Merge branch 'main' of https://github.com/CogitoNTNU/NEATtactics

gui_with_pygame.py

@@ -125,14 +125,13 @@ def __init__(self, x, y, width, height, items, font, text_color, bg_color, selec
         self.scroll_offset = 0  # This tracks where we are in the list
         self.padding = padding  # Distance between items
         # Create a base list of items without positioning them
-        print(items[0])
+
         self.list_items = [
             SelectableListItem(
                 x, y, width, (height - (visible_count - 1) * padding) // visible_count,  # Adjust height to account for padding
-
                 genome_id=item[1], fitness=item[0].fitness_value, font=font, text_color=text_color, 
                 bg_color=bg_color, selected_color=selected_color
-            ) for item in items
+            ) for item in self.items
         ]
 
     def draw(self, screen):
@@ -171,6 +170,12 @@ def handle_event(self, event):
                 self.scroll("up")
             elif event.y < 0:
                 self.scroll("down")
+
+
+    def get_selected_genomes(self):
+        # Return a list of selected genome IDs
+        print(f"Item: {self.items[0]}")
+        return [item[1] for item in self.items if item[0].selected]
 
 
 class GenomeViewer:
@@ -445,7 +450,7 @@ def __init__(self):
         ## Genome viewer
         self.genome_viewer = GenomeViewer(self.genomes, st.normal_font, st.text_color, st.input_field_bg, st.input_field_active_bg)
 
-        self.watch_genes_visualize = ImageSprite("data/genome_frames/genome_0.png", (600, 100), (600, 400))
+        self.watch_genes_visualize = ImageSprite("data/latest/genome_frames/genome_0.png", (600, 100), (600, 400))
 
         ## Run button
         self.run_button = Button(600, 20, 200, 50, "Run Selected Genomes", st.normal_font, st.text_color, st.button_color, st.hover_color, st.pressed_color, self.run_selected_genomes)
@@ -498,7 +503,7 @@ def visualize_genome_scene(self):
 
     def run_selected_genomes(self):
         # Get the selected genome IDs and run them
-        selected_genomes = self.genome_viewer.get_selected_genomes()
+        selected_genomes = self.scrollable_list.get_selected_genomes()
 
         print(f"Running genomes: {selected_genomes}")
         # Add logic here to execute the selected genomes (e.g., visualize, simulate, etc.)

main.py

@@ -1,7 +1,7 @@
 from src.environments.debug_env import env_debug_init, run_game_debug
 from src.utils.config import Config
 from src.genetics.NEAT import NEAT
-from src.utils.utils import read_fitness_file, save_fitness, save_best_genome, load_best_genome, save_neat, load_neat, save_fitness_graph_file
+from src.utils.utils import read_fitness_file, save_fitness, save_best_genome, load_best_genome, save_neat, load_neat, save_fitness_graph_file, get_latest_generation
 import warnings
 import cProfile
 import pstats
@@ -10,29 +10,28 @@
 warnings.filterwarnings("ignore", category=UserWarning, message=".*Gym version v0.24.1.*")
 
 def play_genome(args):
-    neat_name = "latest"
-    if args.neat_name != '':
-        neat_name = args.neat_name
+    neat_name = args.neat_name if args.neat_name != '' else 'latest'
 
     if args.to_gen is not None:
-        to_gen = args.to_gen
-        if args.from_gen is not None:
-            from_gen = args.from_gen
-        else:
-            from_gen = 0
-        test_genome(from_gen, to_gen, neat_name)
+        from_gen = args.from_gen if args.from_gen is not None else 0
+        test_genome(from_gen, args.to_gen, neat_name)
+        return
+
+    if args.from_gen is not None:
+        latest_gen = get_latest_generation(neat_name)
+        test_genome(args.from_gen, latest_gen, neat_name)
+        return
 
-    generation_num = args.generation if args.generation is not None else -1
-    genome = load_best_genome(generation_num, neat_name)
+    genome = load_best_genome(args.generation if args.generation is not None else -1, neat_name)
     env, state = env_debug_init()
-    run_game_debug(env, state, genome, 0, visualize=True)
+    run_game_debug(env, state, genome, neat_name, visualize=True)
 
 def test_genome(from_gen: int, to_gen: int, neat_name: str):
     for i in range(from_gen, to_gen + 1):
         print(f"Testing genome {i}...")
         genome = load_best_genome(i, neat_name)
         env, state = env_debug_init()
-        fitness = run_game_debug(env, state, genome, i)
+        fitness = run_game_debug(env, state, genome, neat_name)
         print(fitness)
 
 def collect_fitnesses(genomes, generation, min_fitnesses, avg_fitnesses, best_fitnesses, neat_name):

src/environments/debug_env.py

@@ -24,7 +24,7 @@ def env_debug_init() -> Tuple[MarioJoypadSpace, np.ndarray]:
     state = env.reset() # Good practice to reset the env before using it.
     return env, state
 
-def run_game_debug(env: MarioJoypadSpace, initial_state: np.ndarray, genome: Genome, num: int, visualize: bool = True) -> float:
+def run_game_debug(env: MarioJoypadSpace, initial_state: np.ndarray, genome: Genome, neat_name: str, visualize: bool = True) -> float:
 
     forward = Traverse(genome)
     fitness = Fitness()
@@ -40,8 +40,8 @@ def run_game_debug(env: MarioJoypadSpace, initial_state: np.ndarray, genome: Gen
         env.render()
         # timeout = 600 + sr.info["x_pos"]
         if visualize and i % 10000 == 0:
-            save_state_as_png(0, sr.state)
-            visualize_genome(genome, 0)
+            save_state_as_png(i, sr.state, neat_name)
+            visualize_genome(genome, neat_name, i)
 
         fitness.calculate_fitness(sr.info, action)
 

src/genetics/NEAT.py

@@ -217,18 +217,14 @@ def check_individual_impovements(self):
                     print("Best specie is not removed")
                     break
                 print("Specie has stagnated, removing it!")
-                self.species.remove(specie)
-                # TODO: Ludvig, kan du forklare hvorfor det er sånn? En liten specie som er shit burde vel ikke overleve videre?
-                # Bare slett kommentarene hvis det ikke skal være der.
-                """
+
                 if len(self.species) > 2:
                     self.species.remove(specie)
                 else:
                     # if there are only two species left, reset their imrovement counters
                     self.improvement_counter = 0
                     for specie in self.species:
                         specie.improvement_counter = 0
-                """
         if self.species == []:
             print("All species have been removed - RIP")
             self.initiate_genomes()

src/utils/utils.py

@@ -14,12 +14,12 @@
     # These imports will only be used for type hinting, not at runtime
     from src.genetics.NEAT import NEAT
 
-def save_state_as_png(i, state: np.ndarray) -> None:
+def save_state_as_png(i, state: np.ndarray, neat_name: str) -> None:
     """Save a frame."""
-    directory = "./data/mario_frames"
+    directory = f"./data/{neat_name}/mario_frames"
     if not os.path.exists(directory):
         os.makedirs(directory)
-    plt.imsave(f"./data/mario_frames/frame{i}.png", state, cmap='gray', vmin=0, vmax=1)
+    plt.imsave(f"{directory}/frame{i}.png", state, cmap='gray', vmin=0, vmax=1)
 
 def normalize_positive_values(positive_vals: np.ndarray) -> None:
     """Takes an ndarray with positive floats as inputs,
@@ -61,22 +61,20 @@ def save_best_genome(genome: Genome, generation: int, name: str):
     with open(f'{path}/best_genome_{generation}.obj', 'wb') as f:
         pickle.dump(genome, f) # type: ignore
 
+def get_latest_generation(name: str) -> int:
+    """Finds the latest generation number from saved genomes for a given NEAT name."""
+    files = os.listdir(f'data/{name}/good_genomes')
+    pattern = re.compile(r'best_genome_(\d+).obj')
+    generations = [int(match.group(1)) for file in files if (match := pattern.match(file))]
+    if not generations:
+        raise FileNotFoundError("No valid genome files found in 'data/good_genomes'.")
+    return max(generations)
+
 def load_best_genome(generation: int, name: str) -> Genome:
-    """Loads the best genome from the given generation. If -1 is passed as argument, the latest generation is displayed."""
-    if generation == -1: # Find the genome from the latest generation.
-        files = os.listdir(f'data/{name}/good_genomes')
-        pattern = re.compile(r'best_genome_(\d+).obj')
-        generations = []
-        for file in files:
-            match = pattern.match(file)
-            if match:
-                generations.append(int(match.group(1)))
-        if generations:
-            generation = max(generations)
-            print("Loading best genome from generation:", generation)
-        else:
-            raise FileNotFoundError("No valid genome files found in 'data/good_genomes'.")
-
+    """Loads the best genome from a given generation or the latest if -1 is provided."""
+    if generation == -1:
+        generation = get_latest_generation(name)
+        print(f"Loading best genome from generation: {generation}")
     with open(f'data/{name}/good_genomes/best_genome_{generation}.obj', 'rb') as f:
         return pickle.load(f)
 

src/visualization/visualize_genome.py

@@ -52,7 +52,7 @@ def add_labels_to_output_nodes(pos_dict: Dict[int, Tuple[float, float]], genome:
         ax.text(x, y + 0.50, '+'.join(movement_list[output_node.id]), fontsize=10, fontweight='bold', color='blue')  # Add label to the right    
 
 
-def visualize_genome(genome: Genome, frame_number: int):
+def visualize_genome(genome: Genome, neat_name: str, frame_number: int):
     fig = plt.figure(figsize=(15, 10))
     ax = fig.add_subplot(111)
 
@@ -88,10 +88,10 @@ def visualize_genome(genome: Genome, frame_number: int):
 
     plt.xlim(GRAPH_XMIN, GRAPH_XMAX)
     plt.ylim(GRAPH_YMIN, GRAPH_YMAX)
-    directory = "./data/genome_frames"
+    directory = f"./data/{neat_name}/genome_frames"
     if not os.path.exists(directory):
         os.makedirs(directory)
-    plt.savefig(f'./data/genome_frames/genome_{frame_number}.png')
+    plt.savefig(f'{directory}/genome_{frame_number}.png')
     plt.close()
 
 

test/visualization/visualize_genome_test.py

@@ -33,4 +33,4 @@ def test_visualize_genome():
     set_input_node_values(state, genome.nodes)
     traverse = Traverse(genome)
     traverse.traverse()
-    visualize_genome(genome, -1)
+    visualize_genome(genome, "test", -1)