Merge pull request #2797 from nicolossus/port_issue_211

Port `issue-211.sli` to Pytest

testsuite/pytests/sli2py_regressions/test_issue_211.py

@@ -0,0 +1,172 @@
+# -*- coding: utf-8 -*-
+#
+# test_issue_211.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/>.
+
+"""
+Regression test for Issue #211 (GitHub).
+
+This set of tests create connections between neurons and devices using multiple
+threads and check whether the actually created connections coincide with the
+expected connections.
+"""
+
+import nest
+import pandas as pd
+import pandas.testing as pdtest
+import pytest
+
+pytestmark = pytest.mark.skipif_missing_threads
+
+
+@pytest.fixture(autouse=True)
+def set_kernel():
+    nest.ResetKernel()
+    nest.local_num_threads = 2
+
+
+def get_actual_connections():
+    """
+    Retrieve actual connections as a sorted `pandas.DataFrame`.
+
+    This is a helper function used by the subsequent tests. The connections
+    created by the kernel must be sorted in order for deterministic comparison
+    with expectations. The connections retrieved from `GetConnections` are
+    sorted by, in decreasing order of priority, the target thread id, source
+    node id and target node id.
+    """
+
+    syn_collection = nest.GetConnections()
+    actual_connections = pd.DataFrame.from_dict(syn_collection.get(["source", "target", "target_thread"]))
+
+    actual_connections.sort_values(by=["target_thread", "source", "target"], ignore_index=True, inplace=True)
+
+    return actual_connections
+
+
+def test_connect_neuron_neuron_multithreaded():
+    """
+    Ensure correct creation of neuron-neuron connections using multiple threads.
+    """
+
+    n1 = nest.Create("iaf_psc_delta")
+    n2 = nest.Create("iaf_psc_delta")
+    n3 = nest.Create("iaf_psc_delta")
+
+    nest.Connect(n1, n3)
+    nest.Connect(n2, n3)
+    nest.Connect(n2, n1)
+    nest.Connect(n3, n1)
+    nest.Connect(n2, n1, syn_spec={"weight": 1.0})
+
+    expected_conns = pd.DataFrame(
+        [[1, 3, 1], [2, 1, 1], [2, 1, 1], [2, 3, 1], [3, 1, 1]],
+        columns=["source", "target", "target_thread"],
+    )
+    actual_conns = get_actual_connections()
+
+    pdtest.assert_frame_equal(actual_conns, expected_conns)
+
+
+def test_connect_neuron_device_multithreaded():
+    """
+    Ensure correct creation of neuron-device connections using multiple threads.
+    """
+
+    n1 = nest.Create("iaf_psc_delta")
+    n2 = nest.Create("iaf_psc_delta")
+    n3 = nest.Create("iaf_psc_delta")
+    sr = nest.Create("spike_recorder")
+
+    nest.Connect(n1, sr)
+    nest.Connect(n2, sr)
+    nest.Connect(n3, sr)
+
+    expected_conns = pd.DataFrame(
+        [[2, 4, 0], [1, 4, 1], [3, 4, 1]],
+        columns=["source", "target", "target_thread"],
+    )
+    actual_conns = get_actual_connections()
+
+    pdtest.assert_frame_equal(actual_conns, expected_conns)
+
+
+def test_connect_device_neuron_multithreaded():
+    """
+    Ensure correct creation of device-neuron connections using multiple threads.
+    """
+
+    n1 = nest.Create("iaf_psc_delta")
+    n2 = nest.Create("iaf_psc_delta")
+    n3 = nest.Create("iaf_psc_delta")
+    sg = nest.Create("spike_generator")
+
+    nest.Connect(sg, n1)
+    nest.Connect(sg, n2)
+    nest.Connect(sg, n3)
+
+    expected_conns = pd.DataFrame(
+        [[4, 2, 0], [4, 1, 1], [4, 3, 1]],
+        columns=["source", "target", "target_thread"],
+    )
+    actual_conns = get_actual_connections()
+
+    pdtest.assert_frame_equal(actual_conns, expected_conns)
+
+
+def test_connect_device_device_multithreaded():
+    """
+    Ensure correct creation of device-device connections using multiple threads.
+    """
+
+    sr1 = nest.Create("spike_recorder")
+    sr2 = nest.Create("spike_recorder")
+    sg = nest.Create("spike_generator")
+
+    nest.Connect(sg, sr1)
+    nest.Connect(sg, sr2)
+
+    expected_conns = pd.DataFrame(
+        [[3, 2, 0], [3, 1, 1]],
+        columns=["source", "target", "target_thread"],
+    )
+    actual_conns = get_actual_connections()
+
+    pdtest.assert_frame_equal(actual_conns, expected_conns)
+
+
+def test_connect_neuron_global_device_multithreaded():
+    """
+    Ensure correct creation of neuron-global device connections using multiple threads.
+    """
+
+    n1 = nest.Create("iaf_psc_delta")
+    n2 = nest.Create("iaf_psc_delta")
+    vt = nest.Create("volume_transmitter")
+
+    nest.Connect(n1, vt)
+    nest.Connect(n2, vt)
+
+    expected_conns = pd.DataFrame(
+        [[1, 3, 0], [2, 3, 0], [1, 3, 1], [2, 3, 1]],
+        columns=["source", "target", "target_thread"],
+    )
+    actual_conns = get_actual_connections()
+
+    pdtest.assert_frame_equal(actual_conns, expected_conns)