changed distance in Fitness to Manhattan

Engine/DecisionTree.py

@@ -10,7 +10,7 @@ class DecisionTree:
 
 
     def __init__(self, doCreation):
-        self.data = pd.read_csv("C:\\Users\\kratu\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\out.csv")
+        self.data = pd.read_csv("C:\\Users\\Konrad\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\out.csv")
         if doCreation:
             self.mapData()
             features = ['bomb_type', 'detonation_duration', 'size', 'detonation_area', 'defusable']
@@ -21,7 +21,7 @@ class DecisionTree:
             decision_tree_model_pkl = open('tree.pkl', 'wb')
             pickle.dump(dtree, decision_tree_model_pkl)
             decision_tree_model_pkl.close()
-        decision_tree_model_pkl = open('C:\\Users\\kratu\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\Engine\\tree.pkl', 'rb')
+        decision_tree_model_pkl = open('C:\\Users\\Konrad\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\Engine\\tree.pkl', 'rb')
         self.dtree = pickle.load(decision_tree_model_pkl)
 
     def getTree(self):

Engine/Fitness.py

@@ -33,7 +33,5 @@ class Fitness:
         return self.fitness
 
     def cdistance(self, fromP, toP):
-        xDis = abs(fromP.getX() - toP.getX())
-        yDis = abs(fromP.getY() - toP.getY())
-        distance = np.sqrt((xDis ** 2) + (yDis ** 2))
-        return distance
+        distance = abs(fromP.getX() - toP.getX()) + abs(fromP.getY() - toP.getY())
+        return distance

Engine/Neurons.py

@@ -19,7 +19,7 @@ from torch.utils.data import DataLoader
 
 class Neurons:
     def __init__(self):
-        dataset = MNIST('C:\\Users\\kratu\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\Engine', gz=True, return_type='numpy')
+        dataset = MNIST('C:\\Users\\Konrad\\PycharmProjects\\Projekt_AI-Automatyczny_saper\\Engine', gz=True, return_type='numpy')
         images, labels = dataset.load_training()
         test_images, test_labels = dataset.load_testing()
         images = images / 255
@@ -41,7 +41,7 @@ class Neurons:
         torch.save(self.train(self.model, 100), 'model.pth')
         imsize = 28
         loader = transforms.Compose([transforms.Resize((imsize, imsize)), transforms.ToTensor()])
-        image = Image.open("C:\\Users\\kratu\\PycharmProjects\\JPG-PNG-to-MNIST-NN-Format\\test-images\\1\\claymore (1).png")
+        image = Image.open("C:\\Users\\Konrad\\PycharmProjects\\JPG-PNG-to-MNIST-NN-Format\\test-images\\1\\claymore (1).png")
         image = image.convert("1")
         image = loader(image).float()
         image = Variable(image, requires_grad=True)

Engine/Population.py

@@ -69,7 +69,7 @@ class Population:
 
     def mutate(self, individual, mutationRate):
         for swapped in range(len(individual)):
-            if (random.random() < mutationRate):
+            if random.random() < mutationRate:
                 swapWith = int(random.random() * len(individual))
 
                 city1 = individual[swapped]