Port regression test 481 to Pytest and remove test 466

testsuite/pytests/sli2py_regressions/test_ticket_481.py

@@ -0,0 +1,114 @@
+# -*- coding: utf-8 -*-
+#
+# test_ticket_481.py
+#
+# 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
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# 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 <http://www.gnu.org/licenses/>.
+import nest
+import pytest
+
+
+def run_simulation(model, syn1, syn2, debugging=False):
+    """
+    Helper function to simulate and check if neuron voltages exceed the reference.
+
+    This function creates two neurons using the specified model and sets their initial voltage to Vref.
+    It then simulates a network with a poisson generator, voltmeters, and the specified synapses.
+
+    Args:
+        model (str): The neuron model to use.
+        syn1 (str): The first synapse model to connect the poisson generator to the first neuron.
+        syn2 (str): The second synapse model to connect the poisson generator to the second neuron.
+        debugging (bool): If True, prints additional information about the simulation results.
+
+    Returns:
+        bool: True if the maximum voltage of both neurons exceeds Vref, False otherwise.
+    """
+    Vref = -70.0
+    # Create neurons with specified model and initial parameters
+    n1 = nest.Create(model, params={"V_m": Vref, "E_L": Vref, "V_th": 1e10, "I_e": 0.0})
+    n2 = nest.Create(model, params={"V_m": Vref, "E_L": Vref, "V_th": 1e10, "I_e": 0.0})
+
+    # Create a poisson generator with a high rate
+    pg = nest.Create("poisson_generator_ps", params={"rate": 10000.0, "start": 0.0})
+    # Create voltmeters to record neuron voltages
+    vm1 = nest.Create("voltmeter", params={"interval": dt})
+    vm2 = nest.Create("voltmeter", params={"interval": dt})
+
+    # Connect poisson generator to neurons with specified synapse models
+    nest.Connect(pg, n1, syn_spec={"synapse_model": syn1})
+    nest.Connect(pg, n2, syn_spec={"synapse_model": syn2})
+    # Connect voltmeters to neurons to record their membrane potentials
+    nest.Connect(vm1, n1)
+    nest.Connect(vm2, n2)
+
+    # Simulate the network for 1000 ms
+    nest.Simulate(1000.0)
+
+    # Retrieve the maximum voltage recorded by each voltmeter
+    vm1_events = nest.GetStatus(vm1, "events")[0]
+    vm2_events = nest.GetStatus(vm2, "events")[0]
+
+    max_v1 = max(vm1_events["V_m"])
+    max_v2 = max(vm2_events["V_m"])
+
+    if debugging:
+        print(f"Max Voltage 1: {max_v1}, Max Voltage 2: {max_v2}")
+
+    # Return True if both neurons' voltages exceeded Vref
+    return max_v1 > Vref and max_v2 > Vref
+
+
+def setup():
+    """
+    Set up the simulation kernel with specified resolution and time settings.
+
+    This function resets the kernel and sets the resolution and ticks per millisecond for precise simulations.
+    """
+    nest.ResetKernel()
+    nest.SetKernelStatus({"tics_per_ms": 1.0 / dt, "resolution": dt})
+
+
+# Define time step
+dt = 0.125  # ms
+
+
+def test_ticket_481():
+    """
+    Ensure that poisson_generator_ps delivers spikes to more than one node.
+
+    This test checks if a poisson generator can correctly deliver spikes to multiple neurons
+    through synapses of identical or different types. The key assertion is that neuron membrane
+    potentials exceed a reference voltage in all valid configurations, indicating successful spike delivery.
+    The test expects exceptions when mixed synapse models are used inappropriately.
+
+    Author: Hans Ekkehard Plesser, 2010-11-03; based on original reproducer by Peiran Gao
+    """
+    # Test 1: Both neurons connected with identical synapse models, should pass
+    result = run_simulation("iaf_psc_delta_ps", "static_synapse", "static_synapse")
+    assert result, "Both neurons should receive spikes with identical synapse models."
+
+    # Test 2: Neurons connected with different named copies of the same synapse model
+    nest.CopyModel("static_synapse", "hoo")
+    result = run_simulation("iaf_psc_delta_ps", "hoo", "hoo")
+    assert result, "Both neurons should receive spikes with identical synapse models, even if renamed."
+
+    # Test 3: Neurons connected with different synapse models, expected to fail
+    nest.CopyModel("static_synapse", "foo")
+    nest.CopyModel("static_synapse", "goo")
+    with pytest.raises(Exception):
+        run_simulation("iaf_psc_delta_ps", "foo", "goo")