final corrections before submission

.gitignore

@@ -1,7 +1,10 @@
+HW3/results/*
 HW3/results
+HW3/plots
 HW4/results
+HW4/plots
 HW5/results
 HW5/plots
 HW5/plots/*
 HW5/dataset.csv
-HW5/trained_model.joblib
+HW5/trained_model.joblib

HW1/core.py

@@ -19,11 +19,8 @@ class Pokemon:
                     raise ValueError(f"{move} is not an available move.")
                 else:
                     self.moves_dict[move] = copy.deepcopy(gd.available_moves[move])
-                    print(gd.available_moves[move]['PP'])
-                    print("TYPE", type(gd.available_moves[move]))
         self.curr_hp = self.baseStats['hp']
 
-
     def _get_baseStats(self):
         return self.baseStats
 
@@ -49,6 +46,7 @@ class Pokemon:
             self.moves_dict[move] = gd.available_moves[move]
 
     def _useMove(self, move, opponent):
+        win_flag = False
         if move['PP'] > 0:
             if random.random() < move['accuracy']:
                 if move['category'] == 'physical':
@@ -64,29 +62,32 @@ class Pokemon:
                 modifier = stability * effect * critical * luck
                 damage = math.floor((( 2 * self.level + 10) / 250 * (attack / defense) * move['power'] + 2) * modifier)
                 opponent.curr_hp -= damage
-                if opponent.curr_hp < 0:
+                if opponent.curr_hp < 0 or opponent.curr_hp == 0:
                     opponent.curr_hp = 0
+                    win_flag = True
+                    print(f"{opponent.name} has fainted!")
                 print(f"{self.name} used {move['name']} and dealt {damage} damage to {opponent.name}!")
+                print("CPU's Pokemon current HP: ", opponent.curr_hp)
                 move['PP'] = move['PP'] - 1
             else:
                 print(f"{self.name}'s attack missed!")
                 move['PP'] = move['PP'] - 1
         else:
             print(f"{self.name} has no PP left for {move['name']}!")
-        pass
+        return win_flag
 
     def useMove(self, move_name, opponent):
         if move_name not in self.moves_dict:
-                raise ValueError(f"{self.name} does not know the move {move_name}.")
+            raise ValueError(f"{self.name} does not know the move {move_name}.")
         else:
-            self._useMove(self.moves_dict[move_name], opponent)
+            return self._useMove(self.moves_dict[move_name], opponent)
 
     def print_move(self,move):
         print(f"Move: {self.moves_dict[move]['name']}")
-        print(f"Type: {self.moves_dict[move]['type']}")
-        print(f"Category: {self.moves_dict[move]['category']}")
+        #print(f"Type: {self.moves_dict[move]['type']}")
+        #print(f"Category: {self.moves_dict[move]['category']}")
         print(f"Power: {self.moves_dict[move]['power']}")
-        print(f"Accuracy: {self.moves_dict[move]['accuracy']}")
+        #print(f"Accuracy: {self.moves_dict[move]['accuracy']}")
         print(f"PP: {self.moves_dict[move]['PP']}")
 
     def get_moves(self):
@@ -111,7 +112,7 @@ class Pokemon:
 
 
 class Trainer:
-    def __init__(self, name, starter_name, items = {"potions": 0, "pokeball": 0}, is_CPU = False):
+    def __init__(self, name, starter_name, items = {}, is_CPU = False):
         self.name = name
         if is_CPU:
             if starter_name not in gd.available_wild_pokemons:
@@ -171,28 +172,6 @@ class Trainer:
         except ValueError as e:
             raise e
 
-    def print_items(self):
-        print(f"1) Potions: {self.items['potions']}")
-        print(f"2) Pokeballs: {self.items['pokeball']}")
-
-    def use_item(self, item_name):
-        if item_name not in self.items:
-            raise ValueError(f"{item_name} is not an available item.")
-        else:
-            if self.items[item_name] > 0:
-                self.items[item_name] -= 1 #use the item
-                print(f"Used {item_name}. Remaining: {self.items[item_name]}")
-                if item_name == "potions":
-                    self.active_pokemon.curr_hp += 20
-                    if self.active_pokemon.curr_hp > self.active_pokemon.baseStats['hp']:
-                        self.active_pokemon.curr_hp = self.active_pokemon.baseStats['hp']
-                    print(f"{self.active_pokemon.name} has been healed by 20 HP!")
-                    return False
-                elif item_name == "pokeball":
-                    return True
-            else:
-                raise ValueError(f"You have no {item_name} left.")
-
     def update_pokemon_list(self, pokemon):
         pass
 
@@ -203,7 +182,7 @@ class Trainer:
         print(f"Pokemon List: {[pok.name for pok in self.pokemon_list]}")
         print("Active Pokemon info:")
         self.active_pokemon.print_pokemon_info()
-        print("Detailed info of Pokemons in your list:")
+        print("Detailed info of Pokemons in the list:")
         print("-"*30)
         for pokemon in self.pokemon_list:
             pokemon.print_pokemon_info()

HW1/hw1.py

@@ -1,8 +1,5 @@
 import random
-import math
-
 import game_data as gd
-
 from core import Trainer
 
 def Main():
@@ -19,11 +16,11 @@ def Main():
             print(e)
             print("Please try again...")
             continue
-    trainer.print_trainer_info()
+    #trainer.print_trainer_info()
 
-    cpu_trainer = Trainer(name="CPU", starter_name=random.choice(gd.available_starter_names))
+    cpu_trainer = Trainer(name="CPU", starter_name=random.choice(gd.available_wild_pokemon_names), is_CPU=True)
     print(f"CPU has chosen {cpu_trainer.get_active_pokemon().name} as their starter Pokemon!")
-    cpu_trainer.print_trainer_info() 
+    #cpu_trainer.print_trainer_info() 
     continue_playing = True
     while continue_playing:
         selected_pokemon_combat_flag = False
@@ -42,7 +39,6 @@ def Main():
             print(f"Choose a move for {player_pokemon.name} to use against {cpu_trainer.get_active_pokemon().name}:\n", player_pokemon.get_moves())
             player_move_name = input("Choose:")
             try:
-                #print the move selected by the player
                 print("Your selected move: ")
                 player_pokemon.checkout_move(player_move_name)
                 selected_combat_move_flag = True
@@ -50,21 +46,24 @@ def Main():
                 print(e)
                 print("Please try again...")
 
-        #make a combat
+        #combat
         print('='*30)
         print("BATTLE RESULTS:")
         print("Your move:")
-        player_pokemon.useMove(player_move_name, cpu_trainer.get_active_pokemon())
-        player_pokemon.checkout_move(player_move_name)
-        print('-'*30)
-        print("CPU's pokemon")
-        cpu_trainer.get_active_pokemon().print_pokemon_info()
-        print('='*30)
-
-        print("Continue playing? (yes/no)")
-        response = input().strip().lower()
-        if response != "yes":
+        opponent_fainted = player_pokemon.useMove(player_move_name, cpu_trainer.get_active_pokemon())
+        #player_pokemon.checkout_move(player_move_name)
+        #print('-'*30)
+        #print("CPU's pokemon")
+        #cpu_trainer.get_active_pokemon().print_pokemon_info()
+        #print('='*30)
+        if opponent_fainted:
+            print("You won the battle!")
             continue_playing = False
+        else:
+            print("Continue playing? (yes/no)")
+            response = input().strip().lower()
+            if response != "yes":
+                continue_playing = False
     
 
 if __name__ == "__main__":

HW2/core.py

@@ -178,7 +178,7 @@ class Trainer:
             raise ValueError(f"{item_name} is not an available item.")
         else:
             if self.items[item_name] > 0:
-                self.items[item_name] -= 1 #use the item
+                self.items[item_name] -= 1
                 print(f"Used {item_name}. Remaining: {self.items[item_name]}")
                 if item_name == "potions":
                     self.active_pokemon.curr_hp += 20

HW2/hw2.py

@@ -160,7 +160,7 @@ def Main():
             print("Adding potions and pokeballs to your inventory...")
             trainer.items = {"potions": 10, "pokeball": 10}
             print("Your character is ready!")
-            trainer.print_trainer_info()
+            #trainer.print_trainer_info()
             player_created_flag = True
             print(f"Welcome {trainer.name}! Your adventure begins now!")
         except ValueError as e:
@@ -201,9 +201,9 @@ def Main():
             battle_prob = random.uniform(0, 1)
             print(f"Battle probability: {battle_prob:.2f}")
             if battle_prob < 0.8:
-                print("A wild Pokemon appeared!")
                 cpu_trainer = Trainer(name='CPU',starter_name=gd.available_wild_pokemon_names[random.randint(0,len(gd.available_wild_pokemon_names)-1)],is_CPU=True)
-                print(cpu_trainer.get_active_pokemon().print_pokemon_info())
+                print(f"A wild {cpu_trainer.get_active_pokemon().name} appeared!")
+                #print(cpu_trainer.get_active_pokemon().print_pokemon_info())
                 game_status = 'battle'
                 Battle(trainer,cpu_trainer)
             else:
@@ -224,7 +224,6 @@ def Main():
             else:
                 print("You exited the Pokemon Center.")
                 game_status = 'story'
-            # Add Pokemon Center logic here
         elif game_status == 'pokemon_store':
             print("You are in the Pokemon Store. You can buy items here.")
             restore_items_flag = input("Type 'yes' to restore your items: ").strip().lower()

HW3/core.py

@@ -21,7 +21,6 @@ class Pokemon:
                     self.moves_dict[move] = copy.deepcopy(gd.available_moves[move])
         self.curr_hp = self.baseStats['hp']
 
-
     def _get_baseStats(self):
         return self.baseStats
 
@@ -51,9 +50,6 @@ class Pokemon:
             self.moves_dict[move] = copy.deepcopy(gd.available_moves[move])
 
     def _compute_effect(self, move, opponent):
-        #check the move type (attack) and the defending
-        #pokemon type (defend) and look at effectiveness list.
-        #this should be done for all type of the defending pokemon
         attack_move_type = move['type']
         defending_types = opponent.get_types()
         

HW3/game_data.py

@@ -1,9 +1,9 @@
 import json
 import random
 
-#load moves from json file
-#eclude moves with power equal to null,
-# do not consider the effect,effects or changes fields
+
+#exclude moves with power equal to null,
+#do not consider the effect,effects or changes fields
 available_moves = dict()
 keys_to_skip = ['effect','effects','changes']
 with open('moves.json', 'r') as file:
@@ -33,7 +33,7 @@ with open('pokemons.json', 'r') as file:
         for m in available_moves.keys():
             if available_moves[m]['type'] in current_pokemon_types:
                 compatible_moves.append(m)
-        #select two random moves
+        #select two (compatible) random moves
         selected_moves = [random.choice(compatible_moves) for _ in range(2)]
         pokemons_dict[p['name']]['moves'] = selected_moves
 

HW3/hw3.py

@@ -1,3 +1,4 @@
+import os
 from core import Trainer
 
 import random
@@ -68,11 +69,7 @@ def Main(starter_choice,Nbattles):
     try:
         starter_name = starter_choice
         trainer = Trainer(name='edo', starter_name=starter_name)
-        #print(f"{trainer.name} has chosen {trainer.starter} as their starter Pokemon!")
-        #print("Adding potions and pokeballs to your inventory...")
         trainer.items = {"potions": 10, "pokeball": 10}
-        #print("Your character is ready!")
-        #print(f"Welcome {trainer.name}! Your adventure begins now!")
     except ValueError as e:
         print(e)
         print("Something went wrong!")
@@ -98,6 +95,8 @@ def Main(starter_choice,Nbattles):
 
 def make_plots(Ngames,Nbattles):
     #SIMPLE PLOT
+    if os.path.exists('plots') == False:
+        os.makedirs('plots')
     cumulative_victories = np.zeros((Ngames,Nbattles))
     plt.figure(figsize=(10, 6))
     for starter_choice in gd.available_starters:
@@ -171,6 +170,10 @@ def make_plots(Ngames,Nbattles):
 if __name__ == "__main__":
     Ngames = 500
     Nbattles = 100
+    if os.path.exists('results') == False:
+        os.makedirs('results')
+    if os.path.exists('plots') == False:
+        os.makedirs('plots')
     for starter_choice in gd.available_starters:
         for i in range(Ngames):
             print(f"Generating data for {starter_choice}, game {i}...")

HW4/game_data.py

@@ -56,6 +56,5 @@ with open('type_effectiveness.json', 'r') as file:
         type_effectiveness.append(json.loads(line))
 type_effectiveness_df = pd.DataFrame.from_dict(type_effectiveness)
 #NOTE: from a practical point of view, since type_effectiveness is accessed many times
-#in the main code, using pandas DataFrame is not efficient. I decided to keep using dictionaries
-#for the type effectiveness. The justification arises especially if we consider 
-#how long data generation will take.
+#in the main code I decided to keep using dictionaries
+#for the type effectiveness

HW4/hw4.py

@@ -7,7 +7,6 @@ import pickle
 import matplotlib.pyplot as plt
 import numpy as np
 import os
-np.seterr(divide='raise', invalid='raise')
 
 #if the results folder does not exist, create it
 if not os.path.exists('results'):
@@ -220,17 +219,19 @@ def make_plots(Ngames,Nbattles):
     plt.savefig('plots/pokemon_types_distribution.pdf')
     
 
-
 if __name__ == "__main__":
     Ngames = 1000
     Nbattles = 150
+
     print("Generating data")
     for i in range(Ngames):
+        #automatic player creation (choose a random starter pokemon)
         starter_choice = random.choice(gd.available_starters)
-        #print(f"Generating data for {starter_choice}, game {i}...")
+        print(f"Generating data for {starter_choice}, game {i}...")
         results = Main(starter_choice = starter_choice, Nbattles=Nbattles)
         pickle_out = open(f"results/{starter_choice}_game_{i}_{Nbattles}_battles.pickle",'wb')
         pickle.dump(results,pickle_out)
         pickle_out.close()
     print("Generating plots")
-    make_plots(Ngames, Nbattles)
+    make_plots(Ngames, Nbattles)
+    print("Finished!")

HW5/hw5.py

@@ -1,22 +1,199 @@
 from core import Trainer
-
+import game_data as gd
 import random
 import copy
-import game_data as gd
+import numpy as np
 import pickle
 import joblib
-import matplotlib.pyplot as plt
-import numpy as np
 import os
 import pandas as pd
+from sklearn.model_selection import train_test_split
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
+from sklearn.model_selection import RandomizedSearchCV
+from scipy.stats import randint
+from sklearn.tree import export_graphviz
+import graphviz
 
-np.seterr(divide='raise', invalid='raise')
+game_status = 'story'
+game_active_flag = True
+if os.path.exists('trained_model.joblib'):
+    recommender_sys_avail = True
+else:
+    recommender_sys_avail = False
 
-#if the results folder does not exist, create it
-if not os.path.exists('results'):
-    os.makedirs('results')
-if not os.path.exists('plots'):
-    os.makedirs('plots')
+def recommend(player_pokemon, opponent_pokemon):
+    global recommender_sys_avail
+    if recommender_sys_avail:
+        model = joblib.load('trained_model.joblib')
+
+        # Prepare input data
+        all_pokemon_types = list(gd.available_types)
+        player_ActStats = list(player_pokemon.ActStats.values())
+        player_pokemon_type = player_pokemon.types
+        player_pokemon_type_encoded = [1 if t in player_pokemon_type else 0 for t in all_pokemon_types]
+        opponent_ActStats = list(opponent_pokemon.ActStats.values())
+        opponent_pokemon_type = opponent_pokemon.types
+        opponent_pokemon_type_encoded = [1 if t in opponent_pokemon_type else 0 for t in all_pokemon_types]
+
+        input_data = player_ActStats + player_pokemon_type_encoded + opponent_ActStats + opponent_pokemon_type_encoded
+        labels = build_dataset()[:-1]  # Exclude the last label which is 'battle_result'
+        df_to_eval = pd.DataFrame([input_data], columns=labels)
+        
+        prediction_proba = model.predict_proba(df_to_eval)
+        return prediction_proba[0][1]  # Returns 1 if prediction is a win, 0 otherwise, and the probability of winning
+    else:
+        raise ValueError("Recommender system is not available. Play NewRandomBattle once!")
+def Battle(trainer,cpu_trainer):
+    global game_status
+    global game_active_flag
+    print(f"You are in battle against CPU's {cpu_trainer.get_active_pokemon().name}!")
+    battle_active = True
+    
+    while battle_active:
+        player_battle_action_selected = False
+        while not player_battle_action_selected:
+            print("Type the number of one of the following actions:")
+            print(f"1) Attack - [Your active Pokemon - {trainer.get_active_pokemon().name}]")
+            print("2) Change pokemon")
+            print("3) Use item")
+            print("4) Consult the Oracle")
+            print("5) Run away")
+            print('6) Check status')
+
+            try:
+                action = int(input("Choose an action (1-6): ").strip())
+                player_battle_action_selected = True
+            except ValueError:
+                print("Invalid input. Please enter a number between 1 and 6.")
+                continue
+
+        if action == 1:
+            #check if the player can sustain a battle: first check the active pokemon,
+            #then check the pokemons in the list
+            if not trainer.active_pokemon_can_battle():
+                print("Your active pokemon cannot battle!")
+                if not trainer.can_battle():
+                    print("You have no more pokemon that can battle! You lost the battle!")
+                    battle_active = False
+                    game_status = 'pokemon_center'
+                    break
+                else:
+                    print("You have other pokemon that can battle! Please change your active pokemon!")
+                    continue
+
+            selected_combat_move_flag = False
+            while not selected_combat_move_flag:
+                active_pokemon = trainer.get_active_pokemon()
+                cpu_active_pokemon = cpu_trainer.get_active_pokemon()
+                print(f"Choose a move for {active_pokemon.name} to use against {cpu_active_pokemon.name}:\n", active_pokemon.get_moves())
+                player_move_name = input("Choose:")
+                try:
+                    active_pokemon.useMove(player_move_name,cpu_active_pokemon)
+                    selected_combat_move_flag = True
+                    #check if the opponent has been defeated
+                    if not cpu_trainer.active_pokemon_can_battle():
+                        print(f"{cpu_trainer.get_active_pokemon().name} has been defeated!")
+                        battle_active = False
+                        game_status = 'story'
+                        break
+
+                    #if the opponent has not been defeated, then its the CPU turn to play
+                    cpu_active_pokemon_selected_move_name = random.choice(cpu_active_pokemon.get_moves())
+                    print(f"CPU's {cpu_active_pokemon.name} is using {cpu_active_pokemon_selected_move_name} against your {active_pokemon.name}!")
+                    cpu_active_pokemon.useMove(cpu_active_pokemon_selected_move_name, active_pokemon)
+
+                    #update the player pokemon list
+                    trainer.update_pokemon_list(active_pokemon)
+                    #check if the player has been defeated
+                    if not trainer.active_pokemon_can_battle():
+                        print(f"Your {active_pokemon.name} has been defeated!")
+                        if not trainer.can_battle():
+                            print("You have no more Pokemons that can battle! You lost!")
+                            battle_active = False
+                            game_status = 'pokemon_center'
+                            break
+                        else:
+                            print("You have other Pokemons that can battle!")
+                            continue
+                except ValueError as e:
+                    print(e)
+                    print("Please try again...")
+
+        elif action == 2:
+            print('='*30)
+            print("Change active pokemon")
+            print('-'*30)
+            change_pokemon_success = False
+            while not change_pokemon_success:
+                try:
+                    print("Select the name of a pokemon in your list:")
+                    print(trainer.get_pokemon_list())
+                    chosen_new_pokemon_name = input('Choose...')
+                    trainer.change_active_pokemon(chosen_new_pokemon_name)
+                    change_pokemon_success = True
+                except ValueError as e:
+                    print(e)
+
+        elif action == 3:
+            print("Select the item index to use:")
+            trainer.print_items()
+            item_selected_flag = False
+            while not item_selected_flag:
+                try:
+                    avail_items = list(trainer.items.keys())
+                    item_index = int(input("Choose an item index (1-2): ").strip())
+                    item_selected_flag = True
+                    is_pokeball = trainer.use_item(item_name=avail_items[item_index - 1])
+                    if is_pokeball:
+                        catch_prob = 1 - (cpu_trainer.get_active_pokemon().get_current_hp() / cpu_trainer.get_active_pokemon().baseStats['hp'])
+                        random_value = random.uniform(0, 1)
+                        if random_value < catch_prob:
+                            print(f"You caught {cpu_trainer.get_active_pokemon().name}!")
+                            trainer.add_pokemon(cpu_trainer.get_active_pokemon())
+                            battle_active = False
+                            game_status = 'story'
+                        else:
+                            print(f"{cpu_trainer.get_active_pokemon().name} escaped your pokeball!")
+                except ValueError:
+                    print("Please enter a number between 1 and 2.")
+                    continue
+
+        elif action == 4:
+            global recommender_sys_avail
+            if recommender_sys_avail:
+                try:
+                    for pokemon in trainer.pokemon_list:
+                        win_prob = recommend(player_pokemon=pokemon, opponent_pokemon=cpu_trainer.get_active_pokemon())
+                        print(f"The Oracle predicts {pokemon.name} to have {win_prob:.2f} of chances to win against {cpu_trainer.get_active_pokemon().name}.")
+                except ValueError as e:
+                    print(e)
+
+        elif action == 5:
+            runaway_prob = 0.6
+            random_value = random.uniform(0, 1)
+            if random_value < runaway_prob:
+                print("You successfully ran away from the battle!")
+                battle_active = False
+                game_status = 'story'
+            else:
+                print("You could not run away from the battle!")
+
+        elif action == 6:
+            print('='*30)
+            print("BATTLE INFO")
+            print('-'*30)
+            print("Your items:")
+            trainer.print_items()
+            print("Your pokemon list info:")
+            for pokemon in trainer.pokemon_list:
+                pokemon.print_pokemon_info()
+                print("-"*30)
+            print("CPU active pokemon info:")
+            cpu_trainer.get_active_pokemon().print_pokemon_info()
+            print('='*30)
+        else:
+            print("Invalid action. Please choose again.")
 
 def RandomBattle(trainer,cpu_trainer):
     #print(f"You are in battle against {cpu_trainer.name}!")
@@ -34,13 +211,20 @@ def RandomBattle(trainer,cpu_trainer):
     cpu_hp_evolution = []
     cpu_selected_moves = []
     cpu_damage_done = []
+    zero_damage_counter = 0
+    zero_damage_max_turns = 10
     while battle_active:
+        #print(f"Starting battle turn {battle_turns_num + 1}")
         player_move_name = random.choice(active_pokemon.get_moves())
         player_selected_moves.append(player_move_name)
         #print(f"{active_pokemon.name} selected {player_move_name} to use against {cpu_active_pokemon.name}:\n")
         try:
-            player_damage_done_value = active_pokemon.useMove(player_move_name,cpu_active_pokemon)
-
+            player_damage_done_value = active_pokemon.useMove(player_move_name,cpu_active_pokemon,game_status='new_random_battle')
+            if player_damage_done_value == 0:
+                zero_damage_counter += 1
+            else:
+                zero_damage_counter = 0
+            #print(f"Player did {player_damage_done_value} damage with {player_move_name}")
             player_damage_done.append(player_damage_done_value)
             player_hp_evolution.append(active_pokemon.get_current_hp())
             cpu_hp_evolution.append(cpu_active_pokemon.get_current_hp())
@@ -58,7 +242,11 @@ def RandomBattle(trainer,cpu_trainer):
             #print(f"CPU's {cpu_active_pokemon.name} is using {cpu_active_pokemon_selected_move_name} against your {active_pokemon.name}!")
             cpu_selected_moves.append(cpu_active_pokemon_selected_move_name)
 
-            cpu_damage_done_value = cpu_active_pokemon.useMove(cpu_active_pokemon_selected_move_name, active_pokemon)
+            cpu_damage_done_value = cpu_active_pokemon.useMove(cpu_active_pokemon_selected_move_name, active_pokemon,game_status='new_random_battle')
+            if cpu_damage_done_value == 0:
+                zero_damage_counter += 1
+            else:
+                zero_damage_counter = 0
 
             cpu_damage_done.append(cpu_damage_done_value)
             player_hp_evolution.append(active_pokemon.get_current_hp())
@@ -67,7 +255,7 @@ def RandomBattle(trainer,cpu_trainer):
 
             #update the player pokemon list
             trainer.update_pokemon_list(active_pokemon)
-            #check if the player has been defeated
+            
             if not trainer.active_pokemon_can_battle():
                 #print(f"Your {active_pokemon.name} has been defeated!")
                 if not trainer.can_battle():
@@ -76,12 +264,16 @@ def RandomBattle(trainer,cpu_trainer):
                     battle_active = False
                     break
                 else:
-                    #print("You have other Pokemons that can battle!")
+                    print("You have other Pokemons that can battle!")
                     continue
-
+            if zero_damage_counter >= zero_damage_max_turns:
+                print("Zero damage detected for too many consecutive turns. Ending battle.")
+                battle_active = False
+                did_player_won = False
+                break
         except ValueError as e:
             print(e)
-
+    flag_1 = True
     #manage those cases for which the player wins in the first turn and the cpu does not play any turn
     if len(player_damage_done) == 0:
         player_damage_done = [0]
@@ -116,112 +308,6 @@ def RandomBattle(trainer,cpu_trainer):
     }
     return battle_results
 
-def Main(starter_choice,Nbattles):
-    try:
-        starter_name = starter_choice
-        trainer = Trainer(name='edo', starter_name=starter_name)
-        #print(f"{trainer.name} has chosen {trainer.starter} as their starter Pokemon!")
-        #print("Adding potions and pokeballs to your inventory...")
-        trainer.items = {"potions": 10, "pokeball": 10}
-        #print("Your character is ready!")
-        #print(f"Welcome {trainer.name}! Your adventure begins now!")
-    except ValueError as e:
-        print(e)
-        print("Something went wrong!")
-
-    game_active_flag = True
-    while game_active_flag:
-        all_battle_results = []
-        for i in range(0,Nbattles):
-            #print("You entered the Random Battle mode")
-            #print("Battle #",i)
-            cpu_trainer = Trainer(name='CPU',starter_name=gd.pokemons_df.index[random.randint(0,len(gd.pokemons_df.index)-1)],is_CPU=True)
-            battle_results = RandomBattle(trainer,cpu_trainer)
-            all_battle_results.append(battle_results)
-            heal_flag = 'yes'
-            if heal_flag == 'yes':
-                for pokemon in trainer.pokemon_list:
-                    pokemon.curr_hp = pokemon.baseStats['hp']
-                #print("All your Pokemon have been healed!")
-
-        game_active_flag = False
-        #save all battle results
-        return all_battle_results
-
-def make_plots(Ngames,Nbattles):
-    files_to_analyze = os.listdir('results/')
-
-    avg_damage_per_level = dict()
-    for file_name in files_to_analyze:
-        pickle_in = open(f"results/{file_name}",'rb')
-        all_battle_results = pickle.load(pickle_in)
-        pickle_in.close()
-        for battle_result in all_battle_results:
-            player_pokemon = battle_result['player_pokemon']
-            player_pokemon_name = player_pokemon.name
-            player_pokemon_level = player_pokemon.level
-            player_avg_damage_done = battle_result['turn_history']['player_history']['player_avg_damage_done']
-
-            if player_pokemon_name not in avg_damage_per_level:
-                avg_damage_per_level[player_pokemon_name] = {}
-            if player_pokemon_level not in avg_damage_per_level[player_pokemon_name]:
-                avg_damage_per_level[player_pokemon_name][player_pokemon_level] = []
-            avg_damage_per_level[player_pokemon_name][player_pokemon_level].append(player_avg_damage_done)
-    for pokemon_name in avg_damage_per_level:
-        for level in avg_damage_per_level[pokemon_name]:
-            avg_damage_per_level[pokemon_name][level] = np.mean(avg_damage_per_level[pokemon_name][level])
-
-    for pokemon_name in avg_damage_per_level:
-        levels = list(avg_damage_per_level[pokemon_name].keys())
-        avg_damages = list(avg_damage_per_level[pokemon_name].values())
-        plt.figure(figsize=(12, 6))
-        plt.bar(levels, avg_damages)
-        plt.xlabel('Pokemon Level')
-        plt.ylabel('Average Damage Done')
-        plt.title(f'Average Damage Done per battle turn for {pokemon_name}')
-        plt.xticks(rotation=45)
-        plt.tight_layout()
-        plt.savefig(f'plots/average_damage_per_turn_{pokemon_name}.pdf')
-       
-    #pie chart
-    available_pokemon_type_distribution = {}
-    for pokemon_name in gd.pokemons_dict:
-        pokemon_types = gd.pokemons_dict[pokemon_name]['types']
-        for pokemon_type in pokemon_types:
-            if pokemon_type not in available_pokemon_type_distribution:
-                available_pokemon_type_distribution[pokemon_type] = 0
-            available_pokemon_type_distribution[pokemon_type] += 1
-
-    encountered_pokemon_types = {}
-    for file_name in files_to_analyze:
-        pickle_in = open(f"results/{file_name}",'rb')
-        all_battle_results = pickle.load(pickle_in)
-        pickle_in.close()
-        for battle_result in all_battle_results:
-            encountered_pokemon = battle_result['encountered_pokemon']
-            encountered_pokemon_types_list = encountered_pokemon.types
-            for pokemon_type in encountered_pokemon_types_list:
-                if pokemon_type not in encountered_pokemon_types:
-                    encountered_pokemon_types[pokemon_type] = 0
-                encountered_pokemon_types[pokemon_type] += 1
-
-    quantities = list(encountered_pokemon_types.values())
-    labels = list(encountered_pokemon_types.keys())
-    plt.figure(figsize=(12, 6))
-    plt.subplot(1, 2, 1)
-    plt.pie(quantities, labels=labels, autopct='%1.1f%%', startangle=140)
-    plt.title('Distribution of Encountered Pokemon Types')
-    plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle
-
-    plt.subplot(1, 2, 2)
-    quantities_base = list(available_pokemon_type_distribution.values())
-    labels_base = list(available_pokemon_type_distribution.keys())
-    plt.pie(quantities_base, labels=labels_base, autopct='%1.1f%%', startangle=140)
-    plt.title('Distribution of Available Pokemon Types')
-    plt.axis('equal')
-
-    plt.savefig('plots/pokemon_types_distribution.pdf')
-    
 def build_dataset():
     all_pokemon_types = list(gd.available_types)
     player_ActStats_labels = ["player_hp", "player_attack", "player_defense", "player_speed", "player_special"]
@@ -229,39 +315,48 @@ def build_dataset():
     opponent_ActStats_labels = ["opponent_hp", "opponent_attack", "opponent_defense", "opponent_speed", "opponent_special"]
     opponent_type_label = ['opponent_type_' + t for t in all_pokemon_types]
 
-    #define a padas dataframe to store the dataset
+    #define a pandas dataframe to store the dataset
     dataset_column_labels = player_ActStats_labels + player_type_label + opponent_ActStats_labels + opponent_type_label + ['battle_result'] 
+    
+    if os.path.exists('dataset.csv'):
+        return dataset_column_labels
+
     dataset = pd.DataFrame(columns=dataset_column_labels)
-
     files_to_analyze = os.listdir('results/')
-    dataset_row = []
-    for file_name in files_to_analyze:
-        pickle_in = open(f"results/{file_name}",'rb')
-        all_battle_results = pickle.load(pickle_in)
-        pickle_in.close()
+    dataset_rows = []
+    num_of_files = len(files_to_analyze)
+    for i, file_name in enumerate(files_to_analyze):
+        print(f"Processing file {i + 1}/{num_of_files}: {file_name}")
+
+        with open(f"results/{file_name}", "rb") as pickle_in:
+            all_battle_results = pickle.load(pickle_in)
+
         for battle_result in all_battle_results:
-            player_pokemon_ActStats = list(battle_result['player_pokemon'].ActStats.values())
-            player_pokemon_type = battle_result['player_pokemon'].types
-            player_pokemon_type_encoded = [1 if t in player_pokemon_type else 0 for t in all_pokemon_types]
-            opponent_pokemon = list(battle_result['encountered_pokemon'].ActStats.values())
-            opponent_pokemon_type = battle_result['encountered_pokemon'].types
-            opponent_pokemon_type_encoded = [1 if t in opponent_pokemon_type else 0 for t in all_pokemon_types]
-            battle_result_integer = 1 if battle_result['result'] else 0
-            dataset_row = player_pokemon_ActStats + player_pokemon_type_encoded + opponent_pokemon + opponent_pokemon_type_encoded + [battle_result_integer]
-            #append the row to the dataset
-            dataset.loc[len(dataset)] = dataset_row
+            player_pokemon = battle_result["player_pokemon"]
+            opponent_pokemon = battle_result["encountered_pokemon"]
+
+            player_stats = list(player_pokemon.ActStats.values())
+            player_types = [
+                int(pokemon_type in player_pokemon.types)
+                for pokemon_type in all_pokemon_types
+            ]
+            opponent_stats = list(opponent_pokemon.ActStats.values())
+            opponent_types = [
+                int(pokemon_type in opponent_pokemon.types)
+                for pokemon_type in all_pokemon_types
+            ]
+            result = int(battle_result["result"])
+
+            dataset_rows.append(
+                player_stats + player_types + opponent_stats + opponent_types + [result]
+            )
+
+    dataset = pd.DataFrame(dataset_rows, columns=dataset_column_labels)
+    dataset.to_csv("dataset.csv", index=False)
 
-    #save the dataset to a csv file
-    dataset.to_csv('dataset.csv', index=False)
     return dataset_column_labels
 
 def train_model(dataset_column_labels):
-    from sklearn.model_selection import train_test_split
-    from sklearn.ensemble import RandomForestClassifier
-    from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
-    from sklearn.model_selection import RandomizedSearchCV
-    from scipy.stats import randint
-
     dataset_labels = dataset_column_labels[:-1]
     # Load the dataset
     dataset = pd.read_csv('dataset.csv')
@@ -276,13 +371,14 @@ def train_model(dataset_column_labels):
     # Create a Random Forest Classifier
     model = RandomForestClassifier()
     param_dist = {
-        'n_estimators': randint(50, 500),
-        'max_depth': randint(1, 20),
+        'n_estimators': randint(30, 300),
+        'max_depth': randint(2, 30),
     }
 
+    #RandomizedSearchCV is used for parameter tuning.
     rand_search = RandomizedSearchCV(model,
-                                     param_distributions=param_dist,
-                                     n_iter=5, cv=5).fit(X_train, y_train)
+                                    param_distributions=param_dist,
+                                    n_iter=7, cv=5, n_jobs=3).fit(X_train, y_train)
 
     # Train the model
     best_model = rand_search.best_estimator_
@@ -299,8 +395,6 @@ def train_model(dataset_column_labels):
     print("Confusion Matrix:")
     print(confusion_matrix(y_test, y_pred))
 
-    from sklearn.tree import export_graphviz
-    import graphviz
     # Visualize the first three estimators
     for i in range(3):
         tree = best_model.estimators_[i]
@@ -313,23 +407,189 @@ def train_model(dataset_column_labels):
         graph = graphviz.Source(dot_data)
         graph.render(outfile=f"plots/tree_{i}.pdf", format='pdf')
 
-    return best_model
+    # Save the trained model
+    joblib.dump(best_model, 'trained_model.joblib')
+
+def MainRandomBattle(starter_choice,Nbattles):
+    try:
+        starter_name = starter_choice
+        trainer = Trainer(name='trainer', starter_name=starter_name)
+        trainer.items = {"potions": 10, "pokeball": 10}
+    except ValueError as e:
+        print(e)
+        print("Something went wrong!")
+
+    game_active_flag = True
+    while game_active_flag:
+        all_battle_results = []
+        for i in range(0,Nbattles):
+            cpu_trainer = Trainer(name='CPU',starter_name=gd.pokemons_df.index[random.randint(0,len(gd.pokemons_df.index)-1)],is_CPU=True)
+            battle_results = RandomBattle(trainer,cpu_trainer)
+            all_battle_results.append(battle_results)
+            heal_flag = 'yes'
+            if heal_flag == 'yes':
+                for pokemon in trainer.pokemon_list:
+                    pokemon.curr_hp = pokemon.baseStats['hp']
+
+        game_active_flag = False
+        #save all battle results
+        return all_battle_results
+
+def Main():
+    global game_status
+    global game_active_flag
+    player_created_flag = False
+    while not player_created_flag:
+        try:
+            trainer_name = input("Enter your trainer name: ")
+            print("Available starter Pokemon: ", gd.available_starter_names)
+            starter_name = input("Choose your starter Pokemon: ")
+            trainer = Trainer(name=trainer_name, starter_name=starter_name)
+            print(f"{trainer.name} has chosen {trainer.starter} as their starter Pokemon!")
+            print("Adding potions and pokeballs to your inventory...")
+            trainer.items = {"potions": 10, "pokeball": 10}
+            print("Your character is ready!")
+            #trainer.print_trainer_info()
+            player_created_flag = True
+            print(f"Welcome {trainer.name}! Your adventure begins now!")
+        except ValueError as e:
+            print(e)
+            print("Please try again...")
+            continue
+
+    while game_active_flag:
+        if game_status == 'story':
+            print("Type the number of one of the following actions:")
+            print("1) Explore ")
+            print("2) Pokemon Center")
+            print("3) Pokemon Store")
+            print("4) Show trainer data")
+            print("5) NewRandomBattle")
+            print("6) Exit")
+
+            try:
+                action = int(input("Choose an action (1-6): ").strip())
+            except ValueError:
+                print("Invalid input. Please enter a number between 1 and 6.")
+                continue
+            if action == 1:
+                game_status = 'explore'
+            elif action == 2:
+                game_status = 'pokemon_center'
+            elif action == 3:
+                game_status = 'pokemon_store'
+            elif action == 4:
+                print("Showing trainer data:")
+                trainer.print_trainer_info()
+            elif action == 5:
+                confirm=input("Are you sure you want to start a new random battle? This will generate data and train the model. Type 'yes' to continue: ")
+                if confirm.lower() == 'yes':
+                    print("Starting a new random battle!")
+                    game_status = 'new_random_battle'
+                else:
+                    print("Cancelled starting a new random battle.")
+            elif action == 6:
+                print("Exiting the game. Goodbye!")
+                game_active_flag = False
+            else:
+                print("Invalid action. Please choose again.")
+
+        elif game_status == 'explore':
+            print("You are exploring")
+            battle_prob = random.uniform(0, 1)
+            #print(f"Battle probability: {battle_prob:.2f}")
+            if battle_prob < 0.8:
+                cpu_trainer = Trainer(name='CPU',starter_name=gd.pokemons_df.index[random.randint(0,len(gd.pokemons_df.index)-1)],is_CPU=True)
+                print(f"A wild {cpu_trainer.get_active_pokemon().name} appeared!")
+                
+                #print(cpu_trainer.get_active_pokemon().print_pokemon_info())
+                game_status = 'battle'
+                #before entering the battle, we predict the win probability of
+                #each of the player's pokemon against the opponent's pokemon
+                try:
+                    win_probs = []
+                    for pokemon in trainer.pokemon_list:
+                        win_prob = recommend(player_pokemon=pokemon, opponent_pokemon=cpu_trainer.get_active_pokemon())
+                        win_probs.append(win_prob)
+                        print(f"The Oracle predicts {pokemon.name} to have {win_prob:.2f} of chances to win.")
+                    #if all the win probabilities are below 0.5, we suggest the player to run away
+                    if all(prob < 0.5 for prob in win_probs):
+                        print("The Oracle suggests to RUN AWAY!")
+                    else:
+                        if len(win_probs) > 1:
+                            #find the pokemon with the highest win probability
+                            best_pokemon_index = win_probs.index(max(win_probs))
+                            best_pokemon = trainer.pokemon_list[best_pokemon_index]
+                            print(f"The Oracle suggests to use {best_pokemon.name}!")
+                except ValueError as e:
+                    print("HINT: Unlock access to the Oracle by playing NewRandomBattle!") 
+
+                Battle(trainer,cpu_trainer)
+            else:
+                print('-'*30)
+                print("No wild Pokemon appeared.")
+                game_status = 'story'
+                
+        elif game_status == 'pokemon_center':
+            print("You are at the Pokemon Center. You can heal your Pokemon here.")
+            heal_flag = input("Type 'yes' to heal your Pokemons or any other key to exit: ").strip().lower()
+            if heal_flag == 'yes':
+                for pokemon in trainer.pokemon_list:
+                    pokemon.curr_hp = pokemon.baseStats['hp']
+                    for move in pokemon.moves_dict.keys():
+                        pokemon.moves_dict[move]['pp'] = copy.deepcopy(gd.available_moves_df.loc[move]['pp'])
+                print("All your Pokemon have been healed!")
+                game_status = 'story'
+            else:
+                print("You exited the Pokemon Center.")
+                game_status = 'story'
+            # Add Pokemon Center logic here
+        
+        elif game_status == 'pokemon_store':
+            print("You are in the Pokemon Store. You can buy items here.")
+            restore_items_flag = input("Type 'yes' to restore your items: ").strip().lower()
+            if restore_items_flag == 'yes':
+                trainer.items = {"potions": 10, "pokeball": 10}
+                print("Your items have been restored!")
+                game_status = 'story'
+            else:
+                print("You exited the Pokemon Store.")
+                game_status = 'story'
+
+        elif game_status == 'new_random_battle':
+            Ngames = 1000
+            Nbattles = 500
+            print("Generating data...")
+            #generate battle data only if the dataset.csv does not exist
+            if not os.path.exists('dataset.csv'):
+                for i in range(Ngames):
+                    starter_choice = gd.pokemons_df.index[random.randint(0,len(gd.pokemons_df.index)-1)]
+                    print(f"Generating data for {starter_choice}, game {i}...")
+                    results = MainRandomBattle(starter_choice=starter_choice, Nbattles=Nbattles)
+                    pickle_out = open(f"results/{starter_choice}_game_{i}_{Nbattles}_battles.pickle",'wb')
+                    pickle.dump(results,pickle_out)
+                    pickle_out.close()
+        
+            print("Setting up the dataset...")
+            dataset_column_labels = build_dataset()
+            try:
+                print("Training model...")
+                train_model(dataset_column_labels)
+                print("Model has been trained! Ending NewRandomBattle")
+                global recommender_sys_avail
+                recommender_sys_avail = True
+            except Exception as e:
+                print(f"An error occurred during model training: {e}")
+                print("Ending NewRandomBattle without training the model.")
+            game_status = 'story'
+
+        else:
+            print("Unknown game status. Try again.")
 
 if __name__ == "__main__":
-    Ngames = 10
-    Nbattles = 5
-    print("Generating data")
-    for i in range(Ngames):
-        starter_choice = gd.pokemons_df.index[random.randint(0,len(gd.pokemons_df.index)-1)]
-        #print(f"Generating data for {starter_choice}, game {i}...")
-        results = Main(starter_choice = starter_choice, Nbattles=Nbattles)
-        pickle_out = open(f"results/{starter_choice}_game_{i}_{Nbattles}_battles.pickle",'wb')
-        pickle.dump(results,pickle_out)
-        pickle_out.close()
+    if not os.path.exists('results'):
+        os.makedirs('results')
+    if not os.path.exists('plots'):
+        os.makedirs('plots')
 
-    print("Generating dataset")
-    dataset_column_labels = build_dataset()
-    print("Training model")
-    best_model = train_model(dataset_column_labels)
-    joblib.dump(best_model, 'trained_model.joblib')
-    print("Ended")
+    Main()