributes, 0),
+         Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([1, 0, "potato", 1, 1, 1], attributes, 0),
+         Case([0, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([5, 1, "potato", 1, 1, 0], attributes, 1),
+         Case([2, 0, "wheat", 0, 1, 0], attributes, 0),
+         Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 0, "potato", 1, 1, 0], attributes, 0),
+         Case([1, 1, "potato", 0, 0, 0], attributes, 0),
+         Case([2, 1, "potato", 0, 1, 0], attributes, 0),
+         Case([2, 1, "wheat", 0, 1, 0], attributes, 0),
+         Case([2, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([3, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([2, 0, "wheat", 1, 1, 1], attributes, 0),
+         Case([5, 0, "wheat", 1, 1, 0], attributes, 1),
+         Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([0, 1, "potato", 0, 0, 0], attributes, 0),
+         Case([5, 1, "strawberry", 1, 1, 1], attributes, 0),
+         Case([4, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([5, 1, "sorrel", 0, 0, 1], attributes, 0),
+         Case([1, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([5, 0, "strawberry", 1, 0, 1], attributes, 0),
+         Case([5, 0, "wheat", 1, 0, 1], attributes, 0),
+         Case([2, 0, "potato", 1, 0, 1], attributes, 0),
+         Case([3, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([0, 1, "strawberry", 1, 0, 0], attributes, -1),
+         Case([0, 1, "strawberry", 0, 1, 1], attributes, 0),
+         Case([3, 0, "wheat", 0, 1, 0], attributes, 0),
+         Case([4, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([3, 0, "potato", 0, 0, 1], attributes, 0),
+         Case([2, 1, "strawberry", 1, 1, 0], attributes, 0),
+         Case([1, 1, "sorrel", 0, 0, 0], attributes, 0),
+         Case([4, 1, "wheat", 1, 0, 1], attributes, 0),
+         Case([2, 0, "potato", 0, 1, 0], attributes, 0),
+         Case([5, 0, "sorrel", 0, 1, 1], attributes, 0),
+         Case([0, 1, "wheat", 1, 1, 0], attributes, -1),
+         Case([5, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([2, 0, "potato", 0, 0, 0], attributes, 0),
+         Case([2, 0, "strawberry", 0, 1, 1], attributes, 0),
+         Case([4, 1, "potato", 0, 1, 1], attributes, 0),
+         Case([0, 1, "sorrel", 1, 1, 0], attributes, -1),
+         Case([1, 1, "strawberry", 1, 0, 1], attributes, -1),
+         Case([3, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([5, 1, "wheat", 1, 0, 0], attributes, 0),
+         Case([4, 0, "sorrel", 1, 1, 0], attributes, 1),
+         Case([2, 1, "sorrel", 1, 0, 0], attributes, 0),
+         Case([0, 1, "wheat", 0, 1, 0], attributes, 0),
+         Case([5, 0, "potato", 1, 1, 0], attributes, 1),
+         Case([3, 1, "strawberry", 0, 1, 0], attributes, 0),
+         Case([5, 1, "strawberry", 0, 0, 0], attributes, 0),
+         Case([4, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([5, 1, "potato", 1, 0, 1], attributes, 0),
+         Case([5, 1, "potato", 1, 1, 1], attributes, 0),
+         Case([0, 0, "sorrel", 0, 0, 0], attributes, 0),
+         Case([1, 1, "sorrel", 1, 1, 0], attributes, 1),
+         Case([0, 1, "potato", 0, 1, 0], attributes, 0),
+         Case([4, 1, "strawberry", 1, 1, 1], attributes, 0),
+         Case([0, 0, "wheat", 0, 1, 1], attributes, 0),
+         Case([3, 0, "wheat", 1, 1, 0], attributes, 1)]

src/colors.py

@@ -6,6 +6,15 @@ BROWN1 = (160, 130, 70)
 BROWN2 = (140, 110, 55)
 BROWN3 = (110, 85, 40)
 BROWN4 = (80, 60, 20)
+BROWN5 = (80, 60, 20)
+
+REDDISH0 = (230, 150, 90)
+REDDISH1 = (210, 130, 70)
+REDDISH2 = (190, 110, 55)
+REDDISH3 = (160, 85, 40)
+REDDISH4 = (130, 60, 20)
+REDDISH5 = (130, 60, 20)
+
 DBROWN = (65, 50, 20)
 LBROWN = (108, 97, 62)
 BLUE = (18, 93, 156)

src/dimensions.py

@@ -1,13 +1,13 @@
-# Grid size
-GSIZE = 10
-
-# This sets the WIDTH and HEIGHT of each grid location
-WIDTH = 35
-HEIGHT = 35
-
-# This sets the margin between each cell
-MARGIN = 5
-
-# Window size
-SCREEN_WIDTH = GSIZE * (WIDTH + MARGIN) + MARGIN
-SCREEN_HEIGHT = GSIZE * (HEIGHT + MARGIN) + MARGIN
+# Grid size
+GSIZE = 10
+
+# This sets the WIDTH and HEIGHT of each grid location
+WIDTH = 80
+HEIGHT = 80
+
+# This sets the margin between each cell
+MARGIN = 5
+
+# Window size
+SCREEN_WIDTH = GSIZE * (WIDTH + MARGIN) + MARGIN
+SCREEN_HEIGHT = GSIZE * (HEIGHT + MARGIN) + MARGIN + 100

src/mapschema.py

@@ -0,0 +1,28 @@
+def createField():
+    field = [["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "soil", "soil"],
+             ["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "soil", "soil"],
+             ["soil", "soil", "soil", "soil", "soil", "road", "road", "road", "road", "road"],
+             ["rocks", "rocks", "rocks", "rocks", "soil", "road", "soil", "soil", "rocks", "soil"],
+             ["soil", "soil", "soil", "soil", "soil", "road", "rocks", "rocks", "soil", "soil"],
+             ["soil", "soil", "soil", "pond", "rocks", "road", "rocks", "soil", "soil", "rocks"],
+             ["rocks", "pond", "pond", "pond", "pond", "road", "rocks", "soil", "soil", "rocks"],
+             ["road", "road", "road", "road", "road", "road", "rocks", "soil", "soil", "soil"],
+             ["soil", "soil", "soil", "soil", "soil", "soil", "rocks", "soil", "rocks", "rocks"],
+             ["soil", "soil", "soil", "soil", "soil", "rocks", "soil", "rocks", "rocks", "soil"]
+             ]
+    return field
+
+
+def createPlants():
+    field = [["wheat", "wheat", "wheat", "wheat", "wheat", "wheat", 0, "strawberry", "strawberry", "strawberry"],
+             ["wheat", "wheat", "wheat", "wheat", "wheat", "wheat", 0, "strawberry", "strawberry", "strawberry"],
+             ["wheat", "wheat", "wheat", "wheat", 0, 0, 0, 0, 0, 0],
+             [0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
+             ["wheat", "wheat", "wheat", "wheat", 0, 0, 0, 0, 0, 0],
+             ["wheat", "wheat", "wheat", 0, 0, 0, 0, "potato", "potato", 0],
+             [0, 0, 0, 0, 0, 0, 0, "potato", "potato", 0],
+             [0, 0, 0, 0, 0, 0, 0, "potato", "potato", "potato"],
+             ["strawberry", "strawberry", "strawberry", "strawberry", "strawberry", 0, 0, "potato", 0, 0],
+             ["strawberry", "strawberry", "strawberry", "strawberry", "strawberry", 0, 0, 0, 0, 0]
+             ]
+    return field

src/sprites.py

@@ -1,4 +1,5 @@
 import os
+
 import pygame
 
 # set up asset folders

tractor.py

@@ -1,20 +1,7 @@
-import pygame
+from src.dimensions import *
+from src.sprites import *
+from plant import *
 
-from pygame.locals import (
-    K_UP,
-    K_DOWN,
-    K_LEFT,
-    K_RIGHT,
-    K_ESCAPE,
-    K_SPACE,
-    K_c,
-    KEYDOWN,
-    QUIT
-)
-
-from dimensions import *
-from colors import *
-from sprites import *
 
 class Tractor(pygame.sprite.Sprite):
     def __init__(self, field, position):
@@ -27,33 +14,32 @@ class Tractor(pygame.sprite.Sprite):
             topleft=((MARGIN + WIDTH) * self.position[0] + MARGIN, (MARGIN + HEIGHT) * self.position[1] + MARGIN))
         self.direction = [1, 0]
         self.field[self.position[0]][self.position[1]].tractor_there = True
-        
+
     def move(self):
         self.field[self.position[0]][self.position[1]].tractor_there = False
-        self.rect.move_ip(self.direction[0]*(WIDTH + MARGIN), self.direction[1]*(HEIGHT + MARGIN))
+        self.rect.move_ip(self.direction[0] * (WIDTH + MARGIN), self.direction[1] * (HEIGHT + MARGIN))
         self.position[0] += self.direction[0]
         self.position[1] += self.direction[1]
         if self.position[0] >= GSIZE:
-            self.position[0] = GSIZE-1
+            self.position[0] = GSIZE - 1
         if self.position[1] >= GSIZE:
-            self.position[1] = GSIZE-1
+            self.position[1] = GSIZE - 1
         if self.position[0] < 0:
             self.position[0] = 0
         if self.position[1] < 0:
             self.position[1] = 0
 
         if self.rect.top <= MARGIN:
-                self.rect.top = MARGIN
-        if self.rect.bottom >= SCREEN_HEIGHT-MARGIN:
-                self.rect.bottom = SCREEN_HEIGHT-MARGIN
+            self.rect.top = MARGIN
+        if self.rect.bottom >= SCREEN_HEIGHT - MARGIN:
+            self.rect.bottom = SCREEN_HEIGHT - MARGIN
         if self.rect.left < MARGIN:
-                self.rect.left = MARGIN
-        if self.rect.right > SCREEN_WIDTH-MARGIN:
-                self.rect.right = SCREEN_WIDTH-MARGIN
-        
+            self.rect.left = MARGIN
+        if self.rect.right > SCREEN_WIDTH - MARGIN:
+            self.rect.right = SCREEN_WIDTH - MARGIN
+
         self.field[self.position[0]][self.position[1]].tractor_there = True
 
-    
     def rotate_right(self):
         if self.direction == [1, 0]:
             self.direction = [0, 1]
@@ -86,10 +72,13 @@ class Tractor(pygame.sprite.Sprite):
         field[self.position[0]][self.position[1]].hydrate()
 
     def cut(self, field, pressed_keys):
-        if pressed_keys[K_c]:
-            field[self.position[0]][self.position[1]].free()
+        field[self.position[0]][self.position[1]].free()
 
-    def plant(self, field, plant, pressed_keys):
-        if field.planted == 0:
-            field.planted = plant
-            plant.field = field
+    def plant(self, plant_map, plants):
+        print(plant_map[self.position[0]][self.position[1]])
+        plant = Plant(self.field[self.position[0]][self.position[1]], plant_map[self.position[0]][self.position[1]])
+        plants.append(plant)
+
+    def fertilize(self, field, plants, type):
+        if plants[self.position[0]][self.position[1]].species == type:
+            field[self.position[0]][self.position[1]].fertility = 1