dodanie drzewa decyzyjnego

Animals/animal.py

@@ -47,6 +47,7 @@ class Animal:
         chance = random.randint(1, 100)
         if chance >= 90:
             return True
+        else: return False
 
     def draw_illness(self, screen, grid_size, x, y):
         scale = 0.45

Animals/animals.py

@@ -46,18 +46,18 @@ def draw_Animals(Animals, const):
 
         Animal.draw(const.screen, const.GRID_SIZE)
 
-        if Animal.getting_hungry(const) == 5:
+        if Animal.getting_hungry(const) == 10:
            Animal.draw_exclamation(const.screen, const.GRID_SIZE, Animal.x, Animal.y)
            Animal.draw_food(const.screen,const.GRID_SIZE,Animal.x,Animal.y,'images/empty_bowl.png')
 
-        if Animal.getting_hungry(const) >= 4 and Animal.getting_hungry(const) < 5:
+        if Animal.getting_hungry(const) >= 8 and Animal.getting_hungry(const) < 5:
            Animal.draw_exclamation(const.screen, const.GRID_SIZE, Animal.x, Animal.y)
            Animal.draw_food(const.screen,const.GRID_SIZE,Animal.x,Animal.y,'images/almost_empty.png')
 
-        if Animal.getting_hungry(const) >= 2 and Animal.getting_hungry(const) < 4:
+        if Animal.getting_hungry(const) >= 5 and Animal.getting_hungry(const) < 4:
            Animal.draw_food(const.screen,const.GRID_SIZE,Animal.x,Animal.y,'images/half_bowl.png')
 
-        if Animal.getting_hungry(const) < 2:
+        if Animal.getting_hungry(const) < 5:
             Animal.draw_food(const.screen,const.GRID_SIZE,Animal.x,Animal.y,'images/full_bowl.png')
 
         if Animal.ill:

Animals/bat.py

@@ -9,6 +9,7 @@ class Bat(Animal):
         environment = "medium"
         food_image = 'images/grains.png'
         parrot_food = 'grains'
+        activity = 'nocturnal'
         super().__init__(x, y,name, Bat_image, food_image,parrot_food, environment, adult)
         self._starttime = datetime.now()
 
@@ -18,8 +19,8 @@ class Bat(Animal):
         minutes_passed = delta.total_seconds() / 30
         self._starttime = checktime
 
-        if const.IS_NIGHT and self._feed < 5:
+        if const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
 
         return self._feed

Animals/bear.py

@@ -21,7 +21,7 @@ class Bear(Animal):
         minutes_passed = delta.total_seconds() / 60
         self._starttime = checktime
 
-        if const.IS_NIGHT and self._feed < 5 and const.season != "winter":
+        if const.IS_NIGHT and self._feed < 10 and const.season != "winter":
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
         return self._feed

Animals/elephant.py

@@ -25,7 +25,7 @@ class Elephant(Animal):
         minutes_passed = delta.total_seconds() / 50
         self._starttime = checktime
 
-        if not const.IS_NIGHT and self._feed < 5:
+        if not const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
         return self._feed

Animals/giraffe.py

@@ -20,7 +20,7 @@ class Giraffe(Animal):
         minutes_passed = delta.total_seconds() / 30
         self._starttime = checktime
 
-        if not const.IS_NIGHT and self._feed < 5:
+        if not const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
         return self._feed

Animals/owl.py

@@ -9,6 +9,7 @@ class Owl(Animal):
         environment = "medium"
         food_image = 'images/grains.png'
         parrot_food = 'grains'
+        activity = 'nocturnal'
         super().__init__(x, y,name, Owl_image, food_image,parrot_food, environment, adult)
         self._starttime = datetime.now()
 
@@ -18,8 +19,8 @@ class Owl(Animal):
         minutes_passed = delta.total_seconds() / 25
         self._starttime = checktime
 
-        if const.IS_NIGHT and self._feed < 5:
+        if const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
 
         return self._feed

Animals/parrot.py

@@ -20,7 +20,7 @@ class Parrot(Animal):
         minutes_passed = delta.total_seconds() / 20
         self._starttime = checktime
 
-        if not const.IS_NIGHT and self._feed < 5:
+        if not const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
         return self._feed

Animals/penguin.py

@@ -20,7 +20,7 @@ class Penguin(Animal):
         minutes_passed = delta.total_seconds() / 15
         self._starttime = checktime
 
-        if not const.IS_NIGHT and self._feed < 5:
+        if not const.IS_NIGHT and self._feed < 10:
             self._feed += minutes_passed
-            self._feed = min(self._feed, 5)
+            self._feed = min(self._feed, 10)
         return self._feed

agent.py

@@ -1,7 +1,10 @@
 import pygame
+import random
 from constants import Constants
 from state_space_search import is_border, is_obstacle
 from night import draw_night
+from decision_tree import add_data
+from constants import Constants
 
 class Agent:
     def __init__(self, istate, image_path, grid_size):
@@ -10,7 +13,8 @@ class Agent:
         self.grid_size = grid_size
         self.image= pygame.image.load(image_path)
         self.image = pygame.transform.scale(self.image, (grid_size, grid_size))
-        self._food = 0
+        self._dryfood = 0
+        self._wetfood = 0
         
     def draw(self, const):
         # Obróć obrazek zgodnie z kierunkiem
@@ -27,16 +31,16 @@ class Agent:
 
         if const.IS_NIGHT: draw_night(const)
 
-    def handle_event(self, event, max_x, max_y, animals, obstacles):
+    def handle_event(self, event, max_x, max_y, animals, obstacles,const):
         if event.type == pygame.KEYDOWN:
             if event.key == pygame.K_UP:
-                self.move('Go Forward', max_x, max_y, obstacles, animals)
+                self.move('Go Forward', max_x, max_y, obstacles, animals,const)
             elif event.key == pygame.K_LEFT:
-                self.move('Turn Left', max_x, max_y, obstacles, animals)
+                self.move('Turn Left', max_x, max_y, obstacles, animals,const)
             elif event.key == pygame.K_RIGHT:
-                self.move('Turn Right', max_x, max_y, obstacles, animals)
+                self.move('Turn Right', max_x, max_y, obstacles, animals,const)
 
-    def move(self, action, max_x, max_y, obstacles, animals, goal):
+    def move(self, action, max_x, max_y, obstacles, animals, goal,const):
         if action == 'Go Forward':
             new_x, new_y = self.x, self.y
             if self.direction == 'N':
@@ -59,29 +63,47 @@ class Agent:
             self.direction = {'N': 'E', 'E': 'S', 'S': 'W', 'W': 'N'}[self.direction]
         
         self.istate = (self.x, self.y, self.direction) 
-        feed_animal(self, animals, goal)
+        feed_animal(self, animals, goal,const)
         take_food(self)
 
-def feed_animal(self, animals, goal): 
+def feed_animal(self, animals, goal,const): 
     goal_x, goal_y = goal
     if self.x == goal_x and self.y == goal_y:
         for animal in animals:
             if animal.x == goal_x and animal.y == goal_y:
-                if animal.getting_hungry(const=Constants()) < self._food :
-                    self._food -= animal._feed
-                    animal._feed = 0
-                    print(animal.name, "fed with", animal.food)
-                    print("Current food level: ", self._food)
+                if (animal.activity == 'nocturnal' and const.IS_NIGHT) or (animal.activity == 'diurnal' and not(const.IS_NIGHT)):
+                    activity_time = True
                 else:
-                    animal._feed -= self._food
-                    self._food = 0
-                    print(animal.name, "fed with", animal.food)
-                    print("Current food level: ", self._food)
+                    activity_time = False
+                guests = random.randint(1, 15)
+                feed_decision = add_data(animal.adult, activity_time, animal.ill, const.season, guests, animal._feed, self._dryfood, self._wetfood)
+                if feed_decision != 1:
+                    if feed_decision == 2:
+                        if animal.getting_hungry(const=Constants()) < self._wetfood :
+                            self._wetfood -= animal._feed
+                            animal._feed = 0
+                        else:
+                            animal._feed -= self._wetfood
+                            self._food = 0
+                        print(animal.name, "fed with wet food")
+                    else:
+                        if animal.getting_hungry(const=Constants()) < self._dryfood :
+                            self._dryfood -= animal._feed
+                            animal._feed = 0
+                        else:
+                            animal._feed -= self._dryfood
+                            self._dryfood = 0
+                        print(animal.name, "fed with dry food")
+                    print("Current wet food level: ", self._wetfood)
+                    print("Current dry food level: ", self._dryfood)
+                else: print(animal.name, " not fed")
+
 
 def take_food(self):
     house_x = 3
     house_y = 1
     if self.x == house_x and self.y == house_y:
-        if self._food == 0:
-            self._food = 25
-            print("Agent took food and current food level is", self._food)
+        if self._dryfood == 0 and self._wetfood == 0:
+            self._dryfood = 50
+            self._wetfood = 50
+            print("Agent took food and current food level is", self._dryfood, self._wetfood)

dane.csv

@@ -0,0 +1,301 @@
+adult,active_time,ill,season,guests,hunger,wet_food,dry_food,decision
+True,True,True,spring,12,4.0462,37.63803,5.60819,2
+True,False,False,spring,9,2.89229,34.37597,27.75948,1
+False,True,True,summer,15,2.4002,45.06447,41.50999,3
+True,False,False,summer,5,0.73248,46.1058,33.44281,1
+True,False,False,summer,12,0.62973,49.99647,41.07699,1
+True,False,False,winter,9,7.0889,46.16796,45.904,2
+False,True,False,summer,2,9.07977,22.08011,20.53507,3
+False,False,True,winter,11,3.5635,14.75823,43.46342,2
+False,False,True,winter,9,8.03113,20.6384,30.81177,2
+True,True,True,summer,0,0.01966,28.27203,3.37575,1
+False,False,False,autumn,12,8.27518,5.91931,21.10505,3
+False,False,True,summer,1,5.058,11.01892,48.04589,3
+False,True,False,winter,9,5.64777,17.19678,12.20864,1
+True,True,True,summer,0,6.86046,19.03315,47.13198,3
+True,False,True,winter,13,0.42516,12.62312,19.15853,1
+True,False,True,summer,14,4.46951,33.59537,47.343,1
+True,True,False,autumn,11,6.49386,0.64398,1.0515,1
+False,False,False,winter,10,1.9354,22.80015,26.01165,1
+True,False,False,summer,7,3.55716,1.91094,41.82462,1
+False,True,True,winter,8,9.01072,15.89341,9.10422,2
+False,True,True,spring,4,4.64513,10.39766,7.57955,2
+True,False,False,autumn,2,4.11019,45.85039,30.34183,1
+True,True,True,spring,8,7.09003,6.92577,24.77301,3
+True,True,False,spring,6,4.12955,47.91516,12.84722,1
+True,True,True,spring,10,2.70845,1.0623,42.6941,3
+True,True,True,spring,15,4.34025,6.89381,3.03923,2
+True,False,False,autumn,5,7.24464,31.34759,6.44719,1
+True,True,True,summer,6,3.8924,18.08964,18.77435,1
+False,False,True,spring,13,4.86962,48.62578,6.05301,2
+False,True,False,spring,11,1.60186,31.34926,14.41007,2
+False,True,False,autumn,2,4.19839,19.58116,28.63919,1
+False,True,True,autumn,6,1.50346,25.88282,24.97486,1
+False,True,False,spring,7,2.67431,17.05587,24.7939,1
+True,True,True,spring,7,1.72828,38.17304,24.3685,1
+False,True,True,summer,12,7.55322,26.52797,42.24754,3
+False,True,False,summer,5,8.74993,30.39317,4.5676,2
+False,True,False,summer,5,7.42862,48.73014,5.94891,2
+True,False,False,spring,4,9.3662,12.90556,41.31266,3
+False,True,False,autumn,8,4.72785,0.1623,19.48377,1
+False,False,False,winter,14,6.49349,29.52121,21.87192,1
+True,False,False,summer,14,1.57899,26.90783,33.03528,1
+False,True,False,summer,3,6.21725,3.60564,23.51978,1
+True,True,True,winter,4,4.18565,25.24209,11.02056,1
+False,False,True,autumn,8,6.5479,39.16107,4.75438,2
+False,False,False,summer,13,2.14609,39.97177,13.98651,1
+True,True,False,winter,9,7.43651,10.09353,15.70939,3
+False,False,True,autumn,5,7.85569,40.47073,49.75818,2
+True,False,True,summer,1,9.03492,23.44692,20.0026,3
+False,True,True,autumn,8,2.36724,42.81768,21.34668,2
+False,False,True,summer,15,6.8222,15.2733,15.14799,3
+True,False,True,summer,4,8.63882,41.36166,17.98981,3
+False,True,False,autumn,12,0.48943,8.67832,40.4952,1
+False,False,False,autumn,3,3.0489,14.81219,8.32707,1
+False,True,True,winter,6,0.41014,49.94757,12.61713,1
+True,False,True,winter,12,5.55017,0.98544,10.25287,1
+True,False,False,summer,11,9.92135,6.80759,48.0665,3
+False,True,True,winter,2,7.14394,11.41862,18.29288,2
+False,True,True,winter,10,1.39924,36.41807,42.95548,2
+False,True,False,summer,1,0.95193,46.53851,25.70391,1
+False,True,False,winter,4,1.44658,6.61497,31.58116,1
+False,True,False,autumn,10,7.9404,26.82316,49.5898,2
+True,False,False,spring,5,5.14951,32.36345,11.32114,1
+True,True,False,summer,5,7.55665,49.12578,29.32983,3
+True,False,True,autumn,3,3.80646,11.86722,35.43034,1
+False,False,False,winter,12,3.65822,0.14026,19.18031,1
+True,False,False,spring,8,8.58384,46.33595,11.52974,2
+True,False,False,summer,3,6.34127,22.66891,19.15813,1
+False,True,False,spring,13,7.86448,8.85557,40.03913,3
+True,True,False,spring,13,8.89316,49.89548,21.04525,2
+True,True,False,autumn,9,0.91339,36.35922,16.09576,1
+False,False,False,summer,3,7.36268,28.50462,29.52973,1
+True,True,True,spring,3,6.1319,37.71758,33.50616,1
+False,True,True,spring,0,0.77228,42.89976,19.19004,1
+True,False,True,autumn,3,7.73055,20.87865,37.18248,1
+False,False,False,summer,1,8.30392,34.47046,34.77926,3
+True,True,False,summer,8,2.96562,17.50839,23.22476,1
+True,True,True,winter,4,2.27279,20.58575,32.17293,1
+True,False,True,spring,7,6.14608,34.46015,17.22245,1
+False,False,True,winter,1,8.32044,12.09058,37.28732,3
+False,True,False,spring,14,9.56618,48.49473,46.37651,2
+True,False,True,spring,10,9.33146,47.99213,35.92519,2
+False,True,False,spring,6,0.47396,37.45415,36.87019,1
+True,False,False,summer,12,7.61463,4.36339,36.07375,3
+True,True,True,autumn,3,6.42039,4.90383,43.29857,3
+False,True,False,winter,13,6.89007,43.09184,3.04284,2
+True,False,True,winter,1,6.56604,19.04681,27.58314,2
+True,False,True,spring,3,1.96784,2.18597,34.02966,1
+False,False,False,spring,0,3.76673,1.64674,34.50649,1
+False,False,True,summer,2,0.05382,10.48896,24.03557,1
+True,False,True,spring,14,5.12387,44.44585,8.35502,3
+True,True,False,autumn,10,4.90335,43.27857,27.22901,1
+True,False,False,winter,11,5.89082,28.91495,15.58095,1
+True,False,True,autumn,3,7.39589,21.53402,44.50694,3
+True,False,False,summer,12,5.68671,49.18777,22.53807,3
+False,False,False,winter,0,0.86765,41.28704,33.77284,1
+False,False,True,summer,10,5.97643,36.23669,48.32615,2
+False,True,True,autumn,7,1.76947,38.34692,13.28679,1
+True,True,True,summer,13,8.63622,16.14861,44.91355,3
+True,False,False,winter,11,8.48481,37.52722,47.76888,2
+True,True,True,summer,12,7.65812,4.16785,34.57922,3
+False,False,True,winter,7,8.44897,42.99815,44.66558,2
+False,False,False,winter,7,0.53067,13.47003,18.45329,1
+False,False,False,winter,14,3.24747,9.51144,6.62824,1
+True,True,False,spring,12,5.19071,47.53107,34.68942,2
+True,False,False,summer,9,6.9442,46.79146,13.92798,2
+True,False,False,autumn,1,3.09242,18.02023,11.03004,1
+True,True,True,spring,3,0.19271,1.00203,1.16671,1
+False,True,True,winter,5,9.00758,37.95091,11.54697,2
+True,False,True,spring,9,6.11904,37.42698,4.82627,2
+False,False,True,autumn,9,6.29507,22.99044,15.46992,2
+False,False,False,winter,13,5.4099,11.75134,6.91861,1
+False,False,False,winter,5,9.92035,21.82547,10.2415,2
+False,True,False,winter,10,6.06913,1.46795,12.76663,1
+True,False,True,spring,5,8.1218,37.03643,32.04156,3
+True,False,False,autumn,11,0.48844,39.36689,0.03464,1
+False,True,True,summer,6,1.72816,26.85829,16.53262,1
+False,False,False,spring,5,6.04025,29.55673,18.85232,2
+False,True,True,winter,2,1.75157,0.6601,49.91163,1
+False,True,True,winter,9,6.75125,15.22221,6.72688,2
+False,True,True,autumn,9,6.72535,24.07403,33.94074,2
+False,False,False,winter,14,0.02843,48.49973,15.81701,1
+False,False,True,autumn,15,1.07944,45.94025,4.05257,1
+False,False,True,winter,12,7.26288,15.82501,22.56163,2
+True,True,True,winter,11,8.50892,23.89966,46.14267,3
+True,False,True,autumn,11,8.10923,24.31448,6.70919,2
+True,True,False,summer,11,4.65313,3.44791,3.96313,3
+True,False,True,summer,2,2.56716,10.85536,49.88738,1
+False,False,True,autumn,4,8.19265,5.43942,48.74041,3
+False,True,False,autumn,5,5.6574,9.75738,25.96888,3
+False,True,False,winter,14,4.87066,33.40134,18.98246,2
+True,True,True,winter,6,8.2623,37.47298,33.76759,2
+True,True,True,spring,10,2.20409,13.6178,5.80078,2
+True,False,True,autumn,7,9.06057,37.8724,23.62209,2
+False,False,True,autumn,3,6.69861,37.07336,16.87187,2
+True,False,True,autumn,13,4.96475,46.87852,3.1412,1
+True,False,True,autumn,9,2.65212,19.06994,37.33364,1
+True,True,False,summer,15,3.47148,35.84529,0.00000,1
+False,True,True,summer,8,1.51025,9.44246,19.05913,1
+False,False,True,autumn,6,6.48485,45.61986,15.91179,2
+False,False,False,spring,2,8.98075,39.32941,42.47669,2
+False,True,True,winter,5,8.37177,12.99299,42.31566,3
+True,True,True,autumn,6,3.38746,48.86975,49.62605,1
+False,True,True,summer,7,7.09358,22.83074,38.5172,2
+False,False,True,spring,9,1.00148,11.16064,0.52706,1
+False,False,True,winter,1,6.08476,37.67744,4.49812,2
+False,True,False,spring,5,4.5182,32.48803,33.44274,1
+True,True,True,summer,8,6.11265,30.32015,46.47287,3
+False,True,True,winter,4,8.50937,22.72015,0.00000,2
+True,False,True,summer,4,7.23924,39.09963,42.82872,3
+False,False,True,summer,5,1.28353,7.18667,38.93923,1
+False,True,False,spring,3,4.50329,22.95269,0.41795,1
+True,True,True,summer,1,0.47824,14.79432,24.64273,1
+False,True,False,spring,10,8.43205,19.1333,20.95803,2
+False,True,False,spring,6,9.94659,18.83814,39.26147,2
+False,True,False,spring,3,3.68802,1.58951,26.4255,1
+False,False,True,autumn,8,4.79336,22.56564,4.95207,2
+False,True,True,spring,10,1.63541,0.00000,31.82704,1
+False,True,False,spring,2,1.2274,47.87731,32.98744,1
+True,True,False,winter,11,7.31457,26.08142,16.5835,2
+False,True,True,summer,2,4.90627,19.73976,49.56272,3
+True,True,False,winter,8,3.02707,35.9547,29.52088,1
+True,True,True,summer,7,5.02577,5.37674,16.61368,3
+False,False,True,spring,8,9.58805,8.12549,0.00000,2
+False,True,True,summer,6,2.08786,37.11126,36.15777,3
+True,True,False,spring,7,8.11839,12.2032,8.26737,2
+True,False,True,summer,7,4.08923,20.77025,11.25944,1
+False,False,True,winter,4,4.85557,0.00000,39.4493,2
+False,False,False,summer,14,9.12718,41.84025,49.51895,2
+True,True,True,summer,15,9.4014,34.10345,26.84361,3
+False,True,False,spring,14,8.61728,28.58017,39.3705,2
+False,True,False,winter,8,7.12808,12.04193,43.86622,2
+True,False,True,winter,1,9.50102,43.46168,28.81571,2
+True,True,False,spring,5,1.35366,6.95688,33.37058,1
+False,False,True,autumn,11,7.61014,11.10761,41.58039,2
+False,True,True,summer,2,6.86814,37.72905,14.64706,3
+True,False,False,winter,1,8.12812,22.55081,9.43532,2
+True,True,True,winter,10,4.18282,27.82423,30.42216,1
+False,False,False,summer,7,2.52646,3.74242,10.61286,1
+False,False,True,spring,13,3.15065,19.01632,34.56097,2
+True,True,False,summer,3,0.18108,46.67684,46.76693,1
+True,True,True,spring,0,1.50217,5.27541,16.18378,1
+False,True,True,summer,5,3.71758,11.15496,12.57224,3
+False,True,False,summer,6,9.92613,8.59078,21.32207,3
+True,False,False,winter,11,0.1261,2.42716,17.23296,1
+True,False,True,summer,14,6.90049,10.76539,3.92394,3
+False,True,True,autumn,15,1.76164,35.60051,2.5168,2
+False,False,True,spring,11,2.39225,36.14198,9.13906,3
+True,True,False,summer,2,4.04026,0.00000,12.47216,1
+True,True,False,spring,13,3.32803,7.59913,1.89442,3
+True,False,True,spring,1,5.15927,44.02139,4.03454,1
+True,True,True,autumn,13,5.52565,7.75133,38.62709,3
+True,True,False,spring,3,8.44216,30.01593,12.45777,3
+False,False,True,summer,13,2.88557,5.18905,5.87065,3
+True,True,True,spring,11,2.45261,7.22671,49.68806,3
+True,True,True,winter,4,8.55814,3.29899,32.82852,2
+False,False,True,summer,4,9.85169,47.62867,17.3155,3
+False,False,True,winter,2,5.30151,26.50068,48.79306,2
+False,False,False,autumn,9,7.59806,0.00000,36.92142,2
+False,True,True,autumn,1,9.28424,17.58014,28.42461,2
+True,False,True,summer,14,7.82306,35.29264,46.36975,3
+False,False,True,winter,2,1.10909,46.37088,40.88245,1
+True,True,False,summer,1,7.71442,43.2301,27.42849,3
+False,True,True,summer,6,1.21255,3.7357,4.31858,1
+True,True,True,winter,8,9.53076,12.54774,17.63524,2
+True,True,True,autumn,3,8.47955,19.04656,3.62988,2
+True,False,True,winter,3,2.58264,28.29242,0.00000,1
+True,False,False,autumn,5,6.83145,0.00000,15.88102,1
+True,False,False,summer,10,3.24742,16.50963,26.24036,1
+False,False,False,summer,8,8.66174,49.55046,33.2433,2
+True,False,True,winter,7,1.40722,4.06585,2.57929,1
+False,True,False,winter,12,4.483,2.42211,20.55941,2
+False,False,True,spring,12,2.98512,30.55243,5.53733,3
+False,False,True,autumn,6,0.84086,33.57311,32.42908,1
+False,True,True,winter,12,1.07916,8.27438,7.9284,1
+False,False,True,spring,12,3.17402,46.59657,14.21739,3
+False,True,True,winter,11,7.09559,14.18261,43.41709,2
+False,False,True,autumn,3,0.53006,21.37664,17.14295,1
+False,False,False,autumn,14,4.67143,4.11788,0.04226,1
+True,False,True,winter,12,3.48493,35.24303,0.00000,1
+True,True,True,spring,9,5.1789,0.97673,8.31413,2
+False,False,False,spring,5,1.50319,28.57762,27.80054,1
+True,True,True,autumn,10,9.23444,43.51842,19.90954,2
+False,False,False,autumn,9,3.84582,40.34953,9.01663,1
+True,True,False,winter,5,3.90587,32.97826,0.67046,1
+True,True,True,autumn,2,9.19994,0.00000,34.36662,3
+False,True,True,summer,6,5.614,29.08038,0.00000,2
+True,True,True,autumn,2,2.15339,6.36751,6.45082,1
+True,False,True,spring,1,9.19416,32.05433,8.27667,2
+True,False,True,autumn,0,8.12282,48.68677,8.38304,2
+False,True,True,spring,12,3.26729,29.61584,1.69993,2
+True,False,True,summer,8,1.99886,31.26437,3.51834,1
+False,False,True,summer,7,7.41314,44.88982,34.46453,2
+True,False,True,summer,0,7.24464,8.85289,34.29828,3
+False,True,False,summer,8,2.38628,21.76861,47.20283,3
+True,True,True,autumn,3,7.12112,12.08359,41.06062,3
+True,False,False,winter,5,6.74504,47.09367,1.97357,2
+False,False,False,summer,8,1.23539,35.47945,7.67276,1
+True,False,False,spring,11,7.91742,34.52557,30.96412,3
+False,True,True,winter,14,5.91181,7.53226,16.37669,3
+False,True,True,spring,13,6.07261,47.43572,15.83885,2
+True,True,True,autumn,2,9.22518,31.25996,28.06488,3
+False,True,True,summer,3,8.47609,0.23934,31.25786,3
+False,True,False,autumn,6,0.97126,13.65648,25.59887,1
+True,False,False,spring,14,9.29029,46.83676,12.58912,2
+False,False,False,winter,14,0.14092,4.6673,20.3859,1
+True,False,True,autumn,2,3.52708,37.61372,32.83573,1
+True,True,True,winter,1,4.37134,43.19138,22.04785,1
+True,False,True,summer,9,1.1614,10.9739,42.3009,1
+False,False,False,winter,9,7.27324,29.74731,47.17759,2
+False,True,True,winter,9,3.17153,35.14715,21.37868,2
+False,True,False,autumn,0,2.37863,20.35733,46.96943,1
+False,False,True,autumn,4,0.70656,8.70201,5.26527,1
+True,True,True,winter,1,8.23562,36.01552,25.03969,2
+True,True,False,winter,3,6.65062,6.75622,24.91086,3
+False,False,False,spring,10,2.30179,19.62758,25.57147,1
+True,True,False,autumn,10,6.60812,6.61336,12.39931,3
+False,False,True,summer,3,8.9948,47.39225,18.11157,2
+True,False,True,autumn,5,6.69302,42.62701,13.01677,2
+False,False,False,spring,14,8.53868,33.42545,2.43572,2
+False,True,True,autumn,10,4.46205,10.37542,39.58137,3
+True,True,False,spring,14,5.34262,15.45545,21.48404,3
+True,False,False,winter,9,7.02885,4.88308,27.56619,3
+False,False,False,autumn,13,3.55279,0.17091,5.43831,1
+True,True,True,autumn,1,9.98637,27.57982,15.82173,2
+False,True,True,summer,9,8.25408,13.10493,27.07596,3
+False,False,False,spring,15,1.9089,33.25115,44.57492,1
+True,False,False,autumn,12,6.65534,38.00972,20.31047,2
+False,True,True,autumn,1,0.01592,6.24929,15.51308,1
+False,True,True,winter,13,1.24017,36.88006,16.50894,1
+False,True,True,winter,13,6.1878,15.18876,9.02381,2
+True,True,True,winter,5,5.45157,13.27868,39.39805,2
+True,False,True,spring,5,2.82881,28.62319,24.03077,1
+False,False,True,spring,2,4.8246,41.45269,48.89539,2
+True,False,False,spring,8,9.3343,39.02018,45.01066,3
+True,True,True,autumn,4,1.8456,2.94366,37.44996,1
+False,True,True,summer,14,0.95333,4.57964,26.37633,1
+False,False,True,autumn,13,9.84087,24.03819,41.72097,2
+True,False,False,autumn,9,3.70617,32.70115,1.69105,1
+True,True,True,spring,12,6.77783,6.67976,20.46179,3
+False,False,True,summer,15,7.15829,31.24546,10.37666,3
+False,True,True,summer,1,2.28393,18.13299,34.38756,3
+True,False,True,autumn,7,3.96302,39.84093,47.0172,1
+True,False,False,summer,1,0.65085,20.20581,14.96995,1
+True,False,False,winter,2,9.24331,26.34543,30.5147,2
+True,False,False,summer,3,2.86309,15.56342,1.04324,1
+True,False,False,summer,1,4.03947,33.84073,6.48891,1
+True,False,False,winter,4,2.46471,24.07929,17.77792,1
+False,False,False,winter,9,3.66415,23.68306,24.43865,1
+True,True,True,autumn,8,5.71809,24.41045,48.78273,2
+False,True,True,spring,3,5.3009,34.83862,6.75862,2
+True,False,True,winter,8,6.23275,8.1183,19.6922,3
+False,True,True,autumn,2,4.21016,11.24334,34.98395,3
+True,True,False,autumn,0,2.79424,13.25106,5.69617,1
+True,True,False,winter,15,2.43843,14.61703,49.57393,2
+True,True,True,summer,8,2.28654,20.9895,5.64007,1
+False,False,False,autumn,1,2.5607,26.85209,47.10784,1
+True,True,True,winter,14,1.56638,18.02703,7.05011,1
+False,False,False,winter,13,3.86632,28.9884,20.1928,1
+True,False,False,summer,13,6.37654,34.3833,34.53892,3
+True,True,False,summer,5,8.10422,7.6617,23.41017,3

decision_tree.py

@@ -0,0 +1,49 @@
+import pandas as pd
+from sklearn.tree import DecisionTreeClassifier, plot_tree, export_graphviz
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+import matplotlib.pyplot as plt
+headers = ['adult','active_time','ill','season','guests','hunger','wet_food','dry_food']
+# Wczytanie danych
+data = pd.read_csv('dane.csv', header=0) 
+X = data[['adult','active_time','ill','season','guests','hunger','wet_food','dry_food']]
+Y = data['decision']
+X = pd.get_dummies(data=X, columns=['season'])
+
+X_train, X_test, Y_train, Y_test = train_test_split(X, Y, train_size=0.8)
+clf = DecisionTreeClassifier(random_state=0, min_samples_leaf = 4, min_samples_split=2)
+clf = clf.fit(X_train, Y_train)
+Y_pred = clf.predict(X_test)
+accuracy = accuracy_score(Y_test, Y_pred)
+print("Dokładność:", accuracy)
+
+
+
+#zapisanie drzewa do pliku
+plt.figure(figsize=(50,30))  
+plot_tree(clf, filled=True, feature_names=X.columns, class_names=['nie karmi', 'karmi mokrą karmą', 'karmi suchą karmą'])  # filled=True koloruje węzły
+plt.savefig('tree.png')
+
+# Nowe dane
+def add_data(adult,active_time,ill,season,guests,hunger,wet_food,dry_food):
+    X_new = pd.DataFrame({
+        'adult': [adult],
+        'active_time': [active_time],
+        'ill': [ill],
+        'season': [season],
+        'guests':[guests],
+        'hunger': [hunger],      
+        'wet_food': [wet_food],    
+        'dry_food': [dry_food]      
+})
+    X_new_encoded = pd.get_dummies(X_new)
+    missing_columns = set(X.columns) - set(X_new.columns)
+    for col in missing_columns:
+        X_new_encoded[col] = 0
+        X_new_encoded = X_new_encoded.reindex(columns=X.columns, fill_value=0)
+    print("Atrybuty zwierzęcia:", adult,active_time,ill,season,guests,hunger,wet_food,dry_food)
+    return (clf.predict(X_new_encoded))
+
+
+
+

main.py

@@ -3,7 +3,7 @@ import pygame
 import sys
 
 sys.path.append('./Animals')
-
+from decision_tree import add_data
 from animals import create_animals, draw_Animals
 from agent import Agent
 from enclosure import create_enclosures, draw_enclosures, draw_gates
@@ -84,7 +84,7 @@ def main():
             if event.type == pygame.QUIT:
                 pygame.quit()
                 sys.exit()
-            agent.handle_event(event, const.GRID_WIDTH, const.GRID_HEIGHT, Animals, obstacles)
+            agent.handle_event(event, const.GRID_WIDTH, const.GRID_HEIGHT, Animals, obstacles,const)
 
         change_time(const)
         draw_background(const)
@@ -93,6 +93,7 @@ def main():
         draw_gates(Enclosures, const)
         draw_house(const)
 
+  
         if not spawned:
             
             spawn_all_animals()
@@ -110,10 +111,10 @@ def main():
 
         if actions:
             action = actions.pop(0)
-            agent.move(action, const.GRID_WIDTH, const.GRID_HEIGHT, obstacles, Animals, goal)
+            agent.move(action, const.GRID_WIDTH, const.GRID_HEIGHT, obstacles, Animals, goal,const)
             pygame.time.wait(200)
         else:
-            if agent._food != 0: 
+            if agent._dryfood != 0 or agent._wetfood != 0 : 
                 animal = random.choice(Animals)
                 goal = (animal.x, animal.y)
                 draw_goal(const, goal)