Merge pull request #2929 from janskaar/sli2py_iaf_psc_alpha_multisynapse

Sli2py `iaf_psc_alpha_multisynapse`

Author: heplesser

testsuite/pytests/test_iaf_psc_alpha_multisynapse.py

@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+#
+# test_iaf_psc_alpha_multisynapse.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/>.
+
+"""
+Test ``iaf_psc_alpha_multisynapse`` recordables and simulated PSCs against expectation.
+"""
+
+
+import nest
+import numpy as np
+import numpy.testing as nptest
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def reset():
+    nest.ResetKernel()
+
+
+def alpha_fn(t, tau_syn):
+    vals = np.zeros_like(t)
+    zero_inds = t <= 0.0
+    nonzero_inds = ~zero_inds
+    vals[nonzero_inds] = np.e / tau_syn * t[nonzero_inds] * np.exp(-t[nonzero_inds] / tau_syn)
+    return vals
+
+
+def test_I_syn_1_in_recordables():
+    """Test that ``I_syn_1`` is in the list of recordables."""
+
+    nrn = nest.Create("iaf_psc_alpha_multisynapse")
+    assert "I_syn_1" in nrn.get("recordables")
+
+
+def test_resize_recordables():
+    """
+    Test resizing of recordables.
+
+    This test ensures that recordables are updated correctly when the number
+    of synaptic ports are changed.
+    """
+
+    tau_syn1 = [5.0, 1.0, 25.0]
+    tau_syn2 = [5.0, 1.0]
+    tau_syn3 = [5.0, 1.0, 25.0, 50.0]
+
+    nrn = nest.Create("iaf_psc_alpha_multisynapse", params={"tau_syn": tau_syn1})
+    assert len(nrn.recordables) == 5
+
+    nrn.set(tau_syn=tau_syn2)
+    assert len(nrn.recordables) == 4
+
+    nrn.set(tau_syn=tau_syn3)
+    assert len(nrn.recordables) == 6
+
+
+def test_simulation_against_analytical_soln():
+    """
+    Test simulated PSCs against analytical expectation.
+
+    This test checks that the integration of the alpha-shaped currents of inputs
+    from multiple different synaptic ports are the same as the analytical solution.
+    """
+
+    tau_syn = [2.0, 20.0, 60.0, 100.0]
+    delays = [100.0, 200.0, 500.0, 1200.0]
+    weight = 1.0
+    spike_time = 10.0
+    simtime = 2500.0
+
+    nrn = nest.Create(
+        "iaf_psc_alpha_multisynapse",
+        params={
+            "C_m": 250.0,
+            "E_L": 0.0,
+            "V_m": 0.0,
+            "V_th": 1500.0,
+            "I_e": 0.0,
+            "tau_m": 15.0,
+            "tau_syn": tau_syn,
+        },
+    )
+    sg = nest.Create("spike_generator", params={"spike_times": [spike_time]})
+
+    for i, syn_id in enumerate(range(1, 5)):
+        syn_spec = {"synapse_model": "static_synapse", "delay": delays[i], "weight": weight, "receptor_type": syn_id}
+
+        nest.Connect(sg, nrn, conn_spec="one_to_one", syn_spec=syn_spec)
+
+    mm = nest.Create("multimeter", params={"record_from": ["I_syn_1", "I_syn_2", "I_syn_3", "I_syn_4"]})
+
+    nest.Connect(mm, nrn)
+    nest.Simulate(simtime)
+    times = mm.get("events", "times")
+    I_syn = np.sum([mm.get("events", f"I_syn_{i}") for i in range(1, 5)], axis=0)
+
+    I_syn_analytical = np.zeros_like(times, dtype=np.float64)
+    for i in range(4):
+        I_syn_analytical += alpha_fn(times - delays[i] - spike_time, tau_syn[i])
+
+    nptest.assert_array_almost_equal(I_syn, I_syn_analytical)