Port test for spatial connections to recorders.

Author: heplesser

testsuite/mpitests/topo_mpi_test_free_layer_to_sd_target_driven.sli

@@ -30,8 +30,8 @@
 - Free and grid layers
 - Different spatial connection rules
 
-Connections to recorders are handled in a separate test, as they do not work
-with fixed_indegree and there is no elegant way of filtering that case out.
+Connections to recorders are handled in a separate test, as they only work with
+the pairwise-bernoulli-on-source connection rule.
 """
 
 

testsuite/pytests/sli2py_mpi/test_spatial_connections.py

@@ -0,0 +1,80 @@
+# -*- coding: utf-8 -*-
+#
+# test_spatial_connections.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 pytest
+from mpi_test_wrapper import MPITestAssertEqual
+
+"""
+Confirm that spatial connections to a generator are created consistently for fixed VP.
+
+This test is parameterized over free and grid layers. Only pairwise-bernoulli-on-source
+is suitable as probabilistic connection rule when connecting to a device.
+"""
+
+
+# We cannot use nest or numpy outside the test function itself, so we need to create
+# the free positions with basic Python commands.
+@pytest.mark.skipif_incompatible_mpi
+@pytest.mark.skipif_missing_threads
+@pytest.mark.parametrize(
+    "geometry",
+    [
+        ("free", {"pos": [(x, y) for x in range(-2, 3) for y in range(-2, 3)], "extent": [6, 6], "edge_wrap": True}),
+        ("grid", {"shape": [5, 5], "extent": [6, 6], "edge_wrap": True}),
+    ],
+)
+@MPITestAssertEqual([1, 2, 4], debug=False)
+def test_spatial_connections(geometry):
+    """
+    Confirm that spatial connections are created consistently for fixed VP.
+
+    The test is performed on connection data written to OTHER_LABEL.
+    """
+
+    import nest
+    import numpy as np
+    import pandas as pd
+
+    nest.ResetKernel()
+    nest.total_num_virtual_procs = 4
+
+    kind, specs = geometry
+    if kind == "free":
+        pos = nest.spatial.free(**specs)
+    else:
+        assert kind == "grid"
+        pos = nest.spatial.grid(**specs)
+    source_layer = nest.Create("parrot_neuron", positions=pos)
+    target_layer = nest.Create("spike_recorder", positions=pos)
+
+    nest.Connect(
+        source_layer,
+        target_layer,
+        {"rule": "pairwise_bernoulli", "p": 0.5, "use_on_source": True, "mask": {"circular": {"radius": 2.5}}},
+        {
+            "weight": nest.spatial_distributions.gaussian(10 * nest.spatial.distance, std=2),
+            "delay": 0.1 + 0.2 * nest.spatial.distance,
+        },
+    )
+
+    conns = nest.GetConnections()
+    df = pd.DataFrame.from_dict(conns.get(["source", "target", "weight", "delay"]))
+    df.to_csv(OTHER_LABEL.format(nest.num_processes, nest.Rank()), index=False, sep="\t")  # noqa: F821