68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
import itertools
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import matplotlib.pyplot as plt
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import networkx as nx
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import numpy as np
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from genome import Genome, NodeType, mutate
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def _find_layer(g: nx.DiGraph, hidden_node: int, inputs: list[int]) -> int:
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paths = []
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for input_node in inputs:
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paths += list(nx.all_simple_paths(g, input_node, hidden_node))
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path_lengths = [len(path) for path in paths]
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return max(path_lengths)
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def genome(genome: Genome):
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graph = nx.DiGraph()
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# Add nodes
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for node in genome.nodes.keys():
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graph.add_node(node)
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# Add edges
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for connection in genome.connections.values():
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if connection.disabled:
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continue
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from_node, to_node = connection.nodes
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graph.add_edge(from_node, to_node, weight=connection.weight)
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inputs = [node.id for node in genome.nodes.values() if node.type == NodeType.INPUT]
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hidden = [node.id for node in genome.nodes.values() if node.type == NodeType.HIDDEN]
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outputs = [node.id for node in genome.nodes.values() if node.type == NodeType.OUTPUT]
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for input_node in inputs:
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graph.nodes[input_node]["layer"] = 0
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max_layer = 1
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for hidden_node in hidden:
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layer = _find_layer(graph, hidden_node, inputs)
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max_layer = max(layer, max_layer)
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graph.nodes[hidden_node]["layer"] = layer
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for output_node in outputs:
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graph.nodes[output_node]["layer"] = max_layer + 1
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plt.subplot()
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pos = nx.multipartite_layout(graph, subset_key="layer")
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nx.draw_networkx_nodes(graph, pos, nodelist=inputs, label=inputs, node_color="#ff0000")
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nx.draw_networkx_nodes(graph, pos, nodelist=hidden, label=hidden, node_color="#00ff00")
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nx.draw_networkx_nodes(graph, pos, nodelist=outputs, label=outputs, node_color="#0000ff")
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nx.draw_networkx_edges(graph, pos)
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if __name__ == "__main__":
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g1 = Genome.new(3, 2)
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g1.add_connection(0, 4, 0.5)
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mutate(g1)
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mutate(g1)
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mutate(g1)
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# mutate(g1)
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genome(g1)
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plt.show()
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