def testChaoticNeuralNetwork3DVisualization(self): stimulus = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE11) network_instance = cnn_network(len(stimulus)) output_dynamic = network_instance.simulate(10, stimulus) network_instance.show_network() cnn_visualizer.show_dynamic_matrix(output_dynamic) cnn_visualizer.show_observation_matrix(output_dynamic) cnn_visualizer.show_output_dynamic(output_dynamic)
def testChaoticNeuralNetwork3DVisualization(self): stimulus = read_sample(SIMPLE_SAMPLES.SAMPLE_SIMPLE11); network_instance = cnn_network(len(stimulus)); output_dynamic = network_instance.simulate(10, stimulus); network_instance.show_network(); cnn_visualizer.show_dynamic_matrix(output_dynamic); cnn_visualizer.show_observation_matrix(output_dynamic); cnn_visualizer.show_output_dynamic(output_dynamic);
def template_dynamic_cnn(num_osc, steps, stimulus, neighbors, connection, show_network = False): network_instance = cnn_network(num_osc, connection, amount_neighbors = neighbors); output_dynamic = network_instance.simulate(steps, stimulus); print(output_dynamic.allocate_sync_ensembles(10)); if (show_network is True): network_instance.show_network(); cnn_visualizer.show_output_dynamic(output_dynamic); cnn_visualizer.show_dynamic_matrix(output_dynamic); cnn_visualizer.show_observation_matrix(output_dynamic);
def template_dynamic_cnn(num_osc, steps, stimulus, neighbors, connection, show_network = False): network_instance = cnn_network(num_osc, connection, amount_neighbors = neighbors); output_dynamic = network_instance.simulate(steps, stimulus); print(output_dynamic.allocate_sync_ensembles(10)); if (show_network is True): network_instance.show_network(); cnn_visualizer.show_output_dynamic(output_dynamic); cnn_visualizer.show_dynamic_matrix(output_dynamic); cnn_visualizer.show_observation_matrix(output_dynamic);