neural_network_plot_dinamico.py

neural_network_plot_dinamico.py

import networkx as nx
import matplotlib.pyplot as plt

def plot_neural_network(entrada, oculta, saida):
    G = nx.DiGraph()

    G.add_nodes_from([f'Entrada{i+1}' for i in range(entrada)])
    G.add_nodes_from([f'Oculta{i+1}' for i in range(oculta)])
    G.add_nodes_from([f'Saida{i+1}' for i in range(saida)])

    for e in range(entrada):
        for h in range(oculta):
            G.add_edge(f'Entrada{e+1}', f'Oculta{h+1}')

    for h in range(oculta):
        for s in range(saida):
            G.add_edge(f'Oculta{h+1}', f'Saida{s+1}')

    pos = {}
    for i, node_type in enumerate(['Entrada', 'Oculta', 'Saida']):
        for j in range(eval(node_type.lower())):
            pos[f'{node_type}{j+1}'] = (i, j-(eval(node_type.lower())-1)/2)

    nx.draw(G, pos, with_labels=True, node_size=800, node_color='skyblue', font_weight='bold', font_size=10)
    plt.title('Representacao dos Neuronios da Rede Neural')
    plt.show()

# Exemplo de uso para 2 nós de entrada, 3 nós na camada oculta e 1 nó de saída
plot_neural_network(3, 4, 1)