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', :])
