def test_libcsa_cgnext(self): """cgnext""" nest.ResetKernel() w = 10000.0 d = 1.0 cs = libcsa.cset(libcsa.oneToOne, w, d) nest.sli_push(cs) nest.sli_run('dup') nest.sli_push(numpy.array([0, 1, 2, 3])) nest.sli_push(numpy.array([0, 1, 2, 3])) nest.sli_run('cgsetmask') nest.sli_run('dup') nest.sli_run('cgstart') for i in range(4): nest.sli_run('dup') nest.sli_run('cgnext') self.assertEqual(nest.sli_pop(), True) self.assertEqual(nest.sli_pop(), d) self.assertEqual(nest.sli_pop(), w) self.assertEqual(nest.sli_pop(), i) self.assertEqual(nest.sli_pop(), i) nest.sli_run('cgnext') self.assertEqual(nest.sli_pop(), False)
def test_libcsa_OneToOne_params(self): """One-to-one connectivity""" nest.ResetKernel() n = 4 # number of neurons pop0 = nest.LayoutNetwork("iaf_neuron", [n]) pop1 = nest.LayoutNetwork("iaf_neuron", [n]) cs = libcsa.cset(libcsa.oneToOne, 10000.0, 1.0) nest.CGConnect(pop0, pop1, cs, {"weight": 0, "delay": 1}) sources = nest.GetLeaves(pop0)[0] targets = nest.GetLeaves(pop1)[0] for i in range(n): conns = nest.GetStatus( nest.FindConnections([sources[i]]), 'target') self.assertEqual(len(conns), 1) self.assertEqual(conns[0], targets[i]) conns = nest.GetStatus( nest.FindConnections([targets[i]]), 'target') self.assertEqual(len(conns), 0)
def test_libcsa_OneToOne_params(self): """One-to-one connectivity""" nest.ResetKernel() n = 4 # number of neurons pop0 = nest.LayoutNetwork("iaf_neuron", [n]) pop1 = nest.LayoutNetwork("iaf_neuron", [n]) cs = libcsa.cset(libcsa.oneToOne, 10000.0, 1.0) nest.CGConnect(pop0, pop1, cs, {"weight": 0, "delay": 1}) sources = nest.GetLeaves(pop0)[0] targets = nest.GetLeaves(pop1)[0] for i in range(n): conns = nest.GetStatus(nest.FindConnections([sources[i]]), 'target') self.assertEqual(len(conns), 1) self.assertEqual(conns[0], targets[i]) conns = nest.GetStatus(nest.FindConnections([targets[i]]), 'target') self.assertEqual(len(conns), 0)