def test_graph_to_conn_BaseConnectivity(self): g = nx.MultiDiGraph() g.add_nodes_from(['A:0', 'A:1', 'B:0', 'B:1', 'B:2']) g.add_edges_from([('A:0', 'B:1'), ('A:1', 'B:2')]) c = graph.graph_to_conn(g, base.BaseConnectivity) np.all(np.array([[0, 1, 0], [0, 0, 1]])==c['A', :, 'B', :])
def test_graph_to_conn_Connectivity(self): g = nx.MultiDiGraph() g.add_nodes_from(['A:0', 'A:1', 'B:0', 'B:1', 'B:2']) g.node['A:0']['neuron_type'] = 'gpot' g.node['A:1']['neuron_type'] = 'spike' g.node['B:0']['neuron_type'] = 'gpot' g.node['B:1']['neuron_type'] = 'gpot' g.node['B:2']['neuron_type'] = 'spike' g.add_edges_from([('A:0', 'B:1'), ('A:1', 'B:2')]) c = graph.graph_to_conn(g, core.Connectivity) np.all(np.array([[0, 1]]) == c['A', 'gpot', :, 'B', 'gpot', :]) np.all(np.array([[0]]) == c['A', 'gpot', :, 'B', 'spike', :]) np.all(np.array([[0, 0]]) == c['A', 'spike', :, 'B', 'gpot', :]) np.all(np.array([[1]]) == c['A', 'spike', :, 'B', 'spike', :])
def test_graph_to_conn_Connectivity(self): g = nx.MultiDiGraph() g.add_nodes_from(['A:0', 'A:1', 'B:0', 'B:1', 'B:2']) g.node['A:0']['neuron_type'] = 'gpot' g.node['A:1']['neuron_type'] = 'spike' g.node['B:0']['neuron_type'] = 'gpot' g.node['B:1']['neuron_type'] = 'gpot' g.node['B:2']['neuron_type'] = 'spike' g.add_edges_from([('A:0', 'B:1'), ('A:1', 'B:2')]) c = graph.graph_to_conn(g, core.Connectivity) np.all(np.array([[0, 1]])==c['A', 'gpot', :, 'B', 'gpot', :]) np.all(np.array([[0]])==c['A', 'gpot', :, 'B', 'spike', :]) np.all(np.array([[0, 0]])==c['A', 'spike', :, 'B', 'gpot', :]) np.all(np.array([[1]])==c['A', 'spike', :, 'B', 'spike', :])
id='lamina') man.add_mod(lpu_lam) (n_dict_med, s_dict_med) = LPU.lpu_parser('./data/medulla.gexf.gz') lpu_med = LPU(dt, n_dict_med, s_dict_med, output_file='medulla_output.h5', port_ctrl=man.port_ctrl, port_data=man.port_data, device=args.med_dev, id='medulla') man.add_mod(lpu_med) g = nx.read_gexf('./data/lamina_medulla.gexf.gz', relabel=True) conn_lam_med = graph_tools.graph_to_conn(g) man.connect(lpu_lam, lpu_med, conn_lam_med) (n_dict_int, s_dict_int) = LPU.lpu_parser('./data/integrate.gexf.gz') lpu_int = LPU(dt, n_dict_int, s_dict_int, output_file='integrate_output.h5', port_ctrl=man.port_ctrl, port_data=man.port_data, device=args.int_dev, id='integrate') # Configure inter-LPU connections between medulla and integration LPU # and between the antennal lobe and integration LPU: N_med_gpot = 3080 # number of public graded potential medulla neurons
n_dict_lam, s_dict_lam, input_file="./data/vision_input.h5", output_file="lamina_output.h5", port_ctrl=port_ctrl, port_data=port_data, device=args.lam_dev, id="lamina", ) man.add_mod(lpu_lam) (n_dict_med, s_dict_med) = lpu_parser("./data/medulla.gexf.gz") lpu_med = LPU( dt, n_dict_med, s_dict_med, output_file="medulla_output.h5", port_ctrl=port_ctrl, port_data=port_data, device=args.med_dev, id="medulla", ) man.add_mod(lpu_med) g = nx.read_gexf("./data/lamina_medulla.gexf.gz", relabel=True) conn_lam_med = graph_tools.graph_to_conn(g) man.connect(lpu_lam, lpu_med, conn_lam_med) man.start(steps=args.steps) man.stop()
dt, n_dict_med, s_dict_med, output_file="medulla_output.h5", port_ctrl=man.port_ctrl, port_data=man.port_data, device=dev2, id="medulla", debug=args.debug, ) print "medulla init done" lam = man.add_mod(lam) med = man.add_mod(med) graph = nx.read_gexf("./config_files/lamina_medulla.gexf", relabel=True) lam_med_conn = graph_tools.graph_to_conn(graph) man.connect(lam, med, lam_med_conn) man.start(steps=10001) man.join_modules() man.stop_brokers() """ The extra step is required as during the first step, only the initial states are passed between the modules. """
def test_graph_to_conn_BaseConnectivity(self): g = nx.MultiDiGraph() g.add_nodes_from(['A:0', 'A:1', 'B:0', 'B:1', 'B:2']) g.add_edges_from([('A:0', 'B:1'), ('A:1', 'B:2')]) c = graph.graph_to_conn(g, base.BaseConnectivity) np.all(np.array([[0, 1, 0], [0, 0, 1]]) == c['A', :, 'B', :])