def testConnectivity(self):
self.setUpNetwork(self.conn_dict)
# make sure all connections do exist
M = connect_test_base.get_connectivity_matrix(self.pop1, self.pop2)
connect_test_base.mpi_assert(M, np.identity(self.N), self)
# make sure no connections were drawn from the target to the source
# population
M = connect_test_base.get_connectivity_matrix(self.pop2, self.pop1)
connect_test_base.mpi_assert(M, np.zeros((self.N, self.N)), self)
def testTotalNumberOfConnections(self):
conn_params = self.conn_dict.copy()
self.setUpNetwork(conn_params)
total_conn = len(nest.GetConnections(self.pop1, self.pop2))
connect_test_base.mpi_assert(total_conn, self.Nconn, self)
# make sure no connections were drawn from the target to the source
# population
M = connect_test_base.get_connectivity_matrix(self.pop2, self.pop1)
M_none = np.zeros((len(self.pop1), len(self.pop2)))
connect_test_base.mpi_assert(M, M_none, self)
def testInputArrayToStdpSynapse(self):
params = ['Wmax', 'alpha', 'lambda', 'mu_minus', 'mu_plus', 'tau_plus']
syn_params = {'synapse_model': 'stdp_synapse'}
values = [np.arange(self.N1, dtype=float) for i in range(6)]
for i, param in enumerate(params):
syn_params[param] = values[i]
self.setUpNetwork(self.conn_dict, syn_params)
for i, param in enumerate(params):
a = connect_test_base.get_weighted_connectivity_matrix(
self.pop1, self.pop2, param)
connect_test_base.mpi_assert(np.diag(a), values[i], self)
def testAutapsesFalse(self):
conn_params = self.conn_dict.copy()
N = 10
# test that autapses were excluded
conn_params['p'] = 1. - 1. / N
conn_params['allow_autapses'] = False
pop = nest.Create('iaf_psc_alpha', N)
nest.Connect(pop, pop, conn_params)
M = connect_test_base.get_connectivity_matrix(pop, pop)
connect_test_base.mpi_assert(np.diag(M), np.zeros(N), self)
def testConnectivity(self):
self.setUpNetwork(self.conn_dict)
# make sure all connections do exist
M = connect_test_base.get_connectivity_matrix(self.pop1, self.pop2)
M_all = np.ones((len(self.pop2), len(self.pop1)))
connect_test_base.mpi_assert(M, M_all, self)
# make sure no connections were drawn from the target to the source
# population
M = connect_test_base.get_connectivity_matrix(self.pop2, self.pop1)
M_none = np.zeros((len(self.pop1), len(self.pop2)))
connect_test_base.mpi_assert(M, M_none, self)
def testInputArrayRPort(self):
syn_params = {}
neuron_model = 'iaf_psc_exp_multisynapse'
neuron_dict = {'tau_syn': [0.1 + i for i in range(self.N1)]}
self.pop1 = nest.Create(neuron_model, self.N1, neuron_dict)
self.pop2 = nest.Create(neuron_model, self.N1, neuron_dict)
self.param_array = np.arange(1, self.N1 + 1, dtype=int)
syn_params['receptor_type'] = self.param_array
nest.Connect(self.pop1, self.pop2, self.conn_dict, syn_params)
M = connect_test_base.get_weighted_connectivity_matrix(
self.pop1, self.pop2, 'receptor')
connect_test_base.mpi_assert(M, np.diag(self.param_array), self)
def testAutapsesFalse(self):
conn_params = self.conn_dict.copy()
N = 3
# test that autapses were excluded
conn_params['N'] = N * (N - 1)
conn_params['allow_autapses'] = False
pop = nest.Create('iaf_psc_alpha', N)
nest.Connect(pop, pop, conn_params)
# make sure all connections do exist
M = connect_test_base.get_connectivity_matrix(pop, pop)
connect_test_base.mpi_assert(np.diag(M), np.zeros(N), self)
def testAutapsesTrue(self):
conn_params = self.conn_dict.copy()
N = 10
conn_params['allow_multapses'] = False
# test that autapses exist
conn_params['p'] = 1.
conn_params['allow_autapses'] = True
pop = nest.Create('iaf_psc_alpha', N)
nest.Connect(pop, pop, conn_params)
# make sure all connections do exist
M = connect_test_base.get_connectivity_matrix(pop, pop)
connect_test_base.mpi_assert(np.diag(M), np.ones(N), self)
def testSymmetricFlag(self):
conn_dict_symmetric = self.conn_dict.copy()
conn_dict_symmetric['make_symmetric'] = True
self.setUpNetwork(conn_dict_symmetric)
M1 = connect_test_base.get_connectivity_matrix(self.pop1, self.pop2)
M2 = connect_test_base.get_connectivity_matrix(self.pop2, self.pop1)
# test that connections were created in both directions
connect_test_base.mpi_assert(
M1, np.transpose(connect_test_base.gather_data(M2)), self)
# test that no other connections were created
connect_test_base.mpi_assert(M1,
np.zeros_like(M1) + np.identity(self.N),
self)
def testMultapsesTrue(self):
conn_params = self.conn_dict.copy()
N = 3
conn_params['allow_autapses'] = True
# test that multapses were drawn
conn_params['indegree'] = N + 1
conn_params['allow_multapses'] = True
pop = nest.Create('iaf_psc_alpha', N)
nest.Connect(pop, pop, conn_params)
nr_conns = len(nest.GetConnections(pop, pop))
connect_test_base.mpi_assert(nr_conns, conn_params['indegree'] * N,
self)
def testInDegree(self):
conn_params = self.conn_dict.copy()
conn_params['allow_autapses'] = False
conn_params['allow_multapses'] = False
self.setUpNetwork(conn_params)
# make sure the indegree is right
M = connect_test_base.get_connectivity_matrix(self.pop1, self.pop2)
inds = np.sum(M, axis=1)
connect_test_base.mpi_assert(inds, self.Nin * np.ones(self.N2), self)
# make sure no connections were drawn from the target to the source
# population
M = connect_test_base.get_connectivity_matrix(self.pop2, self.pop1)
M_none = np.zeros((len(self.pop1), len(self.pop2)))
connect_test_base.mpi_assert(M, M_none, self)
def testInputArray(self):
syn_params = {}
for label in ['weight', 'delay']:
if label == 'weight':
self.param_array = np.arange(self.N_array, dtype=float)
elif label == 'delay':
self.param_array = np.arange(1, self.N_array + 1) * 0.1
syn_params[label] = self.param_array
nest.ResetKernel()
self.setUpNetwork(self.conn_dict,
syn_params,
N1=self.N_array,
N2=self.N_array)
M_nest = connect_test_base.get_weighted_connectivity_matrix(
self.pop1, self.pop2, label)
connect_test_base.mpi_assert(M_nest, np.diag(self.param_array),
self)
def testInputArrayWithoutAutapses(self):
self.conn_dict['allow_autapses'] = False
for label in ['weight', 'delay']:
syn_params = {}
if label == 'weight':
self.param_array = np.arange(self.N1 * self.N1,
dtype=float).reshape(
self.N1, self.N1)
elif label == 'delay':
self.param_array = np.arange(1, self.N1 * self.N1 + 1).reshape(
self.N1, self.N1) * 0.1
syn_params[label] = self.param_array
self.setUpNetworkOnePop(self.conn_dict, syn_params)
M_nest = connect_test_base.get_weighted_connectivity_matrix(
self.pop, self.pop, label)
np.fill_diagonal(self.param_array, 0)
connect_test_base.mpi_assert(M_nest, self.param_array, self)
