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import numpy as np |
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from graphviz import Digraph |
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import os |
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import matplotlib.pyplot as plt |
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import matplotlib.colors as colors |
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"visualization functions" |
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def execute_program(program, input_grid) : |
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return program.evaluate(input_grid) |
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def save_tree_as_dot(program, filename): |
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dot = Digraph(comment='Program Tree') |
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def add_nodes_edges(node): |
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if node.children: |
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node_label = f"{node.value}\nID:{node.id}" |
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dot.node(str(node.id), node_label, shape='box', style='filled', color='lightblue') |
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else: |
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node_label = f"{node.value}\nID:{node.id}" |
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dot.node(str(node.id), node_label, shape='ellipse', style='filled', color='lightgreen') |
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for child in node.children: |
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dot.edge(str(node.id), str(child.id)) |
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add_nodes_edges(child) |
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add_nodes_edges(program) |
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dot.render(filename, view=False, format='png') |
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print(f"Program tree saved as {filename}.png") |
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def generate_composite_dot(all_generations, filename): |
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dot = Digraph(comment='All Programs Across Generations', graph_attr={'compound': 'true', 'rankdir': 'TB'}) |
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dot.attr(rankdir='TB') |
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for gen_idx, generation in enumerate(all_generations): |
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with dot.subgraph(name=f'cluster_gen_{gen_idx}') as c: |
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c.attr(label=f'Generation {gen_idx}') |
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c.attr(style='filled', color='lightgrey') |
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c.attr(rank='same') |
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for prog_idx, (program, fitness) in enumerate(generation.programs_with_fitness): |
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is_selected = program in generation.selected_programs |
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is_best = program == generation.best_program |
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if is_best: |
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node_color = 'gold' |
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node_shape = 'doublecircle' |
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elif is_selected: |
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node_color = 'orange' |
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node_shape = 'box' |
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else: |
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node_color = 'lightblue' |
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node_shape = 'ellipse' |
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def add_nodes_edges(node, parent_id: str = None): |
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label = f"{node.value}\nID:{node.id}" |
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dot.node(str(node.id), label, shape=node_shape, style='filled', color=node_color) |
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if parent_id: |
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dot.edge(parent_id, str(node.id)) |
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for child in node.children: |
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add_nodes_edges(child, str(node.id)) |
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add_nodes_edges(program) |
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output_path = dot.render(filename, view=False, format='png') |
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print(f"All programs across generations saved as {output_path}") |
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def plot_comparison(input_grid, expected_output, predicted_output, task_number): |
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fig, axs = plt.subplots(1, 3, figsize=(12, 4)) |
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fig.suptitle(f'Task {task_number}') |
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cmap = colors.ListedColormap(['#000000', '#0074D9', '#FF4136', '#2ECC40', '#FFDC00', '#AAAAAA', '#F012BE', '#FF851B', '#7FDBFF', '#870C25']) |
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norm = colors.Normalize(vmin=0, vmax=9) |
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axs[0].imshow(input_grid, cmap=cmap, norm=norm) |
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axs[0].set_title("Input Grid") |
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axs[1].imshow(expected_output, cmap=cmap, norm=norm) |
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axs[1].set_title("Expected Output") |
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axs[2].imshow(predicted_output, cmap=cmap, norm=norm) |
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axs[2].set_title("Predicted Output") |
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plt.tight_layout() |
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plt.show() |
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