Source code for nest.tests.test_connect_one_to_one

# -*- coding: utf-8 -*-
# This file is part of NEST.
# Copyright (C) 2004 The NEST Initiative
# NEST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
# NEST is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with NEST.  If not, see <>.

import numpy as np
import unittest
from . import test_connect_helpers as hf
from .test_connect_parameters import TestParams

[docs]class TestOneToOne(TestParams): # specify connection pattern rule = 'one_to_one' conn_dict = {'rule': rule} # sizes of populations N = 6 N1 = N N2 = N N_array = 1000
[docs] def testConnectivity(self): self.setUpNetwork(self.conn_dict) # make sure all connections do exist M = hf.get_connectivity_matrix(self.pop1, self.pop2) hf.mpi_assert(M, np.identity(self.N), self) # make sure no connections were drawn from the target to the source # population M = hf.get_connectivity_matrix(self.pop2, self.pop1) hf.mpi_assert(M, np.zeros((self.N, self.N)), self)
[docs] def testSymmetricFlag(self): conn_dict_symmetric = self.conn_dict.copy() conn_dict_symmetric['make_symmetric'] = True self.setUpNetwork(conn_dict_symmetric) M1 = hf.get_connectivity_matrix(self.pop1, self.pop2) M2 = hf.get_connectivity_matrix(self.pop2, self.pop1) # test that connections were created in both directions hf.mpi_assert(M1, np.transpose(hf.gather_data(M2)), self) # test that no other connections were created hf.mpi_assert(M1, np.zeros_like(M1) + np.identity(self.N), self)
[docs] 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 hf.nest.ResetKernel() self.setUpNetwork(self.conn_dict, syn_params, N1=self.N_array, N2=self.N_array) M_nest = hf.get_weighted_connectivity_matrix( self.pop1, self.pop2, label) hf.mpi_assert(M_nest, np.diag(self.param_array), self)
[docs] 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 = hf.nest.Create(neuron_model, self.N1, neuron_dict) self.pop2 = hf.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 hf.nest.Connect(self.pop1, self.pop2, self.conn_dict, syn_params) M = hf.get_weighted_connectivity_matrix( self.pop1, self.pop2, 'receptor') hf.mpi_assert(M, np.diag(self.param_array), self)
[docs] def testInputArrayToStdpSynapse(self): params = ['Wmax', 'alpha', 'lambda', 'mu_minus', 'mu_plus', 'tau_plus'] syn_params = {'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 = hf.get_weighted_connectivity_matrix( self.pop1, self.pop2, param) hf.mpi_assert(np.diag(a), values[i], self)
[docs]def suite(): suite = unittest.TestLoader().loadTestsFromTestCase(TestOneToOne) return suite
[docs]def run(): runner = unittest.TextTestRunner(verbosity=2)
if __name__ == '__main__': run()